ارائه مدل پویای توسعه سرمایه‌گذاری و بهبود مزیت رقابتی خوشه‌های صنعتی ایران

Introduction
Clusters are suitable methods for creating competitive advantage, not only for enterprises of the same cluster, but for the country on which the clusters are based. In Iran, although more than 90% of the industries are small and medium-sized enterprises, unfortunately, these firms have not been able to make a significant contribution to the creation of added value and suffer from severe deficits. This paper intend to provide and examine a model for the development of industrial clusters and the effects of different policies applying system dynamic approach. The proposed conceptual model includes the interaction of cluster size, resources, staff, market demand, production capacity, profitability, and investment. Considered policies include firms' strategies such as increasing the utilization of production capacity, reducing lead time as well as national and international policies, including granting low-interest governmental loans, and sanctions cancellation. The results show that if the intended policies apply, the cluster get bigger and grow faster.
 
Literature and the theoretical background
Nowadays, in most countries, Smalland Medium-sized Enterprises (SMEs) play important roles, ranging from the various aspects of economy, manufacturing and offering services. In many countries, these industries are the major suppliers of employment, evolution, innovation, and are pioneer in novel technology invention. Unfortunately, in Iran, despite a significant presence of small industries, such enterprises face numerous challenges because of the same approach in policy making and regardless of the scale of production units. Thus, playing of expected role like the developed and developing countries have been a failure. Therefore, the development of this sector of industry predisposes the endogenous development of the country and accelerates industrial growth.
The industrial clusters are known as one of the successful organizing patterns of SMEs which eliminates the SMEs weaknesses and reinforces the various advantages of small business, like flexibility and diversification. Today, planning of the development of Smalland Medium-sized Enterprises (SMEs), based on clustering approach, is considered as a method for achieving the developmental goals in many countries. Although industrial clusters have high potential for ongoing economic growth, the development is a difficult affair.
However, it is normal that enterprises inside a cluster are influenced by evolutions; therefore in cluster developmental planning, the impacts of the factors should be considered; the determination of such factors is important because appropriate scenario can be launched and the better practice plans can be implemented, the existing potential in the cluster in favor of stakeholders interests can be effectively used, which will result to sustainable development. Therefore, the relationships between involved factors in the success of industrial clusters should be organized by suitable structure which will result in the creation of a coherence model of clear relationship of factors. This study presents a quantitative model for the development of industrial clusters. For this purpose, variables affecting the development of industrial clusters including cluster size, interaction of clusters with suppliers, staff, internal and external market demand, production capacity, training and research institutions are represented in a dynamic model. Then, the impacts of different policies on the development of industrial clusters that are vital to the industrial and national competitive advantage are examined. Therefore, the following objectives will be pursued:

To provide a dynamic model of industrial clusters development.
To examine the behavior of main variables in the model.
To analyze decision-making scenarios using simulation of mentioned variables behavior.

 
Method
In general, simulation is a process of designing a model based on a real system. The purpose of simulation is to provide models that are close to reality as much as possible. In systems dynamic method, it is possible to study and examine the effect of varying one agent while other factors are constant. Therefore, new perspectives are achieved toward system specifications.Doing so with real systems is rarely possible and even if carried out, it would be very costly and time consuming. Also, the effect of different policies on the system can be examined through the model and its sensitivity to internal and external changing conditions studied. For this purpose, by using decision variables and explanations presented in the previous section, the dynamic model for industrial clusters development was provided. This model will be able to study the behavior of reference modes and analyze the impact of different decisions on these variables. Hence, the present study can be applied to compare different policies of industrial clusters development.
 
Findings and discussion
To analyze a system, its components needs to be identified and their relationship with each other examined. This paper evaluated the impact of specific policies on cluster development, using system dynamic approach. According to the literature review, dynamic conceptual model of clusters includes cluster size, cluster interaction with supplier, number of skilled staffs, local workforce, market demand, production capacity, innovation, profitability and investments, expenses and incomes, loans and government support etc. Graphical representation of the problem helps in the conceptualization of policies structure; but the diagrams will be changed to mathematical equations for computer simulation. To do so, the stock-flow models are developed according to the literature review and the casual loop diagrams earlier presented.
A strategy for development of industrial clusters can be formulated in the form of internal cluster policies: 1) increasing the efficiency of employees, 2) increasing advertising, 3) reducing prices and 4) increasing the quality and performance.
By increasing the efficiency of employees, increasing advertising, reducing prices and increasing the quality and performance; the key variables of production capacity, skilled labor, cluster size, profitability, total demand, intermediate goods and competitive advantage, which are the main factors of the development of industrial clusters, upgrade to a higher level.
Another desirable strategy to develop industrial cluster is optimal investment, as follows: 1) increasing investment in research and development activities; 2) increasing investment in production capacity (machinery). By increasing investment in research and development activities and increasing investment in production capacity; key variables such as production capacity, skilled labor, cluster size, profitability, total demand, intermediate goods and competitive advantage, which are the main factors for the development of industrial clusters, are upgraded to a higher level.
The main goal of the present paper is to develop the competitive advantage of industrial clusters. Therefore, an optimal strategy for maintaining industrial cluster development is the following: 1) increasing the level of technology; 2) increasing the level of innovation; 3) increasing the level of business intelligence. By increasing in the level of technology, innovation and business intelligence, the key variables of production capacity, skilled labor, cluster size, profitability, total demand, intermediate goods and competitive advantage, which are the main factors for the development of industrial clusters, are upgraded and placed at a higher level.
 
Conclusions
In this study, system dynamic modeling was used to simulate various policies impact on the industrial clusters development. Here, some of the decisions were studied and analyzed as scenarios and acceptable results were obtained. Some of them are as follows:

The model consists of 7 main variables. These variables include: the number of cluster firms (cluster size), the number of clerical professional labor force, production capacity, raw material stock, total demand, profitability and competitive advantage
As a result, the model predicts the development of industrial clusters in 96 months or 8 years.
The model of causal relations was developed for the development of industrial clusters.
The fellow diagram was presented.
Policies within the cluster, including changes in employee productivity, advertising, price and quality and performance, have a significant impact on the development of industrial clusters and will promote key variables.
Investment policies on research and development activities and production capacity (machinery) can affect the development of industrial clusters and will promote key variables.
Competitive advantage in addition to low cost, which leads to profitability, will be created by technology, business intelligence and innovation. The effects of competitive advantage will appear after a period of time, which will change the main variables after several months of competitive advantage changes.