Search results

The purpose of this paper is to study the 14 principles of Edwards Deming and create significant relationships between them. No research has been reported on the implementation of Total Quality Management (TQM) using Deming’s 14 principles. To fill this gap, Interpretive Structural Modeling (ISM) and MICMAC analysis have been developed to understand mutual interactions among variables and find both the dependence and driving power of these variables.

The research paper discusses a blend of practical applications and introduces a theoretical framework. An ISM-based methodology is used to study and examine interactions between identified variables, while MICMAC analysis is used to identify the dependence and driving power.

This research utilizes Deming’s 14 quality principles, with experts from academia and industry consulted to identify contextual relationships among variables. The result shows that the stated principles “take action to accomplish the transformation,” “institute training,” “encourage education to employees” and “institute leadership” are strategic requirements, while “drive out fear,” “break down barrier between staff areas” and “eliminate numerical quotas” are tactical requirements. “Adopt the new philosophy,” “create constancy in improvement of product and service” and “cease dependence on mass inspections” are operational requirements for TQM applications.

An ISM-based quality framework, dependence power and driving power of variables using MICMAC analysis have been recommended to the service and manufacturing industry as a new focus area in the implementation of TQM.

The purpose of this paper is to identify the challenges surrounding the implementation of digital technology (DT) agri-food supply chain (AFSC) and explore how these challenges relate to the various sustainability dimensions. Additionally, it aims to assess how these challenges are interconnected in relation to achieving sustainable development goals (SDGs).

The study employs a mixed-method approach utilizing the EFA-ISM-Fuzzy DEMATEL technique. To support and validate the findings, exploratory factor analysis (EFA) categorized 12 critical challenges in sustainable dimensions from 141 participants' responses. Furthermore, interpretive structural modeling (ISM) and decision-making trial and evaluation (DEMATEL) methods were used to obtain the interrelationship and hierarchical structure of the challenges.

The study identified 12 critical challenges while adopting DT in AFSC. These challenges were categorized into four sustainable dimensions: technological, economic, environmental and social. These challenges hinder the achievement of SDGs as well. Lack of regulatory and policy framework with security and privacy issues were the key challenges faced while adopting DT. These observations emphasize the necessity for government and policymakers to prioritize tackling the identified challenges to successfully endorse and execute DT initiatives in AFSC while also fulfilling the SDGs.

The implication underscores the need for collaboration among various stakeholders, such as governments, policymakers, businesses and researchers. By collectively addressing these challenges, DT can be leveraged optimally, fostering sustainable practices and making progress toward achieving the SDGs within the AFSC.

The study uses a combination technique of EFA and ISM-DEMATEL to identify the challenges faced in Indian AFSC while adopting DT and categorizes the interrelation between the challenges along with fulfilling the SDGs.

Disruptive technologies can significantly contribute to the sustainability of operations in the petroleum supply chain. The present study aims to identify the prime sustainable dimensions and disruptive technologies implementation in the supply chain of the petroleum industry. The authors used content analysis in the literature and experts input to explore the sustainable dimensions and disruptive technologies in the supply chain.

This study used a hybrid method of hesitant fuzzy set and regret theory to identify the prominent sustainability dimensions and prominent disruptive technologies. This method emphasizes the decision-makers psychological characteristics under uncertain environments.

The result indicates that social responsibility, labor practices, safety and technical standards hold the most prominent sustainable dimensions in the petroleum supply chain. Further, the result also depicts that when consider an equal degree of regret and rejoice, artificial intelligence and big data could significantly enhance operations sustainability in the petroleum industry.

This study considers only 11 sustainable dimensions and 43 sustainable factors, whereas other dimensions and factors could also be considered in future research. The research uses hesitant fussy set and regret set theory to identify the prominent sustainable dimensions and disruptive technologies, whereas other multiple-criteria decision-making (MCDM) techniques can also be used.

To the best of the authors’ knowledge, this is the first paper to explore the sustainable dimensions (environmental, social and economic) and disruptive technologies in the supply chain of the petroleum industry. This research intended to guide the practitioners, policymakers and academicians to emphasize their effort toward sustainable operations supply chain management.