of the Ministry of Science and Technology, Department of Science andTechnology,documentsonhumanresourcedevelopmentofthecityandtheinternet.The research conducted questionnaires survey of
Researchrelatedtointermediariesinthescienceandtechnologymarket
Intermediaries operating within the science and technology (S&T) market haveattractedconsiderablescholarlyinterest,resultinginavarietyofconceptualframeworkssuchas
"technologycommunity,""bridgeorganization,"" O p e n innovation mediation," or
"middleman" (Rappa and Debackere, 1992; Bessant andRush, 1995; Howells, 2006;
Sapsed et al., 2007; Spithoven et al., 2011; Spithoven andKnockaert,2012).
Historically, intermediaries in the S&T market, also known as "GCs"
(GeneralContractors)i n t e c h n o l o g i c a l i n n o v a t i o n a n d d e v e l o p m e n t , c a n t r a c e t h e i r o r i g i n s t o the 'middlemen' in England's agriculture, wool, and textile industries during the 16th,17th, and 18th centuries (Hill, 1967) Later on, it is continuely studied by Farnie in1979 and Smith in 2002 These intermediaries not only engaged in commerce but alsoplayedinformalyetsignificantrolesindisseminatingknowledge,includingadvancements in agricultural techniques, fabric production methods, and processessuchasthe collection,separation,carding,andspinningof wool.
According to Akerlof (1970), intermediaries are the answer for the problem ofinformation asymmetry The problem occurs when the supply and demand sides havedifferentinformation(aboutproductsormarkets).Informationasymmetryc r e a t e s three prominentproblems:unreasonabletransactioncosts,limitedtrustb e t w e e n parties, and limited capability to transfer technology The study of Czarnitzki et al.
WatkinsandHorley(1986)contendthatintermediariesinthescienceandtechnology market play an indispensable role in identifying technology providers forentitiesseekingtechnologicalsolutions.Theseintermediariesareresponsibleforpinpointing appropriate partners to facilitate technology transactions across varioussectorswithinthetechnologyindustryandplayaroleinidentifyingpartners,technologie s, selecting technology component suppliers, and supporting technologyapplication Over time, the function of science and technology market intermediarieshastranscendedmereinformationexchange.Theynowactivelypromotetheappli cationoftechnologyintransactions,therebyassistingbothsuppliersanddemanders in achieving a comprehensive understanding of the technological productsorservicesinvolved.Thisactiveengagementensuressmooth,transparent,a n d efficie nttechnologytransactions.
Additionally, according to Dodgson and Bessant (1995), the specific scale ofresearch institutes, universities, and intermediaries within the science and technologymarket plays a crucial role in role in the innovation process, expanding the scope ofuniversity research, and promoting the commercialization of S&T research endeavors.Numerousresearchinstitutesanduniversities,particularlyinthedomainsofeconomi cs, engineering, and science, are increasingly focusing on research-orientedactivities.
Intermediaries in the science and technology market, both within and outside academic institutions, are crucial drivers of innovation They significantly influence the development, scope, and impact of research, as well as the reputation and image of schools and institutes within the scientific community These intermediaries facilitate the commercialization of scientific and technological outputs, bringing valuable research work to the market.
Furthermore, policymakers and researchers alike affirm the role of technologyintermediaries in thedevelopment oftheS & T m a r k e t I n t e r m e d i a r i e s p l a y a c r u c i a l role in innovation activities (Cooke et al., 1997; Howells, 2006), particularly for smalland medium enterprises (SMEs) or businesses within industrial clusters Additionally,the benefits of technology intermediaries in the innovation process can be consideredfrom a strategic perspective, technology intermediaries can provide strategic resourcesandorganizationfortheirpartners,suchassupportservices,businessi d e a s , knowle dge,andtrust,therebygeneratingmoreexplicitresourcesandinnovationopportunities(Hargado nandSutton,1997;KlerkxandLeeuwis,2009).
Fromadifferentperspective,McEvilyandZaheer(1999)viewtheseintermediaries as crucial nodes within information systems They not only connecttechnology suppliers and demanders but also link all organizations engaged in thescienceandtechnologymarket.Additionally,non- governmentalorganizations,researchinstitutions,andtransnationalnetworksplaycrucialroles astechnologyintermediarieswithintheS&Tdomain(MetzandTurkson,2000).
AccordingtothetechnologytransfermodelproposedbyLean(1999),intermediary organizations can emerge throughout the entire process of technologytransfer, from the stageof conceptualization to the stageofdevelopingprototypeproducts and bringing them to the market During this process, these intermediaryorganizations act as connectors between the various parties involved in the technologytransfer process The perspectives of Lean (1999) and André Spithoven & MirjamKnockaert (2012) align closely with the views of Intarakumnerd and Chaoroenporn(2013).
Science and technology market intermediaries play a critical role in national innovation systems (Bessant & Rush, 1995; Bozeman, 2000; Malerba, 2002; Howells, 2006; Sapsed et al., 2007; Nelson, 2008) These intermediaries facilitate the development and advancement of science and technology fields, which are essential for achieving national innovation goals By enabling technology transfer and driving technological progress, science and technology market intermediaries serve as pivotal tools for countries to enhance their innovation capabilities.
According to Czarnitzki et al (2001), these are also the three tasks of scienceand technology market intermediaries To overcome the cost problem, science andtechnologymarketintermediariesprovideonlineplatformsordirectplatforms(technology exchanges, technology exhibitions, etc.) to supply and demand side.
Meetandexchangeaccurateandup-to- dateinformation.Alongwiththat,scienceandtechnologymarketintermediariesalsoprep arefinancialanalyzesofthemarketvalueof products / services provided by the supplier; analysis of market trends that thedemandsideneeds;designandconsultingpackagestoensurethatthevalueoftechnology products and services on the market is appropriate for both buyers andsellers In order to increase the trust of the parties, intermediaries in the science andtechnology market ensure smooth and accurate information not only between twotransactional parties but the transparency of the whole market Finally, in order todevelop technology transfer capacities where trust has been built in and costs areappropriate, science and technology market intermediaries provide support activitiessuchascoursesonmarketresearchanddevelopmentassociatedwitht e c h n o l o g y t rends, courses on training of innovation managers, or incentives for high commercialtransactions.
Another angle when doing research, scientists perceive intermediaries in thescienceandtechnologymarketaccordingtotheservicesandproductsthattheintermediariesp rovidetotheirstakeholders.Birkenmeier(2003)studiesandconcretizesfourtasks:providinginf ormationandservicesrelatedtotechnologyapplications, market data, industry, companies, and competitors regarding existingtechnologyknowledgeandcertainfundingsources;advisingoninnovationandtechnol ogy management; supporting patent applications, licensing contracts,businessacumen,a n d h u m a n r e s o u r c e d e v e l o p m e n t ; a n d p o s s i b l y s u p p o r t i n g c o m p a n i e s i n projectmanagement Th e first t as k o f ascienceand techno logymarket intermediary according to Birkenmeier is to provide information technology or support informationtechnologyapplication.Itseemsthatorganizationsinthescienceandtechnologymar ket have been and are being very professional in using information technologyapplications such as using big data to analyze and understand the market However, inreality, duetothe limitationsof resources, humanresources and mentality, manyorganizationscannotorcannotdirectlyaccessanduseinformationtechnologyeffectively.
Science and technology market intermediaries support organizations by providing valuable data, knowledge, and consulting services They assist organizations in managing scientific and technological innovation, enhancing productivity while minimizing waste Intermediaries play a crucial role in leveraging resources and expertise to facilitate effective project management Furthermore, they ensure legal compliance by securing patents and licenses for research organizations seeking commercialization, safeguarding against technology piracy By providing comprehensive support, intermediaries empower organizations in the science and technology sector to navigate the complexities of innovation and project management.
In another aspect, Krattiger (2004) suggests that intermediaries in the R&Dmarketp l a y t h e r o l e o f a c o p y r i g h t o f f i c e , asb r o k e r s , p r o v i d i n g I P m a n a g e m e n t services(lawfirmsandconsultants).Additionally,intermediariesfunctiona scommercial agents, commercial banks, or patent development agencies Millien andLaurie (2007) also describe various types of intermediaries, including patent licensing,patent pools, technology development, licensing agents, financial companies, patentbrokers, mergers and acquisitions advisors, technology auctions, online technologyexchanges,securitizationofcopyrightrevenue,software,patentrankingservices,un iversitytechnologytransferintermediaries,aswellassomeemergingbusinessmodelsliketradin gplatforms.
Approachingfromtheperspectiveofinnovation,theOECD(2005)alsohighlightsthattheinter mediaries inthescienceandtechnologymarket havebecome more dynamic and diverse as the demand for technology transfer and patent valuationhas increased Consequently, these intermediary organizations play a crucial role ininnovationactivitiesandthedevelopmentofthescienceandtechnologymarket.
Smedlund (2005) argues that intermediaries in the R&D market play a role in:providing services in commercialization and technology brokerage, moving inventionsfromthepreparationphasetothecommercializationphase,andconnectingthedevelop ment side of an invention or new technology with potential users; connectingcompanieswiththeneedforsupplementaryexpertise,knowledge,andresources;conn ectingandsupportingjointprojectsbetweenbusinessesandresearchorganizations.
Researchrelatedtoorganizationallearningcapabilityofintermediariesinthescie nceandtechnologymarket
Organizational learning capability of intermediaries in science and technologymarket is set of activities of third parties to facilitate and process knowledge to connectdifferent stakeholders and identify suitable partners for technology transactions andtakeadvantageoftechnologicaldevelopment,variousResearchandDevelopment(R&D) activities to build learning capability It is ability to create, receive, transfer andintegrate knowledge, and at the same time, modify behavior to invent, educate, train,support, and provide and advise legal, financial, and exchange services to reflect newperceptions, with the aim of improving ability to maintain and improve organizationalperformance.
In light of the preceding definitions, organizational learning aids organizationsinthecontinualcreation,acquisition,transfer,andintegrationofknowledgeandex periences The effectiveness of organizational learning relies on the organizationalandmanagerialcomponentsthatfostertheprocessoforganizationallearning.Ac cording to Chiva, Alegre, and Lapiedra, the capability for organizational learningencompassesalltheorganizationalandmanagementpracticesthatfacilitatethelearning process.Similarly,MbengueandSanéelaborateonthis,characterizingorganizational learning as a set of management practices or mechanisms that enhanceanorganization'scapabilitytosustainandimproveperformance.Theseconceptscollect ivelyrefertoorganizationallearningcapability.
Dibella,Nevis,andGoulddefineorganizationallearningcapabilityasthemanagerial elements that facilitate the process of organizational learning or enable theorganization to learn.
Organizational learning capability plays a crucial role in fostering the learning process within an organization It encompasses the resources and skills that promote competitiveness and enable learning By implementing appropriate management practices, procedures, and structures, organizations can enhance, facilitate, and motivate learning These practices reinforce the organization's ability to continuously learn and adapt, thereby contributing to its long-term success.
According to Hsu and Fang, organizational learning capability is defined as theorganization'sability toassimilateand convertnewknowledgeinto the develop mentofnewproducts,therebygainingacompetitiveadvantageandachievinghighproductionef ficiency.Allameh,Abbasi,andShokrani'sdefinitionfocusesonorganizationallearningcapabilityast hemanagerialandorganizationalfactorscontributingt o t h e e n h a n c e m e n t o f t h e o r g a n i z a t i o n a l l e a r n i n g p r o c e s s w i t h i n t h e o rganization.Uponreviewingthevariousdefinitionsoforganizationallearningcapability,itisperceiv edasaprocessinvolvingtheacquisition,dissemination,distribution,andutilizationofknowledg e.
According to Argyris and Schon, organizational learning involves the detectionand rectification of errors, representing a comprehensive process of error investigationundertakenbyallmembersoftheorganization.Similarly,BoffandAntonellochara cterize organizational learning as a field focused on the cognitive and socialprocesses of knowledge within organizations, deeply integrated into organizational andwork practices In this context, knowledge is viewed as content, whereas learningdenotestheprocessoractivitiesthroughwhichknowledgeisacquired.
To comprehend organizational learning capability, it is imperative to grasp theessence of organizational learning Organizational learning, which gained prominenceas afocal point forresearchersand asa buzzword in the1990s, emphasizes thenecessityofoptimizingknowledgeutilizationforeffectiveo r g a n i z a t i o n a l performa nce Despite substantial scholarly interest in this area, a precise definition oforganizational learning remains elusive, with diverse interpretations existing in theliterature Most scholars perceive organizational learning as a process or series ofactivitiesevolvingovertime,intertwinedwiththeacquisitionofknowledgebyorganizational memberstoenhancedecision-makingandperformance.
Organizational learning involves the creation of knowledge, insights, and relationships between past actions, their effectiveness, and future organizational actions It encompasses the assimilation of insights and successful reconfigurations of organizational challenges by individuals, which are reflected in the organizational structure and outcomes The concept of organizational learning capabilities within intermediaries encompasses various interpretations and studies on these capabilities can be primarily categorized into three groups.
Firstly,somescholarscontendthatcompaniescancultivatethee x p e r t i s e neededtoeffectiv elymanagespecifictasksthroughdeliberate,organization-wideprocedures These companies can acquire and accumulate task-relevant knowledgethrough training(Grant,1996).Theycan alsofoster groupcohesion andtrustbyengaging in semi-structured investigative tasks through training (Clegg et al, 2005).Withinthecontextof"learningintermediaries,"companiescanstrengthentheircapabiliti esandreducetechnologicaluncertaintiesbyacquiringandleveragingknowledge from their own organization or from their partners (Grant & Bader-Fuller,1995) Lane & Lubatikin (1998) illustrate that a firm's capability to learn from anotherfirmdependsonthecompany'sstrategies,whichrepresenteffortstoaccessnewknowledge from partner firms and dynamically moderate the impact of diversity on theintermediary'slongevityandeffectiveness(Parkhe,1991).
Secondly, prior research in this area has indicated that a firm's
"absorptivecapability"representstheoverallabilityofthefirmtorecognize,assimilate,a n d expl oit new external knowledge (Cohen and Levinthal, 1990) The existing knowledgebases determine a firm's capability to learn from other firms (Lane
& Lubatkin, 1998).Implicit connections are found between technical expertise and IT capabilities, whichpositivelyimpact firmperformance (Melville et al,2004).Froma resource-basedperspective, these knowledge and skills represent scarce resources that play a criticalroleinthedevelopmentoflearningcapabilities(Szulanski,1996).Knowledgedevelopm entandlongevitycontributetoimprovedperformanceinintermediaries(Steensma&Lyles,2000).Furthermore,thelevelofexpertiseinimplementingtechnologiesandtheabilitytoeffectivelyutili zethesetechnologiessignificantlyinfluenceafirm'slearningcapabilitytocreatevalueintermsofresourc es(Zhu&Kraemer,2002).McEvily&Chakravarthy(2002)arguethattechnologicalknowledgerefl ectsthelevelofinnovativeness and competitiveness of the company, indicating that higher levels oftechnologicalknowledgepromptincreasedengagementinintermediaries.
A firm's learning capabilities evolve cumulatively, following a specific trajectory based on past investments in individual absorptive capabilities (Cohen & Levinthal, 1990) Prior learning experiences and challenges enhance the ability to learn from specific intermediaries (Anand & Khanna, 2000) Familiarity and comfort with information content and context, fostered by previous experience with a given knowledge base, facilitate knowledge acquisition (Simonnin, 1999) Distinct firm histories result in unique capabilities for executing activities in strategic intermediaries (Lane & Lubatkin, 1998).
In 1997, research demonstrated that collaborative abilities can stem from both domestic and international joint ventures Companies proficient in learning from diverse experiences will continue to enhance their capabilities at an accelerated rate, while those lacking such investment may face challenges.
Moreover, organizational learning capability acts as a driving force behind theorganization's learning process (Goh & Richards, 1997) This capability is identified astangible and intangible resources of the organization, concretized as the operationalskillsoftheorganization.Buildingorganizationallearningcapabilityisunderst oodasa way of promoting competitive advantage and allowing the organizational learning tobe enhanced (Alegre & Chiva, 2008) For Hsu and Fang (2009), the organizationallearning capability is understood as the organization's ability to acquire and transformnew knowledge and apply it to the development of new products with competitiveadvantagesandspeed.highproductionlevel.
Meanwhile, the definition of organizational learning capability often revolvesaround theorganization's ability to processknowledge, includingits capability tocreate,receive,transfer,andintegrateknowledge,therebydrivingbehavioralmodifications that lead to enhanced performance (Jerez-Gomez, Cespedes-Lorente, &Valle-Cabrera, 2005) Goh and Richards (1997) have emphasized that the tangible andintangible resources of an organization contribute to the development of its learningcapability,ultimatelybolsteringitscompetitiveadvantage.
As per Popper & Lipshitz (1998), the ultimate aim of organizational learning istoimplementnewlyacquiredknowledgeintotheorganizationalframework,ensur ingitbecomesthestandardfortheactionsandconductofitsmembers.Arobustorganizationallear ningcapabilitynotonlyfacilitatestheadaptationofexistingknowledgeb u t a l s o e n a b l e s t h e a m a l g a m a t i o n o f i n t e r n a l k n o w l e d g e w i t h e x t e r n a l insights Simultaneously, it encourages the dissemination and effective management oftheorganizationalknowledgebase(lnkpen&Dinur,1998).Theresearchhasdetermined that organizational learning capability manifests through: (1) the intent tolearn(Hamel,1991;Inkpen&Dinur,1998);(2)thecapabilityforknowledgeassimilation (Zahra & George, 2002); (3) the ability to integrate knowledge (Okhusen&Eisenhardt,2002;Teece,Pisano&Shuen,1997).
- Learning intention: The concept of organizational learning intention refers tothe perspective that companies engaged in a Technology-Related Development Project(TRDP) view problem-solving and task execution as a chance for learning right fromthe project's outset (Hamel, 1991) When a company is resolute in its commitment tolearning, it establishes a more conducive environment for learning within collaborativeresearch.
Researchrelated t o factorsaffecting or g a n i z a t i o n a l l ear ni ng ca pa
Thefiveconceptualdimensionsoforganizationallearningcapabilityareoutlined below, along with an elucidation of their connections with other conceptualcategoriesandwithorganizationallearningcapabilityitself.
Experimentation refers to the extent to which new ideas and suggestions aretakenintoconsiderationandhandledsympathetically.Itisthemostextensivelysupported dimension in the literature on organizational learning (Hedberg, 1981; Neviset al., 1995;
Tannenbaum, 1997; Weick and Westley, 1996; Goh and Richards, 1997;Pedleretal.,1997).Nevisetal.
(1995)proposethatexperimentationinvolvesthetrial of new ideas, curiosity about how things function, or the implementation of changes inwork processes It encompasses the pursuit of innovative solutions to problems, basedon the potential utilization of different methods and procedures Weick and Westley(1996) emphasize the significance, for organizational learning, of small rather thanlarge changesorexperiments.
Risk-taking is understood as the tolerance of ambiguity, uncertainty, and errors.Hedberg (1981) presents a range of activities that facilitate organizational learning,highlightingthecreationofenvironmentsthatembracerisk-takingandembracemistakes.
Embracing or taking risks involves the potential occurrence of errors andfailures Sitkin (1996) goes so far as to assert that failure is a fundamental prerequisitefor effective organizational learning, and to this end, examines the advantages anddisadvantages of success and errors If the organization seeks to promote short-termstability and performance, then success is recommended, as it tends to encourage themaintenance of the status quo According to Sitkin (1996), the benefits brought aboutby errors include risk tolerance, prompting attention to problems and the quest forsolutions,easeofproblemrecognitionandinterpretation,anddiversityinorganizational responses Since the emergence of this work, numerous authors haveemphasized the importance of risk-taking and embracing mistakes for organizations tolearn(PopperandLipshitz,2000).
Interactionwiththeexternalenvironmentisdefinedastheextentofrelationshipswiththeexternalenvir onment.Theexternalenvironmentofanorganization encompasses factors that lie beyond the organization's direct control orinfluence, including industrial agents such as competitors, as well as economic, social,monetary,andpolitical/legalsystems.
Environmental attributes play a significant role in learning, and their impact onorganizationallearninghasbeenexaminedbynumerousresearchers(BapujiandCrossan, 2004) Relations and connections with the environment hold considerableimportance,asthe organizationseeksto evolve intandemwithits ever- changingsurroundings Hedberg (1981) regards the environment as the primary catalyst behindorganizational learning More turbulent environments foster organizations with greaterneedsanddesirestolearn (PopperandLipshitz, 2000).Nevisetal.
(1995) highlight thegrowingemphasisplacedbyresearchersonobserving,openingupto,a n d engagingwiththe environmentinrecentyears(e.g.,GohandRichards,1997).
In particular, authors from the social perspective (Brown and Duguid,1991;WeickandWestley,1996)underscoretheimportanceofdialogueandcommunicatio n for organizational learning Dialogue is characterized as a sustained collective inquiryinto the processes, assumptions, and certainties that constitute everyday experience(Isaacs,1993).Schein(1993)viewsdialogueasafundamentalp r o c e s s f o r constru ctingcommonunderstanding,allowingindividualstouncoverthehiddenmeaningsofwordsinitial lybyrevealingthesehiddenmeaningsintheirowncommunication.
The conception of organizational learning as a social construction implies thecultivationofsharedunderstanding,stemmingfromasocialfoundationandinteractions among individuals (Brown and Duguid, 1991) Nevis et al (1995) arguethatlearningisaproductofspontaneousdailyinteractionsamongindividuals.Encounters with people from various areas and groups augment learning.
Similarly,GohandRichards(1997)advocateteamworkandgroupproblem-solving,withaspecific emphasis on multifunctional teams Through teamwork, knowledge can besharedanddevelopedamongteammembers(Senge,1990).
Easterby-Smith et al (2000) suggest that recent literature is transitioning awayfrom a perspective that advocates integrating dialogue for consensus-seeking purposesto one that encourages pluralism and even conflict Oswick et al (2000) argue thatauthentic dialogue fosters organizational learning by giving rise to diverse perspectivesrather than suppressing them.
When individuals or groups with varying viewpointscometogethertosolveproblemsorcollaborate,theycreateadialogiccommunity.
Participative decision-making refers to the extent of employees' influence in thedecision- makingprocess(Cottonetal.,1988).Organizationsadoptparticipativedecision-making to leverage the motivational effects of increased employee involvement, jobsatisfaction,andorganizationalcommitment(Scott- LaddandChan,2004).
Scott-LaddandChan(2004)provideevidencesuggestingthatparticipativedecision-making allows for better access to information and enhances the quality andownership of decision outcomes Parnell and Crandall (2000) also assert that sharinginformationisessentialforparticipativedecision- making.Itisassumedthatsubordinates mustbe well-informed in order to participate effectively.
Bapuji andCrossan (2004), Nevis et al (1995), Goh and Richards (1997), Pedler et al.
(1997), andScott-Ladd and Chan (2004) all consider participative decision-making as one of thekeyfactorsthatcanfacilitatelearning.
Researchgap
Inthecourseofreviewingbothdomesticandinternationalresearch,t h e majorityofstudiesperta iningtothefactorsinfluencingorganizationallearningcapabilities in general and the characteristics of intermediary organizations in the fieldofscienceandtechnologyinVietnamandgloballyhaveoverlookedthespecificorganizationallea rningcapabilitiesoftheseintermediaryorganizationswithintherealmofscienceandtechnology.
Building upon the literature review, this dissertation will assimilate relevantcontentandmethodologiesalignedwiththeresearchobjectivesandcontextualframewo rk Additionally, it will supplement areas that are currently limited or notentirely congruent with the demands of the science and technology market Throughthis approach, the dissertation aims to establish research objectives that address thesegapsintheexistingbodyofscientificandtechnologicalknowledge.
In terms of content, the literature review reveals that the organizational learningcapabilities, in general, have garnered significant attention and research from scholars,policy-makers, businesses, and individuals.
Research literature has identified groups offactors capable of influencing or enhancing the learning capabilities of organizationsunderd i f f e r e n t e n v i r o n m e n t a l c o n d i t i o n s a n d a c r o s s d i v e r s e o r g a n i z a t i o n a l c o n t e x t s
This dissertation will assimilate and inherit these factors during the literature reviewprocessforapplicationintheresearchmodel.
Concerningthefoundationaltheoreticalframework,the"theoryoforganizationallearningcapa bilities"hasbeenemployedbyscholarstoassessorganizations or individuals and construct an analytical framework to evaluate theenhancement of organizational or individual learning for organizational development.Exemplaryt h e o r i e s s u c h a s t h e B C G m a t r i x , a b s o r p t i v e c a p a b i l i t y , a n d t h e o r y o f plannedbehaviorwillbeinheritedandfurtherdevelopedbythedi ssertationt o facilitate the exploration of factors influencing the learning capabilities of intermediaryorganizationsinthescienceandtechnologydomain.
Int e r m s o f r e s e a r c h m e t h o d o l o g y , s o m e s t u d i e s r e l a t e d t o t h e d i s s e r t a t i o n ' s topicutilizequalitativeresearchmethodsthroughliteraturereviewsandin- depthinterviews,whileothersemployquantitativeresearchmethodsbysurveyingintermediary organizations and subsequently conducting regression analyses or usingStructuralEquationModeling(SEM).Thisdissertationwillinheritbothofthesemethods for its research through literature reviews, in-depth interviews, surveys oforganizations and individuals, and the application of SPSS software to measure therelationshipswithintheresearchhypotheses.
Any inadequacies in these approaches will be addressed and refined during theresearchprocess.
Through the literature review, the doctoral candidate identified certain gaps intheexistingresearchrelatedtothedissertationthatneedfurtherrefinement:
Firstly, a majority of studies have been conducted using qualitative researchmethodssuchasliteraturereviews,individualin-depthinterviews,o r g r o u p interviews.
While a few quantitative studies have been conducted, they have primarilymeasuredtheimpactofsomefactorsonthelearningcapabilityofintermediaryorganizatio nsi n v a r i o u s f i e l d s H o w e v e r , a c o m p r e h e n s i v e a n a l y s i s o f t h e f a c t o r s influencing the learning capability of intermediary organizations in the field of scienceand technology is lacking Additionally, there is a need to investigate the effects ofvariables on the learning capability of organizations in the science and technologysector.
Secondly,thereisaneedforasupplementaryandmorecomprehensiveapproach to factors related to the science and technology market in Vietnam or factorsassociatedwithintermediaryorganizationsinthefieldofscienceandtechnology.This includes factors such as clarity in the organization's mission and the ability to leadknowledge, and how these factors influence the learning capability of organizations.Theseareaspectsthatpreviousstudieshavenotadequatelyaddressedinacompreh ensive manner.
Studies on the learning abilities of intermediary organizations in the science and technology sector are scarce in Vietnam Most existing research in this field is conducted by international scholars and focuses on general aspects of the Vietnamese science and technology market or intermediary organizations Notably, there is a significant gap in research examining the factors that influence the learning capabilities of intermediary organizations in the science and technology industry, both in Vietnam and globally.
This stimulates doctoral candidates to be highly motivated to conduct more in-depth research, both theoretically and practically The research is likely to encounterchallenges since this is recognized as a relatively new topic In the course of theresearch, searching for literature and collecting data, especially in the Vietnamesemarket, which is known for its high information security and data protection, may posedifficulties.
Intermediariesinthescienceandtechnologymarket
Conceptsandcharacteristicsofintermediariesinthescienceand technologymarket
Inthecontextofcommercialactivitiesandknowledgedissemination,Hill(1967), Farnie (1979), and Smith (2002) indicate that intermediaries in the science andtechnology market, also referred to as General Contractors (GCs) in technologicalinnovation and development, have their origins in the 'middlemen' of the agriculture,wool,andtextileindustriesin16th,17th,and18thcenturyEngland.
Inthecontextofconnectingresearchorganizations,DodgsonandBessant(1995) perceive intermediaries within the science and technology sector as researchinstitutes or universities These entities significantly influence the development, scope,and impact of research, as well as the reputation and image of academic institutionswithin the scientific community By facilitating the commercialization of scientific andtechnological outputs, these intermediaries contribute valuable research works to themarket.
From a perspective as crucial nodes within information systems, McEvily andZaheer(1999)perceivetheseintermediariesasfacilitatingconnectionsnotonlybetweentech nologysuppliersanddemandersbutalsoamongallo r g a n i z a t i o n s engagedinthesciencea ndtechnologymarket.
From another perspective, intermediaries in the science and technology marketserveastheintersectionofinformationsystems,linkingnotonlythet e c h n o l o g y suppl y and demand sides but also all organizations participating in the S&T market(McEvilyandZaheer,1999).
AccordingtothetechnologytransfermodelproposedbyLean(1999),intermediary organizations can emerge at any stage of the technology transfer process,from conceptualization to the development of prototype products and their marketintroduction.T h r o u g h o u t t h i s p r o c e s s , t h e s e i n t e r m e d i a r i e s a c t a s c o n n e c t o r s a m o n g the various parties involved in technology transfer The perspectives of Lean (1999)and Spithoven and
Knockaert (2012) are closely aligned with those of
Intermediariesinthescienceandtechnologymarket,conceptualizedasconnectingorganizatio ns,aredefinedasbrokersorthirdpartiesthatfacilitatelinkages betweendiversestakeholderswithinanopensystem(Howells,2006).These"technologyinterm ediaries"areestablishedtoassistorganizationsinleveragingtechnological advancements By specializing in various Research and
Development(R&D)activitiesandrelatedfunctions,technologyintermediariesenhanceorgani zations'absorptioncapabilities.Additionally,theyaidinbuildingmarketresearchcapacitiesfor emergingtechnologiesandfacilitatetheacquisitionoftechnologies while conducting relevant R&D activities Acting as intermediaries, theseentities bridge the gap between creators or inventors and knowledge disseminators(Spithovenetal.,2011).
Science and technology (S&T) market intermediaries are regarded as "tools tobridgethegapbetweenkeyfactors"(SpithovenandKnockaert,2012).Theseintermediariesen gageinactivitiessuchastechnologytransfer,innovationmanagement,systemandmethodestabl ishment,andtheprovisionoftechnologyservicestoorganizations(SpithovenandKnockaert,20 12).ThediversityofintermediariesintheS&Tmarketincludesthosefromspecializedgovernmentage ncies,energyserviceorganizations,publicuniversities,orregionaltechnologycenters.Additionall y,S&Tmarketintermediariesencompassnon- governmentalorganizations,researchandtechnologyorganizations,andtransnationalnetwork sservingastechnologyintermediaries(MetzandTurkson,2000).
In Vietnam, intermediaries play a crucial role in fostering the science and technology market Defined under Article 43 of the Law on Technology Transfer (2017), these organizations facilitate technology-related transactions by providing a range of services, including brokerage, consulting, promotion, price evaluation, and connection services They serve as a bridge between the supply and demand sides, supporting the efficient transfer and development of technology within the country.
In conclusion, intermediaries in the science and technology market function asbrokers or third parties, bridging various stakeholders such as creators, inventors, andknowledgedisseminatorswithinanopensystem.Theseintermediariesassistorganizationsi nidentifyingsuitablepartnersfortechnologytransactionsandleveraging technological advancements They play a crucial role in facilitating variousResearchandDevelopment(R&D)activities,therebyenhancingorganizationallearning capabilities Moreover, intermediaries in the science and technology marketare integralcomponentsofthenationalinnovationsystem.
Rolesof intermediariesinthescience andtechnologymarket
Intermediaries play a crucial role in the science and technology market by connecting entities seeking technological solutions with appropriate providers They identify partners and technologies, select suppliers, and facilitate technology application Their functions have evolved beyond information exchange, as they now actively advocate for technology adoption Intermediaries help both suppliers and demanders understand technological products and services, ensuring seamless and efficient technology transactions.
Dodgson and Bessant (1995) emphasize intermediaries within the science andtechnology market, both affiliated with academic institutions and independent, playcrucialrolesascatalystsforinnovation.Theyexertsignificantinfluenceonthedevelopment, scope, and impact of research, as well as on the reputation and standingofeducationalinstitutionsandresearchcenterswithinthescientificcommunity.Moreo ver,theseintermediariesplayavitalroleinfacilitatingthecommercialexploitationofscientifica ndtechnologicaloutputs,therebyenhancingtheircontributiontothebroadermarketofresearcho utcomes.
Krattiger (2004) proposes that intermediaries within the R&D market fulfillvariousfunctions:theyactascopyrightoffices,offeringIPmanagementservicesthroughenti tieslike lawf ir ms andconsultants Moreover,these intermediaries serveascom mercialagentsakintocommercialbanksorpatentdevelopmentagencies.
Smedlund (2005) delineates three critical roles of intermediaries in science andtechnologymarkets.Firstly,intermediariesplayapivotalroleinfacilitatingthecommerciali zationofinventionsthat are still int h e d e v e l o p m e n t a l p h a s e a n d t h u s carry inherent risks These intermediaries act as bridges between inventors seekingcommercialization and potential early-stage investors Secondly, intermediaries in thescience and technology market contribute to education and training by enhancing theexpertise of technologysuppliers, thereby fostering the development of skillsandknowledgenecessaryforinnovation.Theyalsoassist technologyusersinstayingabreast of technological trends and advancements, ensuring they capitalize on newinventionsandtechnologicalresources.Thirdly,scienceandtechnologymarketintermediar iessupportresearchinstitutionsbyfacilitatingtheimplementationandsuccess of programs and projects developed jointly by business organizations andresearchentities.
Theinterestintheroleofintermediariesininnovationhassurfacedf r o m various research domains over the past two decades These include documentation ontechnology transfer and dissemination, general studies on innovation encompassing theroles and management styles of diverse organizational types, and research focusing onservicedeliveryorganizations(Howells,2006).
In conclusion, intermediaries in the science and technology market perform diverseroles that encompassfacilitating inventions, providing educationand training, supportingresearchinstitutions,andofferinglegal,financial,andexchangeservices.Theyserveasco nsultants, providing advice and support in identifying, acquiring, and leveraging intellectualproperty and technology assets Acting as intermediaries, they facilitate transactions amongmultiplepartiesinvolvedintechnologyexchanges.Intermediariesalsoactasmediators,impartially aidingorganizationsinestablishingmutuallybeneficialcollaborations.Furthermore, they function as resource providers, supplying information, infrastructure, andessential resources toparties engaged intechnological activities Science and technologymarket intermediaries are involved in copyright exploitation, such as royalty collection andserving as trading platforms, merger brokers, manufacturing brokers, or technology productsecuritizers.Theseactivitiescontributesignificantlytoenhancingorganizationallearningc apabilitiesbyenablingorganizationstogeneratenewknowledgeandintegratenewexperiences.
Classificationsofintermediariesinthe scienceandtechnologymarket
Krattiger (2004) and Millien and Laurie (2007) offer specialized perspectives onintermediaries within the science and technology market based on the services andproducts they provide These intermediaries are recognized as offering legal, financial,and exchange services, particularly as legal consultants in patent registration, patentlicensing, and commercial licensing within the science and technology sectors Theyare identifiedasintegralconsultingfirmswithinthe scientificandpublicrealms.
Building on Lopez and Vanhaverbeke's (2009) research categorizing intermediariesbased on their functions in Science and Technology (S&T), intermediary organizationscanbeclassifiedintothreedistinctgroups:Enterprises/S&Tserviceunits:Theseinclude businesses whose primary revenue is derived from S&T services,TechnologyDevelopmentCenters(TDCs),organizationsspecializinginindustrialpropertyowners hip and legal support within the S&T sector, as well as assessment,valuation,andinspectionorganizationsoperatinginboththeS&Tandfinancialsectors.Collabor ativeandsupportiveintermediaryorganizationsforS&T:Thiscategoryencompassesmainlyun iversity-basedResearchandDevelopment(R&D)centers, institutes, S&T application centers affiliated with governmental departments, otherS&Torganizations,S&Tenterprises,financialinstitutions,fundingorganizations,innova tion centers, and business incubators Connecting intermediaries or networkingorganizations: These entities serve as trading platforms, technology and equipmentexposa n d f a i r s , i n d u s t r y a s s o c i a t i o n s , a n d r e g u l a t o r y b o d i e s f a c i l i t a t i n g n e t w o r k i n g andcollaborationamongstakeholdersintheS&Tmarket.
AccordingtoAndréSpithovenandMirjamKnockaert(2012),ScienceandTechnologyInter mediaries(STIs)encompassavarietyoforganizationssucha s scienceandtechnologytradingpl atforms/centers,technologyincubators,researchconsortiums, and industry associations.
They also include profit-oriented enterprisesthatf a c i l i t a t e c o n n e c t i o n s b e t w e e n t e c h n o l o g y s u p p l i e r s ( u n i v e r s i t i e s , r e s e a r c h institutes,publicresearchorganizations,non- profitorganizations/companies)andtechnologydemanders(enterprises).
Frank Tietze and Cornelius Herstatt (2010), adopting a market-oriented perspectiveon technology transfer and innovation, view technology transfer intermediaries in thescience and technology sector as entities or agencies acting as brokers or agents Theseintermediaries aim to facilitate and support connections between technology suppliers,providers of research and development services, and users seeking technology andR&D services They are actively involved throughout the entire process, from theresearch and development of products to their supply and sale in the market, as well asintheinnovationandimprovementof subsequentproductiterations.
Within the framework of science and technology legislation in Vietnam, intermediaries inthescienceandtechnologymarketaredefinedthroughsixdistinctforms:TechnologyExchange, Technology Transaction Center, Center for promoting and supporting technologytransferactivities,IntellectualPropertyValuationSupportCenter,Centerforinnovation support,and TechnologyIncubatororScienceandTechnology BusinessIncubator.
As per the provisions of the Law on Technology Transfer (2017), Article 43outlines that intermediaries within the science and technology market are defined asorganizationsofferingbrokerageservices,consultancy,promotionoftechnologytransfer,ev aluation,pricingappraisal,technologyassessment,andfacilitatingconnections.Theseintermed iariesassistthesupplyside,demandside,ando t h e r partiesinvolvedintransactionsrelatedtotec hnology.
The Technology Transfer Law defines the role of intermediaries in the science and technology market into two main categories: (1) organizations that provide brokerage, consulting, technology transfer promotion, evaluation, pricing appraisal, and technology assessment services; and (2) organizations that provide connection services to support various parties involved in technology-related transactions These services include technology research and development support, technology commercialization, intellectual property management, standards and quality assurance, investment consulting, trade promotion, startup and business incubation support, assistance for small and medium enterprises, cooperative alliances, and professional associations.
Organizationall e a r n i n g c a p a b i l i t y o f i n t e r m e d i a r i e s i n t h
Conceptsoforganizationallearningcapabilityofintermediariesinthesciencea ndtechnologymarket
A literature review of organizational learning capability delves into the variousdimensions,definitions,andimplicationsofthisconceptwithinthecontextoforganizati onal studies Scholars have extensively examined the role of organizationallearningcapabilityinfosteringinnovation,improvingperformance,andensurin gcompetitivenessindynamicandevolvingenvironments.Thefollowingreviewprovidesanove rviewofthekeythemesandfindingsinthisarea.
Organizational learning capability, as elucidated by Goh and Richards (1997),serves as a pivotal driver in advancing the organization's learning progression Thisconcept encapsulates both the tangible and intangible resources of the organization,reflectingitsoperationalcompetenciesandskills.
Jerez-Gomez,Cespedes-Lorente,andValle- Cabrera(2005)characterizeorganizationallearningcapabilityastheabilityofanorganizationto manageknowledge,whichincludescreating,receiving,transferring,andintegratingknowledge Thiscapabilityalsoinvolvesadaptingbehaviorstoincorporatenewperspectiveswiththeultima tegoalofenhancingorganizationalperformance.Organizational learning capability is constituted by the organization's tangible andintangible resources, reflected in its operational competencies and skills.
Developingthisc a p a b i l i t y i s s e e n a s a s t r a t e g y toc u l t i v a t e c o m p e t i t i v e advantagea n d boost organizational learning (Alegre & Chiva, 2008) According to Hsu and Fang (2009),organizational learning capability is the proficiency of an organization to acquire andtransform new knowledge, effectively applying it to the development of innovativeproductsthatoffercompetitive advantagesandincreasedproductionefficiency.
Regardingorganizationallearningcapability,Tohidi,Seyedaliakbar,andMandegari(2012)identif yitasthemanagementcharacteristicsthatfacilitatetheorganization's learning process Similarly, Chiva, Alegre, and Lapiedra (2007) defineorganizational learning capability as encompassing all management and operationalcompetencies that enhance the learning process within the organization.
According toMbengueandSané(2013),itisthecombinationofmanagementpracticest h a t facilitatethele arningprocessandestablishmechanismstosustainandimproveorganizationalperformance.
Organizations are advised to implement mechanisms and practices that promoteknowledgegeneration,leveragingbothsocialandendogenousresourceswhilefostering an environment conducive to capability building (Mbengue & Sané, 2013).These mechanisms are central to the concept of organizational learning capability,which is defined as a collection of activities that streamline the learning process or as asetofmechanismsthatbolsterorganizationalfunctioning,therebyenhancingcapabilities and overall performance (Alegre & Chiva, 2008; Mbengue & Sané,
Organizations should establish mechanisms to foster knowledge creation, leveraging both internal and external resources (Mbengue & Sané, 2013) These mechanisms facilitate the learning process, encompassing actions that enhance the organization's ability to learn and support its operations (Alegre & Chiva, 2008; Mbengue & Sané, 2013) By supporting capability development within a conducive environment, organizations empower themselves to improve their overall performance.
Inconclusion,organizationallearningcapabilitycanbecharacterizedasacollection of activities that facilitate the acquisition, processing, and management ofknowledge This encompasses the organization's ability to create, receive, transfer,andintegrateknowledge,whilesimultaneouslyadaptingbehaviorstoincorporatenewinsights,ultimate lyaimedatenhancingandsustainingorganizationalperformance.
Rolesoforganizationallearningcapabilityofintermediariesinthesci enceandtechnologymarket
Von Glinow (1999), is the ability to create and disseminate impactful ideas acrossvariousorganizationalboundariesthroughspecificmanagementstrategiesandpractices.
Yeung et al (1999) conceptualize organizational learning capability as aproductratherthanasum,representingitasthemultiplicationofthea b i l i t y t o generateidea sandthecapacitytogeneralizetheseideaswithsignificance.Thisapproachoffersanuancedpersp ectiveonanorganization'slearningenvironment.Within organizations, "learning" extends beyond individual knowledge acquisition toencompassthetransferofknowledgetootherindividuals,units,andfunctions.Consequently, three fundamental aspects are central to organizational learning: (i) ideageneration, (ii) idea generalization, and (iii) the identification of learning impediments,such as barriers to idea generation and generalization Furthermore, organizationallearning is characterized by six dimensions: (i) the location of learning, whether itoccurs within or across organizational boundaries; (ii) the agents of learning, whetherindividuals or teams; (iii) the timing of learning, whether directed toward mastery or asan ongoing process; (iv) the focus of learning, which can be on improving existingprocesses or inventing new ones; (v) the method of learning, including learning styles;and(vi)the purpose oflearning,whetherdrivenbystrategicoroperationalobjectives.
The process of idea generation refers to the organization's ability to originateideas through various learning approaches, including acquisition, discovery, invention,and sourcing Yeung et al.
(1999) categorize basic learning styles into four groups,based on two fundamental dimensions: learning from direct experience versus learningfrom others' experiences, and learning through exploration (experimenting with newcompetencies,technologies,andparadigms)versusexploitation(refininga n d extending existing competencies, technologies, and paradigms) Managers generateideas through four primary methods: (i) experimentation, involving the trial of newproductsandprocesses(directexperienceandexploration);
(ii)continuousimprovement,enhancingpreviouspracticesandmasteringeachstepb e f o r e pr ogressing(directexperienceandexploitation);
(iii)knowledgeacquisition,consistentlyacquiringnewknowledge(learningfromothers'experi encesandexploration);and(iv)benchmarking,studyingandadaptingothers't e c h n i q u e s (l earningfromothers'experiencesandexploitation).
The generalization of ideas pertains to the ability to disseminate and share ideasacrossvariousorganizationalboundaries.Learningisfeasiblewhenideasaretransmittedove rtime,physicalspace,and/ortheorganizationalhierarchy.
- Homogeneity:Restrictioninthevarietyofinformationandperspectives,limitingthe organization'sunderstanding.
- Superstitious Learning: Misinterpretation of experiences due to reliance onlimiteddataorirrationalbeliefs.
- DiffusionDeficiency: Failure tod i s s e m i n a t e i n f o r m a t i o n e f f e c t i v e l y a c r o s s theorganizationduetopoliticalpowerdynamics,rigidstructures,andsilos.
Theseinsightsunderscoretheimportanceoffosteringane n v i r o n m e n t conducive to both the generation and dissemination of knowledge, thereby enhancingorganizationallearningcapabilitiesandoverallperformance.
Overall,theliteraturereviewunderscoresthe criticalroleoforganizationallearningcapabilityinfosteringinnovation,knowledgecreation,a n d a d a p t i v e behaviors within organizations, ultimately contributing to their sustained performanceandcompetitivenessinarapidlychangingbusinesslandscape.
Componentso f o r g a n i z a t i o n a l l e a r n i n g c a p a b i l i t y o f i n t e r m e d i a
Studiesontheorganizationallearningcapabilitiesofintermediariescanbecategorized into three primary groups Firstly, some scholars argue that companies candevelop the expertise needed to effectively manage specific tasks through deliberate,organization-wideprocedures.Thesecompaniescanacquireandaccumulatetask-relevant knowledge through training (Grant, 1996), fostering group cohesion and trustby engaginginsemi-structured investigative tasks (Clegg et al., 2005).I n t h e c o n t e x t of" l e a r n i n g i n t e r m e d i a r i e s , " c o m p a n i e s c a n e n h a n c e t h e i r c a p a b i l i t i e s a n d m i t i g a t e technological uncertainties by acquiring and leveraging knowledge from their ownorganization or their partners (Grant & Bader-Fuller, 1995) Lane & Lubatkin (1998)demonstrate that a firm's ability to learn from another firm depends on its strategies,which involve efforts to access new knowledge from partner firms and dynamicallymoderate the impact of diversity on the intermediary's longevity and effectiveness(Parkhe,1991).
Secondly,priorresearchhasindicatedthatafirm's"absorptivecapability"representsitsoveralla bilitytorecognize,assimilate,andexploitnewexternalknowledge (Cohen & Levinthal,
1990) The existing knowledge bases determine afirm'scapacitytolearnfromotherfirms(Lane&Lubatkin,1998).I m p l i c i t connections exist between technical expertise and IT capabilities, which positivelyimpact firm performance (Melville et al., 2004) From a resource-based perspective,theseknowledgeandskillsarescarceresourcescrucialfordevelopinglearningcapa bilities (Szulanski, 1996) Knowledge development and longevity contribute toimproved performance in intermediaries (Steensma & Lyles, 2000) Furthermore, thelevel of expertise in implementing technologies and the ability to effectively utilizethese technologies significantly influence a firm's learning capability to create value interms ofresources (Zhu &Kraemer,2002).McEvily &C h a k r a v a r t h y ( 2 0 0 2 ) a r g u e thattechnologicalknowledgereflectsthecompany'slevelofinnovativenessandcompe titiveness,indicatingthathigherlevelsoftechnologicalknowledgepromptincreasedengageme ntinintermediaries.
Organizations' learning abilities accumulate, following a specific trajectory, and build on past investments in their members' individual absorptive capabilities (Cohen & Levinthal, 1990) Prior learning experiences enhance the ability to learn from specific intermediaries (Anand & Khanna, 2000) Familiarity with a knowledge base facilitates the acquisition of new knowledge (Simonnin, 1999) Unique firm histories result in distinct capabilities for executing activities in strategic intermediaries (Lane & Lubatkin, 1998).
(1997) illustratethatthe ability tocollaboratecanbe acquirednot only from prior international joint ventures but also from previous domestic jointventures Firms that have cultivated the ability to learn will continue to do so at anaccelerated pace, whereas firms that have never invested in learning from diverseexperienceswillencounterdifficulties(Cohen&Levinthal,1990).
According to Popper and Lipshitz (1998), the ultimate aim of organizationallearning is to embed newly acquired knowledge into the organizational framework,thereby standardizing the actions and behavior of its members A robust organizationallearning capability not only facilitates the adaptation of existing knowledge but alsointegrates internal knowledge with external insights.
This capability further promotesthe dissemination and effective management of the organizational knowledge base(Inkpen & Dinur, 1998) Research identifies that organizational learning capabilitymanifests through: (1) the intention to learn (Hamel, 1991; Inkpen & Dinur, 1998); (2)the capacity for knowledge assimilation (Zahra &
George, 2002); and (3) the ability tointegrateknowledge
(Okhusen&Eisenhardt,2002;Teece,Pisano&Shuen,1997).
- Learning Intention: The concept of organizational learning intention suggeststhatcompaniesinvolvedinTechnology-
RelatedDevelopmentProjects(TRDPs)perceiveproblem- solvingandtaskexecutionaslearningopportunitiesfromtheproject's outset (Hamel, 1991) When a company is committed to learning, it fosters anenvironmentconducivetolearningwithincollaborative research.
- Absorption Capability: Absorption capability refers to a company's ability torecognizetheimportanceofnewknowledge,acquirefreshinformation,a n d incorporateittoe stablishandretainorganizationalknowledge(Szulanski,1996).Typically, when a company invests in a specific technology, its absorption capability(Helfat,1997)helpsdistinguish,clarify,andstimulatethecoretechnologyandknowle dge of its research partners This capability also determines how the companyapplies,integrates,andoptimizesitsfundamentalskills(Zahra&George,2002).
- Knowledge Integration Capability: The concept of organizational knowledgeasanamalgamationofinformationdivergesfromfocusingsolelyonanalyzingkn owledgeatspecificstages.Dynamiccapabilityscholars(Blyler&C o f f , 2 0 0 3 ; Teeceetal ,1997)emphasizethatthecapabilitytointegrateknowledgeassistsorganizations in enhancing their performance in knowledge creation In this study, thegoal of knowledge integration is to enable the effective utilization of knowledge withinorganizations,therebyimprovingtechnologicalknowledgetransferincompaniesengaged inTRDPs(Popper&Lipshitz,1998).
Each company operates with distinct motives within the intermediary context,such as enhancing competitive positioning, bolstering market power, and acquiringknowledge and skills from partners (Kogut, 1988) These company-specific objectivesareformulatedbasedonsuchmotives,withtheattainmentoftheseobjectivesdependin go n s e v e r a l f a c t o r s T h e s e f a c t o r s i n c l u d e t h e c o m p a n y ' s e f f i c a c y i n facilitating organizational learning (Parkhe, 1991), its capacity to improve as a partnerover time to enhance value creation for partner firms (Anand & Khanna, 2000), and itsabilitytodevelop"absorptivecapability"tostreamlineorganizationalchallenges,accelerate capability development, and mitigate technological uncertainties (Lane &Lubatkin, 1998) This study hypothesizes a positive association between a company'sstrategicintermediaryobjectivesanditslearningcapabilities.Specifically,theavaila bility of training, technical expertise, and intermediary experience is posited toincrease thelikelihoodofachievingthecompany'sintermediaryobjectives.
According to Dao Thi Thanh Lam, Nguyen Anh Loi, Nguyen Thi Anh Tho,TranCamTu(2020),anintermediaryinthescienceandtechnologymarketisrecognized in two main groups of competencies, which are static and competencymoving.Staticcapabilityincludesfacilities,andoperatingcapability.Dynamicco mpetencies includeself-organizing capacities, flexible capability in strategy andlearningcapability.Amongtheabovecompetencies,thelearningcapabilityisconsideredtop layanimportantrole.
In conclusion, there are 3 groups of factors that affect the learning capability ofscience and technology intermediaries The first group of factors is the structure of theorganization.
Factors influencing organizational knowledge sharing include organizational standards, complexity, authority distribution, management level, division distribution, and personnel professionalism The organizational culture also plays a role, with factors such as control-oriented, market-oriented, role-centered, and mission-focused cultures influencing knowledge sharing Additionally, knowledge sharing capabilities involve the ability to explore, exchange, and create knowledge.
Experiencesenhancingorganizationallearningcapabilityofintermediariesinthe scienceandtechnologymarket
In China, the advancement of Science and Technology (S&T) has emerged as acrucial element within the national development strategy and various other initiatives.However,the transfer of S&T achievements has long been identified as a weak link inChina's national innovation system Accelerating the dissemination of knowledge andtechnology transfer has become imperative, necessitating active participation from thegovernment,universities,researchinstitutions,andintermediaries(MiesingandTan g,
2018) The expansion of S&T intermediary services aimed at bolstering agriculture,industry,andtheknowledgebasehasplayedasignificantroleinpropellingthemoderniz ationprocess,strengtheningthenation'scapabilities,andenhancingtheoverall quality of the industry in China (Liu, 2017) As reported by Miesing and Tang(2018),theoperationalframeworkoftechnologytransferorganizationsinChinatypicallyc omprisesanAdministrationdepartment,aConsultingdepartment,anInformation department, a Marketing department, a Human resources department, andconceivablyadditionaldivisions.Thesetechnologytransferorganizationsmayb e eitherre gion-specificorfocusedonparticularsectors.
Chinahasdemonstratedakeeninterestinestablishingac o m p r e h e n s i v e network of intermediaries and facilitators aimed at fostering connections and bridgingthe gap between supply and demand This network encompasses both non- commercialstateOrganizationsandunitsaffiliatedwithprofessionalorganizationsandassociat ions,aswellasprivateenterprises.TheprivateO r g a n i z a t i o n s , e i t h e r associated with professional organizations or functioning independently, adopt self- accountingmethodsandreceivegovernmentsupportandtaxincentives.
State-owned non-commercial Organizations functioning as intermediaries andbrokersinthedomainoftechnologytransfercomprisevariousbodiessuchasinformationcent ers,consultingfirms,traininginstitutions,technologytransferagencies,technologyexchanges,and capabilitydevelopmentcenters.TheseOrganizations operatewith diverse market penetration strategies,adoptingn o n - p r o f i t or partially self-accounting models,and are financially supportedby thestate forregular operational expenses and specific activities outlined in the approved annualplan.Revenuesgeneratedfromservicesaretypicallyreinvestedindevelopmentalinitiatives, staff remuneration, and other pertinent expenditures Notably, these unitsreceive substantialinfrastructureinvestmentsfromthe state.
Atpresent,Chinaboastsanextensivenetworkcomprisinga p p r o x i m a t e l y 60,000inform ationcenters,consultingfirms,andtechnologytransferbrokers,employing over 1.2 million personnel who are dedicated to facilitating the connectionbetween scientific and technological organizations and enterprises It is pertinent tonotethattheseintermediariesandbrokersundergorigoroustrainingandskilldevelopmentprog ramsunderthe auspicesoftheChinesegovernment.
In a parallel pursuit, Vietnam, in its endeavor to foster the growth of the scienceand technology(S&T) market and enhance the efficacy of S&T intermediaries,shouldpersisti n i t s s t r a t e g i c i n v e s t m e n t s i n c r i t i c a l i n f r a s t r u c t u r e T h i s i n i t i a t i v e s h o u l d b e complemented by sustained financial support in the form of directed funding for non- commercial Organizations Furthermore, an emphasis must be placed on bolstering thecomprehensive trainingof human resourcestaskedwith carryingout intermediaryfunctions,thuseffectivelybridgingthegapbetweenS&Torganizationsa n d enterpri ses.
In Belgium, technology intermediaries are represented by collective researchcenters, which secure funding from both public and private sectors Initially institutedtostimulatescienceandtechnology(S&T)researchindomainscharacterizedbyrelatively low technological intensity, these research centers were designed to enhanceproductivity,quality,andmanufacturingcapability.
These centers are engaged in a spectrum of key activities, including but notlimited to: (i) conducting tests, analyses, and investigations; (ii) providing consultancyservices and facilitating technology transfer; (iii) establishing technical informationsystems; (iv) contributing to standardization and certification efforts; (v) monitoringtechnological advancements; and (vi) delivering educational programs and trainingsessions,a l l i n a c c o r d a n c e w i t h t h e g u i d e l i n e s d e l i n e a t e d i n t h e F r a s c a t i M a n u a l , published bytheOrganisationforEconomicCo-operation andDevelopment(OECD).
Spithoven and Knockaert's (2012) research revealed that collective researchcentersserveastheexclusiveagentswithintheinnovationframework,activelyparticipa tinginbothresearchanddevelopment(R&D)initiativesasw e l l a s technology transfer operations This involvement is contingent upon the scale of theinstitution,itsallocatedR&Dbudget,andthenumberofmembers,allaimedatbolstering the technology absorption capabilities of the affiliated Organizations Thesecenters are primarily engrossed in collaborative R&D ventures, collaborating closelywith theirmember organizations, thereby facilitating thep r o v i s i o n o f a d i v e r s e a r r a y of technology transfer services.The data put forth by Spithoven and Knockaert(2012)underscored the significant role played by a total of 12 collective research centers inBelgium,servingaspivotaltechnologyintermediariesacrossvariousindustrialdomains,encompassing industries such as woodworking, ceramics, machinery,sugarprocessing,transportation,construction,cementproduction,textiles,diamondprocessin g,painting,metallurgy,welding,andpackaging.Thesesectorsweretraditionallycharacterizedb ylimitedinvolvementinresearchanddevelopmentpursuits.C o m p a n i e s o p e r a t i n g w i t h i n t h e a f o r e m e n t i o n e d s e c t o r s a r e m a n d a t e d t o becomemembersofthesecenters.Ontheotherhand,firmswithinalternativeindustriesarenotobl igedtojointhecollectiveresearchcenters.A l t h o u g h t h e s e centersareestablishedbasedo nindustry-driveninitiatives,theyarecapableofsoliciting financial backing for specific projects, thus emphasizing the existence of arobust public-private partnership underpinning the sustenance and progression of thesecenters Over their extensive history, these collective research centers in Belgium havedemonstrated their adaptability in responseto thee v o l v i n g l a n d s c a p e o f t e c h n o l o g y andbusinessmodels.
Hence, drawing insights from the Belgian context, it is imperative for countrieslike Vietnam to establish collective research centers tailored to specific professionalsectors, particularly those housing numerous small and medium enterprises Such aninitiative would enable the concentrated allocation of resources to stimulate scientificandtechnologicalresearchactivitieswhilefacilitatingtheseamlessexchangeandtransfer ofscientificknowledgeandtechnology,therebyfosteringenhancedproductivity,qualityenhanc ement,anda bolsteredcompetitive edgeforenterprises.
Int h e c o n t e x t o f t h e h i g h l y f r a g m e n t e d U S t e c h n o l o g y m a r k e t d u r i n g i t s nascent stages, the development of technology intermediaries is observable throughvariousmeans.IntheUnitedStates,thetraditionoftechnologytradeshowshaspersistedandisw idelyorganizedacrossdifferentstates.Notably,theConsumerElectronicsShow(CES),establis hedin1967bytheConsumerT e c h n o l o g y Association (CTA), stands out as one of the largest technology exhibitions, not solelywithin the United States but also extensively open to participation from the globaltechnologycommunity.CESservesasaplatformforshowcasingtechnologicaldemonstr ations and innovations linked to consumer electronic products With a historyspanning over 60 years, CES has garnered significant attention, attracting key industryplayerstounveilthelatestadvancementswithinthe contemporarytechnologymarket.
Furthermore, various technology exhibitions in the United States have directedtheirfocustowardspecificsectors,suchastheHIMSS,concentratingontheapplication of information technology in healthcare, and the OTC fairs that encompassseminars and exhibits tailored to the oil and gas industry In parallel, an array of othersmallandmediumtechnologyeventsarealsowidespreadthroughouttheU n i t e d States.
States revolves around defining the notion of 'transaction value', as highlighted byShailesh P Sheth (2013) According to Sheth, the transaction value comprises any sumthat the purchaser is obligated to pay during the procurement of goods Consequently,the establishment of a vibrant technology market holds significant sway in determiningthe valueof a technology transaction.
Evidently,marketd y n a m i c s p l a y a p i v o t a l r o l e in this context Presently, most contemporary research emphasizes valuing technologybased on methodologies grounded in cost-based, market-based, and cash-flow- basedapproaches.Severalscholarsadvocatethattransactionvaluationrepresentsthesubsequen tphasesubsequenttotheinitialestimationoftechnologyworth.
In the United States, the advancement of technology intermediaries has significantly streamlined the registration and integration of technology products into transactions These intermediaries, such as copyright lawyers and copyright brokers, provide expertise and assistance, resulting in a more efficient process for businesses seeking to protect and utilize technology-related assets.
Presently, the valuation of transactions is contingent upon thejoint efforts of the seller and the broker in promoting and introducing the technology,alongsidethebuyer'scapabilitytoeffectivelyleveragethechosentechnology.Typic allyshroudedinsecrecybetweeninvolvedparties,covert,proprietarytechnologies are meticulously appraised prior to finalization and subsequent publicrelease Owing to this inherent characteristic, technology transactions unfold over anextended timeframe, meticulously governed by specific terms agreed upon among theparticipatingOrganizations.
Anoveltrendcurrentlysurfacinginthetechnologymarketinvolvesthedetermination of certain technology transaction values through public patent auctions.Although initially inaugurated in San Francisco in 2006, technology auctions haverapidly gained traction and expanded not only within the United States but also acrossother regions including
Researchdesign
Researchcontent
Thestudyisprimarilydrivenbysecondarydataanalysistoexaminetheinfluencingfactors onorganizationallearningcapabilityofintermediariesinthescienceandtechnologymarketinVi etnam.Theresearchc o m m e n c e s b y systematicallyorganizingtheliteraturereview,enco mpassingbothdomesticandinternationalsources,toidentifytheoreticalmodels,appliedmetrics,e m e r g i n g research trends, research methods, and data collection techniques This initial phaseaimstodiscoveranddelineatethescopeofthestudy.
- Investigating the metrics and innovative research methodologies applied inpriorstudies,emphasizingrecentadvancementsinthefield.
- Extracting relevant information from the literature review to construct thetheoreticalfoundationforthestudy.
Throughsynthesizingtextualinformationandtheoreticalfoundations,theresearchfram eworkisdeveloped,adjustingtocontemporaryperspectiveso n behavioral factors influencing organizational learning capability of intermediaries inthescienceandtechnologymarket inVietnam.
The preliminary research phase involves demonstrating the relevance of thestudythroughvariousresearchactivitiesthatarebothcomprehensiveandmethodologically sound for its objectives In the initial stages, toe n s u r e c o h e r e n c e with the topic and appropriateness of the research content, the author conducted ananalysiso f t h e o r e t i c a l f r a m e w o r k s a n d r e s e a r c h m o d e l s , s u b s e q u e n t l y f o r m u l a t i n g a research model suitable for the doctoral thesis Additionally, to ensure alignment withtheVietnamesecontextoftheresearchtopic,theauthorconsultedexpertsfromuniversities and businesses specializing in relevant science and technology fields.
The preliminary survey questionnaire, conducted by the author, was deployedwith input from experts to refine the first round of survey questions This collaborativeeffort aimed to clarify the content and questions, ensuring accurate responses andavoidingredundancyordifficultyforrespondentsduringthesurveyprocess.Supplementary questionswereaddedtoaddressanymissingobservations,andadjustmentsweremade toensuretherelevance ofvariablesfortheauthor'sresearch.
Subsequently, the author implemented the second round of the survey with asample size of 100 individuals After receiving feedback from experts and surveyparticipants and obtaining preliminary survey data, the author further adjusted thequestionnaireforthesecondround,aimingtoenhancethesurvey'sclarityandpresentation.
Upon completing the preliminary survey and adjusting it through feedback, themain survey instrument was directed towards individuals The selection method for thesurveymodel,alongwiththedatadescribingtherelevantsurveymodel,willbepresentedinthefollo wingsection.Furthermore,thesurveydatawillundergoprocessingforcleaningandwillbesubjec tedtoanalysis.
To ensure comprehensive and updated life information, statistical informationrelatedt o v a r i a b l e s a n d a s u m m a r y o f t h e r e s u l t s , i n c l u d i n g b o t h d e s c r i p t i v e a n d inferential statistics, will be detailed The research employs the Partial Least SquaresStructural Equation Modeling (PLS-SEM) to calculate the impact of individual factorson organizational learning capability of intermediaries in the science and technologymarket in Vietnam The primary goal of the structural equation model(SEM) is toidentify and analyze complex relationships among observed and latent variables in aresearch model This is a statistical analysis method used to test theoretical consistencyand the strength of relationships between variables in a research model PLS-SEM iscommonlyusedinvariousresearchcontextstounderstandrelationshipsbetweenvariables and develop predictive models for decision-making purposes In the model,individual factors will be validated for reliability and model fit using measures such asCronbach'sAlpha,OuterLoading,AverageVarianceExtracted(AVE),anddeviatio n fromthediagonaltotestthediscriminantvalidityof HITMT.
To assess multicollinearity among observed variables, the Variance Inflation Factor (VIF) will be calculated and compared Bootstrapping, with 300 replications, will ensure model robustness and serve as a pivotal method to revalidate the model This technique aids in confirming hypotheses and determining the direct and indirect effects of organizational learning capabilities.
Based on the results of this research model, the findings will be combined withqualitative research to provide a deeper understanding and offer recommendations forimplementation.
ResearchApproach
Theq u a l i t a t i v e r e s e a r c h a p p r o a c h i s a m e t h o d o l o g i c a l f r a m e w o r k u t i l i z e d f o r the exploration and analysis of data typically based on language and behavior Its aimist o c o m p r e h e n s i v e l y u n d e r s t a n d t h e m e a n i n g s , c h a r a c t e r i s t i c s , a n d r e l a t i o n s h i p s o f the phenomena under study This approach finds application across various disciplinessuchassociology,psychology,education,andmarketresearch.
Purpose: The qualitative research approach provides profound insights into thethoughts,emotions,andbehaviorsofindividualsinvolved.Itdelvesintodetailedexplorationof causes,relationships, and previouslyu n k n o w n o r u n c l e a r o u t c o m e s Thisapproachsuppliesinformationcrucialforpolicymakerstomakeinformed decisionsbasedonpracticalandcontextualinsightsfromrelevantstakeholders.Consequently,t hismethodcontributestotheproductionofhigh-qualityresearchoutcomes that positively influence the development and implementation of effectivepoliciesinthefieldof scienceandtechnologyinVietnam.
- To comprehend the learning capacity and current status of intermediary organizationsinthefieldofscience andtechnologyinVietnam.
- Toevaluatethecurrentconditions,advantages,disadvantages,andunderlyingcausesofli mitationsinthislearningcapacityandproposeimprovementstrategies.
- Whatarethemost significant factors influencing thelearning capacity oftheseintermediaryorganizations?
- Whatare t h e s t r e n g t h s and wea knes sesi n t h e i r lea rn in gca pac it y?
- Whatmeas ur es areneeded toi m p r o v e t he learningcapacity o f i n t e r m ed i a r y organizationsinthefieldofscienceandtechnology?
Data Collection Method: Conduct face-to-face interviews, each lasting between45to60minutes.
DataHandlingandAnalysis:Utilizecontentanalysistoidentifyt h e m e s , models,andtrendsf rominterviewdata.Integrateinterviewdatawithe x i s t i n g research,reports,andstatisticstoe nhancethe accuracyandreliabilityoftheanalysis.
The quantitative research approach is a scientific method employing statisticaltechniques,mathematics,orcomputationaltoolstogatherandanalyzedata.Thisapproach is primarily aimed at measuring and analyzing variables to determine causalrelationships, trends, or predict outcomes.
Data collection is often in numerical formand may be collected through surveys from large representative samples to ensureobjectivityandhighreliability.
- Togatherandanalyzenumericaldatatotesthypothesesanddeterminerelationships between variables Quantitative research is widely utilized across variousfieldssuchashealthcare,socialsciences,education,andeconomics.
- Hypothesis Testing: Identifying causal relationships between variables basedon statistical analysis This approach helps confirm or refute hypotheses establishedpriortostatisticalanalysis.
- Trend Description and Modeling: Analyzing and describing trends, models, orspecific characteristicsderivedfromarepresentative sampleofdata.
- Prediction and Simulation: Forecasting outcomes or behaviors of variablesbasedonstatisticalmodels.
- ComparisonandEvaluation:Comparingdifferentgroups,conditions,orbefore- and-after specific interventions This is commonly used in intervention studiestoassesstheeffectivenessofaprogram,product,ormethod.
Inconclusion,quantitativeresearchprovidesasystematic,objective,a n d reliable method to analyze phenomena, aiding researchers in understanding the causes,outcomes, and mechanisms of variables within a controlled environment It serves as apowerful tool tovalidate hypotheses andpredict socialand scientific phenomena,contributingtothesystematicdevelopmentandevidence- basedadvancementofknowledge.
- Statistical Software Usage: Utilization of statistical software for data analysis.Analysis may include descriptive statistics, hypothesis testing, correlation analysis,regression,andothermethodstailoredtotheresearchobjectives.
HypothesisandResearchModel
ExpertInterviewsontheProposedResearchModel
Based on the literature review and theoretical foundation from previous studies,the research model has been proposed on the basis of theories related to consumerneurobehavior, rational behavior theory, sustainable behavior theory, prospect theory,and loss aversion theory The model has been tailored by the author to align with theresearchobjectivesandwasfurtherrefinedthroughinterviewswith16experts,includingpoli cymakers,scientists,andinsuranceindustryexecutives.Theinterviews were conducted directly from May to August 2022 at institutions The following is asummary of the expert interviews on the robustness of the research model, presented inSection3.1ofthethesis.
Factor1:Decisionmaking DE1Providesinformationtostakeholders DE2Provideslegaladviceontechnologyproductstostakeholders DE3Supportsthevaluationandappraisaloftechnologyproducts DE4Supportsthe organizationof technologysupplyanddemandconnections DE5Advisesontechnologytransfercontracts
TR2Legalconsultancyontechnologyproducts TR3Supportforvaluationandappraisalof technologyproducts TR4Supportinorganizingtechnologysupplyanddemandconnections TR5Advisoryondraftingtechnologytransfercontracts
EX1Providinginformationtosuppliers,buyers,andrelevantparties EX2Connectingwithvaluationandappraisalservicesfortechnologyproducts EX3Organizingactivitiestoconnectsupplyanddemandfortechnologyproducts EX4Advisingonthe draftingoftechnologytransfercontracts
RI3 Applying new procedures in supporting the valuation and appraisal of technologyproducts
IN1Providinginformationontechnology products IN2Advisingonlegal aspectsoftechnologyproducts IN3Supportingthevaluationandappraisalof technologyproducts IN4Supportingtheorganizationofsupplyanddemandconnections IN5Advisingontechnologytransfercontracts
Theability toabsorbexternalknowledge to innovate internal organizationalactivities: AB
AB1 The organization is capable of recognizing new knowledge and skills necessary forcurrentoperations.
AB2 The organization has the ability to acquire new knowledge and skills for application incurrentoperations asneeded.
AB3 The organization is willing to apply new knowledge and skills to enhance the efficiencyof organizationaloperations.
Knowledgesharing within theorganization: SH SH1Theorganizationhasinternal regulationsandpoliciesregardingknowledgesharing.
SH2 Interaction during the process of knowledge sharing within the organization iscomfortableand straightforward.
SH3Managerswithintheorganizationsupportknowledgesharingamongdepartmentsandunitswit hin the organization.
SH4 The organization is equipped with a technological system to effectively supportknowledgesharing within the organization.
SH5Does yourorganization have technologiestosupport internalknowledgesharing?
UN1The organizationhastheabilityto integrate newknowledgeand skillsforapplication incurrentoperations.
UN2 The organization is capable of processing and applying new knowledge and skillsappropriatelyto specificcases.
UN4Theorganizationhastheabilityto experimentandgenerate newknowledgeand skillsfromtheacquired knowledgeand skills.
Organizational learning capability of intermediaries in the science and technology market:
Transformative capability of knowledge into specific organizational activities (transformativecapability):TC
TC1 The organization has supportive activities for employees to successfully applyknowledge,skills, and experience to work.
TC2 The organization supplements successful application of knowledge, skills, andexperienceinto workprocesses andpractical applications withinthe organization.
TC3 The organization conducts learning sessions, updates, and knowledge sharing foremployeesonsuccessfulknowledge,skills,and experiencefromotherorganizationsin the samefield.
TC4 The organization does not negatively reiterate unsuccessful activities in applyingknowledge,skills, and experience to work.
ResearchmodelandHypotheses
After a period of literature review, data collection, and expert consultation, theresearcher observed that all experts provided valuable insights and concurred with thefoundational theories and selected variables employed in the study However, based onsome suggestions from the experts, the researcher also assimilated and incorporatedadjustments, subsequently conducting additional comprehensive literature reviews toproposeaformalresearchmodel.
H1:Experimentationwithnewideas(EX)positivelyimpactstheadaptivecapacityofinter mediaryorganizations(OLC).
H3: Organizational resilience (RI) positively affects the adaptive capacity ofintermediarySTIorganizations.
H4: Clarity of roles and responsibilities within organizational departments (TR)positivelyinfluencestheadaptivecapacityof intermediarySTIorganizations.
H5: Organizational decision-making (DE) significantly impacts the adaptivecapacityofintermediarySTIorganizations.
These hypotheses form the basis for investigating the relationships and impactsof various factors on the adaptive capacity of intermediary organizations in science,technology,andinnovation.
DataCollectionMethods
PrimaryData
In my study, I collected primary data through a survey to ensure scientific rigorand alignment with the research objectives within the real context of Vietnam.
Step1:Buildingonthesynthesisoftheoriesfrompreviousstudiesandtheoretical foundations, I established the constructs for measuring variables in mymodel After presenting the theories and reviewing studies in the preceding chapters, Irefined and adjusted the detailed content of each construct in the model based on therecommended theoretical foundations The outcome of this step was a draft scale fortheconstructs,readyforuseintheexpertpanelinthesubsequentstep.
Step2:Conductinganin-depthexpertpanelreview Inthisstep, Iengagedwith
16 experts, including policy makers, scientists, and insurance industry executives frominstitutions in science and technology businesses These experts possess specializedknowledge in the particular area of my research During the expert panel, feedback onthe survey instrument was sought, and adjustments were made to improve clarity,precision, and the inclusion of relevant variables and information to align with themodel.The resultwasanenhancedpreliminarysurveyreadyforthenextstep.
Step 3: Conducting a pilot survey after refining the survey instrument based onthe expert feedback In this step, I distributed the first survey to 100 respondents.
Afterreceivingresponsesandevaluatingtheirfeedbackregardingcomprehension,expression, and relevance to the research variables, I consolidated the suggestions forrefining the survey implementation Subsequently, I perfected and adjusted the surveyinstrumenttoproducethefinalversionforthesecondsurvey.
The evaluation of the survey instrument was conducted through a pilot surveywith a sample size of 100 respondents to assess the reliability of the measurementscales The aim of this step was to select suitable observed variables for measuringresearchconceptsandtocreateanappropriatemeasurementmodelforthemainquanti tative study The primary method for assessing the reliability of the scales was toexaminetheconfidenceintervalforvariabilitywithintherangeof0.7to0.95.According to Hundleby and Nunnally (1968), if Cronbach's Alpha is greater than orequal to 0.70, the scale is considered acceptable However, if Cronbach's Alpha isexcessivelyhigh(>0.95),indicatingalackofdiversityamongtheitems,a reevaluationoftheite msisrecommended(NguyenDinhTho,2013).
The scale evaluation process using Cronbach's Alpha yielded two simultaneousresults: the internal consistency of the observed variables within each construct and thecorrelation coefficient between each observed variable and the remaining variableswithin the same construct For both of these indices, higher values would lead to alarger Cronbach's Alpha Considering the importance of maintaining a balance, theauthor chose a minimum correlation value of 0.3, and any correlation coefficientsbelow0.3wereexcludedfromtheanalysis.
The results of the scale evaluation indicate that all eight independent variablesand two dependent variables meet the criteria for Cronbach's Alpha, the inter-itemcorrelation coefficient, and the correlation coefficient between observed variables andotherv a r i a b l e s w i t h i n t h e s a m e c o n s t r u c t A l l t e n v a r i a b l e s w e r e r e t a i n e d i n t h e i r originalformforfurther analysisbasedonthis assessment.
Currently,therearetwocommonlyusedapproachesforsampling:non- probabilitysamplingandprobabilitysampling.Inthisstudy,Iemployednon-probability sampling,specifically using Convenience Sampling – a method whereparticipants are selected based on their easy accessibility and willingness to participatein the study With technological advancements, the survey instrument was transformedintoaGoogleFormforconvenience,facilitatingdatacollectionfromdiverseparticipants between September 2022 and June 2023 The survey targeted individualsin three major urban areas, including Hanoi, and Ho Chi Minh City, as well as a fewother selected provinces Participants from these urban areas are expected to havehigherawarenessandpreferencesrelatedtoriskissuesinlifeandinsuranceparticipation,ma kingthemsuitableforthestudy.
Thedataanalysisapproachforthisdissertationwillinvolveassessingthereliability and validity of the model, evaluating convergent validity, assessing modelfit,evaluatingthemodel'sdiscriminantvalidityanditsrelevancetorealissues,assessingco nstructvalidityandreliability,andexaminingthePLS-SEMm o d e l through bootstrapping to determine the impact of intermediary variables on the modelandtheoverallresearchfindings.
Barclay et al (1995) and Hair et al (2021) have suggested guidelines for theminimum sample size in PLS-SEM applications, recommending at least 10 times thenumber of observed variables To ensure reliability, the sample size in this dissertationis determined based on the number of questions in the survey instrument.
With 8independent variables and 35 observed variables used for measurement, a minimumsample size of 350 respondents was targeted to ensure credibility Additionally, due tothe impracticality of surveying the entire population across major cities such as Hanoi,Da Nang, and Ho Chi Minh City, the focus will be on a proportionate sample sizebasedonthepopulationofeachcity(Tepping,1968).
Through the utilization of the scales, the author employed both exploratory andconfirmatoryfactoranalysismethodstorefinethefinalquestionnaire.Thequestionnairecom prisesthreesectionswithatotalof39questions:
- Collects basic information about the respondents, including personal detailsand information about dependent intermediaries, the form of premium payment ifapplicable.
- Aims to assess the general awareness of intermediaries in the science andtechnologyinVietnam.
Section 3: Survey on organizational learning capability of intermediaries in thescienceandtechnologyinVietnam(16questions):
- Reflects various influencing factors within the scope of the study Each factoris evaluated through 3-6 questions, depending on the specific nature of the factor.Notably, the "personal intention" and "personal decision" factors are assessed throughfourquestionseach.
After finalization, the questionnaire was administered to a sample of1,173respondents Out of this sample, 47 responses were deemed invalid due to missingcrucial information or lack of cooperation from the respondents, leaving 1,126 validresponses.Withthisdataset,thedatawillundergopreprocessing,cleaning,andanalysisusi ngtheSMARTPLS4software.
SecondaryData
- InternationalLabour Organization(ILO)- UnitedNationsDevelopmentProgramme(UNDP)
- WorldBank - Organisation for Economic Co-operation and Development (OECD)GovernmentReports:
- ReportsfromtheMinistryofFinance - Reports from the Ministry of Science and TechnologyIntermediaries
- Utilizedr e p u t a b l e international s c i e n t i f i c j o u r n a l s, e s p e c i a l l y thos ea v a i la b l e onGoogleScholarandSciencedirect,coveringthe fieldsofscienceandtechnology.
DataAnalysisMethods
Descriptive StatisticalAnalysisMethod
Thedescriptivestatistical analysismethodisatechniqueusedtoanalyzeda taby summarizing key statistical measures such as mean, standard deviation, variance,range, frequency, ratio, percentiles, distribution, charts, and graphs This method isemployed to depict and summarize data in a meaningful and understandable manner,facilitatingaclearunderstandingofthedata'sdistributionandcharacteristics.Descripti ve statistical analysis is commonly used to present research results or analyzedata,aidinginthe comprehensionofdatadistributionandproperties.
Thismethodisparticularlyusefulwhendealingwithdatathatpossessesqualitative characteristics Descriptive statistical techniques often include indices likemean, ratio,column charts, pie charts, etc., to effectively communicate relationshipsbetweenvariablesinthedata.
StructuralEquationModelingMethod
Inobservationalstudiesconductedintherealworld,therealwaysexistsa certain amount of measurement error, which may be related to systematic or randomerrors (Hair et al., 2014) For traditional regression methods, these techniques can onlybe applied when there is no systematic or random error However, in this study, themaino b j e c t i v e i s t o a s s e s s t h e r e l a t i o n s h i p s b e t w e e n c o n s t r u c t s d e r i v e d f r o m theoreticalconcepts,suchasattitudes,perceptions,knowledge,responsibility,andintentionsord ecisions.Toovercometheselimitations,thePartialLeastSquaresStructuralEquation Modeling (PLS-SEM) method has been developed by Hair and colleagues(2014),allowingresearcherstobuildtheoreticalmodelsandestimatecomplexrelationshi ps between dependent and independent variables more accurately, offeringpreciseadjustmentstothetheoreticalconceptsofinterest(Cole&Preacher,2014).
PLS-SEMisastatisticalmethodusedtodeterminerelationshipsamongvariables in a complex model It operates effectively with small sample sizes andpartial models,making it highlyb e n e f i c i a l f o r r e s e a r c h s t u d i e s w h e r e l a r g e s a m p l e s are not available (Cassel et al., 1999; Esposito et al., 2010) PLS-
SEM is robust inhandlingviolationsofnormaldistributionassumptions,makingitsuitablef o r analyzing data that do not follow a normal distribution Additionally, PLS-SEM iswell-suited for predictive modeling, emphasizing the ability to predict latent variablesfrom observed variables This method allows constructing a structural model withobserved variables measured by measurement indices and latent variables measuredusing latent constructs by incorporating additional indices PLS-SEM is widely used inresearchfieldssuchasmanagement,economics,business,marketing,andrelateddisciplines It is commonly applied in exploratory research, theory generation, andtheory building, enabling studies to explore a range of variables and relationshipswithinamodel.
Partial Least Squares Structural Equation Modeling (PLS-SEM) employs a partial least squares regression method to analyze relationships between latent variables and predict dependent variables This technique identifies relationships among variables by extracting principal components Notably, PLS-SEM facilitates the examination of relationships involving mediating and moderating variables, allowing researchers to explore how third variables influence associations between other variables.
In this study, the application of PLS-SEM involves analyzing the impact ofindividual factors on intentions and decisions, using intention as an indirect variable totest the influence of individual factors on intermediaries in the science and technologyin Vietnam The roles of individual factors are also tested as moderating variables inthemodel.PLS- SEMprovestobeamoreuser- friendlyandv e r s a t i l e m e t h o d comparedtootherSEMtechniques.
AsthedataanalyzedinPLS- SEMisassumedtobe non- normally distributed, the significance of coefficients, such as path coefficients, cannot be examined usingtraditionalstatistical significancetestslikethet-test.Instead,PLS- SEMreliesonbootstrappinganalysisofnon- parametricprocedurestoassesstherobustnessandconfidence of the model results (Hair et al., 2014) To evaluate whether the pathcoefficientsdiffersignificantlyfromzero,thet- valuescalculatedt h r o u g h bootstrapping are used Bootstrapping captures the variability in parameter estimatescaused by the sampling process By resampling with replacement, it considers theinherentuncertaintyinthedata,providingmoreaccurateestimatesofparameteruncertainties Bootstrapping is particularly useful for assessing the precision of modelparameters, such as path coefficients, and determining their confidence intervals Thistechnique is valuable for obtaining reliable confidence intervals for model parameters,suchaspathcoefficients,whichare essentialforhypothesistesting.
In this study, the bootstrapping technique without parameters was employed for1,126observations,with5,000iterationstomeettherequirementsforstructuralequation modeling verification The aim is to ensure robust and reliable assessments ofthestructuralmodelanditsparameters.
Dataused:surveydatafrom505observations,includingemployeesandmanagersatvariouslevel sworkinginintermediaryorganizationsinthefieldo f science and technology in Vietnam.
The table of Cronbach's alpha reliability analysisresults below indicates that all Cronbach's Alpha coefficients are greater than 0.6.Therefore, the scale used for the research variables is deemed acceptable, and allobservedvariablesareacceptedandutilized.
Table3.1:Cronbach'sAlphaCoefficients Item-Total Statistics
KMO coefficient = 0.745 > 0.5 Therefore, the factor analysis is suitable for theresearchdata.