Authors Prof. Martie-Louise Verreynne, Associate Prof. Rui Torres deÊOliveira, Prof.ÊAnne.LaureÊMention, Dr George Feast. Acknowledgment We would like to thank Dr. Tam Nguyen (statisticalÊanalysis), Dr. Leroy Machirori (systematic literature review), DrÊMonikaÊSzabo andÊSelinaÊCao, who also contributed toÊthis report. Creating value for SMEs: AÊcollaboration readiness index and tool Introduction An important recommendation from the Enablers and barriers to industry-research collaboration report (Verreynne, et al. 2021) was to better understand the collaboration readiness of businesses and researchers alike. It found that when small- to medium-sized enterprises (SMEs) collaborate with Universities and Research Institutes (URIs) in Australia, they have higher levels of innovation, are more able to deal with uncertainty (e.g., COVID-19), and are more profitable. It also showed that some types of businesses are more prepared to collaborate with universities than others. To create solutions from science that help address the most pressing economic, societal and environmental challenges facing Australia, businesses and URIs need to find Ôways of working better together and ways of reinventing and creating new industries that [grow] new jobs as wellÕ (Marshall, 2022, p. 1). SMEs have an important role to play in this process, and it is therefore necessary to understand how they mature over successive stages of collaboration, from being a non-collaborator to a regular URI-industry collaborator. In addition, while research is clear about the importance of collaborations for the sustainability of SMEs and the impact of innovations on their opportunities and growth (Di Maria, et al. 2019; Nave and Franco 2019; Wirsich, et al. 2016), we know little about how ÔreadyÕ different parties are to take part in a collaborative process. This problem is exacerbated for facilitators in technology transfer agencies, URI business development offices, and institutional funding bodies; all want to work with businesses and researchers who are prepared to engage, yetÊwithout an understanding of the knowledge asymmetries between parties, successful relationship establishment is highly uncertain (JohnstonÊandÊHugginsÊ2018). This report describes the process of developing a URI.industry collaboration readiness index that can help businesses understand appropriate engagement activities, as well as assist academics, managers, policy-makers, and facilitators to measure SMEsÕ readiness to collaborate with URI partners. ÔCollaborationÕ can come in many forms, and the collaboration readiness index aims to cover the entire spectrum from informal mechanisms (e.g., joint lectures and attending workshops) to formal agreements (e.g.,ÊR&DÊconsortia, patenting and licensing arrangements, and contract research). Building a URI collaboration readiness index DeVellisÕ (2016) approach to scale development was used to design, develop and validate a Collaboration Readiness Index (CRI) and accompanying diagnostic tool. The process involved validating literature-led survey questions with a group of experts, conducting an extended survey with Australian SMEs, and utilising advanced data analysis to create and refine the collaboration readiness levels and associated diagnostic tool. AnÊoverview of this process is provided in Figure 1. CRI development process 1 Literature review Provide an overview of: ¥ existing readiness models ¥ stages of collaboration readiness ¥ behavioural constructs to include in survey ¥ items used to test those behaviouralÊconstructs 2 Interviews with experts In-person and online interview of draft survey items to improve face validity and refine items 3 Survey Undertake CATI survey of businesses 4 Final survey items Use factor analysis to improve validity andÊreliability of scale items 5 Final scale Use regression analysis to further establishÊvalidity Use cluster analysis to confirm collaborationÊreadiness levels Figure 1: Research method Literature review (Step 1) While no index has been previously developed to assess the readiness of SMEs to collaborate with URIs, our review of the literature identified several papers from which we could draw on to develop our collaboration readiness index. These included the well-known Technology Readiness Index (Mankins 2009) and Technology Readiness Levels (TRL) (Parasuraman 2000) as well as the Commercialisation Readiness Index (ARENA 2014). In addition, we drew from collaboration models developed in other contexts, such as the automotive industry (e.g., Badillo et al. 2017) and service industries such as tourism (e.g., Yang and Ren 2021) and software (Chedid et al. 2020). The development of these existing tools guided our research design. The systematic literature review and previous research further helped to identify 16 behavioural constructs suitable to inform collaboration readiness. ExistingÊscales (questionnaires) were utilised to assess a businessÕ performance for each of these constructs. Where no questions existed, the themes of that construct were used to develop a set of questions. Interviews with experts and survey (Steps 2 and 3) Using our literature review and previous work, a survey to assess behavioural constructs was developed. We then: ¥ sought expert opinion on draft survey questions from 11 innovation and collaboration experts, including academics, facilitators, senior officials, andÊseniorÊmanagers ¥ finalised the initial survey, which comprised 52 questions about general business characteristics, collaboration, innovation, andÊfinancial performance ¥ undertook computer-aided telephone interviews (CATI), targeting a sample of 800 companies (254 responses were reached) to test the initial survey and further inform the final scale. Final survey items and final scale (Steps 4 and 5) To refine the index and reduce the survey length by omitting questions deemed less important, a three-staged analytical strategy was undertaken: 1. Explanatory factor analysis (EFA) extracted factors such as leadership capabilities. 2. The convergent and discriminant validity of each dimension/factor was tested with a CFA model to evaluate 10 factors: Teamwork orientation, risk orientation, co-creation orientation, leadership capabilities, employee capabilities, business resources andÊcapabilities, mutual trust, knowledge sharing; systemsÊandÊprocess; and outcomes. 3. Additional predictive validity tests were conducted by running regressions, analysis of variance (ANOVA), and t-tests for the ten resulting factors. The results show that teamwork orientation, employee capabilities, co-creation orientation, and mutual trust were not significantly associated with collaboration. Five factors remained after completing the analysis: (i)Êleadership capabilities, (ii) systems and processes, (iii)Êoutcomes, (iv) knowledge-sharing and (v)Êbusiness resources and capabilities. ThisÊalso led to the final survey, which consisted of 17Êquestions related to theseÊfiveÊfactors. Once the five factors were identified, we sought to understand how these inform the different levels of collaboration readiness. A cluster analysis was performed to group businesses, which led to five groups (see FigureÊ2) Ð these became the five levels of collaboration readiness. The five factors were then benchmarked across each of these levels to group businesses according to their collaboration readiness (see Figure 3). Cluster 1 Cluster 2 Cluster 3 Cluster 4 Cluster 5 Figure 2: Cluster analysis (K-means clustering) to groupÊbusinesses. Figure 3: Benchmarking each cluster level across the five factors via a radar chart. Final URI collaboration readiness index and tool The following five levels form the basis of our final Collaboration Readiness Index (Figure 4). 1. Considering: Not all businesses collaborate with URIs, and even businesses that previously collaborated, at one point, needed to decide deliberately whether to enter aÊnew collaboration. 2. Networking: Initial conversations around collaborative research are instigated and/or businesses present to students or industry placements occur. 3. Cooperating: Collaboration is in the form of coordinated partnerships, often on smaller projects, to test initial ideas/approaches. 4. Engaging: Businesses formally engage with URIs through established relationships with specific objectives. 5. Partnering: Businesses undertake URI collaborations ofÊaÊrecurrent and ongoing nature. Based on CSIRO SME Connect expert feedback, types of collaboration activities at each level have been proposed, and relevant programs and activities suggested for businesses at each level. 1 Considering 2 Networking 3 Cooperating 4 Engaging 5 Partnering Definition Acknowledge the need to collaborate for innovation purposes Identify external agents for innovation collaboration through networking activities Engage and interact with external agents to commence collaboration forÊinnovation Purposeful collaboration with external agents toÊinnovate Recurrent collaboration for innovation through partnering agreements Types of activities No active interaction or exchange. TheÊself.realisation or external recognition ofÊan emerging need. Informal, initial conversations and exchanges, such as placements or industry guest lectures. Typically, aÊone.offÊapproach. The emergence of more tangible cooperation, but focusing on discrete, specific, ad hoc initiatives of minor ambition, such as individual research student placements or third-party research. It remains embryonic and lacks systematisation. Emergence and implementation of engagement mechanisms on larger.scale (R&D) initiatives, such as contract research activities and cooperative research projects. Remains transactional but in the scale-up phase. A transformative approach to research partnerships, including joint innovation labs, co.creation of knowledge or co.patenting. Strategic intent to cooperate with long.term commitment. TheÊsystematisation of research cooperation for innovation. Figure 4: Collaboration Readiness Index Collaboration Readiness Tool Available online at collaborationreadinesstool.com, businesses will be able to complete a survey and receive a report that provides information and guidance on areas of potential focus toÊbetter engage with URIs. Each report will consist of: 1 An overall collaboration readiness score with an accompanying description of what that means for the business and engagementÊrecommendations. 2 A description of the types of collaborative activities with URIs they should consider along with relevant links and resources. 3 A further breakdown of their scores in each factor of the scale (leadership capabilities, systems and processes etc.) along withÊrecommendations. Importantly, a business can be put in one level for the overall collaboration readiness but have different scores in individual factors. For example, some businesses that are in overall CRL1 may have a similar or even higher score in the business resources and capabilities factor than those in CRL2. Therefore, recommendations are given for both the overall collaboration readiness level and the individual factors. Business characteristics at each level The tool also allows a deeper dive into the general characteristics of SMEs at each level. A complete matrix table of characteristics/levels is provided separately, and general observations from our data are outlined below (Figure 5). Figure 5: General business characteristics at each level. 1 Considering While previous collaboration experience influences leadership capabilities and systems and processes, expected outcomes and knowledge-sharing capabilities are usually low for all SMEs atÊthisÊstage. 2 Networking SMEs may expect improvements in outcomes, knowledge sharing willingness, andÊto a lesser extent, the systems and processesÊinÊplace. 3 Cooperating Business resources and capabilities and leadership capabilities become more prevalent for SMEs at this level; as businesses refine details of URI collaborations, leadership become engaged in signing agreements and defining contractÊterms. 4 Engaging Leadership capabilities and the business resources and capabilities remain stable, but knowledge sharing and systems and processes become moreÊprominent. 5 Partnering Businesses need a much higher degree of leadership capabilities than at previous levels. Strong business resources and capabilities and systems and processes are also important forÊthisÊstage. Conclusion Earlier studies, coupled with our previous work (Verreynne,Êet al. 2021), show that businesses thinking about collaborating with URIs exhibit certain characteristics. These characteristics can be grouped into five clusters which have become collaboration readiness levels. A self.assessment tool was created, which: ¥ provides information to participants on the types of collaborative activity with URIs that most suits their business at the present time. ¥ enables facilitators and granting bodies to manage the expectations of SMEs. ¥ enables SMEs to focus business developmental efforts onÊspecific areas for improvement. ¥ indicates how businesses can move through stages toÊincrease collaboration readiness. Of course, firms should carefully assess their individual circumstances in relation to collaboration with URIs before making strategic investment decisions. This data does not assess the marginal returns of an increase in readiness level on performance outputs (e.g., measured as new products, services, or increases in turnover from innovative sales), but past research shows a positive relationship between collaboration andÊinnovation outputs. It is anticipated that the tool will help build relationships between SMEs and URIs at an entry-level appropriate for the business, and by growing relationships gradually, collaborations are well set for successfulÊoutcomes. References ARENA (Australian Renewable Energy Agency) 2014. Commercial readiness index for renewable energy sectors, Commonwealth of Australia. Badillo, E.R.,ÊGalera, F.L.ÊandÊMoreno Serrano, R.Ê2017. Cooperation in R&D, firm size and type of partnership: Evidence for the Spanish automotive industry.ÊEuropean Journal of Management and Business Economics, 26(1),Ê123Ð143. Chedid, M., Carvalho, T. and Teixeira, L. 2020. 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