Search results

Total factor productivity (TFP) change is an important driver of long-run economic growth in the construction sector. However, examining TFP alone is insufficient to identify the cause of TFP changes. Therefore, this paper employs the infrequently used Geometric Young Index (GYI) and stochastic frontier analysis (SFA) to measure and decompose the TFP Index (TFPI) at the firm-level from 2009 to 2018 based on Malaysian construction firms' data.

To improve the TFPI estimation, normally unobserved environmental variables were included in the GYI-TFPI model. These are the physical operation of the firm (inland versus marine operation) and regional locality (West Malaysia versus East Malaysia). Consequently, the complete components of TFPI (i.e. technological, environmental, managerial, and statistical noise) can be accurately decomposed.

The results reveal that TFP change is affected by technological stagnation and improvements in technical efficiency but a decline in scale-mix efficiency. Moreover, the effect of environmental efficiency on TFP is most profound. In this case, being a marine construction firm and operating in East Malaysia can reduce TFPI by up to 38%. The result, therefore, indicates the need for progressive policies to improve long-term productivity.

Monitoring and evaluating productivity change allows an informed decision to be made by managers/policy makers to improve firms' competitiveness. Incentives and policies to improve innovation, competition, training, removing unnecessary taxes and regulation on outputs (inputs) could enhance the technological, technical and scale-mix of resources. Furthermore, improving public infrastructure, particularly in East Malaysia could improve regionality locality in relation to the environmental index.

This study contributes to knowledge by demonstrating how TFP components can be completely modelled using an aggregator index with good axiomatic properties and SFA. In addition, this paper is the first to apply and include the GYI and environmental variables in modelling construction productivity, which is of crucial importance in formulating appropriate policies.

This chapter examines the significance of green innovation and technologies for sustainable business in Asia, focussing on the issues and challenges confronted by contemporary sustainable business models. The concept of sustainable development is introduced, which seeks to minimize negative impacts on ecosystems and preserve the environment for future generations. This chapter's methodology entails a comprehensive review of existing literature and research on green innovation, green technology, and sustainable business models in Asia. The expansion of ‘green’ energy is directly proportional to the global demand for energy resources. Understanding how green innovation influences a company's capacity for sustainable development is essential for identifying the factors that influence sustainable business models and their economic consequences. Green innovation practices encompass a variety of factors, including government regulations, preferences, supplier competence, and consumer concerns. Green technologies, such as green human resource management (HRM) practices and green innovation practices, play a crucial role in attaining sustainable development by conserving energy, protecting the environment, and enhancing business efficiency. Businesses that adopt green innovation acquire a competitive edge and enhance their performance. This chapter emphasizes the importance of green innovation research and application for business stability in Asia, where sustainability and green concepts are acquiring momentum. Customer, government, and societal pressures further emphasize the significance of green innovation in businesses. For the success of ecological innovation practices, collaboration and knowledge-sharing among various stakeholders are crucial. The adoption of green innovation practices is influenced by external environmental impacts, stakeholder pressure, and organizational support. Green technology innovation, which concentrates on resource conservation, energy efficiency, and environmental protection, is crucial to the sustainability of a business. This chapter concludes by emphasizing the importance of business sustainability in achieving environmental and economic goals and assuring sustainable corporate development. Long-term success requires an understanding of the process of value creation, delivery, and capture within sustainable business models.

The purpose of this manuscript is to detect heart fault using Electrocardiogram. Mutually low and high frequency noises such as electromyography (EMG) and power line interference (PLI) degrades the performance of ECG signals.

The ECG record depicts the procedural electrical movement of the heart, which is non-invasive foot age obtained by placing surface electrodes on designated locations of the patient’s skin. The main concept of this manuscript is to present a novel filtering method to cancel the unwanted noises in ECG signal. Here, intrinsic time scale decomposition (ITD) is introduced to suppress the effect of PLI from ECG signals.

In the existing ITD, the gain control parameter is a constant value; however, in this paper it is an adaptive feature that varies according to certain constraints. Simulation outcomes show that the proposed method effectively reduces the effect of PLI and quantitatively express the effectiveness with different evaluation metrics.

The results found by the proposed method are compared with Fourier decomposition technique and eigen value decomposition methods (EDM) to validate the effectiveness of the proposed method.

This paper aims to investigate the antecedents of recombinant innovation from the perspective of ego–network dynamics, and further disentangle whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under heterogeneous knowledge base.

This paper uses 1,801 patent data in China’s biotechnology field as a sample and adopts fixed effects regression model to examine the effects of ego–network dynamics on recombinant innovation and further uses the Wald tests to discern which ego–network dynamic is more conducive to recombinant innovation under heterogeneous knowledge base.

The empirical results indicate that ego–network dynamics have a positive impact on recombinant innovation. Specifically, for firms with high knowledge breadth and high knowledge depth as well as high knowledge breadth and low knowledge depth, ego–network stability is more conducive to recombinant innovation. By contrast, for firms with low knowledge breadth and high knowledge depth, recombinant innovation benefits more from ego–network expansion. As for firms with low knowledge breadth and low knowledge depth, both ego–network stability and ego–network expansion can promote recombinant innovation, while the effects are not significant.

This research may enlighten managers to choose suitable ego–network dynamics strategies for recombinant innovation based on their knowledge base.

This research not only contributes to the literature on recombinant innovation by revealing the impact of different ego–network dynamics on recombinant innovation but also contributes to network dynamics theory by exploring whether ego–network stability or ego–network expansion is more conducive to recombinant innovation under a heterogeneous knowledge base.

New ways of working have rapidly increased in organizations, promising employees a better control over their work time, space, and more autonomy. The present study analyzes the relationship between new ways of working and employee engagement and productivity.

A survey was conducted to evaluate organizational practices developed based on flexible schemes and the relevance of employee engagement for better productivity based on digital tools. Data were analyzed using structural equation modeling.

New ways of work requires an integration of workspaces' design, social interaction, and individual wellness. Organizations need to recognize how employees' trust, commitment, and passion are fundamental to face current and future changes. Flexibility in time and space and digital tools for work are critical.

A personalization of organizational practices to support individual well-being and flexible and hybrid schemes of work are needed. Developing policies collaboratively to work together respectfully in a hybrid environment is necessary.

Hybrid work format is allowing women to balance career and childcare, reducing the wage gap with men. The green imperative has also played a role reducing the amount of carbon monoxide produced via commuter.

The present study exposes how organizational practices must ensure employee well-being and autonomy to perform their tasks. In this regard, employees need to be recognized as individuals, physically and mentally. Attempting to force a one-size-fit-all solution can have detrimental effects on the workforce, particularly on women, people of lower socioeconomic status, and people in less advanced economies. Personalization requests empowerment and democratization at work.

Internal knowledge transfer is crucial for firms to improve their employees’ abilities and improve their work performance. However, there is still a gap in the knowledge management field regarding whether internal knowledge transfer can leverage employee personality traits and service performance in service-oriented organizations. To address this gap, this study aims to validate a multilevel model of the mediating (i.e. internal knowledge transfer as a mediator) and moderating (i.e. task interdependence as a moderator) mechanisms underlying personality traits and employee service performance.

Multilevel structural equation modeling was applied for model validation using an original data set from 45 team leaders and 333 employees working in Chinese hotels.

Internal knowledge transfer mediated the link between extraversion and employee service performance and the link between openness to experience and employee service performance. Task interdependence played a moderating role that strengthened both the impacts of extraversion and openness to experience on internal knowledge transfer.

Through the use of an original data set, this study advances the knowledge management discipline by investigating the mediating impact of internal knowledge transfer between personality traits and employee service performance and revealing the moderating impact of task interdependence that underlies the links between personality traits and internal knowledge transfer.

With increasing complexity of construction projects and new construction processes and methods are adopted, more safety hazards are emerging at construction sites, requiring the application of the modern risk management methods. As an emerging technology, digital twin has already made valuable contributions to safety risk management in many fields. Therefore, exploring the application of digital twin technology in construction safety risk management is of great significance. The purpose of this study is to explore the current research status and application potential of digital twin technology in construction safety risk management.

This study followed a four-stage literature processing approach as outlined in the systematic literature review procedure guidelines. It then combined the quantitative analysis tools and qualitative analysis methods to organize and summarize the current research status of digital twin technology in the field of construction safety risk management, analyze the application of digital twin technology in construction safety risk management and identify future research trends.

The research findings indicate that the application of digital twin technology in the field of construction safety risk management is still in its early stages. Based on the results of the literature analysis, this paper summarizes five aspects of digital twin technology's application in construction safety risk management: real-time monitoring and early warning, safety risk prediction and assessment, accident simulation and emergency response, safety risk management decision support and safety training and education. It also proposes future research trends based on the current research challenges.

This study provides valuable references for the extended application of digital twin technology and offers a new perspective and approach for modern construction safety risk management. It contributes to the enhancement of the theoretical framework for construction safety risk management and the improvement of on-site construction safety.

This paper aims to examine the effects of investor sentiment on the development of the real estate corporate bond market in Vietnam.

The research uses an autoregressive distributed lag (ARDL) model with quarterly data. Additionally, the study employs Google Trends search data (GVSI) related to topics such as “Real Estate” and “Corporate Bond” to construct a sentiment index.

The empirical outcomes reveal that real estate market sentiment improves the growth of the real estate corporate bond market, while stock market sentiment reduces it. Also, there is evidence of a long-run negative effect of corporate bond market sentiment on the total value of real estate bond issuance. Further empirical research evidences the short-term effect of sentiment and economic factors on corporate bond development in the real estate industry.

Due to difficulties in collecting data, this paper has the limited sample of 54 valid quarterly observations. Moreover, the sentiment index based on Google search volume data only reflects the interest level of investors, not their attitudes.

These results yield important implications for policymakers in respect of strengthening the corporate bond market platform and maintaining stability in macroeconomic and monetary policies in order to promote efficient and sustainable market development.

The study offers some suggestions for regulators and governments to improve the real estate corporate bond market.

This is the first quantitative study to examine the effect of sentiment factors on real estate corporate bond development in Vietnam.

Modular integrated construction (MiC) is an innovative and effective manufacturing-based method of construction that has become the mainstream development direction of projects in Hong Kong (HK). However, large-scale promotion of MiC practice still needs efforts. A pressing concern is that the impact of relevant policies on stakeholders during project implementation is rarely explored in depth. Therefore, to fill the research gap, this study aims to investigate the influence of policies on stakeholders to drive the successful implementation of MiC in HK.

This study uses a strategy of multiple methods. First, a comprehensively literature review and survey were adopted to identify critical policies and stakeholders. Second, semi-structured interviews with 28 experts were conducted to quantify their relationships. Third, three policy–stakeholder networks at initiation, planning and design and construction stages were established using social network analysis.

Environmental protection policy, COVID-19 pandemic policy and environmental protection policy and quality acceptance standard for project completion are found to be the most important policies of the three stages, respectively. The HK government and developers are highlighted as prominent stakeholders influencing policy implementation at all three stages. The dynamics of the influence stakeholders receive from critical policies at different stages of MiC are discussed. Valuable recommendations are accordingly proposed to enhance the successful implementation of MiC projects from the perspective of various stakeholders.

This study contributes to the body of knowledge by considering the mediating influence of stakeholders during policy implementation in the MiC uptake, and is valuable in helping policymakers to deeply understand the influence of policies to further forward successful MiC implementation and practicality in HK.

This review provides an overview of recent advances in electrochemical sensors for analyte detection in saliva, highlighting their potential applications in diagnostics and health care. The purpose of this paper is to summarize the current state of the field, identify challenges and limitations and discuss future prospects for the development of saliva-based electrochemical sensors.

The paper reviews relevant literature and research articles to examine the latest developments in electrochemical sensing technologies for saliva analysis. It explores the use of various electrode materials, including carbon nanomaterial, metal nanoparticles and conducting polymers, as well as the integration of microfluidics, lab-on-a-chip (LOC) devices and wearable/implantable technologies. The design and fabrication methodologies used in these sensors are discussed, along with sample preparation techniques and biorecognition elements for enhancing sensor performance.

Electrochemical sensors for salivary analyte detection have demonstrated excellent potential for noninvasive, rapid and cost-effective diagnostics. Recent advancements have resulted in improved sensor selectivity, stability, sensitivity and compatibility with complex saliva samples. Integration with microfluidics and LOC technologies has shown promise in enhancing sensor efficiency and accuracy. In addition, wearable and implantable sensors enable continuous, real-time monitoring of salivary analytes, opening new avenues for personalized health care and disease management.

This review presents an up-to-date overview of electrochemical sensors for analyte detection in saliva, offering insights into their design, fabrication and performance. It highlights the originality and value of integrating electrochemical sensing with microfluidics, wearable/implantable technologies and point-of-care testing platforms. The review also identifies challenges and limitations, such as interference from other saliva components and the need for improved stability and reproducibility. Future prospects include the development of novel microfluidic devices, advanced materials and user-friendly diagnostic devices to unlock the full potential of saliva-based electrochemical sensing in clinical practice.