Purpose The purpose of this paper is to investigate whether, in the context of a cross-border acquisition, the acquirer’s country image (CI) could moderate the relationship between the acquirer’s corporate reputation (CR) and consumers’ repurchase intentions towards the products of the post-acquisition target. Design/methodology/approach The authors examined the roles played by the acquirer’s CR and the acquirer’s CI on consumer behaviour by considering an Italian target firm with a high reputation and comparing four foreign acquiring firms with different combinations of CR (poor/good) and CI (high/low). Findings It was found that both CR and CI have a significant impact on Italian consumers’ intention to repurchase the products of the post-acquisition target. Furthermore, the results show a greater increase in consumers’ repurchase intentions when a good reputation of the acquirer is paired with a high CI for the acquirer, but a high CI cannot compensate for a poor CR. Originality/value The research investigates, in the context of cross-border acquisitions (CBAs), the impact of the acquirer’s CR and the acquirer’s CI on the host country consumers’ repurchase intentions after the CBA, which has not previously been thoroughly examined. It can help managers to understand the conditions under which CBAs will be favourably evaluated.

Nowadays, Big Data and Artificial Intelligence (AI) play an important role in different functional areas of marketing. Starting from this assumption, the main objective of this theoretical paper is to better understand the relationship between Big Data, AI, and customer journey mapping. For this purpose, the authors revised the extant literature on the impact of Big Data and AI on marketing practices to illustrate how such data analytics tools can increase the marketing performance and reduce the complexity of the pattern of consumer activity. The results of this research offer some interesting ideas for marketing managers. The proposed Big Data and AI framework to explore and manage the customer journey illustrates how the combined use of Big Data and AI analytics tools can offer effective support to decision-making systems and reduce the risk of bad marketing decision. Specifically, the authors suggest ten main areas of application of Big Data and AI technologies concerning the customer journey mapping. Each one supports a specific task, such as (1) customer profiling; (2) promotion strategy; (3) client acquisition; (4) ad targeting; (5) demand forecasting; (6) pricing strategy; (7) purchase history; (8) predictive analytics; (9) monitor consumer sentiments; and (10) customer relationship management (CRM) activities.

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Virtual Reality (VR) is shaping all human activities, and with the advent of the metaverse, buyers are going to experience new ways of doing shopping. What would happen if consumers will be asked to assess a product's attribute, i.e., packaging, in a virtual environment, instead of being able to physically hold the product, like in a traditional purchasing process? The aim of this study is to analyze consumers' evaluation of packaged products in immersive VR, manipulating packaging structural and haptic cues, and clarify potential differences with the consumers' responses in the real life. We conducted two focus groups (Study 1), with 16 participants, a mixed design experiment (Study 2), involving 167 consumers, to analyze consumers' attitudes, and a choice‐based conjoint analysis (Study 3), with 41 individuals, to study actual choice behavior. The main findings reveal that consumer behavior in VR is consistent with everyday life, except for minor variations. VR proves to be an efficient and rigorous research environment, also suitable for testing sensory cues and non‐tangible attributes. Finally, the article suggests managers can effectively use VR for product and packaging development, through a more sustainable process that requires fewer resources and time compared to traditional tests.

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