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The purpose of this paper is building the regression model related to tool wear, and the regression model is used to identify the state of tool wear.

In this paper, genetic programming (GP), which is originally used to solve the symbolic regression problem, is used to build the regression model related to tool wear with the strong regression ability. GP is improved in genetic operation and weighted matrix. The performance of GP is verified in the tool vibration, force and acoustic emission data provided by 2010 prognostics health management.

In result, the regression model discovered by GP can identify the state of tool wear. Compared to other regression algorithms, e.g. support vector regression and polynomial regression, the identification of GP is more precise.

The regression models built in this paper can only make an assessment of the current wear state with current signals of tool. It cannot predict or estimate the tool wear after the current state. In addition, the generalization of model has some limitations. The performance of models is just proved in the signals from the same type of tools and under the same work condition, and different tools and different work conditions may have influences on the performance of models.

In this study, the discovered regression model can identify the state of tool wear precisely, and the identification performances of model applied in other tools are also excellent. It can provide a significant information about the health of tool, so the tools can be replaced or repaired in time, and the loss caused by tool damage can be avoided.

Collaboration with universities is an important innovation strategy for enterprises. However, currently very little research has focused on how such university-industry collaborative innovation activities should be managed. The paper aims to discuss this issue.

This paper introduces the university-industry collaborative innovation practices of Zhejiang NHU Company in China. By using a case study as the method, this paper aims to illustrate the mechanism of university-industry collaborative innovation and how to manage the collaborative innovation activities efficiently.

Zhejiang NHU Company established a university-industry collaborative innovation link through three innovation platforms: the technology R&D center, the ZJU-NHU joint-research center, and the national engineer center. Zhejiang NHU Company manages its collaborative relationships with universities through this innovation network.

NHU Company managed the collaborative relationship efficiently with the institutions, representing an effective degree of university-industry collaborative innovation management.

Innovation ecosystem is an emerging and popular concept in both academic and industrial circles. It offers a new perspective for enterprise strategy positioning. A business can create more value through a healthy innovation ecosystem. The paper aims to discuss these issues.

In this paper, the authors utilize a new triple-layer core-periphery framework to analyze Insigma Group’s multi-platform collaboration innovation ecosystem, in order to explore the architecture and heterogeneous functions inside an innovation ecosystem.

The authors illustrate the components and working mechanisms of the four platforms, which function as ideation, entrepreneurship, financing and investment, and innovation, inside Insigma’s innovation ecosystem in detail, and explain how they interact and collaborate toward a shared aim of the whole innovation ecosystem.

The innovation ecosystem is an emerging concept. In this study, the authors combined two existing analytical frameworks of innovation ecosystem, and proposed a triple-layer core-periphery framework, which enable us to analyze the heterogeneity inside an innovation ecosystem.

The authors discussed the role of government and its policies in shaping the innovation ecosystem at the enterprise level.

The authors believe that this paper provides a holistic study of Insigma’s innovation ecosystem. The triple-layer core-periphery framework can be used to study other enterprise innovation ecosystem in the future.

Drawing upon the Elaboration Likelihood Model, the purpose of this paper is to examine how the characteristics of social media moderate the effect of a firm’s apology on the attitude of its customers.

An online experiment including 360 active users of internet was employed to test the research model.

Results revealed that an after-crisis apology and firm reputation both have a positive effect on after-crisis user attitude toward the firm. Furthermore, the positive effect of apology becomes stronger as online media interactivity increases, whereas the positive effect of reputation becomes weaker.

This study included only one important characteristic of social media, and experimental scenarios were limited to car recall crisis. Considering that social media has so many platforms that may have different kinds of interactivity, further studies can be conducted to figure out the most suitable social media for firms to deal with an online crisis.

The results inform managers of the importance of after-crisis apology and firm reputation. It is worthwhile for managers to find out the levels of online media interactivity at which users focus on apology and reputation and accordingly conduct an effective online crisis management response strategy.

This study extends the literature on online crisis management and the literature on ELM by highlighting the role of online media interactivity in influencing the persuasive effectiveness of firm’s crisis response in the context of social media.

The purpose of this paper is to present a simple and effective method to search the optimal turn-on and turn-off angles on-line for the control of the switched reluctance motor (SRM). The optimal turn-on and turn-off angles are defined as the ones that can meet torque production requirements with minimum copper loss.

The optimal turn-on and turn-off angles are first defined based on the analysis of the SRM losses and torque production principles. Then the algorithm for optimal angles searching is developed, and the searching parameters are determined through analytical computation. The optimal angles are approached on-line with iterative process. Simulation and experiments are finally performed to verify the proposed method.

The presented method can meet torque production requirements while copper loss is minimized. The optimal turn-on and turn-off angles are generally approached within five phase cycles for most of the SRM operation modes. Furthermore, the SRM drive system using the presented method exhibits good dynamics during starting and sudden load operations.

The presented method is simple, and implementation of it is easy. It is an eligible candidate for industrial applications where energy conversion efficiency is crucial.

The optimal turn-off angle definition that considers both torque production and copper loss minimization is proposed. The turn-on and turn-off angles are searched independently on-line with little SRM geometrical information. The searching steps are derived through analytical computation and qualitative analysis so that both the searching speed and algorithm convergence are balanced.

Focusing on micro-level indicators, we investigate financial inclusion levels in rural China, examining its determinants and impact on household welfare. We construct a financial inclusion index of four essential financial services: savings, digital payments, credit and insurance. We identify factors influencing financial inclusion among Chinese rural households and assess the effects of financial inclusion on household welfare.

With the entropy method, we use data from the 2019 China Household Finance Survey to assess financial inclusion levels in rural China. Determinants and their impact on welfare are analyzed through probit and ordinary least squares models, respectively. Propensity scoring matching is applied to address potential endogeneity.

We reveal that rural households exhibit limited usage of formal financial services, with notable regional disparities. The eastern region enjoys the highest financial inclusion and the central region lags behind. Household characteristics such as family size, education level of the household head, income, employment status and financial literacy significantly influence financial inclusion. Financial inclusion positively impacts household welfare as indicated by household consumption expenditure. The use of different types of financial services is crucial with varying but significant effects on household welfare.

This study offers valuable insights into China’s rural financial inclusion progress, highlighting potential barriers and guiding government actions.

Urbanisation, environmental sustainability and property markets are intertwined. Consequently, studies on any of these three topics need to take the other two topics into consideration. By critically reviewing 33 hedonic pricing studies in 16 key journals in the urban studies and environmental policies areas, we summarise quantitative evidence on the price of environmental externalities resulting from China's urbanisation process. We find that Chinese residents are willing to pay more for the access to green space and waterbody as well as the treatment of urban pollution. The cost and benefit of these amenities and disamenities have already been capitalised in house prices. The central and local government in China can leverage market force to encourage, support and facilitate sustainable urban development and environmental protection, instead of directly intervening in the property market by using public resources. Meanwhile, the estimated hedonic price of Urban Green, Urban Blue and Urban Grey helps policymakers to understand the cost and benefit of their urban development decisions. Our review of the papers on Urban Green, Urban Blue and Urban Grey suggests that there have been promising and encouraging development in studies on all three topics in the last decade. The quality and quantity of hedonic price research has been improving notably. However, it is also clear that there is virtually no empirical evidence from the second- or third-tier cities, particularly, regarding Urban Green and Urban Blue investigations. The small number of existing hedonic studies is far from sufficient to draw reliable conclusions about the costs of environmental externality for cities that have not been studied. What works in first-tier cities may not hold elsewhere in China due to the large geographical variation in natural endowment, economic development status and local customs. There are many pieces that are missing from this big picture. More hedonic price studies are needed.

China has climbed from 22nd in the Global Innovation Index Rankings in 2017 to 11th in the 2022 due to the transition of its manufacturing firms from assemblers to system integrators. This paper examines how firms can enhance their innovation capability through inbound and outbound open innovation.

This paper applies both open innovation and a knowledge-based view and proposes a conceptual framework that encompasses innovation capability and the significance of tacit knowledge acquisition. A questionnaire was designed to collect relevant data from 139 Chinese manufacturing firms in six regions to test this framework.

The authors found that inbound open innovation has a stronger impact than outbound open innovation on synergistic innovation capability. The acquisition of skill-based tacit knowledge has a slightly stronger intermediary role between open innovation (no matter inbound or outbound) and synergistic innovation capability than cognitive tacit knowledge does.

Firms should improve external tacit knowledge acquisition efforts to generate new knowledge, inspire the innovation passion of employees and implement ambidextrous open innovation.

This paper makes a good first step to analyze the effect of ambidextrous open innovation on the synergistic innovation capability of Chinese manufacturing firms. It verifies the role of skill-based and cognitive tacit knowledge acquisition and provides new reflections on open innovation strategy in emerging economies, thus enriching open innovation and knowledge-based theories.

The link between openness and innovative performance has been established as an inverted U-shape relationship, namely, the openness-performance connection is not always positive. The purpose of this paper is to introduce the concept of partner heterogeneity to characterize the influence of “quality” changes in partners on innovative performance, that is, the focus of this paper. Given that partner heterogeneity is crucial in explaining open innovative performance, it is also worth placing the examination of this key construct in emerging regions such as China.

The sample selection of this study covers a wide range of industries, but requires that the sample firms be manufacturing enterprises with an open innovation strategy. With opportunities and challenges associated with partner collaboration toward open innovation, the Chinese province of Zhejiang has established its reputation. Thus, empirical data were collected randomly from data pool of Zhejiang Province Economic and Information Commission, as well as a survey questionnaire. Data were using a cross-sectional survey methodology encompassing diverse organizations, industries, and nations.

Empirical testing of this assumption in a sample of 217 manufacturing firms indicates that partner heterogeneities, which are classified as organizational heterogeneity, industry heterogeneity, and national heterogeneity are all positively associated with innovative performance, but the strength of this association is influenced by environmental turbulence. Technological turbulence significantly and positively modulates the relationships of organizational and national heterogeneities with innovative performance. Market turbulence also plays a significant positive role on the relationship between national heterogeneity and innovative performance, while technological and market turbulence roles on the relationship between industry heterogeneity and innovative performance are not confirmed.

This paper refines the connotative dimensions of partner heterogeneity around the core concept of partner heterogeneity in open innovation in the context of emerging region, China. The study presents a systematic, in-depth analysis, and verifies the impact mechanisms of partner heterogeneity in open innovation on innovative performance by integrating the resource-based view, organizational learning theory, and transaction cost theory.

Textile and contemporary apparel manufacturers are adopting and integrating cutting-edge technologies to reduce their impact on the environment and gain an advantage in the marketplace. Most previous studies have ignored business intelligence systems (BIS), notably in the textile and apparel industry (T&A), in favor of looking at the larger picture of how big data would affect retail and distribution in a company. This is especially true for the T&As.

The authors report that they conducted 14 semi-structured interviews with 12 international luxury tourism service providers. In this case, researchers use snowball features and systematic techniques to select participants. A qualitative content analysis strategy is used to capture the focus of the interviews.

Problems with T&A company sustainability, opportunities to increase value creation via use of industry-leading business intelligence (BI) solutions and perceived roadblocks to BIS adoption were all found by the poll. Garment retail and distribution sector has benefited greatly from the increased use of Industry 4.0 technologies, especially those that provide better BI solutions. Determine the extent to which industry participation slows down or speeds up the process. The Company Information System (BIS) will help convince non-tech-savvy business owners of the financial, economic and environmental benefits of adopting certain technologies developed as part of the industry 4.0 movement.

The authors of this research claim theirs is one of the first to investigate what variables affect the uptake of BIS, ultimately hoping to find out how BIS may be used by T&A businesses to tackle environmental issues through the use of Industry 4.0 technologies. The purpose of this study was to see whether BIS might aid T&A firms with their sustainability issues.

In the last several years, there has been a meteoric rise in interest in big data and business analytics among firms and educational institutions alike. This paper tries to introduce readers to the concept of business analytics in a way that is both academic and accessible, considering both the present and future of the field. This paper begins with a quick introduction, followed by a summary of the three distinct forms of predictive modeling discussed.

In an effort to help aspiring analytics professionals, they have identified, categorized and evaluated the nine distinct players that are now active in the analytics market. Following this, they will provide a high-level summary of the many different research projects currently being worked on by their group.