HOME | ÍNDICE POR TÍTULO | NORMAS PUBLICACIÓN Espacios. Vol. 37 (Nº 03) Año 2016. Pág. 11
Eduardo Gomes CARVALHO; Rodrigo Marçal GANDIA 1; Cassiano de Andrade FERREIRA; Marcelo de Oliveira GARCIA; Joel Yutaka SUGANO
Recibido: 14/09/15 • Aprobado: 04/11/2015
ABSTRACT: Open innovation has been an important issue for the scientific community and therefore has been widely studied by researchers. This study arose from the gap found by the authors related to the absence of studies about open innovation in small and medium organizations. This article brings, through a meta-analysis of quantitative papers, a summary of behavioral similarities and differences between small and large companies that work with open innovation. In the results and discussions are presented the aspects in which organizations of different sizes have similar behaviors and the points of divergence observed in their performance. |
RESUMO: A inovação aberta tem se mostrado um tema importante para a comunidade científica e tem sido amplamente estudado pelos pesquisadores. O presente estudo surgiu diante do gap encontrado pelos autores relacionado à ausência de estudos sobre inovação aberta em pequenas e médias empresas. Este constructo traz, através da meta-análise de trabalhos quantitativos, uma síntese das similaridades e diferenças de comportamento entre as pequenas e grandes empresas que trabalham com a inovação aberta. Nos resultados e discussões são apresentados os aspectos em que as organizações, de tamanhos distintos, apresentam comportamentos semelhantes e os pontos de divergência observado na atuação das mesmas. |
The term open innovation was coined by Chesbrough (2003) and according to Chesbrough et al. (2006) open innovation is the intentional use of inputs and outputs of knowledge to accelerate internal innovation and expand the markets for external use of innovation. After Chesbrough (2003) seminal work, companies and researchers began to pay attention to the intentional use of knowledge inputs and outputs. Thus, some companies started to foster open innovation process and the researchers started to study this phenomenon.
However, the researchers' efforts are focused on the employment of open innovation by large companies. Regardless the reasons for this fact occurrence, it means, if it is because the big companies focus more on the open innovation paradigm than small and medium-sized organizations, or if it occurs because researchers mainly heed to these big companies due to the editorial appeal that exists for studying large companies, the fact is that open innovation in small and medium organizations has been few addressed by researchers.
There are some efforts to study open innovation in small and medium organizations. Van de Vrande et al. (2009) can be considered one of the most notorious works exploring this gap. Such awareness is supported by the high number of citations of that paper and probably is due to the fact that it is the first paper exploring the small and medium companies as a research gap. Obviously, there are more recent efforts as will be presented during the article.
However, it should be stressed from the beginning that because open innovation is a subject still growing and forming, research protocols were very different between them. Although such situation, it is important to conduct a meta-analysis of the studies exploring this gap in order to advance the studies about open innovation. When performing a meta-analysis, the coincidences, discrepancies and limitations of the studies are identified, allowing future studies to outline a closer picture of the reality referring to the subject. Therefore, this paper presents perspectives for researchers wishing to contribute to filling this gap.
Thus, knowing the reported context, the aim of this paper is to present a meta-analysis of studies about open innovation in small and medium organizations. But to achieve this aim, we must first carry out a synthesis of basic bibliography in order to better understand the interest of this study and to position the reader. This theoretical framework will be presented in the next section. Then will be presented the research method applied, aiming not only to allow the replication, but also understand the applied effort to survey data sources. Following, will be presented the discussion about the synthesized data and after all will be presented the closing remarks of this article.
The potential for innovation or even the adoption of a technology comes from research and development activities, from the political and institutional context of the country, its technological quality, the availability of human resources and industrial structure (BARRETO, 2012). According to Norman (2014), an innovation can be incremental if the improvements are applied in some activity that already exists, or can be radical, which occurs when you create a new procedure. Among the existing types of innovation they can be classified according to its object.
Regarding to open innovation, despite being credited to Chesbrough (2003) the beginning of the current research, some authors as Huizingh (2011) argue that open innovation has become an "umbrella" that encompasses, connects and integrates a number of existing activities, while Hossain (2013) practices similar speech by stating that open innovation overlays other concepts such as user production, crowdsourcing and distributed innovation.
Even the concept of open innovation is still questioned. Hossain (2013), for example, claims that open innovation definition is not yet totally clear. If we observe the number of definitions given by Chesbrough himself, Hossain (2013) statement has sense. In the seminal paper, Chesbrough (2003) stated that open innovation means that value ideas can be originated inside or outside the company and can use both internal and external paths to market. Three years later, Chesbrough et al. (2006) presented a new definition that emphasized the intentionality of knowledge flows, being such definition cited in the introductory section. Recently, West et al. (2014) presented the latest definition provided by Chesbrough and Borges (2014), which considered the growing interest in non-monetary knowledge flows, defining open innovation as a distributed innovation process, based on knowledge flows intentionally managed through organizational boundaries, using monetary and non-monetary mechanisms in accordance with the organization's business model. In just over a decade there were three definitions for the same concept, and all presented by the same author. However, these definitions have in common the fact of proposing organizational boundaries as something permeable, in constant symbiosis with other agents and the external environment. These definitions meet the paradigm of closed innovation, through which the company should close itself, and develop and exploit their own innovations.
Despite being antagonistic to the concept of closed innovation, open innovation is not something that came out of nowhere. It is an evolution that has gradually occurred in corporate behavior. If you return to the beginning of the section, when was presented Huizingh (2011) statement that open innovation has become an "umbrella" that encompasses, connects and integrates a number of existing activities, it can be seen that some companies, if not most, have practiced open innovation by involving suppliers, customers, forming alliances, among other activities. Chesbrough (2003) contribution was to organize such activities within this "package". Several advances followed consequently. Enkel and Gassmann (2004), for example, divided open innovation into three macro processes: outside-in, inside-out and coupled.
According to Gassmann and Enkel (2004), the outside-in macro process, which is also known as inbound open innovation (CONBOY and MORGAN, 2011) or exploitation (VAN DE VRANDE et al., 2009), is the enrichment of the knowledge base of the own company through the integration of suppliers, customers and outsourcing of external knowledge to enhance the innovation capability of a company.
The inside-out macro process is defined by Gassmann and Enkel (2004) as the process of recording profits taking ideas to the market, selling intellectual property and multiplying technology by the transfer of ideas to the external environment. This process is also called outbound open innovation by Conboy and Morgan (2011) or exploitation by van de Vrande et al. (2009).
Some authors only work with the classification of the process into inside-out and outside-in, but Gassmann and Enkel (2004) recommend a third macro process, the coupled. This situation occurs because the coupled macro process refers to the connection of the outside-in and inside-out processes working together (joint ventures, alliances, and other forms) with complementary partners (universities, suppliers, competitors, etc.) where "give and receive" is crucial to success.
Most studies of open innovation focuses on such processes in large companies, yet few studies show how small and medium sized companies use such activities. This way, after the presentation of the used method, a compilation of the activities identified by the papers that address open innovation in small and medium organizations will be presented.
In order to achieve the main objective, this research involved the following steps:
• Definition of the research question;
• Finding relevant research;
• Inclusion and exclusion criteria;
• Extraction and encoding of data;
• Data Analysis;
• Discussion.
The first step refers to the definition of the research question and assists in defining the criteria for searching, inclusion and exclusion of studies and development of the tool for extraction and data encoding, and also assists in data analysis. The research question is: "how has open innovation been used in small and medium organizations?". Such research question presents as direction the analysis of open innovation activities and processes adopted in small and medium organizations.
The second step, named the location of relevant research, is concerned with the choice of the database and the definition of the search terms. Thus, the chosen database was SCOPUS due to the wide range of magazines from different publishers that it has. Aiming at a first result a greater amount of papers, given that the research on open innovation in small businesses is still recent, the keywords used were only open innovation and SMEs (acronym for small and medium enterprises), which resulted in 57 papers. Filtering was done in the third stage, through the inclusion and exclusion criteria.
As inclusion criteria were only accepted papers in English or Portuguese (where there was no papers in Portuguese), and published in journals. Qualitative articles that did not focus activities and primary emphasis was not open innovation, in addition to repeated articles, were not included. A limitation of this study refers to the access to some journals that were not provided by CAPES (Commission for Improvement of Higher Education Personnel). In this step, we first read abstracts. If we could not identify the criteria defined by the abstract, we analyzed introduction and methodology. At the end, there were 11 papers.
During the fourth stage, extraction and encoding of the data, it was realized that one paper did not distinguish firms by size. Thus, we analyzed 10 articles. Data were grouped into a spreadsheet with the following fields: reference, research question, number of small and medium companies analyzed, data source, sample type, response rate, criteria for defining the company as small and medium, sector (technology, software, manufacturing, etc.), country, data analysis method, other applied constructs (performance, marketing, etc.), corporate performance indicators, assumptions, open innovation construct reference, amount of measurement items for open innovation, applied scale and observations. The activities were tabulated in fields according to the activities presented by Gassmann and Enkel (2004), Morgan (2011) and van de Vrande et al. (2009). At this stage some problems arose. The main thing is the lack of definition of a more accepted construct; some articles pointed activities not listed by the authors mentioned above, which forced the change of the sheet during encoding. Other authors presented factors and not the activities individually, besides the studies using secondary data from other quantitative papers. There are also cases that did not present the descriptive statistics of the activities (mean and standard deviation), or even those who did not have the scale used. Such problems have impacted the analysis of the data.
Therefore, for the data analysis was impossible to employ statistical methods, which requires the use of comparative qualitative considerations between the studies.
Finally, the next section presents a discussion about the collected data.
At the end, a total of 5.553 companies were analyzed. The majority of studies used data from companies located in European countries like Netherlands, Belgium, UK, Hungary and Sweden. There are data of companies from South Korea and Taiwan. Some studies did not show the sector of the companies, but there were companies in the manufacturing sector, services, electronics, information technology and wine producers. Regarding to the criterion to define as small and medium enterprises, the authors divided it into companies of 10 to 250 employees, with fewer than 250 employees and less than 500 employees. Any study has addressed companies with over 500 employees. It should be noted the lack of studies in micro-enterprises and startups.
Some authors did not mention the sample type or database source of the companies, nor the response rate. However, those who presented the response rates showed large discrepancies, with response rates between 16% and 50%, which highlights the difficulty in carrying out quantitative research of survey type. Methods of analysis varied from descriptive statistics, multivariate analysis and structural equation modeling. The authors most often preferred to use their own construct.
As highlighted, before there was no standardization in constructs related to organizational modes of open innovation, which leads some authors to question about different activities in relation to other authors. However, some activities stand out over others. An important example is the engagement with consumers. Van de Vrande et al. (2009) found that such practice is common in 97% of studied Dutch companies, with 99% of companies stating that they tend to increase or stabilize in using this mode. Wynarczyk (2013) also found a very significant result in the UK, being such activity practiced in 57.5% of companies, while Parida et al. (2012) also found evidences of the high use of vertical technology collaboration (which would be the collaboration with current customers, potential and end users) in high-tech companies in Sweden. It should be noted that unlike Van de Vrande et al. (2009) who analyzed 605 companies and Parida et al. (2012) who analyzed 252 technology companies, Wynarczyk (2013) analyzed only 33 companies considered open innovative.
The authors also presented more detailed evidence, as Van de Vrande et al. (2009) who concluded that the involvement of consumers is informal and unstructured so as not to require substantial investments, while Wynarczyk (2013) provides additional evidence that the involvement of consumers occurs mainly in marketing and new products development. Such Van de Vrande et al. (2009) conclusion makes sense because small and medium businesses often lack capital for large investments in research and development activities. It should also be noted the fact that the involvement of consumers is apparently more important in the early stages of development, because the risk of opening the process decreases in opening it as soon as possible, once it gets to know the needs of users from the beginning, which is corroborated by the evidences presented by Wynarczyk (2013). Parida et al. (2012) also add other important information, that small and medium enterprises in the high tech industry can gain information from consumers and end users about the development of disruptive innovations. Van de Vrande et al. (2009) also suggest that companies start adopting open innovation by involving customers, followed by the involvement of employees and external networks and ending with more advanced practices that require formal budget. However, a barrier to consumer participation in small and medium enterprises are the cultural issues, as pointed out by Van de Vrande et al. (2009), despite the fact that for high-tech companies, the customers are often large companies (PARIDA et al., 2012) that can be current or future competitors and suppliers. An important warning about the study of Van de Vrande et al. (2009) is that they claim that a limitation of the study can be in the form that the statement about such activity was presented, which would encourage respondents to position themselves as practitioners of such organizational mode. It should be highlighted that the impact of the consumers involvement in performance has not been studied, but it is suggested that future studies analyze such situation, since meet the needs of them implies a great chance to positively impact the sales potential.
The involvement of employees was another organizational mode for open innovation that stood out and again in the Van de Vrande et al. (2009) research, who accused its use by 93% of companies. It is the only outbound open innovation activity that stood out in terms of high utilization, being that 99% of companies said they tend to maintain or enhance its use. Its low cost justifies its use. However, according to Van de Vrande et al. (2009), companies capitalize the knowledge and employees' initiatives who do not work in research and development, aiming an optimum use of the human capital and also as a result of an "internal organizational policy" or aiming to stimulate the commitment and motivation of the employees.
However, it was not found only coincidences about the organizational modes of open innovation. One discrepancy was found about the use of external networks. Though, before presenting the analysis it is important to clarify what means to use external networks. Van de Vrande et al. (2009) defined it as the process to be based or collaborate with partners to support innovation processes, for example, for external knowledge or human capital. It is felt that such definition allow to deduce that these partners can be competitors and non-competitors, excluding consumers, suppliers, universities, laboratories and research centers that have been analyzed in other issues. However, it is possible to consider joint ventures as a way to use external network. Van de Vrande et al. (2009) presented evidences on the use of this mode by 94% of the surveyed companies. Teirlinck and Spithoven (2013) used the term "cooperation in research" as synonymous for the use of external networks and adopted the definition of Chesbrough et al. (2006) that define cooperation in research both as formal collaborative projects and activities in informal network with people and organizations. It can be seen that the definition employed by Teirlinck and Spithoven (2013) is broader and may include consumers, suppliers, universities, laboratories and research centers. This situation occurred mainly due to the fact that Teirlinck and Spithoven (2013) use secondary data in their study, that is, the authors conducted an analysis on micro-level data of 140 companies provided by the survey of research and development in business from the Organization for Cooperation and Economic Development. The data presented by Teirlinck and Spithoven (2013) show that companies use less cooperation in research than outsourcing in research and development, being this mode used by less than half of the firms, while external networks were used by 94% of the companies studied by Van Vrande et al. (2009).
If expanded the scope of partners for cooperation in research and with the insertion of universities, the discrepancy between different papers remains. Wynarczyk (2013), for example, realized that universities were the preferred partners for 57.5% of the companies studied, while Csath (2012) when searching 814 small and medium-sized Hungarian companies noted that only 8.7% indicated some connection with universities and 9.2% with other partners. Csath (2012) states, however, that in Hungary open innovation is hampered primarily by a lack of trust and regulations that discourage cooperation and partnership in defense of "free competition", and the lack of trust results from weak social capital. Van Hemert et al. (2013) when studied 243 Dutch companies have found that they prefer to use international networks as organizational mode of open innovation to the detriment of cooperation with universities.
Other research cooperation modes continue highlighting the discrepancy between countries and studies. Wynarczyk (2013) presented evidences of low utilization of partnerships by small and medium-sized companies in the UK with laboratories (used by 30.3%) and joint ventures (used by 24.2%), in contrast to Van de Vrande et al. (2009).
A discrepancy found that differs not only for studies of Van de Vrande et al. (2009) but which also confronts what is taken for granted in the open innovation literature is the higher use of outbound open innovation modes than the inbound open innovation in the companies surveyed by Huang et al. (2013). Huang et al. (2013) analyzed 141 small and medium organizations in Taiwan, which may indicate cultural differences due to the region and/or the type of company, in the case, companies in the electronics and information sector. The regional issue and type of industry deserve further investigation because Török and Tóth (2013) when searching 119 wine producers in Hungary came to the conclusion that the presence of open innovation is still very limited. Perhaps the explanations proposed by Csath (2012) about the lack of confidence and regulations of the country suit to the case of Török and Tóth (2013). It should be noted that the study of Huang et al. (2013) used a convenience sampling, which can influence the results.
Still, an inbound open innovation mode that was very used was the Internet, as shown by Lee et al. (2010), and applied for 71% of the 2,414 small and medium Korean companies studied. Other studies did not analyze this activity in particular.
Among the unsuccessful organizational modes of open innovation there is no apparent disagreement. The use of intellectual property as an organizational mode is deprecated by the companies both as inbound as outbound activity, as pointed out by Van de Vrande et al. (2009). This situation is probably due to the cost to license a product or process, or to acquire such licenses. However, Lee et al. (2010) point out that buying technology appears to be more prevalent than strategic alliances between small and medium enterprises. Lee et al. (2010) add that while such types of companies prefer to collaborate with other firms for technology purchases (where there is no danger of technological reveal), they prefer universities and research centers than other firms for strategic alliances, although the number of alliances is quite low.
Finally, Lee et al. (2010) state that the commercialization after the invention is essential for innovation, being small and medium companies good at inventing, but lacking resources to trade, suggesting that a chance to boost open innovation in small and medium enterprises lies on the collaboration with other companies at the marketing stage. In large companies, the open innovation activities do not reach the marketing stage, but the study of van Hemert et al. (2013) supports the assumption that innovation in small and medium-sized enterprises can apparently benefit a lot from external support in the commercialization stage. Outbound open innovation activities such as the use of intellectual property, involvement of consumers and external networks can assist in this step.
It is evident that the researchers clearly include major companies in their studies because of the appeal of such studies present in terms of publication and visibility. So, the small and medium enterprise is relegated to the background in the studies of open innovation. However, this situation is changing and studies about open innovation in small and medium enterprises emerge as a dynamic and important field of study.
Although Van de Vrande et al. (2009) claim that small businesses are widely practicing open innovation and increasing its use, there are realities that contradict this assumption, as the Hungarian companies presented by Csath (2012), Török and Tóth (2013). This situation confirms the fact that open innovation is dependent on context. Thus, studies in specific regions such as eastern European countries, Asia, Africa, Latin America can contribute to the theoretical framework of open innovation. The same goes for specific sectors, as many studies focused small and medium enterprises, not differentiating the sector.
It is noticeable that small and medium-sized companies adopt open innovation motivated by objectives related to the market. These companies seek to open new markets and serve customers preferring, at first, to unstructured activities and that do not require large investments, such as involvement with customers and working informally with external networks.
However, Lee et al. (2010) state that small and medium-sized businesses generally specialize in one specific area and involvement in a network can be an effective way to successfully enter into broader markets and acquire additional resources, and to increase the essential skills to improve their chances to compete against its major competitors. The authors call attentions to the fact that for startups, the network model to invest jointly to share risk and profits can help small and medium-sized businesses to develop new business opportunities. It is important to highlight that two significant gaps for studies are presented: microenterprises and startups. Microenterprises are disregarded in several studies while startups are early stage companies that often lack capital for large investments, being that structured models for the adoption of open innovation in these types of businesses can bring important managerial contribution.
When it comes to managerial contribution, authors should focus on benefits from open innovation and not focus on the open innovation itself as the companies' objective. The company adopting open innovation expects some return and, therefore, future studies should focus on the impact of different activities on specific performance criteria.
In this perspective, explanatory approaches are suggested; it is, conducting quantitative studies to point out evidences of the impact of the open innovation use in the business performance, followed by qualitative studies which examine in detail how each activity impacts in different performance criteria, to offer solutions for managers and administrators.
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