High product return rates are an increasingly pressing challenge for many e-retailers around the world. To address this problem, this paper offers a new perspective by focusing on the critical moment of the package-opening process. Going beyond previous research, which has primarily focused on...

Discrete choice experiments have emerged as the state-of-the-art method for measuring preferences, but they are mostly used in cross-sectional studies. In seeking to make them applicable for longitudinal studies, our study addresses two common challenges: working with different respondents and...

Companies often rely on customer feedback to build and improve their business. Customers, in turn, are expected to (i) fill in customer feedback surveys (participation) and (ii) provide accurate responses (performance). To encourage active participation and ensure accurate responses, companies...

In the emerging business of online lead generation, many conversational touchpoints have moved to the online space. These companies capture leads, sell them to partners, and often generate millions of revenue in the process. We abstract this novel digital business model in a framework, derive...

Der Aufenthalt im stationären Handel ist häufig kurz, nur Bruchteile des Layouts werden besucht und dies mündet in ungenutztem Konversionspotenzial. Das wachsende Online-Geschäft verschärft den Bedarf nach stationärer Effizienz. In diesem Spannungsfeld systematisiert der Beitrag die...

Our study applies empirical scrutiny to the network effects of a leading European online dating platform. While one might expect equal gender representation on such a platform to yield the best user experience and the highest revenue per user, our analysis shows that the platform requires only...

Network analytical metrics often seek to capture the structural dimension of social capital, but such data collections using traditional social research tools often suffer from biases like interviewer effects and are usually only suitable to study small groups of participants. Digital sources of...

Using experimental data from a comprehensive field study, we explore the causal eects of algorithmic discrimination on economic eciency and social welfare. We harness economic, game-theoretic, and state-of-the-art machine learning concepts allowing us to overcome the central challenge of missing...

The possibility to investigate the impact of news on stock prices has observed a strong evolution thanks to the recent use of natural language processing (NLP) in finance and economics. In this paper, we investigate COVID-19 news, elaborated with the "Natural Language Toolkit" that uses machine...

Advances in Machine Learning (ML) led organizations to increasingly implement predictive decision aids intended to improve employees' decision-making performance. While such systems improve organizational efficiency in many contexts, they might be a double-edged sword when there is the danger of...