Showing papers by "Kannan Govindan published in 2022"

Financing equilibrium in a capital constrained supply Chain: The impact of credit rating

Abstract: In this study, we investigate a supply chain comprising one well-funded supplier and one small-sized retailer with capital constraints. The supplier acts as a leader to distribute one newsvendor-type product via the retailer in the uncertain market demand. In the presence of capital shortages, the retailer has two different financing alternatives: bank financing and trade credit. Moreover, the small-sized retailer has an imperfect credit rating, which reflects the exogenous credit risk beyond the current supply chain transaction. By capturing both the demand risk and credit risk, we model each financing strategy and derive the optimal solutions. When both financing strategies are feasible, we prove that the retailer always benefits from bank financing, while the supplier’s preferences are determined by two critical factors (i.e., the retailer’s credit rating and the production cost). Considering that the supplier’s preferences are not always aligned with the retailer’s, we characterize a wholesale price Pareto zone, in which trade credit is the unique equilibrium. We further generalize our model to consider that the retailer with a positive initial budget, finding that the feasible regions of two financing formats shrink as the initial budget builds up. Interestingly, when the initial capital of the retailer is moderate (still capital shortages), we observe that trade credit is more likely to be the financing equilibrium if the retailer’s credit rating is low. These findings enrich our understanding of the impact of credit rating on financially constrained supply chain operational and financial decisions.

Tunneling the barriers of blockchain technology in remanufacturing for achieving sustainable development goals: A circular manufacturing perspective

Abstract: As a concern with manufacturing industries, circular economy (CE) practices—often labeled “circular manufacturing (CM)”—are industrial tasks through which several circular economy principles have been integrated. Among these circular manufacturing strategies, “3R” (recycle, refurbish/remanufacture, and reuse/redistribute) is the key strategy that assists the manufacturing industry with closing the loop for sustainability. An effective inclusion and management of 3R lead a firm to a greater likelihood of successfully integrating CE and CM. In recent years, remanufacturing has gained greater prominence, especially with the emergence of technology, including cyber-physical systems. These technologies assist the remanufacturing firm with efficient take-back systems through tracking. However, data transferred through these technologies among value chain partners in remanufacturing are not reliable. Due to the lack of trust and transparency, value chain partners are hesitant to participate in remanufacturing supply chains. To address the limitation of technologies in remanufacturing, blockchain has been introduced to secure the data. Despite the advantages of blockchain technology, practitioners face difficulties in integrating these blockchain technologies into the remanufacturing context. Several earlier studies addressed the challenges of implementing blockchain, but no earlier studies have specifically examined remanufacturing industries, which are entirely different from forward supply chain industries. Concerning the fact, this study identifies the barriers that exist with the implementation of blockchain technology in the application of the remanufacturing sector. A framework has been proposed and validated in a Danish automotive parts remanufacturing company. Multi-criteria decision-making method has been used to identify the effective and most influential barriers among common barriers. Results reveal that “scaling of technology” (B6) is the key barrier of BCT implementation in remanufacturing context. This study concludes with useful discussions based on the results along with the recommendations to eradicate those influential barriers and their respective impacts on SDGs (SDG4, SDG8, SDG9, and SDG17). Finally, this study sheds light on future enhancements on the integration of blockchain technology in remanufacturing to reap several benefits of circular manufacturing.

Energy performance contracting in a supply chain with financially asymmetric manufacturers under carbon tax regulation for climate change mitigation

Abstract: Energy performance contracting is a turnkey service for an enterprise to achieve the goal of energy-saving or emission abatement. This study investigates the value of energy performance contracting in a two-echelon supply chain consisting of one supplier and two financially asymmetric manufacturers under carbon tax regulation for climate change mitigation. The supplier provides a trade credit for a financially weak manufacturer who engages in Cournot competition with a financially strong manufacturer. Furthermore, the supplier can act as an energy service company to offer energy performance contracting for the two manufacturers to achieve carbon tax savings. The impact of sharing ratio of energy performance contracting and coefficient of variable cost are analyzed to explore whether and which manufacturer should be chosen by the supplier to implement energy performance contracting. The results suggest that when the coefficient of variable cost is within a high range, the supplier will not provide energy performance contracting for any manufacturer. However, when the coefficient of variable cost and sharing ratio are not very high, the supplier prefers to provide energy performance contracting for the financially weak manufacturer. With the increasing of sharing ratio, the supplier changes the decision to select the financially strong one. Moreover, the model is extended to consider the impact of demand uncertainty and coefficient of investment cost. Furthermore, the result of numerical studies indicates that there exists a Pareto zone for the three supply chain members to achieve a multi-win situation, if the supplier provides the energy performance contracting for both the manufacturers.

Circular economy adoption barriers: An extended fuzzy best–worst method using fuzzy DEMATEL and Supermatrix structure

Abstract: In the real world, there are complex decision-making problems in which a variety of intertwined factors and hierarchical structures exist, and it is difficult or impossible to solve these problems using classical methods. The prioritization of circular economy (CE) adoption barriers is one such complex problem that cannot be solved using current classical methods. Hence, in this paper, for the first time, a new method, namely, FBWDS, is developed. FBWDS derives from the combination of fuzzy best–worst method (BWM), fuzzy decision-making trial and evaluation laboratory (DEMATEL), and Supermatrix structure. This proposed method establishes weights of the intertwined factors in hierarchical networks under uncertainty; these weighted factors and their interdependencies are calculated using the fuzzy BWM and fuzzy DEMATEL techniques, respectively. In addition, the Supermatrix structure is applied to integrate the results of these two techniques. The proposed approach efficiency is evaluated in the field of the CE adoption barriers using data from a cable and wire industry in Iran. The results showed that “high setup costs,” “financial limitations,” and “absence of public awareness about CE” rank as the most challenging barriers, and “lack of standards for designing recycled products” and “absence of standard system to evaluate performance” are the least important barriers to CE adoption in the cable and wire industry.

Manufacturer's selling mode choice in a platform-oriented dual channel supply chain

Abstract: This paper considers a platform-oriented dual channel supply chain (PDCSC), in which the online retailer resells products in a marketplace provided by the platform and the manufacturer chooses a selling mode to introduce a dual channel. Three possible selling modes for the manufacturer are considered: (1) Reselling mode (Mode R); (2) Agency selling mode (Mode A); and (3) Direct selling mode (Mode D). We examine the manufacturer’s equilibrium strategy and how this choice affects the other supply chain members’ preferences. By comparing equilibrium profits in the three selling modes, we demonstrate that the manufacturer prefers Mode D when the direct operating cost is relatively low. Otherwise, either Mode R or Mode A is optimal, largely depending on the interaction between competition intensity and commission rate. More specifically, if both the competition intensity and commission rate are low, Mode A is the optimal choice; if the competition intensity is low but commission rate is high, Mode R is optimal; if the commission rate is relatively high, the manufacturer should choose Mode R. Finally, we further characterize the influences of the different selling modes on the profits of the online retailer, the platform, and the whole supply chain. We also extend the model by considering the case where the online retailer and platform have equal channel power and set prices simultaneously, the case of Cournot competition, and the case where the platform acts as the channel leader.

Prioritizing adoption barriers of platforms based on blockchain technology from balanced scorecard perspectives in healthcare industry: a structural approach

Abstract: ABSTRACT Since the advent of blockchain technology (BT), extensive research has explored using this technology in non-financial cases. The healthcare industry is one of the non-financial sectors that BT has significantly impacted. In this paper, for the first time, barriers to implement BT-based platforms from a balanced scorecard perspective in the healthcare sector are introduced, and these barriers are prioritized using a structural approach based on the weighted influence non-linear gauge system. Unlike other structural models such as decision-making trial and evaluation laboratory (DEMATEL), in this approach, both strength and influence intensity of components are considered in the ranking process. The proposed approach is applied in networks that have a hierarchical structure and intertwined components. The performance of the proposed approach is evaluated using the ranking of BT-based platform adoption barriers in the healthcare industry in Iran. The results show that financial issues, security issues, lack of expertise and knowledge, and uncertain government policies are the most important barriers to BT adoption in the healthcare industry.

Supply Chain 4.0 performance measurement: A systematic literature review, framework development, and empirical evidence

Abstract: Companies require a greater understanding of the Supply Chain (SC) benefits that can be gained from industry 4.0 (I4.0) and, more specifically, which technologies and concepts that can improve certain SC performance measures. A state-of-the-art systematic literature review (SLR) has been done on supply chain performance measurement linked with various industry 4.0 technologies. Based on the findings of the review through content analysis, this paper presents a framework for exploring the usage of I4.0 technologies to identify the potential supply chain performance measures. This framework includes the dimensions of Procurement 4.0, Manufacturing 4.0, Logistics 4.0, and Warehousing 4.0. As a scientific contribution, this study has validated the proposed framework through case studies, where the existing studies are limited. Finally, several fruitful future possible extensions have been discussed based on the proposed framework.

Outsourcing logistics operations in circular economy towards to sustainable development goals

Abstract: One of novel manners to achieve sustainable development is concentrating on circular economy in order to manage greenhouse gas emissions, energy consumption, and waste. It also helps to protect the environment and optimize usage of input resources. The main element of circular economy is closed-loop supply chain which covers both forward and reverse products flows. This study aims to outsource logistics operations in a closed-loop supply chain. An innovative analytical multi-step fuzzy decision-making method is proposed to rank sustainable third-party logistics service providers (3PLSPs). Fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL) is first used to evaluate the relationships among the main criteria. Then, fuzzy analytic network process (ANP) is applied to weight the determined set of criteria. In order to develop the hybrid fuzzy DEMATEL-ANP method and to simplify the computation, the expert judgment method is used between the two techniques as a middle step to reduce the number of criteria. As many of the criteria overlap with each other on content and context, expert opinions are used to shortlist and rank the criteria. Finally, the 3PLSPs are ranked through the fuzzy complex proportional assessment (COPRAS) method. To validate the practicability and applicability of the improved decision-making model, a household appliance case study is applied with data obtained from industry experts. In this case, five service providers are considered and ranked, while the first one gets the best score. A sensitivity analysis is performed by altering the criteria weights to validate the proposed approach, data, and the obtained results. In terms business and the environment, this study provides success critical criteria for decision-making problems in circular economy for addressing sustainable development.

Fuzzy multi-objective programming: A systematic literature review

Abstract: • Various multi-objective optimization (MOO) methods are systematically reviewed and summarized. • 439 articles are reviewed on fuzzy MOO published from 1978 to 2019. • The basic features of MOO methods are briefly presented along with current trends. • Recommendations for future research directions are provided. Multi-objective programming is commonly used in the literature when conflicted objectives arise in solving optimization problems. Over the past decades, classical optimization methods have been developed as useful tools to discover optimal solutions for multi-objective problems (MOPs). In recent years, under uncertainty, multi-objective Optimization (MOO) has received much attention due to its practical applications in real-world problems. However, many studies have been conducted on this matter. Some of which ignored the effects of uncertainty on optimization problems. This paper systematically reviews and summarizes various multi-objective methods applied to the problems with more than one objective in uncertain environments where uncertainty is expressed using fuzzy sets. In this paper, 439 articles on fuzzy multi-objective programming published from 1978 to 2021 are reviewed using corresponding texts, charts, and tables. Finally, the basic features of MOO are briefly presented, along with a prologue of MOO techniques and current trends. Recommendations for further research are also is provided.

A decision support model for selecting unmanned aerial vehicle for medical supplies: context of COVID-19 pandemic

Abstract: PurposeIn recent times, due to rapid urbanization and the expansion of the E-commerce industry, drone delivery has become a point of interest for many researchers and industry practitioners. Several factors are directly or indirectly responsible for adopting drone delivery, such as customer expectations, delivery urgency and flexibility to name a few. As the traditional mode of delivery has some potential drawbacks to deliver medical supplies in both rural and urban settings, unmanned aerial vehicles can be considered as an alternative to overcome the difficulties. For this reason, drones are incorporated in the healthcare supply chain to transport lifesaving essential medicine or blood within a very short time. However, since there are numerous types of drones with varying characteristics such as flight distance, payload-carrying capacity, battery power, etc., selecting an optimal drone for a particular scenario becomes a major challenge for the decision-makers. To fill this void, a decision support model has been developed to select an optimal drone for two specific scenarios related to medical supplies delivery.Design/methodology/approachThe authors proposed a methodology that incorporates graph theory and matrix approach (GTMA) to select an optimal drone for two specific scenarios related to medical supplies delivery at (1) urban areas and (2) rural/remote areas based on a set of criteria and sub-criteria critical for successful drone implementation.FindingsThe findings of this study indicate that drones equipped with payload handling capacity and package handling flexibility get more preference in urban region scenarios. In contrast, drones with longer flight distances are prioritized most often for disaster case scenarios where the road communication system is either destroyed or inaccessible.Research limitations/implicationsThe methodology formulated in this paper has implications in both academic and industrial settings. This study addresses critical gaps in the existing literature by formulating a mathematical model to find the most suitable drone for a specific scenario based on its criteria and sub-criteria rather than considering a fleet of drones is always at one's disposal.Practical implicationsThis research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.Social implicationsThe proposed methodology incorporates GTMA to assist decision-makers in order to appropriately choose a particular drone based on its characteristics crucial for that scenario.Originality/valueThis research will serve as a guideline for the practitioners to select the optimal drone in different scenarios related to medical supplies delivery.

Net-zero economy research in the field of supply chain management: a systematic literature review and future research agenda

Abstract: PurposeThe purpose of this study is to systematically review the state-of-art literature on the net-zero economy in the field of supply chain management.Design/methodology/approachA systematic literature review of 79 articles published from 2009 to 2021 has been conducted to minimise the researchers' bias and maximise the reliability and replicability of the study.FindingsThe thematic analysis reveals that studies in the field of net-zero economy have mostly been done on decarbonisation in the supply chain, emission control and life cycle analysis and environmental and energy management. The findings highlight the strong positive association between digitalisation, circular economy and resources optimization practices with net-zero economy goals. The study also addresses the challenges linked with the net-zero economy at the firm and country levels.Research limitations/implicationsPractitioners in companies and academics might find this review valuable as this study reviews, classifies and analyses the studies, outlines the evolution of literature and offers directions for future studies using the theory, methodology and context (TMC) framework.Originality/valueThis is the first study that uses a structured approach to analyse studies done in the net-zero field by assessing publications from 2009 to 2021.

Alliance strategy in an online retailing supply chain: Motivation, choice, and equilibrium

Abstract: • A co-opetitive online retailing supply chain is investigated. • The alliance motivation, choice and equilibrium are identified. • Win-win-win situations can be achieved if the manufacturer and the retailer/platform form an alliance. • Lose-lose-lose situations can be achieved if the retailer and the platform form an alliance. • A higher agency rate benefits the retailer when the manufacturer and the platform ally. In this paper, we investigate the alliance strategy in an Online Retailing Supply Chain (ORSC). Three alliance models in addition to one no alliance model are built and examined. The no alliance model as a benchmark is developed to characterize the alliance motivation for each supply chain member. Afterwards, we identify the optimal alliance strategy and the final alliance equilibrium. The results show that the manufacturer always has motivations to form an alliance with each of other two members, while the retailer and the platform may form an alliance only when the agency rate is relatively low. Moreover, under certain conditions, all supply chain members could achieve a win-win-win result in the manufacturer-retailer and manufacturer-platform alliance models, but fall into a lose-lose-lose situation in the retailer-platform alliance model. Additionally, it is interesting that a higher agency rate makes the retailer more profitable when the platform and manufacturer enter into an alliance. Finally, we find that each of the three alliance models may be the final equilibrium, which is largely dependent on channel competition and the agency rate.

How Artificial Intelligence Drives Sustainable Frugal Innovation: A Multitheoretical Perspective

Abstract: Recent globalization and industrialization efforts have pushed many companies to seriously consider innovation efficiency and its effectiveness. Industries seek to integrate innovation thinking in the company, resulting in different innovation theories. However, these theories become mostly ineffective when disruptions such as pandemics, political instability, or other natural events occur. In response to such disruptions, frugal innovation has been adopted in recent years because it can maximize efficiency with fewer resources. While frugal thinking is effective from an economic perspective, not enough attention has been devoted to exploring this innovative thinking method from the perspective of other pillars of sustainability (environment and society). This article focuses on this gap to deepen the understanding of sustainable frugal innovation in a recent business environment under various theoretical perspectives (triple bottom line, diffusion of innovation, and critical success factor theories). Technology is a vehicle for innovation, so this article integrates the technological advantages of AI with sustainable frugal innovation as a driving force for its effective implementation; other existing studies are limited. Integrating AI with sustainable frugal innovation requires precise actions that can be the result of understanding AIs critical success factors from the perspectives of sustainable frugal thinking. Therefore, this article analyzes the critical success factors for AI through grey DEMATEL. A research framework has been proposed and validated with a Danish case study context. Among 24 overall common critical success factors, “understanding the concept of AI” and “level of AI investment” in sustainable frugal innovation are identified as the most influential success factors. In addition, influential connections among other overall common success factors are presented. These findings could motivate industries to explore different options for successfully integrating AI with their sustainable frugal thinking, which may increase their business competitiveness during disruptions in a more sustainable way.

Theory Building Through Corporate Social Responsibility 4.0 for Achieving SDGs: A Practical Step Toward Integration of Digitalization With Practice-Based View and Social Good Theory

Abstract: Corporate social responsibility (CSR) has become a hot topic in recent years, especially following the introduction of the sustainable development goals (SDGs). Among various strategies for achieving SDGs, CSR has become a dominant practice by which managers eliminate corporate social impact and develop social responsibility and commitment. To improve the integration of CSR into organizational practices, companies began to explore various available options. Academic studies began to analyze drivers, barriers, and best practices in CSR. More recent organizational structures are being transformed with the advent of new industry 4.0 technologies. There is good evidence that these technological integrations can improve the organization's overall performance. This article attempts to consider such technologies in CSR management. Industry 4.0 technologies, integrated with CSR and their practices, have been analyzed as “CSR 4.0 practices.” A theoretical framework has been proposed that links the practice-based view with the theory of social good. Further, the theory has been validated through a case study in which 23 CSR 4.0 practices that enhance better integration of digitization with the company's conventional CSR were collected from the literature and validated with experts for social good. These practices were further analyzed with DEMATEL, a multicriterion decision-making tool using case decision-makers’ responses. Case study methods have been adapted to this article, where the textile sector from one of the developing contexts, India, has been considered. Among 23 CSR 4.0 practices, “data ownership policy and rights” (P22) has been identified as the most influential CSR 4.0 practice, while “digital technology recycling” (P19) ranks as the least influential. The resulting influential practices have been correlated with CSR 4.0 performances and, further, those performances are connected with their respective SDGs. This article warrants several scientific and societal contributions to CSR; this article is groundbreaking and contributes to theory building in CSR through the identification and analysis of CSR 4.0 practices. Further expansion of this article may be more fruitful due to the digitized changes in organizational culture.

A CM-BWM Approach to Determinants of Open Innovation in Small and Medium-Sized Enterprises

Abstract: Open innovation has gradually gained greater importance over time as commitment to a culture of constant innovation has become increasingly indispensable for organizations' long-term survival. This trend has made understanding the factors that affect innovation capacity and success imperative. Given the wide range of determinants already identified, researchers seeking to analyze these factors face difficult, extremely complex challenges in terms of determining their effects on small and medium-sized enterprises (SMEs). The existing literature mentions limitations arising from how criteria have been selected for evaluation systems and how these determinants' relative weights have been defined. This article develops an analysis system that combines cognitive mapping—based on the jointly understanding, reflecting, and negotiating strategy making approach—and the best-worst method. The two main aims are to identify the most significant criteria for evaluations of SME propensity to engage in open innovation and to calculate these factors' relative weights. This article focuses on promoting realistic, comprehensive analyses that foster clearer and more conscious decision making based on a holistic view of open innovation assessment.