International Journal of Services Technology and Management (47 papers in press)
Distinguishing aggregate air travel demand from air passenger volume in China: based on the partial adjustment theory
by Yingxiao Zhou, Peng Zhao
Abstract: Air travel demand estimation is vital for airlines and governmen
Keywords: air travel demand estimation; air travel volume; partial adjustment theory.
Impacts of Day Trading on the Intraday Pattern of Market Quality
by Tsung-yu Hsieh, Ying-Fen Fu, Shih-Ya Ma
Abstract: In Taiwans stock market, buying first and selling later, as well as selling first and buying later, are permitted, as of January 1, 2014, and June 30, 2014, respectively. This study investigates day trading stocks (pilot stocks) and nonday trading stocks (control stocks) that appear in the Taiwan 50 index and Taiwan mid-cap 100 index during 20132014, with the goal of investigating the impact of day trading on the intraday pattern of market quality. With a difference analysis and cross-sectional regression analysis, this study reveals insights into a stock market that is populated mainly by individual investors. Prior research into intraday patterns of market quality rarely focused on individual investors. The current study demonstrates that the effective spread of pilot stocks decreases significantly, and trading depth increases significantly, after the implementation of buying first and selling later options. This liquidity increase phenomenon then is offset when the selling first and buying later option is permitted.
Keywords: Market Quality; Day Trading; Buying First and Selling Later; Selling First and Buying Later; Intraday Pattern.
Innovative Behaviour and Performance of Technology-based Knowledge-Intensive Business Service: An empirical study
by Xavier Amores Bravo, Anna Arbussa, Andrea Bikfalvi, Josep Llach, Marc Saez
Abstract: The aim of this paper is to learn more about how technology-based knowledge-intensive business service firms (t-KIBS) innovate. To do so, we examine the range of innovation practices employed by a sample of 50 t-KIBS in Catalonia, Spain and the impact these practices have on innovation and business results. We distinguish between practices widely used among manufacturing and services firms and practices that are more typically used by services. Our results reveal that, on the one hand, practices common to manufacturing and services are significant in explaining improvements in both innovation and financial performance, while on the other hand, innovation patterns and practices that are more often used in services are not significant in explaining either innovative outputs or increases in operational profits and returns. These results are important for refining the design of innovation policies at a regional level in Catalonia, as well as abroad. Further research is needed to establish whether the innovative behaviour of t-KIBS is more akin to that of manufacturing firms than to that of service firms.
Keywords: innovation; performance; service firms; service business; technology; knowledge-intensive; KIBS; t-KIBS.
Measuring e-service quality: A review of literature
by Amit Shankar, Biplab Datta
Abstract: In the competitive electronic service (e-service) context, favorable consumer perception about performance is the key to success and marketers are keen to explore consumers perceived service quality. Therefore, several scales have been developed to evaluate electronic service quality (e-SQ) in different contexts. This study explores methodological issues relating to the scale development process while undertaking content analysis of e-SQ literature. The study also focuses on the identification of crucial dimensions of e-SQ measurement scale in different e-service contexts. The review indicates that privacy and security, website design, responsiveness, efficiency, reliability, ease of use and system availability are prominent measures of e-SQ regardless of the context. This study also provides a comprehensive framework including antecedents and outcomes of e-SQ to help managers and researchers in evaluating e-SQ.
Keywords: E-S-QUAL; e-retailing; scale development; e-banking; e-services; Website quality.
An Approach to Reengineering Applied to Control of Container Logistics Cost Using the PERT Network
by Hao Zhang, Yan CUI, LIYU ZHU, Qing-xiao Hou
Abstract: With the development of society and the advancement of science and technology, Chinese automobile manufacturers are struggling with increasingly intense competition in the market. To earn a place in the industry and improve brand competitiveness, many companies are beginning to focus on the logistics of cost control, such that the whole supply chain cost is at its lowest when the value is at its highest, as this is the key to the future survival and development of China's automobile industry. As an example, this paper uses the container transport of Changan Ford auto parts logistics, and based on the cost analysis derived from the Program Evaluation and Review Technique (PERT), the existing transport process is reengineered. Through the comparison of the costs before and after the transformation and the sensitivity analysis based on the reengineered process, it is determined that the reengineered process is superior to the initial process and exhibits strong practical guiding significance for logistics cost control and the development of China's automobile companies.
Keywords: transport process optimization; PERT network; logistics cost control.
Service Supply Chain Incentive Strategy: From the Perspective of Win-win
by Weiping Zhu, Hongguang Yao
Abstract: Classical principal-agent model based on the hypothesis of decision-maker completely self-interest is the mainstream in classical economics; however it reduces the stability of long-term cooperation and cannot reflect win-win cooperation. The paper introduces principals value parameter reflecting win-win relation into incentive strategy, expands the traditional model, and establishes Service Supply Chain dynamic incentive model from the perspective of win-win. In the new incentive strategy, the paper further considers implicit incentive and service providers opportunism behavior. Research shows that the value preference parameter can effectively coordinate the value relation between service integrator and service provider, motivate service provider to improve productive input and decrease opportunistic behavior; implicit incentive has definite substitute effect on explicit incentive; under the joint effect of explicit and implicit incentives, service provider will keep higher productive input level, and its opportunistic input will be controlled effectively at the same time.
Keywords: Service Supply Chain; value preference parameter; implicit incentive; win-win.
Combined Fuzzy Theory and Delphi Method for Instruments Designing Framework of Online Marketing Flexibility Dimensions
by Anil Kumar, Piyush Sindhwani, Shrawan Kumar Trivedi
Abstract: With progressive globalization and market dynamism, the business environment is becoming more turbulent than ever and in a chronic state of flux. Continual changes in technology, demand fluctuations, the emergence of new business models and the internet add further challenges to achieve sustainable growth for businesses. This constant turbulence, combined with rapid changes in the external environment, has forced the business sector to become more agile and flexible. Customers want flexibility so that they can choose specific products and services according to their needs. Therefore, providing flexibility to customers has become a major task for service providers, especially in an online context where competition is fierce and there is no direct interaction with the customer. In literature very little has been written by researchers on this context; therefore, the aim of this study is to design a framework for online marking flexibility. To achieve this objective, a combined method i.e. a mixture of fuzzy theory and qualitative Delphi method has been used with data collected through non-probabilistic sampling methods combined with a survey of experts. The findings of this study can help online service providers to target their customers in online platforms according to their needs and flexibility demands.
Keywords: Fuzzy Theory; Flexibility; Delphi; Globalization; Market Dynamism; Online Platform.
A novel multiple attribute decision making method based on grey relational projection and its application for e-commerce risk assessment
by Xiaoyue Liu, Dawei Ju
Abstract: With respect to multiple attribute decision making (MADM) problems in which the attribute values take the form of hesitant fuzzy elements, the traditional grey relational projection (GRP) method is extended to solve multiple attribute decision making problems under hesitant fuzzy environment. Since the weights of attributes are incompletely known, a nonlinear optimisation model is established, i.e., a reasonable weight vector of attributes should make all alternatives have the largest grey relational projections on positive ideal solution and the smallest grey relational projections on negative ideal solution. Then, based on the hesitant fuzzy decision matrix provided by decision makers, all feasible alternatives are ranked according to the descending order of relative grey relational projections and the most desirable alternative(s) should have the largest grey relational projection on positive ideal solution and the smallest grey relational projection on negative ideal solution. Finally, a numerical example of e-commerce risk assessment is given to illustrate the application of the proposed method.
Keywords: multiple attribute decision making; MADM; hesitant fuzzy set; HFS; grey relational projection; GRP; incomplete weight information.
What Constitutes Excellent User Experience in Online Consumers Return Services?
by Jingwen Chen, Yan Ma
Abstract: More transactions of the commodities are in digital as the development of the internet conditions. However, non-face-to-face transactions may lead to one main problem, which is the possibility that commodities fail to meet consumers expectations and the inevitable occurrence of return problems. Hence, improving the return service experience of customers and building their trust have become the focus of business considerations. The author studied 1,002 after-sales review samples based on the research model on the influencing factors of online consumers return service satisfaction. By compiling and labelling the sample data, the author quantified consumers emotion through emotion analysis and multiple linear regressions. This study provides basis for businesses to improve the quality of return service by validating and explaining the research model.
Keywords: online consumers; e-commerce; return service; return satisfaction; multiple linear regressions analysis.
Co-evolution Path and Its Innovative Design of Chinas Export Cross-border E-commerceA case study
by Mingli Zhang, Man Chen, Wei Zuo
Abstract: Cross-border e-commerce (CBE) is a new mode of trade and has recently become a major new growth point in Chinas e-business market, in which export cross-border e-commerce (ECBE) has created significant advantages for Chinas cross-border trade. Within ECBEs rapid development, issues such as information asymmetry between buyers and sellers, and an inefficiency of professional logistics remain unsolved. This is mainly attributable to the numerous participants ECBE has attracted, who prefer to enhance their competitiveness to maximise their self-interest, without considering long-term development on a win-win basis. The CBE ecosystem is composed of participants and its existing environmental factors. Essentially, the main dynamic of an ecosystem is co-evolution. This article analyses the path of co-evolution of Chinas ECBE, based on the theory of co-evolution and stakeholder theory. By studying four cases of e-commerce enterprises, this paper proposes an innovative interest coordination mechanism for promoting the quick, sustainable development of ECBE.
Keywords: export cross-border e-commerce; ECBE; stakeholders; interest coordination mechanism; co-evolution; China.
Examining mobile SNS continuance from a dual perspective of social support and privacy concern
by Tao Zhou, Zuoning Xu
Abstract: Mobile SNS enable users to conduct ubiquitous interactions with their peers and exchange social support conveniently. This may strengthen social relationships and facilitate their continuance. At the same time, users are concerned with their personal information disclosed to the service providers. Integrating both perspectives of social support and privacy concern, this research examined mobile SNS continuance usage. The results indicated that social support, which includes informational support and emotional support, has significant effects on flow and trust. Privacy concern affects privacy risk. Flow, trust and privacy risk determine continuance usage. The results imply that service providers need to build a supportive climate and alleviate privacy concern in order to facilitate users continuance.
Keywords: mobile SNS; social support; privacy concern; flow.
Social resources and value creation: A consumer perspective
by Tuan Nguyen
Abstract: Consumer role in value creation is recently an emerging theme in service research. In the contemporary networked economy, consumer social resources, specifically social capital and social identity, are opportunely suggested as the determinants of their co-creation that, in turn, presumably cause their perceived value. A survey study with SEM analysis of 439 consumers in health care and education in HCMC, VietNam shows all of 13 hypotheses empirically supported. The finding reinforces that social capital and social identity, as interconnected operant resources, influence both consumer co-creation and perceived value that further affects consumer satisfaction and loyalty. The theoretical and managerial implications of the paper are derived.
Keywords: service management; value creation; consumer perspective; perceived value; social capital; social identity.
Does CRM Technology Implementations Mitigate Employee Intention to Quit in Call Centres.
by Olanrewaju Kareem, Olayemi Abdullateef Aliyu, Sany Sanuri Mohd Mokhtar
Abstract: In the contemporary business environment technology is vital to an organizations performance. Therefore, in the context of an inbound call centre, this study examines the effect of technology-based customer relationship management (CRM) on employees intention to quit. A cross-sectional research approach was used and data was collected from the Malaysian call centre industry. By using survey data, the conceptualized model was tested through structural equation modelling. The findings revealed that the deployment of state-of-the-art technology based CRM, followed by proper training, could significantly and positively engender employee job satisfaction. Furthermore, qualitative overstretch could be prevented, consequentially resulting in a significant reduction in employees intention to quit. Moreover, this study confirms that technology-based CRM implementations within the call centre industry can be a powerful initiative toward resolving the problem of employees low job satisfaction and intentions to quit. This study recommends ways in which management of call centres might best develop, deploy and assess their technology applications so that employees will be less stressed, more satisfied, and willing to remain with the organization. Areas for future research were also discussed.
Keywords: Call centres; technology based CRM; employee job satisfaction; qualitative overstretch; intention to quit.
The Joint Effect of Buyer-Supplier Interaction and Service Complexity on Satisfaction
by Rafael Teixeira, Ely Paiva, Celso Matos, Patrick Vesel
Abstract: This study investigates the influence of interaction frequency between service providers and business-to-business (B2B) buyers on buyer satisfaction, taking into account technological services of varying degrees of complexity. Simply put, interaction frequency is moderated by service complexity. Higher levels of service complexity require more interactions between service providers and B2B buyers so that they can exchange information and prepare for service co-production. Data were collected from 228 B2B buyers of telecommunications services in Brazil. The results show that buyer satisfaction is associated with low and medium levels of service complexity and interaction frequency; however, high levels of these variables were not found.
Keywords: service complexity; interaction frequency; business-to-business; technological services.
Applying Smarter Commerce Analysis for Click and Mortar of Integration Platform in the Retail Industry
by Tzu-Chun Weng, Chen-Te Hsu
Abstract: In the recent years, business models of physical store and online store have become mature. Terminal services increase the numbers of consumers through the physical channels and Internet. Effectively integrate and link between the Internet and physical services will be a challenge for all channel business and e-commerce industry. E-commerce has developed rapidly by evolving from sales online only into the actual situation integration (online to offline, offline to online, O2O). The industry will reshape the composition of the target customer, redefine marketing strategy and rethink interactive content and service depth. The goal of this paper provides a total solution with an interoperable interface, forward-looking technology, field deployment, and configuration flexibility from the development of business intelligence data collection and analyzes services to support the operation development of business service in the retail industry.
Keywords: business models; online; business intelligence; data collection; retail industry.
Periodic review integrated inventory model with controllable lead time and setup cost in the presence of a service level constraint
by Fu Huang, Huaming Song
Abstract: The impact of lead time reduction on an integrated periodic review inventory system comprising a single vendor and multiple buyers with a step crashing cost function and service-level constraints is studied. We revised Hsu and Huang's  distribution free procedure and extended normal distribution procedure, applied Lagrange multipliers to determine the lead time, the common shipment cycle time, the target levels of replenishments and the number of shipments per production cycle so that the expected total system cost is minimized. Some numerical examples are presented to illustrate the model. We perform a sensitivity analysis to see the effects of parameter changes on the objective function.
Keywords: inventory; integrated model; lead time; service level.
Cloud platform to improve performance outcomes: role of customer relationship management and innovation capabilities
by Chu-Ching Wang, Li-Ren Yang, Hsiu-Chen Chuang
Abstract: Conceptualizing implementation of cloud platform in the new product development (NPD) context is still rudimentary. The primary objective of this study was to investigate the relationships among implementation of cloud platform, customer relationship management (CRM), innovation capabilities, and NPD performance. This study empirically investigated a sample of NPD projects in the Taiwanese high-tech industry. The structural equation modeling (SEM) approach was used to validate the research model. The findings indicate that implementation of cloud platform is associated with level of customer relationship management. In addition, these analyses suggest that customer relationship management has a positive effect on innovation capabilities. Finally, innovation capabilities contribute significantly to NPD performance.
Keywords: cloud platform; customer relationship management; innovation capability; new product development.
To what extent does a knowledge-intensive business service firm need customer knowledge integrative activities? The case of DigiCAP
by Jong-Seok Kim
Abstract: This study examines the relationship between customer knowledge degree and integrative activity of customer knowledge in a new custom product development process by using an exploratory and qualitative single case study of a knowledge-intensive business service (KIBS) firm. In spite of the importance of customer knowledge integrative activities to a KIBS firm and the traditional significance of customer knowledge in the field of marketing, there is an unexplored question of to what extent a KIBS firm needs to have customer knowledge integrative activities. This study empirically identifies that a KIBS firm requires much effort and time for customer knowledge integrative activity to develop a new custom product, while there were different properties and contents of customer knowledge integrative activity at each stage of a new custom product development process. It also identifies that the degree of customer knowledge integrative activity depends on the degree of complexity of a customer product, while the degree of prior customer knowledge in a KIBS firm can reverse influence the degree of customer knowledge integrative activity. Finally, this study further explores two factors which can influence customer knowledge integrative activity: the range of customers and product characteristics.
Keywords: KIBS firm; customer knowledge; customer knowledge integrative activity; new custom product development process.
When Big Data made the headlines: Mining the text of Big Data coverage in the news media
by Murtaza Haider, Amir Gandomi
Abstract: Big Data-driven analytics emerged as one of the most sought-after business strategies of the decade. This paper reviews the news coverage of this phenomenon in the popular press. The study uses natural language processing (NLP) and text mining algorithms to determine the focus and tenor of the news media reporting of Big Data. A detailed content analysis of a five million-word corpus reveals that most news coverage focused on the newness of Big Data technologies that showcased usual suspects in Big Data geographies and industries. The insights gained from the text analysis show that Big Data news coverage indeed evolved where the initial focus on the promise of Big Data moderated over time. This study also offers a detailed expos
Keywords: Big Data; news content analysis; text mining; natural language processing (NLP); topic modelling; modal verb analysis.
Special Issue on: “Big Data Management in the Cloud”
Striving to make better decision quicker in cloud: big data event trading in high frequency trading perspective
by Arodh Karn, Niranjan Sapkota
Abstract: In the world of big data, cloud computing in trading and rapid development in computing hardware and software; cloud computing and high frequency trading (HFT) unconditionally turn to be tightly related as the way market is changing rapidly. We find the practicability of event trading strategy of HFT in Finnish stock market based on auto regressive empirical test and comparative ratios insinuating the impression on positive recovers of event trading. A specialized version of cloud trading system is then architected after discovering and exploring the feasibility of HFT in event based trading in Finnish stock market so that afresh get going HFT firms who are speculating what tact to exercise with what holding period and not capable to get micro second favors of news feed earlier than their adversaries; can practice this discipline and the proposed cloud trading architect for alpha generation.
Keywords: high frequency trading; event trading; limit order book; big data; cloud architect.
SDPBDVC: Secure Data Processing on Big Data using Visual Cryptography
by N. Jeyanthi, K. Brindha
Abstract: The rapid and vast deployment of modern technologies such as iPhone, laptops, digital watch, social network, Internet has resulted in handling of an enormous amount of data in our day to-day life. Since the data storage has increased abundantly, the issues related to the techniques to retrieve the relevant information and protect the huge quantity of data are to be focused upon efficiently. However various organizations and IT industries dealing with big data are faced with many security risks in the storage and processing of data. Hence protecting the big data is challenging task for the researchers. MapReduce is an efficient tool for processing large volume of data in a distributed environment. Security and secrecy of data are vital concerns while processing data carried out in MapReduce. In this article, the proposed SDPBDVC (Secure Data Processing on Big Data using Visual Cryptography) technique ensures the protection of sensitive information by applying the Visual Cryptography technique and the processing done only by authorized entities
Keywords: MapReduce; Cloud Computing; Security; Visual Cryptography.
A Novel Approach for Improving Data Locality of MapReduce Applications in Cloud Environment through Intelligent Data Placement
by Shabeera T P, Madhu Kumar S D
Abstract: In this world of big data, hosting storage and analytics as cloud service is extremely relevant. In multi-user environments, there are chances for load imbalance during data placement. MapReduce like frameworks move computation towards data. However, because of load imbalance, some nodes cannot start computation on the node on which data is stored and may be compelled to start computation on some other nodes. This results in deteriorating data locality. In this case, data have to be copied to the computing node. This data transfer increases the job completion time. This paper proposes a data placement policy for clouds in which the data and virtual machines are colocated in the
same set of physical servers. The physical servers in the cloud are grouped into partitions created using the minimum spanning tree. Experimental results show that this proposal improves node utilization and reduces execution time over default placement in the cloud environment.
Keywords: Cloud Computing; Big Data; MapReduce; Data Locality.
Special Issue on: LISS16-SIM Service Innovation and Management for Logistics and Supply Chains
Research on Risk Control of Vehicle Dynamic Logistics Alliance Based on SD and Evolutionary Game Model
by Mingbao Wang, Zhiping Du, Hong Duan
Abstract: Based on the evolutionary game theory and system dynamics theory, this paper analyzes the characteristics of vehicle logistics supply chain and vehicle dynamic logistics alliance system and the dynamic characteristics of system risk control, analyzes the internal risk control of vehicle dynamic logistics alliance. The evolutionary game model of two game agents under bounded rationality is established by taking the dynamic logistics alliance of two members as the research object. And uses the system dynamics theory, transforms the vehicle dynamic logistics alliance evolution game model into the system dynamics model. The model was simulated by Vensim software. Combined with the characteristics and advantages of the two methods to analyze what factors will promote cooperation between the two sides, what factors tend to make both sides appear egoistic breach of contract and thus affect the cooperation, what will trigger the situation of default. So as to provide reasonable suggestions for risk control of vehicle dynamic logistics alliance.
Keywords: Vehicle logistics alliance; system dynamics; evolutionary game theory; risk control.
Special Issue on: ICCM 2016 Computers and Management
Multi-Depot Vehicle Routing Problem Based on Customer Satisfaction
by Sonu Rajak, P. Parthiban, R. Dhanalakshmi
Abstract: Nowadays, meeting the customers demands in the shortest time and least cost is the most challenging task of maintaining any supply chain. Vehicle Routing Problem (VRP) plays an important role in the logistics. In typical VRP, customers are used to serving as a single depot, but in real-life single depot will not be sufficient to meet the customers demand or customers satisfaction. In this context, this article presents the Multi-Depot Vehicle Routing Problem based on Customers Satisfaction (MDVRPCS). Since MDVRPCS is an NP-hard problem so, Ant Colony Optimization (ACO) has been proposed to solve the MDVRPCS. The proposed algorithms have two phases. The first Phase involves clustering the nodes into a desired number of groups. This has been done by using K-means clustering algorithm. The second Phase involves optimization of routes for each cluster. This is achieved by using ACO. The proposed algorithm has been tested for wellknow problem instances from the literature. The results show that the algorithm is capable of obtaining good optimal solutions.
Keywords: Vehicle Routing Problem; Combinatorial Optimization; K-Means Clustering Algorithm; Ant Colony Optimization; Customers Satisfaction; Fuzzy Time Windows.
Energy-Efficient Fairness-Aware Memory Access Scheduling
by Aastha Modgil, Vivek Sehgal, Nitin Chanderwal
Abstract: In a chip multiprocessor (CMP) major resource that is being shared among multiple cores is main memory as it is responsible for storing data structures needed for execution of a program. Chip multiprocessor system enables multiple threads to run simultaneously on a chip. Diverse threads running simultaneously on same chip may compete with each other for resources. Because of interference among threads, each thread can experience extremely different memory system performance. If interference among threads is not controlled, then one thread can experience extreme starvation or slowdown while another is unfairly prioritized. Performance, power consumption and capacity are three major factors that affect the design of a memory system. By efficiently reordering concurrent memory requests, power consumption and performance can be improved. Intelligent reordering of memory accesses reduce the number of operations to be performed thereby resulting in decreased average latency and power consumption. This work proposes a memory access scheduler, Energy-Efficient Fairness-Aware Memory Access Scheduling (EEFA) that provides each thread equal opportunity to access memory banks by prioritizing requests generated from reorder buffer head thus ensuring thread fairness. The scheduler exploits bank level parallelism by pre-issuing issuable read commands during drain-write mode. Also, proposed scheduler prioritizes row buffer hit requests, hence reduces average access latency and power consumption. The authors show that Energy-Efficient Fairness-Aware Memory Access Scheduling significantly reduces unfairness among threads and energy consumption in DRAM memory system while also improving performance.
Keywords: DRAM; Energy Efficiency; Thread Fairness; Bank Level Parallelism; Row Buffer Hit; Memory Access Scheduling; Chip Multiprocessor.
Design of Fuzzy Controlled Routing Protocol to Save Energy in Ad Hoc Networks
by Hemraj Saini, Madan Mohan Agarwal, Mahesh Chandra Govil, Madhavi Sinha
Abstract: The performance of the network protocol depends on a number of parameters like mobility, distance between source and destination, queue length, hop count, residual energy, etc. In this paper, a new energy efficient protocol IAOMDV-F is developed based on fuzzy logic. In first phase, the proposed protocol discovered the multiple paths between source and destination using AOMDV protocol. These multiple paths received in phase one is processed to identify mutually exclusive disjoint and best paths in second phase. To achieve this, a fuzzy based controller FBRS is designed and developed to find the best path at destination nodes. The fuzzy logic is build using rule base and input parameters - average mobility, queue length, degree of node and distance of path. Since the paths obtained are already constrained by node disjoint process used in first phase. The path is further optimized using the concept of fuzzy logic i.e. fuzzy controller, thus the proposed protocol become more energy constraint, efficient and stable. Comparative analysis of the proposed protocol IAOMDV-F is done across two performance metrics routing overheads and energy consumption. The results show that the proposed protocol outperforms other existing protocols. NS-2 is used to simulate and analyses the proposed protocol.
Keywords: Probabilit; neighbours node; Multipath; Fuzzy controller; Degree of node; Ad hoc networks.
Special Issue on: ICSS 2017 Services Design and Innovation and Serviceology
A user preference awareness k-neighbour optimised selection algorithm: modelling and implementation
by Mingjun Xin, Wenfei Liang, Weimin Li
Abstract: With the development of the massive amount of web services, the popular research area is involved with the solution to select the required services according to the personal preference for different users. To solve these urgent problems, a user preference awareness k-neighbour optimised selection algorithm is proposed in this paper. Initially, the potential interest of the user is explored by using association rules method of data mining technology. Then, an expanded LDA model is used to analyse the influence on user preference calculation for different types of services caused from the functional attributes of web services. To improve the accuracy of the service selection result, the ant colony algorithm is modified to optimise the service selection process of k-neighbours in traditional collaborative filtering. The experiment shows that our proposed method leads to a higher accuracy and coverage than the traditional web service selection methods based on the real service set.
Keywords: association rules; collaborative filtering; ant colony optimised algorithm; service selection.
Service recommendation using conditional restricted Boltzmann machines
by Tianyang Li, Ting He, Zhongjie Wang
Abstract: We propose methods based on the conditional restricted Boltzmann machine (CRBM) for the service recommendation. First, we construct a CRBM model, the individualised characteristics of customers and indexes of satisfaction have been encoded into its conditional units, and the using status of services has been encoded into its visible units. Next, a method for dynamically adjusting learning rates is proposed to improve the training process of the CRBM. Finally, we develop a neighbourhood-based approach to further boost recommendation results. The evaluation on a dataset extracted from a manufacturing company, validates that the above-proposed methods have highly practical relevance to the service recommendation problem in real world business.
Keywords: service recommendation; the conditional restricted Boltzmann machine; CRBM; service; restricted Boltzmann machine; RBM; learning rate.
An optimal selection method of model transformation rules based on clustering
by Li Jin, Bai Yu, Cheng Xuhong
Abstract: Model transformation methods tend to create many transformation rules, but there is still some redundancy among these transformation rules. Therefore, how to obtain effective transformation rules has become an unsolved important problem. However, current model transformation methods do not focus on these rules. Therefore, we propose a clustering-based method for the selection of transformation rules. The main idea is to classify the target model elements, transform the rules of each class and finally, obtain the appropriate conversion rules via the post-clustering conversion rules. We also present an algorithm to automatically validate the optimal selection of model transformation rules. A motivating example is presented to illustrate our approach. Furthermore, the comparison experiments of these algorithms are conducted, which have proved the effectiveness of the optimal selection method.
Keywords: model transformation rule; cluster; optimal selection.
Mining resource service sequences based on similarity for collaborative tasks
by Haibo Li, Yingchuan Sun, Tangquan Lin
Abstract: To improve the efficiency of selection of resource services and collaboration among them, the business link between resource services is essential for collaborative tasks. Service flow can better describe the business relationship between resource services. Although a workflow model can describe the relationship of resource service sequences (RSSs), it describes the static relationship between resource services and does not reflect the frequency of RSSs in real business. A method of mining frequent RSSs is proposed. First, by analysing the task-relevance that exists between resource services, an equation is presented to calculate the distances between resource services. Next, for an RSS, the similarities of resource services are measured by the equation to resolve the set of frequent resource service sub-sequences. Finally, an evaluation method of frequent subsequences is proposed. The result of the experiment proves the proposed approach is valid.
Keywords: collaborative task; resource service sequence; RSS; similarity; workflow.
A multi-modal health data fusion and analysis method based on body sensor network
by Lei Wang, Yibo Chen, Zhenying Zhao, Lingxiao Zhao, Jin Li, Cuimin Li
Abstract: As an important branch of wireless sensor network (WSN) in biomedical field, body sensor network (BSN) could remotely monitor a variety of human health data in real time by means of energy-saving and high-accuracy sensor technology. We proposed a multi-modal health data fusion and analysis method based on the data collected from BSN. Single-modal Holter monitoring and multi-modal health monitoring were performed on 60 patients with confirmed heart disease and proved that the proposed method could effectively improve the detection rate of asymptomatic myocardial ischemia and provide a new auxiliary judgment method for clinical application. Aiming at the requirement of privacy preserving in the data fusion process of wireless body sensor network, a new SMART-RR algorithm was proposed. Simulation results showed that MART-RR was an energy-saving privacy preserving data fusion algorithm with small data communications, high privacy protection and accuracy.
Keywords: body sensor network; BSN; multi-modal; data fusion; privacy preserving; healthcare service.
The QoS analysis of web services composition based on Jackson queuing network
by Hao Wang, Jianmao Xiao, Hao Long, Leyue Wang
Abstract: With the popularity of distributed computing and mobile internet, services composition has become a hot research in the field of service computing. The QoS of web services composition organised by BPEL is determined by the internal structure, the probability distribution in the variables value of BPEL process and the external factors such as the hardware and software processing capabilities of web servers and the load of web servers. At present, the generalised Petri nets, queuing Petri nets, Markov processes and stochastic process algebra model which are widely used and cannot have a comprehensive analysis in obtaining the actual performance of web services composition in internet environment. In this paper, a set of mapping rules are established to transform the internal and external factors which have impacts on the QoS of web services composition into Jackson queuing network, meanwhile, a set of performance indexes and their formula are given. Based on these performance indexes, we comprehensively analyse the performance of web services composition and locate the bottleneck of web services composition when the internal and external factors are changed so that, the performance of web services composition can be predicted before its deployment.
Keywords: business process execution language; BPEL; QoS; web services; distributed computing; composition; Jackson queuing networks.
Finding service compositions in complex homecare service network
by Qi Wang, Chunshan Li, Dianhui Chu
Abstract: With the development of pension service industry, there have been numerous homecare services. The demands of the elderly are becoming increasingly complex and a single service is difficult to meet the demands of the elderly, so homecare service composition becomes particularly important. According to the homecare service features, this paper builds a complex network model with homecare services as nodes and relationship between services as edges. Then, the search strategies are used to search in the complex network to obtain service composition. This method can find high quality service composition which meets the complex demands of the elderly.
Keywords: homecare service; complex network; R programming language; association rules; service composition; search strategy; services technology.
Application study on image recognition algorithm in visual service of deaf mute under complex environment
by Xiaoyi Yang, Qian Wu, Xinmei Deng
Abstract: In order to benefit the disadvantaged deaf people and eliminate the communication disorder between the hearing and deaf mute to get harmony and symbiosis really, the visual identification and service research of deaf people has been paid more and more attention by experts and scholars. The paper presented an improved advanced local binary pattern (ALBP) algorithm for face feature recognition. Aimed at being not ideal in recognition effect resulted in ignoring the contrast between the local image in traditional face feature recognition algorithm and discarding some important texture feature information, it first made the illumination normalisation pre-processing of face images under different illumination conditions to control the illumination changes in a certain range, then the improved local binary pattern (LBP) algorithm is used to map the contrast value of the local area pixels into an interval value, so that it made the image own the illumination invariance, thereupon then it could better identify the face features. The experimental results show that the presented ALBP algorithm can be better applied to the visual service system of the deaf.
Keywords: disadvantaged people; visual service system; deaf people; communication disorder; ALBP algorithm; face recognition; feature recognition algorithm; texture feature; feature information; image process; illumination normalisation; illumination invariance.
Research and application of ambient air quality monitoring service based on data fusion
by Jingang Li, Ting He
Abstract: Requirement of air quality has become higher with the living standard development and population increase. Therefore, establish the efficient ambient air data detection and fusion service system based on wireless sensor network and device cloud will be more convenient for searching existent problems that can figure them out with benefit living and leave away from the damage of air pollution. Moreover, in order to improve the accuracy and reliability of multi-source heterogeneous data in collection process according to the analysis of the limitations and the features of data collected, a proper data fusion approach based on extended Dempster-Shafer theory is proposed to expose the faulty information of sensor nodes for monitoring service. Results validate that the service can effectively improve the ability in terms of flexibility and extensibility, decrease the inherent uncertainty of the signal detection and reduce the decision-making risk.
Keywords: monitoring service; device cloud; wireless sensor network; WSN; data fusion.
Customer satisfaction-oriented after-sales service node analysis for home appliance enterprise
by Taiqi Wang, Ting He, Yanjiang Cheng
Abstract: After-sales service plays an increasingly vital role in home appliance enterprises. Quantitative analysis is supposed to be focused on when researching after-sales service for home appliance rather than qualitative analysis only. In addition, the importance of each node should be distinguished. To solve the two issues, a customer satisfaction-oriented after-sales service index system which can evaluate the quality of after-sales service nodes is presented based on customer satisfaction framework, and the key indexes with crucial influences on customer satisfaction are selected by association rule algorithm. The significance test verifies the effectiveness of the mining results. Besides, the importance of each key node is analysed by random forest. Furthermore, the quantitative analysis of the key nodes is performed by multiple linear regression and the moderating effect of consumption level is verified. Finally, the Kano theory and the prospect theory are employed to explain the results, and optimisation strategies are put forward.
Keywords: after-sales service for home appliance; customer satisfaction; index system; key nodes.
Pattern-based service composition for user satisfaction and service revenue
by Hanchuan Xu, Yaou Zhuang, Hao Gu, Xiaofei Xu, Yuxin Zhang
Abstract: Service composition is an effective means of building profit-added service in a service-oriented computing environment. Most of the current research neglects characteristics of domain business as well as successful domain experiences, so optimisation performance cannot be further improved in specific service context. Firstly, the concept of service pattern is proposed to describe the knowledge extracted from previous composite solutions in domain business. Both service patterns and related advantageous services are pre-computed and organised, so that they can be reused in optimisation of service composition. Then a pattern-based bi-objective service composition method whose objective is to obtain a service solution for maximisation of user satisfaction and service revenue quickly is presented. Experimental results show the effectiveness and advantages of the proposed approach.
Keywords: service composition; service pattern; bi-objective; user satisfaction; service revenue; artificial bee colony algorithm; ABC.
Special Issue on: ICMC 2016 Reframing to Leverage New Opportunities in Advanced Services economy
THE BOMBAY STOCK EXCHANGE SENSEX AND FOREIGN INSTITUTIONAL INVESTMENT IN INDIA: ANALYSIS
by Pooja Misra, Ankit Yadav, Arpit Kumar Parhi
Abstract: With liberalization and privatization in 1991, foreign institutional investors (FIIs)were allowed to make investments in Indian securities from 1992 onwards. Today, India offers higher growth rates than many a developed economies and the same has helped it gain favor amongst investors as a foreign investment destination. According to a poll conducted by Bank of AmericaMerill Lynch (Bofa-ML) during 2015, India was voted as the most favorite global equity market for investors at 43%. On the other hand, although FII investments have grown steadily since liberalization, Standard & Poor Bombay Stock Exchange (BSE) SENSEX has been highly volatile. Keeping in mind, a volatile S&P BSE SENSEX the research aims to understand the impact of FIIs money flow into India and whether Foreign Institutional Investments have a role to play in accelerating the growth rate of the index, i.e. the research was undertaken to determine if there exists any correlation between BSE SENSEX and net Foreign Institutional Investments as well as the strength of the relationship, if any, taking India as a case example.
Keywords: Foreign Institutional Investment; BSE SENSEX.
Top Managements Sensemaking as a Strategic Practice: The Case of Private Organisations as Strategic Actors in Finnish Healthcare Changes
by Maarit Lammassaari, Esa Hiltunen, Hanna Lehtimaki
Abstract: The purpose of this study is to examine top managements sensemaking as a strategy practice. Building on the sensemaking perspective (Balogun, et al., 2014; Weick, 1995), this research proposes that top managements sensemaking both enables and constrains strategizing. This empirical analysis of a key informant interview and publicly available materials examines the sensemaking that constructs the role of the private healthcare service industry in Finland. This in-depth analysis of sensemaking in top management contributes to the literature on sensemaking in strategic management by adding empirical evidence on the role of language in strategy making.
Keywords: Top management; sensemaking; strategy practice; healthcare; case study; strategy language.
Punjab National Bank: Implementing Core banking Solution
by Bala Krishnamoorthy, Archana Shivkumar
Abstract: This case study narrates Punjab National Banks (PNB) journey from a computerized bank to a Core Banking Solution (CBS) operated bank. It provides a brief background on the banks vision for achieving long-term growth followed by a short introduction to the concept of CBS. This case study explores PNBs CBS implementation process in detail and provides a road map for other banks to replicate the CBS system. The case further analyzes the competitive advantages especially the first mover advantage gained by PNB due to CBS, and impact of CBS on its market value. The comparative advantages gained by PNB due to CBS and its impeccable contribution towards human resource management (HRM), business diversification, and financial inclusions have been analyzed. The case identifies potential challenges likely to be encountered by PNB in the future with respect to maintenance of CBS systems.
Keywords: Core banking solution; CBS implementation phases; first-mover advantage; comparative performance; market value; business diversification; financial inclusion.
Special Issue on: ICSS 2018 Services Computing in the Tide of Artificial Intelligence
An approach for composite service selection based on the records of request/matching
by Rong Yang, Dianhua Wang, Shuwen Deng
Abstract: As the emergence of more and more Web services, it becomes more difficult to find the candidate atomic services, and composing them to form a matched service process, where not only time is strictly limited, but also user demand must be satisfied. In order to solve this problem, this paper presents a service process selection method, which is driven by historical successful service request /matching solutions. Firstly, the system framework model is analyzed, and several concepts about service selection and composition are formalized. Then, the method model and algorithm are detailed. Finally, through a set of experiments, the effectiveness and robustness of our approach are evaluated.
Keywords: Service Selection; Service Composition; Service Process.
An approach to the mobile social services recommendation algorithm based on association rules mining
by Mingjun Xin, Lijun Wu, Wenfei Liang, Jie Shu
Abstract: With the continuous development of social network, more and more research areas have emerged. Among them, service recommendation has always been a research hotspot. Yet achieving accurate personalized recommendation is challenging because of the large amount of data generated in social networks as the data available for each user is highly sparse. In this paper, it focuses on the association rules in the mobile social network recommendation algorithms. By introducing the mobile users location information to the collaborative filtering recommendation process, the association rules between the items are minded. Then the association rules are filtered and split, which are integrated into the similarity matrix to combine user location information with them. Also, an association rule mining model is proposed, which considers time factor to further improved the recommendation accuracy. Experimental results show that the performance of our algorithm is better than the baseline.
Keywords: association rules; Similarity; Collaborative filtering; Recommendation algorithm.
CKGECS: a Chinese Knowledge Graph for Elderly Care Service
by Hanchuan Xu, Jingxuan Li, LanShun Nie, Xiaofei Xu
Abstract: Developing high-quality elderly care services supporting with modern information techniques is important to solve the increasing aging problem. Knowledge base is essential to the development of elderly care services. In which, knowledge graph is the most promising knowledge representation methodology. However, there are still more challenges on construction of Chinese knowledge graph, especially for elderly care service. Thus, based on three existing knowledge graphs, we proposed a new knowledge processing and fusion method to construct the Chinese knowledge graph for elderly care service. The experiments show that the proposed method can construct knowledge graph in a rapid way and the knowledge graph has better quality for elderly care service.
Keywords: Chinese knowledge graph; elderly care service; knowledge data filter; knowledge fusion.
An Approach for Identifying the Abstraction Scopes of Business Process Petri Nets System Using Binary Search Tree
by Huan FANG, Shuya SUN, Juan GUO, Xianwen FANG
Abstract: Since it is difficult to form a quick overview understanding for large and complex business process models, the studies of the technologies and methods of model abstraction are crucial. The state-of-the-art abstraction studies are mostly concentrated on the abstraction method for various process systems, however they are a little vague about the scope orientation that is to be abstracted in the model. A search-tree-based abstraction scope identification method for a business process model is purposed in the paper, which is founded on the basis of behavioral relation theory of Petri nets and the Depth-First Search ideas. First, the concepts of three kinds of block structures and boundary places in work-flow Petri net systems are formalized, and the transition association tree of the system is then obtained, where the interactive semantic of system is taken into consideration. The transition association tree is further used to identify and locate the areas that are to be abstracted in the model, and the aim of model abstraction is then accomplished. Finally, two kinds of case examples are applied to illustrate the validity and feasibility of the proposed method. Therefore, compared to the existing studies, the main contributions of this study are a sound block-based abstraction scope identification method and its corresponding abstraction method, on which the well-performed properties of initial systems can be preserved after abstraction, and the proposed methods are in polynomial time complexity.
Keywords: abstraction scopes identification; sound blocks; business process system; behavioral profile; Petri nets.
Provisioning Big Data Applications as Services on Containerized Cloud: A Microservices-based Approach
by Jing Gao, Wubin Li, Zhuofeng Zhao, Yanbo Han
Abstract: We present the fundamental challenges for dynamic provisioning of big data applications. The findings are based on our previous experience in this domain, as well as a comprehensive study on a selected set of state-of-the-art tools in the big data ecosystem. We then incorporate these findings in a framework aiming at dynamically provisioning big data applications as services on containerized cloud. The innovations behind the framework are to optimize the whole lifecycle of big data applications in a holistic manner by the adoption of microservices~(uServices) methodologies. The feasibility of our approach is verified through a case study of provisioning a large-scale user traffic data processing application in a private cloud environment backed by Kubernetes. We also show that while hosting big data applications in containerized cloud can significantly eliminate the presumed complexity of deployment and operation, it in the meantime also comes with a certain amount of cost in terms of learning curve and traceability. Our research helps technical decision makers to assess the adoption of microservices for big data applications more objectively.
Keywords: Big data application; Cloud computing; Container; Microservices; Automation.
Detect and analyse the concurrent flaws of the BPEL process in a VPN-based approach
by Puwen Cui, Ru Yang, Zhijun Ding
Abstract: Business Process Execution Language (BPEL) is a standard specification in service composition area. However, it is still lack of effective verification mechanisms based on formal methods. This paper describes a new modelling method for BPEL process by using a novel Petri net named Variable Petri Net (VPN). Several analysis methods are proposed to verify the concurrent flaws and an automated transformation and analysis tool is developed. Furthermore, the case study conducts a comparison with previous studies and validates the efficiency of our work.
Keywords: BPEL; concurrent flaws; data; Variable Petri Net.
Resource-constrained O2O service recommended strategy research
by Shuai Huangfu, Xiao Xue
Abstract: With the development of Internet, the problem of information overload is becoming more and more serious. Recommendation technology can screen out information that is useful to people. Therefore, many scholars pay attention to it. There are two types of Internet services: online and offline. At present, recommendation technology has become more and more mature in purely online applications, including news recommendation and commodity recommendation. However, O2O service recommendation needs the support of offline resources. Owing to the constraints of limited resources, many users adopt recommendation result at the same time, which often leads to crowded service points, useless recommendations and poor user experience. How to improve the effectiveness of O2O service recommendation under condition of resource constraints is a crucial issue. This paper proposes a group of O2O service recommendation strategies from the prospect of supply & demand matching to solve the problem step by step. Furthermore, we utilize computational experiment to perform performance comparison analysis for these service strategies. The results show that the adaptive adjustment mechanism based on current supply & demand conditions is conductive to improving effectiveness of O2O service recommendation so as to increase profit of the merchant and improve user experience.
Keywords: Online to Offline; collaborative filtering; resources constrained; service recommendation strategy; computational experiment.