Knowledge sharing in industrial research

Over the past decade, the field of organization studies has increasingly focused on knowledge and knowledge processes in organizations. This thesis describes a study of one of those processes, knowledge sharing, in the context of industrial research. Though the attention for knowledge in organizations is rather new, technical communication in industrial research has been subject of research for over the last fifty years (e.g., Herner 1954; Allen 1977; Tushman 1978; Keller 1994). One major lesson that can be learned from past research is that technical communication contributes to research performance. In a study of 1311 researchers from industry and government laboratories, Pelz and Andrews (1966) already found a significant correlation between a researcher’s performance and his communication with colleagues within and outside his group. Recently Anderson et al. (2001) established again that colleagues are the most important source of information for researchers (after the use of their own knowledge). Although the importance of technical communication has been confirmed over and over again, we do not know very much about the details of the contribution of technical communication to industrial research practices. With a few exceptions (Johnston and Gibbons 1975; Faulkner and Senker 1995), the content of technical communication has not been systematically studied. Nevertheless, inspired by linear communication models (e.g., Shannon and Weaver 1949), most studies in the field have interpreted technical communication as the transfer of information or knowledge (e.g., Gerstenfeld en Berger 1980; Kogut en Zander 1992; Moenaert en Caeldries 1996). Furthermore, the way in which technical communication is accomplished, is not systematically explored. Most of the things researchers might say will be irrelevant for the work of others. Nevertheless researchers manage to contribute to each others work. Several authors assume that this is because communication is initiated by those in need of information or knowledge (e.g., Leckie et al. 1996; Hansen 1999). Past research has found many factors that enable or constrain knowledge sharing (e.g., Szulanski 1996; van der Bij et al. 2003), but these studies did not yield insight in the ways in which communication is realized. The first objective of the study reported in this dissertation was to gain insight in these issues: in what ways does technical communication contribute to industrial research practices and how is this accomplished. This study had an important theoretical objective as well. Within the field of organization studies two theoretical perspectives have offered an explanation for the value of technical communication. These are the information processing approach (Galbraith 1973; 1977; Tushman and Nadler 1978; Daft and Lengel 1986) and the knowledge-based theory of the firm (Kogut and Zander 1992; 1996; Grant 1996a; 1996b; 2001). According to the information processing approach (IPA), organization members face uncertainty and ambiguity, caused by task characteristics, task interdependencies and the organizational environment. Furthermore, the IPA assumes, in line with others, that technical communication consists of information transfer, making it capable of reducing uncertainty and ambiguity. The central hypothesis of the IPA is that higher performing organizations match their actual information processing to the information processing needs associated with the degrees of uncertainty and ambiguity they face. Thus, the core of the explanation for the value of technical communication is that it is capable of reducing uncertainty or ambiguity by transferring information. Recently, the knowledge-based theory of the firm (KBT) has been developed. This theory starts from the observation that a fundamental asymmetry exists between knowledge development and knowledge application (Demsetz 1991). To develop a thorough knowledge base, individuals have to specialize. However, to produce or develop complex products, a broad range of knowledge is necessary. Therefore, according to the KBT, the performance of an organization depends upon the integration of the specialized knowledge of individuals, that is, upon the coordinated application of this knowledge. The KBT, and the literature on knowledge management, interprets technical communication first and foremost as knowledge transfer. Knowledge transfer is interpreted as one among a number of possible knowledge integration mechanisms. In this way the KBT offers an explanation of the value of communication as well. However, the explanations of the IPA and the KBT are not based on detailed investigations of the content and process of technical communication. Van de Ven and Drazin (1985) note that the IPA uses information as an abstract, latent, unmeasured variable. Grant (1996a; 1996b) calls for detailed empirical research on knowledge sharing and knowledge integration to enhance his theoretical analyses. Therefore, the second objective of this study was to use empirical research results to reflect critically upon the assumptions and explanations of the IPA and the KBT. The objectives of this study called in the first place for exploratory, empirical research. Past studies have emphasized that communication should be studied within the context of the situated practices of group members (Lynch 1985; Orr 1990; Knorr- Cetina 1995). For that reason, a choice was made to study communication among mechanisms, of which 16 were found in the data. Examples of these origination mechanisms are: - ‘diffusing’: ego selecting existing information without an orientation at a specific problem - ‘pushing’: ego selecting existing information oriented at a problem of alter - ‘pulled origination’: existing information is asked by alter - ‘thinking along’: ego develops new content oriented at a problem of alter - ‘self-suggesting’: ego develops new content oriented at one of his own problems within an interaction It should be noted that one interaction is often characterized by more than one origination mechanism. This holds especially for interactive communication. Quantitative analyses showed that these origination mechanisms are associated with different moves and effects. For example, ‘diffusing’ is associated with the description of own activities and own results, and reporting about others. Out of 26 cases (in a total 227) in which this mechanism was found, 23 yielded an indirect contribution and only 5 a direct contribution. Conversely, ‘thinking along’ is predominantly associated with moves like giving arguments, suggesting experiments and technical solutions, agreeing, rejecting, questioning and concluding. Thinking along yielded a direct contribution in 26 out of 37 cases. The concept of origination mechanisms is a contribution to the existing literature. Only fragments of it have been acknowledged before, such as the distinction between ‘pushing’ and ‘pulling’ (e.g., Langrish et al. 1972; Schulz 2001). Furthermore, it enables the identification of biases in the existing literature. For example, most literature on information transfer assumes that this information is always existing before communication, waiting to be transferred. Another bias in the existing literature is that it assumes that information transfer and knowledge transfer are initiated by information searching individuals. A general finding with regard to origination mechanisms is that those origination mechanisms that are oriented at a problem of alter or a shared problem are most likely to yield direct contributions (in 82 out of 112 cases). Nevertheless, direct contributions are also produced via originations that are not oriented at such a problem and by self-suggesting: thinking up new ideas with regard to one’s own problem in interaction. The effectiveness of origination mechanisms oriented at a shared problem or a problem of alter depends upon the application and development of knowledge. For example, asking a targeted question is enabled by knowing what knowledge one is lacking and by knowing who has that knowledge. For thinking along that is not necessary. But thinking along requires that ego knows about alter’s problem and has relevant background knowledge. Each of the origination mechanisms has its conditions for effective employment. Therefore it is not wise to limit communication to one or a few mechanisms. These empirical results were used to reflect upon the theoretical explanations of the value of technical communication offered by the IPA and the KBT. With regard to the IPA, the following conclusions were drawn. First, a reflection upon the effects of technical communication showed that technical communication does not always reduce uncertainty or ambiguity, as is assumed by the IPA. Communication also leads to new questions and problems, to vanishing certainties and to conflicting interpretations. The increase of uncertainty or ambiguity may be valuable effects of technical communication in research as well. The assumption that technical communication can be interpreted as information transfer is questionable too. Several interpretations of ‘information’ were discussed (e.g., Shannon and Weaver 1949; Dretske 1981). For example, if information is interpreted as a capacity to reduce uncertainty or to increase knowledge (like Galbraith (1973) and Tushman and Nadler (1978) assume), the assumption that useful technical communication can be interpreted as information transfer is false. Both conclusions undermine the core of the explanation of the value of communication by the IPA. The KBT interprets technical communication as knowledge transfer, and knowledge transfer as a knowledge integration mechanism. According to this perspective, the integration of knowledge determines the performance of firms. However, a reflection upon moves and effects showed that useful technical communication cannot always be interpreted as knowledge transfer. Some instances of technical communication are better described as ‘knowledge conducive communication’. Moreover, in contrast with existing views, knowledge application and knowledge generation play a central role in technical communication as well. But, in fact, this strengthens the explanation of the KBT. The analysis of knowledge processes occurring in technical communication shows other ways of integrating knowledge. For example, in thinking along ego applies his knowledge to a problem of alter. In one of the studied episodes, an expert in fracture mechanics applied his knowledge to determine the cause of a broken disc, showed to him by a colleague. The expert communicated his conclusion but did not communicate all knowledge on fracture mechanics that he used. This form of knowledge integration, temporarily applying one’s knowledge to somebody else’s problem, is more efficient than knowledge transfer, since not all knowledge that gets integrated needs to be transferred. Thus, a number of origination mechanisms that are effective in yielding direct contributions, including thinking along, are efficient as well. Further, the discovery of this knowledge integration mechanism shows the incompleteness of the taxonomy of mechanisms developed by Grant (1996b; 1997). Insight in the effectiveness and efficiency of the origination mechanisms in which ego selects or develops with an eye on a problem of alter or a shared problem was furthered by interpreting research findings in terms of distributed cognition (Hutchins 1995). In these origination mechanisms, including thinking along, a particular distribution of cognitive labor is realized. The temporary distribution of the cognitive labor over more people, for example during an interactive presentation, improves creativity and reliability (probably in an efficient way). Finally this study indicated that the value of this form of integrated cognitive work is not limited to cases in which a need for task integration exists. That suggests that the focus on the integration of knowledge and cognition is a valuable addition to the traditional orientation on the integration of tasks and not just a semantical shift. The research results provide a new explanation for the specific value of personal communication. Existing explanations include that some information cannot be found in published sources or databases (Holland et al. 1976), that personal communication is a richer communication medium (Daft and Lengel 1986) and that personal communication enables the transfer of tacit knowledge (Nonaka 1994). This study suggests that personal communication enables those origination mechanisms in which content is selected or developed by ego with an orientation at a problem of alter or a shared problem. Enabled by the application of knowledge, these origination mechanisms yield effective and efficient contributions to research practices. Finally, it can be concluded that technical communication is a heterogeneous, active and integral part of industrial research practices. These characteristics are insufficiently captured by interpretations of technical communication as information transfer or knowledge transfer

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management, technological, sciences, design

Knowledge integration by thinking along

knowledge, integration

Knowledge management challenges in corporate venturing and technological capability building through radical innovations

radical innovation, technological capability, corporate venturing, knowledge management

The structuration of organizational learning

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Playing the Numbers Game: Dealing with Transparency

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The fibres that hold an innovation network: An analysis of knowledge sharing in the Glare network

No abstract

Learning while (re-)configuring: business model innovation processes in established firms

This study addresses the question of how established organizations develop new business models over time, using a process research approach to trace how four business model innovation trajectories unfold. With organizational learning as analytical lens, we discern two process patterns: “drifting” starts with an emphasis on experiential learning and shifts later to cognitive search; “leaping,” in contrast, starts with an emphasis on cognitive search and shifts later to experiential learning. Both drifting and leaping can result in radical business model innovations, while their occurrence depends on whether a new business model takes off from an existing model and when it goes into operation. We discuss the implications of these findings for theory on business models and organizational learning