The present age is moving through Industry 4.0 with massive technological developments. Supply chains have become digital, keeping sync with consumer demands and preferences. The recent pandemic has reinforced the need of embracing digital technologies in managing supply chains effectively. Therefore, it is necessary that supply chains adopt 5G mobile technologies. In this regard, the present study aims to discern the critical issues for the successful adaptation of 5G technologies for supply chain management (SCM) in developing countries such as India. The success factors for the adaptation of 5G in Indian supply chains are derived from the discussions made in the related past work regarding the challenges of implementing 5G technology. Then, the listed factors are finalised through initial rounds of face-to-face discussions with a focus group of five experts. Then, a q-rung-orthopair-fuzzy (qROFS)-based rating scale is used to rate the success factors. A new qROF-weighted-neutrality-average (q-ROFWNA)-based full-consistency method (FUCOM) approach for multicriteria decision-making (MCDM) problems involving group decision making is utilised to find out the critical success factors. Based on the comparative analysis of 17 success factors (grouped into four main factors), the spectrum availability, awareness of technology and usage, the development of supporting technologies and smart cities, and skill development are found to be the top five critical factors for the successful adaptation and implementation of 5G technologies in SCM. We further carry out a sensitivity analysis and validation test and observe that our model provides a reliable and stable solution.

The subject of this research is the evaluation of electric cars and the choice of car that best meets the set research criteria. To this end, the criteria weights were determined using the entropy method with two-step normalization and a full consistency check. In addition, the entropy method was extended further with q-rung orthopair fuzzy (qROF) information and Einstein aggregation for carrying out decision making under uncertainty with imprecise information. Sustainable transportation was selected as the area of application. The current work compared a set of 20 leading EVs in India using the proposed decision-making model. The comparison was designed to cover two aspects: technical attributes and user opinions. For the ranking of the EVs, a recently developed multicriteria decision-making (MCDM) model, the alternative ranking order method with two-step normalization (AROMAN), was used. The present work is a novel hybridization of the entropy method, full consistency method (FUCOM), and AROMAN in an uncertain environment. The results show that the electricity consumption criterion (w = 0.0944) received the greatest weight, while the best ranked alternative was A7. The results also show robustness and stability, as revealed through a comparison with the other MCDM models and a sensitivity analysis. The present work is different from the past studies, as it provides a robust hybrid decision-making model that uses both objective and subjective information.

Sales and operations planning translates the requirements of the customers at the market place (related to new and/or existing products and services) into actionable tactical plans to drive the activities of the value chain of the organization. The present work aims to provide a multi-period and multi-perspective evaluation framework to compare the sales and operational performance (SOP) of firms in an emerging market. SOP is one of the frontline KPIs that describes the efficiency and effectiveness of the sales and operations planning. There is a scantiness in the extant literature about well-defined indicators to measure SOP. The current work fills the gap in the literature by developing a hybrid multi-criteria decision making (MCDM) framework utilizing the Logarithmic Percentage Change-driven Objective Weighting (LOPCOW) and Evaluation based on Distance from Average Solution (EDAS) models for a novel application in assessing SOP. From the data analysis, it is also evident that there is a variations in the year wise ranking of the companies. However, all individual year wise rankings maintain statistically significant correlations with the aggregated ranking. For aggregation purpose, Borda Count Method is used. The companies like ITC Limited, Hindustan Unilever Ltd., Avanti Feeds Ltd., Britannia Industries Ltd., and Symphony Ltd. hold the top five positions on aggregate. The comparison with other MCDM models is made and sensitivity analysis is carried out. The present work is a first of its kind that would encourage the analysts and the policy makers to evaluate the sales and operational performance using a scientific way.

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