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This paper aims to propose a conceptual framework to investigate the influences of innovative services on customer satisfaction and behavioural intentions. As service innovation has been focusing on the influences of product and technology innovation, this paper provides another insight into service innovation.

The proposed conceptual framework is based on findings from reviewing key theories and concepts, together with relevant literature in the service operation management, service innovation and hospitality management.

The proposed conceptual framework can be used to test empirically and explicate customer satisfaction and behavioural intentions towards service innovation of the hospitability operations. There are seven determinants can influence customer satisfaction: innovative mechanic clues, innovative humanic clues and innovative functional clues to influence customer transaction-specific satisfaction; complexity, meaningfulness, novelty and affordability to influence customer overall satisfaction. Customer expectation is formed by social factors, information, knowledge and their need to influence their actual perception, and the comparison between customers’ expectation and actual perception cause their satisfaction. The relationships amongst transaction-specific satisfaction, overall satisfaction and behavioural intentions can explain customer satisfaction comprehensively as a process of before, during and after their perception.

This paper highlights the importance of innovative service delivery and customers’ evaluation to contribute to creating service innovation. A synthetic definition of service innovation emphasised can help practitioners to define key determinants to effectively influence customer satisfaction and their behavioural intentions. Thus, marketing strategy aligned with operation management, can be practised appropriately.

This study provides key determinants to influencing customer satisfaction of service innovation through innovative service delivery in the hospitality operation, based on key theories and relevant literature.

本论文建立一个理论模型, 以研究创新型服务对顾客满意度和行为意向的影响。随着服务创新逐渐成为产品科技创新的焦点, 本论文针对服务创新提出一个新的角度。

本论文采用审阅服务运营管理、服务创新、和酒店管理的关键理论和概念, 提出理论模型。

本论文提出的理论模型可以进行实际测试, 以检测酒店运营中服务创新相关的顾客满意度和行为意向。研究表明, 影响顾客满意度的因素有七个：创新性硬件因子、创新性人文因子、创新性功能性因子以影响顾客交易方面的满意度、复杂性、有意义性、新意、以及可负担度以决定整体顾客满意度。顾客期待是由社会因子、信息、知识、和其影响实际感官的需求、以及顾客期待和实际感知之间的差别。交易性满意度、整体满意度、和行为意向之间的关系能够全面解释顾客满意度, 其在感知前、中、和后的过程中。

本论文强调了创新性服务流程和顾客评价对服务创新的重要性。本论文综合文献给出服务创新的概念能够帮助从业人员找到有效影响顾客满意度和行为意向的关键因素。因此, 制定出配合运营管理中的营销策略。

本论文根据审视关键理论和相关文献, 提出了酒店运营中营销服务创新的顾客满意度关键因素。

This study aims to investigate the effects of hotel customers’ perceived utilitarian and hedonic values on their intention to use service robots. In addition, the influences of innovativeness, ease of use and compatibility on hotel customers’ perceived utilitarian and hedonic values were examined.

The data of the current study was collected from 11 countries including the USA, UK, Turkey, Spain, Romania, Japan, Israel, India, Greece, Canada and Brazil. A structural equation modeling was used to test the study hypotheses.

The results indicated that hotel customers’ intention to use service robots was positively influenced by their utilitarian and hedonic value perceptions. In addition, customers’ perceptions of robots’ ease of use and compatibility had a positive impact on their perceived utilitarian and hedonic values.

The findings of the current study provide unique contributions in the context of hospitality robotics technology adoption literature. In addition, this study provides valuable insights and novel opportunities for hospitality decision-makers to capitalize on, as they strive to strategize the integration of robot-based services into their operations.

本研究调查了酒店顾客感知功能性价值和享乐性价值对服务机器人使用意向的影响。此外, 本研究考察了创新性、易用性和兼容性对酒店顾客感知功能性价值和享乐性价值的影响。

本研究的数据来自美国、英国、土耳其、西班牙、罗马尼亚、日本、以色列、印度、希腊、加拿大和巴西等十一个国家, 采用结构方程模型（SEM）对研究假设进行测试。

结果表明, 酒店顾客使用服务机器人的意向受到他们对功能性价值和享乐性价值的感知的积极影响。此外, 机器人易用性和兼容性对功能性价值和享乐性价值有积极影响。

本研究的发现对酒店行业机器人技术应用文献提供了独特的贡献。此外, 本研究为酒店业的决策者提供了宝贵的见解和新机遇, 使他们能够在将机器人服务的优势整合到酒店运营中。

The purpose of this paper is to evaluate the hotel selection problem of airlines for their hotel and airline alliance (HAA) to develop potential customers of airlines. This paper will propose a hybrid mathematics evaluation model to help airline to select an optimal hotel with both qualitative and quantitative criteria.

To solve the hotel selection problem of airlines for their HAA, this paper focuses on the implementation of the NGT, Fuzzy TOPSIS and MCGP models in the hotel selection process. Initially, the NGT was used to create HAA decision-making criteria based on the literature review and expert opinions, and it was found that scale and scope possibility, brand value, tourism attraction, operating cost and industrial conditions are the most important criteria. Later, the Fuzzy TOPSIS method was used to obtain the general normalized fuzzy preference and to compute the closeness coefficients of each alternative hotel with respect to each criterion. Third, five tangible constraints were incorporated into the Fuzzy TOPSIS-MCGP model to calculate the optimal hotel with LINGO software.

Airline managers can use the proposed model to form a clear view of how to choose the most suitable hotel to cooperate with to outperform their competitors. Having access to this information allows airline managers to take steps to perform better and improve the performance of the partnership, helping them to gain more confidence in their decision-making capabilities while reducing investment risks.

This is the first paper that has adopted Fuzzy TOPSIS-MCGP to select hotel for their HAA from the airline’s point of view. The major contributions of this study are as follows: an efficient and simple evaluation framework is proposed for handling vagueness and uncertainty in real-world hotel selection problems; the advancement of treating uncertainty in the MCDM process; the fuzzy TOPSIS-MCGP method is extended for such problems, taking into account tangible and intangible criteria; airline managers can now make decisions in choosing to select the best hotel for their HAA that meets the airline's business goals and passenger demands; hotel operators are flexible in selecting their airline partnership, thus creating greater profit for both parties.

饭店和航空公司之间横向联盟的选择模型：NGT, fuzzy TOPSIS和MCGP方法的综合应用

本文的主要目的是在协助驾驶评估酒店选择的问题, 并通过由酒店与航空公司的合作联盟HAA, 开发整合的潜在客户。评估模型, 以帮助航空公司选择同时满足定性和定量标准的最佳酒店。

这些研究集中在规模和范围的可能性, 品牌价值, 旅游吸引上力, 运营成本和产业条件上。第二个步骤是日期近似近似最佳解排序技术（fuzzy TOPSIS）计算每家替代酒店与理想解决方案的接近度系数。规划方法（MCGP）选择最佳酒店, 同时选择方法同时考虑酒店的定性和定量标准, 并且从未在酒店选择文献中被采用过。

为了帮助评估评估合适的酒店和建立合作联盟, 因此本文提出了NGT-Fuzzy TOPSIS-MCGP模型, 以帮助决策的决策者实现替代的酒店。在此模型中, 决策者通过最后, 在名目人群技术（NGT）确定客观的酒店选择规范, 然后他们可以根据模糊近似最佳解排序技术（TOPSIS）确定标准权重, 并计算模糊的TOPSIS-MCGP模型中, 决策制定者可以使用多选择目标规划（MCGP）, 通过设定每个目标的期望水准寻找最佳酒店。

这是第一篇以航空的角度, 同时采用模糊TOPSIS-MCGP方法选择合适的酒店的论文。本文最主要的贡献是: 1. 提出了一种有效而简单的评估框架, 用于处理现实世界中酒店选择问题中的模糊性和不确定性。2. 在处理MCDM过程中不确定性方面的进展；模糊TOPSIS-MCGP方法针对此类问题进行了扩展, 同时考虑了有形和无形的标准。3. 航空公司经理现在可以做出决定, 选择适合其HAA的最佳酒店, 借以满足航空公司的业务目标以及乘客的需要。4. 酒店运营商可以灵活选择航空公司合作伙伴关系, 从而为双方创造更大的利润。

饭店, 航空公司, 名目人群技术（NGT）, 最佳解排序技术（TOPSIS）, 多选择目标规划（MCGP）, 横向联盟

El modelo de selección Para alianzas horizontales entre hoteles y aerolíneas (Haa): una aplicación integrada de los métodos NGT, fuzzy TOPSIS y MCGP

El objetivo principal de este documento es evaluar el problema de selección de hoteles de las aerolíneas para su HAA (hotel airline alliance) a fin de desarrollar clientes potenciales para las aerolíneas. Este documento propondrá un modelo híbrido de evaluación matemática para ayudar a la aerolínea a seleccionar un hotel óptimo con criterios cualitativos y cuantitativos.

Para resolver el problema de selección de hoteles de las aerolíneas para su HAA, este documento se centra en la implementación de los modelos NGT, Fuzzy TOPSIS y MCGP en el proceso de selección de hoteles. Inicialmente, el NGT se utilizó para crear criterios de toma de decisiones de HAA basados en la revisión de la literatura y las opiniones de expertos, y se descubrió que la escala y la posibilidad de elección, el valor de la marca, la atracción turística, los costes operativos y las condiciones industriales son los criterios más importantes. Posteriormente, se utilizó el método Fuzzy TOPSIS para obtener la preferencia fuzzy general y normalizada y calcular los coeficientes de cercanía de cada hotel alternativo con respecto a cada criterio. En tercer lugar, se incorporaron cinco restricciones tangibles al modelo Fuzzy TOPSIS-MCGP para calcular el hotel óptimo con el software LINGO.

Los gerentes de aerolíneas pueden usar el modelo propuesto para tener una visión clara de cómo elegir el hotel más adecuado para colaborar con el fin de superar a sus competidores. Tener acceso a esta información permite a los gerentes de las aerolíneas tomar medidas para gestionar mejor y mejorar el resultado de la alianza, lo que les ayuda a ganar más confianza en su capacidad de toma de decisiones y al mismo tiempo reducir los riesgos de inversión.

Este es el primer documento que adopta el modelo Fuzzy TOPSIS-MCGP para seleccionar un hotel para su HAA desde el punto de vista de la aerolínea. Las principales contribuciones de este estudio son las siguientes: 1. Se propone un marco de evaluación eficiente y simple para manejar la imprecisión y la incertidumbre en los problemas de selección de hoteles del mundo real. 2. El avance del tratamiento de la incertidumbre en el proceso MCDM; extiende el método fuzzy TOPSIS-MCGP a tales problemas, teniendo en cuenta criterios tangibles e intangibles. 3. Los gerentes de aerolíneas ahora pueden tomar decisiones al elegir el mejor hotel para su HAA que cumpla con los objetivos comerciales de la aerolínea y las demandas de los pasajeros. 4. Los operadores de hoteles son flexibles en la selección de su asociación de aerolíneas, creando así mayores ganancias para ambas partes.

Hotel, Aerolínea, Técnica de grupo nominal (NGT), Técnica Para el orden de preferencia por similitud a solución real (TOPSIS), Programación de objetivos de opción múltiple (MCGP), Alianza horizontal

Trabajo de investigación

Voice assistants (VAs) empower human–computer interactions by recognising human speech and implementing commands pronounced by users. This paper aims to investigate VA-enabled interactions between hotels and guests in the hospitality context. The research positions VAs within the artificial intelligence (AI)-enabled Internet of Things (IoT) context, disrupting old practices and processes. Smart hospitality uses VAs to support effortless value cocreation for guests cost-effectively. The research examines consumer perceptions and expectations of hospitality VAs and explores VA capabilities through expert technology providers.

This empirical paper investigates the current use and future implications of VAs for hotel environments. It uses qualitative, semi-structured in-depth interviews with 7 expert hospitality VA technology providers and 21 hotel guests who have VA experience. The research adopts a demand and supply approach, addressing the VAs in hospitality holistically.

The findings illustrate the requirements from both end-users’ sides, hotels and guests, exploring VA advantages and challenges. The analysis demonstrates that VAs increasingly become digital assistants. VA technology helps hotels to improve customer service, expand operational capability and reduce costs. Although in its infancy, VA technology has made progress towards optimising hotel operations and upgrading customer service. The study proposes a speech-enabled interactions model.

This research stimulates the transformation of hospitality services by using VAs and the development of smart hospitality and tourism ecosystems. The study can benefit from further research with hotel managers, to reflect hoteliers’ points of view and investigate their perception of VAs. Further research can also explore different aspects of consumer–VA interaction in different contexts.

The paper makes a significant contribution to hospitality management and human–computer interaction best practices. It supports technology providers to reconsider how to develop suitable technology solutions towards improving their strategic competitiveness. It also explains how to use VAs cost-effectively and profitably while adding value to travellers’ experience.

VA studies are often focussed on the technology in private households, rather than in commercial or hotel spaces. This paper contributes to the emerging literature on AI and IoT in smart hospitality and explores the acceptance and operationalisation of VAs. The research contributes to the conceptualisation of VA-enabled hotel services and explores positive and negative features, as well as future prospects.

语音（数码, 虚拟或者人工智能）(VAs) 助理能够识别真人声音和系统指令声音从而为人机互动提供助力。 本研究基于酒店业已有的案例探索了酒店和客人语言支持的互动的本质。本研究探索了关于客房服务的表现和实用性的顾客认知和顾客期望。

本研究借用了定性半结构化深入访谈来收集一手数据, 调查了酒店环境中的语音助理目前的运用情况和未来影响。本研究访谈了7位酒店科技服务提供者和21位有使用个人智能扬声器经验的酒店客人。本研究以供需模型来全方位解决此项问题。

研究结论强调了从双方使用者（酒店和客人）角度考量, 并且考虑到语音仪器带来的所有的优势和挑战的重要性。基于顾客之前对这些仪器的使用经验, 本论文深入阐述了对公共空间这些语音助理的使用功能。本分析证明了由AI技术支持下, VAs 可以灵活的识别语音。VAs理解词汇内容并且也懂得词汇作为数据助手来支持智能家庭的自动化以及履行商业职责背后的意义来。酒店从业人员可以尝试运用此科技来提高用户体验, 扩展运营空间和减少成本。从访谈的数据可以证明, 尽管还在初级阶段, VAs 科技已经对酒店运营优化和晋级客户服务做出了显著的贡献和成就。本研究提出了一项介于酒店和客人之间的VA 语言支持的互动模型。

之前的研究主要针对私人使用, 而不是商业或者酒店空间。考虑到敌对环境和客人和酒店的文化差异, 旅游和酒店成为了尤其有挑战性的领域。本研究通过语音识别革新了酒店服务。本研究针对VAs接受程度和运用进行详细研究从而为酒店领域的AI和IoT提供了专业文献。本文为酒店服务中的VAs使用做出了开拓性的调查并且探讨了正面以及负面的特征和未来展望。

本研究为酒店和旅游管理补充了文献, 尤其是在酒店业人机互动领域。本研究通过语音识别技术对酒店服务的转型革新做出贡献。此项研究可以受益于以酒店管理者为视角的进一步研究。相比于收集科技设备供应方的见解, 对酒店管理者进行访谈可以提供更直接的信息来了解酒店员工对数码语音助理和对语音科技的总体接受程度。

酒店经常寻求途径来提高和客户的互动。本论文对酒店管理和人机互动领域提供了应用典例。本研究提供了酒店客人针对语音设备功能性的总体评价作为有价值的信息, 进而帮助科技提供者来重新审视针对顾客需要从而量身定制服务的策略和方式。最终, 本研究在提高行业战略竞争力层面分享了关于发展和采用此项强大有力科技的见解。