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In recent times, organizations are increasingly adopting blockchain technology in their supply chains due to various advantages such as cost optimization, effective and verified record-keeping, transparency, and route tracking. This paper aims to examine the factors influencing the intention of small and medium enterprises (SMEs) in India to adopt blockchain technology in their supply chains. A questionnaire-based survey was used to collect data from 216 SMEs in the northern states of India. The study has considered an integrated technology adoption framework consisting of the Technology Acceptance Model (TAM), Diffusion of Innovation (DOI), and Technology-Organization-Environment (TOE). Using this integrated TAM-TOE-DOI framework, the study has proposed eleven hypotheses related to factors of blockchain technology adoption. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) have been used to test the hypotheses. The results show that relative advantage, technology compatibility, technology readiness, top management support, perceived usefulness, and vendor support have a positive influence on the intention of Indian SMEs to adopt blockchain technology in their supply chains. The complexity of technology and cost concerns act as inhibitors to the technology adoption by SMEs. Furthermore, the three factors, namely, security concerns, perceived ease of use, and regulatory support, do not influence the intention to adopt the technology. The study contributes to filling a significant gap in the academic literature since only a few studies have endeavored to ascertain the technology adoption factors by supply chains of SMEs in a developing country like India. The study has also proposed a novel integrated technology adoption framework that can be employed by future studies. The findings are expected to enable SMEs to understand important factors to be considered for adopting blockchain technology in their supply chains. Furthermore, the study may benefit the blockchain technology developers and suppliers as they can offer customized solutions based on the findings.

A Multi-Depot Green Vehicle Routing Problem (MDGVRP) is considered in this paper. In MDGVRP, Alternative Fuel-powered Vehicles (AFVs) start from different depots, serve customers, and, at the end, return to the original depots. The limited fuel tank capacity of AFVs forces them to visit Alternative Fuel Stations (AFS) for refueling. The objective is to minimize the total carbon emissions. A Two-stage Ant Colony System (TSACS) is proposed to find a feasible and acceptable solution for this NP-hard (Non-deterministic polynomial-time) optimization problem. The distinct characteristic of the proposed TSACS is the use of two distinct types of ants for two different purposes. The first type of ant is used to assign customers to depots, while the second type of ant is used to find the routes. The solution for the MDGVRP is useful and beneficial for companies that employ AFVs to deal with the various inconveniences brought by the limited number of AFSs. The numerical experiments confirm the effectiveness of the proposed algorithms in this research.

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