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This paper aims to demonstrate the synthesis of polyesterification reaction of non-edible jatropha seed oil (JO) and acrylic acid, which leads to the production of acrylated epoxidised-based resin. To understand the physico-chemical characteristics when synthesis the JO-based epoxy acrylate, the effect of temperature on the reaction, concentration of acrylic acid and role of catalyst on reaction time and acid value were studied.

First, the double bond in JO was functionalised by epoxidation using the solvent-free performic method. The subsequent process was acrylation with acrylic acid using the base catalyst triethylamine and 4-methoxyphenol as an inhibitor respectively. The physico-chemical characteristics during the synthesis of the epoxy acrylate such as acid value was monitored and analysed. The formation of the epoxy and acrylate group was confirmed by a Fourier transform infrared spectroscopy spectra analysis and nuclear magnetic resonance analysis.

The optimum reaction condition was achieved at a ratio of epoxidised JO to acrylic acid of 1:1.5 and the reaction temperature of 110°C. This was indicated by the acid value reduction from 86 to 15 mg KOH/g sample at 6 hours.

The JO-based epoxy acrylate synthesised has a potential to be used in formulations the prepolymer resin for UV curable coating applications. The JO which is from natural resources and is sustainable raw materials that possible reduce the dependency on petroleum-based coating.

The epoxidised jatropha seed oil epoxy acrylate was synthesised, as a new type of oligomer resin that contains a reactive acrylate group, which can be alternative to petroleum-based coating and can used further in the formulation of the radiation curable coating.

Hot and humid climates (HHCs) are potential environmental hazards that directly affect construction workers' health and safety (HS) and negatively impact workers' productivity. Extensive research efforts have addressed the effects of HHCs. However, these efforts have been inconsistent in their approach for selecting factors influencing workers in such conditions. There are also increasing concerns about the drop-off in research interest to follow through intrusive and non-real-time measurements. This review aims to identify the major research gaps in measurements applied in previous research with careful attention paid to the factors that influence the intrusiveness and selection of the applied data collection methods.

This research integrates a manual subjective discussion with a thematic analysis of Leximancer software and an elaborating chronological, geographical and methodological review that yielded 701 articles and 76 peer-reviewed most related articles.

The literature included the physiological parameters as influencing factors and useful indicators for HHC effects and identified site activity intensity as the most influencing work-related factor. In total, three main gaps were identified: (1) the role of substantial individual and work-related factors; (2) managerial interventions and the application of the right time against the right symptoms, sample size and measurement intervals and (3) applied methods of data collection; particularly, the intrusiveness of the utilised sensors.

The focus of researchers and practitioners should be in applying nonintrusive, innovative and real-time methods that can provide crew-level measurements. In particular, methods that can represent the actual effects of allocated tasks are aligned with real-time weather measurements, so proactive HHC-related preventions can be enforced on time.

This review contributes to the field of construction workers' safety in HHCs and enables researchers and practitioners to identify the most influential individual and work-related factors in HHCs. This review also proposes a framework for future research with suggestions to cover the highlighted research gaps and contributes to a critical research area in the construction industry.

The purpose of this paper is to systematically review and assess the current status of research on supply chain sustainability from a network structural perspective and provide an organising framework for future scholarship in this area.

By adopting an evidence-based approach, this study conducts a systematic review of 73 articles from 18 peer-reviewed journals published between 2000 and 2020.

Adopting a social network analysis approach, the review identifies specific node-level (i.e. degree centrality, closeness centrality and betweenness centrality) and network-level (i.e. network density, network sub-groups and network diversity) structural properties that play a role in supply chain sustainability. The results reveal that structural properties determine the extent of perception of sustainability risks, the diffusion of sustainability targets, introduction of sustainable innovations, development of sustainability capabilities, adoption of sustainability initiatives and the monitoring of sustainability performance throughout the supply chain.

By distinguishing between supply network and sustainable supply network types, this study extends the existing understandings of the role of network connectivity patterns in supply chain sustainability through synthesising and evaluating the extant literature. This study further clarifies the role of these network structural properties in supply chain sustainability by describing their impact on a set of sustainable supply chain management practices through which firms achieve sustainability goals across their supply chains.

Although the Chinese economy has experienced a strong and rapid growth due to the success of its economic reform, the Chinese central government faces a stern fiscal decline. The fiscal problem has undermined the ability of the central government in completing many crucial governing tasks. By examining the institutional root of the fiscal problem, this paper argues that the fiscal decline is part of the ironic corollary of the decentralization strategy of China’s economic reform which produces a “weak center, strong local” outcome. To fully address the problem, China should undertake major institutional reforms to redefine as well as institutionalize the fiscal roles of different levels of government.

The purpose of this study is to examine the potential process through which leadership exerts impacts on organizational innovation. A thorough analysis was conducted by highlighting the contribution of ambidextrous leadership to organizational innovation.

Data were collected from companies located in mainland China. A total of 200 cases were included in the final sample. Hierarchical regression analysis was adopted to test the hypotheses in this study.

The results showed that exploitation knowledge search and exploration knowledge search partly mediated the relationship between ambidextrous leadership and organizational innovation, respectively. Strategic flexibility could positively moderate the relationship between exploitation knowledge search and organizational innovation and had no significant impacts on moderating the relationship between exploration knowledge search and organizational innovation.

In this study, not only were managers provided with a sophisticated understanding of how and when ambidextrous leadership could influence organizational innovation but also concrete strategies were given for enhancing organizational innovation.

In this study, the interaction among ambidextrous leadership, knowledge search and organizational innovation were elucidated and the moderating impacts of strategic flexibility on the relationship between knowledge search and organizational innovation were explored. The findings of this study enriched the literature on leadership, knowledge management and innovation.

This paper aims—based on past research works which have shown that transformational leadership has positive impact on knowledge sharing—to explore the impact of different leadership dimensions of transformational leadership on knowledge sharing and further to explore the mechanism through which transformational leadership affects employee knowledge sharing in China.

Based on the transformational leadership theory and the team learning theory, it is proposed that all four dimensions of transformational leadership, including intellectual stimulation, individualized consideration, inspirational motivation and idealized influence, have unique impact on employee knowledge sharing. It is further proposed that psychology safety and team efficacy mediate these relationships. Then data were collected from over 400 employees from knowledge-based companies in China to empirically test the proposed relationships with the method of structural equation modeling.

The results show that psychological safety fully mediated the impact of intellectual stimulation on knowledge sharing, and team efficacy fully mediated the impact of inspirational motivation on knowledge sharing. Both factors also mediated the impact of individualized consideration on knowledge sharing. The results thus provide empirical support for the impact of transformational leadership on employee knowledge sharing in an international context.

The past years have seen increasing interest in leadership and knowledge sharing in emerging markets, yet the mechanism through which leadership affects employee knowledge sharing remains understudied. This study explores the impact of different dimensions of transformational leadership on employee knowledge sharing, and further shows that psychological safety and team efficacy mediate these relationships in a collectivistic society where knowledge sharing is consistent with cultural norms. The findings help develop more robust knowledge sharing theories in the international context and provide insightful suggestions for management practitioners in emerging markets.

Green consumption behaviour (GCB) has been advocated to mitigate the environmental consequences of traditional consumption patterns. Besides the current circumstances, Generation Z college students are a sizable consumer group who are likely to be concerned about the future. Thus, this study aims to examine the factors affecting the college students’ GCB and the moderating effect of government support to provide new evidence from college students in China.

In addition to environmental knowledge and social media influence as the variables, government support was used as a moderator to develop the extended theory of planned behaviour (TPB) model. Purposive sampling was used to obtain 328 valid responses from Chinese college students. The collected data were analysed using partial least squares structural equation modelling.

The findings indicated that subjective norms, perceived behavioural control, environmental knowledge and social media influence substantially affect students’ GCB. Notably, the moderation analysis suggested that government support greatly strengthens the relationship between subjective norms and social media influence on the GCB of Chinese college students.

The study provides several significant practical implications as the findings could be referred by stakeholders, such as government and businesses entities, in formulating policies and strategies to encourage the consumers’ GCB in mitigating ecological consequences.

The extended TPB model that integrated environmental knowledge and social media influence with the government support as the moderator contributes to the extant literature with the evidence derived from Generation Z in China.

This study aims to investigate whether firms purchase directors' and officers' liability (D&O) insurance when the country-level economic policy uncertainty (EPU) is high.

This study uses D&O insurance data from Chinese listed firms between 2003 and 2019 to conduct regression analyses to examine the association between D&O insurance and EPU.

The results show that government EPU, despite being an exogenous factor, increases the likelihood of firms' purchasing D&O insurance, and this effect is more pronounced when firms are exposed to great share price crash risk and high litigation risk, suggesting that firms intend to purchase D&O insurance possibly due to the accentuated stock price crash risk and litigation risk associated with EPU. In addition, the results indicate that the effect of EPU on the D&O insurance purchase decision is moderated by the provincial capital market development and internal control quality.

The study highlights the role of uncertain economic policies in shareholder approval of D&O insurance purchases.

The study enriches the literature on the determinants of D&O insurance purchases by documenting novel evidence that country-level EPU is a key institutional factor shaping firms' decisions to purchase D&O insurance.

The purpose of this paper is to make a theoretical comprehensive efficiency evaluation of a nonlinear analysis method based on the Woodbury formula from the efficiency of the solution of linear equations in each incremental step and the selected iterative algorithms.

First, this study employs the time complexity theory to quantitatively compare the efficiency of the Woodbury formula and the LDLT factorization method which is a commonly used method to solve linear equations. Moreover, the performance of iterative algorithms also significantly effects the efficiency of the analysis. Thus, the three-point method with a convergence order of eight is employed to solve the equilibrium equations of the nonlinear analysis method based on the Woodbury formula, aiming to improve the iterative performance of the Newton–Raphson (N–R) method.

First, the result shows that the asymptotic time complexity of the Woodbury formula is much lower than that of the LDLT factorization method when the number of inelastic degrees of freedom (IDOFs) is much less than that of DOFs, indicating that the Woodbury formula is more efficient for local nonlinear problems. Moreover, the time complexity comparison of the N–R method and the three-point method indicates that the three-point method is more efficient than the N–R method for local nonlinear problems with large-scale structures or a larger ratio of IDOFs number to the DOFs number.

This study theoretically evaluates the efficiency of nonlinear analysis method based on the Woodbury formula, and quantitatively shows the application condition of the comparative methods. The comparison result provides a theoretical basis for the selection of algorithms for different nonlinear problems.

Supply chain resilience (SCR) has attracted much attention in the context of the high uncertainty caused by the coronavirus disease 2019 (COVID-19), local regional conflicts and natural disasters. Based on information processing theory (IPT), this study investigates the role of supply chain information processing capability in enhancing SCR through supply chain governance (SCG), under different conditions of environmental uncertainty.

The hypothetical model is tested by using hierarchical regression on the primary samples collected from the Chinese manufacturing industry.

The results indicate that supply chain information processing capability has a significant positive effect on SCR. Also, SCG plays a mediating role between supply chain information processing capability and SCR. Furthermore, environmental uncertainty positively moderates the effect of supply chain information acquisition and supply chain information analysis on relational governance. However, environmental uncertainty only positively moderates the effect of supply chain information analysis on contractual governance.

This is the first study to explain the effect of information processing capability on SCR from the supply chain perspective, while also exploring the mediating role of SCG between SCR and supply chain information processing capacity, based on IPT.