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Existing research has examined the results of women’s political leadership participation (WPLP) and the reasons for the lack of advancement of women to management positions. However, little research has been adopting a more comprehensive framework and configuration perspective to investigate the determinants of WPLP. By integrating institutional theory and institutional complementarities theory, this study aims to construct an institution–culture–structure framework to investigate the multiple driving mechanisms of WPLP.

Drawing on the fuzzy set qualitative comparative analysis method and a sample of 66 countries, the authors identify multiple equifinal combinations of conditions related to high and not-high levels of WPLP.

According to the results, the authors summarize five pathways influencing WPLP. These pathways include education and culture-driven pattern, political institutions-driven pattern, political institutions and structure-driven pattern, integrated-driven pattern and political institutions and culture restrictive pattern.

The authors shed new light on the driving mechanism of WPLP and contribute to research on making full out of women’s leadership.

The COVID-19 pandemic has caused havoc on a global scale for supply chains, which put forward higher demand for organizations to reassess their global supply chain strategy and improve supply chain sustainability. The purpose of this paper is to understand how leader's paradoxical cognition affect supply chain sustainability.

This study conceptualizes a research model grounded in upper echelons theory and propose a chain-mediating model under the moderating effect of big data analytics. Using PLS-SEM method, we test the hypotheses using survey data collected from supply chain managers or leaders of the supply chain team from 193 firms.

The results indicate that supply chain ambidexterity and organizational learning play a mediating role in the relationship between leaders' paradoxical cognition on supply chain sustainability, respectively, and these two variables have a chain-mediating role in the relationship above. In addition, the big data analytics negatively moderates the relationship between leader's paradoxical cognition and organizational learning, and further moderates our chain mediating model.

This research initiatively focuses on the micro-foundations of supply chain sustainability from managerial cognition and firstly provides empirical evidence about the impact of leader's paradoxical cognition on supply chain sustainability.

Despite the escalating significance and intricate nature of supply chains, there has been limited scholarly attention devoted to exploring the cognitive processes that underlie supply chain management. Drawing on cognitive-behavioral theory, the authors propose a moderated-mediation model to investigate how paradoxical leadership impacts manufacturing supply chain resilience.

By conducting a two-wave study encompassing 164 supply chain managers from Chinese manufacturing firms, the authors employ partial least squares structural equation modeling (PLS-SEM) to empirically examine and validate the proposed hypotheses.

The findings indicate that managers' paradoxical cognition significantly affects supply chain resilience, with supply chain ambidexterity acting as a mediating mechanism. Surprisingly, the study findings suggest that big data analytics negatively moderate the effect of paradoxical cognition on supply chain ambidexterity and supply chain resilience, while positively moderating the effect of supply chain ambidexterity on supply chain resilience.

These findings shed light on the importance of considering cognitive factors and the potential role of big data analytics in enhancing manufacturing supply chain resilience, which enriches the study of behavioral operations.

The results offer managerial guidance for leaders to use paradoxical cognition frames and big data analytics properly, offering theoretical insight for future research in manufacturing supply chain resilience.

This is the first empirical research examining the impact of paradoxical leadership on supply chain resilience by considering the role of big data analytics and supply chain ambidexterity.

The alienation of megaproject environmental responsibility (MER) behavior is destructive, but its mechanism has not been clearly depicted. Based on fraud triangle theory and the fuzzy set qualitative comparative analysis (fsQCA) method, this study explored the combined effect of antecedent factors on alienation of MER behavior.

Based on the fraud triangle theory and literature review, eight influencing factors associated with the alienation of MER behavior were first identified. Subsequently, the fuzzy-set qualitative comparative analysis was used in this study to reveal configurations influencing alienation of MER behavior.

The study found nine configurations of MER behavioral alienation antecedent factors, integrated into three types of driving modes, i.e. “economic pressure + learning effect,” “institutional defect + moral rejection,” and “information asymmetry + economic pressure + expectation pressure.”

By analyzing the configuration effects of various induced conditions, this study puts forward a comprehensive analysis framework to solve the alienation of MER behavior in the megaprojects and a practical strategy to control alienation of MER behavior.

The purpose of the study is to investigate the financing channels and carbon emission abatement preferences of supply chain members, and further examine the optimal contract design of the retailer.

This paper develops a low-carbon supply chain composed of one retailer and one manufacturer, in which the retailer provides trade credit to the manufacturer. Considering the cap-and-trade regulation, the manufacturer with uncertain yield makes decision on whether to invest in emission abatement. There are bank loan and trade credit to finance production for the manufacturer and green credit to finance emission abatement investment. Meanwhile, the retailer may provide the manufacturer with three kinds of contracts to improve emission abatement efficiency, namely, revenue sharing, cost sharing or both sharing.

The results show that the retailer prefers to offer financing service at lower interest rate, but trade (and green) credit financing is always optimal for manufacturer and supply chain. The investment in emission abatement is value-added to all players. The sharing contracts offered by the retailer at lower sharing ratios can realize Pareto improvement of the system regardless of the financing scheme. However, comparing with the revenue or cost sharing contract, the existence of optimal sharing ratios makes the both sharing contract more favorable to the retailer.

The findings provide guidance for the emission-dependent manufacturer in financing and emission abatement decisions, as well as recommendations for the retailer to offer loan service and sharing contract.

This paper integrates green credit into bank loan or trade credit to analyze the financing decision of the manufacturer with uncertain yield and further considers the influence of three kinds of sharing contracts introduced by the retailer on improving operational performance.

This study intends to review studies on the success criteria and critical success factors (CSFs) for mega infrastructure construction projects (MICPs) from journal articles between 2000 and 2018 to (1) identify the publication trend of success criteria and CSFs for MICPs; (2) explore distributions of selected papers, including the distribution of journals, authors’ origin/country and publications by country or region focus; and (3) summarize the findings of success criteria and CSFs studies of MICPs.

A methodical and systematic analysis of 38 selected journal articles was conducted using descriptive analysis to obtain the annual trend of publications, distributions of publication sources, contributors’ origin/country, regions/countries of research focus, methods involved in publications and thematic analysis to identify and categorize success criteria and CSFs for MICPs.

Australia, the USA, UK, China and Hong Kong had been the leading contributors for publications on success criteria and CSFs for MICPs; meanwhile, China, Australia and the UK have been the countries of focus for most studies on this specific topic. This review identified 20 success criteria grouped into 5 constructs and 36 CSFs grouped into 5 categories and, respectively, integrated them into two conceptual frameworks. The top five CSFs were adequate resource availability, partnering/relationships with key stakeholders, adequate communication and coordination among related parties, public support or acceptance and clear strategic vision. Three implications, namely, evaluation indicators, relationships between CSFs and the success of MICPs and human-related factors, are highlighted in future research.

The identified success criteria and CSFs provide a basis for evaluating the success possibility of MICPs and serve to identify areas for further improvement. Additionally, the CSFs checklist and framework have been established, which could help to conduct further empirical studies. Finally, the holistic analysis identifies gaps in the body of knowledge, revealing avenues for future research.

Sustainable development calls for a larger share of intermittent renewable energy. To mitigate this intermittency, Compressed Air Energy Storage (CAES) technology was introduced. This technology can be made more sustainable by recovering the heat of the compression phase and reusing it during the discharge phase, resulting in an adiabatic CAES without the need for burning of fossil fuels. The key process parameters of CAES are temperature, pressure ratios, and the mass flow rates of air and thermal fluids. The variation in these parameters during the charge and discharge phases significantly influences the performance of CAES plants. In this chapter, the transient thermodynamic behavior of the system under various operating conditions is analyzed and the impact of heat recovery on the discharge phase energy efficiency, power generation, and CO₂ emissions is studied. Simulations are carried out over the air pressure range from 2,500 to 7,000 kPa for a 65 MW system over a five-hour discharge duration. It is also assumed that the heat loss in the air storage and the hot thermal fluid tank is insignificant and standby duration does not impact the status of the system. This result shows that the system exergy and the generated power are more sensitive to pressure change at higher pressures. This work also reveals that every 10°C increase on the temperature of the stored air can lead to a 0.83% improvement in the energy efficiency. The result of the transient thermodynamic model is used to estimate the reduction in CO₂ emissions in CAES systems. According to the obtained result, a 65 MW ACAES plant can reduce about 17,794 tons of CO₂ emission per year compared to a traditional CAES system with the same capacity.

The purpose of this paper is to investigate the impact of intellectual capital (IC) and its components (human, structural, relational and innovation capitals) on financial performance (FP) at different life cycle stages.

The study uses the data from Chinese manufacturing listed companies during 2014–2018. The modified value added intellectual coefficient (MVAIC) model is employed as the measurement of IC efficiency. Finally, multiple regression analysis is used to test the research hypotheses.

This study shows that the impact of IC on FP is different across life cycle stages. Specifically, at the birth stage, human capital (HC), structural capital (SC) and innovation capital (INC) have a positive impact on FP. At the growth and mature stages, all IC components contribute to FP improvement. HC and SC play an important role at the revival stage, while only HC positively affects FP at the decline stage.

The findings may help corporate managers to make optimal strategies to improve FP by effective utilization of IC resources in the complex and competitive business environment. Meanwhile, companies can invest in the core elements of IC at different stages of development, so as to maximize the contribution of IC to company value.

This is among the few studies to explore the impact of IC on FP of manufacturing listed companies in the Chinese context from the perspective of life cycle. It also makes novel contributions in measuring IC by the MVAIC model with the inclusion of relational capital and INC that are largely neglected in previous research.

This study aims to prepare an imprinted composite membrane with grafted temperature-sensitive blocks for the efficient adsorption and separation of rhenium(Re) from aqueous solutions.

PVDF resin membrane was used as the substrate, dopamine and chitosan (CS) were used to modify the membrane surface and temperature-sensitive block PDEA was grafted on the membrane surface. Then acrylic acid (AA) and N-methylol acrylamide (N-MAM) were used as the functional monomers, ethyleneglycol dimethacrylate (EGDMA) as the cross-linker and ascorbic acid-hydrogen peroxide (Vc-H₂O₂) as the initiator to obtain the temperature-sensitive ReO4⁻ imprinted composite membranes.

The effect of the preparation process on the performance of CS–Re–TIICM was investigated in detail, and the optimal preparation conditions were as follows: the molar ratios of AA–NH₄ReO₄, N-MAM and EGDMA were 0.13, 0.60 and 1.00, respectively. The optimal temperature and time of the reaction were 40 °C and 24 h. The maximum adsorption capacity of CS–Re–TIICM prepared under optimal conditions was 0.1071 mmol/g, and the separation was 3.90 when MnO4⁻ was used as the interfering ion. The quasi first-order kinetics model and Langmuir model were more suitable to describe the adsorption process.

With the increasing demand for Re, the recovery of Re from Re-containing secondary resources becomes important. This study demonstrated a new material that could be separated and recovered Re in a complex environment, which could effectively alleviate the conflict between the supply and demand of Re.

This contribution provided a new material for the selective separation and purification of ReO4⁻, and the adsorption capacity and separation of CS–Re–TIICM were increased with 1.673 times and 1.219 time compared with other Re adsorbents, respectively. In addition, when it was used for the purification of NH₄ReO₄ crude, the purity was increased from 91.950% to 99.999%.

The purpose of this study is to examine tacit knowledge sharing within information systems development (ISD) projects by exploring the combination of social interdependence theory and regulatory focus theory (RFT).

A survey was conducted on 198 ISD professionals to investigate the effect of social interdependence on tacit knowledge sharing. The survey data were analyzed using partial least squares structural equation modeling (PLS-SEM), and the results were discussed.

This study reveals that team members tend to share tacit knowledge in a way characterized by cooperative interdependence, and different patterns of social interdependence have an impact on tacit knowledge sharing. The RFT explains the disparities in attitude toward tacit knowledge sharing. Specifically, individuals with a prevention-focused orientation positively moderate the impact of competitive interdependence on tacit knowledge sharing, while those with a promotion-focused orientation have a negative moderating effect on the effect of competitive interdependence on tacit knowledge sharing. Moreover, promotion-focused individuals negatively moderate the effect of cooperative interdependence on tacit knowledge sharing.

The study identifies important aspects of social interdependence in ISD projects that affect the management of tacit knowledge. Furthermore, the study shows that the influence of cooperative and competitive interdependence on tacit knowledge sharing is moderated by the regulatory focus of an individual, providing new insights into ISD knowledge management.