Knowledge Reuse for Innovation

Abstract

This study was conducted to better understand the knowledge reuse process when radical innovation (e.g., experiments to prepare for human exploration of Mars) is expected. The research involved detailing the knowledge reuse process in six case studies varying in degree of innovation. Across the six cases, a six-stage reuse-for-innovation process was identified consisting of three major actions: reconceptualize the problem and approach, including deciding to search for others' ideas to reuse; search-and-evaluate others' ideas to reuse; and develop the selected idea. Findings include (1) the need for an insurmountable gap in performance to stimulate the decision to reuse others' knowledge; (2) the critical importance of an adapter to bridge the idea source and recipient; (3) three layers of search-and-evaluate activities in which the first layer of scanning to find ideas to reuse and the last layer of detailed analysis of ideas are bridged by a layer of brief evaluations of ideas assessing the presence (or absence) of targeted information about each idea; and (4) the differential use of metaknowledge about each idea to facilitate proceeding through each search-and-evaluate layer. In addition, reusers in the more (versus less) innovative cases redefined problems at the outset in nontraditional ways using analogies and extensions, rather than accepting the preexisting problem definition; used a substantially broader search strategy with a greater variety of search methods; and worked more closely with adapters during the latter stages of the reuse process.knowledge management, knowledge transfer, innovation

Knowledge Gathering, Team Capabilities, and Project Performance in Challenging Work Environments

“…Similarly, organizational learning theories argue that learning from others can enhance organizational performance (e.g., Levitt and March 1988, Huber 1991, Argote 1999. Applying these theories to work groups suggests that project teams in knowledge-intensive work settings should perform better if they engage in more external knowledge gathering, defined here as the active solicitation of task-related information, know-how, and feedback from experts and document sources external to the team, either within or beyond the organization (Ancona and Caldwell 1992, Hansen 1999, Cummings 2004, Majchrzak et al 2004). Many knowledge-intensive work settings are characterized by overload, ambiguity, and politics, however, where project teams face a multitude of possible problems to address and solutions with which to address them, little way to know which problems and solutions to select, and multiple stakeholders with an interest in their selections (Alvesson 2004).…”

Exploring and Yet Failing Less: learning from past and current exploration in R&D

“…However, although accumulated experience is important, the transfer of existing practices to specific contexts is not always either easy or feasible, particularly in contexts that involve the identification of actionable responses related to radically new lines of inquiry -which is what exploratory search is about (Cook & Brown, 1999;Majchrzak et al, 2004). This leads to an acknowledgement of the temporal dimension of the knowledge creation and learning processes associated to exploration activity (Nerkar, 2003), and the distinction between learning from accumulated experience and learning in practice (Cook & Brown, 1999).…”

“…Past exploration activities can help to map and navigate the relevant search space and, thereby, contribute to making current exploration activities more efficient and to developing a learning process associated to current exploration (Eisenhardt & Martin, 2000;Zollo & Winter, 2002). Majchrzak et al (2004) report that past experience can support different stages of current radical and exploratory innovation: from the conceptualization of new ideas, through the use of analogies and extensions linked to previously developed concepts, to final product development, in which experience is shared in the course of testing, review and improvements on prototypes.…”

The Hierarchy Myopia of Organizational Learning

“…The third stream examined the procedural aspects of organizational learning behavior, such as knowledge search (e.g., Knudsen and Levinthal 2007), knowledge creation (e.g., Gupta, Tesluk and Taylor 2007), knowledge transfer (e.g., Cohen and Levinthal 1990), and knowledge retention (e.g., Moorman and Miner 1997). Moorman and Miner (1997), for instance, examined the effect of organizational memory on organizational learning performance, while Majchrzak, Cooper and Neece (2004) investigated how organizations reuse retained knowledge. The fourth stream centered on how learning was affected by organizational characteristics such as structure (Bunderson and Boumgarden 2010;Fang, Lee and Schilling 2010), culture (Weber and Camerer 2003), identity (Kane, Argote and Levine 2005), and inter-firm alliances such as joint ventures (Hansen 2002).…”