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Many genuine aspects of the high level behaviour of the nervous system (NS) can be understood in terms of co‐operative processes among neurons computing at the algorithmic level. This conception of the NS is applied to the study of the co‐operative control of incompatible modes of behaviour generally associated to reticular formation. The KM space is defined to generalise the problems of modal decision. Some drastic convergence agreement algorithms in the mode selection are proposed in such a way that the NS is stable in situations of lesion or cortical inhibition which eleminates the participation of a large number of reticular units.

The significance of the McCulloch‐Pitts formal neural net theory is still nowadays frequently misunderstood at present, and their basic units are wrongly considered as factual models for neurons. As a consequence, the whole original theory and its later addenda are unreasonably criticized for their simplicity. But, as it was proved then and since, the theory is after the modular neurophysiological counterpart of logical machines, so that it actually provides biologically plausible models for automata, Turing Machines etc and not viceversa. In its true context, no theory has surpassed its proposals. In McCulloch and Pitts Memoriam and for the sake of future theoretical research, we stress this important historical point, including also some recent results on the neurophysiological counterparts of modular arbitrary probabilistic automata.

This paper aims to provide a comprehensive review of research on robotics in travel, tourism and hospitality, and to identify research gaps and directions for future research.

This paper analyzes 131 publications published during 1993-2019, identified via Scopus, Web of Science, ResearchGate, Academia.edu and Google Scholar. It offers quantitative analysis of frequencies and cross-tables and qualitative thematic analysis of the publications within each of seven identified domains.

The paper identifies “Robot,” “Human,” “Robot manufacturer,” “Travel/tourism/hospitality company,” “Servicescape,” “External environment” and “Education, training and research” as the research domains. Most research studies are dedicated to robots in restaurants, airports, hotels and bars. Papers tend to apply engineering methods, but experiments and surveys grow in popularity. Asia-Pacific countries account for much of the empirical research.

The analysis was limited to publications indexed in four databases and one search engine. Only publications in English were considered. Growing opportunities for those who are anxious to publish in the field are identified. Importantly, emerging research is branching out from the engineering of robots to the possibilities for human/robot interactions and their use for service providers, opening up new avenues of research for tourism and hospitality scholars.

The paper identified a myriad of application areas for robots across various tourism and hospitality sectors. Service providers must critically think about how robots affect the servicescape and how it needs to be adjusted or re-imagined to ensure that robots and employees can augment the service experiences (co-)created within it.

This is the first study to systematically analyze research publications on robotics in travel, tourism and hospitality.

本论文全面评论了在旅游酒店业中的机器人技术的研究, 并指出文献缺口和未来研究方向。

本论文分析了在1993年至2019年发布在Scopus、Web of Science、ResearchGate、Academia.edu、和Google Scholar的131篇文献。本论文对文献做了一系列定量分析, 包括频率分析、交叉表、定性文本分析、在七大确立的领域中对每个领域的文献进行分析。

本论文确立了七个研究领域：机器人、人类、机器生产者、旅游酒店企业、Servicescape、外部环境、和教育培训和研究。大多数文献集中在对饭店、机场、酒店、和酒吧的机器人研究。文献往往采用工程手段进行研究, 但是实验和问卷方式正在呈增长趋势。亚太国家占据大多数实证研究作品。

本论文样本库局限于四个数据库和一个搜索引擎。只有英文文献被采样。本论文为对相关领域感兴趣的学者指出研究方向。重要的是, 本论文发现用工程角度研究机器人的文献有了分支, 有一小部分文献开始着手研究人/机器人交互和其在服务过程中的使用的研究, 这对旅游酒店学者提供新研究视角。

本论文指出了一系列有关旅游酒店领域中机器人的应用。服务商必须重视机器人如何影响Servicescape以及如何审视机器人与人的交互, 确保其与员工加强消费者的服务体验（价值共创）。

本论文是首篇系统评论旅游酒店领域中机器人研究文献的文章。

关键词：机器人、机器人经济、机器人设计、机器人使用、Servicescape、rService、人-机器人交互、研究议程

The purpose of this study is to review recent work in the robotics literature and identify future opportunities for consumer/tourist experience research in human-robot interactions (HRIs).

The paper begins by covering the framework of robotic agent presence and embodiment that are relevant for HRI. Next, the paper identifies future opportunities for hospitality and tourism scholars to undertake consumer/tourist experience research in HRIs.

The result of this study provided potential directions for advancing theoretical, methodological and managerial implications for tourism experience research in HRI.

Concepts from robotics research are diffusing into a range of disciplines, from engineering to social sciences. These advancements open many unique, yet urgent, opportunities for hospitality and tourism research.

This paper illustrates the speed at which robotics research is progressing. Moreover, the concepts reviewed in this research on robotic presence and embodiment are relevant for real-world applications in hospitality and tourism.

Developments in robotics research will transform hospitality and tourism experiences in the future.

This research is one of the early papers in the field to review robotics research and provide innovative directions to broaden the interdisciplinary perspective for future hospitality and tourism research.

This paper aims to research, identify and discuss the benefits and overall role of big data and artificial intelligence (BDAI) in the tourism sector, as this is depicted in recent literature.

A systematic literature review was conducted under the McKinsey’s Global Institute (Talwar and Koury, 2017) methodological perspective that identifies the four ways (i.e. project, produce, promote and provide) in which BDAI creates value. The authors enhanced this analysis methodology by depicting relevant challenges as well.

The findings imply that BDAI create value for the tourism sector through appropriately identified disseminations. The benefits of adopting BDAI strategies include increased efficiency, productivity and profitability for tourism suppliers combined with an extremely rich and personalized experience for travellers. The authors conclude that challenges can be bypassed by adopting a BDAI strategy. Such an adoption will stand critical for the competitiveness and resilience of existing established and new players in the tourism sector.

Besides identifying the benefits that BDAI brings in the tourism sector, the research proposes a guidebook to overcome challenges when introducing such new technologies. The exploration of the BDAI literature brings important implication for managers, academicians and consumers. This is the first systematic review in an area and contributes to the broader e-commerce marketing, retailing and e-tourism research.

本论文旨在研究、指出、和讨论大数据和人工智能（BDAI）在旅游业中的优势和整体作用。这些方面也在近文献中有所提到。

本论文采用系统综述方式, 在McKinsey’s Global Institute方法论的指导下, 确认BDAI可以在四种方面（预测、产出、提高、以及提供）创造价值。我们也通过阐述相关挑战来增强这个分析方法。

本论文结果显示BDAI通过适当的传播方式来为旅游业中创造价值。采用BDAI战略的好处包括：对旅游提供商带来高效、多产、盈利, 以及对旅游者们带来极度丰富和个性化的旅游体验。我们还总结了采取BDAI战略带来的诸多挑战。采用BDAI战略对旅游业中现有和新参与者的竞争力和弹性起到至关重要的作用。

除了指出了旅游业中BDAI带来的优势, 本论文还提出了一个指南, 来指导当新科技被引进时如何克服挑战。本论文通过对BDAI文献的梳理, 其文献综述结果对经理、学者、和消费者都有重要的启示作用。本论文是首篇在BDAI领域的系统综述, 对拓展电子商务营销、零售、和电子旅游科研有着重大贡献。

The purpose of this study is to explore consumer reviews with robotics based on the five dimensions for evaluating user experiences (i.e. embodiment, emotion, human-oriented perception, feeling of security and co-experience), as derived from research in human-robot interactions (HRI).

The study first reviews the five dimensions for evaluating user experiences in HRI and then analyzes user experiences with robotics at four hotels (i.e. Yotel New York, Aloft Cupertino, Henn-na Hotel Japan and Marriott Residence Inn LAX) based on reviews on TripAdvisor, Agoda, Yelp and Booking.com.

The findings highlight the influence of robotic embodiment and human-oriented perceptions on consumer experiences. The findings also suggest that users and robots can co-create novel experiences, with some guests even proactively seeking new opportunities to interact and communicate with robots to develop a certain level of “relationship” with them.

An understanding of user experiences from HRIs can inform future hospitality and tourism research and management.

This study contributes to hospitality and tourism management by highlighting current practices with robotics to suggest areas of improvements for enhancing future consumer experiences.

Consumer experiences will change rapidly as hospitality and tourism management deploys robotics in the future.

This is one of the early studies in the field to explore consumer experiences with robotics based on the five dimensions for evaluating user experiences from research in HRI. In doing so, this study provides a number of theoretical and managerial implications relevant for hospitality and tourism research and practice.

The paper is concerned with static plants described by a knowledge representation in the form of relations or logical formulas with unknown parameters. The learning algorithms consisting of step‐by‐step knowledge validation and updating have been presented for different versions. The theorems concerning the convergence of the learning processes have been given for the open‐loop and closed‐loop learning decision‐making system. The extension for the case with uncertain observations has been suggested. Simple examples illustrate the presented approach.

The definitions and basic properties of so called uncertain variables are presented. The uncertain variables are described by certainty distributions given by an expert and characterizing approximate values of the variables. Control problems for uncertain systems with static and dynamic plants are considered. A method of the stability analysis for a system with uncertain parameters is described. Simple examples illustrate the presented approaches.

Internet of Things (IoT) interconnects many heterogeneous devices to each other, collecting and processing large volumes of data for decision making without human intervention. However, the information security concern it brings has attracted quite a lot of attention, and, at this stage, the smart step would be to analyze the security issues of IoT platform and get to the state of readiness before embarking upon this attractive technology. The purpose of this paper is to address these issues.

IoT risk assessment through the application of the analytical hierarchy process (AHP), a favorite multi-criteria decision making technique, is proposed. The IoT risks are prioritized and ranked at different layers, before which a well-defined IoT risk taxonomy is defined comprising of 25 risks across six layers of the IoT model for developing control and mitigation plans for information security of IoT.

People and processes layer, network layer and applications layer are the top three critical layers with risks like the lack of awareness, malware injection, malicious code injection, denial of service and inefficient policies for IoT practice get the highest priority and rank. Pareto analysis of the overall risk factors revealed that the top ten factors contribute to 80 percent of the risks perceived by information security experts.

The study focuses only on certain predefined constructs or layers of the IoT model traced from legacy studies. It is essential to re-look these constructs on a timely basis to prolong the results’ validity. The study’s empirical scope is confined only to the risk perception of select IoT experts and does not encompass a broader segment of the IoT ecosystem. Therefore, the risks assessment may not be sweeping to a bigger audience.

The study implications are two-fold: one it consolidates the earlier siloed works to intensify the need for risk assessment in the IoT domain, and second the study brings yet another contextual avenue of extending the application AHP and Pareto principle combination. The paper also draws specific critical organizational interventions about IoT risks. A comprehensive approach to prioritizing and ranking IoT risks are present in this research paper.

The contribution of this study to the benchmarking of IoT risk assessment is two-fold. One, a comprehensive risk assessment taxonomy is proposed, and two, the risks are prioritized and ranked to give a convincing reference for the organizations while making information security plans for IoT technology.

This paper aims to propose a system for the semantic annotation of audio‐visual media objects, which are provided in the documentary domain. It presents the system's architecture, a manual annotation tool, an authoring tool and a search engine for the documentary experts. The paper discusses the merits of a proposed approach of evolving semantic network as the basis for the audio‐visual content description.

The author demonstrates how documentary media can be semantically annotated, and how this information can be used for the retrieval of the documentary media objects. Furthermore, the paper outlines the underlying XML schema‐based content description structures of the proposed system.

Currently, a flexible organization of documentary media content description and the related media data is required. Such an organization requires the adaptable construction in the form of a semantic network. The proposed approach provides semantic structures with the capability to change and grow, allowing an ongoing task‐specific process of inspection and interpretation of source material. The approach also provides technical memory structures (i.e. information nodes), which represent the size, duration, and technical format of the physical audio‐visual material of any media type, such as audio, video and 3D animation.

The proposed approach (architecture) is generic and facilitates the dynamic use of audio‐visual material using links, enabling the connection from multi‐layered information nodes to data on a temporal, spatial and spatial‐temporal level. It enables the semantic connection between information nodes using typed relations, thus structuring the information space on a semantic as well as syntactic level. Since the description of media content holds constant for the associated time interval, the proposed system can handle multiple content descriptions for the same media unit and also handle gaps. The results of this research will be valuable not only for documentary experts but for anyone with a need to manage dynamically audiovisual content in an intelligent way.