Thesis

An investigation of relational behaviours and supply chain risk information sharing : a mixed method study of firms in Nigeria

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Awarding institution
  • University of Strathclyde
Date of award
  • 2020
Thesis identifier
  • T15702
Person Identifier (Local)
  • 201669448
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Department, School or Faculty
Abstract
  • Supply chain risk information sharing is one of the proactive strategies for mitigating risks and making supply chains more resilient. The ability to sense threats before they disrupt the supply chain is strengthened by risk information from supply chain partners and other stakeholders who are usually not mandated to share risk information. This study responds to calls (Sheffi and Rice Jr., 2005; Juttner and Maklan, 2011; Johnson, Elliott and Drake, 2013) for advancing the research on supply chain risk management especially in the developing country context which Tukamuhabwa, Stevenson and Busby(2017) argues that the way in which threats are handled may differ. Antecedents such as trust, relationship length, commitment and reciprocity have been identified as relational enablers in the literature; however, they might not be sufficient or be the only enablers for firms to share supply chain risk information from the onset of a supply chain relationship, especially in the context of Nigeria. Apart from the cultural peculiarities of Nigeria, which affect business practices and relationships, there is on-going insurgency in the North-east and other human-made risk events that disrupt supply chains in the country. Hence, there is the need to carry out research of this kind that investigates how firms in Nigeria mitigate supply chain risk by leveraging on their informal relationships to share and receive risk information.;This thesis addresses this research gap by first focussing on collecting qualitative data through semistructured interviews from supply chain managers, about the relational behaviours they leverage for supply chain risk information sharing. Data from the interviews were transcribed and coded for thematic analysis. Three propositions relating to relational closeness, relational incentive, and collective prosperity emerged. Subsequently, the result of the qualitative strand was used to develop a survey instrument and was administered to members of the Chartered Institute of Procurement and Supply in Nigeria. Data for the quantitative strand was collected through an online and self-administered questionnaire. Partial least squares structural equation modelling was used to analyse the quantitative data. The result indicated that relational closeness and collective prosperity have a significant influence on supply chain risk information sharing. However, the result does not find support for the relationship between relational incentive and supply chain risk information sharing. A mixed method discussion was further presented to explain how the quantitative findings generalised the qualitative result.;The originality of this research lies in its attempt to integrate social capital and social network theories with supply chain management literature to create new knowledge of how to mitigate supply chain risk in the Nigerian context. The overall theoretical implication of this study is that it contributes to supply chain management literature by identifying new relational attributes that are vital in enhancing supply chain risk information sharing. Regarding the managerial implication, this research highlights the need to consider investing in social relationships, particularly through relational closeness and collective prosperity as a means of receiving and sharing supply chain risk information in the sample firms. Although the findings of this study are only generalised to the sample, the findings could be insightful to multinational firms operating or expanding their supply chain to Nigeria on the need to enhance relational closeness and collective prosperity for supply chain risk information sharing. In light of the findings of this study, limitations and areas for future research were outlined.
Advisor / supervisor
  • Whitfield, Ian
Resource Type
DOI
Date Created
  • 2020
Former identifier
  • 9912922291602996

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