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Article

Jie Jian, Milin Wang, Lvcheng Li, Jiafu Su and Tianxiang Huang

Selecting suitable and competent partners is an important prerequisite to improve the performance of collaborative product innovation (CPI). The purpose of this paper is…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Originality/value

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.

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Article

Feiqiong Chen, Jieru Zhu and Wenjing Wang

The purpose of the paper is to examine the coevolutionary dynamics between multistage overseas mergers and acquisitions (M&A) integration and knowledge network…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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

Practical implications

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.

Originality/value

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.

Details

Journal of Business & Industrial Marketing, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0885-8624

Keywords

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Article

Shiona Chillas

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…

Abstract

Purpose

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.

Design/methodology/approach

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

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.

Practical implications

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

Originality/value

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.

Details

Employee Relations, vol. 32 no. 2
Type: Research Article
ISSN: 0142-5455

Keywords

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Article

Ming Li, Jun Wang and Yingcheng Xu

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…

Abstract

Purpose

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.

Design/methodology/approach

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.

Findings

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.

Research limitations/implications

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.

Practical implications

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.

Originality/value

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.

Details

Kybernetes, vol. 46 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

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Article

Femi Emmanuel Ayo, Olusegun Folorunso and Sakinat Oluwabukonla Folorunso

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…

Abstract

Purpose

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.

Design/methodology/approach

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).

Findings

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.

Research limitations/implications

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.

Originality/value

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.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 12 no. 1
Type: Research Article
ISSN: 1756-378X

Keywords

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Article

Sisay Adugna Chala, Fazel Ansari, Madjid Fathi and Kea Tijdens

The purpose of this paper is to propose a framework of an automatic bidirectional matching system that measures the degree of semantic similarity of job-seeker…

Abstract

Purpose

The purpose of this paper is to propose a framework of an automatic bidirectional matching system that measures the degree of semantic similarity of job-seeker qualifications and skills, against the vacancy provided by employers or job-agents.

Design/methodology/approach

The paper presents a framework of bidirectional jobseeker-to-vacancy matching system. Using occupational data from various sources such as the WageIndicator web survey, International Standard Classification of Occupations, European Skills, Competences, Qualifications, and Occupations as well as vacancy data from various open access internet sources and job seekers information from social networking sites, the authors apply machine learning techniques for bidirectional matching of job vacancies and occupational standards to enhance the contents of job vacancies and job seekers profiles. The authors also apply bidirectional matching of job seeker profiles and vacancies, i.e., semantic matching vacancies to job seekers and vice versa in the individual level. Moreover, data from occupational standards and social networks were utilized to enhance the relevance (i.e. degree of similarity) of job vacancies and job seekers, respectively.

Findings

The paper provides empirical insights of increase in job vacancy advertisements on the selected jobs – Internet of Things – with respect to other job vacancies, and identifies the evolution of job profiles and its effect on job vacancies announcements in the era of Industry 4.0. In addition, the paper shows the gap between job seeker interests and available jobs in the selected job area.

Research limitations/implications

Due to limited data about jobseekers, the research results may not guarantee high quality of recommendation and maturity of matching results. Therefore, further research is required to test if the proposed system works for other domains as well as more diverse data sets.

Originality/value

The paper demonstrates how online jobseeker-to-vacancy matching can be improved by use of semantic technology and the integration of occupational standards, web survey data, and social networking data into user profile collection and matching.

Details

International Journal of Manpower, vol. 39 no. 8
Type: Research Article
ISSN: 0143-7720

Keywords

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Article

Fuli Zhou, Yandong He, Panpan Ma and Raj V. Mahto

The booming of the Internet of things (IoT) and artificial intelligence (AI) techniques contributes to knowledge adoption and management innovation for the healthcare…

Abstract

Purpose

The booming of the Internet of things (IoT) and artificial intelligence (AI) techniques contributes to knowledge adoption and management innovation for the healthcare industry. It is of great significance to transport the medical resources to required places in an efficient way. However, it is difficult to exactly discover matched transportation resources and deliver to its destination due to the heterogeneity. This paper studies the medical transportation resource discovery mechanism, leading to efficiency improvement and operational innovation.

Design/methodology/approach

To solve the transportation resource semantic discovery problem under the novel cloud environment, the ontology modelling approach is used for both transportation resources and tasks information modes. Besides, medical transportation resource discovery mechanism is proposed, and resource matching rules are designed including three stages: filtering reasoning, QoS-based matching and user preferences-based rank to satisfy personalized demands of users. Furthermore, description logic rules are built to express the developed matching rules.

Findings

An organizational transportation case is taken as an example to describe the medical transportation logistics resource semantic discovery process under cloud medical service scenario. Results derived from the proposed semantic discovery mechanism could assist operators to find the most suitable resources.

Research limitations/implications

The case study validates the effectiveness of the developed transportation resource semantic discovery mechanism, contributing to knowledge management innovation for the medical logistics industry.

Originality/value

To improve task-resource matching accuracy under cloud scenario, this study develops a transportation resource semantic discovery procedure from the viewpoint of knowledge management. The novel knowledge management practice contributes to operational management of the cloud medical logistics service by introducing ontology modelling and creative management.

Details

Journal of Intellectual Capital, vol. 22 no. 2
Type: Research Article
ISSN: 1469-1930

Keywords

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Article

Tomaž Deželan, Danica Fink Hafner and Mateja Melink

The purpose of this paper is to examine the education-job match of political science graduates from Slovenia, as well as from selected EU countries, in the context of…

Abstract

Purpose

The purpose of this paper is to examine the education-job match of political science graduates from Slovenia, as well as from selected EU countries, in the context of other disciplines. In the frame of contested theoretical approaches, the implications of matching the knowledge that is acquired during education to the skills that are needed on the job are also examined.

Design/methodology/approach

Using the REFlex HEGESCO database, as well as other secondary data, the wider disciplinary and contextual environments are presented. Disciplinary and contextual mapping is followed by binary logistic regression of primary data collected from Slovene political science graduates. Based on the results, the authors determined the validity of certain theoretical premises of human capital, credentialist, and assignment approaches, specifically regarding education-job matching.

Findings

In terms of graduate education-job match, the results indicate that the relevance of the sector of employment relates to educational as well as skill match. The results also indicate that matched candidates utilize the skills acquired during the education process to a greater degree, which adds weight to the assignment theory's presumption. The effect of formal credentials is relevant, because graduates with Bologna degrees, despite having attended programs with virtually identical curricula at the same institution, are significantly less matched when compared to non-Bologna graduates. Accordingly, the effect of the change to the structure of the system of higher education (HE), which is amplified by the period effect of the economic crisis, implies a serious change to graduates’ opportunity structure.

Practical implications

The study should motivate a re-examination of the teleological purpose of the study by professional associations in the state. It should also motivate the adjustment of the study programs to the new conditions graduates face and strengthen the educator-employer relationship to make the latter cognizant about the study programs and the skills of graduates. In addition, the study should provide grounds for a critical discussion about the implications of governmental austerity measures on the public sector.

Originality/value

The paper provides new insights into the early careers of political scientists and social scientists at large. It also offers early evidence on the effect of the Bologna's HE reform and indications about the early career achievements in a crisis-struck post-communist country.

Details

International Journal of Manpower, vol. 35 no. 4
Type: Research Article
ISSN: 0143-7720

Keywords

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Article

Yong Liu and Kevin W. Li

The purpose of this paper is to propose a novel prospect-based two-sided matching decision model for matching supply and demand of technological knowledge assisted by a…

Abstract

Purpose

The purpose of this paper is to propose a novel prospect-based two-sided matching decision model for matching supply and demand of technological knowledge assisted by a broker. This model enables the analyst to account for the stakeholders’ psychological behaviours and their impact on the matching decision in an open innovation setting.

Design/methodology/approach

The prospect theory and grey relational analysis are used to develop the proposed two-sided matching decision framework.

Findings

By properly calibrating model parameters, the case study demonstrates that the proposed approach can be applied to real-world technological knowledge trading in a market for technology (MFT) and yields matching results that are more consistent with the reality.

Research limitations/implications

The proposed model does not differentiate the types of knowledge exchanged (established vs novel, tacit vs codified, general vs specialized) (Ardito et al., 2016, Nielsen and Nielsen, 2009). Moreover, the model focuses on incorporating psychological behaviour of the MFT participants and does not consider their other characteristics.

Practical implications

The proposed model can be applied to achieve a better matching between technological knowledge suppliers and users in a broker-assisted MFT.

Social implications

A better matching between technological knowledge suppliers and users can enhance the success of open innovation, thereby contributing to the betterment of the society.

Originality/value

This paper furnishes a novel theoretical model for matching supply and demand in a broker-assisted MFT. Methodologically, the proposed model can effectively capture market participants’ psychological considerations.

Details

Journal of Knowledge Management, vol. 21 no. 3
Type: Research Article
ISSN: 1367-3270

Keywords

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Article

Tayybah Kiren and Muhammad Shoaib

Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many…

Abstract

Purpose

Ontologies are used to formally describe the concepts within a domain in a machine-understandable way. Matching of heterogeneous ontologies is often essential for many applications like semantic annotation, query answering or ontology integration. Some ontologies may include a large number of entities which make the ontology matching process very complex in terms of the search space and execution time requirements. The purpose of this paper is to present a technique for finding degree of similarity between ontologies that trims down the search space by eliminating the ontology concepts that have less likelihood of being matched.

Design/methodology/approach

Algorithms are written for finding key concepts, concept matching and relationship matching. WordNet is used for solving synonym problems during the matching process. The technique is evaluated using the reference alignments between ontologies from ontology alignment evaluation initiative benchmark in terms of degree of similarity, Pearson’s correlation coefficient and IR measures precision, recall and F-measure.

Findings

Positive correlation between the degree of similarity and degree of similarity (reference alignment) and computed values of precision, recall and F-measure showed that if only key concepts of ontologies are compared, a time and search space efficient ontology matching system can be developed.

Originality/value

On the basis of the present novel approach for ontology matching, it is concluded that using key concepts for ontology matching gives comparable results in reduced time and space.

Details

Aslib Journal of Information Management, vol. 68 no. 1
Type: Research Article
ISSN: 2050-3806

Keywords

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