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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.

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.

This study aims to evaluate the thermal performance of sodium alginate (SA) aerogel attached to nano SiO₂ and its radiative cooling effect on firefighting clothing without environmental pollution.

SA/SiO₂ aerogel with refractory heat insulation and enhanced radiative cooling performance was fabricated by freeze-drying method, which can be used in firefighting clothing. The microstructure, chemical composition, thermal stability, and thermal emissivity were analyzed using Fourier transform infrared spectroscopy, scanning electron microscopy, thermogravimetric analyzer and infrared emissivity measurement instrument. The radiative cooling effect of aerogel was studied using thermal infrared imager and thermocouple.

When the addition of SiO₂ is 25% of SA, the prepared aerogel has excellent heat insulation and a high radiative cooling effect. Under a clear sky, the temperature of SA/SiO₂ aerogel is 9.4°C lower than that of pure SA aerogel and 22.1°C lower than that of the simulated environment. In addition, aerogel has more exceptional heat insulation effect than other common fabrics in the heat insulation performance test.

SA/SiO₂ aerogel has passive radiative cooling function, which can efficaciously economize global energy, and it is paramount to environment-friendly cooling.

This method could pave the way for high-performance cooling materials designed for firefighting clothing to keep maintain the wearing comfort of firefighters.

SA/SiO₂ aerogel used in firefighting clothing can release heat to the low-temperature outer space in the form of thermal radiation to achieve its own cooling purpose, without additional energy supply.

Purpose: In this chapter of this book, the role and contributions of blockchain in Industry 5.0 are examined. Especially, the advantages offered by blockchain in mass customization, hyper-personalization, human–robot collaboration and cognitive systems, which constitute the main theme of Industry 5.0, are mentioned.

Need for the study: With developing technology, revolutions are taking place in the industry. While these revolutions are occurring, various technologies serve as enablers. In this chapter, one of these technologies, blockchain, is examined.

Methodology: Industrial revolutions represent important technological developments for societies. In this chapter, Industry 5.0, one of these revolutions, is discussed. In the first section, the main themes of Industry 5.0 were examined. Afterward, the transition from Industry 4.0 to Industry 5.0 was analyzed. Then, the opportunities offered by Industry 5.0 were reviewed. Subsequently, the contributions of blockchain to Industry 5.0 were examined. Finally, the role of blockchain in Industry 5.0 is summarized.

Findings: The main themes of Industry 5.0 enable customized processes and smart production approaches. Blockchain makes significant contributions to these processes with its security and traceability features. In addition, smart contracts can increase transparency, traceability and security among stakeholders in the production process with their distributed ledger structure and immutability features. In blockchain networks, each transaction is carried out and approved by consensus. This consensus, provided by smart contracts, also secures transactions by reducing administrative costs. With these contributions, blockchain meets the security and smart management requirements of Industry 5.0.

Aluminum foam-filled thin-walled unit structures have received much attention for their excellent energy absorption properties. To improve the energy absorption effect of car energy absorption box under axial compression, this paper optimizes the fiber lay-up sequence, fiber angle and aluminum foam density of aluminum foam filled carbon fiber reinforced plastic (CFRP) thin-walled square tubes.

Design of sample points required to construct the proxy model using design of experiments (DOE) method, and the data sample points of different models are obtained through Abaqus simulation and test. A double high-precision proxy model with the maximum specific energy absorption (SEA) and the minimum initial peak crash force (PCF) as the evaluation index is constructed based on the response surface function method. The NSGA-II multi-objective genetic algorithm was used to optimize the design parameters and obtain the optimal solution for the Pareto front, and the results were verified by using the multi-objective optimization toolbox in design-expert.

The results show that the optimal solution to the multi-objective optimization problem with the inclusion of the lay-up sequence is ρ = 0.5g/cm3 for a fiber lay-up angle varying in the range ±15–90° and an aluminum foam density varying in the range 0.2g/cm3-0.5g/cm3, with a lay-up method of [±87°/±16°/±15°/±89°]. The two optimization methods correspond to SEA and PCF errors of 2.109% and 4.1828%, respectively. The optimized SEA value is 18.2 J/g and the PCF value is 18,230 N. The optimized design reduces the peak impact force and increases the specific energy absorption, which improves the energy absorption effect of thin-walled energy-absorbing boxes for automobiles.

In this paper, the impact resistance of CFRP thin-walled square tubes filled with aluminum foam is optimized. Based on numerical simulations and experiments to obtain the sample point data for constructing the dual-agent model, we investigate the effect of filling with different densities of aluminum foam under the simultaneous change of fiber lay-up angle and order on its mechanical properties in this process, and carry out the multi-objective optimization design with NSGA-II algorithm.

This study investigates the relationship between digitalization and agricultural carbon intensity from 2006 to 2021.

Utilizing panel data from 30 provinces in China from 2006 to 2021, this study employs a threshold and a spatial Durbin model to investigate the relationship between digitalization and agricultural carbon intensity. In addition, a heterogeneity analysis was conducted to understand variations across regions.

The study used threshold models and spatial Durbin models to reveal that in agricultural production, digitalization can significantly reduce the carbon emission intensity of planting and livestock production. Through the threshold effect, it was found that the effectiveness of digitization in curbing emissions varies by region and is influenced by the level of urbanization, with the inhibitory effect being: western > central > eastern. In addition, through spatial analysis, it was found that the impact of digitalization on carbon emission intensity has significant spatial effects, presenting a “high-high” and “low-low” clustering pattern. Moreover, through the Durbin model, digitization exhibits a significant negative spatial impact on the planting industry, and the development of the local digitalization can significantly reduce the carbon emission intensity of the planting industry in neighboring areas. There is a significant positive spatial effect on livestock production, and the development of local digitalization will, to some extent, increase the carbon emission intensity of livestock production in neighboring areas. This study underscores the critical importance of digitalization in reducing agricultural carbon emissions and highlights the necessity for tailored digital strategies that consider regional characteristics and urbanization levels.

This study shows the critical importance of digitalization in reducing agricultural carbon emissions and highlights the necessity for tailored digital strategies that consider regional characteristics and urbanization levels.

This paper pioneers the investigation of the spatial impact of digitalization on agricultural carbon emissions using provincial-level panel data and classifies agriculture into planting and livestock production. This study contributes to the literature by filling the research gap and enhancing our understanding of the relationship between digitalization and environmental sustainability in rural areas.

China is experiencing an economic revolution focused on reducing carbon emissions (CEs). Various technological research and development (R&D) frameworks also hasten the growth of the digital economy, which then fuels this economic revolution. Nevertheless, several correlation uncertainties in China have been observed between R&D investment and CE reduction with green economic transformation. This phenomenon is attributed to insufficient spatial impact considerations.

Therefore, this article explored the spatial impacts of the digital economy and R&D expenditures regarding environmental quality using Chinese-related panel data between 2012 and 2021. This study uses the Moran I index to test whether there is a spatial relevance between regional carbon emissions in China and assess the digital economic advancement level using the entropy weight approach. In addition, this article analyzes the direct and indirect impacts following the partial differentiation approach, and then creates an interaction term between the digital economy and R&D investment to assess the moderating effect for examining the influence of investing in R&D on reducing CO2 levels of the digital economy.

A positive spatial relevance between the digital economy and CEs was then highlighted from the empirical findings. The digital economy expansion also demonstrated higher local CEs while negatively impacting nearby regions. Notably, the digital economy concurrently lowered and increased local CEs in the Eastern and Central zones, respectively. Overall, a larger R&D investment directly impacted the capacity of the digital economy in decreasing the carbon emission intensity (CEI) at a regional level. An accelerated digital economy expansion and lower CEI were recorded in the Eastern zone owing to more significant R&D investments.

China has gradually shifted its focus from reducing CEs to implementing “dual control of carbon” to achieve the “dual carbon” target. Future studies should then involve additional studies concerning the impact mechanism and path selection related to “dual carbon control.”

Investment in R&D plays a key role in reducing carbon emissions from the digital economy. By fostering innovation and technological advances, R&D investment activities can create more energy-efficient digital infrastructures, develop sustainable practices and optimize resource use. In addition, these R&D investments can facilitate the transition to renewable energy sources, enhance data management systems to minimize waste and promote the adoption of green technologies by businesses and consumers. As the digital economy continues to evolve, prioritizing R&D in this area is critical to achieving long-term sustainable development goals and addressing the pressing challenges of climate change. Stakeholders across industries must therefore recognize the importance of investment in research and development as a strategic approach that not only drives economic growth but also ensures environmental stewardship in an increasingly digital world.

Investments in research and development not only foster innovation and technological progress, but also promote sustainable practices, which can have significant environmental benefits. In addition, they have the potential to create new jobs, improve public health through better air quality and drive economic growth in a manner consistent with climate goals. As society becomes increasingly dependent on digital solutions, it is critical to harness the power of the digital economy to achieve a more sustainable and inclusive society.

Research development investment is critical to all aspects of regulation. Research on R&D investment can provide direction to local governments in formulating digital economy policies and can be beneficial to local governments in considering regional differences in resource availability. The research and technical innovation strategies in the policies for developing the digital economy can substantially expedite carbon neutrality achievement by 2060.

Open innovation platform has become an effective field through which enterprises can acquire valuable knowledge for incremental and breakthrough innovation. However, as more entities join the innovation platform, the knowledge activities in the platform ecosystem are now facing higher complexity and vulnerability due to the differences in the knowledge demands as well as conflicting interest claims of participants. The lack of mature governance mechanisms has caused opportunistic behaviors like knowledge infringement, leakage and hiding, which seriously hinder the in-depth knowledge sharing and effective utilization. What’s more, the enthusiasm for collaborative innovation also reduced among multi-subjects. Therefore, the purpose of this study is to improve platform participants’ innovation ambidexterity under the guidance of scientific design of platform knowledge governance mechanisms through improved knowledge transformation processes.

Therefore, based on knowledge governance theory and knowledge transformation model (SECI, socialization-externalization-combination-internalization), the study explored the influence of relationship and contractual knowledge governance on the innovation ambidexterity of platform participants through the mediation effect of knowledge transformation. To better analyze complex causal relationships among variables and the chain multiple mediation effect, structural equation modeling is used, coupled with bootstrap analysis verification.

Platform contractual governance and relationship governance can positively influence the innovation ambidexterity of participants through knowledge trading and reuse, as well as through knowledge sharing and creation. The findings not only contribute to optimizing the effectiveness of knowledge activities on digital platforms but also provide empirical evidence and practical insights to support enterprises’ incremental and breakthrough innovation according to their own knowledge bases.

The findings offer valuable insights for providing decision-making guidance not only for platform-leading enterprises but also for individual and enterprise users on effectively using open innovation platforms to conduct knowledge seeking, trading or sharing and knowledge reuse or creation to enlarge the incremental innovation value and to trigger breakthrough innovation value in their product and technology developments.

Through diverse knowledge governance mechanisms, platform-leading enterprises do not only act as “economic agents” with private attributes to reduce knowledge asymmetry in the public trading market, diffuse knowledge broadly and mitigate cooperation costs to increase economic value; they also serve as “social actors” for multilateral participants to increase the cohesion of knowledge sharing and creation to provide sustainable knowledge fuel for the higher level of breakthrough innovation. Overall, knowledge arrangement efficiency can be optimized, and breakthrough innovation value can be activated in a well-governed platform, gradually escaping the diminishing marginal benefits of exploitative innovation.

This study has extended the views of the knowledge transformation model under the platform context and proposed dualistic knowledge transformation pathways, named “tacit knowledge socialization” and “explicit knowledge combination,” respectively. Besides, it discovered that under the contractual and relationship knowledge governance mechanisms’ guiding, participants in open innovation platforms may choose different knowledge searching and exchange ways according to their knowledge needs and thus trigger the different knowledge transform process. Then, “tacit knowledge socialization” transformation can show larger positive impact on breakthrough innovation, while “explicit knowledge combination” transformation makes larger impact on incremental innovation.

Artificial Intelligence (AI) has become an integral part of every business organisation across the world. It is a system designed to mimic human attributes such as speech, learning and problem-solving. It promotes cognitive functioning and can supplement and replace human workers in social, intellectual and professional contexts. AI serves as a versatile toolbox encompassing a range of technologies, including machine learning (ML), natural language processing, expert systems, neural networks, deep learning, robots and automation. These tools transform the business and marketing landscapes and infuse entertainment with innovation to boost consumer engagement. The growth of AI has set a new standard for what customers expect from businesses. AI provides companies with powerful tools to comprehend and meet customer expectations effectively. AI has given rise to diverse technologies, including robots, avatars, virtual bots and narrowcasting. The advent of AI-driven chatbots is revolutionising customer service by delivering instant responses, efficiently addressing queries and slashing wait times. This blend of AI and a customer-centric approach establishes the foundation for sustainable growth and enduring customer loyalty. This chapter will shed light on the present state of awareness regarding AI and ML and their impact on consumer engagement. We aim to illustrate how AI is utilised and its effects on the marketing landscape.

While extensive research exists on how positive life circumstances and positive personality traits promote entrepreneurship, there is little research focusing on how negative personal circumstances may potentially breed entrepreneurship. This study aims to build upon the theory of underdog entrepreneurship to examine the effect of challenging life circumstances such as poverty on the development of entrepreneurial traits in underdog entrepreneurs. This research analyzed the effect of risk-taking (RT) on the entrepreneurial success (ES) of underdog entrepreneurs and the role of optimism (OPM) and persistence (P) as mediating variables and poverty as a moderator variable.

A cross-sectional survey was conducted to collect data from 400 micro-finance borrowers of Akhuwat Foundation Pakistan. Akhuwat provides interest-free small loans to the poor segment of society. Preliminary testing of the survey questionnaire with a sample of 35 borrowers of Akhuwat Foundation in Lahore city was conducted before data collection. Data was collected from four randomly selected branches in Lahore city.

The authors found that OPM and P significantly mediate the relationship between RT and ES. In addition, the authors analyzed the moderating effect of poverty on the relationship between OPM and ES and found a negative moderating effect. A strong positive moderating effect of poverty was found on the relationship between P and ES. The results of multi-group analysis show that successful and unsuccessful underdog entrepreneurs differ in their RT propensity, which is significantly mediated by OPM and P.

This study provides empirical evidence on entrepreneurial traits and success of poor entrepreneur in an emerging economy. This work is original and has not been submitted elsewhere.