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This study aims to explore the impact mechanism of social support on individual health knowledge creation among users in online patient communities, guide and promote the creation of health knowledge and provide insights into managing online patient communities.

A theoretical model was constructed by integrating social impact and social support theories. Data were collected through questionnaires, and 750 valid responses were analysed using a structural equation model.

This study found the following. (1) Social support influences individual health knowledge creation through the mediating effects of creative self-efficacy and positive emotions. (2) The general rule of the strength of the influencing factors on individual health knowledge creation is that creative self-efficacy > positive emotions. (3) The general pattern of the mediating effect of attitude factors between social support and health knowledge creation is that creative self-efficacy > positive emotions. (4) The key path for social support to influence individual health knowledge creation is “social support → creative self-efficacy → health knowledge creation”. (5) The dimensions of social support in online patient communities can be divided into information, emotional, respect and network support. Individual health knowledge creation can be divided into health knowledge externalisation, combination, socialisation and internalisation.

This study expands the application scope of social influence theory and opens up the “black box” of the impact of social support on individual health knowledge creation behaviour. Simultaneously, the dimensions of social support, individual health knowledge creation and the mediating role between social support and health knowledge creation are discussed.

This study aims to explore the factors influencing the adoption of social media payment platforms (SMPPs) and examines the interrelationships among these factors.

A systematic literature review identified 31 key adoption factors. Using social network analysis (SNA), we mapped and analyzed the interrelationships among these factors. Additionally, we used the Delphi technique to validate and assess their impact.

The study reveals that perceived usefulness emerges as the most critical factor driving the adoption of SMPPs. Moreover, the SNA highlights significant interdependencies among factors, providing deeper insights into the ecosystem of SMPP adoption.

The findings offer practical guidance for users and socially innovative companies in decision-making related to SMPP adoption. Additionally, the study identifies avenues for future research, particularly in leveraging network-based methodologies for service management research.

This study is the first to apply SNA tools in the context of SMPPs, offering a novel methodological perspective and advancing the understanding of adoption dynamics in this emerging field.

This study proposes a novel algorithm based on the finite volume method for simulating groundwater flows and presents the practical application of this method in geotechnical engineering.

The matrix-free implicit iteration method based on the finite volume method and preconditioning conjugate gradient algorithm was used to discretize and solve the groundwater seepage governing equation. Implicit residual smoothing and GPU parallel techniques were utilized to speed up the computation with the solver.

The new method was assessed and evaluated using benchmark and typical infiltration cases. Both the analytical solutions and solutions of the commercial software GEO-Studio were used to verify the accuracy of the proposed algorithm. The speedup performance of the GPU parallel algorithm was also well reflected.

The results demonstrate that the new algorithm is simple and practical, with fast convergence and high accuracy and can satisfy engineering application requirements.

This paper aims to compare and analyze the effect of the dual-credit policy and product substitution rate on the automakers’ operational strategies under different production modes (e.g. centralized and independent), and further illustrate which production mode is more conducive to improving new energy vehicle (NEV) development.

The decision-making models for a centralized production mode where an integrated automaker produces both NEVs and fuel vehicles (FVs) and for independent production mode where an NEV automaker faces competition from a traditional FV automaker were formulated. The equilibrium solutions of each production mode were obtained by extreme value and game theory methods. The conclusions of the theoretical analysis were further verified with numerical analyses using IBM-MATLAB R2019a. Some management insights could be obtained by comparison analysis.

Under the dual-credit policy, an increase in the NEV credit trading price will always raise production quantity of NEVs, but only in an independent production mode where a higher trading price will also bring higher total profits to NEV automakers. In addition, only when the NEV credit trading price is high enough, a rising product substitution rate will be more favorable to NEV production and restrain FV production. Furthermore, an independent production mode is more favorable for the initial production of NEVs, but as each of the two vehicle types captures a certain amount of market share, a centralized production mode will be more conducive to the full replacement of FVs by NEVs.

The main contributions of this study include the formulation of decision-making models for FVs and NEVs in not only a centralized production mode but also an independent production mode. Moreover, this paper comprehensively analyzes how the dual-credit policy and product substitution relationship affect automakers’ production and pricing decisions. Then, the specific conditions under which each production mode is more conducive to NEV production and sales are summarized. The results proposed in this study provide scientific managerial insights for automakers and policy makers.

The use of technological innovations to effectively deliver construction projects is gaining significant coverage. This study aims to assess the inhibiting factors to the utilisation of laser scanners for the delivery of construction projects in developing economies using South Africa as the study area.

Adopting a quantitative technique, this study elicited responses from construction professionals using a questionnaire as the instrument for data collection. A four-pronged data analysis method was used, comprising descriptive statistics, Kruskal−Wallis h-test, exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).

Findings from the study show that lack of awareness and high cost of acquisition are the barriers rated by the study’s respondents the most. Also, findings from the EFA and CFA conducted showed and affirmed the significance of three constructs inhibiting factors to the utilisation of laser scanners for construction project delivery: technical hindrances, financial impediments and institutional challenges.

This study makes practical contributions to the discourse of using innovative technologies for effective construction project delivery by inhibiting factors to the use of laser scanners.

Evidence from the literature shows that no study has assessed the barriers to the utilisation of laser scanning technology for construction projects in the South African construction industry. This study strives to close this gap in the literature.

The emergence of virtual reality (VR) has the potential to revolutionize various industries, including tourism, as it delivers a simulated environment that closely emulates real-life experiences. Therefore, this study aims to explore how the factors, i.e. enjoyment, emotional involvement, flow state, perceived privacy risk, physical risk and cost, influence the customers’ intention to use VR for tourism.

This study integrates the technology acceptance model, hedonic consumption theory with other factors, including cognitive response, authenticity, perceived privacy risk, perceived physical risk, perceived cost and perceived presence. Partial least squares structural equation modelling approach was used to test the proposed research model.

The finding based on the sample of 252 respondents revealed that authenticity is the most influential factor impacting behavior intention followed by perceived cost, attitude, cognitive response and enjoyment. Also, the study supported the moderating impact of personal innovativeness between attitude and behavioral intention to use VR for tourism.

The findings of the study offers practical implications for service providers, site managers, destination marketers, tourist organizations and policymaker to develop more effective strategies for offering VR services for tourism.

This study enriches the current understanding of VR adoption in context of tourism with empirical evidences.

虚拟现实的出现有可能彻底改变包括旅游在内的多个行业, 因为它提供了一个模拟环境, 密切模拟真实生活体验。因此, 本研究旨在探讨愉悦、情感投入、流体状态、感知隐私风险、身体风险和成本等因素如何影响顾客使用虚拟现实进行旅游的意愿。

本研究将TAM模型、享乐消费理论与其他因素相结合, 包括认知反应、真实性、感知隐私风险、感知身体风险、感知成本和感知存在。 PLS SEM 方法用于测试所提出的研究模型。

基于 252 名受访者样本的研究结果表明, 真实性是影响行为意图的最大因素, 其次是感知成本、态度、认知反应和享受。此外, 该研究还支持个人创新性对使用虚拟现实进行旅游的态度和行为意图之间的调节影响。

该研究的结果为服务提供商、站点管理者、目的地营销人员、旅游组织和政策制定者制定更有效的策略来为旅游业提供 VR 服务提供了实际意义。

本研究通过实证证据丰富了当前对旅游背景下虚拟现实采用的理解。

La aparición de la realidad virtual tiene el potencial de revolucionar diversas industrias, incluyendo el turismo, ya que proporciona un entorno simulado que emula de cerca las experiencias de la vida real. Por lo tanto, este estudio tiene como objetivo explorar cómo los factores, como la diversión, la participación emocional, el estado de flujo, el riesgo percibido de privacidad, el riesgo físico y el costo, influyen en la intención de los clientes de utilizar la realidad virtual para el turismo.

Este estudiointegra el modelo TAM, la teoría del consumohedónico con otrosfactores que incluyen la respuestacognitiva, la autenticidad, el riesgo de privacidadpercibido, el riesgofísicopercibido, el costopercibido y la presenciapercibida. Se utilizó el enfoque PLS SEM para probar el modelo de investigaciónpropuesto.

El hallazgobasadoen la muestra de 252 encuestadosreveló que la autenticidades el factor másinfluyente que afecta la intención de comportamiento, seguido del costopercibido, la actitud, la respuestacognitiva y el disfrute. Además, el estudioapoyó el impactomoderador de la innovación personal entre la actitud y la intención de comportamiento al utilizar la realidad virtual para el turismo.

Los hallazgos del estudioofrecenimplicacionesprácticas para que losproveedores de servicios, administradores de sitios, comercializadores de destinos, organizacionesturísticas y formuladores de políticasdesarrollenestrategiasmásefectivas para ofrecerservicios de realidad virtual para el turismo.

Este estudioenriquece la comprensión actual de la adopción de la realidad virtual en el contexto del turismo con evidenciasempíricas.

Based on the Social Exchange Theory (SET), the paper attempts to extend the research on the relationship between green self-managed teams and firm performance by exploring the serial mediation of extra-role green behavior and environmental performance. Furthermore, via moderated mediation, the study inspected the differences in relationships among these variables for manufacturing and service organizations.

Data of 407 respondents from 122 manufacturing and service organizations (having green self-managed teams) operating in India were collected using purposive sampling. Various statistical techniques like confirmatory factor analysis (CFA), correlations, multiple regressions and bootstrapping were employed.

The results indicated that extra-role green behavior and environmental performance served as serial mediators. Additionally, the nature of the organizations significantly moderated several indirect relationships, with one pathway found to be insignificant.

The study may be limited by the fact that the data were collected at a single moment in time rather than using a longitudinal design.

The study guides service organizations to attract environmentally conscious employees by promoting green self-managed teams and manufacturing organizations to enrich their operations and service delivery through such teams.

The study uniquely examines how green self-managed teams addressing environmental issues contribute to improved firm performance through mutual exchanges. It also advances existing literature by conducting a comparative analysis across manufacturing and service organizations in an emerging Indian market.

This research aims to improve the efficiency of information retrieval in a construction or renovation project, the aim is to deliver the right information to the right stakeholder at the right time throughout the project lifecycle.

The approach involves creating a knowledge graph-based semantic search system. This system is structured by developing an ontology to organize the knowledge graph, which will adhere to linked data principles. Three key indicators—relevance, contextual awareness and integrity—are developed to assess query results, ensuring that the system provides the most accurate and relevant answers for the user querying the data.

The case demonstrated the potential of using linked data principles and the semantic search system to facilitate communication between different stakeholders. With the implementation of the indicators, the system ensured that the most suitable answer was always provided at the time of the query. Even if the information queried did not yet exist in the graph, the system attempted to find the best available match. Additionally, the system proved effective in knowledge discovery by suggesting contextually relevant information that was not directly queried.

This research shows promise in improving information management in construction projects, but some limitations remain. The indicators used in our assessment framework are designed to support information retrieval, but certain parameters, such as the exponents, are arbitrarily set and require optimization. Additionally, while only three indicators are currently being tested, incorporating other relevant indicators could further enhance the system’s efficiency and effectiveness.

Our approach offers an efficient semantic search system specifically tailored for the construction field; however, the query assessment framework (indicators) we created can be applied to any semantic search, as we attempt to provide a method for assessing the relevance and quality of semantic searches.

By improving the assessment of semantic search results, our approach enhances information accessibility and decision-making across various domains. This contributes to more effective knowledge sharing, reducing miscommunication and inefficiencies in collaborative environments.

A real case study implementing linked data in renovation project and the development of a novel framework for query evaluation consisting of three main metrics. While each metric has been individually discussed in the literature, the relationship between actor, information and process has not been described or quantified as indicators to ensure the semantic search quality.

This study aims to assess the feasibility and effectiveness of incorporating predictive maintenance (PdM) into existing practices of spare part inventory management and pinpoint the barriers and identify economic values for such integration within the supply chain (SC).

A two-staged embedded multiple case study with multi-method data collection and a combined discrete/continuous simulation were conducted to diagnose obstacles and recommend a potential solution.

Several major organisational, infrastructure and cultural obstacles were revealed, and an optimum scenario for the integration of spare part inventory management with PdM was recommended.

The proposed solution can significantly decrease the inventory and SC costs as well as machinery downtimes through minimising unplanned maintenance and addressing shortage of spare parts.

This is the first study with the best of our knowledge that offers further insights for practitioners in the Industry 4.0 (I4.0) era looking into embarking on digital integration of PdM and spare part inventory management as an efficient and resilient SC practice for the automotive sector by providing empirical evidence.

Promoting technological innovation is important to address the complexity of major engineering challenges. Technological innovations include short-term innovations at the project level and long-term innovations that can enhance competitive advantages. The purpose of this study is to develop an incentive mechanism for the public sector that considers short-term and long-term efforts from the private sector, aiming to promote technological innovation in major engineering projects.

This study constructs an incentive model considering the differences in short-term and long-term innovation efforts from the private sector. This model emphasizes the spillover effect of long-term efforts on current projects and the cost synergy effect between short-term and long-term efforts. It also explores the factors influencing the optimal incentive strategies for the public sector and innovation strategies for the private sector.

The results indicate that increasing the output coefficient of short-term and long-term efforts and reducing the cost coefficient not only enhance the innovation efforts of the private sector but also prompt the public sector to increase the incentive coefficient. The spillover effect of long-term innovation efforts and the synergy effect of the two efforts are positively related to the incentive coefficient for the public sector.

This research addresses the existing gap in understanding how the public sector should devise incentive mechanisms for technological innovation when contractors acting as the private sector are responsible for construction within a public-private partnership (PPP) model. In constructing the incentive mechanism model, this study incorporates the private sector's short-term efforts at the project level and their long-term efforts for sustained corporate development, thus adding considerable practical significance.