A Knowledge-Based Model of Radical Innovation in Small Software Firms

Abstract

Internet as Radical Innovation Internet computing can be viewed as a radical IS innovation as follows: (1) Unique: Internet computing added new elements into the existing computing architectures that significantly departed from existing alternatives. These included a universal thin browser and the idea of hyperlinking included in HTML (Lewin and Volberda 1999; Van Den Bosch et al. 1999). Firm-owned network-based systems with traditional user interfaces were insufficient substitutes for Web interface-based systems across the shared, worldwide infrastructure. (2) Novel: The elements were organized using new architectural principles including open and universal access through URL resources (http) and an n-tier architecture, which separated data, business rules, access, and control flow. Knowledge of traditional systems patterns, languages, platforms, architecture, and designs provided little assistance in learning the prerequisite vast, volatile, and resource-intensive new skills for building Internet systems. This can be contrasted with a move from network to relational data base systems, which did not significantly change architectural principles, the types of applications being built, or how they were viewed or built; or the adoption of UML after SAD as a baseline for designing applications.

Substructures of perceived knowledge quality and interactions with knowledge sharing and innovativeness: a sensemaking perspective

“…That is, knowledge should be organically refined or reproduced in the global competition to sustain the quality of the knowledge. With its growing importance, there have been some studies to empirically examine knowledge quality or similar concepts such as "content rating" (Poston and Speier, 2005), "knowledge content quality" (Kulkarni et al, 2007), "perceived knowledge quality" (Durcikova and Gray, 2009) and "knowledge depth" (Carlo et al, 2012;Majchrzak et al, 2013). These studies, however, have some limitations.…”

“…When knowledge has a high level of perceived intrinsic knowledge quality but lacks contextual relevance or practical applications, it may not facilitate innovativeness. In fact, literature contends that individuals generate more innovation when knowledge is recontextualized and deeper (Carlo et al, 2012). Few research studies have examined how PKQ's substructures have differing impacts on innovativeness.…”

“…The intrinsic knowledge needs to be transformed contextually and practically, and once transformed, it will increase the likelihood of innovativeness. Individuals equipped with contextualized knowledge have a tendency to experiment and thus produce good outcomes (Carlo et al, 2012). The progressive transition from perceived intrinsic knowledge quality to perceived contextual, actionable knowledge quality will be facilitated by individuals' sensemaking processes.…”

University endowment committees: how a learning orientation and knowledge factors contribute to portfolio diversification and performance

“…The first process relates strongly to the acquisition of new knowledge, whereas the second involves the application of the expanded knowledge (Van Wijk, Van Den Bosch, and Volberda 2011). These two dimensions or processes also have been described as organizational search and experimentation (Carlo, Lyytinen, and Rose 2012;Levitt and March 1988); reflection and action (Edmondson 2002); exploration and exploitation (March 1991); and potential and realized absorptive capacity (Zahra and George 2002). Zahra and George (2002) maintain that potential absorptive capacity consists of acquisition and assimilation of new external knowledge while realized absorptive capacity consists of knowledge transformation and exploitation.…”

Managing Knowledge and Managing Knowledge Work: What we know and what the Future holds

“…Recent research has suggested that the processes involved in acquiring, assimilating and using knowledge may differ across situations. For example, Carlo et al (2012) studied three different types of IT innovation in software firms and showed that there were distinct knowledge antecedents for each. For example, the diversity of knowledge (i.e., the heterogeneity of a firm's knowledge base) directly impacted the level of service innovation (the creation of new software functionality for a client's tasks); but for base innovations (changes to computing capabilities and related architectures) knowledge diversity had no direct effect, but was rather mediated by sensing routines (the types of scanning and focused search undertaken) and experimentation routines (the ways in which firms attempted to 'try-out' new ideas through trial and error learning).…”