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The study seeks to shed light on the estimates of the carbon shadow price in the literature relying on frontier techniques. The shadow price of undesirable outputs, such as greenhouse gas emissions, assists policymakers in determining the most cost-effective methods for reducing emissions.

The study relies on the PSALSAR and PRISMA approaches for a systematic literature review. The Web of Science and Scopus databases were used for the references.

Both parametric and nonparametric methods have been employed in the literature to estimate the shadow prices of undesirable outputs. Also, results were discussed according to the methodological and application aspects, and broad conclusions on obtained results were provided, bridging climate change mitigation policies and the shadow price of undesirable outputs.

The present study applies an integrated method, PSALSAR, to conduct a systematic review of 53 studies published between 2014 and 2023 in which efficiency models were applied to estimate the shadow price of undesirable outputs, especially CO₂. After presenting the most applicable parametric and nonparametric estimation models, a systematic summary of included articles was provided, highlighting the key features of publications.

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.

This study aims to analyse the influence of the pillars (hard and soft skills) of digital academic entrepreneurship on students' entrepreneurial intention.

This was done by adopting a quantitative methodology involving empirical research with a sample of 761 university students from two countries and adopting structural equation analysis to validate the theoretical model proposed.

The results indicate a direct influence between hard and soft skills and entrepreneurial intention, and a positive, indirect influence between these and entrepreneurial intention mediated by the dimensions of the theory of planned behaviour (TPB) – entrepreneurial attitude, subjective norms and perceived behavioural control. Therefore, the pillars of digital academic entrepreneurship have a direct and indirect influence on university students' entrepreneurial intention.

This study also contributes to better operationalization of entrepreneurial education in university environments, since the development of hard and soft skills can be planned better based on the model proposed here. Considering the relations between the dimensions of hard and soft skills and those of TPB, this study shows there can be an influence on students' entrepreneurial intention.

In this study, a new and innovative construct is inserted in the model of entrepreneurial intention: “structural pillars of digital academic entrepreneurship” through structural equation modelling, to determine the degree of influence of these pillars (hard and soft skills) constructs on HEI students' entrepreneurial intention.

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.

This study examines how project uncertainties (environmental uncertainty and participant uncertainty) affect guanxi and contractual governance and assesses the mediating role of guanxi governance between project uncertainty and contractual governance.

Data were collected in two stages from Chinese contractors. First, in-depth interviews were conducted with nine construction engineering project practitioners in different contracts as a pilot for questionnaire designing. Second, a cross-sectional questionnaire survey was conducted with professionals and practitioners of construction enterprises to collect primary data. Partial least squares structural equation modeling (PLS-SEM) was used to test seven hypotheses based on data collected from 198 respondents.

Project environmental uncertainty promotes the use of guanxi governance, while project participant uncertainty hinders it; the relationship between both types of uncertainty and contractual governance is the same as with guanxi governance. Furthermore, guanxi governance promotes contractual governance and partially mediates project environmental uncertainty and contractual governance and a complete mediating role between project participant uncertainty and contractual governance.

As the interviewed samples are mainly from China, the study should be replicated using large representative samples from East Asian countries, such as Japan and South Korea, to gain a more comprehensive understanding of the influence of guanxi governance. Further, while the internal consistency reliability and convergent validity of the questionnaire data in this study align with the standards, a larger sample size would improve the reliability and validity of the research results and better represent the overall work situation of contractors, owners and public policymakers.

The results provide insights into project governance research and have implications for construction practitioners in deploying governance-related resources.

This study aims to evaluate students' satisfaction with university library services in southern Punjab, Pakistan, emphasizing their perspective on service quality (SQ).

A LibQUAL+® survey with 22 core items was conducted within university settings using convenience sampling. In total, 345 usable responses were returned through Google Forms. Data analysis involved descriptive statistics, ordinal logistic regression test, Pearson and Deviance statistics and chi-square test to assess the satisfaction status of library users.

The study found that libraries generally meet SQ standards. However, there were minor gaps in information control (IC) and library as place (LP).

The study provides library administrators with actionable insights to enhance services, encouraging stakeholders to adopt optimal library practices for heightened efficiency and user satisfaction.

It highlights the crucial role of libraries in shaping future societal progress by emphasizing the need for elevated user services. Librarians can use this knowledge to modify their planning and take impactful initiatives that align with the evolving needs of their users.

While many studies have utilized LibQUAL, this research is unique for its focus on addressing university library services in underdeveloped regions facing economic challenges. It attempts to fill the information gap by offering a transferable approach for strategic priorities in similar settings.

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.