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This study aims to determine the barriers hindering the incorporation of blockchain technology (BCT) in two key service industries – hotel and health care – as well as to assess their readiness for implementing BCT after overcoming the barriers.

The barriers of this study are determined through two phases: a review of prior literature and obtaining expert opinions, which are then analyzed to identify specific barriers that are impeding the incorporation of BCT. Moreover, to generate a blockchain implementation reluctance index (BIRI), this study presents an interval-valued intuitionistic fuzzy set (IVIFS) that uses graph theory and matrix approach (GTMA). The permanent function in the GTMA approach is computed using the PERMAN algorithm. Finally, to compare the readiness of the hotel and health-care industries to adopt BCT, the BIRI values are plotted and evaluated.

The barriers identified by this study are listed under five major headings, namely, financial, operational, behavioral, technical and legal. This study revealed that the operational and technical barriers of BCT are critically hindering its widespread integration in hotel and health-care industries. Furthermore, on comparing the BIRI values of both industries, the result suggested that the hotel industry needs to work more on these barriers to effectively incorporate BCT. Besides the comparison, the BIRI values clearly indicate that both industries have to put a lot of effort into the mitigation of the barriers found by this study to successfully integrate BCT.

The experts’ opinions are used to evaluate the identified barriers, which raises the chance that the opinions are prejudiced based on the experts’ perspectives and ideologies. The sensitivity of decision-maker loads toward preference outcomes is not analyzed in this manuscript. Therefore, any recent sensitivity analysis may be considered a prospective field for future research. This study applies a multicriteria decision-making (MCDM) approach, IVIFS–GTMA, which limits the evaluation of the influence caused by individual barriers on the integration of BCT in the hotel and health-care industries. Henceforth, in future investigations, alternative MCDM methods may be used to analyze individual barriers.

According to the findings, if the hotel or health-care industry aims to incorporate BCT in its supply chain operations, it is recommended to emphasize more on the operational barriers along with the technical and behavioral barriers. The barriers mentioned in this manuscript can be used as guidance for developers in their development activities, such as scalability concerns, establishment costs, the 51% attack and the inefficient nature of BCT. Furthermore, they may address the potential users’ negative perceptions about security, privacy, trust and risk avoidance through creatively developed blockchain solutions to promote BCT implementation.

To the best of the author’s knowledge, this is the first study that identifies barriers toward BCT incorporation in the major service industries, i.e. hotel and health care. Moreover, this is the first study that compares the preparedness of the hotel and health-care industries to determine the industry that requires more work to implement BCT.

A separate study of the different behavioral biases does not allow for a full understanding of the complexity and stability of the heterogeneity of beliefs. Therefore, through a more global view of these anomalies, the authors wish to show that they can converge on a single concept, which is the heterogeneity of beliefs.

It is therefore essential to stress that the importance of this study is mainly reflected in the methodological approach used in the construction and analysis of the map and not only in the results achieved. This contribution states that structural analysis, as a means of building the cognitive map, can facilitate the task of investors and other decision-makers, in the identification and analysis of the heterogeneity of beliefs that can therefore guide investors' strategy in decision-making.

The authors have studied the behavior of the investor and its way of interpreting the information and the authors have emphasized the value of studying the concept of heterogeneity of beliefs in its complexity. So that part of the work seems to be relevant and crucial to filling, if you will, that void. In this sense, the authors have shown that behavioral abnormalities are multidimensional concepts: “self-deception”, “cognitive bias”, “emotional bias” and “social bias”.

In particular, this article will aim to achieve the objective of proposing a model for measuring the heterogeneity of beliefs. Thus, the authors want to show that the heterogeneity of beliefs can be measured directly through the different behavioral anomalies.

This study aims to model tourist activities in a network and explore the properties of the network. Such network enables the author to explain and quantify how tourist activities are connected in determining tourist consumption as well as the organization of destination supply.

The author developed a network formation mechanism to create edges between nodes based on the joint probability of a pair of activities undertaken by tourists at a destination. By adjusting network sparsity, the author created an ensemble of four topologically similar networks for empirical testing. The author used tourist activity data of Hong Kong inbound tourists to test the network model.

The author found a robust hub–periphery topological structure of the tourist activity network. In addition, the network is featured by high clustering, short diameter and positive correlations between four node centralities, namely, degree, closeness, betweenness and eigenvector centralities. The author also generated the k-cores of the networks to further unravel the structure of hub nodes. The author found that the k-cores are dominated by tourist activities related to shopping or sightseeing, suggesting the high complementarity of these activities.

This study provides a different lens through which tourist consumption can be understood from a macroscopic angle by examining network topology and from a microscopic angle by examining node centralities.

To the best of the author’s knowledge, this is the first study attempting to model tourist activity and consumption in a network and explore the properties of the network. Not only has this study provided a new real-world network for network research, but it has also suggested an innovative modeling approach for tourist behavior research.

This tourism study delves into the universal impact of authenticity on tourists' preferences. This study aims to enhance understanding and present a model delineating authenticity's intricate relationship with behavioral intention, involvement and nostalgia.

The research entails administering a sample survey to travelers located in the departure lounge of Macau International Airport. Ultimately, 499 fully completed questionnaires are obtained through convenience sampling. The analysis of the collected data incorporates an innovative method, using a quadratic model.

Results undeniably validate that a destination's perceived authenticity significantly influences tourists' intentions, engagement and nostalgic sentiments. Findings strongly support the assertion that this authenticity demonstrates a nonlinear pattern in its association with behavioral intention, involvement and nostalgia.

Through quantitative analysis and interpretation, this study has advanced the comprehension of the interplay between authenticity and tourism. It introduces a novel perspective that adds depth to the broader understanding in this domain. This foundational research is crucial for acknowledging the unique contributions made by this study to the fields of tourism and authenticity.

这项旅游研究深入探讨了真实性对游客偏好的普遍影响。它旨在增强理解并提出一个模型来描述真实性与行为意图、参与和怀旧之间的复杂关系。

该研究需要对位于澳门国际机场候机室的旅客进行抽样调查。最终通过便利抽样获得完整填写的问卷499份。对收集的数据的分析采用了一种创新方法, 利用二次方模型。

结果无可否认地证实, 目的地的感知真实性会显着影响游客的意图、参与度和怀旧情绪。研究结果有力地支持了这一主张, 即这种真实性在其与行为意图、参与和怀旧的关联中表现出一种非线性模式。

通过定量分析和解释, 这项研究增进了我们对真实性与旅游之间的回应的理解。它引入了一种新颖的视角, 加深了我们对这一领域更广泛的理解。这一基础研究为承认本研究对旅游和真实性领域做出了独特贡献。

Este estudio turístico profundiza en el impacto universal de la autenticidad en las preferencias de los turistas. Pretende mejorar la comprensión y presentar un modelo que delinee la intrincada relación de la autenticidad con la intención conductual, la implicación y la nostalgia.

La investigación consistió en administrar una encuesta por muestreo a los viajeros situados en la sala de embarque del Aeropuerto Internacional de Macao. Finalmente, se obtuvieron 499 cuestionarios totalmente cumplimentados mediante un muestreo de conveniencia. El análisis de los datos recogidos incorpora un método innovador, utilizando un modelo cuadrático.

Los resultados validan sin lugar a duda que la autenticidad percibida de un destino influye significativamente en las intenciones, la implicación y los sentimientos nostálgicos de los turistas. Los hallazgos apoyan firmemente la afirmación de que esta autenticidad demuestra un patrón no lineal en su asociación con la intención conductual, la implicación y la nostalgia.

Mediante el análisis cuantitativo y la interpretación, este estudio ha hecho avanzar nuestra comprensión de la interacción entre autenticidad y turismo. Introduce una perspectiva novedosa que añade profundidad a nuestra comprensión más amplia en este ámbito. Esta investigación fundacional es crucial para reconocer las contribuciones únicas de este estudio a los campos del turismo y la autenticidad.

The purpose of the paper is to present an integrated methodology for identifying trends in a particular subject area based on a combination of advanced text mining and expert methods. The authors aim to test it in an area of clinical psychology and psychotherapy in 2010–2019.

The authors demonstrate the way of applying text-mining and the Word2Vec model to identify hot topics (HT) and emerging trends (ET) in clinical psychology and psychotherapy. The analysis of 11.3 million scientific publications in the Microsoft Academic Graph database revealed the most rapidly growing clinical psychology and psychotherapy terms – those with the largest increase in the number of publications reflecting real or potential trends.

The proposed approach allows one to identify HT and ET for the six thematic clusters related to mental disorders, symptoms, pharmacology, psychotherapy, treatment techniques and important psychological skills.

The developed methodology allows one to see the broad picture of the most dynamic research areas in the field of clinical psychology and psychotherapy in 2010–2019. For clinicians, who are often overwhelmed by practical work, this map of the current research can help identify the areas worthy of further attention to improve the effectiveness of their clinical work. This methodology might be applied for the identification of trends in any other subject area by taking into account its specificity.

The paper demonstrates the value of the advanced text-mining approach for understanding trends in a subject area. To the best of the authors’ knowledge, for the first time, text-mining and the Word2Vec model have been applied to identifying trends in the field of clinical psychology and psychotherapy.

Despite ongoing research into archival metadata standards, digital archives are unable to effectively represent records in their appropriate contexts. This study aims to propose a knowledge graph that depicts the diverse relationships between heterogeneous digital archive entities.

This study introduces and describes a method for applying knowledge graphs to digital archives in a step-by-step manner. It examines archival metadata standards, such as Records in Context Ontology (RiC-O), for characterising digital records; explains the process of data refinement, enrichment and reconciliation with examples; and demonstrates the use of knowledge graphs constructed using semantic queries.

This study introduced the 97imf.kr archive as a knowledge graph, enabling meaningful exploration of relationships within the archive’s records. This approach facilitated comprehensive record descriptions about different record entities. Applying archival ontologies with general-purpose vocabularies to digital records was advised to enhance metadata coherence and semantic search.

Most digital archives serviced in Korea are limited in the proper use of archival metadata standards. The contribution of this study is to propose a practical application of knowledge graph technology for linking and exploring digital records. This study details the process of collecting raw data on archives, data preprocessing and data enrichment, and demonstrates how to build a knowledge graph connected to external data. In particular, the knowledge graph of RiC-O vocabulary, Wikidata and Schema.org vocabulary and the semantic query using it can be applied to supplement keyword search in conventional digital archives.

Cross-laminated timber (CLT) is an innovative construction material that provides a balanced mix of structural stiffness, fabrication flexibility and sustainability. CLT development and innovation diffusion require close collaborations between its supply chain architectural, engineering, construction and manufacturing (AECM) stakeholders. As such, the purpose of this study is to provide a preliminary understanding of the knowledge diffusion and innovation process of CLT construction.

The study implemented a longitudinal social network analysis of the AECM companies involved in 100 CLT projects in the UK. The project data were acquired from an industry publication and decoded in the form of a multimode project-company network, which was projected into a single-mode company collaborative network. This complete network was filtered into a four-phase network to allow the longitudinal analysis of the CLT collaborations over time. A set of network and node social network analysis metrics was used to characterize the topology patters of the network and the centrality of the companies.

The study highlighted the scale-free structure of the CLT collaborative network that depends on the influential hubs of timber manufacturers, engineers and contractors to accelerate the innovation diffusion. However, such CLT supply collaborative network structure is more vulnerable to disruptions due to its dependence on these few prominent hubs. Also, the industry collaborative network’s decreased modularity confirms the maturity of the CLT technology and the formation of cohesive clusters of innovation partners. The macro analysis approach of the study highlighted the critical role of supply chain upstream stakeholders due to their higher centralities in the collaborative network. Stronger collaborations were found between the supply chain upstream stakeholders (timber manufacturers) and downstream stakeholders (architects and main contractors).

The study contributes to the field of industrialized and CLT construction by characterizing the collaborative networks between CLT supply chain stakeholders that are critical to propose governmental policies and industry initiatives to advance this sustainable construction material.

Adopting a self-congruence theory (SCT) and service dominant logic (SDL)-informed perspectives; we develop a model that investigates the interface between social media involvement (SMI), self-brand congruence (SBC), customer-brand engagement (CBE), brand co-creation behavior (BCB), brand interactivity and behavioral intentions (BIN) with luxury service hotel–brands.

We test a sample of hotel-customers to probe this matter using partial least squares structural equation modeling.

The results revealed that SBC and SMI positively impact CBE and BCB and behavioral intentions. The findings also exposed SMI’s and SBC’s indirect effect on customers' BCB and behavioral intentions, mediated through CBE. Finally, the results explored the moderating role of brand interactivity to enhance our model’s explanatory power.

We focus on SMI, CBE and BCB. This study contributes to the existing marketing and hospitality management research and spawns rich opportunities for further studies.

The study article assists marketers in comprehending the CBE-based antecedents and consequences and facilitates their increasing CBE, BCB and behavioral intentions.

While the growing insight into social media, customer engagement and co-creation within the service industries, little remains accredited concerning the link of these and related variables in the luxury hotel-brand context.

Career plateau and employee silence are negative employee management phenomena that should be overcome but are challenging. However, relatively speaking, when employees reach a particular career stage, it is inevitable that the hierarchical plateau in the career plateau will occur, while the phenomena of employee silence have the chance to improve. This paper aims to study the influence mechanism of the career plateau on employee silence in an uncertain environment and then provides theoretical support for enhancing the organizational phenomenon of employee silence.

After considering the effects of career plateau and social desirability of employee silence, this paper obtained 313 samples based on the pilot survey, which were collected anonymously online and offline. Based on passing the data quality test, this experiment uses hierarchical regression, Bootstrap method, interaction graph and slope test to test the mediating variable

The results show a significant positive correlation between career plateau and employees' silent behavior. Affective commitment plays a partial mediating role between career plateau and employees' silent behavior. Organizational justice not only negatively moderated the relationship between career plateau and affective commitment but also negatively moderated the indirect effect of career plateau on silent behavior through affective commitment.

First, based on the theory of uncertainty management and social exchange theory, this paper develops a behavioral response to the organizational environment based on the principle of fair exchange when employees perceive an uncertain environment. This study innovatively applied the two theories together in one study, establishing a link between the two theories. Second, this study explores the influence of career plateau on employee silence and empirically tests the silent behavior based on the previous division of three dimensions of career plateau. The third study explores affective commitment, the black box of the relationship between career plateau and employee silence. This research also enriches the related research on affective commitment.

Purchasing real estate is one of the most important and complex decisions in a life of an individual, which should take numerous factors into account. The purpose of this research is to identify which behavioral factors significantly affect the intention to buy real estate. Since the real estate market is continuously changing, along with other economic and life conditions, it is expected that different generations have different characteristics which affect their behavior; therefore, it is important to analyze generational influence on buyers' behavior.

A survey analysis was conducted on a sample of 434 respondents in Croatia. Partial least squares structural equation modeling was used to obtain the results. The moderating effect of generational affiliation was observed.

Overconfidence significantly affects intention to buy real estate, but it doesn't affect the level of importance individuals give to financial factors. On the other hand, herding significantly affects the level of importance given to financial factors, whereas it does not directly affect buying intention. A significant moderating effect of generational affiliation was found for the impact of overconfidence on financial factors, suggesting a negative effect for younger generations and a positive effect for older generations.

This research proposes a novel unique model with both behavioral and financial factors as predictors of the intention to buy real estate, together with generational differences in buyers' behavior. Understanding normal human behavior is crucial to determine how buyers' decisions and intentions change under the influence of certain biases or characteristics such as generational affiliation.