Information Technology and Management最新文献

E-commerce livestreaming innovatively transforms interactions between sellers and consumers. Customers can participate into multiple conversations by watching live video and exchanging danmaku messages simultaneously, which is known as the multicommunicating phenomenon. Although previous studies found the negative effect of multicommunicating on customer engagement behavior, in practice many platforms have created the multicommunicating context by allowing customers to communicate with different people at the same time. The inconsistency between theory and practice needs more evidence to verify the complicated effects of multicommunicating. To answer the question, we collected 476 questionnaires as data and applied structural equation model method to test the hypothesis. The research findings revealed that multicommunicating can positively impact customer engagement through social presence and negatively impact customer engagement through information overload; communicating consistency as communicating feature and online interaction propensity as customer feature can moderate the impacts of multicommunicating. These findings contribute to multicommunicating theory, which only focus on the negative effect of multicommunicating but ignore the positive effect, and can offer some practical suggestions to platforms and anchors.

In the era of innovation, the application of open innovation is gradually becoming the main source of innovation. This paper investigates how degrees of variation in the depth and breadth of open innovation affect firms’ innovation performance, in addition to the mechanism of the activity in the knowledge field and the chain mediating role of knowledge transfer in this process. This paper collects data from 283 Chinese firms using a questionnaire survey commissioned by Chinese industry associations, heads of relevant listed companies, and the Questionnaire Star platform, and develops a chain mediation model to test the hypotheses. The analysis results demonstrate that both the breadth and depth of open innovation have a significant positive impact on firms’ innovation performance. Additionally, knowledge field activity and knowledge transfer assume the role of chain mediators in this process. This paper investigates the different effects of the depth and breadth of open innovation on innovation performance, further analyzing the mechanism of the effect on innovation performance under the influence of chain mediation of knowledge field activity and knowledge transfer, providing valuable insights for both innovation management research and practice.

In a complex competitive market environment, service enterprises should focus on the dynamics of consumer needs, integrate resources, and adjust their strategies to adapt to market changes. SWOT analysis is a tool that supports strategic planning and decision-making, it relies on the insight and analysis of managers. Therefore, it suffers from subjectivity and a lack of reliable inputs from the customers’ perspective. In addition, Strengths, weaknesses, opportunities and threats (SWOT) analysis cannot track the factors affecting enterprise development in real time and quantitatively determine the degree of influence of these factors. Therefore, managers are unable to make timely strategic adjustments. Online reviews that reflect consumer needs provide a new basis for dynamically formulating strategies to compensate for the shortcomings of traditional SWOT model. Therefore, this study proposes a SWOT model based on online reviews, which takes feature extraction, revised importance-performance analysis (IPA), and SWOT analysis as the framework. Through text mining and sentiment analysis methods, we construct satisfaction and importance indicators, and determine the priority of feature improvement based on opportunity algorithms, the framework can also perform dynamic SWOT analysis. The case studies of the 7Days Inn and Home Inn show that the analysis model can integrate consumer opinions, conduct a fine-grained quantitative analysis of features, and provide a basis for dynamic adjustments to corporate strategies based on horizontal and vertical comparisons between enterprises. The model is realistic and operational.

The monetary effects of online reviews motivate firms to manipulate such reviews, and electronic marketplaces then adopt online review filtering systems to combat manipulation. We develop an analytical model to explore the role of a filtering system for a monopoly firm, electronic marketplaces and consumer surplus in the monopoly context and then extend it to the symmetrical competition context to explore whether competition changes the role of the filtering system. The results show that the existence of such a filtering system strengthens the possibility of manipulation by the monopoly firm when the intelligence of the filtering system is relatively low. However, in the competitive context, whether the existence of such a filtering system strengthens the possibility of manipulation by both firms relates to the difference between the total consumer base with manipulation under no filtering system and that under the filtering system. We also find that in the monopoly context, the electronic marketplace will adopt the filtering system only when the intelligence of the filtering system is relatively low and the unit misfit cost is moderate. However, in the competitive context, the intelligence of the filtering system is irrelevant to whether the electronic marketplace adopts the filtering system. Finally, the adoption of the filtering system always benefits consumers in both the monopoly and competing contexts.

In contrast to traditional e-commerce platforms, social commerce platforms offer users opportunities to communicate and profit, instead of merely rating and purchasing products. This study examines a sample of 1859 user-generated (UG) e-books from a popular Chinese social commerce website to identify the factors that impact consumers to purchase UG products. The network analysis results reveal that UG products on social commerce platforms exhibit varying sales patterns and form three distinct communities, comprising 1393, 291, and 175 e-books respectively. By employing the Elaboration Likelihood Model (ELM), this study examines the impact of certain variables on UG product sales within three communities. These variables encompass central route factors such as product rating and rating numbers, peripheral route factors like follower adoption, and the elaboration likelihood encompassing ability (the proportion of experienced purchasers) and motivation (the proportion of purchased transactions, serving as an indicator of the gifted marketing strategies). The findings of this study have implications for the design and improvement of UG product marketing in social commerce platforms.