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Brand alliance strategy is a popular strategy for multinational enterprises entering foreign markets, especially when domestic firms in the host market have a relatively weaker brand image. However, Volvo Construction Equipment's failure to acquire a domestic firm in China (Shandong Lingong Construction Machinery Company Limited [SDLG]) challenges existing management theory. Thus, the purpose of this study is to understand the reasons behind the failure of a leading international brand’s acquisition of a local brand in a fast-growing developing country.

This paper conducted a case study to illustrate how Volvo failed to benefit from the dual-brand strategy by analyzing its brand architecture strategy, the industry specificity of its heavy equipment, issues around its complex dealership and the implementation of optimal distinctiveness for the Volvo brand after acquiring SDLG.

Although Volvo’s dual-brand strategy with SDLG was theoretically valid, in practice, the strategy made the two brands very distinct in their business-to-business (B2B) consumers’ perception and dealers’ operation. Given a wrong estimation of Chinese demand in its premium market, Volvo, which targeted only the Chinese premium market, failed to benefit from its brand alliance with SDLG in the Chinese market.

The analysis of Volvo’s acquisition of SDLG enriches the current theory of international business and brand management. In particular, the results provide new insights into how leading international brands can avoid potential failure in a fast-growing market. Moreover, this paper highlights the difference of branding strategy in the B2B and business-to-consumer markets, which carries value to business executives.

The purpose of this paper is to explore the impact and mechanism of WeChat public platforms articles (abbreviated as WPP) on blood donation behavior using data of WPPA and donation behavior data.

This paper uses multiple linear regression methods, web crawlers and natural language processing technology. It first quantifies the impact of WPP published articles on donation behavior. On this basis, it then selects data from the day of article publication to further study the impact of article dissemination on donation behavior from the perspective of reading quantity, and analyzes the influencing factors of article reading quantity.

The results show that on the same day that an article is published, there is an increase of 13.8 and 14.3% in blood donation volume and fan registrations, respectively. The mediating effect exists. However, the day after an article is published, there is no longer any effect on blood donations. With a 1% increase in reading quantity, blood donation volume on the day of article publication increases by 0.13%, and this positive impact is promoted by the quality of the articles. A conc ise articles title and body and rich images help drive reading quantity. Moreover, blood donors prefer to read articles about blood dynamics and donation promotion, while articles about news, announcements and administrative affairs make them less inclined to read.

First, it focuses on WPPA, quantifies the impact of articles on blood donation behavior and analyzes the mechanism. Second, the authors study the impact and timeliness of social media article dissemination to address the insufficiency of existing research. Third, the study provides a scientific basis for the editing and publishing of articles, helping blood banks improve the effectiveness of publicity and recruitment.

The purpose of this paper is to link subjective data obtained from a questionnaire survey with blood donation behavioral data, constructs a conceptual model of the factors that influence repeated blood donation behavior, and explores the mechanisms and degrees of influence of the value and cost elements of blood donors on repeated blood donation behavior.

First, this study constructs a conceptual model of the factors that affect repeated blood donation based on delivered value theory. Second, this paper is driven by subjective data obtained from a questionnaire and big data on blood donation behavior; the use of multisource data can help us understand repeated blood donation behavior from a broader perspective. Through data association and systematic research, it is possible to accurately explore the mechanisms through which various factors affect repeated blood donation behavior.

The results show that among the value elements, personnel value (PV), image value and blood donation value affect blood donation behavior in decreasing order. The change in PV per unit directly caused a 0.471-unit change in satisfaction, which indirectly caused a 0.098-unit change in donation behavior. Among the cost elements of blood donors, only the impact of time cost (TC) on repeated blood donation behavior was significant, and a change of one unit in TC caused a change in repeated blood donation behavior of −0.035 units. In addition, this paper groups subjects according to gender, education and age and explores the differences in the value and cost factors of different groups. Finally, based on the research results, the authors propose corresponding policy recommendations.

First, the authors expand the application field of the delivered value theory, and provide a new perspective for studying repeated blood donation. Second, through questionnaire data and blood donation behavior data, the authors comprehensively explore the factors that influence repeated blood donation behavior.

The purpose of this paper is to explore the impact of WeChat public platforms (abbreviated as WPP) on blood donation behavior using data from the platforms’ backend and information system.

First, this paper established a time-varying difference-in-difference (DID) model to evaluate the change before and after following the WPP under normal scenarios. The difference-in-difference-in-difference (DDD) method was further used to analyze the heterogeneous effects of gender, age, occupation and education. Second, a logit model was used to examine the impact of WPP on blood donation behavior under emergency scenarios (i.e. COVID-19).

The research shows that following WPP has a positive impact on donation volume. For each donor, the average blood donation volume after following WPP increased by 12.94% compared to before following. The WPP has a greater impact on groups with males, medical staff, middle-aged individuals and those with primary school education. Following WPP also enhanced blood donation behavior in emergency scenarios. During the COVID-19 pandemic, the probability of fans donating blood was 2.6% higher than non-fans, and the average blood donation volume of fans was 7.04% higher than non-fans, which was 5.9% lower than in normal scenarios.

For theory, this paper quantified the impact of WPP on blood donation behavior in normal and emergency scenarios and addressed the research gap surrounding the impact exerted by social media on blood donation behavior. For methodology, the time-varying DID model, DDD model and logit model were applied to the field of blood donation, which expanded the application scenarios. For practice, the findings are of great significance for recruiting blood donors and providing evidence for promotion on WPP.

Although blood banks have recently started to recruit blood donors through social media platforms, including WeChat, to increase recruitment effectiveness, few researchers have studied their effects on blood donation behavior. The aim of this study is to examine the influence of using official WeChat accounts on repeat blood donation behavior.

This paper used the backstage operation data of official WeChat accounts and blood supply chain management system data from the blood bank for the study to analyze the changes in repeat blood donation behavior. First, to analyze the changes in the average frequency of blood donation per year, average volume of single blood donation and blood eligible rate of repeat blood donors before and after following the official WeChat accounts by difference-in-differences model combined with propensity score matching (PSM-DID). Second, we examined the impact of official WeChat accounts on the proportion of repeat blood donors through survival analysis.

The results show that following WeChat accounts increases the average frequency of blood donation and blood eligible rate of repeat blood donors by 14.36% and 1.19%, respectively, and have no significant effect on the average volume of single blood donation. Further, WeChat accounts have a more significant impact on the average frequency of blood donations per year for workers, farmers, medical staff and groups with education levels of junior high school. In addition, official WeChat accounts can effectively increase the proportion of repeat donors.

The results provide a quantitative basis for the influence of official WeChat accounts on repeat blood donation behaviors. On the one hand, it is of great significance to guide the publicity and recruitment of unpaid blood banks. On the other hand, it provides an evidence for the promotion of official WeChat accounts.

A common pipeline of apparel design and simulation is adjusting 2D apparel patterns, putting them onto a virtual human model and performing 3D physically based simulation. However, manually adjusting 2D apparel patterns and performing simulations require repetitive adjustments and trials in order to achieve satisfactory results. To support future made-to-fit apparel design and manufacturing, efficient tools for fast custom design purposes are desired. The purpose of this paper is to propose a method to automatically adjust 2D apparel patterns and rapidly generate acustom apparel style for a given human model.

The authors first pre-define a set of constraints using feature points, feature lines and ease allowance for existing apparels and human models. The authors formulate the apparel fitting to a human model, as a process of optimization using these predefined constraints. Then, the authors iteratively solve the problem by minimizing the total fitting metric.

The authors observed that through reusing existing apparel styles, the process of designing apparels can be greatly simplified. The authors used a new fitting function to measure the geometric fitting of corresponding feature points/lines between apparels and a human model. Then, the optimized 2D patterns are automatically obtained by minimizing the matching function. The authors’ experiments show that the authors’ approach can increase the reusability of existing apparel styles and improve apparel design efficiency.

There are some limitations. First, in order to achieve interactive performance, the authors’ current 3D simulation does not detect collision within or between adjacent apparel surfaces. Second, the authors’ did not consider multiple layer apparels. It is non-trivial to define ease allowance between multiple layers.

The authors use a set of constraints such as ease allowance, feature points, feature lines, etc. for existing apparels and human models. The authors define a few new fitting functions using these pre-specified constraints. During physics-driven simulation, the authors iteratively minimize these fitting functions.

With the fierce competition in the cold chain logistics market, achieving and maintaining excellent customer satisfaction is the key to an enterprise's ability to stand out. This research aims to determine the factors that affect customer satisfaction in cold chain logistics, which helps cold chain logistics enterprises identify the main aspects of the problem. Further, the suggestions are provided for cold chain logistics enterprises to improve customer satisfaction.

This research uses the text mining approach, including topic modeling and sentiment analysis, to analyze the information implicit in customer-generated reviews. First, latent Dirichlet allocation (LDA) model is used to identify the topics that customers focus on. Furthermore, to explore the sentiment polarity of different topics, bi-directional long short-term memory (Bi-LSTM), a type of deep learning model, is adopted to quantify the sentiment score. Last, regression analysis is performed to identify the significant factors that affect positive, neutral and negative sentiment.

The results show that eight topics that customer focus are determined, namely, speed, price, cold chain transportation, package, quality, error handling, service staff and logistics information. Among them, speed, price, transportation and product quality significantly affect customer positive sentiment, and error handling and service staff are significant factors affecting customer neutral and negative sentiment, respectively.

The data of the customer-generated reviews in this research are in Chinese. In the future, multi-lingual research can be conducted to obtain more comprehensive insights.

Prior studies on customer satisfaction in cold chain logistics predominantly used questionnaire method, and the disadvantage of which is that interviewees may fill out the questionnaire arbitrarily, which leads to inaccurate data. For this reason, it is more scientific to discover customer satisfaction from real behavioral data. In response, customer-generated reviews that reflect true emotions are used as the data source for this research.

This paper aims to analyze high-quality papers on the research of electronic word-of-mouth (eWOM) for product and service quality improvement from 2009 to 2022, in order to fully understand their historical progress, current situation and future development trend.

This paper adopts the bibliometrics method to analyze the relevant literature, including publishing trend and citation status, regional and discipline area distribution, and influential publications. Secondly, the VOSviewer is used for literature co-citation analysis and keyword co-occurrence analysis to obtain the basic literature and research hotspots in this research field.

Firstly, the study finds that the number of publications basically shows an increasing trend, and those publications are mainly published in tourism journals. In addition, among these papers, China has the largest number of publications, followed by the USA and South Korea. Through co-citation analysis of literature and keyword co-occurrence analysis, 22 foundational papers and six main research topics are obtained in this paper. Finally, this paper elaborates on the development trend of the research topic and future research directions in detail.

This is the first paper that uses bibliometrics to analyze and review relevant researches on eWOM for product and service quality improvement, which is helpful for researchers to quickly understand its development status and trend. This review also provides some future research directions and provides a reference for further research.

Based on the attention-based view (ABV), this study examines the mechanism of external pressure and internal managerial interpretation affecting the promotion of green entrepreneurial orientation (GEO) of agricultural enterprises.

Based on data collected from 208 agricultural enterprises in China, the conceptual model was tested by using hierarchical regression.

The results show that managerial interpretation can affect the promotion of GEO. Command and control regulation, market-based regulation and green market pressure are important external pressures that affect the promotion of GEO. In addition, managerial interpretation mediates the relationship between command and control regulation and GEO, market-based regulation and GEO, as well as green market pressure and GEO.

This study proposes a key path for promoting the adoption and implementation of GEO by agricultural enterprises. The research results provide experience for emerging and developing countries to promote the GEO of agricultural enterprises, which is helpful to alleviate the environmental problems caused by the development of agricultural enterprises.

For the first time, this study introduced the ABV into the research of GEO. The research results enrich the theoretical perspective of GEO and expand the research field of the ABV. In addition, this study fills the research gap that existing research has not paid enough attention to the internal driving factors of GEO and opens the black box between the external pressure and GEO.

The purpose of this paper is to investigate the relationships between business risks and credit choices of 400 farm households surveyed in Shaanxi province in October 2007 in the Yangling district. More specifically, this paper investigates whether or not rural farm households in China balance business risks from agricultural production with financial risk from the use of debt.

The data were collected through a survey of 400 farm households in Shaanxi province conducted in October 2007. Four separate regressions are run using a credit measure as the dependent variable and measures of profitability, risk, risk aversion, and demography, and debt source (formal versus informal lending) as independent variables.

The model shows evidence of risk balancing. That is, there is strong evidence that Chinese farmers reduce credit use and financial risk, as business risks increase.

The results suggest that Chinese policy makers could encourage the use of finacial leverage and prudent debt use by offering risk reducing programs such as crop insurance, weather insurance, or price insurance.

This paper uses a unique survey form to collect production risk data as well as gather information on credit use and sources. Data were collected so that risk measures could easily be computed using a triangular distribution. Furthermore, this is believed to be the first empirical validation of the risk balancing hypothesis.