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Family holiday decision-making (FHDM) is a process composed of several stages. This paper aims to describe two objectives: to identify at each stage the roles in couples, the main decision-maker in the case of family holidays; and to determine the most influential variables.

To identify the roles played by the partners, a frequency analysis has been conducted, which provides a graphic representation of the so-called feasibility triangles. The technique selected to identify the variables that explained the decision structure was binary logistic regression. In total, 375 useful dyads of questionnaires were received.

Holidays follow a joint decision-making process in the initiation phase and in the final decision, while the search for information is carried out equally by either partner. The woman’s work situation, the type of destination travelled to and the difference in education levels between them are the variables that best explain how couples decide on their family holidays.

A better understanding of the FHDM process will help tourism companies to improve their marketing campaigns.

The characteristics of the sample composed of 375 couples whose members completed a questionnaire separately have allowed not have to rely on one response per household, which adds reliability to the results. This sample is higher than the one of many reference publications on the subject. Furthermore, this paper revealed differences between male and female perception.

Given the substantial number of social conversations on the Internet, companies must remain vigilant about protecting their reputations and businesses. The purpose of this research is to measure the impact on share prices of reputational variables, measured through online comments, at the banking sector level as well as patterns of behavior between these variables and fluctuations in share prices.

Using big data and business intelligence techniques, bank reputation was analyzed through online social comments. The sample includes seven Spanish banks. To measure the impact of reputational variables on share prices, an Online Reputation Index was created. These variables were then correlated and filtered with the share price variation rate of each bank on a daily basis under two scenarios: using all share price data and also focusing on times of sharp fluctuations. Finally, multiple linear regression analysis was used to identify patterns in these relationships.

The findings reveal that negative comments focusing on attitude, emotions and governance experiences – particularly regarding ethical performance – are the only reputational variables with a clear impact on share price fluctuations in the banking sector. Strong correlations between reputation variables and share prices were observed only when online comments were extremely negative. These behaviors were more frequent during periods of significant price fluctuations.

This is the first study to analyze the impact of the reputation of the banking sector measured in the online environment on share price, taking into account its multidimensional construct.

Given the importance of chatbots in customer service in tourism, this paper aims to understand the drivers that predispose regular consumers of restaurant recommendation chatbots to continue using them.

A total of 386 regular consumers of a chatbot via WhatsApp restaurant recommender responded to an online questionnaire (inspired by scales found in the literature on technology adoption). Structural equation modeling was used to test the hypotheses.

Significant predictors of intention to continue using these chatbots included “effort expectancy (EE),” “hedonic motivation (HM),” “price value (PV)” and “habit (HT).” Specifically, HT still has a long way to go in terms of its performance, and it will be possible to work on it. Furthermore, two variables, EE and HM, act as a bottleneck when it comes to explaining this recurrent usage intention. Factors such as “performance expectancy (PE),” “facilitating conditions (FC)” and “social influence (SI)” did not influence “behavioral intention (BI).” Likewise, the moderating variables, age and gender, are not significant. Finally, the predictive capability of the model is demonstrated. The study findings will enable the development of effective strategies to foster consumer loyalty to this new technology in the restaurant industry.

This study contributes, building on the suitability of the unified theory of acceptance and use of technology 2 model, to explain users’ intention to continue using chatbot tourism services in the context of an information search for an unplanned and varied purchase decision, namely, restaurant recommendation services. To the best of the authors’ knowledge, this is the first analysis of tourist’s intention to reuse a real and fully functional chatbot via mobile instant messaging.

鉴于聊天机器人在旅游客户服务中的重要性, 本研究旨在了解驱动消费者持续使用WhatsApp餐厅推荐聊天机器人的因素。

共收集386名WhatsApp餐厅推荐聊天机器人的常规用户在线问卷数据（问卷设计参考技术采纳相关文献中的量表）。研究采用结构方程模型（SEM）验证假设。

影响用户持续使用意图的显著预测因素包括“努力期望（EE）”、“享乐动机（HM）”、“价格价值（PV）”和“习惯（HT）”。其中, “习惯（HT）”表现仍有提升空间, 而“努力期望（EE）”和“享乐动机（HM）”是解释持续使用意图的瓶颈因素。此外, “绩效期望（PE）”、“促进条件（FC）”和“社会影响（SI）”对“行为意图（BI）”无显著影响。性别和年龄等调节变量同样不显著。研究结果验证了模型的预测能力, 能够为餐厅行业制定有效策略以增强消费者对这一新技术的忠诚度提供指导。

本研究基于UTAUT2模型, 首次分析了消费者在餐厅推荐服务中持续使用移动即时通讯（MIM）聊天机器人的意图, 为探索非计划性和多样化购买决策背景下的信息搜索服务提供了新见解。

Meetings, incentives, conventions/conferences and exhibitions (MICE) tourism is a segment of business travel, which is experiencing a process of disintermediation. Using the value chain concept, this study aims to analyze the role and value of intermediaries in the MICE value chain. As the interests and perceptions of stakeholders are different, the authors also study if there is consensus or dissonance in their opinion.

This study uses mixed methods. First, by means of interviews with MICE professionals to identify the research variables and validate the test sample and questionnaire. Then, an international survey, which uses logistic regressions to identify the variables that support value. The post-hoc ANOVA test identifies the differences of opinions and determines the existence of consensus or dissonance.

Incoming agents create value by means of convenience and good rates and outbound agents by trust. The incoming agent is more valued and enjoys a position of power and therefore has more chances of remaining active in the market. However, there is no consensus about the role of intermediaries, hotels being the most dissonant stakeholder.

Instead of focusing on the negative aspects of disintermediation, this study uses a multifaceted perspective to identify the reasons that lead to value creation by intermediaries. This is vital for MICE stakeholders to acknowledge disintermediation and act consequently. Conclusions can also provide valuable guidance for intermediaries in other business to business interactions to better understand their value, competitive advantages and position of power.