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ISSN : 1598-7248 (Print)
ISSN : 2234-6473 (Online)
Industrial Engineering & Management Systems Vol.17 No.3 pp.550-561

Designing a Communicational Model between the Competitiveness Types of Small and Medium Industries in Iran

Alireza Khakpour, Mostafa Kazemi*, Ahmad Tavakkoli, Safar Fazli
Department of Management, Ferdowsi University of Mashhad, Mashhad, Iran
Department Of Social Sciences, Imam Khomeini International University, Qazvin, Iran
Corresponding Author, E-mail:
April 15, 2018 June 11, 2018 June 26, 2018


Competitiveness is a multi-dimensional concept that organizations must inevitably strengthen themselves in all its dimensions to develop competitive power. Competitiveness is effective on the success of an enterprise in a worldwide level. Accordingly, the purpose of this research was to design a communicational model between the competitiveness types of small and medium industries in Iran. Regarding the research purpose, the study is applied, which is conducted based on the descriptive-causal method. The statistical population of this research in identifying factors affecting competitiveness includes all small and medium enterprises in Qazvin province, Iran. In order to design a model for competitiveness, the experts familiar with the issue of competitiveness were used. Accordingly, two questionnaires were used in this research to collect data. This questionnaire is distributed among members of the statistical sample after the determination of validity and reliability. The exploratory factor analysis, the Interpretative-Structural Modeling (ISM), and Structural-Equation (Path) Model (SEM) have been used to analyze the data. The results findings indicated that among the factors influencing competitiveness, the competitiveness factors related to firm management and the competitiveness factors related to suppliers and resources have the most impact on the competitiveness of small and medium firms. The results (findings) also showed that the competitiveness factors related to demand and customers are recognized as an absolutely influential component. The results of the Structural-Equation (Path) Model (SEM) have evaluated the path coefficients significance. According to the research’s findings, it can be said that the factors affecting the competitiveness related to firm management and competitive factors related to suppliers and resources should be firstly strengthened in order to make small and medium industries more competitiveness and stimulate resources.



    The competition among economic, production, or commercial rivals in a business environment is one of the most important criteria for the growth and development of industries. In fact, the appropriate level of competition and competitiveness is considered as a tool for achieving a favorable economic growth and sustainable development in a healthy business environment (Ahmedova, 2015; Becuţ, 2016). In fact, the industry competitiveness is considered as a means of achieving desirable economic growth and sustainable development (Andzelic et al., 2011); therefore, the industrial competitiveness promotes the economy through promoting the global trade and the development of diverse thinking (Hussain et al., 2012). In fact, the competitiveness is the power of economic maneuver in a unit (firm), which is in a competitive market against the competitors and offers goods, services, skills, and ideas to a degree beyond the geographical boundaries under the terms and conditions of its business environment (Gonzalez, 2017; Rensmann, 2017).

    Competitiveness is a multi-dimensional concept in which organizations need to strengthen themselves in all its dimensions in order to develop their competitive power (Akimova, 2000). The previous types of research focused on the competitiveness of new products on market responses to product design, and others focused exclusively on markets or competition (Suharyanti and Tontowi, 2015).

    Competitiveness affects the success of a business firm at the global level (Ceptureanu, 2015; Ülengin et al., 2014). An enterprise is a competitor from the perspective of its customers when it can provide a value more than its competitors. This value will be measured by offering products with lower prices, but with a similar quality to competitors, or creating a distinction in quality that can justify higher prices (Divandari et al., 2009). However, one of the major problems in the industry in developing countries is the lack of competitiveness. One of the most important reasons for firms’ inability in competitiveness is the lack of a clear approach to increase competitiveness. In other words, organizations or even the state specifically do not pursue a steady approach and policy toward the competitive advantage for industries. Therefore, changing the conditions changes the competitiveness increasing methods. On the other hand, because many experts believe that the competitiveness of firms should be increased in order to increase competitive power or competitiveness of a country, therefore, firms have a primary role in raising the competitiveness of industry and the country (Schwab et al., 2007). Competitiveness at the firm level can be defined as the ability of the firm to design, produce, product marketing, and selling them more than competitors. Porter (1998a) states that governments are able to compete if their firms can compete. Porter expresses that these firms compete in the market rather than the government (Porter, 1998a). According to experts at Institute for Management Development (IMD, 2012), national competitiveness is not simply the concept of a simple community of firms, but it is the result of many factors, such as the administration of the economy by the government, social policies, and the mechanism of value creation. Competitiveness is the concept of the country’s ability to create value added and increase the wealth of society by managing assets and creating attractiveness, etc. According to Ma (1999), national competitiveness is the rate of production of goods and services that a country can reach international markets.

    According to Marts, competitiveness is equivalent to the economic power of a unit versus its rivals in a market that easily delivers goods, services, skills, and ideas beyond geographic boundaries. Competitiveness at the firm level can be defined as the ability of the firm to design, produce, product marketing, and selling them more than competitors. One of the characteristics of successful firms is the power of competitiveness, and at the same time, the characteristic of unsuccessful firms is the lack of this power. Therefore, if the roots and factors affecting the competitiveness of the enterprises could be identified and their relationship could be determined, effective strategies could be developed to increase the competitiveness of firms.

    A review on presented models in the field of competiveness shows that lack of sufficient knowledge about factors affecting the competiveness of small and medium industries in countries of origin has made the proposed models to be inefficient in this regard. Different models have been presented for competiveness including Studies by Jiang et al. (2016), Zhao et al. (2015), Yang et al. (2015), Ahmedova (2015), Utami and Lantu (2014) and Rostek (2012) in some of which the relationship between one or more limited variables and competiveness has only been studied or the presented models have been more in qualitative manner and the relationship between variables of competiveness has not been investigated and tested. Accordingly, given that the discussion of providing competitive models for industrial managers and organizations is very t important due to the increasing competitive space and shows the complexity of competitiveness processes. This issue needs more functional models and methods development. Therefore, in this paper, while fully studying the literature, the variables affecting competitiveness on the firm level are firstly identified. In continue, considering the logic of impressibility and competiveness of the competitive variables, the relationship between the competitiveness variables are firstly determined based on the ISM method, and finally the model will be tested in order to ensure its suitability among small and medium enterprise. Accordingly, due to the high simplicity and capability of this method, on the one hand, and the lack of similar models in the examination and presentation of competitive models, especially for small and medium industries on the other hand, it can be said that the competitiveness modeling by using these methods makes development of an applied model in this field possible.

    In other words, recognizing the characteristics of different firms in terms of competitiveness and providing effective models based on the factors affecting competitiveness is an issue that the researcher in this study is seeking to investigate. In this regard, the researcher has tried to provide an appropriate answer to the main research question in developing a communication model between the competitiveness factors by understanding this issue and considering the importance of competitiveness.


    According to Miller and Whitney (1999), there is no general and universal approach that has specific and identical components to accurately measure and assess the competitiveness that can be applied to all types of organizations. However, Miller and Whitney (1999) developed a general methodology for developing an organization-level competitiveness measurement tool through conducting interviews with experts within and outside the organization, in five distinct parts and collecting information in order to create the tool from the extracted components. The five distinct parts are 1. Organizational values and targets, 2. The market, 3. Key Concepts, 4. Genesis and Evolution, and 5. Supporting Systems (Miller and Whitney, 1999; Nilsson and Rapp, 2005):

    Factors influencing competitiveness enhancement in terms of subject literature are collected from various studies in the form of Table 1.

    The results of Table 1 show that totally, 41 factors have been identified and extracted as factors affecting the competiveness through research literature.


    The study is an applied study with respect to the purpose and it is a descriptive modeling study in terms of methodology. The statistical population of this research in identifying factors affecting competitiveness includes all small and medium enterprises in Qazvin province. The size of the statistical sample with the critical value of the standard normal variable was calculated according to z = 1.96, 1−α = 95% confidence interval, and 95% confidence interval ε = 0.0250 and the research questionnaire is provided to the managers of these enterprises. In the second part, ten experts who have been familiar with the topics of competitiveness have been used to determine the communication model and leveling the factors influencing competitiveness.

    In order to collect the research data, two researchermade questionnaires were used. The first questionnaire was designed to identify the main components affecting competitiveness, and the second questionnaire was designed to level the effective factors and determine the communication model in small and medium enterprises. The views of university professors and experts in this field have been used in this study to determine the validity of the questionnaires according to the content validity method. If necessary, corrective suggestions have been made by them.

    In order to investigate the reliability of the questionnaire, the competitiveness factors (type I questionnaire) have been calculated based on the reliability test of the construct considering the dimensions of competitiveness and their evaluation indicators. The results of the reliability test are summarized in Table 2.

    The results of Table 2 for determining the reliability of each of the effective dimensions on competitiveness show that the Cronbach’s alpha coefficient for each of the effective dimensions on the competitiveness is more than 0.7 which indicates the suitable reliability of each dimension and research questionnaire (type I).

    The reliability of the paired comparison questionnaire is based on collecting the information required by the ISM method through re-test and using Spearman’s correlation coefficient. To assess the reliability of the responses provided by the expert group, the paired comparison questionnaire was distributed among 10 experts in two rounds with 6 days intervals and they were asked to answer the questionnaire questions. Then, the responses were entered into SPSS 23 software in two different rounds (by the same individuals) and the Spearman correlation test was performed. The results are shown in Table 3.

    Regarding the calculated correlation coefficients that were more than 0.7, it can be stated that the data collected through the type II questionnaire had a good reliability.


    4.1. Exploratory Factor Analysis

    Considering that the purpose of this research is to design a communicational model between the factors affecting competitiveness for the competitive species of small and medium industries, therefore, factor analysis has been used to achieve the main dimensions of competitiveness in the dynamics of the studied society. Table 4 shows the results of the adequacy of data are shown for determining the competitiveness dimensions.

    Table 4 shows the value of the KMO index, the Bartlett test statistic, the degree of freedom, and the level of significance. Since the KMO index is calculated as much as 0.877 (greater than 0.5), the sample number is sufficient for factor analysis. Also, the level of significance level (sig) of the Bartlett test is less than 5%, which shows that factor analysis is appropriate for identifying the structure of the factor model and the hypothesis of the recognition of the correlation matrix is rejected. Table 5 shows the confirmed components and the total explained variance.

    Table 5 shows that totally five factors from all the questions of research’s questionnaire have been extracted and these five factors explain 70.928 percent of variance of factors affecting the competiveness in population under study. These five factors have been named as the cost of obtaining superiority, suppliers and resources, strategy and prediction, management, demand and customers.

    4.2. Leveling the Factors Affecting Competitiveness and Formulating the Communication Model

    Given the small number of dimensions and the lack of transparency in order to identify the causal relationships, the researcher distributed the paired comparison matrices to 14 members of the research, including the experts in the field of competitiveness and asked them to determine the type of relationship between the decision matrix ordered pairs based on the structural-interpretive approach. Therefore, Table 6 summarized the frequency of responses provided by 14 experts for each of the internal relationships (regular pairs) of the research variables according to the process of collecting and summarizing the data related to the impact and effectiveness of the components based on the structural-interpretive approach.

    For example, the number 3 in line of cost of obtaining superiority and column of suppliers and resources shows that three experts have believed that the cost of obtaining superiority can be considered as factor affecting the suppliers and resources. In continue, according to the ISM method, obtaining a majority vote of experts indicates the existence of a relationship and non-obtaining a majority, equal to the absence of a relationship between each regular pair. The number of majority votes is also obtained by using equation (1) as follows:

    n 2 + 1 = 14 2 + 1 = 8

    Thus, in Table 6, the entries with more than 8 votes have connections (1), and the entries with less than 8 votes indicate the lack of relationship (0) between regular pairs. With this argument, the initial access matrix (Dij) is constructed in the form of Table 7.

    Also, the initial diagram of the relations between the research components can be formulated based on the initial access matrix in the form of Figure 1.

    For example, Figure 1 shows that according to results of the initial acquisition matrix t Table 7, suppliers and resources can influence strategy and prediction and the strategy and prediction can influence cost of obtaining superiority.

    Following the technique steps, the final achievement matrix (Tij), which contains direct and indirect relationships between the components, is calculated. In the next step, the leveling is done according to the structuralinterpretative method. In Figure 2, the final pattern of the leveling of relationships between the competitiveness components is based on the ISM technique output.

    The results of Figure 2 show that the competitiveness factors associated with firm management and the competitiveness factors related to suppliers and sources (Level 4) have the most impact on the competitiveness of small and medium enterprises. After these two components, the factors including strategic competitiveness and prediction (Level 3) and the cost of obtaining superiority in the business environment (Level 2) are placed as the next. Finally, the most influential component of competitiveness was the competitiveness factors associated with demand and customers (Level 1), which were recognized as an absolute influential component.

    4.3. Testing the Relationship Model between the Factors Affecting Competitiveness

    Following the implementation of the ISM method, according to the paper’s model, the data related to key dimensions affecting competitiveness for 196 recognized industrial firm were prepared and imported into Smart PLS software. After implementing the conceptual model of the research and obtaining outputs, composite reliability, reliance on reliability, the convergent validity, and discriminated validity are investigated usually to evaluate reflection measurement models in equation (path)-structural models with partial least squares approach. Table 8 shows the external loads of factors related to each structure.

    In assessing the reliability of the reagent, it should be noted that the external loads on the structure should be greater, indicating that the corresponding reagents have a large subscriptions, which are obtained by the structure. Also, the rule for examining external loads indicates that the values should be at least 0.4 and the best value is considered to be greater than 0.708. According to the factor load indicators in Table 8, most of the obtained factor loads are more than 0.708, which indicates an excellent factor load in the reliability of the reagents. The lowest factor load belongs to the BM_6 reagent as much as 0.639, which is considered to be appropriate due to being more than 0.4. In other words, the results of Table 8 show that each construct has appropriately convergent reagents.

    In the study of equation (path)-structural models for enterprises, the indicators including convergent validity, composite reliability, and compatibility reliability have been investigated for the model components. In Table 9, the values of these indicators are given for the main structures.

    Convergent validity is the measure in which a measurement is positively correlated with the alternate measurements of the same structure. Convergent validity measurement is usually based on the average of the variance extracted (AVE). The minimum average variance extracted as much as 0.5 indicates sufficient convergent validity. This means that a latent n variable can averagely explain more than half the distribution of its reagents.

    The Cronbach’s Alpha is the traditional criterion for controlling the reliability. If the Cronbach’s Alpha of a block was larger than 0.7, the block is single-dimensional and the measurement model is confirmed. According to the results reported in Table 9, it is observed that the Cronbach’s alpha values for all measured structures are greater than 0.7. Therefore, the one-dimensionality of all structures for the first cluster is confirmed based on Cronbach’s alpha. However, in many studies, an alpha greater than 0.6 is also acceptable, nevertheless, another criterion entitles the composite reliability is also applied to make sure that all structures are single-dimensional. Based on the results of Table 9 related to this index, it is seen that the composite reliability values for all meas-ured models are greater than 0.7. Therefore, the one-dimensionality of all measured models is reconfirmed based on the composite reliability. Finally, the estimated coefficients for the structural-equation (path) model described in the first cluster can be summarized in the form of Figure 3.

    After ensuring the appropriateness of the validity and reliability estimations, the structural part should be evaluated and the data should be extracted. Findings of the coefficient of determination and its significance test are presented in Table 10.

    The basic criterion for evaluating the endogenous latent variables is the coefficient of determination. The values of the coefficient of determination as much as 0.67, 0.33, and 0.19 n the PLS path models are signifi-cant, moderate, and weak, respectively. Based on the results of Table 10, the values of the coefficient of de-termination for the latent variables are somehow weak.

    In the following, the path coefficients of the model are investigated. Each path coefficient in the structural model can be considered as a standardized beta coeffi-cient in regressions of the ordinary least squares. The path coefficients in the model have been calculated for the structural part of the research regarding the direct and indirect effects as shown in Table 11. According to the results obtained in the above table, the direct and indirect effects of each of the components on the other can be determined.

    The BT procedure must be implemented in PLS in order to make a significance assessment of direct and indirect effects and finally, the total effects and the t value should be obtained for each of the coefficients to assess the significance. In the following, the results of the t-test are shown in Table 12 and Figure 4 to assess the significance of path coefficients (direct and indirect effects).

    The results of Table 12 and Figure 4 shows that computed t value in competitiveness model is more than 1.96 for all direct effects which represents the dif-ference of the coefficients with zero. But indirect effects have not been in most cases significant. For example, the direct effect of suppliers and resources on strategy and forecast has a coefficient of 0.482 with a t value of 2.76, while the indirect effect of suppliers and sources on demand and customers with a coefficient of 0.92/0 and the value of 30.41 t has not been significant.


    One of the major problems of the industry in de-veloping countries is the lack of competitiveness. In addition, one of the most important causes of firms’ inability in these countries is the lack of a clear ap-proach to increase competitiveness. In other words, or-ganizations or even the government specifically does not pursue a steady approach and policy toward the competitive advantage for industries. Therefore, chang-ing the conditions changes the way of increasing com-petitiveness. On the other hand, in the opinion of many experts, the competitiveness of firms should be increased in order to increase competi-tive power or competitiveness of a country; therefore, firms have a primary role in raising the competitiveness of industries and the country. According to the results of the various analytical approaches used to provide a response and designing a communicational model among the factors affecting the competitiveness of small and medium industries using ISM, the research model has five main dimensions: “Competitiveness factors related to suppliers and resources,” “Strategic competitiveness and strategic prediction factors,” “Competitiveness factors related to firm management,” “Competitiveness factors of the cost of obtaining supe-riority in the business environment,” and “Competitive-ness factors related to demand and customers” have been identified. Considering the findings of interpretive structural modeling, four main relationships between the factors are definitively identified among the identified relationships. The mentioned relationships are:

    • The Effects of “Competitiveness factors related to firm management” on “Strategic competitive-ness and strategic prediction factors”

    • The Effects of “Competitiveness factors related to suppliers and resources” on “Strategic compet-itiveness and strategic prediction factors”

    • The Effects of “Strategic competitiveness and strategic prediction factors” on “Competitiveness factors of the cost of obtaining superiority in the business environment”

    • The Effects of “Competitiveness factors of the cost of obtaining superiority in the business envi-ronment” on “Competitiveness factors related to demand and customers”

    The research results in this section show that first, the effective factors affecting the competitiveness of firm management and the factors of competitiveness with suppliers and resources should be strengthened to have more competitiveness in the small and medium industries and stimulate demand to enhance strategic competitiveness and strategic prediction at the firm lev-el. This factor affects the competitiveness factors of the cost of obtaining superiority in the business environ-ment, which ultimately can stimulate demand and cus-tomers. Considering the above findings, it can be said that the causal relations confirm some of the main hy-potheses, findings, and research results such as Miller and Whitney (1999), Porter (1990), Szerb and Ulbert (2009) and Siriqari and Tang (2006).

    On the other hand, given the causal relationship be-tween the competitiveness variables and the causal model test, the competitiveness model presented in this research can make various industry managers easily identify their competitiveness priorities. The model pre-sented in this research for small and medium enterprises can guide managers in proper programming to enhance competi-tiveness compared to the previous models for testing the final model among small and medium enterprises and determining the main effective variables. Previous models, such as the Utami and Lantos (2014) and Ros-tock (2012) studies, have somehow tried to explain some of the competitiveness in the small and medium industries that the model presented in this paper has been somehow a complement to the previous work in terms of the comprehensive examination of various variables affecting competitiveness and the presenta-tion of a conceptual model and testing the model for competitiveness.

    Therefore, managers are suggested to develop goals, perspectives and organizational missions in order to improve the competitiveness of the business firm and review at various stages in order to increase competi-tiveness. It is also proposed to increase the quality and level of access to required resources and raw materials. Paying attention to the efficient supply chain can be beneficial in this regard.



    The causal relationship model (conceptual model of the research).


    The final model of the relationship between the components of competitiveness.


    Estimation coefficients of the structual-equation (path) model for this cluster.


    The t-values for the estimated coefficients of the structural-equation (path) model.


    Factors influencing competitiveness enhancement

    Results of the reliability of the type I questionnaire

    Spearman correlation test for type II questionnaire

    The results of KMO and Bartlett tests to determine the dimensions of competitiveness

    The number of verified components of the total variance

    The frequency of responses provided by experts for internal relationships between regular pairs of the research variables

    The access matrix of regular pairs

    The external loads of factors related to each structure

    Validity and reliability indicators of the structure

    Coefficients of determination and their significance test

    The total effects of latent variables (direct and indirect) in the estimated structural model

    The significance test results of the path coefficients in relation to direct and indirect effects


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