Nowadays, individuals interact with companies/institutions in different ways: over the telephone, on mobile devices, tablets, or through self-service machines. Depending on the system used, they make decisions orally (by speaking) or manually (e.g., by touch on a tablet). Surprisingly, scant attention has been paid to the possibility that merely changing the way individuals express decisions - here termed as expression modalities - might impact how and what kind of decisions they make. Yet, companies and government institutions frequently offer individuals innovative ways to express their decisions (e.g., voice control mode in a mobile banking app) possibly unaware that a change in modality might impact individuals decisions. The aim of my three projects is to understand differences between oral and manual expression modalities with the goal of deriving managerial implications and public policy recommendations. Predominantly (but not exclusively) utilizing experimental research, individuals will be asked to make decisions either orally or manually. Project 1 explores whether these different expression modalities will trigger fundamentally different decision-making processes. I propose that speaking prompts automatic, impulsive decisions while manual responding prompts cognitive, reasoned decisions. This difference has important - positive and negative - consequences for decisions that we make daily. In project 2, I explore the influence of utilizing oral or manual expression modality on financial decision making; in particular individuals? likelihood to save money. If speech triggers more automatic, impulsive decisions, this suggests that individuals are less likely to save money (= cognitive/reasoned decision) when using voice-controlled than touch-activated systems. Finally, project 3 fulfills the purpose to explore a positive consequence of orally expressed decisions: if speaking triggers automatic, intuitive decisions, I argue that it increases decision satisfaction with decisions that require intuition. The results of the projects will be insightful to guide various stakeholders (e.g., policy makers) in designing strategies to increase savings and decision satisfaction.

This research seeks to understand what makes consumers buy sustainable and healthy food options. It empirically studies grocery purchases of individual consumers over the past 2 decades, during which many of such food options were introduced. The research program will disentangle three forces on the formation of food preferences: (1) personal characteristics, (2) consumption history, and (3) marketing by retailers and manufacturers. It will empirically test to what extent preferences are formed or intrinsically present, and whether the marketing strategies of firms affect long-term preferences. These findings will next be used to propose policy to stimulate sustainable food choices.

Firms increasingly use various methods to involve external parties in innovation projects, along the stages of research, development, commercialization, and service delivery (through co-creation, supplier involvement, customer participation, open innovation, outsourcing, crowdsourcing, among other). With a focus on business markets, this research project will contribute both conceptually and empirically to the emerging literature in this domain. (a) Conceptually, first a classification of involvement methods is developed, which serves as a basis for a comprehensive study of the phenomenon of involving external parties. Second, involving multiple external parties turns innovation projects into small-scale networks, posing new challenges for project coordination and control. A typology of network control mechanisms is developed. (b) Empirically, the consecutive studies examine the consequences of implementing alternative involvement methods and network control mechanisms. To achieve this, a longitudinal survey, econometric analysis of secondary datasources, and experimental research will be conducted. The proposal consists of three sub-projects. In project 1, with a focus on the pre-commercialization stages of the innovation process, I examine the consequences of alternative methods of involving external parties on project outcomes and firm innovativeness. In project 2, I examine the involvement of external parties in commercialization and service delivery and its consequences in terms of end customer attitudes and behaviors. In project 3, I address the coordination and control consequences of having multiple parties involved in innovation projects and the resulting small-network nature of such projects. Network control mechanisms, rather than traditional dyadic (one-to-one) control mechanisms, are required to curb opportunism and promote positive behaviors in the innovation project. The combined studies provide a comprehensive and nuanced view on the multifaceted phenomenon of external party involvement in innovation projects. The proposed research may guide firms in shaping and controlling their innovation projects, and achieving the ultimate objective of providing superior value to their customers.

Price promotions like “buy-one-get-one-free” deals are abundant in grocery retailing and many households buy on promotion to save on groceries. Yet, price promotions are also often criticized for causing household food waste. Such criticism rests on the assumption that larger-than-usual purchases are excessive and, therefore, inherently wasteful. Yet, this logic has never been tested empirically. In this project, I combine unique household panel data covering all grocery purchases of a representative set of households with survey data on usage of products, including wasting. Together, these data will show whether price promotions are to blame for household food waste.

Online platform-based marketplaces are central to our internet experience, but they present unique challenges compared to traditional stores. A key issue is ensuring trust between buyers and sellers without physical product inspection. My research explores how platform policies influence consumer choices using big data. I apply advanced techniques like causal inference, econometrics, and natural language processing to analyze data from e-commerce clickstreams and user-generated content on platforms like Reddit and Goodreads. By identifying patterns, my work aims to enhance trust and efficiency in online marketplaces for all users.