Modeling enablers of supply chain quality risk management: a grey-DEMATEL approach

Managing supply chain resilience assessment model-relevant factors and activities using an FCM-FBWM approach

Supply chain resilience is essential for companies to survive in today's competitive market, as they face environmental and unforeseeable challenges in their supply chain. This paper aims to model and manage the factors and activities that influence supply chain resilience and how they relate to each other. This will help us devise plans for enhancing the resilience of a supply chain. By taking into account the factors and activities and their interrelationships, organizations can use their limited resources more efficiently to improve their supply chain resilience. We use a management matrix to rank the factors based on how they affect and contribute to the supply chain resilience. We conduct an empirical study in a pharmaceutical company to demonstrate the proposed management approach and provide improvement scenarios based on the ranking of the factors. The results show that the most important factors are "the cooperation and trust between supply chain members", "Visibility & Agility", and "Leadership Support and Commitment". The ranking of the factors may vary in different companies. Therefore, other companies can apply the method described in this paper and perform different improvement scenarios according to the ranking of the factors to effectively allocate their limited management efforts.

Supply chain sustainability risk assessment model using integration of the preference selection index (PSI) and the Shannon entropy

Purpose

This study proposes a new model for assessing supply chain sustainability risk integrating subjectivity and objectivity of decision-maker. Research has shown the vacancy of study in dealing with the above issue. To fill this research gap, a new decision support model considering the subjectivity and objectivity of decision-makers in assigning the weight of the supply chain risk reprioritization criteria is presented and demonstrated using a case example.

Design/methodology/approach

This study adopts a new decision support model for assessing supply chain sustainability risk based on additional failure mode and effect analysis (FMEA) parameters and its integration with preference selection index (PSI) methodology and the Shannon entropy. A case example of the supply chain small and medium enterprise (SME) producing handy crafts has been used in this study.

Findings

The result of the study reveals critical sustainability risk dimensions and their risk elements demanding management attention to support realization to a more sustainable business operation.

Research limitations/implications

The use of a single case study is often associated as a limitation in the research studies, and this study is based on findings from SMEs in the handy craft sector in a developing country. Nonetheless, future studies may focus on replicating this study using more samples. This preliminary study provides academics and practitioners with an exemplar of supply chain sustainability risk assessment from the SME in a developing country.

Practical implications

The result of this study is beneficial for practitioners, particularly owner-managers of SMEs who can use this study as guidance on how to identify and select the critical sustainability risks and plan mitigating strategies accordingly.

Originality/value

Scientific effort on appraising criticality of supply chain sustainability risks considering subjectivity and objectivity of decision-maker simultaneously is missing in earlier studies. To the best of the author’s knowledge, this is the first paper applying the PSI and Shannon entropy method and using it for evaluating the impact of supply chain risk based on five sustainability pillars. The findings and suggestions for future research initiatives will provide new insights for scholars and practitioners in managing SME supply chain sustainability risks.

A new fuzzy approach for managing data governance implementation relevant activities

Purpose

The purpose of this paper is to propose an approach for managing relevant factors and activities for implementing data governance in an organization. The process of assessing the establishment of data governance in an organization is intrinsically imprecise, due to the characteristics of new problem settings, particularly in relation to newly generated alternatives or vaguely defined qualitative assessment criteria.

Design/methodology/approach

To reject the inherent subjectiveness and imprecision involved in the evaluation process, the authors use the concept of fuzzy logic in this approach for developing the assessment model and analyzing the model for allocating the management efforts in the most efficient way to improve the data governance deployment level.

Findings

This paper identifies relevant factors and activities for implementing data governance in an organization and evaluates the state of data governance based on causal relationships between influential factors. In this study, factors are prioritized for effective allocation of limited management efforts in any improvement plan.

Research limitations/implications

The interrelationships among factors are contextual and based on the perceptions of experts who may be biased as per their background and area of expertise. Meanwhile, lack of a data governance plan may cause failure during its implementation in an organization, as the worth of an organization's data will not be determined precisely. The paper has tremendous practical implications for organizations that intend to implement the data governance program and evaluate its state to design an improvement plan.

Originality/value

The paper proposes an approach for implementing data governance in an organization faced with limited resources for improvement.