JOURNAL OF TECHNOLOGY DEVELOPMENT MANAGEMENT
Year:2018 | Volume:6 | Issue:2 |Papers Count:5

During last decades the subject of complex product systems (CoPS) in latecomer countries has been remarkably considered by many scholars. However, investigation of technological learning and catching up in these industries from windows of opportunity perspective has been overlooked. Even the research works that employed the windows of opportunity perspective to expose phenomena such as catch-up cycles, does not distinguish between products and complex systems with consumer products with a mass production system. So, the present study uses a qualitative approach and a case study strategy to explore the opportunity windows in the gas turbine industry in Iran as an industry with complex products and systems. Moreover, this study compared the windows of the gas turbine industry in Iran with the 5 selected industries to identify similarities and distinctions among them. Our findings show that the sequence of opportunity windows in the gas turbine industry in Iran is as follow: the opportunity window for the domestic market, the opportunity window of policies, technology learning window instead of technology opportunity window, and the window of opportunity for the foreign market. Some parts of our findings can be explained by considering the technological and market regimes for complex products and systems.

The present study was conducted with an innovative approach and the integration of system dynamics with ground theory to provide a system model for commercial soft technology diffusion in Iran's oil industry and was carried out in two stages. In the first stage, the ground theory was used. An interview with the 19 experts who dominated the process of commercial soft technology diffusion in the Iranian oil industry was carried out and a total of 785 final code, 184 concepts and 71 sub categories were extracted by performing necessary coding. The key variables of the system model were extracted from the first stage coding and a system model was developed in the form of 18 reinforcing loops and 4 equilibrium loops. In the following, the stock flow model was prepared, the necessary formulation was performed and after the validation of the model, the necessary simulations were done. The model data was gathered through expert comments and the model was simulated for a period of 50 years from 1390 to 1440. The results indicate that the best priority for improving the process of commercial soft technology diffusion is train, create an appropriate organizational structure, outsourcing and, ultimately, research and development.

Despite international sanctions against Iran's nuclear activities, radiopharmaceutical technology has made significant progress over recent years. This paper intends to investigate the radiopharmaceutical technology innovation system in Iran using the innovation motors approach. This study uses both the field and the library research and conducted between 1369-1359. The theoretical basis of this research is innovation motors model. This paper is carried out using the “ mixed method” to evaluating all aspects of the system using "exploratory method". This purpose was done in the qualitative section using the "Event History Analysis"method and in the quantitative section using the survey research and Structural Equation Modeling. Then, according to the exploratory method, the innovation motors of the radiopharmaceutical technological innovation system were identified. According to the result of the quantitative method we found that the "system building motor" loops are formed, but according to the qualitative section, it can be seen that the characteristics of the system in the system building motor are not completely consistent with the current situation. Therefore, the incomplete formation of the system building motor has been accepted and accordingly, we identified the threshold of the system building motor. Finally, recommendations were presented to complete construction motor and complete climb to the system building motor.

The researches carried out on R & D assessment and the relationship between production of science and technology at the macro level of countries were limited due to the high volume of information and rapid rate of changes. This paper presents application of data mining algorithms for modelling technology indicator of countries based on their science production. Furthermore, the impact of any scientometrics indicator on the technology indicator was separately determined using sensitivity analysis of neural networks. In the research, the number of patents registered by countries in the World Intellectual Property Organization (WIPO) was considered as technology indicator and data collected from the SCImago Journal & Country Rank (SJCR) was considered as indicators of science production. Data were ranged from 2001 to 2015. The artificial neural networks and regression were used to model the data. According to validation results, the artificial neural networks had more accuracy for modelling the science and technology indicators. The results of sensitivity analysis showed that the H-index parameter was the most important indicator for predicting the technology indicator. Predicting the technology is the first stage for Planning at the macro level and the purpose of that is making better decisions and programming for future.

Today, innovation is considered as a vital principle for organizations in such a way that ongoing improvement of the organization innovation performance is one of the key factors in survival of such organizations. Considering this objective, the present study investigated the effect of open inbound and outbound innovation on performance of information and communication technology (ICT) organizations. The community of the study consisted of 116 companies chosen from the ICT companies in Tehran. The tools of the study were a questionnaire. The collected data from the sample group calculated the statistics and by using testing and estimation technicians these statistics were embedded into the parameters of the community by using SPSS software. Finally, considering the results of the statistical, inferential and descriptive analysis of the collected data, six hypothesis are investigated. The results showed that there is a significant relationship between open inbound and open outbound innovation. Two variables of outbound and inbound innovation influence the organization performance while open outbound innovation, open inbound innovation and organization performance can explain 84% of the changes in innovation performance, therefore, open inbound innovation has smaller effect than the other two variables.