Kobi'lerde rekabetçiliği etkileyen değişkenlerin analizi ve kobi rekabetçilik endeksi: örme sektörü uygulaması
Kobi'lerde rekabetçiliği etkileyen değişkenlerin analizi ve kobi rekabetçilik endeksi: örme sektörü uygulaması
Dosyalar
Tarih
2019
Yazarlar
Taçoğlu, Caner
Süreli Yayın başlığı
Süreli Yayın ISSN
Cilt Başlığı
Yayınevi
Fen Bilimleri Enstitüsü
Institute of Science and Technology
Institute of Science and Technology
Özet
Rekabetçilik kavramı uzun yıllardır var olmakla birlikte, özellikle 1980 sonrası dönemde bilgi, iletişim ve teknoloji alanlarındaki hızlı gelişmeler aracılığı ile artan küreselleşme, bu kavramın önemini arttırmış ve üzerinde daha çok konuşulur hale getirmiştir. Rekabetçilik günümüzde işletmelerde, endüstrilerde ve şehirlerden ülkelere kadar uzanan geniş bir yelpazede yer alabilmektedir. Rekabet gücünün artması, işletmeler veya ülkeler için büyüme ve gelişmeyi kolaylaştırmaktadır. Diğer yandan rekabet güçlerini arttıramayan işletmeler zaman içerisinde gerilemekte, müşteri kaybetmekte ve kapanma tehlikesiyle karşı karşıya gelmektedir. Bu işletmeler arasında Küçük ve Orta Ölçekli İşletmeler (KOBİ) ayrı bir öneme sahiptir. Zira KOBİ'ler, ülke ekonomilerinin temel dinamiğini oluştururlar. İstihdamın büyük bölümü, üretim, katma değer, ciro ve ihracatın önemli kısmı KOBİ'ler tarafından sağlanmaktadır. Bu nedenle KOBİ'lerin performansları ülke ekonomilerini doğrudan etkilemektedir. Rekabetçiliğin öneminin artması sonucunda dünyanın her yerinden birçok bilim insanı ile birlikte ulusal veya uluslararası kuruluşlar rekabetçiliğe yönelik farklı çalışmalar yapmış, rekabet gücünün nasıl arttırılabileceğini araştırmış ve rekabetçiliği ölçen endeksler oluşturmaya çalışmıştır. Rekabetçilik ile ilgili ulusal ve uluslararası veritabanları, geniş literatür taramaları ve aynı zamanda proje ve akademik çalışmalar incelenmiş olup, bu çalışmaların genellikle ülke bazında veya büyük ölçekli işletmeler bazında yapıldığı ve KOBİ ölçeğinde rekabetçiliği ölçen, inceleyen ve analiz eden bilimsel çalışmaların yetersiz olduğu gözlemlenmiştir. Dolayısıyla KOBİ'lerin rekabet gücünü arttırabilmek için rekabetçiliği etkileyen değişkenlerin bilimsel yaklaşımla analiz edilmesine ve KOBİ rekabetçiliğini ölçebilen sistematik yöntemlerin oluşturulmasına ihtiyaç olduğu anlaşılmaktadır. Bu çalışma, KOBİ'lerin rekabet güçlerini arttırabilmek için rekabetçiliği etkileyen değişkenleri bütünsel bir yaklaşım aracılığı ve bu çalışmada önerilen melez yöntem ile analiz ederek KOBİ Rekabetçilik Endeksi oluşturmayı hedeflemektedir. Rekabetçiliği etkileyen değişkenlerin bütünsel analizi ve orijinal algoritma ile oluşturulan KOBİ Rekabetçilik Endeksi'nin sistematik çerçevesi, rekabetçilik literatürüne katkıda bulunmayı ve KOBİ yöneticilerine strateji ve politika önerileri geliştirmeyi amaçlamaktadır. Bu çalışma birbirini takip eden iki bölümden oluşmaktadır. Birinci bölümde, rekabetçiliği etkileyen değişkenlerin belirlenmesinin ardından bu değişkenlerin analizi için Delphi ve bulanık DEMATEL (Decision-Making Trial and Evaluation Laboratory) yöntemleri kullanılarak bu çalışmaya özgü melez bir yöntem oluşturulmuştur. Öncelikle, bütünsel analizi etkin kılabilmek için geniş kaynak çerçevesi altında, KOBİ rekabetçiliğini etkileyen 73 değişken, KOBİ'lerde Rekabetçiliği Etkileyen Değişkenler Havuzunda toplanmıştır. Ardından 3 aşamadan oluşan melez yöntemin aşamalarına geçilmiştir. Melez yöntemin birinci aşamasında sahadaki uzmanlar aracılığı ile 73 değişkenden oluşan havuz, tekrar gözden geçirilip filtrelenerek imalat sanayisine özel 60 değişkene indirilmiştir. Melez yöntemin ikinci aşamasında tekstil sektörüne yoğunlaşılarak KOBİ rekabetçiliğini etkileyen 60 değişken arasından en önemli 15 değişken belirlenmiştir. Son aşamada ise, bu değişkenler analiz edilmiş, sıralanmış ve değişkenlerin nedensel ilişkileri haritalanmıştır. Bu sayede, tekstil sektöründeki KOBİ yöneticileri, önemli değişkenlere yoğunlaşarak rekabetçiliğin arttırılmasında rol oynayacak stratejik yöntem ve önerileri ele alabilecektir. Çalışmanın ikinci bölümünde, KOBİ rekabetçiliğini ölçmeye yarayan KOBİ Rekabetçilik Endeksi oluşturulmuştur. Bu endeks, üç aşamadan oluşan orijinal ve sistematik bir algoritmayı takip eder. Algoritmanın birinci aşaması melez yöntemi ve melez yöntemden elde edilen verileri kapsar. Algoritmanın ikinci aşamasında rekabetçiliği ölçmek için kullanılan ölçüm soruları ve ölçüm sorularının ölçeklerinin nasıl belirleneceği yer alır. Son aşamada ise, endeksin uygulandığı KOBİ'ler için matematiksel puan hesaplamaları yapılır. KOBİ Rekabetçilik Endeksi'nin kullanılabilirliğini kanıtlamak için algoritmanın ampirik uygulaması tekstil alt sektöründe yer alan örgü sanayisine uygulanmıştır. Öncelikle, bu değişkenleri ölçebilmek için uzmanlar aracılığı ile sektöre özgü ölçekler belirlenmiştir. KOBİ Rekabetçilik Endeksi daha sonra, Türkiye'de İzmir, Bursa ve Denizli'de faaliyet gösteren 32 örgü sanayi KOBİ'lerine sektöre özgü ölçekler kullanılarak uygulanmıştır. KOBİ Rekabetçilik Endeksi'nin ampirik uygulamasından elde edilen sonuçlar, örgü sanayi için endüstriyel standartları ortaya çıkaran değerli makro ve mikro çıkarımlar sunmaktadır. KOBİ Rekabetçilik Endeksi sonucu KOBİ'lerin güçlü ve zayıf rekabetçilik yönlerini ortaya çıkaran bireysel KOBİ rekabetçilik analizi raporları bu çalışmanın sonuçlarından elde edilebilir. Bu çalışmadan elde edilen sonuçlar, KOBİ'lerin ilgili sektördeki rekabet güçlerini arttırmayı hedefleyen ve stratejik rekabetçilik geliştirme politikalarını içeren bir rehber ve yol haritası oluşturmada kullanılabilir. Rekabetçiliği etkileyen değişkenlerin bir arada toplanması, melez yöntem aracılığı ile analizi ve rekabetçiliği ölçen orijinal algoritma ile yaratılan KOBİ Rekabetçilik Endeksi, rekabetçilik literatüründeki eksikliklere önemli katkılarda bulunmayı hedeflemektedir.
Although the concept of competitiveness has existed for many years, the increasing globalization especially through the rapid developments in the fields of information, communication and technology in the post 1980 period has affected the importance of this concept greatly. Competitiveness can take place in a wide range of things including businesses, industries, cities or countries. Increasing competitiveness facilitates growth and development of businesses and countries. On the other hand, enterprises that do not increase their competitiveness are declining in performance over time, losing customers and facing the danger of closing. Small and Medium-sized Enterprises (SMEs) have a special importance among these enterprises. SMEs form the basic dynamics of national economies. In nations, majority of the employment and a significant part of production, revenues and exports are provided by SMEs. Therefore, the performance of SMEs directly affect the economic power of a country. As a result of the increased importance of competitiveness, many scientists from all over the world and national or international organizations conducted different studies on competitiveness. They researched how to increase the competitive power of nations and businesses and tried to create indices that measure competitiveness. In this study, national and international datasets related to competitiveness, extensive literature reviews, as well as projects and academic studies have been examined, and it has been observed that there is a lack of competitiveness studies on SME scale. Therefore, it is understood that there is a need for studies that analyze the SME competitiveness by exploring the variables that affect competitiveness using scientific approach and creating systematic methods that can measure SME competitiveness. This study aims to create an SME Competitiveness Index by analyzing the variables that affect competitiveness using holistic approach, a proposed hybrid method and a systematic index algorithm. The holistic analysis of the variables affecting competitiveness and the systematic framework of the SME Competitiveness Index aims to contribute to the competitiveness literature and develop strategy and policy recommendations for SME managers. This study consists of two consecutive chapters. In the first chapter, following the determination of the variables that affect competitiveness, a hybrid method specific to this study was created by using Delphi and fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) methods. First of all in order to make an effective holistic analysis, 73 variables affecting the SME competitiveness were collected in the SME Competitiveness Variable Pool using broad literature review. Then, the 3 phased hybrid method was introduced. In the first phase of the hybrid method, the SME Competitiveness Variable pool was reviewed and filtered by the experts in the manufacturing industry, and 60 competitiveness variables specific to the manufacturing industry were selected. In the second stage of the hybrid method, most important 15 variables were determined among the 60 variables affecting the SME competitiveness, this time focusing on the textile sector. In the final stage, most important 15 variables were analyzed, ranked and the causal relationships of the variables were mapped using fuzzy DEMATEL method. Using the results gained from the hybrid method, SME managers in the textile sector were able to discuss strategic methods and suggestions that can play a significant role in increasing the competitiveness of their firms. The results of the first chapter suggest important managerial implications. Some are deducted directly from the fuzzy DEMATEL results, and others are our recommendations to managers operating in the field of textile industry based on the results of our model. Employee Skills is a high influencer and one of the key variables for focus and improvements to Product Quality should be another priority. To increase customer satisfaction, influencer variables, such as these should be addressed first. A good pricing strategy is not influenced by Product Cost as much as Product Quality. Influencer variables have no considerable impact on the Degree of Customer Orientation. Therefore, it is crucial for managers to implement TQM strategies to increase their firm's competitive power. Conducting personality and skill tests before hiring, and implementing performance rewarding systems or programs that focus on improving Employee Skills should be a high priority for SME managers. Lastly, managers should be educated about the importance of logistics and responsiveness. There are also three research implications gained from the first chapter. Firstly, the competitiveness variable pool, in which all of the variables that affect competitiveness of SME's in the production field are accumulated, can form the basis for future studies. Secondly, using holistic approach in the analysis of competitiveness variables contributes to addressing the gap in the competitiveness literature. Thirdly, a hybrid model that investigates the variables that affect SME competitiveness was presented, as well as their degree of importance, in the textile industry. The hybrid model offers a platform to examine and analyze these variables by focusing on the opinions of valuable academic experts and SME managers. In the second chapter of the study, SME Competitiveness Index was established that measures SME competitiveness. This index follows an original and systematic algorithm consisting of three steps. The first step of the algorithm includes the hybrid method and the data obtained from the hybrid method application and results to the industry. In the second step of the algorithm, measurement questions and determination of the scales of measurement questions are included. At the last stage, mathematical calculations that gives the final score values of SMEs are shown. In order to prove the usability of the SME Competitiveness Index, the empirical application of the algorithm has been applied to the knitting industry in the textile sector. First, sector-specific scales were determined by experts to measure the competitiveness variables. After that, SME Competitiveness Index was applied to the 32 SMEs operating in Izmir, Bursa and Denizli in Turkey. The results obtained from the empirical application of the SME Competitiveness Index offers valuable macro and micro implications that reveal the industrial standards for the knitting industry. SMEs operating in Textile industry, knitting sub-sector severely lack the required emphasis on proactivity, employee skills and knowledge management. Research and Development should be supported, the hiring process should include skill and personality tests, ability management and TQM strategies should be implemented, meetings and external training should become more common. The absence of sufficient knowledge and expertise of correct resource management and allocation has lead SMEs in this sector to focus and improve misguided activities thus resulting in weak competitive power in the sector. SME managers should receive training on competitiveness, and become more aware of the industry standards. SME Competitiveness Index results can be used to derive micro firm level analysis reports. In this study, with the empirical application of SME Competitiveness index, detailed competitiveness reports for each SME that participated in the study was created. The summarized version of a sample report was presented. These results can be used to create a guide or a roadmap that aims to increase the competitiveness of SMEs in the relevant sector and develop strategic competitiveness policies. The SME Competitiveness Index, which is created by using the SME Competitiveness Variable Pool, hybrid method and the analysis of competitiveness variables with the original algorithm, aims to make significant contributions to the gap in the competitiveness literature. SME Competitiveness Index is applicable to any industry, however the scales must be defined by the relevant industry experts before the practical application. Also, the selected experts are still derived from human judgement and knowledge, therefore the scales may not perfectly represent the whole industry. However it still serves the purpose of enlightening the SME managers by providing the information on industry standards, competitor's standings and individual firm weaknesses It is imperative for SMEs to benchmark themselves with the available standards to continuously improve their business performance and competitive power. SME Competitiveness Index enables SMEs to have a clearer vision about their competitive strengths and weaknesses and benchmark themselves with the industry standards. We acknowledge that applying Delphi method has its own limitations and issues; however, the new modifications introduced in our study are designed to reduce these limitations. For the DEMATEL method, we use fuzzy method to further enhance the decision making process of SME managers. Using precise numerical values for human judgment and decisions can cause a lack of clarity, introducing fuzzy logic is essential in respect to issues inherently characterised by ambiguity and imprecision. However, although an appropriate method, fuzzy logic for DEMATEL can never be entirely problem free when dealing with human decisions. The competitiveness variable pool and the hybrid model framework can be applied to other sectors in the production field but it should be noted that the results obtained in this specific study apply only to the textile industry in Turkey. SME Competitiveness Index framework can be used in different country or sector contexts for the purposes of comparison. For future studies, each industry or sub-sector may contribute their own scales defined by the experts, therefore allowing the application of SME Competitiveness Index to any industry without any pre-work. When each sector or sub-sector have defined their own scales, the index can be used automatically for any SME and relevant benchmarking and analysis can be made for much higher sample sizes.
Although the concept of competitiveness has existed for many years, the increasing globalization especially through the rapid developments in the fields of information, communication and technology in the post 1980 period has affected the importance of this concept greatly. Competitiveness can take place in a wide range of things including businesses, industries, cities or countries. Increasing competitiveness facilitates growth and development of businesses and countries. On the other hand, enterprises that do not increase their competitiveness are declining in performance over time, losing customers and facing the danger of closing. Small and Medium-sized Enterprises (SMEs) have a special importance among these enterprises. SMEs form the basic dynamics of national economies. In nations, majority of the employment and a significant part of production, revenues and exports are provided by SMEs. Therefore, the performance of SMEs directly affect the economic power of a country. As a result of the increased importance of competitiveness, many scientists from all over the world and national or international organizations conducted different studies on competitiveness. They researched how to increase the competitive power of nations and businesses and tried to create indices that measure competitiveness. In this study, national and international datasets related to competitiveness, extensive literature reviews, as well as projects and academic studies have been examined, and it has been observed that there is a lack of competitiveness studies on SME scale. Therefore, it is understood that there is a need for studies that analyze the SME competitiveness by exploring the variables that affect competitiveness using scientific approach and creating systematic methods that can measure SME competitiveness. This study aims to create an SME Competitiveness Index by analyzing the variables that affect competitiveness using holistic approach, a proposed hybrid method and a systematic index algorithm. The holistic analysis of the variables affecting competitiveness and the systematic framework of the SME Competitiveness Index aims to contribute to the competitiveness literature and develop strategy and policy recommendations for SME managers. This study consists of two consecutive chapters. In the first chapter, following the determination of the variables that affect competitiveness, a hybrid method specific to this study was created by using Delphi and fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) methods. First of all in order to make an effective holistic analysis, 73 variables affecting the SME competitiveness were collected in the SME Competitiveness Variable Pool using broad literature review. Then, the 3 phased hybrid method was introduced. In the first phase of the hybrid method, the SME Competitiveness Variable pool was reviewed and filtered by the experts in the manufacturing industry, and 60 competitiveness variables specific to the manufacturing industry were selected. In the second stage of the hybrid method, most important 15 variables were determined among the 60 variables affecting the SME competitiveness, this time focusing on the textile sector. In the final stage, most important 15 variables were analyzed, ranked and the causal relationships of the variables were mapped using fuzzy DEMATEL method. Using the results gained from the hybrid method, SME managers in the textile sector were able to discuss strategic methods and suggestions that can play a significant role in increasing the competitiveness of their firms. The results of the first chapter suggest important managerial implications. Some are deducted directly from the fuzzy DEMATEL results, and others are our recommendations to managers operating in the field of textile industry based on the results of our model. Employee Skills is a high influencer and one of the key variables for focus and improvements to Product Quality should be another priority. To increase customer satisfaction, influencer variables, such as these should be addressed first. A good pricing strategy is not influenced by Product Cost as much as Product Quality. Influencer variables have no considerable impact on the Degree of Customer Orientation. Therefore, it is crucial for managers to implement TQM strategies to increase their firm's competitive power. Conducting personality and skill tests before hiring, and implementing performance rewarding systems or programs that focus on improving Employee Skills should be a high priority for SME managers. Lastly, managers should be educated about the importance of logistics and responsiveness. There are also three research implications gained from the first chapter. Firstly, the competitiveness variable pool, in which all of the variables that affect competitiveness of SME's in the production field are accumulated, can form the basis for future studies. Secondly, using holistic approach in the analysis of competitiveness variables contributes to addressing the gap in the competitiveness literature. Thirdly, a hybrid model that investigates the variables that affect SME competitiveness was presented, as well as their degree of importance, in the textile industry. The hybrid model offers a platform to examine and analyze these variables by focusing on the opinions of valuable academic experts and SME managers. In the second chapter of the study, SME Competitiveness Index was established that measures SME competitiveness. This index follows an original and systematic algorithm consisting of three steps. The first step of the algorithm includes the hybrid method and the data obtained from the hybrid method application and results to the industry. In the second step of the algorithm, measurement questions and determination of the scales of measurement questions are included. At the last stage, mathematical calculations that gives the final score values of SMEs are shown. In order to prove the usability of the SME Competitiveness Index, the empirical application of the algorithm has been applied to the knitting industry in the textile sector. First, sector-specific scales were determined by experts to measure the competitiveness variables. After that, SME Competitiveness Index was applied to the 32 SMEs operating in Izmir, Bursa and Denizli in Turkey. The results obtained from the empirical application of the SME Competitiveness Index offers valuable macro and micro implications that reveal the industrial standards for the knitting industry. SMEs operating in Textile industry, knitting sub-sector severely lack the required emphasis on proactivity, employee skills and knowledge management. Research and Development should be supported, the hiring process should include skill and personality tests, ability management and TQM strategies should be implemented, meetings and external training should become more common. The absence of sufficient knowledge and expertise of correct resource management and allocation has lead SMEs in this sector to focus and improve misguided activities thus resulting in weak competitive power in the sector. SME managers should receive training on competitiveness, and become more aware of the industry standards. SME Competitiveness Index results can be used to derive micro firm level analysis reports. In this study, with the empirical application of SME Competitiveness index, detailed competitiveness reports for each SME that participated in the study was created. The summarized version of a sample report was presented. These results can be used to create a guide or a roadmap that aims to increase the competitiveness of SMEs in the relevant sector and develop strategic competitiveness policies. The SME Competitiveness Index, which is created by using the SME Competitiveness Variable Pool, hybrid method and the analysis of competitiveness variables with the original algorithm, aims to make significant contributions to the gap in the competitiveness literature. SME Competitiveness Index is applicable to any industry, however the scales must be defined by the relevant industry experts before the practical application. Also, the selected experts are still derived from human judgement and knowledge, therefore the scales may not perfectly represent the whole industry. However it still serves the purpose of enlightening the SME managers by providing the information on industry standards, competitor's standings and individual firm weaknesses It is imperative for SMEs to benchmark themselves with the available standards to continuously improve their business performance and competitive power. SME Competitiveness Index enables SMEs to have a clearer vision about their competitive strengths and weaknesses and benchmark themselves with the industry standards. We acknowledge that applying Delphi method has its own limitations and issues; however, the new modifications introduced in our study are designed to reduce these limitations. For the DEMATEL method, we use fuzzy method to further enhance the decision making process of SME managers. Using precise numerical values for human judgment and decisions can cause a lack of clarity, introducing fuzzy logic is essential in respect to issues inherently characterised by ambiguity and imprecision. However, although an appropriate method, fuzzy logic for DEMATEL can never be entirely problem free when dealing with human decisions. The competitiveness variable pool and the hybrid model framework can be applied to other sectors in the production field but it should be noted that the results obtained in this specific study apply only to the textile industry in Turkey. SME Competitiveness Index framework can be used in different country or sector contexts for the purposes of comparison. For future studies, each industry or sub-sector may contribute their own scales defined by the experts, therefore allowing the application of SME Competitiveness Index to any industry without any pre-work. When each sector or sub-sector have defined their own scales, the index can be used automatically for any SME and relevant benchmarking and analysis can be made for much higher sample sizes.
Açıklama
Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2019
Thesis (Ph.D.) -- Istanbul Technical University, Institute of Science and Technology, 2019
Thesis (Ph.D.) -- Istanbul Technical University, Institute of Science and Technology, 2019
Anahtar kelimeler
Bulanık DEMATEL,
Delphi tekniği,
KOBİ,
Fuzzy DEMATEL,
Delphi technique,
Small and Medium Sized Firms