Zaoli Yang

To effectively address challenges that stem from e-commerce, it is crucial to harness diverse review data from e-commerce platforms. These data support consumers in making informed purchase decisions and aid manufacturers in optimizing product attributes. Incorporating sentiment data from heterogeneous reviews across different time periods into a decision-making framework is a pivotal consideration in purchase decisions and product design. The goal of the study is to establish an online product decision support method grounded in consumer irrational behavior and segmented reviews over time. It aims to offer users reliable and consistent outcomes when making personalized purchase decisions. The probabilistic linguistic term set is employed to represent consumer sentiments with varying degrees of granularity across different time periods. Subsequently, stochastic sampling is utilized to simulate the decision-making process of individual consumers. Regret theory is then applied to analyze consumers' irrational psychological behavior. Building upon heterogeneous data gathered from e-commerce platforms, including review ratings, likes, and follow-up reviews, a multiperiod group decision approach based on maximum similarity and review helpfulness is proposed. This decision-making method is advanced through a decomposition-aggregation process, safeguarding against information distortion and ensuring result reliability. This method provides consumers with product selection solutions across the temporal dimension and serves as a theoretical compass for manufacturers and sellers seeking product enhancement and sales optimization.

The intelligent strategy of the new energy vehicle (NEV) industry has triggered the rapid prevalence of in-vehicle anthropomorphic artificial intelligence (AI) assistants. There is still a lack of clarity regarding NEV users' attitudes toward this cutting-edge technology and whether they receive a satisfactory intelligent service experience. To circumvent potential emerging technology resistance, in this article, we utilize text analysis techniques for the identification of AI interaction emotions, love and disgust (enablers and inhibitors) with significant influence on user satisfaction, and validates the improving role of multimodality on the effectiveness of anthropomorphic interaction. In addition, this study innovatively constructs a multidimensional corpus of modality × emotion, using structural topic modeling to uncover the constituent elements and real-time changes of love and disgust emotions in different modalities, from which development opportunities and improvement directions for AI anthropomorphic interaction technologies are identified. The findings provide new insights into the application of emotion analysis methods to improve users' intelligent service experience and provide a realistic reference for mitigating emerging technology resistance in the NEV industry.

The competitive landscape of multiple e-commerce platforms and the vast amount of product reviews associated with these platforms have supported both consumers' online shopping decision making and also served as a reference for product attribute performance improvement. This paper proposes a sentiment-driven fuzzy cloud multi-criteria model for online product ranking and performance to provide purchase recommendations. In this novel model, Bi-directional Long Short-Term Memory Network-Conditional Random Fields (BiLSTM-CRF), sentiment analysis, and K-means clustering are first integrated to mine product attributes and compute sentiment values based on reviews from various platforms. Next, considering the confidence of the sentiment value, the cloud model is combined with q-rung orthopair fuzzy sets to define the new concept of the q-rung orthopair fuzzy cloud (q-ROFC) and the interaction operational laws between q-ROFCs are given. The sentiment values of each product attribute from different platforms are cross-combined and transformed into a type of q-ROFC, while multiple interactive information matrices are established. To investigate the correlation among homogeneous attributes, the q-ROFC interaction weighted partitioned Maclaurin Symmetric mean operator is proposed. Finally, we provide real-world examples of online mobile phone ranking and attribute performance evaluation. The results show that our proposed method offers significant advantages in dealing with customer purchase decisions for online products and problems with performance direction identification. Managerial implications are discussed.

The mechanism of the impact of inter-firm social networks on innovation capabilities has attracted much research from both theoretical and empirical perspectives. However, as a special emerged and developing complex production system, how the scenario factors affect the relationship between these variables has not yet been analyzed. This study identified several scenario factors which can affect the firm’s technological innovation capabilities. Take the manufacturing scenario in China as an example, combined with the need for firms’ ambidexterity innovation and green innovation capability, a multi-objective simulation model is constructed. Past empirical analysis results on the relationship between inter-firm social network factors and innovation capabilities are used in the model. In addition, a numerical analysis was conducted using data from the Chinese auto manufacturing industry. The results of the simulation model led to several optimization strategies for firms that are in a dilemma of development in the manufacturing scenario.

This article introduces a new model, the catastrophe model of intellectual property cooperation behavior. The purpose of the model is to analyze the evolutionary track of intellectual property cooperation behavior. After providing a general of catastrophe mechanism of intellectual property cooperation behavior and introducing stochastic catastrophe theory, this article offers a catastrophe model of intellectual property cooperation behavior. And then, based on the survey data of high-tech enterprises, the model parameters were given by introducing the qualitative simulation algorithm. The results demonstrate that intellectual property cooperation is composed of a cooperation strategic planning stage, cooperation system formation stage, cooperation system working stage, and cooperation profit distribution stage. Under the influence of control variables, the intellectual property cooperation behavior will appear catastrophic near the set of bifurcation points. Most previous studies on intellectual property cooperation have disregarded the characteristic of the sudden changes in cooperation behavior. Therefore, this article offers an integrated catastrophe model and explains the nature of intellectual property cooperation behavior.

In the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), a series of natural environmental, economic, and social issues have emerged sequentially in the process of rapid economic and social development. Therefore, for the sustainable development of the GBA, how to closely integrate nature protection with economic and social development to improve the sustainable development level of the social-economic-natural compound ecosystem, and realize the coordinated development of the system is particularly important. Based on the perspective of complex network and the theory of compound ecosystem, this study proposes a set of sustainable development evaluation model based on complex network modeling to evaluate the sustainable development level of compound ecosystem in GBA from 2014 to 2018, and further analyze the coupling coordination degree. The major findings include: 1) For the sustainable development in the GBA, the development of the natural subsystem is an important foundation, and the synchronous development of the social and economic subsystems are the main driving force. 2) The sustainable development level in the GBA shows an overall steady upward trend; the average level of the compound ecosystem’s coupling coordination development is in a “good” state, and it shows an evident upward trend. 3) Whether it is within the GBA or the GBA and its surrounding regions, there are problems of unbalanced and insufficient regional development. Policy recommendations include increasing the emphasis on the sustainable development of the natural subsystem, promoting the coordinated development of the economic, social, and natural subsystems, and promoting the balanced development of cities within the GBA, as well as the GBA and surrounding regions.