The Third European Conference on Management of Technology "Industry-University Collaborations in Techno Parks" EuroMOT 2008 Proceedings MODELING TECHNOLOGY TRANSFER PROCESS: PROPOSITION OF A QUALITATIVE AND QUANTITATIVE OBSERVATION APPROACH H. KOOLI-CHAABANE, Nancy University / ERPI (Equipe de Recherche des processus Innovatifs, 8, rue Bastien Lepage 54010 Nancy Cedex, France, [email protected] M. CAMARGO, V. BOLY Nancy University / ERPI (Equipe de Recherche des processus Innovatifs, 8, rue Bastien Lepage 54010 Nancy Cedex, France [email protected], [email protected] B. YANNOU Ecole Centrale Paris / LGI (Laboratoire Génie Industriel, Grande Voie des Vignes F92290 Châtenay-Malabry, France) [email protected] Technology transfer is well recognized as one of the most critical factors to enhance innovative capabilities within firms. Technology transfer results from actions taken by various actors and organizations. One obstacle is: when the transfer emerges the participants don’t label it as technology transfer. This paper presents a comprehensive literature analysis about technology transfer factors of success. The aim is to study technology transfer in terms of stakeholders and material outcomes. Material outcomes are considered as vectors of knowledge as they are means of knowledge transfer. A quantitative and qualitative methodology is proposed to describe the technology transfer process. In particular, form and direction of exchange are pointed out as well as the nature of subjects discussed during the technology transfer project meetings. The main goal is to identify invariable patterns between several technology transfer projects in order to extract best practices. Our second goal is a better understanding of the technology transfer on a micro point of view. Keywords: technology transfer, methodology, factors of success, Intermediary Object, anthropology, qualitative. Introduction Recent studies suggest that the key of success for an organization is embodied in its ability to implement and appropriate new technology (Willmann, 1991). (Cohen and Levinthal, 1990) indicate that knowledge transfer is a critical factor in the firm’s ability to innovate. It contributes to allow firms to sustain a competitive advantage even in a dynamic industry context (Zahra and George, 2002; Chauvet, 2003). Technology transfer results from the actions taken by various actors and organizations. It can occur between university and industry, between two firms or more from the same country or from different ones, and between transfer agencies and industry. Technology transfer occurs informally and effectively in most business and other organisations. Often, when it happens the participants don’t label it as technology transfer or they are not aware that this is an activity they are undertaking. The term of “technology transfer” has several definitions. Moreover, because of its abstract nature, it is often difficult for potential participants to understand it in relation to their own set of circumstances. (Zhao and Reisman, 1992) note that the technology transfer definition differs substantially from one discipline to another. (Bozeman, 2000) affirms that it differs according to the purpose of the research too. As a result, there is no comprehensive definition covering all the technology transfer aspects. Trying to be too specific about its meaning and application field can restrict its usage and efficiency. Within the scope of this paper, we will define technology transfer as an exchange of ideas, practices, objects, know-how, technical knowledge, intellectual property, discovery or 1 invention resulting from scientific research conducted at universities, or in industry. This exchange process occurs between an institution that holds knowledge and an industrial one. This process is dynamic, limited in time and can involve other stakeholders such as public institutions or other industrial structures. The theoretical background of the present research is the constructivist framework (Seville and Perret, 1999; Glaserfeld, 1988; Lemoigne, 1995). In this context, the technological knowledge is considered as a progressive process of learning. This process is carried out by exchanges between actors. In addition, Bozeman’s position based on Sahal’s works (1981; 1982) is adopted. Bozeman considers the technology and knowledge transfer as inseparable: “Without the knowledge base the physical entity cannot be put to use. Thus, the knowledge base is inherent, not ancillary”. There are many models describing the process of technology transfer. Some models consider this process as a linear progression of steps. This process begins with idea generation and technology development at the university in order to establish a university-private firm relationship through a formal research agreement (Zhao and Reisman 1992; Cole 1992). Other models describe technology transfer as networking arrangements between two parties without relevant formal research. (Gilbert et al, 1996) propose a four steps process: “acquisition”, before being transferred, knowledge must be acquired. The organization might learn from its past, by doing, by acquiring individuals with new knowledge and by a continuous process of searching or scanning. “communication” of knowledge acquired. Communication may be written or verbal. Some barriers can prevent the dissemination of information. “application”, the third step is to apply the knowledge acquired and communicated to be retained. It is the result of the application of the knowledge that enables the organization to learn, rather than the knowledge itself. “assimilation”, the last step is the key to the process of knowledge transfer. It is the assimilation of the results and effects of applying the knowledge gained. This requires the transfer of the results of history into the routines of the organization. Another major concern is objects. Material outcomes are seen as a vector of knowledge (Vinck, 2006). They are means of knowledge transfer. This work aims to study technology transfer in term of stakeholders and material outcomes. Our main goal is to identify invariable patterns between technology transfer projects in order to extract best practices. Our second goal is a better understanding of the technology transfer in order to describe this process from a micro point of view. Thus, rigorous observation is necessary to describe technology transfer. In this paper a qualitative and quantitative experimental methodology of observation is presented. The objective is to test its pertinence towards a better understanding. This new model is proposed taking into account our special interest about knowledge and Intermediary objects. Thereafter, this paper is structured in three main sections. In section 1, an overview of factors that can enhance or inhibit the process of technology transfer is presented. After, in section 2, choices and methodology approaches are explained. Then data collection procedures and analysis method are detailed. The sample of firms is also described. In section 3, preliminary results are presented and discussed. Factors of success of technology transfer 2 Numerous practices have been proposed to improve technology transfer, such as adapting the management of the process, overcoming organizational (Gilbert, 1995) and human barriers (Carr, 1992) to success, making the process more systematic, improving the conveying of technologies, and increasing the users willingness (Sounder et al, 1990) to adopt new technologies. (Kumar and Uruthirapathy, 2007) reported that “It was often stressed by the technology transfer officers that successful technology transfer depends primarily on the people who are handling it. Confidence in each other, diligence, and trust are vital when different individuals meet for the purpose of technology transfer. Open interaction and dialogue is essential in building a true partnership”. The author’s investigation reported a strong believe that technology transfer is a people sport. (Sounder et al, 1990) summarize the best practices in categories such as analytical, facilities, pro-actions, people-roles, conditions, technology quality, and organization. The authors determined the importance of these factors during the four stages of technology transfer: prospective, development, testing, and adoption (see Table 1), For example, (Sounder et al, 1990) classified the factors “strategy matching”, “Open interactions”, “Transfer as R&D goal”, “R&D/User partners” and “Early involvement” as essential in different stages of technology transfer. Table 1 Summary of best practices (Sounder et al, 1990) 3 (Carr, 1992), through a series of interviews with technology transfer professionals in the U.S government, highlights some best practices in technology transfer. The author identifies methods and techniques that seem to be used to increase technology transfer effectiveness and outcomes. Carr’s conventional approach emphasizes people’s role as a key of success in technology transfer. Barriers to technology transfer are mostly man-made. (Carr, 1992) insists that the technology transfer process is a business activity and not a legal process. This process requires a champion on both sides. According to (Carr, 1992), the most active technology-transfer laboratories have a dedicated division and may be directly linked to associate-director or vice-president level. Usually, this division includes licensing, cooperative research and development activities and, less frequently, the patenting process. The author observes an evolution toward the consolidation of technology transfer efforts into a single function in order to achieve better coordination. All the laboratory management personnel are invited to support science and technology staff efforts. Recognizing the technology transfer formally can accelerate its activities. Formal or informal technology-transfer networks can also link the central technology-transfer office and the group level, thanks to individuals who are interested and knowledgeable in the field. The individuals making up the network may receive some formal training in technology transfer theory, policy, and practice. A major part of technology transfer is the passing of intellectual property from laboratories to private-sector firms. Training and assistance of technology transfer officials, members of technology-transfer networks, and scientists themselves to recognize their intellectual property will improve capturing them and participate to the technology transfer effectiveness. Many laboratories give significant award to inventors (or their research group) for any applied or received patent. (Erlich and Gutterman, 2003), outlined the importance of the protection of intellectual property and stated it as “the currency of technology transfer”. They consider that active participation of laboratory directors is critical to effecting cultural changes. (Cohen and Levinthal, 1990) introduced the concept of “absorptive capacity”, which refers to a firm’s ability to recognize the value of new, external information, assimilate it, and apply it to commercial ends. Since, this concept was largely used in many research fields (see (Zahra and George, 2002)), (Chauvet, 2003) tried to build a scale to measure the absorption capacity. (Cohen and Levinthal, 1990) argue that the ability to evaluate and utilize outside knowledge is largely a function of the level of prior related knowledge. In fact, we can consider that the success of a technology transfer in a firm is highly correlated to her “absorptive capacity”. (Kodama, 2008) conclude after an empirical study that the ‘absorptive capacity’ of the recipients firm’s is a key element for the success of university-industry linkages. The author finds that building an efficient regional technology-transfer system between universities and firms involves an intermediary function. (Trott et al,1995) found that successful transfers were due to the development of good working relationships, both within the developing and using organizations. (Greiner and Franza, 2003) present an interested point of view about key barriers and bridges in the environmental of technology transfer. (Kumar and Uruthirapathy, 2007) focus on a better understanding of the critical factors in technology transfer between government laboratories and another setting. Based on a literature review, the authors identified 17 factors and classified them into three categories: “technical”, “organizational” and “people”. “Technical” category deals with the technical and operational aspect of the transfer process: 4 (1) Technology dimensions that refer to the pertinence and quality (new, old, tangible…) of the transferred technology, (2) Strategy matching means if the transfer plan consider the adopter’s level of familiarity with the technology. If the technology transferred is new to the adopter, the unit takes this into consideration and deploys the most suitable strategy for transferring new technologies, (3) Post transfer inspection which is an assessment of the transfer results and whether the adopter’s need has been met by the technology, (4) Decision checklist designed to ensure that the technology choice is the best one to transfer, (5) Protection of intellectual property confirms the technology transfer unit had a clear procedure to protect her intellectual properties, (6) Commercialization assessment which is an assessment of the viability of industrial applications for a given technology. “Organizational” category factors focus on facilitating the technology transfer: (7) Work plan with proof-of-concept for new technology. This plan includes milestones and deliverables needed to be achieved in a technology transfer, (8) Outside influence shows the level of third party support for the technology developed and the involvement of other institutes and universities, (9) Market access determines the amount of assistance provided by the government unit to the technology adopters to market the products and services of the transferred technology, (10) Advertising refers to activities like sending news letters, demonstrations conducted by the government units to transfer their technologies to the public, (11) Technology transfer as a goal this factor means that the government department set the technology transfer as an early goal and the technology adopter had early involvement in the development of the technology, (12) Facilities this factor refers to the amount of incubator facilities, joint demonstration, joint evaluation and funding provided by the transfer unit, (13) Collective actions investigated the amount of interactions between the transfer unit and the adopters. “People” category analyzes the role of human beings in an organization’s technology transfer process. It includes: (14) Champions and leadership factor that refers to the champions and R&D leader’s direct responsibility to transfer technology, (15) Alignment of interest which is a very important factor since successful technology transfer depends on the alignment of interests between source and destination parties, (16) Level of interaction between the government transfer unit and the adopter. These factors focus on the amount of one- on-one consulting between the unit and the potential adopter, and the open interaction between the top management and scientist at both organizations, (17) Teams this factor means that the government department had life cycle teams where scientists working on a technology would also work on transferring it to customers. Across the analysis of four technology transfer projects in the federal Canadian context, (Kumar and Uruthirapathy, 2007), demonstrate the effectiveness of some factors described earlier. Some other factors were not observed such as post transfer inspection and decision checklist in the “technical” category factors. Indeed most of the technology transfers projects in the study context are chosen by scientists based on their expertise rather than from a 5 decision check list. Among the organisational proof-of-concept and facilities and collectives actions were not found but they are likely to exist. (Kumar and Uruthirapathy, 2007) argue that the nature and the operations of technology played a key role in determining which factors contribute to its successful transfer. Some of the 17 factors identified by the literature review were very essential and were found to be common in Canadian federal technology transfer like “Strategy matching”, “protection of intellectual property”, “clear work plan” “market access”, “advertising”, “alignment of interest” and “interactions”. While, others were not so common like “Post transfer inspection” The role of champions in successful technology transfer was difficult to determine. The authors observe additional factors to enhance effective technology transfer. These additional factors are about organization and people. Organizational factors such as keeping administration simple, rewarding the scientist, and considering the technology transfer as the natural outcome are essential to overcome the bureaucratic barriers that may be hindering speedy technology transfer. People factors such as confidence among parties, collaborative attitude, continued relationship among parties, and meeting of the minds can be classified. (Malik, 2001) based on a review of some key literature in the area of intra-firm technology transfer classified factors influencing the technology transfer as ‘likely to help factors’ and ‘likely to inhibit factors’. Among the ‘likely to help factors’ he distinguishes: - The ‘market pull’ factor that refers to the strength of end customer ‘marketing pull’. The more this pull is significant, the less a business unit can ignore it. This facilitate the ‘transmitters’ task and encourage them to develop the required technology. - The availability of ‘adequate resources’ for the technology transfer process. If there are sufficient human resources available that can be transferred with the technology, this may help overcome a certain amount of the problems. - Developing ‘culture of trust’ between the involved organisations. Building trust requires the use of mutually understandable, explicit language and often, prolonged socialisation including organisational networks. This culture crates the ‘willingness to transfer staff’. - ‘Good listening’ and ‘communication skills’ capability are very important. This importance is obvious since technology transfer is assumed as a two-way communication process. - ‘Familiarity with technology’, which is a factor that could be linked to prior knowledge. Among the ‘likely to inhibit factors’ (Malik, 2001) listed: - ‘No interest in a project’ is mentioned as a barrier to technology transfer. - The ‘threatened by new technology’ issue that refers to staff feeling threatened by the new technology that can ultimately affect their jobs - Lack of ‘training’ provision in both cases showed that this element is linked to the availability of people transfer. (Sabourin, 1998) examines the question of technology adoption from a strategic management perspective with an intermediate approach between the macro view of industrial economics and the micro perspective of management. He classified, the factors influencing strategic adoption of revolutionary processes into three categories: scale, vertical scope, and horizontal scope. The previous literature review reveals the multiplicity of factors that can influence the technology transfer. This is an indicator of how complex this process is. Thanks to this review, we noted that there is some convergence between different studies. We also noted that 6 according to the perspective adopted by the research some factors are more highlighted than others. Furthermore, the analysis of success factors is largely based on the investigation of technology transfer projects through interviews of actors or documents analysis. That’s why our research is interested in ongoing technology transfer projects. Methodology This work is a part of a project conducted in the global policy of the French eastern regional technology cluster (Innovative materials and intelligent products (IFA, 2006)). The aim of the French eastern regional technology cluster is to bring key actors (Regional political and governmental institutions, regional university members, regional technology transfer centre and regional industrial companies) together to enhance local economy. This direct channel, allow the formal and informal network construction. The project supports technology transfer process for innovative applications of brazing technologies into a group of Small and Medium-sized Enterprises (SMEs) within the French Lorraine region. “BRAZING is a process for joining solid metals in close proximity by introducing a liquid metal that melts above 450 °C (840 °F)” (Schwartz and Aircraft, 1993). Within the scope of this work, we focus on technology transfer (TT) from a technology transfer centre (TTC) to the target group of firms. The technology transfer centre has the capacity to develop and transfer brazing technology. Its role is to study the adequate solution to the company’s problem. The technology transfer team has access to the university’s resources, but it is independent from it in its business dealing. The role of the regional governmental organisations will be examined in terms of promoting technology transfer by financial aid to the enterprises, in particular to the SMEs. Our role is to achieve a day to day observation campaign. Every stakeholders meetings, technology deployment and product results will be follow-up. The originality of this work is the possibility to follow the whole set of activities of different projects from inside of the transfer team. Moreover the observation delay is long: from 18 months to two years. In this section, a description of the methodology adopted is presented. First, the choice of a qualitative and quantitative approach is justified. Then, the data collection procedures described. After, the data analysis method is explained. After that the sample of firms is characterised. Finally, results and discussion are presented. A quantitative and qualitative approach Qualitative methods are used extensively by anthropologists, sociologists and educationalists. In addition to quantitative methods of analysis they have increased the ability of researchers to understand the complexity of the behaviour of actors in industry and particularly during the design process (Boujut and Blanco, 2003), (Eckert and Boujut, 2003). These methods are also used to study the health system (Borges Da Silva, 2001), (Greenhalgh and Taylor, 1997). The use of qualitative approach to study the process of innovation is on going (Buckler and Zien, 1996) and (Boly et al, 2000). Qualitative research encompasses a variety of methods such as semi-structured interviewing, observation studies, group discussions, and the analysis of written documents. They provide a deeper understanding of social phenomena in their natural context. It tries to set a criterion and study changes depending on various circumstances. For example: how is accomplished the adoption of new technology by professionals and how this adoption varies depending on 7 the context? The aim is not to know how many professional have appropriated the technology. This last question can be answered with a quantitative approach is explained. The end product of qualitative research may be elucidation of a new concept, construction of a new typology, mapping of the range of phenomena within a subject area, development of an explanatory framework, or the basis for an intervention strategy, generation of new ideas or hypotheses which can then be explored by the quantitative approach (constructivism). Qualitative methods allow a holistic perspective which preserves the complexities of human behaviour. Data collection takes place in situ (individual or group study of observations or documents, etc.). These data induce a hypothesis. The formulation of the working hypothesis becomes clearer with accumulation of data. In this approach, the researcher is itself an instrument of research. In fact, during his study, the researcher is doing a go - back between data collection and analysing. This leads to change the orientation of the method and possibly the constitution of the sample being studied. The guiding principle for sampling is to maximize diversity in order to understanding the process studied. The statistical representation is not usually sought. In quantitative approach the study protocol is defined at the beginning of the study and data are used only at the end of the collection. The quantitative approach tries to verify a hypothesis through a breakdown that reduces necessarily the reality (positivism). It seeks to corroborate a hypothesis through a series of measures, often in an experimental context. The data are used then to derive a conclusion on the verification of the hypothesis. The researcher is testing a hypothesis by a deductive reasoning. His method gives the results with a certain level of reliability and reproducibility. In our observation we have to deal with quantitative and qualitative data and we aim to study TT actors in their natural context. Our work is consistent with all the emphasis on precision and exhaustiveness of the description of every stage of the technology transfer process. That is why we mainly based our methodology on an anthropological type approach: data gathering includes observation, listening, conversations, questions and answers. This approach suits our special interest in reporting qualitative and quantitative data. We have chosen this clinical methodology whose primary characteristic is that the researcher, usually PhD student, is a witness of the different exchanges between the TT team and enterprise (email, documents, mail and meeting). The Phd Student participates in 4 technology transfer projects with 4 different enterprises. Through this involvement, it is possible to gain access to a wealth of data which is denied to other approaches (Karlsson and Ahlstrom, 1997). The advantage of this methodology lies in the descriptions of actual technology transfer practices in real world settings. Data collection procedures In order to gather data related to project evolution and better understanding of technology transfer process the same mode of inquiry is used (direct observation and analysis of documents). Data is assembled thanks to two tools an “observation grid” (see Fig. 1) and “recapitulation grid” (see Fig. 2). An “observation grid” is completed at each meeting. 8 Fig. 1 Observation grid The “recapitulation grid” aims to summarize all the exchanges done between the Technology Transfer team and the enterprise team. 9 Fig. 2 Recapitulation grid Clinical research goes over periods of 18 months to 24 months. Factors influencing the experimental period include: delays in technical problem solving, team members not involved full-time in TT project, skills of top management and project leaders in anticipating future problems and particular events (e.g. steel supplier in stock out). Experimental work starts when the first contact is stated between the technology transfer centre team and the company how benefit of the transfer. It ends when the technology transfer project is over. Data analysis method To analyse collected data two main approaches are used: (1) “Form/Direction/Content” (2) “Intermediary Transfer Objects (ITO)” and four hypotheses are considered: (H1) Subjects discussed during the process of exchange are determinant to the achievement of technology transfer project, (H2) Technology transfer is a process of exchange that increases the competences of the different stakeholders, (H3) In every technology transfer project exist an activation event named «Activation trigger» and (H4) the knowledge transfer goes through stages defined by the model of (Gilbert and Cordey-Hayes, 1996). The first approach (“Form/Direction/Content”) aims at the determination of invariable patterns within the information exchange. A special attention is directed toward the subjects discussed, their form (meeting, phone call, e-mail) and the predominate direction of exchange. During the observation period, a list of topics potentially discussed in technology transfer project has been established. Table 2 describe this topics. Each exchange is then characterized by the correspondent code: 10 Table 2 List of topics potentially discussed in technology transfer project Family of topics Confidentiality Market Activity/Product Technique/ technology Organisation of production Quality Security Environnement Cost Expertise Description The requirements in terms of confidentiality. Exchanges dealing of description and specificity of the market: partners, competitors, suppliers… • Products description, • Details of the activity, • The objectives of the products, • The product strategy. Exchanges dealing about technical problems, possible technological solutions, development of process, without going into a logic of a problem solving. Exchanges dealing of organization of production and logistic: reorganization of a workshop production, redeployment of material and human resources, transporting, supply chain... • Products quality, processes quality, • Legislation, standards… • Applying a standard in particular, • Creating a checkpoint quality. Requirements related to the security of: workstations, personnel and product. The installation of ventilation is an example of security issues. The environment impact: pollution, toxicity… • Any form of investment: machinery, workstation, new structure… • Financial charges • How to finance an investment. General Expertise: the need to know its environment: technological monitoring, market research, economic intelligence. Customised Expertise: Solution to a specific technical problem; finding subcontractors, suppliers; attend the development of a product. Code C M AP T O Q S E € EXG EXp The second approach highlights the relation (“Intermediary Transfer Objects (ITO)”) between the objects exchanged during the technology transfer project and the success level of the project. We name theses objects ITO (Intermediary Transfer Object), a parallel is made with the (IO/IOC) intermediary objects in design process. The identification of these objects provides access to actor involved in the action but which do not appear spontaneously in the speeches of stakeholder interviewed. The characterization of ITOs indicates important differences from one project to another. IOs (Intermediary Object) are subject to important investment (time, money, negotiation and concern) help to reveal relations, actors and activities (Vinck, 2006). An analysis of each ITO is conducted as a cause that will achieve the ultimate goal of the TT project. To do this we use the diagram cause-effect. The causes are divided according to 5 families. These families are inspired of the model of (Gilbert and Cordey-Hayes, 1996). In fact during our observation, we notice that in addition to “acquisition”, “communication”, “application” and “assimilation” stated by (Gilbert and Cordey-Hayes, 1996) there is a fifth ITO family “Activation trigger”(see Fig. 3). An inventory of ITOs in each family is done for each exchange in order to identify invariants in the evolution of the different technology transfer projects. 11 Fig. 3 List of potential Intermediary Transfer Object (ITO) Sample of firms Our study concerns 4 technology transfer projects with 4 different enterprises. In Table 3 we present a description of the enterprises and projects studied. We made the choice of a limited number of project observed in order to promote the quality and duration observation. We also favourite the variety in terms of technical level of enterprises involved, as well as the ultimate goals of transfer projects. Table 3 Project’s description Enterprise Secteur of activity Brief description of the TT project A Aerospace B Agricultural tools C Aeronautics D mecanic Substitution of technology on a product line Creation of a new activity based on brazing Assembling with brazing exotic materials Optimization of the brazing process Existence of leadership Yes Market pull Decider maker engagement Technical level Yes Yes (High tech SMB) No No No (Low tech SMB) Yes Yes Yes (High tech SMB) Yes No No Active (High tech SMB) Results and Discussion The analysis of the first observation grids shows that the most discussed topics are "customized technical expertise" (EXP) and "technical"(T). The "cost" (€) comes in third place (See Fig. 4). The most common medium of exchange used is the e-mail. The direct exchange (meeting) is in second place with an average of 137 minutes (see Fig. 5). The figure shows the result of the enterprise “A” as example. The analysis of IOTs shows that the "acquisition" and "communication" steps appear very early in the process of technology transfer. In addition, the transfer of knowledge didn’t transit necessarily by the four stages defined by the model of (Gilbert and Cordey-Hayes, 1996). The results exposed must be moderated since the observation is still on going. 12 12 10 8 frequency 6 Série1 4 2 0 C M AP Q S E O € EXG EXP T Topics Fig. 4 Classification of topics in entreprise « A » project’s Number of exchange 7 6 5 4 Number of exchange 3 2 1 0 meeting E-mail phone call Fig. 5 Classification of the medium used within the TT projects of enterprise « A » Conclusion In this paper, a literature review of factors influencing TT process was presented. This review reveals the multiplicity of factors that can influence the technology transfer. This is an indicator of how complex this process is. Thanks to this review, we noted that there is some convergence between the different studies such as trust communication between actors and miles stones. We also noted that according to the perspective adopted by the research some factors are more highlighted than others. Furthermore, the analysis of success factors is largely based on the investigation of technology transfer projects through interviews of actors or documents analysis. Conversely, our work focus on technology transfer project which are on going. Moreover, we use direct observation and analysis of documents through clinical approach during the observation period. The use of qualitative and quantitative approaches as a research methodology was argued and detailed across this paper. In fact, our final aim is to better understand the technology transfer process thanks to a double approach: determining invariable patterns within the information exchange and studying “Intermediary Transfer Objects (ITO)”. A model of TT data presentation was described and applied. We presented some intermediary results obtained. These results must be moderated since the observation is still on going. 13 However, our approach attests of some limitation. Indeed, the close relationships between the observer and the actors involved in TT projects open up the possibility of bias. Moreover sample sizes in qualitative research are smaller than those in quantitative research. Hence, further experimentation may be necessary to confirm our results, to check the existence and importance of factors identified in our literature survey in the context of Brazing TT projects. Acknowledgements The authors wish to acknowledge to Mr Thierry Mazet the technology transfer expert for his implication on the project. Thanks are extended to all stuff of the technology transfer centre (CM2T) for accepting the presence of the Phd student in day to day observation period. 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