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The uncertainty of consumers' perceived value makes online education enterprises face great challenge in developing the pricing strategy. So the purpose of this paper is to research the pricing strategies of online education products by considering knowledge consumers' characteristics.

Considering consumer matching degree and price comparison, this study establishes the utility functions of consumers in normal sales period and discount selling period. On this basis, the research builds pricing models of the online education enterprise under the strategy of price undertaking and intertemporal pricing strategy. It further discusses the impact of consumer matching degree, consumer price sensitivity and different types of consumers on the product price and profit of online education enterprises, and reveals the optimal pricing strategy of the enterprise.

Consumer matching degree and price sensitivity coefficient have positive effects on product price and enterprise profit, but they have different effects on product demand; there are differences in the perceived value of the three types of consumers, and matching consumers are the optimal consumer group; the intertemporal pricing strategy is better than the strategy of price undertaking only when the price sensitivity coefficient is greater than a critical value.

This study enriches the literature on the pricing model of online education products and owns a practical significance to guide the online enterprise to make marketing strategies to increase profit.

Selecting suitable and competent partners is an important prerequisite to improve the performance of collaborative product innovation (CPI). The purpose of this paper is to propose an integrated multi-criteria approach and a decision optimization model of partner selection for CPI from the perspective of knowledge collaboration.

First, the criteria for partner selection are presented, considering comprehensively the knowledge matching degree of the candidates, the knowledge collaborative performance among the candidates, and the overall expected revenue of the CPI alliance. Then, a quantitative method based on the vector space model and the synergetic matrix method is proposed to obtain a comprehensive performance of candidates. Furthermore, a multi-objective optimization model is developed to select desirable partners. Considering the model is a NP-hard problem, a non-dominated sorting genetic algorithm II is developed to solve the multi-objective optimization model of partner selection.

A real case is analyzed to verify the feasibility and validity of the proposed model. The findings show that the proposed model can efficiently select excellent partners with the desired comprehensive attributes for the formation of a CPI alliance.

Theoretically, a novel method and approach to partner selection for CPI alliances from a knowledge collaboration perspective is proposed in this study. In practice, this paper also provides companies with a decision support and reference for partner selection in CPI alliances establishment.

The purpose of the paper is to examine the coevolutionary dynamics between multistage overseas mergers and acquisitions (M&A) integration and knowledge network reconfiguration and the impact of this coevolution on industrial technology innovation.

This paper builds a coevolution analysis framework in stages and constructs structural equation models for empirical tests using the Chinese technology-sourcing overseas M&A events that occurred from 2001 to 2012.

Overseas M&A integration and knowledge network reconfiguration are in a coevolutionary relationship, driving industrial technology innovation. The acquirer adopts initial integration degree that matches the resource relatedness between the acquiring and acquired parties, promoting initial industrial technology innovation through initial knowledge network reconfiguration. Initial knowledge network reconfiguration will feed back to the M&A integration decision in the mid-to-late stage through increasing knowledge similarity and narrowing network position difference. The higher the improvement of mid-to-late integration degree, the more it can drive mid-to-late industrial technology innovation through mid-to-late knowledge network reconfiguration.

Future research can accurately classify overseas M&A integration stages through case tracking and explore other network attributes.

Practical guidelines are provided for managers on how to implement a multistage overseas M&A integration strategy, optimize knowledge network reconfiguration and promote industrial technology innovation. Significant practical implications are presented, especially in academia, society and quality of life.

Different from the previous research considering M&A integration as a single-stage decision, this paper emphasizes the dynamics of the M&A integration process and explores the coevolution mechanism of multistage overseas M&A integration and knowledge network reconfiguration.

The reasons for turnover intention of millennial employees show intergenerational differences and gradually have become a hot topic in the field of management. From the perspective of knowledge management, this paper aims to explore the mechanism of individual knowledge distance on the turnover intention of millennial employees. Based on the social comparison theory and the person-environment fit theory, this study discusses the moderation role of individual perception of organizational innovation climate in this model by integrating social and cultural factors into the cognitive behavior model, and empirically tests the impact of individual knowledge distance on the turnover intention of millennial employees.

In this paper, 585 valid questionnaires were collected from the millennial employees, and the moderated intermediary model was empirically tested by using hierarchical regression analysis and conditional process analysis.

The results show that the knowledge distance between individuals has a significant positive impact on the turnover intention of the millennial employees; the ability-based Mianzi stress has a significant positive impact on the turnover intention of the millennial employees; in organizations with a high innovation climate perception, the ability-based Mianzi stress partially mediates the positive impact of the knowledge distance between individuals on the turnover intention; the organizational innovation climate perception positively moderates the influence of individual knowledge distance on ability-based Mianzi stress, and the boundary condition of ability-based Mianzi stress is discussed, which shows that knowledge distance can induce ability-based Mianzi stress only when individual are able to perceive organizational innovation climate.

This study explores the influence mechanism between knowledge distance and employee turnover intention from the perspective of Mianzi, which is a supplement and enrichment to the study of millennial employees’ turnover intention. It enlightens managers to take effective measures to reduce the negative impact of knowledge difference among millennial employees in the process of actively creating innovation climate in the organization. Because Western countries also have face problems, the conclusion of this study is also of practical significance to managers in Western countries.

With the advent of the Digital 2.0 era, online doctor–patient (D–P) interaction has become increasingly popular. However, due to the fact that doctors use their fragmented time to serve patients, online D–P interaction inevitably has some problems, such as the lack of pertinence in the reply content and doctors' relative unfamiliarity with their individual patients. Therefore, the purpose of this study is to excavate whether potential D–P social ties and D–P knowledge ties accentuate or attenuate the influence of patient selection (online and offline selection).

The authors used the methods of text mining and empirical analysis on the structured and unstructured data of an online consultation platform in China to examine the research hypotheses.

The findings illustrate that the potential D–P social ties increase the influence on patient selection, as do the potential D–P knowledge ties. Specifically, the effect of social ties on patient selection is positively moderated by patient health literacy. Conversely, health literacy weakens the link between knowledge ties and patient selection. In addition, the doctor's title weakens the influence of social ties on patient selection, in contrast to knowledge ties (partially).

This study provides guidance for doctors and patients on how to communicate effectively and alleviate tension within D–P relationships. The study’s findings have both theoretical and practical implications for both doctors' and online platforms' decision-making.

This study is aimed at making an inspection of the effects of collaborative innovation network characteristics on firm innovation performance, and the intermediary roles of knowledge transfer efficiency is taken into account.

This study used a convenient sampling method to obtain population and samples. Using data obtained by publishing online and paper questionnaires, and using on-site interviews in Anhui Province in the Yangtze River Delta region of China, descriptive analysis, regression analysis and correlation analysis are utilized to study the direct influence of collaborative innovation network characteristics on knowledge transfer efficiency as well as firm innovation performance, and the intermediary roles of knowledge transfer efficiency on firm innovation performance, respectively. In this study, 3,000 questionnaires were distributed to the employees of enterprises engaged in research and development (R&D) activities, of which 2,560 were valid. With the help of SPSS24.0 software, the reliability and validity of the questionnaire was analyzed.

The results are indicative of that network centrality and relationship strength positively affect knowledge transfer efficiency and firm innovation performance. Nevertheless, network scale has no significant correlation with knowledge transfer efficiency and enterprise innovation performance. In addition, knowledge transfer efficiency is an intermediary between collaborative innovation network characteristics and enterprise innovation performance, and positively affects enterprise innovation performance, which demonstrated that managers should take advantage of collaborative innovation network characteristics to elevate knowledge transfer efficiency because well-realized transferals of knowledge can help accelerate the coordination of resources in knowledge, and finally bring about the advancement of firm's innovation abilities and performance.

There are few previous studies that fully examined the relationships among collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. This paper developed previous researches on the relationships between collaborative innovation network characteristics, knowledge transfer efficiency and firm innovation performance. The mediation of knowledge transfer efficiency on the relationship between collaborative innovation network characteristics and firm innovation performance is analyzed. Further, studies on collaborative innovation network characteristics using data obtained from employees engaged in R&D activities are very limited in the literature. On account of that, the findings in this study may make sense to the innovation ability of innovative enterprise and expand the literature in the field of enterprise strategic management and knowledge management.

This analysis shows that collaborative innovation network characteristics have both positive and negative effects on firm innovation performance. Therefore, business managers should pay attention to their position in the collaborative innovation network and maintain the relationship strength with other innovation subjects. Special consideration should be given to the knowledge transfer of innovative enterprises, so as to improve firm innovation performance practically.

The study may provide additional understandings for researchers, government managers, universities and enterprises with regard to strategic management from the visual angle of innovation ecosystems. It is instrumental in the exploration of the mechanisms enabling firm innovation performance.

The purpose of this article is to examine matching in the graduate labour market (GLM) in order to understand how expansion of higher education is perceived and translated in practice.

The article uses meritocracy and credentialism as frames of reference to explain the role of educational certification in systems of social structuring. Correspondingly, qualifications may function as signals, screens or proxies. Qualitative evidence, drawing on 40 interviews with graduates, employers and educators gives insights on access requirements, recruitment and selection and transfer of knowledge and skills, in three graduate occupations: chartered accountants; active schools co‐ordinators; and risk managers.

Findings suggest that expanding graduate numbers has produced altered patterns of closure. Employers use the availability of relevant degrees to limit applications, define jurisdictional boundaries and exclude the less, or inappropriately qualified. Yet correspondence between degree and occupation cannot necessarily be read off by a connected degree.

Closer connections between degree and occupation imply labour market segmentation although this requires further evidence in other occupations.

Supply‐side policy interventions are countered by strategic use of graduates. The paper explores issues of relevance to policymakers, employers, educators and graduates and will be of interest to those in the field.

Consulting experts is an effective way to utilize tacit resource. The purpose of the paper is to optimize the matching between panels of experts and groups of demanders to improve the efficiency of tacit knowledge sharing.

Experts and demanders express preferences using linguistic terms. The estimate method based on trust is developed to get missing ratings. Weights of demanders are determined and knowledge needs are identified. Three kinds of satisfaction are measured based on grey relational analysis. To maximize satisfaction of experts and demanders and safeguard meetings of knowledge needs as well as the workload of experts, the optimization model is constructed and the solution is optimal matching results.

The presented approach not only optimizes the matching between demanders and experts but also sets up a panel of experts in case that knowledge needs exceed a single expert’s capacity.

The approach expands research works of methods for tacit knowledge sharing. The continuous updating of matching results and the processing of the data with mixing formats need to be studied further.

The presented approach acts as a valuable reference for the development of knowledge management systems. It can be used in any scene that needs the match between experts and demanders.

The approach provides a new way of helping demanders to find appropriate experts. Both experts’ and demanders’ preferences are considered. A panel of experts is set up when needed. Expert resources are utilized more efficiently and knowledge needs are met more comprehensively.

The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience.

By integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed.

By fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components.

The process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.

Over the past decade, the cost of product development has increased drastically, and this is due to the inability of most enterprises to locate suitable and optimal collaborators for knowledge sharing. Nevertheless, knowledge sharing is a mechanism that helps people find the best collaborators with relevant knowledge. Hence, a new approach for locating optimal collaborators with relevant knowledge is needed, which could help enterprise in reducing cost and time in a knowledge-sharing environment. The paper aims to discuss these issues.

One unique challenge in the domain of knowledge sharing is that collaborators do not possess the same number of events resident in the knowledge available for sharing. In this paper, the authors present a new approach for locating optimal collaborators in knowledge-sharing environment using the combinatorial algorithm (CA-KSE).

The proposed pattern-matching approach implemented in Java is considered efficient for solving the issue peculiar to collaboration in knowledge-sharing domain. The authors benchmarked the proposed approach with its semi-global pairwise alignment and global alignment counterparts through scores comparison and the receiver operating characteristic curve. The results obtained from the comparisons showed that CA-KSE is a perfect test having an area under curve of 0.9659, compared to the other approaches.

The paper has proposed an efficient algorithm, which is considered better than related methods, for matching several collaborators (more than two) in KS environment. The method could be deployed in medical field for gene analysis, software organizations for distributed development and academics for knowledge sharing.

One sign of strength of this approach, compared to most sequence alignment approaches that can only match two collaborators at a time, is that it can match several collaborators at a faster rate.