技術策略(Technology Strategy)大約是從1970年代起才開始被考慮，並被當作公司整體策略的一部份。在此之前技術策略只是被當做R&D活動的一部份。 　　監視器產業是資訊硬體工業的一項。從1981年起監視器產業一直都是以高速成長的科技產業。本研究是以個案研究方式來探討台灣此一從零到世界第一產業的廠商在各技術策略構面上的作為，做一個橫斷面的研究。 　　本研究以產品技術能力、製程技術能力、研發／製造功能之耦合、競爭時機、技術來源等五個構面來描述技術策略，以領導者和追隨者劃分經營者技術策略意向的類型。然後從中導引出三個命題建構： 　　(1)在部門功能耦合上，採研發／製造並重者其新產品研發的績效較高；而採重研發輕製造者其新產品研發績效較低。(2)企業產品技術的來源，採多元化方式者，其新產品研發績效較高；而採單純化方式者，其新產品研發績效較低。(3)企業的製程技術能力採內部發展累積經驗為主者，其新產品研發績效較高。而不強調內部發展順其自然形成者其新產品研發績效較低。 　　本研究並以本產業為實例，對管理實務提出三項建議：(1)給予研發和製造同等的重視(2)注重內部製程技術能力的培養(3)尋求可能途徑以取得產品技術

<p>Communication, coordination and cooperation are critical for a successful organization. This master's thesis work presents a literature study of the factors that influence the interface between Research & development and manufacturing functions. Research & development and manufacturing functions rarely share information among each other and rarely combine their skills and knowledge to produce effective and efficient work within organization. This is due to lack of mutual understanding improper communication and coordination among members in the teams. In the late 1990's, competition, Information Technology proliferation, increasing customer demands for better products at shorter lead times emphasized increased need for effective product development. Each function has its specialization and is effective in their domain. Each department has roles and responsibilities to complete given tasks. But they neglect the organizational and management issues and lack the focus where they are a part of a bigger process (i.e. delivering value to customer and making the company successful at the end of the day). The main focus of the thesis is to give deeper knowledge on communication and coordination between Research and Development and manufacturing. This is achieved by review of the articles, analysis and finally synthesis of literature to develop constructs and analysis models. This will help to understand the factors and its interaction. The factors identified are individual responsibilities, artefacts and system or domain understanding, communication idea, control and role distribution, teams, accessibility and arena for personal meetings and finally overall leadership.</p><p>Each factor has its own and unique contribution to success with in the organization. These factors are interrelated and dependent on one another. Artefacts understanding deals with some actions and steps has to be taken in order to executive the give tasks, individual role plays an important role in what sense he\she will contribute to the team as well as to the organization. Even active responsibilities must understand the system or domain and quickly adjust to the environment and get practice on it. Teams are essential tool in any organization, working together creates creative problem solving,  improves effective of communication, improves development skills and ability of an individual, mutual understanding and cooperation among group members all will constitute to the teams. Finally teams are the critical building blocks of an organization. The model developed needs further testing through empirical evidence to increase its validity.</p>

Communication, coordination and cooperation are critical for a successful organization. This master's thesis work presents a literature study of the factors that influence the interface between Research &amp; development and manufacturing functions. Research &amp; development and manufacturing functions rarely share information among each other and rarely combine their skills and knowledge to produce effective and efficient work within organization. This is due to lack of mutual understanding improper communication and coordination among members in the teams. In the late 1990's, competition, Information Technology proliferation, increasing customer demands for better products at shorter lead times emphasized increased need for effective product development. Each function has its specialization and is effective in their domain. Each department has roles and responsibilities to complete given tasks. But they neglect the organizational and management issues and lack the focus where they are a part of a bigger process (i.e. delivering value to customer and making the company successful at the end of the day). The main focus of the thesis is to give deeper knowledge on communication and coordination between Research and Development and manufacturing. This is achieved by review of the articles, analysis and finally synthesis of literature to develop constructs and analysis models. This will help to understand the factors and its interaction. The factors identified are individual responsibilities, artefacts and system or domain understanding, communication idea, control and role distribution, teams, accessibility and arena for personal meetings and finally overall leadership. Each factor has its own and unique contribution to success with in the organization. These factors are interrelated and dependent on one another. Artefacts understanding deals with some actions and steps has to be taken in order to executive the give tasks, individual role plays an important role in what sense he\she will contribute to the team as well as to the organization. Even active responsibilities must understand the system or domain and quickly adjust to the environment and get practice on it. Teams are essential tool in any organization, working together creates creative problem solving,  improves effective of communication, improves development skills and ability of an individual, mutual understanding and cooperation among group members all will constitute to the teams. Finally teams are the critical building blocks of an organization. The model developed needs further testing through empirical evidence to increase its validity.

The key objective of Part I is to synthesize 23 years of innovation research findings from economic, strategy, and marketing literatures and extend the current theoretical knowledge base in these domains through meta-analysis. In general, empirical evidence of the nature of the relationship between innovation and its antecedents and consequences is provided, while at the same time providing answers to conflicting conclusions within this field. The conclusions reached provide a more comprehensive understanding of the drivers of innovation as well as the implications associated with the phenomena. In addition, this study seeks to aid in building a strong theoretical foundation relating to the nature of the relationship of innovation with key antecedents and outcomes. It is demonstrated that innovation serves as a partial mediator of the relationships between organizational and environmental antecedents and firm performance. Part II builds upon the innovation foundations set forth in Part I and extends the focus to consider how innovations are commercialized outside traditional organizational boundaries. Drawing upon the Resource-based view of the firm, the impact of two dynamic capabilities (network ties and absorptive capacity) on marketing strategy formulation effectiveness is explored. Utilizing a unique sample of university pre-startup teams, this research is able to track these teams over time (longitudinal research design) and provide an empirical examination of the role of dynamic capabilities in the effective formulation of marketing strategies. There has been very little empirical research on the formation of strategies at the team level and furthermore, even less research examining marketing strategy making for technologies that were developed outside traditional organizational boundaries and without a predefined market application. Overall, this research will not only contribute significantly to the current innovation and marketing strategy literature, but will also open up new avenues of research in marketing entrepreneurship.

Increasing competition and technological improvements have created new challenges for the firms. In Turkey, low-tech small and medium scale furniture industry does not seem to be well equipped to compete in this respect due to their weak economic and cultural capital. Necessity of innovative and distinguishing design-led policies has already arisen for improving the position of the low-tech small and medium scale furniture producers. However, to generate effective policies for them, it is essential to understand the design process and production domain related to cultural factors which affect the position of design and the designer. Within this perspective, this thesis examines the position of design and the designer within the product development process in eight cases of small and medium scale furniture companies based on the data gathered from, firstly, in-depth interviews with the owners, and secondly, product development stories narrated by the owner, the designers and head of the production departments of the companies.

This thesis addresses important operational aspects relating to fundamental components of any successfully executed NPD strategy: the processes, incentives and structure of decision rights that should be implemented given the objectives and capabilities of the firm. The first chapter outlines when a firm might prefer to compensate members of a NPD project team either, as individuals (e.g. based on their functional contribution to overall value) or as a team (e.g. based on the overall profit generated). We find that neither team nor individual based compensation is preferred for all types of projects. Specifically, when there is higher uncertainty, the firm can benefit by employing team-based compensation. We discuss the implications of our findings towards the firm's ability to pursue different types of projects. In Chapter 3, we look at the strategic resource allocation processes that are employed by firms in order to decide whether NPD initiatives get funded or not. We find that there is not a "one size fits all" resource allocation process that all firms should employ. Furthermore,we extend this finding by further by providing a rationale explaining why even a single firm could benefit by employing multiple processes internal to the firm. Finally, in Chapter 4, we empirically explore how key managerial levers of the firm (i.e. incentives, tolerance for failure, and project management structure) affect an individual's propensity to invest in a project. Our analysis brings forth several under-explored and novel aspects. We examine how multiple managerial levers work in concert with one another (revealing interactions that, to our knowledge, have not been exposed). We also recognize an important aspect of most (if not all) NPD contexts: the probability of success is strongly tied to the level of resources that are invested.

Emerging markets are fraught with uncertainty, diverse global players, rapid technological change, wide-spread price wars, and seemingly endless reorganization (Ilinitch, 1996). These changes have presented challenges to organizations in the form of shorter product cycles, increased segment fragmentation, blurring industry boundaries, breaking corporate hierarchies, and increased interdependence of world markets (Ozsomer et. al., 1991). Organizations are responding to competition by capitalizing on global policies and adopting self-directed teams and horizontal structures that enhance external activities. To do this organizations are getting conscious of the boundaries they are operating in. With hyper competition and globalization organizations blur boundaries to gain maximum business opportunity from other geographic boundaries. For this to happen organizations must engage in boundary crossing behaviour. Competition is also managed by focussing on bringing out new products to the market. Product development (PD) is critical because new products are becoming the nexus of competition for firms (Clark and Fujimoto, 1991). They are the means by which members of organizations diversify, adapt, and even reinvent their firms to match evolving market and technological conditions (Schoonhoven et. al., 1990). This calls for a closer look at boundary crossing behaviour as part of the external activity during PD. The studies carried out in the process of PD identify external activity orientation as important criteria for success (Brown and Eisenhardt, 1995). PD processes involve project management activity. Unlike other processes of an organization, PD is a knowledge intensive activity, which brings together individuals having different skill sets and mindsets. These individuals need to interact regularly to understand and coordinate their activities. The non-routine nature of the process makes boundary-crossing activity more critical for successful PD. This thesis focuses on the boundary crossing behaviours performed by PD teams. Literature review showed that external activities play a crucial role in PD (Calantoue and Di Benedetto 1990a, b; Griffin and Hauser 1992; Olson et. al., 1995; Song et al., 2000; Souder 1987). The importance of external activities for successful project development was shown by Allen (1971, 1977) based on his seminal work on communication and organizations. He showed that R&D team’s frequency of communication within the team has no relationship to performance, while increased communication between teams and other parts of the laboratory was strongly related to project performance. Teams carrying out complex tasks in uncertain environments were found to perform higher levels of external activities (Ancona and Caldwell 1992). External activity was found to result in high percentages of successful projects and sales derived from new products (Cooper 1984; Dougherty 1987; Ancona and Caldwell, 1992; Ancona, 1990; Sheremata 2002). PD is an activity with high uncertainty. The external activities that are performed by PD teams and their nature of relationships shared are variously classified as interactive and collaborative behaviour (Kahn 1996). Underlying this classification is a dichotomous behaviour where in the former embodies presence of informal behaviour between partners, while the latter embodies formal behaviour. Further research on these behaviours have shown that informal type of external activity also known as collaborative behaviour plays an important role in the successful development of products. Collaboration represents the unstructured, affective nature of interdepartmental relationships. They were found to result in improved product development. A study on software product development teams by Kraut and Streeter(1995) also showed the importance of informal behaviour. He found that product development requires personal communication across functional boundaries to cope with uncertainty. The external activities performed by PD teams were also found to be influenced by variables like product development life cycle (Brodbeck, 2001; Sawyer & Guinan, 1998; Boehm, 1987), informal groups (Hirschhorn and Gilmore, 1992), awareness, (Pinto and Slevin, 1987), and open climate (Ashkenas et. al., 1990). After identifying the missing gaps in gaps were the objectives of the study was defined. The objectives of the study are as follows: To understand the interactive and collaborative boundary crossing behaviour of product development teams To study the difference in boundary crossing behaviour of horizontal, geographic and value chain boundaries of product development teams To understand the relationship of variables influencing boundary crossing behaviour of product development teams To give suggestions to better understand management of boundary crossing behaviour in product development teams A combination of qualitative and quantitative techniques was adopted to study these objectives. Based on the past literature a conceptual framework was developed. It consisted of defining the role of collaborative and interactive boundary crossing behaviours across product development teams and certain variables influencing this behaviour. The model was validated through preliminary interviews. These interviews were conducted across team members, team leaders and knowledge management experts. A few more variables were identified that were considered to influence the collaborative behaviour performed by PD teams. These variables are sharing behaviour and confidence with the time available for developing the product. The variables were operationally defined and measurement instrument, namely a questionnaire, was developed. The questionnaire was administered to team leaders and team members. The measurement instrument was tested for its psychometric properties namely, reliability and validity. Cronbach alphas are reported. For the main study, data was collected from 73 product development teams of IT organizations located in Bangalore. From the team leader the general characteristics of the PD team were understood, as well as the level of newness of the product developed. The latter was used as a measure of level of innovation. From team members, the interactive and collaborative behaviour of PD team members was studied. The statistical techniques that were used for analyzing the data are F-Test, t-test, Kruskall Wallis test, chi-square test , correlation and regression analyses. After the analysis it was found that the interactive and collaborative behaviour expressed by the teams across the three boundaries showed that as compared to collaborative behavior, product development teams more commonly used interactive behaviour. Interactive behaviours were also found to be used to the same extent across all the three boundaries. Since interactive behavior is formal and forced in organizations it is predominantly practiced although its efficiency may vary. The challenge for organizations hence is the collaborative behaviors. On the other hand, collaborative behaviour was seen used the most across horizontal boundary and the least across value chain boundary. Since the geographic distance across boundaries increases when moving from horizontal to value chain boundaries the chances of collaboration get decreased. Hence an influence of distance on boundary crossing behavior was sense influencing collaborative behaviour of product development teams. Hence further analysis focused on collaborative behaviors. The collaborative behaviour was further studied to understand its relationship with product development team behaviour, sharing behaviour of teams of outside the boundary, demographic variables and innovation level of product developed. Correlation analysis showed that the collaborative behaviour of teams were correlated with the sharing behaviour, informal groups, autonomous team leader behaviour, and open climate only. These variables were termed direct influencers of collaborative behavior.Innovation level did not play any significant role in influencing collaborative behavior.Collaboration behaviour was further studied to understand how they are causally related with these variables. Using regression analysis, the causal study considered collaboration behaviour of PD teams in general, as well as the collaboration behaviour across horizontal, geographical and value-chain boundary as the dependent variable. The independent variables studied are sharing behaviour, informal groups, open-climate behaviors, autonomous team leader behaviour. Regression results showed that open climate behaviours was causally related to overall collaboration behaviour of PD teams in all boundaries. With respect to collaboration across horizontal boundary, it was found that sharing behaviour, as well as autonomous team leader behaviour influenced them. Across geographical boundary, the open-climate was found causally related. Across value chain boundary sharing behaviour was found to influence collaborative behaviour. It was found that only some variables influence boundary crossing behavior namely, collaborative behavior, the most. These were open climate behaviors, sharing behaviour, and autonomous team leader behaviour. These were labeled direct influencers. The ones that did not show a direct influence were termed as indirect influencers. Since the role of direct influencers was clearly understood, the role of indirect influencers needed further analysis as these were variables selected from literature and expert interviews and expected to have influence on boundary crossing behaviour. Those variables that did not directly enter the regression analysis were further studied tounder stand if they had a relationship with the direct influencers independent of collaborative behaviors. It was assumed that if they did then they may indirectly influence collaborative behaviors. For this the indirect variables were correlated with the direct influencers. The results showed that open-climate was positively correlated with awareness of objectives, PD life cycle and the team’s confidence in time line of the project. Interestingly sharing behavior and autonomous behaviour of the team leader was not correlated with any potentially indirect influencer or variable. This meant that awareness of objectives, PD life cycle and the team’s confidence in time line of the project can influence collaborative behavior indirectly. In the next analysis the role of PD was understood deeper in the context of level of innovation and duration of projects vis-à-vis collaboration. This is specifically done as the poor influence of level of innovation and duration were a surprise since they were expected to have influence on boundary crossing behavior. Teams were classified into low, medium and high innovation level teams. The collaboration behaviour within these teams was then studied. The results showed that there was a pattern in the usage of collaboration behaviour across the different channels. Collaboration behaviour was used most across medium innovation level team as compared to low and high innovation level teams. This was the case of collaboration across horizontal and geographical boundary. In the case of value chain boundary, no such pattern was recognizable. Interestingly it meant that in low and high innovation collaborative behavior was lower and it increased only during medium innovation. Further to this, the influence of collaboration on duration of product developed was studied. The correlation study showed negative relation between the two only for horizontal boundaries. This meant that increase in collaborative behavior across horizontal boundaries result in lesser time taken to develop the product. The last chapter in this thesis describes the conclusions from this study and the managerial implications regarding nurturing and managing boundaries of PD teams.

This thesis addresses the challenges that firms are faced with when collaborating with suppliers in new product development (NPD) projects under technological uncertainty. A critical observation that is made in this context is that technologies are evolving faster, making products more complex. At the same time, firms become more specialized. Due to increased complexity and specialization, firms do not possess all the necessary technologies in-house and therefore need to collaborate with external organisations to incorporate new technology into their products. Common collaborators are suppliers who become integrated into the buying firm’s NPD project. However, finding suppliers and collaborating with suppliers in NPD can be problematic. In addition, external collaborations also impact the buying firm internally, since it often needs to coordinate its departments. The purpose of this thesis is to explore supplier involvement in NPD under technological uncertainty. Challenges in supplier selection are concerned with the issues of involving new suppliers or relying on old acquaintances, managing uncertainties, the dilemma of whether to commit to long-term relationships or to maintain flexibility, and deciding on which department that is responsible for evaluating and selecting the supplier. The present study of buyers and suppliers in NPD, shows the challenges that are involved in balancing control, reaching goal alignment, and managing transactional and relational governance. Internal challenges investigate the coordination between the R&amp;D department and purchasing in NPD projects where suppliers are involved. The present findings may be of value for firms who engage in collaborative NPD, or for firms who aim to involve suppliers in their development of new products.

Designers do not merely develop concepts; they are increasingly involved in testing product concepts and learning consumer preference. However, designers’ decision making processes in these tasks have been little studied. In the two essays, I apply decision making frameworks to concept testing and preference learning to study consumer’s and designer’s biases. In my first essay, I study consumer bias in concept testing. When consumers test new products, they are often asked to choose which product they prefer. However, a choice question can elicit biased preference because consumers simply choose the product that is superior on the attribute serving their purchase purpose. My studies show that when consumers are asked to predict which product they will enjoy more, they are more likely to prefer the product that actually reflects their consumption utility. These findings suggest that making trade-offs is avoided in the choice question, but is encouraged in the enjoyment prediction question. Thus, a simple change of question format, in otherwise identical product comparisons, elicits different answers. This holds true when product attributes are easy to evaluate; when product attributes are hard to evaluate, changing question format does not affect consumer choice. My second essay examines designer bias in preference learning. When designers predict consumer preference for a product, they often base their predictions on consumer preference for similar products. However, this categorization-based strategy can result in biased predictions because categorical similarity is not diagnostic for preference prediction. I conducted two studies by applying a Multiple Cue Probability Learning experiment to a designer’s prediction task. I found that when subjects used a sequential learning strategy, making a sequence of predictions and receiving feedback, they increased prediction accuracy by 14% on average. When they made predictions with multiple sets, with a break between each set during which they reflected on what they had learned, their prediction accuracy further improved by 7% on average. In sum, I demonstrate bias and propose approaches to avoid them in two design tasks. My two essays show that the decision making frameworks are crucial in understanding and improving the successful outcome of the design process.

Designers do not merely develop concepts; they are increasingly involved in testing product concepts and learning consumer preference. However, designers’ decision making processes in these tasks have been little studied. In the two essays, I apply decision making frameworks to concept testing and preference learning to study consumer’s and designer’s biases. In my first essay, I study consumer bias in concept testing. When consumers test new products, they are often asked to choose which product they prefer. However, a choice question can elicit biased preference because consumers simply choose the product that is superior on the attribute serving their purchase purpose. My studies show that when consumers are asked to predict which product they will enjoy more, they are more likely to prefer the product that actually reflects their consumption utility. These findings suggest that making trade-offs is avoided in the choice question, but is encouraged in the enjoyment prediction question. Thus, a simple change of question format, in otherwise identical product comparisons, elicits different answers. This holds true when product attributes are easy to evaluate; when product attributes are hard to evaluate, changing question format does not affect consumer choice. My second essay examines designer bias in preference learning. When designers predict consumer preference for a product, they often base their predictions on consumer preference for similar products. However, this categorization-based strategy can result in biased predictions because categorical similarity is not diagnostic for preference prediction. I conducted two studies by applying a Multiple Cue Probability Learning experiment to a designer’s prediction task. I found that when subjects used a sequential learning strategy, making a sequence of predictions and receiving feedback, they increased prediction accuracy by 14% on average. When they made predictions with multiple sets, with a break between each set during which they reflected on what they had learned, their prediction accuracy further improved by 7% on average. In sum, I demonstrate bias and propose approaches to avoid them in two design tasks. My two essays show that the decision making frameworks are crucial in understanding and improving the successful outcome of the design process.