فصلنامه مدیریت توسعه فناوری
سال دوازدهم شماره 2 (تابستان 1403)

Dynamic Managerial Capabilities (DMCs) refer to a firm's ability to adapt and innovate in response to shifting market dynamics by its manager/s. These capabilities are believed to develop over time through accumulated knowledge and experience. The competencies of managers in these types of firms could play a crucial role in shaping decision-making and strategic choices. This study explores the influence of DMCs on the innovative performance of Iranian economic firms across four business-level strategies: defensive, analyzer, reactive, and proactive. A mixed-methods approach was employed, combining document analysis and a survey questionnaire. The survey data was processed and analyzed through statistical software packages such as SPSS and AMOS. The findings revealed that DMCs indirectly influence innovative performance, but only when coupled with proactive or reactive strategies. Interestingly, no such indirect effect was observed for defensive or analyzer strategies. The study highlights the importance of DMCs for fostering innovation in Iranian firms. This knowledge can inform both managers and policymakers. Managers should prioritize developing their own DMCs and cultivating a proactive or reactive strategic orientation. Furthermore, Iranian policymakers can create an environment that encourages businesses to invest in innovation.

With the emergence of digital technologies and their significant impacts on various industries such as the petroleum industry, their convergence in these industries and forecasting this convergence have always been questioned. This article attempts to forecast the convergence of artificial intelligence and drilling as digital and petroleum technologies. To address this topic, the patent data of these two technological areas were collected from a valid patent database and the co-occurrence network of these two technologies was created. The convergence of the sub-technologies of these two technologies was forecasted by using the link prediction method. Findings indicate that machine learning, computer vision, and robotics, as sub-technologies of artificial intelligence, have a broader application in different parts of drilling operations, and their growth and convergence are anticipated.

The growth and development of nations, as well as the resolution of their challenges, necessitate investment in technological advancement through research. Proper allocation of research funding is crucial to effectively address a country's problems. To understand the challenges within Iran's research funding distribution system, we conducted applied research using a qualitative approach. Analyzing qualitative data from 32 interviews with research funding beneficiaries through thematic analysis, this study reveals significant challenges in two major dimension: external and internal. External challenges encompass issues in the macro environment of the research funding system, categorized into five areas: defining research budgets for government agencies, allocating budgets to these agencies, macro management of the research sector, national and sectoral programs for funding distribution, and monitoring program implementation. Internal challenges involve the internal affairs of government institutions and fall into five categories: organizational characteristics, identifying organizational and national needs, conducting searches and selecting project leaders, implementing projects, and monitoring and evaluating research endeavors. Recognizing these challenges is the initial step in crafting effective strategies for research funding implementation

Renewable energy technologies present viable solutions to a range of environmental, economic, and social challenges, facilitating sustainable energy access for communities. However, to realize their potential impact on economic development and enhance the energy supply portfolio, it is essential to establish and sustain businesses centered on renewable energy by addressing existing obstacles. This study aims to identify and rank the barriers to the establishment of renewable energy Businesses framed within a business model context and viewed through the lens of sustainable development. A comprehensive literature review led to the formulation of seven primary hypotheses regarding these barriers in the northern provinces of Iran. Data were collected via a survey involving 59 industry professionals, and the results were analyzed using structural equation modeling and path analysis in SmartPLS software. The findings reveal that cultural barriers significantly impede value provision, while economic barriers predominantly affect value creation and acquisition. These insights offer critical recommendations for policymakers and business leaders seeking to mitigate obstacles and foster the growth of renewable energy Businesses for sustainable development.

The current research has provided a structural, functional, functional, and contextual framework for the entrepreneurial university eco-system. This research is applied in terms of its purpose, meta-synthesis research in terms of research strategy, and qualitative research in terms of its approach. The sampling method is non-probability and judgmental sampling. The sampling method is a non-probability and judgmental sampling from among the research published in reliable domestic and foreign scientific databases. After selecting the selected research, the coding and analysis process was done through the thematic analysis method and MAXQDA software. The results of the research show that the structural components include startups, spin-offs, proof-of-concept centers, and technology transfer centers, and the functional dimensions include the role of facilitating communication with the triple helix, encouraging policies to promote entrepreneurship, and training entrepreneurial human resources. In terms of performance indicators, inputs include financing research and development activities industrial research projects, and entrepreneurship training, and outputs include financial achievements income generation, and effective research in line with the needs of the market and society. The influential contextual factors also include the entrepreneurial environment with entrepreneurial culture and the financial support of the government and the private sector for entrepreneurship.

The aim of this research is to investigate the relationship between "knowledge relatedness" and “strategic alliance formation”. The tendency to cooperate has been increasing among companies in recent decades. Strategic alliances are considered one of the main types of cooperation. In a complex environment (especially in knowledge-based industries), there are few companies that prefer to rely only on their knowledge and technical capabilities to achieve innovation goals. It seems that the degree of relatedness of the knowledge base between two firms influences their decision to enter into a strategic alliance. Knowledge relatedness is evaluated through the complementarity or similarity of the knowledge bases. In this research, we seek to clarify the relationship between “knowledge similarity” and “alliance intensity” on the one hand, and between “knowledge complementarity” and “alliance intensity” on the other hand. For this purpose, a regression model is developed. Analyzing a sample of 121 companies from the biotechnology industry between 2005 and 2010, we found a positive relationship between knowledge complementarity and firms’ alliance intensity. While the relationship between knowledge similarity and alliance intensity is not supported.