The knowledge spillover theory (Acs et al.,
2009,
2013; Audretsch & Lehmann,
2005; Audretsch et al.,
2012) dates back at least to the early work of Marshall (
1890) taking positive externalities and spillover effects of agglomeration as the starting point. Over the years, this approach has been refined and defines regional growth as an endogenous phenomenon (Krugman,
1991; Romer,
1994), where knowledge spillovers explain much of the (statistical) variation of regional innovation activities and regional growth (Griliches,
1979; Jaffe,
1989). In particular, Jaffe (
1986) stimulated a new stream of research analyzing the sources of knowledge production, in particular universities and research institutes (Acs et al.,
1992,
1994; Audretsch,
2014; Audretsch & Feldman,
1996; Audretsch & Stephan,
1996; Brown,
2016; Guerrero et al.,
2015; Lehmann,
2015), emphasizing that geographic proximity to these sources of knowledge spillovers shapes location decisions (Audretsch & Lehmann,
2005), firm performance, and local competitiveness (Anselin et al.,
1997; Audretsch et al.,
2005; Hall et al.,
2003; Henderson et al.,
1998; Mowery & Ziedonis,
2001). The “transport” mechanism triggering geographical proximity and knowledge spillovers is the tacit component of knowledge (Kogut & Zander,
1992). In contrast to codified knowledge, such as patents or academic articles, tacit knowledge is sticky and bound to the individual as the source of knowledge and therefore difficult to record in such a way that it is meaningful and readily understood (Teece,
2005). Ambiguities inherent in the tacitness of knowledge can thus only be overcome by face-to-face communication in the presence of intensive, trust-based personal contacts, which may be ineffective or infeasible over long distances (Teece,
1977,
1981). Jaffe (
1986) thus argues that the “transport” mechanisms are mainly based on informal and personnel conversations and geographic proximity a necessary condition in capturing and exploiting the spillover benefits (Gertler,
2003; Kogut & Zander,
1992; Polanyi,
1967).
Local universities have thus been identified as critical sources of knowledge production and knowledge spillovers whereas academic research has made different attempts to measure and capture both the quantity and quality of knowledge spillovers (see Perkmann et al.
2013 for a comprehensive survey). The quantity aspect is mostly captured by measuring the amount of money spent on R&D, the number of employees engaged in research, the number of articles published, or the number of patents (Hall et al.,
2003; Henderson et al.,
1998; Varga,
2000), whereby data is publicly available through Web of Science or official statistics. The quantity effects are highly correlated with the size effects, whereby such measures are not necessarily linked to the absorption and exploitation of knowledge spillovers. Thus, more recent research is concerned about also including quality effects of academic research, like the number of citations linked to patents and articles, ranking positions of universities, faculties or academics like star scientists, and a more differentiated view of researchers, like their position in national and international research rankings, their networks, and distinguishing between general and specific knowledge and the nature of spillovers in the social sciences and the natural sciences (Audretsch et al.,
2005; Graf & Menter,
2021). Especially the understanding of the role of universities as knowledge producers and processes of formal as well as informal technology transfer to the private sector is important to emphasize the origins and sources of local knowledge spillovers (Leyden & Menter,
2018). The impact of universities as an important source of knowledge spillovers is undisputed and the empirical evidence overwhelming. We thus follow the existing literature and posit:
2.1.1 Absorptive capacities
The production and provision of knowledge to spill over as a necessary ingredient for firm performance and local competitiveness is unquestionable (Lau & Lo,
2015; Li et al.,
2013). While knowledge from universities and other sources of production may spill over like ‘manna from heaven’ or is just ‘in the air’ (Marshall,
1890), spillovers do not necessarily lead to innovations, technologies, and marketable products. Unfortunately, only a few studies focus on measuring the effects of knowledge spillovers. Carlsson and Fridh (
2002) state that only half of the invention disclosures in US universities result in patent applications. From these 50%, only about half, 25%, result in actual patents, and one third, about 16%, of these patents are licensed. From these 16%, only 10–20% of licenses yield a significant income. Hence, only about one percent of the invention disclosures in US universities yield in a significant income. Braunerhjelm et al. (
2010, p. 107) confirm these results by stating that “only 1% or 2% of inventions are successful in reaching the market”. The overwhelming part of invention disclosures, the other 98% of uncommercialized ideas, should thus rest in tacit knowledge.
One strand of the literature has identified new venture creation and entrepreneurship on the local level as a mechanism to pass the knowledge filter by filtering out the most promising ideas overlooked by others and to transform them into marketable products (Acs et al.,
2014,
2016; Audretsch et al.,
2016; Fritsch,
2013). There exists considerable empirical evidence confirming that knowledge spillovers and new venture creation play a fundamental role in forwarding innovations (Audretsch,
2014; Brown,
2016; Guerrero et al.,
2015; Lehmann & Menter,
2018; Teece & Linden,
2017). New venture creation captures only a fraction of the knowledge that spills over, and although entrepreneurial firms play an important role in the regional ecosystem, incumbent firms are the backbone of the national and regional economy.
2
While the entrepreneurship literature has focused on the filtering mechanisms linking new venture creation to knowledge spillovers, a parallel strand of literature has emerged, linking knowledge spillovers to incumbent firms. Cohen and Levinthal (
1989) provide a compelling interpretation of this link. They argue that by developing the capacity to adapt new technologies and ideas developed by universities and firms, firm-specific investments in knowledge such as R&D provide the capacity to absorb external knowledge. Consequently, incumbent firms should develop the absorptive capacity by R&D investments to appropriate at least some of the knowledge that spills over from external sources (Catozzella & Vivarelli,
2014). The more firms invest in R&D activities, the more knowledge is produced, leading to both, an increase of the absorptive capacity as well as the total pool of tacit and hitherto unexplored knowledge that could be then exploited and transformed into economic knowledge. The internal endowment of resources and capacities has since then widely been considered as a strategic source of performance, made popular by the so-called resource-based view of the firm (Barney,
1991). Among these resources, absorptive capacities have been identified as one of the most significant notions to emerge in organizational and management research in recent decades (Audretsch et al.,
2021b; Lane & Lubatkin,
1998; Lane et al.,
2006; Zahra & George,
2002) to explain firm incremental innovations and performance (Ritala & Hurmelinna-Laukkanen,
2013; Rodrigo-Alarcón et al.,
2020; Tomás‐Miquel et al.,
2019; Tödtling et al.,
2009; Zahra & George,
2002).
The concept of absorptive capacities describes the ability to “recognize the value of new, external information, assimilate it, and apply it to commercial ends” (Cohen & Levinthal,
1990, p. 128). The recognition and judgement of opportunities, the ability to evaluate and utilize external knowledge, are characteristics of entrepreneurial firms. But also established firms have to manage innovations as well as the utilization of ideas and access to external and internal sources of knowledge, given sufficient absorptive capacities (Cohen & Levinthal,
1990; Guerrero et al.,
2016; Qian & Acs,
2013). In particular, for high technology and knowledge-intensive industries, the in-depth understanding of state-of-the-art techniques and updated knowledge is central to value external developments and innovations. Focusing on individuals, learning is cumulative and results are the best if there is a relation between new and consisting knowledge (Cohen & Levinthal,
1990).
The importance of the absorptive capacity model is undisputed and provides robust results and stylized facts on the national (Qian & Acs,
2013), regional (Fritsch & Medrano Echalar,
2015; Lau & Lo,
2015; Miguélez & Moreno,
2015; Mukherji & Silberman,
2013) or firm level (Kostopoulos et al.,
2011; Moilanen et al.,
2014; Wales et al.,
2013; Zahra & Hayton,
2008) and seems to be robust and independent from the national context. Cozza and Zanfei (
2016) investigate the R&D activities as a proxy for absorptive capacities of Italian companies, Bishop et al. (
2011) examine data from a survey of UK firms, Kostopoulos et al. (
2011) for a sample of Greek firms, Moilanen et al. (
2014) focus on SMEs in less developed and peripheral regions in the North of Norway, or Miguélez and Moreno (
2015) analyze a sample of 274 regions of 27 European countries, all confirming that the quality of collaborations to universities as well as geographical proximity between partners influence different capabilities that foster absorptive capacities.
As the adaption of new technologies and ideas is a key factor for innovation and renewal and thus essential for the long-term survival of firms, it is obvious that also firm performance is influenced by absorptive capacities. In conclusion, we follow previous research that the access and utilization of external ideas and sources of knowledge is shaped by firms’ absorptive capacities (Cohen & Levinthal,
1990; Qian & Acs,
2013). To measure the impact of absorptive capacities, we include firm performance as a relevant output.
Previous research suggests that a possible partial substitution effect between internal R&D efforts and external knowledge activities exists (Escribano et al.,
2009; Tomás-Miquel et al.,
2019), leading to a reduction in (incremental) firm performance. Such reductions can be produced because of the effects of higher motivation and coordination costs induced by competing teams and tasks (Minbaeva et al.,
2003; Pitt & Clarke,
1999) and a costly excessive oversizing in absorptive capacity (Tomás-Miquel et al.,
2019). Todorova and Durisin (
2007) reorganize a new model based on a critical reflection of the central ideas on absorptive capacities by Cohen and Levinthal (
1990) and Zahra and George (
2002), taking circumstances into account that can be hindrance. Especially the ability to value new external knowledge is crucial for further steps in the overall transformation process and should be considered, if research detangles the concept of absorptive capacities. At the same time, it is precisely on this point that there is a risk of overinvestment, as it is extremely difficult to learn or improve the ability to value new knowledge.
Additionally, the contingent factors have a crucial influence on a successful transformation. Especially in incumbent firms, social integration mechanisms as well as power relations play an important role when it comes to leveraging capabilities in organizations. The relationships with customers, but also commitments to other stakeholders can prevent a proper valuation and exploitation of new knowledge (Hill & Rothaermel,
2003). Activities of managers as internal stakeholders as well as suppliers and customers as external stakeholders and their influence through power can result in substitution and crowding out effects (Hagedoorn & Wang,
2012). Consequently, social integration mechanisms as well as power relations influence the whole process of building absorptive capacities and can have a negative effect on the economic performance of firms. According to the weak-tie theory of Granovetter (
1973), especially relationships that are distant, unsteady, and thus weak are beneficial when new knowledge should be absorbed. All these effects indicate that there is an optimum for investing in absorptive capacities, leading us to posit an inverted U-shaped relationship between absorptive capacities and firm performance:
2.1.2 Joint effects of knowledge spillovers and absorptive capacity
Despite the potential partial effects of the link between absorptive capacities and knowledge spillovers on firm performance, diverse effects may occur because of the interaction between both levels. First, absorptive capacities and knowledge spillovers are not (mathematically) linked together, both variables are selected independently from each other to shape performance positively, like parallels, without an intersection. Both, R&D management in firms and higher education and cluster policy, are chosen independently. For the empirical testing, we would also abstract from the so-called ‘Demsetz-Hypotheses’ that policy makers and top managers are fully rational and statistically insignificant results reflect that all decisions are made optimally (Demsetz,
1973). Instead, we follow the overwhelming and convincing literature emphasizing the importance of firms having absorptive capacities as an essential pre-condition for translating knowledge spillovers into new technologies and products, the research question being not whether but how both variables are linked together.
The first approach, dating back to the early post-war period (Leyden & Menter,
2018), took the so-called ‘linear model of innovation’ as a starting point. In this framework, a linear unidirectional relationship is drawn running from basic research and knowledge spillovers and innovation to the ultimate goal of economic performance and economic growth (Balconi et al.,
2010; Leyden & Menter,
2018). This approach has been refined and amended including feedback relationships and contextual influences, and greatly benefited from the micro econometric work of Griliches (
1979), Jaffe (
1989), as well as Audretsch and Feldman (
1996).
This literature, that empirically tested the link between knowledge production and performance, generated a series of econometrically robust results substantiating the view that firms’ investment in knowledge inputs in the form of R&D expenditures were required to produce innovative output (Cohen & Klepper,
1992a,
1992b; Griliches,
1984). Firm performance in this framework follows a linear relationship with absorptive capacity, usually measured by R&D expenditures, and local knowledge spillovers, most often measured by patents or publication numbers of universities at the regional level (Audretsch & Feldman,
1996; Jaffe et al.,
1993). An increase in the decision variable, either knowledge spillovers or absorptive capacity, would lead to a linear increase in the output variable. The ‘knowledge production function’ made popular by Griliches (
1979) has become the most popular approach to measure the effect and performance of both the production of knowledge and the absorption capacity of firms. In this regard, several authors have proposed a direct, linear, and positive association between the regional innovation systems and the existence of knowledge spillovers, and innovation and firm performance (Bell,
2005; Coombs et al.,
2009; Pellegrino & Piva,
2020). Fritsch and Slavtchev (
2011, p. 914) examine the efficiency of different factors in regional innovation systems and find that “knowledge spillovers within the private sector as well as those that occur between public research institutions (universities as well as non-university research institutes) and actors in the private sector have a positive impact on private sector innovation activity”, especially when the technical fields of research in public research institutes match the innovation efforts in the private sector. The authors find that a higher R&D intensity in firms stimulates knowledge spillovers. Additionally, the intensity of university- industry linkages, measured as third-party funding, is beneficial for regional innovation systems and regional wealth (Lehmann, & Menter,
2016). Summing up, it is the combination of knowledge spillovers and absorptive capacities that positively affects firm performance. We express these arguments in a more formal way by positing: