A model for supply chain risk management in the automotive industry using fuzzy analytic hierarchy process and fuzzy TOPSIS

Risk assessment in supply chains: a state-of-the-art review of methodologies and their applications

The year 2020 can be earmarked as the year of global supply chain disruption owing to the outbreak of the coronavirus (COVID-19). It is however not only because of the pandemic that supply chain risk assessment (SCRA) has become more critical today than it has ever been. With the number of supply chain risks having increased significantly over the last decade, particularly during the last 5 years, there has been a flurry of literature on supply chain risk management (SCRM), illustrating the need for further classification so as to guide researchers to the most promising avenues and opportunities. We therefore conduct a bibliometric and network analysis of SCRA publications to identify research areas and underlying themes, leading to the identification of three major research clusters for which we provide interpretation and guidance for future work. In doing so we focus in particular on the variety of parameters, analytical approaches, and characteristics of multi-criteria decision-making techniques for assessing supply chain risks. This offers an invaluable synthesis of the SCRA literature, providing recommendations for future research opportunities. As such, this paper is a formidable starting point for operations researchers delving into this domain, which is expected to increase significantly also due to the current pandemic.

A multi-product and multi-period aggregate production plan: a case of automobile component manufacturing firm

Purpose

The study attempts to develop a multi-product multi-period (MPMP) aggregate production plan (APP) to fulfill the customers' demand in terms of throughput and lead time for achieving market competence.

Design/methodology/approach

This research proposes an integrated Fuzzy analytical hierarchy process (FAHP), multi-objective linear programming (MOLP), and simulation approach. Initially, FAHP is used to select the essential objectives a firm desires to achieve. Adopting the MOLP, an APP is formulated for the firm under study. Later, the simulation model of a firm is created in a discrete-event simulation (DES) software Arena© to evaluate the applicability of the proposed APP. A comparative analysis of the manufacturing performance levels (namely throughput, lead time, and resource utilization) achieved through the implication of an existing production plan and proposed APP is conducted further.

Findings

The findings from the study depict that the proposed MOLP-based APP can satisfy the customers' requirement (namely throughput and lead time) and improve the level of resource utilization compared with the firm's existing production plan.

Research limitations/implications

The proposed research facilitates researchers and practitioners to understand the process of developing MOLP-based MPMP APP and analyzing its applicability through simulation technique to be utilized for developing APP at their firm.

Originality/value

An integrated FAHP-MOLP-simulation framework is the novel contribution to the literature on production planning. It can be extended to solve strategic, tactical, and operational problems in different domains like service, healthcare, supply chain, logistics, and project management.

Modelling supply chain risks and their impacts on the performance of the sago starch agro-industry

Purpose

Supply chain risks (SCRs) have uncertainty and interdependency characteristics that must be incorporated into the risk assessment stage of the SCR management framework. This study aims to develop SCR networks and determine the major risk drivers that impact the performance of the sago starch agro-industry (SSA).

Design/methodology/approach

The risk and performance variables were collected from the relevant literature and expert consultations. The Bayesian network (BN) approach was used to model the uncertain and interdependent SCRs. A hybrid method was used to develop the BN structure through the expert’s knowledge acquisitions and the learning algorithm application. Sensitivity analyses were performed to examine the significant risk driver and their related paths.

Findings

The analyses of model indicated several significant risk drivers that could affect the performance of the SSA. These SCR including both operational and disruption risks across sourcing, processing and delivery stage.

Research limitations/implications

The implementation of the methodology was only applied to the Indonesian small-medium size sago starch agro-industry. The generalization of findings is limited to industry characteristics. The modelled system is restricted to inbound, processing and outbound logistics with the risk perspective from the industry point of view.

Practical implications

The results of this study assist the related actors of the sago starch agro-industry in recognizing the major risk drivers and their related paths in impacting the performance measures.

Originality/value

This study proposes the use of a hybrid method in developing SCR networks. This study found the significant risk drivers that impact the performance of the sago starch agro-industry.

A supply chain risk management maturity model and a multi-criteria classification approach

Purpose

The purpose of this paper is to propose a supply chain risk management (SCRM) maturity model combined with a fuzzy TOPSIS classification method to evaluate and sort an organization into a pre-defined maturity level.

Design/methodology/approach

An axiomatic and prescriptive research method guided this study. Therefore, it proposes a prescriptive approach of maturity classification based on a theoretical SCRM maturity model combined with a multi-criteria decision technique.

Findings

The results of a pilot application indicated a consistent classification and the value of the model for diagnosing flaws and pointing directions for improving operational and disruption risk management. Its comprehensiveness allows applying it to supply chains of several industry sectors.

Research limitations/implications

The proposed model does not include all possible risks and could be revised in further developments. Also, adjustment of the maturity profiles of the multi-criteria decision-making (MCDM) model requires a learning process from practical applications.

Practical implications

The adoption of the risk management maturity grid by practitioners may bring the benefit of a more objective and comprehensive evaluation of risk management processes in the supply chain context.

Social implications

An immediate social implication derives from the improvement actions that may result from the diagnosis of risk management vulnerabilities identified in the pilot application. In general, the proposed model has the potential to reduce risks, improve results and contribute to economic sustainability.

Originality/value

The maturity grid and decision model integrate overall aspects of risk management, bringing together managerial concepts to deal with a variety of supply chain operational risks. The combined multi-criteria classification procedure to sort the maturity level of an organization is also a novelty.

A systematic literature review on supply chain risk management: is healthcare management a forsaken research field?

Purpose

This paper aims to present a systematic literature review (SLR) to investigate how supply chain risk management (SCRM) is applied to the healthcare supply chains and which improvement opportunities are being missed in this segment.

Design/methodology/approach

This SLR used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) method to answer three research questions: (1) Which are the main gaps concerning healthcare supply chain risk management (HCSCRM)? (2) What is the definition of HCSCRM? and (3) What are the risk management techniques and approaches used in healthcare supply chains?

Findings

The authors present a complete summary of the HCSCRM body of research, investigating research strings like clinical engineering and high reliability organizations (HROs) and its relations with HCSCRM; (1) This research revealed the five pillars of HCSCRM; (2) The authors proposed a formal definition for HCSCRM considering all the literature blocks explored and (3) The authors generated a list of risks present in healthcare supply chains resulting from extensive article research.

Research limitations/implications

The authors only reviewed international journal articles (published in the English language), excluding conference papers, dissertations and theses, textbooks, book chapters, unpublished articles and notes. In addition, the study did not thoroughly investigate specific countries' particularities concerning how the healthcare providers are organized.

Originality/value

The contribution of this article is threefold: (1) To the best of authors knowledge, there is no other SLR about HCSCRM published in the scientific literature by the time of realization of authors’ work, suggesting that is the first effort to fulfill this research gap; (2) Following the previous contribution, in this work the authors propose a first formal definition for HCSCRM and (3) The authors analyzed concepts such as clinical engineering and HROs to establish the building blocks of HCSCRM.

Modelling the supply chain risk variables using ISM: a case study on Indian manufacturing SMEs

Purpose

In the Indian manufacturing SMEs context, supply chains have a complex structure having multiple echelons, multiple partners and multiple locations. Due to these complexities, most of the Indian manufacturing SMEs face several types of supply chain risks. This paper aims to identify the dominant risk variables and to develop the interrelationship among these risk variables.

Design/methodology/approach

Based on the literature review and experts’ opinion, nine dominant risk variables faced by an Indian manufacturing SMEs have been identified. An interpretive structural modelling (ISM) approach has been adopted to establish the interrelationship among the risk variables. These risk variables have been classified by using MICMAC analysis. Based on ISM-MICMAC approach, a case study on three Indian manufacturing SMEs has been carried out.

Findings

This study would help the supply chain managers to understand and prioritize the significant risk variables. Nine significant risks variables of Indian manufacturing small and medium enterprises (SMEs) have been studied. External risk, information technology risk and financial risk have identified as most influencing risk variables, while delay risk and market risk have emerged as the most dependent risk variables. These results will provide a guideline to supply chain managers for implementation of supply chain risk management (SCRM).

Research limitations/implications

In this study, an ISM-based model is developed based on the opinion of experts from a group of Indian manufacturing SMEs; as such, this model may be biased and limited to a selected company. This framework can be extended further by adding more risk variables and sub-risk variables from the other sectors/organizations.

Originality/value

Many SCRM models are available in past literature, but no model has been proposed for the Indian Manufacturing SMEs. This research finding can be useful for managers to understand the characteristics and interrelationships among the risk variables for building a robust supply chain. These results will also help the supply chain managers in making proactive plans for SCRM, especially in the Indian SMEs context.