جستجوی مقالات مرتبط با کلیدواژه « technological collaboration » در نشریات گروه « مدیریت »

Technological collaboration in the global value chain of the copper industry has attracted the attention of large and small companies in this industry due to the increase in productivity, smartness and design of new products. Iran's National Copper Industries Company, as the parent organization of copper industries, is the subject of this research in the field of technological cooperation. In this regard, the aim of the current research is to identify the drivers of technological collabration of the National Iranian Copper Industries Company with knowledge-based companies in order to achieve higher value-added copper base products, job creation and profitability. This research was carried out with thematic analysis method of Attride-Stirling approach and data collection by library method and conducting semi-structured interviews with purposeful sampling method with 26 copper industry experts. As a result of this research, 26 effective drivers for the cooperation between the National Copper Industries Company of Iran and knowledge-based companies were identified, which are in seven categories: unpredictable environmental disturbances, development plans and policies of the country's mining sector, requirements for cooperation with knowledge-based companies, industry requirements Downstream of copper, the requirements of Iran's National Copper Industries Company, the challenges of international technological collabration and access to energy carriers were placed.

Creating demand for technological products, financing innovation, outsourcing research and development, etc. are among the effective actions of large firms in interaction with knowledge-based firms. On the other hand, knowledge-based firms can also play an effective role in meeting the technological needs of large firms with their scientific and technical ability do However, the interaction of these firms is facing problems due to various reasons and the cooperation of these two pillars of Iran's knowledge-based economy is far from its desired position. In the meantime, government policies can play a significant role in facilitating these connections. South Korea is one of the governments that has taken effective steps to develop interaction between firms by passing the Law on Mutually Beneficial Cooperation between Large Firms and Small Firms and forming the Ministry of Small and Medium Enterprises and Startups. This research, with a comparative analysis and a comparative study of the policies for the development of technological cooperation between South Korea and Iran and the division of the policy tools of these two governments into three categories of tools including tools for stimulating demand, tools for stimulating supply and tools for improving cooperation infrastructure, looking for solutions to develop these cooperations in Iran Is. The focus on supply stimulation tools and cooperation infrastructures is remarkable in Iran, but unlike South Korea, which has used important tools to stimulate demand, there is a serious gap in demand stimulation tools in Iran.

Imposing sanctions on some industries in Iran over the years have led many large industries to seek supplies from domestic companies. In these circumstances, and given that many needs are met through the collaboration of companies, the development of technological collaboration seems essential. Therefore, many large companies are looking for technological collaboration with other companies. Despite the need for technological collaboration in the current situation, technological collaboration faces serious challenges and in some cases this collaboration does not take shape. Hence, the government could develop collaborations by establishing policy tools. So, this research aims to identify the policy tools for the development of technological collaboration between industries and knowledge-based companies to achieve the desired situation in country. In this regard, by conducting purposeful interviews with experts in the field, the policy tools for the development of technological collaboration were extracted and examined by content analysis. These tools can be classified into three categories: supply stimulation tools, demand stimulation tools and infrastructure improvement tools.

The present study aims to identify the factors affecting technological collaboration between large and technology-based firms (KBFs). In this regard, using multi-case study method, 9 collaborations cases in the period 2006 to 2016 between 3 large firms and 9 KBFs in the field of nanotechnology and biotechnology in Iran have been studied. Data gathering tool is 19 semi-structured interviews with key people of large and KBFs involved in collaborative experiences and has been done from autumn to spring 2016. the method of data analysis is through content analysis and axial codin. Based on the results, the factors affecting the collaborations are presented separately for specific challenges and drivers for large and KBFs, as well as in the field of technology. Based on the results, the factors affecting collaborations are divided into two types of specific challenges and drivers. Challenging factors include the complex procedures of large firms and the unfamiliarity of KBFs with business rules. The dominance of KBFs over technical knowledge and the access of large firms to the market have also been the main drivers of collaborations. These factors can help policymakers, large firms and KBFs to overcome challenges and strengthen the collaboration drivers.

Buy back contracts have been one of the most common upstream contracts in the oil industry. This investment method allows the government to attract foreign capital and technical services and knowledge, while at the same time reducing the cost of foreign trade and increasing export capacity. On the other hand, Learning is one of the most important functions of technological collaboration, to which the success of collaborations will largely depend. This study, is a qualitative study with a case study strategy, attempted to determine the dimensions of learning in buy back contracts  with a case study on the North Azadegan Field Development Contract.  Data were collected through semi-structured interviews and document review. Purposeful sampling was used to interview the experts in this project. Data analysis was done by thematic analysis and a qualitative research model was designed by MAXQDA. According to the findings of this study, the technological learning framework has five main themes including contract features, infrastructure, learner characteristics, external peer characteristics, and the nature of knowledge and technology. The findings also indicate that informal and informal factors have a direct and indirect impact on technological learning, and their attention is very important.

In recent years, many studies have been conducted on collaboration networks, however, the process of evolution and network creation has been considered in a small number of studies. In this context, comprehensive identification and analysis of the challenges in the network forming process are important in order to solve them and to stabilize the network. In this research, an active collaboration network in the field of medical equipment that engineered by a Hub in 2009 and consisting of a large company, a small and medium-sized company, two subcontractors, three universities, a start-up, an accelerator and a venture capital fund, was studied. The presence of diverse members in the network is the basis for the emergence of various challenges and allows for a comparative analysis between them. For process-centric and rich analyze of information that gathered from deep interviews and supporting documents, a qualitative approach and case study were used. Finally, after analyzing the structure and framework of the network, 4 collaboration models and 28 different challenges were identified in the network, and in order to provide an analysis, those 28 different challenges (based on their existence or absence in each of the 4 identified collaboration models) divided into 7 categories and analyzed

According to the competitive environment of the business over the last few decades, large companies despite access to financial resources and distribution channels, face with bureaucracy, inefficiency and inertia, in contrast small technology-oriented companies with the flexibility and high innovation capability face with resource shortages And lack of access to the market. Therefore, both large and small companies need to work together to maintain their competitive position and survival. However, technological collaboration between companies is a complex subject that a comprehensive review of which requires a systematic approach. In this regard, an ecosystem approach can be used to analyze and explain the process of technological collaboration between the two groups of companies. To this end, using a systematic literature review method to develop an appropriate framework for the analysis of the ecosystem of technological collaboration and 605 documents were searched in valid databases, after which 63 of them were identified as valid documents. Subsequently, the selected documents were examined and coded using the Meta synthesis method. Finally, the codes extracted are as follows: five categories, one category about the characteristics of the ecosystem, and four others refer to the categories to be considered in the ecosystem analysis. These categories include life cycle, analysis dimensions, roles and institutions in the technological collaboration ecosystem

The present study aim to present a model of technological collaboration between university spin offs and ITC industries. Therefore, the authors of this study try to find the related factoes for proposing the model.
Introduction Althogh technological collaboration between university spin offs and industries is an important issue nowadays, there is little attention given to research on the factors shaping the model of collaboration. Thus, proposing this model was the main reason to carry out this study.
Case study This study is related to Information Technology and Communication industries. After finding the factors, we proposed them to 30 experts and asked for their suggestions about the same.
Materials and Methods The methodology of this study is the combination of qualitative and quantitative methods. First of all, we extracted the related factors by reviewing the literature and also by interviewing the experts. Then, we categorized the factors according to their similarities by thematic analysis. Then, we created a model of technological collaboration. We also used SPSS software and used Binomial test for analysis of data.
Discussion and Results By reviewing the lelevant literature and interviewing with experts, we found 72 factors related to technological collaboration between university spin offs and industries. Then, we sorted these factors into 3 categories and proposed a model in this regards.
Conclusion The proposed model of this study should be tested by future studies to be conformed or revised. Further, future studies can also expand the model of this study by proposing new factors which are effective on the technological collabortion between university spin offs and industries.

Turbulent environment, increasing competition and diverse and changing needs of customers, highlighted innovation role to promote firms’ competitive advantage. The limitations of knowledge sources and the need to respond quickly to their changes have led them to collaboration. In recent years, researchers have also been studying how and how to collaborate effectively. This paper aims to measure the impact of innovation on knowledge-based companies by typology of types of partnership-based, structured-based collaboration. A questionnaire was distributed among 185 sample companies, and they were asked to specify the types of cooperation. The results show that scientific cooperation is the most important collaboration type in creating innovation and market collaboration has the least effect on creation of product innovation. Of course, in this section, cooperation with the consultant has had a significant effect on the creation of innovation; however, cooperation with customers, competitors and provider has not had a significant effect on the creation of innovation. In the second part, the results also show that upstream collaboration has a significant effect on innovation and downstream collaboration has the least impact on creativity innovation

Nowadays، with the rapid pace of technological developments، no company or country is able to provide all of its needed technologies. Therefore، technology collaborationswith holders of technology is inevitable. Since every technology transfer project has different aspects، including technical، economic، legal and social issues and in many cases، the consequences of ignoring these issues may cause irreparable losses to the economy. Understanding and considering the basic criteria before transferring the technology is vital for managers and policy makers. In this paper، the commonmethods of technology transfer models in the world have been studied. Then، by considering the appropriate criteria influencing the choice of technology transfer models and technology collaboration methods، multiple attribute decision making method (MADM) was used to rank them. More precisely، analytic hierarchy process (AHP) was utilized to obtain the most appropriate method for transferring technology in establishing a graphite electrode plant. The results of this study indicate that the best method for transferring technology of graphite electrode was foreign direct investment، joint venture، and licensing، respectively.

Many studies carried out on the technological collaboration achievements in the field of science and technology policy. Some focus on how science and technology policies work. Iran’s science and technology policies support technological collaboration by providing many incentives especially for emerging technologies as Nano. There are still some debates over the issue whether these policies are effective or not. This research conducted to investigate the affecting factors on achievements of technological collaborations. Given related literature on the topic, affecting factors on technological collaborations classified into four factors: Individual, Institutional, Organizational, and Interactional. Conducting interviews asking about twenty active experts in science and technology policy and nanotechnology sector in Iran ended in the verified model. Next, the research model examined via structural equations and path analysis methods. All seventy-two researchers participated in the survey were randomly selected from Nanotech experts’ database. The results show that interactional factors including social networks, people interactions, organizational interactions and technological networks directly and positively relate to collaboration achievement.

Today, there is increasing emphasis on innovation between large multinationals around the world. Some factors influencing this trend such as the increasing competition, overlapping of industrial boundaries, and shorter cycle of product life have led to the variant trade environment and highlighting innovation in Technological Collaboration. Technological Innovation’s Collaborations (TICs) emphasize on innovation impress as a focal concept in technological collaboration in order to improve innovative capability, change competitors to collaborators, and decrease R&D expenditures. First of all this research has surveyed different related indicators for TIC at petrochemical industry in Iran. Then, each of indicators has been classified and ranked. Having analyzed the literature of TIC along with feedbacks from experts, there are about 20 indicators for TIC in commercial petrochemical company, which have been formed in questionnaire framework. We gathered experts’ opinions by means of these forms. Finally, using some statistical methods like explorative factor analysis and variance analysis, the related indicators were weighted and ranked. These indicators have been ranked based on four dimensions namely characteristics of collaborator, methods of technological collaboration, the size of collaborator’s enterprise, and scientific-research. In this research characteristics of partner are a strong determinant and scored the highest rank. Therefore, learning about the partner with lowest risk and highest efficiency, negotiating with the partner, and developing innovative capabilities are undertaken to make TIC go more flexible and efficient.