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This study aims to analyze the importance and performance of customer-facing technologies in luxury hotels. The study also assessed differences between and within the four generations in the importance-performance analysis (IPA).

Data were collected using a Qualtrics panel of recent luxury hotel customers in the USA belonging to all four generations. The cross-generational IPA was conducted using t-tests and (ANAOVA).

The IPA matrix concentrated most technology items in either low importance – low performance or high importance – high performance quadrants. One-way ANOVA revealed significant differences between generations on the importance ratings of all technology items except wireless charging power solutions and on the performance ratings of all technology items. Furthermore, post hoc tests indicated that millennials rated luxury technology most favorably among the four cohorts, followed by generations Z, X and Baby Boomers. In addition, significant differences between the importance and performance of many technology items within each generational cohort were observed. Overall, Wi-Fi was unanimously ranked across generations as the most important technology among luxury guests, but it was the only one that scored lower in performance than importance.

The findings of this study contribute to hospitality scholarship in two primary ways: the importance and performance of technology and generational differences. The results advance the understanding of the impact of generational factors on customer-facing technological adoptions in the luxury hotel sector.

Technologies that are pervasive in the home also become vital offerings for hotels. The more pervasive technology, the more a luxury hotel must work to ensure that it performs at optimal levels. Additionally, which technologies are most important to targeted generations are provided so practitioners may budget for their implementation.

This research is a pivotal step forward in unraveling the intricate interplay between generational factors and technological evaluations, providing a foundation for future research and practical applications in a rapidly evolving technological landscape in the hospitality industry.

This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic response signals.

The paper conducts time-frequency analysis on signals of pavement dynamic response initially. It also uses two common noise reduction methods, namely, low-pass filtering and wavelet decomposition reconstruction, to evaluate their effectiveness in reducing noise in these signals. Furthermore, as these signals are generated in response to vehicle loading, they contain a substantial amount of data and are prone to environmental interference, potentially resulting in outliers. Hence, it becomes crucial to extract dynamic strain response features (e.g. peaks and peak intervals) in real-time and efficiently.

The study introduces an improved density-based spatial clustering of applications with Noise (DBSCAN) algorithm for identifying outliers in denoised data. The results demonstrate that low-pass filtering is highly effective in reducing noise in pavement dynamic response signals within specified frequency ranges. The improved DBSCAN algorithm effectively identifies outliers in these signals through testing. Furthermore, the peak detection process, using the enhanced findpeaks function, consistently achieves excellent performance in identifying peak values, even when complex multi-axle heavy-duty truck strain signals are present.

The authors identified a suitable frequency domain range for low-pass filtering in asphalt road dynamic response signals, revealing minimal amplitude loss and effective strain information reflection between road layers. Furthermore, the authors introduced the DBSCAN-based anomaly data detection method and enhancements to the Matlab findpeaks function, enabling the detection of anomalies in road sensor data and automated peak identification.

Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance.

In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis.

Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation.

The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals.

Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs’ CE performance.

This study uses a comprehensive theoretical framework that combines social cognitive theory and neighborhood effect to investigate the influence of neighborhood effects on farmers’ outcome expectations, observational learning and self-efficacy. This study aims is to analyze the mechanisms that underlie the adoption of social media by farmers for knowledge exchange in the agricultural context. Specifically, this research explores the role of neighborhood effects, outcome expectations, observational learning and self-efficacy in shaping farmers’ decision-making process regarding the use of social media platforms for exchanging agricultural knowledge.

The study data was collected through a sample survey conducted among 570 agricultural households residing in the provinces of Thai Nguyen, Cao Bang, Bac Kan and Phu Tho, located in the northern region of Vietnam. To analyze the data, structural equation modeling was used as the statistical technique of choice.

The findings of the study indicate a significant influence of neighborhood effects on outcome expectations, observational learning and self-efficacy. These factors, derived from social cognitive theory, also exhibit a positive association with farmers’ adoption of social media for knowledge exchange. Additionally, the study highlights that neighborhood contribute to a favorable adoption of social media among farmers via outcome expectations, observational learning, and self-efficacy.

The study is limited in examining farmers’ social media adoption for agriculture knowledge exchange in Northern mountainous area of Vietnam. This study could be replicated across various regions or nations, providing comparative insights into the adoption of social media among farmers for knowledge exchange.

The study findings suggest practical and innovative means to promote farmers’ social media adoption for agriculture knowledge exchange.

This study presents a pioneering approach by integrating social cognitive theory and neighborhood effect to elucidate the factors influencing farmers’ adoption of social media for the purpose of agriculture knowledge exchange.

Against the background of the I50 paradigm, this paper queries in what ways blockchain and blockchain-based applications deployed in the smart city context facilitate the integration of the I50 paradigm in smart urban contexts.

A mixed methods approach is applied. First, by means of desk research and thematic literature review, a conceptual model integrating the I50 paradigm, smart city and blockchain-based solutions is built. Second, science mapping bibliometric analysis (SciMat) based on keywords’ co-occurrence is applied to a sample of 491 research articles to identify key domains of blockchain-based applications’ use in smart city. Third, a semi-systematic literature review complements insights gained through SciMat. Fourth, the findings are interpreted through the precepts of the conceptual model devised earlier.

The key blockchain-based applications in smart cities pertain to two domains, i.e. the foundational, service facilitation-oriented domain, including security (and safety), networks, computing, resource management and the service delivery-oriented domain, including mobility, energy and healthcare. Blockchain serves as the key building block for applications developed to deliver functions specific to each of the thus identified domains. A substantial layering of blockchain-based tools and applications is necessary to advance from the less to the more complex functional domains of the smart city.

At the conceptual level, the intricacies of the (making of the) I50 paradigm are discussed and a case for I50 – smart city – blockchain nexus is made. Easton’s input–output model as well as constructivism is referenced. At the empirical level, the key major domains of blockchain-based applications are discussed; those that bear the prospect of integrating the I50 paradigm in the smart city are highlighted. At the methodological level, a strategic move is made aimed at restoring the literature review’s role as subservient to the key line of exploration, to justify and ultimately support it, rather than to showcase the literature review as the ultimate purpose for itself.

Contemporary technological disruptions are espoused as though they stimulate sustainable growth in the built environment through the Green Internet of Things (G-IoT). Learning from discipline-specific experiences, this paper articulates recent advancements in the knowledge and concepts of G-IoT in relation to the construction and smart city sectors. It provides a scoping review for G-IoT as an overlooked dimension. Attention was paid to modern circularity, cleaner production and sustainability as key benefits of G-IoT adoption in line with the United Nations’ Sustainable Development Goals (UN-SDGs). In addition, this study also investigates the current application and adoption strategies of G-IoT.

This study uses the Preferred Reporting Items for Systematic and Meta-Analyses (PRISMA) review approach. Resources are drawn from Scopus and Web of Science repositories using apt search strings that reflect applications of G-IoT in the built environment in relation to construction management, urban planning, societies and infrastructure. Thematic analysis was used to analyze pertinent themes in the retrieved articles.

G-IoT is an overlooked dimension in construction and smart cities so far. Thirty-three scholarly articles were reviewed from a total of 82 articles retrieved, from which five themes were identified: G-IoT in buildings, computing, sustainability, waste management and tracking and monitoring. Among other applications, findings show that G-IoT is prominent in smart urban services, healthcare, traffic management, green computing, environmental protection, site safety and waste management. Applicable strategies to hasten adoption include raising awareness, financial incentives, dedicated work approaches, G-IoT technologies and purposeful capacity building among stakeholders. The future of G-IoT in construction and smart city research is in smart drones, building information modeling, digital twins, 3D printing, green computing, robotics and policies that incentivize adoption.

This study adds to the normative literature on envisioning potential strategies for adoption and the future of G-IoT in construction and smart cities as an overlooked dimension. No previous study to date has reviewed pertinent literature in this area, intending to investigate the current applications, adoption strategies and future direction of G-IoT in construction and smart cities. Researchers can expand on the current study by exploring the identified G-IoT applications and adoption strategies in detail, and practitioners can develop implementation policies, regulations and guidelines for holistic G-IoT adoption.

This study aims to provide an overview of the evolution of knowledge on smart destinations and identify the key issues addressed in the smart destination research domain, the main themes and sub-themes and research gaps in smart destination research as well as the future research agenda to address those gaps.

A bibliometric analysis of 409 studies published on smart destinations literature was conducted using the Bibliometrix R-package to provide a comprehensive review of studies published on smart destinations and identify the main research themes, gaps in the literature and future research opportunities.

Based on the research findings, a conceptual model of smart destination research has been proposed. This conceptual model can serve as a foundation for further knowledge generation in this research area. The findings also shed light on future research directions, highlighting research opportunities for the exploitation of cutting-edge innovations and digitalization across various dimensions of smart destinations.

Although past research has paid attention to the theme of smart destinations, this work advances scientific knowledge by providing a foundation for a new smart destination management paradigm focusing on accessibility, sustainability, digitization, experience co-creation and creativity as milestones.

本研究旨在提供关于智慧目的地知识演变的概览, 并确定智慧目的地研究领域中涉及的关键问题、主要主题和子主题, 以及智慧目的地研究的研究空白, 同时提出未来研究议程以填补这些空白。

本研究利用 Bibliometrix R 软件对发表的409篇智慧目的地文献进行了文献计量分析, 以全面回顾关于智慧目的地的研究, 并确定主要研究主题、文献中的空白以及未来的研究机会。

基于研究结果, 本研究提出了智慧目的地研究的概念模型。该概念模型可作为进一步知识生成的基础。研究发现还为未来研究方向提供了启示, 强调了利用先进创新和数字化技术在智慧目的地各个维度上进行研究的机会。

尽管过去的研究关注了智慧目的地的主题, 但本研究通过提出以可达性、可持续性、数字化、体验共创和创意为里程碑的新智慧目的地管理范式, 推进了科学知识的发展。

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

This research paper explores how human resource management can embrace new perspectives to create smart and happy workplaces post-pandemic. Analysis of smart human resources and human resource analytics findings revealed opportunities to connect these areas and to use data-driven talent practices to optimize organizational and individual outcomes. The key results show that aligning smart technologies with competency development, while applying analytics ethically to elevate engagement, can transform competitive advantages. Major managerial insights from the paper include adopting smart tools to actively empower employees, and developing analytics measuring the impact of smart practices on happiness.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

In recent decades, a significant number of research contributions have been made to the intersection of digital technologies and the tourism industry. However, a thorough examination of digitalization and digital transformation in the tourism industry has not been given sufficient consideration. This study aims to provide a bibliometric review of digitalization and digital transformation research in the tourism industry and devise future research agendas to advance the research field.

This study uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) protocol and a bibliometric analysis to examine the research progress and scientifically map the research domain of digitalization and digital transformation in the tourism industry from 2002 to 2023 using bibliographic data retrieved from the Scopus and Web of Science.

This study presents the trends in publications and citations within the digitalization and digital transformation research domain in tourism. The findings also provide insights into the four primary clusters of the research field: digital innovation, smart tourism ecosystem, eTourism and smart destination experience. To further augment the application of digital transformation, this study offers several recommendations for future research on digitalization and digital transformation of the tourism industry.

This study provides valuable implications to researchers, managers and policymakers seeking to understand the current state and future research directions in tourism’s digitalization and digital transformation research field.

This study advances the research field of digitalization and digital transformation in the tourism industry by thoroughly examining the primary research clusters in the research corpus of the past two decades. Furthermore, it guides future research, thereby setting the stage for further progress in this domain.

近几十年来, 数字技术与旅游业的交叉领域做出了大量研究贡献。 然而, 对旅游业数字化和数字化转型的深入审视尚未得到充分考虑。本研究旨在对旅游业数字化和数字化转型研究进行文献计量回顾, 并制定未来的研究议程以推进该研究领域的发展。

本研究利用系统文献综述的科学程序和原理（SPAR-4-SLR）协议和文献计量分析来检验研究进展并科学地绘制旅游业数字化和数字化转型的研究领域 使用从 Scopus 和 Web of Science (WOS) 检索到的书目数据从 2002 年到 2023 年。

本研究呈现了旅游业数字化和数字化转型研究领域出版物和引用的趋势。 研究结果还提供了对该研究领域的四个主要集群的见解：数字创新、智能旅游生态系统、电子旅游和智能目的地体验。 为了进一步增强数字化转型的应用, 本研究为旅游业数字化和数字化转型的未来研究提出了几点建议。

本研究通过深入研究过去二十年研究语料库中的主要研究集群, 推进了旅游业数字化和数字化转型的研究领域。 此外, 它指导了未来的研究, 从而为该领域的进一步进展奠定了基础。

本研究为寻求了解旅游业数字化和数字化转型研究领域现状和未来研究方向的研究人员、管理者和政策制定者提供了有价值的启示。

En las últimas décadas, se ha realizado un número significativo de contribuciones de investigación a la intersección de las tecnologías digitales y la industria del turismo. Sin embargo, no se ha prestado suficiente atención a un examen exhaustivo de la digitalización y la transformación digital en la industria del turismo. Este estudio tiene como objetivo proporcionar una revisión bibliométrica de la investigación sobre digitalización y transformación digital en la industria del turismo y diseñar futuras agendas de investigación para avanzar en el campo de la investigación.

Este estudio utiliza el protocolo de Procedimientos y fundamentos científicos para revisiones sistemáticas de la literatura (SPAR-4-SLR) y un análisis bibliométrico para examinar el progreso de la investigación y mapear científicamente el dominio de investigación de la digitalización y la transformación digital en la industria del turismo. de 2002 a 2023 utilizando datos bibliográficos recuperados de Scopus y Web of Science (WOS).

Este estudio presenta las tendencias en publicaciones y citas dentro del dominio de investigación sobre digitalización y transformación digital en turismo. Los hallazgos también brindan información sobre los cuatro grupos principales del campo de investigación: innovación digital, ecosistema de turismo inteligente, turismo electrónico y experiencia de destino inteligente. Para aumentar aún más la aplicación de la transformación digital, este estudio ofrece varias recomendaciones para futuras investigaciones sobre la digitalización y la transformación digital de la industria turística.

Este estudio avanza en el campo de investigación de la digitalización y la transformación digital en la industria del turismo al examinar en profundidad los principales grupos de investigación en el corpus de investigación de las últimas dos décadas. Además, orienta la investigación futura, sentando así las bases para mayores avances en este ámbito.

Este estudio proporciona implicaciones valiosas para los investigadores, administradores y formuladores de políticas que buscan comprender el estado actual y las direcciones futuras de la investigación en el campo de la digitalización y la transformación digital del turismo.

This practitioner-focused article highlights a collaborative, school-wide project at a PDS that showcased elementary students’ strengths and talents. Based on the children’s book, The Smart Cookie (John, 2021), teachers and the university professor-in-residence developed professional learning communities, which inspired the creation of a space for all students to demonstrate ways in which they were “smart cookies” that aligned with our comprehensive mission of promoting inclusive practices.

Rooted in professional learning communities, teachers at our PDS spent the first half of the school year learning about chosen topics of social–emotional learning, stamina and neurodiversity. The Smart Cookie Project was created to demonstrate the connections between these topics. Students at the PDS were given the opportunity to create an original project that showcased their creativity, interests and talents. Projects were then displayed during a schoolwide showcase.

The impact of the project and the showcase demonstrated the importance of creating opportunities for both teacher and student innovation. The project brought the community together, allowed students to be viewed through strengths-based perspectives, helped teachers see how their own learning can positively impact their practice and emphasized the need for honoring student choice in the classroom.

The project discussed here can lend itself to fellow PDSs looking to adopt innovative instructional approaches, honor inclusive practices and situate students in places of strength.