Search results

Employee voice is crucial for organizations to identify problems and make timely adjustments. However, promoting voice in organizations is challenging. This study aims to investigate how social media use (SMU) in the workplace affects employee voice by examining its intrinsic mechanisms and boundary conditions. Specifically, this study examines the mediating roles of social identifications and the moderating effects of job-social media fit on the relationship between SMU and social identifications.

This study conducted a survey of 348 employees in China.

First, SMU affects voice through social identifications. Second, distinct identifications have different effects on voice, such that organizational identification positively affects employee voice, while relational identification positively affects promotive voice and negatively affects prohibitive voice. Third, when social media is highly suitable for the job, the positive effect of work-related SMU on organizational identification is strengthened, while the positive effect of social-related SMU on organizational identification is weakened.

The results indicate that different identifications have distinct impacts on voice. Additionally, this study reveals a double-edged sword effect of SMU on voice through different social identifications. Further, job-social media fit moderates the relationship between SMU and social identifications. These findings have important implications for organizations adopting social media.

In the last decades, various building information modeling–life cycle assessment (BIM-LCA) integration approaches have been developed to assess the environmental impact of the built asset. However, there is a lack of consensus on the optimal BIM-LCA integration approach that provides the most accurate and efficient assessment outcomes. To compare and determine their accuracy and efficiency, this study aimed to investigate four typical BIM-LCA integration solutions, namely, conventional, parametric modeling, plug-in and industry foundation classes (IFC)-based integration.

The four integration approaches were developed and applied using the same building project. A quantitative technique for evaluating the accuracy and efficiency of BIM-LCA integration solutions was used. Four indicators for assessing the performance of BIM-LCA integration were (1) validity of LCA results, (2) accuracy of bill-of-quantity (BOQ) extraction, (3) time for developing life cycle inventories (i.e. developing time) and (4) time for calculating LCA results (i.e. calculation time).

The results show that the plug-in-based approach outperforms others in developing and calculation time, while the conventional one could derive the most accuracy in BOQ extraction and result validity. The parametric modeling approach outperforms the IFC-based method regarding BOQ extraction, developing time and calculation time. Despite this, the IFC-based approach produces LCA outcomes with approximately 1% error, proving its validity.

This paper forms one of the first studies that employ a quantitative and objective method to determine the performance of four typical BIM-LCA integration solutions and reveal the trade-offs between the accuracy and efficiency of the integration approaches. The findings provide practical references for LCA practitioners to select appropriate BIM-LCA integration approaches for evaluating the environmental impact of the built asset during the design phase.

This paper aims to investigate the pricing of discretionary earnings in South Africa. This is a unique setting, as South African listed firms also report mandatory non-GAAP earnings (“headline earnings”).

Results are based on multivariate regression analyses for South African firms that report from 2010 to 2019.

Findings show that the value-relevance of discretionary earnings exceeds that of both GAAP earnings and headline earnings. In addition, placement of discretionary earnings reconciliations communicates information about the decision-usefulness of earnings.

Discretionary earnings remain the most value-relevant earnings measure, despite the divergent decision-useful characteristics offered by headline earnings and GAAP earnings. Therefore, the most decision-useful earnings reflect unique industry or firm characteristics rather than the assurance arising from regulation.

The negative effects of job stress and burnout on construction professionals (CPs) at the construction site have been widely concern in the construction industry. The purpose of this study is committed to explore the impact of job stress on CPs on the construction site, especially in the context of the widespread use of social media to express their emotions.

This study developed a job-related stress-burnout-health conditions-turnover intention (S-B-HT) framework to explore the direct and lagged effects of job stress, we also examined the moderating effects of online emotions, operationalized in terms of emotional intensity and expression pattern, on the relationship between job stress with job burnout under two evolution paths (i.e. health conditions or turnover intention). This study collected 271 samples through a survey questionnaire for empirical testing, and introduced structural equation models to validate the proposed conceptual model.

The results show that job stress has a significant positive effect on job burnout, and job burnout maintains a positive relationship with health conditions (or turnover intention) under the interference mechanism. Simultaneously, the online emotions expressed in social media have a positive moderating effect in two stages of the evolution path.

The findings of this study remind the project manager need to timely find and solve the job burnout characteristics of CPs due to excessive job stress, especially to prevent the accidental consequences caused by job burnout.

On this basis, this study provides an important value of using social media to express emotions for the project team to alleviate the adverse of professionals under job stress.

Human resource (HR) process research emerged as a response to questions about how (bundles of) HR practices related to organizational outcomes. The goal of HR process research is to explain variability in employee and organization outcomes by focusing on how HR practices are intended (adopted) by senior managers, the way that these HR practices are implemented and communicated by line managers, and how employees perceive, understand, and attribute these HR practices. In the first part of this chapter, we present a review of 20 years of HR process research from the start, to how it developed, and is now maturing. Within the body of HR process research, several different research theoretical streams have emerged, which are largely studied in isolation without benefiting from each other. Therefore, in the second part of this chapter, we draw on previous work to propose a staged process model in which we integrate the different research streams of HR process research, recognizing contingencies in the model. This leads us to an agenda for future research and practical implications in the final part of the chapter.

Given the growing concern about employees' well-being, numerous researchers have investigated the causes and effects of occupational stress. However, a review study on identifying existing research topics and gaps is still deficient in the extant literature. To fill this gap, this review study aims to present a bibliometric and science mapping approach to review the state-of-the-art journal articles published on occupational stress in the construction industry.

A three-fold comprehensive review approach consisting of bibliometric review, scientometric analysis and in-depth qualitative discussion was employed to review 80 journal articles in Scopus.

Through qualitative discussions, mainstream research topics were summarized, research gaps were identified and future research directions were proposed as follows: versatile stressors and stress model; an extended subgroup of factors in safety behavior; adaptation of multiple biosensors and bio-feedbacks; evaluation and comparison of organizational stress interventions; and incorporation of artificial intelligence and smart technologies into occupational stress management in construction.

The findings of this review study present a well-rounded framework to identify the research gaps in this field to advance research in the academic community and enhance employees' well-being in construction.

This study aims to examine the effect of board gender diversity on corporate litigation in China’s listed firms. The key questions this study addresses are: what are the effect of board gender diversity on corporate litigation in terms of both the frequency and severity of consequence, is there any heterogeneous effects of the relationships across firm performance?

A sample consists of 25,668 firm-year observations from over 3,340 firms is examined using logistic regression analysis and negative binomial regression analysis. The authors also use event study method and ordinary least square (OLS) regression to explore female directors’ effects on reducing the negative consequences of litigation. The logistic regression and OLS regression are reestimated with interaction terms when examining the firm performance heterogeneity.

The authors document that firms with greater female representation on their boards experience fewer and less severe corporate litigations. Moreover, in high-performing firms, board gender diversity plays a more potent role in reducing the frequency and consequences of corporate litigation than low-performing firms.

This study is among the first to examine the relationship between board gender diversity and the comprehensive corporate litigations under Chinese context. It sheds new light on China’s boardroom dynamics, offering valuable empirical implication to Chinese corporate policymakers on the role of female directors.

This research aims to determine the contribution of publications in the context of Türkiye to the international entrepreneurship literature between 2005 and 2022. We examined 471 articles published in international journals in the Web of Science (WoS) Core Collection database using bibliometric analysis techniques. We analyzed the data with the software Biblioshiny+Bibliometrix, SciMAT, and VOSViewer. We used performance, theme and evolution, co-authorship, and document analysis in data analysis. Performance analysis findings show that the most publications were made in 2021, the journal with the most publications was sustainability, and the author with the most publications was Bakır, C. Theme and evolution analysis revealed that the motor themes were corporate entrepreneurship, gender and entrepreneurial intentions in the first period (2005–2014), while institutional entrepreneurship stood out as the niche theme. In the second period (2015–2022), “corporate entrepreneurship” and “performance” emerged as the motor themes, while the niche themes in this period were “Syrian refugees” and “entrepreneurial intentions.” Document analysis findings show that the most studied entrepreneurship types are gender, family, corporate, social, and small business, respectively. In addition, immigrant/refugee entrepreneurship is emerging as a new topic, while indigenous entrepreneurship, informal entrepreneurship, sustainable entrepreneurship, and religion entrepreneurship are the most minor studied topics in entrepreneurship. Evidence-based decision-making inputs were obtained for those holding the resource allocation authority in Türkiye. Policymakers and funders, as well as individuals and institutions that want to design the future in terms of resources, can benefit from the findings and analysis of this chapter. Türkiye, which ranks 26th in the world regarding entrepreneurship, must develop a policy based on data.

Due to the frenetic and dynamic working conditions ascribed to architecture, engineering and construction (AEC) project organizations, enormous research has addressed the poor mental health propensity of project management practitioners (PMPs). However, research has not considered the distant factors related to organizational design causing poor mental health. Therefore, this study addresses the problem by integrating institutional theory, agency theory and resource-based theory (RBT) to explore the relationship between organizational design elements: project governance, knowledge management, integrated project delivery, project management skills and mental health management indicators. Examples of mental health management indicators include social relationships, work-life balance and project leadership.

Purposive sampling method was adopted to collect survey data from 90 PMPs in 60 AEC firms in Australia. Structural equation modelling (SEM) was utilized to test the relationship between the variables.

The research found that project governance, knowledge management and integrated project delivery are positively correlated to mental health management indicators. However, the research finding suggests that project management skills have a negative impact on mental health management indicators.

The findings offer guidelines to AEC firms on achieving positive mental health management outcomes through concentration on project governance, knowledge management and integrated project delivery. It further calls for a reconsideration of existing project management skills causing poor mental health management outcomes.

One of the most neglected sources of energy loss is streetlights that generate too much light in areas where it is not required. Energy waste has enormous economic and environmental effects. In addition, due to the conventional manual nature of operation, streetlights are frequently seen being turned ‘ON’ during the day and ‘OFF’ in the evening, which is regrettable even in the twenty-first century. These issues require automated streetlight control in order to be resolved. This study aims to develop a novel streetlight controlling method by combining a smart transport monitoring system powered by computer vision technology with a closed circuit television (CCTV) camera that allows the light-emitting diode (LED) streetlight to automatically light up with the appropriate brightness by detecting the presence of pedestrians or vehicles and dimming the streetlight in their absence using semantic image segmentation from the CCTV video streaming. Consequently, our model distinguishes daylight and nighttime, which made it feasible to automate the process of turning the streetlight ‘ON’ and ‘OFF’ to save energy consumption costs. According to the aforementioned approach, geo-location sensor data could be utilised to make more informed streetlight management decisions. To complete the tasks, we consider training the U-net model with ResNet-34 as its backbone. Validity of the models is guaranteed with the use of assessment matrices. The suggested concept is straightforward, economical, energy-efficient, long-lasting and more resilient than conventional alternatives.