Hashem Dadashpoor; Sadegh Saeidi
Abstract
Transition of economy towards knowledge-based economy highlighted innovation as a requirement for metropolitan regions. Innovation which is understood in broad sense to include product, process and organizational innovation in the firms as well as social and institutional innovation at the level of an ...
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Transition of economy towards knowledge-based economy highlighted innovation as a requirement for metropolitan regions. Innovation which is understood in broad sense to include product, process and organizational innovation in the firms as well as social and institutional innovation at the level of an industry, region and nation has assumed to play ever more central role in theories of economic development. On this basis, improvement on different types of innovation at different levels is assumed as a strategy for the development of metropolitan areas. In spite of this, studies show that only investment in R & D units cannot solely improve innovation. In the context of learning regions, this gap which is called innovation gap is filled by regional characteristics of firms. Accordingly, this article seeks to study the impact of regional learning variablesof firms on their innovative capacities. For this aim, it studies regional learning features namely commercial relations volume (vertical relations), feedbacks, horizontal relations with other firms, firm’s size, inter-firm competition, employing local skilled labor and relation with academic institutional infrastructure. In this p, effect of these regional learning variables on different types of innovation evaluated including innovation in the production of new products, innovation in improving quality of current products, innovation in improving production processes, innovation in marketing and innovation in the organization. Two groups of industrial firms (food and auto parts industries) were chosen as case study, and features of regional learning were studied and compared with each other, then, the effect of these features on innovative capacities was studied in all firms.
Methodology
On this basis, prepositions of the research are:
1) There is meaningful relation between regional learning variables in industrial firms of food and auto parts industries in Toos Industrial Township;
2) Regional learning variables influence innovation of food and auto parts industries locating in Toos Industrial Township.
A quantitative method was used to test these prepositions. First, required data for regional learning features and firms’ innovation were collected through half-structured interview with mangers. Then,
the regional learning features of the two studied industries were described and regional learning variables of these firms were compared, then, the effect of these variables on the regional innovation was examined. Collected data were analyzed using t-test for Equality of Means for comparing of groups of firms and correlation and linear regression for examining effect of regional learning on innovation. Statistical analysis was done using SPSS software.
Results and Discussion
Results show that firms are different in some components of regional learning and are equal in the rest. T-test for equality of means confirms the inequality with 90 percent level of significance only in variables of feedback providing and size of firms. The preposition was rejected regarding variables of commercial relations, receiving feedback, horizontal relations, competition among firms, employing local skilled labor, and relation with academic institutional infrastructure. Considering the second preposition, significance of affecting of some regional learning variables such as size of firms, competition among firms, employing local skilled labor and relation with academic institutional infrastructure on the innovation of the firms was confirmed; it was calculated that 44% of varieties of firms innovation was the result of difference in their regional learning variables (correlation coefficient = 0.67).
Model Unstandardized Coefficients Standardized Coefficients t Sig.
B Std. Error Beta B Std. Error
1 (Constant) .175 .670 .261 .796
Vertical relations -.045 .076 -.085 -.595 .556
Horizontal relations .094 .084 .150 1.122 .270
Size of the firms (number of employees) -.175 .078 -.312 -2.255 .031
Number of Competitor) .235 .085 .396 2.765 .009
Ratio local labor in the total labor .133 .078 .237 1.708 .097
Relation with academic institutions .097 .052 .250 1.856 .072
Providing feedback -.102 .063 -.227 -1.608 .117
Receiving feedback .001 .032 .006 .045 .964
Conclusion
Given the fact that the impact of regional learning variables on innovations of firm was confirmed in the case study, thus, the reinforcement of these characteristics seems to be necessary. Accordingly, since relation with scientific institutes highly influences firms’ innovation in the studied cases, paying especial care on relations of firms and academic institutes and providing necessary institutional infrastructures to strengthen this relation can positively influence innovation of firms locating in Toos Industrial Township. In addition, academic institutions and facilitated relation between them and industrial firms must be taken into consideration in development of third phase of Toos Industrial Township. It was confirmed that smaller firms have more innovative employees; accordingly, firms can add to their products’ competitiveness. Out-sending can make firms more specialized and innovative. Taking into account that the third phase of the Township is under preparation, allocating facilities for small and medium firms can add to innovation in township level and promote its status.
Based on observations, firms locating in the studied Industrial Township (in both groups) had low level of non-zero horizontal relations, which explains meaningful influence of these relations on firms’ innovation. Cooperation among industrial firms – either within official or non-official frameworks – and formation of horizontal relations among them are known as the most influential factors in firms’ innovation. These relations among firms can help their becoming more innovative and consequently more competitive.
Based on the present research, numerous competitors for a firm is an influential factor for its innovation. Thus, homogenizing industrial sites – in a way that variety of producers exist for each stage of production chain – is a useful strategy to improve firms’ innovation.
