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This study explores the link between additional reviews, credibility, and consumers’ online purchasing behavior.

We employ a 2 × 2 between-subjects design to measure subjects’ purchasing behavior with versus without additional reviews and with important versus non-important attributes. A total of 529 valid questionnaires are collected from university students across 30 Chinese provinces.

The addition of negative reviews to a positive initial review enhances consumers’ perceived credibility of the reviewer and the overall review content. This effect is positively moderated by the attribute importance in additional reviews. Moreover, we find that as the time interval increases, consumers’ perceived credibility gradually increases but eventually decreases after reaching a certain threshold. In addition, the attribute importance in additional reviews negatively moderates the impact of perceived credibility on consumer purchasing behavior.

Existing studies on first and subsequent reviews mainly focus on the difference in perceived usefulness between the two. They do not examine how additional reviews affect potential customers’ perceived credibility and their purchase decision-making. This study bridges the gap between the word-of-mouth literature and marketing practices.

With the global economic slowdown in 2023, most universities in the central and western regions of China may face the problem of shortage of government financial funding, which is directly related to the development of science and technology of the universities. With the support of the local government, most of the ordinary universities have shifted attention to the transfer and transformation of intellectual property based on school-enterprise cooperation, hoping to seek more commercialization income as an extra source of income. Therefore, this paper aimed to study the current situation of university intellectual property, i.e. the reserve and distribution of transferable patents, discipline distribution of patents, and regional cooperation of university patents.

A patent database of 10 key universities in Henan Province of China from 2012 to 2021 was established. The evaluation indicator model by the Entropy method was conducted to reveal the interaction mechanism between quantity indicators, quality indicators, and value indicators. Based on the data analysis, the development direction of the discipline construction and school-enterprise cooperation for local universities was clear.

The findings indicated that the number of patent applications from ten key universities in Henan Province has been increasing rapidly over the years. The trend for authorized invention patents has remained relatively stable. Compared with the patent applications and authorizations, the growth of transferable patents was notably slow. The significance of strategic layout of dominant disciplines and related high-value patents was not appreciated enough by Chinese government and universities. There was a large difference of dominant disciplines between 10 key universities, and the patent level of each university was directly proportional to the number of dominant disciplines. The university patent level heavily relied on the researchers' contributions and the distribution mechanism of scientific research resources within the university. Guangdong Province and the Yangtze River Delta of China, being economically developed regions, exhibited the most active engagement in patent technology cooperation. Conversely, the central and western regions displayed relatively lower participation in high-value patent research and development.

This study can provide a unique perspective to understand and solve the financial bottleneck problem of ordinary universities in the central and western regions of China. The discipline construction and school-enterprise cooperation are just one of the existing schemes, but it still cannot solve the financial problems faced by local universities in China towards the government.

The findings of this study can serve as a foundation for further investigation into policies aimed at improving the financial problems of ordinary universities in the central and western regions of China.

As an important attempt, the study tried to focus the financial problem of universities in the central and western regions of China based on the evaluation of the current situation of university intellectual property. This research findings are of great value in finding optimal layout between university patents, disciplines and school-enterprise cooperation.

The study aimed to analyze the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong Province.

A conceptual model of the influence of network embeddedness on the innovation performance of high-tech enterprises in Guangdong province is established, which takes the business model as the mediating variable and political association as the moderating variable. Multivariate statistical analysis and the MacKinnon confidence interval method were used to analyze 418 questionnaires.

The results show that both relational embeddedness and structural embeddedness have significant positive effects on the innovation performance of high-tech enterprises in Guangdong Province. The business model has a partial mediating effect between relationship embeddedness, structure embeddedness, and innovation performance of high-tech enterprises in Guangdong Province, respectively. Political relevance has a significant negative moderating effect on the relationship between the relationship embeddedness and innovation performance of high-tech enterprises in Guangdong Province, but the moderating effect on structural embeddedness and innovation performance of high-tech enterprises in Guangdong province has not been verified.

The study of this paper also has some shortcomings: very few data research samples exist; the external factors affecting the performance of high-tech enterprises in Guangdong Province need to be further refined. The research scale needs further improvement.

In this paper, embedding theory, transaction cost theory, resource dependence theory, rent-seeking theory, new institution theory and uncertainty management theory were integrated by system attempt to reveal the mediating and moderating roles of business model and political relevance, respectively, between network embeddedness behavior and entrepreneurial innovation performance of high-tech enterprises. The research conclusions expand the relevant research in the field of entrepreneurial innovation. At the same time, the research results provide theoretical support and reference for the innovative growth of high-tech enterprises and government behavior decision-making in Guangdong province.

Network embeddedness will have a profound impact on the entrepreneurial innovation performance of high-tech enterprises. Existing research has overlooked discussing this issue from the perspective of internal and external influencing factors within the enterprise. Therefore, this study addresses this issue by (1) introducing the business model as the mediating variable from an internal perspective of the enterprise, (2) introducing political association as the moderating variable from an external perspective of the enterprise and (3) 418 original questionnaires of high-tech enterprises in Guangdong Province were used to test the effect of the study variables.

This paper aims to develop a method based on artificial intelligence capable of predicting the due date (DD) of job shops in real-time, aiming to assist in the decision-making process of industries.

This paper chooses to use the methodological approach Design Science Research (DSR). The DSR aims to build solutions based on technology to solve relevant issues, where its research results from precise methods in the evaluation and construction of the model. The steps of the DSR are identification of the problem and motivation, definition of the solution’s objectives, design and development, demonstration, evaluation of the solution and the communication of results.

Along with this work, it is possible to verify that the proposed method allows greater accuracy in the DD definition forecasts when compared to conventional calculations.

Some limitations of this study can be pointed. It is possible to mention questions related to the tasks to be informed by users, as they could lead to problems in the performance of the artifact as the input data may not be correctly posted due to the misunderstanding of the question by part of the users.

The proposed artifact is a method capable of contributing to the development of the manufacturing industry to improve the forecast of manufacturing dates, assisting in making decisions related to production planning. The use of real production data contributed to creating, demonstrating and evaluating the artifact. This approach was important for developing the method allowing more reliability.