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This study aims to investigate the effectiveness of two types of social media videos used for destination image development: induced/commercial-oriented content and organic content (where content is made without commercial interest, such as vlogs classified as user-generated content).

Experimental research using “Emotive EEG” (electroencephalogram) in a controlled environment was conducted with 30 participants (20 males, 10 females), age range 18 to 26. Emotive EEG recording was performed while the participants watched both types of video clips. Test results for both groups indicate that induced content is preferred over organic content.

This study opens up future research avenues where neuromarketing’s “Marketer Friendly” EEG equipment can be applied to the customer selection process.

Marketing analysts can gauge the interest and response of customers on different types of social media video content for destination marketing based on the findings of this study.

There is limited research on the behavior of different categories of space tourists as identified by different types of space tourism. To address this deficiency, the purpose of this study is to examine what factors make consumers participate in orbital and/or suborbital space tourism, along with three dimensions of motivation, constraint and artificial intelligence. To achieve this study’s goals, a comprehensive research model was developed that included three dimensions of intrinsic and extrinsic motivation, intrapersonal and interpersonal constraint and awareness of and trust in artificial intelligence, in comparing orbital and suborbital space tourism groups.

A questionnaire was carried out with respondents who wanted to participate in orbital (n = 332) and suborbital (n = 332) space tourism in the future. Partial least squares-structural equation modeling, fuzzy-set qualitative comparative analysis, multi-group analysis and deep learning were used to understand potential space tourist behavior.

Extrinsic motivation has the greatest positive impact on behavioral intention, followed by awareness of and trust in artificial intelligence, while intrapersonal constraint strongly negatively affects behavioral intention. Surprisingly, interpersonal constraint is insignificant by partial least squares-structural equation modeling but is still one of sufficient causal configurations by fuzzy-set qualitative comparative analysis. Interestingly, the two types of space tourism have very distinct characteristics.

This study created a comprehensive integrated research model with three dimensions of motivation, constraint and artificial intelligence, along with potential orbital and suborbital space tourist groups, to identify future consumer behavior. Importantly, this study used multi-analysis methods using four different approaches to better shed light on potential orbital and suborbital space tourists.

对不同类型太空旅游所识别的不同类别太空游客行为的研究有限。 为了解决这一缺陷, 这项工作研究了哪些因素使消费者参与轨道和/或亚轨道太空旅游, 以及动机、约束和人工智能三个维度。 为了实现研究目标, 在比较轨道和亚轨道太空旅游群体时, 开发了一个综合研究模型, 包括内在和外在动机、内在和人际约束以及对人工智能的认识和信任三个维度。

对希望在未来参与轨道 (n = 332) 和亚轨道 (n = 332) 太空旅游的受访者进行了问卷调查。 利用偏最小二乘法 (PLS)-结构方程模型 (SEM)、模糊集定性比较分析 (fsQCA)、多组分析和深度学习来了解潜在的太空游客行为。

外在动机对行为意图的积极影响最大, 其次是对人工智能的认识和信任, 而内在约束对行为意图有强烈的负面影响。 令人惊讶的是, 人际约束对于 PLS-SEM 来说是微不足道的, 但对于 fsQCA 来说仍然是充分的因果配置之一。 有趣的是, 这两类太空旅游具有非常鲜明的特点。

这项工作创建了一个全面的综合研究模型, 具有动机、约束和人工智能三个维度, 以及潜在的轨道和亚轨道太空旅游群体, 以确定未来的消费者行为。 重要的是, 这项研究采用了多种分析方法, 使用四种不同的方法来更好地揭示潜在的轨道和亚轨道太空游客。

existe una investigación limitada sobre el comportamiento de las diferentes categorías de turistas espaciales identificados por diferentes tipos de turismo espacial. Para abordar esta deficiencia, este trabajo examina qué factores hacen que los consumidores participen en el turismo espacial orbital y/o suborbital, junto con tres dimensiones de motivación, restricción e inteligencia artificial. Para lograr los objetivos del estudio, se desarrolló un modelo de investigación integral que incluía tres dimensiones de motivación intrínseca y extrínseca, restricción intrapersonal e interpersonal, y conocimiento y confianza en la inteligencia artificial, al comparar grupos de turismo espacial orbital y suborbital.

se realizó un cuestionario con los encuestados que querían participar en el turismo espacial orbital (n = 332) y suborbital (n = 332) en el futuro. Se utilizaron modelos de ecuaciones estructurales (SEM) de mínimos cuadrados parciales (PLS), análisis comparativo cualitativo de conjuntos borrosos (fsQCA), análisis multigrupo y aprendizaje profundo para comprender el comportamiento potencial del turista espacial.

la motivación extrínseca tiene el mayor impacto positivo en la intención de comportamiento, seguida de la conciencia y la confianza en la inteligencia artificial, mientras que la restricción intrapersonal afecta negativamente la intención de comportamiento. Sorprendentemente, la restricción interpersonal es insignificante por PLS-SEM, pero sigue siendo una de las configuraciones causales suficientes por fsQCA. Curiosamente, los dos tipos de turismo espacial tienen características muy distintas.

este trabajo creó un modelo de investigación integral integral con tres dimensiones de motivación, restricción e inteligencia artificial, junto con posibles grupos de turistas espaciales orbitales y suborbitales para identificar el comportamiento futuro del consumidor. Es importante destacar que este estudio empleó métodos de análisis múltiple utilizando cuatro enfoques diferentes para arrojar mejor luz sobre los posibles turistas espaciales orbitales y suborbitales.

Global supply chains are increasingly becoming more prone to high-impact disruptions, which has been fairly evident with the coronavirus disease 2019 (COVID-19) pandemic. The capacity to address disruptions is essential for the survival of any organization. Coping with increasing complexity and uncertainties requires a systemic view of supply chains. Furthermore, a comprehensive understanding of the governance structure and timely decision-making are critical in times of disruptions. Although several aspects of supply chain resilience (SCRES) are broadly studied in the literature, the relationship between supply chain orientation (SCO), decentralization in decision-making and SCRES is an understudied area.

This study takes a longitudinal approach to address this research gap with a comprehensive meta-analytic review to explore the relationships between the constructs of interest through the lenses of contingency and dynamic capability theories. Furthermore, 2 surveys with sample sizes of 250 and 200 were conducted with supply chain professionals to test the research framework before and after the pandemic to compare the findings.

Structural Equation Modeling (SEM) analysis indicates a positive relationship between SCO and decentralization and between decentralization and SCRES. The post-COVID-19 analysis further validates the influence of agility, collaboration and situational awareness related to decentralization and resilience. More importantly, capabilities have a higher impact on resilience during the pandemic than before.

The results entreat organizations to attain decentralized decision-making vis-à-vis dedicated functional teams charged with reacting timely to disruptions. The teams should be empowered to leverage their knowledge and experiences regardless of their position in the hierarchy.

Although SCRES is an active research stream, the structural aspects of SCRES and its relationship with SCO are understudied. Therefore, this research puts forth a research framework and empirically tests hypotheses that frame the relationship between SCO, decentralization and resilience outcomes in pre- and post-COVID environments.

This paper aims to identify the corporate social responsibility (CSR) patterns of Indian manufacturing firms using a CSR index based on ISO26000 and India’s National Voluntary CSR Guidelines.

A total of 121 manufacturing enterprises in the national capital region (NCR) were surveyed. The questions related to the involvement of CSR in business strategy, involvement in CSR planning, involvement in environmental activities, involvement in social activities, monitoring, evaluation and involvement in CSR, reporting and policy and deployment of CSR. A two-step cluster analysis using log-likelihood measures was used to identify groupings in the data set based on their performance across the seven issues.

The two distinctive segments identified adopted intermediate CSR activities, and one undertook advanced CSR activities.

This study has several limitations. First, the survey data were drawn exclusively from medium-sized enterprises in the NCR. Second, all the indicators in the CSR index were equally weighted.

This paper contributes to the literature by grouping manufacturers’ CSR activities based on seven dimensions suggested in ISO26000 and India’s National Voluntary Guidelines. The results of this study can help managers, boards and regulators better understand CSR and identify ways to improve it further.

The purpose of this study is to explore the suggestions that construction processes could be considerably improved by integrating building information modelling (BIM) with 3D laser scanning technologies. This case study integrated 3D laser point cloud scans with BIM to explore the effects of BIM adoption on ongoing construction project, whilst evaluating the utility of 3D laser scanning technology for producing structural 3D models by converting point cloud data (PCD) into BIM.

The primary data acquisition adopted the use of Trimble X7 laser scanning process, which is a set of data points in the scanned space that represent the scanned structure. The implementation of BIM with the 3D PCD to explore the precision and effectiveness of the construction processes as well as the as-built condition of a structure was precisely captured using the 3D laser scanning technology to recreate accurate and exact 3D models capable of being used to find and fix problems during construction.

The findings indicate that the integration of BIM and 3D laser scanning technology has the tendency to mitigate issues such as building rework, improved project completion times, reduced project cost, enhanced interdisciplinary communication, cooperation and collaboration amongst the project duty holders, which ultimately enhances the overall efficiency of the construction project.

The acquisition of data using 3D laser scanner is usually conducted from the ground. Therefore, certain aspects of the building could potentially disturb data acquisition; for example, the gable and sections of eaves (fascia and soffit) could be left in a blind spot. Data acquisition using 3D laser scanner technology takes time, and the processing of the vast amount of data acquired is laborious, and if not carefully analysed, could result in errors in generated models. Furthermore, because this was an ongoing construction project, material stockpiling and planned construction works obstructed and delayed the seamless capture of scanned data points.

These findings highlight the significance of integrating BIM and 3D laser scanning technology in the construction process and emphasise the value of advanced data collection methods for effectively managing construction projects and streamlined workflows.

Inaccurate capturing and processing of customer requirements result in negative economic and ecological effects. Digital twins of customer demands promise to remedy these issues. However, successful implementation necessitates users' technology acceptance. This study contrasts three hierarchical digital twin levels with different degrees of user integration and examines determinants for their respective acceptance.

A structural equation model is applied in a comparative manner, considering different levels of digital twin radicalness. A multidimensional approach is used to measure attitudes towards usage. Data are collected in the context of organisational supply management.

Results show harmonious effects across digital twin levels. This indicates that technological radicality plays only a subordinate role when assessing acceptance determinants such as user perception on ease of use, usefulness, trust and risk.

Rather than focussing solely on technological factors, findings suggest that users prioritise the actual outcome and efficiency of the system. This perspective offers practical implications for organisations seeking to implement advanced systems and emphasises the significance of user perceptions beyond technological features.

The societal impact of this research are an appreciation of customer roles in the supply chain where an enhanced detection of customer needs and preferences aligns businesses with the dynamic and evolving demands of a diverse and a continuously environmentally-conscious consumer base.

This study applies a measurement model for technology acceptance in a unique and multidimensional manner. Thereby, a comparative analysis of user perceptions across different digital twin levels sheds more light on a nascent, promising and underexplored technological method. This interdisciplinary research combined knowledge from the supply chain management and management information systems fields by highlighting key factors for the adoption of complex technological methods.

This study was conducted to investigate the impact of indoor environmental quality (IEQ) and internal design on the performance of students in university dormitories in Tehran and North Cyprus.

Using a survey questionnaire, 298 students living in student dormitories in Tehran and North Cyprus were surveyed for data collection.

Research has shown that the academic performance and well-being of students are heavily impacted by factors related to IEQ and internal design. The study conducted in Tehran and North Cyprus has identified the most effective components of IEQ and internal design for student dormitories. The study suggests that proper ventilation, furniture design, temperature control and lighting design are key factors that significantly affect IEQ and internal design. Control and lighting design are key factors that significantly affect IEQ and internal design.

Originality: The study utilizes a comparative study designed to analyze the differences and similarities between the two locations.

The purpose of this research is to investigate the effects of service recovery experiences on customer engagement in negative word-of-mouth (WOM) in the hotel industry and explore the psychological motives and mediating mechanisms driving consumer behavior.

A scenario-based experimental design on Qualtrics was used, with a pre-test (N = 200). The main study data were collected using Amazon's Mechanical Turk platform.

Findings reveal that negative service experiences lead to higher engagement in negative WOM compared to positive and satisfactory recovery service experiences. Even well-executed recovery efforts may not completely eliminate negative WOM. The mediating role of emotional responses is substantiated, as heightened negative service experiences result in more intense negative emotional responses, leading to increased engagement in negative WOM.

The study emphasizes the importance of service recovery strategies and the need for businesses to consistently strive for exceptional service quality. It also highlights the complexity of customer reactions to service experiences, suggesting that further research is needed to explore the factors that minimize negative WOM across various service contexts.

Community-police relations have gained increasing public attention during the past decade. The purpose of the present study was to better understand the relationship between perceived community support and police officer burnout and engagement.

Data were gathered via online survey from 117 officers from a city police department in the Southeastern United States.

Community support was negatively correlated with burnout and positively correlated with engagement. Moreover, multiple regression analyses showed that community support explained significant incremental variance in most dimensions of burnout and engagement, above and beyond demographic factors and community stressors. Qualitative results showed that police officers had mixed perceptions of how they were viewed by the general public, with more negative than positive responses. However, officers felt more positively perceived in their own communities, but concerns were raised that national events affected the perceptions of officers even in positive relationships with their communities. Finally, officers felt that public perceptions impacted their job satisfaction, job performance and personal lives.

The results have practical implications for how to encourage positive interactions between officers and their community, with recommendations for both law enforcement leaders and civilians.

This study is one of the few that highlights the officers' perspective on how public perceptions affect their work. This is important in understanding how to maximize quality community interactions while minimizing conditions that would increase burnout.

To make more smart health-care system, the health-care data should be shared in the secure manner, and it improves health-care service quality. This paper aims to implement a modern decentralized blockchain, safe and easy-to-use health-care technology application in the cloud.

On observing the graph, the convergence analysis of proposed Levy Flight-integrated moth flame optimization method at 80th iteration was 4.59%, 2.80%, 3.316%, 8.92% and 2.55% higher than the traditional models MFO, artificial bee colony (ABC), particle swarm optimization (PSO), moth search algorithm (MSA) and glow worm swarm optimization (GWSO), respectively, for Hungarian data set. Particularly, in best case scenario, the adopted method attains low cost value (5.672671) when compared to all other traditional models such as MFO (5.727314), ABC (5.711577), PSO (5.706499), MSA (5.764517) and GWSO (5.723353).

The proposed method achieved effective performance in terms of key sensitivity, sanitization effectiveness, restoration effectiveness, etc.