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Drawing upon strengths-based inclusive work theory, this study explores how strengths-based leadership promotes employee career sustainability, particularly in the absence of protean career orientation (PCO), with career adaptability as a mediator.

A three-wave survey of 329 Chinese employees tested the moderated mediation model. Hypotheses were assessed using SPSS 26.0 and Mplus 8.3.

Strengths-based leadership positively influences career adaptability, leading to greater career sustainability. The effect is stronger when PCO is low, highlighting the compensatory role of strengths-based leadership.

The present paper extends the existing literature on strengths-based leadership and unveils that strength-based leadership can compensate for a lack of PCO. Also, it augments strengths-based inclusive work theory and provides meaningful insights to cultivate employee career sustainability.

The cross-sectional design and self-reported data limit causal conclusions. Future research should use longitudinal methods and diverse cultural contexts to improve generalizability.

This study aims to investigate the predictive role of team personality composition in facilitating shared leadership through team member exchange (TMX), while also to examine the moderating effect of organizational culture.

The authors conducted a two-stage online survey and selected the customer service teams, claims teams and financial teams of 26 Chinese insurance companies as the research samples. The authors finally obtained validated questionnaires from 107 teams with 457 members. The hypothesized relationships were tested using SPSS 25.0 and Mplus.

The results indicate that both team relationship-oriented and task-oriented personality composition have significant positive effects on shared leadership with team-member exchange serving as a full mediator for both paths. As a boundary condition, organizational culture (i.e. including internal integration values and external adaptation values) has a moderating effect on the influence of TMX on shared leadership.

The study investigates the predictive role of team personality composition on shared leadership, which complements the empirical studies of shared leadership antecedents in the literature. Drawing on social exchange perspective, the authors find out that TMX serves as a mediator between team personality composition and shared leadership. The authors also identify the moderating effect of organizational culture on the emergence of shared leadership. The research emphasizes the contextual boundary condition in this process.

To deepen the structural reform of the financial system on the supply side and mitigate associated risks in the economic and financial fields, with significant practical implications for FinTech development.

Based on microdata of listed companies, this paper constructs multi-level indicators of FinTech development. Robustness tests include alternative measures of the degree of long-term use of short-term debts, sample adjustments and heterogeneity in firm characteristics and regional differences.

FinTech can significantly alleviate the long-term use of short-term corporate debt, although there are heterogeneous effects. The alleviation effect is more pronounced for state-owned enterprises, non-technology-intensive enterprises and other companies with lower levels of short-term debt maturity. Additionally, in regions with high capital mismatch and high levels of financial development, FinTech exhibits a significant suppressive effect on the long-term use of short-term corporate debt.

The paper suggests promoting the diversification of FinTech products, emphasizing the importance of inclusive finance through FinTech, and driving China’s economic transformation and high-quality development.

By constructing a theoretical analysis framework of “FinTech—corporate investment and financing term mismatch,” this paper provides a multi-level estimation of the factors influencing FinTech’s impact on the long-term use of short-term corporate debt. This framework aids in developing a more dialectical and objective understanding of the economic effects of FinTech’s development.

The purpose of this study is to address the challenge of task allocation in multi-robot systems by getting the minimum overall task completion time and task allocation scheme while also minimizing robot energy consumption. This study aims to move away from traditional centralized methods and validate a more scalable distributed approach.

This paper proposes a distributed algorithm for the multi-robot task allocation problem, aimed at getting the minimum task completion time along with the task allocation scheme. The algorithm operates based on local interaction information rather than global information. By using the Consensus-Based Auction Algorithm (CBAA), it seeks to effectively minimize energy consumption without affecting the minimum completion time required for overall task allocation.

The proposed distributed algorithm successfully reduces robot energy consumption while effectively obtaining the shortest overall task completion time and corresponding task allocation scheme. Numerical simulations conducted using MATLAB software demonstrated its superior performance, and empirical testing on the Turtlebot3-Burger robot platform further substantiated these findings.

The original contribution of this study lies in the development of an enhanced distributed task allocation strategy using CBAA to improve efficiency in multi-robot environments. Its value extends to applications that require rapid and resource-aware coordination, such as automated logistics or search-and-rescue operations.

This paper aims to study the problem of starvation lubrication of high-speed ball bearings due to temperature rise during operation and to avoid thermal failure of bearing lubrication.

Under the quasi-statics model of grease lubrication, both the oil film dragging force and the rolling friction between the balls and raceways collectively counteract the gyroscopic torque. Initially, the static model for grease lubrication is solved, followed by calculating the generated heat using the local heat generation method and ultimately the multinodal thermal network model is solved, and the solved results of the quasi-statics are updated by the temperatures of the grease nodes based on the relationship of the grease temperature and viscosity, as well as the relationship of the viscosity and the film thickness.

By comparing the numerical calculation results of bearings under different working conditions, the influence of starvation lubrication on the oil film thickness, oil film drag force and rolling friction of bearings is discussed, and it is found that the numerical calculation results of the outer ring temperature of bearings under the starvation lubrication due to the consideration of temperature rise are closer to the experimental values.

This study reveals the dynamic characteristics of bearings under starvation lubrication, which is more practical and engineering guiding significance for the design of bearings, and introduces a new method and basis for the calculation of temperature rise of rolling bearings.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-06-2024-0208/

Despite the continuous development and application of new digital technologies in the construction industry, there has been little research on digital technology trajectories in the construction industry. The study addresses the issue faced by the construction industry in exploring digital technology trajectories: how to comprehensively identify and analyse digital technology pathways across multiple technology fields in the construction industry.

Firstly, the digital technology patent identification and classification method based on text mining is used to identify digital technology patents and construct a digital technology innovation network. Second, the main path of the digital technology innovation network is identified with the help of SPNP. Then, the subpaths of the digital technology innovation network are identified with the help of the Louvain algorithm and SPNP. Finally, starting from the technology nodes where the main path and subpaths intersect, the technological similarity of the paths is analysed to explore the evolutionary characteristics of the technology trajectories. In light of this, the developed method is applied to the global construction industry patent dataset to analyse the trajectories of digital technologies.

The technological innovation path in the construction industry starts with construction materials and gradually expands to intelligence, automation and digital data processing technology. Equipment and devices with electronic digital data processing capabilities as well as improvements in green building technologies and user experience-enhancing technologies, may be the future of the construction industry. With the increasing demand for green buildings and intelligent buildings, the direction of digital technology innovation in the construction industry is gradually tilted towards these areas. In addition, influenced by geographic and economic factors, there is a spatial clustering effect of digital technology innovation in the construction industry.

Future research should analyse in depth the performance of different countries and regions in digital technology innovation and explore the root causes, motivations and influencing factors behind it, such as the policy environment, the level of the economy and the investment in research and development. Exploring the reasons affecting digital technology innovation can help formulate more targeted policies and promote cooperation and exchange of digital technology innovation in the global construction industry. Meanwhile, to solve the problems of overly broad IPC categorization and the difficulty of accurately describing cross-field innovations, combining IPC co-occurrence networks with patent citation networks is an effective strategy. This strategy can track technologically interrelated patents and provide more specific contents to know the advantages and challenges of the construction industry in the field of digital technology innovation.

The study has practical implications for the construction industry. The identification of digital technology innovation trajectories provides valuable insights for industry firms and research institutes. It helps them understand the current and future directions of digital technology in construction, enabling them to stay at the forefront of technological advancements. The findings highlight the importance of focusing on areas such as solar energy utilisation, green energy, intelligence, automation and data applications. This knowledge can guide firms in developing new building materials, incorporating digital information technologies and enhancing user experiences. The study’s results can inform strategic decision-making, technology adoption and innovation management in the construction sector.

The social implications of this study are significant for various stakeholders. The identification of digital technology innovation trajectories in the construction industry highlights the potential benefits for society. The focus on green energy, intelligent buildings and enhanced user experiences aligns with the increasing demand for sustainability, energy efficiency and comfortable living environments. These technological advancements can contribute to reducing environmental impact, improving quality of life and promoting sustainable development. The findings can inform policymakers, urban planners and architects in shaping regulations, designing sustainable cities and creating buildings that prioritize energy efficiency and user well-being. Ultimately, the study’s social implications aim to foster a more sustainable and livable built environment.

An identification method integrated with SPNP and the Louvain algorithm is developed to map digital technology innovation trajectories in the construction industry. This study helps to reveal the trajectories of digital technology innovation, provides new perspectives, insight and ideas for research in related fields and has great potential for applications in practice to promote the innovation and development of the construction industry.

This paper examined the factors influencing the participation of rice processors in short supply chains and the participation impact on the amount of rice processed, per capita expenditure of household and value of sales.

The Seemingly Unrelated Regression and Doubly Robust Augmented Inverse Probability Weighting Model (AIPW) were used to analyse the determinants of short supply chain participation and the impact of short supply.

From the results, the mean value of rice processed was GH₵18385 (US$ 3,069.28), with the minimum value being GH₵ 25 (US$ 4.17) and the maximum GH₵ 67200 (US$ 1,1218.70) per annum. Processed rice aroma and grade characteristics positively influence the value of processed rice sold via short supply chains as well as the expertise rate of the processor, Farmer-Based Organisation membership, and marketing information availability. Women rice processors' per capita expenditure, total sales value and the value of processed rice was positively influenced by the short supply chain participation.

Even though the sample size was appropriate, a larger sample size could further support the study's finding since a limited geographical area with predominant domestic rice processors was studied. Again, future studies should consider behavioural theories, such as the Theory of Planned Behaviour, amongst others, in understanding the reasons for the choices of short supply chains compared to other sales outlets.

Although there is a growing body of literature on rice, most of the studies focussed on the marketing outlet of rice producers, rice processing, constraints and opportunities faced by rice farmers and processors and an out-grower scheme involving rice processors amongst rice producers with none of these on the choice of short supply chains amongst women processors. Also, amongst all the studies on rice producers, none applied a theory; however, the Women in Development (WID) Theory was used to analyse the impact of the short supply chain on the impact on household per capita expenditure (poverty), the value of sales and amount of rice processed, a modest theoretical contribution of the paper to literature.

Drawing on the frustration-aggression-displacement (FAD) hypothesis, this study investigates the link between supervisor incivility and workplace deviant behavior through the mediating pathways of supervisor-targeted aggression and emotional exhaustion. Additionally, it examines the moderating role of psychopathy in the relationships between supervisor incivility and supervisor-targeted aggression and supervisor incivility and emotional exhaustion.

Data were collected from hotel employees through a three-wave study, and variance-based partial least square structural equation modeling (VB-SEM) was employed to analyze the hypothesized associations.

Results indicate that supervisor-targeted aggression and emotional exhaustion mediate the relationships between supervisor incivility and workplace deviant behavior. However, psychopathy did not show any significant moderating effect.

The findings provide valuable insights for managers to develop effective strategies for reducing organizational incivility and deviant behaviors.

This study identifies two mediating mechanisms linking supervisor incivility to workplace deviant behavior and adds to the limited understanding of how supervisor incivility can lead to negative employee behaviors.

Exponential organizations (ExOs) are purpose-driven companies that leverage exponential technologies and exponential business practices to grow and scale rapidly, transform industries and create massive value and impact. In contrast, non-ExOs follow a linear approach to business and organizational strategy design and execution. This study aims to validate the hypothesis, based on financial metrics, that ExOs outperform their competitors and linear counterparts. Furthermore, it also brings a new understanding of the gap raised in the past eight years about how ExOs can achieve significantly better performance, measured with financial metrics.

For measuring how exponential an organization is, this study elaborated a completely new assessment tool called Exponential Quotient (ExQ). This study applied ExQ to the 100 largest US headquartered companies as ranked by Fortune magazine in 2014. Calculating the ExQ enabled this study to rank these Fortune 100 companies and identify the most and the least exponential firms. This study tracked these companies as to how they performed on different financial metrics over the eight years of 2014–2021 and analyzed the results.

Through the analysis, this study revealed that the top 10 ExOs have significantly outperformed their bottom 10 non-exponential peers, delivering 40x higher shareholder returns, 2.6x better revenue growth, 6.8x higher profitability and 11.7x better asset turnover. Furthermore, this study could identify commonalities and similarities between the two groups. This means that ExOs can thrive even in tough times and that accelerating technologies unlock abundance and allow every organization to become a disruptive innovator and stay ahead of the competition. These are novel results in the research focusing on the gap between exponential and traditional organizations.

Using the ExQ diagnostics tool, every organization can see how flexible, scalable and agile they are, which is the starting point for an exponential transformation program. Although this approach has already found its way into practice and is applied globally by thousands of organizations (startups, scaleups and incumbents), so far, the academic establishment is in its nascent phase. With this research, the authors wanted to extend this field of science. On the other hand, because of its novelty, no appropriate previous studies existed to compare the results.

The possible implications showed that there is a plannable way for significantly increasing an organization’s ExQ and advance it from a linear toward an exponential organizational model.

The results validated the robustness of the ExO framework and philosophy and shed light on the importance of exponential transformation – a proven method to increase an organization’s ExQ. This framework is not a “how to be successful” guide. Instead, it uncovered some of the previously unknown and universal mechanisms of scalability – which, in turbulent times, make companies successful (based on financial metrics). To the best of the authors’ knowledge, this study was among the first kind of in-depth analyses to validate the whole ExO model.

In this chapter, the author compares two representations of the child from two famous films by the Fifth Generation’s top director in China, Chen Kaige, Yellow Earth (1984) and Together (2002). The girl’s story in the former and the boy’s story in the latter show respectively the dissolution of the Party/state as an extended family home, and it being replaced by the atomized, fluid, and flexible family home in the new state-led neo-liberal order. Compared with the girl, the boy in the new century tries to convey an equally lyrical articulation of the family/home, but differently, with a strong sense of his subjectivity. Thus, the boy’s voice in Together, self-reflective, artistically innovative, and affective, becomes a voice of resistance against authoritarian neoliberalism in post-socialist China.