Search results

This paper proposes a decision-making framework for assessing various dimensions and barriers that have affected the admission process in management educational institutions during the ongoing pandemic. The framework considers the interrelationship between the obstacles and highlights the importance of each barrier.

An integrated method based on decision-making trial and evaluation laboratory and analytical network process is proposed to structure the barrier assessment framework. Results obtained from the study are validated by comparing them against the conventional analytical hierarchy process.

The results obtained from this study indicate four significant dimensions that hinder admission in Indian management institutes, namely, governmental, financial, sectoral, institutional and market. The top five barriers are demand shift towards technical (alternative) skills, acceptance of the graduated students, lack of industry–institute collaboration, lack of long-term vision and opening new Indian Institute of Technologies (IITs) and Indian Institute of Managements (IIMs).

During this ongoing pandemic, many educational institutes have been forced to shift from the traditional classroom to a virtual teaching model. In this regard, this study helps identify and assess the barriers to admission in Indian management institutes during this epidemic and thus, contribute to the literature. The findings will assist all stakeholders and policymakers of management institutions design and develop appropriate managerial strategies. The study is conducted in the Indian management educational institute context and can be extended to technical education institutions for deeper insights.

The paper develops an assessment framework for analysing the barriers to admission in Indian management institutes during the ongoing COVID-19 pandemic. Research implications are discussed in the context of a developing country.

An amalgamation of Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytical Network Process (ANP) has been performed to develop a decision-making framework for improving the overall performance of the microfinance institutions. A primary survey was conducted to collect real-time data from the heterogeneous stakeholders of microfinance institutions across India. The validation of the proposed framework is performed by comparing the results against the conventional method of Analytical Hierarchy Process (AHP).

This study identifies various dimensions and indicators for measuring the performance of Indian microfinance institutions. Additionally, the ranking and prioritisation of the performance dimensions and indicators is obtained by considering the mutual interrelation between them.

The study indicates that there exists a significant dyadic relationship between financial performance and social performance for improving the overall performance of the microfinance institutions. Governance is found to unidirectionally influence both financial and social performance. Among all the considered dimensions, financial performance of a microfinance institution is the most critical dimension for improving the overall performance. The top five performance indicators of the Indian microfinance institutions are funding source, borrowing and overhead cost, size of the firm, end-use of the money and depth of outreach.

The study was conducted in the context of Indian microfinance institutions; hence the scope of generalisation of the results is limited. This research considers both subjective and objective aspect of the performance dimensions and indicators from the perspective of multiple stakeholders (i.e. firm, society and regulator). The integrated framework is expected to aid in improving overall performance of microfinance institutions by focusing on the most critical (high prioritised) performance indicators.

An integrated DEMATEL-ANP framework is used in the domain of microfinance to assess the performance dimensions. This study is unique in terms of analysing performance of microfinance institutions from the perspective of heterogeneous stakeholders.

The purpose of this research is to identify and analyse the perceived risk factors affecting the safety of electric two-wheeler (E2W) riders in urban areas. Given the exponential growth of the global E2W market and the notable challenges offered by E2W vehicles as compared to electric cars, the study aims to propose a managerial framework, to increase the penetration of E2W in the emerging market, as a reliable, and sustainable mobility alternative.

The perceived risk factors of riding E2Ws are relatively scanty, especially in the context of emerging economies. A mixed-method research design is adopted to achieve the research objectives. Four expert groups are interviewed to identify crucial safety risk E2W factors. The grey-Delphi technique is used to confirm the applicability of the extracted risk factors in the Indian context. Next, the Grey-Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is employed to reveal the causal-prominence relationship among the perceived risk factors. The dominance and prominence scores are used to perform Cause and Effect analysis and estimate the triggering risk factors.

The finding of the study suggests that reckless adventurism, adverse road conditions, individual characteristics and distraction caused by using mobile phones, as the topmost triggering risk factors that impact the safety of E2Ws drivers. Similarly, reliability on battery performance low velocity and heavy traffic conditions are found to be some of the critical safety factors.

E2Ws are anticipated to represent the future of sustainable mobility in emerging nations. While they provide convenient and quick transportation for daily urban commutes, certain risk factors are contributing to increased accident rates. This research analyses these risk factors to offer a comprehensive view of driver and rider safety. Unlike conventional measures, it considers subjective quality and reliability parameters, such as battery performance and reckless adventurism. Identifying the most significant causal risk factors helps policymakers focus on the most prominent issues, thereby enhancing the adoption of E2Ws in emerging markets.

We have proposed an integrated framework that uses grey theory with Delphi and DEMATEL to analyse the safety risk factors of driving E2W vehicles considering the uncertainty. In addition, the amalgamation of Delphi and DEMATEL helps not only to identify the pertinent safety risk factors, but also bifurcate them into cause-and-effect groups considering the mutual relationship between them. The framework will enable practitioners and policymakers to design preventive strategies to minimize risk and boost the penetration of E2Ws in an emerging country, like India.

The purpose of this paper is to develop a decision support system (DSS) to assist supply chain (SC) risk managers to select a suitable risk management (RM) strategy and expedite the implementation of corresponding RM enablers. The relationship between RM strategies and RM enablers is explored by identifying the underlying factors between them, which is further used to build the DSS.

The DSS is built by integrating heterogeneous techniques. A systematic review approach is employed to explore both proactive and reactive RM enablers, and they are further mapped to various RM strategies by using correspondence analysis (CA). An in-depth interview is conducted to develop the rules for constructing the decision system. A rule-based fuzzy inference system (FIS) is utilized to counteract the uncertainty involved in the decision variables. The efficacy of the proposed DSS is demonstrated by considering two conjectural scenarios in the case of Indian petroleum SC (IPSC).

The results reveal three primary underlying factors between the risk mitigation strategies viz. SC managers' preparedness to face risk, organization's resource capability to deal with risk and the sophistication of the implementation of the RM enablers; with explained variances of 37%, 29% and 22%, respectively. Risk avoidance strategy comprises of RM enablers such as supplier evaluation, technology adaption, information security, etc. Whereas, the risk-sharing strategy includes revenue sharing, insurance, collaboration, public-private-partnership, etc. as essential RM enablers. The DSS recommends risk-mitigation and risk-sharing as effective RM strategies for the IPSC under the considered scenarios.

This paper develops a decision support framework for recommending an effective risk mitigation strategy and outranking the corresponding enablers. The study explicitly focuses on the risk mitigation step of the supply chain risk management (SCRM) process. Pre- and post-risk mitigation steps of the SCRM process, such as risk assessment and risk monitoring are beyond the scope of this research.

The operational procedure of the proposed DSS is explained by considering a real-life case of petroleum SC in the Indian scenario. The unique contributions of this study are presented as theoretical implications and managerial propositions in the context of a developing country.

In the recent post-pandemic era, the globe has been anxious for the sustainable disposal of healthcare waste to protect public health, protect the environment and enhance future preparedness. Developing countries, in particular, have struggled to dispose of healthcare waste (HCW) to eradicate the hazardous effects of medical waste generated during and after the deadly COVID-19 pandemic. Hence the purpose of the research paper is to develop a hybrid decision-making framework to identify various barriers for sustainable disposal of healthcare waste use of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP).

A hybrid framework of Grey-Decision Making Trial and Evaluation Laboratory (G-DEMATEL) and Analytical Network Process (ANP) has been used to rank barriers and sub-barriers in the disposal of healthcare waste.

The study’s findings suggest that lack of segregation practices, absence of green procurement policy, obsolete technologies and resistance to adopting change management are the topmost causal barriers influencing the remaining barriers. Lack of commitment among healthcare administrations, lack of standard performance measures and resistance to adopting change appear to be the topmost crucial barriers.

The study’s finding enables all stakeholders to prioritize the barriers systematically for better performance and save resources during the process. The policymakers can use the results to design a clear regulatory framework.

The literature has highlighted the factors and their association with the disposal of healthcare waste mainly in isolation. The results are validated against the Grey-Analytical Hierarchy Process (G-AHP) to ensure the robustness of the proposed framework. This paper is one of the preliminary attempts to propose a framework of the interrelationships of the factors that have a direct role in survival for management education.

The purpose of this paper is to explore the relationship between various risk management strategies and risk management practices in order to design and hence enact a suitable supply chain risk mitigation (RM) plan. Additionally, this study proposes a hierarchical framework to explain the mutual relationship between supply chain risk management (SCRM) practices and strategies by considering the underlying dimensions between them.

An amalgamation of systematic literature analysis (SLA) and correspondence analysis (CA) has been performed to develop the conceptual framework. A real-life case of Indian petroleum supply chain has been considered to validate and explain the proposed model.

The results reveal three underlying dimensions, which associate the relationship between RM strategies. They are, risk adaptability of SC managers with a variance of 34.71%, followed by resource capability of the firm and the degree of sophistication of RM practices, with variances of 27.72 and 20.35%, respectively. Risk avoidance strategy comprises of practices such as supplier evaluation, technology adaption, flexible process and information security. On the other extreme, the risk sharing strategy includes revenue sharing, insurance, collaboration, public–private partnership and so on as essential RM practices.

The study not only focuses on the distinction between RM strategies and practices, which were used interchangeably in the prior literature, but also provides an association between the same by exploring the underlying dimensions. These underlying dimensions perform a crucial role while developing a risk management plan. This study explicitly focuses on the RM step of SCRM process. Pre and post risk mitigation phases of SCRM process, such as risk assessment and risk monitoring, are beyond the scope of the current research.

The paper develops a framework for mapping various RM strategies with their corresponding practices by considering the Indian petroleum supply chain as a viable case study. Various theoretical and business implications are derived in the context of the developing country.

The purpose of this study is to identify, analyse and model the post-processing barriers of 3D-printed medical models (3DPMM) printed by fused deposition modelling to overcome these barriers for improved operational efficiency in the Indian context.

The methodology used interpretive structural modelling (ISM), cross-impact matrix multiplication applied to classification (MICMAC) analysis and decision-making trial and evaluation laboratory (DEMATEL) to understand the hierarchical and contextual relations among the barriers of the post-processing.

A total of 11 post-processing barriers were identified in this study using ISM, literature review and experts’ input. The MICMAC analysis identified support material removal, surface finishing, cleaning, inspection and issues with quality consistency as significant driving barriers for post-processing. MICMAC also identified linkage barriers as well as dependent barriers. The ISM digraph model was developed using a final reachability matrix, which would help practitioners specifically tackle post-processing barriers. Further, the DEMATEL method allows practitioners to emphasize the causal effects of post-processing barriers and guides them in overcoming these barriers.

There may have been a few post-processing barriers that were overlooked by the Indian experts, which might have been important for other country’s perspective.

The presented ISM model and DEMATEL provide directions for operation managers in planning operational strategies for overcoming post-processing issues in the medical 3D-printing industry. Also, managers may formulate operational strategies based on the driving and dependence power of post-processing barriers as well as the causal effects relationships of the barriers.

This study contributes to identifying, analyzing and modelling the post-processing barriers of 3DPMM through a combined ISM and DEMATEL methodology, which has not yet been reviewed. This study also contributes to decision makers developing suitable strategies to overcome the post-processing barriers for improved operational efficiency.

Despite IoT’s huge potential, enterprises’ ability to leverage it is their competitive advantage. Thus, competitive differentiation is primarily predicated on leveraging IoT toward customer needs. To examine the research gap, this study aims to explore the drivers of customer satisfaction and how they are affected by the interaction between IoT capabilities.

A mixed-method research framework is applied to assess the impact of IoT capabilities on customer satisfaction. Based on the theoretical underpinning of the resource-based view and dynamic capability, the study highlights the importance of IoT capabilities in active resource allocation and effective resource utilization. First, DEMATEL is used capture the interrelationship between IoT capabilities. Further, the impact of each IoT capabilities on customer satisfaction is studied using CoCoSo method.

The study highlights the importance of IoT capabilities in active resource allocation and effective resource utilization. The findings are enriched through the complementarity of resources in a dynamic business-to-business-to-customer (B2B2C) scenario. The authors expand the IoT capabilities from conventional business-to-business (B2B) or business-to-customer (B2C) scenario to tri-nodal B2B2C relationship triangle.

Based on the findings, the authors offer a business transformation strategy for firms in key areas of customer satisfaction by leveraging IoT. The study can help management prioritize and develop key IoT capabilities to meaningfully increase customer satisfaction metrics.

Building on the dynamic capabilities and resource-based view of the firm, an integrated decision-making research model is proposed. In addition, this study investigates the product and service capabilities unlocked using IoT capabilities. This work can be considered one of the leading attempts to improve customer satisfaction using IoT capabilities from traditional dyadic (B2B or B2C) structure to triadic (B2B2C) framework.

The purpose of this paper is to identify various risk and sub-risk drivers that affect the supply chain (SC) performance and to propose a framework to quantify the overall SC risk index by considering the importance of each risk and sub-risk drivers and their mutual interactions.

A hybrid method based on decision-making trial and evaluation laboratory and analytical network process has been proposed to develop the risk quantification framework. A case study of Indian petroleum supply chain (PSC) has been illustrated to explain the proposed method.

The results of this study found that transportation/logistics (delivery system), quality of the petroleum products, crude supply, customer’s order and legal/political regulations are the most significant risk drivers of a typical PSC. It is also found that the Indian PSC possesses a risk score of 34 percent.

The quantification of risk in operational measure provides an unblemished representation of the overall SC risk. Unlike the existing financial measure, it takes complex subjective operational effectiveness like product quality, customer satisfaction, etc., into consideration. Identifying the high-prioritized risks helps the decision and policy makers to merely focus on the most prominent risk drivers, and reduce the impact of overall SC risk. Planning a risk mitigation strategy at a given level of risk is however beyond the scope of this research.

The paper develops a risk quantification framework in the context of a PSC.

The purpose of this paper is to present a framework for identifying various inbound supply-risk factors and analyzing its indicators considering the contextual relationship between them. This study additionally proposes a framework for developing an overall inbound supply-risk score considering a real-life case of the electronics supply chain (ESC) in the Indian context.

In total, 32 risk indicators are identified by a systematic literature review approach and are validated by supply chain practitioners/experts and further categorized into six main risk factors. A hybrid multi-criteria decision-making-based DANP (DEMATEL and ANP) framework is employed to develop the overall inbound-supply-risk score (ISRS) and to prioritize the risk indicators. Indian ESC is chosen as a viable case study to demonstrate the effectiveness of the proposed framework.

The outcomes from the study reveal that the overall ISRS in the ESC is 36 percent and additionally forewarns critical inbound-supply-risk factors such as supplier performance, product, and buyer organization. Further, the study also identifies the most significant risk indicators such as price margin, investment, on-time delivery, order fulfillment and design changes for ESC.

Supply chain practitioners can adopt this framework as a useful inbound supply-risk assessment tool. Moreover, the hybrid framework will address subjectivity and interrelations among various factors through experts’ judgments. The results will assist the managers to have better insights on the critical risk factors and their complicated interrelationships and further strategize action plans to nullify the impact of incoming risks. This study mainly focused on risk identification and assessment of electronics inbound-supply-risk indicators in the Indian context. The framework can be used for other manufacturing and service industries, albeit the results derived are in the context of a developing country.

This paper provides an effective risk assessment framework for the supply chain practitioners/managers to develop a decision-support system for inbound-supply-risk quantification and prioritization of risk factors in the context of the ESC.