Strategic Collaboration for Open Innovation with Global High-Tech Small and Medium Enterprises

Strategic Collaboration for Open Innovation with Global High-Tech Small and Medium

Enterprises

Successful global business thrives on competitive innovation and creativity, particularly

in the fast-paced high-tech sector; however, once businesses become successful, process

standardization may make them resistant to further innovation (Ding, 2021; Neely, n.d.; Rasler &

Thompson, 1994). To overcome resistance to change, open innovation collaborations with

global small and medium enterprises (SMEs) help businesses seek new ideas from outside the

boundaries of the organization and uphold a culture that accepts innovation (Yun et al., 2020).

High-tech SMEs are particularly wellsuited to open innovation due to their potential for greater

agility, allowing them to adapt to a rapidly advancing technological environment (Stentoft et al.,

2021). The introduction of new technologies in the development of products and business

processes drives productivity and competitiveness of enterprises across the economy.

SMEs that are able to implement open innovation strategies report greater operational

and innovation performance (Mazur & Zaborek, 2016); however, only a small fraction of SMEs

worldwide engage in open innovation (McPhillips, 2020; Messeni Petruzzelli et al., 2022).

Expanding open innovation practices to more SMEs around the world may help create sustained

sources of innovation and competitive advantage. Businesses able to accept innovation have

been observed to more readily develop new products, experience improvements in

performance, and adopt more sustainable business processes (Obradović et al., 2021).

Collaborative business ventures have also resulted in the creation of entirely new ecosystems

ripe for commercialization (Alkhazaleh et al., 2022). Strategic collaboration among high-tech

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SMEs around the world allows participants to jointly develop and commercialize innovations via

a process of co-creation of shared value (Chaurasia et al., 2020; Dubouloz et al., 2021). Since

SMEs make up 30– 40% of the world’s GDP (US SBA Office of Advocacy, 2022; The World Bank,

n.d.a), increasing the adoption of open innovation practices among high-tech SMEs has the

potential to increase productivity of a large portion of the world economy.

Background and Overview

Chesbrough (2003) identified and defined open innovation as the purposive creation of

value through accessing both internal and external ideas. This process looks for opportunities

outside of established production streams. Collaboration with external partners in particular

advances a company’s innovation and creates new markets for commercialization (Chesbrough,

2012, p. 21). Additionally, the close relationship developed by collaboration itself becomes an

asset that proves valuable, rare, and difficult to imitate and serves as a source of sustained

competitive advantage (Jones et al., 2018, p. 372). While open innovation results in improved

processes and new uses for formerly underutilized resources, it has been noted that the more

important asset was the close, long-term, collaborative relationships with the partners who

produced those

improvements (Khan et al., 2022, p. 9; Wang et al., 2015).

While the initial research by Chesbrough (2003) defining open innovation initially

focused on practices to augment the R&D (research and development) efforts of large high-tech

companies, such as Xerox and IBM, subsequent research has studied the impact of open

innovation in low-tech sectors and SMEs. As a result, Obradović et al. (2021) noted that only 2%

of the total surveyed articles on open innovation covered large companies, and only 8% of the

COLLABORATION FOR OPEN INNOVATION 3

articles covered medium- and low-tech companies. The present study focuses on the

intersection of the high-tech sector and SMEs, as these segments show

potential for greater use of open innovation.

Strategic collaboration provides a framework for improving the success of open

innovation. Strategic collaboration is the practice of co-creating value with stakeholders, but the

primary emphasis is placed on first building a relationship with stakeholders rather than

achieving an immediate outcome. Working with stakeholders in advance helps form a closer

relationship characterized by high levels of cooperation, knowledge sharing, and trust (Jones et

al., 2018). These three characteristics of strategic collaboration align with the three major

barriers to the adoption of open innovation expressed by high-tech SMEs: resistance to change,

lack of legal framework for knowledge sharing, and trust. Research from both perspectives of

stakeholder theory and open innovation theory agrees that the relationships formed between

stakeholders and collaborators result in a stronger, more unique, and more lasting competitive

advantage than the individual and incremental product and process improvements that result

from those collaborations (Gould, 2012; Lee et al., 2010; Mei et al., 2019; Popa et al., 2017).

Therefore, the initial focus on strategic collaboration was often observed to be critical to the

success of open innovation, but not vice versa.

Problem Statement and Significance of the Problem

The management problem examined in this dissertation is that among global hightech

SMEs, barriers to entering collaboration partnerships and risks related to the innovation process

can result in below-average business performance (Coraş & Tanţău, 2013). Sustained innovation

in global high-tech SMEs is restricted due to several factors, including risk aversion, resource

COLLABORATION FOR OPEN INNOVATION 4

costs, and lack of a legal framework (Alkhazaleh et al., 2022; McPhillips, 2020; Müller, 2019).

SMEs simply do not have access to the R&D resources and expertise of large and multinational

companies. This contributes to their risk aversion, as they must use more care with the limited

resources they have. Finally, external collaboration for open innovation may mean putting

sensitive intellectual property and customer data at risk, leading to potential legal liabilities. As

technology advances, SMEs unable to adapt also might fall victim to obsolescence threats and

fail to remain competitive (Popa et al., 2017). Global high-tech SMEs must overcome these

barriers to

innovate and succeed.

The specific management problem is that despite the effectiveness of open innovation

(collaboration with stakeholders outside the organization), there is low adoption of open

innovation among global high-tech SMEs (Chaurasia et al., 2020; Dubouloz et al., 2021;

Obradović et al., 2021). Existing systematic reviews on innovation practices by Chaurasia et al.

(2020), Dubouloz et al. (2021), and Obradović et al. (2021) have highlighted the open innovation

model as an effective framework to address the main issues in pursuing innovation reported by

SMEs: lack of resources, resistance to change,

and lack of legal framework.

Despite this evidence, open innovation by SMEs remains limited. Dubouloz et al. (2021)

and Obradović et al. (2021) cited resistance to change as a major impediment to open

innovation. For example, Dubouloz et al. (2021) reported that SMEs resist change due to the

“not invented here” syndrome, which is a cultural barrier based on secrecy and lack of shared

COLLABORATION FOR OPEN INNOVATION 5

values (p. 128). McPhillips (2020) and Müller (2019) cited examples of restrictions in knowledge

sharing due to concerns over intellectual property. Finally, Dubouloz et al. (2021), McPhillips

(2020), and Mubarak and Petraite (2020) all cited a lack of trust in their external partners as a

major barrier in implementing open innovation. Data from SMEs from Poland and southern Italy

concurred that only half of the surveyed companies participated in any kind of open innovation,

and only 10% considered their open innovation collaborations a success (McPhillips, 2020, p. 6;

Messeni Petruzzelli et al., 2022, p. 622). This represents a missed opportunity for improving

products or processes through open innovation.

Significance of the Problem

The problem is significant because without strategic partnerships, the efforts of global

high-tech SMEs are less likely to be commercialized without access to the resources made

available through open innovation (Orlova, 2020, p. 405). SMEs make up a substantial portion of

the global economy. In the US alone, 33.2 million SMEs make up

99.9% of US businesses, create jobs for 61.7 million employees (46.4%), and account for

32.6% of exports (US SBA Office of Advocacy, 2022). The World Bank (n.d.a.) estimated similar

figures worldwide, with global SMEs making up 90% of businesses, providing up to 50% of

employment, and accounting for up to 40% of GDP. SMEs are a key contributor to

the global economy.

High-tech SMEs in particular form an important sector of that world economy. In the

US, high-tech SMEs account for only 4% of the workforce but produce 11% of the US GDP

(Headd, 2021). Moretti and Thulin (2013) analyzed decades of census data in the US and

COLLABORATION FOR OPEN INNOVATION 6

Sweden and found that high-tech jobs have a multiplicative effect on the local economy. Their

statistical analysis found that each high-tech job corresponded to the creation of three to five

service and support jobs in the area (pp. 347, 355). The high-tech sector contributes a

disproportionate share to the GDP and has a ripple effect on the rest of the economy, making it

worthy of dedicated study.

Due to the comparatively smaller size of global SMEs compared to large and

multinational enterprises, SMEs have the capacity for greater organizational agility, allowing

them to quickly adapt to innovation and pivot for competitiveness (Stentoft et al., 2021).

Innovation is particularly important among the high-tech SME sector (Dubouloz et al., 2021;

Wang et al., 2015). The ability to use their agility to incorporate new technologies through open

innovation could help sustain the long-term survival and growth of global high-tech SMEs.

Evidence suggests that global high-tech SMEs are more susceptible to product and

process improvements through open innovation. Enjolras et al. (2019) found that international

high-tech companies had greater revenue growth driven by product innovation, whereas low-

tech companies were less affected by disruptive changes in the marketplace (p. 44). This means

high-tech firms must react more quickly to survive, especially to changes in their international

markets. Wang et al. (2015) confirmed that the knowledge gained through external

collaborations was critical to improving the effectiveness of internal innovation efforts, leading

to improved performance (p. 228). The knowledge gained through open innovation practices is

exceptionally important to global high-tech SMEs.

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Purpose of the Study and the Research Question

The purpose of this study was to investigate the role of strategic collaboration for open

innovation with global high-tech SMEs. The decomposition of the research question is

presented below.

This systematic review used the CIMO decomposition framework by Denyer and

Tranfield (2009). The CIMO framework (presented in Table 1) focused the research question

along four components: context, intervention, mechanism, and outcome. CIMO guided the

formation of the research question, search strings, and critical evaluation of search results for

relevancy. The CIMO framework was thus critical to establish early in the research process.

Table 1

CIMO Framework for the Systematic Review

Component

Definition specific to the research question

Context

Open innovation is important to global high-tech SMEs. While SMEs have

limited resources, they also have the organizational agility to better take

advantage of disruptive innovations (Stentoft et al., 2021, p. 812).

Intervention

Strategic collaboration (Alkhazaleh et al., 2022; McPhillips, 2020;

Obradović et al., 2021)

Mechanism

Close stakeholder relationship capability (Jones et al., 2018)

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Outcome

Open innovation with global high-tech SMEs leading to higher innovation and

productivity (Dubouloz et al., 2021; Messeni Petruzzelli et al., 2022;

Mubarak & Petraite, 2020; Obradović et al., 2021)

The CIMO framework delimited the scope of this study, which was synthesized to form

the research question: What is the role of strategic collaboration for open innovation with

global high-tech SMEs? The selections for the CIMO framework helped bound the scope of the

systematic review and were referred to across this dissertation.

Rationale for the Study or Significance of the Study

This systematic review contributed to the academic body of knowledge by applying

instrumental stakeholder theory (IST) to the problem of low adoption of open innovation by

global high-tech SMEs. Limited studies have applied stakeholder theory to open innovation.

Obradović et al. (2021), for example, did not list stakeholder theory among the common

theories encountered in their systematic review dataset. IST appears much less often than the

other theories mentioned by Obradović et al. (2021) in any type of scholarly research in the

Scopus database. Albats et al. (2020) applied stakeholder theory to a small number of SMEs in

11 case studies, and Chaurasia et al. (2020) noted the impact of stakeholder theory to low-tech

SMEs in the textile industry. Few other research studies have applied the IST component of

stakeholder theory to open innovation in SMEs. Jones et al. (2018), however, proposed that

future work with IST could help assess stakeholder relationships by measuring behaviors and

attitudes and lead to better explanations of variance in economic performance (p. 386). The

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literature highlighted a need to explore the explanatory power of IST on building strategic

collaboration relationships required for

successful open innovation.

Research gaps aside, the larger issue in practice is that the adoption of open innovation

by SMEs remains limited (Dubouloz et al., 2021; McPhillips, 2020; Mubarak & Petraite, 2020;

Müller, 2019; Obradović et al., 2021). The low adoption of open innovation by global high-tech

SMEs, as documented by McPhillips (2020) and Messeni Petruzzelli et al. (2022), presents an

opportunity to increase productivity in an important segment of the world economy. Better

understanding of the role of strategic collaboration in building a close relationship capability

with stakeholders has the potential to directly address the three main barriers to open

innovation: risk aversion, resource costs, and lack of a legal framework. The benefits of close

relationship capability described by IST are characterized by high levels of cooperation,

knowledge sharing, and trust. These align with the three main barriers to open innovation. Since

the application of IST could address these barriers to open innovation, this systematic review

contributed to management by applying the perspective of IST to form strategic collaborations

that help overcome potential barriers to successful open innovation in high-tech SMEs globally.

Definitions and Terminology

For the purposes of this research, the following definitions were used to provide context

and clarity for the scope of this systematic review.

Strategic Collaboration. The co-creation of value with stakeholders (Freeman et al.,

2018). Strategic collaboration is performed through close relationship capability with

stakeholders, which is characterized by high levels of cooperation, knowledge sharing, and

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trust (Jones et al., 2018).

Stakeholder. A party with an impact or interest in the company, which can include

primary or secondary stakeholders (Freeman et al., 2018).

Cooperation. Synchronization between stakeholders and a willingness to work

together (Jones et al., 2018).

Knowledge Sharing. A two-way interaction where assisting others to solve problems also

allows the knowledge sharer to acquire new knowledge or skills from feedback and interactive

discussions (Zhang et al., 2022).

Trust. The ability and willingness of a party to be vulnerable to the actions of another

party based on the expectation that the other will perform a particular action important to the

trustor (Mayer et al., 1995, p. 712). Trust can be established through multiple mechanisms via

swift trust or knowledge-based trust. Swift trust is formed via characteristic similarity, trust

intermediaries, or predisposition to trust. Knowledge-based

trust is built on experiences (Robert et al., 2009)

Open Innovation. The purposive creation of value through accessing both internal and

external ideas, extending to suppliers, customers, partners, third parties, and the

general community as a whole (Chesbrough, 2012).

SMEs. The thresholds for businesses that qualify as small and medium enterprises varies

by country, but SMEs generally have fewer than 250 employees and corresponding revenue

limits (European Commission, n.d.). The US uses larger thresholds than the rest of the world:

generally fewer than 500 employees but can be up to 1,500 for certain sectors

(US SBA, n.d.).

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Global Enterprise. A company that operates facilities across many countries around the

world (BDC, n.d.). SMEs included in this systematic review are not limited to any specific country

or region. Due to globalization, many of the SMEs under study export their products and

compete on the global market. Chen et al. (2014) found that collaboration with foreign partners

led to greater innovation than domestic partners, attributing the effect to increased diversity of

knowledge and skills compared to local and thus more similar partners.

High-Tech Sector. The OECD (Organization for Economic Cooperation and

Development) classifies high-tech industries as those with R&D spending above 5% of revenues.

Specific high-tech industries include aerospace, computers, electronics, and pharmaceuticals

(Hatzichronoglou, 1997, p. 6).

Chapter Summary

Chapter 1 introduced the challenge of driving adoption of open innovation within the

context of global SMEs. SMEs must integrate new technologies to maintain their

competitiveness on the global market. While assistance is available in the form of support for

open innovation practices, SMEs show some reluctance to accept this help due to risk aversion,

resource costs, and lack of a legal framework. The management problem to be addressed, the

research question for this study, and significance of the study based on evidence-based

management were presented. The concepts introduced set the stage for the scoping literature

review and theoretical framework offered in Chapter 2.

Organization of the Dissertation

This dissertation is organized following the CEBMa guidelines for systematic reviews, as

defined by Denyer and Tranfield (2009). Chapter 1 has provided an overview of the background

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and problem domain, purpose and rationale for the study, and definitions of key concepts and

terminology. Chapter 2 provides a scoping literature review of the state of understanding of

open innovation in the context of global high-tech SMEs and introduces the theoretical and

conceptual frameworks used to help explain the phenomena of interest. Chapter 3 covers the

systematic review methodology, detailing the qualitative steps used to search for available

evidence to answer the research question. It also details the search strategy and PRISMA

diagram for the search process for and quality appraisal of the results. Finally, the coding and

thematic synthesis of the research are discussed and interviews with subject matter experts are

proposed. Chapter 4 presents and discusses findings, critically evaluated using the CERQual

framework. Chapter 5 concludes with a discussion of the findings and implications for

management, along with recommendations for the effective practice of open innovation, future

research directions,

and disclosure of study limitations.

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Chapter 2: Scoping Literature Review and Theoretical Framework

Chapter 2 presents the theoretical and conceptual frameworks for this dissertation. The

chapter then provides a scoping literature review to clearly define concepts and

summarize the state of academic discourse on the research question.

The world is always in flux, with change being the only constant. This paradigm is even

more meaningful in the information technology (IT) industry, where technology that was current

only a few years ago may be obsolete almost as soon as it is introduced.

Innovation plays a key role in the long-term survival and growth of technology companies. An

initial interest in open innovation in IT firms focused on large companies, starting with research

from Chesbrough (2003), who introduced the concept of open innovation. By 2010, however,

research began to focus more on small and medium-sized enterprises (Lee et al., 2010).

Research suggested that sustained innovation can be accomplished through open innovation

and external collaboration (Yun et al., 2020). This collaboration takes place between a variety of

stakeholders, including other SMEs, large enterprises, government and academic technology-

transfer organizations, trade groups, and public interest groups. Each plays an important role in

the success of the process. Even though open innovation addresses the innovation gap for

global high-tech SMEs, adoption of open innovation remains limited (McPhillips, 2020, p. 6;

Messeni Petruzzelli et al., 2022, p. 622).

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Theoretical Framework

Initial Theory—Freeman (1984/2010)

This systematic review uses the instrumental stakeholder theory (IST) perspective.

Freeman (1984/2010) characterized stakeholder theory as a decision-making process that

includes consideration for critical stakeholders affected by an organization. Freeman made a

distinction between “stockholders” and “stakeholders,” proposing that organizations should not

only focus on the needs of the stockholders but also consider all the stakeholders impacted by

the organization. Stakeholder theory has evolved over the decades to gain more precise

definitions.

Adaptations of IST Over the Decades

Goodpaster (1991) was credited with introducing the concept of IST to reflect the

strategic nature of stakeholder management (p. 58). This concept specifies that not all

stakeholders need to be treated with equal priority, but their needs can be considered

appropriately based on their projected impact. Goodpaster (1991) specified that certain

stakeholders could be taken into account in the decision-making process as external

environmental forces that present potential sources of either goodwill or retaliation. Freeman et

al. (2018) accepted and incorporated IST into stakeholder theory as a practical strategic

management approach. The strategies increased the potential for cooperation and co-creation

of more value with stakeholders. This language of co-creation of value matches the language

used to describe the co-creation of value in open innovation collaboration partnerships

(Chaurasia et al., 2020; Dubouloz et al., 2021). Albats et al.

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(2020) also established an explanatory connection between stakeholder theory and open

innovation collaboration among SMEs and recommended further research from this

perspective.

IST Iteration Used for Dissertation—Jones et al. (2018)

Jones et al. (2018) further developed the definition of modern IST through a conceptual

framework based on the theory. The application of IST provided practical insights for making

collaborations work by focusing on building close relationships between stakeholders. Effective

relationships between stakeholders are characterized by high levels of trust, cooperation, and

knowledge sharing. The relationship between stakeholders itself becomes a valuable, rare, and

difficult-to-imitate capability that serves as a sustainable competitive advantage (p. 372). The

relationship between stakeholders plays a major and valuable role in a company’s success in a

competitive market. Thus, instrumental stakeholder theory, as proposed by Jones et al. (2018),

implies that the strategic collaboration between stakeholders is crucial. Since the present study

focused on the role of strategic collaboration for open innovation, IST—which emphasizes the

value of strategic collaboration in creating sustained sources of innovation from external

stakeholders—was a helpful lens for understanding the topic.

IST and Strategic Collaboration

Jones et al. (2018) thus addressed the main conditions—such as high levels of

cooperation, knowledge sharing, and trust—for a successful collaboration, as well as the

economic benefits of achieving it. Establishing these conditions comes with costs, according to

Freeman (1984/2010), due to the principle of contracting costs between stakeholders. One

focus of relationships established through IST was to minimize these time and labor costs, such

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as explicitly enforced NDAs (non-disclosure agreements) and SoWs (statements of work). Jones

(1995) had earlier described the benefits of forming mutually trusting and cooperative

economic relationships that are realized through reduced contracting costs (p. 442). These

competitive benefits can be achieved by firms

that establish trust with their stakeholders by not behaving opportunistically.

Jones et al. (2018) also made an important distinction between close relationships and

distant relationships among cooperating stakeholders. It may not always be appropriate to use

the close relationship style for every type of collaboration. Close relationships require more

investment to build but are critical for knowledge-intensive industries such as high-tech,

pharmaceuticals, and healthcare. In contrast, distant relationships are more appropriate for low-

tech business transactions that are more readily interchangeable between suppliers, such as

commodities (p. 381). Simply collaborating in every case was not sufficient: one should choose

which collaboration to

pursue strategically to make sure a company uses the right approach for each situation.

Applying instrumental stakeholder theory refocused the priority of high-tech SMEs on

building the close relationship capability with stakeholders compared to open innovation theory,

which prioritizes the outcomes of the collaborations. Jones et al. (2018) stressed that the three

main characteristics of close relationships—high levels of cooperation, knowledge sharing, and

trust—are built through strategic collaboration, providing examples of how these are formed:

Cooperation. Tasks shared between collaborators in knowledge-intensive environments

could have a high level of task and outcome interdependence (p. 381). This provides scheduling

challenges that require the collaborators to build coordination. Sharing communal resources

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also effectively reduces the costs of meeting these objectives. Therefore, the close relationship

capability allows collaborators to enjoy more efficient relational contracting (rather than

expensive formal written contracting) through cooperation (p. 382). The practice of cooperation

also saves costs on dispute resolution, allowing companies to avoid the expensive litigation

incurred by companies failing to relate transactionally. Cooperation through strategic

collaboration provides time and cost

savings and serves as a competitive advantage for firms pursuing open innovation.

Knowledge Sharing. Knowledge-intensive businesses such as high-tech depend on

knowledge creation and transfer as a means of generating value (p. 381). Collaborating firms

must be able to trust a stakeholder to not act opportunistically when provided access to

proprietary or potentially damaging data. The ability to provide knowledge sharing between

collaboration partners means they have legal frameworks in place to protect intellectual

property and provide secure data transparency (Müller, 2019). These frameworks may include

non-disclosure agreements and cross-licensing of patents, which allows for greater ease of

relevant knowledge sharing. Again, this lower overhead and reduced risk of litigation provide a

competitive advantage for firms pursuing open innovation.

Trust. Creating collaboration built on trust saves costs by making frequently

renegotiated, detailed, formal contracts with elaborate safeguards unnecessary (Jones et al.,

2018, p. 378). Yet what guarantees could be made to a risk-averse firm that a trusted

stakeholder would not act opportunistically and take advantage of exposure to vulnerability?

Robert et al. (2009) provided a comprehensive model of trust with explanatory power for the

observations made through open innovation practices. Robert et al. (2009) divided trust into

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two components: swift trust and knowledge-based trust. Swift trust had five main sources, but

two were of particular relevance to strategic collaboration for open innovation. The first was

category-based swift trust, meaning that people and firms were more likely to trust new

collaborators who were characteristically similar to them. The second source of swift trust was

based on third-party recommendation, meaning that trust was conferred by a trusted

intermediary (p. 245). Swift trust aside, the other source of trust was knowledge-based trust,

which was built through previous timeintensive experiences through interacting with a known

collaborator (p. 247). These models of trust between collaborators were useful in explaining the

sustained competitive advantage of collaborators who had built a close relationship capability,

thereby lowering

the costs of cooperation and knowledge sharing.

While stakeholder theory has been explicitly used to interpret open innovation

collaboration by a few studies—including Albats et al. (2020) and Chaurasia et al. (2020)— this

systematic review contributed to the management field by incorporating the strategic insights

provided by IST as defined by the theoretical framework provided by Jones et al. (2018). Viewing

the best available evidence through the IST lens helped form the conceptual framework for this

dissertation. The following section reviews the evidence provided by the scoping literature

review.

Scoping Literature Review

This literature review summarizes the state of available research on the topic of open

innovation by global high-tech SMEs and is presented in the following sections: global SMEs,

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open innovation, the high-tech sector, and an exploration of strategic collaboration between

stakeholders.

Global Small and Medium-Sized Enterprises

Early research on open innovation focused predominantly on large firms and

multinational companies (Dubouloz et al., 2021, p. 113; Sikandar & Abdul Kohar, 2022, p. 743).

SMEs are more likely to benefit from open innovation but paradoxically also tend to face greater

barriers and challenges adopting open innovation (Dubouloz et al., 2021; Messeni Petruzzelli et

al., 2022; Sikandar & Abdul Kohar, 2022). Some of these barriers include lack of resources, lack

of skills and knowledge, and lack of time (Dubouloz et al., 2021). However, SMEs also have

advantages due to their smaller size, such as potential for

greater organizational agility and opportunities for greater efficiency.

Cho et al. (2021) explored an important justification for focusing on the relative size of

SMEs. They looked at the data gathered from quantitative surveys from 223 Korean export firms

and found that larger firms were more likely to adopt innovative technologies. Cho et al. (2021)

noted that resource constraints were one of the primary hindrances to success of SMEs. Rocha

et al. (2019) also reported a connection with enterprise size in their findings. Via qualitative case

studies of four Brazilian tech startups participating in an international innovation center, the

authors identified “challenges and bottlenecks . . . to build collaboration networks to promote

tech innovation” (p. 1484). The studies from Korea and Brazil corroborated the difference in

innovation performance between large and small firms, indicating that SMEs around the world

were applying fewer innovations than their larger counterparts.

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The diminutive size of SMEs also introduces constraints. One of the major challenges

researchers have agreed on is the relative lack of resources of SMEs (Cho et al., 2021; Dubouloz

et al., 2021). Cho et al. (2021) reported that resource constraints formed a barrier to SMEs

adopting innovative technologies. Dubouloz et al. (2021) noted a similar challenge when looking

at the collaboration between large and small firms. Dubouloz et al. (2021) interviewed principals

of seven SMEs via a qualitative case study to determine barriers to implementing open

innovation in collaboration with large firms. The researchers identified four categories of

resource constraints that prevented SMEs from successfully pursuing open innovation

collaboration with large firms: finances, time, expertise, and

skills.

Sikandar and Abdul Kohar (2022) also noted the lack of financial resources as a

shortcoming of SME collaborations, but their research pointed out several other shortcomings

of SMEs compared to large multinational enterprises. Sikandar and Abdul

Kohar (2022) performed a qualitative systematic review of 40 articles on the topic of open

innovation with SMEs from 2010 through 2019 and documented deficiencies in knowledge,

collaboration issues with partners, lack of infrastructure, and labor shortages along with

organizational, managerial, and strategic barriers to open innovation (p. 751). The authors

concluded that “government can play an important role in the implementation of policies for

OI” to overcome these shortcomings (p. 752).

The literature also lists several reasons why overcoming these barriers could be

beneficial, particularly in “developing countries” (Sikandar & Abdul Kohar, 2022, p. 752) and

“transition economies” (McPhillips, 2020, p. 2). Thus, the research points to a number of

COLLABORATION FOR OPEN INNOVATION 21

barriers that hinder adoption of open innovation in small and medium enterprises, including

limited resources in finances, time, expertise, and skills, which create internal resistance to

allocating resources toward open innovation activities. Research on strategies to help overcome

these barriers could help drive open innovation and contribute to success for global SMEs.

The relative size and resource constraints of global SMEs can also provide advantages

over large multinational enterprises. Stentoft et al. (2021) proffered three reasons why focusing

on SMEs could benefit a nation’s economy: (1) there are a large number of SMEs, (2) SMEs can

operate with fewer resources, and (3) SMEs are usually less bureaucratic and thus have the

potential for greater organizational agility (p. 812). Stentoft et al. (2021) performed a

quantitative cross-sectional survey of 190 SMEs in Denmark and identified a gap between SMEs

and large enterprises in the development of innovative technologies. The gap was attributed to

organizational readiness, which was partly caused by reactive rather than proactive investments

in those technologies. The authors recommended addressing those deficiencies in SME use of

open innovation with conscious proactive strategic investments in digital technologies,

observing the need to “focus on the drivers . . . instead of the barriers” (p. 824). They suggested

that government agencies focus on ways to incentivize open innovation rather than focusing on

ways to

eliminate barriers to increase technology adoption of SMEs.

The available research highlighted how SMEs formed a critical part of the global

industrial base. The literature on open innovation pointed to the importance of collaboration

with global SMEs for the development of innovative technologies. While open innovation

originated with large multinational enterprises, SMEs now had a greater need for open

COLLABORATION FOR OPEN INNOVATION 22

innovation. Supporting SMEs could also impact other sectors, as they were often suppliers to

other industries (Chesbrough, 2012, p. 20; Freeman, 1984/2010). The small size of SMEs also

meant that they not only could benefit more from open innovation but also could potentially be

more efficient and agile at adjusting to rapid changes in the business environment.

Open Innovation Support for High-Tech Product and Process Innovation

Much of the literature on becoming receptive to innovative technologies has supported

the implementation of open innovation. The reviewed articles presented findings that

highlighted how open innovation contributed to productivity and performance compared to

closed business practices. Alkhazaleh et al. (2022), Chaurasia et al. (2020), and Dubouloz et al.

(2021), among others, established the link between SME engagement

in collaboration with the ability to adopt open innovation.

A Culture Receptive to Innovation. Alkhazaleh et al. (2022) studied open innovation

from the theoretical perspective of collaborative technology transfer. The technology transfer

perspective emphasized knowledge sharing and expertise from academic organizations to

industry. Using a qualitative systematic review of 40 research articles, Alkhazaleh et al. (2022)

noted that dynamic OI and an OI culture were among the most effective ways to commercialize

innovative technologies (p. 15). The authors found that when companies included interactions

that not only spanned communication within the company but also went outside its boundaries

(via dynamic OI) and when they also upheld a culture of accepting innovation (Mazur &

Zaborek, 2016; Yun et al., 2020), the company was more likely to adopt new technologies in

COLLABORATION FOR OPEN INNOVATION 23

their products and services. As a result, Alkhazaleh et al. (2022) documented two aspects of OI:

dynamic OI and OI culture.

This is important to the current study because a culture of accepting innovation (dynamic OI and

OI culture) reduces the resistance to change that SMEs experience.

Measurement of Open Innovation Adoption Through Inbound and Outbound Modes.

Other studies have echoed the importance of OI models in companies that are receptive to

innovative technologies. Obradović et al. (2021) detailed the evolution of the open innovation

concept across 11 years of research (p. 2). In the development of their conceptual framework,

they identified two modes of open innovation: inbound and outbound. Inbound OI activities

include the incorporation of new knowledge, ideas, and technologies from outside the firm.

Outbound OI is less commonly studied but can comprise commercializing ideas by licensing

intellectual property. Through a qualitative systematic review of 239 articles using automated

homogeneity analysis by means of alternating least squares (HOMALS), Obradović et al. (2021)

studied the impact of both forms of open innovation in the manufacturing sector. The results

indicated that businesses receptive to innovation could more readily develop new products,

experience improvements in performance, and more easily adapt to more sustainable business

processes (Obradović et al., 2021). The overall findings of their study supported the

effectiveness of adopting OI models for companies that switched their closed business

models and started to cooperate with other stakeholders.

Coupled Modes of Open Innovation. Other authors went a step further in defining

different modes of open innovation. Dubouloz et al. (2021) defined the open innovation

paradigm as the flow of valuable ideas through markets both within and across companies,

COLLABORATION FOR OPEN INNOVATION 24

identifying three distinct modes: (1) inbound OI, (2) outbound OI (both defined above), and (3)

coupled OI, which is the most collaborative of the three modes. The coupled mode of open

innovation involves co-creation of value and affects the strategic posture of the company.

Dubouloz et al. (2021) highlighted how deeper, more collaborative modes of open innovation

impacted innovative technology adoption, finding that the most collaborative approach

(coupled OI) led to the most effective commercialization of innovation. This connection between

greater collaboration and success of innovation shows the promise of strategic collaboration for

global high-tech SMEs.

Chaurasia et al. (2020) provided another study on coupled OI in the manufacturing

sector. The authors defined open innovation as the co-creation of shared value, and they found

that co-creation involved active participation, interaction, and collaboration among

manufacturers, retailers, and other stakeholders. Chaurasia et al. (2020) applied stakeholder

theory using a mixed-methods study combining a qualitative systematic review with a

quantitative cross-sectional survey. The systematic review used thematic analysis of 183 articles

to establish antecedents to open innovation for sustainability among 48 textile manufacturers

who served as suppliers to two major Indian retailers. While limited to a single research

database and sector in a single country, the mixedmethods study by Chaurasia et al. (2020)

established the value of openness as an antecedent to the creation of shared value via coupled

OI with low-tech SMEs. As one of few researchers to apply stakeholder theory to open

innovation, Chaurasia et al. (2020) highlighted a research gap for applying instrumental

stakeholder theory to open innovation with global high-tech SMEs.

COLLABORATION FOR OPEN INNOVATION 25

Increased Impact of the High-Tech Sector

Chaurasia et al. (2020) applied stakeholder theory to show how open innovation led to

process innovation in low-tech textile manufacturers. Their evidence, however, has pointed to

the increased impact of open innovation on both product and process innovation in high-tech

industries. Quantitative and qualitative studies by Fındık and Beyhan (2015) and Enjolras et al.

(2019) compared firms of different sizes and technology sectors and found that high-tech

companies developed greater process improvements and were more likely to develop radical

new product innovations using open innovation. Many studies focused exclusively on the high-

tech sector due to their higher growth

potential from open innovation compared to the low-tech sector.

The findings of these articles indicated the value of adopting open innovation to help

global high-tech SMEs accept innovative technologies, innovations that may otherwise remain

out of reach due to resource constraints. The next section explores the collaboration among the

various forms of stakeholders available.

Strategic Collaboration Between Stakeholders

Another key to open innovation acceptance is the establishment of a more collaborative

environment (Alkhazaleh et al., 2022). The research presented in the sections above suggested

that collaboration makes major contributions to the ability of firms to generate innovation.

Collaboration between any two enterprises is not in itself sufficient to achieve success.

Alkhazaleh et al. (2022) also noted that culture “affects the success of technology transfer”

through the “norms, traditions, and social conventions” (p. 10). Without a culture accepting of

COLLABORATION FOR OPEN INNOVATION 26

collaboration, technology transfer between stakeholders may not occur. Risk aversion due to

“employee uncertainty about the unknown as well as

the unfamiliar” overrode the acceptance of technological changes (p. 10).

The research identified multiple types of stakeholders and indicated that the most

critical collaborators can come from outside the industry (Alkhazaleh et al., 2022;

Dubouloz et al., 2021; McPhillips, 2020; Messeni Petruzzelli et al., 2022; Obradović et al.,

2021; Sikandar & Abdul Kohar, 2022). McPhillips (2020) identified stakeholders and categorized

them into academia, government, industry, and society. The following preliminary findings have

presented the importance of collaboration between multiple stakeholders, the categories and

types of stakeholders involved in collaboration, and the critical importance of a type of

collaborator called an innovation intermediary, which facilitated the success of open innovation

for SMEs.

Multiple Stakeholders. SME collaborations often involve more than two stakeholders.

Alkhazaleh et al. (2022) reported that to be effective, the technology transfer environment is

complex and multidisciplinary, requiring the diverse skills and expertise of various stakeholders.

Collaboration partners included the recipients of innovative technology transfer, technology

agents, and inventors who came from academic, government, and other industry partnerships

and consortiums. These collaboration stakeholders and partners were also identified as coming

from not only customers and suppliers (Sikandar & Abdul Kohar, 2022, p. 750) but also

government agencies, research institutions, consulting firms, nonprofit institutions, and even

startups (Rocha et al., 2019,

p. 1475). The importance of collaborations was so significant that special terms for these

COLLABORATION FOR OPEN INNOVATION 27

diverse groups of stakeholders had appeared in the scholarly literature.

Quadruple Helix Model. One such term highlighting the expanded importance of

multiple external stakeholders was the quadruple helix model. Obradović et al. (2021) and

McPhillips (2020) referred to the quadruple helix as a collaboration model between the industry

and government, academia, and society. However, these collaborations did not emerge

naturally. McPhillips (2020) studied clusters of collaborations in the quadruple helix model from

the perspective of the paradox of openness. The paradox acknowledged that innovation

required openness, but the ensuing commercialization of those innovations required

acceptance of vulnerability or some form of legal protection.

McPhillips (2020) conducted a quantitative cross-sectional survey of the coordinators of 31

innovation clusters consisting of startups and other SMEs collaborating with government and

research institutions in regions across Poland. The results of the surveys and two follow-up case

studies emphasized the need for the deliberate cultivation of mutual trust, compatibility, close

cooperation, and common principles among

stakeholders with diverse interests (p. 10).

McPhillips (2020) reported that creating an ecosystem where companies could

coinnovate required abandoning traditional management models in favor of joint management

frameworks, mediated by specialized legal counsel. McPhillips (2020) found that member

companies—particularly SMEs—reported being unable to take full advantage of open

innovation due to limited knowledge about open methods and tools, as well as a lack of

documented open innovation best practices they could use to take full advantage of

collaborations (p. 9). The McPhillips (2020) study illustrated the importance of collaboration

COLLABORATION FOR OPEN INNOVATION 28

among various stakeholders, yet success depended on the ability to build trust, form compatible

bonds, and implement knowledge and intellectual property management. The resistance that

companies encountered illustrated different forms of difficulties for companies attempting to

collaborate to achieve open innovation.

Categorizing and overcoming this resistance was crucial to enabling open innovation

adoption.

To determine how open innovation better served the various stakeholders described by

the quadruple helix model, Müller (2019) interviewed 102 German and

Austrian engineering managers on the benefits of open innovation collaboration.

Congruent with the findings of McPhillips (2020), Müller (2019) reported several findings on

collaboration, including the need for knowledge management systems and the challenge of

finding appropriate collaboration partners. Several findings for the engineering companies

under study matched those of McPhillips (2020) as well as Chaurasia et al.

(2020), who reported knowledge management systems as an antecedent for co-creation (p.

2506). Müller’s study also matched findings from Sikandar and Abdul Kohar (2022), who

reported challenges with lack of knowledge of open innovation collaboration and issues with

compatibility with collaboration partners (p. 751). These findings collectively reported similar

antecedents to knowledge management for open innovation and also highlighted the challenge

of identifying appropriate collaboration partners across a range of cultural, geographic, and

industrial sector contexts. The results reinforced how stakeholders came from multiple

backgrounds and the need for both knowledge-sharing systems and mediating relationships

with collaborators from various groups.

COLLABORATION FOR OPEN INNOVATION 29

Innovation Intermediaries. Several researchers have noted the critical importance of a

particular class of stakeholder, referred to as innovation intermediaries. These include entities

such as academic and government technology transfer organizations, consultants, and industry

consortiums. Alkhazaleh et al. (2022) defined intermediaries as a source of technology from

innovation centers and laboratories, noting that the role of universities has shifted toward the

commercialization of inventions (p. 15). Dubouloz et al. (2021) described intermediaries as

entities performing four distinct roles in overcoming cultural barriers, acting as brokers,

mediators, connectors, and collectors (p. 130). Rocha et al. (2019) did not explicitly mention

intermediaries but repeatedly called for entities that could raise market awareness so that

companies could see the value of digital solutions (p. 1483). McPhillips (2020) considered

innovation intermediaries a potential central element of industry due to their ability to combine

new solutions, ideas, and talent to enable innovation within other organizations, “offering far

greater societal value than the value which they present to companies” (p. 10). The researchers

in this section provided multiple examples of critical roles performed by innovation

intermediaries. The recommendation of Uluh (2021) and TEDx Talks (2015) suggested initiating

open innovation by finding these innovation intermediaries. Engaging with these intermediaries

facilitated the adoption of open innovation by providing knowledge, skills, expertise, marketing,

and even matchmaking to find the capabilities that many SMEs lack resources to build. Both

Rocha et al. (2019) and McPhillips (2020) noted that innovation intermediaries had a limitation

in that they did not provide financing for open innovation activities. Other researchers and open

innovation practitioners included banks, venture capital firms, and angel investors as innovation

COLLABORATION FOR OPEN INNOVATION 30

intermediaries that also provided financing along with scouting and matchmaking expertise

(TEDx Talks, 2015).

IST Conceptual Framework

Given the time and resource costs of strategic collaboration for open innovation, the

effectiveness of strategic collaboration needed to be analyzed systematically.

Evidence-based management provides a powerful tool to analyze the world. Formal theory

“provides the base for knowledge and understanding of important relationships in various

disciplines” (Smith & Hitt, 2005, p. 1) and is the result of a deliberate process of investigation,

validated and improved using scientific methods based on data collection and analysis.

Bhattacherjee (2012, p. 28) elaborated that “good theory” had the following

properties:

● logical consistency between constructs, propositions, boundary conditions,

and assumptions;

● explanatory power to measure how well the theory explained and predicted

observed reality;

● falsifiability to allow the theory to be tested and potentially refuted by newer

evidence; and

● parsimony in that the theory simplified understanding by using the fewest

variables, exceptions, and edge cases.

This systematic review applied the instrumental component of stakeholder theory using

the detailed conceptual framework adapted from Jones et al. (2018)—depicted in Figure 1—

which is unique among research applying stakeholder theory because it includes a resource cost

COLLABORATION FOR OPEN INNOVATION 31

component to building and maintaining close relationships with other stakeholders. Therefore,

the model may better appeal to cost-conscious SME managers who need to see a more tangible

return on investment.

Figure 1

IST Conceptual Framework

Note. Adapted from Jones et al. (2018).

Jones et al. (2018) addressed the barriers to change, knowledge sharing, and trust that

prevented companies from investing in building close cooperative relationships. Resistance to

change fell into three categories: (1) not being aware of collaboration benefits, (2) not having

the motivation to pursue collaboration strategies, and (3) not being able to successfully

implement a collaboration strategy (Chen, 1996, p. 382). The conceptual framework for this

dissertation described how to address these management barriers by getting corporations—and

particularly SMEs—out of the individualistic, closed innovation competitive mindset by building

cooperation, knowledge sharing, and trust with stakeholders. The framework begins with the

concept of strategic collaboration on the left. This influences the trust in the close relationship

COLLABORATION FOR OPEN INNOVATION 32

capability, which in turn affects levels of cooperation and knowledge sharing. These concepts

work to increase the perceived value of the partnership as well as create more efficient cost

structures. When the value of the strategic collaboration is higher than the resource costs

needed to maintain the relationship, the adoption of open innovation is achieved, potentially

leading to a measurable improvement in product or process.

Chapter Summary

This chapter presented a scoping literature review, underscored by IST to support the

use of a systematic review to answer the dissertation’s research question. The next chapter,

Chapter 3, presents the methodology adopted for this dissertation.

COLLABORATION FOR OPEN INNOVATION 33

Chapter 3: Method

This chapter discusses the methodology used to answer the research question. The

qualitative systematic review methodology is divided into a sequence of steps to systematically

search and review available evidence for quality and relevance. The process of analyzing the

evidence through coding and thematic synthesis is then described. Consultations with subject

matter experts are also included to help interpret the process and findings discussed in Chapter

4. This chapter justifies the level of rigor, applicability, and validity of the methodology used to

fulfill the research purpose.

Review Design and Methodology

The review design and methodology for this dissertation followed evidence-based

management described in this chapter. Evidence-based research, as part of evidencebased

management, ensured that research was conducted via a transparent, repeatable process, in

keeping with the principles of the scientific method. The purpose was to minimize potential

sources for bias and provide a window for investigating the truth through rigorous application of

deductive and inductive reasoning. Systematic review, as a type of qualitative study, was used as

the evidence-based methodology for this dissertation.

The Evidence-Based Research Framework

According to Barends et al. (2014), “Evidence-based practice is about making decisions

through the conscientious, explicit and judicious use of the best available evidence from

multiple sources” (p. 4). Researchers engaging in evidence-based practice incorporate studies

from multiple sources, including qualitative and quantitative data across a variety of contexts in

COLLABORATION FOR OPEN INNOVATION 34

order to reach thoughtful conclusions about the underlying mechanisms. Through this analysis,

relationships between concepts can be established,

providing useful explanations and predictions for interactions between concepts.

Scientific evidence-based management provided the methodological framework used for

this study. Evidence-based practice uses scientific methods, which Saunders et al. (2023)

categorized into five major philosophies: positivism, critical realism, interpretivism,

postmodernism, and pragmatism (p. 145). Of these philosophies, critical realism was chosen for

this study since it provided an appropriate approach to answering the research question.

Applicability and Use of Critical Realism

This study adapted a critical realism philosophy, which asserts that reality exists but can

only be known through experiencing it through the senses while maintaining objectivity. Critical

realism enabled the researcher to condense evidence from multiple data types—both

qualitative and quantitative—to provide a practical approximation of the truth. This approach

allowed for probabilistic outcomes that would be ruled out by a positivist reductive philosophy

while being less subjective than interpretivist, postmodernist, and pragmatist philosophies,

which relied more on inductive reasoning. The philosophy of critical realism struck a middle

ground between strict deductive reasoning via randomized controlled trials and more inductive

cross-sectional and case studies.

Saunders et al. (2023) characterized the philosophy of critical realism by its use of

retroductive reasoning, which Summers (2005, p. 9) described as an approach that integrated

the three types of reasoning—deductive, inductive, and abductive—to retroactively create a

hypothesis based on observed evidence that could be tested and applied to future situations.

COLLABORATION FOR OPEN INNOVATION 35

The purpose of critical realism is grounded in utility, with a theory supporting the parsimony

factor of Bhattacherjee’s (2012) elements of good theory and leading to a simplified

understanding of a phenomenon by using the fewest variables,

exceptions, and edge cases (p. 28).

This study explored strategic collaborations between groups and individuals, where

social interactions are often complex and nonlinear. Pawson et al. (2004) described complex

social interactions as a set of interventions based on theories that rely on human actions and

understanding motivations. These interventions consist of nonlinear steps with negotiation and

feedback shaped by social systems that can be modified, that evolve through learning, and that

vary in outcomes (p. iv). Due to the complex nature of such interactions, a retroductive

approach of critical realism philosophy was a more appropriate tool for research and data

analysis for this study.

Ontology, Epistemology, and Axiology of Critical Realism

Critical realism is one of several types of philosophy for interpreting the world. Each

philosophy has distinct ontologies, epistemologies, axiologies, and preferred methods of

investigation. Saunders et al. (2023) described features of critical realism in terms of ontology

(the nature of reality), epistemology (what constitutes acceptable values), and axiology (the role

of values) as well as the typical methodology corresponding to each (p.

146). According to Saunders et al. (2023), the ontology for critical realism is the measurement

and interaction of components that are “stratified/layered (the empirical, the actual and the

real),” the epistemology is characterized by relativist, historically transient, and socially

COLLABORATION FOR OPEN INNOVATION 36

constructed truths, and the axiology is described by value-laden research, shaped by differing

worldviews and cultures, entrusting the researcher to try to maintain objectivity to minimize

sources of bias and errors. When critical realism is used, it can be investigated through

retroductive methods, using a range of qualitative and

quantitative methods and data types.

Critical realism was appropriate for this study because the underlying truths behind the

mechanisms of strategic collaboration cannot be directly measured or even fully known. The

ontology allowed the truth to be approximated through empirical measurements on the

observable layer that indicate what is going on in the invisible actual and real layers. This allows

a theory about the underlying mechanism to be confirmed or

refuted.

In this study on strategic collaboration, the truths investigated were socially constructed

concepts such as trust, cooperation, and knowledge sharing. A researcher unable to directly

gather absolute measurements for these concepts must collect data indirectly on trust,

cooperation, and knowledge sharing. These indirect measurements would be relative between

different pairs of entities and also vary temporally between the same pair of entities. This study

on global SMEs fit into the axiology of socially constructed truths, which were widely influenced

by different worldviews and cultures. The emphasis on different values challenged the

researcher to maintain objectivity in their own context in order to minimize sources of bias and

errors.

COLLABORATION FOR OPEN INNOVATION 37

Realist Synthesis

Pawson et al. (2004) described realist synthesis review as a way “of adding rigour and

structure to what has been called the ‘old fashioned narrative review’ . . . about the

mechanisms of programme success or failure and about the apparently conflicting results of

‘similar’ studies” (p. 1). What is the nature of truth, and how can we know what is true to the

extent that the truth can be known? “Realist synthesis is an approach to reviewing research

evidence on complex social interventions, which provides an explanatory analysis of how and

why they work (or don’t work) in particular contexts or settings” (Pawson et al., 2004, p. iv).

Realist synthesis focuses on the extraction of knowledge from historical data in order to

determine the truth from the ever-changing environment. Context plays a key role in realist

synthesis because it defines by whom, where, when, and

under what circumstances the outcomes of interventions are determined.

Pawson et al. (2004) saw intervention in realist synthesis as a product of its context

across four nested contextual layers: the individual, interpersonal relations, institution, and

infrastructure (p. 8). The individual will have the greatest impact on how a theory works but will

at the same time be influenced by all of the other layers surrounding them from interpersonal

relations to the encompassing institution and infrastructure. When contextualizing how an

intervention works, one should consider differences across all four layers. In the context of

strategic collaboration, realist synthesis from an outside-in approach included consideration of

government-provided infrastructure made available for open innovation, followed by

institutions that take advantage of it, followed by the interpersonal relationships between

collaborating individuals. This became especially important for collaborations across country

COLLABORATION FOR OPEN INNOVATION 38

borders, where cultural and historical contexts came into play. The number of possible

combinations between collaborating SMEs from different countries grows geometrically and

even exponentially when studying collaborations with more than two partners. For the purposes

of this study, contextualizing across all four layers was especially important in exploring the

dynamics of open innovation globally, given that collaboration across cultural contexts can vary

greatly. Realist synthesis provided a method of examining these historically situated research

findings related to intricate social interventions, allowing for a framework for examining

interactions across a global environment of collaborative relationships.

Systematic Reviews

The systematic review originated as a surveying method to consolidate all related

evidence pertaining to a particular research question of interest. Systematic review

methodology has been adapted for use in evidence-based management to produce stronger

arguments backed by a solid foundation of multiple independent studies. Popay et al. (2006)

explained that the systematic review differed from the more traditional narrative review process

used for literature reviews. Traditional literature reviews are not conducted systematically or

transparently in their approach to synthesis (p. 5). In contrast to the traditional literature review,

Harden and Thomas (2005) described the systematic review as a method to reduce biases in the

review itself and the studies used as source data, thereby supporting an explicit goal of avoiding

drawing wrong or misleading conclusions to the research question. By deliberate and careful

evaluation of all evidence rather than just a subset of the evidence, a systematic review allows

the data studies collected to be conceptualized more as primary research than secondary

COLLABORATION FOR OPEN INNOVATION 39

research (p. 259). While the systematic review is defined as a qualitative method, it bears some

similarity to quantitative methods by using the articles in the dataset as individual data

points and analyzing across the body of data.

Gough et al. (2012) identified two main categories of systematic review: aggregative and

configurative (p. 3). Aggregative review is focused on confirming or measuring the impact of a

theory, while the configurative review is more exploratory in identifying the important

components of a theory. Realist synthesis is used for aggregative reviews to test instrumental

interventions (Gough et al., 2012, p. 3). This study fit the aggregative review paradigm, as it

followed the theories proposed by Jones et al. (2018) in their conceptual framework for how

instrumental stakeholder theory applied to the challenges of open innovation. Relying on an

aggregative review to quantify the preponderance of each of component of the research

question, this study synthesized the effect of strategic collaborations for open innovation with

global high-tech SMEs by assessing common themes in qualitative and quantitative data over

the past decade.

Systematic Review Process

Denyer and Tranfield (2009) provided an overarching systematic review methodology

used for evidence-based management research. Systematic review informs

the critical realist philosophy of the researcher by taking historically situated retroductive

reasoning to identify useful theories supported by the best available evidence. This study looked

at heterogeneous data on open innovation over the past decade and identified insights through

the lens of instrumental stakeholder theory that may explain the effects of strategic

COLLABORATION FOR OPEN INNOVATION 40

collaboration for open innovation with global high-tech SMEs. An important advantage to

conducting a systematic review over a narrative literature review was that a systematic review

was much more rigorous and transparent in its methodology. The level of rigor achieved by a

systematic review is due to the level of effort to mitigate researcher biases.

Denyer and Tranfield (2009) provided a five-step overview of the systematic review

process for evidence-based management: (1) question formulation, (2) locating studies, (3)

study selection and evaluation, (4) analysis and synthesis, and (5) reporting and using the

results. In each step, relevant articles were filtered and evaluated for applicability through the

CIMO framework and assessed for relevance to the research question. Careful attention to bias

and critical assessment for each step of the systematic review process helped ensure the validity

of the results.

Step 1—Question Formulation. The first step for initiating a successful systematic review

was to identify the right research question. The question formulation must be more detailed to

go beyond “what works” and probe into underlying causes and contextual settings. Detailed

research should not be started until a precise question is formulated. Denyer and Tranfield

(2009) proposed the CIMO framework (see Chapter 1) to assist in the precise definition of a

comprehensive, researchable, and answerable research question (p. 683). The involvement of

expert advisory groups was particularly important at this step to help identify specific focus

areas (p. 682). Tranfield et al. (2003) recommended performing a scoping literature review to

assist in defining all concepts in the research question (p. 215). The scoping literature review

would help situate the research question as one that replicated an existing study, further

developed a study, or addressed a

COLLABORATION FOR OPEN INNOVATION 41

research gap in the existing body of literature (p. 212).

The gap in available literature was established in Chapter 1 and resulted in the research

question: What is the role of strategic collaboration for open innovation with global high-tech

SMEs? Frequent consultations with dissertation faculty and subject matter experts, including

systematic review specialists and academic research librarians, were used to incrementally

refine the question into its current form. The research question was further developed using the

CIMO framework, which provided the four critical components of a well-built systematic review

(Denyer & Tranfield, 2009, p. 682). The question-formulation step aided by a scoping literature

review resulted in a comprehensive, specific, and researchable research question that guided

and directed the subsequent steps of the study.

Step 2—Locating Studies. The second step of conducting a systematic review was the

deliberate and exhaustive search for evidence from a variety of sources. The primary source for

data relevant to the research question came from searches of peer-reviewed journals published

in academic databases, which represented high levels of confidence in rigor, trustworthiness,

and validity. While Barends et al. (2017) suggested classifying article studies by level of

methodological appropriateness with randomized controlled trials representing the gold

standard for trustworthiness (p. 17), Pawson et al. (2004) allowed realist systematic reviews to

include a broad, heterogenous search for evidence that includes more exploratory qualitative

and quantitative methodologies (p. 21). Denyer and Tranfield (2009) also advocated for the

inclusion of other reliable sources of crossreferenced data such as gray literature, snowballed

references gathered from relevant citations, data repositories maintained by government and

trade groups, and consultation with subject matter experts (p. 684). Adhering to the guidelines

COLLABORATION FOR OPEN INNOVATION 42

above, three academic research databases and two professional publication databases were

searched for studies related to the management problem for this study. Systematic reviews

require complex search and inclusion criteria to integrate information from diverse sources to

incorporate more timely information and reduce publication bias (Wilson, 2009). This step is

discussed in more detail in the Search Strategy subsection of Chapter 3.

Step 3—Study Selection and Evaluation. The third step of the systematic review process

according to Denyer and Tranfield (2009) comprised the selection and evaluation of studies

through critical appraisal. Realist systematic review provided a broad view of phenomena from

multiple perspectives. The purpose of critical appraisal was to determine whether to include

each study in the dataset for further analysis. Petticrew and Roberts (2006) and Popay et al.

(2006) advocated for triangulation from multiple perspectives by including evidence from

different types of qualitative and quantitative studies. Harden and Thomas (2005) noted that

while the inclusion of different study methodologies may potentially reveal conflicting results

and weaken the conclusions drawn, this variety helped produce a more nuanced, reliable, and

valid answer to a research question (p. 268). For example, both quantitative and qualitative

studies were included in this systematic review, and confirmation bias was avoided to the best

of the researcher’s

ability.

Petticrew and Roberts (2006) noted that a single critical appraisal tool was not sufficient

to inform research questions about process or implementation (p. 190). Therefore, each article

in the search results underwent screening through multiple

appraisal tools.

COLLABORATION FOR OPEN INNOVATION 43

1. A descriptive summary of each article using the fields in Appendix A was collected to

provide critical methodology details needed by the next two

appraisal tools.

2. The summary provided data necessary to complete the Mixed-Methods Appraisal

Tool (MMAT) defined by Hong et al. (2018) in order to screen the articles in a

transparent manner for methodological appropriateness. The MMAT used two

screening questions and five methodology questions that

corresponded to the type of study. Appendix B provides the full table of MMAT

questions.

3. Finally, the TAPUPAS appraisal tool was used to assess each article for relevance to

the research question using Gough’s (2007) Weight of Evidence (WoE) framework.

See Table 3 for a detailed depiction of the TAPUPAS WoE

framework.

Step 4—Analysis and Synthesis. The fourth step of the systematic review process

according to Denyer and Tranfield (2009) was analysis and synthesis of the dataset. In a

systematic review, the objective of the literature analysis and synthesis is to ultimately create

new and useful information supported by the data. For Popay et al. (2006), synthesis involved

bringing together the findings from the included studies to draw conclusions based on the body

of evidence (p. 10). Data extracted from each study not only were subjected to critical appraisal

and summary tabulation but also underwent analysis via coding and thematic synthesis using

the coding process described by Saldaña (2013). Coding and thematic synthesis distilled the core

concepts, relationships, and themes provided by each study and established how they

COLLABORATION FOR OPEN INNOVATION 44

reinforced each other in the aggregate across articles of the dataset. This process is discussed in

more detail in the Analysis and Synthesis Methodology section of Chapter 3.

Step 5—Reporting and Using the Results. The final step of the systematic review

included both reporting and interpreting the findings. Chapter 4 covers reporting the findings,

the purpose of which is to discuss the aggregative findings supported by the dataset. Lewin et

al. (2018) recommended applying a CERQual evaluation of each finding to indicate the relative

confidence of each finding. The findings section includes the statement of what is known and

unknown based on the evidence, as well as any unexpected or counterintuitive results to adjust

the initial conceptual framework into a final conceptual framework. Step 5 also encompassed

the appropriate use of the results discussed in the implications for management section of

Chapter 5. The implications for management were bound by the limitations on the

generalizability of the study, which are discussed as part of Chapter 5 of this dissertation.

Search Strategy

With the research question for the systematic review established, the purposive search

for the best available evidence commenced. The search began with a selection of databases of

scholarly research to query and the search terms to explore. According to Petticrew and Roberts

(2006), the initial search is more inclusive and seeks not to exclude studies on the grounds of

study design alone (p. 186). A broad selection of search terms related to the research question

was initially used across various databases to cast a wide net for a variety of articles in different

fields. Due to the differences in terminology, a broad range of academic search terms was

utilized to find the common elements. After a range of highly relevant articles was identified, a

COLLABORATION FOR OPEN INNOVATION 45

targeted search string was created that reliably returned articles from formal queries of the

databases, along with several other similar articles in that search space.

Search Process and Terms. The search process resulted in an initial dataset of highly

relevant studies for further analysis. While the initial broad search should often return

thousands of results, as the search process was refined to an area of a researchable research

gap, the final number of studies to be included for detailed review should number in the tens

rather than the hundreds (Petticrew & Roberts, 2006, p. 187). The original set of search strings

was derived from the CIMO criteria used to develop the research question and filter articles for

relevance. This ensured the search was conducted in a systematic manner that was

“transparent, verifiable, and reproducible” (Barends et al., 2017, p. 12). These searches

provided several primary search terms as well as related theoretical models and contextual

terms from the CIMO. A sampling of highly relevant articles was scanned and lexically analyzed

for top word counts that revealed common terminology.

The search space was then condensed to find common synonyms and alternative terms.

The final search strings used on each database were recorded in Table 2.

Table 2

Database Search Strings

Database

Aggregator or

Database

Boolean Search Term Expression Results

COLLABORATION FOR OPEN INNOVATION 46

UMGC

OneSearch/

EBSCO

( “open innovation” (SMEs OR SME) (tech* OR

R&D) strateg* (stakeholder* OR partner* OR

collab*) )

TX (global* OR *national OR world* OR countr*

OR 49urope* OR asia* OR pacific OR OECD)

NOT ( low OR eco OR green OR environment* )

(26 unique)

ProQuest

ABI/Inform

noft(“open innovation” (SMEs OR SME) (tech* OR 19

R&D) strateg* (stakeholder* OR partner* OR collab*)

(global* OR international OR world* OR countr* OR

europe* OR asia* OR pacific OR

OECD))

Scopus

TITLE-ABS-KEY ( “open innovation” AND ( smes OR 20

sme ) AND ( tech* OR r&d ) AND strateg* AND (

stakeholder* OR partner* OR collab* ) AND NOT (

low OR eco OR environment* OR green ) ) AND (

global* OR *national OR world* OR countr*

OR europe* OR asia* OR pacific OR oecd )

AND PUBYEAR > 2013 AND PUBYEAR < 2022

ACM Digital

Library

[All: “open innovation”] AND [All: smes] AND 44

[[All: tech*] OR [All: r&d]] AND [All:

strateg*] AND [[All: stakeholder*] OR [All:

partner*] OR [All: collab*]] AND [[All: global*]

OR [All: *national] OR [All: world*] OR [All:

countr*] OR [All: europe*] OR [All: asia*] OR

[All: pacific] OR [All: oecd]]

AND NOT [[Abstract: low] OR [Abstract:

environment*] OR [Abstract: eco] OR [Abstract: green]]

IEEE Digital

Library

“open innovation” AND SMEs AND (tech OR R&D) 48

AND (strategic OR strategy) AND (stakeholder OR

partner OR relationship OR collaboration)

For the primary academic databases, this study used the UMGC OneSearch database

aggregator consisting of over 40 individual databases based on EBSCO records and the Scopus

database using Elsevier records. These databases allowed the search to cover a variety of

COLLABORATION FOR OPEN INNOVATION 47

scholarly academic journals. Additionally, a selection of databases from a list not included in

OneSearch was accessed for a more comprehensive search: ProQuest’s ABI/INFORM contained

business journals and dissertations, including those from the UMGC DBA program, providing

more detailed exploration of the research topic. Two professional databases covering

technology were also searched. The IEEE (Institute for Electrical and Electronics Engineers)

Computer Science Digital Library and the ACM (Association for Computing Machinery) Digital

Library were included to provide access to more technically focused engineering articles to

complement the academic journals. The search interface to those databases did not allow

wildcards, so the search strings were modified to spell out the variations of common search

terms.

Inclusion and Exclusion Criteria. Pawson et al. (2004) described the inclusion and

exclusion criteria of a realist systematic review as much broader than a traditional systematic

review (p. 20). The reasoning was that while setting a high bar for inclusion of only the most

rigorous experimental data was useful for simple interventions, the study of complex social

interventions required a more iterative approach to find the best set of relevant articles.

Instead, the purposive search for evidence evolved as evidence was accumulated and was

considered complete when data had reached theoretical saturation, during which little to no

new information was contributed by subsequent

investigation.

This systematic review primarily included qualitative, quantitative, and mixedmethods

studies conducted in the English language and published in peer-reviewed journals. This

COLLABORATION FOR OPEN INNOVATION 48

research applied realist synthesis to interpret the research question about the role of strategic

collaboration for open innovation with global high-tech SMEs over the last 10 years. The search

was limited by publication date to a one-decade range between 2013 through 2022, inclusive,

so only the latest relevant literature was included. Results from 2023 were omitted for

consistent repeatability of future search results. Articles returned by the search were

deduplicated and underwent abstract screening for relevance and then quality appraisal for

inclusion in the dataset.

Method of Quality Appraisal of the Included Studies

Multiple quality appraisal tools were used to assess the articles, as recommended by

Petticrew and Roberts (2006). Before the articles identified through the search could be

assessed, data from each article were extracted into a summary table (see Appendix A). The

summary table provided the major information needed by both quality appraisal tools, including

the article’s research purpose, methodology, sample size and population details, findings, and

limitations. Pawson et al. (2004) indicated that no “data extraction form” template exists with

standard questions for each article, meaning the summary table fields must be customized to

the task of collecting information relevant to the quality appraisal tools and any subsequent

analysis (p. 23). This extracted information was used to categorize and critically appraise each

article to determine trustworthiness and relevance.

The data from these summaries fed directly into the quality appraisal tools for MMAT and

TAPUPAS Weight of Evidence frameworks, allowing the results to be collected and

analyzed.

COLLABORATION FOR OPEN INNOVATION 49

In keeping with the application of realist synthesis, as described by Gough et al. (2012)

and Pawson et al. (2004), this systematic review incorporated evidence from a variety of

qualitative, quantitative, and mixed methods studies. The Mixed Methods Assessment Tool

(MMAT) by Hong et al. (2018) provided a flexible and reliable qualityappraisal tool that

supported consistent evaluation of several study types. The MMAT questionnaire (see Appendix

B) consisted of two screening questions followed by a set of five questions appropriate to the

type of study. The two screening questions asked whether the article included an identifiable

research question and whether the data collected answered the research question. Articles that

did not pass the screening questions did not provide evidence appropriate for consideration in a

systematic review and were removed from further analysis. The screening questions effectively

removed several pure concept articles without attached studies and “show and tell” articles in

which authors described a

design project but did not contribute to scientific inquiry.

Following the screening questions were method-specific sections for each type of study

with a different set of five questions specific to the particular methodology for (1) qualitative

studies, (2) quantitative randomized control trials, (3) quantitative crosssectional surveys, (4)

quantitative descriptive studies, and (5) quantitative mixed-method studies. These method-

specific questions made the MMAT appropriate for use in a systematic review that included a

blend of various research methodologies. The MMAT scoring of each article was calculated from

the sum of the answers to these five questions using a three-level Likert scale where “yes”

counted as two points, “can’t tell” counted as one point, and “no” counted as zero points. With

COLLABORATION FOR OPEN INNOVATION 50

a possible total scoring range from 0 to 10, articles that rated higher than 6 were appraised as

appropriately conducted studies and were retained in the dataset.

Studies that passed the MMAT appraisal were then subjected to the TAPUPAS Weight of

Evidence appraisal, which included seven dimensions with particular consideration for the fit

and relevance to this study’s research question. Each article was critically appraised for inclusion

using Gough’s (2007) Weight of Evidence framework, which organized appraisal across seven

dimensions using the TAPUPAS acrostic (p. 11).

Gough (2007) categorized the seven dimensions into three sections for:

1. generic quality of execution of the study;

2. review-specific fit regarding the appropriateness of the method; and

3. review-specific fit based on the focus and approach of the study to this study’s

research question.

These three characteristics roughly translated to an assessment of transparency, rigor, and

relevance, respectively. Rearranging the dimensions of TAPUPAS into a new acrostic—

ATSA PUP—allowed these dimensions to fit more naturally into Gough’s (2007) three

Weight of Evidence categories (see Table 3). The assessment of each dimension was performed

using a similar three-level Likert scale, with 1 point for each dimension, a half point for partial

credit, and a total passing score of 4.5 out of a maximum score of 7. Articles with acceptable

relevance on the TAPUPAS Weight of Evidence scale were assessed to be of sufficient quality

and relevance for inclusion in the dataset.

Table 3

COLLABORATION FOR OPEN INNOVATION 51

Weight of Evidence Scoring Hierarchy for Critical Appraisal

Dimension Meaning Weight of Evidence Weight of

Category Evidence

Accuracy

groundedness of the

research

Transparency

Specificity

Accessibility

clarity of purpose

method-specific quality

understandability

A—quality of execution

D—overall score

Purposivity

fit for purpose of study’s

methodology

B—fit to methodological

appropriateness

Utility

provided relevant

answers

C—fit to focus and

Propriety

conducted legally and

ethically

approach

The critical appraisal scores provided by MMAT and the TAPUPAS Weight of Evidence

tools helped inform the strength or weight of the evidence to support conclusions drawn from

each study, or whether to exclude the study entirely (Popay et al., 2006, p. 16). The

transparency, reliability, and repeatability of these quality appraisal steps were of paramount

importance to the rigor of this systematic review.

PRISMA Diagram

Moher et al. (2009) provided a template for the Preferred Reporting Items for

Systematic Review and Meta-Analysis (PRISMA) flow chart used to filter search results. The

PRISMA flow chart shown in Figure 2 succinctly depicts the number of articles identified from

COLLABORATION FOR OPEN INNOVATION 52

each database search, screened for relevance and eligibility with causes of dismissal, and

subsequently included in the systematic review.

Figure 2

PRISMA Flow Chart

Note. Adapted from “The Preferred Reporting Items for Systematic Reviews and MetaAnalyses:

The PRISMA Statement,” by D. Moher, A. Liberati, J. Tetzlaff, D. G. Altmann, and The PRISMA

of the Creative Commons Attribution License, which allows unrestricted use, distribution, and

reproduction in any medium, provided the original author and source are credited.

Articles published in 2023 were accessed but excluded to make the search more

repeatable in the future. A total of 13 articles were excluded due to falling outside of the

publication date range. After duplicates, abstracts, and articles unavailable for full-text access

were screened, a total of 80 full-text articles were assessed for eligibility. Of these, 28 were

excluded due to irrelevant topics or low-tech sectors such as travel, fashion, or services. An

additional 14 were excluded due to quality appraisal screening primarily for being conceptual

COLLABORATION FOR OPEN INNOVATION 53

papers without data from an attached study. This produced a total dataset of 39 articles with

sufficiently high-quality appraisal suitable for detailed analysis and synthesis.

Analysis and Synthesis Methodology

Once the dataset was identified, detailed analysis occurred through a process of coding

and thematic synthesis. The articles were coded in accordance with Saldaña’s (2013)

methodology for qualitative research. Coding was performed using Atlas.ti, a qualitative data

analysis computer software. Following the practice recommended by Barends et al. (2017), only

the findings sections from “the collation of the results and other information of the studies

included” were coded (p. 15). This focused the findings on the evidence and removed any

author bias introduced in the conventional literature review and introductory sections.

Method of Synthesis

The epistemological framework used by this systematic review was critical realism.

This view accepted observable data as a reflection of the real world but acknowledged that

observation could be mediated by the observer’s perceptions and beliefs (Gough et al., 2012).

Therefore, a goal of critical realism was to continually account for possible biases by letting the

text speak for itself and allowing the coding process to objectively extract

meaning from the text.

Coding Process. The findings were condensed by lumping and linking codes into

categories and themes in multiple cycles. Initial first-cycle codes were primarily drawn from the

CIMO terminology and instrumental stakeholder theory components. Terms and synonyms

related to the context of strategic collaboration and small and medium business in the global

high-tech sector were included in initial coding, along with statements related to the value and

COLLABORATION FOR OPEN INNOVATION 54

costs of establishing trust, cooperation, and knowledge sharing from instrumental stakeholder

theory. Other significant terms encountered repeatedly in the dataset were coded using

“exploratory coding” methods described by Saldaña (2013), which focused on using “in vivo

coding” of terms encountered directly in the source

material and “versus coding” of terms presented in opposition (p. 63).

The next coding cycle included identifying and forming emergent categories. The process

of identifying and grouping synonymous terms in subsequent passes was described by Saldaña

(2013) in order to simplify and merge common sentiments (p. 53). The collected individual in

vivo codes using Saldaña’s (2013) practice of “lumping” and “splitting” and Atlas.ti’s “merge

codes” and “split codes” features helped bring the number of unique codes from potentially

hundreds to just over 60 concepts. The merging of grammatical forms and synonyms further

reduced the codes of interest into categories related to each other across a more manageable

number of subthemes organized into five major thematic findings. Relationships between

themes, subthemes, and codes were diagrammed with networks, code groups, and codes using

Atlas.ti’s thematic synthesis process described in Friese et al. (2018). This provided traceability

back to the individual codes linked to the source documents identified in the systematic review.

Reporting of Synthesis Findings. Synthesis culminated in identifying the relationships

between concepts and themes supported by the data. Petticrew and Roberts (2006) described

three main phases of synthesis: (1) the logical organization in the included studies, (2) within-

study analysis of findings, and (3) cross-study synthesis (pp. 171–179). Organizing the results

into a description of the dataset facilitated the identification of trends and meta-analysis of the

studies. A table of themes across the studies supporting each theme was reported in the

COLLABORATION FOR OPEN INNOVATION 55

findings section. The combination of support for each theme allowed the findings to be

organized into common themes and

patterns.

After the findings from the thematic synthesis were reported, the confidence in each

thematic finding was rated using the CERQual approach created by Lewin et al. (2018). The

CERQual ratings add rigor to the systematic review by assessing the confidence in each finding

on four levels—high, moderate, low, or very low—according to whether “each review finding

should be seen as a reasonable representation of the phenomenon of interest” (p. 6). The

CERQual rating for each finding was based on an assessment of the four components defined in

Table 4. The rating used to evaluate the components were minor, moderate, or severe. A

deficiency in at least one component resulted in a rating of minor. Two deficiencies were given a

rating of moderate.

Components that had three or more deficiencies received a downgrade rating as severe. Lewin

et al. (2018) did not recommend assigning numerical values to the calculation of each

component, “as this may give a false sense of precision regarding these assessments” (p. 16).

Out of the three findings assessed in Table 11, one finding was rated high confidence, one

finding was rated moderate confidence, and one finding was rated low confidence. The finding

with low confidence was retained because it was still rated higher than the lowest available

rating level (very low).

Table 4

CERQual Assessment Components

Component

Definition

COLLABORATION FOR OPEN INNOVATION 56

Methodological

limitations

The extent to which there were concerns about the design or conduct of

the primary studies that contributed evidence to an individual review

finding

Coherence

An assessment of how clear and cogent (well supported or compelling)

the fit was between the data from the primary studies and a review

finding that synthesizes that data

Adequacy of data

An overall determination of the degree of richness and quantity of data

supporting a review finding

Relevance

The extent to which the body of evidence from the primary studies

supporting a review finding was applicable to the context (perspective or

population, phenomenon of interest, setting) specified in the review

question

Finally, the findings were used to update the initial conceptual framework proposed in

Figure 1 into a final revised conceptual framework with relationships supported by the evidence.

The revised conceptual framework represents a model of strategic collaboration for open

innovation among global high-tech SMEs supported by the articles included in the systematic

review.

Subject Matter Experts

In accordance with stakeholder theory, Barends et al. (2014) recommended collecting

evidence from practitioners and stakeholders to inform the research question in addition to the

empirical evidence provided by scientific literature. For this study, two subject matter experts in

the field of telecommunications were contacted to share their lived experiences on open

innovation. These experts were asked to provide feedback on the research question, findings,

and recommendations. Notes recorded during these

conversations were used to help validate the systematic review.

COLLABORATION FOR OPEN INNOVATION 57

Once the systematic review data were analyzed and the discussion section of the

dissertation completed, the same two experts were emailed and asked to provide feedback on

the review. The subject matter experts were provided with a presentation version of the

research question briefed at the Student Opportunities to Advance Research and Scholarship

(SOARS) forum along with preliminary versions of the findings from coding and synthesis from

Chapter 4 and recommendations to management for Chapter 5. The feedback solicited from the

experts provided practitioner validation of the research findings and external confirmation of

the applicability of the results.

Chapter Summary

Chapter 3 discussed the scientific method via a qualitative systematic review using the

evidence-based research framework. The realist synthesis method was described and linked to

the systematic review. The details of coding, aggregating, synthesizing, and developing findings

were provided. The next chapter presents the findings and analysis of the study data.

COLLABORATION FOR OPEN INNOVATION 58

Chapter 4: Analysis and Findings

This chapter outlines the findings compiled from the 39 articles on open innovation

within global high-tech SMEs. The discussion includes the thematic results based on the

analysis. The chapter begins with a review of the research question driving this inquiry, followed

by a description of the dataset and its quality appraisal scoring and CERQual rating. Finally, the

conceptual framework is depicted to explain the interrelated components for strategic

collaboration based on the qualitative findings.

Review of the Research Question

The research question explored in this systematic review was: What is the role of

strategic collaboration for open innovation with global high-tech SMEs? The best available

evidence was sought to address the research question using search criteria for literature across

five databases: EBSCO, ProQuest, Scopus, the IEEE (Institute for Electrical and Electronics

Engineers) Computer Science Digital Library and the ACM (Association for Computing

Machinery) Digital Library. The resultant 39 articles used in this research were filtered and

appraised to identify themes and findings, within the context of the research question,

discussed in this chapter.

Description of the Dataset

The systematic review resulted in 39 scholarly peer-reviewed articles. As recommended

by Pawson et al. (2004) and Denyer and Tranfield (2009), an aggregative systematic review

integrates a variety of study methodology types. As shown in Figure 3, the articles included

three mixed methods studies and 18 qualitative and quantitative studies each. The articles were

COLLABORATION FOR OPEN INNOVATION 59

published between 2013 and 2022 with roughly 80% of the articles published within the past 4

years. There were over 30 countries represented in the study.

Figure 3

Summary of Dataset

Table 5 summarizes the distribution of over 30 countries represented across studies in

the dataset. While 70% of the articles focused on strategic collaborations within a single

country, several studies went beyond country borders to participate in strategic collaborations

globally.

Table 5

COLLABORATION FOR OPEN INNOVATION 60

Summary of Countries Included by Review Articles

Code Country included in Articles in World Bank International Monetary

study dataset economy Fund economy

classification classification

vr various / unspecified 6

COLLABORATION FOR OPEN INNOVATION 61

IT Italy 8

KR Korea (the Republic of) 6

FI Finland 5

IN India 3

GB United Kingdom of Great 3

Britain and Northern

Ireland (the)

MX Mexico 3

NL Netherlands (the) 3

ES Spain 3

BE Belgium 2

BR Brazil 2

CH Switzerland 2

DE Germany 2

FR France 2

IE Ireland 2

LU Luxembourg 2

RU Russian Federation (the) 2

NO Norway 2

TH Thailand 2

High income

Advanced

High income

Advanced

High income

Advanced

Lower middle

income

Emerging and

Developing

High income

Advanced

Upper middle

income

Emerging and

Developing

High income

Advanced

High income

Advanced

High income

Advanced

Upper middle

income

Emerging and

Developing

High income

Advanced

High income

Advanced

High income

Advanced

High income

Advanced

High income

Advanced

Upper middle

income

Emerging and

Developing

High income

Advanced

Upper middle

income

Emerging and

Developing

Upper middle

income

Emerging and

Developing

High income

Advanced

High income

Advanced

COLLABORATION FOR OPEN INNOVATION 62

AR Argentina 1

AT Austria 1

AU Australia 1

Table 5 (continued)

Code Country included in Articles in World Bank International Monetary study dataset economy

Fund economy

classification classification

DK PL

SG US

Bosnia and Herzegovina

Canada China

Denmark Poland

Sweden

Singapore

United States of America

(the)

South Africa

Upper middle

income

Emerging and Developing

High income

Advanced

Upper middle

income

Emerging and Developing

High income

Advanced

High income

Emerging and Developing

High income

Advanced

High income

Advanced

High income

Advanced

Upper middle

income

Emerging and Developing

Note. Country codes are from IBAN (2023); the World Bank lending classification is from the

World Bank (n.d.b); the International Monetary Fund economy classification is from the

International Monetary Fund (2012).

Table 5 also identifies the World Bank and International Monetary Fund economy

classification for every country. The researchers from 6 of the 39 articles specifically indicated

their study represented “emerging or developing economies,” which was an impetus for open

COLLABORATION FOR OPEN INNOVATION 63

innovation. Most countries included across the research were classified as high-income,

advanced economies.

Results of the Quality Appraisal of the Dataset

After selection for inclusion into the dataset, each of the 39 articles was critically

appraised according to the MMAT by Hong et al. (2018) for methodological appropriateness and

the TAPUPAS Weight of Evidence criteria by Gough (2007) for relevance to the research

question. Table 6 summarizes the critical appraisal scoring.

Table 6

Dataset With Critical Appraisal Assessment

Citation Countries MMAT Type MMAT TAPU Google

Score PAS Scholar

Score Citations

Agostini et al. (2017) IT 3. Quantitative

nonrandomized

Albats et al. (2020) DK, FI, NO, NL 1b.

Qualitative case study

101

Alvarez-Aros et al. MX (2022)

3. Quantitative

nonrandomized

Benitez et al. (2022) BR

3. Quantitative

nonrandomized

Bigliardi & Galati IT (2016)

3. Quantitative

nonrandomized

216

D’Angelo & Baroncelli IT (2020a)

3. Quantitative

nonrandomized

D’Angelo & Baroncelli IT (2020b)

3. Quantitative

nonrandomized

de las Heras-Rosas & vr Herrera

(2021)

1a. Qualitative systematic

review

Dooley et al. (2022) IE

1b. Qualitative case study

6.5

COLLABORATION FOR OPEN INNOVATION 64

Edison et al. (2018) vr

1a. Qualitative systematic

review

6.5

Garbade (2014) NL, DE, CH,

AT, BE

5. Mixed methods

Gonyora et al. (2021) ZA

1b. Qualitative case study

6.5

Guertler & Sick (2021) vr

1b. Qualitative case study

Henttonen (2013) FI

1b. Qualitative case study

6.5

Table 6 (continued)

Citation Countries MMAT Type MMAT TAPU Google

Score PAS Scholar

Score Citations

Henttonen & FI

Lehtimäki (2017)

1b. Qualitative case

study

6.5

106

Hongsaprabhas et al. TH (2018)

1b. Qualitative case

study

Jang et al. (2017) KR

5. Mixed methods

Jeon & Degravel KR

(2019)

1b. Qualitative case

study

5.5

Jung & Andrew (2014) KR

3. Quantitative

nonrandomized

Katzy et al. (2013)

EU, vr

1b. Qualitative case

study

213

Kim & Kim (2018)

4. Quantitative

descriptive

6.5

Krishna & Jain (2022)

IN, vr

4. Quantitative

descriptive

6.5

Kumar & Jyotishi (2014)

1b. Qualitative case

study

Marangos & Warren

(2017)

1b. Qualitative case

study

6.5

Marullo et al. (2020)

3. Quantitative

nonrandomized

COLLABORATION FOR OPEN INNOVATION 65

Mejia-Trejo (2017)

3. Quantitative

nonrandomized

Noh & Lee (2015)

3. Quantitative

nonrandomized

Passarelli et al. (2021)

5. Mixed methods

Pilav-Velic & Jahic

(2022)

3. Quantitative

nonrandomized

Podmetina & Albats

(2021)

FI, FR, SE, BE, 1b. Qualitative case

LU, ES, NL, study NO, CH

Table 6 (continued)

Citation

Countries MMAT Type

MMAT TAPU Google

Score PAS Scholar

Score Citations

Pöntinen et al. (2022)

FR, DE, GB, LU 1b. Qualitative case study

Runeson & Olsson

(2020)

1b. Qualitative case study

6.5

Santoro et al. (2020)

1b. Qualitative case study

Sedita & Grandinetti

(2022)

3. Quantitative

nonrandomized

Son & Zo (2021)

3. Quantitative

nonrandomized

6.5

Srisathan et al. (2022) TH

3. Quantitative

nonrandomized

6.5

Trzeciak et al. (2022) US, BR, CA,

RU, CN, AU,

AR, IN, et al.

3. Quantitative

nonrandomized

Turki et al. (2017) SG, MX, RU,

FI, ES

1b. Qualitative case study

6.5

Wynarczyk (2013) GB

3. Quantitative

nonrandomized

181

COLLABORATION FOR OPEN INNOVATION 66

Note. Country codes are from IBAN (2023), with vr. representing various countries left

unspecified in the source article. MMAT scores are out of 10 maximum. TAPUPAS WoE scores

are out of 7 maximum.

The critical appraisal scoring validated that the 39 articles were sufficiently trustworthy

for secondary research purposes. All articles that passed the MMAT screening questions also

passed the MMAT score threshold of 6 out of 10 points. Eighty-seven percent of the articles

were appraised with a high MMAT score of 9 or above, and the remaining 13% were scored at 7

or above.

Based on the TAPUPAS WoE assessment for relevance, all 39 articles scored above the

minimum threshold of 4.5. Fifty-four percent of the articles yielded a full score of 7, and 44%

scored between 6 and 7. The remaining 2% consisted of an article that was appraised with a low

score of 5.5 due to transparency concerns but was still a full point above the cutoff threshold.

Ultimately, the findings of that study were in harmony with several other highly appraised

articles; therefore, no reason was found to further challenge its inclusion in this study.

The findings and conclusions identified in the articles that passed critical appraisal were

coded and analyzed using Saldaña’s (2013) thematic synthesis process to reveal novel

interpretations of the data, as discussed below.

Findings and Discussion

The findings presented in this section are based on three overarching themes prevalent

in the dataset. The major themes are associated with global high-tech SMEs’ use of strategic

collaborations to (1) overcome barriers to open innovation, (2) build relational capital, and (3)

innovate. Strategic collaboration determined the context for the stakeholder partnership and

COLLABORATION FOR OPEN INNOVATION 67

the open innovation outcomes achieved. The theme of overcoming barriers to open innovation,

building relational capital, and innovating was evidenced in 29 (74%), 33 (85%), and 21 (54%) of

the articles, respectively. Table 7 summarizes the number of thematic findings across all 39

articles.

Table 7

Article Support for Thematic Findings

Citation Overcome Build Relational Innovate

Barriers Capital

Agostini et al. (2017) X X X

Albats et al. (2020) X X

Alvarez-Aros et al. (2022) X

Benitez et al. (2022) X X X

Bigliardi & Galati (2016) X

D’Angelo & Baroncelli (2020a) X X D’Angelo & Baroncelli

(2020b) X X de las Heras(2021) -Rosas & Herrera

Dooley et al. (2022) X X

Edison et al. (2018) X X X

Garbade (2014) X X X

Gonyora et al. (2021) X X X

Guertler & Sick (2021) X X X

Henttonen (2013) X X X

Henttonen & Lehtimäki (2017) X X X

Hongsaprabhas et al. (2018)

Jang et al. (2017) X X X

Jeon & Degravel (2019) X X

Jung & Andrew (2014) X X

Katzy et al. (2013) X X X

Kim & Kim (2018) X X

Krishna & Jain (2022) X X

Kumar & Jyotishi (2014) X X

COLLABORATION FOR OPEN INNOVATION 68

Marangos & Warren (2017) X X

Marullo et al. (2020) X X X

Mejia-Trejo (2017) X X

Noh & Lee (2015) X X X

Passarelli et al. (2021) X X

Pilav-Velic & Jahic (2022) X

Podmetina & Albats (2021) X X

Pöntinen et al. (2022) X X

Runeson & Olsson (2020) X X

Santoro et al. (2020) X X X

Sedita & Grandinetti (2022) X X X

Son & Zo (2021) X Table 7 (continued)

Citation

Overcome Build Relational Innovate

Barriers Capital

Srisathan et al. (2022)

X X

Trzeciak et al. (2022)

Turki et al. (2017)

X X

Wynarczyk (2013)

Articles supporting theme: 29 33 21

Percentage of dataset: 74% 85% 54%

Thematic Finding 1: Overcome Barriers to Open Innovation

A major finding on the role of strategic collaboration for open innovation was that it

helped global high-tech SMEs overcome barriers. Twenty-nine (74%) of the articles in the

dataset provided evidence that strategic collaboration helps global high-tech SMEs overcome

barriers. The main barriers encountered were grouped into three categories of risk aversion,

resource costs, and compliance with laws governing intellectual property

and data privacy, as shown in Table 8.

The following discussion details the findings associated with the role of strategic

collaboration in overcoming barriers to open innovation and is organized into three

COLLABORATION FOR OPEN INNOVATION 69

subsections.

Table 8

Barriers to Open Innovation

Barriers

Articles Providing Support

Risks

41%: Albats et al. (2020), Alvarez-Aros et al. (2022), Garbade (2014),

Guertler & Sick (2021), Jeon & Degravel (2019), Jung & Andrew (2014),

Katzy et al. (2013), Kim & Kim (2018), Kumar & Jyotishi (2014), Marangos &

Warren (2017), Noh & Lee (2015), Pöntinen et al. (2022), Runeson &

Olsson (2020), Santoro et al. (2020), Son & Zo (2021), Turki et al. (2017)

Resource

Costs

46%: Agostini et al. (2017), Albats et al. (2020), Benitez et al. (2022),

Bigliardi & Galati (2016), D’Angelo & Baroncelli (2020a), Edison et al.

(2018), Gonyora et al. (2021), Henttonen (2013), Jang et al. (2017), Jung &

Andrew (2014), Krishna & Jain (2022), Marangos & Warren (2017), Marullo et

al. (2020), Noh & Lee (2015), Pöntinen et al. (2022), Runeson & Olsson

(2020), Sedita & Grandinetti (2022), Turki et al. (2017)

Legal

Compliance

21%: Dooley et al. (2022), Edison et al. (2018), Henttonen & Lehtimäki (2017),

Marangos & Warren (2017), Noh & Lee (2015), Pöntinen et al.

(2022), Santoro et al. (2020), Turki et al. (2017)

Risks. Among global high-tech SMEs, open innovation can be a risky endeavor that

requires significant resources with uncertain outcomes. Strategic collaboration allows

businesses to share the risks of open innovation. For example, strategic collaboration provided a

way for global businesses to jointly research shared technology solutions, which mitigated the

financial burdens of technology experimentation, or to outsource entirely to external

government and university research labs (Jung & Andrew, 2014; Kim & Kim, 2018; Noh & Lee

2015). Global high-tech SMEs shared risks by collaborating with each other through several

types of risk-sharing partnerships (Albats et al., 2020), including alliances (Garbade, 2014), local

COLLABORATION FOR OPEN INNOVATION 70

partners (Jeon & Degravel, 2019), innovation intermediaries (Katzy et al., 2013), and

collaborations with enterprise partners large and small (Marangos & Warren, 2017). Kumar and

Jyotishi (2014) found that newer and thus smaller global high-tech SMEs were likely to have a

higher appetite for risk-taking and uncertainty which facilitated their openness to engage in

open innovation compared to

more established companies.

Researchers described other types of risk that went beyond the financial burden of

investing in potentially unviable technology solutions. Sedita and Grandinetti (2022) described

technology leakage risk, which could erode a global high-tech SME’s competitive advantage.

Runeson and Olsson (2020) and Turki et al. (2017) described legal risks of leaked knowledge

sharing, which carry punitive financial impacts. Guertler and Sick (2021) described a different

type of risk in selecting unsuitable partners for collaboration (p. 112). However, according to

Alvarez-Aros et al. (2022) even “collaboration with rivals minimizes risks in project

development” by allowing “sharing of resources, improving times, costs and financial indicators”

(p. 12). Working together with their least trusted stakeholder—competitors—could still produce

benefits through strategic collaboration. Strategic collaboration was shown to reduce the risk

barrier by allowing

partners to share the risks.

Resource Costs. Even with the financial risks mitigated or even completely removed,

another barrier to global high-tech SMEs was the time and resource costs necessary to engage

in open innovation. These businesses still require investment of human resources to

commercialize products and services (Agostini et al., 2017). Strategic collaboration can increase

COLLABORATION FOR OPEN INNOVATION 71

available human resources by sharing allocation among stakeholders. For example, one of the

challenges noted was the significant personnel time investment needed to procure government

grants. Even with government financial assistance, Marangos and Warren (2017) discovered that

firms in many European Union countries chose not to take advantage of R&D grants because

they were “administratively time consuming” (p. 218). However, if this human investment could

be shared, the personnel challenge would be addressed. Similarly, the paperwork needed to

comply with regulations adds an increased burden on the human capital of global high-tech

SMEs. Sharing these burdens could further aid product development and company success.

Marangos and Warren (2017) indicated that the “cost of complying with the regulatory

authorities” was taken care of by transferring “the test phase to other organisations and

institutions through third party agreements, thus saving valuable time and resources that can be

invested in other projects” (p. 216). As a result, using strategic collaboration to overcome time

and human resource constraints had the side effect of freeing up resources to pursue other

productive endeavors and allowing companies to use their limited personnel more strategically

(Agostini et al., 2017). Similarly, Pöntinen et al. (2022) described instances where global high-

tech SMEs that failed to collaborate with customers to understand market and customer

demands ended up “spending a lot of resources” to develop products that did not achieve

commercial success (p. 11).

In addition to personnel investment, other assets such as labs, equipment, and capital

present a burden to global high-tech SMEs who have limited resources. Similar to the benefits in

sharing personnel through strategic collaboration, there were significant advantages in sharing

capital investments when engaging in open innovation through strategic collaborations. Noh

COLLABORATION FOR OPEN INNOVATION 72

and Lee (2015) found that outsourcing to R&D organizations was likely for “SMEs lacking

internal resources” (p. 20). Thus, as companies worked together, they were able to share the

burden of technology costs. Similarly, Benitez et al. (2022) found that collaborations with R&D

centers and supply chain networks reduced technology costs (p. 102). Henttonen (2013), Jang et

al. (2017), Jung and Andrew (2014), and Krishna and Jain (2022) also documented the benefits

of R&D collaboration and outsourcing to reduce costs, especially for resource-constrained SMEs.

Runeson and Olsson (2020) and Turki et al. (2017) described that the additional resource

investment required for knowledge sharing in strategic collaborations was offset by access to

larger markets and a larger collaboration base. Bigliardi and Galati (2016) used transaction cost

theory to account for how high-tech SMEs could acquire “strategic resources and knowledge”

through open innovation cheaper and faster than their competition (p. 880). Therefore, strategic

collaborators were able to benefit from their joint work by sharing

expensive labs and absorbing the costs of certifications.

Legal Compliance. Even with the elimination of the risk of uncertain outcomes and

reduced resource costs, a third major barrier consisting of legal compliance was discussed by

researchers. Strategic collaboration was found to assist global high-tech SMEs in legal

compliance with patent protections, nondisclosure agreements, contracts, and data privacy laws

that normally present a burden for the limited legal teams of these

SMEs. The consequences of errors in legal compliance could have far-reaching impacts on the

survival of a company; therefore, compliance requires meticulous study and vigilance, according

to examples presented by Bigliardi and Galati (2016), Dooley et al. (2022), Edison et al. (2018), and

Gonyora et al. (2021), among others.

COLLABORATION FOR OPEN INNOVATION 73

Bigliardi and Galati (2016) noted that even with the costs of open innovation completely

removed, to perform open innovation “without perceiving any kind of financial impediments,”

the firm could still see legal compliance as a barrier requiring “IP licensing, . . . formalized

contracts, and a structured innovation portfolio approach” (p. 880). Strategic collaboration was

found to reduce some of the burdens of legal compliance by replacing onerous contracts with

trust to work together in good faith. Garbade (2014) described how companies could reduce

legal liabilities through more speculative R&D contracts without guaranteed deliverables.

Garbade further found that these types of open innovation alliances had more participation

when protected by “risk-related agreements” rather than other contractual delivery

agreements, showing that certain legal frameworks were more effective at reducing legal

barriers to knowledge sharing. Through strategic collaboration, global high-tech SMEs were able

to engage with each other while protecting

themselves from potential lawsuits.

Other strategic collaborations among global high-tech SMEs helped reduce intellectual

property exposure. One strategy to avoid exposing intellectual property was to focus

collaboration on less sensitive parts of the global high-tech SMEs’ products. For example,

Henttonen (2013) presented a strategy SMEs have used to minimize their vulnerability to

intellectual property theft by collaborating on projects that “were not related to their core

technological competencies” (p. 8). As a result, companies were able to successfully share costs

and collaborate on open innovation, benefitting from the collaboration while still keeping their

core technologies under sole control and ownership. A related strategy shared by Henttonen

and Lehtimäki (2017) was for each company to work on a component of a complete system,

COLLABORATION FOR OPEN INNOVATION 74

contributing their domain expertise while at the same time incorporating technologies from

other companies through open innovation. The participants were therefore able “to protect the

technology from potential rivals” while also establishing a unique product with a “technology

base . . . protected from imitation and replication” (p. 341). A competitor would need to

replicate not only a product but also the relationships and supplier agreements to gain a

competitive edge with customers. This type of strategic collaboration provides relational capital

that bolsters a global high-tech

SME’s competitive capability.

Thematic Finding 2: Build Relational Capital Through Open Innovation

Strategic collaboration was found to help global high-tech SMEs build relational capital

with stakeholders through open innovation. Relational capital is defined as the relationships

between two stakeholders and can be either social capital (i.e., external) or human capital (i.e.,

internal). The creation of relational capital was studied directly by several researchers (Agostini

et al., 2017; Garbade, 2014; Jung & Andrew, 2014; Marullo et al., 2020; Santoro et al., 2020;

Srisathan et al., 2022). More broadly, 33 of 39 articles (85%) identified relational capital in the

form of alliances and partnerships (i.e., social capital) that provided access to markets and

networks. Thus, research suggests that the main benefit of open innovation is building relational

capital. This systematic review categorized relational capital as (1) social capital comprised of

external relationships and (2) human capital consisting of internal relationships with employees.

Social Capital. A major outcome of strategic collaborations for open innovation was

building social capital between global high-tech SMEs and their external stakeholders. Open

COLLABORATION FOR OPEN INNOVATION 75

innovation required an exchange of ideas from outside the organization; hence, it first involved

building a relationship with external stakeholders. According to social exchange theory,

stakeholders would be compelled to reciprocate goodwill, thus promoting knowledge sharing

that could lead to innovation. Santoro et al. (2020) and Srisathan et al. (2022) examined the

importance of social capital to global high-tech SMEs, which allowed them to leverage partner

networks to make up for resources that SMEs lacked due to the liabilities of smallness. Agostini

et al. (2017) investigated social capital and found support for strengthening the practice by

building “close and high-quality relationships outside the firm” (p. 1158). Similar to instrumental

stakeholder theory, such close relationships reinforced the basic tenets of instrumental strategic

collaboration described by Jones et al. (2018) involving high levels of trust, cooperation, and

knowledge sharing. Instrumental stakeholder theory provides a useful framework for

investigating social capital in detail. Trust, cooperation, and knowledge sharing were essential

components of the close relationship capability for successful open innovation, as shown

in Table 9.

Table 9

Building Relational Capital Through Open Innovation

Open

Innovation

Component

Articles Providing Support

Knowledge

sharing

54%: Agostini et al. (2017), Alvarez-Aros et al. (2022), Benitez et al. (2022),

D’Angelo & Baroncelli (2020a), D’Angelo & Baroncelli (2020b), de las Heras-

Rosas & Herrera (2021), Edison et al. (2018), Garbade (2014), Jang et al.

(2017), Jung & Andrew (2014), Krishna & Jain (2022), Marangos & Warren

(2017), Passarelli et al. (2021), Runeson & Olsson (2020), Santoro et al. (2020),

Sedita & Grandinetti (2022), Son & Zo (2021), Srisathan et al.

(2022), Trzeciak et al. (2022), Turki et al. (2017), Wynarczyk (2013)

COLLABORATION FOR OPEN INNOVATION 76

Cooperation

44%: Alvarez-Aros et al. (2022), D’Angelo & Baroncelli (2020b), de las

Heras-Rosas & Herrera (2021), Dooley et al. (2022), Edison et al. (2018),

Garbade (2014), Jang et al. (2017), Noh & Lee (2015), Podmetina & Albats

(2021), Pöntinen et al. (2022), Runeson & Olsson (2020), Santoro et al.

(2020), Sedita & Grandinetti (2022), Son & Zo (2021), Srisathan et al.

(2022), Trzeciak et al. (2022), Turki et al. (2017)

Trust

21%: Dooley et al. (2022), Garbade (2014), Jang et al. (2017), Noh & Lee

(2015), Passarelli et al. (2021), Pöntinen et al. (2022), Runeson & Olsson

(2020), Santoro et al. (2020)

Knowledge Sharing. Strategic collaboration was found to facilitate knowledge sharing

among global high-tech SMEs. Knowledge sharing was the most prevalent term related to open

innovation among global high-tech SMEs, with over 300 mentions across 21 (54%) articles. The

articles used various terminology to refer to knowledge sharing, including the flow of knowledge

(Agostini et al., 2017; Dooley et al., 2022), knowledge transfer (de las Heras-Rosas & Herrera,

2021; Trzeciak et al., 2022), knowledge resources exchange (Garbade, 2014), knowledge

appropriation (Marullo et al., 2020), and knowledge sourcing (Marullo et al., 2020; Pilav-Velic &

Jahic, 2022). Knowledge sharing was linked with the ability of global high-tech SMEs to extract

value from strategic collaborations through open innovation. Several articles acknowledged that

effective knowledge sharing needed an internal party to share with, whether through skilled

human resources (Agostini et al., 2017; Garbade, 2014) or via internal R&D teams (Son & Zo,

2021). Agostini et al. (2017) described ways to “leverage employee awareness of the value of

knowledge coming

from outside the firm” (p. 1158).

COLLABORATION FOR OPEN INNOVATION 77

Furthermore, studies distinguished between implicit or tacit knowledge sharing and

explicit knowledge sharing. Tacit or informal knowledge sharing could be described as

unintentional knowledge spillover (de las Heras-Rosas & Herrera, 2021, p. 16). Garbade

(2014) positively related “tacit knowledge exchange . . . to explicit knowledge exchange” (p. 65).

In contrast, formal, intentional, and explicit knowledge sharing was encouraged through open

data-collaboration efforts (Runeson & Olsson, 2020) and increased codification of knowledge

and tools (Passarelli et al., 2021, p. 747). Sedita and Grandinetti (2022) recognized the

“importance of absorbing knowledge from customers” (p. 1060). All these forms of knowledge

sharing benefited global high-tech SMEs in various ways, such as helping them make decisions

more aligned with the needs of customers in target markets and allowing “entrepreneurs to

acquire information and knowledge and link products and services to new markets” (Santoro et

al., 2020, p. 6). The findings of the studies emphasized “knowledge and information . . . a crucial

issue” to open innovation (Jeon & Degravel, 2019, p. 62). Without strategic collaboration, few

opportunities for knowledge sharing with external stakeholders were presented, leaving global

high-tech SMEs to their own suppositions.

Cooperation. Strategic collaboration fosters cooperation between global high-tech SMEs

by encouraging them to share costs, resources, and assets. Cooperation was the second most

referenced open innovation concept with over 280 mentions across 17 (44%) articles. The data

showed that cooperation provided a means for global high-tech SMEs to share costs, resources,

and assets (Edison et al., 2018; Srisathan et al., 2022), requiring compromise (Guertler & Sick,

2021) and reciprocity (Albats et al., 2020; Santoro et al., 2020). In order to be successful at

cooperation, studies found that the goals of the partners were aligned (D’Angelo & Baroncelli,

COLLABORATION FOR OPEN INNOVATION 78

2020a, 2020b; Garbade, 2014) and their skills and resources were complementary (Albats et al.,

2020; Guertler & Sick, 2021; Henttonen,

2013; Henttonen & Lehtimäki, 2017; Katzy et al., 2013; Kumar & Jyotishi, 2014; Marangos &

Warren, 2017; Noh & Lee, 2015; Podmetina & Albats, 2021; Pöntinen et al., 2022; Santoro et al.,

2020; Sedita & Grandinetti, 2022; Son & Zo, 2021). Complementary SME resources were found

to increase the interdependency of the partners, which in turn increased their communication

and knowledge sharing. Because SMEs were small, they were less likely to have all of the

resources they needed and thus more likely to need to cooperate with partners to obtain open

innovation resources. The enhanced cooperation led to higher levels of knowledge sharing with

global high-tech SMEs, thus increasing the opportunities

for innovation.

Trust. Strategic collaboration builds trust by enabling cooperation and knowledge

sharing among global high-tech SMEs. Trust was the third relational capital factor critical to the

success of strategic collaboration for open innovation with over 170 mentions across eight

articles. References to trust among the studies emphasized its importance in establishing an

open innovation relationship with global high-tech SMEs. Garbade (2014) highlighted the role of

trust in making “communication among alliance partners easier and leads to a higher level of

knowledge exchange” (p. 67). Jang et al. (2017) described “trust between firms . . . as an

internal factor for a sustainable relationship” (p. 22) and emphasized the need for “balance

between trust and contact” (p. 24). Pöntinen et al. (2022) attributed “trust issues” and “lack of

trust between partners” as key factors in the failure of open innovation collaborations. Related

to knowledge transfer, Runeson and Olsson (2020) reported that “trusting data sources, and

COLLABORATION FOR OPEN INNOVATION 79

trusting other organizations” to use shared knowledge properly is a major concern, noting that

“building trust in a network is hard” (p. 211). Entrepreneurs interviewed by Santoro et al. (2020)

stated that trust “is a vital component for engaging in OI,” and a relationship “strengthened by

trust and reciprocity” can mitigate other challenges from “collaborating with external partners

with different goals, structure and culture” (p. 6). In the context of SMEs, Dooley et al. (2022)

found cases where SMEs “relied heavily on interpersonal trust and reciprocity” as an alternative

to expensive “formalized contractual partner agreements” often used by larger companies (p.

16). Trust constitutes both an important antecedent to open innovation collaborations and a

byproduct of continued cooperation and knowledge sharing. Strategic collaboration requires

that global high-tech SMEs build and maintain trust through open innovation, which enables the

cooperation and knowledge sharing necessary

for innovation to occur.

Access Markets and Networks. With the relational capital in place characterized by high

levels of knowledge sharing, cooperation, and trust, strategic collaboration provides global high-

tech SMEs with access to markets and networks through partnerships. This type of relational

capital includes distribution agreements and sharing of technology patent portfolios. Access and

control of markets could be provided by overcoming regulatory overhead for international

export—as described by Podmetina and Albats (2021), Jeon and Degravel (2019), and

Wynarczyk (2013)—or overcoming national certification overhead—as discussed by Jang et al.

(2017) and Kim and Kim (2018). Access and control of networks also refers to participation in

newly created markets through trade associations or intermediaries as well as securing patent

protections and non-disclosure agreements with partners. Some examples of trade associations

COLLABORATION FOR OPEN INNOVATION 80

include the data marketplaces and broker platforms described by Runeson and Olsson (2020),

technology incubators described by Turki et al. (2017), and industry-driven innovation

intermediaries analyzed by Katzy et al. (2013). Many of these government and industry

organizations also controlled these networks through patent-protection systems and other risk

mitigations; however, strategic collaboration with other partners and government regulators

helped maintain access to trade networks.

Strategic collaboration was also found to indirectly build relational capital with

customers. Benitez et al. (2022) highlighted the creation of relational capital through sustained

product innovation, referred to as product “focalization,” which builds customer loyalty. The

development of relational capital with customers through product innovation

provides one example of how complex and intertwined the use of open innovation may be.

Relational capital provides value as a critical intangible outcome of open innovation.

Agostini et al. (2017) identified these “intangible assets” as “underinvestigated in the context of

SMEs,” meaning they may well be overlooked and undervalued with relation to their ability to

provide positive feedback into other parts of the open innovation mechanism. Mejia-Trejo

(2017) referred to intangible assets as including “data, information, talent, personnel” accessed

through the relational capital exchange with external partners (p. 408). The range of access and

control of shared resources through relational capital provides substantial value to a company

partnering in a strategic collaboration. As an intangible, however, the value of relational capital

is difficult to measure objectively.

Human Capital. While social capital described the relationships between global high-

tech SMEs and external stakeholders, strategic collaboration also encouraged the development

COLLABORATION FOR OPEN INNOVATION 81

of internal relationships by building human capital among employees and other internal

stakeholders. Of the 33 articles that discussed the importance of relational capital, 18 (46%) also

included the impact of internal human capital on global high-tech SMEs. Srisathan et al. (2022)

explained how human capital—in the context of global hightech SMEs—is distinct from ordinary

human resources in that the definition of the employee goes beyond the “tangible elements” of

education and training, also including

“intangible elements” such as the employees’ “job satisfaction and willingness to change”

(p. 7). Garbade (2014) also noted that intellectual property—such as “secret recipes”—is

“embedded in their human capital,” making employees a more critical part of relational trust

and governance than an ordinary human resource (p. 89). Strategic collaborations between

global high-tech SMEs eventually must be executed through interactions with

employees; therefore, the company’s internal human capital is critical to the partnership.

Researchers attributed improvements to human capital performance as an outcome of

open innovation through strategic collaboration. For example, studies by de las Heras-Rosas and

Herrera (2021) and Srisathan et al. (2022) concluded that the development of internal human

capital was one major byproduct of open innovation. Jung and Andrew (2014) discussed how

global high-tech SMEs could “gain experience, confidence, and commitment” to further

collaborate (p. 1189). Guertler and Sick (2021) noted that development of human capital

through “internal stakeholders proved to be critical” due to their increased expertise. Guertler

and Sick (2021) also credited strategic collaboration with changing organizational culture and

reducing resistance to change, otherwise known as “not invented here” syndrome (p. 108).

COLLABORATION FOR OPEN INNOVATION 82

Relational capital with other external and internal stakeholders was found to impact skills and

capabilities of all parties to the collaboration partnership.

Thematic Finding 3: Innovate Through Open Innovation

The final finding of this systematic review was that strategic collaboration could help

global high-tech SMEs use open innovation to innovate. However, with support from only 54%

of the articles, this finding was not as strongly supported as the previous three findings and

barely crossed the 50% threshold for a thematic finding. For global high-tech SMEs, 100% of the

39 articles in the dataset presented innovation as an outcome of open innovation. However,

only 21 articles documented clear product and process innovations as measured outcomes from

open innovation, while the remaining studies only produced indirect evidence of innovation

outcomes through measurement of financial or other overall performance metrics. This low

incidence indicated that innovation may not be the most prevalent outcome of open innovation

despite being a primary expectation. Table 10 summarizes the articles that documented product

and process innovation associated with open innovation.

Table 10

Product and Process Innovation

Finding

Articles Providing Support

Product Innovation

41%: Agostini et al. (2017), Benitez et al. (2022), D’Angelo &

Baroncelli (2020a), D’Angelo & Baroncelli (2020b), Dooley et al.

(2022), Garbade (2014), Gonyora et al. (2021), Henttonen (2013),

Henttonen & Lehtimäki (2017), Jang et al. (2017), Kumar &

Jyotishi (2014), Marullo et al. (2020), Noh & Lee (2015), Passarelli et

al. (2021), Pilav-Velic & Jahic (2022), Santoro et al. (2020)

COLLABORATION FOR OPEN INNOVATION 83

Process Innovation

44%: Agostini et al. (2017), Dooley et al. (2022), Edison et al.

(2018), Garbade (2014), Gonyora et al. (2021), Guertler & Sick

(2021), Henttonen & Lehtimäki (2017), Jang et al. (2017), Katzy et al.

(2013), Kumar & Jyotishi (2014), Marullo et al. (2020), Noh & Lee

(2015), Passarelli et al. (2021), Pilav-Velic & Jahic (2022),

Santoro et al. (2020), Sedita & Grandinetti (2022), Srisathan et al.

(2022)

Two distinct types of innovation were present in the dataset: product innovation and

process innovation. Product innovations were improvements to the final product sold to

customers, and process innovation focused on enhancements to the manufacturing line,

resulting in cost savings or productivity gains. These innovations provide value to the company’s

performance by increasing revenue or decreasing costs. As Gonyora et al. (2021) noted, global

high-tech manufacturing executives claimed that “since engaging in consistent innovation in

terms of new products, new processes, quick and positive response to market demand changes,

and customer preferences, we have seen our financial performance improving tremendously”

(p. 10). Increased innovation is expected to produce increased profits. The evidence from the

studies in the systematic review indicated that the innovation outcomes in either product

innovation or process innovation

depend on the strategic collaboration partner chosen.

Product Innovation. Product innovation involves improvements to tangible products

offered by global high-tech SMEs. Pilav-Velic and Jahic (2022) discussed the two styles of

product innovation as between “incrementally and radically improved products” (p. 781). While

global high-tech SMEs may prefer to market exciting radical disruptive innovations, modest

COLLABORATION FOR OPEN INNOVATION 84

incremental innovations also provide competitive value, especially when introduced

consistently. Benitez et al. (2022) found that any type of product

“technology innovation” provided market “differentiation” (p. 101), which Agostini et al. (2017)

said helps “outperform those of competitors” (p. 1158). While product improvements constitute

a one-time outcome of an open innovation collaboration, sustained competitive advantage

through product innovation relies on continued innovation driven by continued open innovation

cycles. The ability to demonstrate consistent and repeated product innovation “contribute to

make the firm be recognized as a technology leader customers are attached to” (p. 1158). While

companies may dream of being launched to the forefront with a radical disruptive innovation

produced from a oneshot strategic collaboration—which has happened on rare and highly

publicized occasions—a more consistent pace of incremental innovation produced through

steady and ongoing strategic collaboration partners can also build up reputation and a loyal

repeat customer base. The incremental product innovation approach may offer a more

competitive strategy over the long term.

Stakeholder Partnerships That Result in Product Innovation. Studies on hightech global

strategic collaborations with R&D institutions and customers found significantly more instances

of product innovation. According to Benitez et al. (2022), “Involvement of both R&D centers and

customers have a direct effect on differentiation through innovation and loyalty” (p. 101).

Strategic collaboration with R&D stakeholders was successful at helping global high-tech SMEs

rise above their competition in the marketplace with more innovative products. Furthermore,

working with customers helped them design products that better met evolving customer needs

and had the side effect of increasing brand loyalty. Moreover, Benitez et al. (2022) documented

COLLABORATION FOR OPEN INNOVATION 85

cost savings from placing less emphasis on product features that were not as important to

customers. This highlighted how strategic collaboration enhanced the outcome of open

innovation partnerships. Similarly, Noh and Lee (2015) found high product innovation from

“ideacreation activities, including the involvement of users and customers” (p. 24), and Sedita

and Grandinetti (2022) found that customer collaborations “appear to be more relevant than

collaborations with suppliers” (p. 1063). These findings show that strategic collaborations with

customers and users led to higher product innovation than other stakeholder groups. These

studies indicated that effective product innovation was most likely to come from garnering

knowledge from customers about their needs and requirements.

Process Innovation. Process innovation refers to novel improvements in the

manufacturing and delivery of products and services. This concept was predominantly referred

to as “process innovation” (Dooley et al., 2022; Jang et al., 2017; Kumar & Jyotishi,

2014; Pilav-Velic & Jahic, 2022) but was also coded as “new processes” (Agostini et al.,

2017; Gonyora et al., 2021; Noh & Lee, 2015; Passarelli et al., 2021), “new services” (Gonyora et

al., 2021; Marullo et al., 2020; Santoro et al., 2020), and “business model innovation” (Srisathan

et al., 2022). Studies on process innovation identified its role as an important driver of

operational efficiency (Dooley et al., 2022, p. 22). Process innovation was more invisible to

customers but was nevertheless a valuable outcome of open

innovation for improving global high-tech SMEs’ competitiveness.

Stakeholder Partnerships That Result in Process Innovation. The research found that

collaborations with R&D institutions and suppliers were significantly more likely to

COLLABORATION FOR OPEN INNOVATION 86

lead to process innovations (Agostini et al., 2017).

Different studies focused on how suppliers increased process innovation from varying

angles. Garbade (2014) looked at strategic collaboration with global high-tech SME suppliers.

Their research provided evidence supporting the effectiveness of alliances with high-tech SME

suppliers for process improvement, meaning that collaboration with suppliers produced process

innovations. Dooley et al. (2022) and Jang et al. (2017), on the other hand, studied both large

and small companies and found that collaborations with suppliers produced process innovations

in both. However, large companies were able to gain measurably more process innovation than

SMEs, indicating that SMEs have greater difficulties capturing value from open innovation. Turki

et al. (2017) focused on strategic collaboration from the public procurement angle. They

observed that public institutions engaged global high-tech SME “suppliers to propose process or

organisational innovation” for public procurement agencies (p. 186). The study noted that global

high-tech SMEs were so successful at process innovation that EU governments were looking for

opportunities to partner with SMEs to improve process innovation in procurement. Thus, public

agencies were interested in SMEs taking a bigger role in the public procurement process. These

studies indicated that process innovation was most likely to come from collaborations with

supplier stakeholders.

Subject Matter Expert Consultation

Consulting with subject matter experts who are practitioners of open innovation in the

industry helps mitigate the sole researcher bias. The consultations with subject matter experts

assisted with the coding and thematic synthesis phases of this systematic review. Accessing their

expertise assisted the researcher in discerning more subtle patterns in the data and reduced the

COLLABORATION FOR OPEN INNOVATION 87

effects of sole observer bias. The resulting findings were discussed with the subject matter

experts, and their feedback is included in Chapter 5.

Summary of Findings and CERQual Ratings

The amount of high-quality research articles producing evidence lends strength to the

findings of this systematic review. The confidence in each major thematic finding was assessed

using CERQual ratings of the findings presented in Table 11 using the guidance of Lewin et al.

(2018). This tool provides a “systematic and transparent framework for assessing confidence in

individual review findings,” adding rigor to systematic reviews by decomposing evidence and

findings into “consideration of four components: (1) methodological limitations, (2) coherence,

(3) adequacy of data, and (4) relevance” (p. 1). Confidence in each finding was reported as

“high, moderate, low, or very low confidence”

based on the average level of concern across the four components (p. 5).

The assessment of the evidence for each finding was rated on a confidence scale

consisting of high, moderate, low, or very low based on a composite judgment of level of

concern against four CERQual components defined by Lewin et al. (2018): methodological

limitations, coherence, adequacy of data, and relevance (p. 15). All findings were supported by

at least half of the articles in the dataset. All findings shared minor concerns in methodological

limitations due to the lack of randomized controlled trial (RCT) studies in the selected dataset.

Finding 2 on relational capital was rated with high confidence, while Finding 1 on barriers was

rated with moderate confidence due to moderate concerns about the adequacy of the data and

coherence of the article findings. Finding 3 on the ability for global high-tech SMEs to innovate

was rated as low confidence due to multiple moderate concerns with adequacy and coherence.

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For a collection of studies on how open innovation helps global high-tech SMEs innovate, only

about half of the articles discussed product and process innovation, and several presented

conflicting evidence on which stakeholders produced significant results. The CERQual ratings

indicated that open innovation was a complex topic that was highly dependent on context, and

the application of strategic collaboration was not yet fully understood enough to provide

reliable, predictable outcomes.

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Table 11

CERQual Evaluation of Major Thematic Findings

Objective: To aggregate evidence on the role of strategic collaboration for open innovation with global high-tech SMEs

Perspective: Stakeholders of open innovation partnerships

Summary of Studies Contributing to the Review Finding CERQual Explanation of CERQual

Review Finding Assessment Assessment

1: Strategic 74% Moderate • Minor methodological collaboration Agostini et al. (2017), Albats et al. (2020),

Alvarez-Aros et al. confidence limitations due to lack helps global (2022), Benitez et al. (2022), Bigliardi & Galati (2016),

D’Angelo & of RCT studies high-tech SMEs Baroncelli (2020a), D’Angelo & Baroncelli (2020b), Edison et al. • Minor

coherence overcome (2018), Garbade (2014), Gonyora et al. (2021), Guertler & Sick concerns barriers to open (2021),

Henttonen (2013), Henttonen & Lehtimäki (2017), Jang et • Moderate adequacy innovation. al. (2017), Jeon &

Degravel (2019), Jung & Andrew (2014), Katzy concerns et al. (2013), Kim & Kim (2018), Krishna & Jain (2022), Marangos •

Minor relevance

& Warren (2017), Marullo et al. (2020), Mejia-Trejo (2017), Noh & concerns

Lee (2015), Podmetina & Albats (2021), Pöntinen et al. (2022),

Runeson & Olsson (2020), Santoro et al. (2020), Sedita &

Grandinetti (2022), Turki et al. (2017)

COLLABORATION FOR OPEN INNOVATION

94 Table 11 (continued)

Summary of

Review Finding

Studies Contributing to the Review Finding

CERQual

Assessment

Explanation of CERQual

Assessment

2: Strategic

collaboration

helps global high-

tech SMEs build

relational capital.

85%

Agostini et al. (2017), Albats et al. (2020), Benitez et al. (2022), de

las Heras-Rosas & Herrera (2021), Dooley et al. (2022), Edison et al.

(2018), Garbade (2014), Gonyora et al. (2021),

Guertler & Sick (2021), Henttonen (2013), Henttonen &

Lehtimäki (2017), Jang et al. (2017), Jeon & Degravel (2019), Jung

& Andrew (2014), Katzy et al. (2013), Kim & Kim (2018), Krishna &

Jain (2022), Kumar & Jyotishi (2014), Marangos & Warren (2017),

Marullo et al. (2020), Mejia-Trejo (2017), Noh & Lee (2015),

Passarelli et al. (2021), Podmetina & Albats (2021), Pöntinen et al.

(2022), Runeson & Olsson (2020), Santoro et al. (2020), Sedita &

Grandinetti (2022), Son & Zo (2021), Srisathan et al.

(2022), Trzeciak et al. (2022), Turki et al. (2017), Wynarczyk

(2013)

High

confidence

• Minor methodological

limitations

• Minor coherence

concerns

• Minor adequacy concerns

• Minor relevance concerns

3. Strategic

collaboration

helps global high-

tech SMEs

innovate.

54%

Agostini et al. (2017), Benitez et al. (2022), D’Angelo & Baroncelli

(2020a), D’Angelo & Baroncelli (2020b), Dooley et al. (2022),

Edison et al. (2018), Garbade (2014), Gonyora et al. (2021),

Guertler & Sick (2021), Henttonen (2013), Henttonen &

Lehtimäki (2017), Jang et al. (2017), Katzy et al. (2013), Kumar &

Jyotishi (2014), Marullo et al. (2020), Noh & Lee (2015),

Passarelli et al. (2021), Pilav-Velic & Jahic (2022), Santoro et al.

(2020), Sedita & Grandinetti (2022), Srisathan et al. (2022)

Low

confidence

• Minor methodological

limitations due to lack of

RCT studies

• Moderate coherence

concerns

• Moderate adequacy

concerns

• Minor relevance concerns

COLLABORATION FOR OPEN INNOVATION

Revised Conceptual Model/Framework

The major thematic findings and subthemes that emerged from the systematic review

and coding and thematic synthesis of the dataset were used to update the initial conceptual

framework presented in Figure 1. The revised conceptual model shown in

Figure 4 represents a clearer view of the three thematic findings from this study.

Figure 4

Revised Conceptual Model

Chapter Summary

Chapter 4 provided three major thematic findings synthesized from the dataset of 39

scholarly articles using the aggregative systematic review methodology. These findings were

elaborated on with relevant citations from the articles in the dataset, and the confidence in the

findings was indicated using Lewin et al.’s (2018) CERQual ratings. The contributions of subject

matter experts were described, and a revised conceptual framework was presented to represent

an explanatory and parsimonious view of the findings supported by the evidence in the dataset.

COLLABORATION FOR OPEN INNOVATION 92

The final chapter of this systematic review interprets these results and projects future

implications and managerial recommendations, with implied costs, study limitations, and areas

for future research.

COLLABORATION FOR OPEN INNOVATION 93

Chapter 5: Conclusions and Implications

The concluding chapter of this dissertation reviews the research and answer to the

research question and highlights the implications for management with recommendations and

implied costs for applied practice within global high-tech SME organizations. The

recommendations interpret the findings and specifically emphasize how global high-tech SMEs

can leverage strategic collaboration for open innovation. Limitations of this systematic review as

well as future research opportunities are discussed.

Review of the Research

This research addressed the problem of low adoption of open innovation among global

high-tech SMEs, despite evidence that innovation drives competition in the globalized

marketplace. Scientific evidence-based management practice was used to investigate this issue.

The scoping literature review established a research gap in the use of instrumental stakeholder

theory and informed the research question—What is the role of strategic collaboration for open

innovation with global high-tech SMEs? Instrumental stakeholder theory builds on Freeman et

al.’s (2018) stakeholder theory, which suggested that enterprises can and should be selective

about the stakeholders they partner with. In the development of IST, Jones et al. (2018)

concluded that successful collaborations are characterized by high levels of trust, cooperation,

and knowledge sharing. Accordingly, the conceptual framework for this study adopted the basic

tenets of instrumental stakeholder theory to explain strategic collaboration within an applied

management context.

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For the current study, the research methodology followed Denyer and Tranfield’s (2009)

five-step systematic review process, which resulted in a rigorous review and critical appraisal of

39 peer-reviewed articles that formed the basis for the themes and recommendations

highlighted in this study. The themes established three findings that evidenced the positive role

of strategic collaboration on open innovation with global hightech SMEs. Each of the findings is

summarized below.

Answer to the Research Question

In addressing the research question—What is the role of strategic collaboration for open

innovation with global high-tech SMEs?—this systematic review provides analysis from the

perspective of instrumental stakeholder theory. Strategic collaboration was found to help global

high-tech SMEs (1) overcome barriers to open innovation, (2) build relational capital among

stakeholders through high levels of trust, cooperation, and knowledge sharing, and (3) innovate

through product and process improvement. This section explains the answer to the research

question based on the findings.

Implications of Overcoming Barriers to Open Innovation

Strategic collaboration was an essential factor in global high-tech SMEs’ ability to

overcome barriers to open innovation. These barriers had potentially consequential implications

on global high-tech SMEs’ appetite for risk and their ability to access necessary resources and

protect against legal threats and liabilities. These collaborations extended global high-tech

SMEs’ networks and crossed industries, for example, joining diverse stakeholder communities,

such as government, academic, and research institutions. The more extensive the stakeholder

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collaborations, the more opportunity for global high-tech SMEs to reduce their risks and access

unique intellectual property, skills, and capabilities for innovation.

Implications of Building Relational Capital Among Stakeholders

Strategic collaboration was found to support the development of relational capital

between global high-tech SMEs and their stakeholders. This type of capital, despite including

intangibles such as social and human capital, was paramount to global high-tech SMEs’

innovation output. Strategic collaboration supported the development of high levels of trust,

cooperation, and knowledge sharing—each of which is instrumental in building effective

partnering relationships. Global high-tech SMEs could leverage relationships with partners to

access broader markets and share information to potentially improve their ability to compete,

innovate products and processes, and develop, test, and market new research. The most

important factor that determined the success of a strategic collaboration was global high-tech

SMEs choosing partners who had goals and objectives aligned to their interests. This goal-

objective commonality enabled global high-tech SMEs to develop relational capital underpinned

by shared open innovation pursuits.

Implications of Innovating Through Product and Process Improvement

Strategic collaboration ultimately enabled global high-tech SMEs to implement product

and process improvements through open innovation. This finding was highly dependent on

what type of stakeholder the firm partnered with. Central to the open innovation collaboration

was global high-tech SMEs’ ability to successfully commercialize and monetize the knowledge

shared through that relationship. Researchers including

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Albats et al. (2020), Benitez et al. (2022), D’Angelo and Baroncelli (2020b), Edison et al.

(2018), Garbade (2014), Guertler and Sick (2021), Henttonen (2013), Henttonen and

Lehtimäki (2017), Jeon and Degravel (2019), Katzy et al. (2013), Marangos and Warren (2017),

Passarelli et al. (2021), Pilav-Velic and Jahic (2022), Son and Zo (2021), and Turki et al. (2017)

indicated that the success of open innovation could take several collaboration cycles that

progress in distinct phases based on the maturity of the global high-tech SMEs and their

stakeholder relationships. Product innovations were more likely to result from collaborations

primarily with customers and through R&D laboratory stakeholders, whereas successful process

innovations generally involved collaborations primarily with suppliers and through R&D

laboratory stakeholders. Collaborations with other types of stakeholders from industry,

academia, government, and the greater public were found less likely to have consistent

significant impact specifically on innovation outcomes. Therefore, global high-tech SMEs should

be cognizant that their chosen strategic collaboration may lead to entirely different innovation

or performance outcomes depending on their initial choice of partner.

Management Implications (Recommendations)

This research evidenced that global high-tech SMEs that adopted open innovation used

fewer resources, created deeper relationships with their strategic collaboration partners, and

introduced higher levels of innovation. The innovation results were evidenced by global high-

tech SMEs’ improved performance and expanded access to markets. Global high-tech SMEs that

did not engage in strategic collaboration had lower innovation and R&D capability, were slower

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to adapt to environmental changes, and recorded more limited commercialization of intellectual

property and export products (Podmetina & Albats, 2021; Wynarczyk, 2013).

Given the opportunities that open innovation strategic collaboration affords, and the

positive outcomes of strategic collaboration on global high-tech SMEs’ business success, the

discussion below outlines management recommendations based on this study’s findings. The

recommendations specify actions that were shown to help global high-tech SMEs overcome

barriers to open innovation, build relational capital through open innovation, and use open

innovation to innovate. The capital and human resource costs to implement these

recommendations are commonly shared among stakeholders and therefore can reduce the

implementation cost to global high-tech SMEs.

Recommendation 1: Seek Innovation Intermediaries to Initiate Open Innovation

A critical step for global high-tech SMEs is to engage with innovation intermediaries

(Bigliardi & Galati, 2016; Garbade, 2014; Henttonen & Lehtimäki, 2017; Katzy et al., 2013;

Wynarczyk, 2013). According to Katzy et al. (2013), the search and selection “for suitable

partners interferes with the actual innovation,” so resource-constrained SMEs can leverage the

networks of innovation intermediaries as initial collaboration partners positioned to help

connect them with the best available partner for open innovation (p. 305). Innovation

intermediaries have expert and broad knowledge of industry partners and other stakeholders.

D’Angelo and Baroncelli (2020a) found the need to “align different R&D partners with different

expectations and final outcomes” (p. 105). The innovation intermediaries use their extensive

knowledge to match aligned stakeholders with each other. Thus, as trusted advisors and

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resources, innovation intermediaries can accelerate the speed at which global high-tech SMEs

strategically collaborate by quickly connecting them to established networks and

complementary partners for open innovation. These intermediaries can be vitally critical to the

success of global high-tech SMEs and include larger, well-connected stakeholders such as banks,

venture capital investment firms, large

multinational enterprises, R&D laboratories, and industry consortiums.

A major barrier to establishing a strategic collaboration is the initial lack of trust between

new partners. Innovation intermediaries are in an ideal position to act as the trusted third party

and mediator between new collaborators until behavioral knowledgebased trust can be

established through shared experience. Therefore, the trust between a global high-tech SME

and a potential partner is facilitated by an introduction through a

mutually trusted neutral third party, such as an innovation intermediary.

In addition, global high-tech SMEs can use innovation intermediaries to establish the

legal framework for collaboration. While trust lowers the risk and costs of potential legal action

between partners, legal protections for intellectual property and data protection are still a

necessity. Bigliardi and Galati (2016) argued that high-tech SMEs could “rely more . . . on

professional actors such as innovation intermediaries” not only to provide initial matchmaking

service for strategic collaborations but also to help them tailor an “adequate and transparent

Intellectual Property Rights (IPRs) strategy with partners” (p. 882). Innovation intermediaries

have ready access to proven industry-standard nondisclosure agreements (NDAs) and other

time-tested legal forms for enforcing intellectual

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property rights.

Furthermore, global high-tech SMEs can use innovation intermediaries to establish their

company’s global market reach. The benefits of global market reach include higher sales and

economies of scale. However, the regulatory environment for exports and branding may create

obstacles beyond the reach of global high-tech SMEs. Partnering with innovation intermediaries

that have an international footprint allows a global high-tech SME to leverage the intermediary’s

existing distribution and supply chains that already comply with export regulations. Podmetina

and Albats (2021) found that high-tech SMEs first needed to adopt open innovation strategies

before they could successfully scale up to being a global high-tech SME by internationalizing

their product market (p. 11). By leveraging the internal capabilities of multinational enterprises

as strategic collaboration partners, the high-tech SME can potentially expand to a global market

footprint. The innovation intermediary therefore enables a win-win condition that allows both

partners to

grow their product offerings and reach.

Additionally, evidence from the current study suggested that higher levels of innovation

were produced through strategic collaborations with partners that were both geographically

and culturally distant. SMEs who collaborated with local clusters out of convenience were found

to produce less innovative solutions. The specialization of technologies used by global high-tech

SMEs means they may often work with international suppliers and customers to leverage

leading world-class technologies. Passarelli et al. (2021) found that “the higher the physical

distance between partners the greater the matching probability” (p. 748). Accessing more

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distant partnerships through international innovation intermediaries could enable global high-

tech SMEs to access world-class partners beyond their normal boundaries.

Recommendation 2: Commit to Multiple Cycles of Open Innovation

Finding 2 implied that much of the benefit of open innovation was due to intangibles

such as relational capital. This means that the more tangible benefits of product and process

innovation are seldom guaranteed after one strategic collaboration cycle and require several

iterative cycles that continue to build trust, cooperation, and knowledge sharing. The

effectiveness of the partnership and the ability to commercialize products and monetize process

improvements increases over successive collaboration cycles. Marangos and Warren (2017)

documented instances in which 20% of SMEs in their case study had exited open innovation

after dissatisfaction with initial results (p. 219). Marangos and Warren (2017) also documented

several distinct phases of open innovation based on the maturity of the partnership and

participants, with other researchers defining similar phases of open innovation such as

exploration or monetization (Albats et al., 2020;

D’Angelo & Baroncelli, 2020b; Garbade, 2014; Henttonen, 2013; Henttonen & Lehtimäki, 2017;

Jeon & Degravel, 2019; Katzy et al., 2013; Passarelli et al., 2021). New SMEs would initially be

expected to operate at lower levels of open innovation, producing more shallow results from

one-way knowledge sharing, while results discussed by Dooley et al. (2022) indicated that more

experienced SMEs could partake in “deeper and more significant strategically aligned projects

for the SME” following several open innovation project phases (p. 17). Therefore, a global high-

tech SME should engage in multiple cycles of strategic collaboration to build strong relational

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capital and incremental improvements. The sustained collaboration increases the potential for

substantially tangible product or

process innovations.

Global high-tech SMEs should also prepare ways to follow up with stakeholders to

preserve relational capital after a collaboration has ended to sustain the relationship for future

strategic collaborations. Engagement activities that build connection, trust, and rapport—such

as ongoing networking opportunities, occasional newsletters, joint socials, and invitations to

product launches—can help strengthen and sustain the relationship with stakeholders. The goal

is to ensure the strategic collaboration partnership remains energized and viable for future

collaborations.

Recommendation 3: Maximize Knowledge Sharing Through Open Innovation

Product and process innovation was correlated with global high-tech SMEs’ ability to

increase knowledge sharing with external stakeholders. Instrumental stakeholder theory posits

that knowledge sharing is increased by any activity that promotes trust and cooperation. Global

high-tech SMEs were observed to gather more valuable and commercializable knowledge

through resource-sharing techniques that encouraged effective knowledge sharing. Methods to

increase knowledge sharing between partners include establishing compatible knowledge-

sharing systems, setting expectations for the regular sharing of knowledge and resources, and

developing human capital by delegating

relationships to internal stakeholders, as described below.

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Recommendation 3a: Establish Compatible Knowledge-Sharing Systems for Open

Innovation. This study showed that global high-tech SMEs and their collaboration partners were

most effective when they had compatible systems for knowledge sharing. Global high-tech SMEs

can use knowledge-sharing systems to communicate with partners across international

boundaries when engaging in open innovation collaborations. Common knowledge-sharing

systems can help encourage a more transparent exchange of intellectual property between

partners while minimizing “risk of unwanted knowledge spillover” of privileged data (Marullo et

al., 2020, p. 449). Effective knowledge-sharing systems “support and promote an open

innovation climate for communication and collaboration” among partners (Agostini et al., 2017,

p. 1158). Examples of knowledgesharing systems include those that enable the following:

• Transfer of technical knowledge and intellectual property: Marullo et al. (2020)

described how firms take advantage of external knowledge sources to develop “new

technical knowledge inside the firm” through access to those systems (p.

448).

• Real-time collaboration for project coordination through meetings and scheduling:

Garbade (2014) cautioned that coordination-related communication may “exhaust

communication channels,” so an efficient knowledge-sharing system could provide more

capacity for useful knowledge exchange (p. 65).

• Data and document sharing through open data collaboration: Runeson and Olsson

(2020) characterized data used and produced within and between organizations in seven

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broad types: map, society, position, images, sensor, human, and business data, which

could be mined for valuable insight (pp. 207–208).

In conclusion, a core aspect of strategic collaboration for open innovation is knowledge

sharing. Ideally, global high-tech SMEs should aim to increase the amount of knowledge sharing

with partners as a main driver of successful collaboration. A knowledge-sharing strategy that

combines the use of different types of knowledge-sharing systems can not only facilitate

purposeful co-creation of internal and external information exchange across international

boundaries, but also make available such information to solve mutual innovation problems

between partners and accelerate the development and

commercialization of joint innovation ventures (Bogers, 2012, p. 1).

Recommendation 3b: Set explicit expectations for external partner contributions on

open innovation projects. Edison et al. (2018) noted,

Even though knowledge sharing is perceived as important in facilitating value creation, it

is difficult to get people to invest time or effort in sharing code or

building skills and knowledge outside their own domain. (p. 6)

While open innovation can allow for knowledge sharing to flow only from one partner to

another, more dynamic collaborations require expanded interchanges of knowledge and

resources whereby both partners contribute. Global high-tech SMEs can establish clearly

structured strategic collaborations by defining the expectations for resource sharing and the

expected contributions between their collaborators. Examples of expectations to address in the

collaboration agreement include the specializations, core competencies, human resources,

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capital investments, patents, technologies, committed outcomes, and knowledge-sharing tools

that each partner will bring to the open innovation project. Garbade (2014) explained that

“clear task division” led to “increased alliance performance” (p. 87). Partners performed better

and engaged in effective knowledge sharing when they had clarity on which part of a project

each partner specialized.

Once expectations are clearly defined, their alignment to outcome-based performance

measures will help motivate accountability and commitment between partners. Furthermore,

global high-tech SMEs can initiate regular meetings and progress reports to help monitor the

status of open innovation projects and partner contributions within the context of agreed-on

expectations. As part of this monitoring cycle, strategic collaboration partners can reevaluate

and reconstitute the partnership as applicable, to

adapt to changing conditions.

Recommendation 3c: Delegate internal stakeholders to manage open

innovation partner relationships. The employees of global high-tech SME are a critical part of

the interpersonal relationships that form the partnership between the enterprise and other

stakeholders. Several researchers highlighted the importance of delegation of authority and

alignment of interests with employees, the internal stakeholders of the enterprise. Agostini et

al. (2017) found that “employees are more likely to have direct contact with business partners,

considering that co-development or R&D projects where firms share their basic knowledge with

them are frequent” (p. 1157). Some researchers recommended developing human capital by

embedding employees in the management of partnerships and consortiums. An entrepreneur

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interviewed by Santoro et al. (2020) echoed the need for internal stakeholders to be “aligned

with . . . vision, culture, feelings and needs” (p. 4), which Gonyora et al. (2021) extended to “all

levels of employees in their firms” (p. 10). When internal stakeholders were able to exercise

autonomy and form ownership of the strategic collaboration relationship, they deepened the

collaborations on

a human level.

Dooley et al. (2022) considered skilled employees “a third channel” of innovation

through “deep employee tacit knowledge of innovation practices” (p. 20). Garbade (2014)

considered the “knowledge embedded in humans” less inimitable and thus an even greater

competitive advantage than complex physical technology (p. 17). The basic premise is that there

is an interdependency between intellectual property and human capital. To be successful in the

case of strategic collaboration for open innovation, the internal stakeholder (i.e., human capital)

should act as a conduit for knowledge shared by external partners. Therefore, global high-tech

SMEs can help build their internal capacity and advantage by designating specific human capital

to manage the stakeholder relationships, thereby being exposed to—and enriched by—the

strategic collaboration. The knowledge sharing that occurs through open innovation is

ultimately absorbed by the human capital of a global high-tech SME, who are therefore the

connectors between the partnership and organizational success.

Limitations of the Study and Areas for Future Research

The study recognizes the following limitations of this systematic review and recommends

promising future research paths to better address these limitations.

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Limitations of the Study

The systematic review on the topic of open innovation returned a mix of qualitative and

quantitative studies but did not include any randomized controlled trials. RCTs contribute some

of the strongest quantitative evidence, so properly conducted experimental evidence would

provide stronger support for the role of strategic collaboration in open innovation with global

high-tech SMEs. The methodologies used by the studies of the dataset also seldom included

longitudinal studies investigating the long-

term implications of strategic collaborations for global high-tech SMEs.

This dissertation was subject to sole researcher bias, which was mitigated by consulting

with subject matter experts on the topic. Consulting with subject matter experts in academic

research techniques and open innovation practice helped remove the effects of sole researcher

bias, which could impact the emphasis on themes, findings, and

recommendations.

Areas for Future Research

Stronger causal evidence on the role of strategic collaboration on open innovation

adoption could be established through RCTs and longitudinal studies. According to Barends et al.

(2017), RCTs represent some of the strongest available methodologies to confirm the impact of

interventions using scientific evidence-based management (p. 17).

Few studies included longitudinal before-and-after data collection, which is important for

establishing causality. Since open innovation strategic collaboration is currently expected to

strengthen across successive collaboration cycles, global high-tech SMEs and their partners

COLLABORATION FOR OPEN INNOVATION 107

should ideally realize increasing performance outcomes as cycles of collaboration are

completed. A longitudinal study could also provide evidence that would confirm or disprove the

feasibility of progressive performance outcomes and specifically under what causal conditions

such outcomes are achieved.

Another promising future study can address the impact of global high-tech SMEs

geographical and cultural distance to their collaboration partners. While proximity provides a

convenience bias in terms of ease of communication and thus knowledge sharing, several

studies offered evidence that collaborations with distant partners provided higher benefits.

These higher benefits were attributed to access to export markets, increased exposure to

innovative ideas outside of a local groupthink cluster, and improved opportunities to reach the

right partner from among a larger pool. Considering that 27 (69%) of the 39 studies in the

dataset were limited to collaborations within a single country, future studies could well

investigate the impact of geographic and cultural

distance between international collaboration partners.

Last, innovation intermediaries are uniquely situated to help understand the full partner

innovation life cycle. Thus, a correlational study that investigates the variables that influence

innovation intermediaries’ successful matchmaking outcomes across the life cycle will enhance

the literature on strategic collaboration for open innovation.

Final Summary and Conclusion

This systematic review investigated the role of strategic collaboration in open innovation with

global high-tech SMEs. Three themes emerged through a thorough examination of a recent 10

COLLABORATION FOR OPEN INNOVATION 108

years of scholarly articles related to the research question. Strategic collaboration helps global

high-tech SMEs overcome the barriers to open innovation, build relational capital with

stakeholders, and innovate through open innovation. These findings imply that global high-tech

SMEs might not successfully produce innovations until they have first matured strategic

collaborations to overcome barriers and build relational capital. Strategic collaboration was

found to help global high-tech SMEs make efficient use of their limited resources to survive in

the global marketplace. Future research could result in longitudinal studies, causal evidence, or

correlations that help frame evolved, highimpact collaboration constructs for stakeholder open

innovation relationships. These relationships can accelerate groundbreaking innovation

activities and impact across broader world economies and markets.

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