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The purpose of this paper is to examine the effect of employees’ perceptions of high-performance work systems (HPWS) on unethical pro-organizational behavior (UPB), and explores the mediating role of psychological ownership and the moderating role of moral identity.

The hypotheses were tested by using two-wave survey data that were collected from 306 employees in Chinese enterprises.

This study found that HPWS were positively related to UPB, and psychological ownership partially mediated this relationship. Results also revealed that moral identity negatively moderated the relationship between psychological ownership and UPB, and the indirect effect of HPWS on UPB via psychological ownership was weaker for employees high in moral identity.

The generalizability of the findings is limited, and the cross-sectional data cannot draw any clear causal inference among variables.

Managers should pay attention to the “dark side” of HPWS and incorporate ethics in the HPWS. Moreover, organizations should provide correct guidance for their pro-organizational behaviors to avoid employees doing bad things for good reasons.

This study first extends HPWS research to employee’s UPB, uncovers employees’ psychological ownership toward organizations as the pivotal mechanism underlying this relationship, and indicated moral identity can regulate employees unethical behavior.

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 this paper is to show how shape analysis and quantitative characterization of fiber cross sections, with the aid of image analysis techniques, provide a quick, powerful approach to automated profiled fiber identification.

In this paper, an effective method of cross‐sectional shape characterization for profiled fiber identification is reported with extraction of the distance fluctuation curve of fiber cross‐sectional boundary to the centroid. By calculating their cross‐correlations using signal processing techniques, the authors tackle the problem of calibrating the starting points of fiber objects orientated arbitrarily in image successfully, which are difficult to deal with by means of image processing, to finish the normalization of distance fluctuation curves. For two fiber cross‐sections, the similarity degree of their boundary fluctuation curves normalized can effectively reflect the similarity degree of themselves.

Based on this, the method presented extracts the curves of all fiber cross‐sections in one sample, compares the similarity degrees between each other, and creates clusters to identify profiled fiber.

Experimental results validate that this curve can effectively characterize profiled fiber cross‐sectional contour for profiled fiber identification and the normalization method is feasible.

Research on grey systems is becoming more sophisticated, and grey relational and prediction analyses are receiving close review worldwide. Particularly, the application of grey systems in marine economics is gaining importance. The purpose of this paper is to summarize and review literature on grey models, providing new directions in their application in the marine economy.

This paper organized seminal studies on grey systems published by Chinese core journal database – CNKI, Web of Science and Elsevier from 1982 to 2018. After searching the aforementioned database for the said duration, the authors used the CiteSpace visualization tools to analyze them.

The authors sorted the studies according to their countries/regions, institutions, keywords and categories using the CiteSpace tool; analyzed current research characteristics on grey models; and discussed their possible applications in marine businesses, economy, scientific research and education, marine environment and disasters. Finally, the authors pointed out the development trend of grey models.

Although researches are combining grey theory with fractals, neural networks, fuzzy theory and other methods, the applications, in terms of scope, have still not met the demand. With the increasingly in-depth research in marine economics and management, international marine economic research has entered a new period of development. Grey theory will certainly attract scholars’ attention, and its role in marine economy and management will gain considerable significance.

The goal of this chapter is to respond to the theoretical inquiries by scholars who are interested in how the public–private partnership (PPP) models adapt to China’s context where political power dictates economic strategies. We also want to provide suggestions to policy designers who aim to promote a sustainable investment environment for domestic and international investors. We review the literature that explains the upside and downside of PPP projects in contemporary China. (1) We classify the trajectory of PPP evolution into four phases, i.e., emergence, growth, recession and revival. (2) We note that private companies take a disadvantageous position in the partnership compared with governments and state-owned enterprises because of a lack of specialized legislation, unequal competition between private companies and state-owned enterprises and the opposition from the civic society. (3) We identify political risks as the most influential risks. Political risks also lead to the misallocation of other risks between public and private parties that contributes to the high failure rate of China’s PPP projects. Based on these findings, we recommend governments to draft specialized legislation, stabilize the political environment and provide favourable subsidies to local governments to limit the risks involved in PPP projects. We also advise private enterprises and state-owned enterprises to focus on negotiating over task and risk division with governments when they make decisions to participate in PPP projects. This full review of studies on PPP development in China provides reliable recommendations to scholars, governments and enterprises.

The paper aims to analyse the Shenzhen housing market.

The paper uses an empirical case study using hedonic modelling that includes not only the property specifics, but also the spatial (via {X, Y} coordinates) and household (buyer's) characteristics. Two expansion models are employed to examine the spatial and socio‐economic heterogeneities in housing attribute prices.

The results provide strong evidence that the marginal prices of key housing attributes are not constant but vary with household profile and absolute‐location context within Shenzhen's housing market.

Examining housing market behaviour in major Chinese cities should eventually be approached more explicitly with the development of China's official statistical system.

Largely supported by the valuable transaction data, this paper makes initial and valuable attempts to examine the interaction behaviour between property specifics, location coordinates and buyers’ characteristics within one of the very complex and immature housing markets, namely Shenzhen, China.

China's accession to World Trade Organization (WTO) opened its financial markets to foreign banks in December 2006. In addition to foreign banks’ expertise and experience in modern banking activities, they also appear to have the interest, competitiveness, and regulatory advantages of competing with Chinese banks in the traditional Renminbi (RMB) business. Such competition will lead to a loss of RMB deposits and loans from local banks. Given that Chinese banks are currently ridden with large non-performing loans and low capital adequacy, the foreign bank entry will exert further pressure on the banks’ profitability and solvency. Without larger regular bailouts from the central government and fundamental changes on the roles of Chinese banks, China may experience a banking crisis in the post-WTO era. We propose two types of policy changes that may improve banks’ competitiveness and reduce the likelihood of a banking crisis.