Publisher
source

Darius-Aurel Frank

7 months ago

PhD Scholarships: Decoding Danish Firm Innovativeness from the Consumer Perspective (Danish Innovation Index) Aarhus University in Denmark

Degree Level

PhD

Field of study

Computer Science

Funding

Available

Deadline

Sep 1, 2026

Country flag

Country

Denmark

University

Aarhus University

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Keywords

Computer Science
Psychology
Artificial Intelligence
Marketing
Business
Management
Monte Carlo Simulation
Environmental Sustainability
Big Data
Panel Data Analysis
Digital Innovation
Wellness
Statistics

About this position

Aarhus BSS Graduate School at Aarhus University is offering two three-year PhD scholarships within the research project “Decoding Danish Firm Innovativeness from the Consumer Perspective,” affiliated with the Danish Innovation Index (DII) at the PhD Programme Management. The positions are available from 1 September 2026 or as soon as possible thereafter. The project aims to explain how Danish firms achieve leadership in innovativeness as perceived by consumers, and to derive insights for innovation practice and theory. The research leverages the Danish Innovation Index database, which contains multi-year consumer perceptions across 20 industries and nearly 100 Danish companies. Empirical work may be complemented by additional data collection and causal designs, such as online experiments, and relevant methods including big data analysis, panel analysis, semantic analysis, and simulation, depending on the candidate’s methodological profile and project proposal.

Applicants may propose projects within one of two focus areas: Track A (Digital and commercial innovation, which should include emerging technologies such as artificial intelligence and spatial computing) or Track B (Responsible innovation, to be defined by the candidate and potentially relating to sustainability, diversity, equity and inclusion, well-being, or similar themes). The projects will be supervised by Associate Professor Darius-Aurel Frank, with co-supervision from Associate Professors Lina Fogt Jacobsen and Helle Alsted Søndergaard. The PhD projects will contribute to the overall research aim and are to be carried out as part of the research group, which is establishing the Danish Innovation Index as a research excellence group at the Department of Management.

The successful applicants are expected to have a relevant Master’s degree (such as management, marketing, innovation, psychology, data science, or a related social science discipline), documented interest in innovation research from a consumer perspective, strong analytical skills, and experience with quantitative methods (regression, multilevel modeling, structural equation modeling) is an advantage. Interest or experience with experimental, big data, and/or mixed methods research designs is preferred. Strong English communication skills and motivation to publish in high-quality journals and engage with stakeholders through dissemination activities are required. Applicants must include a project description outlining their intended PhD research within the frames of the overall project.

The Danish Innovation Index (DII), established in 2021, is a member of the Innovation Index Coalition (IIC), and a 3-6 month research stay at one of the IIC’s member institutions is expected. The Department of Management at Aarhus University is highly international and culturally diverse, with more than 160 academic staff and a broad range of disciplines within management. The department is accredited by AASCB, AMBA, and Equis, and is committed to high-quality research and teaching.

Funding for these PhD projects is provided by the Carlsberg Semper Ardens Accelerate grant, covering tuition and stipend for three years. The place of work is the Department of Management, Universitetsbyen 61, DK-8000 Aarhus C, Denmark. Applicants are encouraged to supply documentation of their academic ranking compared to peers. The enrolment happens in accordance with the Ministerial PhD Order and the terms stated in the Rules and Regulations for the PhD programmes at Aarhus BSS Graduate School.

For further information about the position, contact Associate Professor Darius-Aurel Frank at [email protected]. For application support, contact HR supporter Anna Bruun Pedersen at [email protected]. For more information about the Department of Management, visit http://mgmt.au.dk/. The application deadline is 1 September 2026.

To apply, submit your application via the Aarhus University online portal, including a project description and documentation of your academic ranking and qualifications. Refer to the application guide and rules for PhD education for detailed instructions.

Funding details

Available

What's required

Applicants must have a relevant Master’s degree (e.g., management, marketing, innovation, psychology, data science, or a related social science discipline). Documented interest in innovation research from a consumer perspective is required. Strong analytical skills and experience with quantitative methods (such as regression, multilevel modeling, structural equation modeling) are advantageous. Interest or experience with experimental, big data, and/or mixed methods research designs is preferred. Excellent English communication skills (written and spoken) and motivation to publish in high-quality journals and engage with stakeholders are expected. Applicants should include a project description outlining their intended research within the overall project. Documentation of academic ranking compared to peers is encouraged.

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Professors

Associate Professor at Aarhus University

University Name
Country flag

Denmark

Research Interests

Behavioral Economics

Artificial Intelligence

Consumer Psychology

Customer Engagement

Consumer Behavior

Associate Professor at Aarhus University

University Name
Country flag

Denmark

Research Interests

Management

Statistics

Panel Data Analysis

Business

Wellness

Associate Professor at Aarhus University

University Name
Country flag

Denmark

Research Interests

Statistics

Environmental Sustainability

Business

Panel Data Analysis

Computer Science