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Facing turbulent environments, firms have strived to achieve greater supply chain resilience (SCR) to leverage the resources and knowledge of supply chain members. Both SCR and supply chain integration (SCI) require digitization in the supply chain, but their interrelationships have rarely been researched empirically. This paper aims to uncover the impact of digital technology (DT) on SCR and SCI and the role of SCI in mediating between DT and SCR.

China manufacturing enterprises were surveyed through a Web-based questionnaire, and 96 responses were received. Structural equation modeling was used to test the conceptual model.

The level of enterprise digitization is not directly related to supply chain resilience, but the level of enterprise digitization has a positive impact on the improvement of SCI and SCI also has a positive effect on SCR. Therefore, SCI has a complete intermediary effect between the level of DT and SCR.

This is a pioneer study to examine the relationships among DT, SCI and SCR. The findings of this study present that firms need to improve DT, SCI and SCR consequently.

Women’s health is considered a big public health issue, impacting personal well-being, family reproduction, and society’s development. Since the foundation of the People’s Republic of China, major improvements in women’s social status and health have been made. However, far less has been achieved with respect to gender equality and women still face health disparities. The purpose of this paper is to provide a better understanding of health and health care disparities among women and their determinants in China today.

This paper used the Statistical Yearbook of Health and Family Planning 2014, the 2010 Women’s Social Status Survey and 2010 census data from the National Bureau of Statistics to give an overall description of disparity in health care and health outcome facing women.

Progress in health is not equally shared by the female population, and the differences in women’s health by region and in urban and rural areas are considerable. The existing health disparities are still faced by women in terms of life expectancy, hazardous working environment, and health care services. As to gender differences among the elderly aged 60+, men have better health status compared to women. In addition, women are more financially dependent on other family members for the main source of daily living, reflecting their economic disadvantages.

This study gives a comprehensive and the latest overview of trends of women’s health progress, disparities in health care, and health outcomes both in female population and between genders by using three data sources.

A combined model involving the intensity of negative emotions and the strategic combinations (timing and means) of service recovery is developed. The purpose of this paper is to evaluate the performances of these different combinations through customer satisfaction, repurchase intention and fitting curves between the two under hotel service scenarios.

A 2 (recovery timing: immediate/delayed) × 2 (recovery means: psychological/economic) × 3 (type of service failure: failure in a delivery system/failure in responding to customer needs/improper employee behavior) between-subject experimental design was used with 456 participants.

The results suggest that immediate and economic recovery effectively raises the service recovery evaluations from customers with low-intensity negative emotions, whereas delayed and psychological recovery helps customers with high-intensity negative emotions to give higher evaluations.

When service failures happen, the strategies for and timing of recovery directly influence customers’ service recovery evaluations. This study sheds light on the role that negative emotions play in the process of service recovery and provides implications for service industry managers.

Tour social network data that are heterogeneous contain not only the quantitative structured evaluation data, but also the qualitative non-structured data. This is a big data scenario. How to evaluate tour online review and then recommend to potential tourists quickly and accurately are important parts of social responsibility of tour companies. The purpose of this paper is to propose a new method for evaluating tour online review based on grey 2-tuple linguistic.

The phenomenon of “poor information” exists in some big data scenario. According to social responsibility, grey 2-tuple linguistic evaluation model for tour online review is proposed.

Tour social networks contain data that are valuable to each individual on tourism industry's value chain. Grey 2-tuple linguistic evaluation model can be used for evaluating tour online reviews. This is a systems thinking method that takes social responsibility into account.

Due to the complex links among reviewers in social network, network mining approaches and models are expected to be added to this research in the near future.

Grey 2-tuple linguistic evaluation method can contribute to the future research on evaluating a variety of tour social network comment data in the real world.

A new evaluation method for making evaluation and recommendations based on tour social network comment information is proposed.

The purpose of this paper is to analyze the impact of reference effects on online purchase intention (OPI) of agricultural products in B2C context and to examine how consumers’ food safety consciousness (FSC) moderates that impact.

An empirical survey was used to test the hypotheses. Data were collected from a total of 297 online consumers in China. A structural equation modeling is utilized to assess the relationships proposed in the research model.

The findings of this study show that reference effects have a significant impact on OPI of agricultural products. Both perceived value (PV) and perceived risk (PR) play a mediating role in the relations between reference effects and OPI, but the mediating effect of the PV is found to be significantly greater than that of the PR. Consumers’ FSC significantly and positively moderates the impact of reference effects on OPI, meaning that the more attention consumers pay to food safety, the greater the impact of reference effects on OPI will become.

First, this study mainly analyzes the positive impact of reference effects on OPI. Future research could discuss the negative impact of reference effects and compare the differences between them. Second, this study only takes the PV and PR as mediators into the research model. Future research could consider adding trust, attitude, and other variables and further explore and clarify the influencing mechanism between reference effects and OPI. Third, this study examines the moderating role of consumers’ FSC but does not fully discuss the moderating role of product categories. Further research could compare the influence of reference effects among multiple product categories.

This study provides valuable insights for agricultural enterprises and online vendors that reference effects are one of the most important factors to influence OPI. It suggests to agricultural enterprises and online vendors that reference effects can be used as a new instrument to influence consumers’ online purchase decisions.

This study for the first time defines reference effects in an online setting and introduces the perspective of reference effects to establish a theoretical model to explain consumers’ OPI of agricultural products. The study reveals the influencing mechanism of reference effects on OPI and thus enriches the theory of online purchase behavior.

The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.

Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.

Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.

This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.

The purpose of this study is to examine whether corporate tax avoidance behavior increases firm value in Chinese context. A large number of studies conduct their designs on the consumption that tax avoidance represents wealth transfer from government to enterprises and therefore enhances firm value. This study argues that, contrast to developed countries, tax avoidance does not necessarily add value to opaque Chinese firms relative to transparent counterparts due to higher agency costs.

Using a large sample of Chinese listed-firms data for the period 2001-2009 and fixed effects regression model, this study examines the relation between tax avoidance and firm value. A series of robustness checks are conducted to alleviate the concern of endogeneity.

The authors find that tax avoidance behavior increases agency costs and reduces firm value. The authors further find that information transparency interacts with corporate tax avoidance, moderating the relation between tax avoidance and firm value. Investors in China react negatively to corporate tax avoidance behavior, but this negative reaction could be mitigated by information transparency. The results are robust to a series of alternative treatments, including varied measures, first-order differential approach and 2SLS.

The results suggest that tax avoidance does not necessarily increase firm value, part of gains are encroached by self-serving managers. Moreover, investors in China downplay the significance of tax avoidance, although corporate information transparency could soften their negative tone.

As the restaurant industry is a representative service industry, long-living restaurants could carry the secrets of key factors that are needed to establish “sustainable business models” in service industry. The authors aim to answer the following question: How can restaurants innovate business model sustainably to last for more than 50 years through the era of digital transformation with open innovation dynamics?

Five long-lived restaurants from Daegu, Kyoto and Naples were selected separately by using the snowballing approach, and were analyzed through in-depth interviews and participatory observations.

Restaurants in Daegu have lived long mainly because of adding value to their recipes. Restaurants in Kyoto have lived very long, primarily by decoupling their original services, ingredients and recipes. Restaurants in Naples have enjoyed long lives by coupling or recoupling their ingredients, services and recipes.

The implication is that long-living restaurants or service firms could maintain their own sustainability by dynamically circling the following services: (1) adding and boning recipes (focusing on special menus or products), (2) coupling of ingredients (creative recoupling of original ingredients) and (3) decoupling of services (disconnecting the value chain and rebalancing it).

The purpose of this study is to determine the cavitation flow characteristics of the high-pressure differential control valve. The relationship between cavitation, flow coefficient and spool angle is obtained. By analyzing the relationship between different spool angles and energy loss, the energy loss at different spool angles is predicted.

A series of numerical simulations were performed to study the cavitation problem of a high-pressure differential control valve using the RNG k–e turbulence model and the Zwart cavitation model. The flow states and energy distribution at different spool angles were analyzed under specific working conditions.

The cavitation was the weakest when the spool angle was 120° or the outlet pressure was 8 MPa. The pressure and speed fluctuations of the valve in the throttle section were greater than those at other locations. By calculating the entropy production rate, the reason and location of valve energy loss are analyzed. The energy loss near the throttling section accounts for about 92.7% of the total energy loss. According to the calculated energy loss relationship between different regions of the spool angle, the relationship between any spool angle and energy loss in the [80,120] interval is proposed.

This study analyzes the cavitation flow characteristics of the high-pressure differential control valve and provides the law of energy loss in the valve through the analysis method of entropy. The relationship between spool angle and energy loss under cavitation is finally proposed. The research results are expected to provide a theoretical basis for the optimal design of valves.