International Journal of Business Information Systems (131 papers in press)
ERP Implementation in University: A Case Study in Thailand
by Nacha Chondamrongkul
Abstract: Enterprise Resource Planning (ERP) is considered a proven solution that enhances the organizations structure, which results in better productivity. Nowadays, universities have many reasons to improve efficiency in administrative operations. Therefore, there are number of universities that aim to enhance administrative efficiency by implementing ERP system. However ERP system implementation in the university has a high failure rate because of its unique characteristic. Even though a number of critical success factors have been proposed but there is rare example of how to put them into practice. This paper presents a case study in a Thai university that implements ERP system, which shows how selected critical success factors are taken into practice throughout implementation process. A combination of semi-structured interviews and survey questionnaires are used as research methods to observe and analyze implementation process in the university environment. The study shows software learnability as a significant challenge that causes problems in the post-implementation phase. Also, the study highlights ERP system as the foundation for the development of forthcoming IT system.
Keywords: Enterprise Resource Planning; University; Critical Success Factor.
Evaluation of Indian universities websites in terms of information quality: Differences in the perspectives of end users segments based on their socio-demographic characteristics
by Bhim Sain Singla, Himanshu Aggarwal
Abstract: To-day, with the advent of Web technologies, there has been a sea change in the business scenario of not only the commercial organizations but also the higher education institutions. The organizational goals can be achieved more easily and efficiently by reaching out to a vast population through this medium. The educational institutes can provide quick and reliable services to the stakeholders of these websites within the shortest span of time and limited financial resources. However, the benefits to be derived from such websites rest more on their content quality in accordance with the requirements and expectations of the end users. Thus, this study is a modest attempt to evaluate the content quality of Indian universities websites through the perspectives of end users based on their demographic variables such as gender, age, education and status. The study is based on primary data which has been collected through a well-structured and pre-tested questionnaire from the respondents. The findings are extremely significant for the Indian universities as the improved quality of their websites would help them to attract more and more number of students for admission, and in improving their ranking.
Keywords: content categories; customer satisfaction; effective website; end users; importance versus performance; information quality; India; service quality; universities’ websites; website quality.
Data Mules Oriented Particle Swarm Optimization Based Mobile Sink Data Gathering Techniques with Analytical Data Analysis using Linear Regression
by Govindarajan Saravanan, MJS Rangachar
Abstract: Wireless sensor networks with convergecast nature poses great challenge on data collection strategies. In order to cut down the issues on constrained resources of wireless nodes, here a sink based (PSOMSDG) Particle Swarm Optimization Based Mobile Sink Data Gathering had been proposed. This PSOMSDG is a rendezvous based protocol which uses three metrics for data gathering based on the nodes position as; when the nodes are in inertia; when they change to optimistic position (based on current scenario); finally when they change to swarms optimistic position. These three metrics avoid long detour path by providing global optimal length constrained trajectory. In addition, residual energy consumption of protocol was achieved in a balanced manner. The performance is noticed with increasing data rates and compared with Biased Sink Mobility with Adaptive Stop Times (BSMAST). Then data obtained with NS2 simulation which was developed into a linear regression model. Finally the analytical study states that there is a strong relationship between data rate and energy consumption. The Analysis Of Variance (ANOVA) based analysis shows that there is a strong influence between groups.
Keywords: PSOMSDG, Energy consumption, ANOVA, Regression.
Cost Benefit Analysis of Cloud computing in Education
by Kiran Nayar, Vikas Kumar
Abstract: Application of Cloud Computing in Education not only relieve the educational Institutions from the burden of handling the complex IT Infrastructure management as well as maintenance activities, but also lead to huge cost savings. Along with many industry sectors, education sector would be largely benefited by adopting cloud services. Cloud promises to deliver affordable, reliable and flexible computing solutions to education sector and enable it to compete more effectively with bigger organizations. Motive of this paper is to analysis approach that has been followed to identify the benefits and limitations of cloud computing. Specific case of a lab setup has been taken to illustrate the financial aspects. A comparative analysis of Cloud-based hosting versus conventional (on-premise) application deployment has also been presented.
Keywords: Cloud Computing challenges; ICT; TCO; ROI; cost factors; ROI Factors.
Acceptance of E-book Reading among Higher Education Students in Developing Country: The Modified Diffusion Innovation Theory
by Nida shah, Syed Ali Raza
Abstract: This study explores the students intention towards the E-book adoption in Pakistan by using the modified diffusion innovation theory. Student attitude, awareness, perceived innovation characteristics (PIC) are taken as independent variables, actual usage is taken as a dependent variable, whereas intention plays the role of the mediator in the relationship. The data is collected through 5-point Likert questionnaire from the 620 university students. The confirmatory factor analysis (CFA), partial least square structure equation modeling (PLS-SEM) has been applied. The results show that compatibility, complexity, observability, trialability, attitude and awareness has a significant positive effect on behavioral intention, whereas, relative advantage has an insignificant effect on behavioral intention. Moreover, behavioral intention creates a significant positive effect on actual usage. This study will be useful in understanding the factors associated with the adoption of E-book reading. This work will help the managers to understand the role of PIC in adoption of new product or technology.
Keywords: E-Book reading, modified innovation diffusion theory, actual usage, Pakistan
Decision Modeling in Evaluating Information Management Strategy in Manufacturing Industry
by Purnendu Mandal
Abstract: Information technologies are exerting ever increasing influences on corporate growth and profitability. However, very little is understood of the mechanisms through which information technologies impact upon long-term organizational growth. We hypothesized several relationships between information technologies and organizational financial performance. We then analyzed those relationships through a structural equation model (SEM) using data collected for a national survey of US manufacturing companies. The major findings of the research are: an organizations financial performance is dependent on its information management and technology management strategies; knowledge management strategies indirectly influence financial performance. These findings are important in framing long-term strategies for sustainable development.
Keywords: Organizational Performance, Information Management Strategy, Technology Management Strategy, Knowledge Management Strategy, PLS analysis, Mediating effect
Investigating Drivers of User Acceptance of Electronic Treasury: A Case Study
by Behrouz Zarei, Kasra Amanati, Amir Hossein Ghapanchi
Abstract: Using information technology to increase efficiency and transparency in public expenditure management can have a great impact on production, collection, processing and providing reliable reports for policy-makers. Thus, it is very important to identify factors which impact the adoption of this technology. The conceptual model of this study is based on the trust and risk model in electronic government (e-government) adoption. In this study, the constructs of perceived ease of use from Technology Acceptance Model (TAM) and optimism bias have been added to the trust and risk model. Using a descriptive-survey method, a sample of 36 top budget managers has been examined. A questionnaire was used to collect the required data. Structural equation modeling using partial least squares was used to test the model. Based on the results, disposition to trust, trust of the e-treasury system, perceived ease of use and optimism bias explained the adoption of electronic treasury system among top budget managers. Disposition to trust and perceived ease of use also affected trust positively.
Keywords: E-treasury; Trust; Risk; Optimism bias; Ease of use
Developing and Validating a Comprehensive Model of Factors Influencing Consumer Acceptance of SMS Advertising: Empirical Evidence Using SEM-PLS
by Mohammad Al khasawneh, Ahmed Shuhaiber
Abstract: This study examined consumers acceptance of SMS advertising, as one of the mobile marketing instruments that is increasingly popular in accessing consumers through their mobile devices, by empirically investigating the factors that influence consumers attitudes towards and acceptance of SMS advertising. A comprehensive model was developed and tested with a sample size of 321 Jordanian mobile phone users, and analyzed quantitatively using Structural Equation Modeling Partial Least Squares (SEM-PLS) method. The findings indicated that SMS advertising values (entertainment and credibility) and SMS content (clarity and relevancy) as well as subjective norm and consumer control have a positive significant influence on consumer attitude and acceptance of SMS advertising. The results represent novel findings that hold important implications and recommendations for future marketing research and practice.
Keywords: Consumer Acceptance, Mobile Marketing, SMS Advertising, SMS Messages.
The Influence of Technological Factors on Individuals intention Towards Knowledge Sharing Practice.
by Dhanapal Durai Dominic Panneer Selvam, Arif Abdelwhab Ali
Abstract: Abstract: Knowledge sharing has been receiving the highest concern among knowledge management processes. It does attract many studies due to its vital role in the success of organizations. In fact, the practice of knowledge sharing in an organization is influenced by employees intention for sharing knowledge. This paper aims to investigate the influence of two technological factors precisely knowledge sharing systems and web2.0 on the individuals intention for knowledge sharing. Likewise, this paper examines the impact of knowledge sharing intention on the practice of knowledge sharing in organizations, particularly in oil and gas industry. Based on these objectives, a model was proposed, and research hypotheses were developed accordingly. Data were collected from seven international petroleum companies using a survey method. In details, an online questionnaire was used as a survey instrument which yielded a sample size of 157. Measurements were verified through reliability analysis using Cronbachs alpha method. Furthermore, factor analysis was also conducted for the purpose of dimension reduction and detecting any complex structure among the model variables. Further statistical tests were completed including correlation and multicollinearity tests. Structural equation modeling approach was used to evaluate the research model and test the proposed hypotheses as well. The findings indicated that both knowledge sharing systems and web2.0 platform positively influence knowledge sharing intention. Moreover, it was found that the intention to share knowledge has a positive influence on the knowledge sharing practice within organizations. All three proposed hypotheses were significantly supported. Finally, an extension of the study was suggested to be considered in the future.
Keywords: Knowledge sharing; knowledge sharing intention; knowledge sharing practice; knowledge sharing systems; web 2.0 technology;
New Local Sedec Pattern(LScP) Descriptor for improving the retrieval efficiency in Content Based Image Retrieval
by Umamaheswaran Subashchandrabose, Suresh Kumar N., Ganesh K
Abstract: In this paper, a novel Content Based Image Retrieval (CBIR) method is proposed using the Local Sedec Pattern(LScP). The Local Binary Pattern (LBP) and the Local Ternary Pattern (LTP), encode the relationship between the referenced pixel and its surrounding pixels, by computing gray-level difference, but in a different way. The proposed methods encode the relationship between the center pixel and its neighbors, based on directions such as vertical, horizontal and diagonal. Calculation based on First Order Derivatives is used here. Second order derivative is also applied to obtain LScP. The performance of the proposed method is compared with the LTrP and other local pattern (LBP,LDP and LTP)which results are obtained using benchmark image databases viz., Corel 1000 database(DB1), Brodatz texture database(DB2). Performance of the LScP shows improvement in retrieval from 75.9%/48.7% to 86.52%/54.4% in DB1, for average precision/average recall as compared with LTrP and other local patterns . A similar comparison shows improvement from 85.30% to 91.5% in terms of average retrieval rate on database DB2
Keywords: Content-based image retrieval(CBIR), Local sedec patterns (LScPs), Local tetra patterns (LTrPs)
Optimal Sentence Clustering for Web Database using Hierarchical Fuzzy Relational Clustering Integrated with Artificial Bee Colony Algorithm
by Santhi Venkatraman, Prasanthini R.
Abstract: Sentence clustering plays a vital role in text mining and text processing activities. The proposed work is a novel Hierarchical Fuzzy Relational Clustering Algorithm (HFRECA) capable of identifying sub clusters. It has features of both hierarchical clustering and fuzzy clustering in which it uses page rank to form multiple clusters present in text documents containing hierarchical structure. To enhance the quality of the clusters formed, an optimization algorithm which is called Artificial Bee Colony (ABC) algorithm is used along with it. The proposed algorithm identifies the sub clusters and finely tunes the cluster to show a better optimized result.
Keywords: Sentence clustering; page rank; fuzzy relational clustering algorithm; artificial bee colony algorithm.
Cognizant Computing and Lean Practices: Interactions with 21st Century Businesses and Implications
by Emmanuel C. Ogu, Benita Amos, Uduakobong Edy-Ewoh
Abstract: Cognizant Computing is one of the emerging, current and rapidly evolving information technologies that portends great promises for savvy businesses of the 21st century, with the potential to create huge savings and returns for businesses by reducing overhead costs and expenses. Lean practices in the business manufacturing and process industries have been proven to also guarantee global competitiveness and enhance efficiency of the manufacturing and process chain operations of businesses, while ensuring enhanced financial performance, productivity and market performance of end products. Until now, the existing nexus between these twain paradigms have remained blurred, with very little knowledge of how both can be combined and harnessed to ensure business success in the 21st century. As the world advanced towards the dawn of the long-deliberated Industry 4.0 revolution, it has become necessary that these twain concepts be re-investigated with a view to uncover a possible nexus between them; which, upon implementation, could guarantee the success, competitive advantage and stability of businesses in the coming industrial revolution. This study utilizes the exploratory research methodology due to the relatively new and emergent nature of the domain of discourse. The study introduces cognizant computing and illuminates its prospects for businesses in the present era, and how lean practices could combine with cognizant computing to guarantee the success and sustainability of businesses in the coming industrial age.
Keywords: Cognizant Computing, Business Operations, Industry 4.0 Revolution, Business Information Technology, Lean Manufacturing.
Patterns affecting structural properties of social networking site Twitter
by Vinay Singh, Anurag Singh, Divya Jain, Vimal Kumar, Pratima Verma
Abstract: With invent of Web 2.0 technology, online interpersonal interaction has been turned into the sensation of twentieth century. Websites and other applications on the Internet provide large amounts of data and new research area to the researchers. Twitter is one of them. Structurally, this site is the complex network of users connected to each other whose nodes represent individuals or organizations, and links mimic the interactions among them. Understanding the graph is critical, both to enhance current frameworks and to plan new applications for this platform. Here, we will endeavor to study the mixing patterns possible in Twitter online social networking site due to the geographic locations mentioned by the user via measuring assortativity coefficient and find out how these patterns are affecting the structural properties of the network. We examined data gathered from Twitter online social network by crawling on this site using the open Application Programming Interface (API)available for us by Twitter. We obtained a small portion of this social networks graph and observed that assortativity is indeed present in this network and also when we ranked the user according to their followers count and then remove few of them from the dataset, we found that network is resilient to the deletion of highest degree nodes and assortativity still exists. We performed the same experiment with random users and found the same results. To validate the above property observed in this social network, we plotted the graph to show the presence of core components in the network.
Keywords: Mixing Patterns, assortativity coefficient, robustness, dynamics of a network, homophily
Internet Banking in Pakistan: An Extended Technology Acceptance Perspective
by Sahar Afshan, Arshian Sharif, Nazneen Waseem, Reema Frooghi
Abstract: The growing attractiveness of internet banking is contributing well in the success and growth process of banking sector around the world (Xu et al. 2009). This study examines the integrative framework of internet banking (IB) in Pakistan using Technology Acceptance Model (TAM) with the integration of several risk dimensions and initial trust model. The techniques of both exploratory and confirmatory factor analyses are employed to assess the reliability and validity of the measurement model. The structural equation modeling method was also applied to investigate the hypothetical framework with the help of literatures recommended goodness-of-fit measurements. The findings of the study found significant contribution of personal propensity to trust, structural assurance, and familiarity with bank in influencing initial trust of people to accept IB. The findings are beneficial for banks that are pursuing IB in formulating strategies of enhancing users acceptance of internet banking in Pakistan.
Keywords: Internet Banking, TAM, Risk Dimensions, Initial Trust, Pakistan.
Evaluation of the StrAli-BPM approach: Strategic alignment with BPM using agreements in different levels
by Guilherme Salles, Vitor Barros, Marcelo Fantinato, João Albuquerque
Abstract: The strategic alignment between business areas and Information Technology (IT) is motivated by the needs of large organizations to thoroughly use the potentials of IT to transform business processes and deliver good products and services. In the treatment of processes and services, it is important to attend also to non-functional requirements, minimizing misapplied IT investments due to inefficiency. However, business process modelling languages do not represent these requirements, focusing only on functional requirements. Thus, in order to fill this gap, this paper presents the StrAli-BPM (Strategic Alignment with BPM) approach, which is divided in two parts BLA@BPMN and BLA2SLA: the former to extend the BPMN language aiming to embody non-functional requirements, in the form of BLAs (Business Level Agreements) enriched with KPIs (Key Performance Indicators); and the latter to semi-automatically derive a set of SLAs (Service Level Agreements), associated with web services, from a pre-defined BLA. This paper mainly describes the results obtained with the evaluation of the StrAli-BPM approach. First, the approach was evaluated by a proof of concept, based on the developed prototype tools, which allowed to verify its technical applicability. Then, a survey experiment was conducted with a panel of experts, members of a real organization. As a result, the proposed approach was well accepted by the experts who judged it as important and necessary to cover a gap in the BPM field. Some lessons learned from both evaluations are presented.
Keywords: strategic alignment; BPM; business process management; business process modelling; BPMN; business process model and notation; non-functional requirements; BLA; business level agreement; KPI; key performance indicator; SLA; service level agreement; SOA; service-oriented architecture; WS-Agreement.
Factors driving consumer loyalty intention towards e-tailers: an integrated model
by Plavini Punyatoya, Anurag Satpathy, Arjun Agrawal
Enhancing Revenue Management Systems Performance with CRM Systems Data
by Vinaysingh Chawan
Abstract: Revenue Management Systems (RMS) and Customer Relationship Management (CRM) Systems are widely used in todays data enriched environments to improve a firms profitability. Though these systems are used to improve business profitability, their approach and evolution are different, as a result of which these systems are being used separately. In case of RMS, the focus is on short term tactical revenue optimization, whereas in case of CRM the focus is on developing long term customer relationships. This paper discusses some ways of enhancing performance of Revenue Management Systems by using CRM data. Synergies and conflicts that may arise with the simultaneous use of these systems are discussed, and numerous applications that help in enhancing RMS performance are suggested.
Keywords: Revenue Management; Customer Relationship Management; Enhancing Performance; CRM Metrics.
The Big Five personality traits and their relationship with the intensity of using Facebook: A developing country perspective
by Ziad El-Tah, Mohammed-Issa Jaradat
Abstract: There is a remarkable increase in the usage of the social networking sites worldwide especially among young people, which has become a lifestyle. This study examines the role of the Big Five personality traits and their relationship with the intensity of using Facebook in a developing country perspective like Jordan. A Paper-based questionnaire was used to collect the data and the WarpPLS 5.0 software was utilized to test the data using a population sample (N=260). The results show that the intensity of using Facebook is negatively affected by the three personality traits (Neuroticism, Agreeableness and Conscientiousness) and positively affected by Extraversion, meanwhile Openness has no significant effect in the current analysis. This study also examines the moderating influence of gender, academic study level, college type and age on the relationships between the Big Five personality traits and the intensity of using Facebook. Furthermore, with respect to the addictive tendencies, the results revealed that the amount of average usage per day exceeds the benchmark of Facebook addiction.
Keywords: Facebook; Big Five Personality Traits; Gender; Academic study level; College; Age; Intensity of Using Facebook; Facebook Addiction; Jordan.
RBACA: Role Based Access Control Architecture for Multi-domain Cloud Environment
by Chaitali Uikey, D.S. Bhilare
Abstract: Cloud computing is an emerging area as a new arrangement of wide-area distributed computing. Sharing of resources and services over the network are heterogeneous, dynamic, and multi-domain. Security issue is also a serious problem in a cloud computing environment. Similarly, access control and authorization are an important aspect of the security. The paper proposes a scalable access control architecture and authorization, for cloud computing environment. A new access control architecture is proposed which is based on traditional access control, Role-Based Access Control (RBAC) model. The paper provides a flexible framework for policy announcement management approach for a multi-domain cloud environment. A policy language (XACML) is used for the demonstration of access control policies. This provides a general and standard provision of different resources and services.
Keywords: cloud computing; multi-domain architecture; role based access control; control architecture.
Towards a new method for designing multidimensional models
by Nawfal EL MOUKHI, Ikram EL AZAMI, Abdelaaziz MOULOUDI
Abstract: Designing a data warehouse as a support of the decision-making process remains a complex task and a major challenge for companies and organizations. This complexity is principally due to data sources that are heterogeneous and to the absence of a conventional method for modeling the data warehouse.
This paper analyzes the most important data warehouse design methods; it enumerates key strengths, limitations for each method, and presents a new design approach that allows to construct multidimensional schemas from relational models by using the MDA (Model Driven Architecture) techniques. This new approach will be able to produce good quality multidimensional schemas in an automated and standardized way.
Keywords: Decision Support System; DSS; data warehouse; data warehousing; relational models; multidimensional models; design methods; designing data warehouses; Model Driven Architecture; MDA.
An empirical investigation of agility factors in select Indian manufacturing industries
by Alok Khatri, D. Garg, G.S. Dangayach
Abstract: In the era of dynamic and customized demand, the organizations cannot to be rigid. Rigidity can be reduced by adopting agile manufacturing paradigm. The agile manufacturing is a tool that facilitates organizations a capability to deal with these challenges. The objective of this study was to identify chief predictors of agile manufacturing, establishing a relationship of agile providers, capabilities, enablers and to distinguish agile developers and enablers. The survey based study has been conducted to identify pinpoint factors of agility to help managers to identify the areas to be focused. To know the important factors that affect agile manufacturing, survey has been conducted for Indian manufacturing industries in selected areas. A hypothetical agile manufacturing framework has been proposed. The data has been analyzed by principal component analysis and linear regression model. The study indicates that nine hypothesized factors have statistically significant relationship with agility. Linear regression model has been developed to recognize agile manufacturing predictors. Linear regression model equation of agile manufacturing has been compared and tested with the mean value of agility. The results obtained from linear regression model and survey was found to be in close proximity. Further using principal component analysis, proposed empirical framework has been restructured as per empirical results of study.
Keywords: Agile manufacturing; agility enabler; agility developer; hypothesis testing linear regression model; principal component analysis.
Sequence Clustering Approach for clustering Web User sessions
by Pradeep Kumar
Abstract: Clustering web usage data is useful to discover interesting patterns pertaining to user traversals, behavior and their usage characteristics. It is also useful for trend discovery as well as for building personalization and recommendation engines. Since web is dynamic, clustering web user transactions results in arbitrary shapes. Moreover, users accesses web pages in an order in which they are interested and hence incorporating sequence nature of their usage is crucial for clustering web transactions. In this paper, we present an approach to cluster web usage sequence data and removing noise using DBSCAN algorithm. We also study the impact of clustering process when both sequence and content information is incorporated while computing similarity measure. We use S3M (Sequence and Set Similarity) measure to capture both the order of occurrence of page visits and the page information itself, and compared the results with Euclidean distance and Jaccard similarity measures. The Inter-cluster and Intra-cluster distances are computed using Average Levensthein distance (ALD) to demonstrate the usefulness of the proposed approach in the context of web usage mining.
Keywords: Sequence clustering ; web usage data; similarity measures; Average Levensthein distance.
MULTI TERM BASED CO-TERM FREQUENCY METHOD FOR TERM WEIGHTING IN INFORMATION RETRIEVAL
by Santhanakumar Markandeyan, Christopher Columbus Chinnappan, Jayapriya Kalyanakumar
Abstract: Now a day, World Wide Web (WWW) has become the only source of all kind of information. Retrieving the relevant web pages based on user queries from WWW is an exigent task. Term Frequency Inverse Document Frequency (TF-IDF) is the most frequently used method for term weighting based on the occurrences and presence of a term inside the document. Retrieved document based on a single query term may not relate to the user search. This may lead the user to process the unwanted information. So, this paper proposes a new term weighting method named Co-Term Frequency, in which the weight is assigned according to the multi terms commonly occur in all documents. From the measures of precision, recall and F-score of the proposed method, it is clearly evident that the proposed framework retrieves the most relevant web pages when compared to other term weighting methods.
Keywords: Term Frequency; Inverse Document Frequency; Co-Term Frequency; Term Weighting; WWW; Precision; Recall; F-score.
Factors Affecting the Adoption of Internet Banking: A Systematic Literature Review
by Shahzad Qamar, Amer Alzaidi
Abstract: Recent developments and trends in Information and Communication Technology (ICT) have significant impact on financial institutions such as banks. Internet Banking (IB) referred to the use of ICT by customers for performing different banking related tasks. The objective of this study is to identify the factors, which are affecting the adoption of IB. A Systematic Literature Review (SLR) methodology is adopted for conducting this research work. Our SLR included 122 papers selected from six digital libraries i.e. Google Scholar, Emerald Insight, Science Direct, IEEEXplore, Springer Link and ACM, published between 1999 and 2015. We classified 122 papers in the years, in which they were published, country in which research was conducted and the methodologies used in the papers. Based on the analysis of 122 papers, we identified 44 factors affecting the adoption of IB. Ease of use, Security, Ease of Usefulness, Trust and Prior IT Knowledge are consider critical among 44 factors. IB adoption is still a hot topic for research because the interest of researchers is still there to work on the factors affecting the adoption of IB.
Keywords: Internet Banking; Adoption Factors; Systematic Literature Review.
The impact of the quality of the service from IS/IT departments on the improvement of operational performance: The point of view of users of technological innovations
by Ricardo Santa, Mario Ferrer, Liliyana Makarova Jørsfeldt, Annibal Scavarda
Abstract: The purpose of this article is to examine how the provision of services from Information Systems / Information Technology (IS/IT) departments helps organisations to achieve reliable operations and improvements in operational performance in the view of the users. A Structural Equation Modeling (SEM) was used to examine structural relationships between the set of observed variables and the set of continuous latent variables from responses of a sample of 138 individuals from large service organisations in Australia that had recently implemented Enterprise Information Systems (EIS). The results suggest that there is no direct influence of the quality of the service from IS/IT departments on the improvement of operational performance, but there is an indirect relationship through the achievement of operational effectiveness. The findings also suggest that focusing solely on the effectiveness of the technological innovation is detrimental to long-term operational benefits.
Keywords: Service quality; system effectiveness; operational effectiveness; improvement in operational performance; enterprise systems.
Social Media Marketing Impact on the Purchase Intention of Millennials
by Ashutosh Pandey, Rajendra Sahu, Manoj Dash
Abstract: During the last decade we have seen an enormous growth of new channel of interaction i.e. Social media such as Face book, twitter and YouTube, where people can share their feelings, likes, dislikes publicly in the forum. Social media is emerging as a new sophisticated and uncontrollable element influencing consumer behaviour. They have also changed the way now businesses and consumers communicate with each other by instigating a power shift from business towards consumers. Due to a widespread use of social media, publicly as a medium of marketing communication, its the need of time to examine the social media marketing (SMM) empirically. From past relevant studies three constructs namely eWom, attitude toward social media advertising and peer communication has been identified and through it, an attempt has been made to find out the effect of all these mediums of SMM on purchase intention of millennial consumers.
Keywords: Social media; marketing; eWom; peer communication; purchase intention.
Evaluation and Performance Analysis of Classification Techniques for Thyroid Detection
by REKHA PAL, TANVI ANAND, SANJAY DUBEY
Abstract: Thyroid is one of the most common disease found in people nowadays which occur due to disorder of thyroid gland that include hypothyroidism(inactive thyroid gland) and hyperthyroidism (hyperactive thyroid gland) that can take place at any age and in either sex. Therefore their prior diagnosis and detection is very crucial and helpful for the betterment of human life. Large amount of complex data is collected by healthcare sector in order to identify hidden patterns for effective identification, detection and decision making. Data mining has become a current trend for achieving effective diagnostic result from massive data set by classifying applicable and unique patterns in data. The aim of the paper is to present an extensive analysis of different classification techniques viz. Naive Bayes, SVM, and K-Nearest Neighbour (K-NN) on the basis of dimensionality reduction for detection of thyroid disease. Results are provided to select best thyroid disease detection technique. The analysis reflected that K-NN is performing better than other classifier on the basis of various parameters. This analysis will help to identify best algorithm for such diseases and give better preventive options in advance.
Keywords: Classification Techniques; Disease; Data Mining; Dimension Reduction.
System Dynamics based Approach to Manpower Planning: A Study of Indian Microfinance Institutions
by Richa Das, Chandan Bhar
Abstract: The purpose of this paper is to analyze the manpower planning process of Indian Microfinance Institutions (MFIs). The paper describes a model that can assist management of MFIs to deal with the challenges microfinance organizations face in case of manpower planning. In this study, a system dynamics based model has been developed for manpower planning and the model estimates the requirement of staff members and executives at different levels under various scenarios that will help the organization in designing effective strategy to successfully manage their human resource strategically. The research methodology is in accordance with the principles of System Dynamics. The model has been developed using iThink software and has been validated by computing root mean square error between the actual values of the variables and the model generated values. The study will help the microfinance organizations to plan, manage and strategically focus on manpower planning in its desired direction.
Keywords: System Dynamics; Simulation; Manpower planning; Microfinance Institutions; Staffs; Executives.
Comprehending Visualizations of Dense Rank Order Data: A Comparison of Alternate Presentation Formats
by Vijay Raghavan, Ben Martz, Morgan Shepherd
Abstract: This study compared two tabular presentations and one graphical presentation of the same rank order data to study differences in participant comprehension. Hypothetical raw voting data by ten different judges ranking ten states on the desirability of each state as a preferred place for retirement was used. Three sets of the data were constructed for the voting scenario with low, high and moderate levels of consensus. The summary data was a table (TABULAR) representing the total count of votes for each rank (first place through tenth place) for all ten states. It was also presented as a 3D cone infographic (GRAPHICAL) and raw voting data (RAW). Participants were asked to estimate the level of agreement (0.00 to 1.00) indicated by each presentation. The results showed that the graphical and tabular presentations differed in participant comprehension for low and moderate levels of agreement but not for high levels of agreement.
Keywords: Analytics; Rank-order data; Visualizations; Pedagogy; Experiential Learning.
Online Car Parking Booking System: The case of Jordan
by Mahmoud Migdadi, AbdelRaouf Dado, Othman Al Safadi, Hisham Shadid
Abstract: With the increase in population and economic development of modern society of world, more and more people have cars of their own. The result is that traffic jam is more often than ever before. What is worse, in the increasingly crowded cities is the possibility of not finding safe parking lot especially in such crowded areas which could be a frustrating experiment. As parking facilities grow large, drivers need advanced methods of parking to reduce inefficiencies in finding spaces. A solution to reduce the drivers searching time for vacant car-park lots will greatly save time, reduce cost and improve the traffic flow in the car park areas. To this end, the researchers has created a web-based application (including PHP and MySQl server) which aims at providing its users (the drivers) several benefits-when they utilize it- such as provide real-time parking spot availability information in order to book a safe parking space any time and from any place, save them time and efforts, subscribe and pay electronically. In addition, the system allows parking owners and/or mangers to manage their own parking spaces bookings and subscriptions more efficiently.
Keywords: Keywords: Car parking; parking space management; web-based application; system analysis and design; Jordan.
Crowd Estimation at a Social Event using Call Data Records
by Sumathi V.P, Kousalya K, Vanitha V, Cynthia J
Abstract: Segregating attendees of the event from other regular visitor, paves way for new applications such as measuring event success and outdoor advertising. Traditional methods of crowd estimation at points of interests such as shopping malls, cinema halls, stadium and exhibitions using sample analysis of visitor through participant count obtained by number of tickets sold. In unstructured (free-to-view) event, the above said method does not help in accurate crowd estimation and social analysis. The objective of this paper is using call data records to estimate the crowd at an unstructured event in a city. The study was conducted at Indian Institute of Science (IISc) campus, Bengaluru on a special event day. To avoid breach of privacy, anonymised Call Data Records have been used. The crowd estimated using call data records shows positive correlation with ground truth-value.
Keywords: Social analysis; crowd estimation; call data records; unstructured event; free-to-view event; attendance estimation.
Identification and classification of parameters affecting service selection efforts in SOA-based applications
by Zeeshan Ali Siddiqui, Kirti Tyagi
Abstract: In recent past, service-oriented architecture (SOA) has evolved as a standard approach of software application development in the business world of information technology. The reason for its popularity lies in its ability to adopt the traditionally developed software applications and provide their functionality as services. Selection of a service from a pool of services, that can fulfill users capabilities requirements from different service providers, is a challenging core task. Selection of a service is eventually been decided by evaluation of quality of service (QoS) parameters based on users business requirements, and budget available. This paper presents identification and classification of significant parameters, based on previous literature, that affect service selection in SOA based applications (SOABAs)along with their definition and relation with service selection effort under the research question, What are the significant parameters that affect service selection efforts in SOABA?
Keywords: Service-oriented architecture; SOA; Service selection; Efforts; Parameters; Factors; Effort estimation.
Bees Algorithm and Support Vector Machine for Malaysian License Plate Recognition
by Nahlah Shatnawi
Abstract: Nowadays the increasing use of vehicles in modern life raises the problem of designing techniques that support effective traffic monitoring and vehicle identification. License Plate Recognition is an advanced machine vision technology used to identify vehicles by their license plates without direct human intervention. License plate recognition system major steps include image capturing, preprocessing, segmentation, feature extraction and classification. In this paper, a complete System for Malaysian License Plate Recognition is proposed to handle special Malaysian license plates under different conditions. In the proposed system, Peak Signal to Noise Ratio (PSNR) and Bees algorithm is used in preprocessing and segmentation stages, Sobel method for edge detection, and Support Vector Machine for classification. The proposed system is applied to dataset that is consisted of 1216 gray scale images, and is compared with different methods in segmentation and classification. Results show the robustness of the proposed system, making them suitable for more real world applications.
Keywords: Image Processing; Segmentation; Plate Recognition; Bees Algorithm; PSNR; Support Vector Machine.
Predictive Auto-Completion for Query in Search Engine
by Vinay Singh, Dheeraj Kumar Purohit, Vimal Kumar, Pratima Verma, Ankita Malviya
Abstract: The main goal of this research is to model an approach to give top-k predictive search results in search engine by the use of a combination of algorithmic and probabilistic approach and compare their processing time. Modified edit distance algorithm is used for spell auto-correction and prefix tree is used for auto-completion. Intersecting Union List algorithm is also used for multi-query predictive results. Wikipedia dictionary words are used for a single word query dataset and IMDB (Internet Movie Database) movie list is crawl by a python crawler, which is built for this research. And the rating of the movie provided by IMDB and frequency of each word is used to rank words.
Keywords: Auto-complete; Prefix tree; Hashing.
Preventing Business And Information Technology Misalignment When Introducing Technology Changes
by Oscar Avila, Kelly Garcés
Abstract: Organisations introduce changes in order to adapt themselves to the extremely changing context. These changes often impact Information Technology (IT) and Business domains. In most of the cases, the scope of the organisational elements in these domains requiring adaptation is not well defined, leaving out elements, which can lead to misalignment. Thus, it is important to know the impact scope with the purpose of performing a full adaptation. When reviewing the literature in the Business-IT alignment research field, we found that there are no works dealing with this aspect. However, several works in adjacent areas have studied change management. In this paper, we report a systematic review of related work in these areas and extract a set of clues applicable to the Business-IT alignment domain which results in a change analysis framework and a set of rules to estimate impact scope and potential adaptation. Framework elements and rules are illustrated by means of an industrial case study
Keywords: Change Management; Information Technology; Business-IT Alignment; Strategic Alignment; Prevent misalignment.
Factors Affecting the Adoption of Internet Banking in Pakistan: An integration of Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB)
by Masoodul Hassan, Asghar Iqbal, Zeeshan Iqbal
Abstract: The use of Internet banking in Pakistan is third largest mode in e-banking after Real Time Online Banking (RTOB) and Automated Teller Machine (ATMs) and it is evolving with an impressive pace and creates its space among other mode of e-banking. Therefore, this study examined the factors that affect the adoption of Internet banking in Pakistan through the theoretical lenses of Technology Acceptance Model (TAM) and Theory of Planned Behaviour (TPB). Structural Equation Modelling (SEM) with the help of Smart-PLS was used to examine the hypothesized relationships among the proposed constructs. A questionnaire survey was used for data collection. The study results confirmed the applicability of TAM and TPB frameworks in predicting the adoption of Internet banking by Pakistani bank costumers. Practically this study guides the strategic decision makers of banking industry especially of Pakistan to develop strategies that will help to increase the adoption of Internet banking in Pakistan.
Keywords: Technology Acceptance Model (TAM); Theory of Planned Behaviour (TPB); Behaviour; Pakistani Banks; Structural Equation Modelling (SEM).
Comprehensive Three-Layer Trust Management Model for Public Cloud Environment
by Vikas Kumar, Prasann Pradhan
Abstract: Public Cloud Offerings are gaining a lot of popularity as they offer consistent savings to the users by their pay-as-you-go model. Parties involved in public cloud transactions may be unknown to each other, however the users need to access the services of unknown cloud providers or third parties and even handover their significant data. Then the genuineness of the service providers or users becomes the most important concern. An established trust between the parties can help in creating sustainable transactions as well as long lasting business relations. To manage and build the trust, there is a strong need of trust management mechanism, which can fulfil the requirements from both the customer and provider perspective. Present work proposes a three-layer trust management model in public cloud environment, which can accomplish the expectations from both the viewpoints and can also support in building a long-term trustworthy relationships between them.
Keywords: Cloud computing; Trust; Trust Management;Trust Acquisition; Trust Development;Trust Retention.
A New Technique for Data Encryption Based On Third Party Encryption Server (TPED) to Maintain the Privacy Preserving in the Cloud Environment
by Ashraf Aljammal
Abstract: As the cloud datacenters are exposed to a various types of attacks, data theft/leakage is considered one of the vital attacks that may affect datacenters credibility. In this paper, a new technique is proposed to store the users data in an encrypted form in the cloud datacenter via a third-party-encryption server. There-fore, the attackers and the datacenter authorities will be able to deal only with an encrypted form of the data. Furthermore, to decrypt the data, they need to know the encryption algorithm as well as the encryption key which is in turn placed on a third-party-encryption server. In addition, using third-party-encryption server (TPED) will lead to reducing the workload on both the cloud servers and the data owners machine.
Keywords: Data Encryption; Cloud privacy preserving; Network security; information security.
Critical Success Factors in ERP Implementation in Indian Manufacturing Enterprises: An Exploratory analysis
by Shree Ranjan, Vijay Jha, Pralay Pal
Abstract: Enterprise resource planning (ERP) implementation projects involve complex processes which influence operations and performance of companies. It is essential to identify critical success factors (CSFs) of ERP implementation projects out of several contributing factors. In most large Original Equipment Manufacturer (OEM) organizations, ERP systems have replaced legacy information systems with integrated and maintainable software. In an attempt to understand what the CSFs are, why they are critical, and to what extent they are relevant to such OEM organizations this paper explores the existing literature empirically to research the CSFs that lead to the success of ERP, which is our basic objective. We conducted Exploratory Factor analysis (EFA) in the context of ERP implementation in large manufacturing organization. The findings of the results provide valuable insights for the researchers, practitioners and managers interested in adopting ERP systems in similar environments, which is also an objective of our research.
Keywords: Enterprise Resource Planning; ERP;Critical success factorsCSF;Exploratory Factor Analysis;EFA.
A bottom-up approach for creating goal hierarchy using OLAP query recommendation technique
by Ranjeet Kumar Ranjan, Parimala N.
Abstract: Traditionally, data warehouses have been designed guided by an analysis of the underlying data sources. On the other hand, goal-oriented approaches build a goal decomposition structure which is further mapped to a data warehouse model. Goal-oriented approaches address the requirements of the decision makers. In this paper, we propose to build a goal decomposition structure for traditional data warehouses. As a result it can be assessed whether the existing data warehouse model satisfies the decision makers requirements. The approach is bottom-up wherein the tasks are identified first and the path to the strategic goal is built later. The tasks themselves are identified using OLAP query recommendation technique.
Keywords: Data Analysis; Data Warehousing; OLAP; MDX; Goal Decomposition; Goal Hierarchy; Strategic Rationale Diagram; Query Recommendation; Cosine Similarity; Similarity Measure.
Reduced Energy Consumption for MC/DC Testing
by Sangharatna Godboley, Arpita Dutta, Durga Prasad Mohapatra
Abstract: After deployment, testing and validation techniques have become an important requirement for the reliability of software. However, these techniques do not measure energy that they consume, which is also an important parameter for software systems with short energy budgets. In this paper, we propose a new energy conservation technique. This novel technique does not affect the coverage percentage, but reduces the energy consumption. Energy conservation is based on test case minimization technique according to Modified Condition/Decision Coverage (MC/DC) requirements. Our experimental study shows that, as compared to existing work, our proposed approach achieves less energy consumption. On an average of five programs, we save 40.8% energy consumption
Keywords: Energy Consumption; Green Software Engineering; Green Software Testing; MC/DC.
To Measure the Business Performance through Cloud Computing Adoption in Indian Scenario: Structural Equation Modelling (SEM)
by Rakesh Raut, Pragati Priyadarshinee, Manoj Kumar Jha, Manoj Kharat
Abstract: The purpose of this research article is to measure the business performance through Cloud computing adoption in Indian industries. Data collection was done through a questionnaire based survey that was completed by 660 managers from Indian industries. The derived hypotheses were tested using structural equation modelling. The results show that six out of eight hypotheses were supported for cloud computing adoption to measure business performance. The research model has been tested empirically through three phases: exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and structural equation modelling (SEM). The findings are: (1) trust is having a major impact on cloud computing adoption followed by perceived IT security risk, technology innovation, risk analysis, management style; (2) usage of technology and industry use are having very insignificant effect on cloud adoption rate. This research identified trust as a major factor influencing the cloud adoption rate. However, further research is required to fully understand all the aspects involved especially with the growing number of vendors available. Some more sub-factors can be derived for business performance which can be analysed through second-order SEM. In the final survey with 660 managers, two factors top management support and market place establishment have been confirmed and found are the most important criteria for cloud computing adoption. So, from this study service, manufacturing and power sectors are benefitted in terms of the business performance. This research provides original insight for cloud computing adoption within Indian industries from a managerial perspective.
Keywords: Cloud computing adoption; Business performance; Exploratory Factor Analysis; Confirmatory Factor Analysis; Structural equation modelling; Indian industries.
A Systematic review on Techniques of Feature Selection and Classification for Text Mining
by Sridharan K, Sivakumar P
Abstract: Nowadays, there is a quick development in the use of internet. The large amount of structured, Unstructured and Semi-Structured forms like videos, images, audio or texts, these types of data that can be shared and used on the internet by the users. The storing of large quantity of unstructured text, which cannot be used for further processing, where the sequence of useful patterns, then the algorithm and methods of preprocessing are required. From the unstructured text, an interesting knowledge and information extraction process is called as text mining. The main analysis of text mining is as follows: Preprocessing, Feature Dimension Reduction (Feature selection or feature extraction) and text classification, clustering on the final features. In this paper, preprocessing is a step, used to remove the stop words, stemming for removing different suffixes by means to reduce the words count. Context sensitive stemmer methods are used for the further feature selection and classification of the storing of unstructured texts. The unsupervised and supervised feature selection methods like document frequency, term strength, chi-square and information gain are compared to produce the best method for the web document feature selection. The classification techniques like Latent Semantic Analysis, Genetic Algorithm, Rocchios Algorithm and Neural Networks are also compared. Finally, a systematic review on the feature selection methods and text classification techniques takes place.
Keywords: Information Gain; Document Frequency; Term Strength; Artificial Neural Network; Latent Semantic Analysis; Text mining; Stemming.
From Information to Interaction: Website and Social Media Usage and Trends in Top Indian Higher Education Institutions
by Rakhi Tripathi
Abstract: Purpose: The purpose of this study is to examine Web 2.0 usage in terms of website development and social media of top 300 higher education institutions (HEI) in India in terms of website and social media.
Design/methodology/approach: Top 300+ Institutions were selected from National Institutional Ranking Framework, India. Content analysis was used in terms of quantitative approach.
Findings: All the selected institutions have website and one third of the institutions are on social media. One-fourth has unofficial accounts on social media. In totality no trend has been noticed in Web 2.0 usage of higher education institutions in India.
Research limitations/implications: This study is completely based on publicly available data regarding presence on website and social media. Outcomes suggest that HEI are using Web 2.0 applications but at a slow pace.
Originality/value: This is the first research that draws an overall picture of the top institutions Web 2.0 usage in India. The study provides academics with helpful information to better meet their user needs by effectively applying digital strategies.
Keywords: Web 2.0; Website; Interaction; Transaction; Higher Education; Social Networking Site.
The Effect of Culture Values on Consumer Intention to Use Arabic E-Commerce Websites in Jordan: An Empirical Investigation
by Kamsuriah Ahmad, Mohannad Moufeed Ayyash, Omar Al-Qudah
Abstract: Abstract: A number of studies on the issues of Technology Acceptance Model (TAM), Hofstedes cultural values, risk and trust, have been done. However, the studies in combining all these issue are still limited especially in defining the relationship between them. Hence, this study attempts to examine the relationship between the variable through a developed model that is expected to improve the intention of consumers to use Arabic E-commerce websites. This study employs the quantitative method for data collection with the help of a questionnaire. The tested variables are significantly influenced the consumer intention behaviour, where intention to use factor positively impacted the utilization of Arabic E-commerce website. The findings showed support for the premise advocated by TAM and Hofstedes cultural dimensions theory as both were revealed to demonstrate the consumers intention towards using Arabic websites. The study enumerates the theoretical and practical implications, limitations as well as recommendations for future direction of studies.
Keywords: Keywords: Culture Values; Consumer Intention; Intention to Use; Arabic E-Commerce Websites; Trust; Risk; Arabic Language.
A Comparative Study of Emerging Scientific Themes in Business Analytics
by Iman Raeesi Vanani, Seyed Mohammad Jafar Jalali
Abstract: The purpose of this research is to investigate the emerging scientific themes in Business Analytics through the utilization of burst detection, text-clustering and word occurrence analysis in top Information Systems journals in order to provide an insight about the future scientific trends of business analytics for scholars and practitioners in the field. Researchers have gathered a rich set of Business Analytics articles from top journals which are indexed in the well-known scientific database of Web of Science (WoS) Core Collection. The burst detection algorithm, text clustering and terms frequency analysis are consecutively applied so as to understand the emerging themes in Business Analytics. The study provides clues, directions, and knowledge-based guidelines on the recent business analytics scientific trends through the utilization of mentioned algorithms over paper abstracts, titles, and keywords. Many of scholars and practitioners who are willing to conduct research over business analytics, business intelligence (BI), data science, and meta-heuristics will find this research helpful as it concentrates on the most deeply studied areas of related research. This study also highlights the most important areas of research and the future research directions that might be interesting to business analysts through an in-depth analytical discussion. An analysis of other academic databases and international publications would enrich the depth and breadth of this research.
Keywords: Business Analytics; Burst Detection; Text Clustering; Words Occurrence; Decision Support.
EI-Annotate: An adaptive collective memory based on annotation ontology and context for decision making in economic intelligence
by Aissa Bensattalah, Faical Azouaou, Fahima Nader, Rachid Chalal
Abstract: In the decision support process, the economic intelligence actors use mental efforts and considerable cognitive activities to solve decisional problems; they deal with a large mass of digital documents during their activities. To facilitate their activities, they use different types of annotations on the manipulated document. To exploit the benefits of these annotations, we propose in this paper, EI-Annotate, an annotation tool dedicated to economic intelligence actors, which enables them to create an adaptive collective memory. The adaptive collective memory based on annotation ontology and context suitable for economic intelligence. This memory is a knowledge management tool that can support economic intelligence actors in their decision process. The EI-Annotate annotation module is implemented as extensions using different technologies; it enables to annotate resources in different formats (document, picture, videos). We present the results of an evaluation study of the proposed architecture of an adaptive collective memory conducted with a research laboratory context, regarding their annotation experience using EI-Annotate.
Keywords: economic intelligence; decision support process; unstructured decision problem; ontology; semantic annotation; context; adaptation; annotation tool.
Prioritization of agile characteristics in products using Fuzzy AHP approach through the referencing of the features of mobile phones
by Thilak VMM, S.R. Devadasan, M. Vinod, D.T. Sunil
Abstract: In order to face the intensification of competition, modern companies are required to implement agile manufacturing paradigm. Since mobile phone manufacturers have implemented the characteristics of agile manufacturing paradigm, mobile phone industry thrives in this competitive world by frequently bringing out several models of mobile phones with amazing features. In the context of this observation, the research reported in this paper was carried out. In this research, 30 features that ascribe the agile characteristics of mobile phones were identified. Subsequently, fuzzy Analytic Hierarchy Process (AHP) technique was applied to prioritize the features and characteristics that infuse agility in mobile phones. The outcome of this research revealed that functional characteristic has been playing major role in enhancing the agility of the mobile phones. This result indicates that modern companies are required to prioritize the infusing of functional characteristic in products for exercising speedy implementation of agile manufacturing paradigm.
Keywords: Agile manufacturing; AHP; Fuzzy logic; Fuzzy AHP; Mobile phones.
An Empirical Examination of Customer Experience Co-creation model in Banking Self Service Technologies (SSTs).
by Amit Kumar Agrawal, Asha Nagendra, Rajiv Divekar, Pravin Kumar Bhoyar
Abstract: The aim of the paper is to develop and validate customer experiences co-creation model in banking SSTs. Primary data collection was done through the field survey method using a self- administered questionnaire. The study is descriptive in nature. Structural equation modelling is used to analyze the data collected through the questionnaires. The study result reflects that customer propensity towards SSTs leads to co-creation of experiences which are responsible for satisfaction of customers with technological products. Present research is performed in the context of banking SSTs and cross sectional in nature which could be further replicated in other SSTs adoption context. The finding of the study would motivate manager to work on newer ways to intensify customer experiences through SST adoption in value co-creation process. The study is the first of its kind to examine SST adoption model that integrates customer experiences. Further study should undertake the quality of customer experiences as a tool for customer retention.
Keywords: Value Co-creation; Experiences; Customer Participation; Banking; Self Service Technologies (SSTs).
Factors Affecting ERP Projects from a Project Management Perspective: A Literature Review
by Rateb Sweis, Ruba Abuhussein, Dana Jandali, Mohammad Mashaleh, Mutaz Al- Debei
Abstract: The purpose of this paper is to identify the factors affecting ERP projects and to classify them based on their project management knowledge areas. Previous studies were reviewed in order to identify the factors affecting ERP project performance. Next, the factors were categorized based on their project management knowledge areas. Finally, the knowledge areas were ranked according to their occurrence in literature. The results showed that, the four knowledge areas that affect ERP project performance the most are communication, human resource, time management and risk management. Understanding the factors that affect ERP projects has been a subject of considerable interest to many academics. Despite the many studies providing clear evidence on factors affecting ERP projects, vast majority of the literature has tended to approach the topic in a general manner while ignoring the issue of categorization of such factors. In this paper, we seek close such gap
Keywords: ERP Projects; Project Management; Communication Management; Human Resource Management; Time Management; Risk Management.
Explaining and Predicting Continuance Usage intention of E-learning Recommender Systems: An Empirical Evidence from Saudi Arabia
by Hadeel Alharbi, Kamaljeet Sandhu
Abstract: This paper examines the factors that may influence students' acceptance and the continuance usage intention of e-learning recommender systems in higher education institutions in Saudi Arabia. A questionnaire was developed based on an extended technology acceptance model (TAM). A total sample of 353 university students from various universities in Saudi Arabia participated in this study. After performing the satisfactory reliability and validity checks, the hypothesized model was tested using structural equation modeling. The findings of this study revealed that perceived usefulness (PU) and perceived ease of use (PEOU) are significant determinants of e-learning recommenders system initial acceptance. The results also showed that the service quality, a newly added external construct, has significant impact on perceived recommender system ease of use. User experience of recommender system, the second newly added construct, was found to have a significant effect on perceived recommender system usefulness. Finally we found that students acceptance of e-learning recommender systems positively and directly influences their continuance usage intention. Overall, the proposed model achieves acceptable fit and explains 55% and 42.8% of the sample variance for this studys key target constructs (i.e. user acceptance and continuance usage intention of e-learning recommender system, respectively) which is higher than that of the original TAM. Our findings suggest that service quality, user experience and TAM factors (i.e. PU and PEOU) are important to consider in explaining students' acceptance and the continuance usage of e-learning recommender systems.
Keywords: E-learning; Adoption; recommender systems; TAM; Saudi Arabia.
Predicting e-commerce adoption in small hotel: the role of technology-organization-environment framework
by Nurhadi Nurhadi, Margo Purnomo
Abstract: This study aims at explaining the determinants of e-commerce adoption at firm level based on the technology-organization-environment framework. The population of this explanatory research included small hotels in Bali Indonesia which had implemented e-commerce system for at least a year. The result of the analysis showed that the four variables (relative advantage, organizational readiness, management commitment and external pressure) had a significant effect to the adoption of e-commerce system. Whereas statistically, the effect of the compatibility was not significant. Future researchers are expected to take more than one respondents as the informants in each of the selected hotel as the unit of the analysis. The result of this study proposed a practical implication suggesting that hotels need to consider the aspects of financial, technology, and human resources as an organizational readiness in implementing e-commerce system.
Keywords: e-commerce adoption; technology-organization-environment framework; small hotel; relative advantage; compatibility; organizational readiness; management commitment; external pressure.
An Event-Driven Dynamic Cross-Layer Business Process Compliance Monitoring and Analysis Framework
by Sridevi Saralaya, Rio D'Souza, Vishwas Saralaya
Abstract: A key feature of any Business Process life-cycle is to persistently monitor adherence to compliance from various sources thus helping in detection, analysis and recovery from anomalies. Whenever a business process implemented as Service-Based System (SBS) deviates from compliance obligations it is imperative to overcome the anomalies, so that requirements of the business process are not adversely affected. This necessitates a monitoring and root-cause analysis process. Performance of the SBS is determined by several factors such as goals \& objectives of Business layer; output data, execution time \& number of services in Service layer; processing load, storage capacity, etc. of the Infrastructure layer. Current approaches to compliance monitoring are inadequate for this purpose as they observe and verify adherence to compliance properties in any one of the layers of the SBS. To identify the exact source of anomaly, the cause that may be rooted in any layer should be analyzed to propose effective recovery actions. We propose a monitoring and root-cause analysis framework capable of congregating and correlating events from all three layers of the SBS. The prototypical implementation based on event paradigm is non-invasive with the business process and hence introduces no overhead to the system under consideration.
Keywords: Cross-Layer Monitoring; Root-Cause Analysis; Event-Based Monitoring; Hierarchical Service-Based Systems; Dependencies.
A Three Pronged Technique For The Intelligent Ranking of Cloud Service Providers
by Tina Esther Trueman, Narayanasamy P
Abstract: Small and medium enterprise systems need to be preserved which is a necessity for our country as the growth is at the grass root levels. Cloud Computing can be a solution to help preserve the small and medium enterprises by promoting their services through the web as they can avoid huge infrastructure costs. However, most of the enterprise practitioners are not technology savvy, and it will be a daunting task to choose the best select service provider from the vast number of cloud service providers present. Hence, in this paper a comprehensive three pronged technique which will facilitate the easy selection of Cloud Service Providers is proposed. An Interval valued Fuzzy Soft Sets algorithm is used to rank the cloud service providers based on the user ratings of the cloud service providers. The information regarding the cloud service providers has been collected to create an ontology to match the service providers with user requirements. This suite of tools can be used by the enterprise owners to select the best cloud service provider for their requirements with minimum IT knowledge.
Keywords: Multi-criteria decision making; Cloud Service Providers Ranking; Fuzzy Soft Systems; Ontology Creation; User Reviews on Cloud Providers.
The Relationship between Business-IT Alignment and Organisational Performance: An Empirical Investigation from Multilevel View
by Hamad Balhareth
Abstract: The previous studies have significantly showed that Business-IT alignment is practically very important for the performance of the organisation. Its value is being derived from the influence of strategy on the outputs of the business. Hence, Business-IT alignment is recognised as very important for the profitability of the organisation. On the other hand, the previous studies have a limited focus on the two approaches: strategy content and strategy process, as impacting to the organisational performance. Therefore, this research study attempts to fill the gap in the literature and to test the relationship between Business-IT alignment and performance .The survey was conducted in universities along with assessing the contribution of strategy content and strategy process in the effects of strategic alignment on the performance. The data collected from the survey is used in the context of Saudi Arabia. The findings of the study show that the positive effects on the performance in the strategic alignment are statistically significant, where the effects can be varied in the absence of either strategic content or process.
Keywords: strategy process; strategy content; performance; business and IT alignment; Strategic alignment; misalignment; PLS analysis; empirical investigation.
Toward Green IT Adoption: from Managerial Perspective
by Shahla Asadi, Ab Razak Che Hussin, Halina Mohamed Dahlan
Abstract: The environmental issues had drawn attention from governments, societies as well as business organisations. Indeed, organisations have put effort on challenging the environment issues. One of the most important logical efforts that organisations put to deal with environmental issues is Green IT which, in turn, leads to enhancement in the organisations performance and improvement. Using Green IT by organisations will be advantageous to the society. There is plethora of research on Green IT in organisations and the adoption of Green IT from managers pro-environmental intention was only explored by a small number of them. The norm activation theory and the Theory of planned behaviour have been used in this study. The study provides the available recent knowledge about information system which is necessary to monitoring the decision makers intention for adoption of Green IT and sustainability by developing a research model which recognises the important aspects for Green IT adoption.
Keywords: adoption; Green IT; Green IS; norm activation model; theory of
planned behaviour; TPB.
Achieving Operational Excellence in ERP Manufacturer Industries: Through Operation Transformations
by Balasubramanian Kannan, Selladurai Velappan
Abstract: Enterprise Resource Planning (ERP) provides a strong opportunity to suits in a manufacturing organisation as the realised technology solution to deliver expecting operational benefits. The ERP application will initiate to support the processes challenge and to carry out company operations and inventory controls of the manufacturing industry. Consequently, implemented ERP system in manufacturing companies has not completely integrate shop floor operations along with workflow. This system skip-off critical operations and metric benefits within the manufacturing organisation. However, this paper proposes a manufacturing operation transformation model which the design describes a methodology based on a critical risk factor including manufacturing operation and advance manufacturer architecture, thus achieving operational excellence in the future means to the organisation. The conceptual model obtains greater control across functional departments system at every stage of production and operation performance driving through transformation brings system in full benefits. The findings are useful for manufacturing organisation considering ERP system achieve better understanding of companys needs and expectation.
Keywords: Enterprise Resource Planning; manufacturing organisation; operational excellence; manufacturing operations transformation.
Analysis of Causal Relationship between Factors Affecting the Successful Implementation of Enterprise Resource Planning using Intuitionistic Fuzzy DEMATEL
by Hossein Sayyadi Tooranloo, Arezoo Sadat Ayatollah, Mohsen Karami
Abstract: The present study aimed is analysis of causal relationship between factors affecting the successful implementation of enterprise resource planning using intuitionistic fuzzy DEMATEL using case studies in Esfahan Steel Company. Effective factors on successful implementation of enterprise resource planning were determined by reviewing literature and Similar studies and interviewing company experts. Accordingly, the 8 factors were identified. On the basis of determinate factors, a questionnaire was designed based on DEMATEL technique and administered to all experts to explain the relationships between those factors. After data were collected, the importance of assessments provided by experts was explained and comments from them were addressed using intuitionistic fuzzy entropy. Finally intuitionistic fuzzy based DEMATEL technique was used to show causal relationships.
Keywords: Enterprise Resource Planning; DEMATEL; Entropy; Intuitionistic Fuzzy.
The effect of service recovery on customers satisfaction in e-banking:An empirical investigation
by Abbas Keramati, Arash Apornak, Helya Abedi, Farnoush Otrodi, Mariam Rudneshin
Abstract: The purpose of this paper is to analyze the service recovery strategies associated with customers satisfaction level of an Iranian private bank. Therefore, by providing an appropriate framework, the relationship between the service failure, service recovery, customers satisfaction and their subsequent behavior is examined.In this paper after a survey on different frameworks in a service failure recovery domain from reviewing of literature, the most appropriate framework based on an Iranian private bank situation has been chosen. Then, the conceptual framework is adapted to the mentioned bank by qualitative case study. Since the main motivation of this paper is to provide empirical knowledge about the service failure and recovery in e-banking, therefore, they are determined and listed based on the frequency rate and the effect on the customers respectively by literature review and field studies in an Iranian private bank. Moreover, by combining two suitable frameworks of service recovery literature and adapted to this bank, a conceptual framework is proposed. Due to the short duration of surveying customers satisfaction in Iranian e-bank, this paper provides an appropriate framework in order to compensate e-bank errors based on the service recovery literature and field studies on an Iranian private bank.
Keywords: Service Failure; Service Recovery; customers Satisfaction; E-banking.
What Managers Think about Big Data
by Ossi Ylijoki, Jari Porras
Abstract: Digitization progresses rapidly, producing vast amounts of big data. Companies can innovate their business models by using big data and related technologies. Some industries and companies are already on their way towards more data-driven businesses, but for most organizations this is an uncharted territory. The process is first and foremost a business transformation issue. Management leads the change and sets the pace; therefore the attitudes and intentions of executives towards big data are important in the transformation process. This survey concerns the behavioural intentions of Finnish executives with regard to big data. Building on a well-established technology acceptance model we explored the factors that explain the intentions. According to the results, executives intend to take actions that will promote the utilization of big data. They have either experienced or expect big data to be beneficial to their business, especially with regard to current products or services, streamlining of processes and increasing customer understanding. In addition to the generally positive attitude towards big data, the results reveal significant differences between respondents with big data experience compared to the inexperienced ones. The role of IT management seems to play an important role in the differences.
Keywords: big data; behavioural intentions; business information systems; business transformation; business model; digitization; Finland; innovation; management survey; management attitudes; technology acceptance model.
Reconceptualizing service firm marketing capability: Scale development and validation
by Shampy Kamboj, Zillur Rahman
Abstract: The purpose of this study is to conceptualize, develop, and validate the multidimensional measure of marketing capabilities of service firms. This study is based on a series of pre-tests, and two large survey-based studies of Indian service firms. The eighteen items scale developed through this study can be used to measure marketing capability of service firms. Researchers and practitioners can use the scale developed through this study to effectively measure marketing capability of service firms. Although, there are scales to measure marketing capability of manufacturing and hi-tech industries, there is no scale that measures marketing capability of service firms. This research fills this gap by developing a scale with eighteen items that effectively measures the marketing capability of service firms.
Keywords: Customer; Marketing capabilities; Scale development; Services; Service firms.
Efficient enhanced Intrusion identification and response system for MANETs
by SANTHOSH BABU A V, MEENAKSHI DEVI P, SHARMILA B
Abstract: Mobile ad hoc networks (MANETs) are the new generation of self organizing networks that offer unrestricted mobility without any underlying infrastructure. It relies on the cooperation of all the participating nodes. Due to diverse nature of MANET routing is the major challenge. Security for MANETS has become a difficult problem than the security in other networks. Authentication and encryption would be used as the primary defense. Second level of defense to detect and respond to the security problem called an Intrusion identification system. In this paper, two phased enhanced intrusion identification and response (t-EIIAR) system for multi hop cluster based MANETs is proposed. The two phases of the proposed method (1) cluster formation and cluster head selection (2) the enhanced identification and response system. The fuzzy c means algorithm (FCM) is used to form the cluster and the Intuitionistic Fuzzy TOPSIS (IFT) method used to calculate the trust value for each node in the cluster, based on the trust value select the cluster head and identify the intrusion levels. Finally the intrusion response action is performed from the intrusion level classifications. In the performance analysis, t-EIIAR system maximizes the intrusion detection ratio, network life time and minimum energy consumption in both transmitter and receiver side.
Keywords: Two phased enhanced intrusion identification and response (t-EIIAR); intrusion detection and adaptive response (IDAR); fuzzy c means algorithm (FCM); Intuitionistic Fuzzy TOPSIS (IFT); clustering; cluster head.
Select and tuning the optimal Query form of Different SQL Commands
by Hasan Idhaim
Abstract: This paper presents the proposed approach of SQL tuning plan and tool in database systems based on experiments using testing data workload in oracle 11g XE; to get for an optimal execution plan for a given SQL statements based on process time consumed and statistics about the object related to tables referenced in the statement. These statistics include of the SQL command running time consumption, tables themselves, their indexes, access methods, and other derived objects. The quality of final execution plan depends primarily on the quality of the information found about the SQL command to improve a poorly-performed Query. This work contributes to research knowledge by proposing a necessary knowledge and information about database tuning using a useful tool to evaluate SQL commands. The proposed approach helps researchers, database administrators (DBAs), and developers to assess the impact of their decisions in the selection the optimal SQL statement form.
Keywords: Oracle 11g; SQL Commands; SQL Code Tuning (SCT); Query; Tuning; Throughput; Evaluation; Optimization; DBA.
Implicit Feature Identification for Opinion Mining
by Farek Lazhar
Abstract: In Opinion Mining area, mining consumer reviews can give a finer-grainedrnunderstanding of consumer needs, which can efficiently help companies and merchants to improve the quality of their products and services. However, identifying features on which consumers express their opinions and sentiments, is not always a simple task. Some existing approaches that attempt to extract implicit features using opinion words as clues or co occurrence techniques lead to unsatisfactory results, and that due to the ambiguity caused by common opinion words which are often expressed on various features. In this paper, we propose, an approach based on Association Rule Mining (ARM) and classification techniques. The first step, consists of creating from a corpus, a set of association rules regrouping explicit feature-opinion pairs. The second step, consists to use this set to build a classification model able to predict for each given set of opinion words the appropriate target. Tested on many classifiers, experimental results show that our approach performs better when incorporating many opinion words than using single ones.
Keywords: Implicit Feature; Opinion Mining; Opinion Word; Association Rules; Prediction.
BARRIERS IN ONLINE SHOPPING
by Ruby Jain, Madhu Kulhar
Abstract: Certain factors affect consumer buying behavior while purchasing products online. Out of these, some commonness is discussed in the present paper which affects the adoption of online shopping. A simple search with keywords online shopping, online shopping of apparels and accessories, factors affecting online shopping, drivers of online shopping and barriers of online shopping has been done with Google Scholar.
Substantial studies have been conducted globally to find out the factors affecting online shopping adoption. Different models and frameworks are available to understand these factors and it is difficult to present all work altogether. Thus, this paper tries to present a comprehensive framework of the relevant literature as barriers of online shopping. All available studies from anytime referred till date have been included to build a said framework of review.
Keywords: online shopping; adoption; information technology; barriers.
Managing Digital Infrastructures: Negotiating Control and Drift in Service Provisioning
by Nils-Petter Augustsson, Agneta Nilsson, Jonny Holmström, Lars Mathiassen
Abstract: The digital infrastructure literature provides important perspectives on the intrinsic relations between information systems in todays organizations. However, little attention has been paid to the challenges involved in providing requisite digital infrastructure services to organizations. In this paper, we argue digital infrastructure service providers operate in highly complex and uncertain environments. Rather than adopting a traditional approach to control, providers must therefore continuously negotiate a balance between control and drift as two complementary strategies.
Our argument is based on a retrospective longitudinal case study of a Swedish infrastructure service team within a large international firm. Using the encounterepisode process model as structuring principle and focusing on the tension between control and drift, we analyze the evolution of the providers efforts to manage a portfolio of digital infrastructure services over a period of ten years. Based on these analyses, we uncover the involved complexities and dynamics, how control efforts and drift constituted and how the infrastructure services were managed by continuously balancing control and drift. In conclusion, we relate the findings to extant literature to discuss new insights into provider management of digital infrastructure services.
Keywords: Digital infrastructures; services; management; control and drift.
Sophisticated Strategic Information Systems and Strategic Performance of Islamic Banks: a Review of Literature
by Ahmad Shukri Yazid, Farouk Umar Kofarnisa
Abstract: Strategic information system sophistication has been regarded as a critical organizational management issue. It has been considered by many researchers as a crucial organizational resource for achieving multiple strategic performances. However, studies of such have been given less attention within the context of the Islamic banking Industry. Therefore, this paper highlights the issue through a systematic review of previous literatures on the subject matter. Thus, the study found a significant relationship between strategic information systems and strategic performances and hence recommends its relevance in achieving strategic performances within the context of the Malaysian Islamic banking industry.
Keywords: strategic information systems; strategic performance; Islamic Banks.
A Semantic Matching Engine for Web Service Composition
by Rouached Mohsen
Abstract: One of the main assets of service-orientation is composition, which consists in developing higher-level services by re-using well-known functionality provided by other services in a low-cost and rapid development process. However, considerable differences on structural, semantical and technical levels along with the growing number of available Web services makes their discovery a significant challenging task. Therefore, services compatibility is an essential pre-requisite to service composition. Measuring the similarity of services is an important and valuable task to get useful information about their compatibility. Similarity measure can be considered as an optimization step before composing services since it enables to reduce the search time by classifying functionally similar services. This paper presents a practical approach to measure the similarity of Web services. Both semantic and syntactic descriptions are integrated through specific techniques for computing similarity measures between services. Formal Concept Analysis (FCA) is then used to classify Web services into concept lattices, and therefore generate a hierarchy of classes of similar Web services. Following this step, a composition engine takes as inputs the set of similar services and the specification of the required service, and generates the candidate composition plans that realize the goal. To determine the composition plan, the composition is reduced to a planning problem.
Keywords: Semantic Similarity; FCA; Web services; Composition.
Effective Selling Strategies for Online Auctions on eBay: A Comprehensive Approach with CART Model
by Yanbin Tu, Y. Alex Tung, Paulo Goes
Abstract: Most existing studies on selling strategies in online auctions do not distinguish auction heterogeneity when providing operational selling recommendations. They also tend to assume single objective for sellers. In this study, we incorporate seller and product heterogeneity into our analytical framework and implement data mining analysis in four auction segments. We use classification and regression tree (CART) to identify the critical factors along with their sequences for auction success and prices. We find different determinants for auction success and ending prices in these four auction segments. The classification and regression trees provide operational choices for sellers to build the most effective selling strategies. We propose that, by using expected auction prices with the classification and regression trees, sellers can integrate auction success and prices as multiple objectives in their selling strategies. Overall, this study contributes to the literature by providing an innovative methodology for effective selling recommendations, which can potentially lead to significant and smooth growth of the online auction market.
Keywords: Online auctions; electronic marketplaces; data mining; selling strategies; classification; regression.
Release Cycle Management: An Action Research Study Into A Software Company
by Kamran Syed, Neda Barqawi, Lars Mathiassen
Abstract: Software is increasingly developed in a recurrent fashion. Still, we lack theoretical knowledge and conceptual models for continuously improving software release management in such dynamic contexts. In response, we conducted an action research study to improve Software Inc.s capability to recurrently release a specific software service, Secure-on-Request. Drawing on contextualist inquiry as theoretical frame, we addressed an initial problematic situation with a recent software acquisition, complexity of service delivery, new engineering and product management teams, and low process maturity to improve the organizations approach to software releases. As a result, we offer a detailed account of the process of, the content of, and the context for transforming release management at Software Inc. through the phases of diagnosing, establishing, acting and learning. Based on these insights, we theorize Release Cycle Management (RCM) as a key practice that integrates software process improvement into recurrent delivery of software. Moreover, we offer a conceptual model for RCM that software managers can use to implement such practices into their organizations.
Keywords: Recurrent Software Development; Release Management; SPI; IDEAL Cycle; Contextualist Inquiry.
Application of the Stimuli-Organism-Response Framework to Factors Influencing Social Commerce Intentions among Social Network Users
by Mehdi Dashti, Ali Sanayei, Hossein Rezai D., Mohammad H. Moshref Javadi
Abstract: Social commerce is a new trend in e-commerce powered by social media. In this type of commerce, individuals share their knowledge, information, and experiences about different products and services. This paper employs the Stimuli-Organism-Response model to investigate the factors affecting social commerce intentions among users of social networks A total of 514 persons on three favorite social networks in Iran (i.e. Telegram, Facebook and Cloob) were investigated. Analysis of the results applying the PLS-SEM approach disclosed that firstly website or application quality, perceived interactivity, and subjective norms act as stimuli to influence, relationship quality, social support, and attitudes toward social commerce as organisms, respectively; furthermore, the latter two organisms are also impacted by social commerce construct, which is a stimulus; and perceived interactivity impacts attitudes toward social support secondly social support, relationship quality, and social attitude as organisms together with subjective norms are positively associated with social commerce intention as the response; and finally social support has a significant positive impact on relationship quality which in turn influences attitudes toward social commerce.
Keywords: social commerce; S-O-R model; social commerce intention; social network users; website or application quality; social commerce constructs; perceived interactivity; subjective norms; social support; relationship quality; attitude to social commerce.
CUSTOMER RELATIONSHIP MANAGEMENT AND THE IMPACT OF E-COUPONS ON B2C RETAIL MARKETS
by Alan D. Smith, James Shock, Robert Beaves
Abstract: As retail consumers are using mobile devices to access the Internet for information and actual purchases, retails are trying to create promotional campaigns that take advantage of this trend by offering digital coupons? However, there are a number of consumer preferences than marketers need to understand when creating marketing strategies. A survey addressed 5 factors that could affect a customers likelihood of utilizing e-coupons. It was hypothesized that customers will consider themselves loyal customers, but will change their purchase habits for retail (e.g., clothing and accessory purchases) and electronic goods due to an e-coupon offer. Customers disliked e-coupons with threshold values regardless of their annual income. Customers will consider coupon misredemption fraud as an issue for businesses in a negative light, but will admit to searching for coupon codes online. Most of the hypotheses were found to be statistically significant, suggesting management may need to re-evaluate its strategy the B2C retail industry and change how retailers implement e-coupon campaigns as a vehicle to drive CRM initiatives.
Keywords: B2C; consumer fraud; customer relationship management (CRM); e-commerce; e-coupons; promotions; customer loyalty; customer satisfaction; price sensitivity; misredemption.
What Is More Important to Internet Banking Website Users: Usability or Functionality?
by Murat Durucu, Mine Isik, Fethi Calisir
Abstract: Unlike the past, the emerging trend is to provide online services due to the developments over the course of years. Online presence becomes the most significant factor of competitiveness. At this peak, firms try to infer the dynamics that increase customers acceptance of these services. The present study aims to identify the complex relationships among the various factors of usability and functionality. Analytic Network Process (ANP) was selected by the merit of its interdependence perspective to see the comparative effects of usability and functionality factors on Internet banking (IB) website selection. The information gathered through two questionnaires that conducted for Is Bank and Yapi Kredi Bank IB website users. The findings reveal that customers give higher priority to usability and usability-related factors, namely navigation and interaction rather than functionality. Another point worth mentioning is that information provision and security also prepossess the customer preference.
Keywords: Internet banking; usability; functionality.
Information technology and the supply chain integration: A business executives context
by José Luis Martinho, Carlos F. Gomes, Mahmoud M. Yasin
Abstract: Despite the abundance of research dealing with the impact of supply chain management on todays organizations, such research tended to emphasize discreet relationships. A cross-sectional sample of Portuguese organizations are used to test several hypotheses pertaining to organizational resources, competencies, different levels of supply chain integration, and organizational performance. Based on the findings, the impact of information technology infrastructure flexibility exhibited mixed results on the constructs studied. Executive information technology competencies tended to positively influence the different types of supply chain integration. Internal integration was found to have a direct influence on organizational performance. Such internal integration is being encouraged by external entities including customers and suppliers. In this context, more integration might lead to more effective organizational performance. Therefore, it is concluded that organizations should integrate their resources, processes, and in the process encourage effective utilization of information.
Keywords: Information Technology; Performance measures; Flexibility; IT Competencies of Business Executives; Supply Chain Integration.
THE DEGREE OF POSSESSION AND KNOWLEDGE OF MOBILE PHONES FOR TRADING ACTIVITIES BY PETTY TRADERS IN NIGERIA
by Bilkisu Farouk, Oyijewu David, Ikwuoche David
Abstract: The study assessed the degree of possession and knowledge of the usage of mobile phones by petty traders in performing their trading activities. Using purposive sampling technique 400 petty traders were selected and administered with questionnaires out of which 249 questionnaires were valid for use after scrutinizing the 400 questionnaires. Percentage and frequency distribution with chi-square test was used for the empirical analysis. The results of the analyses showed that at 5% significance level, the possession of mobile phones and the knowledge of the use of mobile phones for performing trading activities by petty traders exist with a significant effect on their businesses, significant loyalty on the side of the petty trader to customers and suppliers and vice versa, significant impact of mobile telephony on the growth of petty traders businesses, convenience in business transaction between the petty trader, supplier and customers and reduced transaction cost. Based on the outcome of the analyses the study recommended that stakeholders in the Nigeria telecommunication industry and the government should devise an enabling purchasing structure for petty traders to own mobile phones through cheap and convenient sources. Also, the level of awareness of petty traders on the benefits of mobile telephony for trading activities should be enhanced by stakeholders in the Nigeria telecommunication industry and government of Nigeria as well.
Keywords: Mobile phones; Petty traders; Possession; Knowledge; Trading activities.
Monitoring and Modeling Service Level Agreement of Multiple Virtual Machines in Cloud Computing
by Abdel-Rahman Al-Ghuwairi, Zaher Salah, Ayoub Alsarhan, Shatha Al Qudah, Ghadeer Al Qahmous, Aladdin Baarah, Ahmad Aloqaily
Abstract: Nowadays, Cloud Computing becomes the most widespread environment that provides several services over the internet. However, improving the customers' trust with cloud computing requires monitoring and ensuring the quality of the provided services continuously. Therefore, this paper provides a model for the process of monitoring the Service Level Agreement (SLA) to maintain specific Quality of Service (QoS) parameters. The proposed model assists in monitoring the cloud with multiple Virtual Machines (VM's) in the same environment, which belongs to the same customer. The core foundations for this model are: SLA, QoS parameters, multiple VM's and violations' penalty assessment. This model helps in enforcing and monitoring the service level agreement (SLA). Moreover; observing the quality of service within multiple virtual machines environment, which is described as complex, resource consuming and imposes workload over the cloud system. The proposed model for monitoring the (QoS) parameter in multiple VMs environment works dynamically and checks for any violation. Moreover; the penalty for each violation will be calculated and informed to the customer and provider at the same time. The same SLA which belongs to the same customer and a specific provider will be monitored and managed through multiple VMs. The proposed model depends on the time factor while running the VMs in sequentially manner with a short period of time as a gap between each VM. The proposed model will prevent any interception between VMs and can maintain synchronization.
Keywords: Cloud Computing; Service Level Agreement (SLA); Quality of Service (QoS); Multiple Virtual Machines (VM's); Violation Penalty.
What Drives the Intention to Repurchase Digital Items in Digital Games? An Integration of Uses and Gratifications Theory and the Expectation-Confirmation Model
by Hilmy Mahfuzra, Achmad Nizar Hidayanto, Ika Chandra Hapsari, Prahastiwi Utari
Abstract: This study aims to investigate the effect of gratification on the intention to repurchase digital items in digital games by extending the expectation-confirmation model in order to include the perceived value. Data obtained from 495 respondents were analyzed using structural equation modeling (SEM) with the help of the SmartPLS 3.0 tool. The results of this study indicate that both enjoyment and customization influence users intention to repurchase digital items in digital games through satisfaction, while enjoyment, social presence, and social interaction influence users intention to repurchase digital items in digital games through perceived value. Our results also demonstrate that both satisfaction and perceived value influence users repurchase intention, which confirms the validity of our extension of the expectation-confirmation model.
Keywords: Digital items; digital games; uses and gratification; online game community; repurchase intention; expectation conformation model; structural equation modeling; SEM.
Factors Influencing Business Intelligence-Enabled Success in Global Companies: An Empirical Study
by Michael Gonzales, Somnath Mukhopadhyay, Kallol Bagchi, Leo Gemoets
Abstract: Global companies recently invested heavily in business intelligence (BI) with an expectation of achieving a long-term BI-enabled success. However, there is little statistical evidence in the past research to answer the following two questions (1) which factors provide BI-enabled success in global companies?, and, (2) what is an acceptable model for achieving BI-enabled success? The study identifies three important factors that influence BI-enabled success in companies. We build a structural model to answer the above questions for global companies. The study concludes with important managerial implications.
Keywords: business intelligence; data warehouse (DW); information technology (IT); structural equation model (SEM).
CONNECTIVE INTELLIGENCE TO STAY SAFE WHILE SHOPPING ONLINE FOR E-PRODUCTS AND E-SERVICES ON BUSINESS-2-BUSINESS AND BUSINESS-2-CONSUMER WEBSITES
by ISAAC OSUNMAKINDE, Thembekile Mayayise
Abstract: E-commerce markets provide benefits for both buyers and sellers; however there are risks involved. Trust in e-commerce is vital to promote adoption. Various models have attempted to mitigate online risks but are limited in certain respects such as factoring compliance in e-commerce assurance models. The aim of this study is to propose a connective intelligent model for safe online shopping called Page Ranking Analytical Hierarchy Process (PRAHP). PRAHP utilises a complimentary techniques of the analytical Hierarchy Process (AHP) and Page ranking (PR) to evaluate the trustworthiness of the web attributes. PRAHP assesses 5 important attributes from 10 selected e-commerce websites. PRAHPs paradigms were evaluated on both Business-to-Business (B2B) and Business-to-Consumer (B2C) e-commerce sites and validated by customer comments. The inbound links were also adjusted to test their effect on the reliability of PRAHP. Fifty percent, 40% and 10% of the sites are partially trustworthy, untrustworthy and fully trustworthy sites respectively. The results revealed that the model provides reliable results to guide customers in making informed purchasing decisions.rnThe work makes a valuable contribution in the e-commerce security and compliance through the integration of the theory of AHP and Page ranking techniques fuzzing into a decision table for alleviating trustworthiness anxiety from e-commerce transacting partners.rn
Keywords: E-commerce Assurance; Compliance; Business-2-Business; Business-2-Consumer; Analytical Hierarchy Process; Page Ranking; Security; Trustworthiness.
EaaS Infrastructure Disruptor for MSE
by Poh Soon JosephNg
Abstract: Equipping Malaysias $3 billion markets worth Medium Size Enterprise with an optimize information technology infrastructure is a major challenge during the volatile business environment. This paper advances beyond traditional cloud-based infrastructure which relies heavily on internet service provider while our solution focuses on LAN based virtual grid to provide reliable services. Our pessimistic discussion into legacy Harvard University theories on the commodity of infrastructure and technology disruptor reveals the need for an updated strategic viewpoints on the possible consolidation available yet hidden infrastructure features while sustaining the economic uncertainty. The research is supported using a test-retest data of 100 samples and 122 sample from Peninsular Malaysia. The compiled information using Spearman Correlation gave alarming contribution from the unproductive 29% investment into building a much needed dynamic infrastructure to storm thru the economic turbulence, yet boost competitive difference when market bull run. Our client-server grid solution redistributes workload into existing and available desktop to form a virtual centralize server that can grow or shrink with the business size. The revised Exostructure as a Service framework concludes the importance to revisit back local infrastructure disruptor.
Keywords: cloud computing; economic turbulence; EaaS; exostructure; framework; grid computing; IaaS; ICT infrastructure; Malaysia; optimization; reusability; resource pooling; Small and Medium Sized Enterprise; virtualization.
Strategic Information Systems Planning (SISP) IN Kingdom of Bahrain: Factors and Impact of adoption
by Jaflah Al-Ammary
Abstract: SISP in most of the Arabian countries is merely tackled to plan for resources allocation and project-based planning with a bottom up approach without any consideration to the strategic role of IT in achieving the business goals and satisfying the overall business strategy. Therefore, the current research tackled to investigate the current situation regarding the adoption of SISP in the organizations in the Kingdom of Bahrain with the focus on the fields of telecommunication, manufacturing and financial. Moreover, the influence of the internal and external factors on the adoption of SISP as well as the impact of such strategic planning on the organization competitive advantage was explored. A quantitative research method was adopted to achieve the research goal. Four hundred surveys were distributed to different levels of management from the selected sectors in Kingdom of Bahrain. The results identified many indications on the importance of the SISP in the organization at Kingdom of Bahrain and the positive perception on the impact of SISP in supporting the business and improving the organization overall performance. Such results will encourage more efforts in developing SISP and assuring the alignment between IT and business in order to enhance the strategic role of Information Systems and gains more sustainable competitive advantage.
Keywords: SISP; Top management involvement; external environment; IT and Business alignment; Competitive advantage; Social pressure.
Role of Electronic Word of Mouth on Purchase Intention
by Wajeeha Aslam, Kashif Farhat, Imtiaz Arif
Abstract: The purpose of this study is to explore the impact of electronic word of mouth on brand image and customer satisfaction and these two variables contribute in consumers purchase intention. Impact of online websites on electronic word of mouth and impact of receivers perspective on customer satisfaction and brand image was also checked. A self-administered Likert scale questionnaire was used in order to get the responses. Research model was tested empirically by using the sample of 253. The study finds out the positive impact of electronic word of mouth on customer satisfaction and brand image. This confirms that electronic word of mouth contributes satisfaction and positive brand image in the mind of consumers who does online shopping. Customer satisfaction and brand image also have a significant impact on purchase intention. Results also confirms that online website have a positive and significant impact on electronic word of mouth. Similarly, receivers perspective has a significant impact on customer satisfaction and brand image. This research explains theory of stimulus- organism- response paradigm to identify the impact of electronic word of mouth which effect brand image and customer satisfaction in online and technological generation. The paper provides valuable information to marketers that how quality website generates positive word of mouth which leads to purchase intention.
Keywords: Electronic word of mouth; brand image; customer satisfaction; social media; online websites; receiver’s perspective; purchase intention; technology.
Impact of Technology Evolution on the Materialised Views: Current Issues and Future Trends
by Abderrazak SEBAA, Amina NOUICER, Abdelkamel TARI
Abstract: To improve query performance materialised views were largely used for such purpose. So far, this technique has been a success as testified by the large and increasing interest among industrial and research communities in the use of this technique. In this paper, we investigate the related issues of materialised views and the most important solutions and framework of the literature review. Then, we explore the information technology impact on the evolution of materialised view applications, related environments, and data models. Finally, we summarize the opportunities and future challenges caused by combination and trends of such evolution.
Keywords: materialised view; view selection; view maintenance; data models; application; Web; data warehouse; database; query; information technology.
Building Federated Data Warehouse Schema Using Web Service Approach
by Nouha Arfaoui, Faiçal Felhi, Jalel Akaichi
Abstract: The data warehouse is considered as a repository that stores data from disparate sources. It is used mainly in the process of decision making.
Because of the diversity of the applications, their heterogeneity and their physical spacing, building a data warehouse, to make decisions in a federated architecture, is a very complicated task. To overcome this problem, we propose a new approach for the design of a federated data warehouse schema based on the web services. The latter are applied because of their capacity to solve many technical problems related to the integration of data source in a federated environment. The proposed solution is based on the bottom-up approach where the data warehouse schema is generated from the set schemas of the data mart. It is composed by two steps. In the first one, a web service is used to generate the schemas of the data mart one for each data source. In the second step, a second web service is used to merge the generated schemas to build the final schema of the data warehouse.
Keywords: Federated Architecture; Federated Data Warehouse Schema; Data Mart Schema; Web Service; Schema Integration; Schema Merging.
Defining One Product Data for a Product
by Risto Silvola, Arto Tolonen, Janne Harkonen, Harri Haapasalo, Tarja Mannisto
Abstract: The growing importance of product data management and master data necessitate companies to have practices for deriving product master data from their corporate strategy. Business drivers need to be understood from the perspective of corporate strategy to capture product master data in relevant systems in a straightforward manner. Ideally master data is created only once and used through the life-cycle of the product. This study clarifies the foundations for determining one product data from corporate strategy. Data definitions are analysed to understand its linkages to business drivers, whereas main business processes are used to support categorisation. The practices of three companies are analysed to understand how business drivers for new products impact product data requirements. The results highlight the importance of business drivers in defining one product data based on the product master data, business-process related product data and IT systems over the product life-cycle.
Keywords: One product data; product data; product master data; master data management; strategy; IT systems; Business Information Systems; product life-cycle; business processes.
A study of Feature Selection techniques for predicting customer retention in Telecommunication sector
by E. Sivasankar, J. Vijaya
Abstract: Churn is a termination of a contract between customer and company or quitting customer using the product or service. The goal of Churn Management (CM) is to reduce customer losses and retain profitable customers. Churn prediction is an important measure that leads to the solutions for the development of any business or industry; mainly it has lots of impact in telecommunication field. The eventual aim of the organization is to retain the existing customer base, because adding new customers may need investment of money, human resource and additional time. In the current era many researches and industries focus on effective research on churn prediction. Based on the analysis of works performed in the past, it is comprehended that there is some lagging in identifying necessary features in the telecommunication field and also the performance of the telecommunication sector is challenging due to the highly complex dimensional data sets.Feature selection is the process of eliminating irrelevant features from the data set, while maintaining acceptable classification accuracy. The selected features play an important role which can directly influence the effectiveness of the resulting classification. In this paper, a methodology is proposed consisting of two phases, attributes selection and classification based on the attributes selected. Phase one uses a Filter and Wrapper method for attribute selection with Random over-sampling (Ros) through which the size of attributes set and misclassification error can be reduced. In the second phase, the selected attributes are taken as inputs by classification techniques like Decision Trees(DT), K-Nearest Neighbor(KNN), Support Vector Machine(SVM), Naive Bayes(NB) and Artificial Neural Network(ANN). In this work the data set KDD Cup 2009 is used for evaluating the performance. Finally True Churn, False Churn, Specificity and Accuracy are measured to evaluate the efficiency of the proposed system and it is found that the above mentioned methodology performs well ahead for churn prediction and suits well for the telecommunication sector.
Keywords: Churn prediction; Random over sampling; Feature selection; Filter method; Wrapper method;Classification;DT;KNN;SVM;NB;ANN.
RELATIVE EFFICIENCY OF SOCIAL CRM SOFTWARES: A HYBRID FUZZY AHP/DEA APPROACH
by V. Raj Kumar, L. Suganthi
Abstract: In todays tech-savvy society, social media platforms revolutionize the way in which people communicate and share information with each other. These platforms enable customers to instantly and openly convey their opinions, criticisms and praises on various topics pertaining to products and brands. Hence it becomes imperative for organisations to integrate social media information into their CRM strategy. In this paper, relative efficiency of the Social CRM packages using fuzzy AHP/DEA:AR-CCR was determined by considering price as the input criterion and functionality, product quality and customer support as output criteria. Using fuzzy AHP it was found that product quality (41.66%) is the most important criteria followed by functionality (33.29%) and customer support (25.05%). Pipedrive and Really Simple Systems were found to be relatively more efficient. In this manner a Social CRM package that best fits an organisations customer-centric work culture is selected. The Social CRM vendors can utilise these results to benchmark their packages against their competitors.
Keywords: Customer Relationship Management; Social media; Fuzzy Analytical Hierarchical Process; Data Envelopment Analysis; Relative efficiency.
An Adaptive Algorithm for Frequent Pattern Mining over Data Streams using Diffset Strategy
by Subbulakshmi Balasubramanian, Deisy Chelliah
Abstract: Frequent pattern mining using sliding window over data streams is commonly used due to its wide applicability. Determining suitable window size and detection of concept change are the major issues and can be addressed by having flexible window based on amount of changes in frequent patterns. For mining frequent patterns over data streams, vertical mining algorithms can be used. However, in these algorithms, size of transaction identifiers (tidsets) and the time for computation of intersection between tidsets is large. Moreover, presence of null transactions does not contribute any useful frequent patterns. A new algorithm called Recent Frequent Pattern mining based on Diffset with Elimination of Null Transactions (RFP-DIFF-ENT) over data streams using variable size window is proposed. It stores difference of tidsets and eliminates null transactions which minimize memory and mining time. Experimental results show that proposed algorithm saves computation time, memory usage and minimizes the number of frequent patterns.
Keywords: Frequent Itemsets; Diffset; Data Streams; Sliding Window Model; Concept Change.
Towards Developing an Automated Attendance Management System using Barcode Reader: Hashemite University as a Case Study
by Subhieh El-Salhi, Safa'a Al-Haj Saleh, Ibrahim Al-Amro
Abstract: In higher educational institutions such as colleges and universities, student attendance has a significant impact on the academic outcomes and thus on the overall educational process. Therefore, the need for an automatic attendance registration system is one of the most critical requirements in educational process nowadays; especially with the tremendous growth in technology sectors. This paper presents an Automated Attendance Management System (AAMS) where the attendance of the students is recorded automatically to overcome the manual attendance tracking system flaws. The proposed system consists of two main components, a student identification number and a hand-held scanner. The AAMS system is mainly designed for the Hashemite University, one of the leading universities in Jordan, to replace the old and inefficient current manual attendance system with a portable, simple, easy and low-cost solution of attendance registration system. Details of a real implementation of AAMS system within the university are illustrated and presented.
Keywords: Automated Attendance Management System (AAMS); Barcode Reader; Student identification card.
Investigating Q-learning approach by using reinforcement learning to decide dynamic pricing for multiple products
by Fakhrddin Maroofi
Abstract: The focus of this paper is on the benefits of application of interdependent dynamic pricing that is unlike individual pricing of products or services. This article considers a revenue management problem of multiple interdependent products, in which adjusted over a finite sales horizon to maximize expected revenue, given an initial inventory for each product. This article is to use reinforcement learning to model the ideal pricing of multiple interdependent products when demand is stochastic and its functional form unknown. We show that reinforcement learning can use to price interdependent products. Moreover, we analyze to behave the Q-learning with eligibility trace algorithm under different conditions. We explain our analysis with the pricing of services.
Keywords: Q-learning approach; Reinforcement learning; Revenue management; Service management; Simulation; Iran.
An Empirical Study on Factors Affecting the Acceptance of M-commerce Application among Small and Medium-Sized Tourism Enterprises by Integrating TTF with TAM
by Saleh Alqatan, Noor Maizura Mohamad Noor, Mustafa Man, Rosmayati Mohemad
Abstract: Tourism is an attractive sector for economic development as it offers potential economic benefits for developing countries. Most tourism sectors throughout the globe consist of Small and Medium-sized Enterprises (SMEs) and as such, tourism SMEs (SMTEs) utilization of Mobile commerce (M-commerce) is crucial in terms of added efficiency, effectiveness and innovation. However, there is a low level of acceptance for M-commerce applications in SMTEs in most developing countries. In such countries, effective applications and factors that impact the acceptance rates of M-commerce in SMEs, is still in the early stage. More importantly, the factors impacting the application of M-commerce are still ambiguous and the relevant theories for M-commerce acceptance have largely been untouched in literatures in the context of developing countries, particularly in Jordan. The paper aimed to test the factors influencing the acceptance of M-commerce application among SMTEs. The questionnaire was distributed to the target sample and the obtained data from questionnaires was analyzed through the SPSS statistical software. Results of the analysis revealed that all factors positively influenced behavioural intention to use M-commerce application in such enterprises. The study provides advanced knowledge of users acceptance of M-commerce in SMTEs, which will help the M-commerce providers in such enterprises to understand the factors that influence the acceptance of M-commerce in SMTEs, which in turn, plays an important role in increasing the acceptance level of M- commerce in SMTEs.
Keywords: M-commerce; Small and Medium-sized Tourism Enterprises; Technology Acceptance Model; Task-Technology Fit model; perceived trust.
Secure Cluster based Data Aggregation in Wireless Sensor Networks with Aid of ECC
by C. SriVenkateswaran, Sivakumar D.
Abstract: Wireless sensor networks are widely deployed for wide range of applications for gathering information about the desired application. In general, sensor nodes sense their environment, collect sensed data and transmit it to the base station. During this transmission of sensed data from node to sink there is a lot of energy get reduce. In-order to overcome this problem, some of the researchers used cluster head-based approach to send the data to the sink node. The cluster heads collects all traffic from their respective cluster and performs data aggregation before transmitting the data to the sink. In this paper, we have presented the approach for cluster head selection for data aggregation in wireless sensor network. For clustering the node, the proposed method is use hybrid k means and fuzzy c means clustering algorithm. Then we select the cluster head from each cluster. Every node in the wireless sensor network sends their sensed data to the cluster head. The data aggregation is done in the cluster head. Finally base station is received the data from one cluster head, in order to reduce the transmission time here the proposed method is remove the duplicate data and then secure transmission is done by Elliptic curve cryptography (ECC). The performance of the proposed technique is evaluated by overall running time and also the encryption and decryption time. Finally, the simulations are performed and the results are analyzed within the simulation set up to determine performance of the proposed algorithm in the sensor network.
Keywords: data aggregation; wireless sensor network; k means clustering; fuzzy c means clustering; Elliptic curve cryptography.
Intention to Adopt Mobile Banking in Bangladesh: An Empirical Study of Emerging Economy
by Md Shamimul Islam, Noorliza Karia, Muhammad Khaleel, Firdaus Bin Ahmad Fauzi, Mohamed Soliman Mohamed Soliman, Jamshed Khalid, Md. Yeasir Arafat Bhuiyan, Md. Abdullah Al Mamun
Abstract: Mobile banking is an advanced form of traditional banking. In Bangladesh, despite the initiatives by the banking companies to continuously upgrade their facilities to support mobile banking, customers' adoption rates are still low. Thus, the aim of this study is to investigate the factors influencing the behavior of customers to adopt mobile banking. By adaptation of the Unified Theory of Acceptance and Use of Technology (UTAUT), the study used Partial Least Square (PLS) and Structural Equation Modeling (SEM) to achieve the result. It was found that all the factors listed are significantly influencing the behavior of the customers, except the factor of performance expectancy. The study concluded that the mobile users outside Dhaka, the capital city of the country, are not much aware of mobile banking as compared to mobile users in the capital city. By extending the previous study, this study contributed to the existing literature and to the body of knowledge in general. The theoretical and managerial implications,as well as the directions for future research were also stated.
Keywords: mobile banking; technology adoption; UTAUT; emerging economy; Bangladesh.
Semantic Technology and Linguistic Modeling in Business Strategy Design and Evaluation
by Jozef Stasak, Peter Schmidt
Abstract: This paper addresses the problem of a knowledge based support, when designing business strategy and adequate key performance indicators (KPI). The business strategy designing is considered to be a business process and is a subject of modelling as well, while a linguistic modelling approach is applied for those purposes, where the business process model semantics plays a role of principal importance and that model is derived from text in natural language (TNL text), which describes structure and functionality of the business processes to be modelled quantified via linguistic sets, which create basis of business process model semantics and might be applied in design and implementation of Business Process Linguistic Modelling - Expert System built up base on semantic technology principles (ST-LM Expert System). The ST-LM Expert system Knowledge Base operates based on semantic networks and (SNW) and reference databases and contains knowledge concerned to KPI Indicator generation and decomposition to lower levels of management. In that paper, the ST-LM Expert System structure and functionality is described together with an appropriate knowledge base and inference mechanism.
Keywords: business process; linguistic modelling; expert system; knowledge base; inference mechanism; semantic networks; reference databases.
A hybrid model for customer credit scoring in stock brokerages using data mining approach
by Rahmat Houshdar Mahjoub, Amir Afsar
Abstract: Credit scoring has become a challenging issue for stock brokerages, as the credit industry has been facing high competition during the past decade. Many methods have been suggested to credit scoring in the literature. The purpose of this study is to set up a hybrid model for customer credit scoring in Iran's National Investment Brokerage. It also provides a way to pay appropriate facilities as tools for CRM. So, after the data preprocessing step, we convert refined data set into RFM model. Customers were clustered using two clustering algorithms, self-organizing map (SOM) and K-means. In both methods, the best optimum number of clusters was calculated at 10. Afterwards, the clusters ranked using TOPSIS and the top three clusters were considered as the target customers. Eventually, the credit score of the superior cluster members were calculated. Coefficient facilities granted to the top three clusters respectively are 0.271, 0.173 and 0.556.
Keywords: Credit scoring; Customer relationship management; RFM; SOM; K-means; Data mining; TOPSIS.
Exploring the antecedents of co-creation in hospital-supplier relationship: An empirical study on private sector hospitals in India
by Samyadip Chakraborty
Abstract: One of the biggest challenges in healthcare is cost containment. In the face of continuously spiralling cost hospitals are facing steep competition to provide increased access to high quality services. In this backdrop, network relationship become vital and offers extensive opportunities to explore hospital-supplier relationships. Past literature highlights interaction and collaborative ambience as prerequisite to value co-creation. This study focuses on co-creation aspect in the hospital-supplier relationship context (medical-surgical suppliers) and uses a Service-Dominant Logic lens besides drawing support from Relational-View and Relational-Coordination-Theory.rnThis study aims at empirically exploring the relational antecedents of co-creation and establishing Prahalad and Ramaswamys (2004) DART(Dialogue-Access-Risk-Assessment-Transparency)framework, trust and commitment as antecedents to co-creation. Data were collected from 229 private tertiary-care hospitals in and around four major urban areas in India. The relationships proposed in the research model were tested using structural equation modelling. Results indicaternthat the DART parameters and the relational variables (trust, commitment) act as antecedents to co-creation and have significant and positive relationship, thereby enhancing co-creation activities. The study also explored the impact of interdependence between hospital and suppliers on DART parameters,rntrust and commitment besides exploring trust to DART linkages and structural model outcomes indicate significant and positive relationship for the linkages.
Keywords: Healthcare; Co-creation; Hospital-supplier relationship; Supply Chain Management; Trust;Interdependence; DART; Purchasing.
Managing Privacy of Sensitive Attributes using Fuzzy based Data Transformation Methods in Privacy Preserving Data Mining Environment
by V.K. SAXENA, Shashank Pushkar
Abstract: When we extract personal, sensitive and business information in data mining applications, then certain problems occurs. Privacy attack occurs due to the misuse of individual information. It means that privacy concerns are challenging for data miners. In data mining applications privacy preservation is multifaceted effort because it assures the privacy of respective devoid of trailing the veracity of the various data mining outcomes. When analyzing the data in any company or government organizations, these types of data become very much important. In privacy preserving, data proprietor have to provide an elucidation for achieving the twin goal of privacy preservation in addition to precise clustering outcome. In centralized database environment, data transformation methods in fuzzy based data in the field of privacy preserving clustering are proposed in this paper. In first case, a fuzzy data transformation method is proposed and different experiments are conducted by changing the fuzzy membership functions such as Z-shaped fuzzy membership function, Triangular fuzzy membership function, Gaussian fuzzy membership function to transform the original dataset. In second case, a hybrid method is proposed as a combination of fuzzy data transformation approach which is specified in first case and Random Rotation Perturbation (RRP). The experimental outcome verified that the hybrid approach permits finest results for every member functions.
Keywords: Fuzzy Membership Function; Privacy Preservation; Data Transformation; Clustering; Random Rotation Perturbationrn.
Privacy preserving of intermediate dataset using hybridization of Oppositional Gravitational Search Algorithm and Elliptic Curve Cryptography
by Saravanan S, Venkatachalam V
Abstract: Distributed computing gives the gigantic capacity ability to the clients to send their applications without any infrastructure investment. Based on the application lot of intermediate dataset will be created. To protecting these intermediate dataset is a challenging task. Moreover, encrypting all dataset is a time and cost consuming. To overcome the problem, in this paper we proposed a privacy preserving of intermediate dataset using a combination of Oppositional Gravitational Search Algorithm and Elliptic Curve Cryptography (OGSA+ECC). Initially, we split the dataset into a number of the intermediate datasets, then, we choose the node corresponding intermediate dataset from the cloud using an oppositional gravitational search algorithm (OGSA). After that, we choose the sensitive data from the dataset using the information gain measure to minimize the processing time and cost. Then, using the ECC algorithm the sensitive data is encrypted and in the cloud the secure data are stored. The experimentation is carried out in terms of encryption time and memory use.
Keywords: Cloud computing; OGSA; ECC; CSP; POS; trapdoor; encryption; decryption.
Predictors of E-government adoption in India: Direct and Indirect effects of Technology Anxiety and Information Quality
by Kapil Kaushik, Rajhans Mishra
Abstract: E-government adoption has been the focus of many research studies in the past. However, few studies have explored the role of technology anxiety and information quality in the E-government adoption process. The purpose of this paper is to examine the direct and indirect effects of technology anxiety and information quality on E-government adoption. The results of our study indicate that technology anxiety indirectly influences E-government adoption. At the same time, the direct effect of technology anxiety on E-government adoption weakens in the presence of effort expectancy. Perceived information quality has positive direct effect on E-government adoption. However, we did not find any significant indirect effect of information quality on E-government adoption. This study contributes to E-government adoption frameworks by analysing the effect of computer and internet related anxiety and information quality on the adoption of E-government services. Implications for theory and practice that would help the policy makers in enhancing the effectiveness E-government services are discussed.
Keywords: E-government adoption; Information quality; Technology anxiety; Indirect effect.
To identify the determinants of the CloudIoT technologies adoption in the Indian MSMEs.: Structural Equation Modeling Approach
by Vaibhav Narwane, Balkrishana Narkhede, Rakesh Raut, Bhaskar Gardas, Pragati Priyadarshinee, Mahesh Kavre,
Abstract: In everyday life, we come across multiple emerging applications of CloudIoT like the smart phone, smart television, smart city, smart factory, smart agriculture, etc. CloudIoT is the collaboration of cloud computing and Internet of Things technology. Even though IoT and cloud are having contradicting characteristics, the collaboration of IoT and cloud helps in solving their issues partially and gives rise to new services. The objective of this study is to develop a model using the structural equation modeling approach to identify the determinants of the CloudIoT technologies adoption in the Indian MSMEs. The determinants considered for the study were cloud computing, perceived IT security risk, social influence, Internet of Things, perceived ease of use, perceived usefulness, trust, and intention to use. The data were collected from the 500 respondents of Indian MSMEs. The results of the investigation revealed that cloud computing, social influence, Internet of Things, perceived ease of use, trust, and perceived IT security risk positively influence the intention to use. The developed model is intended to guide the organizational managers, decision, and policy makers in understanding the relationship between the various determinants and intention to use CloudIoT technologies.
Keywords: Internet of Things (IoT); cloud computing; CloudIoT; micro; small and medium enterprises (MSMEs); structural equation modeling (SEM).
Evaluation of Telecommunications Regulatory Practice in the Kingdom of Bahrain: Development and Challenges
by Adel Al-Alawi, Sara Al-Bassam
Abstract: This study has investigated the evaluation of Telecommunications Regulatory Authority (TRA) practice in the Kingdom of Bahrain. Having realized the importance of telecommunication, Bahrain has become one of the leading Information and Communication Technologies (ICT) economies in the Gulf Cooperation Council (GCC) region and is ranked among the top 30 in the world. Such a ranking has encouraged the researchers to take Bahrains TRA as the focus of this study. The aim of this paper is to evaluate and identify the factors that have influenced the TRA framework in the Kingdom and to investigate the development and challenges of TRA in Bahrain and how to lead to the best performance in the market place. The study also investigated the role of certain factors in Telecommunication Regulation. Interviews and surveys with the TRA and major operators in Bahrain were conducted. The findings show that Licensing, Interconnection, Price Regulation, Competition Policy and Universality Access are key factors influencing the telecommunication regulatory framework in Bahrain.
Keywords: TRA; telecommunication regulatory authority; Bahrain; licensing; interconnection; price regulation; foster competitive markets and universality access; Batelco; Zain; VIVA; Menatelecom .
Identification and prioritization of the critical success factors for research project-based organizations using fuzzy analytic hierarchy process
by Mehdi Tabaroki, Changiz Valmohammadi, Nader Khalesi
Abstract: The main purpose of this study is to identify and prioritize critical success factors by using analytic hierarchy process (AHP) technique in research project-based organizations which is based on literature review and related research in this field and experts opinions .To this purpose , in the model selection and validation step , a questionnaire was designed and distributed among professionals and its validity and reliability have been investigated .In order to complement and enhance the validity of the study ,experts were interviewed and then the model was presented and information was analyzed. The ranking of the main of critical success factors (CSFs) using fuzzy AHP method reveals that the project factors with a weight of 0.445 is the most important among the identified factors. Considering the current lack of understanding of CSFs within the local context, this study is one of the first attempts to gain an understanding of the CSFs in the Iranian industry context. The results of this research can be remarkably help to project leaders of these organizations in the face of project challenges and successful implementation of research projects.
Keywords: Project-based organizations; Research organizations; Critical Success Factors (CSFS); Fuzzy Analytic Hierarchy Process (FAHP); Iran.
Cluster Analysis for Diabetic Retinopathy Prediction using Data Mining Techniques
by Tanvi Anand, Rekha Pal, Sanjay Dubey
Abstract: Diabetic Retinopathy is a one of the increasing medical situation occurs due to fluctuating insulin level in the blood that leads to loss of vision. It is an ophthalmic disease which is mainly occurs due to the generation of the new abnormal blood vessels. Diabetic retinopathy with exudates are causing main health problem that leads to loss of sight. Patient suffering from diabetes are advised to undergo continual retinal test by reason of diabetic retinopathy. As the population is quite large as compared to health care system available, tests should be optimized and identification of the disease is complex and time consuming task. In this paper clustering technique is used among the various Data Mining techniques, clustering is the good approach to handle the complex task. Experiment is conducted to identify the best clustering technique which can easily identify the various impacting factors pf DR in less complex way. The experimental results reflect that the performance of K-Means is better than other clustering techniques. This analysis will help the medical practitioner to identify best algorithm for disease detection and provide preventive measures in advance.
Keywords: Clustering techniques; disease; data mining; classification.
An Exploratory SOLAP Tool for Linked Open Data
by Daniel Farias Batista Leite, Claudio De Souza Baptista, Brunna De Sousa Pereira Amorim
Abstract: Business intelligence (BI) Technologies are being successfully applied in data analytics, including in the use of spatial data. The advent of the Semantic Web brought semantically rich and semi-structured data formats, such as RDF (Resource Description Framework), which are external to the BI infrastructure. The integration of both conventional and Semantic Web data into a BI system results in a new category of analytical tools called exploratory OLAP. We extend exploratory OLAP with spatial capabilities, providing an exploratory SOLAP, called ExpSOLAP. ExpSOLAP is the first analytical tool that integrates semantic, spatial, semi-structured data with traditional spatial, structured data sources. Additionally, SOLAP queries can be posed in both data sources.
Keywords: Business Intelligence; Exploratory SOLAP; Semantic Web; Ontology; Linked Data; SPARQL; SOLAP; Open Data; RDF; DW.
The Significant of Personal Characteristics and Situational Characteristics as mediating factors in influence Information Source and Information Choice strategies of the Arab Tourists in Malaysia
by Bilal Al-khateeb
Abstract: In an attempt to further explain how information source influences the information choice strategies; the study investigates the mediating effects of both personal characteristics and situational characteristics on the relationship between information source and information choice strategies of the Arab tourists. The study covered all the Arab tourists visiting Malaysia between 2011 to 2012. A questionnaire data was generated from 358 respondents of Arab tourists in Malaysia through self-administered questionnaire procedure, and the questionnaire data was analyzed using the SmartPLS analysis technique. Overall, the study found significant mediating effects of both personal characteristics and situational characteristics on the relationship between personal characteristics and information choice strategies. The findings further show a partial mediating effect for the personal characteristic while a full mediating effect was found on the situational characteristics variable. Based on this, the study concludes that personal characteristics and situational characteristics can jointly mediate the relationship between personal characteristics and information choice strategies. The study provides some insights on the importance of personal characteristics and situational characteristics and the need to consider the two factors when planning for tourism adventures by the Arab tourists.
Keywords: Personal characteristic; Situational Characteristics; Information Source; Information Choice strategies; Tourism; SmartPLS.
Designing an e-commerce recommender system based on collaborative filtering using a data mining approach
by Samira Khodabandehlou
Abstract: E-commerce recommender systems have been converted to a very important decision-making helper for customers, due to the wide variety of goods and services offered by e-commerce companies. These systems provide online personalized recommendations using information technology and customers information. In the meantime, Collaborative Filtering (CF) recommender systems are one of the key components of successful e-commerce systems. Despite the popularity and successes of CF, these systems still face a series of serious limitations, including cold start, Sparsity of user-item matrix, scalability and change of user interest during the time that impede exact recommendations to customers. Although much research has been presented to overcome these limitations, but no comprehensive model is yet offered to reduce them. Therefore, the present research aims to eliminate the limitations of CF and to provide a comprehensive system by employing a set of data collection methods in order to present the best and most reliable recommendations to customers for product selection. The proposed system has been implemented in 5 stages including: 1. Customer segmentation based on LRFM variables in the level of product category to evaluate the Length of customer relationship with the company, Recency, Frequency, and Monetary of purchasing product categories 2. Extracting association rules based on user-category matrixes in the level of each cluster 3. Customer segmentation according to demographic variables 4. Change of user-item matrix and reduction of its dimensions 5. Developing a new similarity function by weighted combination of results of segmentation methods and CF. According to the gained results, the proposed system of this research has resulted in the removal of traditional CF constraints and presenting more accurate and appropriate recommendations for the preferences of customers.
Keywords: collaborative filtering; data mining; e-commerce; recommender system; temporal information.
E-Government Procurement Implementation in India: Evolving Decision Parameters for Project Success
by Prabir Panda, Ganesh P. Sahu, Babita Gupta
Abstract: Research indicates that up to 25% savings can accrue to the Indian Government by migrating to E-Government Procurement (E-GP). Thus improved utilization of public procurement (valued 3.4% to 5.7% of Indian GDP) would have significant impact on the overall efficiency in the government spending. However, E-GP projects, like any other e- Governance projects, have 70% chances of failure. This paper empirically studies stage-wise importance of eleven critical success factors (CSF) that were identified through extensive literature review in E-GP project outcome in the Indian context. We developed a research model for ascertaining the impact of identified CSFs on various stages of E-GP evolution building on the models of Layne and Lee (2001). Pinto and Slevin (1987), and Nasi (2005). Literature review, did not yield any study that focused on E-GP in India. Therefore, we conducted an exploratory study to understand the status of E-GP implementation in India and for fine-tuning the research model. A survey of the stakeholders involved with the E-GP system in India was conducted for testing eleven hypotheses related to eleven CSFs. We used regression analysis and mean score to empirically test the relationships identified between the CSFs and E-GP project success. The results show that five of the eleven CSFs are not important at stage 2 of E-GP project evolution, while all eleven CSFs contribute to the E-GP project success in Stages 3 and 4. This study is one of the few empirical studies conducted on the stage-wise analysis of CSFs in the E-GP domain and the first one to focus on E-GP projects in the Indian context. This study makes a significant contribution in the formulation of India specific CSF based parameters for managerial decision making for the E-GP project managers.
Keywords: Electronic Government Procurement; E-Procurement Implementation in India; Critical Success Factors; Public Procurement; Decision Parameters.
A study of relationship between Transformational leadership and task performance: The Role of social media and affective organizational commitment
by Ali Nawaz Khan, Ahsan Ali, Naseer Abbas Khan, Noor Jehan
Abstract: In today's society, social media have become an almost essential part of everyday life, particularly in the organizations where almost every employees and manager/leader use social media. Recently scholars have started to investigate leader's communication with their employees by using social media. However, leader's role in motivating their followers to use this innovation and increase performance is ignored by researchers. Using social capital theory as a base, the objectives of the present study is to examine the role of social media and affective organizational commitment between the relationship of transformational leadership (TFL) and employee's task performance (ETP). The proposed model was tested with the data collected from 254 employees from insurance companies situated in China. Model was tested by PLS-SEM with using SmartPLS 3. Findings of the study suggest that Transformational leadership has a direct positive relationship with task performance and affective organizational commitment as well as indirect positive relationship via social media on task performance. This study contributes to the existing literature in the field of Social media, leadership, commitment, and performance. Implications, limitation and future research have been discussed.e been discussed.
Keywords: Social Media; Transformational leadership; Affective commitment; Performance; Insurance Companies.
FORECASTING AGRICULTURAL COMMODITY PRICING USING NEURAL NETWORK BASED APPROACH
by Nikhila Varma, K. Padma
Abstract: Over the last decade, unprecedented spikes and drops in commodity prices have been a recurrent source of concern to both policymakers and the investors. This research paper focus on effective prediction of commodities prices which will be a key contribution to the investment world and policy makers to devise strategies. Neural Network and Multiple Regression models were built that would efficiently predict the price in advance for different forecasting ranges considering Kapas as the product. Historical prices along with various price influencing factors like inflation, rainfall, exchange rate and cottonseed oil cake price were given as input parameters to the feed forward multi-perceptron neural network and multiple regression models for forecasting prices. The results were compared using Mean Absolute Percentage Error(MAPE) as an accuracy measure. Artificial neural network models outperformed multiple linear regression model for medium term and long-term data. The results indicate that for long term predictions, neural network models have high predictive power.
Keywords: Commodities; Forecasting; Neural Networks; Multiple Regression.
A Systematic Review on Opinion Mining and Sentiment Analysis in Social Media
by Zaher Salah, Abdel-Rahman Al-Ghuwairi, Ahmad Aloqaily, Aladdin Baarah, Bar'a Qadoumi, Momen Alhayek, Bushra Alhijawi
Abstract: This paper introduced the employing of information retrieval techniques and statistical techniques in producing Systematic Literature Review (SLR). Sentiment Analysis (SA) and Opinion Mining (OM) in social media domain were considered as a case study to produce an example of SLR. The produced SLR introduced the field of sentiment analysis and opinion mining and surveyed current issues in user content based mining in social media field. The main aim of the research work described in this SLR was to investigate the use of sentiment analysis and opinion mining techniques for the analysis of social media. Social media has become one of the most important electronic phenomena in the present age; where everyone can access these networks such as Facebook, Twitter, Google+ and LinkedIn to broadcast their daily news or to express personal opinions or their sentiment orientations toward various subjects. As a result, a huge amount of data transmitted daily by users around the world and thus it may be impossible to deal with such a huge amount of data and analyse it manually. Therefore, researchers have conducted several research studies to discover new approaches, tools and techniques that can be used to analyse and explore such huge amount of data; more specifically data that are generated through social media websites. Systematic literature reviews retrieve and evaluate the multiple relevant research papers concerning specific research questions. In response to the lack of current systematic literature reviews concerning the Opinion Mining and Sentiment Analysis in Social Media, the authors present this comprehensive systematic review to introduce the field of sentiment analysis and opinion mining techniques applied to the data originated from social media and surveys the current issues and challenges for sentiment mining in the context of social media. The paper first detailed different approaches for conducting opinion mining and sentiment analysis and provided a common framework for searching and selection procedure applied to extracting the research papers that covering comprehensively the intended research directions in the field. It then discussed the most common techniques found in the literature for conducting opinion mining and sentiment analysis, which aims basically to determine whether an opinion expresses a positive or negative sentiment polarity in order to use this predicted polarity in further analysis or extensions. This systematic review investigated the opinion mining and sentiment analysis techniques that are found in more than 60 specialised research papers in the field of data mining with respect to social media in a systematic manner.
Keywords: Social Network Analysis; Opinion Mining; Sentiment Analysis; Data Mining Techniques; Information Retrieval.
A Structural Equation Model to Assess Behavioral Intention to Use Biometric Enabled e-Banking Services in India
by Ruchika Gupta, Siddharth Varma
Abstract: India has one of the largest and rapidly growing population of internet users in the world. Yet it seems that Indian banking industry has not been able to utilize this opportunity. This is reflected in a recent survey which showed that only a meager percentage of internet users does banking transactions online in the country. Security risks have been one of the prime reasons for such restrained usage. Biometric technology presents a viable solution to get over such security risks. The objective of this study is to assess the adoption of biometric enabled e-banking services in India. The paper primarily focuses on evaluating the customers behavioral intention to adopt such services. The Technology Acceptance Model has been used to determine customer intention to use biometric services. A sample of 200 respondents has been analyzed. In the first step, Confirmatory Factor Analysis (CFA) has been carried out and subsequently a Structural Equation Model has been developed using AMOS. Hypothesis testing has been done to develop the model. The study is based on a survey conducted in the National Capital Region of Delhi which includes Delhi and surrounding areas adjacent to Delhi. Perceived Ease of Use was found have a positive relationship with Perceived Usefulness which in turn was an important factor in determining Attitude towards the technology. Attitude was found to be a strong determinant for Behvioral Intention to use the technology. Demographic factors: age, income and prior use of Internet Banking were found to have no significant effect on the Attitude towards use of the technology. The implication of this result is that intention to use biometrics in banking services is unaffected by these three demographic factors which is positive news for use of biometrics. Moreover, Ease of Use has to be kept in mind while designing such systems.
Keywords: E-banking; Biometric; Customer intention; Demographic; SEM.
Use of Social Media by Professional Workers in the Basque Region of Northern Spain: A New Way of Networking
by Aitziber Nunez-zabaleta, Anjel Errasti
Abstract: Companies social media strategies have different objectives that are usually implemented by the marketing department and can therefore be said to pursue a communicational approach. Yet there are also many workers, both self-employed and employees, who use social networking sites for business purposes. This paper seeks to establish the use that these workers make of Web 2.0 tools in the professional field. We therefore conducted a survey among 283 workers from the Basque Country region in Spain to establish which specific Web 2.0 tools they are using and the possible statistical differences with certain variables related to the workers themselves and to the companies they work for. We also considered a series of studies that analysed the Social Media Strategy conducted both by companies and by their workers.
Keywords: Social Media; Professional relationship; Business Networking; Web 2.0 tools; B2B market; Self-employed; Big and Small Companies in the Web 2.0; Young and Old in SNS; Business Purpose; Contacts of professional interest.
Behavioural intentional to use computers among educators
by Loh Wai Ling, Wan Fatimah Wan Ahmad, Termit Kaur Ranjit Singh
Abstract: Abstract- This study hopes to provide an in-depth understanding on computers adoption and acceptance issues among educators in Malaysian schools. The Unified Theory of Acceptance and Use of Technology (UTAUT) model developed by Venkatesh et al. (2003) was utilized to identify the strength of predictors for educators behavioural intention to adopt, accept and utilize computers in the process of learning and teaching. Questionnaires were distributed to 40 secondary school educators in Perak Darul Ridzuan with 400 returned, and a 100% return rate. Statistical Package for the Social Sciences (SPSS) version 17 was utilized for data analysis. Structural Equation Modelling (SEM) was also used to appraise the measurement and structural model. Performance Expectancy (PE) (0.31, p < 0.05) and Effort Expectancy (EE) (0.41, p < 0.05) predicted significantly Behavioural Intention (BI) to use computers, while Social Influence (SI), Facilitating Conditions (FI) and the new construct Perceived Needs (PN) was statistically not significant. Studies in the future should include educators from other schools in other states in Malaysia for more and better reliable outcomes as well as conclusions.
Keywords: computer usage; educators; UTAUT model; predictors; SPSS and SEM.
BEFORE GAME OVER: A STUDY ON THE EXPERIENCES, PREDICTION AND VALUES OF CONSUMPTION OF PLAYERS OF SEVENTH-GENERATION VIDEOGAME CONSOLES
by Emilio Jose M. Arruda-Filho, Igor De Jesus Lobato Pompeu Gammarano
Abstract: This paper presents an exploratory qualitative analysis of the elements that influence the consumption behavior of users of seventh-generation videogame consoles. It aims to improve comprehension about consumers preferences and intentions related to brand devotion, technology convergence, hedonism versus utilitarianism, ease of use, innovation, social positioning and social interaction of videogame users in order to understand which factors are likely to motivate the adoption process of this type of technology. The categories were derived from theories of consumer behavior and marketing that deal with the use and adoption of technology products, focusing on consumers usage symbols and values. The study method used was netnography, with the data collected from blogs/discussion forums on the internet. For data analysis, thematic categories were used to describe types of users in relation to their consumption propensities on videogaming platforms such as the Xbox 360, PlayStation 3 and Nintendo Wii. The results show that factors related to consumer culture and behavior, such as social positioning (status), influence the preferences of users of seventh-generation videogames.
Keywords: Videogames; Consumer Behavior; Netnography; Technological Convergence; Consumption Culture.
Ontology based Feature-Level Sentiment Analysis in Portuguese Reviews
by Larissa Freitas, Renata Vieira
Abstract: Sentiment Analysis is the field of study that analyzes peoples opinions in texts. In the last decade, humans have come to share their opinions in social media on the Web (e.g., forum discussions and posts in social network sites). Opinions are important because whenever we need to take a decision, we want to know others points of view. Opinions may be looked at considering different levels. A general opinion expressed in a whole text or review, in a sentence, or even parts of the sentence, when one finds to figure out what are the particular features that are liked or disliked regarding a certain product, entity or event. In this work we study this more detailed level of analysis, which is called the aspect-level or feature-level. This more detailed type of analysis requires going deeper in the parts of a sentence and an effort to deal with their meaning, therefore knowledge rich approaches are specially useful. For that we use ontologies, as they can be used to represent the relevant aspects of entities, in a semantic organized way, for instance, aspects that are part-of or properties of an entity in a certain domain of knowledge. Our approach is built for Portuguese and is evaluated on a reviews data set of the accommodation sector.
Keywords: Sentiment Analysis; Feature Level; Ontology.
Relationship between Customer Loyalty and Service Failure, Service Recovery and Switching Costs in Online Retailing
by Aakash Kamble, Shubhangi Walvekar
Abstract: Service failures in e-tailing are inevitable, understanding how service failure and recovery efforts affect customer loyalty forms an important topic for discussion among researchers and practitioners. This study investigates the relationship of service failure severity, service recovery justice and perceived switching costs with customer loyalty. It also studies the moderation relationship between service recovery justice and perceived switching costs. Data collected from 306 respondents tested against the research model adopted from previous studies suggests that, service failure severity. Interactional justice, procedural justice and perceived switching costs have a significant relationship with customer loyalty, and that interactional justice can mitigate the negative relationship between service failure severity and customer loyalty.
Keywords: Customer loyalty; switching costs; service failure severity; e-tailing; service recovery; e-commerce; retailing.
Dynamic Changes of QoS Parameters in Cloud Computing Service Level Agreement
by Abdel-rahman Al-ghuwairi, Mohammad Khalaf, Zaher Salah, Ayoub Alsarhan
Abstract: Cloud computing is considered one of the most important topics in software engineering research trends. It provides many advantages and benefits for all users whether they are organizations or individuals, by compromising the needed resources and services. These resources and services could be classified into three categories: Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS). Service Level Agreement (SLA) is a contract between cloud user and cloud provider in cloud computing environment. This contract is needed to manage, control, and monitor these services. Also, SLA is considered an essential document or factor to manage the relationship between the cloud user and cloud provider in cloud computing. SLA can be defined as a contractual agreement signed between cloud user and cloud provider in order to manage the level of access for the resources and quality of services provided. Continuous changes of technologies and requirements make updating SLA an urgent priority for both cloud user and cloud provider to ensure that the services provided are meeting their needs among multiple Quality of Service (QoS) parameters. Coping with multiple and frequent changes in QoS parameters is considered the main reason behind the intensive studies that have been presented for building a dynamic SLA. The current dynamic SLA monitoring approaches have considered the cloud provider view only; on the other hand the cloud user side view has been ignored. To solve the user concerns in dynamic SLA monitoring system, this paper proposed a dynamic SLA monitoring approach in IaaS system by generating new SLA terms based on analyzing the SLA penalties. This research paper applied a new proposed tradeoff mechanism between monthly cost and QoS guarantee values. This research paper proposed a dynamic model for updating QoS parameters of SLA in cloud computing environment. Java language was used with a QoS measurement dataset to experiment the proposed approach. Moreover; the selected database is used to compare the Static SLA (SSLA) approach with the proposed Dynamic SLA (DSLA) approach. The results of this experimental study show that the number of SLA violations in DSLA approach are less than the number of SLA violations in SSLA approach.
Keywords: Cloud Computing; Quality of Service; QoS; Service Level Agreement; SLA; Static Service Level Agreement; SSLA; Dynamic Service Level Agreement; DSLA.
Citizen centric assessment framework for e-governance services quality
by Vinay Singh, Garima Singh
Abstract: Citizen-centric e-governance services are essential to enhance the quality of life of citizens while ensuring citizen empowerment. The present study proposes a framework of assessing quality of e-governance services from the citizens' perspective to find out the degree of its quality impacting citizen satisfaction. The framework is validated through primary data collected from 213 respondents. Confirmatory factor analysis and structured equation modelling are employed to validate the model. The results depict quality of e-governance service and the information being disseminated to the citizens' impact on their satisfaction significantly. The study contributes a parsimonious model that can significantly contribute in future theoretical advances in e-governance quality assessment. The findings can bridge the gap between government initiatives and citizens' needs. Thus, designing high quality e-governance services while keeping the needs and expectations of citizen in focus translates its functional efficacy.
Keywords: citizen centric e-governance; e-governance services; citizen satisfaction; quality assessment; information quality; service quality; governance quality.
Developing SOA-enabled service agility capabilities: case studies in services industry
by Aparna Raman, Sangeeta Shah Bharadwaj, Jaydeep Mukherjee
Abstract: The research paper explores how information technology, specifically service-oriented architecture (SOA)-enabled service agility capabilities, were developed. The paper defines the service agility capabilities (sensing and responding) using dynamic capabilities theory and service dominant logic. In this research, we present two case studies, based on the services sector. This paper explains, 'how' these capabilities were developed by responding organisations. Based on the research results, the propositions were proposed. Further, the model was supported through thematic analysis. The study contributes towards the knowledge base of agility and reveals how SOA-enabled capabilities are developed to achieve agile services.
Keywords: service agility; capabilities; service-oriented architecture; SOA; environmental turbulence; dynamic capabilities theory.
Code refactoring using slice-based cohesion metrics and aspect-oriented programming
by Jagannath Singh, Pabitra Mohan Khilar, Durga Prasad Mohapatra
Abstract: Software restructuring is essential for maintaining software quality. It is a usual practice that we first design the software and then go for coding. After coding, if there is any change in the requirement or if the output is incorrect, then we have to modify the code again. For each small code modification, it is not feasible to alter the design. These minor changes made to the code causes decay in the software design. Software refactoring is used to restructure the code to improve the design and quality of the software. In this paper, we propose an approach for performing code refactoring. We use slice-based cohesion metrics to identify the target methods that require refactoring. After identifying the target methods, we use program slicing to divide the target method into two parts. Finally, we use the concept of aspects to alter the code structure in a manner that does not change the external behaviour of the original module.
Keywords: software refactoring; program slicing; AOP; cohesion metrics; code restructure; AspectJ.
A triangular perception of scope creep influencing the project success
by K. Lakshmi Madhuri, V. Suma, Uma Mohan Mokashi
Abstract: Project management strategies are a part of every organisation as developing high quality customer satisfied software is always one of the challenges for any software organisation. Though the scope creep is known to be one of the factors which influence project success, existing project management strategies do not effectively measure or predict the scope creep. This paper focuses on effective scope creep management which is achievable through a comprehensive analysis of the scope creep and its impact on project success. The paper further presents a case study conducted in one of the leading software companies to investigate the significance and impact of scope creep in the project success. An investigation was carried out on several empirical projects and a three-dimensional visualisation of scope creep on success of project was brought out. This trio visualisation comprises of historical data perspective which leads to visualise the inferences in a pictorial representation perspective. Facts, thus, gained from historical and pictorial data perspectives lead one towards visualisation of scope creep and its management using a mathematical modelling perspective. This mode of visualising the scope creep and its implications on project success ensures one to effectively modulate their strategies in order to develop software products which attain total customer satisfaction.
Keywords: software engineering; software quality; software metrics; scope creep management; total customer satisfaction.
An empirical examination of antecedents determining students' usage of clickers in a digital marketing module
by Nripendra P. Rana, Yogesh K. Dwivedi
Abstract: As more and more educational institutions are integrating new technology such as clickers into their learning system, it becomes increasingly essential to have an understanding of students' perceptions about such technology on their overall learning process. The incorporation of clickers into teaching instructions has created implications for teaching practices and student satisfaction. The purpose of this research is to understand student use and satisfaction with clickers in a large undergraduate digital marketing class in a British university. To do so, we propose a conceptual model based on information systems (IS) success models to understand student's usage behaviour and satisfaction with clickers. The data were analysed based on 138 valid responses gathered from the students, where clickers are effectively used for teaching and learning purposes. The results provided a strong support for all eight hypothesised relationships and adequate variance on its key dependent variables in the proposed research model.
Keywords: clickers; higher education; IS success models; student; usage; UK.
Relative importance of CSF in ERP implementation strategy: a multi-participant AHP approach
by Shruti Nagpal, Ashok Kumar, Sunil Kumar Khatri
Abstract: Enterprise resource planning (ERP) systems have found a wide acceptability among organisations, albeit with a pinch of salt. ERP systems appropriately bring about uniformity in the software across the organisation by bringing all the processes under one umbrella. But the low adoption rates and greater time to value are often reasons for low ERP implementation success rates and even ERP implementation failures. Researchers have chronicled various critical success factors (CSF) that determine a successful ERP implementation. This paper utilises multi-participant analytic hierarchy process (AHP) to determine the relative importance of CSF in various ERP implementation strategies. The paper contributes to the existing knowledge of CSF in ERP implementations by showcasing that CSF have varying importance across ERP implementation strategies.
Keywords: enterprise resource planning; ERP; critical success factors; CSF; analytic hierarchy process; AHP.
Emergence of multipresence - a theoretical underpinning
by Somesh Gaur, Bala Krishnamoorthy
Abstract: 'Anytime anywhere' and 'immersive' information and communication technologies have penetrated all spheres of our life. Because of these technologies, an individual can be present in multiple environments either real or virtual at a given time or in a time frame. Such technology driven multipresence has emerged as a prominent behavioural phenomenon today. Multipresence might have significant influence on an individual's behaviour as well as on team, organisation and society. Despite being such a prevalent and important behavioural phenomenon, there has been limited research and literature in this area. In this conceptual paper, we explore and refine the concept of multipresence. We start with the exploration of concept of presence, which forms the basis for understanding multipresence. We further discuss various aspects of multipresence from the literature. We also introduce a new revised definition and new concepts about multipresence. Finally, we discuss possible implications of such behaviour on performance of an individual and suggest potential future research opportunities in this area.
Keywords: presence; multipresence; multitasking; polychronicity; attention sharing; attention switching; technology affordance.
Special Issue on: ICCOINS 2016 Information Systems in Support of Business Functions
A User Study on Trust Perception in Persuasive Technology
by Wan Nooraishya Wan Ahmad, Nazlena Mohamad Ali
Abstract: A wide range of persuasive technologies has been developed for many different issues to assist people in changing their attitude or behavior. However, whether or not users trust persuasive technology and which trust perception affects them more in making trust decision are yet to be found out. Therefore, this study aimed to examine users trust level and its trust perceptions using two types of persuasive technologies, for example, health application and educational games on the environmental issues. The questionnaire is used as an instrument to measure trust level and trust perceptions. A pre-and-post-test approach is used to study 25 participants who are required to use both types of persuasive technology concurrently for 6 weeks. The finding shows that the users trust is at low-level, indicating a significant lack of trust problem. Cognitive trust dominates the trust decision-making though it is correlated with affective trust.
Keywords: trust; cognitive; affective; persuasive technology.
E-Collaborative Learning experience, Interdependencies of Presences and Learning Outcomes: Evidence of Mediating and Moderating Effects
by Alimatu-Saadia Yussiff, Wan Fatimah Wan Ahmad, Emy Elyanee Mustapha
Abstract: E-collaborative teaching and learning have gained much attention from practitioners, businesses and academics. However, the impact of e-collaborative teaching and learning on students learning outcomes with the mediating and moderating effects of three presences (social, cognitive and teaching presences) has not been thoroughly investigated. To bridge this gap, we conducted an experimental research design consisting of two main groups experimental and control groups. The control group, consisting of 42 students is the group using the conventional methods of in-class collaboration. The experimental group, consisting of 60 students used a developed e-collaboration system after which a survey was conducted using four sets of instruments the Community of Inquiry Survey Instrument, effectiveness for teamwork survey, pre-test and post-test questions. Partial least square approach to structural equation modeling was employed to analyze the experimental groups data based on the hypothesized relationship model. The results demonstrated that the constructs in the hypothesized model are reliable and valid. In addition, findings also indicated that e-collaborative learning experience strongly predict learning outcomes indirectly through the mediating and moderating effects of the three presences. This research offers significant contributions to practice, research and theory.
Keywords: learning outcome; collaborative learning; reliability; validation; Social presence; cognitive presence; teaching presence; Community of Inquiry.
Mobile Decision Support System with Dynamic Knowledge Base using Decision Tree and Case-Based Reasoning
by Hasimah Hj Mohamed, Muhammad Rafie Hj Mohd Arshad, Muhammad Dzulhimi Azmi
Abstract: Muslims from around the world performing Hajj and Umrah every year. The rituals involve many rules and procedures in which can become a challenge for pilgrims to remember. While performing the ritual, pilgrims might encounter some problems that need an immediate solution, especially those related to dos and donts in the ihram. The best way to get the solution is by referring to the ustaz or muttawif (Hajj Guider). However, theyre limited and not available all the time. It is best to have a knowledge that can be stored digitally that enable the pilgrims to refer it anytime and anywhere. We proposed a dynamic knowledge-based approach that can capture possible problems and solutions from the expert on mobile platform. Users can query both simple and advance questions to the system. The system is on android and web based platform. The system has been implemented using an artificial intelligence method of Decision Tree and Case Based Reasoning methodology. We use case based reasoning to retrieve similar cases (Question and Answer). Decision tree with dynamic knowledge based is being used to predict the solutions for problems inquired by users. Rules are stored in databases, and it will be retrieved according to the problems given. We have implemented these methods on hajj domain to solve the dumm imposition for the ihram ritual which can be referred by pilgrims anywhere and anytime to solve any problems encounter during hajj ritual.
Keywords: Case-based Reasoning; Decision-Tree; Hajj ritual; dynamic knowledge base; interactive Question-Answering; Dumm Imposition;rule based system;.
Predicting Generalized Anxiety Disorder Among Women Using Decision Tree Based Classification
by Neesha Jothi, Nur'Aini Abdul Rashid, Wahidah Husain
Abstract: Mental health presents as one of the greatest challenges to the current generation. It has been reported that about 5% of the population in developed countries are affected by Generalized Anxiety Disorder (GAD) withwomen twice as likely to be affected as compared to men. Predicting GAD among women is no longer an arduous task especially with the assistance of data mining technology. In this paper, a methodology encompassing data collection, data preprocessing, data analysis and data mining process using random forest approach is drawn for an effective prediction. The random forest approach is one of the classification data mining techniques which is embedded with good predictive characteristic. The result of this study in term of accuracy, sensitivity and specificity conforming to its high predictive performance in GAD prediction based on depressive symptoms. Besides that, several popular machine learning techniques are also applied to the resultant dataset of this study and the comparison result attests to random forest algorithm outperformed other methods. The generated prediction model is expected to provide an effective screening process to detect Generalized Anxiety Disorder earlier among women in Malaysia.
Keywords: Data Mining; Data Mining in Healthcare; Generalized Anxiety Disorder; Random Forest.
Business to Customer (B2C) E-Commerce Implementation Process: A Case Study Experience in Fashion and Apparel Business in Malaysia
by Deborah Paris, Mahadi Bahari, Noorminshah A. Iahad
Abstract: Despite various studies conducted on the implementation of business-to-customer (B2C) e-commerce, prior studies presumed that B2C e-commerce implementation as a plug and play exercise rather than a process-based. This paper presents a model for the implementation process of B2C e-commerce in a fashion and apparel business. Based on qualitative research approach using a case study and summary of experience, a model for the implementation process of B2C e-commerce is proposed. The model describes the characteristics of 14 implementation factors that occurred during Lewins and Kotters stages of implementation. Although the models generalisability is limited, it offers a guideline for the existing and future senior managers of B2C e-commerce in fashion and apparel business. This model helps managers to identify the highlights in each stage of the B2C e-commerce implementation process.
Keywords: Implementation Process; Business-to-Customer (B2C); E-Commerce; Kotter’s Model; Lewin’s Model; Case Study.
Validation of a Multimodal Interaction Model for Foot Reflexology Virtual Reality Stress Therapy Application
by Suziah Sulaiman, Hector Chimeremeze Okere, Dayang Rohaya Awang Rambli, Oi-Mean Foong
Abstract: Multimodal interactivity when supported in a foot reflexology virtual reality environment has the potential to relief stress. Current works leading to the development of such an environment have focused on creating models involving human to human (H-to-H) interactions which later could be used as design requirements. The goal is to translate these requirements and lay foundation for future foot reflexology virtual reality stress therapy (VRST) application. Despite the intention, the development missed an important activity that is feedback from those experts in the domain. This paper closes the gap by presenting an expert review to the multimodal H-to-H interaction model as a form of validation. Eight experts from the Human Computer Interaction (HCI) domain or related field reviewed and provided feedback on the model. The reviews were utilized to reconstruct the multimodal H-to-H interaction model, consequently yielding a final validated model for foot reflexology VRST application.
Keywords: Expert Review; Foot Reflexology (FR); Virtual Reality (VR); Virtual Reality Stress Therapy (VRST); Interaction Model; Validation.
An investigation of factors influencing the intention to use mHealth apps for self-care
by Faiz Aiman Azhar, Jaspaljeet Singh Dhillon
Abstract: This paper reports factors that are essential to be considered in the design mHealth apps for self-care. Self-care is an emerging area that refers any intentional actions people take to care for their physical, mental and emotional health. Encouraging people to practice self-care is a challenge and it is known to be an important part of a healing process. There are numerous health support applications in the market that can be downloaded via smartphones. These apps are typically designed to enable healthcare consumers to improve their health or maintain their good health. However, recent research indicates that with the exception of physical activity, more consumers are currently tracking key health factors on paper or in their heads than with mobile applications. In this paper, we identify factors that influence the intention to use mHealth apps for self-care that were identified via a systematic literature review approach and which thereafter were investigated quantitatively by involving 203 consumers. These factors when considered in the design of future mHealth apps could address the requirements and expectation of consumers towards mHealth apps in general and could possibly motivate them to use mHealth continuously in achieving their health goals.
Keywords: mHealth; consumer health informatics; self-care; mobile health applications.