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Article
Publication date: 9 November 2022

Ruihan Zhao, Liang Luo, Pengzhong Li and Jinguang Wang

Quality management systems are commonly applied to meet the increasingly stringent requirements for product quality in discrete manufacturing industries. However, traditional…

Abstract

Purpose

Quality management systems are commonly applied to meet the increasingly stringent requirements for product quality in discrete manufacturing industries. However, traditional experience-driven quality management methods are incapable of handling heterogeneous data from multiple sources, leading to information islands. This study aims to present a quality management key performance indicator visualization (QM-KPIVIS) system to enable integrated quality control and ultimately ensure product quality.

Design/methodology/approach

Based on multiple heterogeneous data, an integrated approach is proposed to quantify explicitly the relationship between Internet of Things data and product quality. Specifically, this study identifies the tracing path of quality problems based on multiple heterogeneous quality information tree. In addition, a hierarchical analysis approach is adopted to calculate the key performance indicators of quality influencing factors in the quality control process.

Findings

Proposed QM-KPIVIS system consists of data visualization, quality problem processing, quality optimization and user rights management modules, which perform in a well-coordinated manner. An empirical study was also conducted to validate the effectiveness of proposed system.

Originality/value

To the best of the authors’ knowledge, this study is the first attempt to use industrial Internet of Things and multisource heterogeneous data for integrated product quality management. Proposed approach is more user-friendly and intuitive compared to traditional empirically driven quality management methods and has been initially applied in the manufacturing industry.

Details

Assembly Automation, vol. 42 no. 6
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 10 June 2020

Ruihan Zhang, Bing Sun, Mingyao Liu and Jian Hou

This paper aims to analyze the spatiotemporal heterogeneity of regional total factor productivity (TFP) growth and explores how haze pollution and different levels of new-type…

Abstract

Purpose

This paper aims to analyze the spatiotemporal heterogeneity of regional total factor productivity (TFP) growth and explores how haze pollution and different levels of new-type urbanization affect China’s economic growth.

Design/methodology/approach

This paper constructs an index for evaluating the TFP growth of China’s 31 provinces by integrating slack-based measures and the Global Malmquist (GM) productivity index. Meanwhile, the panel threshold estimation method is used to examine the complex relationships among haze pollution, new-type urbanization and TFP growth.

Findings

The results reflect conspicuous spatiotemporal heterogeneity in TFP growth in China. Interestingly, the influence of haze pollution on TFP growth is limited by the “critical mass” of new-type urbanization in China. When new-type urbanization does not cross the first threshold, haze pollution has a negative but non-significant effect on TFP growth. When new-type urbanization crosses the first threshold but not the second, haze pollution has a significant positive impact on TFP growth. When new-type urbanization crosses the second threshold, haze pollution significantly and positively affects TFP growth with the strongest positive effect.

Originality/value

This study innovates by combining haze pollution and TFP growth and proposing an integrated framework from the perspective of new-type urbanization, providing insight into how different degrees of new-type urbanization impact the mechanism between haze pollution and TFP growth. Using panel data in China and emphasizing green development, a sustainable economy and new-type urbanization, this study contributes to the current studies on haze pollution and economic development based on developed countries.

Article
Publication date: 17 May 2022

Haiyan Li, Manman Wang and Ruihan Zhang

This study examines the effect of cross-border network ties of returnee entrepreneurs on the foreign market diversity of their ventures. The study further investigates how two…

Abstract

Purpose

This study examines the effect of cross-border network ties of returnee entrepreneurs on the foreign market diversity of their ventures. The study further investigates how two cross-cultural competencies (global mindset and cultural intelligence) moderate this effect.

Design/methodology/approach

A sample of 135 returnee entrepreneurial ventures from China was used to test the hypotheses.

Findings

This study finds that returnee entrepreneurs tend to enter into a wide range of culturally different country groups when returnee entrepreneurs have strong cross-border network ties. Moreover, global mindset and cultural intelligence function as complements in strengthening the effect of the cross-border network ties on foreign market diversity.

Originality/value

The authors contribute to both returnee entrepreneurship and foreign market entry literature in two ways. First, by examining the effect of cross-border network ties on foreign market entry, the authors add new and important insights into the role of social networks in the pre-internationalization phase. This is useful in understanding the internationalization process of new ventures founded by returnees, which have not been fully understood in returnee entrepreneurship literature. Second, by examining the moderating roles of global mindset and cultural intelligence, the authors enhance the understanding of the extent to which cross-border networks can be valuable in foreign market entry.

Details

Cross Cultural & Strategic Management, vol. 29 no. 4
Type: Research Article
ISSN: 2059-5794

Keywords

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