Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2016 ; Thesis (PhD) -- İstanbul Technical University, Institute of Science and Technology, 2016 ; Günümüzde firma sınırlarının çok ötesine geçen inovasyon için işbirliği yapmak, özellikle küçük ve orta ölçekli işletmeler için hayati önem taşımaktadır. İşbirliği ağları ve inovasyon birbirinden kopmaz bir duruma gelmiştir. Bundan hareketle, bu alanda önde gelen veri tabanlarından öncelikle son yıllarda yapılmış çalışmaları da kapsayacak şekilde literatür taraması yapılmıştır. Kobilerin yaptıkları bu işbirlikleri firma sınırları dışında iken, firma sınırları içinde ise, inovasyon yeteneklerini ve performanslarını etkileyen organizasyonel faktörler olarak, öğrenme yeteneği ve absorbe kapasitesi belirlenmiştir. Daha sonra uluslararası literatürün yanı sıra, Türkiye'de yapılan projeler ve akademik çalışmalar incelenmiştir. Bu çalışmalar değerlendirildiğinde, işbirliği ağları ve inovasyon ilişkisi üzerine yapılan çalışmaların, son yıllarda odaklanılan konulardan birisi olduğu gözükmektedir. Türkiye gibi gelişen ekonomilere sahip ülkelerde, kobilerin inovasyon yeteneklerinin artırılması konusu devlet politikalarının önemli bir ayağını oluşturmaktadır. Bunun yanı sıra, Türkiye'de yapılan çalışmalar, genellikle belli iller ve bölgelerin yanı sıra, sadece belli sektörler üzerinde yoğunlaşmaktadır. Ayrıca, Türkiye'de yapılan çalışmalarda absorbe kapasitesinin işbirliği ağları ve inovasyon ile olan ilişkisini inceleyen bir çalışmaya ise rastlanmamaktadır. Dolayısıyla, kobilerin inovasyon yetenekleri ve işbirlikleri ile ilgili yapılacak çalışmalara ve ortaya konulacak politikalara yön vermesi açısından, bu konuda yapılacak akademik araştırmalara ihtiyaç olduğu gözükmektedir. Bu yüzden, yapılan çalışmada, bu alandaki boşlukların doldurulması açısından, işbirliği ağları ve inovasyon ile ilgili literatürde değinilen kavramları inceleyen kapsayıcı bir model kurulmuştur. Model oluşturulurken ele alınan bu yaklaşım ile her bir yeteneğin tanımlamasına uygun olarak konumlandırmaları yapılmış ve aralarındaki ilişkiler belirlenmiştir. Dolayısıyla bu üç kavram, kobilerin yaptıkları işbirlikleri ile inovasyon arasındaki ilişkiyi temel alan bu araştırmada, literatüre uyumlu, kapsayıcı ve bütünleştirici olarak sunulmuştur. Daha sonra modeldeki kavramların operasyonel tanımlamaları yapılmış ve değişkenler tanımlanmıştır. Bu kapsamda, işbirliği ağları için tüm işbirliklerini içerecek ve işbirliğinin yoğunluğunu da soracak şekilde ölçek oluşturulmuştur. Organizasyonel öğrenme yeteneği ve absorbe kapasitesi için hâlihazırda literatürde geliştirilmiş ölçekler kullanılmıştır. İnovasyon ölçümü konusunda da, ölçüm modelleri incelenerek çalışmaya uygun bir model oluşturulmuş ve inovasyon yeteneği ve inovasyon performansı olarak ayrı ayrı ele alınmıştır. İnovasyon yeteneğinin ölçümü için literatürdeki çalışmalar dikkatlice incelenerek ölçüm havuzu oluşturulmuş ve yapılan uygulama ile inovasyon yeteneği ölçüm skalası geliştirilmiştir. İnovasyon performansı için literatürdeki en yaygın olarak kullanılan değişkenlerden ölçüm soruları belirlenmiştir. Dolayısıyla çalışmada kullanılacak anket soruları için tüm girdiler sağlanmıştır. Kosgeb ve İTÜ-BAP aracılığı ile veri toplama gerçekleştirilmiştir. Elde edilen veriler ayıklanmış ve paket programlar yardımıyla açıklayıcı istatistiksel analizlerin yanı sıra, modelin test edilmesi için yapısal eşitlik modellemesi yöntemi uygulanmıştır. İki aşamalı yaklaşım uygulanarak önce ölçme kısmı doğrulayıcı faktör analizi yardımıyla test edilmiş ve yapılan modifikasyonlarla nihai ölçümler elde edilmiştir. Daha sonra hipotezlerde belirtilen ilişkiler eklenerek yapısal model kurulmuş, yapılan analizler ile hipotezler test edilmiş ve elde edilen bulgular literatür ile karşılaştırılarak tartışılmıştır. Elde edilen sonuçları, çalışmanın amacı göz önünde bulundurularak şu şekilde özetlemek mümkündür. Kobilerin müşteriler ile yapılan işbirlikleri en yoğun işbirliği türü olurken, en düşük işbirliği derecesi ise araştırma merkezleri ve enstitüleri ile olduğu gözükmektedir. İşbirliği kümeleri olarak işbirliği derecesine bakıldığında ise; firmalar, aracı kurumlar, kamu destek kurumları ve araştırma örgütleri olarak sıralanmaktadır. İşbirliği ağlarının diğer değişkenlerle ilişkisi hem ikinci seviye örtük değişken olarak alınıp, topluca değerlendirilmiş, hem de alt seviye örtük değişkenler ile ayrı bir model kurularak incelenmiştir. İşbirliği ağları olarak genel ele alındığında, absorbe kapasitesi ile ilişkisi literatürde ileri sürülen şekliyle pozitif olarak gerçekleşmişken, inovasyon yeteneği ve inovasyon performansı üzerinde doğrudan bir etkisi bulunamamıştır. Diğer yandan, absorbe kapasitesinin inovasyon yeteneği ve inovasyon performansı üzerinde anlamlı pozitif bir etkisinin olduğu görülmektedir. Dolayısıyla, kobilerin bilgiyi elde edip, o bilgiden yeni bilgiler elde ederek faydalanma kapasiteleri arttıkça, inovasyon yetenekleri artmakta ve sonrasında inovasyon performansına dönüşmektedir. İkinci olarak, kamu destek kurumlarını ile yapılan işbirlikleri ve alınan destekler, inovasyon yeteneklerini artırırken, araştırma örgütleri ve aracı kurumlar ile yapılan işbirliklerini inovasyon yeteneklerini azaltmaktadır. Diğer yandan, sadece pazarlama inovasyon yeteneğinin inovasyon performansı üzerinde etkisi varken, diğer inovasyon yetenek türlerinin etkisinin bulunmaması önemli bir bulgudur. Bu çalışmada elde edilen sonuçlar, başta kobiler olmak üzere, kamu destek ve araştırma kurumları, aracı kurumlar için politika yapıcılar ve kanun koyucular için önemli bir referans kaynağıdır. Bu amaçla tüm bu kesimlere yönelik çıkarımlar ve ileride yapılabilecek çalışmalar hakkında bilgiler aktarılmıştır. Ayrıca, bu çalışmalar kapsamında, TÜBİTAK yurtdışı doktora sırası araştırma bursu ile University of Kentucky, ABD de 1 yıl süre ile araştırmalar yapılmıştır. ; Nowadays, innovation has gone beyond the boundaries of a firm and needs more partnerships than available within the organization, especially for small and medium size enterprises. Organizations must be innovative to have a competitive advantage by developing new products, processes, novel marketing, and organizational methods. In order to become innovative, an organization has to develop and improve its innovation capability. Firms' innovation capability is not only determined by internal factors, but also depends on the nature a firm's interaction with external actors. Cooperation with research organizations, public support institutions, intermediary organizations and other firms as external actors play an important role in innovation capability. The relationship between cooperation networks and innovation is one of the most popular issues in the innovation management field. In order to constitute a base for this relationship, a literature review especially on recent studies was conducted. Absorptive capacity, organizational learning capability, and innovation capability and performance are determined as internal factors in accordance with the literature. At the same time, dissertations, projects and other academic studies about this issue conducted in Turkey were investigated. There are many studies about innovation, especially product innovation is the most frequently studied one. Some of them focus on a single sector, e.g. manufacturing, and specific region or province in Turkey, e.g. Marmara Region. In addition, all sectors and regions should be taken into consideration in accordance with the classification of small and medium enterprises development organization in 2012. Because, government and other policy makers consider SMEs from whole sectors and regions in Turkey while developing strategies and policies for SMEs. This is very important to for the generalizability of the results of this study. Moreover, Turkish government and other public organizations need comprehensive models to determine policies for SMEs while the relationships between absorptive capacity, cooperation networks and innovation were not come across in Turkish studies. Moreover, the study should incorporate all innovation types (product, process, organizational, and marketing) in accordance with the literature. At the same time, the output of innovation capability which is defined as innovation performance should be investigated in order to see whether innovation capability converts into innovation performance. In light of these explanations above, it is seen that there are some gaps in this field. In order to fulfill these gaps, more research is needed to better understand the role of cooperation for innovation. For this reason, the aim of this study is proposition of an overarching model and validation of it by industry data. This model presents an integrated approach that clarifies the relationship between cooperation networks and innovation taking internal factors into consideration by employing literature review. SMEs should use knowledge acquired from collaborations, then assimilate and transform it in order to gain new knowledge via their absorptive capacities. Absorptive capacity is defined as the firm's ability to identify, assimilate, and exploit knowledge gained from external sources. The capability that use and convert this knowledge into new product, process, method, organizational models, and innovations is innovation capability. Organizational learning capability is also a moderator capability that can be considered providing a firm atmosphere in order to constitute necessary condition for organizational learning instead of a capability that does not focus on firm learning processes. Although there are many studies about these three capabilities in terms of relationships between cooperation networks and innovation, there is no consensus on the relationships among them. Therefore these three concepts should be taken into consideration together and comprehensively. An integrated approach was used while proposing the conceptual model, making operational definition, and measuring these concepts. In terms of operational definition and measurement, cooperation networks were classified in four groups as: research organizations, public support institutions, intermediary organizations and other firms in accordance with the literature. Research organizations consist of universities, research centers and institutes, community colleges and academies. Public support institutions include the scientific and technological research council of Turkey, small and medium enterprises development organization, development agencies, and other ministries. Intermediary organizations contain commercial and industry associations, commercial labs, service providers, non-governmental organizations, and venture capital organizations. Other firms also comprise customers, suppliers, and rivals. At the same time, scales that are available in the literature were used for absorptive capacity and organizational learning capability. There are different approaches about conceptualizing and measuring in absorptive capacity literature. In this study, four-factor measure of absorptive capacity was used as acquisition, assimilation, transformation, and exploitation. Similarly, researchers have conceptualized and measured organizational learning capability differently. Because of the nature of learning, organizational learning capability should be measured as multidimensional approach. These dimensions are called managerial commitment, systems perspective, openness and experimentation, and knowledge transfer and integration were considered in this study. Moreover, absorptive capacity and learning capability measurement scales were used in order to provide accordance with the model. On the other hand, special attention was paid to innovation measurement. Innovation capability and innovation performance measurement were separated in accordance with proposed model in order to observe the results of innovation. In the literature, innovation capability is mentioned in a good number of studies; however, innovation capability measurement scale and proposed measurement models have been limited. The measurement of innovation is difficult because of the broad nature of the scope of innovative activities. Simultaneously, innovation capability and related concepts such as innovation performance, innovation capacity, innovative capability, innovativeness, organizational innovation, and innovation have been interchangeably used in the literature. Interchangeable usage of these concepts has caused confusion in defining and measuring innovation capability. The aim of this phase is to generate a solution in order to eliminate this confusion by presenting a literature-based model and developing a scale for measuring innovation capability. For this purpose, first, a conceptual model of innovation capability measurement based on a review of the innovation capability and performance measurement literature was proposed. Each model in the literature review was analyzed based on its own focus to decide components of our model. After that, measurement scale items were gathered from literature and eliminated by evaluating each item while taking into account assumptions of proposed model consideration. Then, these items were sent to business and academic experts to evaluate the initial item pool in accordance with measuring innovation capability and the final items pool was gained. After this step, a survey was conducted to collect data and factor analysis was conducted to develop the measurement scale for innovation capability. While obtaining measurement scale for innovation capability, innovation performance literature was reviewed and gained the most cited items to be used to evaluate innovation performance. In the event, a literature based measurement scale was obtained for innovation performance. In order to test the model hypotheses after operational definitions and measurements, data collection phase was conducted. In order to overcome the difficulties of data collection, supports from Istanbul Technical University- scientific research project center and Kosgeb were received. In this phase, a web-based survey was prepared with explanatory information of the companies (year of establishment, sector, number of employee, and position of respondent) to collect data. An e-mail invitation that included a brief introduction and a link to the web questionnaire was sent to a senior manager by using computer aided telephone interview method to encourage them to participate. A number of screening questions were used to ensure only qualified respondents participated in the survey. The five-point Likert scales that ranged from "strongly disagree" to "strongly agree" was used to evaluate the questions. Overall, 450 questionnaires were returned, of which 366 were considered valid in accordance with sampling. Some descriptive statistics were obtained to see a general picture of data and cooperation networks. The type and degree of cooperation networks were analyzed in order to ask first questions of this research. The results show that SMEs have the strongest cooperation with their customers while the cooperation with research centers and institutes is the lowest. Furthermore, in terms of cooperation groups, the degree of cooperation ranged as firms, intermediary organizations, public support institutions, and research organizations, respectively. Structural equations modelling was conducted in order to test the model hypotheses. Measurement model and structural model were analyzed by employing two phase approach. For the measurement model, confirmatory factor analysis was conducted to validate measurements and to obtain final measurements in order to create the structural model. For this purpose, every one of the concepts -called latent variable in SEM- was analyzed to provide reliability, construct, convergent, and discriminant validity, and also goodness of fitness. These analyses were conducted step by step for every latent variable via modification index by helping AMOS and "Stats Tools Package" software. After these analyses, 'firms' variable was removed from cooperation networks latent variable due to not having sufficient validation. Other latent variables maintain to have the same first level latent variables even though they missed some observed variables. In the second phase, all validated latent variable put together by establishing the relationships from literature to obtain structural model in order to test the hypothesis. According to the results, cooperation networks have a direct positive influence on absorptive capacity while there is no significant effect on innovation capability and innovation performance directly. On the contrary, absorptive capacity has a positive effect not only on innovation capability, but also on innovation performance. Similarly, a positive relationship between innovation capability and innovation performance was found. At the same time, a separated structural model was established to see whether there is a relationship among cooperation types and innovation types. The results show that public support organizations have positive effects on every innovation type while there is no significant impact on innovation performance directly. Hence, public support organizations should revise the support policy to increase the SMEs' innovation output. Furthermore, research organizations and intermediary associations have no significantly direct influence on innovation performance while there are negative relationships between research organizations and every innovation type, and between intermediary associations and every innovation type, too. This result indicate research organizations and intermediary associations should scrutinize and revise their collaboration policy and strategies for SMEs. In a similar vein, SMEs should pay more attention to cooperate with research organizations and intermediary associations and lean towards innovation-oriented collaboration. On the other hand, the relationship between innovation capability types and innovation performance was analyzed to see the innovation output convertibility of SMEs. Marketing innovation capability has a direct effect on innovation performance only while other types have no influences. It is shown that SMEs and their partnerships should pay special attention to product, process and organizational innovation. Consequently, these results obtained from analyses make valuable contributions to managers of SMEs and all stakeholders, policy makers and law makers to scrutinize and revise their policies and strategies in order to increase effective usage of resources in innovation oriented targets. For this purpose, managerial implications and further research were mentioned in the last part of the study. As well as these whole studies, scientific research on cooperation networks and innovation had been done for one year, at University of Kentucky, USA via support of TUBITAK, 2214-International Doctoral Research Fellowship Programme. ; Doktora ; PhD