INTRODUCTION
Open innovation (OI) has become a research topic that has stimulated interest in business and academia in various disciplines recognizing the role played by SMEs (Sabando-Vera, Yonfa-Medranda, Montalván-Burbano, Albors-Garrigos, & Parrales-Guerrero, Reference Sabando-Vera, Yonfa-Medranda, Montalván-Burbano, Albors-Garrigos and Parrales-Guerrero2022; Santoro, Ferraris, Giacosa, & Giovando, Reference Santoro, Ferraris, Giacosa and Giovando2018). In this sense, Bogers, Chesbrough, Heaton, and Teece (Reference Bogers, Chesbrough, Heaton and Teece2019) advocate OI activities in SMEs as a vehicle for increased growth. OI is a strategic alliance that encompasses a range of innovative methods and procedures in firms to stimulate internal innovation and widen the external use of innovation to markets (Chesbrough, Reference Chesbrough2012; Spithoven, Vanhaverbeke, & Roijakkers, Reference Spithoven, Vanhaverbeke and Roijakkers2013). With a collaborative approach among strategic collaborators, the objective of OI is to adopt and take advantage of external knowledge, and internal ideas that are not generating value can be used by others (Bogers et al., Reference Bogers, Chesbrough, Heaton and Teece2019; Chesbrough, Reference Chesbrough2012). In short, as OI combines knowledge inflows and outflows (inbound and outbound OI processes) (Bogers, Reference Bogers, de Pablos Heredero and López2012), it promotes more expansive, cooperative, and attractive innovation for a broad diversity of players (West & Bogers, Reference West and Bogers2017). OI has the potential to manage innovation by joining complementary knowledge, skills, and ideas, sharing the risks and costs linked to the innovation process, and providing more effective results assessments by larger groups of actors (Kimpimäki, Malacina, & Lähdeaho, Reference Kimpimäki, Malacina and Lähdeaho2022).
Despite the relevance of OI as a key factor in entrepreneurial systems (Pustovrh, Rangus, & Drnovšek, Reference Pustovrh, Rangus and Drnovšek2020) and SME competitiveness, some papers state that there is a lack of empirical studies supplying valid knowledge about OI in SMEs (Bogers et al., Reference Bogers, Chesbrough, Heaton and Teece2019; Chesbrough, Reference Chesbrough2012; Greul, West, & Bock, Reference Greul, West and Bock2018). The latest literature underlines the need to carry out studies on the variables that affect SMEs when moving from closed to OI (Barham, Dabic, Daim, & Shifrer, Reference Barham, Dabic, Daim and Shifrer2020; Duong, Voordeckers, Huybrechts, & Lambrechts, Reference Duong, Voordeckers, Huybrechts and Lambrechts2022; Grama-Vigouroux, Saidi, Berthinier-Poncet, Vanhaverbeke, & Madanamoothoo, Reference Grama-Vigouroux, Saidi, Berthinier-Poncet, Vanhaverbeke and Madanamoothoo2020; Lyu, Zhu, Han, He, & Bao, Reference Lyu, Zhu, Han, He and Bao2020; Spithoven et al., Reference Spithoven, Vanhaverbeke and Roijakkers2013). Implementing successful OI activities in SMEs has several challenges: internal assets protection, management of external relations, relatedness, and business model innovation (De Marco, Martelli, & Di Minin, Reference De Marco, Martelli and Di Minin2020). The theoretical framework around OI is the knowledge-based view that highlights the significance of the organization's knowledge characteristics, in addition to the organization's ability to integrate new external knowledge (Grant, Reference Grant1996). The application of broader knowledge stock may not just disrupt existing organizational routines due to increased complexity of knowledge, but also escalate the cost of assimilating new knowledge (Leiponen & Helfat, Reference Leiponen and Helfat2010). In this scenario, OI activities do not always achieve the most effective innovation results (Hofstetter, Zhang, & Herrmann, Reference Hofstetter, Zhang and Herrmann2018). Sometimes implementing costs related to OI activities are higher than the benefits linked to them (Bogers, Chesbrough, & Moedas, Reference Bogers, Chesbrough and Moedas2018). That is why researchers should look into factors that might facilitate/impede achieving a successful OI adoption by SMEs (Barham et al., Reference Barham, Dabic, Daim and Shifrer2020).
Due to OI characteristics, one important limitation that impedes effective results comes from the lack of a clear vision that limits strategic resources or strategic decisions related to the previous challenges (De Marco et al., Reference De Marco, Martelli and Di Minin2020; Filiou, Reference Filiou2021; Tang, Fisher, & Qualls, Reference Tang, Fisher and Qualls2021; Ullrich & Vladova, Reference Ullrich and Vladova2018) and makes it difficult for the alignment of OI activities with strategic objectives (Cavallo, Burgers, Ghezzi, & van de Vrande, Reference Cavallo, Burgers, Ghezzi and van de Vrande2021; Chesbrough, Reference Chesbrough2019). The role planning plays in promoting OI in SMEs has not been sufficiently addressed, even though such planning can be a key factor in promoting OI (Madrid-Guijarro, Martin, & García-Pérez-de-Lema, Reference Madrid-Guijarro, Martin and García-Pérez-de-Lema2021). The formalization of the strategy has to do with the formal planning and written innovation activities, the existence of long-term innovation plans, and adequate coordination of innovation activities (Cândido & Sousa, Reference Cândido and Sousa2017; Madrid-Guijarro et al., Reference Madrid-Guijarro, Martin and García-Pérez-de-Lema2021; Majama & Magang, Reference Majama and Magang2017; Sivam, Dieguez, Ferreira, & Silva, Reference Sivam, Dieguez, Ferreira and Silva2019). This concept is especially interesting to analyze as SMEs usually suffer from unclear innovation strategies (Müller, Buliga, & Voigt, Reference Müller, Buliga and Voigt2021) or even the lack of strategic planning or formal planning because they frequently face situations where insufficient time is available for strategic issues (Edvardsson & Durst, Reference Edvardsson and Durst2013). The lack of rules and procedures dictated by the formalization of the strategy may result in the messy creation and integration of diverse knowledge (Chaudhary, Reference Chaudhary2019). The crucial role of the definition of strategy that allows integration of organizational knowledge through ‘formal processes that ensure the capture, analysis, interpretation, and integration’ of knowledge (Luca & Atuahene-Gima, Reference Luca and Atuahene-Gima2007) should be present when defining innovation strategy. Literature reveals that the choice on whether to manage the knowledge-sourcing process with external parties formally or informally is contingent on the sources of knowledge involved (Du, Leten, & Vanhaverbeke, Reference Du, Leten and Vanhaverbeke2014; Gesing, Antons, Piening, Rese, & Salge, Reference Gesing, Antons, Piening, Rese and Salge2015). High levels of formalization promote the relationship between market-based partnerships and financial performance of innovation projects, as some firms have a competitive relationship with some suppliers and need measures to protect innovation projects from unwanted knowledge spillovers while sourcing external knowledge (Schultze, Prandelli, Salonen, & Van Alstyne, Reference Schultze, Prandelli, Salonen and Van Alstyne2007). Furthermore, a formal collaboration approach increases the chance that new idea development will take place according to plan and that unfeasible suggestions from customers will be filtered out (Du et al., Reference Du, Leten and Vanhaverbeke2014).
Previous literature also highlights an important stream of research on innovation control systems (Saunila & Mäkimattila, Reference Saunila, Mäkimattila, Vrontis, Weber, Thrassou, Shams and Tsoukatos2018). The use of control systems can help SMEs to increase sales, improve customer satisfaction, and increase innovation performance (Brenes, Mena, & Molina, Reference Brenes, Mena and Molina2008). Control systems include performance evaluation, monitoring tools, and a culture of regular control and monitoring of progress (Brenes et al., Reference Brenes, Mena and Molina2008). In this article, control is defined following Cândido and Sousa (Reference Cândido and Sousa2017), including not only the knowledge and control of costs linked to innovation activities but also the use of indicators to monitor innovation activity performance along with technical and economic control of innovation activities. Through control, firms can identify their development, strengths, and weaknesses.
Through management, firms ensure compliance with innovation strategies and implementation of OI activities with long- or short-term measurements that allow SMEs to improve their competitiveness and performance (Akhmetshin, Vasilev, Mironov, Yumashev, Puryaev, & Lvov, Reference Akhmetshin, Vasilev, Mironov, Yumashev, Puryaev and Lvov2018). However, Drechsler and Natter (Reference Drechsler and Natter2012) clarify that there is not yet a complete understanding of the effect control systems have on the performance of OI activities, and Carneiro, Farias, da Rocha, and Ferreira da Silva (Reference Carneiro, Farias, da Rocha and Ferreira da Silva2016) identify that managers make extensive use of economic/accounting metrics and little or no use of indicators related to innovation suggesting a possible short-term perspective. Consequently, there are an important number of papers that ask for an additional study about the effects of innovation control (Chesbrough & Appleyard, Reference Chesbrough and Appleyard2007; Rubera, Chandrasekaran, & Ordanini, Reference Rubera, Chandrasekaran and Ordanini2016; Saulina, Reference Saulina2017; Saunila & Mäkimattila, Reference Saunila, Mäkimattila, Vrontis, Weber, Thrassou, Shams and Tsoukatos2018).
The scarcity of empirical papers on the effect of OI planning in SMEs and the role played by control mechanisms is even more evident in the case of companies in developing countries or Latin America (Brenes, Montoya, & Ciravegna, Reference Brenes, Montoya and Ciravegna2014; Cirera & Muzi, Reference Cirera and Muzi2020). Although promoting innovation in Latin America is a key priority to enhance economic prosperity, the region is struggling to bring innovation to the forefront. Innovation in emerging markets mostly deals with incremental changes to implement existing practices and technologies (Perez-Aleman, Reference Perez-Aleman2011; Pietrobelli & Rabellotti, Reference Pietrobelli and Rabellotti2011). McDermott and Pietrobelli (Reference McDermott, Pietrobelli, Camuffo and Pedersen2017), grounded on the theories of knowledge transfer, discuss how innovation for SMEs in Latin America depends largely on certain types of knowledge which might come from different types of network structures or sources.
Latin American context is worth noting. Latin America benefitted from a period of relative political stability and economic growth between the 2000s and mid-2010s, as a result of the reforms implemented during the 1990s and increase in prices in the commodities it exports (Brenes, Haar, & Requena, Reference Brenes, Haar and Requena2009; Ciravegna, Fitzgerald, & Kundu, Reference Ciravegna, Fitzgerald and Kundu2014). However, from 2014 to 2016, as a result of the decrease in commodity prices, emerging economies’ contribution to world economic growth deteriorated abruptly, reducing the attractiveness of Latin America, with its comparative advantage in natural resource-based products (Brenes, Camacho, Ciravegna, & Pichardo, Reference Brenes, Camacho, Ciravegna and Pichardo2016). Resource-based product dependency implies that the manufacturing of products not related to commodities declined as a share of Latin America's output. With growth deceleration, it is harder for firms to be profitable. Only those who invest in innovation, differentiate their strategies and establish collaborations with multinational firms, government agencies and other types of organizations can develop their capabilities to compete (Brenes et al., Reference Brenes, Camacho, Ciravegna and Pichardo2016). Cuervo-Cazurra et al. (Reference Cuervo-Cazurra, Carneiro, Finchelstein, Duran, Gonzalez-Perez, Montoya, Borda Reyes, Fleury and Newburry2019), in the Latin American context, identify that some firms have been able to break away the focus on price with low-quality products and develop uncommoditizing strategies using innovation.
In emerging economies, SMEs have limited resources as well as a basic supply chain. Caballero-Morales (Reference Caballero-Morales2021) identifies innovation as a key recovery factor for SMEs in these economies because it allows SMEs to equip themselves with the skills and tools to continue operating and maximize growth opportunities. Innovation allows them to modernize its operations for economic development (Markovic, Koporcic, Arslanagic-Kalajdzic, Kadic-Maglajlic, Bagherzadeh, & Islam, Reference Markovic, Koporcic, Arslanagic-Kalajdzic, Kadic-Maglajlic, Bagherzadeh and Islam2021). Therefore, analyzing innovation in emerging economies is important, because it is widely suggested as one of the most effective strategies to respond to crises and to improve their performance (Wenzel, Matthias, & Lieberman, Reference Wenzel, Matthias and Lieberman2020). Perez-Aleman (Reference Perez-Aleman2011) highlights two relevant points about the Latin American context that somehow can affect innovation at SMEs. First, she points out the technological disadvantage suffered by firms in late-developing economies (knowledge and resource disadvantages) being depending on learning. Second, the Latin American context is characterized by a low-income environment where there are coordination problems, lack of infrastructure, and government assistance and technical services. All these factors involve a real challenge when many actors need to act in simultaneous and complementary changes aimed at gaining a competitive advantage based on innovation.
Though approaches to the topic of innovation appear in the ‘Bogotá Manual’ for Latin America (Jaramillo, Lugones, & Salazar, Reference Jaramillo, Lugones and Salazar2001) and the manual of ‘Innovation and regional specialization in Latin America’ (Barroeta, Paton, Palazuelos, & Giraldez, Reference Barroeta, Paton, Palazuelos and Giraldez2017; Navarro & Olivari, Reference Navarro and Olivari2016), there is a deficiency of innovation data on developing countries (Bortagaray, Reference Bortagaray2016), and absence of a standardized methodology in innovation issues for these types of economies is evident (Castro, Flores, & Rajadel, Reference Castro, Flores and Rajadel2017). The purpose of this research is (1) to analyze how the formalization of innovation strategies affects innovation activities in Ecuadorian SMEs, (2) to verify whether inbound and/or outbound OI activities affect innovative performance in Ecuadorian SMEs, and (3) to study the moderating effect control measures have on the influence of OI activities on innovative performance. Innovative performance is the ‘contribution of product and process innovation to a firm's economic performance’ (Meeus & Oerlemans, Reference Meeus and Oerlemans2000: 47). In this sense, innovative performance includes the ability to introduce new products/services, its effect on sales, and efficiency.
Ecuador is especially interesting for this research since it is a country at mid-stage in its development, very dependent on natural resources, and interested in promoting industrial growth (Castro et al., Reference Castro, Flores and Rajadel2017). One of the most important challenges for this country is to add value to its productive matrix through highly innovative products (Espinel, Reference Espinel2014). However, accomplishing sustainable growth can be delayed by an overreliance on commodity exports, and a failure to develop appropriate innovation systems that respond to dynamic changes in competitiveness (Anand, McDermott, Mudambi, & Narula, Reference Anand, McDermott, Mudambi and Narula2021). Considering all these characteristics, more research on the main factors that contribute to implementing OI in Ecuadorian SMEs is needed.
To tackle the main aims of this article, an empirical study is developed on 543 Ecuadorian companies. The proposed structural model is estimated by partial least squares. The findings show that the formalization of strategies favors the performance of OI activities in Ecuadorian SMEs. Outbound activities positively affect innovative performance of the company, while there is a moderating effect of the control of innovation on the relationship between inbound activities and innovative performance of Ecuadorian SMEs. In general, the results have important implications for SME management and Public Administrations. Thus, SMEs that wish to obtain competitive advantages through innovation must be aware that they have to carry out strategic formalization to promote OI activities that result in improved innovative performance. In turn, they must include control mechanisms to benefit from all the effects associated with inbound innovation activities. These results are also relevant in the design of public policies that seek competitiveness through OI in SMEs.
This study contributes to the literature in several aspects. First, it provides a comprehensive approach where OI is examined in a context of an emerging country. It is important to contextual innovation in the field of emerging markets (Bahar Kaya, Abubakar, Behravesh, Yildiz, & Sani Mert, Reference Bahar Kaya, Abubakar, Behravesh, Yildiz and Sani Mert2020; Beltramino, Garcia-Perez-de-Lema, & Valdez-Juarez, Reference Beltramino, Garcia-Perez-de-Lema and Valdez-Juarez2021). These markets are characterized by their relatively low levels of innovation (Heredia-Pérez, Geldes, Kunc, & Flores, Reference Heredia-Pérez, Geldes, Kunc and Flores2018), clients are more sensitive to prices (Derbyshire, Reference Derbyshire2014), and institutions play a very important role in their strategic processes (Stock, Greis, & Fischer, Reference Stock, Greis and Fischer2002). As pointed out by Gassmann (Reference Gassmann2006), broad context-related characteristics (such as degree of globalization, degrees of technological intensity and technology fusion, and knowledge leveraging) can modify the efficiency of collaborative efforts on innovation. Although there are studies in other emerging regions (Bahar Kaya et al., Reference Bahar Kaya, Abubakar, Behravesh, Yildiz and Sani Mert2020), there are still very incipient studies in the reality of Ecuador, which has characteristics that make the study of OI in this region interesting such as less-aligned innovative structures and systems (Castro et al., Reference Castro, Flores and Rajadel2017). Second, it considers a broad variety of OI activities, distinguishing between inbound and outbound activities, which allows more specific conclusions to be drawn about the situation of SMEs. The research gap identified by Greul et al. (Reference Greul, West and Bock2018) is also filled by simultaneously considering the use of both types of OI activities. Third, this work contributes to reducing the limits and risks organizations face when innovating. In doing so, it expands the research on the importance of implementing OI as a strategy that helps improve the performance of SMEs in developing countries (Chesbrough, Reference Chesbrough2003; Gentile-Lüdecke, Torres de Oliveira, & Paul, Reference Gentile-Lüdecke, Torres de Oliveira and Paul2020; Wang, Chang, & Shen, Reference Wang, Chang and Shen2015).
THEORETICAL BACKGROUND AND HYPOTHESES DEVELOPMENT
OI is an ‘innovation process based on knowledge flows intentionally managed across organizational boundaries’ (Chesbrough, Reference Chesbrough2003: 34) that seeks to accelerate innovation in the market. According to Chesbrough and Appleyard (Reference Chesbrough and Appleyard2007), SMEs can take advantage of OI to expand their internal innovation by adopting external innovations. The use of OI tools promotes innovation in SMEs in a shared way (Harel, Schwartz, & Kaufmann, Reference Harel, Schwartz and Kaufmann2019; Lichtenthaler, Reference Lichtenthaler2008a). The collaborative framework of OI implies a change in the traditional innovation processes of companies (Sivam et al., Reference Sivam, Dieguez, Ferreira and Silva2019). Thus, OI facilitates the use of other companies’ capabilities in the management of innovative processes (Lichtenthaler, Reference Lichtenthaler2008b), favors the integration of external networks to develop new products (Sisodiya, Johnson, & Grégoire, Reference Sisodiya, Johnson and Grégoire2013), and transfers external knowledge in a collaborative way (Chesbrough & Appleyard, Reference Chesbrough and Appleyard2007; Schneckenberg, Reference Schneckenberg2015; Sisodiya et al., Reference Sisodiya, Johnson and Grégoire2013). Companies can offer their internal knowledge (Rosa, Mello, Chimendes, & Amorim, Reference Rosa, Mello, Chimendes and Amorim2020) and at the same time as they integrate knowledge that has been generated by other companies. As pointed out by Chesbrough (Reference Chesbrough2003), developing a collaborative business model with OI increases long-term innovation in the market.
The literature distinguishes two types of OI activities: (1) acquisition of external technology (inbound) and (2) exploitation of internal technology (outbound) (Bogers et al., Reference Bogers, Chesbrough and Moedas2018; Chesbrough & Crowther, Reference Chesbrough and Crowther2006). Inbound activities include customer and external network participation in innovative processes, R&D outsourcing, and internal intellectual property (IP) licenses (van de Vrande, de Jong, Vanhaverbeke, & de Rochemont, Reference van de Vrande, de Jong, Vanhaverbeke and de Rochemont2009). Network collaborations allow businesses to compensate for inefficiencies in regulatory and judiciary systems by relying on long-term relationships based on reciprocity and allow firms to reduce the risk of opportunism without having to internalize transactions (Brenes, Ciravegna, & Pichardo, Reference Brenes, Ciravegna and Pichardo2019). Universities and public–private R&D, training centers, and trade associations can enhance technological change and the implementation of new practices (McDermott, Corredoira, & Kruse, Reference McDermott, Corredoira and Kruse2009). Outbound activities include ‘the creation of new organizations, external licenses of IP, and the participation of non-R&D workers in innovation initiatives’ (van de Vrande et al., Reference van de Vrande, de Jong, Vanhaverbeke and de Rochemont2009: 424). The theoretical framework around OI is the knowledge-based view that highlights the significance of the organization's knowledge characteristics, in addition to the organization's ability to integrate new external knowledge (Grant, Reference Grant1996), knowledge is the masterpiece. OI accepts that knowledge that enhances innovations is anywhere in a company's value chain (Chesbrough, Reference Chesbrough2003). Since knowledge is an idiosyncratic good, transactions are complex and require specific skills (Teece, Reference Teece2000). Knowledge management comprises the use of mechanisms that help companies to manage knowledge as an asset that promotes business development (Zemaitis, Reference Zemaitis2014). This article is focused on two steps of the OI process proposed by Lichtenthaler (Reference Lichtenthaler2007), planning and control.
Innovation Strategies and OI Activities in SMEs
Formally developed strategy and long-term vision help the organization to detect implementation discrepancies and priorities, and ease organizational alignment around a clear message (Brenes et al., Reference Brenes, Mena and Molina2008). The formalization of innovation strategies favors the development of scientific, technological, organizational, financial, and commercial activities that lead to the implementation of successful innovations. Defining and communicating the innovative objectives to be pursued lead to designing appropriate inter-organizational policies and networks (Cândido & Sousa, Reference Cândido and Sousa2017). Also, as pointed out by Bowonder, Dambal, Kumar, and Shirodkar (Reference Bowonder, Dambal, Kumar and Shirodkar2015), in these cases, CEOs promote long-term success strategies in their companies. Planning allows companies to have a vision of the future to predict and face opportunities and threats that can arise in their environments (Chesbrough & Appleyard, Reference Chesbrough and Appleyard2007; Stonehouse & Pemberton, Reference Stonehouse and Pemberton2002). Therefore, the formalization of these strategies represents an important approach for those who wish to lead the market through innovation. The clear majority of successfully implemented strategies include formal planning (Brenes, Ciravegna, & Woodside, Reference Brenes, Ciravegna and Woodside2017). This fact is even more important for smaller firms because as highlighted by Corredoira and McDermott (Reference Corredoira and McDermott2020) even though diverse knowledge can be crucial for innovation, SMEs can have an inadequate understanding of which new knowledge is most pertinent to improve their innovative capabilities.
OI activities have certain characteristics that make the formalization of innovation strategies necessary. OI involves the search for partners and accepting risk, uncertainty, and exchange (Kratzer, Meissner, & Roud, Reference Kratzer, Meissner and Roud2017; Sivam et al., Reference Sivam, Dieguez, Ferreira and Silva2019). Working with a multitude of partners can lead to management problems and entail significant cost (Du Chatenier, Verstegen, Biemans, Mulder, & Omta, Reference Du Chatenier, Verstegen, Biemans, Mulder and Omta2009; Sieg, Wallin, & Von Krogh, Reference Sieg, Wallin and Von Krogh2010). In addition, absorbing knowledge from different sources can be very challenging (Gentile-Lüdecke et al., Reference Gentile-Lüdecke, Torres de Oliveira and Paul2020). The integration of external knowledge in a company's own products (inbound) can lead to resistance known as the ‘Not Invented Here’ syndrome (van de Vrande et al., Reference van de Vrande, de Jong, Vanhaverbeke and de Rochemont2009). On the other hand, Dahl and Pedersen (Reference Dahl and Pedersen2004) point out that outbound activities also involve important challenges since they are affected by the imperfections of the technology market and lack of internal process formalization.
The formalization of an innovation strategy that is aligned with a company's strategy facilitates the development of structures, horizontal and vertical channels of knowledge communication within the company, active listening from outside boundaries of the company (Sivam et al., Reference Sivam, Dieguez, Ferreira and Silva2019), and commitment of all the company's members. van de Vrande et al. (Reference van de Vrande, de Jong, Vanhaverbeke and de Rochemont2009) identify innovation strategies as key elements in establishing successful collaborations with stakeholders, allowing a change in the business model that favors openness. The formalization of innovation strategies helps prevent risks and barriers to innovation and contributes to the successful economic growth of SMEs in the long term in different competitive markets. Sivam et al. (Reference Sivam, Dieguez, Ferreira and Silva2019), through a survey, addressed Portuguese researchers, and concluded that the formalization of an innovation strategy is one of the main antecedents to OI in SMEs. These authors advocate the improvement of SME innovation strategies through action plans and medium- and long-term objectives. Du Chatenier et al. (Reference Du Chatenier, Verstegen, Biemans, Mulder and Omta2009) point out that if an OI project is not properly planned, this weakness can cause great difficulties. Brunswicker and Ehrenmann (Reference Brunswicker and Ehrenmann2013) conclude that German SMEs integrate innovation practices that seek growth based on planning. Cândido and Sousa (Reference Cândido and Sousa2017) find that those Brazilian SMEs that formalize their strategy are more likely to implement OI. While Mamula and Popovic-Pantic (Reference Mamula and Popovic-Pantic2015) observe that Serbian SMEs with strategic planning can present successful innovation projects with greater confidence. If a firm proactively manages knowledge inflows and outflows, it can strategically leverage a multitude of new strategic options (Kutvonen, Reference Kutvonen2011).
Based on this evidence, we identify the need to consider the different types of OI activities as they involve different risks (‘Not Invented Here’ syndrome vs. imperfections of the technology market), and propose the following hypotheses:
Hypothesis 1a: The formalization of an innovation strategy positively affects outbound OI in SMEs.
Hypothesis 1b: The formalization of an innovation strategy positively affects inbound OI in SMEs.
Open Innovation and Innovative Performance in SMEs
Inbound OI practices are crucial to achieving a sustainable competitive advantage (Chesbrough, Reference Chesbrough2003; Hung & Chou, Reference Hung and Chou2013; Sisodiya et al., Reference Sisodiya, Johnson and Grégoire2013). The search for external sources establishes connections with commercial and scientific partners, creating advantages over the competition (Gambardella & Panico, Reference Gambardella and Panico2014; Tsinopoulos, Yan, & Sousa, Reference Tsinopoulos, Yan and Sousa2019). This practice aims to acquire novel ideas for the development of new products (Hung & Chou, Reference Hung and Chou2013; Parida, Westerberg, & Frishammar, Reference Parida, Westerberg and Frishammar2012), increasing SME sales and growth (Ritala, Olander, Michailova, & Husted, Reference Ritala, Olander, Michailova and Husted2015; Rubera et al., Reference Rubera, Chandrasekaran and Ordanini2016; Stephan, Andries, & Daou, Reference Stephan, Andries and Daou2019).
Inbound innovation helps SMEs solve problems that arise in the integration and creation of ideas among individuals or organizations (Lee, Fong, Barney, & Hawk, Reference Lee, Fong, Barney and Hawk2019). Inbound innovation helps SMEs to manage specialized and complex knowledge (Lee, Lee, & Garrett, Reference Lee, Lee and Garrett2019), increasing the likelihood of boosting innovative performance at the organizational level (Kafouros, Love, Ganotakis, & Konara, Reference Kafouros, Love, Ganotakis and Konara2019; Kim, Kim, & Foss, Reference Kim, Kim and Foss2016).
Previous empirical evidence has shown a positive relationship between inbound OI and SME performance (Wang et al., Reference Wang, Chang and Shen2015). Parida et al. (Reference Parida, Westerberg and Frishammar2012) report that inbound OI activities, like the acquisition of technology, are necessary to increase innovative performance. D'Angelo and Baroncelli (Reference D'Angelo and Baroncelli2020) conclude that Italian companies that have an inbound OI model based on R&D collaboration with universities and research centers and other private companies report positive results in both the development of new products and innovative performance. The analysis by Jasimuddin and Naqshbandi (Reference Jasimuddin and Naqshbandi2019) on a sample composed of French managers reveals that the alliance with the external knowledge of contracted research centers can help SMEs develop innovative capabilities. Considering the Latin American agribusiness, Brenes et al. (Reference Brenes, Montoya and Ciravegna2014) obtained that innovation capabilities which include the company's relation with universities have a direct effect on the way a firm is perceived by its clients, and thus also on the clarity of its positioning in the market. In this sense, McDermott and Pietrobelli (Reference McDermott, Pietrobelli, Camuffo and Pedersen2017) suggest that to upgrade SME capabilities we cannot forget that certain nonmarket institutions can act as social and knowledge bridges. Based on the previous reasoning, inbound activities in Ecuadorian SMEs are expected to influence innovative performance positively.
Hypothesis 2a: Inbound OI positively affects innovative performance in SMEs.
Outbound OI is the outbound movement of ideas and knowledge based on technological development and external connection among different companies that influence the innovative performance of SMEs (Lee, Fong, et al., Reference Lee, Fong, Barney and Hawk2019; Lichtenthaler, Reference Lichtenthaler2008b, Reference Lichtenthaler2015). The exploitation of knowledge allows SMEs to commercialize IP assets that are underused or not used in their companies, generating new ventures, external IP licenses, and collaboration with work teams (Bianchi, Croce, Dell'Era, Di Benedetto, & Frattini, Reference Bianchi, Croce, Dell'Era, Di Benedetto and Frattini2016; Bogers et al., Reference Bogers, Chesbrough, Heaton and Teece2019; Chesbrough, Reference Chesbrough2012; Enkel, Gassmann, & Chesbrough, Reference Enkel, Gassmann and Chesbrough2009; van de Vrande et al., Reference van de Vrande, de Jong, Vanhaverbeke and de Rochemont2009). This type of activity promotes technological standardization in industries (Lichtenthaler, Reference Lichtenthaler2008a), leading to the creation of new businesses (Chesbrough & Garman, Reference Chesbrough and Garman2009; Hung & Chou, Reference Hung and Chou2013). In addition, through outbound innovation, companies can sell their underused ideas to their partners (van de Vrande et al., Reference van de Vrande, de Jong, Vanhaverbeke and de Rochemont2009), which leaves SMEs free to focus on developing their internal capabilities and, therefore, outperforming their competitors (D'Angelo & Baroncelli, Reference D'Angelo and Baroncelli2020; van de Vrande, Vanhaverbeke, & Gassmann, Reference van de Vrande, Vanhaverbeke and Gassmann2010). Outbound innovation models are crucial for SMEs as they minimize uncertainty since companies are already familiar with the projects (Popa, Acosta, & Conesa, Reference Popa, Acosta and Conesa2017; Remneland Wikhamn & Styhre, Reference Remneland Wikhamn and Styhre2019). Firm resources and experience are better aligned to outbound activities (Stephan et al., Reference Stephan, Andries and Daou2019). This makes a difference when it comes to reducing the time needed to launch a new product or service (Lee, Lee, et al., Reference Lee, Lee and Garrett2019) and decreasing the risk of obsolescence by increasing competitiveness (Laursen & Salter, Reference Laursen and Salter2006; Xin, Yeung, & Cheng, Reference Xin, Yeung and Cheng2010). Therefore, the benefits of outbound innovation are presented as productivity gains, improvements in product quality, and savings in costs and time (Greco, Grimaldi, & Cricelli, Reference Greco, Grimaldi and Cricelli2016). These are benefits that can lead to a decrease in prices, an increase in sales, and, therefore, an improvement in SME innovative performance (Greul et al., Reference Greul, West and Bock2018). Outbound innovation generates monetary and nonmonetary benefits from the commercial exploitation of internal knowledge and technologies and, at the same time, reduces the threats of competition (Popa et al., Reference Popa, Acosta and Conesa2017). On the other hand, it is worth noting that this type of OI leads companies to assume the risk of transferring relevant knowledge, which could weaken their competitive positions. Consequently, companies that opt for these activities should avoid selling what is known as their core knowledge (Bianchi, Campodall'Orto, Frattini, & Vercesi, Reference Bianchi, Campodall'Orto, Frattini and Vercesi2010; Da̧browska, Fiegenbaum, & Kutvonen, Reference Da̧browska, Fiegenbaum and Kutvonen2013). Additionally, outbound activities entail greater challenges given the imperfections in the technology market (Lichtenthaler & Ernst, Reference Lichtenthaler and Ernst2007).
Singh, Gupta, Busso, and Kamboj (Reference Singh, Gupta, Busso and Kamboj2021) and Inauen and Schenker-Wicki (Reference Inauen and Schenker-Wicki2012) found that outbound activities have a relevant impact on SMEs’ innovative performance, especially through the generation of radical innovations. Lee, Park, Yoon, and Park (Reference Lee, Park, Yoon and Park2010), in the Korean context, revealed that knowledge and technology transfers to other companies maximize the success of new products and services in the long term. Similarly, Bigliardi and Galati (Reference Bigliardi and Galati2016) showed that internal knowledge exchange in open networks generates a collaborative environment that allows SMEs to undergo continuous improvement. They reported that new firms which establish alliances with others (outbound OI) increase the likelihood of profiting from their innovations without requiring commercialization capabilities. Based on the previous literature, we hypothesize the following.
Hypothesis 2b: Outbound OI positively affects innovative performance in SMEs.
Control of Innovation as a Moderating Variable in the Relationship Between Open Innovation and Innovative Performance
Control is based on formal rules, procedures, and standardized routines that facilitate the coordination of innovation projects (George, Walker, & Monster, Reference George, Walker and Monster2019; Ylinen & Gullkvist, Reference Ylinen and Gullkvist2014). This includes the initial stages of innovation activities, monitoring their processes, implementation, and commercialization (Bisbe & Malaguenõ, Reference Bisbe and Malaguenõ2015). Control systems are important evaluation tools to reduce potential errors and costs (Cui, Wu, & Tong, Reference Cui, Wu and Tong2018) and technical and economic uncertainty (Akhmetshin et al., Reference Akhmetshin, Vasilev, Mironov, Yumashev, Puryaev and Lvov2018; Bogers et al., Reference Bogers, Chesbrough, Heaton and Teece2019). The use of control systems can help SMEs increase sales, improve customer satisfaction, and increase innovation performance. Similarly, control exerts an effect on product innovation, investigating how different systems of control are related to different phases of innovation processes, which can have an important influence on creativity, coordination, and integration of knowledge, as well as on the filtering phases of innovation processes.
Inbound and outbound activities may require different controls, as they call for varying degrees of change due to a combination of environmental, organizational, managerial, and structural forces (Nguyen, Larimo, & Wang, Reference Nguyen, Larimo and Wang2019). With inbound OI activities, formal and standardized rules should be implemented with greater rigor (Bogers et al., Reference Bogers, Chesbrough, Heaton and Teece2019; Havlíček, Thalassinos, & Berezkinova, Reference Havlíček, Thalassinos and Berezkinova2013; Ylinen & Gullkvist, Reference Ylinen and Gullkvist2014) as these activities are meant to change how firms develop their innovation (Parida et al., Reference Parida, Westerberg and Frishammar2012). In contrast, outbound activities involve a lower level of uncertainty as firms are familiar with their internal knowledge (Burcharth, Knudsen, & Søndergaard, Reference Burcharth, Knudsen and Søndergaard2014; Chesbrough, Reference Chesbrough2016), and use external channels to generate added value (Laursen & Salter, Reference Laursen and Salter2006; Ylinen & Gullkvist, Reference Ylinen and Gullkvist2014). In this case, controls can be more flexible (Ylinen & Gullkvist, Reference Ylinen and Gullkvist2014), keeping in mind that this control allows SMEs to share their internal knowledge and avoid the risk of sharing core knowledge (Akhmetshin et al., Reference Akhmetshin, Vasilev, Mironov, Yumashev, Puryaev and Lvov2018; Havlíček et al., Reference Havlíček, Thalassinos and Berezkinova2013; Lichtenthaler, Reference Lichtenthaler2009).
In general, controls lead to process improvements (Guo, Paraskevopoulou, & Santamaría Sánchez, Reference Guo, Paraskevopoulou and Santamaría Sánchez2019), make knowledge and skills more explicit, and reduce possible deviations (Benner & Tushman, Reference Benner and Tushman2003). In addition, control systems can be used to codify innovation practices, facilitating their efficient incorporation (Bedford, Reference Bedford2015; Ylinen & Gullkvist, Reference Ylinen and Gullkvist2014). Empirical research signals the positive influence innovation control has on OI activities affecting innovation performance (Nguyen et al., Reference Nguyen, Larimo and Wang2019; Saunila & Mäkimattila, Reference Saunila, Mäkimattila, Vrontis, Weber, Thrassou, Shams and Tsoukatos2018). Ylinen and Gullkvist (Reference Ylinen and Gullkvist2014) demonstrate that the use of control systems associated with performance improvement in SMEs differ according to the types of innovation activities involved, and they are tools to define the resources necessary to carry out improvements and obtain benefits. Similar results are found by Guo et al. (Reference Guo, Paraskevopoulou and Santamaría Sánchez2019) for the Spanish context. The following hypothesis is proposed:
Hypothesis 3a: The control of innovation moderates the effect of inbound innovation on innovative performance.
Hypothesis 3b: The control of innovation moderates the effect of outbound innovation on innovative performance.
Figure 1 shows the research model proposed by the previous hypotheses.
Figure 1. Research model
SETTING AND METHODS
Ecuadorian Context
Although Ecuador experienced a boom in both mining and construction, this economic boom helped the rise of political leaders who used government revenues to buy their popularity by expanding public sector investment and employment (Aguilera, Ciravegna, Cuervo-Cazurra, & Gonzalez-Perez, Reference Aguilera, Ciravegna, Cuervo-Cazurra and Gonzalez-Perez2017). Fernández and Martin (Reference Fernández and Martin2017) describe Ecuador as a lower-middle-income economy with a productive structure specialized in goods and services with low value-added and based, mainly, on the export of raw materials. SMEs are crucial for Ecuador, since they strengthen the value chain of large organizations (Peña & Vega, Reference Peña and Vega2017), represent 95% of productive units, and generate around 70% of employment (Ron & Sacoto, Reference Ron and Sacoto2019).
The National Innovation System of Ecuador has made the first approach to OI by promoting ‘a network of institutions from the public and private sectors, whose interactions initiate, develop, modify, and commercialize new technologies’ (Acosta & Kumar, Reference Acosta and Kumar2015: 1). The objective of this initiative is to encourage organizations to implement research and development (R&D) (Fagerberg & Sapprasert, Reference Fagerberg and Sapprasert2011). However, Ecuadorian SMEs do not have the incentives or infrastructures to manage science and technology, nor do they have the human capital to guarantee the expansion of OI as a performance facilitator (Castro et al., Reference Castro, Flores and Rajadel2017; Fernández & Martin, Reference Fernández and Martin2017). According to INEC (2019), 69.3% of Ecuadorian SMEs stated that they had not innovated in their organizations in the last three years, due to lack of knowledge, lack of technological resources, and organizational culture.
The absence of support from innovation centers and universities, and lack of infrastructures in Ecuador make its innovation system to be still at an emerging stage (Fernández-Sastre & Reyes-Vintimilla, Reference Fernández-Sastre and Reyes-Vintimilla2020). Ecuador is considered one of the most entrepreneurial countries in Latin America among Chile, Colombia, and Peru, but the last in innovation according to the Global Innovation Index elaborated by Dutta, Lanvin, and Wunsch-Vincent (Reference Dutta, Lanvin and Wunsch-Vincent2020). This responds to the fact that in Ecuador, businesses arise out of necessity rather than an opportunity, avoiding turning a venture into an innovative and sustainable business over time. According to Zapata-Cantu and González (Reference Zapata-Cantu and González2021), about seizing capability, Ecuador ranks below 10 Latin American countries, among them Brazil, Chile, Mexico, and Costa Rica, and below 11 Latin American countries concerning its transforming capability. Fernández-Sastre and Vaca-Vera (Reference Fernández-Sastre and Vaca-Vera2017) highlight the importance of non-R&D cooperative relationships as sources of innovation for the Ecuadorian context, revealing a positive influence of this type of relationship on the likelihood of introducing new products. This article used data from the Ecuadorian Survey of Innovation (ENAI) covering mainly large Ecuadorian companies. Research about how Ecuadorian SMEs is needed.
Sample
In this study, 543 CEOs of Ecuadorian SMEs were personally interviewed. The sample selection process was based on the principles of stratified sampling in finite populations discarding very small companies (fewer than five employees) and considering the segmentation by industrial activity. To compute the size of each stratum, information from the Ministry of Industries of Ecuador was used. Sample estimation contemplates in the worst case (p = 0.5), 3% maximum error with a 95% confidence level. The firms that refused to participate were substituted by similar companies selected at random. Sample distribution is reported in Table 1. The mean age of the firms in the sample is 17.96 years and the average number of employees (size) is 20.75.
Table 1. Sample distribution
Interviews with company CEOs were accomplished between September and December 2018, using a questionnaire. SME CEOs are approached because they are the main decision-makers in this type of firm (Brenes et al., Reference Brenes, Mena and Molina2008; Van Gils, Reference Van Gils2005). The knowledge CEOs have significantly influenced the strategic behavior of an organization (O'Regan & Sims, Reference O'Regan and Sims2008). Control tests were conducted during the process of preparing our survey. In addition, when developing the questionnaire, special care was taken to minimizing social convenience bias. Therefore, words associated with confidence-success were eliminated (Bstieler, Hemmert, & Barczak, Reference Bstieler, Hemmert and Barczak2015), special emphasis was placed on the validity of all answers (Yang, Zhang, Jiang, & Sun, Reference Yang, Zhang, Jiang and Sun2015), and the confidentiality of the data was assured (Harms, Reference Harms2015). In addition, we conducted a pre-test with five SME owners to verify a proper understanding of the questionnaire (Madrid-Guijarro et al., Reference Madrid-Guijarro, Martin and García-Pérez-de-Lema2021).
Measures
Scales used in this research have been previously verified in the literature. Formalization strategy is measured considering a scale built of four items using a 5-point Likert scale (1: totally disagree, 5: totally agree). The items are: there is a formally defined innovation strategy (Brenes et al., Reference Brenes, Mena and Molina2008; Sivam et al., Reference Sivam, Dieguez, Ferreira and Silva2019), the company carries out formal planning and written innovation activities (Cândido & Sousa, Reference Cândido and Sousa2017; Madrid-Guijarro et al., Reference Madrid-Guijarro, Martin and García-Pérez-de-Lema2021; Majama & Magang, Reference Majama and Magang2017), the company plans long-term innovation activities (Brenes et al., Reference Brenes, Mena and Molina2008; Majama & Magang, Reference Majama and Magang2017; Sivam et al., Reference Sivam, Dieguez, Ferreira and Silva2019), and the company carries out adequate coordination of innovation activities (Sivam et al., Reference Sivam, Dieguez, Ferreira and Silva2019). To measure the Innovation Control variable, we used a scale with four items based on previous research. This scale considers control and knowledge of the costs of innovation (Cândido & Sousa, Reference Cândido and Sousa2017), control of innovation activity performance through indicators (Majama & Magang, Reference Majama and Magang2017), control of innovation activities through the role of budgets (Batra, Sharma, Dixit, & Vohra, Reference Batra, Sharma, Dixit and Vohra2017), and frequent technical and economic control of innovation activities (Majama & Magang, Reference Majama and Magang2017).
To measure OI activities, an adaptation of the scale by van de Vrande et al. (Reference van de Vrande, de Jong, Vanhaverbeke and de Rochemont2009) was used. Outbound innovation is built of three items: (1) starting a new business from the internal knowledge of the company itself, (2) the sale or offer of licenses or royalty agreements to other companies to obtain benefits from their IP, patents, copyright, or trademarks, and (3) the use of the knowledge of and initiatives by employees who are not involved in R&D. Inbound activities are measured through three items: (1) the direct participation of clients in their innovation processes, (2) participation in new or established companies to obtain access to their knowledge or to obtain other synergies, and (3) the purchase of R&D services from other organizations, such as universities, public research bodies, commercial engineers, or suppliers. For the Latin American context, Brenes et al. (Reference Brenes, Montoya and Ciravegna2014) highlighted ‘company's relationship to academic organizations’. Innovative performance is measured by adapting the scales proposed by Gunday, Ulusoy, Kilic, and Alpkan (Reference Gunday, Ulusoy, Kilic and Alpkan2011), Pino, Felzensztein, Zwerg-Villegas, and Arias-Bolzmann (Reference Pino, Felzensztein, Zwerg-Villegas and Arias-Bolzmann2016), van de Vrande et al. (Reference van de Vrande, de Jong, Vanhaverbeke and de Rochemont2009), and Wang et al. (Reference Wang, Chang and Shen2015). We consider the skill of introducing new products and services into the market in comparison with a firm's competitors, quality of new products and services, increase in sales due to new products, increase in sales caused by improved products, efficiency in delivery processes, both inside and outside of the company, and improved processes to save costs and time.
RESULTS
To estimate the proposed model, we use partial least squared estimations (PLS-SEM). This technique delivers reliability and validity of the measures and estimates the paths being superior to the multiple regression analysis (Barroso, Cepeda, & Roldán, Reference Barroso, Cepeda, Roldán, Esposito, Chin, Henseler and Wang2010). Rigdon, Sarstedt, and Ringle (Reference Rigdon, Sarstedt and Ringle2017) explain that the technique has to be consistent with the model type established in the research. In this sense, when the research aims to estimate a factor model, researchers should use CB-SEM, while in a model of composites they should use a composite-based method such as PLS-SEM (Chin, Reference Chin and Marcoulides1998; Rigdon et al., Reference Rigdon, Sarstedt and Ringle2017; Sarstedt, Hair, Ringle, Thiele, & Gudergan, Reference Sarstedt, Hair, Ringle, Thiele and Gudergan2016). Furthermore, when there is any hesitation about the nature of the construct, Sarstedt et al. (Reference Sarstedt, Hair, Ringle, Thiele and Gudergan2016) recommend using PLS as this technique provides the least biased results. Composite indicators are the operational definition of the emergent construct (Henseler, Reference Henseler2015). This type of construct does not have an error term, acting as contributors to a construct instead of causing it (Bollen, Reference Bollen2011; Bollen & Bauldry, Reference Bollen and Bauldry2011). Composite indicators share the same consequences (Henseler, Reference Henseler2017), but they do not need to be unidimensional. Thus, composite indicators may represent different aspects relating to the construct. As clarified by Sarstedt et al. (Reference Sarstedt, Hair, Ringle, Thiele and Gudergan2016), PLS uses Mode A and Mode B. Mode A links to the correlation weights derived from bivariate correlations between each indicator and the construct, while Mode B has to do with regression weights. Indicators of composite B constructs are not correlated. This technique is suitable in this research because we use composite types B and A in our model (Chin, Reference Chin and Marcoulides1998; Dijkstra & Henseler, Reference Dijkstra and Henseler2011; Tenenhaus & Tenenhaus, Reference Tenenhaus and Tenenhaus2011). OI activity constructs (inbound and outbound) are composite type B as their items identify different activities which do not need to be correlated. We analyze the moderating effect linked to the innovation control variable estimating three models using the orthogonalization method proposed by Henseler and Chin (Reference Henseler and Chin2010). In model 1, we do not consider the innovation control variable. In model 2, we introduce the effect of the innovation control variable on the innovative performance of the company. Finally, in model 3, we consider the moderating effect of this variable on the relationship between OI activities and innovative performance. To test the hypotheses, we run 5,000 subsamples using the bootstrapping technique.
Measurement Model
Type A composite constructs
We proved the reliability and convergent validity of the type A composite constructs of the model considering: factor loads (value and significance), Cronbach's alpha, composite reliability (Chin, Reference Chin and Marcoulides1998), Dijkstra-Henseler rho ratio (Dijkstra & Henseler, Reference Dijkstra and Henseler2015), and the average variance extracted (AVE) (Table 2). Our results reveal that three type A composite constructs (strategy, innovative performance, and innovation control) have items whose factor loads are above the minimum threshold of 0.707 (Carmines and Zeller, Reference Carmines and Zeller1979), varying between 0.730 and 0.940 (p-value: 0.000). Cronbach's alpha is higher than 0.7 for all the constructs, reaching important levels, such as 0.948 for strategy, 0.914 for innovative performance, and 0.961 for innovation control. We find similar results when it comes to composite reliability (ρ c) and Dijkstra-Henseler's ratio (ρA), which leads us to verify the reliability of the constructs; that is, their internal consistency (Cepeda-Carrion, Cegarra-Navarro, & Cillo, Reference Cepeda-Carrion, Cegarra-Navarro and Cillo2019). Following Fornell and Larcker (Reference Fornell and Larcker1981), we confirm that the level of the AVEs is equal to or higher than 0.5 for each construct. In this research, the AVE varies between 0.604 and 0.859.
Table 2. Measurement model
Notes: VIF, Variance Inflation Factor. SRMR 0.079; CR, Composite Reliability; AVE, Average Variance Extracted.
Finally, we examine discriminant validity through the Fornell-Lacker criterion and the Heterotrait-Monotrait ratio (HTMT) proposed by Henseler, Ringle, and Sarstedt (Reference Henseler, Ringle and Sarstedt2016) (Table 3). In our research, (1) the square root of the AVE of each construct is higher than the correlation with the rest of the constructs, verifying the criteria proposed by Fornell-Larcker, and (2) the HTMT between each pair of constructs varies from 0.261 to 0.814, which is below the proposed maximum of 0.85 (Henseler et al., Reference Henseler, Ringle and Sarstedt2016).
Table 3. Measurement model. Discriminant validity based on Fornell-Larcker criterion (F-L) and HTMT ratio
Type B composite constructs
The indicators used previously are not valid when we talk about type B composite constructs. In this case, we rely on the indicators’ weights and their significance and on the variance inflation factor (VIF) among the indicators to examine the potential multicollinearity among them (Diamantopoulos & Siguaw, Reference Diamantopoulos and Siguaw2006; Table 2). The results reveal that all the weights are significant (two tails T-Student p-value: 0.000) which leads us to believe that all the indicators are relevant for the type B composite constructs. Furthermore, the factor loads are above 0.7 in all the cases. As the VIF is lower than 3 (Hair, Risher, Sarstedt, & Ringle, Reference Hair, Risher, Sarstedt and Ringle2019), varying between 2.938 and 1.460, we confirm that there are no multicollinearity problems.
Structural Model
Coefficient values and their significance along with the value of the adjusted R 2 are individual measures of the explanatory power of the model (Chin, Reference Chin2010). The significance of the relationships is performed with a bootstrapping analysis with 5,000 subsamples. The results of the three estimated models (Table 4) reveal that there is a positive and significant path between the formalization of innovation strategies on the performance of outbound activities (Model 1: 0.492, p-value: 11.302; Model 2: 0.492, t-value: 11.369; Model 3: 0.493, t-value: 11.340) and inbound activities (Model 1: 0.565, t-value: 17.159; Model 2: 0.565, t-value: 17.304; Model 3: 0.565, t-value: 17.221). These results verify hypotheses H1a and H1b. Given that the coefficients linked to the strategy-inbound activity relationship are higher than those obtained for the outbound activities, we can affirm that the effect of formally defining an innovation strategy affects the performance of inbound activities to a greater extent. While in the three models we find that outbound activities positively affect the innovative performance of SMEs (Model 1: 0.213, t-value: 2.353; Model 2: 0.184, t-value: 1.959; Model 3: 0.214, t-value: 2.259), this relationship is not significant for inbound activities when the variable control of innovation is introduced in the structural model (Models 2 and 3). In fact, in Model 1, the coefficient of this path is 0.147 with an adjusted significance since the t-value is 1.746, while in Models 2 and 3, this relationship is no longer significant, with associated t-values of 1.209 and 0.694, respectively. These results verify hypothesis H2a but not hypothesis H2b. The influence of the innovation control variable on the effect of inbound activities on innovative performance was verified through the study of the moderating effect. Thus, Model 3 shows a significant and positive moderating effect (0.246, t-value: 2.622). Furthermore, it is relevant to highlight the large increase (from 0.12 to 0.19) that occurs in the adjusted R 2 linked to innovative performance when introducing this moderating effect in the model. This result leads us to consider that the establishment of innovation controls causes inbound innovation activities to have a positive effect on innovative performance that would not exist if these controls had not been established. The analysis of the f 2 following the heuristic rules by Cohen (Reference Cohen1988) shows that in this model there is a strong effect of the formalization of strategies on inbound innovation activities (0.470), a moderate effect of strategies on outbound activities (0.322), and two weak effects regarding the relationships between outbound activities and innovative performance (0.021) and moderating effect of control on the relationship between inbound activities and innovative performance (0.026). Figure 2 shows the main results.
Table 4. Structural models
Notes: t-values in brackets. Bootstrapping 95% Confidence Intervals (bias-corrected) in square brackets (n = 5,000 subsamples). ***p = 0.001; **p = 0.01; *p = 0.05. Estimations considering size and age sector as control variables show similar results.
Figure 2. Model 3 results
Since estimations of the path coefficients are made based on ordinary least squares regressions, we must avoid the presence of multicollinearity between the antecedent variables of each of the endogenous constructs. Therefore, we must analyze the multicollinearity between inbound and outbound innovation activities and the control of innovation activity since they are the antecedents of the endogenous construct of innovative performance. As Table 5 shows, in Model 3, the VIF values comply with that indicated by Hair et al. (Reference Hair, Risher, Sarstedt and Ringle2019) since they are less than 3.
Table 5. VIF value for inner model (Model 3)
Predictive Validity Using Hold-Out Samples
Following Shmueli et al. (Reference Shmueli, Sarstedt, Hair, Cheah, Ting, Vaithilingam and Ringle2019), we include the analysis of the predictive validity of our model in samples not used for the estimation to evaluate the practical relevance of the model. To do this, we use the PLS predict analysis with ten sections and ten repetitions. First, since all the Q 2 of the PLS model are greater than 0 (Table 6), the prediction errors of the PLS model results are fewer than the prediction errors resulting from simply using the mean values. Therefore, our PLS model has better predictive performance (Shmueli et al., Reference Shmueli, Sarstedt, Hair, Cheah, Ting, Vaithilingam and Ringle2019). Second, we compare the root values of the root-mean-squared error (RMSE) obtained in the PLS-SEM analysis and those obtained with a linear regression (LM) model that regresses all the exogenous indicators to predict each endogenous indicator. Our PLS model, supported theoretically through the hypotheses presented, produces fewer prediction errors for all the indicators except for 3. Therefore, according to Shmueli et al. (Reference Shmueli, Sarstedt, Hair, Cheah, Ting, Vaithilingam and Ringle2019), our model has a medium predictive level.
Table 6. The predictive capacity of the model. PLS predict
DISCUSSION
OI is important for SMEs because it helps them to expand their limits both in the creation and commercialization of innovations (Greul et al., Reference Greul, West and Bock2018; West, Salter, Vanhaverbeke, & Chesbrough, Reference West, Salter, Vanhaverbeke and Chesbrough2014). Some authors consider that OI is a necessity for SMEs because it strengthens their resources and supplies missing assets (Brunswicker & Vanhaverbeke, Reference Brunswicker and Vanhaverbeke2015; De Marco et al., Reference De Marco, Martelli and Di Minin2020). However, openness involves certain risks and costs (Dahlander & Gann, Reference Dahlander and Gann2010; Enkel et al., Reference Enkel, Gassmann and Chesbrough2009) that need to be assessed and controlled. This study analyses whether formalising innovation strategies helps SMEs to carry out inbound and/or outbound OI activities, in addition to the effect that control measures have on innovation performance. Based on a survey of 543 Ecuadorian SMEs, results indicate that formalisation is positively associated with the performance of inbound and outbound activities in Ecuadorian SMEs. Latin American OI is still very underrepresented in strategic formalization studies (Aulakh, Kotabe, & Teegen, Reference Aulakh, Kotabe and Teegen2000; Nicholls-Nixon, Davila, Sanchez, & Rivera Reference Nicholls-Nixon, Davila, Sanchez and Rivera2011); especially in countries such as Ecuador, where OI is a limited and little-explored topic (Fernandez-Sastre & Vaca-Vera, Reference Fernández and Martin2017; Santos, Reference Santos2015).
Among the variables that make this study interesting is Ecuador's need to reduce poverty at the national level and mainly in urban and rural areas where SMEs with low innovation indicators are located (INEC, 2021). Latin America is a special scenario because most countries have gone through extensive economic, political, and regulatory structural reforms (Borda, Geleilate, Newburry, & Kundu, Reference Borda, Geleilate, Newburry and Kundu2017; Brenes, Reference Brenes2000; Cuervo-Cazurra, Maloney, & Manrakhan, Reference Cuervo-Cazurra, Maloney and Manrakhan2007; Dau, Reference Dau2013) that have boosted SME productivity/performance and innovation, however, progress has been slow, lagging behind international economies, as well as those of Central, Eastern Europe, and Asia (McDermott & Pietrobelli, Reference McDermott, Pietrobelli, Camuffo and Pedersen2017).
To accelerate progress in the formalisation, companies can determine precisely what kind of knowledge they need to access from international economies and how to obtain it (Giannopoulou, Yström, & Ollila, Reference Giannopoulou, Yström and Ollila2011). These results are in line with some authors who have argued that without formalization, inbound activities would be ‘disorganised, sporadic and ineffective’ (Okhuysen & Eisenhardt, Reference Okhuysen and Eisenhardt2002). Formalization reduces ambiguity by providing ‘behaviour directives’ (Pertusa-Ortega, Zaragoza-Sáez, & Claver-Cortés, Reference Pertusa-Ortega, Zaragoza-Sáez and Claver-Cortés2010), with positive effects on the use of external knowledge (Duong et al., Reference Duong, Voordeckers, Huybrechts and Lambrechts2022).
Our result sustains the latest data on innovation in Ecuador published by the Ecuadorian Institute of Statistics and Census (INEC) and the World Intellectual Property Organization (WIPO), that report that Ecuadorian companies that have formal innovation processes can contribute to the economic performance of the country, and advocate for encouraging the way to involve working with OI networks to implement mechanisms for the management of ideas, increase knowledge and reach solutions that benefit the participants is encouraged (Correa-Quezada, Alvarez-García, De la Cruz Del Río-Rama, & Maldonado-Erazo, Reference Correa-Quezada, Alvarez-García, De la Cruz Del Río-Rama and Maldonado-Erazo2018). These results lead to relevant theoretical implications since there are few studies on how formalization shapes the OI paradigm (Gentile-Lüdecke et al., Reference Gentile-Lüdecke, Torres de Oliveira and Paul2020). Organizations that plan systematically facilitate collaboration with external and relevant partners and improve their collaboration methods. They develop skills to use resources distinctively (Griffith, Huergo, Mairesse, & Peters, Reference Griffith, Huergo, Mairesse and Peters2006), reconfigure and gain new resources, and strengthen planning for subsequent innovation projects (Zahra, Sapienza, & Davidsson, Reference Zahra, Sapienza and Davidsson2006). Organizations must ensure the operationalization of the strategy and its correct and timely implementation, aligning the organization and providing detailed monitoring (Brenes et al., Reference Brenes, Mena and Molina2008).
Regarding the effect that these OI activities have on SME innovative performance, our results are in line with Kang and Hwang (Reference Kang and Hwang2019), who show that OI practices are important to improve innovative performance in these companies. However, this effect is moderated by control activities in the case of inbound activities. Fu, Liu, and Zhou (Reference Fu, Liu and Zhou2019) consider that the difficulties SMEs have controlling inbound activities come from the wide range of resources involved. These difficulties lead to incomplete data about inbound collaboration, decreasing the reliability of the indicators used in control systems. Regarding outbound-type activities, we find a positive effect on the innovative performance of companies, showing the capacity that these companies have to benefit from their collaborators’ and workers’ knowledge, fostering an improvement in SME innovative performance, as other papers have shown (Dahlander & Gann, Reference Dahlander and Gann2010; Masucci, Brusoni, & Cennamo, Reference Masucci, Brusoni and Cennamo2020). Therefore, our findings report evidence on the importance of inbound activity control to achieve a significant effect on innovative performance.
Theoretical Implications
The results of this investigation have important implications for managers and public policymakers who seek an efficient innovative ecosystem in the Ecuadorian economy. Given that OI generates greater innovative performance in Ecuadorian SMEs, activities linked to the promotion of innovation should be established through inbound and outbound OI strategies. Managers should be aware of the relevant role that innovation strategy formalization plays in promoting OI. Even though many Ecuadorian SMEs face daily operational problems, this research highlights the need to dedicate time and resources to establishing innovation strategies for the promotion of OI activities in those companies that seek a competitive advantage through innovation. In addition, managers should understand that control systems must be established for these activities, especially for inbound innovation, to ensure a significant effect on innovative performance. Therefore, Ecuadorian SMEs are advised to manage the transition from a traditional innovation model to an open one based on the specific planning and control of inbound activities.
In the interest of promoting innovation in the Ecuadorian context, the following issues should be addressed: regulatory changes, laws that do not facilitate innovation, bureaucracy, limited size of the market, lack of access to technology, lack of collaboration with universities, lack of tolerance to failure, short-term thinking which expects immediate rewards from innovation, and the scarce resources available to innovate. In addition, encourage governmental public entities to support knowledge diffusion as they are necessary to cultivate radical innovation (Sánchez, Rojas-Ávila, & Giraldo-González, Reference Sánchez, Rojas-Ávila and Giraldo-González2021). In both cases, innovation allows exploiting actors’ knowledge resources and is associated with prior concerted efforts to build capacities to drive OI (Weber & Heidenreich, Reference Weber and Heidenreich2017).
Ecuadorian public administrations should consider the results of this work when designing their innovation policies. Public administrations should foster an ecosystem that supports OI in SMEs, helping to establish orderly and planned OI models within SME strategies, implementing communication programs to socialize innovation, providing training programs in matters of innovation management, and controlling inbound and outbound activities in Ecuadorian SMEs to promote the transformation of the Ecuadorian productive matrix. Ecuadorian industries should depend less on nonrenewable natural resources and more on products with added value and highly innovative content. High-impact policy actions are required within the framework of an industrial policy for the SME sector with an emphasis on institutional development and regional collaboration, specially oriented to the development of an innovative market for Latin America. In this context, Ecuador, along with consolidating the efforts made so far, should bet on a renewed institutional framework that contributes to adjusting development policy in key areas and in those aimed at promoting business innovation, private investment, and coordination between companies and institutional actors in a perspective of productive linkages (Carpio, Figueroa, & Alvarado, Reference Carpio, Figueroa and Alvarado2015). Ecuadorian managers should seek the support of public administrations, together with chambers of commerce and business associations, to obtain the funding required to implement the OI activities SMEs need.
Limitations and Future Research Directions
This work is not free from limitations which, in turn, present opportunities for new lines of research. Thus, it is noteworthy that the study is limited to the Ecuadorian context. To extend these results to developing economies, it would be interesting to analyze the context of OI and control in the economies of Latin American countries, such as Colombia, Peru, Brazil, Argentina, and Chile, to corroborate the results obtained. The study has been based on cross-sectional data. A time-series or panel data study in future research would allow us to analyze how SMEs evolve in terms of OI activities and their efficiency. Given the importance that communication has in companies and among companies in the development of OI, in future research, it would be interesting to analyze how different means of communication within companies and among companies affect OI activities.
New research could also focus on how gaps in market support institutions underpin the functioning of developing country economies, influencing the costs of doing business, complicating the conduct of IO activities (Khanna & Palepu, Reference Khanna and Palepu2010), and hindering the formalization of innovation strategy. These institutional gaps include uncertainty in regulatory frameworks, inefficient enforcement mechanisms, poorly functioning factor markets, excessive bureaucracy, and lack of protection of human rights and property rights (Brenes, Ciravegna, & Pichardo, Reference Brenes, Ciravegna and Pichardo2017), and the absence of control mechanisms. For example, emerging markets often lack certain institutions that allow for more efficient trade. The absence or malfunctioning of these institutions is referred to as institutional gaps (Khanna & Palepu, Reference Khanna and Palepu2010).
Finally, OI is closely related to the learning capacity of the firm. This capacity has been highlighted in SMEs by Perez-Aleman (Reference Perez-Aleman2011) to understand the diffusion of new norms and change existing local practices using the collective capacity building considering the multinational's effect. Similarly, the effect of multinationals on the learning process of SMEs through collective learning is relevant when analyzing the factors within the control systems and the formalization of the strategy that reinforce collective learning and, therefore, the OI capabilities of SMEs.
DATA AVAILABILITY STATEMENT
The authors confirm that the data supporting the findings of this study are available within the article and its supplementary materials.
