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The purpose of this paper is to empirically examine how different supply chain attributes as determinants of the openness of supply chain affect organizational performance (OP).

Data were collected from 259 supply chain executives in Pakistan. Structural equation modeling was used to test the hypotheses.

The findings indicate that organizations may take the selective view of their supply chains resulting in a varying focus on different SC attributes. The results show that though all identified supply chain attributes positively relate to OP, some attributes such as combined agility and cooperation among supply chain partners have a weak correlation coefficient. This indicates that overall the relative openness of supply chain among selected sample of Pakistani organizations is low.

Supply chain executives may not have a selective focus on some attributes; rather, they may consider to have a broader perspective drawing upon a wider range of supply chain attributes as identified in the current study. In order to remain competitive, Pakistani manufacturing organizations need to learn more about opening up their boundaries and enhance the openness of their supply chain.

The contribution of the current study is two folds. First, drawing upon the current literature, it proposes the instrument to measure the relative openness of supply chain. Second, it empirically tests the selected conceptual model which highlights the relevance of supply chain attributes and their role in the resulting relative degree of supply chain openness. The empirical examination of the selected conceptual model of supply chain openness tends to make contribution to the wider literature on supply chain management.

E-commerce companies use different types of dark patterns to manipulate choices and earn higher revenues. This study aims to evaluate and prioritize dark patterns used by e-commerce companies to determine which dark patterns are the most profitable and risky.

The analytic hierarchy process (AHP) prioritizes the observed categories of dark patterns based on the literature. Several corporate and academic specialists were consulted to create a comparison matrix to assess the elements of the detected dark pattern types.

Economic indicators are the most significant aspect of every business. Consequently, many companies use manipulative methods such as dark patterns to boost their revenue. The study revealed that the revenue generated by the types of dark patterns varies greatly. It was found that exigency, social proof, forced action and sneaking generate the highest revenues, whereas obstruction and misdirection create only marginal revenues for an e-commerce company.

The limitation of the AHP study is that the rating scale used in the analysis is conceptual. Consequentially, pairwise comparisons may induce bias in the results.

This paper suggests methodical and operational techniques to choose the priority of dark patterns to drive profits with minimum tradeoffs. The dark pattern ranking technique might be carried out by companies once a year to understand the implications of any new dark patterns used.

The advantages of understanding the trade-offs of implementing dark patterns are massive. E-commerce companies can optimize their spent time and resources by implementing the most beneficial dark patterns and avoiding the ones that drive marginal profits and annoy consumers.

This paper aims to investigate the usage pattern of electronic resources (e-resources) among management graduates. The respondents were asked about the types of e-resources they used, who their influencers were, their preferred place for surfing, the frequency of use, purpose for which they used e-resources, its benefits and the problems they faced while using e-resources. The findings of the study will help in enhancing the usage of e-resources among students who opt for management courses.

This descriptive research was conducted in Nagpur, Maharashtra (India). Data collected from 150 management students through purposive sampling were analyzed through descriptive statistics, and the responses were presented in tabular form.

The investigation reveals that students are well aware of e-resources and consider them to be very useful for their academic performance. Interestingly, students are found to be using non-paid resources more than paid ones because of a lack of search skills. Discipline-wise investigation reveals that students from the disciplines of information technology, economics and finance use e-resources more frequently than those studying subjects like marketing, operations and human resource management. Faculty and training have emerged as strong influencers that have persuaded students to use e-resources.

The present study is limited to students studying management courses in Nagpur, Maharashtra (India).

This research will help institutions, librarians and publishers in gaining insight on the utilization patterns of e-resources. The uniqueness of this study lies in the fact that it has analyzed and presented the responses of management students belonging to different disciplines in management studies such as, marketing, finance, human resource management operations, economics and information technology regarding their usage patterns of e-resources.

The purpose of this paper is to understand the scholarly contributions to the field of marketing by analyzing top ten journals of marketing.

The marketing journals were selected using SciMago marketing journal list, and SCOPUS database was used to identify the publications of the journals. A total of 9,190 articles were analyzed having 562,322 citation references. Methodologies like Wordle and Gephi were used to understand the most researched keywords and co-citation analysis among top five researchers. This paper also captured the information on most cited article along with author, most published author, most publishing country, most publishing university, the year with maximum publications and most used keywords.

The analysis indicates that “Kumar, V.” is most published author, that is, 68 publications, the most cited article is “On the evaluation of structural equation models” by Bagozzi and Yi (1988) with 6989 citations. The USA contributed the highest 6,720 publications, while University of Pennsylvania, Wharton School topped the list with 235 articles. In 2009, highest publication work was done by publishing 382 articles. “Game theory”, “Pricing” and “Advertising” are most used keywords which have been discussed in the literature.

This analysis will help researchers in understanding the growth in the field of the marketing in recent years and possible direction it could take in future. However, this paper considered only top ten marketing journals as listed in SciMago marketing journal list; therefore, future researchers may incorporate more research journals to get a clearer picture of the field of marketing.

This paper is one of the first attempts in recent time to understand the research work in the field of marketing considering top ten journals.

The purpose of this paper is to understand the integrated impact of the application of protection measures against identity theft on consumers’ synergistic perception of trust, the cost of products/services and operational performance (OP) – all of which in turn is postulated to contribute to purchase intention (PI) when shopping online.

In order to accomplish the specified aim, this study first conducted an experiment by involving the students from a university in Bangladesh. Then a survey was conducted to capture their opinion based on the previous experiment.

The study identified that in e-commerce, OP and trust have potential impact on pursuing consumers’ PI. Traditionally, price is always an issue in marketing; however, for e-commerce, this issue does not have direct impact on PI.

The main limitation of this study is that a less established e-commerce example was utilized to conduct the experiment and survey for validating the model. Also, the study was conducted only in the context of Bangladesh and a student sample was utilized. Future studies can test the model in different contexts (particularly to verify the impact of privacy) by utilizing data from consumers.

This study has resolved a controversial issue by generating clear guidelines that the overall conjoint effect of OP, trust, and price on PI is neither negative nor neutral. Synergistically, the application of these controlling tools of identity theft can substantially enhance consumers’ trust, which is the single most predictor to pursue consumer PI.

This study has provided in-depth insight into the impact of different controlling measures in e-commerce PI. Practitioners have potential learning from this study that if consumers find the application of different controlling mechanisms against cybercrimes, particularly identity theft, enhancing the reliability, authenticity and security of transactions in this virtual medium, they do not mind paying a higher price. Such insights have not been provided by existing studies on this topic. Developing trust on e-commerce purchase is the driving force, not the price.

The purpose of this paper is to identify the criticality of various sub-systems through the behavioral study of a multi-state repairable system with hot redundancy. The availability of the system is optimized to evaluate the optimum combinations of failure and repair rate parameters for various sub-systems.

The behavioral study of the system is conducted through the stochastic model under probabilistic approach, i.e., Markov process. The first-order differential equations associated with the stochastic model are derived with the use of mnemonic rule assuming that the failure and repair rate parameters of all the sub-systems are constant and exponentially distributed. These differential equations are further solved recursively using the normalizing condition to obtain the long-run availability of the system. A particle swarm optimization (PSO) algorithm for evaluating the optimum availability of the system and supporting computational results are presented.

The maintenance priorities for various sub-systems can easily be set up, as it is clearly identified in the behavioral analysis that the sub-system (A) is the most critical component which highly influences the system availability as compared to other sub-systems. The PSO technique modifies input failure and repair rate parameters for each sub-system and evaluates the optimum availability of the system.

A bottom case manufacturing system is under the evaluation, which is the main component of front shock absorber in two-wheelers. The input failure and repair rate parameters were parameterized from the information provided by the plant personnel. The finding of the paper provides the various availability measures and shows the grate congruence with the system behavior.

The purpose of this paper is to optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm optimization (BFO-PSO) evolutionary algorithm. For this, a performance model is developed with an objective to analyze the system availability.

In this paper, a Markov process-based performance model is put forward for system availability estimation. The differential equations associated with the performance model are developed assuming that the failure and repair rate parameters of each sub-system are constant and follow the exponential distribution. The long-run availability expression for the system has been derived using normalizing condition. This mathematical framework is utilized for developing an optimization model in MATLAB 15 and solved through BFO-PSO and basic particle swarm optimization (PSO) evolutionary algorithms coded in the light of applicability. In this analysis, the optimal input parameters are determined for better system performance.

In the present study, the sensitivity analysis for various sub-systems is carried out in a more consistent manner in terms of the effect on system availability. The optimal failure and repair rate parameters are obtained by solving the performance optimization model through the proposed hybrid BFO-PSO algorithm and hence improved system availability. Further, the results obtained through the proposed evolutionary algorithm are compared with the PSO findings in order to verify the solution. It can be clearly observed from the obtained results that the hybrid BFO-PSO algorithm modifies the solution more precisely and consistently.

There is no limitation for implementation of proposed methodology in complex systems, and it can, therefore, be used to analyze the behavior of the other repairable systems in higher sensitivity zone.

The performance model of the paint manufacturing system is formulated by utilizing the available uncertain data of the used manufacturing unit. Using these data information, which affects the performance of the system are parameterized in the input failure and repair rate parameters for each sub-system. Further, these parameters are varied to find the sensitivity of a sub-system for system availability among the various sub-systems in order to predict the repair priorities for different sub-systems. The findings of the present study show their correspondence with the system experience and highlight the various availability measures for the system analyst in maintenance planning.

Marketing, Retail Marketing and E-commerce.

Graduate and Post-graduate.

The Future Group is the most profitable retailer in India without having any foreign direct investment (FDI). In September 2013, the retailer launched its online retailing platform, “Big Bazaar Direct” (BBD). BBD is a franchisee-based model which aims to partner with people having rich customer networks to reach more shoppers. This novice idea of BBD is the result of Big Bazaar’s greater mind share over its market share. Mr Kishore Biyani, CEO Future Group, has lot of expectation from this business model.

The outcomes include: to familiarize students with Indian Retail Industry; to develop student’s skills in critically analyzing an online retail-based new business model; and to explain key factors that work for success of a retail-based business model.

Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 8: Marketing

The purpose of this paper is to study corporate social responsibility (CSR) enablers, with special reference to Indian firms. Further, the CSR enablers have been identified and their ranking obtained, and interactions and interrelationships among the different enablers have also been studied.

The interpretive structural modeling (ISM) approach was used to evaluate the interactions among the various enablers of CSR implementation, from the perspective of Indian companies.

In the course of this paper, based on a detailed literature review, nine enablers were identified and after seeking expert opinion, eight CSR implementation enablers were shortlisted. The present study has identified that top management commitment, organizational culture and formal strategic planning are the main enablers of CSR implementation in Indian companies, whereas corporate reputation, better financial performance and customer satisfaction are the dependent enablers that have high dependence power but weak driving power.

The ISM-based model of CSR enablers presented in this paper will prove to be of interest to academicians and practitioners alike. While academicians will gain a better understanding of enablers of CSR implementation from the perspective of one of the fastest growing economies of the world, practitioners will gain a better understanding of CSR enablers, and their enhanced knowledge will help them to effectively implement CSR in their organizations.

The purpose of this paper is to identify the critical challenges in the implementation of cloud enterprise resource planning (ERP). The challenges identified were customization, organizational change, long-term costs, business complexity, loss of information technology competencies, legal issues, integration, data extraction, monitoring, migration, security, network dependency, limited functionality, awareness, performance, integrity of provider, perception, and subscription costs. Here the small and medium enterprises (SMEs) and large organizations were differentiated with respect to the challenges identified. This paper also suggested ranked lists of challenges both for SMEs and large organizations.

An online survey was conducted and data of 93 respondents were analyzed. Exploratory factor analysis and one-way analysis of variance (ANOVA) was used to statistically test the data. Here the SMEs and large organizations were differentiated with respect to the challenges identified.

This study shows that SMEs and large organizations differ from each other for most of the challenges except business complexity, integration, monitoring, security, limited functionality, performance, and integrity of provider. Also from the ranked list of challenges in cloud ERP, security was the top concern for both SMEs and large organizations.

The findings may help organizations to get a broad idea about the challenges which are critical for the implementation of cloud ERP.