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Social media fatigue (SMF) has been widely recognized; however, previous studies have included various concepts into a single fatigue construct. Fatigue has typically been explored from the stressor-strain-outcome (SSO) or stimulus-organism-response (SOR) perspectives. To further investigate SMF, the authors split it into the two constructs of exhaustion and disinterest. Furthermore, the authors introduced the concept of emotional labor and identified rules that may affect surface and deep acting strategies.

The authors designed and conducted a survey to collect data from social networking platform users.

Results from 364 users of social networking platforms supported most of the authors' hypotheses. First, most of the display rules affect the choice of deep or surface acting. Second, both types of acting lead to exhaustion, but only surface acting leads to disinterest. Third, discontinuance intention is affected by both types of fatigue.

This study contributes to SMF research by adding more antecedents (deep and surface acting) based on the emotional labor perspective and showing the impacts of communication rules on emotional labor. In addition, this study also distinguishes disinterest-style fatigue from exhaustion.

Studies have explored the determinants of customer advocacy because of customer advocacy's vital role in improving the efficiency and effectiveness of marketing. The current research complements the existing literature in the hospitality field by examining the association between restaurant innovativeness and customer advocacy while also investigating the mediating roles of self-image congruity and customer engagement.

The statistical software AMOS version 25 and bootstrapping were employed to test the hypotheses. Purposive sampling was employed for participant recruitment, and a self-administered questionnaire was used to collect data. Data were collected from Taiwanese customers who had dined at selected restaurants.

The results from 385 restaurant customers reported that self-image congruity had an indirect impact on customer advocacy through customer engagement. Customer advocacy was influenced by restaurant innovativeness through the mediation of customer engagement. The influence of restaurant innovativeness on customer advocacy was positively and sequentially mediated by self-image congruity and customer engagement.

Restaurant innovativeness is linked to customer advocacy through self-image congruity and customer engagement. Thus, restaurant managers should implement strategies focusing on innovativeness to improve self-image congruity and engagement among customers.

The current research may be the first to provide a research model that explores restaurant innovativeness, self-image congruity, customer engagement and customer advocacy in the hospitality context. This study also has practical implications for enhancing customer advocacy.

The purpose of this paper is to propose and validate a robust industrial control system. The aim is to design a Multivariable Proportional Integral controller that accommodates multiple responses while considering the process's control and noise parameters. In addition, this paper intended to develop a multidisciplinary approach by combining computational science, control engineering and statistical methodologies to ensure a resilient process with the best use of available resources.

Taguchi's robust design methodology and multi-response optimisation approaches are adopted to meet the research aims. Two-Input-Two-Output transfer function model of the distillation column system is investigated. In designing the control system, the Steady State Gain Matrix and process factors such as time constant (t) and time delay (?) are also used. The unique methodology is implemented and validated using the pilot plant's distillation column. To determine the robustness of the proposed control system, a simulation study, statistical analysis and real-time experimentation are conducted. In addition, the outcomes are compared to different control algorithms.

Research indicates that integral control parameters (K_i) affect outputs substantially more than proportional control parameters (K_p). The results of this paper show that control and noise parameters must be considered to make the control system robust. In addition, Taguchi's approach, in conjunction with multi-response optimisation, ensures robust controller design with optimal use of resources. Eventually, this research shows that the best outcomes for all the performance indices are achieved when Kp11 = 1.6859, Kp12 = −2.061, Kp21 = 3.1846, Kp22 = −1.2176, Ki11 = 1.0628, Ki12 = −1.2989, Ki21 = 2.454 and Ki22 = −0.7676.

This paper provides a step-by-step strategy for designing and validating a multi-response control system that accommodates controllable and uncontrollable parameters (noise parameters). The methodology can be used in any industrial Multi-Input-Multi-Output system to ensure process robustness. In addition, this paper proposes a multidisciplinary approach to industrial controller design that academics and industry can refine and improve.

This study aims to contribute to social identity theory in tourism by exploring the reflections of Chinese tourists visiting North Korea and how they negotiate their intergroup identity in this similar-others destination.

Data were collected via online platforms and in-depth interviews. A qualitative approach, i.e. thematic analysis, was used to analyse the two sets of data.

Results showed that when encountering North Koreans perceived as similar others amid the social, economic and political environments in which they were embedded, Chinese tourists often categorised themselves as ordinary tourists, preferentially treated tourists and vicarious tourists based on intergroup similarities to North Koreans. They also performed intergroup comparison to boost their self-esteem at group and collective levels and developed corresponding strategies to generate distinct emotional group commitments.

It is recommended that destinations reinforce the friendly and unique relationship with their similar-others source markets to improve their attractiveness. Destinations should also strive to enhance the experience of tourists from their similar-others markets by arousing their positive collective-level affection, emotional resonance and nostalgic memories and avoiding negative emotions.

This study offers a theoretical framework analysing the features of tourists’ social identities while visiting a similar-others destination, contributing to our understanding of the interactive and contingency nature of social identity in tourism, and responding to the call for addressing the broader social contexts in which tourists’ group identity is embedded.

本文致力于探索赴朝中国游客的反思以及他们在这个“类似他者”目的地如何协商群际身份, 以对旅游领域的身份认同理论做出贡献。

本文运用主题分析方法; 资料来源于网络文本和深度访谈。

当中国游客面对被视为“类似他者”的朝鲜人时（具有相似的社会、经济和政治环境）, 他们会根据与朝鲜人的群际相似性, 将自我分类为“普通游客”、“受优待者”和“过来人”三类。此外, 他们还会通过群际比较来提高群体层面和集体层面的自尊, 并且采取对应策略以产生不同的群体承诺。

本文提出了一个分析游客访问“类似他者”目的地时的社会认同的理论框架, 对理解旅游中的社会认同的互动性和偶然性做出了贡献, 并响应了在考察游客群体认同时关注其所处的更广泛的社会背景的呼吁。

目的地应该强化它们与“类似他者”客源市场之间友好且独特的关系, 以提升自身吸引力。目的地还应该唤醒游客积极的集体情感和怀旧, 产生主客情感共鸣, 并避免负面情绪, 以尽力提升来自“类似他者”客源地的游客的体验。

Este estudio pretende contribuir a la teoría de la identidad social en turismo mediante la exploración de las reflexiones de los turistas chinos que visitan Corea del Norte y cómo negocian su identidad intergrupal en este destino similar a otros.

Los datos se recogieron mediante plataformas en línea y entrevistas en profundidad. Se utilizó un enfoque cualitativo a través de análisis temático para analizar los dos conjuntos de datos.

Los resultados mostraron que, al encontrarse con norcoreanos percibidos como otros similares en el entorno social, económico y político en el que estaban integrados, los turistas chinos a menudo se categorizaban a sí mismos como turistas ordinarios, turistas con trato preferente y turistas vicarios basándose en las similitudes intergrupales con los norcoreanos. También, realizaban comparaciones intergrupales para aumentar su autoestima a nivel grupal y colectivo, y desarrollaban las estrategias correspondientes para generar distintos compromisos emocionales grupales.

Se presenta un marco teórico en el que se analizan las características de las identidades sociales de los turistas que visitan un destino similar a otro, lo que contribuye a nuestra comprensión de la naturaleza interactiva y contingente de la identidad social en turismo y responde a la necesidad de abordar los contextos sociales más amplios en los que se inserta la identidad de grupo de los turistas.

Se recomienda que los destinos refuercen las relaciones amistosas y únicas con sus mercados emisores similares para mejorar su atractividad. Los destinos deberían esforzarse por mejorar la experiencia de los turistas de sus mercados emisores similares, estimulando su afecto positivo a nivel colectivo, su resonancia emocional y sus recuerdos nostálgicos, y evitando las emociones negativas.

The Metaverse is an immersive virtual world where individuals interact with each other using an avatar. The Metaverse is promised to offer several potentials for different sectors. While the Metaverse promotes innovative interaction between individuals (e.g. learners), there is a scarcity of knowledge on what influences its acceptance and use in higher educational institutions (HEIs), particularly in developing countries. Thus, this paper aims to identify the factors that affect the users' intentions toward Metaverse technology for educational purposes in the HEIs in Jordan.

A study model was created by incorporating variables from the unified theory of acceptance and use of technology (UTAUT) (performance expectancy, PE; effort expectancy, EE; social influence, SI; and facilitating conditions, FC) and information system success (ISS) model (user satisfaction, SAT; system quality, SQ; service quality, SVQ and information quality, IQ) with perceived curiosity (PC) and hedonic gratification (HG) constructs. Both PC and HG were added as context-related factors that could contribute to improving the applicability of UTAUT and ISS to a wide range of technology use contexts. Data were gathered from 441 Jordanian university students using an online questionnaire.

The analysis of the structural model revealed that users' behavioural intentions toward using Metaverse were significantly affected by user satisfaction (SAT), performance expectancy (PE), facilitating conditions (FC) and hedonic gratification (HG). Also, information quality (IQ) and services quality (SVQ) were revealed to have a significant influence on user satisfaction. Likewise, the results illustrated a significant impact of systems quality (SQ), information quality (IQ) and service quality (SVQ) on PE. Lastly, a significant effect of PC on the EE factor was found.

This study will shed light on a number of practical implications for developers, designers, service providers and decision-makers supporting the acceptance and adoption of the Metaverse technology in the educational context. Also, it will contribute to developing the right strategies, and Metaverse content which will draw the attention of learners.

As per the surveyed literature and the researcher's prior knowledge, this is one of the first studies that integrate the UTAUT model, ISS model and two contextual factors (PC and HG) besides testing the proposed model in a developing country (Jordan). This paper is one of the few in which the individuals' acceptance behaviour of Metaverse technology was examined in the HEIs context.

With growing concern about sustainable development and increased awareness of environmental issues, digital technologies (DTs) are gaining prominence and becoming a promising trend to improve productivity, sustainability and project performance in the construction industry. Nonetheless, the uptake of DTs in the construction industry has been limited and plagued with roadblocks. This study aims to identify critical barriers for construction organisations to adopt DTs and to demonstrate relationships between organisational characteristics and the perceived DTs adoption barriers.

This study adopted an explanatory sequential design by combining the advantages of quantitative and qualitative data. Data collection methods include literature review, a pilot study, questionnaire survey, and semi-structured interviews. Questionnaire data were analysed by using SPSS and multivariate regression technique. The interview data were processed by using content analysis to validate and supplement findings from the questionnaire.

Based on the survey and interview results, eight critical barriers were identified: the three top critical barriers are (1) “status quo industry standards”, (2) “lack of client interest” and (3) “lack of financial need/drive for using DTs”. The eight critical barriers were further classified into technical, environmental, and social dimensions to determine the major constructs that hinder DTs adoption. A theoretical framework articulating critical barriers with underlying components and root causes was also proposed. Furthermore, by using multivariate regression analysis, a model was developed to link the organisational characteristics with barriers to DTs adoption.

By referring to the framework and the model developed, academics, industry practitioners, and decision makers can identify pivotal areas for improvement, make informed decisions and implement remedial measures to remove the barriers to digitalisation transformation.

This study contributes to the literature on construction innovations by investigating barriers to DTs adoption holistically as well as perceptions of the impact of organisational attributes on these barriers. It establishes the groundwork for future empirical research into the strategic consolidation of movement of DTs adoption and diffusion.

This paper aims to investigate how information and communication technology (ICT) services and digital finance affect the development of international tourism.

The two-way fixed effect panel regression model, spatial econometric model, panel threshold regression model and panel quantile regression model are used. Data on tourism, economic and social development in 198 Chinese cities from 2011 to 2020 are analyzed.

This study finds that digital economy including ICT services and digital finance has significantly promoted the development of international tourism industry, while there is a negative spatial spillover effect. The promotion effect of international tourism increases significantly after digital innovation reaches the threshold value. International tourism is benefiting more from digital economy with the development of international tourism industry.

The development quality of international tourism industry has not been analyzed due to data limitations, and the mechanism has not been tested.

This study creatively reveals the development of international tourism industry in the digital economy era from ICT services and digital finance perspectives. This study also shows the spatial, nonlinear and asymmetric relationship between digital economy and international tourism.

The purpose of this study is to understand the effect of different brand positions (underdog vs top dog) and comparative advertising on consumers’ brand attitudes. Additionally, this study also aims to demonstrate the effects of inspiration, self-relevance and empathy on the relationship between brand positioning and comparative advertising.

A two-by-three factorial design was employed with brand positions (underdog vs top dog) and three types of comparative advertising (noncomparative, indirect comparative and direct comparative) as the independent variables. Inspiration serves as the mediator, while self-relevance and empathy act as moderators and brand attitude is the dependent variable.

The results show that different brand positions significantly affect brand attitudes, with respondents having a better brand attitude toward the underdog brand. Brand attitude is partially mediated by inspiration. Self-relevance moderates the relationship between brand positioning and brand attitude. However, brand positioning, comparative advertising and empathy do not have interaction effects.

This study contributes to a better understanding of the effect of psychological variables on brand positioning and comparative advertising.

The results suggest that the underdog setting requires a real and honest story because consumers will spot a fake underdog story, which will damage consumer trust in the brand and harm the brand image.

There is a lack of research using psychological variables to demonstrate the effect of being the underdog brand. This study contributes to the literature by employing psychological variables to illustrate the effect of underdog positioning. These findings can help brands develop branding positioning strategies.

The authors construct two time-varying political connection (PC) indexes to measure a firm's political tendencies toward ruling and opposing parties and analyze whether a firm with ruling party tendencies obtains better bank loan contracts compared to the contracts obtained by a firm with opposing party tendencies and a firm with fixed PC tendencies.

Linguistic text mining is used to construct the two time-varying PC indexes from news sources that reflect the tone and frequencies of characteristic texts to determine a firm's tendencies to favor the ruling or opposing parties.

The results show that varying PC firms connected to the ruling party receive preferential loan contracts when their political tendencies increase but varying PC firms connected to the opposition party do not. In contrast, fixed PC firms gain similar benefits only when the connection is determined in the presidential election year but not in other years. Firms supporting two parties receive minimal financial rewards in terms of loan terms.

In past studies, once a firm is identified as having a connection with a political party, it is assumed to have PC throughout the sample period (i.e. fixed PC firms). The authors lift this assumption and examine how varying PC affect bank loan contracts. The two time-varying PC indexes can identify a firm's more immediate party tendencies and more precise effects of a firm's party tendencies on bank loan contracts.

Our proposed machine learning model contributes to improving the quality of Hire by providing a more nuanced and comprehensive analysis of candidate attributes. Instead of focusing solely on obvious factors, such as qualifications and experience, our model also considers various dimensions of fit, including person-job fit and person-organization fit. By integrating these dimensions of fit into the model, we can better predict a candidate’s potential contribution to the organization, hence enhancing the Quality of Hire.

Within the scope of the investigation, the competencies of the personnel working in the IT department of one in the largest state banks of the country were used. The entire data collection includes information on 1,850 individual employees as well as 13 different characteristics. For analysis, Python’s “keras” and “seaborn” modules were used. The Gower coefficient was used to determine the distance between different records.

The K-NN method resulted in the formation of five clusters, represented as a scatter plot. The axis illustrates the cohesion that exists between things (employees) that are similar to one another and the separateness that exists between things that have their own individual identities. This shows that the clustering process is effective in improving both the degree of similarity within each cluster and the degree of dissimilarity between clusters.

Employee competencies were evaluated within the scope of the investigation. Additionally, other criteria requested from the employee were not included in the application.

This study will be beneficial for academics, professionals, and researchers in their attempts to overcome the ongoing obstacles and challenges related to the securing the proper talent for an organization. In addition to creating a mechanism to use big data in the form of structured and unstructured data from multiple sources and deriving insights using ML algorithms, it contributes to the debates on the quality of hire in an entire organization. This is done in addition to developing a mechanism for using big data in the form of structured and unstructured data from multiple sources.