In the case of sales and marketing organization reform discussed in this paper, organizational routines with excellent results were created. Despite visibility and standardization in a form usable for other organizations, the routines were not transferred between sales offices due to the rules of the sales organization, where “autonomy is maintained if an organization achieves KPIs.” In other words, in organizations where each sales office achieves KPIs and has good performance, the high level of autonomy in each office is preserved, and the offices (a) may make their own improvements to organizational routines and (b) will not have the organizational routines of other organizations forced on them. In organizations with good performance, it was observed that organizational routines (a) evolve uniquely in each sales office and (b) undergo an adaptive radiation where they are not rolled out to other sales offices.
The open innovation proposed by Chesbrough (2003a) had a heavy impact on practical business, and not just academia. However, the definition of open innovation is broad and ambiguous, with Chesbrough himself not providing a clear, specific example of open innovation practice (OIP). Thus, practitioners interpret it in many ways. Accordingly, to accurately measure the impact of open innovation, OIP must be classified into several types. This paper proposes two methods for classification. The first is whether the OIP of Chesbrough and that of the practitioner are aligned. From this perspective, OIP can be categorized in three ways: (a) what both Chesbrough and the practitioner call OIP; (b) what Chesbrough calls OIP, but not the practitioner; and (c) what a practitioner calls OIP but not Chesbrough. (a) can be clearly evaluated as the impact of open innovation, while more attention is required when interpreting (b) and (c). Second is the differentiation of whether activities that are currently implemented as OIP were started (i) before or (ii) after Chesbrough (2003a). (ii) can be seen as the impact of open innovation, though (i) is nothing more than changing the name of something that was previously just a “practice” into “OIP.” If (i) is included in the impact of open innovation, there is a risk of exaggerating the assessment of open innovation.
In the field of management research, the grounded theory approach (GTA) pioneered by Glaser and Strauss (1967) is frequently cited to assert methodological validity in qualitative theory-building studies, in contrast with quantitative research that uses majority hypothesis validation. Glaser and Strauss eventually came to disagree with each other, and GTA branched into three perspectives. Of these, Strauss and Corbin (1990), which defines coding and other analytical processes in detail, is cited most frequently although the studies that cite it do not necessarily reflect its characteristics. It is, therefore, clear that the differences in these three perspectives are not connected with differences in research methodologies.
Japan has since ancient times had a custom called omiai (loosely translated as “matchmaking” when searching for a marriage partner). The examples of the matching of large firms and start-ups at the Innovation Leaders Summit in Japan discussed in this paper can truly be called “omiai.” Unlike Western-style matching, in this summit, participating firms and managers alike have little experience with alliances, and matchmakers have no strong commitment, as noted by Holzmann, Sailer, and Katzy (2014). Instead, just as with omiai, matchmakers exchange profiles of large firms and start-ups new to alliances and simply create a place for them to meet and make matches.