Since the advent and rapid diffusion of the Internet, the subject of consumer channel choice has attracted a large amount of research, mainly focused on the influence of channel, consumer and product category characteristics as its drivers. The interaction between channel choice and the purchase situation has been largely ignored, however. This paper is an attempt to fill this gap by identifying the key purchase situation variables and conducting an experiment to assess their impact on the choice between the traditional retail outlet and the online store. The results show that the key determinants of channel choice relate to time and distance. Distance-to-store and time pressures are among the factors affecting the probability of online purchase. Using a conceptual framework to explore differences in the impact of situational variables across product categories (high/low involvement, search/experience good), we show that distance-tostore has more influence on the likelihood of online purchase in situations involving search goods, while social variables are found to play a role only in the context of highinvolvement goods.

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The appearance of Artificial Intelligence implementations, such as text-based virtual assistants (chatbots) in education is relatively new. These implementations can be useful for helping teachers and students to solve both educational questions and routine tasks. This paper examines the factors that explain teachers' acceptance of chatbots through the dimensions of the Technology of Acceptance Model (perceived usefulness and perceived ease of use), its conversational design (use of social language and proactiveness), and the teachers' age and digital skills. The data collection process included a pretest and an online survey with four different types of chatbots. We analyze 225 responses of primary and secondary education teachers. The results show that the perceived easiness and perceived usefulness leads to greater acceptance of chatbots. As for the chatbots' features, formal language by a chatbot leads to a higher intention of using them. These results can help in chatbot design and communication decisions, improving the acceptance of the educational community.

PurposeThis paper aims to examine the way in which consumers integrate experts' opinions into their own evaluations of a selection of red wines.Design/methodology/approachThe authors conduct an experiment to measure the influence of experts' opinions in relation to the complexity of the information, the level of consensus between different experts, and the consumer's level of category knowledge.FindingsConfirmation is found for the effect of received information on consumers' product evaluations. Variation is found in relation to the consumer's level of category knowledge. Expert ratings have a stronger influence on individuals with low knowledge of the wine category than on those with high knowledge. The level of consensus between experts and the complexity of the information in this case have no effect on the impact of their opinions.Originality/valueThis paper takes a deeper look into the effect of “weak‐tie” personal information sources, particularly the opinions of experts regarding wine. Scientific research into the effect of expert judgments on consumer perceptions is still scant and businesses also need to assess the factors underlying its impact, given that the influence of expert judgment can be as crucial as quality to a product's success. The main feature that distinguishes this paper from the previous literature is that it integrates all three moderating effects in a single experiment: level of expert consensus, the complexity of the information provided and the prior knowledge of the consumer.

Purpose: The purpose of this study is to identify customer-specific differences in a general model of e-loyalty taking into account the existence of unobserved heterogeneity. Specifically, we aim to 1) test for the presence of customer heterogeneity 2) assess the impact of potential bias when there is no control for heterogeneity; 3) analyze the distinct customer segments that emerge from the empirical estimation of the model, and 4) describe the segments by their demographic and psychological characteristics. Design/methodology/approach: Panel data from a survey of online shoppers is used in a post hoc segmentation method, which will enable us to identify segments, while estimating the parameters by means of structural equation models; Findings. Three distinct consumer segments emerge. The relative importance of e-loyalty and e-satisfaction is significantly determined by consumers' shopping styles. Originality/value This study highlights the need to consider unobserved customer heterogeneity when attempting to explain satisfaction and loyalty development processes in the retail context in general, and e-commerce in particular. To our knowledge, this is the first time this approach has been used to analyze the impact of customer heterogeneity on esatisfaction and e-loyalty.

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