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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。

The paper seeks to bridge the already familiar benefits of 3D printing (3DP) to the rehabilitation of cultural heritage, still based on the use of complex and expensive handcrafted techniques and scarce materials.

A compilation of different information on frequent anomalies in cultural heritage buildings and commonly used materials is conducted; subsequently, some innovative techniques used in the construction sector (3DP and 3D scanning) are addressed, as well as some case studies related to the rehabilitation of cultural heritage building elements, leading to a reflection on the opportunities and challenges of this application within these types of buildings.

The compilation of information summarised in the paper provided a clear reflection on the great potential of 3DP for cultural heritage rehabilitation, requiring the development of new mixtures (lime mortars, for example) compatible with the existing surface and, eventually, incorporating some residues that may improve interesting properties; the design of different extruders, compatible with the new mixtures developed and the articulation of 3D printers with the available mapping tools (photogrammetry and laser scanning) to reproduce the component as accurately as possible.

This paper sets the path for a new application of 3DP in construction, namely in the field of cultural heritage rehabilitation, by identifying some key opportunities, challenges and for designing the process flow associated with the different technologies involved.