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The purpose of this study is to explore the use of Internet of Things (IoT) in hospitality and examine its relationship with Big Data. Drawing upon theoretical and practical considerations, it lays a foundation for its adoption in practice and future research.

This paper uses a conceptual approach. It demonstrates the use of IoT and its impact on Big Data in hospitality through exemplars. The paper further explores the convergence of IoT, Big Data and hospitality in the context of the literature, value attributes and vendor offerings. Theoretical models from information systems and business are used to support the concepts proposed.

The study compiles and contextualizes the applications of IoT in hospitality by applying an input–process–output model, demonstrating the link to Big Data. The resulting value dimensions are represented by the IoT–Big Data triple impact intensity model.

An outlook toward the future trajectory of IoT adoption is provided by proposing to extend the prevalent social, mobile, analytics and cloud framework with an IoT component.

Practical implications of the use of IoT and Big Data in hospitality on information technology infrastructure, business models, security and standardization highlight the scope for further empirical research.

By synthesizing IoT applications in hospitality and by bringing to light their relationship with Big Data, the study demonstrates how IoT, Big Data and hospitality converge – a synthesis that has thus far been largely unexplored. This study lays the groundwork for increased deployment of IoT and Big Data in hospitality and future academic research in this area.

本论文开发了酒店管理中的物联网（IoT）的使用, 并且检验了其与大数据的关系。根据其理论和实际考虑, 这方面的科技缺乏应用理论基础和未来研究方向。

本论文采用理论讲述的方式, 通过例子来阐述IoT的应用和大数据对于酒店管理的影响。本论文还拓展了IoT、大数据、以及酒店管理在文献范畴、价值属性、以及供应商考量中的认识。本论文借鉴了信息系统和商业管理中的理论模型以支撑提出的理论概念。

本论文综合审视了IoT在酒店管理中的应用, 提出了一个输入-处理-输出的模型, 指出了其与大数据的关联。其相关价值维度通过IoT-大数据三重影响强度模型来显示。

本论文提出了对IoT使用的未来展望, 拓展了著名的SMAC模型（social, mobile, analytics, cloud）, 加入了IoT成分。

本论文对IoT和大数据在酒店IT架构、商业模型、安保和标准化等方面的使用, 强调了其未来应用研究的方向。

本论文通过酒店管理中的IoT应用综述, 以及其与大数据分析的关联, 展示了IoT、大数据、酒店覆盖等概念如何融合, 这方面的研究还未真正被开发。本论文对于酒店领域中的IoT和大数据应用以及相关领域的未来研究, 有着奠基作用。

The study aims to investigate if lodging research suffers from a method bias by comprehensively reviewing the research methodology used in lodging related research articles.

In all, 2,647 published papers in 16 leading hospitality and tourism published between 1990 and 2016 are analyzed using bibliometric technique.

In all, 69% of the empirical studies in lodging research across 26 years period used quantitative methods, with an increasing reliance on regression-based analysis and structural equation modeling, a disturbing plunging trend in methods diversity. Findings also suggest an increasing trend of using secondary data.

Based on the findings of this study, theoretical and practical implications for hospitality and tourism researchers are provided.

This is the first study that reviewed a large corpus of published research (2,647 papers in 16 hospitality and tourism journals from the last 27 years) to highlight (a) methodology used, (b) methods employed and (c) data collection and analysis procedures.

本论文旨在通过全面审阅酒店管理相关科研文章的方法论内容，来审视是否酒店管理研究遭受方法论偏见。

本论文采用文献计量分析法，样本数据为2647篇发表在1990年-2016年间酒店旅游期刊的文章。

近26年间发表的酒店管理研究文章的69%使用定量分析法，往往采用回归分析和结构方程模型法，大大降低了方法多样性。研究结果还表明越来越多的文章采用二手数据分析。

根据本论文研究结果，酒店旅游研究学者们得到理论和实践的启示。

本论文是首篇审阅16个酒店旅游期刊发表的2647篇文章，以强调(a)方法论(b)研究方法以及(c)数据收集和分析过程。

This paper aims to investigate hospitality study abroad experiences as an educational service in which the experience encompasses services that combine tangible and intangible actions that require students to move from the classroom to a practical setting. It empirically investigates the relationship between students’ study abroad, perceived value and perceived sacrifice (monetary and non-monetary) with their overall satisfaction and internationalization intentions.

A total of 57 students who had completed an international externship experience were contacted and invited to complete an online survey. The online survey gauged the student’s perception of their externship experience, the overall satisfaction and the internationalization intentions. The instrument also gathered demographic information about the participants. The proposed model was estimated by using partial least squares (PLS) path modeling.

The results indicate that PLS can be used to assess the theory of consumption value for study abroad experiential learning. The results of the hypotheses testing indicate that the value students get and give is a suitable and significant predictor of satisfaction and internationalization. However, students’ satisfaction with their study abroad internship does not predict future internationalization intentions.

This study sheds light on hospitality students’ perceived value, satisfaction and internationalization intentions when they complete a study abroad internship program. The results indicate that the value students get and give is an appropriate and important predictor of satisfaction and attitude toward international education.

本论文旨在研究酒店管理专业出国留学的学生体验, 此体验既包括实体化行动又包括非实体化行动, 使学生走出教室, 进行实际操作。本论文实际检验学生出国留学、价值感知、牺牲感知（物质上和非物质上）、以及他们整体满意度和国际化意向。

本论文采用在线问卷采样形式, 57名参加出国实习项目的学生为问卷样本。问卷主要衡量了学生出国实习体验、整体满意度、和国际化意向。此外, 问卷还采集了人口统计信息。本论文采用偏最小二乘回归（PLS）路径建模的分析方法来分析数据。

分析结果表明PLS可以检验出国体验学习的消费价值理论。 研究结果表明学生得到和给与的价值是一项决定其满意度和国际化意向的指标。然而, 学生对于出国实习的满意度并不能决定其国际化意向。

本论文主要研究了酒店管理专业的学生, 当完成出国留学项目后, 他们的价值感知、满意度、以及国际化意向。研究结果表明学生得到和给与的价值是他们满意度和国际化意向的有效的决定指标

国际化行为、酒店管理专业实习、体验学习、校外实习、出国留学、价值、满意度

This paper aims to use an organizational ethnography perspective to explore how subsidiary hotel properties of a multinational hotel corporation experience planned organizational identity (OI) change instituted by headquarters.

This study uses a multi-site approach to collect ethnographic data on organizational change from six hotel subsidiaries in California, USA. Over three years, multiple sources of data were collected including: 31 interviews with hotel subsidiary leaders; more than 100 participant observation hours including job shadows, conferences and meetings; and photographs and internal communication materials.

Multinational hospitality companies face struggles between corporate standardization and subsidiary localization. This paper reveals that when headquarters plan changes focused on employees at their subsidiaries, the ways the latter initially accept and resist change are significantly impacted by the organizational memory and history of subsidiary leaders. However, as time progressed, properties with strong financial performance continued to operationalize new identity initiatives while properties with poorer profit margins played a balancing act between headquarters’ visionary identity and subsidiary ownership’s revenue expectations. Additionally, the situational realities caused by the COVID-19 pandemic put a halt to all properties which amplified practical and emotional challenges of organizational ethnography in hospitality research.

This paper contributes to hospitality literature by introducing an under-researched concept, OI change and advances understanding of the struggles in managing multinational company change. More importantly, this paper is a stepping stone for future hospitality management to embark on organizational ethnography.

本研究运用了组织民族志的视角来探索跨国公司旗下酒店如何经历由总部主导的计划性组织身份改变。

本研究通过多点民族志方法收集了美国加州六个附属酒店关于组织变化的数据。在三年中本研究收集了多种渠道的数据, 包括：1） 31份关于酒店领导层的访谈资料; 2）100多个小时对职业见习和会议等的观察数据; 3）图片和内部沟通资料。

跨国公司面临来自集团总部标准化和附属子公司本土化的挑战。本研究发现当总部计划对附属公司的员工进行改革的时候, 员工初始的接受或者反对会显著受到组织记忆和附属公司领导层历史的影响。然而, 随时间变化, 财务业绩较强的附属公司会继续奉行新的组织身份计划, 然而财务业绩较差的公司会采取平衡的策略来调节总部期待的愿景身份以及附属公司本身的收益预期。此外, 新冠疫情导致的所有产业停滞的局面也增大了运用组织民族志在酒店管理研究的实践和情绪方面的挑战。

本文通过引入新的概念——组织身份变革, 以及通过推进关于管理跨国公司组织变化挑战的理解对酒店研究领域做出了贡献。更加重要的是, 本研究为今后的酒店管理研究领域的组织民族志学的研究创造了跳板。

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。

Many hotels allocate guests to specific rooms immediately after reservation. This happens because individual rooms are sold (and there is no concept of room type) or because the assignment is done by hand at reservation or because of a connection with a channel manager, which is immediately fixing the room number after a reservation request. This early allocation is suboptimal, and it causes the unnecessary rejection of some reservations when the hotel has a high occupancy level. The purpose of this paper is to investigate different room allocation algorithms, including an optimal one (called RoomTetris), aiming at higher occupancy levels and profitability.

The methodology is based on theoretical results and experimentation. The optimality or the proposed RoomTetris algorithm is demonstrated. Experiments are executed in different contexts, including realistic ones, through the adoption of a hotel simulator, to measure the improvements in the occupancy rate of the optimal and heuristic strategies with respect to random or sub-optimal assignments of rooms.

The main results are that smart allocation algorithms can greatly reduce the rejection rate (reservation requests which cannot be fit into the hotel room plan) and improve the occupancy level, the percentage of available rooms or beds sold for the various periods.

This analysis can be extended by considering cancellations and overbookings. A second possibility to add flexibility in room allocation for hotels having more than one type of rooms is that the hotel can upgrade and offer a high-price room to the customer, which given an even large flexibility to fix rooms by shifting customers to other compatible types. In addition, more complex integrations with revenue management can also be considered, for cases in which the cost of a room depends on the number of guests.

Given that the difference in occupancy rate of the optimal algorithm is particularly large in high season and high-request periods, periods which are usually associated to higher rates and higher volumes, the proposed algorithm will improve the main financial performance indicators such as revenue per available room by an even bigger multiplier, depending on the hotel pricing policy. Because the room allocation process can be completely automated, the adoption of appropriate smart allocation algorithms represents a low-hanging fruit to be picked by efficient hotel managers.

To the best of the knowledge this is the first proposal of an optimal algorithm (with proof of optimality) for the considered problem.

很多酒店, 特别是私人、家庭经营型、或者精品酒店, 在客人预定后立刻分派指定的房间给客人。这往往是因为独立房间售卖（没有特殊房型概念）或者因为客人在预定时, 工作人员手动指派房间, 亦或者是因为预订系统与渠道管理系统链接, 直接在预定后指派房间号。这种早期的分派程序是不优化的, 往往在酒店住房率高的时候, 会造成一些不必要的房间预定失败, 继而带来的利润损失。本论文旨在研究不同房间指派参数配置, 包括最优系统（RoomTetris）, 使得酒店达到更高住房率的同时产生高利润。

本论文采用理论讨论和实验等研究方法, 并展示了提出的RoomTetris参数的最优性。本论文还将其参数放在不同的情景中做实验, 以显示其提高酒店针对随机或者次优化分派的最佳启发式策略中的住房率。

研究结果表明智能型分派参数能够大大降低预定失败率（预定需求不能符合酒店房型供给）, 并且提高住房率和利润。住房时间并不是必须的参数, 极具个性化服务, 比如让客人选房间号, 可能导致利润损失（因为最优房间分派无法实现）, 房型的设计也应该参与到最优房间分派的效果中来。

预定取消和超额预定的情况也应该加入到分析中来。第二种对于拥有不止一种房型的酒店来说, 可能增加房间分派的情况在于为客人升级房型, 这样可以将客人转到其他适合房型以解决房间分派问题。此外, 更复杂系统兼容财务管理系统应该被考量, 有的时候, 房间的成本取决于客人的数量。

由于最优算法的住房率区别在于旺季和高预定时段, 也就是高房间价格和高预定量, 本论文提出的最佳算法将提高主要财务指标, 比如RevPAR（平均客房收益）。由于房间分配系统可以完全实现自动化, 那么采用智能分派系统无疑是有效酒店管理中的优质选择。

据作者所知, 此文章是首篇关于此类话题的研究优质算法（且被证实其最佳）。

This paper aims to examine the main developments of virtual reality (VR) and augmented reality (AR) research in hospitality and tourism. It also aims to pinpoint fruitful directions for tourism and hospitality research on VR and AR applications.

A selective literature review of full-length papers published in the period from 2000 to 2018 was conducted. A total of 60 journal papers were retrieved and thoroughly reviewed.

This paper first presents a summary of the distribution of published papers. Then, this paper synthesizes the stimuli, dimensions and consequences of VR/AR-related user behavior experience, upon which a theoretical framework is developed. Additionally, this paper provides a detailed report for the progress on the theories and research methodologies, offering a useful background concerning what remains to be achieved. Finally, this paper puts forward fruitful directions for advancing the current understanding of VR/AR and its management.

This research presents diverse positive outcomes of using VR/AR technologies, which encourage industry practitioners such as destination marketing organizations (DMOs) and marketing firms to incorporate recent technological developments into their strategic plans.

This paper represents one of the first endeavors that critically reviews research progress on VR/AR in tourism and hospitality from 2000 to 2018. Not only are information technology researchers provided with a comprehensive guide to the latest, influential VR/AR literature but also the proposals of wide-ranging directions for future research would stimulate further investigation of VR/AR.

本论文研究旅游酒店业在VR和AR研究的主流发展情况。此外, 本论文还指出AR和VR在旅游酒店应用的未来发展方向。

研究样本为2000年至2018年发表的文章选集, 共60篇研究文献。

本论文首先总结了发表文章的分布情况。其次, 本论文总结了VR/AR相关行为体验研究的起因、方向、以及影响, 并开发了一个理论架构。此外, 本论文还对相关理论和方法进行总结, 从而指出哪些方面需要进一步研究。最后, 本论文还为如何进一步加深对VR/AR及其管理的理解做出指示性说明。

本论文展示了多个不同层面的使用VR/AR科技的积极影响, 从而鼓励行业者如DMOs和营销机构来应用最近科技创新来完善战略决策。

本论文是前沿研究著作之一, 对VR/AR在旅游酒店行业2000年至2018年文献进行梳理的文章。这不仅仅对科技研究学者对信息技术研究、VR/AR文献做了全面梳理, 还对未来VR/AR研究提出多角度全面的启发。

虚拟现实 、增强现实 、酒店管理 、旅游管理 、科技 、述评

纸张类型 - 文献综述

Radical changes in consumer habits induced by the coronavirus disease (COVID-19) pandemic suggest that the usual demand forecasting techniques based on historical series are questionable. This is particularly true for hospitality demand, which has been dramatically affected by the pandemic. Accordingly, we investigate the suitability of tourists’ activity on Twitter as a predictor of hospitality demand in the Way of Saint James – an important pilgrimage tourism destination.

This study compares the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) time-series model with that of the SARIMA with an exogenous variables (SARIMAX) model to forecast hotel tourism demand. For this, 110,456 tweets posted on Twitter between January 2018 and September 2022 are used as exogenous variables.

The results confirm that the predictions of traditional time-series models for tourist demand can be significantly improved by including tourist activity on Twitter. Twitter data could be an effective tool for improving the forecasting accuracy of tourism demand in real-time, which has relevant implications for tourism management. This study also provides a better understanding of tourists’ digital footprints in pilgrimage tourism.

This study contributes to the scarce literature on the digitalisation of pilgrimage tourism and forecasting hotel demand using a new methodological framework based on Twitter user-generated content. This can enable hospitality industry practitioners to convert social media data into relevant information for hospitality management.

2019冠狀病毒病引致消費者習慣有根本的改變; 這些改變顯示，根據歷史序列而運作的慣常需求預測技巧未必是正確的。這不確性尤以受到大流行極大影響的酒店服務需求為甚。因此，我們擬探討、若把在推特網站上的旅遊活動視為聖雅各之路 (一個重要的朝聖旅遊聖地) 酒店服務需求的預測器，這會否是合適的呢?

本研究比較 SARIMA 時間序列模型與附有外生變數 (SARIMAX)模型兩者在預測旅遊及酒店服務需求方面的表現。為此，研究人員收集在推特網站上發佈的資訊，作為外生變數進行研究。這個樣本涵蓋於2018年1月至2022年9月期間110,456個發佈資訊。

研究結果確認了傳統的時間序列模型，若涵蓋推特網站上的旅遊活動，則其對旅遊需求方面的預測會得到顯著的改善。推特網站的數據，就改善預測實時旅遊需求的準確度，或許可成為有效的工具; 而這發現對旅遊管理會有一定的意義。本研究亦讓我們進一步瞭解朝聖旅遊方面旅客的數碼足跡。

現存文獻甚少探討朝聖旅遊的數字化，而本研究不但在這方面充實了有關的文獻，還使用了一個根據推特網站上使用者原創內容嶄新的方法框架，進行分析和探討。這會幫助酒店從業人員把社交媒體數據轉變為可供酒店管理之用的合宜資訊。

In recent years, students have found careers in the tourism and hospitality (T&H) industry less attractive. Attracting and retaining young talents has become more challenging for the T&H industry in the post-pandemic era. To help solve the talent shortage problem, it is vital to understand how students perceive careers and what influences their career planning. The career construction theory indicates an integration between personal needs and career-related expectations. It provides a theoretical framework for the present study to understand what motivates students to begin their careers in the T&H industry. This study aims to empirically examine the relationship between students’ career adaptability and optimism and their effect on future career intentions.

An online survey was conducted in mainland China to investigate the interrelationships between career adaptability, career optimism and future career intention. A total of 492 valid responses were collected from students studying T&H.

The findings revealed that career optimism positively influences career adaptability and future career intention, respectively. Conversely, career adaptability is found to have a negative impact on future career intention. Moreover, career optimism has a mediating effect on the relationship between career adaptability and future career intention. The results would benefit educators in career counselling for students and industry practitioners to develop effective career management strategies for young talents in their respective organisations.

The application of career construction theory drawn from vocational psychology is suitable to provide knowledge and insights into the development of T&H career research. This study contributes to fill the knowledge gap concerning career adaptation, career optimism and future career intention.

近年来, 旅游和酒店行业领域的工作对于学生的吸引力下降。对于旅游和酒店行业, 吸引和留住人才变得更具有挑战性。为了解决人才短缺问题, 了解学生如何看待职业以及影响他们职业规划的因素至关重要。职业建构理论指出个人需求与职业相关期望相结合。它为本研究提供了一个理论框架, 以了解是什么促使学生在旅游和酒店业开始工作。本研究实证检验了大学生职业适应力与职业乐观度的关系及其对未来职业意向的影响。

本研究采用在线问卷调查的方式, 探讨职业适应力、职业乐观度与未来职业意向之间的相互关系。问卷对象为目前在中国学习旅游和酒店管理专业的本科学生。一共收集了492份有效回复。

研究发现, 职业乐观度对职业适应力和未来职业意向有正向影响。相反, 职业适应力对未来职业意向有负向影响。此外, 职业乐观度对职业适应力与未来职业意向之间的关系具有中介作用。研究结果将有助于教育机构和相关企业设计有效的职业策略, 帮助学生为未来的职业生涯做好准备, 并加强生涯辅导。

运用职业心理学的职业建构理论, 为旅游与酒店职业研究的发展提供了知识和见解。此外, 本研究填补了职业适应力、职业乐观度与未来职业意向之间关系的知识空白。

Se realizó una encuesta online en China continental para estudiar las interrelaciones entre la adaptabilidad laboral, optimismo laboral y la intención vocacional futura. Se recogieron 492 respuestas válidas de estudiantes de turismo y hostelería.

En los últimos años, las carreras de turismo y hostelería han resultado menos atractivas para los estudiantes. Atraer y retener a los jóvenes talentos es cada vez más difícil para la industria del turismo y la hostelería en la era postpandemia. Con el fin de contribuir a resolver el problema de la escasez de talentos, es crucial comprender cómo perciben los estudiantes las carreras profesionales y qué influye en su planificación profesional. La Teoría de la Construcción de la Carrera indica una integración entre las necesidades personales y las expectativas relacionadas con la carrera. Proporciona un marco teórico para el presente estudio con el fin de comprender qué motiva a los estudiantes a iniciar su carrera profesional en el sector del turismo y la hostelería. Se examina empíricamente la relación entre la adaptabilidad profesional y el optimismo de los estudiantes y su efecto en la intención vocacional futura.

Los resultados revelan que el optimismo profesional influye positivamente en la adaptabilidad profesional y en la intención profesional futura, respectivamente. Por el contrario, la adaptabilidad profesional influye negativamente en la intención vocacional futura. Además, el optimismo profesional tiene un efecto mediador en la relación entre la adaptabilidad profesional y la intención vocacional futura. Los resultados podrían beneficiar a los educadores en la orientación profesional de los estudiantes y a los profesionales de la industria en el desarrollo de estrategias eficaces de gestión de la carrera profesional de los jóvenes talentos en sus respectivas organizaciones.

La aplicación de la Teoría de la Construcción de la Carrera extraída de la psicología vocacional es adecuada para aportar conocimientos y perspectivas al desarrollo de la investigación sobre carreras profesionales en turismo y hostelería. Este estudio contribuye a llenar el vacío de conocimientos sobre la adaptación de la carrera profesional, el optimismo profesional y la intención de carrera futura.

The purpose of this study is to develop a model that accurately forecasts hotel room cancelations and further determines the key cancelation drivers.

Predictive modeling, specifically the machine learning methods, is used to forecast room cancelations and identify the main cancelation factors.

By using three different classification algorithms, this study demonstrates that hotel room cancelation can be accurately predicted using XGBoost, as well as the ensemble method involving Support Vector Machine, Random Forest and XGBoost.

This study attempted to forecast hotel room cancelations by applying a relatively new method, machine learning. By implementing predictive modeling, one of the most emerging and innovative research methods, this study ultimately provides prediction suggestions in various aspects and levels for hotel management operations.

本研究旨在开发一个能够准确预测酒店客房取消的模型, 并进一步确定主要的取消因素。

采用预测建模, 具体来说是机器学习方法, 来预测客房取消, 并识别主要的取消因素。

通过使用三种不同的分类算法, 本研究表明使用XGBoost以及涉及支持向量机、随机森林和XGBoost的集成方法可以准确预测酒店客房取消。

本研究尝试通过应用相对较新的方法, 即机器学习, 来预测酒店客房取消。通过实施预测建模, 这是目前新兴和创新的研究方法之一, 本研究最终为酒店管理运营在各个方面和层面提供了预测建议。