Search results

Building on new trends in tourism and smart city governance, this study aims to examine the degree of interrelation between stakeholder networks involved in tourism governance and smart city development. A model describing the transition towards smart tourism city governance is proposed.

The proposed model is tested through a multiple case study of seven European cities. This choice of sample makes the study highly representative. Data collection is based on an exhaustive search and analysis of available data on smart city initiatives, destination management organisations and tourism plans. Social network analysis using Gephi software is used to build stakeholder networks.

Analysis of the stakeholder networks that shape tourism governance and smart initiatives in several cities reveals a disconnection between the two types of networks. The results show limited progress towards the expected synergies of true smart tourism city governance.

Theoretically, the study contributes to the debate on new forms of governance for the complex evolution of urban tourism. In practice, the relationship between tourism governance and smart city initiatives needs to be redefined to achieve synergies that increase the inclusiveness and efficiency of urban tourism policies.

This study examines the under-researched topic of the interrelation between tourism governance and smart city initiatives. By comparing the networks of actors resulting from these two processes, it assesses the extent to which this interrelation helps the emergence of new governance models (smart tourism city governance).

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.

The purpose of this paper is to provide a deeper understanding of the relevance of shore excursions in the distribution of cruise passenger flows; an approach which has been overlooked by many studies on cruise tourism. Specifically, the paper focuses on two destinations: Barcelona, a mature cruise destination suffering from the impact of overcrowding; and Valencia, an emerging cruise destination facing the risk of future (similar) impacts.

The method used is multiple-case study with replication logic. First, web content analysis is conducted of shore excursion descriptions of the destinations selected so as to identify the itineraries, as well as the municipalities and the specific tourist attractions included in the tours. Then, word-processing tools are used to create a regional and local data set to arrange the narrative data. Finally, density maps are drawn in order to examine the different visitor flows within the tourist hinterlands from the supply perspective.

The results indicate that most shore excursions are concentrated in the port cities. Comparing the two destinations, the paper argues that the redistribution within the cities is not equally balanced. Nevertheless, the results also reveal that the excursions offered by local shore tourism operators (TOs) in both destinations have contributed to the expansion of the cruise tourist hinterland over a wider regional area.

This paper evaluates the visitor flow distribution from a supply perspective. Hence, future studies should examine the demand dimension in order to gain a deeper understanding of the concentration intensity. Additionally, it would be worth examining not only visitors taking guided tours but also the independent ones (those who visit the destination on their own).

Despite the growing importance of cruise tourism, research on the role of local shore TOs in this sector is quite limited. One element that deserves more research attention is related to the role of shore excursions in the spatial configuration of the cruise tourist hinterland. Finally, the results obtained could also have significant implications for policy makers developing and promoting effective measures to prevent overcrowding.

Companies are currently facing the challenge of understanding how their business is affected by the large volume of opinions continually generated by their stakeholders in social media regarding their intangible assets (experiences, emotions and attitudes). With this in mind, the purpose of this paper is to present an innovative management model, named E2AB, to measure and analyse reputational intangibles from digital ecosystems and their impacts on tangible assets.

The methodology applied was big data and business intelligence techniques. These methods were used in the computing process to obtain daily data from every asset guarantees that the model is validated with robust data. This model has been corroborated using data from the banking sector, specifically 402,383 net data inputs from the digital ecosystems.

This study illustrates the existence of a holistic influence of intangible assets over tangible assets. The findings demonstrate complex relationships between tangible and intangible assets, determined not only by the type of variable but also by its valence and intensity.

These findings may help chief communication officers and general managers a better understanding of how intangible assets extracted from online users’ opinions are related to their organisation’s tangible assets plus a chance to find out about their impact and how to manage them for a practical and agile decision making in real time.

It is a pioneering work in establishing a model, which demonstrates transversal and holistic relationships between relational intangible and tangible assets of firms from digital ecosystems, using business intelligence techniques.

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。

This study aims to examine the relationships between a firm's corporate social responsibility (CSR) activities and its performance and risk. The authors hypothesize that industry-level effects are highly determinant of the sign and magnitude of these relationships to establish a ranking of industries to identify the position of the most prominent tourism-related industries: hotels and airlines. Based on the cybernetic model of decision making and the heuristics thereof, shareholders base their investment decisions derived from CSR announcements on the idea that the industries behave differently; their fixed costs being a relevant factor.

The authors estimate the industry-specific effects of CSR initiatives on firms' performance and risk using a sample of 583 announcements from the Spanish Stock Market.

The results show that while CSR announcements have a positive effect on performance when the authors do not account for industry-specific factors, once the authors incorporate these factors into the analysis, the authors find that firm performance and risk vary quite substantially as a function of the industry to which the firm belongs. Interestingly, while the hotel industry presents an average behavior (standing at 9th position in returns, 15th in terms of risk, and 8th according to the ratio returns/volatility), the airline industry presents the worst situation of all industries: last in performance and last in risk.

The results help managers assess their decisions and allocate CSR resources optimally.

This article is the first attempt to empirically test and comprehensively detect the different relationships between CSR and firm performance across industries.