جستجوی مقالات مرتبط با کلیدواژه « ارتباط صنعت و دانشگاه » در نشریات گروه « علوم انسانی »

To acquire innovations produced by universities and higher education institutions, organizations can use the strategy of boundary-spanning to meet their needs. The results of the previous research also indicate the effect of boundary spanning on organizational innovation. Based on this, it is possible to develop innovation in the industry by using boundary spanning. On the other hand, from 2015 to 2023, several researches have been conducted and published regarding the positive impact of boundary spanning on organizational innovation in different countries. By analyzing and summarizing the findings of previous studies by making sure of the relationship between the two considered variables and by making sure of the accuracy of the current findings, it is possible to provide solutions to improve the boundary spanning between industry and university as well as to improve the effect of boundary spanning on organizational innovation. Therefore, the primary question of the research is to what extent does the boundary spanning affect organizational innovation?

THEORETICAL FRAMEWORK:

As a description of boundary spanning in the field of organizational innovations, Tashman expanded the communication boundaries that are conceptual and linguistic differences in a laboratory environment, between the laboratory and other parts of the organization, and between different organizations. To increase the level of interaction and participation between industry and university and to take advantage of the innovations created in universities and higher education institutions, there is a need to develop the relationship between industry and university and acquire knowledge resources through the frontier strategy. In bridging and establishing inter-institutional communication and connecting separate groups, these people face boundaries and should cross these boundaries and obstacles and communicate with organizations outside the borders. Accordingly, boundary spanning helps the universities share scientific and technical information, and the industry acquire and understand academic innovations. Generally, boundary spanning is an effective strategy for developing the university-industry relationship to cultivate, share, and apply organizational innovations. Industries and companies are less willing to invest in research and development due to the high cost of complex laboratory equipment, the difficulty of access to international research and development centers, the risks associated with innovation, and the investment limitations. Hence, they are interested in getting the latest innovations in knowledge through higher education institutions. For industry-university collaboration to thrive, companies must learn to operate outside their organizational boundaries and develop their capabilities to interact and collaborate with partners with different characteristics.

In terms of its purpose, the current research is an applied study, and by its meta-analysis method, it is considered a quantitative study. In this research, the investigated community was the research studies published in English about the role of boundary spanning in organizational innovation from 2015 to 2023. In the first stage, 189 studies regarding the relationship between boundary-spanning and organizational innovation were selected from various databases. Then, 33 duplicate articles indexed in different databases were identified and removed. The number of 156 articles was identified for title and abstract review. By examining the titles and abstracts of all identified articles, 129 articles were excluded from the article review process due to lack of relevance to the research topic and lack of inclusion criteria. Therefore, 27 articles were selected for full review. By examining the remaining articles more closely and studying their results, 18 were picked for meta-analysis.

The findings showed that the average effect of boundary-spanning (random mixed effects) on organizational innovation equals 0.347. Considering that this effect size (0.347) is within the confidence range, it should be said that boundary spanning affects innovation. The obtained point estimate (0.347), based on Cohen's criterion, indicates an effect in the upper medium range. In general, boundary-spanning moderately affected organizational innovation.

CONCLUSIONS & SUGGESTIONS:

In general, innovation is a competitive advantage for organizations and industries, and innovative organizations can compete with other competitors and maintain the survival of their organization. Companies and organizations will be removed from the competition scene if they cannot achieve innovation to meet the new needs of society and the market. One of the ways to achieve innovation is the interaction of industry and university in the form of boundary-spanning activities. In this way, industries can obtain new academic knowledge innovations to develop new products and services to satisfy the market needs. Boundary-spanning operations can facilitate disseminating the innovation produced in universities for industry use. Therefore, it is suggested that to acquire and develop innovations produced in universities and scientific institutions, organizations and industries should turn to boundary-spanning and use boundary-spanning strategies in developing cooperation with universities.

Boundary spanning is a critical strategy for fostering the growth and development of both industry and university institutions. This strategy necessitates identifying the requirements, drivers, and antecedents that influence the interaction between industry and university, ultimately leading to enhanced effectiveness for both parties. Moreover, as a collaborative strategy between industry and university, boundary spanning has significant impacts on various organizational components, resulting in consequences that contribute to the growth and development of both sectors. Previous research has examined the relationship between boundary spanning and specific variables on a case-by-case basis. Variables like academic motivation, deep understanding of organizational procedures, complex communication and interpersonal skills, organizational structure, environmental dynamics, organizational agility, and flexibility have been investigated in relation to boundary spanning. However, a comprehensive research effort that identifies the antecedent-consequence components of boundary spanning and elucidates the role of each variable in the industry-university relationship is lacking. To address this gap and provide a comprehensive model of boundary spanning variables in the context of industry and university, it is necessary to conduct a comprehensive review of previous studies and systematically examine the antecedents and consequences within a framework. Therefore, this research aimed to answer the following questions: 1) What are the antecedents of boundary spanning between industry and university? 2) What are the ramifications of boundary spanning between industry and university?

This research employed a qualitative study design, utilizing a systematic review approach and a mixed research synthesis approach. The research focused on English-language studies published between 2012 and 2023 sourced from various scientific databases. Sampling was conducted in a targeted manner. To achieve the research objectives, the 7-step model proposed by Sandelowski and Barroso (2007) was employed.

During the analysis of the selected studies, a total of 148 categories were identified and extracted. Subsequently, the number of categories was reduced to 94 through further analysis. Finally, these categories were classified into general categories, resulting in 16 thematic components. Among these components, 6 components fell under the broader category of Antecedents, while the remaining ten were categorized as Consequences.The research findings revealed that the antecedents of boundary spanning could be classified into 6 general categories: structural-technological antecedents, structural-organizational antecedents, individual-organizational antecedents, leadership style, psychological-individual antecedents, and team-building antecedents.The research findings indicated that the consequences of boundary spanning could be classified into 10 general categories. These included the development of knowledge management skills, promotion of organizational creativity and innovation, enhancement of social capital, establishment of effective communication networks, impact on organizational performance, fostering of psychological capital, individual career-related outcomes, personal development, promotion of organizational commitment, and potential organizational role damage.Furthermore, this study emphasized the importance of fulfilling specific requirements for the successful implementation of boundary spanning in the industry-university relationship. Neglecting these requirements could hinder favorable outcomes in terms of industry-university communication. To enhance and strengthen the interaction between industry and university, various solutions could be implemented, such as offering internship programs for students in the industry, organizing joint meetings between university faculty and industry officials, facilitating exchange visits between industry employees and university staff, recruiting graduates from the university, providing training opportunities for company employees in universities, facilitating researcher transfers between academia and industry, licensing university patents to companies, offering industry study opportunities, conducting joint research programs, and engaging in community-level problem-solving projects. Employing the boundary spanning strategy can greatly benefit these initiatives.

This article aims to redesign parts of the promotion regulations for faculty members in order to strengthen the connection between industry and university.

This research uses design science methodology and within its framework, semi-structured interviews with experts and specialists in designing and focus group in validating of results have been used.

After analyzing different clauses of the regulation and identifying the relationship of these clauses with different types of industry-university communication paths, 11 clauses have been proposed in which more priority and credit have been given to the paths of creating spin-off companies and joint research with industry.
Discussion and

Industry-university communication is one of the recognized policies in the world for benefiting from the synergy between university and industry for economic growth and development. Industry-university communication is influenced by various factors and among them, the role of policy tools in creating industry-university communication is very essential; instruments that create institutional grounds for this communication in the form of laws and regulations have a direct impact on the behavior and decisions of actors involved in this communication. The promotion regulation is one of the effective policy tools that has a direct relationship with faculty members as the main actors of the university sector and with a proper design, it can direct the activities of faculty members towards strengthening industry-university communication. This article, while maintaining the current structure of the regulation, tries to transform this regulation into an effective policy tool for strengthening industry-university communication by proposing some clauses.

Since the university is considered as an educational and training center of human resources based on modern science in every country and that its task is to train educated and specialized human resources in a wide variety of sciences and skills. It is expected that the required forces will be selected and used from among university graduates according to the type of expertise and skills required for the industry and technology used. Therefore, the purpose of this study is to develop a strategic model to study and Analysis of factors affecting the relationship between industry and university (Case study: Islamic Azad University of Tehran).

In this research, the combined method of theme analysis- Network analysis process was used..

The research findings were obtained both quantitatively and qualitatively through interviews with 15 experts (who were university professors and industry experts) and the combined theme-process Network analysis process (ANP, using the theme analysis technique first. , A strategic model was developed to study and analyze the factors affecting the relationship between industry and university (Case study: Islamic Azad University of Tehran) and then the Network analysis process (ANP) technique was used to rank these criteria.

The data from the theme analysis led to the extraction of 26 sub-factors affecting the relationship between industry and academia, which are classified into 5 main groups or themes. Also, the output results of (ANP) method showed that among the criteria affecting the relationship between industry and academia, the criteria of industrialization of science with a score of (0.26), scientificization of industry with a score of (0.23), and politics, respectively. Scoring (0.19), rules and regulations with a score (0.18), transformation in education with a score (0.14) were ranked first to fifth, respectively.

Todays, higher education institutions need to integrate entrepreneurship in all Field of Study Specialized orientation and Education Courses in order to move in line with the dynamic labor market in the 21st century. This study aims to investigate study the entrepreneurial ecosystem of the world's innovative universities in a descriptive-analytical done. The population of the present study Society is the top universities in the field of entrepreneurship selected according to the annual ranking of Reuters. Reuters ranks the world's top universities in terms of innovation. Three Stanford, the Massachusetts Institute of Technology and Harvard University, ranked respectively first to third in the 2019 Reuters rankings, were studied as sample. Various methods and tools have been used to collect information, such as reviewing documents published on the official websites of universities, their reports and articles. In this research, the information of the studied universities is discussed in four sections: patents, university entrepreneurial activities, entrepreneurship training courses and relation with industry.

Policy makers have always considered developing the relationship between industry and academia due to its positive effects on creating technological, economic, and social developments. The present study investigated the effective components on industry-university relationship through applying structural equation modeling based on quantitative and qualitative methods.  By applying Cochran’s formula, 337 experts out of 1486 study population were selected, including the deans of universities, faculty of the Azad University based in Tehran and heads of industry relations centers. The collected data were analyzed by descriptive and inferential methods using SPSS 16 and Smart PLS software. Three dimensions and their components including individual (intellectual, attitude, skill), organizational (legal and statutory, cultural, managerial), and environmental (industry, infrastructure) were extracted along with 14 components and 55 indicators. To check for the fit of the model, the X2, R and RS were calculated. The presence of low X2 and the ratio of chi-square to the degree of freedom less than three, indicated a good fit of the model. Comparatively, the organizational dimension with %979 operating load claimed the highest priority.

Even though many efforts have been made to promote the relationship between industry and university in Iran, a proper systematic relationship between them has not yet been established. This paper seeks to study and examine the status of policy instruments effective in promoting the relationship between industry and university in Iran. To do so the provisions of five laws and regulations were examined and 41 legal articles were reviewed. The results of the analysis show that about 86% of the laws and regulations are only indirectly related or just have a capacity to promote the industry-university relations.

Moving on the path of innovation and entrepreneurship (value-creating) and fulfilling the desired social responsibility is one of the axes of the evolution of universities in recent years, especially in the last two decades. Innovative and value-creating university, for which various definitions have been proposed and various dimensions and criteria have been proposed for its introduction and creation, is one of the new initiatives and ideas for transformation in university systems. Despite identifying and introducing various components and criteria for an innovative and value-creating university, creating this type of university and purposeful and managed movement in the path of innovation and entrepreneurship requires a comprehensive roadmap and a balanced action guide. In order to evolve and achieve a comprehensive model, a guideline framework consisting of eight dimensions, as an action plan and operational model of an innovative and value-creating university by the European Commission and OECD, design and more than 600 universities and higher education institutes in Europe and OECD has evaluated this model. In this paper, through a review of documents, the guide to innovative and value-creating university is introduced as a guide for mainly European programs, for the gradual and systematic transformation of existing universities into innovative and value-creating universities with local considerations. All Iranian universities and higher education institutions with any mission, by learning and adapting actively and productively from this framework and gradually adapting their conditions to its dimensions and criteria, can take fundamental steps in the path of innovation and entrepreneurship and become an innovative and value-creating university in the Relation of Industry and University, Innovative and Entrepreneurial University, Value-creating University, Third Generation University, Guiding Framework for Innovative Higher Education Institute (HEInnovative)true and actual word.

The main purpose of the present study is to design a model of entrepreneurship education in public universities in Tehran. This research is a qualitative-quantitative mixed-method research. The statistical population in the qualitative section consisted of 12 expert professors and experts who had been involved with the dimensions of the research problem and subject for many years of experience in universities. The sampling method in the qualitative section was snowball. The statistical population in the quantitative section includes 400 students and professors of selected public universities in Tehran who were selected by multistage cluster sampling. The data gathering tool in the qualitative part of the research was semi-structured interviews and in the quantitative part of the researcher made a questionnaire, to analyze the data in the qualitative part of the foundation data method which eventually led to the extraction of research indices and categories, and according to the indices. Extracted, a research questionnaire was developed which was used to determine the validity of the indices and model of research using CVR method. Pls software is also used in the quantitative part to analyze the data. The results show that infrastructure and capital as causal conditions, industry-university relationship as contextual, skills and competencies as intervening conditions, education as a core issue, support and promote entrepreneurial culture as strategies and create employment and increase welfare are productive outcomes in the public universities in Tehran.

The main objective of this research is to explain the strategic objectives of establishing a quality management system for universities. This research has been conducted within the framework of a qualitative approach. To this end, 27 experts, decision-makers and quality managers were selected through targeted sampling in a systematic way and interviewed by semi-structured method. Data from the interviews are subject to analysis. In order to validate the results of the review approaches by the members, self-review of the researcher and reliability between the two coders were used and the results were adjusted in several stages. The findings indicate that there are two key strategic actions for the initial commitment to establishing a quality management system for academics, namely: efforts to internationalize universities and strengthen the interrelationships between universities and industry

The purpose of this research is systematically studying of theoretical models and researches carried out on the subject of entrepreneurial university in order to summarize, classify and integrate its components. 

This study is an applied research with a meta-synthesisqualitative approach. For this purpose, 128 articles were analyzed for collecting and analyzing data using an inductive qualitative content analysis approach based on open, axial and selective coding. 

Following coding, the components of entrepreneurial university were organized in 15 main categories, 44 concepts and 293 codes, and the significance and priority of each concept was determined using Shannon entropy.

Based on the findings of the research, the concepts of structure type, entrepreneurial support culture, management support from entrepreneurial activities, entrepreneurial goals and strategies, knowledge commercialization, entrepreneurial curriculum, introducing university entrepreneurs as role models, forming marketing centers, developing communication and networking have the highest importance and highest rank among the concepts. Finally, the suggested model was presented based on the derived components.

This study aimed to damage the relationship between industry and academia in the field of human sciences. The population of this study, two groups of faculty members in the humanities and industry leaders formed in Tehran. That 233 people multistage sampling among the first group of 87 chain sampling (snowball) were selected for the second group. To collect the data from the questionnaire was used. To determine the validity of health experts and experts in the field (teachers and advisors) were used. And to ensure the reliability of Cronbach's alpha coefficient formula is used, the results have been reported for items 87/0. For analysis of data from both descriptive and inferential statistics were used. According to research findings between all components (inability to networking, management weaknesses, lack of knowledge and skills, lack of proper culture and beliefs, lack of infrastructure and support, reluctance to communicate and inflexible processes and structures) significant relationship exist. And the Scheffe post hoc test between each of the two components Dvmvlfh except inflexible processes and structures with lack of proper culture and beliefs have a significant relationship.