Supply Chain Management Enablers Research Articles

The impact of the supply chain orientation fit between supply chain members: A triadic perspective

AbstractExisting literature has established supply chain orientation (SCO) as a critical enabler of supply chain management. Although SCO is predicated on alignment across supply chain members, it has primarily been examined at the individual firm level. Given this limitation, we collected triadic archival and survey data from multiple levels of the supply chain to introduce the concepts of SCO supplier fit (i.e., firm's SCO matches its supplier) and SCO customer fit (i.e., firm's SCO matches its customer). The results reveal that SCO supplier fit and SCO customer fit each positively impacts firm operational and customer performance in return on assets (ROA) and return on sales (ROS). More specifically, a firm with an SCO matching its primary upstream or downstream partners performs significantly better than a firm with a higher or lower SCO. In fact, firms with relatively more SCO than key supply chain partners perform significantly worse than those having relatively less SCO. Finally, firms with both SCO supplier fit and SCO customer fit perform better than firms with SCO supplier or customer fit alone. Ultimately, SCO alignment across the supply chain appears to be more important than the level of SCO itself.

Modelling the leagile enablers of supply chain management in Indian automobile sector

Modelling the leagile enablers of supply chain management in Indian automobile sector

Modelling the leagile enablers of supply chain management in Indian automobile sector

Modelling the leagile enablers of supply chain management in Indian automobile sector

Structural modeling of lean supply chain enablers: a hybrid AHP and ISM-MICMAC based approach

PurposeToday the role of industry 4.0 plays a very important role in enhancing any supply chain network, as the industry 4.0 supply chain uses Big Data and advanced analytics to inform the complete visibility. Latest data are available to bring clarity and support real-time decision-making in the entire supply chain that’s why adopting optimization techniques such as lean manufacturing and lean supply chain concept for enhancing the supply chain network of the organizations is a good idea and would benefit them in increasing their cost efficiency and productivity. The purpose of this work is to develop a technique, which may be useful for future researchers and managers to identify and classification of the significant lean supply chain enablers.Design/methodology/approachIn this paper, the authors considered hybrid analytical hierarchy process to find the ranking of the identified lean supply chain enablers by calculating their weightage. Interpretive structural modeling (ISM) is applied to develop the structural interrelationship among various lean supply chain management enablers. Considering the results obtained from ISM the Matrices d'Impacts Croises Multiplication Appliqué a un Classement (MICMAC) analysis is done to identify the driving and dependence power of Lean Supply Chain Management Enablers (LSCMEs).FindingsFurther, the best results applying these methodologies could be used to analyze their inter-relationships for successful Lean supply chain management implementation in an organization. The authors developed an integrated model after the identification of 20 key LSCMEs, which is very helpful to identify and classify the important enablers by ISM methodology and explore the direct and indirect effects of each enabler by MICMAC analysis on the LSCM implementation. This will help organizations optimize their supply chain by selective control of lean enablers.Practical implicationsFor lean manufacturing practitioners, the result of the study can be beneficial where the manufacturer is required to increase efficiency and reduce cost and wastage of resources in the lean manufacturing process, as well as in enhancing the supply chain.Originality/valueThis paper is the first research paper that considered firstly deep literature review of identified lean supply chain enablers and second developed structured modeling of various lean enablers of supply chain with the help of various methodologies.

Using ISM-fuzzy MICMAC method: Develop enablers' framework of sustainable supply chain management in textile sector

The assembling area has contributed altogether to construction the country's financial system for agricultural nations similar to India; however it have likewise made numerous ecological and cultural issues. The arrangement with these issues, the current examination has recognized the empowering influences and displayed their interrelationships for the situation association of IndianThe aim of this paper is to identify and create relations between Sustainable Supply Chain Management Enablers (SSCMEs), to comprehend common impacts of these SSCMEs on SSCM use, and to discover the driving and reliance strength of SSCMEs. This paper has recognized 20 SSCMEs based on review and the sentiments of specialists from the scholarly community and industry. A nation poll-based study has been led to rank these recognized SSCMEs. The results of the study and interpretive basic demonstrating (ISM) strategy have been connected to develop shared connections among SSCMEs, which uncovers the immediate and aberrant impacts of each SSCMEs. The consequences of the ISM are utilized to contribute to the fluffy MICMAC (Matriced' Impacts Cruise's Multiplication Applique ea' un Classement) examination, to recognize the driving and the reliance intensity of SSCMEs. The 20 SSCMEs out of 25 SSCMEs (Mean ≥ 3.00) have been considered for investigation through an across-the-country poll that reviews Indian car associations. The coordinated methodology is produced since the ISM show gives just a twofold relationship among SSCMEs. In contrast, fluffy MICMAC examination gives detailed investigation identified with driving and the reliance intensity of SSCMEs. The weighting for ISM show improvement and fluffy MICMAC is based on the opinions of a few industry experts. It is the most emotional decision, and many biases on the part of the judge can have an effect on the final result.The examination gives vital rules to the two professionals, just as the academicians. The professionals need focus on these SSCMEs all the more cautiously amid SSCM execution. SSCM administrators may deliberately design its long-haul development to meet the SSCM activity plan. While, academicians might be urged to classify diverse issues, which are huge intending to these SSCMEs. The course of action of SSCMEs in a progression, the classification into the enablers and ward classifications, and fluffy MICMAC are a selective exertion in the territory of SSCM usage.

Modelling hierarchical circular supply chain management enablers in the seafood processing industry in Vietnam under uncertainties

ABSTRACT This study establishes a valid set of circular supply chain management enablers in Vietnam under uncertainties. Circular supply chain management optimises resource utilisation and minimises waste in achieving competitive advantage; however, prior studies failed to build enablers for industrial improvement under qualitative information. This study adopts the fuzzy Delphi method to arrive at a valid group of attributes. Fuzzy set theory deals with the uncertainties from qualitative data, and fuzzy interpretive structural modelling builds the hierarchical structure under uncertainties. The best-worst method confirms the consistencies. This study stipulates a four-level hierarchical structure in the seafood processing industry. The results show that organisational capability and agility, technological advancement and economic benefit are dominant aspects. Commitment of leadership and managerial support, suppliers’ collaboration, firm culture, readiness for organisational change and sustainability concept integration are top criteria for industrial improvement.

Analysis of sustainable supply chain management enablers and their benefits realised to business organisations

The objective of this study is to identify and analyse the sustainable supply chain management (SSCM) benefits realised due to adoption of SSCM enablers. A hybrid modified step-wise weight assessment ratio analysis (SWARA) - weighted aggregated sum product assessment (WASPAS) approach has been adopted in this research work for the analysis. Modified SWARA is used to determine the relative importance of SSCM enablers while WASPAS method is used to prioritise the benefits. The findings of the study reveal that more attention should be on the adoption of environmental and regulatory enablers for effectiveness in SSCM implementation. It is also found that improved ability of 6R practices is a highly realised benefit due to the adoption of SSCM enablers. This research will help decision makers to effectively implement sustainability in their business organisation by developing a strategic action plan at the initial stage of SSCM implementation.

An interpretive structural modeling approach to enablers of green supply chain management on construction projects

The objective of this study is to understand and evaluate the interactions of the Green Supply Chain Management enablers from a construction project's perspective in Imo State, Nigeria. This paper discusses the mix of practical intuition and determination through an interpretive structural modeling (ISM)-driven methodology. Eight (8) enablers were identified from a literature review, expert consultation, and real-world examples. While Matrice d’Impacts croisesmultipication applique a classement analysis (MICMAC) was used to identify dependence and driving power, it was used as a way to understand the relationship between the enablers. The study found that strong, yet fragile, forces drive GSCM adoption, with enhanced awareness of GSCM, increased market appeal for green construction projects, and government support through incentives and tax rebates.

Analysis of sustainable supply chain management enablers and their benefits realised to business organisations

Analysis of sustainable supply chain management enablers and their benefits realised to business organisations

Modeling the enablers of humanitarian supply chain management: a hybrid group decision-making approach

PurposeThis paper intends to explore and appraise the humanitarian supply chain management enablers (HSCMEs) for efficient and effective humanitarian operations. This research aims to analyze the interaction of enablers for humanitarian supply chain management (HSCM) using a proposed hybrid framework consists of fuzzy Delphi (FD), interpretive structural modeling (ISM)–matriced impacts croises multiplication appliquee a un classement (MICMAC) and revised Simos approach.Design/methodology/approachThis research is deliberate to identify 28 HSCMEs through a literature review and experts' opinions; out of which 20 HSCMEs are selected using FD. ISM is applied to know contextual relationship among the selected HSCMEs for developing a hierarchical model. The MICMAC analysis classifies the HSCMEs based on driving power and dependence power to validate the developed hierarchical ISM structure. The revised Simos technique is used to prioritize the HSCMEs to access its relative significance in humanitarian operations.FindingsThe finding of the analysis suggests that government policy and leadership support obtained the highest priority, having high driving power and low dependence power is significantly strategic and emerged as the leading driver for the HSCM implementation.Research limitations/implicationsISM model presents an insight into interrelationship among HSCMEs, but this cannot quantify the impact of each HSCMEs.Practical implicationsDisaster relief aid agencies and stakeholders may focus on the enablers having high driving power and higher weight in designing and executing an effective and efficient humanitarian supply chain and to improve their activities and strategies of HSCM.Social implicationsThis research helps humanitarian logisticians and humanitarian organizations to make better decisions to improve their operational performance in pre and postdisaster phases.Originality/valueThis paper explores the application of proposed hybrid framework to analyze the HSCMEs that can be considered as the original contribution.

Supply chain management enablers, barriers and disruptions in the animal feed industry in the Western Cape Province of South Africa

Background: The animal feed supply chain in South Africa is an important industry that has experienced numerous changes as it evolved. However, not much is known empirically about the dynamics of implementing supply chain management (SCM) in the animal feed industry in specific South African contexts. Objectives: This study investigates the SCM-related factors for growth (enablers), barriers and disruptions within the animal industry in the Western Cape Province of South Africa. Method: This study used a qualitative method in which managers drawn from the animal feed industry in the Western Cape Province were interviewed. The collected data were examined using thematic analysis. Results: This study showed that the use of technology to achieve goals, bargaining power of the industry and unity, and procurement and supply chain strategy served as the main SCM enablers. The lack of infrastructure, ineffective change management, health and safety, nature of the industry, and skills and qualifications are the primary barriers hindering the effective implementation of SCM. Economic factors, natural disasters and diseases, and a lack of customer loyalty within the animal feed industry were the main SCM disruptions highlighted in the study. Conclusion: This study provides information regarding the factors (enablers) that deserve attention when developing interventions to improve the performance of the animal feed supply chain. The information on SCM barriers and disruptions is relevant when developing risk management initiatives in the animal feed industry.

Identification and analysis of enablers of SCM by using MCDM approach

PurposeThe purpose of this paper is to differentiate the empowering influences of critical enablers of supply chain management (SCM) along with their interrelationships. These empowering enablers are significant, as they encourage productive execution to improve organizational performance and stakeholder's satisfaction.Design/methodology/approachFrom the literature review, incidence of a number of SCM enablers were found and they were subjected to critical scrutiny by a considerable number of experts engaged in SCM research and application to identify significant and applicable empowering enablers by grounded interactions. By using Impact Matrix Cross-Reference Multiplication Applied to a Classification analysis, the driving and dependence power were analyzed and the empowering enablers were ordered. This was pursued by building up a structural model of the empowering enablers using interpretive structure modeling, followed with measuring cause–effect relationship using decision-making trial and evaluation laboratory (DEMATEL).FindingsAmong these identified enablers of SCM, operational performance, green SCM, employee empowerment and motivation and strategic association came out to be strategic enablers.Research limitations/implicationsThe findings may help the practicing professionals to develop clarity in understanding of these essential enablers and their contextual as well as cause–effect relationship in SCM. The practicing professionals need to focus on all these enablers during implementation of SCM for enhancing the organizational performance and stake holders' satisfaction.Originality/valueThis study is of practical utility in real-life implementation of SCM. The algorithm used in applying the multi-criteria decision-making approach is very user-friendly, and the application of DEMATEL is an innovation compared to previous research. Further, the findings can be used as a benchmark for improving the performance of SCM by considering the cause–effect relationship.

Interpretive Structural Modeling-based Framework for Analysis of Sustainable Supply Chain Management Enablers: Indian Thermal Power Plant Perspective

Indian thermal power industries, being perceived as the most polluting, are experiencing tremendous pressure to implement sustainable supply chain practices. In this light, the purpose of this article is to explore the factors that initiate sustainable supply chain management (SSCM) adoption in Indian thermal power industries and understand the interrelationship existing among them. Interpretive structural modeling (ISM) technique is employed to extract the structural relationship existing among the SSCM enablers and portray the same through a hierarchical model. Further, MICMAC (Matrice d’Impacts Croisés Multiplication Appliquée á un Classement) analysis has been employed to classify the enablers by taking their driving and dependence power as a measure. Eleven SSCM enablers have been explored through an extensive review of the literature. The interpretive structural model of selected enablers indicates that SSCM adoption in thermal power plants is mainly due to “pressure from environmental advocacy groups” and “government policies and employee pressure”. Prior knowledge of these influential factors and their interdependence will help the decision makers to develop suitable strategies that would enable the organizations to reduce the impact of barriers while optimizing the benefits derived from the enablers.

Sustainable supplier selection by way of managing knowledge: a case of the automotive industry

Knowledge management (KM) is globally known as an enabler for supply chain management (SCM). By developing the literature of 'sustainability' in SCMs, sustainable supplier selections (SSS) have widely been recognised as an important issue. The current research aims at investigating the relationship between knowledge management process capability (KMPC) and SSS in one of the Iranian automobile manufacturer, so called 'SAIPA'. After reviewing the related literature, the research's model was extracted. Meanwhile, well-designed questionnaires were distributed among the 191 SAIPA Corp's experts who have had the adequate understanding of KM. Besides, in this study an applied research has been used as a research method, and a canonical correlation coefficient for collecting the data. Furthermore, cross-sectional study has been utilised. Based on the results, in regards to the SAIPA's SCM, there is a meaningful, as well as positive linkage between KMPC and SSS criteria.

Sustainable supplier selection by way of managing knowledge: a case of the automotive industry

Knowledge management (KM) is globally known as an enabler for supply chain management (SCM). By developing the literature of 'sustainability' in SCMs, sustainable supplier selections (SSS) have widely been recognised as an important issue. The current research aims at investigating the relationship between knowledge management process capability (KMPC) and SSS in one of the Iranian automobile manufacturer, so called 'SAIPA'. After reviewing the related literature, the research's model was extracted. Meanwhile, well-designed questionnaires were distributed among the 191 SAIPA Corp's experts who have had the adequate understanding of KM. Besides, in this study an applied research has been used as a research method, and a canonical correlation coefficient for collecting the data. Furthermore, cross-sectional study has been utilised. Based on the results, in regards to the SAIPA's SCM, there is a meaningful, as well as positive linkage between KMPC and SSS criteria.

An assessment of green supply chain framework in Indian automobile industry using interpretive structural modelling and its validation using MICMAC analysis

The goal of delivering a green product starts with green procurement and then continue further with green logistics, green process and green manufacturing specially in a strong supply chain like that in an automobile organization. The purpose of this paper is to identify the green supply chain management enablers (GSCMEs) for Indian automobile industry and establish relationships among them using interpretive structural modelling (ISM) and find out driving and dependence power of enablers, using Matriced' Impacts Croisés Multiplication Appliquée á un Classement (MICMAC) analysis. A survey method is used to get the primary data for this research from fifteen automobile organisations in the Pune-Nashik area. Although currently the research has been conducted only in one industrial region but in future this study can be replicated to other Indian regions as well. The study identifies environmental regulations along with relationship with suppliers as main enablers for a better green supply chain.

An Assessment of Green Supply Chain Framework in Indian Automobile Industry using interpretive structural modelling and its validation using MICMAC analysis

The goal of delivering a green product starts with green procurement and then continue further with green logistics, green process and green manufacturing specially in a strong supply chain like that in an automobile organization. The purpose of this paper is to identify the green supply chain management enablers (GSCMEs) for Indian automobile industry and establish relationships among them using interpretive structural modelling (ISM) and find out driving and dependence power of enablers, using Matriced' Impacts Croises Multiplication Appliquee a un Classement (MICMAC) analysis. A survey method is used to get the primary data for this research from fifteen automobile organisations in the Pune-Nashik area. Although currently the research has been conducted only in one industrial region but in future this study can be replicated to other Indian regions as well. The study identifies environmental regulations along with relationship with suppliers as main enablers for a better green supply chain.

Modeling the enablers of green supply chain management

PurposeThe purpose of this paper is to identify and develop the relationships among the green supply chain management enablers (GSCMEs), to understand mutual influences of these GSCMEs on green supply chain management (GSCM) implementation, and to find out the driving and the dependence power of GSCMEs.Design/methodology/approachThis paper has identified 35 GSCMEs on the basis of literature review and the opinions of experts from academia and industry. A nationwide questionnaire-based survey has been conducted to rank these identified GSCMEs. The outcomes of the survey and interpretive structural modeling (ISM) methodology have been applied to evolve mutual relationships among GSCMEs, which helps to reveal the direct and indirect effects of each GSCMEs. The results of the ISM are used as an input to the fuzzy Matriced’ Impacts Croisés Multiplication Appliquéeá un Classement (MICMAC) analysis, to identify the driving and the dependence power of GSCMEs.FindingsOut of 35 GSCMEs 29 GSCMEs (mean⩾3.00) have been considered for analysis through a nationwide questionnaire-based survey on Indian automobile organizations. The integrated approach is developed, since the ISM model provides only binary relationship among GSCMEs, while fuzzy MICMAC analysis provides precise analysis related to driving and the dependence power of GSCMEs.Research limitations/implicationsThe weightage for ISM model development and fuzzy MICMAC are obtained through the judgment of few industry experts. It is the only subjective judgment and any biasing by the person who is judging might influence the final result.Practical implicationsThe study provides important guidelines for both practitioners, as well as the academicians. The practitioners need to focus on these GSCMEs more carefully during GSCM implementation. GSCM managers may strategically plan its long-term growth to meet GSCM action plan. While the academicians may be encouraged to categorize different issues, which are significant in addressing these GSCMEs.Originality/valueArrangement of GSCMEs in a hierarchy, the categorization into the driver and dependent categories, and fuzzy MICMAC are an exclusive effort in the area of GSCM implementation.

Hybrid decision making approach to predict and measure the success possibility of green supply chain management implementation

The aim of this study is to help organizations to build awareness of the green supply chain management enablers (GSCMEs), and to predict and measure the success possibility of successful green supply chain management (GSCM) implementation. Integrated fuzzy decision-making trail and evaluation laboratory (DEMATEL) and fuzzy multi-criteria decision making (FMCDM) based framework has been developed to predict and measure the success/failure of GSCM implementation. It uses fuzzy DEMATEL to evaluate the weight of each evaluation criteria's and FMCDM to obtain possible rating of success for GSCM implementation. The nationwide questionnaire survey method is used to rank and to identify correlation among the GSCMEs. Total 35 GSCMEs were identified through literature review and expert discussion, out of which 29 GSCMEs (Mean ≥ 3.00) were selected for the analysis. Subjectivity, ambiguity and vagueness within the prediction process are dealt with using fuzzy set theory. The applicability of the proposed framework approach is demonstrated with empirical case study of Indian gear manufacturing organization. The predicted outcome of the study indicates that the possibility of successful GSCM implementation is roughly twice that of unsuccessful GSCM implementation. The major contribution of this study highlights on the prediction possibility, proposes a new theoretical approach, and demonstrates the proposed approach for solving complex and ambiguous multi-criteria prediction problems, which shows the right path to predict and measure the success/failure of GSCM implementation.

Supply chain management practices in state-owned enterprises environment

The South African government’s supply chain management (SCM) system is not adequately implemented in state-owned enterprises (SOEs). There are weaknesses in the SOEs SCM enablers, strategies, policy implementation and poor enforcement of government SCM rules and regulations. This is resulting in governance and compliance failures, waste and fraudulent activities. Also, top management of SOEs still do not see SCM as strategic enough to deserve their attention, and therefore, there is little support from senior management, thus making it even more difficult for SCM practitioners to execute their day-to-day functions, let alone deliver the letter and spirit of the relevant legislation. In most SOEs Senior SCM practitioners have not been involved in the corporate strategy development. This has led to supply chain and organisational strategies being misaligned. The misalignment has resulted in service delivery backlog, high levels of corruption and continuous strikes across the country for better services. Given the massive expenditure and the financial challenges facing government, an effective public-sector SCM becomes a primary requirement. Government leaders should be more strategic around using SCM as a tool to improve service delivery. This article explores supply chain practices in SOEs. It is based on a conceptual review of SCM practices in the South African SOE environment and suggests that the supply chain and organisational strategies of SOEs must be aligned to ensure efficient delivery of public services.