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This study aims to identify the impact of affective components on behavioral intentions applying electronic word of mouth (eWOM) and is based on the “cognitive–affective–conative” model. EWOM allows researchers to get new insights about consumers’ behavior and explores new patterns of consumers’ decision-making processes.

This study is based on the theory of planned behavior (Ajzen, 1991), doubled with “cognitive–affective–conative” model (Oliver, 2014). This study applies structural topic modeling to examine the impact of satisfaction dimensions from all the Tripadvisor reviews on consumer behavioral intentions. The research sample covers all restaurants located in St. Petersburg (n = 10,424) and all consumers’ reviews (n = 286,642).

In this study, the dimensions of the affective component were identified. The results demonstrate that dimensions of the affective component (food quality, service quality, atmosphere and cost fairness) affect behavioral intention (willingness to share positive emotions). In total, 20 topics, forming these dimensions, have been indicated. Consumers tend to pay more attention toward food quality and restaurant staffs’ work when they are willing to share positive emotions and tend to point out auxiliary service when they have less willingness to share positive emotions. Random restaurant visits tend to increase the willingness to share positive emotions.

Research originality lies in a new methodological approach which is based on text mining techniques. To the best of the authors’ knowledge, this study is the first attempt to examine consumer behavior through the lens of the “cognitive–affective–conative” model based on eWOM and covers all businesses in the specific economic sphere. This has allowed the researchers to reveal new dimensions of consumer behavior and brought more insights into the consumers’ decision-making process.

This study aims to determine consumer satisfaction dimensions that lead to a willingness to share positive emotions through the study of TripAdvisor users’ reviews on St. Petersburg museums. The explorative study reveals the most significant factors that could predict museum visitors’ behavioral intentions.

The study is based on the theory of planned behavior and the “cognitive-affective-conative” model to analyze TripAdvisor reviews (n = 23020) and understand the relationship between the affective and the conative components of consumer behavior. Quantitative text-mining analysis allowed us to view every lemma of every review as a single factor for a deeper understanding of the phenomenon.

The research has enlarged the literature on museum consumer behavior. Behavioral intentions of museum visitors are affected by satisfaction dimensions, especially emotions felt; the esthetic dimension and museums’ surroundings affect consumers’ overall willingness to share positive emotions, while bad service quality and pricing policy make a visit to the museums less satisfying.

Managers can enhance their offerings and attract new consumers by identifying the satisfaction dimensions that influence their intentions to share positive emotions. The research findings can aid museums, tour agencies and government officials in developing targeted products and strategies to meet consumers’ expectations and promote urban tourism.

The research identified the dimensions that influence visitors’ willingness to share positive emotions through user-generated content in the context of museums. The study applies quantitative text analysis based on logit regression, which is a novel approach in the field of urban tourism research.

The main purpose of this study is to examine the relationship between ranges of affective components that have an impact on the revisit intention of museum visitors, in the context of a major city event. The study reveals the most significant factors that affect decision-making by applying the findings to a structural equation modelling (SEM) and conditional inference tree (CTree).

The paper utilises face-to-face survey research at the “Long Night of Museums” event in Saint Petersburg, 298 questionnaires were completed on the night of the event. The empirical part of the research is based on the SEM and interpreted by using the CTree. The SEM model measures the direct and indirect influence of the cognitive and affective components; the CTree enables the testing of both component and the joint effect they both produce.

This study shows a strong indirect correlation between the cognitive component of the major city event and the revisit intention of museum visitors. When focussing on affective components, both the SEM and the CTree demonstrated that attractiveness and atmosphere are revealed to be the most impactful elements regarding visitor retention and repeat custom. The research allows for a deeper understanding of visitor behaviours, intentions and their decision-making processes.

The results of the study allow museum managers to understand how to create repeat custom amongst visitors, by appreciating the importance of participation in major city events and the role that attraction and atmosphere play when creating intention for repeat visit. The research has uncovered which dimensions are the most important to visitors, and as a result, these particular dimensions should be thoroughly developed by museums in future in order to attract and repeat visits. This study has demonstrated the practical implications for museums participating in city events. When considering policy makers, this particular research provides an opportunity to develop recommendations for future city events, as well as using the CTree to assess and predict the effectiveness of visitor behaviour.

This is an original study which aims to integrate the impact of the perceived value of the cognitive component and a new range of affective elements regarding museum retention in the context of a major city event. The study includes newly developed dimensions of perceived value, as well as a unique focus on affective dimensions such as – atmosphere and attraction. Another point of originality is provided by using a CTree, which captures an in depth understanding of the intention formation process. This study provides an opportunity to advance our understanding of visitor decision-making processes.