This thesis addresses the unresolved issues of responsibility and accountability in autonomous vehicle (AV) development, advocating for human-centred approaches to enhance trustworthiness. While AVs hold the potential for improved safety, mobility, and environmental impact, poorly designed algorithms pose risks, leading to public distrust. Trust research focuses on technology-related aspects but overlooks trust within broader social and cultural contexts. Efforts are underway to understand algorithm design practices, acknowledging their potential unintended consequences. For example, Baumer (2017) advocates human-centred algorithm design (HCAD) to align with user perspectives and reduce risks. HCAD incorporates theoretical, participatory, and speculative approaches, emphasising user and stakeholder engagement. This aligns with broader calls for prioritising societal considerations in technology development (Stilgoe, 2013). The research in this thesis responds to these calls by integrating theories on trust and trustworthiness, autonomous vehicle development, and human-centred approaches in empirical investigations guided by the following research question: “How can human-centred approaches support the development of trustworthy intelligent vehicle technology?” This thesis approaches the question through design ethnography to ground the explorations in people’s real-life routines, practices and anticipations and demonstrate how design ethnographic techniques can infuse AV development with human-centred understandings of people’s trust in AVs. The studies reported in this thesis include a) interviews and participatory observations of algorithm designers, b) interviews and probing with residents, and c) staging collaborative, reflective practice through the design ethnographic materials and co-creation with citizens, city, academic and industry stakeholders, including AV algorithm designers. 

Through these empirical explorations, this thesis suggests an answer to the research question by coining a novel and timely framework for intelligent vehicle development: trustworthy algorithm design (TAD). TAD demonstrates trustworthiness as an ongoing process, not just a measurable outcome from human-technology interactions. It calls to consider autonomous vehicle algorithms as construed through a network of stakeholders, practices, and technologies and, therefore, defines trustworthy algorithm design as a continuous collaborative learning and evolvement process of different disciplines and sectors. Furthermore, the TAD framework suggests that for autonomous vehicle algorithm design to be trustworthy, it must be responsive, interventional, intentional and transdisciplinary. 

The TAD framework integrates ideas and strategies from different well-known trajectories of research in the field of responsible and human-centred technology development: Human-Centred Algorithm Design (Baumer, 2017), algorithms as culture (Seaver, 2017) and Responsible Innovation (Stilgoe et al., 2013). The thesis contributes to this field by empirically investigating how this integrated framework helps expand existing understandings of interactional trust in intelligent technologies and include the relevance of participatory processes of trustworthiness and how these processes are nurtured through cross-sector co-learning and design ethnographic materials.

This thesis presents work conducted in the domain of sequential decision-making in general and Bandit problems in particular, tackling challenges from a practical and theoretical perspective, framed in the contexts of mobile Health. The early stages of this work have been conducted in the context of the project ``improving Medication Adherence through Person-Centred Care and Adaptive Interventions'' (iMedA) which aims to provide personalized adaptive interventions to hypertensive patients, supporting them in managing their medication regimen. The focus lies on inadequate medication adherence (MA), a pervasive issue where patients do not take their medication as instructed by their physician. The selection of individuals for intervention through secondary database analysis on Electronic Health Records (EHRs) was a key challenge and is addressed through in-depth analysis of common adherence measures, development of prediction models for MA, and discussions on limitations of such approaches for analyzing MA. Providing personalized adaptive interventions is framed in several bandit settings and addresses the challenge of delivering relevant interventions in environments where contextual information is unreliable and full of noise. Furthermore, the need for good initial policies is explored and improved in the latent-bandits setting, utilizing prior collected data to optimal selection the best intervention at every decision point. As the final concluding work, this thesis elaborates on the need for privacy and explores different privatization techniques in the form of noise-additive strategies using a realistic recommendation scenario.         

The contributions of the thesis can be summarised as follows: (1) Highlighting the issues encountered in measuring MA through secondary database analysis and providing recommendations to address these issues, (2) Investigating machine learning models developed using EHRs for MA prediction and extraction of common refilling patterns through EHRs, (3) formal problem definition for a novel contextual bandit setting with context uncertainty commonly encountered in Mobile Health and development of an algorithm designed for such environments. (4) Algorithmic improvements, equipping the agent with information-gathering capabilities for active action selection in the latent bandit setting, and (5) exploring important privacy aspects using a realistic recommender scenario.   

To save the planet from previous devastating corporate actions, corporations have enormous responsibilities toward the environment, economy and society. Implementing corporate sustainability practices through establishing effective governance mechanisms can be considered a transformative initiative with potential implications for social and green innovation. Social and green innovation thus shifts companies’ focus from for-profit objectives to the creation of mutual benefit and shared values.

Over the past four decades, extensive academic research has been conducted on the topic of corporate sustainability and financial performance. Therefore, conducting research on a similar topic might appear to the reader to be carrying coal to Newcastle. However, the aim of this thesis is not to reproduce previous studies but rather to address the following research question:  

What is the nexus between corporate sustainability and financial performance? 

This thesis identifies that previous literature has produced blended results when explaining the nexus between corporate sustainability and financial performance; they have asserted that firms are solely responsible for sustainability activities and thus financial performance. In this regard, previous literature has argued for institutional pressure and legitimacy requirements to shape corporate behavior. However, I contradict the views of previous scholars and argue that power distance and hierarchy always hamper the relationship. I further posit that corporations are not solely responsible for sustainability activities and thus financial performance. Rather, the nexus between corporate sustainability and financial performance is transformed, modified, and shaped through an interaction of the trajectories of multiple actors, an interaction that I was able to capture through the multi-theoretical approach. In this regard, I propose a comprehensive framework, that is effective under a macro business ecosystem. With this framework, companies that prioritize sustainability strategies would eventually ensure financial performance but after a time lag. In contrast, companies that engage in greenwashing and selfies will always achieve misleading outcomes.

The appended articles further examine the nexus between corporate sustainability and financial performance empirically using data from European countries by applying several static and dynamic econometric models under different time spans. The overall empirical result suggests that corporate sustainability practices have a positive impact on financial performance but with a time lag. However, in order to ensure durable long-term corporate sustainability practices, the macro and micro business environments – a network governance relationship – play a crucial role. The consistent and empirically robust results reveal the multiple trajectories of the nexus between corporate sustainability and financial performance. Therefore, the thesis disseminates key messages to policymakers and practitioners about the importance of an effective network governance mechanism.