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The case depicts an opportunity for undergraduate and postgraduate students to be exposed to the basic digitization of supply chain management, technology adoption, change management and cost-benefit analysis concepts. The study aims to encourage them to use the data given in the case and exhibits to compare and contrast physical and digital supply chains (SC); design the digitized version of the traditional SC; examine the nitty-gritty of technology adoption in the SC context; develop the change management plans for the successful adoption and implementation of SC digitization; design the risk register and Explore the business process management; and conduct the return on investment analysis.

Amber Yen, Chief Operating Officer Apparel Sourcing at Ransys Partners Ltd (RSL), was presented with the task of reducing physical sample production cost and time without impeding order pipeline. RSL was experiencing significant capacity constrain during the COVID-19 crisis, failing to deliver physical samples to international brands. To win large export orders, RSL had to adopt a new innovative way to reduce the sample approval process while meeting customer requirements. Ms Yen wanted to convert the entire sample approval process into a digital mode. She was facing multiple challenges related to the design, implementation and adoption of the digital sample approval process to coordinate the entire SC. She had limited time and was grappling with other impending constraints such as increasing cost, intense competition, demanding customers, shortage of labor due to COVID-19, reducing the bottom line. It was her time to test the idiom “necessity is the mother of innovation”.

The target audience for this case is management or business school students. This case can be used to teach digitization of SC, operations management, organization behavior, digitization of enterprises, IT for business, new service development, supplier management technology adoption, and change management in management or business schools.

Teaching notes are available for educators only.

CSS 9: Operations and Logistics.

The purpose of this paper is to investigate the complex interrelationships among the key constructs, supply chain orientation (SCO), supply chain integration (SCI) and supply chain performance (SCP) in Indian manufacturing industries. These relationships have been studied using the relational view (RV) and the knowledge-based view (KBV) theoretical perspectives.

The conceptual model was derived from the existing body of knowledge in the supply chain domain. The study is based on a sample size of 122 data collected via face-to-face meetings with the Indian manufacturers using well-established scales. The covariance-based structural equation modeling was used to test the proposed hypotheses.

In Indian manufacturing and supply chains, SCO has a positive relationship with SCI and SCP. Moreover, the direct impact of SCO on SCP diminishes when SCI is used as a mediating variable. This study also observes positive impact of: i) SCO on SCP, ii) SCI on SCP and iii) discovery of mediating role of SCI on SCP under the theoretical lenses of RV and KBV.

Cross-sectional survey of manufacturing firms of one country (using one response per firm) calls for validation covering other parts of the world and demands a longitudinal survey. This research will trigger more scholarly, practice and policy debate among researchers studying Indian and emerging economies context.

The notion of a holistic view of the SC with a focus on improving the customer value can enhance strategic partnerships among the SC partners (i.e. SCI) and overall SCP. Firms should make efforts to include SCI in SC designs to successfully transform SCO into SCP.

The originality of the research lies in studying the complex interrelationships among key concepts of SC in a unique Indian manufacturing context. The Indian supply chains operate in a set of unique characteristics, which have been detailed out in this paper. This paper not only establishes the mediating role of SCI for overall SCP in emerging economies but also enhances the scholarly knowledge in the SC domain. Most studies report SCO as a single-order construct, measured by scales comprising of only few items. The second-order SCO measures in this study bring credibility to the findings. Additionally, it contributes to both academicians and practitioners alike in the context of an integrated SC in emerging economies.

The purpose of this research is to address the challenges of selecting optimal drones for disaster response operations under uncertainties. Traditional static (deterministic) models often fail to capture the complexities and uncertainties of disaster scenarios. This study aims to develop a more resilient and adaptable decision-making framework by integrating the best-worst method (BWM) with stratified multi-criteria decision-making (SMCDM), focusing on various uncertainty scenarios such as weather conditions, communication challenges and navigation and control issues.

The methodology involves identifying seven essential criteria for drone evaluation, guided by contingency theory. The BWM derives optimal weights for each criterion by comparing the best and worst alternatives. The SMCDM incorporates different uncertainty scenarios into the decision-making process. Sensitivity analysis assesses the robustness of decisions under various criterion weightings and operational scenarios. This integrated approach is demonstrated through a practical application to the Kerala flood scenario.

The integrated stratified BWM method proves to be highly effective in adapting to different uncertainty scenarios, enabling decision-makers to consistently identify the optimal drone for disaster response. The method’s ability to account for uncertain conditions such as weather, communication challenges and navigation issues ensures that the optimal drone is selected based on the situation at hand.

The methodology fills critical gaps in the literature by offering a comprehensive model that incorporates various scenarios and criteria for optimal drone selection. However, there are certain limitations. The reliance on expert opinions for criterion weightings introduces subjectivity, potentially affecting the generalizability of the results. In addition, the study’s focus on a single case, the Kerala floods, limits its applicability to other geographic contexts. Integrating real-time data analytics into the decision-making process could also enhance the model’s adaptability to evolving conditions and improve its practical relevance.

This research offers a practical, adaptable framework for selecting optimal drones in disaster scenarios. By integrating BWM with SMCDM, the methodology ensures decision-makers can account for real-time uncertainties, such as weather or communication disruptions, to make more informed choices. This leads to better resource allocation and more efficient disaster response operations, ultimately enhancing the speed and effectiveness of relief efforts in various contexts. The method’s ability to adjust based on scenario-specific factors ensures that drones are optimally deployed according to the unique demands of each disaster.

By incorporating SMCDM, the proposed methodology assists decision-makers in appropriately choosing drones based on their characteristics crucial for specific scenarios, thereby enhancing the efficiency and effectiveness of relief operations.

This study presents a unique integration of the BWM with SMCDM, creating a dynamic framework for drone selection that addresses the challenges posed by uncertain disaster environments. Unlike traditional methods, this approach allows decision-makers to adjust criteria based on evolving disaster conditions, resulting in more reliable and responsive drone deployment. The method bridges the gap in existing literature by offering a comprehensive tool for disaster response, providing new insights and practical applications for optimizing drone operations in complex, real-world scenarios.

The case depicts an opportunity for students to be exposed to the decision theory concept. The study aims to encourage them to use the data given in the case and exhibits to explore as follows: decision-making under uncertainty; decision-making under risk; compare and contrast uncertainty and risk; and evaluate the value of perfect information EVPI and understand its application in decision-making.

Vikas Teerth, a budding entrepreneur, wanted to venture out into the pineapple business. He had three land plots available, but he would like to take up a single plot after analyzing the possible returns factoring the volatile prices and other impending constraints. He wanted to use the decision-making approaches with the aid of probability to arrive at the best decision. This case helps the instructors to introduce the concept of decision-making under risk and under uncertainty which comes under the preview of decision theory. Students can use the data given in the case and exhibits to do the necessary calculations required and thereby get an insight into the process of calculated decision-making.

This case can teach decision theory in undergraduate-level and graduate-level courses in operations research, decision-making and industrial engineering. It can also be used to discuss issues and challenges faced in start-ups or SME entrepreneurship.

Teaching notes are available for educators only.

CSS 7: Management Science.

The purpose of this paper is to examine the state of readiness of the Indian retailing sector for the implementation of mobile retailing applications. It also identifies the most critical success factors (CSFs) for mobile retailing implementation through retailing process reengineering (RPR) framework.

This paper attempts to identify a few CSFs through questionnaire survey and interview, subsequently establishing the inter-factor relationships through interpretive structural modeling framework and computing the priority weights of the interrelated factors using analytic network process. Finally, the authors compute the retailers’ RPR implementation readiness indices for mobile retailing using Multi-Level data envelopment analysis methodology.

The 11 CSFs have been identified. Out of these, two factors namely Strategic Alignment and Management Control and Quality Contribute profoundly for mobile retailing implementation. Finally, a readiness index has been computed for implementation of mobile retailing in the selected retail outlets through RPR framework.

Only a few selected large retail outlets have been considered in this study and the sample size was modest. This study only revolves around the Indian retail sector.

This study can be used as a decision support system for mobile retailing implementation in Indian retail sector. Moreover, based on the results of this study, a few retail outlets are completely ready for mobile retailing implementation. Apart from them, the other retail outlets can improve their readiness index by emphasizing on performance scores of the CSFs.

Due to the scanty literature on mobile retailing, this study contributes to the mobile retailing body of literature in three ways: first, identification of CSFs in mobile retailing; second, interrelationship among the factors; and third, proposes a rational framework to compute retail outlets’ readiness indices for the implementation of mobile retailing through RPR framework.

The purpose of this paper is to investigate the analogy of the human immune system with the economic auction theory.

The paper develops an analogy of bio‐immune system with competitive bidding in auction, then develops a model of the situation and discusses its managerial implications.

The human immune system can be benchmarked to model decision making under competitive environment, such as biddings in auctions and obtains gainful insights.

Various engineering, management, social science, and defense and security‐related applications of the model are suggested.

The paper presents a novel and innovative model with tremendous potential for varied applications.

The purpose of this paper is to conduct empirical investigation of value co-creation phenomena in IT services outsourcing. This survey based research enabled to identify antecedents of value co-creation and their impact on value outcomes.

This empirical study identifies 25 drivers of value co-creation in IT outsourcing services. These drivers were identified from reported literature and by studying IT project reports. The data were collected from client and supplier organizations followed by verification of the drivers (using PCA and CFA methodologies) that contribute significantly to value co-creation in the IT services outsourcing domain. Furthermore, using SEM and linear regression, the authors have verified the strength of their relationships with value co-creation.

This research is subjected to exploratory factor analysis, which resulted in six antecedents of value co-creation in IT services outsourcing. These antecedents include alliance relationship, strategic intent, service actualization, intrapreneurship, collective capabilities, and resource management. The alliance relationship, strategic intent, service actualization, and intrapreneurship are found to be significant for value co-creation. While collective capabilities as a standalone was not significant, the relationship of collective capabilities to value co-creation has achieved significance under the influence of alliance relationship, strategic intent, and other antecedents – when tested and hypothesized through the SEM path model.

The research has the following limitations. The antecedents identified are contextual. The potential illustrative, but not exhaustive reasons, for the change of the context may be due to contract duration, age of the project, relationship maturity, expected value outcome from both the parties, etc. The drivers identified in this research are applicable only to IT services (IT and ITES outsourcing). They cannot be generalized to other B2B outsourcing relationship. The authors propose the conducting of separate research to identify the priorities of these antecedents for different types of outsourcing as well different types of value outcomes.

This study has added to the knowledge on value co-creation in IT services outsourcing relationships through empirical modeling. From the perspective practitioners of IT industry, this work brings rich information of what are the drivers to value co-creation and their significance on value outcomes in IT services outsourcing. It can provide guidelines to both clients and service providers of similar industry to assess their current practices for value co-creation and re-prioritize their activities and budgets based on the significance of value based benefits. Moreover, practitioners in the IT services industry can use these value drivers and understand the antecedents for value co-creation. As this work is from a dual perspective, both clients and suppliers can assess the applicability of these drivers and antecedents and adopt them to realize mutual value.

In the past, researchers have focussed on value after it was created and shared among the respective relationship partners, and very few emphasized the need for proactive identification of the antecedents of value co-creation. Researchers have emphasized on the need for an empirical approach, because most of the published studies are theoretical and conceptual in nature. Hence, the significant contribution of this empirical study is to validate the value co-creation drivers identified from literature and qualitative study (case studies) with IT industry practitioners (no. 256) across the globe and the relevance of antecedents to B2B IT services outsourcing body of knowledge.

This paper aims to implement a maiden methodology for load frequency control of an AC multi micro-grid (MG) by using hybrid fractional order fuzzy PID (FOFPID) controller and linear quadratic Gaussian (LQG).

The multi MG system considered is consisting of photovoltaic, wind turbine and a synchronous generator. Different energy storage devices i.e. battery energy storage system and flywheel energy storage system are also integrated to the system. The renewable energy sources suffer from uncertainty and fluctuation from their nominal values, which results in fluctuation of system frequency. Inspired by this difficulty in MG control, this research paper proposes a hybridized FOFPID and LQG controller under random and stochastic environments. Again to confer viability of proposed controller its performances are compared with PID, fuzzy PID and fuzzy PID-LQG controllers. A comparative study among all implemented techniques i.e. proposed multi-verse optimization (MVO) algorithm, particle swarm optimization and genetic algorithm has been done to justify the supremacy of MVO algorithm. To check the robustness of the controller sensitivity analysis is done.

The merged concept of fractional calculus and state feedback theory is found to be efficient. The designed controller is found to be capable of rejecting the effect of disturbances present in the system.

From the study, the authors observed that the proposed hybrid FOPID and LQG controller is robust hence, there is no need to reset the controller parameters with a large change in network parameters.