A comprehensive approach for the evaluation of the impact of blockchain on photovoltaic supply chain using hybrid data analytic method

Abstract

Blockchain technology has emerged as a disruptive and transformative innovation, drawing significant interest from organizations for its potential advantages. This study employs an exploratory research approach, utilizing a hybrid data analytics method, to investigate the impact of blockchain on the photovoltaic supply chain. Our research employs a comprehensive methodology, combining both quantitative and qualitative techniques. The research journey begins with the identification of crucial indicators, followed by the collection of data through a carefully designed questionnaire and the utilization of the Delphi method for expert insights. Subsequently, we employ advanced data analytics techniques, specifically the fuzzy Analytic Network Process (ANP) and fuzzy Interpretive Structural Modeling (ISM) methods, to prioritize these indicators and unveil their intricate relationships. Our findings underscore the paramount importance of several key criteria among the twelve identified indicators. These include data security, effective data management, data quality assurance, robust system documentation, and streamlined access protocols. Notably, customer satisfaction emerges as a pivotal factor, exerting substantial influence within our model. Moreover, our analysis underscores that data security stands as the foundational element in this multifaceted framework. This study offers valuable insights for stakeholders in the photovoltaic supply chain, aiding in the strategic adoption of blockchain technology to enhance transparency, efficiency, and overall performance. It serves as a robust framework for organizations seeking to navigate the evolving landscape of sustainable energy supply chains while harnessing the potential of blockchain innovation.