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This study intend to investigate a theoretical model looking at how particular tourist emotions, such as “joy,” “love,” and “positive surprise,” might predict their behavior by looking at how satisfied they are with their whole experience when visiting spas, and to examine the relationship of emotional experience, destination image, satisfaction and intention to revisit for spa tourism.

A sample of 345 individuals who traveled to Alleppey as domestic tourists participated in the research study. A non-probability (purposive) sampling method in this study. The structural model was analyzed using Structural Equation modeling (SEM), and the path coefficients were examined to test the hypotheses.

The results supported the hypotheses, indicating that specific emotions, image of the destination, and satisfaction significantly impacted tourists' intentions to revisit Alleppey as a spa tourism destination. This study demonstrated that “emotions of joy, love, and positive surprise” have a considerable influence on the image of the destination and satisfaction. The findings reveal a substantial correlation between satisfaction and behavioral intention (“Intention to revisit”). The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location.

The research suggests that a higher degree of satisfaction would encourage visitors to revisit the location. This research offers vital information for developing, planning, and putting into practice tourism policies in the spa tourism sector. This article focuses on domestic travelers who travel to Alleppey, so the conclusions may not be relevant to research utilizing foreign tourists.

According to the literature study, and to the authors` knowledge, only limited number of studies that look at spa tourism from a wellness perspective. Additionally, Alleppey is used in the study as the study’s setting, providing insight into the visitor experiences of this expanding spa tourism business. This study gives understanding about how emotional experience predicts behavioral intentions.

This study investigates entrepreneurial overconfidence (EOC) levels among solo entrepreneurs at the country level. Although transitions from solo to employer entrepreneur are relatively rare, the solo self-employed have become an important source of potential job creation by virtue of the sharp increase in their numbers in the past two decades. When EOC levels are too high, job creation ambitions may be unrealistic and unrealised. Unrealised ambitions and business failure can lead not only to psychological and financial costs for the individual entrepreneurs involved, but at the societal level also to wasted government resources, and increased costs for the entrepreneurial ecosystem as a whole. Therefore, it is important to know more about the entrepreneurial overconfidence levels of solo entrepreneurs in different countries and their determinants.

Using Global Entrepreneurship Monitor data for 71 countries over the period 2013–2016, the authors construct a new measure of entrepreneurial overconfidence of solo entrepreneurs and relate this to three recently developed indicators of national culture.

The findings indicate that EOC levels are positively related to Joy (versus Duty), and negatively related to Trust (versus Distrust). Finally, no significant relationship between entrepreneurial overconfidence and Individualism is found in the study (versus Collectivism).

Given the lack of literature examining the relationship between EOC levels and cultural variables hypotheses were developed using the existent body of knowledge in the area, which is at the early stage of development. The hypotheses derivation has used mostly theoretical arguments relating to the link between national culture and overconfidence of entrepreneurs in general, rather than relating specifically to solo entrepreneurs. The measure of EOC uses expectations of employment growth to proxy overconfidence, but other measures of entrepreneurial success may also be explored.

As the hiring of employees can be a costly process (Coad et al., 2017), it is important that entrepreneurs have realistic expectations of what it requires to hire employees. This is especially the case for solo entrepreneurs since they do not have experience of hiring their own employees. This paper addresses such issues at an aggregate level by exploring what factors explain country differences in overconfidence levels of solo entrepreneurs.

It is worthwhile to distinguish between solo and employer entrepreneurs when studying their EOC levels, as the ambitions of these two types of entrepreneurs are different. Empirically, this study introduces a new measure of EOC tailored towards the solo self-employed.

This study contributes to entrepreneurship literature by expanding current knowledge on entrepreneurial overconfidence at the country level. Past research has studied EOC at the individual level, however limited research exists on the phenomenon of EOC from a country level perspective. This is important as unrealised entrepreneurial ambitions may not only create substantial costs for the individual entrepreneurs involved, it may also lead to substantial societal costs, including waste of government resources.

The purpose of this paper is to use the data analysis method of sentiment analysis to improve the understanding of a large data set of employee comments from an annual employee job satisfaction survey of a US hospitality organization.

Sentiment analysis is used to examine the employee comments by identifying meaningful patterns, frequently used words and emotions. The statistical computing language, R, uses the sentiment analysis process to scan each employee survey comment, compare the words with the predefined word dictionary and classify the employee comments into the appropriate emotion category.

Employee responses written in English and in Spanish are compared with significant differences identified between the two groups, triggering further investigation of the Spanish comments. Sentiment analysis was then conducted on the Spanish comments comparing two groups, front-of-house vs back-of-house employees and employees with male supervisors vs female supervisors. Results from the analysis of employee comments written in Spanish point to higher scores for job sadness and anger. The negative comments referred to desires for improved healthcare, requests for increased wages and frustration with difficult supervisor relationships. The findings from this study add to the growing body of literature that has begun to focus on the unique work experiences of Latino employees in the USA.

This is the first study to examine a large unstructured English and Spanish text database from a hospitality organization’s employee job satisfaction surveys using sentiment analysis. Applying this big data analytics process to advance new insights into the human capital aspects of hospitality management is intriguing to many researchers. The results of this study demonstrate an issue that needs to be further investigated particularly considering the hospitality industry’s employee demographics.

This qualitative study aims to explore the activities that guests perform while staying in Airbnbs, emotions associated with these experiences and the components of memorable Airbnb experiences.

An empirical study of a qualitative nature was conducted using a self-administered open-ended questionnaire among tourists who had stayed in an Airbnb in the past three years. Data were collected using two different sources for triangulation purposes, referred to as Studies 1 and 2.

Many respondents reported conducting similar activities while at home and while staying in an Airbnb, supporting Burch’s (1969) spill-over theory. Travellers mostly recalled mundane activities, such as cooking. The results suggest that the spill-over effect is more prevalent in the Airbnb context than in other accommodation types, as one often travels from one’s own home to another’s home. Respondents associated their Airbnb experience with the positive emotion of joy. Respondents mentioned numerous reasons for having felt joy during their Airbnb experiences, such as sharing the trip with travel companions and spending time with friends.

Airbnb should clearly define host’s tasks and responsibilities, hosts should treat guests in a friendly manner, which includes resolving any problems they face in relation to the rental property.

This paper proposes a new conceptual framework for a memorable Airbnb experience, which comprises several components: socialising and bonding with friends and family members, location, the host’s hospitality, a homely feeling, home amenities and negative experiences (the poor condition of the room and a dishonest host).

This study aims to analyze communication from the perspective of social marketing, positive emotions, and the topics chosen by Spanish tourist destinations to show their destination image. Additionally, this research shows a message classification model, based on the aforementioned characteristics, that has generated a greater impact, offering clarity to tourism managers on the type of content they should publish to achieve greater visibility.

The methodology used in this work combines content analysis and data mining techniques. The classification tree using the chi-square automatic interaction detector (CHAID) algorithm was selected to determine predictors of like behaviour.

The results show that the predictor variables have been emotions, social marketing and topics. Also, the characteristics of the messages most likely to have a high impact are those related to emotions of joy or happiness, their purpose is behavioural, and they talk about rural, cultural issues, special dates, getaways, or highlights of a town or city for something specific.

This study is the first to analyze the content of the tweets shared by destination tourism managers from a social marketing, positive emotions, and sustainability perspective, determining the possible predictors of likes on Twitter. The authors contribute to the literature by deepening the understanding of how social marketing and the positive emotions promoted drive a more significant impact in tourism communication campaigns on social media. The authors provide destination managers with a way better to understand the variables relevant to users in tourism content.

Previous research has studied interactive value formation (IVF) using resource- or practice-based approaches but has neglected the role of emotions. This article aims to show how emotions are correlated in problematic social media interactions and explore their role in IVF.

By combining a text mining algorithm, nonparametric Spearman's rho and thematic qualitative analysis in an explanatory sequential mixed-method design, the authors (1) categorize customers' comments as positive, neutral or negative; (2) pinpoint peaks of negative comments; (3) classify problematic interactions as detrimental, contradictory or conflictual; (4) identify customers' main positive (joy, trust and surprise) and negative emotions (anger, dissatisfaction, disgust, fear and sadness) and (5) correlate these emotions.

Despite several problematic social interactions, the same pattern of emotions appears but with different intensities. Additionally, value co-creation, value no-creation and value co-destruction co-occur in a context of problematic social interactions (peak of negative comments).

This study provides new insights into the effect of customers' emotions during IVF by studying the links between positive and negative emotions and their effects on different sorts of problematic social interactions.

Social media allow for observing different aspects of human behaviour, in particular, those that can be evaluated from explicit user expressions. Based on a data set of posts with user opinions collected from social media, this paper aims to show an insight into how the readers of different news portals react to online content. The focus is on users’ emotions about the content, so the findings of the analysis provide a further understanding of how marketers should structure and deliver communication content such that it promotes positive engagement behaviour.

More than 5.5 million user comments to posted messages from 15 worldwide popular news portals were collected and analysed, where each post was evaluated based on a set of variables that represent either structural (e.g. embedded in intra- or inter-message structure) or behavioural (e.g. exhibiting a certain behavioural pattern that appeared in response to a posted message) component of expressions. The conclusions are based on a set of regression models and exploratory factor analysis.

The findings show and theorise the influence of social media content on emotional user engagement. This provides a more comprehensive understanding of the engagement attributed to social media content and, consequently, could be a better predictor of future behaviour.

This paper provides original data analysis of user comments and emotional reactions that appeared on social media news websites in 2018.

Understanding consumer brand relationships from the perspective of the consumer has been a research topic for years. Despite this, there are still various ways in which the construct is interpreted. This paper aims to identify the most typical interpretation of brand relationships by consumers.

A four-study prototype analysis was conducted, in which a bottom-up approach was applied to identify lay people’s conceptualization of consumer brand relationships.

The prototype analysis generates a comprehensive list of features of consumer brand relationships that provide a nuanced understanding of the concept. The most typical characteristics of a brand relationship according to consumers are quality, bond, value and joy. Comparing this relationship prototype with existing literature shows that there may be a gap between theory and practice regarding the concept of brand relationship.

The prototypical conceptualization of brand relationships shows which aspects play a role in consumers' most common interpretation of the construct. This provides an opportunity to assess the validity of existing conceptualizations of brand relationships. Knowing which aspects are most relevant for consumers’ brand relationships allows brands to make adjustments as needed and improve at establishing and maintaining relationships with consumers.