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Delivering messages and information to potentially interested users is one of the distinguishing applications of online enterprise social network (ESN). The purpose of this paper is to provide insights to better understand the repost preferences of users and provide personalized information service in enterprise social media marketing.

It is accomplished by constructing a target audience identification framework. Repost preference latent Dirichlet allocation (RPLDA) topic model topic model is proposed to understand the mass user online repost preferences toward different contents. A topic-oriented preference metric is proposed to measure the preference degree of individual users. And the function of reposting forecasting is formulated to identify target audience.

The empirical research shows the following: a total of 20 percent of the repost users in ESN represent the key active users who are particularly interested in the latent topic of messages in ESN and fits Pareto distribution; and the target audience identification framework can successfully identify different target key users for messages with different latent topics.

The findings should motivate marketing managers to improve enterprise brand by identifying key target audience in ESN and marketing in a way that truthfully reflects personalized preferences.

This study runs counter to most current business practices, which tend to use simple popularity to seek important users. Adaptively and dynamically identifying target audience appears to have considerable potential, especially in the rapidly growing area of enterprise social media information service.

An increasing number of users are inspired by enterprises to repost social media messages, which greatly contributes to the dissemination of such messages in an online social network. The purpose of this paper is to discover the repost patterns of users regarding enterprise social media messages to help enterprises improve information management abilities for social media.

This paper proposes a novel method to discover the repost patterns of users in enterprise social networking (ESN) at the macro-level through topic analysis. Specifically, it proposes the message-diversity metric to measure the latent topic diversity degree of the social media messages. Through this technique, the paper analyzes the message-diversity characteristics of the enterprise social media messages and then explores the repost patterns of users.

The experimental results show that a high repost rate is more prominent for the messages with diverse latent topics, where message-diversity is as high as 0.5.

The findings have great potential in several management areas, such as employing social media marketing, predicting popular messages, helping enterprises strengthen their online presence, and gathering more potential customers.

This study explores how the repost patterns of users in ESN can be determined through general macro-level behavior of users instead of their micro-level processes. The patterns can also lead to a deeper understanding of which contents can drive people to diffuse information. This study gives an important insight into the information behavior of social media users for enterprise management researchers.

It is widely known that fast-fashion retailers are struggling to keep up with consumer attention for quick responses within the fashion industry. With the advance of Internet and e-commerce, consumers prefer to purchase online. Online platform information has become an essential source for exploring consumer attention. However, there is often a mismatch between the information provided by retailers and the feedback received from consumers, leading to an imbalance between the supply side and demand side of online information. The purpose of this study is therefore to provide a unified approach to discover consumer attention from the design topic aspect by revealing the information imbalance between supply side and demand side.

To address the issue of online information imbalance and discover consumer attention, this study proposed an approach that focuses on the design topic perspective. The design topic is a collection of design elements that represent a clothing-design feature more comprehensively and accurately compared to a single design element. The proposed approach begins with generating design topics through topic modeling based on online information provided by retailers on e-commerce platforms. Two indicators, influence degree and attention degree, are then used to quantify the intensity of supply information and consumer attention related to design topics. Finally, design topic strategy diagrams are constructed to reveal information imbalance and discover consumer attention.

The experimental case demonstrates the existence of information imbalance, indicating that the intensity of supply information and consumer attention from the perspective of design topics is not uniform, although both follow the Pareto principle. The results of consumer attention distribution with heavy power-law tails are consistent with current research findings. This further demonstrates that the proposed approach is capable of discovering consumer attention in the design topic strategy diagrams.

The issue of information imbalance between retailers and consumers poses a challenge in keeping up with customer attention. The proposed approach offers a practical solution by visually identifying the symptoms of information imbalance and discovering consumer attention through design topic strategy diagrams. This approach provides fast-fashion retailers with a valuable reference to seize market opportunities, improve product design and adjust marketing or management strategies.

This study proposes a novel approach to disclose the issue of information imbalance between supply side and demand side and therefore to discover consumer attention from the perspective of design topics. In addition, guidelines for applying the proposed approach for fast-fashion marketing and management are presented.

The purpose of the study is to propose a normative approach for market segmentation, profile and monitoring using computing and information technology to analyze User-Generated Content (UGC).

The specific steps include performing a structural analysis of the UGC and extracting the base variables and values from it, generating a consumer characteristics matrix for segmenting process, and finally describing the segments' preferences, regional and dynamic characteristics. The authors verify the feasibility of the method with publicly available data. The external validity of the method is also tested through questionnaires and product regional sales data.

The authors apply the proposed methodology to analyze 53,526 UGCs in the New Energy Vehicle (NEV) market and classify consumers into four segments: Brand-Value Suitors (32%), Rational Consumers (21%), High-Quality Fanciers (26%) and Utility-driven Consumers (21%). The authors describe four segments' preferences, dynamic changes over the past six years and regional characteristics among China's top five sales cities. Then, the authors verify the external validity of the methodology through a questionnaire survey and actual NEV sales in China.

The proposed method enables companies to utilize computing and information technology to understand the market structure and grasp the dynamic trends of market segments, which assists them in developing R&D and marketing plans.

This study contributes to the research on UGC-based universal market segmentation methods. In addition, the proposed UGC structural analysis algorithm implements a more fine-grained data analysis.

Multinational enterprises (MNEs) play a dominant role in the international business (IB) literature. Traditionally, by far the majority of IB studies deal with issues at the micro level of the individual MNE, or at the meso level of a sample of individual MNEs in industries. This paper focuses on the impact of MNE behavior through foreign direct investment (FDI) on a country’s international trade, and vice versa. In so doing, this study responds to a recent plea for more macro‐level studies in IB into the effect of MNE behavior on the macroeconomic performance of countries as a whole, particularly developing and emerging economies. In the current study, we focus on the largest developing or emerging economy of all: China. Applying sophisticated econometric techniques, we unravel the causality and direction of FDI‐trade linkages for the Chinese economy in the 1980‐2003 period.

Based on media choice theories and real option theory, this study aims to explore the role of communication media portfolio in achieving collaborative innovation with suppliers.

Using data of the Study of Competitiveness, Technology and Firm Linkages 2002 collected by the World Bank and the Enterprise Survey Organization of the Chinese National Bureau of Statistics, this study employed logit model to test the hypotheses. Moreover, some robustness analyses were conducted.

This study suggests that media multiplicity increases the probability for a firm to achieve collaborative innovation with suppliers on the basis of real option theory. Furthermore, distance from the suppliers and relationship formality make media multiplicity further important in collaborative innovation with suppliers.

Through investing how communication media portfolio affecting collaborative innovation with suppliers and the contingency factors, this study complements existing studies just concentrating on supplier capabilities, relationships with suppliers and characteristics of supplier network. Moreover, this study contributes in the information system field by exploring the role of media portfolio rather than individual media.

This paper sets out to discuss white‐collar crime and fraud in China and to draw implications for Western businesses wishing to enter the Chinese market.

The paper provides examples of recent frauds committed in China and also provides a brief review of the literature. It traces the development of China's economy, describing China's modern‐day economy, and also looks at cultural issues and differences between Western and Chinese attitudes.

Western businesses planning to enter the Chinese market need to do their due diligence before committing resources. What works in Western society may not work in another culture, like China's. However, gaining an understanding of the culture and general way of life will go a long way towards laying the groundwork for success.

Additional focus should be placed on examining how cultural differences affect judgments and behaviors.

From a practical standpoint, the paper provides insights into possible areas of disagreement between employees from different cultures that can result from their divergent opinions about individuals' responsibility for fraudulent acts.

The purpose of this paper was to solve the shortage of carrying energy in probing robot and make full use of wind resources in the Antarctic expedition by designing a four-wheel land-yacht. Land-yacht is a new kind of mobile robot powered by the wind using a sail. The mathematical model and trajectory of the land-yacht are presented in this paper.

The mechanism analysis method and experimental modeling method are used to establish a dual-input and dual-output mathematical model for the motion of land-yacht. First, the land-yacht’s model structure is obtained by using mechanism analysis. Then, the models of steering gear, servomotors and force of wing sail are analyzed and validated. Finally, the motion of land-yacht is simulated according to the mathematical model.

The mathematical model is used to analyze linear motion and steering motion. Compared with the simulation results and the actual experimental tests, the feasibility and reliability of the proposed land-yacht modeling are verified. It can travel according to the given signal.

This land-yacht can be used in the Antarctic, outer planet or for harsh environment exploration.

A land-yacht is designed, and the contribution of this research is the development of a mathematical model for land-yacht robot. It provides a theoretical basis for analysis of the land-yacht’s motion.

Encouraging employees to bolster their performance in today's turbulent business environment is an important priority for all types of organizations. Even though few studies reported the impact of transformational leadership (TL) on job performance (JP), the role of mediators namely corporate social responsibility (CSR) in this relationship is not given due attention. The purpose of this paper is to assess the mediating role of CSR in the relationship between TL and JP in the Indian context.

Data from 306 full time employees working in the manufacturing industry in India were collected through an online survey. The manufacturing organizations were selected on the basis of their active participation in CSR activities and robustness of HR practices. Three structured questionnaires were used for eliciting data from the employees, and AMOS software was used for testing the validity of the hypothesized model. PROCESS macro was used for testing the mediating role of CSR.

TL impacted both JP and CSR. Additionally, CSR showed a positive relationship with JP of employees. The pivotal finding of the study is the partial mediation of CSR in the TL–JP relationship.

Based on neo-charismatic paradigm theory, TL theory, stakeholder theory and social identity theory, this paper enriches the literature by demonstrating the mediation mechanism driving TL and JP relationship.