International Journal of Applied Management Science (46 papers in press)
Trust, commitment and business expansion in automotive supply chains in a developing country: a principal-agency perspective
by J.A. Badenhorst-Weiss, A.S. Tolmay
Abstract: The automotive industry is important for sustaining developing countries economies. Literature states the South African automotive buyer-seller relationships are hampered by conflict where both parties reveal self-serving behaviour. This results in a decrease of trust and commitment, and increased supply chain uncertainty that is hampering business expansion. Hence, this study aimed to investigate the relationships between trust, commitment and business expansion through buyer-seller relationships. A quantitative study was conducted through a structured close-ended questionnaire among 114 managers from automotive component manufacturers. The empirical research found a strong presence of trust and commitment in automotive buyer-seller relationships. The influence of trust and commitment on possible business expansion was determined through a regression-based analysis. Findings revealed trust in a seller (agent) results in business expansion and commitment to a seller acts as a mediator between trust and business expansion. Action plans for both agents and principals (buyers) are recommended to sustain business.
Keywords: Automotive industry; supply chains; supply chain relationships; supply chain risk; social exchange theory; agent-principal theory; trust; commitment; business expansion; South Africa.
An Application of Integer Programming to Producing Aircraft Engine Parts
by Danny Solow, Dan Magri, Qiong Wu
Abstract: Integer programming models are developed for optimizing the production of a part used in aircraft engines. For some potentially large real-world problems, one of these models cannot be solved efficiently to optimality, so appropriate heuristics are developed. These heuristics are shown computationally to be both effective and efficient using randomly generated data.
Keywords: Integer Programming Application; Integer Programming Heuristic; Aircraft Manufacturing.
Multi-objective hazardous materials routing and scheduling for balancing safety and travel time
by Kamran Moghaddam
Abstract: Hazardous materials (hazmats) logistics and distribution is inherently a multi-criteria decision problem with conflicting objectives. Since the safest paths can be long and costly, this research develops a new multi-objective multi-period optimization model to find optimal links and routes to maintain a balance between safe and fast distribution of hazmats between origins and destinations through the transport network. The transport network includes multiple origins and destinations along with multiple hazmat classes to better mimic the challenges faced by practitioners. Due to the lack of sufficient historical data or unreliability of the past data (because of possible changes in regulations, network structures, and developments), we consider unknown probabilities for hazmat incidents along with a game-theoretic demon approach in a link-based model. Using the Nash game theory approach, an integrated routing and scheduling hazmat shipment problem is formulated. The objective functions of the mathematical model are defined to minimize both the probability of population exposure affected by hazmat transport risks (social objective) and the total transportation time (economic objective) in the distribution network. Since the formulated problem is multi-objective, this paper also proposes a solution method based on an integrated Monte-Carlo simulation and fuzzy goal programming to obtain Pareto-optimal (non-dominated) solutions. A numerical example is provided to illustrate the effectiveness of the developed mathematical model and the solution method in obtaining Pareto-optimal solutions.
Keywords: Transportation; Vehicle Routing; Game Theory; Hazardous Materials; Multi-Objective Optimization; Fuzzy Goal Programming.
A Cost Allocation Model Based on the Combination of Data Envelopment Analysis and Shannon Entropy (Case Study: Branches of the Central Post of Isfahan)
by Reza Maddahi
Abstract: The method used for allocation of costs in this study has several stages. In stage 1, various types of data envelopment analysis (DEA) models were used to assess the efficiency of decision-making units (DMUs), including constant return to scale and variable return to scale with a variety of input and output types in radial and non-radial states. In stage 2, Shannon entropy method was used to combine the obtained efficiencies for each decision making unit. In stage 3, the allocation of costs was done based on the combined efficiency number for each unit obtained in phase 2. The proposed cost allocation model was then implemented in an example and its fairness was compared with similar methods using the Gini coefficient method. Finally, the proposed model was investigated in Central Post of Isfahan. For this purpose, the seven postal areas of Isfahan were identified as decision-making units, operational cost and timely delivery factors were considered as inputs, and operating income, traffic, productivity, and items sent were considered as outputs. The results showed that Feyz and Neshat were the most efficient areas, while Malek Shahr was the least efficient area; thus, the highest cost was allocated to Feyz and Neshat, while the lowest cost was allocated to Malek Shahr.
Keywords: Cost allocation; Data Envelopment Analysis; Shannon Entropy; Gini coefficient method.
Self-Organization Migration Technique for Enhancing the Permutation Coded Genetic Algorithm
by Dinesh Karunanidy, Rajakumar Ramalingam, Subramanian Ramalingam
Abstract: Genetic Algorithm (GA) is well-known optimization algorithm for solving
various kinds of the optimization problem. GA is based on the evolutionary
principles and effectively solves the large-scale problem. In addition, it
incorporates the variety of hybrid techniques to achieve the best performance
in complex problems. However, self-organization is one of the popular model,
which acquire global order from the local interaction among the individuals.
The combined version of self-organization and genetic algorithm are adopted
to improve the performance in attaining the convergence. This paper proposes
a bi-directional self-organization migration technique for improving the genetic
algorithm which achieves the convergence and well-balanced diversity in the
population. The experimentation is conducted on the standard test-bed of
travelling salesman problem and instances are obtained from TSPLIB. Thus, the
proposed algorithm has shown its dominance with the existing classical GA in
terms of various parameter metrics.
Keywords: Genetic Algorithm; Self-Organization Migration Algorithm;
Hybrid Genetic Algorithm; Traveling Salesman Problem; Pattern Replacement;
Optimum prediction and forecasting of wheat demand in Iran
by Reza Babazadeh, Meisam Shamsi, Fatemeh Shafipour
Abstract: Wheat is the staple food source in most countries and is grown in bad climatic conditions such as cold areas. Wheat contains about 55% carbohydrates and 20% calories. Optimum prediction of wheat demand would help policy makers to take optimum strategic decisions about the amount of domestic wheat production, import, and export for mid and long terms. In this study, Firstly, the factors affecting demand for wheat are identified according to market analysis. Then, Artificial Neural Network (ANN) method is employed for optimum forecasting of wheat demand in Iran. Different regression methods are used to justify the efficiency of the ANN model. The Mean Absolute Percentage Error (MAPE) of the ANN method is achieved equal to 4.64% which shows about 95% precision of the ANN method. According to acquired results, the ANN method could be efficiently applied for wheat demand prediction in order to take appropriate related strategic decisions.
Keywords: Wheat demand; Forecasting; ANN; Regression models.
An Energy Efficient Cluster Formation in Wireless Sensor Network using Grey Wolf Optimization
by Rajakumar Ramalingam, Dinesh K, Vengattaraman T
Abstract: With the emerging technology, Wireless Sensor Network (WSNs) plays a vital role in monitoring day-to-day life activities. At the same time, wireless sensor networks are suffering from various issues such as such as routing, intrusion detection, topology control and so on. However, to address these issues an energy efficient cluster formation is quite important. Thus, the successive cluster formation improves the lifetime of the networks in terms of reducing the size of routing overheads. Our contribution to this work includes on selecting an energy efficient cluster heads with the aid of the Grey Wolf Optimization (GWO) algorithm. GWO has been introduced in recent years and resides in the division of swarm intelligence algorithm (SI). This algorithm attracts several researchers with its efficient leadership capability and hunting methodology but it lags in exploration and exploitation which leads to poor clustering in WSN when it applied. The proposed methodology includes tuning of the coefficient parameter for efficient exploration and exploitation process then the algorithm has been utilized efficiently to solve the issue which resides in the wireless sensor network. The performance of the proposed work is examined with other swarm intelligence algorithm. The experimental results show that the GWO algorithm performs better in providing optimal results over cluster head selection and minimized energy consumption in WSN.
Keywords: Wireless Sensor Network (WSN); Clustering; Grey Wolf Optimization (GWO); Swarm Intelligence (SI); coefficient parameter.
'Influence of Organizational Career Management Variables: Mentoring on Career Success of faculty academics An Empirical study from an Indian Perspective
by Seema A
Abstract: The main purpose of the present study is to determine the influence and relationship between mentoring and career success of faculties. Career success is termed as the individuals subjective or intrinsic feelings of accomplishment and ultimate satisfaction pertaining to his or her career. This study also highlights on one of the organisational career management practices, that is, mentoring in bringing its importance and linkage with career success from an individual point of view in support with literature review. Descriptive research design has been adopted for the study. Stratified random sampling method followed by random sampling technique was used for the study. It was decided to conduct the data collection with 450 (around 59% proportionate) faculty members of selected 17 Arts and Science colleges at Vellore district, Tamil Nadu, India. This present study has utilized Structural Equation Modeling (SEM) through Smart Partial Least Square (PLS) 2.0 Version. The study outcomes show the significant influence and correlation between mentoring and career success in terms of career prospect, career commitment and career satisfaction.
Keywords: Keywords: Career Management; Organizational Career Management; Mentoring; Career Success; Faculty; Academics; Indian Perspective.
Exploring Safety Climate Factors in Construction
by Tariq Umar
Abstract: This paper aims to explore and to make explicit of the existing safety climate assessment tools and dimensions. The concept of safety climate is firstly discussed with a review of different safety climate factors from the published literature. A qualitative research method was employed to explore the safety climate factors through a systematic review using four databases and specific keywords. A total of 68 papers were selected for the screening process. The screening process allowed to select the final 18 safety climate assessment tools and papers consisting of 98 safety climate factors spanning over a period of 39 years (1980 2019). Construction organizations may consider these factors to assess the current maturity level of their safety climate and to develop plans to achieve the required level. It is recommended that the factors discussed in this paper may be validated first before they are incorporated in the assessment of safety climate.
Keywords: Health & Safety; Management; Safety & hazards; Safety Climate; Assessment; Construction Industry; Qualitative and Quantitative Research Methods; Systematic Review; Safety in Construction; Safety Climate Factors.
ADVANCED CLASS FOR VARIANCE ESTIMATION UTILIZING KNOWN QUARTILES OF THE AUXILIARY VARIABLE
by Dinesh Sharma, S.K. Yadav, Hari Sharma
Abstract: Variance is a natural phenomena among similar objects in nature and it is one of the majors of dispersion. Therefore, its estimation is of crucial importance for large populations to save time, money and manpower. In this paper, we propose an estimator for estimating population variance of the primary (study) variable using known quartiles of the secondary (auxiliary) variable and their functions. The optimum value of the scalar in the suggested estimator is acquired to ensures mean squared error (MSE) of the suggested estimator as a minimum. A comparison has been presented between suggested and the competing estimators, and the theoretical efficiency conditions are derived. For the verification of these efficiency conditions through the calculation of mean square errors of various estimators, a numerical study is performed.
Keywords: Primary variable; Secondary variable; Quartiles; Bias; MSE; Efficiency.
Perceived Determinants and Barriers of Recruitment Process Outsourcing in Service Sector of Pakistan- A Qualitative Approach
by Mehreen Memon, Muhammad Aqil, Kamran Ahmed Soomro, AHMAD Adeel
Abstract: Purpose: Human resource management is one of the challenging jobs for organizations and Recruitment and Selection of right person has emerged as a biggest challenge for Human Resource Management. In order to cope with this challenge, the organizations are taking assistance from specialized agencies. This is called Recruitment process outsourcing. This study aims at finding out the determinants for and barriers in Recruitment Process Outsourcing.rnResearch Design: The study adopts Qualitative Approach to explore the objective. The research is based on the inductive approach and phenomenology has been used as a research methodology. The participants are selected through non-probability purposive sampling method with a sample size of 10 organizations in service sector of Pakistan. The organizations were grouped into two categories: one that is adopting RPO and other which is not adopting RPO. The primary data has been collected through in-depth interviews with HR professionals and the analysis is conducted through thematic analysis. rnFindings: The study finds out that diversified pool of candidates, bulk hiring, professional expertise, replacement option, focus on core HR responsibilities and promoting fair recruitment process are the major determinants for adopting RPO by Organizations. rnOriginality: The factors such as additional cost, RPO branding with non-management positions, incompatibility issues and emotional detachment are the major barriers in adopting RPO. The study suggests that the use of RPO in small size organizations as an emerging theme. Organizations can make decision of adopting RPO for management level positions according to the determinants highlighted in the study.rn
Keywords: RPO; Phenomenology; Thematic analysis.
A shortest path problem in a stochastic network with exponential travel time
by S.K. Peer, Dinesh Sharma, B. Chakraborty, R.K. Jana
Abstract: A shortest path problem in a stochastic network is studied in this paper. Assuming travel times between the nodes in the network as exponential random variables, a chance constrained programming formulation of the problem is obtained. Then the deterministic separable convex programming formulation of the problem is derived by using a proposed upper bound technique. The expected length and probability of the shortest path are obtained by solving the converted problem. Finally, the results obtained from the proposed approach are compared with Kulkarnis (1986) method as well as Peer and Sharmas (2007) method for a network of a practical application under consideration with exponential random variables.
Keywords: Chance constrained programming; separable convex programming; upper bound technique; stochastic network.
Impact of brand mascot in advertising on brand image among Indian consumers.
by Siddharth Shimpi
Abstract: Using brand mascot to promote products was once a creative concept. Today, brand mascot has become commonplace. The present study explained and explored the impact of brand mascot in advertising on brand image among Indian consumers. A structured and un-disguised questionnaire was developed and used to collect the primary data from 576 respondents. Conceptual model was investigated by using structural equation modeling. Study delivered detailed insight on various elements used for analysis and revealed that brand mascots attractiveness and brand mascots trustworthiness influenced brand credibility and brand image. Further, study confirmed mediating role of brand credibility between brand mascots attractiveness and brand mascots trustworthiness on brand image.
Keywords: Brand mascot; brand mascot’s attractiveness; brand mascot’s trustworthiness; brand credibility and brand image.
An integrated approach of Fuzzy ELECTRE I for Supplier Selection
by Diep Thi Hong Le, Tran Thi Tham
Abstract: Supplier selection is a strategic decision and calls for serious attention in both academian and industry daily. It is the process of selecting suitable suppliers, who offer necessary products or services that match the needs of the organizations. Cooprating with the suitable suppliers will bring many benefits to the enterprises, helping businesses reduce costs, reduce risk, improve flexibility, customer service and competitiveness. This paper is aimed to present a fuzzy decision-making approach for supplier selection problem. In which, a set of 22 criteria are used and the Fuzzy ELECTRE method with trapezoidal membership function is applied to evaluate and select appropriate suppliers. A case study of plastic packaging company is given to illlustrate the proposed methodology.
Keywords: Fuzzy theory; ELECTRE I; Supplier selection; Supplier evaluation; Supply chain management.
Designing a Model of Recruitment and Selection System with Talent Management Approach: The Case of Iranian National Tax Administration
by Roya Khayer Zahed, Hadi Teimouri, Ali Shaemi Barzoki
Abstract: This study aimed to explore the effects of recruitment and selection on talent management in Iranian National Tax Administration (INTA). The type of research, in terms of the nature of data, is mixed (qualitative-quantitative). The goal of this paper in the qualitative phase was to design and describe the model of recruitment and selection system with talent management approach. The qualitative data were gathered through thematic interviews. Using insights from 20 managers in this organization and 3 academic experts, five broad levels of factors of recruitment and selection were identified for implementing talent management. The five dimensions of recruitment and selection with talent management approach included the organizations macro policies and strategies, future attitude, merit orientation, value- orientation and comprehensiveness. In the quantitative stage, the impact of the recruitment and selection system on talent management implementation was examined. The quantitative data, in the stratified random sampling, were gathered with questionnaires from 493 managers and experts of INTA organization. The data were analyzed using structural equation modeling in PLS software. The results of the quantitative research indicated that the recruitment and selection system had a positive and significant impact on implementing talent management. The results can be useful in helping to plan organizational staffing in order to identify, recruiting and selecting talents
Keywords: Recruitment and selection; Human Resource management; talent management; mixed method; qualitative research; quantitative research.
Planning the Next Generation for Family Business: Affecting Factors on Successes Succession at Padang City
by Dahliana Kamener, Norasekin Ab. Rashid, Daniati Puttri
Abstract: The succession topic is a trending view of a family business in terms of inter-generational leadership. This study aimed to examine the role of strategic planning as a mediate in affecting succession planning, non-family leadership on the successful succession of family businesses in Padang city, West Sumatera, Indonesia. The population is the family businesses that have been identified where they have businesses in the second or third generation. One hundred managers or CEOs of the family businesses were selected as samples using non-probability sampling method which was purposive and convenience sampling technique. The data were collected through interviews, observations, and questionnaires. Quantitative analysis methods are applied to analyze the data, such as the multiple regression analysis by using SEM PLS 3.2.8 to see the direct effect of independent variables and strategic planning as mediating on the succession of the family businesses. The result showed that succession planning does not significantly and directly affect the successful succession of family businesses. Nevertheless, the effect of succession planning is significant to strategic planning, and strategic planning was significant affected success succession . Therefore, succession planning is fully mediated by strategic planning through the success succession of family business. Furthermore, non-family management does not significantly and directly affect the successful succession, and neither, non-family management is mediated by strategic planning through the successful succession of the family business at Padang city.
Keywords: succession planning; non-family management; strategic planning; success succession.
THE DIFFERENCE OF CUSTOMER SATISFACTION AND LOYALTY ON THE USE OF POINT OF SALE (POS)
by Yuhelmi , Surya Dharma, Mery Trianita
Abstract: The purpose of this study is to empirically test the differences in customer satisfaction and loyalty from the minimarket service in using a Point of Sale (POS) system application based on the level of system utilization. From 243 respondents, the results showed that there were differences in satisfaction between the high level of POS utilization and the low level, but there was no difference in customer loyalty. This proves that the use of POS can satisfy customers, but does not always make them loyal because customers prefer to shop at minimarkets that are close to their homes even though the POS utilization level is still low. Future research is suggested to examine the influence of minimarket locations on customer loyalty
Keywords: POS; Customer Satisfaction; Loyalty.
Establishing a relationship between risk tolerance and the investor lifecycle
by A. Van Den Bergh, S. Ferreira, J. Dommisse, Z. Dickason-Koekemoer
Abstract: The concept of risk tolerance has increasingly gained importance in the financial industry after the global financial crisis (GFC) in 2007/2008. Individual investors risk perception and willingness to tolerate risk may vary during different phases of the investor lifecycle. However, it is important to analyse individual investors risk tolerance during different phases of the investor lifecycle, as it will mainly influence their investment decisions. This paper aims to determine the influence of age, risk tolerance and risk perception on the investor lifecycle within a South African context and the deviation from theory during different phases of the investor lifecycle. The findings indicated that age is significant in predicting the probability of individual investors being categorised into one of the three phases in the investor lifecycle. Furthermore, the level of risk tolerance individual investors tolerate are not entirely according to theory and depends on individual investors perceptions and attitudes towards risk.
Keywords: age; risk tolerance; risk perception; individual investors; investor lifecycle; South Africa.
Entrepreneurship Curriculum Practice in Malaysian Universities: Successes and Challenges
by Abubakar Sani, Hazri Jamil
Abstract: Entrepreneurship promotes economic development in a country, mainly through addressing problems of self-employment and unemployment. Generally, new businesses registered, new business density, and ease of doing business are considered as some of the important indicators of entrepreneurship activities. Against this backdrop, this paper employed mixed method approach to explore the efforts and commitments of the Malaysian government towards promoting entrepreneurship activity among its citizens, especially the university graduates and how that helps in reducing the current issue of unemployment among its populace. Essentially, academic journals and other relevant documents on the successes and challenges of implementing entrepreneurship program in Malaysian universities were reviewed. Again, secondary data was also obtained from the world development indicator (2017) on entrepreneurship and graduate unemployment (GU) in the country to test the relationship between the two variables. Entrepreneurship activities were measured using variables such as the new businesses registered (NBR), new business density (NBD), and ease of doing business (EODB) all as independent variables; whereas as GU is the dependent variable. Eviews 10.5 software was used to analyse the data using the Ordinary Least Square model. Findings from the review reveal that the Malaysian universities have achieved number of successes in implementing the program; yet, the rate of unemployment among the graduates is quite alarming. It also shows that the higher the number of registered new rate of business, the lower the graduate unemployment in Malaysia, showing the significance of entrepreneurship in reducing unemployment in the country. More so, the findings depict that ease of doing business in Malaysia contributes to 3.44% reduction in unemployment, elucidating that the business-policy in Malaysia needs to be revised
Keywords: Entrepreneurship; curriculum practices; ease of doing business; new business density; new businesses registered; Malaysia.
An inventory model for deteriorating item under permissible delay in vendor managed system
by Ali Akbar Shaikh, Leopoldo Eduardo Cardenas-Barron, Asoke Kumar Bhunia
Abstract: This paper discusses a vendor managed inventory system with the credit policy. The vendor-managed inventory (VMI) plays an important role in inventory as well as supply-chain management. In VMI system the supplier is responsible for decisions relating to the timing and replenishment quantity. Shortage are allowed with a partially backlogged waiting up to arrival of the next lot. Demand dependent on selling price as well as frequency of advertisement. Finally, to illustrate and validate of the model we have taken a numerical example. We have performed a sensitivity analysis changing one parameter at a time and other parameters their original value.
Keywords: VMI policy; deterioration; permissible delay in payment; advertisement and price dependent demand.
Addressing resiliency in supply chains through a multi-criteria group evaluation approach under interval type-2 fuzzy uncertainty
by M.H. Haghighi, S.M. Mousavi, V. Mohagheghi
Abstract: In real-world supply chain problems because of the non-existence of exact information and various fluctuating conditions, resilient supplier selection problems (RSSPs) are considered. In this paper, interval type-2 fuzzy sets (IT2FSs) are used in a modified VIKOR method to achieve more accuracy in the results. Moreover, a new method for computing weights of decision makers and a new method for computing weight of each evaluation criterion based on subjective and objective data are introduced. Finally, to verify the presented method a numerical example from the existing literature is presented and solved.
Keywords: Resilient supplier selection; Multi-criteria group decision making (MCGDM); Interval-valued type-2 fuzzy sets (IT2FSs); Subjective and objective weights; Weights of decision makers; Modified VIKOR method.
An Approach to arrive at Stationarity in Time Series Data
by Nafeesathul Basariya M.I, M. Punniyamoorthy Murugasean
Abstract: This paper presents a framework for converting non-stationary data into stationary data in a systematic way. Initially, the data is fitted with a unit root model to check the presence of unit root. The model which confirms the absence of the unit root is considered for stationarity check. The error term of the model that has passed the unit root test is checked for randomness and homoscedasticity. The data is considered to be stationary if it satisfies the conditions like the absence of unit root, presence of error randomness and homoscedasticity of error term. The non-stationary data has to be differenced and is checked for absence of unit root, presence of error randomness and homoscedasticity of error term. This process is continued to ensure the stationarity. This framework has been elucidated for macroeconomic variables namely consumption, gross domestic product and consumer price index.
Keywords: Dickey Fuller; Durbin Watson; Lagrangian Multiplier Test; Augmented Dickey Fuller; Stationarity; Randomness of error term; Homoscedasticity of error term.
ANTECEDENTS OF PURCHASE INTENTION: A STUDY ON FASHION BRANDS
by G. Aiswarya, Jayasree Krishnan
Abstract: Purchase intention depends on various factors, based on the product or a brand. With the rapid growth in urban, rising disposable income, and exposure to more fashion brands has led to the purchase of more branded apparels and much emphasis is required in this category. There were fewer studies in this segment and hence this study gains momentum. The primary objective of this research is to derive the factors which influence purchase intention on fashion brands. Exploratory factor analysis is conducted and four factors were obtained; Brand perception, Brand cues, Purchase decision and Brand awareness. Our secondary objective is to analyze the extent of the relationship between the factors obtained and purchase intention. Multiple regression analysis is conducted which reveals that Brand perception and Branding cues play a key role and have a positive relationship with Purchase Intention. However, purchase decision and Brand awareness have a positive role in influencing Purchase Intention. This study gives an insight into various aspects of buying behavior which leads to purchase intention based on consumer perception. It also throws light on the cues which greatly influence them to purchase a particular brand.
Keywords: Antecedents; Factors; Fashion brands; Purchase intention.
Determining Optimal Inventory Policy and Sales Price under Promotional Expenditure for Some Veblen Products
by Anil K. Agrawal, Amit Ambar Gupta, Manu K. Vora
Abstract: This paper focuses on determining the optimal promotional expenses as well as optimal sales price and lot-sizing policies for Veblen products, generally being luxury goods consumed conspicuously. The price-demand relationships considered for the product are the ones suggested by Leibstein (1950). The promotion is assumed to increase the products perceived value facilitating in increasing the selling price without sacrificing the demand. The effect of promotional expenses has been analysed for the niche and mass markets using two different relationships. For obtaining the optimal pricing, lot-sizing and promotional expenses, a mathematical model has been developed and a GA based heuristic is also proposed. Numerical examples are taken to illustrate the use of the proposed problem-solving approaches and also to carry out sensitivity analyses. The results show almost no impact of variation in setup cost and carrying cost rate on optimal inventory policy, but of the product unit cost.
Keywords: Conspicuous consumption; Veblen effect; Pricing; Promotion; Price-sensitive demand.
Design of TSSFD technique and its application study in a traditional Pump Manufacturing Company
by Thirunavukkarasu Venkatachalam, Devadasan S R
Abstract: During the last two decades Six Sigma concept and Quality Function Deployment (QFD) technique have been widely applied in various types of organization. The common goal of Six Sigma and QFD is achieving customer satisfaction. Yet QFD is rarely found in Six Sigma programs. Hence, the research community has just started to indicate the importance of impregnating QFD in Six Sigma programme. In this context, during the research reported in this paper the technique called Total Quality Function Deployment (TQFD) was impregnated with Six Sigma concept to evolve a model named as Total Six Sigma Function Deployment (TSSFD). The application of TSSFD was studied by examining it in a pump-manufacturing environment. The anticipated results of this application study were fruitful and helped in unearthing hidden facts that are currently obstructing the pump industry to achieve Six Sigma level quality through the translation of customer voices into practically understandable languages.
Keywords: Six Sigma; QFD; DMAIC; Training; Pump manufacturing.
The impact of FDI on economic growth: An empirical study of Moroccan FDI.
by Chafik Bakour, Riad ABADLI, Mohamed Yassine Abahamid
Abstract: The main objective of this article is to empirically examine the impact of foreign direct investment flows on growth in Morocco, for which we have designed an econometric model based on the Cobb-Douglas production function which allowed us to take into account also the contribution of human capital; in practice we used data extracted from the data center for the development of the World Bank and cover the period 1976 2016. The results demonstrated a two-way causality between GDP and FDI, between GDP and human capital, and between FDI and human capital. Thus, we have found that the mechanisms of interactions between these different variables are operational in the medium term. These results are of great importance on the one hand for the researchers because they answer partially on the questions of causal links between the economic growth and the FDI, and on the other hand for the public authorities by illuminating the strategies of opening and attraction of foreign capital.
Keywords: Foreign Direct Investment; economic growth; Moroccan economy; Economic reforms; Human capital; Times series; Toda and Yamamoto causality tests.
A competitive facility location problem using distributor Stackelberg game approach in multiple three-level supply chains
by Maryam Esmaeili, Sara Gharegozlou Hamedani
Abstract: This paper studies a discrete facility location problem in two different supply chains including suppliers, distributors, and customers. The current and new distribution firm act as the leader and the follower respectively in a Stackelberg game. The model considers the lead-time as a competitive factor between the new distribution centers (DCs) and the existing ones as well as optimizing the location and number of to-be-established DCs in the new supply chain by minimizing the total cost. The e Branch and Bound as well as Genetic Algorithm (GA) are used for solving the model, and the results are compared with the situation that there is no competitor. results show in case of competition; there is more possibility of lost sales ignoring the rival decision in making strategic decision of locating new DCs. While, when there is no other player, decisions are taken independently as the only possible option for consumers.
Keywords: Competitive facility location; supply chain network design; Stackelberg equilibrium; lead-time.
Intention to use mobile wallets: An application of the Technology acceptance model
by Rishabh Shekhar, Uma Pricilda Jaidev
Abstract: The research aim is to determine the factors influencing the adoption of the mobile wallet payment services, an innovation in the contactless payment. Constructs namely personal innovativeness, perceived enjoyment and perceived self-efficacy were included in the technology acceptance model. Using the structural equation modelling and multi-group analysis, the effect of the personal innovativeness, perceived enjoyment, perceived usefulness, perceived ease of use, and attitude towards using were examined. Age, gender, usage, and experience were introduced as the moderator variables in the proposed research model as there is a dearth of studies incorporating these variables. The mediating effect of the perceived usefulness was also studied using the procedure specified by Baron and Kenny (1986). The findings of this study revealed that personalrninnovativeness, perceived enjoyment is associated with the perceived ease of use, and perceivedrnenjoyment perceived ease of use was found to influence perceived usefulness. Attitude towardsrnusing is influenced by Perceived usefulness and Perceived ease of use. Attitude towards usingrninfluences the behavioural intention to use the mobile wallet payment services. There moderatingrneffects of age, gender and experience were not significant, while the previous usage significantlyrnmoderates the relationship between i) perceived enjoyment and perceived usefulness and ii)rnperceived ease of use to Attitude towards using. Theoretical and practical implications arerndiscussed. Future research directions have been suggested.
Keywords: Mobile wallet payment service; technology acceptance model; Structural Equation modelling; Multi group analysis.
A hybrid two stage algorithm for solving the blocking flow shop scheduling problem with the objective of minimize the makespan
by Harendra Kumar, Shailendra Giri
Abstract: Flow shop scheduling is an important tool for a variety of industrial system and it has important applications in manufacturing and engineering. This paper considers the blocking flow shop scheduling problem involving processing times and provides a hybrid approach based on artificial neural network and genetic algorithm technique. The objective of this paper is to focus on to minimize the makespan. In this paper a multi layer neural network algorithm is developed to find the initial schedule of jobs and then a genetic algorithm is designed to improve the initial sequence of jobs to obtained the best job schedule that minimize the makespan. A numerical example is illustrated to explain the proposed approach and demonstrate its effectiveness. The performance of our suggested hybrid model is compared with the various existing method in the literature and the results indicate that the proposed model performs significantly better than the other methods in the literature. The computational results that are presented in this paper are very encouraging and have shown that the proposed algorithm is superior.
Keywords: Artificial neural network; genetic algorithm; flow shop scheduling; blocking time; makespan; job sequencing.
Antecedents and intention to revisit: experimental research for the beach resort tourism in central provinces, Vietnam
by Nguyen Huy Tuan, Le Duc Toan
Abstract: This research clarifies the relationships among antecedents (destination risk, destination image, destination satisfaction), and intention to revisit in the literature. This study draws new insights by examining the effects of antecedents on the intention to revisit through analysis of linear structure model (SEM). The findings of this study showed that the perceived destination risks influenced destination images, both of perceived destination risk and destination images not only have significant direct impact on revisit intention but also significant indirect affect the revisit intention through the satisfaction. Evaluating the mediating role of destination satisfaction and the moderation role of the number of times that tourists have visited the destination before by multi-group analysis. The study results also showed that the more number of times that tourists have visited the destination before, the higher the destination image has a positive influence on the destination satisfaction, and the higher the destination image has a positive influence on the intention to revisit. The findings of this study provide insights for beach resort tourism managers, allows them understand the relationships between antecedents and the revisit intention of tourists, thereby contributing to the beach resort tourism development.
Keywords: Destination image; Destination risk; Destination satisfaction; Revisit intention.
A novel proposal to use the WINGS method in a multi-criteria context
by Frederico Silva Valentim Sallum, Luiz Flavio Autran Monteiro Gomes, Jerzy Michnik
Abstract: We propose a new way to apply the WINGS method in a multi-criteria context. In the WINGS application the decision maker can set the strength degree of each component and the influence degree of each component on others in the studied system. We consider a system whose components are alternatives. We then generate the strength degree of each alternative by applying the TOPSIS method. We denote the influence degree as preference degree. This preference degree is generated by the PROM
Keywords: WINGS method; TOPSIS method; Strength Degree; PROMÉTHÉE II method; Preference Degree.
A Goal Programming Strategy for Bi-Level Decentralized Multi-Objective Linear Programming Problem with Neutrosophic Numbers
by INDRANI MAITI, Tarni Mandal, Surapati Pramanik
Abstract: This paper develops a goal programming (GP) algorithm to evaluate bi-level decentralized multi-objective linear programming problem (BLDMOLPP) in neutrosophic number (NN) environment. In a BLDMOLPP a single decision maker (DM) is present at the upper level and multiple decision makers at the lower level. Here the parameters of the problem are considered to be NNs in the form of [P+QI], where P and Q are real numbers and indeterminacy is represented through the symbol I. I is expressed in the form of a real interval as agreed upon by the DMs. The BLDMOLPP with NNs then gets converted into an interval BLDMOLPP. Using interval programming, the target intervals for the objective functions are identified and subsequently the goal achievement functions are constructed. The upper level DM provides some possible relaxation on the decision variables under his/her control to cooperate with the lower level DMs to attain a compromise optimal solution. Thereafter, goal programming (GP) models are formulated by minimizing the deviational variables and thereby obtaining the most satisfactory solution for all DMs. Finally, a numerical example demonstrates the feasibility and simplicity of the proposed strategy.
Keywords: neutrosophic number; bilevel decentralized programming; multi-objective programming; goal programming.
Extreme Value Modelling of the South African Industrial Index (J520) returns using the Generalized Extreme Value Distribution.
by Owen Jakata, Delson Chikobvu
Abstract: The aim of this study is to analyse the behaviour of extreme returns of the South African Industrial Index (J520) (years: 19952018) and estimate extreme risk measures using the Generalised Extreme Value Distribution (GEVD). The results reveal that for the: 8, 20 and 40 quarterly return periods, the estimated extreme losses are 9.28%, 13.65% and 17.03% respectively. The extreme possible gains for the same periods are: 9.81%, 11.63% and 12.68% respectively. Therefore, in the short term (8 quarters) the extreme losses are less than the extreme gains, but in the medium to long term (20 and 40 quarterly return periods), the extreme losses are greater than the extreme gains. This study uses the GEVD to build models that can be used to estimate extreme risk measures that can act as effective decision making tools for minimising risk exposure and maximising on the potential gains in equity portfolio risk management.
In the short term the gains in the South African Industrial Index are greater than the losses.
However, in the medium to long term, for an investor invested in the same Index, the losses are greater than the gains.
Keywords: Block Maxima/Minima; Extreme Value Theory; Generalised Extreme Value Distribution; Maximum Likelihood Estimation; Return Level; Return Period.
Measuring Dynamic Capabilities-Based Synergies Using Real Options in M&A Deals: Amazons Acquisition of Whole Food
by Andrejs ?irjevskis
Abstract: Dynamic capabilities have become well established as a new imperative for organizing M&A processes. However, understanding the full benefits and possible limits of real options applications to measure a dynamic capability-based (managerial) synergies remains a challenge. The author developed three propositions and justified them by application of dynamic capabilities framework and real options theory to highly strategic and not standard M&A deal: Amazons acquisition of Whole Foods in 2017. The illustrative case study made it possible to bridge together two streams of research on dynamic capabilities and real options. While the empirical application of the dynamic capabilities framework makes them more visible, the application of the real options is making dynamic capabilities measurable in the M&A deals. In the end, the author discusses theoretical and managerial contributions, limitations, and future work.
Keywords: merger and acquisition; dynamic capabilities; synergy; real option.
Use of known population median of study variable for elevated estimation of population mean
by S.K. Yadav, Dinesh Sharma, Hari Sharma
Abstract: In this research, we propound a new enhanced estimator of population mean of the variable under study utilizing the acquaintance on the known median of the main variable. We perusal the features of the sampling distribution of the suggested estimator up to the approximation of order one. The articulated estimator is collated with the competing estimators of the population mean, and the prerequisites of the proposed estimator to be more efficient over competing are derived. These conditions are put to the proof using the numerical example. The efficiencies are compared in terms of the mean squared errors.
Keywords: Main variable; Modified ratio estimator; Mean Squared Error; Percentage Relative Efficiency.
Municipal Water Supplies Efficiencies in Gaza Strip: A Data Envelopment Analysis Approach
by Abdelrahman AbuSerriya, Hatem Abu Hamed, Salah Agha
Abstract: This paper reports the findings of a research carried out to evaluate the efficiency of municipal water supply systems using Data Envelopment Analysis (DEA). Input and output variables needed for DEA were identified using literature review and questionnaires. Input variables considered in this paper include Number of Connections (NC), Length of Water Network (LWN), Number of Employees (NE) and Maintenance and Operation Costs (MOC), while Total Revenues (TR) and Number of People Served (NPS) were used as output variables. Values of these variables were obtained for the existing 25 municipalities for the years of 2015, 2016, and 2017 and the averages of these variables were calculated and used in the model.
The paper uses Charnes, Cooper and Rhodes model (CCR) and Banker, Chames and Cooper model (BCC). Results indicate that length of water network and maintenance and operation costs were the major sources of inefficiencies. It has been further found that the municipality size effect as represented by the number of connections; length of water network; number of employees or maintenance and operation cost on the efficiency is very small. Therefore, it was decided to use the CCR for the rest of the paper.
In order to make results more tangible, benchmarks for each of the inefficient municipalities were identified such that each of the inefficient municipalities can learn from best practicing ones. It was found that only 5 efficient municipalities can be used as benchmarks for all the inefficient ones. Further, each of the non-efficient municipality is advised by how much to reduce some of its inputs in order to become efficient.
Keywords: Efficiency; Data Envelopment Analysis; water services; municipalities.
The Mediating Impact of Motive Fulfilment on the Relationship Between Supervisors and Volunteers Intention to Stay
by Queen Usadolo, Yvonne Brunetto, Silvia Nelson, Patrick Gillett
Abstract: In this study, the effects of relationships with immediate supervisors, or leader-membership exchange (LMX), on volunteers intentions to stay with their organisations through motive fulfilment are examined. Data were collected from 213 volunteers working in community nonprofit organisations in Queensland, Australia, and hypotheses tested with simple and multiple linear regression analysis. The findings show that the fulfilment of values, understanding, enhancement, social, and career motives partially mediated the effect of LMX on volunteers intentions to stay. The results indicate that motive fulfilment is important in promoting positive workplace outcomes by enhancing volunteer-supervisor relationships.
Keywords: Volunteers; leader-member exchange; motive fulfilment; intention to stay; and NPOs.
Special Issue on: AIC 2018 Qualitative and Quantitative Research in Management
CEO Power as an important mechanism of corporate governance: Available founds and Social engagements
by Sihem Bouguila, Victor Surjit
Abstract: While there are growing bodies of research examining corporate governance effect on corporate social performance, little has been done in examining the effect of Manager Power on corporate social performance (CSP). This study addresses this issue by using Citizens firms as rated by the KLD Research Analytics, to show that CEO power influence the financial performance and therefore can affect the process of the global value creation for all the firm' stakeholders. Using a sample of 256 Top citizen firms, we find that a good level of CEO Compensation and a social Humanities Background with an effective control of outsiders may align the managers interests on these of others Stakeholders. This effect is not direct it should be moderated by the achievement of a good financial performance in order to generate available resources and funds which will be used to finance the costs of the social demands of stakeholders. There is a positive synergy between the financial and the social demands if the managers have the initiative and are really committed to serve and balance all the interest of the stakeholders, this depends in great measure on their background and on their own benefits. This suggests that CEOs Power is decisive in influencing the social performance. Nonetheless the availability of the resources and a satisfactory compensation can attenuate the negative effect of the managerial discretion. there are many fruitful directions for future research, the benefits and challenges to conducting similar studies in other contexts is focused upon to correspond to the global nature of this special issue.
Keywords: Manager power; manager background; Corporate governance; fFinancial performance; Social performance; FCF; available Founds.
Special Issue on: Recent Multidisciplinary Research Advancements in Information Technology and Applied Management for Sustainable Development
DNA-SKA: A DNA Congruous Secure Symmetric Key Generation Algorithm
by Monika Poriye, Shuchita Upadhyaya
Abstract: An efficient algorithm DNA-SKA (DNA based Symmetric Key Algorithm) for generating secret keys for sensor nodes is proposed in this paper. The key feature of the proposed algorithm is the usage of a DNA sequence as an initial key which is proffered to be selected from National Council of Biotechnological Information (NCBI) database available publically. Authentication process is required to make a secure communication between nodes. The Base Station then provides both nodes with two unique DNA strands generated by the unwinding of a single DNA molecule selected from NCBI database. The nodes then perform a simple but ingenious mechanism on the strands to obtain a similar symmetric key to be used for further encryption of the data to be communicated between the nodes. Computationally, it is a light-weight algorithm and better suitable` for devices like sensor nodes because of their limited computing resources.
Keywords: Wireless sensor networks; DNA Computing; DNA Replication; DNA Cryptography & DNA Steganography.
Machine Learning-Based HR Appraisal System (ML-APS)
by Madapuri Rudra Kumar, Vinit Kumar Gunjan, Mohd Dilshad Ansari
Abstract: Appraisal systems hold critical importance in organizational human resource management. The way HR departments have developed over the period to the recent trends of AI-based human resource management systems and practices reflect on the emerging importance of effective HRM. In this present work, one of the key functionalities of the HRM process the Appraisal systems are focused upon. This work presents a comprehensive model of appraisal system that relies on the machine learning solution for predicting evaluating the appraisal score. The developed model is trained with SVM classifier and is tested with 600+ records for evaluation. The precision and recall values indicated by the test results reflect that the model is potential and if more effectively pursued in terms of training and incorporating more in-depth analysis, the model can be a sustainable solution for human resource appraisal system.
Keywords: Machine learning-based appraisal system; ML-APS; 360 degree performance system analysis.
Binary and Multi-class Classification of Android Applications using Static Features
by Meghna Dhalaria, Ekta Gandotra
Abstract: In recent years, the Android platform has ruled the market of smart mobile phones. As a result, there is a massive increase in Android applications such as banking, education and gaming etc. With the increase in the number of mobile applications and the dependency of users on these, Android has become the prime target of the attackers. Thus, the growth of sophisticated and complex Android malware is increasing that poses various threats such as stealing information, system damage etc. Thus, there is a need to find new ways to detect Android malware. For this purpose, machine learning algorithms have been used to build classifiers. To train such classifiers, there is a need of set of features that could describe the behavior of applications. Thus, we have created two datasets (binary and multiclass datasets) and made these publically available on GitHub. In this paper, a framework has been proposed which is capable of performing binary and multi-classification of Android applications. Static features such as Intents, Permissions, API calls and Command Strings are extracted from the applications and six machine learning algorithms are used to classify these into malicious and benign. Further, the malicious Android applications are classified into their families using the same machine learning algorithms. It is concluded that the accuracy of classification of malicious applications into the families gives very less accuracy (86.70% achieved by Random Forest) as compared to the binary classification accuracy (96.50% achieved by Random Forest).
Keywords: Android malware; Binary classification; Deep learning; Machine learning; Multiclass classification; Static features.
Special Issue on: AICAI 2019 Optimisation, Decision Making and Artificial Intelligence
Modeling and measuring attributes influencing Agile implementation in an enterprise using structural equation modeling
by Abhishek Srivastava, P.K. Kapur, Deepti Mehrotra, Vijay Kumar
Abstract: Todays software applications deployed in an enterprise caters to the complex business processes, integrate various business units and address requirements of global customer base. Critical characteristics of success of Agile development has to be taken into account in order to make this process of software development a rewarding one. One of the great features of Agile is that the life cycle of the project is based on collaborative work for continuing repeatedly with respect to expected changes with the benefit of added flexibility as compared to earlier traditional approaches. In this paper, a significant perception is showcased for the adept to analyse and measure the specified Agile attributes using statistical analysis. A thorough analysis of sixteen attributes is done in order to find vital independent factors and measure them steer the maturity of Agile employment in a business. For this purpose, a framework has been suggested which accelerates the process. An observation of the association among sixteen attributes was done. With the help of Exploratory and Confirmatory Factor Analysis, a structural model was set up with affirmation using Structural Equation Modeling. We pinpointed important distinct attributes that affect other attributes and the all-around execution of Agile. These important attributes were measured and the maturity of Agile execution in a project was found with the help of Explanatory factor analysis. The sixteen attributes were categorized in four latent variables: Planning, Execution, Tools and Infrastructure and People. This was done using exploratory and Confirmatory Factor Analysis. Moreover, Structural Equation Modeling was done to deduce thirteen key independent attributes that have an impact on other attributes. For the purpose of measuring these key attributes, Structural equation modeling was implemented using AMOS and it was determined that three of the attributes were working below the threshold. By identifying this, the management team was able to take certain reparative actions and a new measurement showed upgraded reliability level of Agile Implementation.
Keywords: Agile; Continuous Delivery; Exploratory and Confirmatory Factor Analysis; Structural Equation Modeling; enterprise applications.
Testing Resource Allocation for software system with Multiple Versions
by Adarsh Anand, Subhrata Das, Ompal Singh, Vijay Kumar
Abstract: Up-gradation has become a mandatory feature for software firms. Companies have now got no time to perform software testing because of coming up of their up-graded products at a fast pace. But even then firms have to test their respective version independently to remove maximum possible number flaws within particular time limit or under testing budget. In the current paper, taking into consideration the aspect of multi up-gradation, different optimization problems are proposed wherein optimal allocation of testing resources to different versions is discussed. The proposed set of models is solved using dynamic programming approach and is supplemented with numerical illustrations.
Keywords: Software Reliability; Multi Versions; Resource Allocation; Dynamic Programming.
Anti-Social Behaviour Analysis using Random Forest and Word to Vector Approach
by Nidhi Chandra, Sunil Kumar Khatri, Subhranil Som
Abstract: Social Networking and microblogging applications provide active platforms for communications, sharing thoughts and ideas. Social platforms and numerous applications dealing with natural text or language, such as Sentiment Analysis and Machine Translation, an Automatic language model is a critical component for searching in the often prohibitively large hypothesis space. Processing natural text coming from varied social platforms possess many technical challenges such as processing messages written in slang, informal short messages, classifying messages into different labels and category based on the meaning. Maximum natural text processing and interpretation systems use n-gram language models, which can be simple and powerful most of the time. Random forest ensemble based classifier have the potential to generalize the unseen data as compared to n-gram language models .In this paper we present an approach to classify the natural language text using Random Forest classifier.
Keywords: Natural Language Processing; Random Forest; Ensemble Classifier; Anti-social Behaviour Analysis; Word to Vector.
Inventory Model for Decay Items with Safe Chemical Storage and Inflation using artificial bee colony algorithm
by Ajay Singh Yadav, Anupam Swami, Navin Ahlawat, Geethanjali Kher, Sachin Kumar
Abstract: A deterministic Safe Chemical Storage inventory model has been developed for the deterioration of items with increasing demand, with inflation effects on stocks using artificial bee colony algorithm. The Safe Chemical Storage has a fixed capacity of C units using artificial bee colony algorithm. Stock outs are allowed and partially deferred, and inventories are expected to deteriorate over time with a variable rate of deterioration using artificial bee colony algorithm. The inflation effect has also been taken into account for the different costs of the Safe Chemical Storage inventory system. The numerical example is also used to examine the behavior of the model using artificial bee colony algorithm. The cost minimization technique is used to obtain the terms of total cost and other parameters using artificial bee colony algorithm.
Keywords: Safe Chemical Storage; inflation; Shortages; ramp time demand; deterioration items; artificial bee colony algorithm.
Predicting sexual offenders using Exhaustive CHAID techniques on victims age
by Bhajneet Kaur, Laxmi Ahuja, Vinay Kumar
Abstract: Sexual offences can spoil the whole culture of the society. So, the identification of any sexual offender, on the basis of major and minor victims should be done separately. So that security measures could be implemented on the required places to prevent and control these issues. This research paper proposes the decision models to classify & predict the sexual offenders on the basis of major or minor victims using CHAID and Exhaustive CHAID algorithms. These models can help to take any kind of decision by police departments, sexual harassment cells, and law enforcement agencies to differentiate the sexual offenders of major or minor victims to take the action accordingly for the security purposes. As concluded through both the models, classification and prediction of the sexual offenders have been done on the basis of certain variables i.e. age, race, weight and height. Further comparison has been done between accuracy rate of two models, deployed by CHAID and Exhaustive CHAID techniques. To deploy the decision models, overall dataset has been divided into 70:30 (training data: test data) ratio. Using CHAID 70% of test data resulted with 79.8% accuracy rate whereas model has been validated through 30% of test data that resulted with 79.1% rate of accuracy. Decision model using Exhaustive CHAID has been resulted with 79.9% accuracy rate through 70% of test data and model validated through 30% of remaining data with 78.8% accuracy rate of prediction.
Keywords: Sexual offenders; minor victim; major victim; Decision tree; Index values; Gain chart; response chart; machine learning; CHAID; SPSS; Exhaustive CHAID.