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As a standard source of capital for entrepreneurs, crowdfunding has recently gained wide attention in business and academia. With scientific endorsement, some research is conducted to explore the antecedents of online crowdfunding success. The factors that can influence the backers’ investment which is the key to success are information from prior backers’ and creators’ behaviors. Based on the signaling theory, the purpose of this paper is to systematically investigate the dynamic influences and interaction effects of signals with different forms (action-based or opinion-based signals) and sources (creator-sourced or backer-sourced signals) on backers’ investment behaviors over a project-funding cycle.

A panel data set of 3,010 projects with 640,625 transaction records from April 28, 2013 to September 31, 2017 is collected from a famous online crowdfunding platform – Zhongchou.cn in China and the negative binomial panel data model with fixed effect is used to obtain our empirical results.

The findings demonstrate that the work of different signals is significantly effective at the early stage of a project and decreases with time. Furthermore, our results show that there are both synergistic effect and substitution effect among different signals. Specifically, the direction of interaction effect depends on the forms of signals and the backers’ sensitivity toward that signal, and the interaction effects are also dynamic.

This paper has shed light on the roles of different signal types and their interactions in influencing funding behavior over a project-funding cycle, enriched the literature on crowdfunding and provided both theoretical and practical implications.

area E-Business; Corporate Strategy; Strategic Management; Operation Management.

level/applicability Senior undergraduate; MBA; EMBA.

overview After development for 10 years, JD was now China’s second largest business-to-customer (B2C) e-retailer and the largest in self-operated sector. It was September 2015 when Liu Qiangdong was deciding whether to persist with JD’s self-operated model and the heavy investment in the self-built logistics system. JD’s business model had been functioning well. However, as JD grew bigger and bigger, it became too expensive to expand its logistics system. JD had not made a profit since it raised funds from investors. Liu had to come up with a good proposal before the next monthly meeting to convince them that JD would finally overtake its biggest rival, Alibaba which ran on a different business model. In addition, JD was exploiting the rural and the global markets, as well as a new business in internet finance. Facing challenges and dilemmas, should JD persist with its model? How could Liu align short-term profitability with long-run development? How could JD overcome attacks from Alibaba and other competitors?

learning outcomes This case is appropriate for courses in e-business and strategy, particularly those with a strong focus on doing e-business in emerging markets (e.g. China). After studying the case, students should be able to: understand the e-commerce market in China; understand business models and key strategies of e-retailers; identify and analyse the pros and cons of the self-operated business model and self-built logistics system in e-commerce; learn how to evaluate performance, strategies and business models of e-commerce companies; and extract key trends in the market and compare different strategies.

materials Teaching notes are available for educators only. Please contact your library to gain login details or email support@emeraldinsight.com to request teaching notes.

CSS 11: Strategy.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

The purpose of this paper is to present the state-of-the-art E-commerce logistics in supply chain management by investigating worldwide implementations and corresponding models together with supporting techniques via furniture industry.

Typical E-commerce logistics companies from North America, Europe, and Asia Pacific are comprehensively investigated so as to get the lessons and insights from these practices.

Future technologies like Internet of Things, Big Data Analytics, and Cloud Computing would be possibly adopted to enhance the E-commerce logistics in terms of system level, operational level, and decision-making level that may be real time and intelligent in the next decade.

This paper takes the furniture industry for example to illustrate the E-commerce logistics and supply chain management (LSCM). Other industries like electronic appliance industry are not considered.

Opportunities and future perspectives are summarized from practical implementations so that interested parties like E-commerce and logistics companies are able to get some guidance when they are contemplating the business.

E-commerce is booming with the development of new business models and will be continuously boosted in the near future. With large number of enterprises carrying out E-commerce, logistics has been largely influenced.

Insights and lessons from this paper are significant for academia and practitioners for considering E-commerce LSCM.

Internet + and Electronic Business in China is a comprehensive resource that provides insight and analysis into E-commerce in China and how it has revolutionized and continues to revolutionize business and society. Split into four distinct sections, the book first lays out the theoretical foundations and fundamental concepts of E-Business before moving on to look at internet+ innovation models and their applications in different industries such as agriculture, finance and commerce. The book then provides a comprehensive analysis of E-business platforms and their applications in China before finishing with four comprehensive case studies of major E-business projects, providing readers with successful examples of implementing E-Business entrepreneurship projects.

Internet + and Electronic Business in China is a comprehensive resource that provides insights and analysis into how E-commerce has revolutionized and continues to revolutionize business and society in China.

Because online shopping is risky, there is a strong need to develop better presentation of online reviews, which may reduce the perceived risk and create more pleasurable shopping experiences. To test the impact of online reviews’ sentiment polarity presentation, the purpose of this paper is to adopt a scenario experiment to study consumers’ decision-making process under the two scenarios of mixed presentation and classified presentation of online reviews collected from Jingdong.com in China: focusing on the comparative analysis on the differences of the consumers’ perceived risk, purchase intention and purchase delay, and further studying the interaction effect of involvement and online reviews’ sentiment polarity presentation.

This paper employed a 2×2 factorial experiment to test the hypothesis. The experimental design is divided into four groups: 2 (online reviews’ sentiment polarity presentation: mixed presentation vs classified presentation) × 2 (involvement: low vs high), each of which contains 90 samples. Through the data analysis, the main effect, mediation effect and moderating effect were examined.

The results show that compared with mixed presentation, classified presentation can reduce purchase intention and increase purchase delay due to the existence of loss aversion and availability heuristic. Furthermore, the paper also confirms that there is a significant interaction effect between involvement and online reviews’ sentiment polarity presentation.

The existing research pays less attention to the impact of online reviews presentation on consumers’ decision making, especially the lack of discussion on the interaction effect between involvement and online reviews presentation. For this reason, this paper proposes a problem, which concerns whether mixed presentation and classified presentation of online reviews will affect consumers’ decision making differently.

Building on the theory of resource-based view (RBV), this paper is determined to explore the key drivers that drive platform ecosystem adoption by small businesses and mediation mechanisms that facilitate the translation of these drivers into improved firm financial and nonfinancial performance.

In this study, structural equation modeling is used to analyze the data. A survey questionnaire was taken from 430 small businesses operating their businesses on various digital platform ecosystems in China to investigate the links between parameters by testing hypotheses. Digital startups operating their businesses on popular Chinese platform ecosystems, including Alibaba, Taobao, Jingdong, Maituan and HelloChe, were chosen.

The finding deciphers a nuanced interplay of the adoption drivers, with innovation capability emerging as a mediation mechanism translating these drivers into improved financial and non-financial performance.

The acknowledgment of potential drawbacks, such as the focus on specific drivers of platform ecosystem adoption, highlights the need for future research to explore additional factors that may influence adoption decisions. By examining institutional factors, market conditions or external shocks like the COVID-19 pandemic, researchers can provide a more comprehensive understanding of the complexities surrounding platform ecosystem dynamics and offer insights into adaptive strategies for businesses facing uncertainty.

The outcome benefits policymakers and ecosystem designers by creating and overseeing platform ecosystems that support the highlighted drivers. This study further serves as a roadmap for both platform owners and prospective small enterprises as they map their path toward the digital frontier.

The findings from the research indicate that small enterprises that embrace platform ecosystems can experience improved financial and non-financial performance, which in turn promotes economic development and the generation of jobs. By utilizing innovative strategies and maximizing their strategic advantages, these enterprises can not only prosper but also make significant contributions to community development and help alleviate joblessness. This highlights the significance of assisting with the incorporation of digital technology in small businesses to achieve wider societal advantages.

Research originality lies in bridging the gap between strategic inputs and measurable outcomes, stressing the vital function of a firm’s innovation in turning ecosystem-driven opportunities into enhanced performance. This means the pivotal role of this study lies in exploring platform ecosystem adoption drivers based on the theory of RBV and the way innovation capability of platform ecosystems facilitates the translation of these drivers into improved financial and nonfinancial performance.

It has always been a hot topic for online retailers to obtain consumers’ product evaluations from massive online reviews. In the process of online shopping, there is no face-to-face interaction between online retailers and customers. After collecting online reviews left by customers, online retailers are eager to acquire answers to some questions. For example, which product attributes will attract consumers? Or which step brings a better experience to consumers during the process of shopping? This paper aims to associate the latent Dirichlet allocation (LDA) model with the consumers’ attitude and provides a method to calculate the numerical measure of consumers’ product evaluation expressed in each word.

First, all possible pairs of reviews are organized as a document to build the corpus. After that, latent topics of the traditional LDA model noted as the standard LDA model, are separated into shared and differential topics. Then, the authors associate the model with consumers’ attitudes toward each review which is distinguished as positive review and non-positive review. The product evaluation reflected in consumers’ binary attitude is expanded to each word that appeared in the corpus. Finally, a variational optimization is introduced to calculate parameters mentioned in the expanded LDA model.

The experiment’s result illustrates that the LDA model in the research noted as an expanded LDA model, can successfully assign sufficient probability with words related to products attributes or consumers’ product evaluation. Compared with the standard LDA model, the expanded model intended to assign higher probability with words, which have a higher ranking within each topic. Besides, the expanded model also has higher precision on the prediction set, which shows that breaking down the topics into two categories fits better on the data set than the standard LDA model. The product evaluation of each word is calculated by the expanded model and depicted at the end of the experiment.

This research provides a new method to calculate consumers’ product evaluation from reviews in the level of words. Words may be used to describe product attributes or consumers’ experiences in reviews. Assigning words with numerical measures can analyze consumers’ products evaluation quantitatively. Besides, words are labeled themselves, they can also be ranked if a numerical measure is given. Online retailers can benefit from the result for label choosing, advertising or product recommendation.

The purpose of this paper is to develop a novel recommendation method using online reviews with emotional preferences for facilitating online purchase decisions. This leads to better use of information-rich online reviews for providing users with personalized recommendations.

A novel method is developed for producing personalized recommendations in online purchase decision-making. Such a method fuses the belief structure and the Shapley function together to effectively deal with the emotional preferences in online reviews and adequately tackle the interaction existent between product criteria with the use of a modified combination rule for making better online recommendations for making online purchase decisions.

An example is presented for demonstrating the applicability of the method for facilitating online purchase. The results show that the recommendation using the proposed method can effectively improve customer satisfaction with better purchase decisions.

The proposed method can better utilize online reviews for satisfying personalized needs of consumers. The use of such a method can optimize interface design, refine customer needs, reduce recommendation errors and provide personalized recommendations.

The proposed method adequately considers the characteristics of online reviews and the personalized needs of customers for providing customers with appropriate recommendations. It can help businesses better manage online reviews for improving customer satisfaction and create greater value for both businesses and customers.