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Purpose: Block chain technology (BCT) has apparent capability of handling information in digital format, which has dragged attention of the practitioners for its utility in industrial and manufacturing practices. Conversely, the managerial adoption of BCT is relatively limited, which motivated the authors to identify crucial dimensions that can persuade the acceptance of BCT from an executive perspective. Thus, the present study is aimed to conduct to understand crucial barriers under BCT for managerial implementation in supply chain management (SCM) of small and medium enterprises (SMEs). Design/methodology/approach: The present study investigated evident barriers to understand implementation of BCT. A questionnaire based survey is performed to collect primary data from service and manufacturing based companies in India. Survey responses are received online and the data is analyzed in a scorecard. The scorecard embedded the scribed entries of Likert scale to determine the relative score. Findings: In present study, sixteen barriers from three categories named as technological, organizational and environmental are evaluated, where, five sub-barriers from technological domain, seven sub-barriers from organizational domain and four sub-barriers from environmental domain are evaluated. The findings of the study determined that the three factors, i.e. “complexity in setup/use”, “Security and privacy concern” and “Technological awareness” mostly affect the adaptation of BCT in SCM. Conversely, “Market dynamics”, “Scalability” and “Cost” do not influence the intention to adopt the technology. Originality/value: Only few studies have endeavored to ascertain the BCT adoption in SCM of SMEs in developing country like India. Thus, the study is filling a momentous gap of mapping BCT dimensions in the scholastic literature. The findings are expected to enable SMEs to understand important factors to be considered for adopting BCT in their curriculum. Furthermore, the study may benefit the BCT developers and suppliers to endure customized solutions based on the findings.

Purpose: The purpose of this study is to identify the barriers to the adoption of blockchain technology in green supply chain management (GSCM) and further analyze the cause and effect relationship to prioritize the barriers for making strategic decisions. Design/methodology/approach: The study examines 15 potential barriers related to the adoption of blockchain in GSCM which is identified from the literature review and finalized after subsequent discussions with industry professionals. Integrated Fuzzy-Decision-Making Trial and Evaluation Laboratory approach is used to analyze cause and effect relationships and prioritize the barriers. Fuzzy set theory is used to handle the uncertainty and vagueness associated with the personnel biases and data deficiency problems. Three small to medium enterprises’ (SMEs’) are considered for gathering data and further analyzing the crucial barriers that are impeding the adoption of blockchain technology in GSCM. Findings: The findings reveal that “lack of management vision” and “cultural differences among supply chain partners” are the most influencing barriers, whereas; “collaboration challenges” and “hesitation and workforce obsolescence” are the most influential barriers in the adoption of blockchain in GSCM. Research limitations/implications: The study is developed based on 15 selected barriers which were further tested using data from three SMEs’ in the emerging economy of India. The adoption of blockchain technology in GSCM is at a nascent stage and more research studies are necessary to extend the knowledge base. Practical implications: Managers need to eliminate the barriers and extend the blockchain technology application in GSCM. Managers need to develop the mission and vision of the company by doing proper alignment of blockchain technology with GSCM goals. Second, managers need to make strong collaborations and remove the hesitation and workforce obsolescence barrier by providing the right education and pieces of training. Originality/value: Blockchain technology in GSCM is in a nascent stage. This study extends the knowledge base by identifying and further prioritizing the leading blockchain barriers that need to be overcome for effectively adopting blockchain in GSCM.

In this reporting, an aforesaid CNC machine tool evaluation appraisement module (index) has been conceptualised from the resource of existing literature to evaluation and ranking order of preferred candidate CNC machine tool. In this reporting, generalised interval-valued trapezoidal fuzzy numbers ordered weighted geometric average (GITFNOWGA) operator has been fruitfully and effectively applied for deliver important weights against measures based on set the expert panel subjective preference assessment (rating) in ascending order and then aggregate appropriate rating with following generalised interval-valued trapezoidal fuzzy numbers rule. Finally, multi objective optimisation by ratio analysis (MULTI-MOORA) based on different parts of MULTI-MOORA, namely: ratio system, reference point, and full multification form has been explored coupled with aggregated interval valued trapezoidal fuzzy number set in perceptive to evaluating and benchmarking the CNC machine tool from preferred options/alternatives. Finally, a case study is shown to highlight the proposed procedure.

Today's more dynamic business environment increases the need for greater agility in supply chains, which increases both the importance and frequency of supplier/partner selection decision–making. The contribution of this paper is the development of a framework and a decision model for supplier/partner selection in agile supply chain by utilising a fuzzy logic integrated with MULTIMOORA method. This paper presents a host of metrics and measures from extant literature on agility, which has been utilised in the development of the appraisement framework and model. Empirical data has been analysed to exhibit application feasibility of the proposed approach.

Supply chain flexibility is considered as a major determinant of competitiveness in the global business market today. Flexibility is the organisation's ability to satisfy an increasing variety of customer expectations without excessive cost, time, organisational disruptions, or performance losses. Effective control of supply chain flexibility can improve overall organisational performance. The present study thus builds a group decision-making structural hierarchy model towards assessment as well as benchmarking of flexibility extent in supply chain management. This study presents a framework for evaluating supply chain flexibility through comprehensive analysis of past literature and identifies five elements (assessment indices) for characterising supply chain flexibility viz. supply network flexibility, operations systems flexibility, logistics process flexibility, information system flexibility, and organisational design flexibility. The subjectivity of the flexibility indices have been tackled through exploration of the concept of fuzzy logic; thus, enabling decision-making which involves linguistic expert judgment.

In the last decades, multi-criterion decision making has also impounded the performance measurement of industries in green extent. In this context, an efficient performance appraisement framework (index system) has been conceptualised from the resource of existing literature in order to appraise and benchmark the candidate industries in green performance extent running under similar green supply chain architecture. In this reporting, on account of the ill-defined criterions and inherent vagueness associated with subjectivity of evaluation indices, the linguistic assessment (evaluated score) of the expert panel have been acquired and fruitfully transformed into generalised triangular fuzzy number (TFN) set. A fuzzy-based computation module embedded with grey relation method (GRM) has been explored from the prospectus of evaluation, appraisal and benchmarking the preferred candidate industries green supply chain performance extent running under similar green indices. Finally, an empirical case study has been led in purpose to checking feasibility of the proposed decision-making approach.

Today's world of globalisation, the problem of judging most appropriate computer numerical control machine tool has been become a critical issue for most companies in fast–growing markets for a long time. The judging of CNC machine tool among the prepared choices is a multi–criteria decision–making (MCDM) problem including both qualitative and quantitative attributes. But under numerous situations, CNC machine tool performance are measured in term of subjective attributes such as productivity, precision and accuracy etc. so, these subjective attributes often imprecisely defined by experts panel judgement 'linguistic assessments'. In the proposed approach, the VIKOR compromise ranking method combined with generalised fuzzy number has explored for determining a compromise ranking (providing a maximum group utility for the majority and a minimum of an individual regret for the opponent solution). Finally, we suggested the ranking of machine tool in decreasing order preferences. Finally, a case study is shown to highlight the proposed procedure.

In today’s competitive global marketplace, supply chain management (SCM) has become a key strategic consideration for achieving the organisational goals. The performance measurement of the entire supply chain is an important issue because it allows for tracking of efficacy and efficiency failures and leads to more informed decision-making with regard to chain design. Performance measurement is important as it affects behaviour that impacts supply chain performance. As such, performance measurement provides the means by which a company can assess whether its supply chain has improved or degraded. To this end, the present research aims to develop an efficient evaluation framework for selecting the best supply chain performance alternative from available alternatives. In this study, a fuzzy multi-criteria decision-making (FMADM) combined with multi-objective optimisation by ratio analysis (MULTIMOORA) has been explored towards appraisement and selection of the best supply chain in accordance with performance.