محمدعلی شفیعا

In the industrial development of Iran, despite significant investments and focus on the upstream petrochemical industry, the development of the mid-stream and downstream industries has been neglected. Although this has resulted in acceptable export performance in the upstream industry, it has created limited export development benefits in the downstream petrochemical industries. This article seeks to analyze the reasons for these conditions from the perspective of the technological capabilities.Through the exploratory study of literature, the dimensions of technological capabilities were identified and adapted to the conditions of these industries during interviews with twelve experts. Using a questionnaire, these dimensions were evaluated in 128 enterprises in three industries: plastics, detergents, and paint, and resin and compared with each other using the "importance-performance" analysis method. Based on the results, the strengths of these industries are limited to project implementation and process engineering capabilities, while their weaknesses are in pre-investment, learning, industrial engineering, product engineering, linkage, and networking capabilities. But the major challenge for these companies is the lack of complementary capabilities including marketing, creating sales networks and distribution channels, managing brands, developing after-sales services and other related capabilities. Although the managers rated these components as very poor in "performance", they did not attach high "importance" to them either. The reasons are the continued dominance of the import substitution approach, lack of expert personnel, lack of long-term planning for a stable presence in regional markets, and deviation in export support policies. In order to develop export technological products, this article suggests that companies design and implement smart programs in upgrading these complementary capabilities with the support of relevant government institutions.

Following the financial crisis of 2008, the newly industrialized countries have re-emphasized to pursue catching up strategy to attain industrialialization. In this strategy, the goal is promoting technological and innovative capabilities on the one hand, and improving competitive capabilities on the other. This study evaluates the technological and competitive capabilities of Iranian plastics companies to provide a clear picture of these companies and their obstacles to catch up. For this purpose, a questionnaire was completed to evaluate 55 companies in the top rankings based on 12 elements, followined by the semi-structured interviews. The analysis showed that strengths of Plastics companies are capabilities of process engineering, project execution, and linkage. However, their weaknesses is quite evident in complementary capabilities even pre-investment and learning capabilities. Afterward, those companies were classified into three groups of imitators, creative imitators and innovators by clustering method, investigating their distinctive characteristics.The paper concludes  the lack of adequate complementary capabilities stands out as a key obstacle in the process of catch up.

We live in a very complex world where we face complex phenomena such as social norms and new technologies. To deal with such phenomena, social scientists often use reductionism approach where they reduce them to some lower-lever variables and model the relationships among them through a scheme of equations. This approach that is called equation based modeling (EBM) has some basic weaknesses in modeling real complex systems so that assumptions such as unbounded rationality and perfect information are strongly emphasized while adaptability and evolutionary nature of all engaged agents along with network effects go unaddressed. In tackling deficiencies of reductionism, the complex adaptive system (CAS) framework has been proven very influential in the past two decades. In contrast to reductionism, under CAS framework, complex phenomena are studied in an organic manner where their agents are supposed to be both boundedly rational and adaptive. As the most powerful methodology for CAS modeling, agent-based modeling (ABM) has gained a growing popularity among academics and practitioners. ABMs show how agents’ simple behavioral rules and their local interactions at micro-scale can generate surprisingly complex patterns at macro-scale. Despite a growing number of ABM publications, those researchers unfamiliar with it have to study a number of works to understand (1) why and what of ABM, (2) its differences with EBM (3) its main functionalities in scientific studies and (4) some of its applications in management science. So, this paper’s major contribution is to help researchers particularly those unfamiliar with ABM to get insights regarding its philosophy and use and gain a big picture of it.