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Social interaction is an essential determinant of self-esteem. However, studies have rarely examined the psychological mechanisms underlying social interaction and self-esteem or variations in the relationship between these factors under different levels of familiarity between interactants. Therefore, the present study filled this research gap by investigating the relationships between online social interaction, social exclusion, self-esteem, and familiarity as well as the mediating effect of social exclusion and the moderation effect of familiarity on the relationship between social interaction and self-esteem.

We employed snowball sampling for conveniently and efficiently sampling a broad range of social media users to investigate how online social interaction affected their self-esteem through the mediating effect of social exclusion and the moderation effect of familiarity.

An analysis of 390 valid questionnaires indicated that online social interaction was positively related to self-esteem. Moreover, the results indicated that this relationship was mediated by social exclusion and moderated by familiarity.

We recommend that social media developers avoid including a “read” mark in their applications because such a mark can result in negative emotions, negative behaviors, and social problems in users.

With the widespread collection and utilization of user data, privacy security has become a crucial factor influencing online engagement. In response to the growing concern about privacy security issues on social media, this research aims to examine the key causes of social media users' privacy calculus and how the balance between perceived privacy risks and benefits affects users' privacy concerns and their subsequent willingness to disclose personal information.

The characteristics of the privacy calculus were extracted through partially structured interviews. A research model derived from privacy calculus theory was constructed, and latent variable modeling was employed to validate the proposed hypotheses.

Information sensitivity, experiences of privacy violations, social influence and the effectiveness of privacy policies influence users' privacy calculus. Privacy risk positively influences privacy concerns. Personal information disclosure willingness is positively influenced by privacy benefits and negatively influenced by privacy concerns, with both paths moderated by social media identification.

This study explores the key antecedents of users' privacy calculus and how these factors influence privacy concerns and subsequent willingness to disclose information on social media. It offers new insights into the privacy paradox observed within social media by validating the moderating role of social media identification on users' information disclosure willingness.

This chapter explored health and safety considerations in stealth construction, emphasising the integration of advanced technologies and innovative practices. It commences with a general introduction, followed by a historical overview of safety practices in the construction industry, highlighting the evolution of a safety culture. The chapter examined various health and safety management techniques, including policy formulation, safety training programs, and job safety analysis. Additionally, it discussed current trends such as wearable technology, IoT, VR/AR, and predictive analytics. The unique requirements of stealth construction are addressed, focusing on building cross-section design, visibility, application of radio frequency emission and countermeasures. Finally, it presents a comprehensive approach to achieving stealth construction, emphasising environmental protection, safety, speed, economy, and aesthetics, and provides practical examples to illustrate these concepts.

Flexibility and efficiency are dual attributes of the organizational structure that are crucial for project-driven enterprises to achieve sustainable development in a dynamic environment. However, there is a lack of research on the patterns by which the dual attributes of a project-driven enterprise’s organizational structure affect business model innovation. Employing organizational theory, this study aims to assess the mediating mechanisms and dynamic capabilities through which the dual attributes of the organizational structure influence business model innovation in project-driven enterprises.

Data were collected from 242 employees from four project-driven companies across 26 cities (e.g. Beijing, Tianjin, Guangzhou and Shenzhen) in China. Structural equation modeling revealed the relationship between organizational structure’s dual attributes and business model innovation.

The findings show that the dual attributes (flexibility and efficiency) of the organizational structure have positive impacts on business model innovation. Moreover, dynamic capabilities mediate the relationship between the dual attributes and business model innovation in project-driven enterprises.

This study provides contributions to innovation research in the context of project-driven enterprises by revealing the influence of organizational structure on business model innovation through the firms’ dynamic capabilities. Such knowledge can enable managers of project-driven enterprises to develop effective interventions to promote business model innovation.

This chapter explains how and why the knowledge economy will increase the demand for knowledge engineering. It defines and traces the evolution of knowledge engineering. It identifies the two components of knowledge engineering – elicitation and representation. It discusses the increased importance of tacit knowledge, specifically know-what and know-how, for organizations and companies. The increased demand for knowledge engineering calls for increased number of knowledge engineers. Knowledge engineering will expand beyond its current homes in systems development and cognitive science. The MASK methodology is an important intermediary between formal knowledge engineering and the methods needed to develop natural language and conceptual modeling for the knowledge economy.

Existing research has generally viewed that temporal leadership has positive impacts on employees but ignores its potential drawbacks. This study aims to develop a model to explore its possible negative impacts on employees, drawing upon social information processing theory.

This study conducts a multi-wave and multisource survey to test the model, and the authors test the hypotheses with multi-level analysis using Mplus 7.4 and R package for Monte Carlo.

Results suggest that temporal leadership induces employee work alienation, thus leading to employee silence. Furthermore, shared temporal cognitions moderate both the relationship between temporal leadership and work alienation and the indirect effect of temporal leadership on employee silence via work alienation.

Taken together, this study reveals the potential dark side of temporal leadership and provides a more comprehensive and dialectical research perspective for temporal leadership literature.

Prior research has demonstrated that temporal leadership brings benefits, whereas scholars know little about its potential drawbacks. This study aims to explore the positive and negative effects of temporal leadership.

A three-wave, multi-source survey was conducted to examine the theoretical model and test hypotheses. Multi-level analysis was performed using Mplus 7.4 and the R package for Monte Carlo simulations.

This study reveals that temporal leadership both decreases employee proactive behavior through emotional exhaustion and increases it through job absorption. Shared temporal cognitions buffer the effect of temporal leadership on emotional exhaustion and its indirect effect on proactive behavior through emotional exhaustion. Conversely, shared temporal cognitions strengthen the effect of temporal leadership on job absorption and its indirect effect on proactive behavior through job absorption.

Our findings show that temporal leadership has costs and benefits. Thus, it is essential to manage temporal leadership behavior.

Our research provides new insight into understanding the costs and benefits of temporal leadership.

Drawing on the conservation of resources (COR) theory, this study aims to examine the effects of servant leadership and despotic leadership on employees’ happiness at work (HAW) through job crafting.

To test the hypothesized relationships, the data were collected from 309 Pakistani employees. Structural equation modeling was used to analyze the data.

The findings showed that servant leadership is an optimal leadership style for creating employees’ HAW. In addition, job crafting was found to mediate the effects of servant leadership on employees’ broad-based positive attitudinal outcome (HAW). Moreover, results showed that despotic leadership negatively influences employees’ HAW through job crafting.

This study is novel as it investigates how newer forms of positive (servant) and negative (despotic) leadership styles influence employees’ multidimensional attitudinal outcome (HAW) via job crafting. By doing so, this research extends the nomological network of servant leadership, despotic leadership, job crafting and HAW.

Innovation capabilities, changes in customer expectations and continuous supply chain (SC) network disruptions bring complexity and challenges to manufacturing firms (MFs). This study examines the influence of uncertainty, supplier innovation, cost reduction and integration of third-party logistics (3PLs) and fourth-party logistics (4PLs) on logistics outsourcing adoption.

Based on data collected from 180 managers in MFs in Jordan, our proposed research model was tested using partial least squares-SEM (PLS-SEM).

The findings suggest that supplier innovation and integration with 3PLs and 4PLs are key enablers of adopting logistics outsourcing in the manufacturing sector. Further, the findings indicate no significant impact of uncertainty and cost reduction as logistics outsourcing enablers. The results also suggest that integration with 3PLs and 4PLs mediate fully and positively the path between supplier innovation and logistics outsourcing adoption.

This study contributes to the manufacturing literature by providing a better understanding of the main enablers of logistics outsourcing in the manufacturing sector, simultaneously tackling dependence and enhancing adoption performance in the innovation and disruptions SC era. Further, it expands the understanding of the integration between SC partners in these twofold roles.

The purpose of this study was to evaluate the environmental footprint of a university of applied sciences in 2019 and 2020, including the effects of the lockdown periods. The study identified the main sources of emissions and assessed the pandemic-related effects.

Using the life cycle assessment methodology, this study analysed the university’s direct and indirect emissions during a regular year of operation (2019) and compared them with those generated during the lockdown periods in 2020. For the activity areas mobility, energy, waste, IT and paper, gastronomy and water, specific, primary bottom-up inventory data were gathered before and during the pandemic. The data were assessed with 15 environmental impact assessment methods of the environmental footprint framework.

The results of a regular year of operation (2019) depicted that student and employee commuting and business travel contributed with 86% largely to the total global warming potential of 2,572 t CO₂-eq. The pandemic-induced changes in commuting and business travel resulted in a 60% reduction, leading to a drop to 1,075 t CO₂-eq (2020). In contrast, the environmental footprint due to energy consumption remained almost on the same level, irrespective of the absences on-site in 2020.

This study has the potential to shape post-pandemic environmental efforts and policies in higher education institutions and contribute to a much-needed baseline against which mitigation efforts can be compared with. Unlike other studies, this study goes beyond the carbon footprint, expanding the discussion to additional environmental and human health impact categories by applying the environmental footprint framework.