Search results

1 – 3 of 3
Article
Publication date: 1 March 2023

Hossein Shakibaei, Mohammad Reza Farhadi-Ramin, Mohammad Alipour-Vaezi, Amir Aghsami and Masoud Rabbani

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so…

Abstract

Purpose

Every day, small and big incidents happen all over the world, and given the human, financial and spiritual damage they cause, proper planning should be sought to deal with them so they can be appropriately managed in times of crisis. This study aims to examine humanitarian supply chain models.

Design/methodology/approach

A new model is developed to pursue the necessary relations in an optimal way that will minimize human, financial and moral losses. In this developed model, in order to optimize the problem and minimize the amount of human and financial losses, the following subjects have been applied: magnitude of the areas in which an accident may occur as obtained by multiple attribute decision-making methods, the distances between relief centers, the number of available rescuers, the number of rescuers required and the risk level of each patient which is determined using previous data and machine learning (ML) algorithms.

Findings

For this purpose, a case study in the east of Tehran has been conducted. According to the results obtained from the algorithms, problem modeling and case study, the accuracy of the proposed model is evaluated very well.

Originality/value

Obtaining each injured person's priority using ML techniques and each area's importance or risk level, besides developing a bi-objective mathematical model and using multiple attribute decision-making methods, make this study unique among very few studies that concern ML in the humanitarian supply chain. Moreover, the findings validate the results and the model's functionality very well.

Article
Publication date: 21 April 2023

Javier Isaac Torres Vergara, Jania Astrid Saucedo Martínez and Daniela Olivo Lucio

In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and…

Abstract

Purpose

In the supply chain performance measurement (SCPM) there seems to be no consensus about measures for performance evaluation and suitable criteria from resilience and sustainability paradigms. In this way, this research aims to identify the attributes that a supply chain (SC) should follow to be resilient and sustainable, and then to evaluate their importance according to industry experts.

Design/methodology/approach

This study suggests a hybrid approach. The authors identified the most commonly used criteria using literature review, and then applied fuzzy Delphi technique (FDT) with the objective of surveying experts to find the attributes used in practice and asked to assess their relevance.

Findings

The resilient-sustainable supply chain (RSSC) is formed by four dimensions: resiliency, economic, environmental and social. A total of 15 criteria are identified, and the most important are visibility, flexibility, supply chain risk management (SCRM) culture, work conditions and communication.

Research limitations/implications

This study used a literature review, so it is subject to a time frame, and the criteria could no longer be relevant as the time and business conditions change. Also, the findings may not be completely applicable throughout different industries, and therefore the finding cannot be replicated to other businesses.

Practical implications

This study will assist decision-makers among other interested parties to construct and/or strengthen an integrated SC that mixes resiliency and sustainability.

Originality/value

This study contributes to the state-of-art by producing a characterization of the resilient and sustainable supply chain for the automotive industry. Also, this research produces a new and holistic framework for resilient and sustainable SCPM supporting the decision-making process.

Details

Benchmarking: An International Journal, vol. 31 no. 3
Type: Research Article
ISSN: 1463-5771

Keywords

Content available
Article
Publication date: 18 April 2023

Emilia Vann Yaroson, Liz Breen, Jiachen Hou and Julie Sowter

Medicine shortages have a detrimental impact on stakeholders in the pharmaceutical supply chain (PSC). Existing studies suggest that building resilience strategies can mitigate…

Abstract

Purpose

Medicine shortages have a detrimental impact on stakeholders in the pharmaceutical supply chain (PSC). Existing studies suggest that building resilience strategies can mitigate the effects of these shortages. As such, this research aims to examine whether resilience strategies can reduce the impact of medicine shortages in the United Kingdom's (UK) PSC.

Design/methodology/approach

A sequential mixed-methods approach that involved qualitative and quantitative research enquiry was employed in this study. The data were collected using semi-structured interviews with 23 key UK PSC actors at the qualitative stage. During the quantitative phase, 106 respondents completed the survey questionnaires. The data were analysed using partial least square-structural equation modelling (PLS-SEM).

Findings

The results revealed that reactive and proactive elements of resilience strategies helped tackle medicine shortages. Reactive strategies increased relational issues such as behavioural uncertainty, whilst proactive strategies mitigated them.

Practical implications

The findings suggest that PSC managers and decision-makers can benefit from adopting structural flexibility and proactive strategies, which are cost-effective measures to tackle medicine shortages. Also engaging in strategic alliances as a proactive strategy mitigates relational issues that may arise in a complex supply chain (SC).

Originality/value

This study is the first to provide empirical evidence of the impact of resilience strategies in mitigating medicine shortages in the UK's PSC.

Access

Year

Last month (3)

Content type

1 – 3 of 3