Enhancing Supply Chain Efficiency and Transparency: A Conceptual Model for Blockchain Adoption and Human Capital Development within the TOE Framework

Abstract

This study intends to develop a model that comprehensively presents how the different effects of vital variables all contribute to the efficiency and transparency of the supply chains which will be grounded within the theory of Technology-Organization-Environment. The methodology proposed follows Saunders' Research Onion and presents a positivist research philosophy by which quantitative data is valued. The research will also be deductive; it will begin by testing theory on blockchain and supply chain management to examine them through the proposed model. The research strategy involves quantitative survey designed for supply chain professionals across all other industries, be it transportation & logistics, and food & beverage. This study develops a conceptual model, which in fact was exhaustive, that showed how the different influences of key variables really affected supply chain efficiency and transparency. This model was built using Technology-Organization-Environment for the said study. Amongst such factors include: blockchain technology adoption, awareness and education of stakeholders, regulatory frameworks, and development of human capital while investigating the moderating effect of organizational readiness regarding these relationships. Data would be collected through structured online surveys testing the five proposed hypotheses regarding the effect of blockchain adoption on supply chain performance. According to the literature, a skilled workforce and stakeholder education are essential in maximizing the potential benefits of blockchain technology. The study further reinforces the requirement of supportive regulatory frameworks, which facilitate the adoption and integration of the technology. Therefore, practitioners, policymakers, and researchers can draw from this work for valuable insights into utilizing blockchain technology strategically to improve supply chain processes. Suggestions for future research directions included the need for empirical testing of the proposed model, longitudinal studies that track change over time, and consideration of other influencing variables across various industries and regions.