Marketing ZFP – Journal of Research and Management publishes four issues and 16-20 peer-reviewed articles per year. As subscriber you find fulltext access (PDF) and search function to the complete archive of all issues on elibrary.vahlen.de.
Please find detailed information on the current issues below:
ISSUE 1/2025
The Role of Regulative Institutions in the Effects of Social, Environmental, and Economic CSR Dimensions across Nations
Lukas Zimmer and Bernhard Swoboda
Multinational corporations (MNCs) implement corporate social responsibility (CSR) initiatives in different regulative environments to attract consumers internationally. However, while CSR in general impacts consumer behavior across nations, it is unclear why and how perceptions of social, environmental, and economic CSR dimensions engage consumers in certain countries but not in other countries. The authors address this research area by referring to theoretical rationales and empirically studying the impacts of CSR dimensions on customer engagement behavior across 26 countries. They aim to contribute to our knowledge of how national institutions, especially important regulative institutions, reinforce or reduce dimensional effects, which is relevant for MNCs and public stakeholders. Using multilevel structural equation modeling, this study shows different and surprising strengths of CSR dimensions for consumer engagement and positive and negative continuous moderations of regulative institutions. The findings provide direct suggestions for MNCs and public stakeholders interested in multidimensional CSR effects across countries. (->to the Executive Summary)
Up- and Cross-selling to Repeat Customers: Empirical Evidence from Optical Retail
Niklas Nagel
By examining repeat purchases, we study the effect of customer loyalty on the ability to up-sell. Using an extensive dataset from optical retail including the sales activities of more than 410 opticians over 20 years, we track and analyze customer purchases using catalogue and invoice prices, depth of discount and gross profit. We find that the first repeat purchase results in deeper discounts and lower prices, thus decreasing the gross profit. In contrast, the subsequent repeat purchases allow retailers to up-sell customers by shifting them towards products with higher prices and profits. Additional purchases deepen the discount at a constant rate and the other variables show decreasing positive marginal effects. Finally, our results suggest that the effect of repeat purchases on discount depth varies between regular and cross-selling activities, with deeper marginal increases to discount for products sold through cross-selling. (->to the Executive Summary)
Sentiment Analysis in Marketing – From Fundamentals to State-of-the-art
Andreas Karasenko
Sentiment Analysis (SA) has found widespread success in marketing. Marketing scholars and practitioners have used SA to identify pain points, user requirements and issues using freely available online customer reviews from shopping websites, or user generated content from online blogs. These can then be used to improve products or services, adjust marketing strategies, and react ad hoc to new issues using automated decision-making pipelines, or use interpretability frameworks to understand the reasons behind sentiment. Despite this potential, research into SA is fragmented, oftentimes lacking a formal pipeline for their empirical evaluations and model selection. Similarly, model comparisons that aim to guide researchers in their model selection often focus on specific aspects and don’t account for current developments in natural language processing. From this background this paper first provides a SA pipeline, showing all common steps involved in SA. We then validate this pipeline in a case study by conducting a systematic model comparison of 12 machine learning, deep learning transfer learning, and few-shot learning models across 12 diverse user generated review datasets. We then use two popular interpretability frameworks to show, how the classifications of black-box models can be interpreted. Based on these results, as well as the strengths and weaknesses of the evaluated models, we derive actionable and practical guidelines for model selection while accounting for multiple key ex-ante considerations. To facilitate the model selection process of researchers we provide readily available Python codes for the complete case study. (->to the Executive Summary)