The influence of knowledge related to innovative performance.
| Autor | Leiva, Juan Carlos |
| Cargo | Texto en ingl |
Introduction
The factors that determine business innovation performance can be grouped into three broad categories: contextual, organizational and personal (Crossan and Apaydin, 2010). There is evidence that many variables related to these categories affect innovation performance. However, understanding all of the factors that affect innovation performance, particularly if we refer to micro and small-sized businesses (which are the most numerous in most countries), remains an open question (Faherty and Stephens, 2016; Fernandez et al., 2012). Knowledge relatedness has not been studied as a possible determinant of innovation performance. Knowledge relatedness is understood as the degree of similarity between a company's knowledge with respect to its parent company, i.e. the company that the entrepreneur left to found his/her own company. (Sapienza et al., 2004; West and Noel, 2009). However, knowledge relatedness has been linked to overall business performance (West and Noel, 2009; Sapienza et al., 2004). There are two positions in this correlation. One maintains that there is a positive and linear correlation between the similarity of knowledge and business performance (West and Noel, 2009). The other stance considers that there is a somewhat curvilinear, inverted U-shaped relationship (Sapienza et al., 2004). This may imply that there is greater performance when there is no extreme, either of knowledge completely related to the parent company or to the contrary.
This paper aims to assess knowledge relatedness as a possible determinant of business innovation performance. Given that it is an unprecedented approach, it is expected to contribute to the understanding of the factors that affect business innovation performance, particularly in start-ups. The empirical application is performed in Costa Rica, whose economy mainly comprises small and micro businesses; therefore, it is also expected to provide a contribution from that perspective, given that studies on innovation are mainly based on large businesses in developed countries (Faherty and Stephens, 2016).
This issue is relevant because the world is continually moving toward an economy that is governed by knowledge and innovation and there is consensus in various areas that "the generation, exploitation and diffusion of knowledge are fundamental to economic growth, development and the well-being of nations" (Mortensen and Bloch, 2005, p. 3).
Our results show a positive and significant correlation between knowledge relatedness and innovation performance for a number of newly established firms in Costa Rica. It is interesting to note that no differences are found in the results when the assessment is based on the founder's prior business experience and the type of company that he/she left to start his/her own business.
The theoretical framework, methodology, results and conclusions are presented later in the text.
Theoretical framework
The relationship between knowledge relatedness and innovation performance has not been directly studied in the literature. In general, business innovation is a somewhat complex subject that can be studied from different approaches. A first approach is dimension. Dimension can be divided into two perspectives: processes versus results. For example, from the processes perspective, the (individual, group, organizational) level, the (internal versus external) sources and their locus (firm or networks), among others, may be analyzed. Additionally, concerning results, the forms (products, services, business models), magnitude (incremental, radical) and type (administrative or technical), among others, may be analyzed. A second approach is to study the determinants, which may be contextual, organizational and personal (Crossan and Apaydin, 2010; Flor and Oltra, 2004). In this section, the literature regarding the determinants of innovation performance and, subsequently, the concept of knowledge relatedness, are reviewed to then connect them in the empirical part of this paper.
The determinants of business innovation performance
As stated above, the factors that determine business innovation performance can be grouped into three broad categories: contextual, organizational and personal (Crossan and Apaydin, 2010).
There are various approaches in the contextual level for attempting to understand the determinants of business innovation. One is the study of geographical areas with a high concentration of innovative companies. These have been examined from various theoretical perspectives with a number of explanatory factors, such as external economies, social relationships, the creation of tacit knowledge and the need for companies to be more flexible and competitive in globalized environments, leading them to create supplier and partner networks that must be close, in addition to organizational routines and path dependency (Simmie, 2005). A second approach is to consider national innovative capacity, understood as the (political and economic) ability of a nation to constantly produce and commercialize a flow of innovative technologies for everyone in the long term (Furman et al., 2002). According to its proponents, this ability is determined by a common infrastructure for innovation (i.e. human capital, financing, education and training investment, protection of intellectual property, etc.) and the specific environment for cluster innovation (i.e. competitive strategies of firms, demand conditions, related and support industries, etc.) Continuing with the perspective of the environment, another approach is to analyze the determinants of innovation that result from the particular context of firms, with factors such as uncertainty and complexity (Tidd, 2001), relationships or networking with that environment (Chen et al., 2011; Pittaway, et al., 2004), relational capital (Capello 2002) and absorption capacity (Liao et al., 2007; Chen et al., 2009).
The second level of analysis of the determinants of innovation is organizational. In this regard, various determinants have been identified, such as structural capital (Santos et al., 2011), implementation capacity (Klein and Knight, 2005), company size (Camison-Zornoza et al., 2004), technological trajectory (Souitaris, 2002), operational strategy (Alegre et al., 2004) and entrepreneurial orientation (Fernandez et al., 2012). At this level of analysis, in a pioneering study, Damanpour (1991) links innovation performance to a number of organizational factors such as specialization, functional differentiation, professionalization, managerial attitude toward change and technical knowledge.
The third level of analysis is personal. In this regard, the determining personal factors of innovation can be grouped into three broad categories according to their origin: factors that result from the individual, from the work environment and from the social environment (Anderson et al., 2014). Some factors arising from the individual as such and that are listed as determinants of innovation are as follows: personality (Raja and Johns, 2010), goals orientation (Hirst et al., 2009; Gong et al., 2009), the values of the individual (Shin and Zhou, 2003), knowledge (Howell and Boies, 2004) and motivation (Yuan and Woodman, 2010). Regarding the work environment, the determinants vary between the complexity of the work (Shalley et al., 2009), the goals and requirements of the position (Ohly and Fritz, 2010; Baer and Oldham, 2006) and rewards (Baer et al., 2003). The factors linked to the social environment are leadership and supervision (Tierney, 2008 cited by Anderson et al., 2014), the influence of customers (Madjar & Ortiz-Walters, 2008), the feedback received (De Stobbeleir et al., 2011) and social...
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