Exploring Factors Influencing Open Innovation Adoption in SMEs: The Evidence from Emerging Markets

Open Innovation (OI) is among the vital innovation paradigms for assisting small and medium enterprises (SMEs) to effectively implement innovation initiatives. Drawing on the concepts of organisational agility and absorptive capacity with transaction cost theory, this study’s goal is to investigate factors affecting the adoption of an Open Innovation (OI) orientation in Thai SMEs. Using data from 214 SMEs in Thailand, structural equation modelling validated the model and analysed the proposed hypotheses. The results show that organisational agility, economic and financial readiness and absorptive capacity relate positively to OI adoption and innovation performance. Organisational agility (b = 0.553) had the greatest influence on OI adoption, then economic and financial readiness (b = 0.405) and absorptive capacity (b = 0.387) followed. The results of mediation analysis also reveal that OI adoption partially mediates the effects of organisational agility and absorptive capacity on innovation performance. Our study provides a trailblazing empirical analysis of the major factors influencing SMEs’ OI adoption and performance, extending knowledge of OI adoption by SMEs in emerging economies. The paper proposes a holistic framework for examining SMEs’ OI adoption and performance, through the integration of organisational agility, absorptive capacity and transaction-cost concepts.


1-Introduction
Innovation is one of the imperative strategic mechanisms for sustainable growth. Firms must innovate in response to changing customer needs, market structure and technology disruption. Innovation has emerged as a critical factor in the survival, growth and competitive advantage of SMEs [1,2]. The need for an ongoing process of innovation is not only vital for their survival; it can also trigger social and economic changes. Innovation is essential for sustainable growth and economic development [3,4]. In emerging economies, most businesses are SMEs and important contributors to job creation and global economic development. Data from the World Bank [5] reveal that SMEs represent about 90% of businesses and over 50% of employment worldwide, contributing 40% of national income (GDP). Both SMEs and innovation are important mechanisms for national economic development. A nation can achieve sustainable development through fostering SME innovation [4]. Open Innovation (OI) has become a widely recognised and implemented concept among large corporations. Applying OI may speed up and enhance organisations' innovation process and commercialisation of their innovations. Academics and scholars have explored the key factors and practices that stimulate the successful adoption of OI. Although recent literature suggests that adopting OI can help SMEs boost their innovation performance, the literature still lacks adequate evidence relating to OI from the SME perspective [4,5]. SME adoptions of OI have garnered researchers' attention [6] in studies focused on OI approaches and practices. Realising OI as a new innovation paradigm is becoming more prevalent. OI utilises purposive knowledge inflows and outflows to expedite internal innovation and expand the markets for its external use [7,8,9]. It encompasses outside-in and inside-out technology and idea movements, dubbed 'technology acquisition and exploitation' [10,11].
OI studies reveal firms' diverse behaviour patterns. Lee, Park, Yoon, and Park (2010) [12] found that OI implementation approaches and adoption models vary according to the size of the enterprise. SMEs benefit differently from OI [13]. Therefore, benchmarking the success of OI implementation cannot use the same criteria for large firms as for SMEs. Greater understanding of SME conditions and contexts would increase the chances of successfully implementing OI approaches. A scant understanding of how SMEs can adopt and implement OI requires more empirical evidence for clarification [14].
Numerous external and internal factors influence firms' innovation adoptions and practices [15]. Internal factors include size, age and research and development (R&D) investment; external factors include technological advances and industry intensity. Both affect large multinational firms' innovation adoption [10,15]. While external factors influence SMEs' innovation adoptions in ways similar to those in large firms, most SMEs lack resources for R&D, due to limited funding and knowledge. Despite attempts to provide empirical evidence for understanding firm innovation adoption, only a few studies focus on the context of SMEs in emerging countries, such as Thailand. Moreover, the lack of a holistic conceptual framework to determine factors influencing an OI adoption allows us to contribute a fruitful body of knowledge, by drawing on organisational-agility and absorptive-capacity concepts and transaction-cost theory, to better understand OI adoption and innovation performance in the SME context. The remainder of this paper is structured as follows. Section 2 focuses on relevant literature concerning organisational agility, absorptive capacity, transaction cost theory and open innovation. Section 3 details some tentative propositions on OI adoption and innovation performance in SMEs and illustrates the research methodology utilised for data collection. Section 4 presents data analysis, results and discussion. Section 5 postulates a conclusion, and Section 6 details the study limitations and prospects for future research.

2-1-Organisational Agility and Open Innovation
Organisational Agility (OA) is a firm's ability to undertake unanticipated changes through immediate and innovative responses. Previous studies confirm that OA is one of the critical capabilities that helps firms properly capture current market trends [16,17]. OA is a multidimensional concept that scholars have classified by specific types, according to their different foci [18]. Bessant et al. (2000) [19] classify four vital OA dimensions: agile strategies, agile processes, agile linkages and agile people. Vázquez-Bustelo et al. (2007) [20] classify OA in five dimensions: agile human resources, technologies, value chain integration, concurrent engineering and knowledge management. Zandi and Tavana (2011) [21] classify organisational agility into three elements: strategic, operational and functional agility. Sambamurthy et al. (2003) [22] also identify three classes: customer, partnering and operational agility. Customer agility is leveraging customers' opinions to earn enhanced market intelligence [23]. Partnering agility is absorbing knowledge from business partners to embolden the firm's response to market requests. And operational agility refers to the ability to cope with volatile market changes using internal business processes and the execution of a product innovation plan to devise a new product design [24].
According to the dynamic-capabilities concept, OA can arise from the integration of strategic resources. Teece et al. (2016) [25] stand by this argument, stating that OI can embolden agility by enhancing and expediting novel product development, to meet upcoming market openings. Yet, OI and OA remain vague in terms of the relationship between them, and we ask again here what it is. Clearly, OA acts as an antecedent to OI adoption. By allowing access to versatile complementary knowledge, inbound OI diminishes experimentation-related risks and stimulates a firm's innovation engine, enabling flexibility when attempting fierce and radical innovation [26]. Utilising external resources helps firms to perpetually communicate and share knowledge, thus enhancing the spread of know-how [27]. Such a firm allows its managers to efficiently respond to external changes, ensuring the organisational structure's flexibility, necessary to predict and tend to future requirements [26]. Scuotto et al. (2017) [27] suggest that intensive inbound OI allows adequate internal proactive efficiency and continuity for environmental signal scanning, enabling a dynamic-management business process that allows for greater market capitalisation and operational adjustment agility. Besides inbound OI, Hu et al. (2015) [28] postulate that outbound OI enables firms to exploit emerging market opportunities through efficiently developing market-related knowledge. Additional market opportunities facilitate firms' obtaining and assessing sufficient customer feedback and scrutinising competitors' activities, ensuring efficient decision-making in operational process adjustment and market capitalisation [29]. Firms with outbound OI usually must watch for a wider range of technological developments, to acquire potential internal opportunities for drastic innovation [28]. Broadly scanning for technology resources can open opportunities for addressing firm imperatives. Operational exploitation can also enhance firm abilities to utilise emerging market opportunities through continuous adoption [26]. Overby et al. (2006) [30] establish absorptive capacity as a set of organisational processes and routines through which firms obtain, digest, transform and employ knowledge, to devise a dynamic organisational capability. Absorptive capacity is classified into four dimensions [31]: (1) acquisition, the ability to pinpoint, identify, assess and obtain operation-critical external knowledge; (2) assimilation, the comprehension of externally acquired knowledge; (3) transformation, the ability to merge old knowledge with newly acquired and assimilated knowledge; and (4) exploitation, the ability to incorporate the obtained, assimilated and transformed knowledge into usable organisational routines. According to Walter (2021) [17], capacity emphasises a focus on knowledge while OA maintains a focus on handling change; absorptive capacity is perpetual, while OA occurs only in response to changes in the environment. Previous literature confirms that the adoption of innovative practices in services or manufacturing requires a firm to be able to obtain, disseminate and employ external and internal knowledge. Innovation processes succeed through the imposing influence of leaders' skills and ability on accessing internal and external knowledge sources [32]. Absorptive capacity is a prerequisite for any knowledge-management activity that involves the deliberate management of knowledge flows beyond organisational limits, to generate innovations [33]. It indicates the presence of a knowledge base facilitating innovation adoption, where the setting is key to inspiring the joint generation of novel concepts and finding novel ways of utilising the external partner's knowledge. The absorptive capacity allows the company to actively collaborate in a pioneering manner, rather than passively observing. In the long term, absorptive capacity allows the consolidation of a high success rate in co-innovation projects, high credibility in virtual environments and a positive valuation by external partners, enhancing collaborative work [31,32,34].

2-3-Transaction Cost Theory
Transaction cost theory explains firms' innovation-adoption behaviours [35,36], based on two behavioural assumptions: opportunism and bounded rationality. Bounded rationality means that humans are unlikely to have adequate capacity, information, time or resources to entertain every state-contingent outcome that a possible transaction entails, while opportunism means that humans will pursue their self-interest by making room for guile [37,38]. In economics and related disciplines, transaction costs are economic-exchange costs, including search and information, bargaining and policing and enforcement costs [39]. Transaction cost theorists suggest classifying a firm's total incurred costs as transaction and production costs. Transaction/coordination costs are the costs of all the required information processing crucial to coordinating the work of primary people and machines, whereas production costs comprise costs incurred for the physical or other primary processes necessary to create and distribute products. When considering 'make-or-buy' sourcing decisions, decision-makers must weigh the production and transaction costs associated with executing a transaction within their firms, versus the costs of executing it in the market [39]. A transaction cost arises from an economic transaction conducted in a market [37,40]. Agents have bounded rationality and maintain opportunistic behaviours to advance their interests above all; they have limited cognitive abilities and cannot entertain all possible events. Williamson (1993Williamson ( , 2008 [37,40] describes a transaction according to asset specificity, frequency and uncertainty. Asset specificity characterises a specialised investment that cannot be redeployed to alternatives or by alternative users without a productive-value loss. Asset frequency reduces transaction costs due to redeployable knowledge and standardised processes and contracts [41]. Asset uncertainty includes internal and external uncertainty. The first encompasses the complexity and tacit nature of the firm's internally performed tasks or that two different firms perform during a technological exchange. External uncertainty includes technological, fiscal and legal regulatory and competitive uncertainty [42].

2-4-Conceptual Framework and Hypothesis Development
The research framework for investigating factors affecting SME OI adoption was developed based on previous relevant literature on organisational agility and absorptive capacity concepts, in addition to transaction cost theory. This study's conceptual framework includes innovation performance since prior studies confirm it as a subsequent outcome of innovation adoption. Figure 1 illustrates the proposed research outline: The hypotheses follow: H1: Organisational agility significantly influences SME Open Innovation adoption.
H2: Economic and financial readiness significantly influences SME Open Innovation adoption.
H3: Absorptive capacity significantly influences SME Open Innovation adoption.

3-1-Research Design and Data Collection
To expand the body of knowledge on open innovation and innovation performance in emerging-market countries, such as Thailand, a self-administered questionnaire with an explanatory cover letter was sent to Thai SME owners in three types of business: manufacturing, service and merchandising. The researcher acquired information on the studied firms from the database of the Department of Business Development, the Ministry of Commerce. Respondents remained anonymous. The study utilised a quantitative method to gauge the proposed research hypotheses and assess the suggested model. AMOS 22.0. SEM (Structural Equation Modelling) supported data evaluation. According to Anderson and Gerbing (1988) [43], the suggested sample size was at least 150 participants; however, other researchers [44] suggest at least 200 participants for SEM analysis or at least 5 cases per parameter for uncomplicated SEM. Since this study contained 28 observable variables, the minimum sample size was 28×5 = 140. Recipients returned a total of 249 questionnaires (approximately a 9% response rate). Following the screening of the returned questionnaires, 214 useable questionnaires remained, exceeding the minimum sample size parameter and retained for further analysis. Figure 2 represents the research procedure.

3-2-Questionnaire Development
The questionnaires comprised two main sections: (1) typical information related to respondent demographics and (2) measurement items on a five-point Likert scale ranging from strongly agree (5) [45]. To assess Economic and Financial Readiness, a five-item measure was modified from Oduro (2020) [46]. For Absorptive Capacity, a four-item measure was modified from [47]. Open Innovation Adoption was measured by four items adapted and modified from [46,48], and Innovation Performance was measured by four items modified from Hameed et al. (2018) and Hoonsopon and Ruenrom (2012) [48,49]. Table 1 illustrates the constructs and measurement scales.

Items Observed Variables
Operational Agility (OPA)

OPA1
We fulfil demands for rapid response, special requests of our customers whenever such demands arise. Our customers have confidence in our ability.

OPA2
We can quickly scale up or scale down our production/service levels to support fluctuations in demand from the market.

OPA3
Whenever there is a disruption in supply from our suppliers, we can quickly make necessary alternative arrangements and internal adjustments.

CA1
We are quick to make and implement appropriate decisions in the face of market/customer changes.

CA2
We constantly look for ways to reinvent/reengineer our organisation to better serve our marketplace.

CA3
We treat market-related changes and apparent chaos as opportunities to capitalise upon quickly.

PA1
We collect detailed information about our suppliers and service providers.

PA2
We can exploit the resources and capabilities of suppliers to enhance the quality and quantity of products and services.

PA3
We work with external suppliers to create high-value products and services.

PA4
We can manage relationships with outsourcing partners.

PA5
We can switch suppliers to access lower costs, better quality or improved delivery times.
Economic and Financial Readiness (EF)

EF1
We have sufficient financial resources to undertake OI projects.

EF2
Our adequacy of state-of-the-art technologies, infrastructure and facilities encourages us to undertake innovation projects with external actors.

EF3
Our enterprise has the economic resources like land, labour and capital goods to embark on OI projects. EF4 * The cost of securing and enforcing IP hinders our OI orientations.
EF5 * The cost of innovation impedes our adoption of the OI model.

AC1
The search for relevant information concerning our industry is an everyday business in our company.

AC2
In our enterprise, there is a quick information flow. For example, if a business unit obtains important information, it communicates this information promptly to all other business units or departments.

AC3
Our employees are used to absorbing new knowledge as well as preparing it for further purposes and making it available.

AC4
Our enterprise regularly reconsiders technologies and adapts them accordingly to new knowledge.
Open Innovation Adoption (OI)

OI1
We adopt OI to improve our internal R&D and innovation process.

OI2
We use the OI to secure market share growth and global market reach.

OI3
New ideas are always welcomed for open innovation in our enterprise.

OI4
Engaging in OI is a good way to commercialise the idea.

IP1
Our new product generates a competitive advantage for the company.

IP2
Our new product is newer compared to the company's existing product.

IP3
Our new product can respond to customers' needs.

IP4
Compared to competitors within our sector, we exhibit a higher innovation performance.

4-2-Measurement Model
For hypothesis testing, the authors used Confirmatory Factor Analysis, following Hair et al. (2010) [50] by defining a construct's validity as a threshold at which the observed variables correspond to latent variables designed to be gauged theoretically. Accordingly, the authors assessed convergent and discriminant validities, with the results confirming the number of items for each construct as follows: OPA (3 items), CA (3 items), PA (5 items), EF (5 items), AC (4 items), OI (4 items) and IP (4 items). Cronbach's Alpha was measured in the range of 0.776-0.944. Tables 3 and 4 summarise the results for the measurement model:  As Table 3 Table 5 indicates that the discriminant validity test was performed. The study attained discriminant validity because every construct's AVE square root was higher than the respective interconstruct correlation estimates.

4-3-Structural Model and Hypotheses Testing
After assessing the measurement model, the structural model was developed. Figure 3 demonstrates outcomes for the path model, illustrating an adequate model fit to the data.  Notes: R 2 (Open innovation adoption) = 0.445; R 2 (Innovation performance) = 0.544; *p < 0.05; **p < 0.01; ***p < 0.001 The hypothesised path model outcomes indicate an adequate model fit to the data (Chi-square = 596.946; df = 340; CMIN/df = 1.756; GFI = 0.901; CFI = 0.966; TLI = 0.962; IFI = 0.966; RMSEA = 0.044). Table 6 shows the results for the hypothesis testing, which indicate significance in the four hypotheses' relationships. Specifically, the outcomes supported the hypotheses concerning the relationship between OA and OI (H1: b = 0.553, t-value = 8.134, sig < 0.001), between EF and OI (H2: b = 0.405, t-value = 6.873, sig < 0.001) and between AC and OI (H3: b = 0.387, t-value = 4.242, sig < 0.001). Meanwhile, supporting H4, OI positively impacted IP (H4: b = 0.637, t-value = 11.253, sig < 0.001).  Table 6 illustrates the results of mediation analysis with bootstrapping.  The results of structural equation modelling analysis provide more insight into antecedents of SMEs' open innovation adoption and the consequent innovation performance. Our results confirm prior studies the World Bank (2018) and Lichtenthaler (2008) [5,10], namely, numerous elements, both explicit and implicit factors, affect firms' innovation adoptions and practices. Our proposed framework is one of a few studies of integrated firms' implicit capabilities-OA and AC with EF-to explain open innovation adoption in an SME context. Based on the path-analysis results, OA had the greatest influence on open innovation adoption. This finding is in the line with Fabian (2019) [51], i.e. fostering firms' innovation adoptions and practices can occur through enhancing organisational agility, leading to the firm's achieving better flexibility, increased speed and enhanced customer focus, which subsequently impact the firm's OI adoption and increase its innovation capacity, improving the effectiveness of innovation performance Fabian (2019) [51]. Considering subdimensions of OA based on the measurement model analysis results, operational agility emerged as the most important determinant of OA. That is, SMEs' ability to modify and adapt their operations and technology to constantly evolving business requirements is the critical element for fostering OI adoption in emerging markets. Customer agility, the second important determinant of OA, refers to the firm's ability to sense and respond quickly to customer-based opportunities for innovation and competitive action. Customer agility also involves leveraging big data to understand customer needs. Modern marketing techniques and practices, such as neuromarketing [52], can provide an innovative method for gaining customer insight, helping firms to achieve this form of OA.
Partnering agility is a significant form of OA influencing OI adoption. SME owners should circumspectly consider the firm's ability to leverage the assets, knowledge and competencies of such stakeholders as suppliers, distributors, contract manufacturers and logistic providers [53] as one of the critical key success factors for attaining open innovation adoptions and practices. SMEs can start using innovation intermediaries in their search for innovation partners. SEM results show economic and financial readiness as the third most important factor affecting SMEs' OI adoption. This finding was consistent with Oduro's (2020) [46] that to a large extent, firms' ability to undertake innovation projects depends on their financial and economic resources. SMEs should consider exploiting newly emerging financial technologies, such as fintech solutions and financial crowdsourcing, to fill an economic and financial-readiness gap. Moreover, designing an appropriate regulatory environment for supporting OI adoptions and practices is one of a government's most critical national-agenda items. A firm's ability to acquire, disseminate and utilise internal and external knowledge can function as absorptive capacity. Our finding confirmed previous findings of Aboelmaged and Hashem (2019) [32] that absorptive capacity positively influences innovation adoption in SMEs. SME owners should stimulate knowledge transfer within a firm and consider employing qualified human resources. Furthermore, SMEs should emphasise exploratory, assimilative, transformative and exploitative learning processes equally. Nurturing learning organisational culture within a firm-e.g. setting up a support network of trainees to encourage exchanges of their learning experiences, supporting employees in applying the knowledge and skills learned in training at work and allowing them to make mistakes in practice-will enhance a firm's absorptive capacity, consequently influencing SMEs open innovation adoption and innovation performance.

5-Conclusion
OI is an imperative firm approach to implementing innovation initiatives. This study explores antecedents of OI adoption and innovation performance among SMEs in emerging economies. As the most frequently occurring enterprises in those economies, SMEs are insufficiently studied in the OI literature [54]. Accordingly, a holistic conceptual framework based on concepts of organisational agility, absorptive capacity and transaction cost theory was proposed for an investigation of factors influencing SMEs' OI adoption. The results showed that organisational agility, economic and financial readiness and absorptive capacity play significant roles in SME adoption of OI. These findings align with identifying absorptive capacity as a prerequisite for co-innovation [31]. Also, these results extend the existing body of knowledge on the correlation between organisation agility and OI [26]. Organisational agility benefits businesses by identifying and adapting to market changes. Agile organisations maintain a solid market knowledge base and responsiveness to current market trends. Organisational agility entails a firm's inclination towards OI adoption. Economic and financial readiness is also a driving factor, aligning with the realisation that an economic and financial issue determines the degree of OI adoption in the SME context [46].
This study also concerns SME owners and policy-makers. First, to effectively implement an OI approach in an organisation, entrepreneurs and SME leaders must cultivate an organisational-agility culture for all employees. Furthermore, nurturing the organisation's absorptive capacity is also essential for SMEs to successfully maintain an OI approach. Being knowledge-intensive and developing capacities to obtain and assimilate internal and external knowledge are also such imperative initiatives for achieving an OI orientation. Information sharing and collaborative rewards develop the absorptive capacity that subsequently entails the firm's ability to successfully adopt an OI approach. Second, to promote OI in society, policy-makers and national innovation agencies should support SMEs gaining organisational agility and absorptive-capacity knowledge. For example, providing training courses for entrepreneurs and SMEs' leaders to better understand and implement organisational agility and absorptive capacity culture in their enterprises should be a national agenda item for SME development in emerging economies. Our study also generates awareness of the necessity of absorptive capacity and shows that practitioners should nurture its development [47]. Our research indicates the beneficial relationship of organisational agility, economic and financial reediness, absorptive capacity, OI adoption and firms' innovation performance. SMEs can benefit from open innovation as it inspires the growth of their knowledge base, rendering them more innovative.

5-1-Limitations and Future Research
This study contains some limitations. First, the results come from a sample of SMEs in Thailand, signalling the need to consider the generalisability of the findings to SMEs in other emerging-economy countries. Second, a self-reported questionnaire was this study's research tool, so respondents may not have answered truthfully or may have provided invalid answers. In the future, a mixed-methods approach could provide deeper insight into factors affecting and driving SME OI adoption in emerging economies. Future research should expand boundaries to comparatively investigate factors influencing OI adoption between large enterprises and SMEs, to better understand and expand our body of knowledge on enhancing nations' innovation capability and achieving higher economic growth towards an innovationdriven economy. The factors this study highlights could serve as a good basis for further exploration of cultivating SME OI adoptions and practices. Future research may capture the dynamics of research variables over time, using longitudinal studies or qualitative research methods.

6-1-Author Contributions
W.P. conceptualized and participated study design, coordinated data collection, carried out the initial analyses, drafted the initial manuscript, and read and approved the manuscript. S.T. participated in study design, guided the methodology coordinated and supervised data collection and analyses, reviewed and edited manuscript. Both authors read and approved the manuscript as submitted and agree to be accountable for all aspects of the work.

6-2-Data Availability Statement
Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.