Presenting a model for determining the level of technological complexity of research and development activities in knowledge-based companies (case study: companies based in Golestan Science and Technology Park)
<p style="text-align: left;"><span style="font-family: times new roman, times, serif; font-size: 12pt;">Today, the research activities of knowledge-based companies are considered important sources of transformation in the fields of technology and knowledge production....
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | fas |
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Islamic Azad University, Tabriz Branch
2025-03-01
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| Series: | مدیریت بهره وری |
| Subjects: | |
| Online Access: | https://sanad.iau.ir/journal/jpm/Article/975808 |
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| Summary: | <p style="text-align: left;"><span style="font-family: times new roman, times, serif; font-size: 12pt;">Today, the research activities of knowledge-based companies are considered important sources of transformation in the fields of technology and knowledge production. The more advanced the level of these activities and the higher their technological complexity are, the more innovative and competitive products grow. The present study was conducted with the aim of providing a model for determining the level of technological complexity of research and development in knowledge-based companies. In terms of its purpose, this research is part of applied research, and regarding methodology, it is in the category of mixed research. In the qualitative section, the data was collected from the literature review and semi-structured interviews with 20 experts in the field of research and development. First, seven categories were extracted for the complexity levels of research and development, and the Frascati category (including basic research, applied research, and experimental development) was selected based on the experts’ opinions. Then, during three stages of coding (open, central and selective), the influential factors in determining the level of complexity were identified and the research model was formed. In the quantitative part, the data was collected from a sample of 290 people from the target statistical population (Golestan Science & Technology Park) through a researcher-made questionnaire. Then, the data was analyzed and model fit test using structural equation modeling method, was conducted. The data analysis was done using smart pls3 software. The results indicated a suitable fit of the data with the final model, including complexity levels and 91 effective indicators in determining complexity levels. This model can be a suitable tool for research and development departments of knowledge-based companies, in order to improve the level of research and development based on global standards and create transformation in the fields of technology and knowledge production and increase added value.</span></p>
<p style="text-align: left;"><span style="font-family: times new roman, times, serif; font-size: 12pt;"><strong>Key Words:</strong>complexity,research and development,technology,knowledge base</span></p>
<p style="text-align: left;"><span style="font-size: 12pt;"><strong><span style="font-family: times new roman, times, serif;">1.Introduction</span></strong></span></p>
<p style="text-align: left;"><span style="font-family: times new roman, times, serif; font-size: 12pt;">Today, knowledge-based economy is considered one of the important and influential areas in the economic development and growth of countries. In this regard, knowledge-based companies, which are known as the main engine of economic growth and development, play an important role in the growth of the knowledge-based economy. During the recent decades, industrial developments and innovations have resulted from innovative and creative activities in knowledge-based companies. Research and development activities make it possible for knowledge-based companies to adapt to the changes and fluctuations in the market through efficient methods, offer new products and achieve sustainable competitive advantages. The more innovative and creative the research and development activities in knowledge-based companies are, the more advanced technologies and higher technological capabilities become available, leading to the production of new more competitive products and services., and increased productivity. An important factor that has led developed countries to be the leaders in the knowledge-based economy is the performance of advanced and fundamental research and development activities, which has improved the efficiency and effectiveness of activities and the production of innovative products with advanced technologies. This has resulted in the growing share of knowledge-based economy in these countries.</span></p>
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<li><span style="font-size: 12pt;"><strong><span style="font-family: times new roman, times, serif;">Literature Review</span></strong></span></li>
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<p style="text-align: left;"><span style="font-family: times new roman, times, serif; font-size: 12pt;">Brockel (2018) conducted a study titled “Measuring technological complexity- current approaches and a new measure of structural complexity”. In this research, while examining two existing empirical measures of technological complexity, including the reflection approach (Hidalgo &Hausman, 2009) and the knowledge synthesis difficulty approach (Fleming & Sorenson, 2001), a new approach of structural complexity is presented , and then, using these three approaches, Five indicators are provided to measure the complexity of technology based on the criteria of increasing complexity over time, larger research and development, collaborative research and development, and spatial concentration. Amsden and Tchang (2003) conducted a study titled “A New Approach to Assess the Technological Complexity of Different Classes of Research and Development” (with examples from Singapore). In this research, a framework for classifying activities that take place in the form of research and development in different countries has been presented. To determine the framework, the five classifications of research and development, including pure science, basic research, applied research, exploratory development and advanced development were used, and eight criteria were used to identify the type of activity class and to determine the level of complexity, including research search, research objective, outputs, performance, time horizon, used techniques, required qualifications and the scope of the work are presented.</span></p>
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<li><span style="font-size: 12pt;"><strong><span style="font-family: times new roman, times, serif;">Methodology</span></strong></span></li>
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<p style="text-align: left;"><span style="font-family: times new roman, times, serif; font-size: 12pt;">The current study is applied research with a mixed-method approach for data collection which was carried out qualitatively and quantitatively. The statistical population of the qualitative part of the research included 20 experts in the field of research and development and specialists of knowledge-based companies who were selected using the snowball sampling method. The desired data was collected through the semi-structured interviews, and the sampling method was theoretical saturation which ended with the interview of the 20th participant. Also, the statistical population of the quantitative part of the research included managers and experts of companies in Golestan Science and Technology Park, and its statistical sample was determined by simple random sampling and sample size table. Library and interview data were used to collect the qualitative data. Also, a researcher-made questionnaire was used to collect the data in the quantitative part of the study, which was designed based on the findings of the qualitative part of the research. To analyze the data of the qualitative section, content analysis and three stages of coding (open, central and selective) were used. Also, for the quantitative data analysis, structural equation modeling method was used with smart pls3 software.</span></p>
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<li><span style="font-size: 12pt;"><strong><span style="font-family: times new roman, times, serif;">Result</span></strong></span></li>
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<p style="text-align: left;"><span style="font-family: times new roman, times, serif; font-size: 12pt;">The results of the present research can be actually a comprehensive solution to solve the problem of the lack of advanced and complex research and development activities in most Iranian knowledge-based companies. In the proposed model, to determine the level of technological complexity of the research and development activities, 91 criteria in the form of six constructs (causal factors, background factors, intervening factors, central category, strategies and consequences) were identified and approved. These criteria include: 18 causal factors, 15 contextual factors, 11 intervening factors, 11 central factors, 21 strategy items and finally 15 consequence items.</span></p>
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<li><span style="font-size: 12pt;"><strong><span style="font-family: times new roman, times, serif;">Discussion</span></strong></span></li>
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<p style="text-align: left;"><span style="font-family: times new roman, times, serif; font-size: 12pt;">Previously, Amsden and Tchang (2003) identified only eight criteria to determine the level of technological complexity of research and development activities (i.e., research search, research objective, outputs, performance, time horizon, used techniques, required competencies and work size) and were indifferent to the role of other factors. Unlike the current research criteria, these eight criteria are only experimental criteria and do not include theoretical criteria, and due to the small number of produced criteria, they lack the necessary comprehensiveness to determine the level of complexity, and therefore, may produce inaccurate results. Zarei Mahmoudabadi et al. (2013) also identified factors that are effective in evaluating research and development activities in the form of two categories of input factors and output factors. These factors play a role in the level of complexity of research and development activities, but their number is limited to only six factors (including the number of enrollments in science and engineering fields, the number of R&D researchers, R&D costs, the number of scientific and engineering articles, received international patents and export of advanced technology) which is not enough to measure the level of complexity of research and development activities. Mohammadzadeh et al. (2013) have also identified and introduced very limited factors (including human capital, company size, profitability, industry concentration and non-governmental ownership) that are effective on the research and development activities of companies. Therefore, the literature review showed that the studies conducted regarding the research and development activities of knowledge-based companies were not comprehensive enough.</span></p> |
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| ISSN: | 2716-9979 2476-7298 |