This project conducts a socio-technical analysis of how the intersection of two innovations - micromobility and AI-driven last-mile delivery - could lead to more sustainable urban logistics.
It identifies opportunities for synergies, but also critically interrogates claims and practices around AI and sustainability. Active micromobility such as cargo-ebikes will be a particular focus.

The specific research aims are to:

• Create a conceptual framework for analysing the intersection of AI and micromobility, drawing on mobility studies, innovation/transition studies, and critical data studies
• Conduct a Multi-Level perspective (MLP) and Strategic Niche Management (SNM) analysis of last-mile logistics in terms of a) AI and b) micromobility and c) their intersection - in the Dutch and EU context
• Analyse how mode-related variation in industry data practices informs or prevents AI approaches (e.g. training data for ML) and how this relates to mobility justice
• Critically assess the potential benefits and downsides of AI-use for micromobility in terms of sustainability transitions (considering both the mobility and the IT side)
• Create industry and policy recommendations for the use of AI in the context of micromobility

Last-mile logistics have a significant carbon footprint, driven up, among others, by the increase
in online shopping and associated (van) deliveries. Micromobility and AI are both discussed as promising solutions to reducing urban emissions (e.g. 30% of trips could be replaced by cargo
e-bike; optimizing routes). This project contributes to understanding how these two innovation niches - micromobility and AI-logistics - can develop in relation to the current, carbon-intensive regime of last-mile logistics. Amongst other issues, this project examines if there is a danger of excluding micromobility from AI approaches due to a lack of suitable micromobility datasets, explores what kind of (data) practices could counteract this, and links this to debates on mobility and data justice.

Scholarship on AI for last-mile delivery and sustainable supply chains does not consider micromobility sufficiently and largely lacks a socio-technical perspective. This is problematic because AI is not just a technology, rather, it is co-produced by human, societal and economic contexts. This project will provide such a socio-technical perspective. It also contributes more generally to research on AI and sustainability, including critical scholarship on the planetary costs of AI.

Conceptually, this project draws on Mobility Studies, paying attention to the global and local flows of humans, objects, ideas and data. Specifically, it combines work on cargomobilities, urban mobilities, (smart) cycling/velomobility and mobility justice. These are operationalized in conjunction with Critical Data Studies approaches, including data justice, to analyse the social, economic, political and entanglements around data. This enables to ask, for example, if and how excluding micromobility from AI-driven logistics might marginalize this sustainability-relevant innovation. This project also builds on Transition Studies, Multi-Level perspective and Strategic Niche Management to examine both micromobility and AI-driven logistics as niche developments that may lead to structural and transformative change of the current logistics regime. This enables, for example, an exploration of how these innovations are, or should be nurtured and protected.

This is a qualitative, socio-technical study. Methods include technology analysis, Multi-Level perspective (MLP) analysis, Strategic Niche Management (SNM) analysis, case studies, expert interviews, policy reviews and stakeholder mapping. In addition to academic outputs, the project will also contribute industry and policy recommendations.

As a successful applicant, you will perform the PhD project outlined above. The research will be concluded with a PhD thesis. You will be supervised by dr. Frauke Behrendt and prof.dr. Floor Alkemade. A small teaching load is part of the job.

Academic and Research Environment

The above PhD project is embedded in the Department of Industrial Engineering and Innovation Sciences (IE&IS) of Eindhoven University of Technology (TU/e). TU/e is one of the world's leading research universities (ranked by the Times Higher Education Supplement). It is in particular well‐known for its joint research with industry (ranked number one worldwide by the Centre for Science and Technology Studies).

Within the Department IE&IS you will be affiliated with the research group Technology, Innovation & Society (TIS). The TIS group of the School of Innovation Sciences is an ambitious, international group. Our research focuses on understanding the development and use of technology in a societal context. Other current mobility research includes projects on smart cycling, electric mobility and cycling cities. Our staff teaches in the BSc program 'Sustainable Innovation', and the MSc program 'Innovation Sciences', as well as in university-wide programs for engineering students.

The department of IE&IS has a strong national and international reputation for both basic research in the academic community and applied research with industry and policy. You will have the opportunity to benefit from that environment and to contribute to the ongoing research.

This PhD project is part of the AI PLANNER OF THE FUTURE program. This ambitious research program is hosted by the TU/e-based Department of Industrial Engineering & Innovation Sciences and is supported by the European Supply Chain Forum, Department of Industrial Engineering & Innovation Sciences, the Eindhoven Artificial Intelligence Systems Institute, and the Logistics Community Brabant. The program connects to the different communities, moonshots strategic agendas and the themes of each of these supporting partners. It combines 25 researchers, 10 PhD students and over 50 Bachelor and Master students, for the coming five years (2021-2026). This AI PLANNER OF THE FUTURE program considers the explicit intertwining of technical and human elements in the context of AI planning for supply chains and logistics, considering all relevant performance indicators (people, profit, and the planet).

The AI PLANNER OF THE FUTURE program
This ambitious research program is hosted by the TU/e-based Department of Industrial Engineering & Innovation Sciences and is supported by the European Supply Chain Forum, Department of Industrial Engineering & Innovation Sciences, the Eindhoven Artificial Intelligence Systems Institute, and the Logistics Community Brabant. The program connects to the different communities, moonshots strategic agendas and the themes of each of these supporting partners. It combines 25 researchers, 10 PhD students and over 50 Bachelor and Master students, for the coming five years (2021-2026). This AI PLANNER OF THE FUTURE program considers the explicit intertwining of technical and human elements in the context of
AI planning for supply chains and logistics, considering all relevant performance indicators
(people, profit, and the planet).

The following 10 individual PhD projects are embedded in this program. We are looking for
PhD candidates from a broad range of disciplines ranging from operations research and management, supply chain management, statistics, ethics, cognivite psychology, artificial intelligence, etc.

Project 1: Learning about Customers: Demand Implications of Logistics-Related Decision-Making in B2B, Gelper, Mutlu, Langerak https://jobs.tue.nl/en/vacancy/phd-on-marketingoperations-interface-878156.html

Project 2: Context matters: optimizing shared decision making in real-world forecasting and inventory management, Le Blanc, van de Calseyde, Ulfert  https://jobs.tue.nl/en/vacancy/phd-on-humanai-collaboration-at-work-878192.html

Project 3: AI-Based Replenishment and Order Fulfillment Strategies for Omnichannel Supply Chains, Atan , Schrotenboer, Van Woensel  https://jobs.tue.nl/en/vacancy/phd-on-aibased-replenishment-order-fulfillment-strategies-for-supply-chains-878193.html

Project 4: Robust data-driven sustainable food supply chain, Marandi, Rohmer, Van Woensel  https://jobs.tue.nl/en/vacancy/phd-in-%E2%80%98datadriven-approaches-towards-robust-and-sustainable-cold-chains%E2%80%99-878195.html

Project 5: Digital Twins: An ingenious AI companion or an evil twin?, Raassens, Schepers,
Van Woensel  https://jobs.tue.nl/en/vacancy/phd-in-ai-and-digital-twinning-878197.html

Project 6: AI for sustainable last-mile delivery by micromobility: a socio-technical perspective, Behrendt, Alkemade  AI for sustainable last-mile delivery by micromobility

Project 7 (Extra: 0.5 EAISI startup package + 0.5 ESCF): Data-driven Optimization using Digital Twins for Sustainable Last-Mile Delivery, Zhang, Bliek, Van Woensel
https://jobs.tue.nl/en/vacancy/phd-on-datadriven-optimization-for-sustainable-lastmile-delivery-878199.html

Project 8: Online Supply Chain Planning, Dijkman, Van Jaarsveld
https://jobs.tue.nl/en/vacancy/phd-in-information-systems-business-intelligence-878200.html

Project 9: From feared competitor to trusted companion: understanding and enhancing trust in AI over time, Snijder, Rooks, Willemsen  https://jobs.tue.nl/en/vacancy/phd-on-humanai-collaboration-in-the-workplace-trust-in-ai-over-time-878201.html

Project 10: Widening the frame: Rational choice beyond a given utility function, Müller 
https://jobs.tue.nl/en/vacancy/phd-on-%E2%80%9Cimproving-automated-rational-choice-through-metacognition%E2%80%9D-878202.html

We are looking for a Ph.D. candidate with a background in mobility studies, transport studies, urban studies, innovation sciences/studies, human geography, cultural geography, science and technology studies, planning, sustainability studies, or any other field with expertise relevant to the project. Ideal candidates are passionate about climate change and have an affinity with mobility studies and/or digital/data/AI aspects of society. Candidates should be interested in research that combines theoretical/conceptual work with practical and societal relevance.

The ideal student for this program will have a strong, demonstrated capacity to undertake advanced study, with a high level of accomplishment in their Master's level study. More specifically, PhD candidates:

• hold a relevant Master's degree (see above).
• are reliable, can work and deliver timely both independently and in a team, and have strong organisational skills and a pro-active work attitude
• are willing to collaborate closely with industry partners and with interdisciplinary research groups
• have strong analytical skills
• have the ability to work on a challenging topic that has both conceptual/theoretical and applied research aspects.
• Have proven excellent verbal and written communication skills.
• Have high proficiency in English

• A meaningful job in a dynamic and ambitious university with the possibility to present your work at international conferences.
• A full-time employment for four years, with an intermediate evaluation (go/no-go) after nine months.
• To develop your teaching skills, you will spend 10% of your employment on teaching tasks.
• To support you during your PhD and to prepare you for the rest of your career, you will make a Training and Supervision plan and you will have free access to a personal development program for PhD students (PROOF program).
• A gross monthly salary and benefits (such as a pension scheme, pregnancy and maternity leave, partially paid parental leave) in accordance with the Collective Labor Agreement for Dutch Universities.
• Additionally, an annual holiday allowance of 8% of the yearly salary, plus a year-end allowance of 8.3% of the annual salary.
• Should you come from abroad and comply with certain conditions, you can make use of the so-called '30% facility', which permits you not to pay tax on 30% of your salary.
• A broad package of fringe benefits, including an excellent technical infrastructure, moving expenses, and savings schemes.
• Family-friendly initiatives are in place, such as an international spouse program, and excellent on-campus children day care and sports facilities.