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By Dr Hendrik Reefke, and Dr Nicky Yates, 星空体育官网 School of Management

Innovation with a Social Focus

The rapid rise of autonomous vehicles (AVs) holds much promise for transforming logistics and supply chains in the future. From redefining transportation efficiency, to reducing emissions, and enabling 24/7 operations whilst increasing safety levels. This undoubtedly disruptive shift is not purely of a technical nature, but it will also have deep social implications. AV adoption raises tangible concerns across many areas including, employment, equity, safety, and data security. These issues, if left unmanaged, can create stakeholder resistance, harm communities, and damage organisational reputation. Hence, successful AV adoption requires more than investment in technology but also demands an intentional strategy that addresses the social dimensions of innovation.

Operationalisation through Social Sustainability Actions and Measures

Decision makers implementing AVs within their supply chain operations, not only need to manage the technical integration, but also need to consider the social implications of AV adoption. Our research combined the insights of domain experts from industry, consulting, academia, and government agencies through a combination of the Delphi method and expert interviews (Gu et al., 2025). We identify and validate a set of practical organisational actions that managers can implement to help mitigate social risks and amplify the social benefits of AV integration. These are grouped into eight action categories populated with specific, workable measures rated by experts for their importance and serving as a checklist for decision-makers. Overall, this model provides implementing managers with targeted strategies to effectively address the social implications of AV adoption in supply chains:

1. Real-world Experiments and Tests
   These actions focus on validating AV technologies through pilot trials, safety tests, and proof-of-concept implementations. They help demonstrate reliability and mitigate perceived risks.
2. Regulation Improvement
   This category emphasises refining legal frameworks to address safety, employment, and privacy concerns. It supports both enabling AV deployment and protecting the public interest.
3. Human Resource (HR) Management
   HR actions specifically target internal stakeholders. These include creating new roles, partnering with training providers, and supporting employee wellbeing to ensure workforce readiness.
4. Promotion
   This category addresses external stakeholder engagement. It involves raising awareness, sharing successful case studies, and clearly communicating the benefits of AVs to improve public trust and reduce resistance.
5. Communication and Stakeholder Involvement
   This category underscores the need for transparent communication with both internal and external stakeholders. It facilitates collective understanding, reduces misinformation, and strengthens stakeholder alignment.
6. Planning
   Planning actions support the strategic and operational integration of AVs into supply chains. They range from high-level governance and compliance frameworks to detailed scheduling and data integration for AV deployment.
7. Continuous Improvement
   Continuous improvement focuses on iterative enhancements in AV services, technology, and organisational structures. It includes feedback loops and lifecycle monitoring to adapt AV systems to evolving stakeholder needs.
8. Corporate Social Responsibility (CSR)
   CSR actions embed AV adoption within broader sustainability strategies. They involve setting CSR performance targets, applying social metrics, and maintaining ethical oversight at each supply chain node.

These eight categories form a comprehensive toolkit for managing the social implications of AVs. They not only address known challenges, such as job displacement and security, but also encourage organisations to pursue continuous and sustainable innovation.

To further support socially sustainable innovation and assist in the development of Corporate Social Responsibility plans and policies. The outcomes of the actions can be assessed against established indicators in the sustainability domain as shown in these examples:

Innovation Process Model and Roadmap for Social Sustainability

To further guide organisations in implementing AVs responsibly, our study offers a prescriptive model grounded in the Diffusion of Innovation (DOI) theory. This model offers practical guidance to help organisations to anticipate and plan for social concerns as well as capitalising on positive outcomes (Rogers, 2003).

Our model aligns the eight categories of social sustainability actions discussed above with the five stages of innovation adoption from DOI theory. Each phase of this adoption journey is matched with the appropriate action categories. Organisations can apply the model as a strategic planning tool, ensuring that each innovation adoption stage incorporates actions targeted specifically at social considerations. The action categories Communication and Stakeholder Involvement and Corporate Social Responsibility are important throughout the adoption process and so run across all five stages. The alignment between key innovation adoptions stages and the remaining six action categories are set out here:

1. Agenda and Knowledge: Raise internal awareness about AVs’ potential and their social implications through cross-functional communication.
2. Matching and Aligning: Engage stakeholders, such as unions, community leaders, policymakers, and employees, early using evidence and real-world pilots to build trust and alignment.
3. Defining and Structuring: Include ethical and social impact assessments in procurement and technology selection criteria.
4. Implementing and Clarifying: Innovation is put into use and targeted actions are rolled out, mapped directly to anticipated social impacts.
5. Confirmation and Routinising: The organisation seeks validation of their decisions and evaluates their effectiveness by iteratively capturing social performance using KPIs.

Organisations can leverage this model in three core ways. Firstly, it supports Structured Decision-Making as it serves as a planning and implementation tool, allowing leaders to assess risks, identify social gaps, and embed actions and responses at the right stage of innovation. This prevents reactive management and enables the building of stronger business cases for AV adoption. Secondly, the model emphasises Cross-Functional Integration since social sustainability actions require coordination across business functions such as human resources, logistics, compliance, IT, and marketing. The model supports interdepartmental collaboration by aligning actions with timelines and responsibilities. Thirdly, it encourages Metrics and Accountability so that organisations can track progress using social sustainability indicators in relation to innovation implementation. This data-driven approach supports transparency and improves reporting to stakeholders and regulators.

In combination the Innovation Process Model and Action Categories offer a practical roadmap for socially sustainable digital transformation in logistics.

Future-Proofing Supply Chains through Responsible Innovation Adoption

As supply chains evolve and the influence of automation and intelligent transport systems evidently increases, social sustainability can no longer be an afterthought. Our research provides grounded, actionable models that transform AV adoption into a socially conscious journey. The study fills a theoretical and practical gap by focusing on the often-overlooked social dimensions of digitalisation. It offers a structured framework to manage the potentially adverse social effects of AV adoption, such as job displacement, safety risks, and data privacy concerns.

We put forward a process-oriented view of digital transformation, highlighting the importance of aligning sustainability initiatives with the distinct stages of technology adoption. Organisations that internalise this framework will not only mitigate risk but can lead to a future in which technology and humans progress together.

References

Gu, C., Reefke, H., & Yates, N. (2025). Autonomous vehicle adoption and supply chain social sustainability: Delphi study and expert interviews. International Journal of Physical Distribution & Logistics Management, 55(3), 275-306.

Available at:

Rogers, E. (2003), Diffusion of Innovations, 5th ed., Simon and Schuster, New York, NY.