Abstract Although Artificial Intelligence can offer significant business benefits, many consumers have negative perceptions of AI, leading to negative reactions when companies act ethically and disclose its use. Based on the pervasive example of content creation (e.g., via tools like ChatGPT), this research examines the potential for human-AI collaboration to preserve consumers' message credibility judgments and attitudes towards the company. The study compares two distinct forms of human-AI collaboration, namely AI-supported human authorship and human-controlled AI authorship, with traditional human authorship or full automation. Building on the compensatory control theory and the algorithm aversion concept, the study evaluates whether disclosing a high human input share (without explicit control) or human control over AI (with lower human input share) can mitigate negative consumer reactions. Moreover, this paper investigates the moderating role of consumers’ perceived morality of companies’ AI use. Results from two experiments in different contexts reveal that human-AI collaboration can alleviate negative consumer responses, but only when the collaboration indicates human control over AI. Furthermore, the effects of content authorship depend on consumers' moral acceptance of a company's AI use. AI authorship forms without human control lead to more negative consumer responses in case of low perceived morality (and no effects in case of high morality), whereas messages from AI with human control were not perceived differently to human authorship, irrespective of the morality level. These findings provide guidance for managers on how to effectively integrate human-AI collaboration into consumer-facing applications and advises to take consumers' ethical concerns into account.
Purpose This study is the first to examine consumer’s neural reaction to different merchandising communication strategies at the point-of-sale (PoS) by applying functional near-infrared spectroscopy (fNIRS). By doing so, the purpose of this study is to extend consumer neuroscience to retail and shopper research. Design/methodology/approach Two experiments were conducted in which 36 shoppers were exposed to a realistic grocery shopping scenario while their brain haemodynamics were measured using mobile fNIRS. Findings Results revealed that mobile fNIRS appears a valid method to study neural activation of the prefrontal cortex (PFC) in the field of “shopper neuroscience”. More precisely, results demonstrated that the orbitofrontal cortex (OFC) might be crucial for processing and predicting merchandising communication strategy effectiveness. Research limitations/implications This research gives evidence that certain regions of the PFC, in particular the OFC and the dorsolateral prefrontal cortex (dlPFC), are crucial to process and evaluate merchandising communication strategies. Practical implications The current work opens a promising new avenue for studying and understanding shopper’s behaviour. Mobile fNIRS enables marketing management to collect neural data from shoppers and analyse neural activity associated with real-life settings. Furthermore, based on a better understanding of shoppers’ perceptual processes of communication strategies, marketers can design more effective merchandising communication strategies. Originality/value The study is the first to implement the innovative, mobile neuroimaging method of fNIRS to a PoS setting. It, therefore, opens up the promising field of “shopper neuroscience”.
Building on Job Demands-Resources (JD-R) theory, a comprehensive model of the determinants of salesperson new product selling outcomes is proposed. Existing empirical support for the proposed model is then assessed through a detailed review of published empirical studies. The results of this comparative process reveal research is needed that: (1) explores important causal linkages implied by JD-R theory which have not been considered in previous research (e.g., new product selling demands--> burnout--> outcomes), (2) proceeds from a more robust understanding of the factors relevant to new product selling situations, including an expanded array of selling demands (e.g., balancing of new and old products), selling resources (e.g., customer orientation), and selling outcomes (e.g., customer satisfaction), and (3) employs growth (e.g., new product burnout growth) and multi-source (e.g., customer and salesperson perceptions) data to improve understanding of the determinants of new product selling outcomes. Aside from fully explicating these knowledge needs, this effort contributes to the literature by advancing a JD-R-based integrative framework for research in this domain, recasting new product selling as a multi-faceted job demand, and by presenting one of the first applications of JD-R theory within a sales context.
This chapter deals with the development of a model to assess the contribution of IT-based logistics solutions to sustainable logistics management. After introducing and explaining the pertinent concepts logistics management, IT-based logistics solutions and sustainability, certain conflict areas between IT and sustainability are discussed to gather relevant insights for the development of the assessment model. The balanced scorecard approach and the concept of maturity models are the main additions to determine the assessment model. The assessment model is embraced by a procedure model which includes guiding principles and success factors to look at before the assessment is executed and methods for navigating within the maturity model, managerial implications and aspects concerning the strategic alignment as subsequent discussion points. The chapter concludes with an outlook into further research and practical application as well as a conclusion.
