Off to "Holi-Work"

Let’s come together on July 4 for a convivial moment to celebrate the end of the year and the start of the holidays!

We’re organizing a shared lunch, and the menu will be made up of dishes prepared by all of you. Whether it’s a starter, main course, or dessert – we can’t wait to taste your homemade specialties and discover your hidden culinary talents!

To help us plan better, please complete the form by 27 June, indicating what dish you’ll be bringing.

Thank you in advance! We are looking forward to celebrating together!

Public thesis defense of Sabrina Courtois

Learning and practicing sustainability collectively: An ethnographic study of a sustainability community of practice of executives

Public thesis defense of Antoine Juquelier

Digital Marketing, customer experience, service research, artificial intelligence, human-AI interaction 

Thesis supervisors: Ingrid Poncin, Simon Hazée

Customer experience in interaction with artificial intelligence According to Statista (2021), 21% of businesses worldwide already integrated artificial intelligence (AI) to their service activities (e.g., chatbots, virtual assistants, service robots). The market for AI interfaces is projected to grow from $12.9 billion in 2019 to $41.5 billion by 2027 (Fortune Business Insights, 2020). In this context, customers increasingly interact with organizations through various touchpoints and channels powered by AI interfaces (Hoyer et al. 2020). This shift from human-to-human to human-to-technology interactions is likely to dramatically influence the customer experience (Bolton et al. 2018, Davenport et al. 2020, Larivière et al. 2017). Considered as a unique source of competitive advantage, understanding and managing customer experience along the customer journey has become an imperative for organizations (Lemon & Verhoef 2016). However, research on how customers respond to and experience interactions with AI is at an early stage, making it a top research priority according to the Marketing Science Institute (2020). Customer experience is by its very nature multidimensional, including emotional and social dimensions (De Keyser et al. 2020). Studies examining customer experience with AI-based interfaces however mainly use a rational-cognitive perspective (Mariani et al. 2022). While the latter provide useful and relevant insights, we argue that they do not capture the complexities of customer experiences with AI interfaces. Responding to calls for research using a more fine-grained experiential perspective (Ameen et al. 2021; De Keyser & Kunz, 2022, Puntoni et al. 2021), this research aims to provide a better understanding of the processes in action by considering the multiple dimensions (e.g., affective, social) of customer experience as well as relevant contextual elements that may dramatically influence customer experience. By doing so, this research aims to make theoretical contributions to the fields of Customer Experience, human-machine interaction, and service research. It also aims to make managerial contributions for businesses and organizations.

Research Seminar: Datagotchi: A Gamified Approach to Predicting Political Choices and Beyond

Datagotchi is a gamified and knowledge transfer tool that aims at guessing users’ vote choice based on their lifestyle and sociodemographic characteristics. Through an interactive widget, the app also allows users to learn about the effects of each key determinant on political preferences. Datagotchi was launched in partnership with the Canadian Press during the 2022 Quebec election and with Léger during the 2025 Canada election, received extensive media coverage, and collected responses from over 220 000 users. Discussions are underway to develop versions of Datagotchi in other electoral contexts, including for the next Canadian, Japanese, and Indonesian national elections. The project also received funding to apply the tool in other areas like health and literature.

Yannick Dufresne Bio

Yannick Dufresne is Leadership Chair in the Teaching of Digital Social Sciences, Director of the Centre d’analyse des politiques publiques (CAPP) and Full Professor of Political Science at Université Laval. He specializes in the study of public opinion, political communication, and elections. Yannick has also contributed since 2011 to the design and development of several large-scale engagement and data collection applications.

Informal research seminar by Min Shuai

The factors that affect the intention to implement crowdsourcing ideas—from company level perspective

Min Shuai, Louvain Research Institute in Management and Organizations
Benoît Gailly, Louvain Research Institute in Management and Organizations
Nadia Steils, University of Liege

Summary

Crowdsourcing has emerged as a powerful open innovation model, enabling firms to tap into global knowledge and creativity at reduced costs. However, despite its potential, many crowdsourcing initiatives fail to translate submitted ideas into implemented solutions, leading to stakeholder dissatisfaction and distrust. While prior research has examined crowdsourcing success from external (crowd and idea-level) perspectives, internal firm-level factors—particularly corporate strategy and idea perception—remain underexplored. This study addresses this gap by investigating how companies' strategic positioning of crowdsourcing (as either an inspirational marketing tool or a necessary innovation driver) and their perceptions of idea durability, reliability, and quality jointly influence implementation intentions. Through a survey of 804 Moroccan marketing managers and cluster analysis, we reveal how distinct configurations of strategy and perception shape firms' willingness to act on crowdsourced ideas. Our findings contribute to crowdsourcing literature by (1) conceptualizing two strategic approaches to crowdsourcing adoption and (2) demonstrating their interplay with idea evaluation in implementation decisions. The study offers practical insights for managers seeking to align crowdsourcing initiatives with organizational goals while mitigating implementation failures.