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This paper aims to discuss and demonstrate the synergies between the western concept of corporate social responsibility that is emerging from a background of individualism and market competition, and the traditional values of Chinese Confucianism, as applied to managerial practice.

The paper is primarily theoretical in perspective. It also draws upon interview data derived from an in depth study of a large state‐owned corporate group in China in order to demonstrate the model that is known as modern Confucian entrepreneurship.

Adherence to Confucian values was demonstrated by both manager and employee interviewees. However, Chinese managers also need to reform some practices as they move into the international market place. As western managers, at the same time, increasingly seek to increase their social capital it is clear that Chinese and western managers can learn from each other.

The examples drawn upon in this paper come from a state‐owned corporation. Indications are that smaller, privately owned companies in China are more aggressively adopting market models built upon competitive individualism. Further research is needed to develop comparisons.

The paper suggests a hybrid model of business management that combines aspects of both western and Confucian‐based management styles that are proven to be successful in building social capital. It also suggests that fundamental change needs to be effected through business school teaching.

The paper urges a more collective view of management that is built upon trust and focuses on employee and social wellbeing. Indications are that increased wellbeing generates more cohesive, productive and happier societies.

The introduction of interview data provides unique insight to Confucian values in practice in a modern Chinese company.

This paper aims to provide an overview of this special issue.

The guest editorial introduces the papers in this special issue, focusing on practical wisdom for management from the Chinese classical traditions.

Chinese culture increasingly will permeate international culture and move from peripheral to mainstream status. To ignore this in management education would be a grave oversight.

The issue offers insights into the value of practical wisdom from Confucianism, the origins of Chinese classical trditions and Daoism, and the various streams of thought within the classical Chinese traditions and their contemporary relevance.

An investor is expected to analyze the market risk while investing in equity stocks. This is because the investor has to choose a portfolio which maximizes the return with a minimum risk. The mean-variance approach by Markowitz (1952) is a dominant method of portfolio optimization, which uses variance as a risk measure. The purpose of this paper is to replace this risk measure with modified expected shortfall, defined by Jadhav et al. (2013).

Modified expected shortfall introduced by Jadhav et al. (2013) is found to be a coherent risk measure under univariate and multivariate elliptical distributions. This paper presents an approach of portfolio optimization based on mean-modified expected shortfall for the elliptical family of distributions.

It is proved that the modified expected shortfall of a portfolio can be represented in the form of expected return and standard deviation of the portfolio return and modified expected shortfall of standard elliptical distribution. The authors also establish that the optimum portfolio through mean-modified expected shortfall approach exists and is located within the efficient frontier of the mean-variance portfolio. The results have been empirically illustrated using returns from stocks listed in National Stock Exchange of India, Shanghai Stock Exchange of China, London Stock Exchange of the UK and New York Stock Exchange of the USA for the period February 2005-June 2018. The results are found to be consistent across all the four stock markets.

The mean-modified expected shortfall portfolio approach presented in this paper is new and is a natural extension of the Markowitz’s mean-variance and mean-expected shortfall portfolio optimization discussed by Deng et al. (2009).

In order to further understand the research status and prospect, the purpose of this paper is to adopt a novel method in the research field of institutional investor to depict the knowledge structure and the evolution path over the past three decades.

Based on the 4,194 records retrieved from Web of Science, Citespace combined with VOSviewer are employed to perform visualized analysis.

The results reveal that the number of published articles of research on institutional investor has an exponential growth. Although the United States is the most significant contributor with more publications compared with other countries, Malaysia and Nigeria show higher centrality in the research network worldwide. Furthermore, “shareholder activism”, “corporate governance”, “global convergence”, “corporate reporting regulation” and “individual investor” are the largest five knowledge clusters. “Media coverage”, “corporate social responsibility” and “stock price crash risk” are the latest three knowledge clusters. Moreover, “governance worldwide”, “institutional character”, “dynamic information environment”, “investment patterns” and “sustainable development” are the potential extended research fields in the future.

This research helps the scholars and participants to capture the knowledge structure of research on institutional investors and to develop a reference to future opportunities.

This paper assesses how discretionary accruals (DAs) affect corporate cash savings policies and the motivation behind this cash saving behavior and, also whether the linkage between DAs and cash saving affect the market-perceived cash value.

We construct the measure of DAs using the previous five-year average information to investigate the association of DAs with the change in cash. Moreover, the Faulkender and Wang (2006) methodology is utilized to examine the market-perceived cash value in DAs.

The key finding is that firms with high DAs save significantly more cash. A one standard deviation increase in DAs saves cash by 12.59%. Furthermore, the value of cash is low for these firms. The effect is stronger in firms with poor governance but not present in financially constrained firms.

The empirical evidence highlights DAs have negative effect on market-perceived cash value, which underscores the insight that managers manage earnings opportunistically using DAs.

Taken together, we provide more evidence on the literature of accruals in earnings manipulation.

Researchers have not reached an agreement on which biomimetic shape has the best lubrication performance. This paper aims to study the influence of microtexture size, shape and direction on bearing capacity, end leakage, friction coefficient and wear of oil film.

Different oil film thickness equations considering the microtexture of bearing surface are gained. The two-dimensional finite difference equation and the calculation equation of wear are established.

The theoretical research shows that the wear value and the wear ratio when long side is perpendicular to the axial direction of the bearing are generally lower than when the long axis is parallel to the axial direction of bearing. The theoretical and experimental results show that the appropriate microtexture shape, such as circular dimple, crescent-shaped dimple, triangular dimple and fish-shaped dimple can improve effectively the lubrication performance of journal bearing and reduce the friction coefficient.

The research has great significance to reduce friction and improve the wear resistance of equipment.

Drawing on institution embeddedness and the resource-based view, the authors develop a theoretical framework and empirically examine how intra-national innovation ecosystems and environmental institutions impact logistics service providers' (LSPs) technological innovation (TI) and green practices.

The authors test the theoretical framework based on survey data of 328 Chinese LSPs. Archival datasets complement the survey data.

The research reveals that intra-national institutional forces of formal and informal environment-related institutions can mitigate LSPs' reliance on their firm-specific advantages when engaging in TI and green practices. Results from a three-way interaction indicate that intra-national innovation ecosystems positively moderate the effects of environmental institutions.

The research has three critical implications. First, the study reveals the contingency role of intra-national environment-related institutions and innovation ecosystems in shaping green logistics. Second, the study finds new results about the roles of informal environmental institutions. Finally, intra-national innovation ecosystems can override environmental institutions in influencing the green practices of LSPs.

Taking a unique angle of institution embeddedness coupled with the resource-based view, the authors examined how intra-national ecosystems and environmental institutions impact LSPs' TI and green practices.

The purpose of this study is to develop a piezoresistive absolute micro-pressure sensor for altimetry. For this application, both high sensitivity and high overload resistance are required. To develop a piezoresistive absolute micro-pressure sensor for altimetry, both high sensitivity and high-overload resistance are required. The structure design and optimization are critical for achieving the purpose. Besides, the study of dynamic performances is important for providing a solution to improve the accuracy under vibration environments.

An improved structure is studied through incorporating sensitive beams into the twin-island-diaphragm structure. Equations about surface stress and deflection of the sensor are established by multivariate fittings based on the ANSYS simulation results. Structure dimensions are determined by MATLAB optimization. The silicon bulk micromachining technology is utilized to fabricate the sensor prototype. The performances under both static and dynamic conditions are tested.

Compared with flat diaphragm and twin-island-diaphragm structures, the sensor features a relatively high sensitivity with the capacity of suffering atmosphere due to the introduction of sensitive beams and the optimization method used.

An improved sensor prototype is raised and optimized for achieving the high sensitivity and the capacity of suffering atmosphere simultaneously. A general optimization method is proposed based on the multivariate fitting results. To simplify the calculation, a method to linearize the nonlinear fitting and optimization problems is presented. Moreover, a differential readout scheme attempting to decrease the dynamic interference is designed.

This special issue reveals how lesson study in China continues to serve as a powerful platform to support change in teaching. The papers included in this issue explore how university faculty members and researchers support teachers to cross boundaries resulting from the introduction of key competencies-based (hexin suyang 核心素养) curriculum reform (KCR).

The theme of continuity and change is examined against the backdrop of Chinese lesson study's (CLS's) consistent supporting role in enabling curriculum reform. These analyses make use of concepts involved in understanding boundary crossing, such as using boundary objects and their roles, to help make sense of the new theories, tools, and resources as well as relationships engendered in responding to the reform's demand. While recognizing the continuity at play in Chinese LS, the authors use the lens of learning at the boundary of research-practice partnerships (RPPs) (Farrell et al., 2022) to contemplate the future of CLS.

The papers touch on three major themes: (1) the role of university-school partnerships in meeting the new demands of key competencies reform; (2) resourceful tools, strategies and structures to support boundary crossing for teachers; and (3) roles and relationships for mutual learning in university-school partnerships. Together these three themes, considered across the papers in this issue, point to the need to redefine CLS to engender versatility and hybridity and to enlist mutual learning relationships in future university-school partnerships. Such redefinition positions lesson study to both continue and change.

The papers in this issue are expected to promote mutualist learning in future CLS research-practice partnerships. To do so, research needs to move from focusing on change of a single case teacher to clarifying what experts and teachers each learn from the LS and from each other. Attention also needs to focus on the collaborative discourse and ways such discourse is able to promote mutual learning, emotional support in facing change as well as critical and constructive problem solving.

Practically, to better support boundary crossing, this special issue encourages academics and teachers to identify and work around boundary objects and their enabling features to enhance knowledge and identity of both university and teacher participants for more effective research-practice partnerships.

This special issue offers a pioneering set of studies that contributes to an in-depth understanding of how CLS is supporting the current competencies-based reform in China. It also provides concrete future directions for research and practice to enhance university-school partnerships' response to reform.

Allocation of complex crowdsourcing tasks, which typically include heterogeneous attributes such as value, difficulty, skill required, effort required and deadline, is still a challenging open problem. In recent years, agent-based crowdsourcing approaches focusing on recommendations or incentives have emerged to dynamically match workers with diverse characteristics to tasks to achieve high collective productivity. However, existing approaches are mostly designed based on expert knowledge grounded in well-established theoretical frameworks. They often fail to leverage on user-generated data to capture the complex interaction of crowdsourcing participants’ behaviours. This paper aims to address this challenge.

The paper proposes a policy network plus reputation network (PNRN) approach which combines supervised learning and reinforcement learning to imitate human task allocation strategies which beat artificial intelligence strategies in this large-scale empirical study. The proposed approach incorporates a policy network for the selection of task allocation strategies and a reputation network for calculating the trends of worker reputation fluctuations. Then, by iteratively applying the policy network and reputation network, a multi-round allocation strategy is proposed.

PNRN has been trained and evaluated using a large-scale real human task allocation strategy data set derived from the Agile Manager game with close to 500,000 decision records from 1,144 players in over 9,000 game sessions. Extensive experiments demonstrate the validity and efficiency of computational complex crowdsourcing task allocation strategy learned from human participants.

The paper can give a better task allocation strategy in the crowdsourcing systems.