INTRODUCTION:

Today's global and digitalized economy has led to increased market and company instability^1,2. Companies need constant cooperation with external agents from whom to absorb the necessary knowledge and technology^3,4. Innovation and technological progress play a key role in the economic growth of companies ^5,6 and therefore economic and social development regions^4,7. Technology is known to be an important factor that determines the level of economic growth⁸. In consequence, both technology transfer (TT)^9–12 and technology adoption (TA)^13,14have received much attention in recent years from the scientific community and governments.

Even though a consensus on the definition of TT remains elusive, it can be described as the process of applying technological innovation to industrializing countries, regions, and industries, which lies at the heart of global technological and economic competition^10,12. The European Patent Office provides a more operational definition, defining it as a fundamental process wherein technology and/or know-how are transferred from one entity to another for the purpose of converting innovative developments into marketable products¹⁵.

In line with the definition given for TT, when technology is transferred, some firm or organisation is in turn adopting it. TA is defined "the stage of selecting a technology for use by an individual or an organization"¹⁶. Moreno del Castillo referred to it as the process of integrating innovative technologies into existing business processes and systems, often necessitating policy changes to meet specific needs or goals¹⁷.

The relationship between TT and TA is not well understood¹⁸. TT is often seen as a necessary but not sufficient step in the TA process, even if the ultimate goal of TT efforts is TA¹⁹. The success of TT depends on the ability of the recipient entity to successfully adopt and commercialise the technology²⁰. In turn, the awareness of a specific technology does not ensure its adoption, and it is desirable for technology transferors to make efforts to facilitate the TA process²¹. As a result, TT and TA complement each other, and together they are interdependent and mutually reinforcing processes²².

Among all the companies, small and medium-sized enterprises (SMEs) are known as the backbone of Europe²³. They comprise 99% of all businesses in the EU; SMEs employ approximately 100 million people, contribute to over half of Europe's GDP, and play a pivotal role in adding value across every sector of the economy²⁴. SMEs play a crucial role in enhancing Europe's economic development, providing sustainability and inserting innovation²⁵.

SMEs face particularly pronounced challenges in TT and TA among others due to their limited capital capabilities^26,27, lower propensity to accept new technologies²⁶, resource constraints²⁸, and the dual challenge of funding internal innovations while allocating resources for the integration of new technologies^29,30.

By reviewing existing literature, the study aims to elucidate the core characteristics of the field, explore accumulated knowledge, and identify thematic areas and prospective directions for future research. Consequently, the primary objective of this analysis is to develop a research agenda for TT and TA in SMEs.

METHODOLOGY:

The Systematic Literature Review (SLR) plays a vital role in generating thorough knowledge concerning the current understanding in a given field of study²⁷. In this study SLR contributed significantly to the identification of emerging research areas and the formulation of a research agenda.

The methodology applied in this study adheres to PRISMA³¹approach. To find bibliographic records in the Web of Science, the words that best describe “technology transfer,” “technology adoption,” and “SME” were used as search terms. The specific queries enclosed in quotation marks used in the search were:

· (“tech* transfer” OR “tech* adoption”) AND (“small businesses” OR “small enterprises” OR “small and medium businesses” OR “small and medium enterprises” OR “SME” OR “SMB” OR “SB”)

Searches were performed using “All fields.” In order to guarantee the most accurate search results, restrictions must be applied by considering the following filters:

1. Time span: The data was obtained on January 8, 2024, and all articles up to that date were collected

2. Type of document: Articles and reviews

3. Research area: business economics, operations research management science and public administration

4. Web of Science Categories: Business or Management

5. Language: English

The search process resulted in a dataset of 225 bibliographic references. Since the articles in this study were identified using only one database— Web of Science—refinement was not required.

As the most cited documents are the most significant ones in the topic³², articles with more than 10 citations were included. An alternative quality criterion was used for document inclusion purposes, based on the premise that top journals typically publish top quality papers. In recognition that the citation-based method may discriminate against recent publications since newly published papers do not have the time to accumulate citations^33,34, all articles appearing in one of the 17 top journals (Table 1.) from 2020 to 08/01/2024 were included.

Table 1. Top contributing journals. TP total papers, TC total cites, TCA cites per article, JIF Journal impact factor in 2002 and JCI Journal Citation indicator in 2023

Journal	TP	TC	C/A	JIF	JCI
Journal of Technology Transfer	17	357	21	4.8	1
Journal of Small Business and Enterprise Development	11	430	39.09	4.6	0.57
IEEE Transactions on Engineering Management	8	72	9	5.8	1.17
Journal of Science and Technology Policy Management	7	106	15.14	2.3	0.57
Technological Forecasting and Social Change	7	303	43.29	12	2.47
Technology Analysis & Strategic Management	7	46	6.57	3.4	0.72
Technovation	7	322	46	12.5	2.13
European Journal of Innovation Management	6	44	7.33	5.1	1.2
Journal of Small Business Management	6	186	31	6.2	1.34
International Journal of Technology Management	5	23	4.6	2.8	0.44
International Small Business Journal-Researching Entrepreneurship	4	158	39.5	7.1	1.27
Journal of Business Research	4	135	33.75	11.3	2.32
Journal of Enterprise Information Management	4	167	41.75	6.5	1.37
Journal of Manufacturing Technology Management	4	188	47	7.6	1.45
International Journal of E-Business Research	3	39	13	1.2	0.21
International Journal of Entrepreneurial Behavior	3	286	95.33	5.5	1.07
International Journal of Innovation Management	3	18	6	2.1	0.46
Internet Research	3	237	79	5.9	1.27
Journal of Asian Finance Economics and Business	3	21	7	-	0.99

Regarding the first criteria, 106 articles have more than 10 citations. In concern with the second criteria, 59 articles with less or equal to 10 citations were published in the last years (2020-08/01/2024), and of those, 36 were published in the top journals (Table 1). In total, out of the 142 (106+36) articles, 19 were excluded because they were not directly researching the topic as they were related to crowdfunding, customer satisfaction, adoption by individuals, servitization, and management.

The 123 articles analysed represent 95% of the total citations of the 225 articles found at the beginning. After analysing the 123 articles, the information was categorised into themes based on thematic similarities that were found^35,36. A primary classification has been conducted based on the subject matter, as the articles address the topics of TT or TA entirely independently, excluding a couple of exceptions that will be explained later, 37 are related to TT and 86 to TA.

RESEARCH STREAMS:

Technology Transfer:

Articles related to TT primarily focus on the transferor, and the transferring entity has been used to categorise the articles into topics and subtopics:

1. University TT and university new ventures

2. Research and technology organisations (RTOs) and public research laboratories (PRLs) TT

3. Inter-firm TT and international TT

4. Public policy and intermediary organisations

5. Miscellaneous related to TT

TT from universities to SMEs has received attention from seven research groups. They examined university-business collaborations which enhance SMEs' innovation performance³⁷, as well as enablers and barriers, including personal relationships, asset scarcity, and geographical proximity³⁸ or factors like expertise and organizational culture alignment³⁹. In this context, challenges such as the lack of sufficient knowledge and resources for intellectual property management, a critical element for open-innovation practices, were also highlighted⁴⁰. Regarding TT from universities, the role of governance models—contractual and relational—has been found to influence innovation outcomes significantly, with relational governance fostering trust that supports contractual agreements, although only the latter directly impacts innovation performance⁴¹. Furthermore, some studies broadened the university's mission to include co-creation as a response to sustainability crises⁴², while others emphasized the importance of social and geographic proximity in fostering technological advancements through localized knowledge spillovers⁴³.

Three articles explored TT through the creation of new ventures originated from universities, focusing on academic spin-offs. Four key stages in spin-off development were identified, providing a framework for policymakers and universities to enhance spin-off policies⁴⁴. Spin-offs were classified based on the status of founders and the type of knowledge transferred, which influenced whether ventures were product- or service-oriented⁴⁵. Science-based university spin-offs that went public were examined, highlighting market dynamics where university affiliation increased attractiveness but decreased acquisition likelihood⁴⁶.

Regarding RTOs, studies highlighted the necessity of tailored collaboration strategies when working with SMEs. Emphasis was placed on the need for tailor-made R&D strategies that take into account industrial environments, innovation focus and organisational structures to improve innovation and turnover^47,48. Trust and the secondment of scientists to SMEs were also identified as critical factors for successful partnerships⁴⁹. Practical insights from case studies offered solutions for overcoming collaboration obstacles in PRLs, recommending managerial tools such as roadmaps and personnel exchanges to enhance the collaboration process⁵⁰. The concentration of knowledge and the impact of TT were shown to be significantly higher within industrial districts, where spatial proximity facilitates effective knowledge exchange⁵¹. Additionally, to optimize engagement modes for TT with PRLs, a framework based on technology readiness level and demand readiness level has been proposed and validated for its effectiveness in assessing commercialization potential^52,53.

For companies as technology transferors, the studies underscored the importance of network embeddedness in R&D consortia⁵⁴ and the need of five qualities for improving TT performance⁵⁵. Additionally, the challenges in successful partnerships between SMEs and large firms were highlighted⁵⁶. Furthermore, the establishment of different types of SME networks was proposed to facilitate the commercialization of emerging technologies⁵⁷.

In international TT approaches, case studies suggested unconventional methods like pilot plants for global competitiveness, indicating that multinational companies could benefit from exploring non-traditional TT strategies⁵⁸. The practice of consecutive licensing emphasized the necessity of viewing TT as an integral part of business strategy⁵⁹. Insights into success and failure stressed the importance of comprehensive planning and evaluation for effective TT⁶⁰.

Public policy research underscored the necessity of coordinated technology and innovation policies for effective TT⁶¹. Similarly, networks required proper management to provide technological infrastructure within national innovation systems⁶². Studies highlighted public policy's role in enhancing TT performance and SME competitiveness, advocating for researcher mobility and alignment of research with industrial policies⁶³. Other research emphasized the appropriate use of technology to enhance competitiveness⁶⁴and the utilization of innovative outcomes to transform the effects of publicly funded collaborative research⁶⁵. The need to restructure government policies to support TT systems was noted, suggesting the adaptation of successful models from developed economies⁶⁶. Additionally, factors influencing TT fees pointed out the importance of strategic investments and efficient management⁶⁷. TT intermediaries ⁶⁸bridging organizations acting as intermediaries⁶⁹were shown to boost SME innovation capabilities. Furthermore, flexible infrastructures with low fixed resources were demonstrated to enhance the performance of existing TT systems⁷⁰.

In the miscellaneous section, each of the three articles addressed different topics. One analysis emphasized the significance of different knowledge linkages⁷¹. Another study highlighted the positive impact of TT sources and mechanisms on firm performance, underscoring the importance of absorptive capacity and calling for supportive government policies to overcome resource constraints⁷². Additionally, a framework for studying TT within projects was introduced⁷³.

Technology Adoption:

In the case of articles related to TA, there is a substantial body of literature that utilises various frameworks as a foundation for analysing the influence of factors on TA. Another significant segment focuses on diverse elements affecting TA, and finally, some articles delve into specific themes.

Therefore, this rationale has been employed to categorise the articles into the following topics and subtopics:

1. Frameworks used to assess the impact of factors on TA

2. Other stages in TA

3. Other specific issues related to TA

The authors employed a framework, or a combination thereof, to scrutinise the impact of various factors on TA (Table 2). Notably, the Technology-Organization-Environment and Diffusion of Innovation frameworks emerged as prominent choices, utilized either independently or in conjunction with others. Multiple authors used a multilevel perspective when selecting the factors to analyse, considering both organizational and individual level factors.

Table 2: The relationship between the analysed articles and the factors or frameworks utilised within each of them to assess their impact on TA

References	Technology-Organisation-Environment	Diffusion of Innovation	Resource-based view	Technology Acceptance Model	Social exchange Theory	Ladder adoption model	Others
74–84	x
85–89	x	x
90	x		x
91,92	x	x		x
93				x			External constructs: “reduced cost” and “efficiency and security”
89,94,95		x
96		x			x		Organisation dynamic, adoption attitude, and adoption intention
97.					x		Structure–conduct–performance paradigm
98,99			x
100			x				Organisational resilience and knowledge complexity on the performance
101							Organisational slack
102						x
103						x	They made a modification of adoption ladder
104						x
105,106							TRL
107							Theory of Planned Behaviour
108							Uniﬁed Theory of Acceptance, and Use of Technology and Uniﬁed Theory of Acceptance and Use of Technology 2
109							Upper echelon theory
110,111							Individual factors
112							Technological and organisational factors
113							Actor network theory
114							Institutional theory
115–117							Creation of new models
25,30,118–137							Multilevel perspective

Several articles were associated with the implementation stage post-adoption^138–140. Additionally, studies have considered continuing factors analyzing perspectives of adopters and non-adopters¹⁴¹. Additionally, there were articles that integrated technology transfer and adoption, analyzing both sides of the equation (vendor and customer)^142,143.

In the miscellaneous section, several articles delved into the adoption of sustainable green practices^144,145 and the impact of leveraging specific eco-inputs for enhanced TA¹⁴⁶. Additionally, research explored the impact of knowledge management stages on TA¹⁴⁷. Various authors emphasized on the dynamic capabilities^148–150 and organizational ambidexterity¹⁵¹. On the other hand, it is shown how the impact of TA on human capital varied depending on the technology's nature, gender, and cross-country factors¹⁵². Some research also focused on the COVID-19 pandemic and its impact on TA^153,154. Finally, research investigated how open innovation can aid in TA¹⁵⁵.

DISCUSSION AND RESEARCH AGENDA:

Based on the conducted analysis, research on TT and TA in SMEs has been conducted practically independently, with separate foci. In the area of TT, major research has focused mainly on investigating the transferring entity, TA, research has focused more on the relevant factors when adopting a technology. While these two research areas have evolved independently, some authors have begun to recognize the importance of considering both aspects together. Sepasgozar et all. addressed both TT and TA as two inextricably linked facets^142,143. Their approach involved a comprehensive study of both perspectives, both from the point of view of the transfer agent and the adoption agent. Other authors have also linked TT and TA; for instance, Azzone & Maccarrone highlighted the diversity of sources from which the technology in question may come⁷⁰; they argued that there is not necessarily always a specific source but that it can also be accessible knowledge. Mannan & Haleem argued that TT is necessary for TA to occur⁸⁹. Interestingly, O’Reilly & Cunningham pointed out that SMEs can adopt technology and knowledge from a variety of sources, which can include but are not limited to: suppliers, customers, competitors, consultancies, public research bodies, industrial research associations, and universities³⁸. In their works, Liu et al., although they focused on TT, also mentioned the adoption processes associated with the transfer that they analyse and the adopter entity^53,156. Pranata et al. developed the idea of the importance of both: on the one hand, the role of knowledge generators and, on the other hand, the transfer of knowledge to SMEs⁸¹.

Technology Transfer:

On the subject of TT, the scientific literature is very fragmented, reflecting the diversity of the 37 articles examined. The classification was done according to the transferor entity, and accordingly, there is future research potential within each of them.

Related to universities, Apa et al. mentioned that the main limitations identified were: (1) the research was geographically bound; (2) self-reporting of innovation performance; and (3) the short period of time under research³⁷. Accordingly, O’Reilly & Cunningham recommended research on other geographical contexts, with more extensive empirical research at the macro and micro levels, focusing on principal investigators, SMEs, and university collaborations, including support from universities and TTOs for SME-university collaborations³⁸. Garcia-Perez-de-Lema et al. pointed out that future studies should focus on differentiating SMEs' profiles, different stages of innovation projects, university status in a local or regional environment, and international institutional and socio-technical regimes⁴¹. These elements can impact the collaborative practices and success of open innovation in SMEs. Trencher et al. indicated that their study has a limited scope and both selection criteria and availability for case comparison⁴².

Delving into new ventures, Pirnay et al. said that the differences in activities, financial needs, material requirements, and growth perspectives among academic spin offs based on the status of persons and knowledge transferred are important factors to consider in future empirical research⁴⁵.

Concerning RTOs, the main limitations of both studies^47,48 were their sample size, which is 100% representative but limits complex regression analysis, and the focus on RTOs in Spain. To gain a deeper understanding of the interactions between RTO and their customers, more research was required to analyse them from the perspective of the serving firm.

As regards the interfirm TT Lin et al. affirmed that the limitations and future research could benefit from larger sample sizes and objective measures, as well as a longitudinal perspective⁵⁴. Pansiri suggested exploring the impact of partner characteristics on alliance performance in other sectors⁵⁵. This should include evaluating both successful and unsuccessful alliances to gain a deeper understanding of what leads to success or failure.

In relation to public policy, Nepelski & Piroli paper had limitations as it relies on survey data, only provides limited information about the innovation output, hinders quantifying the economic value of innovations, and oversimplifies the assessment of the innovative potential by not considering differences between radical and incremental innovations⁶⁵. The focus on marketable outcomes of research projects also favours private organisations. To improve the research, it could benefit from considering the technological relatedness and geography of the participating organisations. Mukherjee also had data limitations, and a future study through a sample survey of selected SMEs could provide a better understanding of their operations⁶⁴. The study could gather data on factors such as age, expertise, sales, import of raw materials, tools, R&D expenditure, and other service-based variables like IT professionals and advertising and marketing expenditure. An econometric analysis could examine the impact of these variables on the competitiveness of SMEs.

As for the miscellaneous section, Reidolf noted that future research should focus more on the role that reactive and weaker relationships play in knowledge networks⁷¹. Though not extensively discussed, non-human actors and wider forums like trade fairs, the internet, and so forth appear to have a unique role for rural SMEs.

Each article manifested its inherent limitations, delineating specific avenues for future inquiry. In a broader context, it can be asserted that addressing TT in SMEs more consistently and systematically is imperative to foster the growth of the body of knowledge in this domain. It is essential to delve further into distinct transferors.

Technology Adoption:

Regarding TA, there is a broad focus on studying the factors that influence TA. Upon reviewing the existing literature, it becomes apparent that, when it comes to analysing the factors influencing TA, researchers approach the subject matter from diverse angles. Some focus on organisational dynamics, others on individual-level considerations, and a subset adopts a multi-level perspective. It should be noted that the exclusive use of one approach to the detriment of the other is a limitation in itself^26,119,157. A notable gap exists, as prior studies often fall short in compiling and categorizing comprehensively all factors discussed by previous authors. Each author tends to capture only a subset of the previously identified factors.

Even if since it was first defined and mentioned, TA has had the dimension of part of a process¹⁵⁸, most studies tend to focus on the factors that influence TA without taking into consideration the different stages involved. This limitation in the approach could restrict the overall understanding of the adoption process and its relationship with the different factors involved¹⁵⁹.

The prevailing trend among authors is to treat adoption as a singular event without delving into the intricacies of the process perspective ²⁵. However, a subset of researchers has conscientiously incorporated the process dimension into their investigations. For instance, Del Aguila-Obra & Padilla-Melendez conducted a comprehensive literature review that delineated adoption into six distinct phases⁷⁴. Cimini et al, in the context of I4.0 technologies, scrutinized the level of adoption by employing a nuanced 6-point scale¹¹². Implementation, a subsequent step after adoption, has been a subject of inquiry for some authors ^{84,138,139,153}. He et al. further contribute to the discourse by analysing the subsequent decision to persist in using the technology¹⁴¹. In the realm of e-commerce, Ghobakhloo & Tang research delves into the impact of factors on both the likelihood of adoption and the post-adoption⁷⁹.

The technologies most widely examined in the studies focused on two main areas: (1) IT^{74,76–78,82,83,85,86,90,91,93,98,99,101,104,105,107–111,113,118,119,121,123,125,127,129,134,135,138,160}, as noted by the author ¹⁴² and (2) Marketing-related technologies^{79–81,85,92,94,96,102,103,115,120,122,128,132,133,136,137,139,141}.

In contrast, it is of interest to direct attention beyond IT and marketing-related topics, as demonstrated by the following authors: (1) ISO 9000 adoption⁹⁵, (2) Innovations^97,130, (3) Citizen-centred technologies¹¹⁷, (4) Technology in general^106,124,149,(5) Advanced manufacturing technologies¹²⁶, (6) I4.0 technologies^112,148,155, (7) Construction equipment^142,143 , (8) Adoption of sustainable practices¹⁴⁴, and (9) Product innovation⁸⁹.

Significantly, according to the analysis of the state of the art, most of the articles were related to mature technologies, so the TRL^161,162 was not considered by the authors. However, it is worth noting that, in the analysis, one article specifically examined drivers and barriers in relation to technology readiness¹⁰⁶. Other authors in several studies also took technology readiness into account, although they discussed its relevance in relation to TT^53,156.

Regarding territories, there were understudied regions, such as Spain, for instance. Spain was the subject of study in the following cases for TT^41,47 and in TA^{74,100,101,124}.

The studies were carried out in various sectors: (1) industrial^77,107,129, (2) manufacturing industry specifically^{79,81,83,92,103,126}, (3) services^96,97,99,124, and in some cases (4) a combination of services and industry^{74–76,85,86,90,91,122,127}, and (5) a mix of various sectors^{85,90,94,95,98,100,104,109,118,133}.

In light of the diverse challenges and opportunities present in the fields of TT and TA, new proposals for future research are collected in Table 3.

Table 3: Future research agenda

Topic	Future research
TT and TA	Analyse TT and TA as two processes that might be occurring together.
	When researching on TT consider the characteristics of the recipient entity.
	When focusing on TA explore if there is a transferor entity, reflect on their characteristics.
	Further focus on the relation between transferor and adopters.
	Elucidate the real impact of public policies and intermediary organisations.
TT	Explore the applicability of existing knowledge across diverse transferors and systematically assess its relevance.
	Consider variables such as geographic locations or industry sectors of the involved SME.
	Foster co-authorships among researchers from diverse countries and organisations to integrate greater heterogeneity in the research scope.
	Employ longitudinal perspectives when analysing TT.
TA	Adopt a more inclusive approach to gain a comprehensive understanding of the factors influencing TA in SMEs, considering technological, organisational, environmental and individual factors.
	Clarify the factors that impact TA as a stage of an ongoing process through additional inquiry and depict the entire process.
	Explore other technologies that still have untapped potential, such as I4.0 technologies or even more emergent technologies, as artificial intelligence.
	Future research may focus on TA considering the TRL, and particularly exploring lower TRL levels.
	Investigate alternative sectors that possess untapped potential, for instance: primary sector, or deepen the knowledge into sector of especial interest, as the ones selected by the Research and Innovation Strategies for Smart Specialisation.

CONCLUSIONS:

This study aims to address one primary objective: to develop a research agenda for TT and TA in SMEs. First, it has been observed that the majority of existing research treats TT and TA as separate entities, addressing them independently rather than in an integrated manner.

The exploration of TT requires researchers to delve into the applicability of existing knowledge across diverse transferors and systematically assess its relevance. Considering variables such as geographic locations or industry sectors of involved SMEs is crucial for contextualizing TT efforts effectively. Moreover, fostering co-authorships among researchers from diverse countries and organizations can enrich the research scope by integrating greater heterogeneity. Lastly, employing longitudinal perspectives when analysing TT enables a deeper understanding of its dynamics over time, thereby facilitating more informed strategies and interventions for successful TT initiatives.

Furthermore, addressing TA in SMEs requires an inclusive approach considering technological, organisational, environmental, and individual factors. It is crucial to clarify the factors influencing TA as a stage of an ongoing process. This clarity can guide policymakers and practitioners in designing targeted interventions to facilitate smoother TA journeys for SMEs. Future research should explore emerging technologies like I4.0 and artificial intelligence, to expand the scope of TA investigations and anticipate emerging trends. Subsequent investigations should also focus on lower TRLs, to shed light on the unique barriers and facilitators encountered during the early stages of TA. Alternative sectors with untapped potential should also be further explored, thereby diversifying insights into TA dynamics in SMEs. Sectors such as the primary sector, and deepening knowledge in sectors of special interest identified by Research and Innovation Strategies for Smart Specialisation, may offer avenues for exploring diverse adoption contexts and strategies.

This article expands research boundaries, equipping the next generation of academics with a research agenda in TT and TA within SMEs. These agenda may act as a catalyst for collaborative multi- and inter-disciplinary studies in the field. The suggested study directions aid in identifying and addressing crucial research problems, advancing current scientific discussions.

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Received on 28.10.2025 Revised on 17.01.2026

Accepted on 20.03.2026 Published on 24.06.2026

Available online from June 30, 2026

International Journal of Technology. 2026; 16(1):11-23.

DOI: 10.52711/2231-3915.2026.00002

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