بررسی عوامل کلیدی موفقیت در اجرای برنامه توسعه خوشه‌های صنعتی کشور
محورهای موضوعی : مدیریت صنعتی
Morteza Daraei
1
(Graduated Student in Executive Management)
Esfandiar Mohammadi
2
(Assistant Professor, Ilam University, Ilam, Iran)
Kiumars Ahmadi
3
(Assistant Professor in Management, Islamic Azad University, Sanandaj Branch, Sanandaj, Iran)
کلید واژه: Industrial clusters, خوشه‌های صنعتی, تیم عامل توسعه خوشه, سازمان کارگزاری و نهادهای پشتیبانی, فضای کسب و کار و توسعه پذیری خوشه‌های صنعتی, The cluster development agent, Broker organizations and support institutions, Business environment and development of industrial clusters,
چکیده مقاله :
این پژوهش با هدف بررسی عوامل کلیدی موفقیت در اجرای برنامه توسعه خوشه‌های صنعتی کشور انجام گردید. حجم نمونهٔ آماری پژوهش حاضر 107 نفر بود که این تعداد به روش نمونه‌گیری تصادفی از بین جامعه آماری و با استفاده از فرمول کوکران محاسبه گردید. ابزار پژوهش شامل پرسشنامه‌ای بود که روایی صوری آن بر اساس نظر جمعی از صاحب‌نظران و اساتید مجرب تأیید گردید. پایایی چهار دسته گویه پرسشنامه مذکور به ترتیب 78.1%، 88.1%، 72.3% و 80.6% به دست آمد. اطلاعات حاصل از تکمیل پرسشنامه، با استفاده از نرم‌افزار Win/ SPSS نسخه 21 در دو بخش آمار توصیفی و بخش آمار تحلیلی شامل آزمون سمیرنوف کولموگروف به منظور بررسی وضعیت نرمال بودن داده‌ها، آزمون فریدمن جهت رتبه‌بندی گویه‌ها و از آزمون مقایسه ای t تک نمونه ای به منظور آزمون فرضیات و پاسخ به سؤالات استفاده شد. یافته‌ها نشان داد که متغیرهای مربوط به تیم عامل توسعه خوشه، سازمان کارگزاری و نهادهای پشتیبانی، فضای کسب و کار و توسعه پذیری خوشه‌ها با اجرای موفقیت آمیز برنامه‌های توسعه خوشه‌ها دارای همبستگی مثبت و معنی داری می‌باشند و این متغیرها می‌تواند در موفقیت اجرای برنامه‌های توسعه خوشه‌های صنعتی مؤثر باشد. همچنین گویه‌های مرتبط با این عوامل نیز اولویت بندی گردیده و مشخص گردید که هر چقدر سطح مقیاس‌های ذکر شده افزایش یابد و از دیدگاه افراد بالاتر ارزیابی شود میزان موفقیت برنامه‌های توسعه خوشه‌ها نیز افزایش خواهد یافت
This study aimed to examine the key success factors in the implementation of the industrial cluster development in the country. Study sample size was 107 individuals randomly chosen from the population of these regions. The sample was calculated by using Cochran formula. Instruments included a questionnaire which its face validity was confirmed by a panel of experts and experienced instructors. The reliability of the four items of the questionnaire was 78.1%, 88.1%, 72.3% and 80.6%, respectively. Data from the completed questionnaires, using Win/SPSS version 21 of the Kolmogorov-Smirnov test statistics, descriptive and analytical statistics to assess the normality of the data, a Friedman test to rank the items in the single-sample t-test comparison was used to test the hypotheses and answer questions. Results showed that the variables associated with the cluster development agent, broker organizations and support institutions, business environment and development of clusters of clusters with the successful implementation of development programs is a positive and significant correlation. These variables can affect the success of the development of industrial clusters. These factors have also been linked to prioritize items. It was found that no matter how the scales will rise above and be evaluated from the perspective of people over the clusters will also increase the success rate of development.
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_||_1- Asmelash Beyene (2002). Enhancing the competitiveness and productivity of Small and Medium scale Enterprises (SMEs). In African analysis of differential roles of national governments through improved support services” Africa Development, XXVII, (3).
2- Cooke, Philip. (2002). Knowledge Economies Cluster, Learning and Cooperative Advantage", Rutledge Press.
3- Eraydin, A. Armatli-Koroglu, B. (2005). Innovation Networking and the new industrial clusters: the characteristics of networks and local innovation capabilities in the Turkish industrial clusters, Entrepreneurship and Regional Development, 17(7),237-266.
4- Hagen, Zucchella, Cerchiello, Givanni. (2012). International Strategy and performance clutring strategic types of smes.
5- Haggi, Pasabani. (2010). UNIDO's approach to the study of the development of industrial clusters SME.
6- Keeble, D. and Wilkinson, F. (2000). High-technology clusters, Networking and collective learning in Europe. Ashgate, England.
7- Lagendijk, A. and Cornford, J. (2000). Regional institutions and knowledge-tracking new forms of regional development policy. Geoforum 31, 209-218.
8- Mackinnon, D. Cumbers, Andrew and Chapman Keith. (2002). Learning, Innovation and regional development: acritical appraisal of recent debates. Progress in Human Geography, 26 (3).
9- Mansouri, isa. (2006). Introduction to industrial clusters, Small Industries & Industrial Parks Organization of Community Affairs, First Edition.
10- Mosaee, M. and Qozatloo Moayed. (2009). Development of knowledge (scientific research). 16(28), 2009.
11- Moulaert, F. and SekiaF. (2003). Territorial Innovation Models: A critical Survey, Regional Studies, 37 (3).
12- Schmitz, Hubert and Khalidi Nadwi. (2002). A new approach in the development of industrial clusters, industrial., translators: Zndbaf Abbas and Abbas informant, Tehran: the New Deal.
13- Zhan Qing, 2012intrenational conference on mechanical and electronic engineering. The research on influence of industrial clusters on regional economic development.
