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The purpose of this paper is to investigate the impact of intellectual capital (IC) and its components (human, structural, relational and innovation capitals) on financial performance (FP) at different life cycle stages.

The study uses the data from Chinese manufacturing listed companies during 2014–2018. The modified value added intellectual coefficient (MVAIC) model is employed as the measurement of IC efficiency. Finally, multiple regression analysis is used to test the research hypotheses.

This study shows that the impact of IC on FP is different across life cycle stages. Specifically, at the birth stage, human capital (HC), structural capital (SC) and innovation capital (INC) have a positive impact on FP. At the growth and mature stages, all IC components contribute to FP improvement. HC and SC play an important role at the revival stage, while only HC positively affects FP at the decline stage.

The findings may help corporate managers to make optimal strategies to improve FP by effective utilization of IC resources in the complex and competitive business environment. Meanwhile, companies can invest in the core elements of IC at different stages of development, so as to maximize the contribution of IC to company value.

This is among the few studies to explore the impact of IC on FP of manufacturing listed companies in the Chinese context from the perspective of life cycle. It also makes novel contributions in measuring IC by the MVAIC model with the inclusion of relational capital and INC that are largely neglected in previous research.

The purpose of this paper is to study distance measuring and sorting method of general grey number.

First, the concept of generalised grey number based on grey system theory is given in this paper. Second, from the perspective of kernel and degree of greyness of general grey number, the method of measuring the distance of general grey number and its properties are given. At the same time, the concepts of the kernel expectation and the kernel variance of the general grey number are proposed.

Up to now, the method of measuring the distance and sorting of general grey number is established. Thus, the difficult problem for set up sorting of general grey number has been solved to a certain degree.

The method exposed in this paper can be used to integrate information form a different source. Distance measuring and sorting method of general grey number could be extended to the case of grey algebraic equation, grey differential equation and grey matrix which includes general grey numbers, etc.

The concepts of the kernel expectation and the kernel variance of the general grey number are proposed for the first time in this paper; the novel sorting rules of general grey numbers were also constructed.

For decades, financing constraints have been a major obstacle to corporate performance. Volumes have been written about the probable factors that can help firms alleviate such financial constraints. Nonetheless, empirical evidence concerning the various perspectives on how inventory control may influence financing constraints has been surprisingly scant. Using the resource- and region-based view as theoretical lenses, this study seeks to estimate the relationship between lean inventory, regional financial technology (fintech) and financing constraints.

Utilizing a large-scale sample of small- and medium-sized enterprises (SMEs) in China's manufacturing sector, the authors empirically test their hypotheses by using hierarchical linear regression models with multiple high-dimensional fixed effects.

Results indicate that firms with higher levels of inventory leanness and those located in more fintech-developed regions are less likely to encounter financing constraints. Furthermore, inventory leanness and regional fintech ecosystem development interact with each other to mitigate financing constraints. Moreover, inventory leanness significantly decreases firms' financing constraints when the regional fintech ecosystem is highly developed.

The present research contributes to the literature on the interface of supply chain management and financial management. It also provides managerial implications for policymakers and SME stakeholders.

The purpose of this paper is to promote the efficiency of RGB-depth (RGB-D)-based object recognition in robot vision and find discriminative binary representations for RGB-D based objects.

To promote the efficiency of RGB-D-based object recognition in robot vision, this paper applies hashing methods to RGB-D-based object recognition by utilizing the approximate nearest neighbors (ANN) to vote for the final result. To improve the object recognition accuracy in robot vision, an “Encoding+Selection” binary representation generation pattern is proposed. “Encoding+Selection” pattern can generate more discriminative binary representations for RGB-D-based objects. Moreover, label information is utilized to enhance the discrimination of each bit, which guarantees that the most discriminative bits can be selected.

The experiment results validate that the ANN-based voting recognition method is more efficient and effective compared to traditional recognition method in RGB-D-based object recognition for robot vision. Moreover, the effectiveness of the proposed bit selection method is also validated to be effective.

Hashing learning is applied to RGB-D-based object recognition, which significantly promotes the recognition efficiency for robot vision while maintaining high recognition accuracy. Besides, the “Encoding+Selection” pattern is utilized in the process of binary encoding, which effectively enhances the discrimination of binary representations for objects.

The purpose of this paper is to investigate the tribological properties of the WC/TiC-Co substrate under different loading conditions under three impact abrasive wear conditions.

The three body collisional wear behavior of Co alloy with WC and TiC at three impact energy was studied from 1 to 3 J. Meanwhile, the microstructure, hardness, phase transformation and wear behavior of these specimens were investigated by scanning electron microscopy, Rockwell hardness (HRV), EDS and impact wear tester. The resulting wear rate was quantified by electronic balance measurements under different pressures.

The specific wear rate increases with the increase of the nonlinearity of the impact energy and the increase in the content of WC or TiC. The effect of TiC on wear rate is greater than that of WC, but the hardness is smaller. The wear characteristics of the samples are mainly characterized by three kinds of behavior, such as cutting wear, abrasive wear and strain fatigue wear. The WC-Co with fewer TiC samples suffered heavier abrasive wear than the more TiC samples under both low and high impact energy and underwent fewer strain fatigue wears under high impact energy.

The experimental results show that the wear resistance of the Co alloy is improved effectively and the excellent impact wear performance is achieved. The results can be used in cutting tools such as coal mine cutting machines or other fields.

The purpose of this paper is to investigate the effects of original equipment manufacturing suppliers’ local network embeddedness on buyers’ relative attention and joint innovation through service innovation competence.

A structural equation model was analyzed using AMOS 21 with data derived from 165 buyers in the Taiwanese electronics industry.

From the buyer perspective, suppliers with embedded network relationships in emerging markets are perceived to be service oriented and to have relative attention and joint innovation that are attractive to buyers. In addition, the findings of empirical testing conducted in this study suggest that perceived exploitative and explorative service innovation competence partially mediate the relationship between perceived network embeddedness and relative attention, while explorative service innovation competence partially mediates the influence of perceived network embeddedness on buyers’ joint innovation.

This study innovatively employed a buyer perspective to examine the servitization of manufacturing suppliers and the effects of this on the buyer–supplier relationship, providing new insights into the role of service innovation competence as well as important theoretical and managerial implications.

Original equipment manufacturing (OEM) suppliers must identify and communicate competences to ensure that they are successfully translated into competitive advantages. This study aims to explore the competence-based marketing capabilities of suppliers based on competence-based marketing view. It integrates resource-based theory and resource dependence theory to conduct a detailed evaluation of the impact of competence-based marketing capabilities on collaboration development, which is classified as either exploitative or explorative collaboration between buyers and suppliers.

The partial least squares method was used to analyse and find direct support for the authors’ hypotheses based on cross-sectional data from a sample of 116 Taiwanese OEM suppliers.

The results find no support as recent arguments that the marketing of competence would directly affect collaborative relationships in a buyer–supplier relationship. The two mediating roles of relative attention from buyers and relationship learning with buyers were confirmed. The empirical findings indicated that relative attention from buyers partially mediates the relationship between competence-based marketing capabilities and exploitative collaboration development, while relationship learning completely mediates the relationship between competence-based marketing capabilities and two-pronged collaboration development.

This study provides a thorough examination of competence-based marketing capabilities, which have attracted substantial attention from business scholars but empirical research investigating and discussing how suppliers develop new collaborations with buyers is lacking.

The purpose of this paper is to identify different automotive coatings using Confocal Raman microscope which could hardly be differentiated with Fourier transform infrared microscope (FTIR).

Raman spectroscopy was used to provide extra vibration information to infrared spectroscopy. Paints preparation was not necessary, and only 30 s was needed for each sample in an optimised method. Paints were first analysed by FTIR and then compared with Raman microscope.

Raman microscope was used to address the lack of ability of FTIR in discriminating four groups of paints in same colours. This study indicated that Raman microscopy is especially effective in sensing pigments and could successfully identify all pigments in the paints.

The two instruments in combination produce accurate results than when used individually, especially in complex and multi-layered paints analysis.

The method proved to be fast, accurate and non-destructive, and it could be easily applied to real cases.

With this method, scientists could discriminate some coating types which were hard to be discriminated by other techniques.

This study conceptualizes the digital transformation (DT) strategy in a supply chain context, identifies its drivers from intra- and inter-organizational perspectives and examines the effect of the DT strategy on the strategic agility and financial performance of Chinese manufacturing firms.

The authors constructed a theoretical model by synthesizing the diffusion of innovation and organizational information processing theory (OIPT) and provided a set of hypotheses. The authors empirically tested the arguments using partial least squares structural equation modeling using data from a sample of 200 manufacturing firms in China.

The findings indicate that while supply chain connectivity positively affects DT adoption and DT routinization, data analytics capability and organizational learning positively influence DT adoption but not DT routinization. The mediation analysis also shows that DT strategy has significant direct effects on financial performance and a stronger indirect influence on financial performance via improved strategic agility.

This study responds to repeated calls for a new understanding of supply chain DT strategy. In addition, the study offers important contributions to the literature by identifying the potential discord between the existing DT strategy and the supply chain context and proposes a new framework that provides essential theoretical underpinnings.

This study enriches the literature by conceptualizing and validating the dimensions, driving factors and performance implications of DT strategy in strategic supply chain management.

While service innovation is an important issue for manufacturers, relatively little research lends empirical support to the perspective that service innovation enhanced by collaborative competence may impact the competitive advantage of original equipment manufacturing (OEM) suppliers. This study aims to advance a service-dominant logic by empirically investigating the linkage between collaborative competence, service innovation and competitive advantage for OEM suppliers.

Surveys were completed by representatives of 142 Taiwanese OEM suppliers in the electronics industry.

The results of path analysis suggest that information competence and coordination competence have positive effects on both exploitative service innovation and explorative service innovation. There only appears to be a significant relationship between joint innovation competence and explorative service innovation. Furthermore, two-pronged service innovations contribute to a supplier’s internal and external competitive advantage.

The empirical findings have important research and practical implications that help elucidate the antecedents and outcomes of OEM suppliers’ service innovation.