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This research examines the phenomenon of food delivery services from the mobile app user’s perspective and how consumers’ lifestyles are changing because of the convenience provided by the apps. By means of an online survey targeted at US food delivery app customers, our study analyzes the main motivations that lead them to use and recommend these technology-based services. The results of the study revealed that some of the theory of planned behavior model variables (i.e., attitude toward the behavior, subjective norms), influence customer use and word-of-mouth (WOM) intentions. Security influences intention to spread WOM, whereas customer lifestyle compatibility influences intention to use the food delivery apps. A post hoc analysis revealed that perceived control is only important for older customers, who need to perceive that they control the apps before they will recommend them to other customers. The findings of the study are discussed and contrasted with previous research in the field. The managerial implications derived from the findings provide practical guidance for food delivery app companies. Further research avenues are suggested to encourage scholars to continue investigating the challenge of the diffusion of mobile apps in the food delivery and related sectors.

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Purpose The purpose of this study is to analyze how positive behaviors toward influencers (customer interaction) and promoted products (looking for product information) can be achieved, taking into account influencer–product fit, in a fashion marketing campaign. In addition, account following and product involvement are examined as possible moderators in these relationships. Design/methodology/approach The data were gathered from online participants. The participants were Instagram users who already knew a popular influencer on the platform. The experimental design manipulated the types of picture posted by the influencer to observe customers’ reactions in terms of intention to interact with the influencer’s account and to look for further information about promoted products. Findings The authors’ findings suggested that influencer–product matches in posts on Instagram encourage users to search for information about promoted products but do not affect their intention to interact with influencers’ accounts. Nevertheless, customers’ reactions toward an influencer’s posts differ based on whether they are followers of the influencer and whether they are highly or lowly involved with the promoted product. Practical implications Both brands and influencers should properly manage influencer marketing actions. Brands should control influencers’ audiences and their involvement with featured products so that they are seen to promote them in a natural way. Influencers should endorse branded products that fit their own style; this will increase the interaction on their accounts. Originality/value This research contributes to a better understanding of how users can be encouraged to undertake positive online actions as regards influencers (interaction with their accounts) and promoted products (information search) in influencer marketing campaigns.

Purpose Building on both the uncanny valley and construal level theories, the analyses detailed in this paper aims to address customers’ explicit and implicit attitudes toward various service robots, categorized by the degree of their human-like appearance, namely, mechanoids (low human-likeness), humanoids (medium human-likeness) and realistic robots (high human-likeness). Design/methodology/approach The analyses reflect a mixed-method approach, across three studies. A qualitative study uses focus groups to identify consensual attitudes. An experiment measures self-reported, explicit attitudes toward the three categories of robots. Another experiment explores customers’ implicit attitudes (unconscious and unintentional) toward robots, using three implicit association tests. Findings Customers express both positive and negative attitudes toward service robots. The realistic robots lead to both explicit and implicit negative attitudes, suggesting that customers tend to reject these robots in frontline service settings. Robots with lower human-likeness levels generate relatively more positive attitudes and are accepted to nearly the same extent as human employees in hospitality and tourism contexts. Practical implications Because customers reject, both consciously and unconsciously, very human-like robots in service encounters, managers should leverage this key finding, along with the more detailed results, to inform their strategic introduction of robots into hospitality frontline service settings. Originality/value The combined qualitative and quantitative studies specify and clarify customers’ implicit and explicit attitudes toward robots with different levels of human-likeness, in the real-world setting of hospitality and tourism services. Such insights can inform continued research into the effects of these service innovations.