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.

Purpose – Supply chains (SCs) have become increasingly vulnerable to catastrophic events/disruptions that may be natural or man-made. Hurricanes, tsunamis and floods are natural disasters, whereas man-made disasters may be strikes, terrorist attacks, etc. Failure at any point in the SC network has the potential to cause the entire network to fail. SCs must therefore be properly designed to survive well in the disruption scenario. The capability of successful survival (of the firm’s SC) against those adverse events/happenings is termed as resilience; and, the SC designed under resilience consideration is called a resilient SC. Effective supplier selection is considered as a key strategic consideration in SC management. It is felt that apart from considering traditional suppliers selection criterions, suppliers’ resiliency strategy must be incorporated while selecting a potential supplier which can provide best support to the firm even in the disaster/disruption scenario. The purpose of this paper is to focus aspects of evaluation and selection of resilience supplier by considering general as well as resiliency strategy, simultaneously. Design/methodology/approach – In this work, subjectivity associated with ill-defined (vague) evaluation information has been tackled through logical exploration of fuzzy numbers set theory. Application of VIKOR embedded with fuzzy mathematics has been utilized here. Sensitivity analysis has been performed to reflect the effect of decision-makers’ (DM) risk bearing attitude in selecting the best potential supplier in a resilient SC. A case empirical example has also been presented. Findings – The work attempts to focus on a decision-making procedural hierarchy towards effective supplier selection in a resilient SC. The work exhibits application potential of VIKOR method integrated with fuzzy set theory to select potential supplier based on general strategy as well as resiliency strategy. The final supplier selection score (obtained by considering general strategy) and that of obtained by analyzing resiliency strategy have been combined to get a final compromise solution. The decision-support framework thus reported here also considers DMs’ risk bearing attitude. Practical implications – The study bears significant impact to the industry managers who are trying to adapt resiliency strategy in their SC followed by potential supplier selection in the context of resilient SC. Originality/value – Exploration of VIKOR embedded with fuzzy set theory towards suppliers’ evaluation and selection by considering general and resiliency criteria both. The decision-support module(s) adapted in this paper considers DMs’ risk bearing attitude to arrive the best compromise solution.

PurposeCircular economy denotes future sustainability that allows optimum utilization of resources. In the present era of technology, plenty of innovations are happening across the world, and digital manufacturing is one of such innovations. However, there are several barriers which are impeding adoption of digital manufacturing in circular economy environment. The study explores the barriers of digital manufacturing initiatives in a circular economy and develops a methodological model to prioritize the identified challenges for automotive parts manufacturing industry.Design/methodology/approachSeven categories of challenges namely process, human resources, financial, collaboration, technological, security and leadership challenges were identified from literature and further validated with subsequent discussions with experts from the industry. The study is conducted in two phases, where in the first phase, the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique is used to define the priority and importance of seven categories of challenges. In second phase, the barriers are ranked using a Fuzzy Performance Important Index (FPII), taking into account contextual factors associated with the challenges and linked barriers, to determine the extent to which they impede the adoption of digital manufacturing in the sample automotive parts manufacturing company.FindingsThe “risk of data security and information privacy in connection with use of external data and protecting customer data” appeared as the most significant barrier to digital manufacturing in circular economy. Furthermore, technological challenges emerged as the most significant category of challenges followed by financial challenges in adoption of digital manufacturing in circular economy.Practical implicationsIdentification of the identified barriers and understanding the interrelationships will lead to easier adoption of digital manufacturing in circular economy.Originality/valueDespite all the potential benefits of implementing Industry 4.0 technologies in manufacturing industries, the adoption thereof is still in nascent phase with significant challenges yet to be overcome to accelerate the pace of adoption. Hence, this study explores the barriers preventing companies from adopting and benefiting from digital manufacturing initiatives and develops a methodological model.

Bioinorganic chemistry is found as a sizzling field in today’s era. It deals with chemistry amongst the heavy metals with natural resources, i.e., air, soil, water, plant byproducts (foods), and environmental essences. The aim of this research is to determine the concentration of heavy metals present in the food waste water sample and to study the environmental effects of metal ion concentration. To conduct the research work, the physicochemical parameters and levels of five heavy metals of food waste water samples were collected from five sampling points of renowned hotels, restaurants, canteens, and confectionaries of a state of India and assessed using the standard analytical procedure. Sampling was carried out from January 2017 up to December 2017. The physicochemical parameters were determined such as pH, temperature, turbidity, conductivity, total dissolved solids, total suspended solids, total alkalinity, biological oxygen demand, chemical oxygen demand, dissolved oxygen, total organic carbon, sulphate, nitrate, and phosphate. The heavy metal concentration was determined by using the UV-spectrophotometer, and the results were compared with the standards prescribed by the WHO, BIS, ICMR, and municipal authorities. The results obtained in the physicochemical analysis revealed that a few parameters were found beyond limits, and the metal ion concentration (iron and zinc) results were found above the permissible limits set by the CPCB (Central Pollution Control Board), ICMR, BIS, and World Health Organization (WHO), most especially, effluent from point P1. It was concluded that all the effluents required further treatment before releasing them into the water body or land to prevent pollution. The obtained results reveal that waste water used for irrigation and farming of nearby areas and water drained from restaurant kitchens were considerably polluted and not suitable for aquatic organisms, irrigation, and agricultural purposes.

Purpose Supplier evaluation is a part of logistic management. In the present era, resilient supply chain performance (RSCP) assessment of the vendor enterprise is respected as a hot topic. The purpose of this paper is to enable the managers to map the performance in percentage system and also enabling managers for identifying the weak indices-metrics, which need to be improved up to ideal or standard level and strong indices-metrics. Design/methodology/approach The authors found two research gaps via a literature survey. The first research gap revealed that the performance of a resilient supplier is computed solely in terms of a fuzzy mathematical scale. The articles are not yet published, which could measure the RSCP in percentage. The second research gap argued about the mitigation of the multi-level hierarchical resilient vendor/supplier evaluation framework for materializing RSCP and identifying weak and strong performing indices-metrics. To compensate the both research gaps, the authors developed a novel fuzzy gain-loss evolutionary computational approach to assess the performance of a firm in percentage. Next, a revised ranking technique coupled with trapezoidal fuzzy set based fuzzy performance importance index is implemented on the framework to seek weak and strong indices-metrics. The performance loss of each metric using the ideal solution concept considering the attitude of decision makers is also revealed. Findings The authors found the RSC performance of supplier firm 74 per cent, whereas performance loss 26 per cent, while actual performance is compared with standard fuzzy performance index (SFPI). Performance loss 26 per cent can be compensated by improving the performance of weak indices-metrics. Originality/value The novelty of the paper is that the authors used the ideal solution concept to compute the SFPI and compare it with actual FPI for evaluating the gain and loss of resilient supplier firm in percentage and identify weak and strong indices so that managers can improve the performance of weak indices. The work possesses the significant for all organizations, as research work enables the managers to map and improve the RSC performance of any vendor firm in future. The presented work considers the case of an automobile parts supplier industry to validate the developed approach.