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By harnessing technology developments such as Internet-of-Things (IoT)-enabled intelligent sensors and immersive virtual reality (VR) experiences, facility managers can access real-time, precise information on thermal comfort-related indicators through virtual facility models. While prior research studies have developed key technologies for improving the understanding of thermal comfort and its impact on the occupants’ well-being and productivity, there remain areas yet to be explored, especially in relation to integrating both real-time data from multimodal IoT-enabled smart sensors and VR technologies. Hence, this study demonstrates the potential of integrating IoT and VR technologies for real-time thermal comfort assessment and visualization as well as user interaction with HVAC systems to enhance thermal comfort.

To develop the proposed integrated analytical framework in this paper, various steps were implemented. First, four multimodal IoT-enabled sensing stations were created and installed to collect real-time thermal comfort-related data (i.e. temperature and relative humidity). Second, a VR environment was developed using the Unity engine to offer an immersive experience. Third, the real-time data from the IoT-enabled sensing stations was integrated into the VR environment by transmitting it to the cloud via the MQTT protocol server, and various programming scripts were developed to provide multiple functionalities to the users, including visualizing the thermal comfort along the entire indoor space as well as interacting with and controlling the cooling and heating HVAC systems. Fourth, the applicability and effectiveness of the developed framework was validated and evaluated by 92 participants using a survey questionnaire.

The obtained survey results validated the importance and effectiveness of the developed framework on various aspects including graphical satisfaction, spatial presence, involvement, experienced realism, low-to-no cybersickness and overall application satisfaction, among others. More specifically, the findings reflected that the participants’ average scores for graphical satisfaction, sense of spatial presence, involvement and experienced realism were 4.69, 4.61, 4.71 and 4.53 out of 5, respectively. Hence, the results showed that the visualization capabilities of the developed framework serve as a powerful feature that enables a comprehensive visualization of thermal comfort variations across the entire room/office space. Also, the results showed that there were no statistically significant differences between the responses of participants with prior VR experience with those from participants with limited-to-no prior VR experience, thus further highlighting the usefulness of the proposed technology not only for experienced users but also for users from different skills and background.

This research has the potential to revolutionize the way built environments are managed and interacted with, where facility managers can monitor, assess and visualize thermal comfort in real-time as well as interact with the HVAC systems and control multimodal IoT devices in the real-world from a distance through virtual facility models. The proposed framework’s ability to provide dynamic and continuously updated assessments of thermal conditions in real-time positions it as a valuable tool for prompt adjustments to optimize occupants’ comfort levels. Ultimately, the proposed framework provides an intuitive and immersive platform to manage thermal comfort, thus promoting healthier, more productive and eco-friendly indoor environments.

This research endeavors to conduct a thorough and holistic analysis of the foundational elements that empower the cultivation of dynamic capabilities in micro, small and medium-sized enterprises (MSMEs). The purpose of this study is to determine whether these capabilities have a noticeable impact on the sustainable performance of these enterprises. The study aims to support future research efforts in understanding this phenomenon by filling this knowledge gap and presenting a conceptual framework, thereby enhancing the scholarly discourse in this field.

The study consists of a systematic review of 126 articles meticulously chosen through a series of screening stages employing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. This examination is conducted within the organized framework of antecedents, decisions and outcomes-theory, context and methods (ADO-TCM), ensuring a structured and comprehensive analysis.

The study uncovers significant insights, identifying four key antecedents: resource base, organizational learning, managerial expertise and external environment management. These factors are instrumental in fostering dynamic capabilities within the enterprise, leading to sustainable entrepreneurial success and a competitive advantage over rivals.

By comprehending the mechanisms by which dynamic capabilities are established within the enterprise, this study provides a valuable resource for entrepreneurs, professionals and managers, offering them practical insights to leverage.

This systematic literature review is the initial attempt to explain how dynamic capabilities can be used to enhance and accomplish sustainable performance in the context of MSMEs.

This paper introduces a formal risk interdependency framework to model cascading effects in collaborative systems. By characterizing risk causal chains and propagation chains, the framework aims to provide decision-makers with a structured tool to systematically identify, analyze, and prevent cascading risks in interconnected networks.

The framework, named the danger-risk-consequence chain, defines core components – danger, stake, risk, condition, and consequence – alongside their causal and propagation relationships, which form the basis for risk characterization. The framework is applied through a use case in the construction supply chain to demonstrate its capacity to model cascading risks.

The framework uncovers risk propagation chains that lead to cascading effects and formalizes the state evolution of these effects within collaborative systems. Through the use case, it demonstrates practical value by enabling stakeholders to visualize interrelated risks, detect vulnerabilities early, and implement targeted mitigation measures to enhance resilience against cascading disruptions.

This study presents a novel approach to modeling cascading effects by integrating risk causality and propagation into a formalized framework. In contrast to previous research, which offers static risk definitions for risk characterization, this framework contributes to risk management theory by providing a structured method for understanding and modeling interdependencies.

Adopting and implementing robotic technology applications in the library is a significant technological up-gradation today. The purpose of this study was to evaluate selected literature focused mainly on robotics technology applications in the field of libraries and to assess the online social attention to research publications.

The study employed Scientometric and altmetric tools to evaluate the research publications. The bibliographic data of research publications were downloaded from Scopus database and scrutinized one by one and 71 articles were selected which mainly focused on robotic technology in libraries. Altmetric data were collected from the Dimensions.ai database. The analysis was performed using MS Excel, Tableau, Biblioshiny, VOSviewer and SPSS software.

Research on robotic technology in the field of libraries has been experiencing a gradual increase, marked by an annual growth rate of 12.93%. The United States has prominently led the way as the most active participant and collaborator in this advancement. Among the various journals, Library Hi Tech has notably stood out as a significant contributor to this field. However, the research articles have garnered limited social attention and impact. Furthermore, the patterns of authorship collaboration have demonstrated relatively modest levels within the field, and a weak correlation has been observed between the social attention received and the Scopus citation metrics of the publications.

The research needs to be disseminated more through various social media platforms to increase its visibility. Sharing research information through social media can bridge the gap between academia and society. The findings of this study can serve as a valuable reference for researchers and policymakers.

This study presents a Scientometric analysis of the selected published literature on robotics technology applications in the field of libraries, highlighting the progress and development of worldwide research in this area.

The proposed research primarily focuses on optimizing process parameters to enhance the surface quality of AA7079 material components formed incrementally through the single-point incremental forming process. The study experimentally investigates the influence of selected process inputs on the surface quality of the formed material. Experiments were conducted on AA7079 aluminum alloy sheets under varying conditions of specific process factors, including tool diameter, side-wall angle, rotational speed, feed rate and vertical step size.

The experimental investigation has been planned by using the concept of design of experiments (DoE) and is based on trial runs using response surface methodology. The observed data has further been analyzed through analysis of variances analysis and desirability method for highlighting the significant parameters and optimization along with their contribution on surface quality measure, i.e. surface roughness.

The side-wall angle, vertical step size, feed rate, rotational speed and forming tool radius have been found to be the major factors that significantly affect the surface roughness. The best value of the SR has been recommended as 0.735 µm under the parametric setting as; tool size (diameter) of 12.291 mm, wall angle of 68.210°, step size of 0.269 mm, speed as 884.672 rpm and a feed rate of 2,791.240 mm/min.

It has been recommended that greater tool diameter, greater wall angle, smaller steps, higher feed and slower speeds are necessary to improve surface roughness. Out of all the characteristics, tool size is the most important one. In addition, validation trials have been carried out to identify any deviations from the optimal value that was expected.

To maximize health synergistic benefits and provide a scientific foundation for enhancing air pollution control policies, this research proposed a causal inference framework with a decomposition ensemble prediction model for comprehensive policy assessment.

We introduced the CD-OASVR-Ensemble-CC method, a policy assessment approach that combined machine learning-based decomposition ensemble prediction (CD-OASVR-Ensemble) with counterfactual contrast (CC) analysis. The CD-OASVR-Ensemble model incorporated support vector regression (SVR) optimized through swarm intelligent optimization algorithms (OA), complete ensemble empirical model decomposition of adaptive noise (CD) and a linear ensemble model (Ensemble). This approach was applied to analyze patterns in historical PM2.5 data and predict the future trend. The predicted PM2.5 served as a counterfactual trend, enabling an evaluation of the policy’s environmental and health effects.

Analysis of prediction errors confirmed the proposed CD-OASVR-Ensemble model’s accuracy and robustness in predicting PM2.5 levels. The findings indicated that the implementation of “Regulation 2019” led to a significant reduction in PM2.5 concentration, preventing an estimated 7,960 premature deaths and saving approximately 2,602.95 m yuan in health-related economic costs.

This study introduces an innovative framework for evaluating the environmental effect of policies, with a specific emphasis on health synergistic benefits.

This paper aims to examine how the number of short videos posted and the number of influencers employed, two important strategies in short video marketing, affect consumer behavior and how price discounts moderate the effects of influencer endorsement on consumer browsing and purchasing behavior.

Drawing on the literature on influencer endorsement, this study used an ordinary least square model to empirically examine the two effects of endorsement strategies in increasing product traffic and sales for consumers at a short video app, Douyin (TikTok).

The results show that the number of short video ads produces the classic inverted U-shape for traffic and sales, and both effects were strengthened under a high discount condition. Whereas the number of influencers has a positive effect on traffic but produces an inverted U-shape for sales, both effects were undermined under a high discount condition.

This study is the first to explore the two distinct effects (repetition effect and diffusion effect) of influencer endorsement on browsing and purchasing behavior and theorize about the moderate effects of discounts on these effects.

This study aims to design a small-size conformable flexible micro-electro-mechanical system (MEMS) vector hydrophone to meet the miniaturization requirements of unmanned underwater vehicle.

The cilia receive the acoustic signal to oscillate to cause changes in the stress on the beam, which in turn causes changes in the piezoresistive resistance on the beam, and changes in the resistance cause changes in the output voltage.

The results show that the flexible hydrophone in the paper has a sensitivity of −182 dB@1 kHz (re 1V/µPa) at 1 Pa sound pressure, can detect low-frequency hydroacoustic signals from 20 to 550 Hz and has good spatial directivity, and the flexible substrate permits the hydrophone to realize bending deformation, which can be well attached to the surface of the object.

In this study, a finite element simulation model of the hydrophone microstructure is constructed and its performance is verified by simulation. The success rate of the proposed MEMS transfer process is as high as 94%, and the prepared piezoresistors exhibit excellent resistance characteristics and high consistency. These results provide innovative ideas to enhance the performance and stability and achieve miniaturization of hydrophones.

This study aimed to verify the impact of e-commerce live streaming interactivity on consumer engagement behavior. Specifically, the multiple dimensions of interactivity and tie strength together form a high-level consumer engagement behavior.

Data collection was carried out in the form of a questionnaire survey. Data from 416 respondents were analyzed by structural, followed by further test by fsQCA method.

Perceived controllability, perceived responsiveness and perceived mutuality positively influence tie strength, and tie strength promotes consumer engagement behavior. Moreover, we found a configuration effect between interactivity and tie strength and revealed four configurations that can affect high-level engagement behavior.

First, the SEM results show that the three dimensions of perceived interactivity positively impact tie strength: perceived controllability, perceived responsiveness, and perceived mutuality. And perceived personalization has no positive impact on tie strength. Second, the relevant results show that tie strength positively impacts consumer engagement behavior. Third, we find that the relationship between perceived interactivity and consumer engagement behavior may not be asymmetric, so the alternative combination of causal conditions may produce the same results. The fsQCA results revealed four configurations that can affect the level of consumer engagement behavior. And tie strength is the core condition.

This study provides specific solutions for e-retailers and live streaming platforms to promote consumers' participation in engagement behavior in e-commerce live streaming.

This study transforms the linear impact of interactivity on consumer engagement behavior into a configuration effect for the first time, and enriches the live streaming commerce and consumer engagement behavior literature.

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.