Yu Lin, Shuaishuai Zhang and Yingjie Shi
The purpose of this paper is to examine the impact of operational stickiness on product quality. Particularly, it analyzes the moderating effect of product diversification on the…
Abstract
Purpose
The purpose of this paper is to examine the impact of operational stickiness on product quality. Particularly, it analyzes the moderating effect of product diversification on the relationship between operational stickiness and product quality of exporting firms from China.
Design/methodology/approach
Using a sample of 3,567 exporting firms between 2002 and 2012 in China, this paper develops a fixed effect model to demonstrate the nonlinear relationship between operational stickiness and product quality.
Findings
Results show that operational stickiness has an inverted U-shaped impact on product quality, while inventory stickiness, property, plant and equipment (PPE) stickiness and labor stickiness are used to measure operational stickiness. Furthermore, the impact of operational stickiness on product quality is found to be moderated by product diversification.
Practical implications
Managers can achieve an optimal level of product quality by adjusting the level of operational stickiness. Firms with excessive operational stickiness should appropriately reduce the degree of stickiness to improve product quality. Besides, managers who focus on product quality should be cautious in adopting the product diversification strategy and be wary of the loss of product quality this strategy may cause.
Originality/value
This paper is the first study that has empirically validated the inverted U-shaped relationship between operational stickiness and product quality, and confirmed the moderating effect of product diversification on the relationship between operational stickiness and product quality. It provides a new idea to improve product quality by operational management.
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Xinyu Wang, Yu Lin and Yingjie Shi
From the intra- and inter-regional dimensions, this paper investigates the linkage between industrial agglomeration and inventory performance, and further demonstrates the…
Abstract
Purpose
From the intra- and inter-regional dimensions, this paper investigates the linkage between industrial agglomeration and inventory performance, and further demonstrates the moderating role of firm size and enterprise status in the supply chain on this linkage.
Design/methodology/approach
Using a large panel dataset of Chinese manufacturers in the Yangtze River Delta for the period from 2008 to 2013, this study employs the method of spatial econometric analysis via a spatial Durbin model (SDM) to examine the effects of industrial agglomeration on inventory performance. Meanwhile, the moderation model is applied to examine the moderating role of two firm-level heterogeneity factors.
Findings
At its core, this research demonstrates that industrial agglomeration is associated with the positive change of inventory performance in the adjacent regions, whereas that in the host region as well as in general does not significantly increase. Additionally, both firm size and enterprise status in the supply chain can positively moderate these effects, except for the moderating role of firm size on the positive spillovers.
Practical implications
In view of firm heterogeneity, managers should take special care when matching their abilities of inventory management with the agglomeration effects. Firms with a high level of inventory management are suited to stay in an industrial cluster, while others would be better in the adjacent regions to enhance inventory performance.
Originality/value
This paper is the first to systematically analyze the effects of industrial agglomeration on inventory performance within and across clusters, and confirm that these effects are contingent upon firm size and enterprise status in the supply chain. It adds to the existing literature by highlighting the spatial spillovers from industrial clusters and enriching the antecedents of inventory leanness.
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Yingjie Shi, Xinyu Wang and Xuechang Zhu
The purpose of this paper is to empirically investigate the effect of lean manufacturing on productivity changes and to identify the root sources of productivity changes…
Abstract
Purpose
The purpose of this paper is to empirically investigate the effect of lean manufacturing on productivity changes and to identify the root sources of productivity changes. Furthermore, the authors explore the moderating effects of research and development (R&D) to examine the relationship between lean manufacturing and productivity changes.
Design/methodology/approach
This paper employs the propensity score matching (PSM) model combined with the difference-in-difference (DID) estimation to overcome the selectivity bias. The Malmquist productivity index is used to capture productivity changes. By analyzing 671 Chinese manufacturing listed firms from 2009 to 2014, the moderating effects of R&D on the relationship between lean manufacturing and productivity changes are measured.
Findings
The results reveal that lean manufacturing implementation has non-significant effects on productivity changes in principle, while a detailed analysis indicates that lean manufacturing could improve scale efficiency significantly. While engaged in R&D could significantly improve the efficiency of technological changes for lean manufacturing implementation firms, there exist negative effects on pure technical efficiency.
Research limitations/implications
This research only covers manufacturing listed firms in China. Further studies should extend the generalizability of the findings.
Practical implications
This study helps managers to identify the important role of R&D on the relationship between lean manufacturing and productivity changes and provides insights into how to improve the lean manufacturing performance.
Originality/value
This paper appears to be one of the earliest studies on the relationship between lean manufacturing and productivity changes by applying the PSM combined with DID estimation in Chinese manufacturing environment.
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Yu Lin, Jiannan Wang and Yingjie Shi
This paper explores the relationship between inventory productivity and the likelihood of venture survival and then examines how financial constraints moderate the inventory…
Abstract
Purpose
This paper explores the relationship between inventory productivity and the likelihood of venture survival and then examines how financial constraints moderate the inventory productivity–survival linkage.
Design/methodology/approach
Accelerated failure time (AFT) model is employed to study the link between inventory productivity and venture survival by using small- and medium-sized enterprise (SME) data from Chinese Annual Survey of Industrial Firms (CASIF) database over the period 1999–2007.
Findings
The paper demonstrates a converse U-curve relation between inventory productivity and venture survival. Additionally, financial constraints as the moderator weaken the marginal effect of inventory productivity on venture survival.
Practical implications
Managers should pay more attention to the important inventory performance indicator: inventory productivity. In the context of prominent financing difficulties, managers should be rapid to adjust the competitive strategy and optimize the internal production process according to the inherent nature of risks in a friction environment, and thus generate resources that enterprises cannot raise in the financial market.
Originality/value
This study may be the first to practically investigate the role of inventory productivity on venture survival and the moderating effect of financing constraints on this relationship. It adds to abundant articles as regards the interface between operation management and venture survival by exploring how financial constraints moderate the inventory productivity–survival linkage.
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Xinyu Wang, Yu Lin and Yingjie Shi
The purpose of this paper is to investigate the relationship between inventory leanness and venture survival, and demonstrate the role of organizational environments in moderating…
Abstract
Purpose
The purpose of this paper is to investigate the relationship between inventory leanness and venture survival, and demonstrate the role of organizational environments in moderating this relationship from three dimensions: environmental complexity, dynamism and munificence.
Design/methodology/approach
Using a large panel data of more than 150,000 new Chinese small- and medium-sized enterprises between 2000 and 2007 in the manufacturing sector, the authors employ the method of survival analysis via an accelerated failure time model to explore the non-linear relationship between inventory leanness and the likelihood of survival. Moreover, the moderation model is applied to examine the moderating role of organizational environments.
Findings
At its core, this paper demonstrates the inverted U-shaped relationship between inventory leanness and the likelihood of survival. Furthermore, the authors find that environmental complexity and dynamism can negatively moderate this relationship, whereas environmental munificence acts the exact opposite.
Practical implications
Managers need to realize the trade-off between inventory leanness and venture survival. Collectively, more than 90 percent of new Chinese ventures have great potential to improve the likelihood of survival by implementing inventory leanness management. In addition, firms ought to be fully aware of the internal management and the external environments.
Originality/value
This is the first study to confirm the inverted U-shaped relationship between inventory leanness and the likelihood of survival, and empirically verify the moderating role of environmental complexity, dynamism and munificence on this relationship.
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Yingjie Shi, Xuechang Zhu, Shuaishuai Zhang and Yu Lin
The purpose of this paper is to examine the existence of operational stickiness, and explores the relationship between operational stickiness and the likelihood of survival…
Abstract
Purpose
The purpose of this paper is to examine the existence of operational stickiness, and explores the relationship between operational stickiness and the likelihood of survival. Furthermore, the authors investigate this relationship in different manufacturing industries.
Design/methodology/approach
Using a large sample of more than 200,000 new manufacturing small and medium enterprises between 2000 and 2013 in China, the authors use the survival analysis method to investigate the non-linear relationship between operational stickiness and the likelihood of survival.
Findings
The authors demonstrate the existence of operational stickiness, such as inventory stickiness, property, plant, and equipment (PPE) stickiness, and labor stickiness. Next, the authors find the inverted U-shaped relationship between operational stickiness and the likelihood of survival. Furthermore, the authors document the differential effect of operational stickiness on the likelihood of survival in different industries.
Practical implications
Managers can improve the firm’s likelihood of survival by maintaining a moderate inventory stickiness and PPE stickiness. However, managers should not adopt sticky labor management in manufacturing industries.
Originality/value
This paper may be the first study to demonstrate the existence of operational stickiness, and confirm the inverted U-shaped relationship between operational stickiness and the likelihood of survival.
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Chaohui Xu and Yingjie Xu
This paper aims to explore the effects of director network on open innovation. As an informal institutional arrangement, the director network is an important source for the…
Abstract
Purpose
This paper aims to explore the effects of director network on open innovation. As an informal institutional arrangement, the director network is an important source for the enterprise to obtain external information, which provide resource basis for open innovation. Chief Executive Officer (CEO) as the top of management team could make short-sighted decisions for personal interests; this paper also investigates the moderating role of CEO short-sightedness between director network and open innovation.
Design/methodology/approach
This paper takes 4,102 Chinese listed companies from 2007 to 2020 as the research sample. By introducing network centrality and structural hole to measure director network and using data mining to extract key words related to CEO short-sightedness from annual reports, this paper constructs several multiple linear regression models to analyze the impact of director network on open innovation and the moderating role of CEO short-sightedness.
Findings
The analysis finds that director network can facilitate corporate open innovation. Enterprises can acquire more external resources in high centrality and structural hole of director network and promote ability for corporate open innovation. The relationship between director network and open innovation is negatively moderated by CEO short-sightedness. When the level of corporate governance and analyst attention is high, the negative effect of CEO short-sightedness on the innovation effect of directors’ networks is suppressed.
Originality/value
This is the first empirical paper to investigate the promotion effect of director network on open innovation as well as the negative moderating role of CEO short-sightedness. The findings bring new perspectives to the open innovation and enlightenments for practical activities from social relationship aspect.
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Guoyuan Shi, Yingjie Zhang and Manni Zeng
Workpiece sorting is a key link in industrial production lines. The vision-based workpiece sorting system is non-contact and widely applicable. The detection and recognition of…
Abstract
Purpose
Workpiece sorting is a key link in industrial production lines. The vision-based workpiece sorting system is non-contact and widely applicable. The detection and recognition of workpieces are the key technologies of the workpiece sorting system. To introduce deep learning algorithms into workpiece detection and improve detection accuracy, this paper aims to propose a workpiece detection algorithm based on the single-shot multi-box detector (SSD).
Design/methodology/approach
Propose a multi-feature fused SSD network for fast workpiece detection. First, the multi-view CAD rendering images of the workpiece are used as deep learning data sets. Second, the visual geometry group network was trained for workpiece recognition to identify the category of the workpiece. Third, this study designs a multi-level feature fusion method to improve the detection accuracy of SSD (especially for small objects); specifically, a feature fusion module is added, which uses “element-wise sum” and “concatenation operation” to combine the information of shallow features and deep features.
Findings
Experimental results show that the actual workpiece detection accuracy of the method can reach 96% and the speed can reach 41 frames per second. Compared with the original SSD, the method improves the accuracy by 7% and improves the detection performance of small objects.
Originality/value
This paper innovatively introduces the SSD detection algorithm into workpiece detection in industrial scenarios and improves it. A feature fusion module has been added to combine the information of shallow features and deep features. The multi-feature fused SSD network proves the feasibility and practicality of introducing deep learning algorithms into workpiece sorting.
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Shaoxuan Li, Yi Xu, Haiqing Xia, Jing Duan, Yingjie Yu, Xingyun Duan, Pengfei Shi and Jiancheng Tang
Tantalum is a kind of metal material with moderate hardness, high ductility, small thermal expansion coefficient, excellent corrosion resistance and outstanding biocompatibility…
Abstract
Purpose
Tantalum is a kind of metal material with moderate hardness, high ductility, small thermal expansion coefficient, excellent corrosion resistance and outstanding biocompatibility. The purpose of this study is that its tribological performance could be tested and analyzed so as to use it in different fields.
Design/methodology/approach
The friction resistance of a-Ta under dry friction conditions was tested at different roads. The relationships between load and friction coefficient, wear rate and two-dimensional shape of wear scars were studied.
Findings
The stable Ta2O5 film with lubrication effect was generated in the process of friction. And, the larger the test load, the more Ta2O5 would be generated.
Originality/value
This work lays a theoretical foundation for tantalum as an excellent wear-resistant material.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-02-2023-0047/
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Jia Shi, Pingping Xiong, Yingjie Yang and Beichen Quan
Smog seriously affects the ecological environment and poses a threat to public health. Therefore, smog control has become a key task in China, which requires reliable prediction.
Abstract
Purpose
Smog seriously affects the ecological environment and poses a threat to public health. Therefore, smog control has become a key task in China, which requires reliable prediction.
Design/methodology/approach
This paper establishes a novel time-lag GM(1,N) model based on interval grey number sequences. Firstly, calculating kernel and degree of greyness of the interval grey number sequence respectively. Then, establishing the time-lag GM(1,N) model of kernel and degree of greyness sequences respectively to obtain their values after determining the time-lag parameters of two models. Finally, the upper and lower bounds of interval grey number sequences are obtained by restoring the values of kernel and degree of greyness.
Findings
In order to verify the validity and practicability of the model, the monthly concentrations of PM2.5, SO2 and NO2 in Beijing during August 2017 to September 2018 are selected to establish the time-lag GM(1,3) model for kernel and degree of greyness sequences respectively. Compared with three existing models, the proposed model in this paper has better simulation accuracy. Therefore, the novel model is applied to forecast monthly PM2.5 concentration for October to December 2018 in Beijing and provides a reference basis for the government to formulate smog control policies.
Practical implications
The proposed model can simulate and forecast system characteristic data with the time-lag effect more accurately, which shows that the time-lag GM(1,N) model proposed in this paper is practical and effective.
Originality/value
Based on interval grey number sequences, the traditional GM(1,N) model neglects the time-lag effect of driving terms, hence this paper introduces the time-lag parameters into driving terms of the traditional GM(1,N) model and proposes a novel time-lag GM(1,N) model.