Exploring the social sustainability implications of autonomous vehicle adoption in supply chains

Adopting autonomous vehicles (AVs) in supply chains has shown significant potential for economic and environmental benefits, however, they are still not widely deployed in supply chains. In order to gain social approval for wider AV adoption in supply chains, it is crucial to understand the social implications. Currently, there is a lack of comprehensive discussion about the social impacts of AV adoption, and how to improve the social sustainability performance in this scenario. Therefore, this thesis aims to explore the social impacts and social sustainability aspects of deploying AVs in supply chains, and the actions organisations enact to improve social sustainability performance and hence achieve wider social approval for adopting AVs in supply chains. Using the paper- based structure, this thesis comprises three interconnected papers which collectively fulfil this overall research aim: the first paper systematically reviews the literature in this research domain, and papers two and three present empirical studies that discuss supply chain social sustainability (SCSS) implications and the actions needed to improve the SCSS performance of AV adoption in supply chains. Paper one titled “Exploring the Social Impacts of Autonomous Vehicle adoption in Supply Chains: a systematic literature review” aims to identify the positive and negative social impacts of AV adoption in supply chains as well as the actions taken by organisations that address the impacts enabling wider AV adoption in supply chains based on a systematic literature review (SLR). Through reviewing 58 identified papers, this paper identified 13 positive and 7 negative social impacts of AV adoption in the supply chain. Based on these impacts, a conceptual model categorising the social impacts under six context-specific SCSS indicators that are derived from seminal social sustainability literature is formed to measure the social sustainability performance of AV adoption in supply chains in aspects including Health and safety, customer satisfaction, employment, transparency, diversity and equality, and welfare. Stakeholder as an essential element in analysing SCSS received limited focus in this context, which serves as a research gap for the second paper to fill. In addition, this paper identifies 20 suggested actions for organisations to enact for wider AV adoption. These actions are synthesised into four groups including pilot experiments, regulation improvement, chain-wide considerations, and education, promotion, and training. However, wider AV adoption requires wide social approval, which requires the social impacts to be addressed for improved SCSS performance. The actions are mentioned to facilitate wider AV adoption, but the existing literature does not clarify how to address the social implications of achieving wider AV adoption in supply chains. This means that the actions taken by organisations to address social implications are currently missing. Therefore, the actions organisations employ to address social impacts for wider AV adoption serve as the research gap for the third paper to fill. Paper two titled “Investigating the Social Sustainability of Autonomous Vehicle Adoption in Supply Chains: A Delphi Study” refines the social implications identified from the literature, and discusses stakeholder roles in the AV adoption context. Based on a three-round Delphi study with 39 experts, 19 positive and 15 negative social impacts are identified and their importance is ranked. In addition to the existing six identified indicators, “Reputation” is recognised, extending the concept of SCSS to the AV adoption context. This study also identifies 9 internal and 17 external stakeholders and evaluates the degree to which they affect or are affected by AV adoption in supply chains. This finding fulfils the first research gap of this thesis. Paper three titled “Improving Supply Chain Social Sustainability in the Autonomous Vehicle adoption context: A Delphi study with expert interviews” empirically investigates the actions that organisations take to address the social impacts of AV adoption in supply chains. The three-round Delphi study suggests eight categories of actions, which are further validated through 14 follow-up interviews to evaluate the key SCSS indicators these actions address. Identifying these actions fills the second research gap of this thesis. To understand how the organisations at various stages of AV adoption act to improve SCSS performance, this paper adopts the Diffusion of Innovations (DOI) theory to align the action categories with the organisational innovation process. This theory structures the actions on the basis of the AV adoption stages of the organisations in a logical sequence. The eight categories of actions provide organisations at various innovation adoption levels with an action plan to address the social impacts of AV adoption to improve their SCSS performance. This thesis contributes to knowledge regarding SCSS concepts through an in- depth investigation of context-specific SCSS indicators and actions for organisations to enact to improve SCSS performance. It defines the SCSS of AV adoption in supply chains with a conceptual framework, highlights the degree of influence of internal and external stakeholders in this context, and defines and evaluates the actions that address the social impacts for improved SCSS performance in the AV adoption context. This thesis provides a novel use of the DOI theory by tailoring the Innovation Process (IP) model with the identified action categories that apply to the AV adoption context, a continuous improvement cycle, and the inclusion of the internal/external stakeholders that enact the actions to improve SCSS. This thesis contributes to practice by offering an overview of social issues and a structured action plan to address these issues to improve SCSS performance when adopting AVs in supply chains. First, the identified social impacts and stakeholders support organisations in the development of social indices for the performance measurement of their operations when adopting AVs. Then, the action plan guides organisations to develop tailored business models to improve SCSS performance when adopting AVs. Regulators can use the action plan as a trail of evidence to check whether the organisations achieve SCSS performance improvement in the AV adoption context by actually implementing the actions or not.