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The purpose of this paper is to propose a prediction model to predict the cost of complex products with lack of data. The cost estimating is one of the key elements of arguments around technological economy and investment decision‐making process of complex product.

A complex product has many characteristics, such as complex structure, large investment, high risk and it usually falls into small‐batch‐production category. Its cost estimation samples are small and cost data are very limited. Based on the characteristics of complex product and cost estimating, this paper introduces performance parameters sequence of associated known data, establishes an N‐GM (0, N) model of characteristic sequence with straddle missing data.

On the basis of the known key performance parameter sequence, N‐GM (0, N) model is used to predict the grey interval of overall cost vacancy data. Overall cost vacancy data is whitened by sorting reference sequence and realizing complex product overall cost estimation.

The method introduced in the paper can be used to solve practical problems, especially cost prediction of complex products with poor data. The model is also applied on the overall cost and the key component cost estimation of similar but different complex products. Moreover, it provides potential theoretical support for the development of complex product industry in the future.

In this paper, the complex product, which now plays a strategic industrial role in China, is systematically studied by utilizing a new methodology based on grey systems, especially the cost evaluation of the complex product. The use of grey correlation analysis in screening control key item index of complex product cost, the overall cost sequence of the complex product as related sequence and sorting reference sequence, the paper predicts and whitens vacant key item index, obtaining the key item cost index of complex product.

The purpose of this paper is to develop a system to analyse the characteristics of infrared objects.

According to the gray scale of image pixel by the image entropy, gray scale estimating is carries on to construct the neural networks. And then the grey relational analysis and grey clustering methods are applied to filter the possible object. The target is predicted through image segmentation pretreatment based on the forecasting value by grey system and assigned corresponding mark. The forecasting precision is greatly elevated by GM (1, 1) model.

The paper illustrates that, based on the analysis and its experimental results, this system has a good recognition rate for infrared target.

This paper provides a way to grasp the minutial feature of the image. The filtering operation based on pixel level provided auto‐adapted filtering with a new stage.

Applications of grey theory deepened the content of detecting infrared targets and enriched technology of image processing.

This system introduces an effective method for detecting infrared targets.

Based on the theory of embodied cognition, this study uses the Mehrabian–Rusell model to explore the influence of tourists’ body involvement during sports vacations on their post-trip behavioral intention, as well as the regulatory role of tourism involvement in this process.

Structural equation modeling (SEM) was used to test the hypotheses, mediating effects and moderating effects. The data were collected through an online survey of 631 visitors to sports tourism destinations in China.

Proprioception and kinesthesia in sports tourism activities can affect post-trip behavioral intention through body arousal and tourism satisfaction. Tourism involvement positively regulates the influence of body embeddedness and body arousal on tourism satisfaction. Furthermore, a “threshold effect” exists in the emotional effect of tourists’ body involvement.

To develop sports tourism, it is important to take the following steps: create multi-sensory stimulation to improve the physical participation of tourists in sports tourism activities, design sports resorts that cater to people of different age groups, evaluate tourists’ satisfaction and use their feedback to make continuous improvements, improve the basic convenience services offered at sports resorts, use social media to display the unique physical environment and others characteristics of sports destinations to expand popularity.

This study constructs a conceptual model of the influence mechanism of tourists’ body involvement on post-trip behavioral intention to present valuable insights that could help promote the sustainable development of sports tourism.

The purpose of this paper is to examine the effects of the government intervention and bank competition on small and medium enterprise (SME) external debt financing in Chinese capital market.

This study uses ordinary least squares with standard errors clustered at the firm level. In addition, the authors use the dynamic system generalized method of moments to address the possible endogeneity issue in the regressions.

Using a sample of 908 firms from 2000 to 2010, the authors found that SMEs are more likely to access bank loans only in regions with higher level of government intervention than median government intervention. Further, the result shows that the government is motivated to help SMEs to obtain more external debt in regions where the level of bank competition is lower than the median bank competition index. Last, the authors found evidence that firms with politically connected CEOs are likely to access bank loans.

This paper highlights that government intervention enables the SMEs to secure more bank loans. Second, the authors’ results imply that the government is motivated to help SMEs to obtain more external debt in regions with low level of bank competition.

This study contributes to the current literature by revealing that government intervention is the driving force alleviating SMEs’ constraints in accessing external financing. Second, this study finds the evidence to supports the argument that government has a strong motive to help SMEs to secure long-term credits for political purpose (Fan et al., 2012), when the level of bank competition is low (Berger and Udell, 2006).

This paper explores the driving factors of parasocial relationship (PSR) in the virtual reality (VR) shopping environment, and how this relationship affects brand equity. The study also investigates the moderating role of the celebrity endorser dynamism (CED) in the relationship between PSR and its antecedents.

The primary data collection tool is a survey administered to Chinese consumers (n = 531) who have experienced the products of UNIQLO brand on Taobao Buy + platform, and who had a PSR with the endorser in their VR shopping process. Structural equation modeling is employed to examine the hypothesized relationships among all variables.

The findings show that VR shopping factors (i.e. physical attractiveness, social presence and technology novelty) perceived by consumers to affect PSR, and this relationship and brand equity are positively associated, while CED moderates the relationship between PSR and its antecedents.

This study sheds light on how PSR in the VR shopping environment can improve brand equity. It contributes to the theory of PSR and persuasion as well as marketing strategies. From a managerial perspective, guidelines are provided for firms to implement value communication activities using VR, and to increase their brand equity.

The purpose of this paper is to synthesize oil-soluble copper (Cu) nanoparticles modified with free phosphorus and sulfur modifier and investigate its tribological properties as environment-friendly lubricating oil additives.

To improve the anti-oxidation properties of these nanoparticles, two kinds of surface modifiers, oleic acid and oleylamine were used simultaneously. The morphology, composition, structure and thermal properties of as-synthesized Cu nanoparticles were investigated by means of transmission electron microscopy, X-ray powder diffraction, Fourier transform infrared spectrometry and differential thermal and thermogravimetric analysis. The tribological properties of as-synthesized Cu nanoparticles as an additive in liquid paraffin were evaluated with a four-ball friction and wear tester.

It has been found that an as-synthesized Cu nanoparticle has a size of 2-5 nm and can be well dispersed in organic solvents. Tribological properties evaluation results show that as-synthesized Cu nanoparticles possess excellent anti-wear properties as an additive in liquid paraffin. The reason lies in that as-synthesized surface-capped Cu nanoparticles are able to deposit on sliding steel surface and form a low-shearing-strength protective layer thereon, showing promising application as an environmentally acceptable lubricating oil additive, owing to its free phosphorus and sulfur elements characteristics.

Oil-soluble surface-modified Cu nanoparticles without phosphorus and sulfur were synthesized and its tribological properties as lubricating oil additives were also investigated in this paper. These results could be very helpful for application of Cu nanoparticles as environment-friendly lubricating oil additives.

The purpose of this paper is to extend prior supply chain research by empirically exploring the relationship among guanxi, supply chain integration (SCI), and operational performance. More specifically, this study investigates the mediating role of SCI.

Ordinary least square regression is used to analyze survey data collected from 126 automobile manufacturers in China.

The results reveal a significant positive relationship between guanxi and SCI, and that SCI is significantly and positively related to operational performance. The authors’ findings further suggest that guanxi indirectly affects operational performance through SCI.

The empirical findings imply that it is vital for managers to recognize the important mediating role of dynamic SCI capabilities.

As a fundamental Chinese cultural norm, guanxi can be critical in a supply chain context. Although previous research has identified the importance of guanxi and SCI in improving firm performance, far less attention was given to the study of the mediating effect of SCI on the guanxi-performance relationship. This study thus fulfills the research gap by providing an initial empirical examination of the mediating role of SCI in China’s automotive industry.

China’s rapid pace of urbanization has resulted in millions of rural residents migrating from rural areas to urban areas for better job opportunities. Due to economic pressures and the nature of China’s demographic policies, many of these migrants have been forced to leave their children with relatives – typically paternal grandparents – at home in the countryside. Thus, while income for most migrant families has risen, a major unintended consequence of this labor movement has been the emergence of a potentially vulnerable sub-population of left-behind children (LBCs). The purpose of this paper is to examine the impacts of parental migration on both the academic performance and mental health of LBCs.

Longitudinal data were drawn from three waves of a panel survey that followed the same students and their families – including their migration behavior (i.e. whether both parents, one parent, no parent migrated) – between 2015 and 2016. The survey covers more than 33,000 students in one province of central China. The authors apply a student fixed-effects model that controls for both observable and unobservable confounding variables to explicate the causal effects of parental migration on the academic and mental health outcomes for LBC. The authors also employ these methods to test whether these effects differ by the type of migration or by gender of the child.

The authors found no overall impact of parental migration on either academic performance or mental health of LBCs, regardless of the type of migration behavior. The authors did find, however, that when the authors examined heterogeneous effects by gender (which was possible due to the large sample size), parental migration resulted in significantly higher anxiety levels for left-behind girls. The results suggest that parental migration affects left-behind boys and girls differently and that policymakers should take a more tailored approach to addressing the problems faced by LBCs.

The main contributions of this paper come from the large and representative sample, as well as the causal effects analysis of being left-behind on both academic performance and mental health. First, the paper uses comprehensive panel data from a representative and populous province in China, and the sample size is the largest one among LBC-related papers to the authors’ knowledge. Second, the paper separately examines the causal effects on the student outcomes of different migration strategies. Third, the paper analyzes the heterogeneous effects of different migration strategies on LBC gender. The authors believe that the paper makes a key contribution to the literature.

The ecological environment of the Loess Plateau, China, is extremely fragile under the context of global warming. Over the past two decades, the vegetation of the Loess Plateau has undergone great changes. This paper aims to clarify the response mechanisms of vegetation to climate change, to provide support for the restoration and environmental treatment of vegetation on the Loess Plateau.

The Savitsky–Golay (S-G) filtering algorithm was used to reconstruct time series of moderate resolution imaging spectroradiometer (MODIS) 13A2 data. Combined with trend analysis and partial correlation analysis, the influence of climate change on the phenology and enhanced vegetation index (EVI) during the growing season was described.

The S-G filtering algorithm is suitable for EVI reconstruction of the Loess Plateau. The date of start of growing season was found to gradually later along the Southeast–Northwest direction, whereas the date of the end of the growing season showed the opposite pattern and the length of the growing season gradually shortened. Vegetation EVI values decreased gradually from Southeast to Northwest. Vegetation changed significantly and showed clear differentiation according to different topographic factors. Vegetation correlated positively with precipitation from April to July and with temperature from August to November.

This study provides technical support for ecological environmental assessment, restoration of regional vegetation coverage and environmental governance of the Loess Plateau over the past two decades. It also provides theoretical support for the prediction model of vegetation phenology changes based on remote sensing data.

This study aims to develop a chain-mediated model to examine how streamer and product characteristics influence consumer behavior inertia (CBI) based on an extended cognitive-affective-conative (CAC) perspective.

This study used an online survey concerning the livestreaming activities of 250 experienced shoppers to measure the proposed model.

Streamer (product) attractiveness mediates the relationship between streamer (product) characteristics and shopping experience memory. Streamer (product) attractiveness and shopping experience memory have a chain mediating effect between the streamer (product) characteristics and CBI.

Theoretically, the study demonstrates the critical role of attractiveness and shopping experience memory in the formation of consumer inertia and complements current explanations of consumer continuance of buying through livestreaming. From a managerial standpoint, the findings provide guidelines for enterprises carrying out livestreaming business on how to improve inertia to realize a stable profit source.