Eindhoven University of Technology is looking for a PhD candidate with a background in Econometrics, Quantitative Marketing, Operations Management, Industrial Engineering, or a related field, interested in empirical field research on the interface of Marketing and Operations Management.

Organization
Eindhoven University of Technology is one of the world's leading research universities (ranked by the Times Higher Education Supplement) and is particularly well known for its joint research with industry (ranked number one worldwide by the Centre for Science and Technology Studies). The Department of Industrial Engineering & Innovation Sciences (IE&IS) of Eindhoven University of Technology is one of the longest-established engineering schools in Europe, with a strong presence in the international research and education community, especially in the fields of Operations Management and Innovation Management, which are at the core of the undergraduate BSc program. The graduate programs (MSc and PhD) in Operations Management & Logistics and Innovation Management attract top-level students from all over the world. Researchers are a member of the Beta research school.

Group
The PhD candidate will be located in the Innovation, Technology Entrepreneurship & Marketing (ITEM) group, and will collaborate closely with the Operations, Planning, Accounting and Control (OPAC) group. Both the ITEM and OPAC groups are part of the School of Industrial Engineering of the department IE&IS. The ITEM group focusses on managing innovation processes and new product development, including marketing of new products and marketing analytics. The OPAC group focusses on the control of operational processes, which can be related to manufacturing systems, distribution, transportation, warehousing, retail, healthcare, public transportation and service processes such as equipment maintenance.

Short description of the PhD Project
'Learning about Customers: Demand Implications of Logistics-Related Decision-Making in B2B'

The PhD candidate will do research in the domain of the marketing-operations interface, studying data-driven tools to optimize business processes for better customer relationships in a business-to-business (B2B) context. In B2B exchanges, customers are more likely to buy from suppliers who know them well and consistently provide good service. Yet, when planners optimize the operations with a focus on cost-reduction, they risk overlooking the importance of building long-term relationships with their customers. These relationships critically depend on learning about the customer's preferences, priorities, and service expectations. While building strong customer relationships in a B2B context has traditionally been the salespeople's responsibility, AI developments now open the possibility for AI-based learning about customers by operational planners.

AI-based learning about customers in a B2B setting is complex though, because each customer has their own needs and preferences, leading to highly customized offerings. These customized offerings often include agreements on critical logistics-related decisions such as lead times, delivery, and maintenance planning. In this setting, close contact between the people from sales and operations - i.e., a strong marketing-operations interface - benefits the customer relationship. Yet as information on customers is embedded both in IT systems (e.g., CRM systems) and people (e.g., salespersons), this is a domain where B2B firms can benefit greatly from AI. This PhD project thus studies on how AI can help planners tailor their operations to better serve customer needs.

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).

This position is part of the AI Planner of the Future Program (https://escf.nl/ai-planner-of-the-future/), a collaboration between the European Supply Chain Forum (ESCF) and the Eindhoven Artificial Intelligence Systems Institute (EAISI) The PhD candidate will benefit from the strong industry relationships of the supervisory team and both institutes (see www.escf.nl and https://www.tue.nl/en/research/institutes/eindhoven-artificial-intelligence-systems-institute/), which will prove important for access to data as well as practical relevance of the research.

Job description
You, as a successful applicant, will perform the research project outlined above in an international team. The research will be concluded with a PhD thesis. A small teaching load is part of the job.

• You have a Master's degree in Econometrics, Quantitative Marketing, Operations Management, Industrial Engineering, or a related field.
• You have a strong affinity with interdisciplinary research, as well as collaboration with industry.
• Strong analytical skills, demonstrated competences for quantitative modeling, knowledge of time series econometrics and machine learning.
• Potential and ambition to become a high-level management scholar.
• You are able to work on a challenging topic that has both basic and applied research aspects.
• Your verbal and written communication skills are excellent as is your proficiency in English and your ability to collaborate in an international setting.

• 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.