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Prior literature has long argued that knowledge networks contain great opportunities for innovation, and researchers can identify these opportunities using the properties of knowledge networks (PKNs). However, previous studies have examined only the relationship between structural PKNs (s-PKNs) and innovation, ignoring the effect of qualitative PKNs (q-PKNs), which refer to the quality of the relationship between two elements. This study aims to further investigate the effects of q-PKNs on innovation.

Using a panel data set of 2,255 patents from the Chinese wind energy industry, the authors construct knowledge networks to identify more PKNs and examine these hypotheses.

The results show that q-PKNs significantly influence recombinant innovation (RI), reflecting the importance of q-PKNs analysed in this study. Moreover, the results suggest that the combinational potential of an element with others may be huge at different levels of q-PKNs.

This study advances the understanding of PKNs and RI by exploring how q-PKNs impact RI. At different levels of PKNs, the potential of the elements to combine with others and form innovation are different. Researchers can more accurately identify the opportunities for RI using two kinds of PKNs. The findings also provide important implications on how government should provide support for R&D firms.

This study aims to explore the factors influencing the evolution of emerging technology innovation network (ETIN) in combination with the key attributes and life cycle of emerging technologies, particularly the impact of multiple knowledge attributes and technology life cycle on the ETIN evolution.

This study collects 5G patent data and their citation information from the Derwent Innovations Index to construct a 5G technology innovation network (5GIN) as a sample network and conducts an empirical analysis of the 5GIN using the temporal exponential random graph model (TERGM).

The results indicate that during the 5GIN evolution, the network scale continues to expand and exhibits increasingly significant core-periphery structure, scale-free characteristic, small-world characteristic and community structure. Furthermore, the findings suggest that the multiple knowledge attributes based on the key attributes of emerging technologies, including knowledge novelty, coherence, growth and impact, have a significant positive influence on the ETIN evolution. Meanwhile, the temporal evolution of ETIN is also found to be correlated with the life cycle of emerging technologies.

This study extends the exploration of emerging technology research from a complex network perspective, providing a more realistic explanatory framework for the factors influencing ETIN evolution. It further highlights the important role that multiple knowledge attributes and the technology life cycle play within this framework.

Due to the increasing size and complexity of construction projects, construction engineering and management involves the coordination of many complex and dynamic processes and relies on the analysis of uncertain, imprecise and incomplete information, including subjective and linguistically expressed information. Various modelling and computing techniques have been used by construction researchers and applied to practical construction problems in order to overcome these challenges, including fuzzy hybrid techniques. Fuzzy hybrid techniques combine the human-like reasoning capabilities of fuzzy logic with the capabilities of other techniques, such as optimization, machine learning, multi-criteria decision-making (MCDM) and simulation, to capitalise on their strengths and overcome their limitations. Based on a review of construction literature, this chapter identifies the most common types of fuzzy hybrid techniques applied to construction problems and reviews selected papers in each category of fuzzy hybrid technique to illustrate their capabilities for addressing construction challenges. Finally, this chapter discusses areas for future development of fuzzy hybrid techniques that will increase their capabilities for solving construction-related problems. The contributions of this chapter are threefold: (1) the limitations of some standard techniques for solving construction problems are discussed, as are the ways that fuzzy methods have been hybridized with these techniques in order to address their limitations; (2) a review of existing applications of fuzzy hybrid techniques in construction is provided in order to illustrate the capabilities of these techniques for solving a variety of construction problems and (3) potential improvements in each category of fuzzy hybrid technique in construction are provided, as areas for future research.

The purpose of this paper is to make a quantitative comparison between induction machine (IM) and interior permanent magnet machine (IPM) for electric vehicle applications, in terms of electromagnetic performance and material cost.

The analysis of IM is based on an analytical method, which has been validated by test. The analysis of IPM is based on finite element analysis. The popular Toyota Prius 2010 IPM is adopted directly, and the IM is designed with the same stator outer diameter and stack length as Prius 2010 IPM for a fair comparison.

The torque capability of IM is lower than IPM for low electric loading and competitive to IPM for high electric loading. The maximum torque/power-speed characteristic of IM is competitive to IPM; while the rated torque/power-speed characteristic of IM is poorer than IPM. The power factor of IM is competitive and even better than IPM for high electric loading in low-speed region. The torque ripple of IM is comparable to IPM for high electric loading and much lower than IPM for low electric loading. The overall efficiency of IM is lower than IPM, and the maximum efficiency of copper squirrel cage IM is approximately 2-3 percent lower than IPM. The material cost of IM is about half of IPM when IM and IPM are designed with the same stator outer diameter and stack length.

The electromagnetic performances and material costs of IM and IPM are quantitatively compared and discussed.

Energy affects all areas of daily life. Especially with the industrial revolution, the fact that manufacturing has become the engine of economic growth has led to a rise in energy consumption. In this process, the countries of the world have increased their economic growth with traditional energy consumption, and this has increased carbon emissions. However, to fulfill the sustainable development goals, both the continuation of economic growth and the reduction of carbon emissions are required. In this context, the substitution of renewable energy consumption in place of traditional energy sources has started to be discussed. The aim of this study is to research the relationships among CO₂ emissions, manufacturing growth, and renewable energy consumption. For this aim, the relationship among carbon emissions, manufacturing growth, and renewable energy consumption is analyzed for the period 1997–2019 in 38 Organisation for Economic Co-operation and Development (OECD) countries. With respect to the findings of autoregressive distributed lag (ARDL) test results, manufacturing growth enhances CO₂ emissions both in the short and long terms. As the proportion of renewable energy consumption in total energy consumption rises, CO₂ emissions decrease both in the short and long terms. On the other hand, according to the Dumitrescu–Hurlin causality test results, there is a one-way causality relationship from carbon emissions to manufacturing growth and from renewable energy consumption to carbon emissions. When the findings are evaluated together, it is understood that renewable energy consumption is a substantial factor in tackling the deadlock of lessening the carbon emissions without adversely impacting manufacturing growth. Therefore, policymakers need to encourage renewable energy consumption.

This study aims to investigate the specific role of the components of ability-based emotional intelligence (their relative importance) in building different aspects of career adaptabilities and job-search success of university students.

This study employed survey data from 729 full-time students enrolled in an Indian university. Hierarchical regression analyses were conducted to test the hypotheses, and the size of indirect effect was tested using SPSS PROCESS macro.

The ability-based emotional intelligence, along with the use and regulation of emotion in job-search success, plays a significant role in shaping career adaptabilities and job-search success. The ability to use and regulate emotions does have its impact on job-search success through a self-regulatory psychological resource of control and confidence over one's career. Self-emotional appraisal is necessary for an individual to be concerned for a career which forms the initiation of any job-search.

Ability-based approach of enhancing emotional intelligence allows the university students to take a developmental approach in employment. This approach benefits the more “targeted approach to training interventions” provided by various stakeholders in the university, associated with career and employment.

Further, the study focuses on the psychological difficulties (over operational) faced by students in their employment endeavour. Both emotions and psychological resources are believed to play an important role in the career intervention. For instance, past researches have studied trait-based emotional intelligence as a personality construct. However, this study considers emotional intelligence as an ability-based aspect of intelligence, which “readily lends itself to interventions that can be enhanced through targeted training, coaching or counselling”.

This study explores the critical role of strategic leadership in driving organizational innovation amid rapid technological advancements. It delves into how strategic leaders, including top management teams and CEOs, capitalize on technological changes to foster innovation and sustain competitiveness. By employing bibliometric analysis, the research identifies pivotal themes within strategic leadership literature, highlighting the importance of adaptable leadership styles, executive influence, and the emergent role of social capital. The study underscores the necessity for strategic leaders to dynamically adjust their strategies to navigate the evolving technological landscape effectively. Through an extensive review, it offers insights into how leadership practices can drive organizational success in an era of technological disruption. This research not only extends the theoretical framework of strategic leadership in the context of technological innovation but also offers practical implications for leaders aiming to cultivate a culture of innovation within their organizations.

This chapter presents an overview of the Bitcoin and its impacts on the environment and economics from the viewpoint of carrying out a systematic analysis of the literature related to the environmental and economic effect of digital currency. It is aimed to summarize and critically examine the points of view regarding Bitcoin mining, considering its effects on global warming and the social environment, employing peer-reviewed data associated through literatures. As a result, this study provides the chance to analyze the set of knowledge regarding the effects of the Bitcoin mining procedure on the ecosystem in regard to energy use and CO₂ emissions regarding unit root tests and causality test based on nonlinear models. The results show that there exists a nonlinear causal relationship between statistics on Bitcoin mining and the CO₂ emissions. The results also imply that Bitcoin remains to be a tool utilized in the economic environment for a range of objectives despite high energy consumption and some negative environmental impact within the scope of renewable energy; hence, authorities would take Bitcoin mining impacts into account to reduce CO₂ emissions.

This paper aims to identify key sectors in carbon footprint responsibility, an introduced concept depicting CO₂ responsibilities allocated through the supply chain containing sectoral activities and interactions. In detail, various key sectors could be identified according to comparative advantages in trade, sectoral linkage and sectoral synergy within the supply chain.

A semi-closed input–output model is used to make the household income–expenditure relationship endogenous through the supply chain where sectoral CO₂ emissions are calculated, and the production-based responsibility (PR) principle is evaluated. Thus, according to “carbon footprint responsibility”, modified hypothetical extraction method is applied to decompose sectoral CO₂ in terms of comparative advantages in trade, sectoral linkage and synergy. Finally, key sectors are identified via sectoral shares and associated decompositions in carbon footprint responsibility.

Compared to 2005, in 2012, the PR principle failed to track sectoral CO₂ flow, and embodied CO₂ in import and interprovincial export increased, with manufacturing contributing the most; manufacturing should take more carbon responsibilities in the internal linkage, and tertiary sectors in the net forward and backward linkage, with sectors enjoying low carbonization in the mixed linkage; inward net CO₂ flows of manufacturing and service sectors were more complicated than their outward ones in terms of involved sectors and economic drivers; and residential effects on CO₂ emissions of traditional sectors increased, urban effects remained larger than rural ones and manufacturing and tertiary sectors received the largest residential effects.

The value of this paper is as follows: the household income–expenditure relationship got endogenous in intermediate supply and demand, corresponding to the rapid urbanization in megacities; key sectors were observed to change flexibly according to real sectoral activities and interaction; and the evaluation of the PR principle was completed ahead of using a certain CO₂ accounting principle at the city level.

The chapter contains an in-depth analysis of contemporary risks confronting terrestrial ecosystems and examines prominent strategies for biodiversity preservation, sustainable tourism, and ecological management. Agroforestry parks and ecological corridors emerge as central mechanisms for safeguarding biodiversity and enhancing habitat connectivity. The chapter delves also into the urgent task of combating desertification, exacerbated by climate change and unsustainable practices, with a particular emphasis on the challenges inherent in the realm of tourism. Within the context of tourism, the chapter identifies nature and adventure tourism as catalysts for fostering biodiversity conservation through emotive engagement, thereby stimulating visitor support for conservation policies. The imperative of sustainable tourism practices, underscored by a dedicated commitment to attenuating adverse impacts while optimizing positive outcomes, assumes paramount importance in this pursuit. The chapter underscores the strategic significance of managing visitor influxes, exemplified by techniques such as access limitations and temporal restrictions, as a key approach to mitigate issues of overcrowding and ecological deterioration.