Modelling the barriers of weather index insurance service adoption integrating expert mining and ISM Fuzzy-MICMAC

PurposeThe purpose of this study is to explore and prioritize the barriers that affect weather index-insurance (WII) adoption among customers by utilizing interpretive structural modelling (ISM) and fuzzy-MICMAC.Design/methodology/approachThis paper utilized the combined approach in two phases. In first phase comprehensive literature study and expert mining method have been performed to identify and validate WII adoption barriers. In second phase, ISM has been utilized to examine the direct relationships among WII adoption barriers in order to develop a structural model. Further, fuzzy-MICMAC method has been utilized to analyse indirect relationships among barriers to explore dependence and driver power.FindingsThis study has identified 15 key barriers of WII adoption among customers and developed a structural model based on binary direct relationship using ISM. Later, the outcomes of ISM model have been utilized for analysing the dependence and driver power of each WII adoption barriers in cluster form using fuzzy-MICMAC. The customer awareness related WII adoption barrier are mainly at the top level, WII demand related barriers are in the centre and WII supply related barriers at the bottom level in ISM model.Practical implicationsThe findings offered important insights for WII insurers to understand mutual relationships amongst WII adoption barriers and assists in developing strategy to eliminate dominant key barriers in order to enhance their customer base.Originality/valueBased on best of author's knowledge this paper firstly integrates the ISM fuzzy-MICMAC method into identification and prioritization of barriers that affects WII adoption among customers.

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.

he Integration of Fuzzy-ISM, Fuzzy-AHP, and Fuzzy-MICMAC Approach under Trapezoid Fuzzy Linguistic to Analyze Enablers of The Logistics Outsourcing Relationship: Mekong Delta, Vietnam Rice Supply Chain Context

The purpose of this paper is to analyze the effects of the factors and determine the importance of these factors to the LO relationship with the desire to improve the efficiency in logistics activities of the supply chain. An integrated approach including Fuzzy Interpretation Structure Model (FISM), Fuzzy Cross-Impact Matrix Multiplication Applied to Classification (FMICMAC) analysis, Fuzzy Analytic Hierarchy Process (FAHP) is structured in reaching this purpose. Specifically, the impact of factors on the LO relationship will be determined through the FISM-FMICMAC method, then FAHP will use the results from this FISM-FMICMAC analysis step to perform the determination of the level of importance of contributing factors to the LO relationship. The fuzzy number formats of this paper are all in trapezoidal format. To evaluate the proposed framework, a typical example of logistics activity in the Mekong Delta Rice Supply Chain (SuC) was selected. The results have shown the impact level of 14 factors on the LO relationship under 4 clusters (Dependent, Linkage, Independent Autonomous). Finally, only the 10 most outstanding of the 14 factors were used to conduct FAHP analysis to find the global weightages which contribute to the LO relationship by each factor.

Measuring agri-food supply chain performance: insights from the Peruvian kiwicha industry

PurposeAgri-food firms face many challenges when assessing and managing their performance. The purpose of this research is to determine important factors for an integrated agri-food supply chain performance measurement system.Design/methodology/approachThis research uses the Peruvian kiwicha supply chain as a meaningful context to examine critical factors affecting agri-food supply chain performance. The research uses interpretative structural modelling (ISM) with fuzzy MICMAC methods to suggest a hierarchical performance measurement model.FindingsThe resulting kiwicha supply chain performance management model provides insights for managers and academic theory regarding managing competing priorities within the agri-food supply chain.Originality/valueThe model developed in this research has been validated by cooperative kiwicha associations based in Puno, Peru, and further refined by experts. Moreover, the results obtained through ISM and fuzzy MICMAC methods could help decision-makers from any agri-food supply chain focus on achieving high operational performance by integrating key performance measurement factors.

Are artificial intelligence and machine learning suitable to tackle the COVID-19 impacts? An agriculture supply chain perspective

PurposeThis article aims to model the challenges of implementing artificial intelligence and machine earning (AI-ML) for moderating the impacts of COVID-19, considering the agricultural supply chain (ASC) in the Indian context.Design/methodology/approach20 critical challenges were modeled based on a comprehensive literature review and consultation with experts. The hybrid approach of “Delphi interpretive structural modeling (ISM)-Fuzzy Matrice d' Impacts Croises Multiplication Applique'e à un Classement (MICMAC) − analytical network process (ANP)” was used.FindingsThe study's outcome indicates that “lack of central and state regulations and rules” and “lack of data security and privacy” are the crucial challenges of AI-ML implementation in the ASC. Furthermore, AI-ML in the ASC is a powerful enabler of accurate prediction to minimize uncertainties.Research limitations/implicationsThis study will help stakeholders, policymakers, government and service providers understand and formulate appropriate strategies to enhance AI-ML implementation in ASCs. Also, it provides valuable insights into the COVID-19 impacts from an ASC perspective. Besides, as the study was conducted in India, decision-makers and practitioners from other geographies and economies must extrapolate the results with due care.Originality/valueThis study is one of the first that investigates the potential of AI-ML in the ASC during COVID-19 by employing a hybrid approach using Delphi-ISM-Fuzzy-MICMAC-ANP.

Modeling and Analysis of Lean Manufacturing Strategies Using ISM-Fuzzy MICMAC Approach

The current research work deals with an identification of different lean strategies and extraction to relevant strategies after discussion with experts and gives the answer of a question “how lean manufacturing strategies can help the organization to enhance the efficiency of the organization with great effectiveness?” In this research work, thirty-six lean strategies have been identified and out of which thirteen lean strategies were filtered in respect of highly importance value by factor analysis using software SPSS 21. Further, to identify and analyze the inter-relationship among filtered strategies, an Interpretive Structural Modeling (ISM) with Fuzzy Matriced’ Impacts Croise´s Multiplication Applique´e a UN Classement (MICMAC) approach has been used. Fuzzy MICMAC help to understand the dependence and driver’s power of the lean strategies. The mutual importance of extracted strategies has been discussed through developing the ISM model and the individual assessment of each strategy with each of the other strategies has been derived using the Fuzzy MICMAC approach.