Mediating effect of strategic management accounting practices in the relationship between intellectual capital and corporate performance evidence from vietnam

Background

In today's knowledge-based economy, organizations are increasingly investing in both physical and intangible assets, with the latter, particularly intellectual capital, becoming vital value drivers (Mehralian et al., 2013) The management of intellectual capital is crucial due to the significant investments involved and the direct and indirect advantages it offers These advantages include the added value derived from processed knowledge, the learning processes associated with measuring intellectual capital (Roos et al., 1997), and the enhancement of sustainable competitive advantages stemming from strategic assets like intellectual capital (Riahi).

Belkaoui,2003),thedeterminantsandtheforemostsourcesofcompanysuccess(Alum&Drucke r,1986).Likethecountrieswithfreetrading,Vietnamhasadoptedanopen- doorpolicysince1990’s,thelevelofcompetitionintheeconomyhasbeenthereforeincreasingsig nificantlyformostVietnameseenterpriseswhenVietnam’sintegrationinAECandTPP,thereby, managersinVietnamesefirmsshouldbeawareoftheimportanceofintangiblesaswellintellectu alcapital,whichachievesustainablecompetitiveadvantagesintheinternationalcompetitivearen a.Thiswillb e a motivatortoimpulsescholarsdoingresearchontheinfluence of intellectual capital inthe Vietnamese context.

The concept of intellectual capital has evolved through three distinct stages, beginning in the 1990s with a focus on awareness, definitions, case studies, and primary definitions (Mehralian et al., 2013) The second stage, starting in 2000, emphasized measurement, modeling, international case studies, and various levels of analysis, revealing a positive correlation between intellectual capital and corporate performance across multiple research methods The third stage, initiated in 2004, concentrates on the managerial implications of effectively managing intellectual capital While most studies have been conducted in developed Western countries, research has also emerged from some Asian and developing nations, including Thailand and Malaysia.

HongKong,thisspecificareao f intellectualcapitalhasbeenneglectedinthebodyo f Vietnamesel iterature.

Strategic management accounting, as defined by CIMA, focuses on information relevant to key strategic decisions and plays a potential role in managing intellectual capital, which is considered a strategic asset under resource-based theory Despite the existing literature on intellectual capital primarily addressing external reporting and evaluation, there is limited discussion on the reciprocal relationship between intellectual capital and strategic management accounting Organizations with strong intellectual capital can develop systems that identify, measure, and communicate value drivers effectively Conversely, once a strategic management system is in place, it can enhance the identification and communication of intellectual capital to support strategic objectives The challenge lies in creating strategic management accounting practices that align with a company's unique attributes and competitive strategies In the context of Vietnam's transitional economy, many enterprises are adopting advanced accounting techniques influenced by foreign-owned companies, highlighting a gap in understanding how to implement strategic management accounting among medium and large Vietnamese enterprises Consequently, research on the correlation between intellectual capital, strategic management accounting practices, and corporate performance has gained traction in Vietnam since the 2010s This study aims to explore the mediating role of strategic management accounting practices in the relationship between intellectual capital and corporate performance within the Vietnamese business environment.

Researchquestions andresearch objectives

TheresearchgapsmentionedinSection1.4suggestthataneedtoinvestigatetheeffectsofi ntellectualcapitalandstrategicmanagementaccountingpracticesoncorporateperformanceinth eorganizationsoperatinginthetransitionaleconomysuchasVietnambecausetheseissueshaven otbeendiscoveredinsucheconomy.Thisalsoraisestheissueo f whetheranorganizationshouldd evelopstrategicmanagementaccountingsystemthatsupportsintellectualcapitalwhichinturnto enhanceitsfinancialperformance.Ifdoingso,itisalsoinevitablethathowstrategicmanagementa ccountingmanagesintellectualcapitaltoboostanorganization’sfinancialperformance.Accordi ngly,threeresearchquestionshavebeen proposed:

Researchquestion 1: What isthedirecteffectofintellectualcapitalcomponentsoncorpora te performance inVietnamese enterprises?

Researchquestion 2 : What istheeffecto f intellectualcapitalcomponentso n corporate performanceinthepresenceofstrategicmanagementaccountingpractices?

Researchquestion 3: How dostrategicmanagementaccountingpracticeshandleeachco mponentofintellectual capital toimprove corporate performance?

Theoverallresearchobjectiveofthisdissertationist o empiricallyexaminetheassociatio nbetweenintellectualcapital,strategicmanagementaccountingpracticesandcorporateperform ance.Moreimportantly,itinvestigatesthemediatingeffectofstrategicmanagementaccountingp racticesontherelationshipamongintellectualcapitalcomponentsandthreefinancialdimensions ofcorporateperformance.Italsoempiricallyanalysestheroleofstrategicmanagementaccountin gpracticesplayingthemanagementofintellectualcapital components.

- RO2:Examiningthedirectinfluenceofstrategicmanagementaccountingpractices over corporate performance.

- RO3:Investigatinganindirectpathbetweenintellectualcapitalcomponentsandcorp orateperformancethroughthemediatingroleo f strategicmanagementaccounting practices.

- RO4:Empiricallyanalysingwhichgroupofstrategicmanagementaccountingpracti ces(i.e.strategiccostmanagement,competitoraccounting,strategicaccountingandc ustomeraccounting)arerelatedtomanagewhichcomponentso f intellectual capital.

Researchobject and researchscope

Theresearchobjectofthisdissertationistherelationshipamongintellectualcapital,strate gicmanagementaccountingpracticesandcorporateperformance.Therefore,theunito f analysis isabusinessorganization.ToinvestigateSMApracticesappliedinabusinessorganization,thedat aiscollectedthroughquestionnairesurveywhichissenttoSMApractitioners;thereby,theunitofo bservationistheinformant(i.e.managersormemberso f topmanagement)withknowledgeabou taccounting,planningorfinanceandatleasttwoyearso f workingexperienceinthecurrentorgan ization.Moreover,theunito f observationisalsofinancialinformationinannualreportsorfinanc ialstatementreportswhichdraw financial dataonICandcorporate performance.

This study focuses on three key aspects: Firstly, it examines Vietnam, a developing Asian country with a transitional economy and collectivist culture, as the research site for observation and empirical testing Secondly, the study targets businesses listed on the Ho Chi Minh Stock Exchange (HoSE) and Hanoi Stock Exchange (HNX) to facilitate the collection of financial data Lastly, the research utilizes financial information from 2016 regarding intellectual capital (IC) and financial performance of public companies where the respondents are employed, rather than employing panel data over multiple years as seen in previous studies However, to calculate variables such as organizational capital, innovation capital, and investment efficiency, financial data spanning seven years (2010 to 2016) has been collected.

Methodology

Thisstudyfirstreviewstheliteraturerelatedtointellectualcapital,strategicmanagementa ccountingpractices,corporateperformancebeforeproposingtworesearchmodelswithsixhypot heses.Thisstudymainlyusesquantitativeresearchmethodbyusingempiricalsurveydataandfina ncialdataobtainedfroma sampleo f atleast127publicenterprisesinVietnamfortheyearof2016. Duetothecomplexoftheresearchmodelswithmediatorsandasmallsamplesizecontext,dataana lysisisconductedbyapplyingpartialleastsquaresstructuralequationmodelling(PLS-

Outlineofthe dissertation

Reviewofinternational studiesofintellectual capital

Whenchangingfromanindustrial-basedeconomytoknowledge- basedeconomy,afirm’svalueisnolongermeasuredsolelyonthebasisoffinancialresults;ratherth anvalueo f activitiesthatdevelopknowledgeresourcesmustalsobeconsidered(Stewart&Ruck deschel,1998).Doingsohelpsunderstandinghowemployees,stakeholdersandactivitiescontrib uteintovaluecreation,leadingtothechallengeo f howtoidentify,measureandreportonthevalue ofintellectualcapital(Dumay,Guthrie,&Ricceri,2012).Therefore,theemergenceoftheintellec tualcapitaltopicinthemid-

1990shasproducedliteraturespanninga rangeo f researchdisciplines.Inretrospect,itappearsth atlikea researchfashion(Alcaniz,Gomez-

Bezares,&Roslender,2011),theintellectualcapital’sspecialistjournalshavebeencontinuously developedincludingtheJournalofIntellectualCapital,theInternationalJournalo f Learningan dIntellectualCapital,theJournalo f HumanResourceCostingandAccounting,aswellaswithint hepagesofmanyleadingbusinessandmanagementjournals,withtheAccounting,AuditingandA ccountabilityJournal,EuropeanAccountingReview,theAccountingOrganizationsandSociety Journalespeciallyimportantintheaccountingdisciplineofintellectualcapitalmeasurementand management.

Thehistoricalperspectiveisavitalcomponentinfosteringanunderstandingofthecontextw ithinwhichintellectualcapitalcametob e viewedastheessentialbusinesselementthatitistoday.P ettyandGuthrie(2000)alsooutlinedtwostagesinresearchingintellectualcapital.Thefirst- stageeffortstypicallyfocusedonraisingawarenessastowhyrecognizingandunderstandingthep otentialofICtowardscreatingandmanagingsustainablecompetitiveadvantagesisextremelyess ential(Petty&Guthrie,2000).Additionally,attemptswerecharacterizedb y thecreationo f guid elinesandstandards.Theseearlypublicationspayattentiontothefactthatintellectualcapitali s so methingsignificantandshouldbemeasuredandreported,butwithoutreferringtospecificempiric alresearch(Petty& Guthrie,2000).Mostresearchconductedpriortothemid-

1990si s consideredfirststage(Petty&Guthrie,2000).ThesecondstageofICresearchgatheredf urtherevidence,atanorganizationallevel,focusingonthehowofICcapitalandlabourmarketreac tedtowardsthepotentialforICtocreatevalue(Petty& Guthrie,2000).Ingeneral,thefirstandseco ndstagescontributedtoacommonlyacceptedterminologyofintellectualcapital.Severalclassifi cationso f IChavebeenprovided,resultingintheidentificationofthreemainICcomponents.Tog etherwiththeappearanceofthreecomponentso f IC,theresearchersdefinedtheaccountingdiscip lineofICasa management,measurementandaccountabilitytowardIC(Dumayetal.,2012).Acco rdingtoDumayetal.

(2012),athirdstageofICresearchisemergingandischaracterisedbyresearchcriticallyexaminin gICinpractice,devotedtothemanagerialimplicationsofhowtouseICinmanagingacompany,att hebeginningwiththe2004specialeditionofJournalo f intellectualcapitalentitled“ICatthecross roads– theoryandresearch”byMarrandChatzkel(2004).WhilesecondstageICresearchispredominate lydevotedtoevaluatingIC’sinfluenceonfinancialoutcomes,third- stageICresearchfocuseso n “thedeepermanagerialimplicationsofmanagingICinalltypesofor ganisationsandcanbeclassifieda s bottom-upresearchasopposedtotop- down”(Dumay&Garanina,2013).Thus,thethirdstageconsidersvaluefromICisnotjustmonetar ybutincorporatesworthandimportanceoftheproductsandservicestocustomersandotherstakeh olders(Dumay&Garanina, 2013).

DespitelookingatthreedevelopingstagesofIC,Guthrie(2001)providesatimelineo f majo r IC researchmilestones,assummarizedinTable 1.1.

Table 1.1.Milestonesofsignificant contributions to the identifications,measurement andreportingofintellectual capital

General notion of intangible value (often generically labelled“goodwill”).

The“informationage”takesholdandthegapbetweenbookvalueandmarket value widens noticeablyfor manycompanies.

Earlyattemptsbypractitionerconsultantstoconstructstatements/accounts that measure intellectualcapital (Sveiby, 1989).

 Initiativestosystematicallymeasureandreportoncompanystocksofi ntellectualcapitaltoexternalparties(e.g.TheSwedishCoalitionof Service Industries (SCSI) (1995)).

 KaplanandNorton(1992)introducetheconceptofaBalancedScorec ard.TheScorecardevolvedaroundthepremisethat“whatyoumeasure is whatyouget”.

“knowledge”,thedistinctionbetweenknowledgeandIntellectualCa pitalissufficientlyfineastomakeitrelevanttothose withapure focusonIntellectual Capital.

 Alsoin1994,asupplementtoSkandia’sannualreportisproducedwhi chfocusesonpresentinganevaluationofthecompany’sstockofIntell ectualCapital.“VisualizingIntellectualCapital”generatesagreatdea lofinterestfromothercompaniesseekingtofollowSkandia’s lead(Edvinsson&Sullivan,1996).

 PioneersoftheIntellectualCapitalmovementpublishbestsellingboo ksonthetopic(KaplanandNorton(1996);EdvinssonandSullivan(1996);Sveiby(1997)).EdvinssonandMalone’swork, inparticular,isverymuchabouttheprocessandthe“how”of measuringintellectual capital.

 IntellectualCapitalbecomesapopulartopicwithresearchersandacad emicconferences,workingpapers,andotherpublicationsfindanaudi ence.

 Anincreasingnumberoflargescaleprojects(e.g.theMERITUMproj ect;Danish;Stockholm)commencewhichaim,inpart,tointroduceso meacademicrigourintoresearcho n IntellectualCapital.

 In1999,theOECDconvenesaninternationalsymposiuminAmsterda monintellectualcapital(OrganizationforEconomicCo- operationand Development (OECD), 2000).

 Throughthe2000sandonwards,ICresearchiscontinuouslydissemin atedtothewideraccountingresearchcommunity.Thegeneralistacco untingjournalsandgeneralistaccountingconferenceshaveopenedth edoorstospecialeditionstoacceptICaccounting papers (Dumayet al., 2012).

 Thereisanincreasingtrendonknowledgemanagementresearchbesid es intellectual capital research(Dumayet al., 2012).

1.1.2.Researchtrendsonintellectual capital inthe accounting discipline

Althoughitisgenerallyacceptedthatintellectualcapitalisaknowledgeresourcethatneedst obewellmanaged,itcanbeanalysednotjustfromamicroeconomicviewpoint,b u t alsofroma macroeconomicaspect.Theissueofintellectualcapitalisstudiedinfourperspectives,suchaseco nomic,strategic,managerialandaccountingperspective(Alcanizetal.,2011).Forexample,onth eeconomicperspective,intellectualcapitalisrelatedtothewealthofcountrieswhichpossessitsuc hashightechnology,well-educatedlabourforces,etc.

The success of a company's strategy increasingly relies on intangible assets rather than tangible ones, with the accumulation of intellectual capital influenced by a reciprocal relationship between resources and strategy (Stewart & Ruckdeschel, 1998; Brooking, 1996) From a managerial perspective, various types of capital—physical, financial, and intellectual—integrate to form an organization's resources, highlighting the importance of their identification and management as foundational to the organization's value (Bontis, 1999) This study focuses on the complexities associated with accounting for intellectual capital, as discussed in the accounting literature (Dumay et al.).

(2012)’spaperexamining423journalpapersintermso f intellectualcapitalduringtheperiodfrom 2000to2009(Table1.2),thepopularfocuso f ICaccountingresearchi s managementaccounting andexternalreportingbutlittlehasbeenpublishedaboutaccountability, governance andauditing.

Table 1.2.Topicsofintellectual capital researchinthe accountingdiscipline

Table1.2presentsthefocusofresearchtrendsonintellectualcapitalintheaccounting discipline, as follows:

External reporting on intellectual capital (IC) can be voluntary and non-quantitative, benefiting both firms and investors when linked to firm performance While significant research has focused on IC disclosure practices in developed countries, there is a notable lack of studies in emerging economies, particularly outside of Asia Existing studies have empirically analyzed IC disclosure through various media, including annual reports and corporate social responsibility reports Findings indicate that IC disclosure varies by company size and industry, with European disclosures showing approximately 49% for relational capital, 30% for structural capital, and 21% for human capital Most previous studies have relied on single-year data, with only a few employing longitudinal approaches for a more comprehensive analysis of IC disclosure practices.

 Accountabilityandgovernance:Somepapers(KeenanandAggestam(2001);J.Li,Pi ke,andHaniffa(2008))examinetheinfluenceofcorporategovernancefactorso n int ellectualcapitaldisclosure,usingvariousdisclosuremeasures.Thesepapershypothe sisethatsignificantrelationshipsexistbetweenintellectualcapitaldisclosureinannua lreportsandboardstructure,roleduality,ownershipconcentration,auditcommitteesi zea n d frequencyo f auditcommitteemeetings, controllingfor listingage, firmsize andprofitability.

Management control is a highly researched area, with 160 articles covering various management-related topics, as shown in Table 1.2 Key studies include the application of Balanced Scorecards for managing intellectual capital (IC) across different organizational contexts, such as service organizations, the banking industry, and the non-profit sector Research suggests that management accounting approaches can effectively support IC control, emphasizing less reliance on traditional budgeting methods and advocating for the beyond budgeting concept Additionally, real options valuation is highlighted as a superior method to capital budgeting for assessing strategic IC investment opportunities.

In the early 1990s, performance measurement frameworks emerged to address the limitations of financial-only metrics, emphasizing intangible resources such as key customers, internal processes, and learning (Tayles et al., 2007; Amir & Lev, 1996) Notable models include the Intangible Assets Monitor, Skandia Navigator, and the Balanced Scorecard (BSC), which collectively focus on intellectual capital and broader strategic goals (Roos et al., 1997; Sveiby, 1997; Kaplan & Norton, 1996) The BSC integrates perspectives on relational, structural, and human capital while considering their influence on financial outcomes Lev (2001) proposed the Value Chain Scoreboard for management and investors to systematically report the effects of intellectual capital on corporate performance and valuation The literature indicates that firms with higher intellectual capital are more inclined to adopt performance measurement frameworks that are linked to shareholder value.

Policystatement:A groupo f articlesd i d nothaveempiricalresearchandtendedtobe eithercommentariesorpolicystatementsreferredtoPettyandGuthrie(2000),Brenna nandConnell(2000),RoslenderandFincham(2001),García-Meca(2005)asfirst- stagecontributions.Thistrendisconductedatthebeginningofthedecadeandtherewe refewerattheendofthedecadeofthe2000s.Theinitialfocuswasonunderstandingan dexplainingthevariousfacetsofICphenomenon,littleinterestintestinghypotheses.Thesestudieshavegivena risewithaccountingliteraturetotheoreticalcontributionso nhowtotake ICcomponents intoaccount.

(2012)paper,theauthorsreviewed423journalpapersintermsofICtoconcludethattherearefiveg roupsofresearchmethodsfound.Table1.3indicatesthatcommentary/normative/ policyisthemostcommonlyused,followedbysurvey/ questionnaire andnext tocase study/ interviews.Dumay et al.

(2012)highlightthatthetrendoverthelast10yearsisasteadyincreaseinempiricalwork,whilenor mativeworkhasdeclined.Dumayetal.(2012)arealsoalarmingthatthereisadangero f over- dependenceo n empiricalstudiesunsupportedbytheoreticalunderpinning.Additionally,theyal sohighlightafailuretoconvertICtheoryintopracticeresultedfroma focusoftop- downresearchinsteadofbottom-upperformativeresearch(Dumayetal.,2012).

Table 1.3.Methods usedinintellectual capital accountingresearch

 Case/fieldstudy/ interviews:TheworksusecasestudiestoexploreandunderstandICphenomenainapa rticularcontext.Forexample,Dumay(2009)foundacasestudyintotheattempttound erstandICreportinginadivisionofalargeAustraliafinancialservicescompany,name dAusFinCowithover 25,000employees.

 Contentanalysis:IthasbeenconductedonannualreportsbyanumberofICresearche rswhowanttomeasurethelevelo f ICdisclosure.This“involvescodifyingqualitative andquantifiedinformationintopredefinedcategoriesin ordertoderivepatternsinthepresentationandreportingofinformation”(Dumayetal., 2012).Theresearchersusedanidenticalframework(i.e.Sveiby(1997)’sframework) ,whichcategoriesintangiblesaccordingwhethertheyaccompanywithanorganizatio n’sinternalstructure,employeecompetenceorexternalrelationships.Doingsohelps tofindthatthekeycomponentsofICareinadequatelyidentified,ineffectivelymanage dandinconsistentlyreported.ThismethodcanbefoundinthestudiesofBrennan(2001 ),Olsson(2001),Guthrie,Petty, Yongvanich, andRicceri (2004),Whitingand Miller (2008).

To conduct empirical research on intellectual capital (IC), two primary measurement systems can be identified: the accounting framework and the perceptual school of thought (Kannan & Aulbur, 2004) The accounting framework utilizes the Value Added Intellectual Coefficient (VAIC) as a quantifiable measure of IC efficiency through financial data In contrast, the perceptual approach focuses on employees' perceptions and their requirements for an effective knowledge management system (Kannan & Aulbur, 2004) Consequently, a survey was developed to assess the constructs of intellectual capital and their impact on business performance within a conceptual model This survey is directed at top management to evaluate the components of IC, leveraging the use of surveys and questionnaires (Bollen, Vergauwen, & Schnieders, 2005; Bontis, Chua Chong Keow).

& Richardson,2000;Tovstiga& Tulugurova,2007)o r questionnairecombinedwith financialdata(S.Cohen&Kaimenakis,2007)canbefoundina greatdealofresearcht oindicatetherelationshipbetweenICorsomeofICcomponents andperformance.

 Commentary/normative/ policy:T h e parto f theextantliteratureevidencea stronglynormativecharacter;here theemphasisisessentiallypolicyorpracticeoriented,focusingondiscussionaboutva riousalternativewaysofidentifying,measuringandreportingthegrowthofstocksofi ntellectualcapitalduringanaccountingperiod(Alcanizetal.,2011).Tocomposeanor mativepaper,theresearcherappliesthemethodologywhichanalysestheassumptions underpinningguidelinesandframeworksthathavebeendevelopedtoprovideanunde rstandingo f thearti n relationtomeasuringandreportingIC

(Abhayawansa,2014).B y anotherway,mostcommentaryresearchinICisregularly builtonabasictheoryderivedfromanotherresearchfieldtoaffirmthe writers’arguments (Alcaniz etal., 2011).

 Theoretical(literature)review:Toconductliteraturereview,theresearchersreadthes electedpapersbasedonbothabstractsandfulltextofthearticlestodiscussandmakepr eliminaryclassifications.Withrespecttothemethodo f literaturereview,oneauthor manuallycodesallthepapersforthecontentsinsimilaritywhilethesecondandthethir dauthorsre- checkthecodingforconsistencytofindtheoutcomeofwhathashappenedinthefieldof intellectualcapitalaccountingresearchoverthepastdecades.Alternatively,some(G uthrieandPetty(2000),Dumayetal.(2012))usedthemeta- analysisoftheselectedICarticlestoanswerthequestionofhowandwhythisfieldisch anging.ThemethodofreviewingpublishedarticleshavebeenfoundinthestudiesofP ettyandGuthrie(2000);Parker(2005);BroadbentandGuthrie(2008);Dumayetal. (2012).

Overall,thereisanopportunityforresearcherstopublishmoreperformativeresearch.A rea sonforthelackofperformativestudiesarethetimeandresourcesrequired,alongsidegainingacces stoinvestigateinsideorganisationsthatmaybereluctanttohaveresearchersexaminewhattheyse easkeycapabilitiesdrivingtheircompetitiveadvantage(Alvesson

&Deetz,2000).Incontrast,performingostensiveresearchbasedonobservationsfrompubliclya vailabledatasetssuchasVAICanalysisorcontentanalysisofcompanydisclosuresavoidsthisacc essproblemandallowsresearcherstoanalysetheseICissuesasresearcherswish.Thus,manyrese archersmaybeputtingperformativeresearchinthetoohard basket and undertake ostensive researchas aneasyway out.

Themainpurposeo f reviewingthepriorempiricalstudiesinvestigatingtherelationshipbet weenICandcorporateperformanceistounderstandandconfirmthatICisthefundamentalandstra tegicassetsfororganizationalsurvivalandsuccess.IfICislinkedto corporateperformanceastheoriginofvaluecreation,investorswouldbenefitfromthisrelationshi p.Therefore,therearenumerouspiecesofresearchinmanycountries,affirmingthis correlationundertakenbyavarietyofresearchmethods Ingeneral, thesestudies find apositiverelationshipbetweenIC(orsomeofitscomponents)andcorporateperformance,althou ghtheexactnatureofthiscorrelationvaries(seeAppendix1).Forinstances,Bontisetal.

(2000)finda positiverelationshipbetweenstructuralcapitalandperformanceinMalaysianfirms, andobservedthatinvestmentinhumancapitalhasanindirectimpactonperformanceviastructural capital.Insimilarity,a Germanstudy,Bollenetal.

(2005)discoverthatallcomponentsofIChaveanindirectcorrelationwithperformanceactingthr oughintellectualpropertyasamediator.Nevertheless,J.Cohen,Krishnamurthy,andWright(20 04)recognizethattheremaybeatime- lagbetweeninvestmentinintellectualcapitalandperformanceincrementalforwhichtheydidn o t control.Unfortunately,thestudiesarerarelydirectlycomparable,differingintheirmeasureofbot hintellectualcapitaland performance (Clarke, Seng,&Whiting,2011).

OnequantifiableandobtainablemeasureforICistheVAIC,developedby(Pulic,2000).VA ICprovidesastandardmeasureofICefficiencytoevaluatethelinkbetweenICefficiencyandperfo rmance.Asevidenceofthis,anumberofstudiesinarangeofcountriesinvestigatetherelationshipb etweenVAICandperformance(seeAppendix1).Forexamples,Hang-

Chan(2009)findasignificantpositiverelationshipbetweenVAICandreturnonassets(ROA),an dlikewise,Ming-Chin,Shu-

Ju,andHwang(2005)observesignificantpositiverelationshipsbetweenVAIC,HCE,CEE,SCE andROA.HongPew,Plowman,andHancock(2007)findthesignificantpositiverelationshipsb etweenthecurrentandprioryearcomponentso f VAICandROEwhileMaditinos,Chatzoudes,T sairidis,andTheriou(2011)alsoobservethisrelationshipwithHCE.However,notallstudiessup portthesameoutcome.Asevidenceofthis,FirerandMitchell-

Williams(2003)discoverthathumancapitalefficiencyhasasignificantnegativerelationshipwit hassetturnoverandmarket-to- bookratio,showingthattheefficiencywithwhichafirmuseitsH C negativelyinfluencefirmperf ormance.Incontrast,Appuhami(2007)doesnotfindasignificantcorrelationbetweeneachcomp onento f ICandthecapitalgainsmadeb y shareholders,althoughtherelationshipbetweenVAICi ngeneralandperformanceisa positive one.

Overall,studiesusingVAICasmeasuresofICcomponentshaveresultedinamixtureo f out comesacrossdifferentcountries,industriesandyears.Forexample,Ming-Chinetal.

(2005)concludethatICisa driverof bothfirmvalueandfinancialperformance.Shiu(2006) finds onlyweakrelationships betweenVAICandperformance Inaddition,Clarke etal.

(2011)discoverthatstructuralcapitalefficiencyisrarelyfoundtohaveasignificantcorrelationwit hperformance.Arangeofinconsistentevidencedonotresultinacompellingconclusionregardin gthecorrelationbetweenICandcorporateperformance.AfurtherinvestigationwithVietnamese dataisthereforeundertakentoprovideevidenceofassociationbetweenintellectualcapitalandcor porateperformance,andifso,itsdirection.

Reviewofinternational studiesofstrategic management accounting

In1981,SimmondspublishedapaperintheUKprofessionalmagazine,ManagementAcco unting,in which hepresentedastrong casefortheadoptionofstrategicmanagementaccounting(SMA)

(Simmonds,1981).Manyprofessionalandacademicpaperscontinuedthistheme.Overall,theres earchcontinuestomaintainfourthemesemphasizingon(1)howtodefinetheconceptofstrategic managementaccounting,

(3)theimpactsofstrategyoptionso n SMAchangesand(4)strategicmanagementaccountingpro cess(seeinAppendix2).Mostofthepublishedempiricalresearchoverthepast30yearshasconsis tedofquestionnairesurveysthatsoughttoestablishtheextenttowhichspecificSMAtechniquesh avebeenadopted(Langfield-

Smith,2008).However,thelimitationsofsurveysandtherelativedearthofcasestudiesmeanthatv erylittleisknownabouthowtheSMAtechniquesare used, bywhomandfor whom(Nixon&Burns, 2012).

ThereisnoagreeddefinitionofSMAintheliterature.Atitsverysimplest,SMAisconceptua lized asan approach thatliesattheinterfacebetween strategicmanagementandaccounting(Roslender&Hart,2003).AccordingtoSimmonds(1981)

’sfirstdefinition,S M A canbe generallydefinedasa genericapproachthatconnectsmanageme ntaccounting,strategyandstrategicpositioningo f thecompany,whileBromwich(1990)provide sadefinitionthatlimitsSMAtofinancialinformation,butwhichisfocusedonperformancerelati vetocompetitors.However,someotherauthorsseemarketingasthemorerelevantorientationforSMA(forexample,FosterandGupta(1994);Roslender(1995);Wilson(1995)).Fromtherelevan tliterature,threemainapproachesinconceptualizingSMA canbedistinguishedas follows:

 Simmonds(1981)’sapproachtoSMAisbasedmoreonPorter’sframework,whichc atalyseda streamo f research,focusingmoreo n costmanagement neededtosupportlowpricecompetitivestrategyratherthandesignandinnovationtoe arnapricepremiumthroughproductdifferentiation.Thus,thereisa demando f finan cialinformationaboutcompetitorstocopewithcorecompetitors’ moves.

 Bromwich(1990)’sS M A approachisbasedonattributecostingtechnique,where the aimistocostaproduct’s benefit providingto customers,as opposedtotheapproachthatdeterminesreasonsdrivingcostsofproduct.Thus,thereis a needofconsideringthebenefitsofferedtocustomers,andhowthesecontribute into buildingsustainable competitive advantage.

 OntheperspectiveofmarketingconnectingtoSMA,RoslenderandHart(2003)arguet hatS M A shouldbecome“morethoroughlyinfusedwithmarketingissues, theories andconcepts toformamarriageofequalpartners” Thus, thereisa necessityo f “brandmanagementaccounting”thatwouldincludeperforma ncemeasuressuchasmarketshare,marketgrowthandbrandstrength,andcustomerpr ofitabilityfocusingonsub-brandsandspecificmarketofferings.

Fromthestateddefinitions,itisobviousthattheterminologyofSMAhasamultitudeo f diffe rentinterpretations,dependingontheresearchers’scientificbackground,underlyingassumption sandstartingpoints.SinceSimmonds’firstdefinitionwasintroducedover30yearsago,thereislittl eagreementwhatisandwhatconstitutesSMA.Thistermitselfisopeningtoanumberofinterpretat ionsduetovariednatureofresearchassociatedwithit,whilesomeresearchershasemphasizedthei nterfacebetweenaccountingandmarketing,whileotherspaymoreattentiononlinkagestostrateg y.The1990saredescribedas“theglorydecade”whereacademics,consultantsandpractitionersal lplayedaroleinpopularizingstrategicaccounting(Langfield-

Smith,2008).ShankandGovindarajan(1993)notethatmanySMAtechniqueshasbeenimpleme ntedaspilotstudiesinUScompaniesandpublishedasteachingcasestudies,oraschaptersinbooks ProfessionaljournalscarriedarticleswithS M A themesandthetrainingactivitieso f professio nalaccountingbodiesfocusedonSCMtoolsandtechniques(Langfield-

Smith,2008).GlobalconsultingfirmsdevelopedveryactivepracticesinthefieldofSMAandthe rebytheSMAterm,duetotheabsenceofgenerallyconceptualframework,rangesinitsdefinition sfromnarrowones(competitor-focusedandperformancemeasurementpractices)tothe umbrella under the viewpointof“external orientation”.

SMA techniques Craven, and Tayles

SMA practices lack a universally accepted conceptual framework, resulting in a variety of accounting techniques with strategic focuses Significant overlaps exist among the classifications of SMA techniques, particularly in areas such as customer accounting and strategic accounting Despite differing research perspectives, techniques like strategic cost accounting, competitor accounting, and strategic accounting are widely recognized as essential components of SMA practices Additionally, Guilding and McManus (2002) introduced three customer-focused techniques, highlighting customer accounting as a potential fourth dimension However, the literature often overlooks customer accounting, possibly due to its late emergence and challenges in observation.

Table 1.4.Literature reviewofessential techniques instrategic managementaccounting toolbox

Recent studies on Strategic Management Accounting (SMA) contribute to the literature by identifying key SMA techniques relevant for corporations and analyzing their dissemination based on structural characteristics Cluster analysis reveals performance differences among various corporate groups, with the usage of SMA techniques varying by firm type For instance, Lachmann, Knauer, and Trapp (2013) note that many SMA techniques initially designed for the non-hospital sector are now applied in hospitals; however, certain widely-used techniques, such as the balanced scorecard and activity-based costing, are only moderately utilized in these settings Additionally, Cadez (2006) identifies that capital budgeting and competitor-focused techniques are the most commonly employed, while customer-focused techniques rank as the least utilized.

Thisthemediscoversstrategicmanagementaccountingintheorganizationalcontextbyb uilding onthepremisesofcontingency theory.Thestudiestried toaffirmthatperformanceisaproductofanappropriatefitbetweenthestructure(managementacc ounting system)andcontext (contingent factors),asthestudyofCadez (2007).Ascanb e showedintheresearchoutcomesofGerdin(2005);SeamanandWilliams(2011 ),SMAplaysaroleasmediumfocusingonperformancemeasurementusingstrategicratherthanta cticalindicators owingtoSMA’ssupport to the organization’s strategic intent.

Recent studies have explored the impact of competitive strategies and strategic management accounting (SMA) techniques on the perceived performance of medium and large businesses For instance, Cinquini and Tenucci (2010) found that Italian manufacturing firms with sales exceeding $25 million are more inclined to utilize SMA techniques focused on cost information when employing defender and cost leader strategies Similarly, Fowzia (2011) highlighted variations in the application of SMA techniques across different strategies, such as cost leadership and differentiation Aykan and Aksoylu (2013) further investigated the significant effects of competitive strategies—cost leadership, differentiation, and focusing—on both qualitative and quantitative performance, revealing that differentiation strategies and customer-oriented SMA techniques positively influence the perceived qualitative performance of businesses.

Surprisingly,thereisanimportantlysmallerattentioninliteraturebeingpaidontheprocesso fSMAusageincomparisonwithsomeotherresearchaspectsthatdiscussedwitha greatdealofarti cles,conferencepapers.SomeresearchershaveseenSMAasaprocessandarguethattheusageofSMAtechniquescanbeframedintoprocessstages(Langfield-

Smith,2008).Likewise,thevarietyo f SMAdefinitions,therearealsovariationsinperceptionsof theSMAprocess.Forexamples,DixonandSmith(1993)presentfourstagestotheirSMAprocess:

“strategicbusinessunitidentification,strategiccostanalysis,strategicmarketanalysis,andstrate gyevaluation”whileBrouthersandRoozen(1999)thinkthatt h e usageofS M A techniquesviat hreeprocessstages:(1)monitoring,(2)decision- makingandplanning,and(3)controlling.Inthiscontext,Lord(1996)differentiatesSMAasasix- stageprocess as follows:

FollowingLord(1996)’sstudy,Shahetal.(2011)summarizeSMAprocessintofourstages: (1)collectinginformationrelatedt o thecompetitors,(2)usingaccountingforstrategicdecisions, (3)cuttingcostso n thebasiso f strategicdecisionsand(4)gainingcompetitiveadvantagethrough identifyingopportunitiesandstrategicchoice.Overall,althoughtheprocesso f strategicmanage mentaccountingusagecanb e variedbytheviewpointofresearchers,theperceptionofthisproces smajorlyreliesontheperceptionofstrategicmanagement process.

Insummary,theissueofstrategicmanagementaccountinghasbeenstudiedworldwidefor morethan25yearsanditcanbearguedthatSMAhasmadeanimpactonpractice,scholarsandaccou nting.AlthoughitexiststheinterestofhowSMAmanagesintellectualcapitalorintangibles,littler esearchtothebestofmyknowledgedoempiricalexploratorystudytodiscoverthisissue.Therefor e,itmayopenmorerecentlyICstageresearchhascontinuedtofocusondevelopinghowintellectua lcapitalismanagedandreportedandmoreimportantlyhowstrategicmanagementaccountingpra cticesareappliedtomanage intellectual capital.

1.2.5.Reviewofstudies investigatingthe relationship betweenstrategic managementaccounting practices andcorporate performance

Theaccumulatedbodyo f evidencealsosuggeststhattailoringanorganisation’sstrategicm anagementaccountingcontrolsystemtoitsstrategymayresultinenhancedperformance.Mostem piricalworkinthisareaassumesa contingencyapproach.Contingencytheoryassumestheexpect ationthatthereisastructuraldesignthatbestfitsagivenstrategyandhenceresultsinhighestperfor mance(Cadez& Guilding,2012).Thereby,manystudies,basedo n contingencytheory,haveex aminedtherelationshipamongststrategy,SMApracticesandcorporateperformance.Thestartpo intoftheempiricalresearchonthecorrelationbetweenSMApracticesandperformanceisthework o f ChenhallandLangfield-

Smith(1998)discoverthattherearepositiveassociationsbetweenperformanceanda rangeo f S MApractices,undervariousstrategicorientations.Thefollowingstudiesalsofinda positivedirec trelationshipbetweenSMApracticesandcorporateperformanceorperceivedstrategymoderati ngthepositivecorrelationbetweenS M A practicesandfirmperformance.Forinstances,Aykana ndAksoylu(2013)discovertheeffectsofcompetitivestrategiesandstrategicmanagementaccou ntingtechniquesontheperceivedqualitativeandquantitativeperformanceofmediumandlargesi zebusinessesinKayseri,Turkey.Insimilarity,Al-MawaliandAl-

In a study by Shammari (2013), an empirical investigation involving 296 companies in Jordan revealed that the use of strategic management accounting (SMA) positively influences organizational performance, with perceived environmental uncertainty moderating this relationship (Al-Mawali & Al-Shammari, 2013) Additionally, Ramljak and Rogošić (2012) demonstrated that the synergistic effect of various SMA techniques enhances cost control and reduction Furthermore, Cadez and Guilding (2012) adopted a holistic configurational approach, utilizing contingency theory to analyze the interplay between strategy, SMA, and performance among 109 manufacturing companies Their findings indicate that higher levels of SMA usage and increased accountant involvement in strategic processes align more closely with a dynamic prospector strategy, ultimately leading to improved performance.

Ingenerally,thecorrelationbetweenSMApracticesandcorporateperformancehasbeenco nductedinarangeofcountriessuchasAustralian(Chenhall&Langfield-

Smith,1998),U K (Ma& Tayles,2009),Malaysian(Hassan,Muhammad,& Ismail,2011),Cro atia(Ramljak& Rogošić,2012),Slovenian(Cadez& Guilding,2012),Jordan(Al-Mawali&Al- Shammari,2013)andtheexactnatureofthispositivecorrelationisconsistent inallofstudies(see Appendix3).

Despite numerous studies across various countries examining the correlation between Strategic Management Accounting (SMA) practices and performance, the research methodologies employed remain largely unchanged Most studies utilize a question format asking, "To what extent does your organization use the following techniques?" followed by a Likert scale from 1 (not at all) to 7 (to a great extent) Managers assess their company's performance relative to major competitors using both financial and non-financial indicators, responding on a seven-point scale from 1 (Poor) to 7 (Excellent) The measurement of SMA techniques often draws on frameworks introduced by Cravens and Guilding (2001) and Guilding and McManus (2002) However, there is a notable gap in research concerning the integration of survey data on SMA techniques with financial data on corporate performance Some studies, like those by Ma and Tayles (2009), employ case study methods to investigate the changes facilitating the adoption of SMA and the strategic repositioning of management accountants, ultimately leading to improved performance.

Reviewofstudiesofintellectual capitalandstrategic management accountinginVietnam

Vietnam, a developing country with a large population, underwent significant changes in 1986 when individual entrepreneurs gained the right to participate in light industry and economic reforms were approved, reducing state control Since these reforms, Vietnam has experienced remarkable economic growth, with an average GDP growth rate of 6.45% from 2000 to 2017, peaking at 8.48% in late 2007 and dipping to 3.12% in early 2009 Despite a smooth transition to a market economy and a strong entrepreneurial spirit, challenges remain, including inadequate physical infrastructure, technology, marketing skills, and clarity in regulations To enhance the competence of its labor force, Vietnam must improve education quality, particularly in areas related to intellectual property protection, where only about 25,000 products and services have been registered For Vietnamese exporters to strengthen their position in the international market, they need to acquire knowledge in international banking, shipping, insurance, and marketing to foster better international relations.

(Dana,1994).ThesuccessofVietnameconomywouldappeartheoutcomeofanintangiblecombi nationofnationalstructuralcapitalandnaturalhumancapitalaswellinternationalrelationsastheo pennesstoideasinpolicyandleadershipaftereconomicreforms,acultureofenduringhardshipsa ndabilitytolearnandadapt.Fromthesereasons,initiativesindevelopingintellectualcapitalinVie tnamisextremelycritical;therebygovernmentandbusinessesshouldgivehigherprioritytointell ectualcapitalasthefutureofthe country,Vietnameseenterprises.

Theemergenceofaprivatesector,thedevelopmentofsecuritiesmarketsandparticipationin internationaltradinghavepositionedVietnamaso n e o f theworld’sgrowingeconomies.Asin manyothercountries,thepublicenterprisesareanimportantcomponentofVietnameseeconomy sincethemarketcapitalizationvalueoflistedcompaniesconsistsof 26.8%of VietnameseGDPi n2015(TradingEconomics,2017).WhenVietnam’sdeeperintegrationintotheglobaleconomy, especiallytheTrans-

PacificPartnership(TPP)ortheestablishmentoftheASEANEconomicCommunity(AEC),thisi mpliesthatthecompetitiveenvironmentfacedb y Vietnameselistedenterpriseshasintensified.

T h e floodo f foreigncompaniesintoVietnamhaspositiveimpactssucha s inflowofknowledge,skillsandinfrastructure.Indirectly,thegreaterlevelofcompetition hasencouragedinnovationandpositivedevelopmentineachindustry.Althoughtherearemany“i ncremental”or“bigbang”changesinVietnameseoverallorganizations,includinglistedcompan ies,duringVietnam’sprogressofinternationalintegration,thesehavenotactuallymeasuredorv aluedtheirintellectualcapital(i.e.humanresourcescapital,structuralcapital,relationalcapital)w hicharegeneratedinthepastandaftertheimpactsd u e tocompetitive pressures.

Mostofthe world’sintellectualcapitalresearchissourcedoutofWesterncountries.T h e empiricalstudieso nintellectualcapitalhavebeenconductedinmanycountries,includingbutnottolimitedto,North America(Bontis,1998;Riahi-

Belkaoui,2003),Germany(Bollenetal.,2005),SouthAfrica(Firer&Mitchell-

Williams,2003),Australia(Dumay,2009),Bangladeshi(T.Hussain,Chakraborty,&Rahman,2 010),China(J.Chen,Zhu,& HongYuan,2004)andconductedinmanyAsiancountriessuchasMa laysian(Bontisetal.,2000),Taiwan(Ming-

Chinetal.,2005),Singapore(HongPewetal.,2007),Thai(Saengchan,2008).Althoughitwoulds eemtheemergingAsianeconomieshavingexperiencedsignificantgrowthinrecentyears,thereis limitedresearchgenerallyintheroleofICinsustainingthatrapidgrowth(Nga&Thomas,2005).In Vietnam,intellectualcapital researchhas not yet obtainedanadequate attention.

Since the 2010s, leading international interdisciplinary accounting research conferences have provided enhanced opportunities for intellectual capital (IC) researchers to share and refine their work While some sessions focus on IC, most papers presented at conferences in Vietnam are authored by international researchers and fail to recognize the unique context of Vietnamese IC studies A review of academic databases reveals only one significant paper by Nga and Thomas (2005), which discusses the role of IC in Vietnam's development at national, industrial, and firm levels, offering policy suggestions Another article by Nhon, Thong, and Van Phuong (2018) examines the impacts of human, organizational, and social capital on firm performance, although it lacks empirical research This indicates a pressing need for more research on IC in Vietnam, as existing Western studies may not be directly applicable to the Vietnamese context Thus, understanding how Vietnamese managers perceive and understand intellectual capital is crucial for effective implementation.

EconomictransformationinVietnamhasbeenakeydriverfordevelopmentoftheeconom yandbusinesses.Intheprogressofintegrationwiththeinternationalaccounting,Vietnameseente rpriseshavegraduallyappliedtheadvancedaccountingtechniques,inlinewithmarketmechanis ms.Overthepastdecade,sinceithasbeenofficiallyrecognizedintheAccountingLaw2003andint heCircular53/2006/TT-

BTC,managementaccountinginVietnamhascertaindevelopmentstagesalthoughitappearedlo ngtimeagointheworld.T h e issuesaboutVietnamesemanagementaccountingsystemwerebeg untostudyfromtheearly1990swithagreatdealofdistinctthemesincluding,butnotlimitedtothel istbelow(seeinTable1.5).

 Theauthorcameupwithorganizationsolutionsofmanagementaccou nting nestedwithinfinancial accounting(Dung,1998).

 Thedirectionsarehowtobuildreportssystemo f managementaccounti ng inVietnamese enterprises (Quang,1999).

2000sManagementaccountinghasbeenstudiedin- depthwithinonenarrowerindustry,suchasinmanufacturingcompanies(Le ,2002),miningorganizations(Hoi,2007),constructionstate- ownedenterprises(Giang,2002),companiesoperatedintransportationind ustry(Dinh, 2003)orpharmaceutical industry(Thuy,2007).

2010sManagementaccountinghasbeenstudiedinassociationwiththeotherresearc hfieldssuchasmanagementofenvironmentalissues(Thien,2010),sus tainabledevelopmentreporting(Thien&Hung,2016),corporatesocia lresponsibilities(Long,2015),managementcontrolsystem(Tran,201 0),strategicdecisionmakinginmarketorientation andcompetition(Nguyen&Doan,2016).

 Thefactorshavefacilitatedtheuseofstrategicmanagementaccounting inVietnam– atransitional economy(Anh,2010).

 Theauthorshavefocusedononlyoneof strategicmanagementaccount ingtechniques(i.e.Strategiccostmanagement(Hoa,2014),Time- drivenABC(Thien,2014),Leanaccounting(Hoa,2015),Balancedsco recard(Van,2015))toanalysetheconditionsresultingin the successful implementation.

Overall,Vietnam’seconomic,politicalandsocialenvironmentaremuchmoredifferentfro mtheWesterncountriesorevenotherAsiancountries.SinceVietnamadoptedanopen- doorpolicy,thelevelofcompetitionintheeconomyhasbeenincreasingsignificantlyformostViet nameseenterprises,becausemanyprivates,jointventuresandthewhollyforeign- ownedenterpriseshavebeenestablishedinVietnamduringthelasttwodecades(Anh,2010).Ther efore,theforeignorganizationsbringpracticalknowledgeofstrategicmanagementaccountingi ntroducedtoVietnamesepractitionersandscholars.Notsurprisingly,hence,theissueofstrategic managementaccountingstartedtobestudiedinVietnamsincethe2010s;however,thereh a s bee nlittlesystematicdocumentationandanalysiso f recenteffortstotheuseo f strategicmanagemen taccountingpracticesi n

Vietnameseenterprises.InVietnam,somestudies(Loi(2014);QueandThien(2014))implythatt hesmallandmediumenterprisesapplythetraditionalmanagementaccountingandonlymedium- to- largeenterprisespaymoreattentiononimplementingstrategicmanagementaccountingtoobtain relevantinformationfordecisionmaking.Littleempiricalresearchisfoundtoinvestigatetheimpa ctofstrategicmanagementaccountingpracticesonVietnameseenterprises’performancealthou ghthisisapopularresearchtopicexaminedinmany other countries.

Researchgaps

Thisstudyhasidentifiedthreemajorresearchgaps:lacko f studiesconcerningperformance implicationofintellectualcapitalinassociationwiththemediatingroleofstrategicmanagement accountingpractices,lacko f empiricalresearchconcerningtherelationshipbetweenICandeach groupofSMApractices,andlackofVietnamempiricalstudiesonintellectual capital andstrategicmanagement accounting practices.

InthehistoryofICaccountingresearch,thefocusofempiricalstudieshasalwaysbeenthed irectrelationshipbetweenintellectualcapitalcomponentsandcorporateperformance.A littleres earchinvestigatesthatintellectualcapitalhasanindirectrelationshiptocorporateperformance.A ccordingtoIttnerandLarcker(1998),managementisrequiredtoidentify,measureandcommunic atet h e valuedrivers(i.e.intellectualcapital)expectedtoimproveinformationsystems,perform ancesandresourceallocationforinvestors.Thissuggeststhatorganizationswithstronglevelofint ellectualcapitalshouldhavedevelopedmanagementaccountingwithstrategicdirectionsthatsup portsuchendeavors.However,accordingtoTaylesetal.

In 2007, it was noted that the relationship between high levels of intellectual capital (IC) and the development of strategic management accounting (SMA) practices to enhance corporate performance remains largely unexplored While existing models typically suggest an indirect link between strategy and performance mediated by management practices, few studies have systematically examined how these practices influence the connection between resources and performance Notably, Asiaei, Jusoh, and Bontis (2018) investigated the mediating effect of performance measurement systems, a key SMA technique, on the relationship between IC and organizational performance Consequently, there is limited understanding of how SMA practices mediate the impact of intellectual capital on corporate performance, as highlighted in the literature review by Alcaniz et al.

(2011),thepractitioner- orientedliteratureo n IChasbecomerepetitive,i.e.thedirectrelationshipbetweenICandperform anceisrepeatedlyexaminedinmanyotherresearchcontexts.Todevelopfurtherresearchdirectio n,thisraisestheneedforastudythatsystematicallyinvestigatesbothdirectandindirecteffectsofi ntellectualcapitaloncorporateperformancethroughthemediatorofstrategicmanagement accounting practices withinorganisations.

1)observe,although ithasbeen arguedthatprofessionalaccountantsshouldadopta morestrategicmanagementaccountingappr oachtoavoidneglectingtheorganization’smostvaluableIC,itis unclearjustwhatrolemanagementaccounting playsinassociationwithICmanagementinhighICcompanies.Itisbecausethereisverylittleempi ricalacademicliteratureo nhowmanagementaccountingpracticesevolveasorganizationsadapt theirmanagementstrategiesaswellpracticestoreflectthevaluedrivers(i.e.intellectualcapital)w hentheyaredevelopingonthebasisofstrategicintangibleassets.Inotherwords,howstrategicma nagementaccountinghandlesintellectualcapital is another gapthat shouldbebridged.

Intermso f researchvenue,mosto f thestudieso n intellectualcapitalandSMApracticesha vebeenconductedindevelopedWesterncountriesandsomeofAsiancountriessuchasChina,Mal aysia,Taiwan,HongKongratherthaninAsiandevelopingcountrieswiththetransitionaleconom y–

Vietnam.Althoughthepopularitiesofwesternstudiesonintellectualcapitalhavebuiltontheasser tionthatitisthekeysourceofsuperiorperformance,thereareveryfewstudiesindevelopingcountri esvalidating,operationalizingabovepropositionswherethebusinessenvironmentisveryunstab lelike

Vietnam's cultural, economic, and political differences from Western countries significantly influence the development of strategic management accounting (SMA) practices While Vietnam's collectivist culture contrasts with the individualism prevalent in the West, it raises questions about how this national culture shapes the implementation of SMA in Vietnamese enterprises Despite numerous international studies highlighting the advantages of SMA, there is a lack of empirical research examining the relationship between SMA practices and corporate performance specifically within the Vietnamese context Therefore, investigating the impacts of SMA on the performance of Vietnamese enterprises could enhance our understanding of whether the benefits of SMA are consistently realized in transitional economies, similar to those in Western settings.

Ontheotherhand,althoughresearchintheextantliteraturehasprimarilyfocusedonthevalue relevanceandthemarketvaluationofintellectualcapitalinmanyothercountries(e.g.Ming- Chinetal.

(2005);MondalandGhosh(2012);Cleary(2015)),theperformanceo f intellectualcapitalremai nsempiricallyunder- exploredinthecontextofVietnam.Morespecially,Vietnameseempiricalcross- sectionalstudiesoftheperformanceimplicationofintangibleinvestmentsorintellectualcapitala rescarceprobablyduetotwomaindifficulties.Firstly, Vietnamese enterprises oftendonotprovideacomprehensive accountforintangibleinvestments.Muchoftheexpendituresinthiscategoryareexpensedrathert hancapitalized.Disclosureonthoseexpendituresisalsoseverelyinadequate.Secondly,because Vietnamesemanagershavenotactuallyrealizedthecriticalvalueofintellectualcapitalintheirma nagingprocess,suchabusinessenvironmenthavingnomoreconcernaboutintellectualcapitalma ynotboostthewaveofICresearchinVietnam.Asevidenceo f this,fewresearchersinVietnamha veaddressedtheissueofperformanceimplicationofintellectualcapital.

Therefore,thestudiesonintellectualcapitalaswellasstrategicmanagementaccountingint hecontextofanAsiancountry,thecaseofVietnamwiththetransitionaleconomy, canaddmore insight to the literature.

Chapter1 reviewstheinternationalstudiesandVietnamesestudiesintermso f intellectual capital,strategicmanagementaccounting,corporateperformancesandtheirmutual relationships to identifyresearchgaps for this research.

Althoughthefocusofempiricalstudieshasalwaysbeenthedirectrelationshipbetweenintel lectualcapitalcomponentsandcorporateperformance,alittleresearchinvestigatesthatintellectu alcapitalhasanindirectrelationshiptocorporateperformance,especiallyviathemediatingcorrel ationofstrategicmanagementaccountingpractices.Inaddition,thereisverylittleempiricalacad emicliteraturethatmakingclearlywhattheroleo f strategicmanagement accounting plays in relationwithintellectual capital.

Liketheothercountries,intellectualcapitalisoneofintangibles,thatareextremelyimporta nttosustainthecompetitiveadvantagesofaneconomyorafirm.Eventhoughintellectualcapitalr esearch beganfromthe1980s,intellectualcapitalresearchinVietnamisverylimitedoritisevenlyundenia blethatthisissuedepartsfromthestartingpointintheVietnamesecontext.Hence,theauthorbeliev esthenecessityofasystematic,completedstudyonthecorrelationbetweenintellectualcapital,str ategicmanagementaccountingpracticesandcorporateperformanceinthecasestudyofVietnam. Thisstudyn o t onlycontributesintoabodyofVietnameseliteraturebutalsodevelopsthegeneral lytheoretical contents relatedtoICmanagement bySMA practices.

Thenextchapterintroducesnotonlythedefinitiono f intellectualcapitalanditscomponents butalsodiscussestheconceptsofcorporateperformanceandstrategicmanagementaccountingpr actices.Theexistingtheoriesunderpinningthemeasurementofintellectualcapitalareintroduced asthepremisesofliteraturetoconstructtheICvariablesinChapter3.

THE CONCEPTS AND INTELLECTUAL

Componentsofintellectual capital

ICresearchers,suchasBarney(1991b),Brooking(1996),EdvinssonandSullivan(1996),S veiby(1997),Stewart andRuckdeschel (1998),Pettyand Guthrie (2000);BontisandFitz- enz(2002),Wang(2011),allincludehumancapital(HC)asacomponentofIC.

Human capital encompasses more than just the workforce; it includes the individual competencies of employees, such as knowledge, skills, innovativeness, and talent (McGregor, Tweed, & Pech, 2004) Barney (1991b) further defines human capital to include training, judgment, relationships, and the tacit knowledge that employees possess (Bontis & Fitz-enz, 2002) This tacit knowledge can be externalized into explicit knowledge, which can be stored in knowledge management systems Edvinsson and Sullivan (1996) describe human capital as comprising skills, attitudes, and intellectual agility Skills generate value through the knowledge and talent of individuals, while attitudes are influenced by personality traits and require minimal organizational effort for improvement Intellectual agility refers to the ability to transfer knowledge across different contexts (Edvinsson & Sullivan, 1996).

Humancapitaliscrucialtoorganizationsasa sourceo f innovationandstrategicrenewaltoi nnovativelyrespondtoenvironmentalchangesbydevelopingground- breakingstrategiesandefficientlyimplementingstrategiesforcomplexanddynamicenvironme nt(Wright,McMahan,&McWilliams,1994).Togetherwiththegrowthofknowledge- basedeconomy,theimportanceo f humancapitalincreases.A s employeesgainexperience,tech niquesandskillsontheirjobs,theymaybecomeafirm’sindispensableasset(HelmStevens,2011). HigherlevelofICoftenresultingreaterproductivityandhigherincomes(HelmStevens,2011);iti sthereforeintheinterestsofhumanresourcemanagerstorecruitbrightestemployeesanddevelope xplicitknowledgeofemployeesasameanofachievingcompetitive advantage(Bontis&Fitz- enz, 2002).

Whenanalysingthecontentsthatshouldb e reportedinICreport,CampbellandAbdul Rahman(2010)illustratetheelementsofhuman capital detailedinAppendix4.

Structural capital, as defined by Bontis (2001), encompasses the hardware, software, databases, organizational structure, patents, trademarks, and other resources that employees utilize to support business processes It focuses on the "knowledge infrastructure embedded within the routines of an organization," which includes technological components and architectural competencies (Gold and Malhotra, 2001) Additionally, structural capital embodies the learning and knowledge enacted in daily activities (Bontis, Bart, & Kong, 2007), representing the knowledge retained by an organization after employees depart (Mouritsen, Nikolaj, & Marr, 2004; Nazari, 2010; Wang, 2011) While human capital is a primary driver of structural capital and influences the organizational form (Nazari, 2010), structural capital exists independently of human capital (J Chen et al., 2004) For instance, patents, initially created by human capital, ultimately belong to the company after their creation.

Structuralcapitalisvitaltoorganizationsbecauseitdealswiththemechanismsandstructure softheorganization(Bontisetal.,2007).Structuralcapitalbecomesthesupportiveinfrastructuref orhumancapitalasitincludesallofnon- humanstorehousesofknowledgeinorganizationssuchasdatabases,processmanuals,routinepro cedures,organizationalcultureandcorporatepublicationsthatcreatevaluefortheorganization( Bontis&Fitz-enz, 2002;Guthrie&Petty, 2000;Nazari, 2010).

Amongthedifferentcomponentsofintellectualcapital,structuralcapitalisthemostcomple xbecauseitintertwineswithothercapitalsintermsofdefinition.Thisstudyadaptsthedefinitionpr ovidedbyBontis(2001)andCampbellandAbdulRahman(2010)toavoidpossibleoverlappedme anings.Hence,technologicalandarchitecturalelementsincludingorganizationalculture,proces sa n d managementphilosophyrepresenttheelementso f structuralcapitalinthisresearch.When analysingthecontentsthatshouldbereportedinICreport,Campbelland AbdulRahman (2010)illustratetheelementsofstructuralcapitaldetailedinAppendix5.

Thethirdcomponentofintellectualcapital,relationalcapital,isalsoproblematicalinterm ofitsdefinition.SomeresearcherssuchasSaint-

Onge(1996);M'PhersonandPike(2001);Wang(2011)refertocustomercapitalasrelationalcapit al,definingcustomercapitalandrelationalcapitalsimilarly.Customercapitalisdefinedasthestre ngthandloyaltyo f customerrelationseitherwithino r outsideorganization(M'Pherson& Pike,2 001;Saint-

Focusing solely on a single customer can be problematic, as it may lead to the neglect of other crucial stakeholders such as shareholders, creditors, and employees For-profit firms operate within a dynamic environment that includes multiple groups of external stakeholders Therefore, the concept of relational capital is essential, as it encompasses all of an organization’s relationships with external stakeholders, expanding beyond just customer capital This broader view includes relationships with suppliers, allies, trade unions, and other partners, as well as customer relationships that contribute to brand image, loyalty, and recognition.

(Sydler,Haefliger,& Pruksa,2014).Generally,MaríaViedmaMarti(2001)definesrelationalca pitalastheabilityo f anorganizationtointeractpositivelywithbusinesscommunitymemberstom otivatethepotentialforwealthcreationbyenhancinghumanandstructural capital.

Relational capital is crucial for organizations as it fosters innovation and future growth opportunities According to Kong (2009), effective organizational relationships involve knowledge exchange with external stakeholders, enhancing the organization's ability to generate creative ideas This close collaboration allows organizations to better understand and meet the needs of their stakeholders, ultimately leading to improved products and services (Helm Stevens, 2011) By building relational capital, companies can enhance their competitive edge and secure sustainable growth opportunities Youndt and Snell (2004) emphasize that alongside investing in structural capital to improve processes, managers should also focus on social relations to safeguard their organizations against unfair competition and maintain their competitive advantages.

WhenanalysingthecontentsthatshouldbereportedinICreport,CampbellandAbdulRahman(2010)illustratetheelementsofrelational capital detailedinAppendix6.

Definitionofcorporate performance

Dorestani(2009)definescorporateperformanceasasetofmeasuresfocusingonfactorst hataremostcriticalforthesuccessoftheorganization.Corporateperformancemeasurementsare indicatorsincludingbothfinancialandnon- financialinformation.Formanyyearsframeworksoncorporateperformancehavebeenusedbyor ganizationstodefinethemeasuresthatmanagersshouldusetoassesstheirfirms’performances.Fr omearlyinthetwentiethcentury,DuPontusesapyramidoffinancialratios,whichlinkedawidera ngeoffinancialratiostoreturnsoninvestmentasexcellentresourcestodeterminethewealtho f an organizationforitsshareholders.F o r examples,thereturnonassets(ROA),returnonequity(RO E),andreturnoncapitalemployed(ROCE)areusedasratio-basedmeasuresofafirm’s overallfinancial performance fromdifferent perspectives.

Kaplan and Norton (2001) emphasize that traditional financial ratios fail to reflect the evolving competitive landscape and strategies of modern organizations, highlighting the limitations of the DuPont pyramid, which focuses on historical costs and promotes short-term thinking Investors argue that in the knowledge-based and innovation-driven era, financial statements become irrelevant as they do not adequately capture the economic value of investments in intangible assets, leading to increased information asymmetry and inefficient resource allocation in the stock market (Arvidsson, 2011) The significant gap between a firm's market value and the book value of its recorded assets has prompted the development of contemporary approaches, such as Economic Value Added (EVA) and Tobin's Q, to better quantify intangibles and address these challenges.

,ormarket-to- bookratio(Gebhardt,2002).Itseemsthatthedevelopmentofalltheseindicatorstakesa tangiblea pproachtointangibles(Gebhardt,2002).A s a result,manyresearcherssuggestusingEVA,Tobin qormarket-to- bookratioasindicatorsofafirm’sfinancialperformancetomakethebesto f a situationaddressin gtheissueso f quantifying intangibles.

Ontheotherhand,manyresearchers(F.Chen,Hope,Li,&Wang,2011;Ming-

Chinetal.,2005)havearguedthatifthemarketisefficient,investorswillputhighervalueonthefir mswithgreaterinvestmentefficiency.Inordertomaximizeshareholders’values,firmshouldinve stuntilthemarginalbenefitequalst h e marginalcosto f investment.

However,d u e toinformationasymmetryproblembetweenthemanagementandtheshareholde rs,managementmaydeviatetheiroptimalinvestmentlevelsandhencesufferfromunderinvestme nt(lowerinvestmentthanexpected)oroverinvestment(greaterinvestmentthanexpected)

(JuanPedroSánchez&Gomariz,2012).Inotherwords,withinperfectfinancialmarkets,allpositi venetpresentvalueprojectsshouldb e financeandcarriedouttoenhancefirmvalue.Nevertheless ,marketimperfections,aswellasinformationasymmetriesand agency costsmay lead tonegativenetpresentvalueprojectsbeingcarriedout(overinvestment)andtotherejectingofposi tivenetpresentvalueprojects(underinvestment)

(Healy&Palepu,2001;Hubbard,1997).Accordingtoagencytheory,bothoverinvestmentandun derinvestmentcanbeexplainedbytheexistenceofasymmetricinformationamongststakeholder s.Therefore,investmentefficiencyisconsideredasanindicator to measure corporate performance ininternalmanagement activities.

In addition to traditional financial metrics like investment efficiency and market value assessments, organizations are increasingly adopting non-financial performance measures that align with their strategic objectives Recent trends indicate that financial analysts and investors are looking beyond financial statements to evaluate a firm's overall value Previous studies highlight a disparity in how management prioritizes the disclosure of non-financial information, with Vandemaele, Vergauwen, and Smith (2005) noting a greater emphasis on external relational structures, such as customer and distributor relationships, compared to human capital aspects like employee education and knowledge Arvidsson (2011) further identifies corporate social responsibility as a category of non-financial information that receives minimal attention in disclosures Consequently, non-financial indicators play a crucial role in helping owners and management assess corporate performance, although this study narrows its focus primarily to financial information as a criterion for measuring corporate success.

Thefour- stagestockmarketvaluationmodelbyDorestani(2009)isusedtoreportcorporate performance inaccountingliterature, as follows:

4 Stock price 3 Intrinsic value 2 Financial indicators

Non- financial indicators Returns Business Activities

Figure 2.1.Four-stage modelofcorporatemarket valuation

Determinantsofstrategicmanagement accounting practices

Worldwidecompetitivepressures;deregulationandadvancesininformationandmanufa cturingtechnologyhavechangedthenatureo f o u r economyandcausedmanymanufacturingan dservicesindustriestodramaticallychangethewayinwhichtheyoperate(Hasen&Mowen,2012) Theeffectsofthisnewenvironmentalsettingcontinuetochangenotonlyapproachestoproducti onandtheapplicationofautomatedequipmentandflexibletechnologies,butalsoorganizational structure,businessstrategiesandmanagerialphilosophies.AsDrury (2013)argues:

“Tocompetesuccessfullyintoday’shighlycompetitiveglobalenvironmentcompaniesa r e makingcustomersatisfactiona n overridingp r i o r i t y , a d o p t i n g n e w management a p p r o a c h e s , c h a n g i n g t h e i r manufacturingsystemsa n d investingn e w tec hnologies.Thesechangesa r e havinga significantinfluenceo n managementaccountingsyst em(Drury,2013, p.549)”.

Thesechangeschallengedthetraditionalmanagementaccountingsystem.Newbusinesss trategieshavealso questioned theconventionalroleofmanagementaccounting.A s Ashton,Hopper, andScapens (1991)note:

“Theexplorationofthisbyindustrialists,academicsandmanagementconsultantshasp r o d u c e d anideologyofcrisisandtransformationinmanufacturing,inwhichtheroleofconve ntionalmanagementaccountingh a s comeu n d e r increasinglycriticalscrutinyAshtonetal

(Bromwich,1990;Kaplan,1984).Thiscontentionwasbasedonthelacko f abilityo f traditionalm anagementaccountingtofulfiltheinformationrequirementsthatcouldcontributetoorganization s’competitiveness,andlong- termperformance(Kaplan,1984;Kaplan& Norton,2001).Drury(2013)summariestheprincipa lcriticismsunderthefollowing headings:

(3)managementaccountingpracticeshavebecomesubservientt o financialaccountingrequir ementsa nd (4 ) conventionalmanagementaccountingfocusesalmostentirelyoninternalacti vities,whereasverylittleattentionisgiventotheexternalenvironmentinwhichthebusinesso p e r a t e s (Drury,2013,p.562)”.

Newly developed techniques in management accounting focus on areas often neglected by traditional methods, such as customers, competitors, and the long-term effects of strategic decisions (Cadez, 2006) This has led to the emergence of strategic management accounting (SMA) as a tool for achieving competitive advantage, a concept introduced in various literature since 1981 Simmonds, recognized as the father of SMA, first coined the term and defined it as the provision and analysis of management accounting data regarding a business and its competitors to aid in strategy development and monitoring (Simmonds, 1981) This innovative perspective emphasizes the externally focused role of management accountants (Cadez, 2006) Additionally, Bromwich (1988) expands on SMA by defining it as the evaluation of an enterprise's comparative advantages relative to competitors, assessing the lifetime benefits of products to customers and the long-term gains for the firm.

AscanbeseeninthedefinitionofSimmonds(1981)andBromwich(1988),itisimportantt oappreciatetheroleofmanagementaccountingwithintheprocessofdevelopingstrategyandSMAisaformofmanagementaccountinginwhichemphasisisplacedoninformationwhichrelatesto factorsexternaltoentity.WhileSMAisatermusedb y accountingacademicsandsometimesprac titionersintheUK,AustraliaandNew

Zealand,intheUSAthetermstrategiccostmanagement(SCM)ismorecommonlyusedintheliter ature(Shank&Govindarajan,1993).ShankandGovindarajan(1993)describeS C M as“theble ndingofthefinancialanalysiselementsofthreethemesfromthestrategicmanagementliterature– valueanalysis,strategicpositioninganalysis,andcostdriveranalysis”.Clearly,thisdescriptiono f SCMhassimilaritieswithS M A However,somewouldviewSMAasbroaderthanSCM.Table 2.2indicatessomekeydifferencesbetweenstrategicandtraditional management accounting.

Table 2.2.Some keydifferencesbetweenstrategic andtraditional managementaccounting Indicators Strategicmanagement accounting Traditional management accounting

- measureandreportbothfinancialand non-financialperformanceensure efficient useofresources

Competitorcost structureCompetitorprod uct costsRelative market shareRelative profitabilityCompetitorpr ice margin

Cost structureProduct costsMarket shareProfitabilit yPrice margins

Inthe1990s,asubstantialnumberofotherresearchersworkedandtodefinetheconceptofs trategicmanagementaccounting,e.g.Bromwich(1990);Ward(1992);DixonandSmith(1993); FosterandGupta(1994);Guildingetal.(2000);(Cinquini&Tenucci,2010).Although theirdefinition anddescriptionofSMAdifferconsiderably,threetypicalcharacteristicsofSMAcanbedrawnfro mtheir writings:

In this study, the authors identified 12 techniques of Strategic Management Accounting (SMA), which include attribute costing, brand valuation, capital budgeting, competitor cost assessment, competitive position monitoring, competitor performance appraisal, lifecycle costing, quality costing, strategic cost management, strategic pricing, target costing, and value chain costing (Cadez, 2006) Cravens and Guilding (2001) expanded this list to 15 techniques by adding activity-based costing, benchmarking, and integrated performance measurement Additionally, Guilding and McManus (2002) introduced three customer-related SMA techniques: customer profitability analysis, lifetime customer analysis, and the valuation of customer groups, bringing the total to 18 techniques categorized into four groups Cravens and Guilding (2001) identified three main dimensions of SMA practices: strategic cost management, competitor accounting, and strategic accounting This study further incorporates three customer-focused techniques, establishing a fourth dimension known as customer accounting.

Intellectual capital measurement models

The debate surrounding intellectual capital often centers on its measurability (Wall, Kirk, & Martin, 2003) However, the real issue lies not in the inability to measure intellectual capital, but in the multitude of measurement methods available, which can yield diverse and sometimes contradictory results (Fritzsche, 2012) Sveiby (2005) emphasizes that the first question for anyone initiating a measurement effort should be the purpose behind it Luthy (1998) and Mitchell Williams (2001) categorize intellectual capital measurement into at least three models, as shown in Table 2.3 The quantitative approach focuses on assigning numerical values to intellectual capital, while the qualitative approach utilizes scorecards to highlight what is significant for the organization in achieving its objectives.

Table 2.3.Summaryofmeasurement approaches that are mainlyusedinintellectual capital research

- Investor-assignedmarket value (IAMV TM )

- Economic value added(EVA TM )

- Total value creation(TVC TM )

- Inclusive valuation methodology(IMV TM )

AccordingtoSveiby(2005),themethodsunderthemarketcapitalizationmodeloffersome waystocalculatethevalueofintellectualcapitalthroughthedifferencebetweenthecompany’sma rketcapitalizationanditsshareholders’equityinbookvalue.Thecharacteristicofthemarketcapit alizationmodelisthattheyallusecapitalmarketvaluestoestimatethevalueofintellectualcapital. ProminentmethodsunderthismodelsuchasTobinq,Market-to-bookvalueandInvestor- assignedmarketvalue(IAMV TM )are discussedshortlyinAppendix8,beyondthescopeofthisstudy.Themarketcapitalizationmodelc opeswiththechallengethatittotallyrelieso n themarketasa mechanismforassessingthe excess valueofafirmover its replacement cost adjustedbalancesheet.

InmostoftheROAmethods,theauthorsattempttodevelopanindicatorinordertodetermine theefficiencyorpotential valueofIC This methodis calculatedas follows:

“Averagepre- taxearningsofacompanyforaperiodoftimearedividedbytheaveragetangibleassetsofthecom pany.Theresultis acompanyROAthatisthencomparedwithi t s industrya v e r a g e Thedifferencei s multipli edb y t h e company'sa v e r a g e tangiblea s s e t s tocalculateaverageannualearningsfro mtheintangibles.Bydividingtheaveragee a r n i n g s bythecompany'saveragecostofcapita lorinterestrate,anestimateofthevalueo f i t s intangibleassetsorintellectual capitalcanbe found.”(Sveiby,2005,p 126)

Someo f themoreappliedmethodsunderthiscategoryincludingValueAddedIntellectual CapitalCoefficient,CalculatedIntangibleValueandEconomicValueAdded,arediscussedbelo winAppendix9.Mostofthemethodsdiscussedunderthiscategoryusesomeindicatorsthatareder ivedfromhistoricalfinancialreportsasproxiesforthevalueo f intellectualcapital.Thelimitation ofthismodelisthatitisnotprovideanymeasureifICrequired tostartacompany because it providesameasureofICwhile operating.

Quantitative approach – Direct intellectual capitalmodel

ThemodelthatdirectlyevaluatethevaluesofICcomponentsarealsovariedduetothewaytha tthesemethodsoptnumerousvariablesinthedirectintellectualcapitalconsideration.Generally,t hesevariablesarefirstlyincludedinsomecategories.EachcategoryhasanumberofICcomponen tsorvariables.Thesecomponentsareidentifiedandmeasuredseparatelywithineachcategoryan dthenarecombinedtoformanaggregatemeasureofintellectualcapital.ThequalificationoftheI Ccomponentsrequiresvariousscalessuchasnumbercounts,dollarvaluesandratios.Someofthe morepopularmethodsunderthiscategoryincludingIntellectualassetvaluation,Totalvaluecreat ion(TVC TM ),Inclusive valuationmethodology(IMV TM ), are discussedbelow inAppendix10.

Inthismodel,thevariouscomponentsofintangibleassetsorintellectualcapitalareidentifie d,andindicators/ indicesaregeneratedandreportedinscorecards.ThescorecardmodelissimilartodirectICmodel,exceptthatnoestimateismadeofthedollarvalueof theintellectualcapital.Thepurposeofqualitativemodelsistoidentifywhatisimportanttotheorga nizationandassisttheorganizationinmonitoringitsprogresswithregardtothosestatedobjectives SomeofthemorepopularmethodsunderthiscategoryincludingIntangibleAssetsmonitor TM ,Sk andiaNavigator TM ,ICindex TM ,BalancedScorecard TM ,Value chainScoreboard.Thedetaileddiscussionofthese methodssummarizedinshort inAppendix11, but is beyondthe scopeofthis research.

Chapter2presentstheconceptsofintellectualcapital,strategicmanagementaccountingpr actices,corporateperformance,andreviewssomeofICmeasurementmodelsbefore developingthis study’s researchmodels.

This study aligns with the prevailing definition of Intellectual Capital (IC), emphasizing its role in managing strategic intangible resources such as information and knowledge to gain competitive advantages It recognizes three primary interrelated components of IC: human capital, structural (internal) capital, and relational (external) capital, in line with existing literature Measurement of IC can be categorized into quantitative approaches, including direct IC models, ROA models, and market capitalization models, as well as qualitative approaches like scorecard models Additionally, this research classifies 18 Strategic Management Accounting (SMA) techniques into four groups: strategic cost management, competitor accounting, strategic accounting, and customer accounting, building on the foundational work by Guilding et al (2000) and subsequent studies.

Thefour- stagestockmarketvaluationmodelbyDorestani(2009)isusedtoreportcorporateperformance, whichisevaluatedo n fourdimensionincludingproductivity,profitability,non- financialindicatorsandmarketablevalue.However,thisstudyislimitedfinancial dimensions focus.

Thefollowingchapterfocusesonunderlyingconceptualframeworkstodeveloptestable hypotheses whichanswer researchquestions to bridge researchgaps.

THEORETICAL FRAMEWORK AND

Humancapital, structural capital andrelational capital reciprocallyaffect

Managerial activities related to intellectual capital (IC) should work in harmony, as human, structural, and relational capital mutually influence and enhance each other (Edvinsson & Sullivan, 1996; Hsu & Fang, 2009) Their collaboration in generating knowledge creates significant synergy Stewart and Ruckdeschel (1998) emphasize that these three forms of capital complement one another, with IC being most effective when they support each other Research by Bontis and Fitz-Enz (2002) indicates that human capital has a substantial impact on relational capital across all industries and significantly influences structural capital in non-service sectors Additionally, relational capital affects structural capital in both service and non-service industries For instance, employee abilities (human capital) enhance a firm’s process efficiency (structural capital), while high-quality employees attract valuable customers and business partners.

(relationalcapital).Ontheotherhand,relationalcapitalalsopositivelyaffectstructuralcapital(H su&Fang,2009).Forinstance,afirmmaintainingagoodrelationshipwithitscustomersandbusin esspartners(relationalcapital)enablesitsemployeestomanagedailyoperations,businessproces seseffectively(structuralcapital).Allinspiresthisstudytodevelopthefollowing hypotheses:

Hypothesis1a:Humancapital positively impacts onrelational capital.Hypothesis1b:Humancapital positively impacts onstructural capital.Hypothesis 1c:Relational capitalpositively impactsonstructuralcapital.

Intellectual capital impactsonSMApractices(H 2 )

(Davenport&Prusak,1998).Teece (2000,p.37)argues that:

“thecompetitiveadvantageo f companiesi n today’seconomystemsnotf r o m marketp o s i t i o n , butfromdifficulttoreplicateintellectualcapitalandthemannerinwhichtheya r e de ployed.”

Companies are increasingly striving to become learning organizations that prioritize intellectual capital, recognizing that their success hinges on effectively managing this asset (Carlucci, Marr, & Schiuma, 2004) Intellectual capital not only influences knowledge management but also enhances strategic management accounting techniques and traditional management accounting systems (Wiig, 1994) However, intellectual capital alone does not create value or drive growth; it must be integrated with other management factors to be effective (Lev & Daum, 2004) For instance, investments in training yield financial benefits only when paired with improved business processes and appropriate information systems Without these enhancements, intellectual capital remains an untapped resource, encompassing human capital, infrastructure, and knowledge that can transform management systems like accounting and information management Consequently, understanding the impact of intellectual capital on strategic management accounting practices is significantly informed by competence-based theory.

Thecompetence- basedviewconsidersthecompany’scapacitytorecognize,create,strengthenandincreaseits“cor ecompetencies”(Carluccietal.,2004)asthesourceofasoundcompetitiveadvantage.Acompete nceisabundleofskillsandtechnologiesorthesumoflearningcapability(Mouritsen,Bukh,Larse n,&Johansen,2002).AsHamelandPrahalad(2013,p.78)write:

“Thecompanyi s perceiveda s a portfolioofcompetenciesa n d itscompetitivenessi s b a s e d o n t h e c r e a t i o n a n d developmento f competenciesa n d o n t h e realisationo f a strate gyabletocreatealinkbetweenaims,resourcesandcompetencies.”

Competencies are crucial for an organization's development and are reflected in its strategic management accounting practices To foster continuous competency growth, companies must have the necessary resources to enhance their capabilities over time From a competence-based competition perspective, organizations require a blend of "knowledge assets" and "knowledge processes" to effectively execute their business operations This highlights the importance of intellectual capital and strategic management accounting as foundational elements of organizational resources Firms with robust intellectual capital can leverage quality personnel to bridge the gap between internal and external networks, facilitating the transformation of external information into actionable knowledge for improved strategic business planning Strong relationships provide valuable external insights, while skilled personnel enable the effective transfer of this knowledge, forming the basis for well-developed strategic management accounting practices Ultimately, well-designed, reporting-oriented strategic management accounting systems ensure that acquired knowledge is effectively accumulated, stored, integrated, and disseminated throughout the organization.

Thestrategicpositioningliteratureshowsthatthedesignofmanagementaccountingsystem differsbasedonfirm- levelstrategy(e.g.differentiationstrategyorcostleadershipstrategy).Inaddition,bothdifferenti ation-basedandlow-cost- basedfirmsmayusehumancapitalasthestrategicresourcethatdrivestheircorporate- levelstrategy.Moreprecisely,humancapitalisadrivingforceinfluencingtheoptedfirm- levelstrategywhichtherebyimpactso n thedesigno f managementaccounting.Widener(2004)il lustratestherelationshipbetweenmanagementaccountingsystem,firm- levelstrategyandthestrategyo f humancapital inTable 3.1.

Table 3.1.Integrationoffirm-level strategy andreliance onhumancapital

Differentiation-basedfirms Low-cost-basedfirms Lower reliancehumanca on Traditional managementaccounting system

Traditional managementaccounti ng system Higher reliancehumanca on Non-traditional managementaccounting system

According to Widener's (2004) study, firms with lower reliance on human capital tend to design management accounting systems that focus on traditional, aggregate financial result controls In contrast, companies that prioritize human capital throughout the organization are more likely to adopt non-traditional, non-financial result controls and leverage employee contributions in strategic decision-making These firms often consider non-financial measures, such as employee loyalty, staff turnover, and skill development, as leading indicators for strategic decisions Additionally, high human capital firms encourage employee participation in budgeting, favoring more frequent forecasting and targeted setting, which shifts their approach from conventional budgeting to rolling budgeting practices.

Hypothesis2a:Humancapital is positively associatedwiththe practicesofstrategicmanagement accounting.

Strategic management accounting (SMA) is defined as the provision of information that aids managers in strategic decision-making, and it is closely related to structural capital, which encompasses a firm's processes, organizational design, information systems, and corporate culture (Cleary, 2015) Corporate culture, a key component of structural capital, significantly influences the development of a firm’s accounting system (Hsu & Fang, 2009) For instance, a firm with a role culture tends to rely on formalized rules and centralized decision-making, utilizing traditional management accounting practices such as imposed budgeting and financial controls (CIMA, 2014b) In contrast, a task culture promotes teamwork and flexibility, leading to the use of non-financial measures and participative budgeting that enhance creativity and job satisfaction (CIMA, 2014b) Firms that prioritize customer-focused and market-driven strategies aim to develop efficient organizational routines, including SMA, driven by intellectual capital to meet informational demands (Cleary, 2015) For example, focusing structural capital on creating a customer database can enhance SMA practices by reducing decision-making costs associated with inadequate information Based on this discussion, the study proposes the following hypothesis.

Hypothesis2b:Structural capital is positivelyassociated withthe practicesofstrategicmanagement accounting.

Organizations with members who possess extensive relationships and networks tend to excel in information acquisition and resource allocation (Hsu & Fang, 2009) Employees with strong communication skills and external connections have greater access to diverse resources, enhancing strategic management practices Improved connections facilitate the sharing of information and professional technology among business partners, thereby increasing a firm's capability for external information development This relational capital fosters a stronger external focus, particularly concerning competitors, customers, and suppliers, which is crucial for understanding the market environment Consequently, firms can better meet stakeholder needs, driving innovation and economic success Strategic management accountants leverage information from external relationships to generate data that supports effective strategic planning, business performance control, and improved decision-making Therefore, this study proposes the following hypothesis:

Hypothesis 2c:Relational capitalis positively associatedwiththe practicesofstrategicmanagement accounting.

Intellectual capital impactsoncorporate performance (H 3 )

The resource-based view (RBV) of organizations serves as the foundational theory in knowledge management and intellectual capital, often referred to as the knowledge-based theory Introduced by Penrose in 1959 and later developed by Wernerfelt and others, RBV posits that a firm's sustainable competitive advantages stem from its resources, enabling the creation of economic value through effective and innovative resource management While RBV treats knowledge and assets as generic resources, it does not adequately address the specific characteristics of these resources, which may influence a firm's core competencies Wernerfelt expanded on this by suggesting that firms achieve superior performance through the acquisition and strategic use of both tangible and intangible assets Barney further identified four criteria for recognizing strategic assets, emphasizing the importance of understanding how these resources contribute to a firm's competitive edge.

 Valuable:Theymustb e abletoexploitopportunitieso r neutralizethreatsinthefirm’senvi ronment;

Thefirsttypeofassets,generallytangibles,suchasproperty,plants,equipmentandphysica ltechnologiesarecommonplaceinthemarket,therebyeasilyimitableandsubstitutableandcanbe easilytradedontheopenmarket.Therefore,itisdissatisfiedtorecognizeasafirm’sstrategicassets becauseofnotgeneratingasuperiorperformanceifonlybasedontheseresources.Thesecondtyp esofassets,generallyintangiblesnotbeingidentifiedonthefinancialstatement,arevaluable,rare andmostlyinimitableandnon- substitutabletobeassessedasafirm’sstrategicassetswhicharecapableofgeneratingsustainabl e competitive advantages andsuperior financial performance (Barney,1991a).

Followingtheconcepto f strategicassetso f theresource- basedtheory,thekeycharacteristicsofintellectualcapitalasstrategicassetsaretheirrarity,inimita bility,non-substitutabilityandtheirunobservability(Riahi-

Belkaoui,2003).Togetherwiththestrictapplicationoftheabovecriteria,intellectualcapitalisam ixofhumancapital,relationalcapitalandstructuralcapital,thatthesecomponentsofintellectualc apitalarerecognizedasstrategicassets(Hall,1992).Forexample,structuralcapital,whichisowne dbythefirmandisassumednottobereproducedandshared,isregardedasthebestapproximationo fIC(Riahi-

Relational capital is a unique intangible asset that cannot be easily replicated by competitors, as it is developed through business operations (Belkaoui, 2003) Human and structural capital are crucial for value creation within firms (Holland, 2003) In a competitive and turbulent environment, structural capital is essential for enhancing enterprise value, as suggested by Alum and Drucker (1986) and Prahalad (1990) Intellectual capital serves as a strategic asset exclusive to a firm, driving competitive advantages and growth through the innovative deployment of these resources to create new products or services (Amit & Schoemaker, 1993) Therefore, there is a positive correlation between intellectual capital and corporate performance.

Hypothesis3a:There isapositive associationbetweenhumancapital andcorporateperformance (asset turnover, investment efficiency, returnonequity, Tobin q).

Hypothesis3b:There isapositive associationbetweenstructural capital and corporateperformance (asset turnover, investment efficiency, returnonequity, Tobin q).

Hypothesis 3c:There isapositive associationbetweenrelational capital and corporateperformance (asset turnover, investment efficiency, returnonequity, Tobin q).

Aspresentedinthesecondchapter,corporateperformanceismeasuredb y assetturnover,in vestmentefficiency,returnonequityandTobinqasfinancialindicatorsofcorporateperformance measurement.Therelationshipsbetweenintellectualcapitalandeachofthesefinancial indicators, exceptforinvestmentefficiencywereexplored in manypriorstudies.ApplyingVAICintellectualcoefficientswithTaiwaneselistedcompanies,M ing-Chinetal.

(2005)discoverthathumancapitalandstructuralcapitalhavepositiveimpactonafirm’sfinancia lperformancemeasuredbyreturnonequity,returnonassets,growthin net sales anditsmarketvalue measuredbymarket-to-bookvalue In additiontousingVAICmodel,Ming- Chinetal.

L.Chang(2007)’sworkindicatesthattheindexesofVAIChavesignificantlypositiverelationship withfirms’marketvalue(market-to- bookvalueandpricetoearningspershare)andprofitability(profitmargin,ROE,ROA)inbroadin formationtechnologyindustry.LongKweh,Lu,andWang(2014)investigatetheeffecto f intelle ctualcapitalontheoperatingefficiencyofnon- lifeinsurancefirmsinChina.ThisstudysuggeststhatmanagersoftheChinesenon- lifeinsurersshoulddevoteattentiontotheinvestmentsinICtostaysustainable(LongKwehetal.,2 014).Theempiricalstudieshavebeenconductedinmanycountries,includingbutnottolimitedto, NorthAmerica(Bontis,1998;Riahi-

Belkaoui,2003),China(J.Chenetal.,2004),Australia(Dumay,2009),Taiwan(Ming-

Chinetal.,2005),Germany(Bollenetal.,2005),Singapore(HongPewetal.,2007)andSouthAfric a(Firer&Mitchell-Williams,2003),butascarcityofstudyinvestigates inVietnam.

This study explores the relationship between intellectual capital (IC) components and investment efficiency, an area that has been largely overlooked in previous research It highlights the importance of employee roles and well-organized structures, such as processes and procedures, in facilitating effective capital allocation A robust internal control system enhances managerial accountability and monitoring, which can mitigate under- and over-investment issues Additionally, standardized processes enable managers to make informed investment decisions by accurately identifying viable projects based on reliable accounting information Ultimately, the findings suggest that higher levels of IC can assist under-investing companies in increasing their investments, while helping over-investing companies to reduce their investment levels, thereby achieving sustainable investment efficiency.

SMA practices impactoncorporate performance (H 4 )

Thecontingencytheoryoftheorganizationsisusedasabasictheoreticalframeworktoexpl aintherelationshipbetweenstrategicmanagementpracticesandcorporateperformance.Asillust ratedbyAndersonandLanen(1999),thecontingencytheorystatesthatfirmsshouldbedesigneda ndmanagedinconnectionwithitsbusinessenvironment.T h e appropriatedesignofanorganizat ionalstructuredependsontheuncertaintylevelofbusinessenvironmentandthestrategicobjectiv eso f thatorganization.AndersonandLanen(1999)demonstrateabasiccontingencymodeltoex plaintheorganizationalstructureandthecollaborationwithmanagementaccountingpractices,as showninFigure

3.1.AndersonandLanen(1999)indicatethat,firstly,bothendogenousfactors(suchasstrategy,te chnologyandorganizationalculture)andexogenousenvironmentalvariables(suchascompetiti on,environmentaluncertainty)influencethecompetitivestrategy.Next,thecompetitivestrategy willdictateorganizationalstructureviamanagementaccountingpracticeswhichareutilizedtodir ectandcontrolanorganizationtoaimdesirablecorporateperformances(Anderson& Lanen,1999).O n thecontraryrelationship,managementaccountingpracticesalsosupporttheprocessofstr ategydevelopmentthroughstrategicmanagementaccountingtechniques.T o sumu p , “conting encyresearchinmanagement accountingprovidesevidencetosupportthecontingentfitbetweenstrategy,organizationaldesig nandmanagementaccountingsystemswithcorporateperformance”(Sanford,2009).

Ascanbeseeninthebasiccontingencyframework(Figure3.2),attheheartofthemodelisma nagementaccountingsystemusage(thisreferstotheuseofSMApractices)intheprocessofstrategi cdecisionmaking.Thefundamentalofcontingencytheoryholdsthat“fit”isunderstoodasapositiv eimpactoncorporateperformanceowingtocertaincombinationsofmanagementaccountingsys tem(i.e.SMApractices)andcontext(contingencyfactors).Inthebasiccontingencymodel,S M

A playsa roleasmediumfocusingonperformancemeasurementusingstrategicratherthantactic alindicatorsbecauseSMApracticesbringsubstantialbenefitswithregardstoidentifyandsupport theorganization’sstrategicintent.Thisisconsistentwiththepriorcontingency- basedmanagementaccountingstudiessuchasAndersonandLanen(1999);HoqueandJames(20 00);Cravens andGuilding(2001);Gerdin (2005);Seamanand Williams(2011).

Effective information management is crucial for supporting managerial decision-making and control According to Foster and Gupta (1994), inadequate strategic information processing can lead to flawed or delayed decisions, resulting in suboptimal performance Improved information quality is linked to more effective managerial decisions, which enhance corporate performance (Chenhall, 2003) As discussed in Chapter 2, strategic management accounting (SMA) provides essential insights into customers, competitors, and cost management, facilitating the development and implementation of business strategies within the strategic planning process The role of SMA is to support activities such as strategy formulation, communication, tactical development, and performance monitoring (Shank & Govindarajan, 1993), aligning with the organization’s strategic intent Ultimately, when business strategies are designed and managed effectively, overall organizational performance improves.

Numerous studies have explored the relationship between Strategic Management Accounting (SMA) practices and corporate performance Cadez and Guilding (2008) highlight how strategic choices, market orientation, and firm size influence SMA, as well as SMA's mediating effect on organizational performance Additionally, research by Buhovac and Slapnicar (2007) indicates that organizations can only achieve high performance by utilizing both financial and non-financial information from an SMA system that aligns with their business strategy While many studies suggest a positive correlation between SMA practices and corporate performance, this study aims to re-examine this relationship in the context of Vietnam, reinforcing the significance of SMA practices on corporate outcomes.

Hypothesis4:SMA practices arepositively associatedwithcorporate performance(assetturnover, investment efficiency, returnonequity, Tobin q).

Corporate performance is assessed through three key financial dimensions: productivity, profitability, and marketable value, measured by asset turnover, investment efficiency, return on equity, and Tobin's Q Higher asset turnover indicates increased productivity in generating revenue from assets Investment efficiency involves selecting projects with positive net present value to maximize shareholder value, highlighting the importance of strategic management accounting practices in making informed investment decisions Return on equity serves as a profitability indicator, reflecting the operational success of a company over a specific period While various metrics exist to assess firm value, this study utilizes Tobin's Q due to its ease of measurement, reliability, and its dual reflection of book and market values.

The relationship between strategic management accounting practices and financial performance metrics, such as return on equity (ROE) and Tobin's Q, can be understood through contingency theory Shareholders, who aim to exert influence over organizations, play a crucial role in shaping the strategies adopted by these entities As organizations define their strategies, they align their strategic management accounting practices accordingly, which provide essential insights for evaluating the effectiveness of these strategies This alignment fosters learning and the development of new strategies, enabling managers and shareholders to effectively respond to emerging opportunities and threats Furthermore, a robust strategic management accounting system serves as a vital component of Porter’s value chain, contributing significantly to an organization’s success Ultimately, improved strategic management accounting practices correlate with higher operating success and enhanced firm value, as reflected in both ROE and Tobin's Q.

The mediatingroleofstrategic management accountingpractices

SMApractices,SMApracticesandcorporateperformance),thisstudyalsohypothesizesanindire ctpathbetweenintellectualcapitala n d corporateperformancethroughthemediatingroleo f stra tegicmanagementaccountingpractices.Thatis,theauthorexpectsthata firmwithstrongintellect ualcapitalinavailabilitywillmakeaneffectiveusageofstrategicmanagementaccountingpractic eswhichinturnenhancecorporateperformance.Empiricalstudies confirmthat thereisarelationship betweenintellectualcapital andcorporate performanceasdiscussedinpart3.1.3.However,alittleresearchinvestigatesthatintellectualcapi talhasanindirectrelationshiptocorporateperformance.Whilemostofthemodelsfollowtheconc eptofclassicalorganizationeconomicparadigm(environmentstrategyperformance),

(2013)),thisstudyusesa modelo f resourcespracticesperformancerelationshipbasedo n there source-basedview.Tostronglysupporttheauthor’shypothesis,research evidenceofCadezand

Guilding (2008) employed path analysis to explore the connections between strategy, accountants' capabilities, strategic management accounting (SMA) usage, and performance across four relational stages Cadez and Guilding (2008) emphasized that the involvement of highly professional accountants, as a key source of human capital in strategic decision-making, enhances the justification and maintenance of SMA systems, thereby adding value to the decision-making process and improving positive outcomes Additionally, Bangchokdee and Mia (2016) demonstrated that non-financial measures fully mediate the relationship between decentralized decision-making structures—considered a form of structural capital in intellectual capital (IC)—and operating performance in Thai hotels While this mediation focuses on a single SMA technique (non-financial performance measures), it also supports the role of SMA practices in linking resource usage to corporate performance Despite inconclusive evidence regarding the relationships among intellectual capital, SMA practices, and corporate performance, particularly in the Vietnamese context, this study hypothesizes that these elements are interconnected.

Hypothesis5a:SMApractices mediate the positiverelationship betweenhuman capitalandcorporate performance.

Hypothesis5b:SMApractices mediate the positiverelationship betweenstructuralcapitaland corporate performance.

Hypothesis 5c:SMApractices mediate the positiverelationship betweenrelationalcapitaland corporate performance.

Human Capital Strategic cost management

Associations betweenintellectual capitalcomponents andeach

The second research model investigates how firms with intellectual capital (IC) have evolved their strategic management accounting (SMA) practices to effectively address the challenges of accounting for IC components It is suggested that managers in these firms should implement more strategic SMA practices to ensure that their organization’s most valuable IC is not overlooked This model focuses on identifying which specific SMA practices—such as strategic cost management, competitor accounting, strategic accounting, and customer accounting—are commonly employed to manage various components of IC Notably, as highlighted by Roslender and Fincham (2001), there is a significant lack of empirical literature examining the relationship between SMA and intellectual capital Based on this discussion, the study proposes the second research model accompanied by relevant hypotheses.

A resource-based strategy alone is insufficient to sustain competitive advantage in turbulent environments, as many firms struggle to manage their valuable assets effectively (Nazari, 2010) Dynamic capability theory highlights the importance of aligning resources with environmental changes, defining dynamic capabilities as the ability to integrate and reconfigure competencies to adapt to rapid shifts (Teece, Pisano, & Shuen, 1997) The transformation of resources into competencies that better fit the environment is a key outcome of dynamic capabilities (Eisenhardt & Martin, 2000) Strategic management accounting can be viewed as a dynamic capability, particularly in uncertain environments, as it adapts more quickly than traditional management accounting models (Sanford, 2009; CIMA, 2014a) Thus, strategic management accounting plays a crucial role in managing a firm's intellectual capital and enhancing its strategic positioning.

According to the theory of short-termism, organizations that overly rely on financial metrics often prioritize short-term outcomes at the expense of long-term objectives, particularly when these metrics are tied to compensation systems (Kaplan & Norton, 2001) Increasing evidence suggests that non-financial performance measures serve as more effective leading indicators of long-term success, guiding managers to focus on sustainable decision-making (Horngren et al., 2012a) Investing in intellectual capital is typically aligned with long-term goals, making strategic management accounting systems that emphasize non-financial indicators more suitable for managing intellectual capital These indicators not only set better targets for long-term profitability but also allow for trend analysis to assess performance improvements or declines over extended periods, offering insights beyond what traditional financial reports reveal Examples of non-financial performance measures include metrics related to research and development and production cycle time.

(structuralcapital),employees’skills(humancapital)andcustomerrelations(relationalcapital), allofwhicharevitalintellectualcapitalcontributingacompany’slong- termperformance.Thereby,manyofliteraturesuggestthatbalancedscorecardsmaybethetechn iquetodevelopandsustainintellectualcapital(Andriessen,2004;Kaplan,1984;Mouritsenet al.,2002;Roos, 1998).

A firm with higher intellectual capital is likely to develop strategic management accounting systems, moving beyond traditional management accounting practices Strategic management accounting serves as the framework for managing intellectual capital, providing essential tools for retaining and utilizing this resource throughout the value chain By focusing on improving the management of existing intellectual capital, organizations can enhance overall corporate performance This connection highlights the significant role strategic management accounting can play in the effective management of intellectual capital.

Strategic Management Accounting (SMA) serves as a crucial tool for leveraging Intellectual Capital (IC) to gain a competitive edge, as it enables firms to analyze their value chain and cost drivers effectively By utilizing strategic cost management, organizations can assess how each component of IC contributes to sustainable development and overall performance This analysis allows firms to enhance customer value while simultaneously reducing costs, thereby strengthening relational capital Additionally, the balanced scorecard approach helps firms understand how employee skills add value to customers, leading to targeted training that boosts human capital at reduced costs Furthermore, research indicates that firms with higher levels of IC prioritize capital budgeting, as it is essential for evaluating long-term projects related to IC investments.

Basedonthediscussionabove,thisstudyhasplacedemphasisthusoncontemporarymanage mentaccounting, whichhaveastrategicorientation, withaparticularfocusonthefourgroupsofSMAtechniques,thosearestrategiccostmanagement, competitoraccounting,strategicaccountingandcustomeraccounting.Itisunclearthath o w each groupofSMAtechniquesmaymanageeachofthedifferentICcomponents.Whiletheliteraturepl acesconsiderableattentiononthevaluation,measurementandreportingintellectualcapitalforex ternalreportingpurposes,littleattentionhassofarbeengiventotheimplicationofstrategicmanag ementaccountingpracticesforICmanagement.Hence,thisstudydoesanexploratoryresearchtoi dentifyanumberofSMAtechniquesexpectedtomanageICcomponents,leadingtothefollowing hypotheses.Thisisinthelinewiththeattemptsoftheauthortocontributetoatheoreticalframewor kofstrategicmanagementaccounting.

Hypothesis6a:Which categoriesofSMAtechniques (strategic cost management,competitor accounting,strategic accountingandcustomer accounting)are stronglyassociated withhuman capital.

Hypothesis6b:Which categoriesofSMAtechniques (strategic cost management,competitor accounting,strategic accountingandcustomer accounting)are stronglyassociated withstructural capital.

Hypothesis 6c:WhichcategoriesofSMAtechniques (strategic cost management,competitor accounting,strategic accountingandcustomer accounting)are stronglyassociated withrelational capital.

Summaryofthe correlations inthe tworesearchmodels

1,3 ATOHCE + + + Bollenet al (2005);Firer andMitchell-

ROEHCE + + + S.-L Chang(2007);HongPewet al (2007)

TOBINQHCE + + + Ming-Chin et al (2005)

1,3 ATOSCE + + + Bollenet al (2005);Firer andMitchell-

ROESCE + + + S.-L Chang(2007);HongPewet al (2007)

TOBINQSCE + + + Ming-Chin et al (2005)

1,3 ATORCE + + + Bollenet al (2005);Firer andMitchell-

ROERCE + + + S.-L Chang(2007);HongPewet al (2007)

TOBINQRCE + + + Sharabati, Naji Jawad, andBontis

H4 2 ATOSMA + fromquestionnaire surveyto affirmthepositiverelationship betweenSMAandcorporateperformance measuredingeneral,notdetailedbyfinancial indicators For examples:Cadez andGuilding(2008),Cadez (2006).

Contingencyt heory,informa tionmanagem enttheory

H6a 4 HCESCM ? Theauthor Dynamiccapa bilitiestheory, Shortermismt heory

1 HCE: humancapitalefficiency,SCE:structuralcapitalefficiency,RCE:relationalcapitalefficiency,SMA:strategicmanagementaccountingpractices,ATO:assetturnover,INVEFF:investmenteffic iency, ROE:returnonequity, TOBINQ:Tobinq,SCM:strategic costmanagement, COM:Competitor accounting, STR:strategic accounting,CUS:customer accounting

Itisofincreasingvitalthatbusinessorganizationsshouldunderstandhowtoleveragetheirint ellectualcapitalina transitionalcontextasinVietnamthatisquicklyshifting.Therefore,thisstudy wantstoexaminethewayinwhichthecomponentsofintellectualcapital influence each other andimpactoncorporate performance.

Followingtheconcepto f strategicassetso f theresource- basedtheory,thekeycharacteristicsofintellectualcapitalaretheirrarity,inimitability,non- substitutabilityandtheirunobservability;therefore,intellectualcapitalareassessedasafirm’sstr ategicassetswhicharecapableofgeneratingsustainablecompetitiveadvantagesandsuperiorfin ancialperformance.Moreespecially,basedontheresources-basedtheoryandcompetence- basedtheory,thefirstresearchmodelhypothesizesanindirectpathbetweenintellectualcapitalan dcorporateperformanceviathemediatingroleo f strategicmanagementaccountingpractices.Th isindirectpathisrarelyinvestigatedinthepreviousstudies.T h e authorexpectsthatfirmswithhig herlevelsofintellectualcapitalattachgreaterimportancetohowmanagementaccountingsystemi schangedinthewaywhichinturnenhancescorporateperformance.

BeyondtheidentificationofhowICcomponentsaremoreimpactfultoSMApracticesandc orporateperformance,eitherpositivelyornegatively,thesecondresearchmodelproposestobepo tentiallyefficaciousintheidentificationofwhichcategoriesofthedifferentSMAtechniquesismo revaluabletothemanagemento f intellectualcapitalcomponents.Thus,thisstudywilldoanexplo ratoryresearchtofindtheroleofeachgroupo f SMAtechniquesasacontributiontotheoreticalfra meworkofstrategicmanagementaccounting.

Aftertheauthorpresentstheunderlyingtheoreticalframeworktodevelopallthehypotheses inthethirdchapter,thenextchapterwillintroduceresearchmethodologyincludingresearchproce ss,unitofanalysis,methodofdatacollection,samplesizedesignedand howto measure allvariablesinall researchmodels.

Thepriorchapterdevelopshypothesesbasedonunderlyingtheoreticalframeworks.Thisch apteraimstodescribetheresearchmethodology,includingtheresearchinstrumentsthatareoptedi nthisstudy.Thischapteralsopresentstheprinciplestoassesstheappropriatenesso f measuremen tscales.Section4.1isspecifyingtheselectiono f anappropriateregressionmodel.Section4.2pre sentstheresearchprocess.Section4.3indicatesthemain characteristicsofthesample.Section4.4 providesadescriptionofhowtomeasureall variables inthe two researchmodels.

Selectionofanappropriate regressionapproach

Social science researchers classify statistical analysis tools into two main categories: first-generation methods, which dominated the research landscape through the 1980s, and second-generation methods that emerged in the early 1980s First-generation methods, such as correlations, regressions, and ANOVA or t-tests, are effective for simple modeling scenarios but have limitations in testing complex models, particularly regarding latent variables and indirect effects In contrast, second-generation techniques, notably structural equation modeling (SEM), excel in complex causal modeling, making them preferable for research models that involve multiple mediators and require simultaneous estimation of complete causal networks.

Ontheotherhand,therearetwotypesofSEM.Firstly,covariance- basedSEMismainlyusedtoconfirmortorejectatestedtheoreticalrelationshipbydeterminingho wwellaproposedmodelcanestimatethecovariancematrixofasampledataset(HairJr&Hult,201 6).Secondly,partialleastsquaresSEM(PLS-

SEM)areprimarilyusedtodeveloptheoriesinexploratoryresearchbyconcentratingonexplainin gthevarianceinthedependentvariablesintestingthemodel(HairJr& Hult,2016).Thereby,theau thordecidedtousePLS-SEMtoexamineproposedrelationshipsintheresearchmodel.When theauthordecideswhetherornottoapplyPLS-SEM,severalconsiderations,basedonthePLS- SEM’s characteristics,are analysedas follows:

SEMhandlesa complexmodelwithmanystructuralmodelrelations.Largernumberofindic atorsarehelpfulinreducingthePLS-SEMbias.PLS-

SEMconvergesafterafewiterationseveninsituationswithcomplexmodelstooptimumsol utionandefficient algorithm(Hair Jr&Hult, 2016).

2 Covariance- basedSEMisa largesampletechnique.Barrett(2007)suggeststhatreviewerso f journalsu bmissionsroutinelyrejectforpublicationanycovariance- basedSEManalysiswherethesamplesizeislessthan200.Incontrasts,PLS-

SEMhasnoidentificationissuewithsmallsamplesize.Thisstudyisextremelydifficulttoob taina largesamplebecausetheauthorhastocollectbothprimarydata(byquestionnairesurv ey)andsecondarydata(i.e.financialinformationintheannualreport) foroneinvestigatedlistedcompany.

3 Normaldistributionsareusuallydesirable,especiallywhenworkingwithcovariance- basedSEM.Incontrast,PLS-

SEMgenerallymakesnoassumptionaboutthedatadistributions(HairJr&Hult,2016).Hen ce,itis moreconvenientthan fortheauthortocollectthesamplewithoutnormaldistributionswhichallowsanalysingthe pathrelationships inthe researchmodel.

SEMcaneasilyhandlereflectiveandformativemeasurementmodels,aswellassingle- itemconstructs,withnoidentificationproblems(HairJr&Hult,2016).Itcanthereforebeap pliedinawidevarietyofresearchsituations.WhenapplyingPLS-

SEM,theauthoralsobenefitsfromhighefficiencyinhandlingconstructsmeasuredwithsin gle-itemmeasure(i.e.Assetsturnover,ROE,Tobinq)andmulti-itemmeasures (i.e. measuresofthe variablesofSMApractices).

SEMapproach,theresearchprocessisdesignedfollowingthe stagesofthe PLS-SEM approach.

Researchprocess

Theresearchprocessstartswiththespecificationo f structuralmodelsandmeasurementsca les,followedbythecollectionandexaminationofdata.Next,theauthorappliesPLS-

Evaluation ofmeasurement ofscales Reflectivemeasurement scales Formativemeasurement scales

Indicator reliability Use: Outer loadings

Examineitscorrelati on withreflectiveconstr ucto f thesameconce pt

Evaluation ofthe fitnesso f structural model

Modelestimationdeliversempiricalmeasuresoftherelationshipsbetweentheindicatorsan dconstructs(measurementmodels),aswellasbetweentheconstructs(structuralmodels).Initiall y,modelassessmentfocuseso n themeasurementmodels.Examinationofmeasurementscalesv iaPLS-

SEMapproachenablesresearcherstoevaluatethereliabilityandthevalidityoftheconstructmeas ures.Forinstance,multivariatemeasurementinvolvesusingseveralconstructstoindirectlymeas uretheconceptofstrategicmanagementaccountingpracticesandeachconstructneedsmanymea surementscales.Whenevaluatingthemeasurementmodels,SEMtechniquesrequiretodistingui shbetweenreflectivelyandformativelymeasuredconstructs.Thetwoapproachesofobservedva riablesarebasedondifferentconceptsandthereforerequireconsiderationofdifferent evaluationmeasures.

Reflectivemeasurementrepresentsthemanifestationso f anunderlyingconstruct.Reflecti vemeasurementdictatesthatallindicatoritemsarecausedbythesameconstruct,indicatorsassoci atedwithaparticularconstructshouldbehighlycorrelatedwitheachother(HairJr& Hult,2016).R eflectivemeasurementmodelsareassessedo n theirinternalconsistencyreliability,indicatorreli ability,convergentvalidityanddiscriminantvalidity(Kline, 1998), as follows:

Internal consistency reliability is traditionally evaluated using Cronbach’s alpha; however, due to its limitations concerning population and sensitivity to the number of items in a scale, it is more appropriate to utilize composite reliability (Hair Jr & Hult, 2016) Composite reliability values range from 0 to 1, with higher values indicating greater reliability For exploratory research, a composite reliability value above 0.60 is considered acceptable (Nunnally & Bernstein, 1994) Conversely, values exceeding 0.95 are undesirable, as they suggest that all observed variables may be invalid when measuring the same phenomenon (Nunnally & Bernstein, 1994).

 Indicatorreliability:Thischaracteristicismeasuredb y outerloadingso n a construct,indicatingthattheassociatedindicatorshavemuchincommon.Acommonruleofthu mbisthattheindicator’souterloadingsshouldbehigherthan0.708(HairJr&Hult,2016).Indicatorswithouterloadingsbetween0.40 and0.70shouldb e consideredforremovalonlyifthedeletionleadstoanincreaseinco mpositereliabilityandaveragevarianceextractedabovethethresholdvalue

 Convergentvalidity:Thischaracteristicismeasuredbyaveragevarianceextractedcr iterionwhichisdefinedasthesumofthesquaredloadingsdividedb y thenumberofin dicators(Nunnally&Burnstein,1994).ThevalueofAVEshouldbehigherthan0.50,i ndicatingthattheconstructexplainsmorethanhalfo f thevarianceofitsindicators(N unnally&Burnstein,1994).Forthesingle- itemconstruct,theAVEisnotanappropriatemeasuresincethisindicator’souter loadingis fixed at 1.00.

The Larcker criterion, established by Fornell and Larcker (1981), states that the square root of the Average Variance Extracted (AVE) for each construct must exceed its highest correlation with any other construct, indicating that a construct shares more variance with its related indicators than with other constructs Discriminant validity is confirmed when an indicator's loading on its designated construct is greater than its cross-loadings with other constructs (Hair Jr & Hult, 2016) Additionally, Henseler, Ringle, and Sarstedt (2015) introduced the Heterotrait-Monotrait Ratio of Correlations (HTMT) as a more reliable measure for assessing discriminant validity in PLS-SEM, where the HTMT value reflects the average correlations of indicators across different constructs compared to the average correlations within the same construct.

1.00becausethetruecorrelationbetweenthetwoconstructsismostlikelydifferent fromone(Henseleretal.,2015).IftheHTMTvalueishigherthan0.85, there isalackofdiscriminant validity(Kline, 2011).

Specially,a single-itemconstructisn o t representedb y a multi- itemmeasurementmodel.Thus,thecriteriafortheassessmento f multi- itemmeasurementmodelsarenotapplicable tosingle-itemconstructs.

Theformativemeasurementmodelistoextentwhereindicatorsarelikelytorepresenttheco nstruct’sindependentcausesandthusdonotnecessarilycorrelatehighly(HairJr&Hult,2016).Ac cordingtoChin(1998b),evaluatingconvergentanddiscriminantvalidityusingcriteriasimilartor eflectivemeasurementscalesisnotmeaningfulwhenformativeindicatorsandtheirweightsarein volved.Thisstudyfocusesonassessingtheempiricalresultsofformativemeasurementmodelsfo llowingproceduresoutlinedinFigure4.1,asbeinginstructedbyHairJrandHult(2016).Theproce dureincludesthreesteps.Thefirststepistoassessconvergentvaliditybycorrelatingtheformativel ymeasuredconstructwitha reflectivemeasureofthesameconstruct.Thesecondstepistoassessfo rmativemeasurementmodelsforcollinearityissue.Thethirdstepistoexaminethestatisticallysi gnificant andrelevanceofthe formative indicators.

 Convergentvalidity:Thischaracteristicismeasuredbycorrelatingbetweentheforma tivelymeasuredconstructwithareflectivelymeasuredconstructofthesameconstruc t.Thistypeofanalysisisknownasredundancyanalysis(Chin,1998b).Themeaningso f thepathcoefficientlinkingbetweenthereflectiveconstructandformativeconstruct o f thesameconceptisindicativeo f thevalidityofthedesignated setofformativeindicatorsin tapping theconstructofinterest(Chin,1998b).Ideally,thecorrelationbetweenthetwoconstru ctsshouldb e thevalueo f minimum0.70,indicatingthatformativeindicatorscontrib ute atasufficient degree to its intendedcontent (Chin, 1998b).

 Collinearityissue:Highcorrelationsbetweenformativeindicatorscanproveaproble maticissue,alsoreferredtoasmulti- collinearity.Arelatedmeasureofcollinearityisthevarianceinflationfactor(VIF).Ea chindicator’sVIFvalueshouldb e lowerthan5.0(HairJr& Hult,2016).Otherwise,co nsidereliminatingormergingindicatorsintoasingleindextosolvewiththecollinearit yproblem.

The significance of formative indicators is determined by the outer weight, which results from a multi-regression analysis between the latent variable and the formative indicators If the outer weight is significant, one should proceed to interpret both the absolute and relative sizes of the outer weight Conversely, if the outer weight is not significant, the focus shifts to the outer loading, which reflects the absolute contribution of the formative indicator to its construct Indicators with a non-significant outer weight but a high outer loading (above 0.50) should generally be retained, while decisions regarding retention or deletion should consider their theoretical relevance (Hair Jr & Hult, 2016).

Oncethemeasurementscalesarereliableandvalid,thenextstepaddressestheassessmentof thestructuralmodelresultsbyexaminingtherelationshipsbetweenconstructs,asoutlinedinFigu re4.1.ThekeycriteriaforassessingstructuralmodelsinPLS-

SEMapproacharethesizeandsignificanceofpathcoefficients,thelevelofR 2value, andtheSRMRv alue.

 Sizeandsignificanceo f pathcoefficients:Evaluatingstandardizedpathcoefficients areveryvitaltodecidewhetherthehypothesizedcorrelationsareagreedordisagreed. Theresearchersnotonlyrelyheavilyonstatisticallevelb u t alsopaysufficientattenti ontoabsolutesizeofapathrelationshipduringinterpretations.Evenwhenarelations hipissignificant,theabsolutesizeofapathcoefficientmaybetoosmalltowarrantman agerialattention(Nitzl,2016).

 Coefficiento f determination(R 2value): Thiscoefficientisa measureo f themodel’spre dictivepower,whichiscalculatedasthesquaredcorrelationbetweenaspecificendoge nousconstruct’sactualandpredictedvalue(Rigdon,2014).TheR 2value rangesfrom0t o1.Ingeneral,R 2values of0.75;0.50or

0.25fortheendogenousconstructcanbedescribedassubstantial,moderateandweak, respectively(Hair Jr&Hult, 2016).

 SRMRvalue:Theclassicalgoodness-of-fitcriterionassociatedwithcovariance- basedSEMisnotappropriatetoPLS-

SEMapproach(HairJr& Hult,2016;Henseleretal.,2015;Nitzl,2016).Anotherprom isinggoodness-of-fitstatisticforuseinPLS-

SEMapproachisthestandardizedrootmeansquare residual.TheSRMRisdefinedastherootmeansquareddiscrepancybetweentheobser vedcorrelationsandthemodel-impliedcorrelationsandshouldb e lower than0.08(Hu&Bentler, 1998) tobeagoodfit.

PLS-SEMisthenon- distributionusedtechniquetoanalysemultivariatedata,asaconsequence,PLS-

Structural Equation Modeling (SEM) does not provide initial t-values to assess the significance of estimates (Hair Jr & Hult, 2016) Researchers must rely on a non-parametric bootstrapping procedure to obtain bootstrap standard errors, which enables them to evaluate the stability and significance of outer weights, outer loadings, and path coefficients with greater accuracy (Kline, 2011) Bootstrapping involves resampling with replacement from the original dataset to estimate path coefficients multiple times under slightly altered data conditions (Hair Jr & Hult, 2016) It is recommended to perform bootstrapping on at least 5,000 samples at a 95% confidence level, ensuring that the number of bootstrap samples meets or exceeds the number of valid observations in the dataset For instance, if the original sample consists of 200 valid observations, each of the 5,000 bootstrap samples should include 200 randomly selected observations.

Thebootstrappingprocedureprovidesthestandarderrorofanestimatedcoefficient.Thisinf ormationallowstodeterminetheempiricalt-values.Thecriticalt-valuesfortwo- tailedtestare1.65(=0.1),1.96(=0.05)or2.57(=0.01).Iftheempiricalt- valueishigherthancriticalt- valueata selected level,thenthecoefficientissignificantlydifferent fromzero.

The bootstrapping procedure provides a bootstrap confidence interval that indicates the stability of coefficient estimation This confidence interval represents the range within which the true population parameter is expected to fall at a specified confidence level (Hair Jr & Hult, 2016) By analyzing the outer weight, standard error, and probability of error level, the bootstrapping method determines the lower and upper bounds of the confidence interval If the zero value does not fall within this interval, the researcher can conclude that the outer weight is significant at the specified probability of error level (Hair Jr & Hult, 2016) Furthermore, a wider confidence interval for a coefficient suggests lower stability (Hair Jr & Hult, 2016).

Unitofanalysis andsample size

Thisstudyfocusestherelationshipbetweenintellectualcapitalandcorporateperformance. Therefore,theunitofanalysisisabusinessorganization.Sincethestudyalsoinvestigatesthemedi atingeffectofstrategicmanagementaccountingpracticeswhicharebeingoperatedinsomefuncti onsordepartments(i.e.accountingandfinancedepartment,planningdepartment,managementa ccountingdepartmentorcontrollingdepartment),thefocalunitunderthisinvestigationisabusine ssorganizationusingseveralo f SMAtechniquestooperateandtomanagebusinessactivities.Ba sedonsomepreviousstudieso f Daske,Hail,Leuz,andVerdi(2008)andFrancisandWang(2008 ),financialserviceorganizationssuchasbanks,insurancefirmsandotherfinancialinstitutionsare excludedbecause computingfinancial calculationscanbeproblematicordifferent for suchentities.

This study utilizes both primary and secondary data, with secondary data sourced from annual reports and financial statements that provide insights into intellectual capital and corporate performance To facilitate the collection of financial data, the research focuses on publicly traded companies listed on the Ho Chi Minh Stock Exchange (HoSE) and the Hanoi Stock Exchange (HNX) The external reports are obtained from reputable websites, such as cophieu68.vn, finance.vietstock.vn, and cafef.vn, which are commonly used by investors, analysts, and researchers in Vietnam.

The primary data for this study is gathered through a questionnaire survey aimed at investigating Strategic Management Accounting (SMA) practices in business organizations The research targets SMA practitioners in public enterprises, utilizing their financial data to assess intellectual capital and corporate performance Given that the organization is the unit of analysis, there is a concern regarding the alignment between respondents and this unit The study is conducted in two phases: the first involves distributing a questionnaire via SurveyMonkey to the management of public enterprises to gather information on SMA practices, while the second phase focuses on collecting 2016 financial data related to intellectual capital and financial performance from the public companies where the respondents are employed.

Toensurethattheinformantsaretrulyknowledgeableabouttheresearchtopics,especiallyi nthefieldofstrategicmanagementaccounting,thekeyinformantsareoptedfromtheseniormana gerso r memberso f topmanagementteamwithknowledgeaboutaccounting,planningorfinance andatleasttwoyearsofworkingexperienceinthecurrentorganizations.Itisbecause,accordingto AlaviandLeidner(2001),itisdifficultforanemployeetohaveenoughtimetothoroughlyundersta ndtheoperatingprocess,organizational structure andcultureofsuchanorganization within one-year participation.

A useful guideline regarding the relationship between sample size and model complexity is known as the N:q rule, as referenced by Jackson (2003), where N represents the ratio of cases to the number of model parameters (q) Additionally, Barclay, Higgins, and Thompson (1995) mention the commonly cited 10:1 rule, suggesting that the minimum sample size should be ten times the maximum number of arrowheads pointing at any latent variable in the model However, Marcoulides and Chin (2013) argue that this generic 10:1 rule is not a reliable method for determining the necessary sample size for PLS-SEM.

SEMisbuiltonOLSregressionswithouttherequirementoftheminimumsamplesize,thusresear chersshouldalwaysawareofrevertingtostatisticalpoweranalysesformultipleregressionmodels (J.Cohen,1988)toderiveasatisfactorysamplesizebetterthancalculatingtheminimumsamplesi zerequiredforthisestimationmethod.Faul,Erdfelder,Lang,andBuchner(2007)suggestdetermi ningthenecessarysamplesizeforPLS-

SEMbasedonthestatisticalpowerrepresentedbytheeffectsize(f 2 ),thenumberofpredictorsandt hesignificantlevel().Alternatively,researcherscanuseprogramssuchasG*Powertocarryoutp oweranalysistocalculatetheappropriatesamplesize.Here,thisstudy’snecessarysamplesizewas calculatedusingthefreedownload(http://www.gpower.hhu.de/)ofthe programG*Power 3.1.9.2(Faul et al., 2007).

Thefollowingsettingsforthecalculationareusedas“F- test”(testfamily),“Linearmultipleregressions:Fixedmodel,R 2deviation fromzero”(statisticaltest) ,and“Apriori:Computerequiredsamplesizes– given,powerandeffectsize”(typeofpoweranalysis).

In business studies, key input parameters include effect size (f²), alpha error probability, power, and the number of predictors An acceptable statistical power is typically at least 0.80 with an alpha level of 0.05 (J Cohen, 1988) The effect size values of 0.02, 0.15, and 0.35 indicate small, medium, and large effects of an exogenous construct on an endogenous construct, respectively (Hair Jr & Hult, 2016) For management accounting research, detecting small effects with extremely large sample sizes is unnecessary; therefore, aiming for a medium effect size (f² = 0.15) with a reasonable sample size is more practical due to the time and costs associated with questionnaire surveys (Nitzl, 2016) The maximum number of predictors allowed in the first research model is 12, while the second model permits 4.

Human Capital (HCE)Structural Capital (SCE)Relational Capital (RCE)

The first and second research models have sample sizes of 127 and 85, respectively, indicating that a minimum sample size of 127 observations is necessary to achieve 80% statistical power for detecting R² values of at least 0.25 with a 5% probability error This study aims to gather at least 127 observations from a research site in Vietnam, an Asian developing country Due to the challenges in obtaining a sampling frame, a convenience sampling approach will be employed to identify listed enterprises and potential informants.

Variables measurement

TheprimarymethodusedtoobtaindatafromarchivalsourcesthatwouldallowICconstruc tsmeasurementisthe“ValueAddedIntellectualCoefficient”model(VAIC TM )developedbyPuli c(2000).ThisstudyoptedtheVAICmodeltomeasureICbecause,FirerandMitchell-

Williams(2003)pointtwoadvantagesofVAIC,whicharethat(1)VAICprovideaneasy-to- calculate,standardizedandconsistentbasisofmeasurementtoenableeffectivelycomparativean alysisacrossthefirms;

Figure 4.4.Thevalue-addedintellectual coefficient model

VAICiscomposedofasetofindicatorsthatareusedasproxiestomeasurevalueandefficienc yo f a firm’sresources.Figure4.4givesanoverallpictureo f variablesbeforestartingtocalculatet heconstructsofintellectualcapital.AccordingtoVAICmodel,theprocedures are usedtomeasure different constructs as follows:

Themodelstartswithacompany’sabilitytocreatevalueadded(VA).Basedonthestakehold erview(Donaldson&Preston,1995),in measuring firmperformance,abroadermeasureofvalueaddedbystakeholdersisbetterthanaccountingprofi tthatonlycalculatesthereturnstostockholders.Therefore,theVAICmodeladoptsa broaderdefin itionindeterminingfirmperformanceviathevalueadded,whichisthedifferencebetweenoutputa ndinput.

RE =SALES– B–DEPN–WAGES–INT– T– DD(4.1) Where:

B: Bought-in materialsandservicesDEPN: Amortizationand depreciationWAGES: Wages andemployee salariesINT: Interest expenses

Equation(4.1) canbere-arranged as equation (4.2):

SALES–BN+WAGES+INT+T +DD +RE(4.2)

Equation4.2isthegrossvalue-addedapproach.Theleft- handsideoftheequationcalculatesgrossvalueaddedandtheright- handsideoftheequationrepresentsthe distributiono f thevaluecreatedbyfirmstostakeholdersincludingemployees,debt- holders,stockholdersandgovernments.VAisdefinedasthegrossvaluecreatedbyfirmduringthe years,andbecausedividends(DD)plusretainedearnings(RE)isequaltoafter-taxincome (NI), equation 4.2canbeexpressedas follows:

VA =SALES– B N+WAGES+INT+T +NI(4.3)

VAICcalculatestheefficiencyo f intellectualcapitalcomponents.BasedonEdvinssonand Sullivan(1996)mentionedinsection2.1,agenerallyacceptedintellectualcapitalcomponents,V AICiscomposedofhumancapital,structuralcapitalandrelationalcapital, whichare calculatedthe efficiency, as presentedinthe followingparts.

AccordingtoPulic(2000),VAICdoesnotconsiderexpendituresonemployeesaspartofIN PUT.Thisdenotesthatexpensesrelatedtoemployeesarenottreatedascostsbutrepresentaninvest ment.Consequently,humancapitalefficiency(HCE)ismeasuredbyhowmanydollarsofvaluead dedanorganizationisabletogenerateforeachdollarinvestedinits humancapital.HCEis calculatedas follows:

Higher wages andsalaries proxyfor workforce withgreater skillsshouldaddmorevalue tothefirmthanstaffonlow wages rateswithlower skills If wages andsalariesarelowandVAis high, the firmisusingitsHCefficiently.IfVAis lowinrelationtowagesandsalaries,afirm’sHCisnotbeing utilisedefficientlyand

Bothstructural capitalandrelational capital are calculatedas follows:

SRC: Structural capital andrelational capitalVA: Value added

AccordingtoNazariandHerremans(2007),structuralcapitalandrelationalcapitalaredepe ndentonhumancapital,andgreaterHCtranslatesintoimprovedinternalstructuresandexternalrel ationships.Therefore,iftheefficiencymeasuresforbothhumancapital,structuralcapitalandrela tionalcapitalefficiencyarecalculatedwithVAasthenumerator,thelogicalinconsistencywillrem ain(Pulic,2000).WhenVAusedinthenumeratorofstructuralcapitalandrelationalcapitalefficie ncy,itdoesmeanthateverydollarofaddedvaluegeneratedfromHCmaycontributeintotheimpro vementofinternalstructuresandexternal relationships Therefore,Pulic (2000)calculatesSRCEas:

SRCE: Structural capital andrelational capital efficiencyV A : Value added

SRC: Structural capital andrelational capital

Structuralcapitalandrelationalcapitalefficiency(SRCE)isthedollarofSRCwithina firm,f oreachdollaro f valueadded,andasHCEincreases,SR CE increases.Alternatively:

SRCE: Structural capital andrelational capital efficiencySCE:Structural capital efficiency(SCis dividedbyVA)RCE: Relational capital efficiency(RCis dividedbyVA)S C : Structural capital

Movingtothelowerlevel,structuralcapitaliscomposedofinnovationcapitalandorganizat ionalcapital(Nazari,2010).Structuralcapitaliscalculatedonthebasiso f itscomponents as:

EquationofSCEcanbe re-arrangedas equation(4.10), basedonequation(4.9):

SCE: Structural capital efficiencyRDCE: Innovation capital efficiencyORGCE: Organizational capital efficiency

Researcha n d developmentexpenditure(R&D)hasbeenusedextensivelyintheliteraturea saproxyforinnovationcapacity(Bosworth&Rogers,2001).Theefficiencyofinnovation is calculatedinthe followingmanner:

AccordingtoVietnameseaccountingstandards,thefirmsarenotcurrentlyrequiredtodiscl osetheinformationonR&Dinvestmentlevelcompulsorily,asaresult,itisdifficulttocollectthisin formationinthefinancialstatements.Therefore,thisstudyusescashoutflowfrompurchasingtan gibleandintangibleassetsexcludingthepurchaseofcontrolledentitiesandbusinesses.Thisspen dingisusedasanindirectmeasureofafirm’sR&Dinvestmentduringayearincaseofunavailablefi nancialinformationonR&D(Lev

&Sougiannis,1996).ThisstudymeasurescumulativeR&Dinvestmentbylumpsumvalueo f the carryingamountoftheprioryears’R&Dinvestments.Therefore,anamortizationrateisneededto measurecumulativeR&Dinvestmentovermultipleyears.FollowingLevandSougiannis(1996);

G u andLev(2001);Shangguan(2005),thisstudyacceptsthatR&Dinvestmentroughlyisstraight lydepreciatedwithina 3- yeareconomiclife.T h e authorisunabletoapplyalongdurationofthedepreciationincasetheaut hormaynotcollectenoughdataina youngVietnamstockexchangemarketwhereinformationhas beenfullyavailablesince2010.Onthebasisof3- yeareconomiclife,thecumulativeR&Dinvestment (RDC) inthe yeartis:

RDCi,t: CumulativelevelofR&Dinvestment inthe yeartRD i,t : LevelofR&Dinvestment inthe yeart

RD i,t-1 : LevelofR&Dinvestment inthe yeart–

1RDi,t-2: LevelofR&Dinvestment inthe yeart–2

Organizationalcapitalappearstobeessentiallytheaccumulatedknowledgeusedtocombin ehuman skillsandphysicalcapitalinto systemforproducing anddelivering want- satisfyingproduct(Shangguan,2005).Followingtheequation4.10,theefficiencyo f organizatio nal capitaliscalculatedinthe followingmanner:

Firms often do not disclose their expenditures on organizational capital in financial statements, primarily focusing on the capitalization of selling, general, and administrative (SGA) spending This approach is akin to the capitalization of research and development (R&D) spending, as discussed in Lev and Sougiannis (1996) While Vietnamese accounting standards mandate that SGA spending be expensed immediately, it encompasses crucial aspects of organizational capital, including investments in human resources, IT, workplace practices, and marketing Therefore, the rationale for capitalizing R&D spending also applies to SGA expenditures Additional support for viewing SGA spending as a capital investment is provided by researchers such as Amir and Lev (1996), Lev (2001), and Lev and Radhakrishnan (2003) It is important to note that when calculating organizational capital, SGA spending excludes employee salaries and wages, as these are accounted for within human capital calculations.

Firstly, this studyconducts the followingfirm-level estimationbyindustry:

Log(Ei,t)=γ0+γ1Log(PPEi,t-1)+γ2Log(RDCi,t-1)+δ1Log(SGAi,t)+δ2Log(SGAi,t-1)+ δ3Log(SGAi,t-2)(4.15) Where:

Logarithmo f annualearningsbeforedepreciation,R&D,andSGAexpens es inyeart

Log(PPEi,t-1):Logarithmofbookvalueofplant,property,andequipmentinyeart-

Log(RDC i,t-1 ):LogarithmofaccumulativelevelofR&Dinvestmentintheyeart–1,RDCis estimatedinthe model 4.13 Log(SGAi,t):

Logarithmofselling,generaladministrativespending(excludingemploye es’ wages and salaries) inthe yeart

1):Logarithmofselling,generaladministrativespending(excludingempl oyees’ wages and salaries) inthe yeart–1

2):Logarithmofselling,generaladministrativespending(excludingemplo yees’ wages and salaries) inthe yeart–2

Therationaleunderlyingequation(4.15)is,becauseSGAexpendituresincorporatemostor ganizationalcapital,theyshouldgeneratefutureearningsforthefirm.Inotherwords,pastS G A e xpendituresshouldaffectcurrentearnings.T h e amounto f effectdependsontherateso f organi zationalcapital,thatarerepresentedbyγ 3 ,γ4,γ5inthe equation4.15.Ascanbeseenintheequation4.15,thisstudyusesamaximumof3yearso f pastSG AexpenditurestoinfluencecurrentearningssothatthedurationofR&DandSGAcontributions on earnings are the same.

The empirical results from simple correlations and multivariate regressions do not account for the potential endogeneity of SGA expenditures and earnings (Shangguan, 2005) To address potential simultaneity bias, instrumental variables are utilized as the exogenous component of SGA expenditures in a two-step regression approach SGA expenditures may be jointly endogenous, influenced by underlying exogenous variables such as total assets and profitability A firm's SGA expenditure is expected to align with its total assets (a proxy for firm size) and prior year's profitability In the first stage of the two-step regression, SGA expenditures are regressed against profitability and firm size to obtain estimates for the general model relating SGA expenditures to earnings.

Logarithmofselling,generaladministrativespending(excludingemploye es’ wages and salaries) inthe yeart

TAi,t-1 Thenatural logarithmoftotal assets inthe yeart–1

ROAi,t-1 Profitabilityis the ratioofnet profit tototal assetsinthe yeart–

1Afterconductingthe2-stepregressionwiththeequation4.16and4.15,thevalueof δ 1 ,δ 2 ,δ 3in theequation4.15areestimatedbyindustry.Thisstudy’smeasuremento f organizational capitalforfirm- specificisbasedontheSGAamortizationratesestimatedb y industry.UnlikemeasurementofR

&Dinvestmentinequation4.13,whereallcurrentR&Dspendingisconsideredascapitalinvestm ent,thisstudyonlycapitalizestheunamortizedSGAexpenditurewhiletheamortizedpartisconsid eredasoperatingexpensesforthecurrentperiod(Shangguan,2005).Afterdeterminingthevalueo fδ1,δ2,δ3intheequation4.15byindustries,thus,δ 1 ,δ 2 ,δ 3 ,ifsignificant,representsthecontributiono f SGAexpenditureinyeart,t-1,t-

2tocurrentearnings,(δ 1 ,δ 2 ,δ 3 )representsthetotalearningsinyeartcontributedbySGAexpendit uresovert,t-1,t-2years,while 1= δ 1 /(δ 1 ,δ 2 ,δ 3 ); 2= δ 2 /(δ 1 ,δ 2 ,δ 3 ); 3= δ 3 /

2, 3 ,thefirm-specific leveloforganizational capitalismeasuredbythe equation4.17.

SGAi,t Selling,generaladministrativespending(excludingemployees’wages andsalaries) dividedbynet revenue in the yeart

SGAi,t-1: Selling,generaladministrativespending(excludingemployees’wages andsalaries) dividedbynet revenue in the yeart–1 ORGC: Organizational capital

Relationalcapitalisa company’sabilitytointeractsuccessfullywithitsexternalstakeholde rsinordertodevelopthepotentialofvaluecreation.Relationalcapitalefficiency(RCE)ismeasure dbytherelationalcapitaldividedbyvalueadded.RCEmeansthatthedollarofRCwithinafirmisge neratedfromeachdollarofvalueadded.However,itisdifficulttodirectlymeasurerelationalcapit alinfinancialterm.Therefore,RC E isindirectlymeasuredastheresidualofintellectualcapitaleff iciencyaftersubtractinghumancapital andstructural capital efficiency.

Relationalcapitalefficiencyissimplyequaltostructuralandrelationalcapitalefficiencymi nus structural capital efficiency Fromequation4.8:

RCE=SRCE–SCE(4.18) 4.4.2.Measuresofthe variablesofstrategic management accountingpractices

Strategic management accounting (SMA) practices encompass 18 techniques categorized into four groups: strategic cost management, competitor accounting, strategic accounting, and customer accounting Each SMA technique is measured using a five-point Likert scale, as developed by Cravens and Guilding (2001) and Guilding and McManus (2002) Respondents are asked to rate the extent of usage of these techniques, with a scale ranging from 1 (not at all) to 5 (to a great extent) A score of 1 indicates minimal usage, while a score of 5 reflects extensive application of the SMA technique in question The survey form related to SMA practices is detailed in Appendix 13, and all variables concerning SMA techniques have been adapted from previous international research to align with the cultural and linguistic context of Vietnamese respondents.

Corporate performance is evaluated through four dimensions: value drivers, financial indicators, non-financial information, and stock price This study focuses specifically on financial measurements, omitting non-financial indicators The constructs of asset turnover and investment efficiency are chosen to represent the productivity that contributes to a firm’s added value Additionally, return on equity is used to assess a firm’s profitability as a key financial indicator While various methods exist to determine firm value, such as free cash flow and residual income discounted by the cost of capital, this study utilizes Tobin's Q as a proxy for evaluating corporate performance by identifying firm value.

Assetturnoverratio(ATO)isusedtomeasuretheproductivityo f oursamplecompanies.T heassetturnovermeasureshowefficientlyanentityusesitsassetstogeneratesales.Itisdetermined bydividingnetsalesbyaveragetotalassetsfortheperiod.Thisfigureshowsthedollarofsalesprod ucedbyeachdollarinvestedinassets.Itisavalidmeasureofproductivity.Althoughthereisnumer ousdifferentproductivitymeasurementmethods,thisindicatoriseasytocollectdataandcompara blebetweendifferentempiricalpriorstudies,itisthereforewellsuitedtothisstudy.Assetturnover isusedtomeasurecorporateperformanceinmanystudiessuchasFirerandMitchell-

Asset turnover= Net salesAverage total assets (4.19)

Conceptually,investmentefficiency(INVEFF)meansundertakingallprojectswith positivenetpresentvalue.GaryC Biddle,Hilary,andVerdi(2009)usea modelthatpredictsinvest mentintermsofgrowthopportunities.Specifically,investmentefficiencywillexistwhenthereis nodeviationfromtheexpectedlevelofinvestment.However,thosecompaniesthatinvestaboveth eiroptimal(positivedeviationsfromexpectedinvestment)over- invest,whilethosethatdonotcarryoutallprofitableprojects(negativedeviationsfromexpectedi nvestment)under-invest.FollowingGaryCBiddleetal.

(2009),inordertoestimatetheexpectedlevelofinvestmentforfirmiinyeart,thisstudyspecifiesa modelthatpredictsthelevelo f investmentbasedo n growthopportunities(measuredbysalesgro wth).Deviationsfromthemodel,asreflectedintheerrortermoftheinvestmentmodel,representth einvestmentinefficiency.Theresidualsfromtheregressionmodelbelowareusedasafirm- specificproxyforinvestmentinefficiency.Apositiveresidualmeansthatthefirmismakinginvest mentsatahigherratethanexpectedaccordingtothesalesgrowth,soitwillover- invest.Incontrast,anegativeresidualassumesthatrealinvestmentislessthanthatexpected,soitwi llrepresentanunder- investmentscenario.Thedependentvariableo f investmentefficiency(INVEFF)willb e theabso lutevalueo f theresidualsmultipliedb y –

1,soa highervaluemeanshigherefficiency.Thisapproachisusedtomeasureinvestmentefficienc yinsomepiecesofresearchsuchasGaryC Biddleetal.(2009),F.Chenet al. (2011),JuanPedroSánchez and Gomariz (2012).

Totalinvestmentoffirmiinyeart,definedasthenetincreaseintotalassetsand scaledbythe previous year’s totalassets

INVEFF: Investment efficiency, the absolute valueofresiduals multipliedby–1

Returnonequity(ROE)isawidelyusedmeasureofprofitabilityfromthepointofviewo f th eordinaryshareholders.Thisratioshowshowmuchprofita companycangenerateforeachdollaro fshareholders’equity.Thisratioprovidesanindicationontheearningspowerofshareholders’bo okinvestmentandisfrequentlyusedwhencomparingtwoormorefirmsinanindustry.Itiscalculate dbydividingnetprofitminusanypreferencesharedividendsbyaverageordinaryshareholders’eq uity.ROEisalsochoseninsteadofrateofreturnonassetstominimizepossiblemulticollinearitybe causeROEiscomposed bytwofactorsthatarereturnonassetsandthedegreeofleverage.Returnonequityisusedtomeasure corporateperformanceinmanystudiessuchasMing-Chinetal.(2005),Dorestani

(2009),Mondal and Ghosh(2012).Theformula toobtain the ROEis:

Net income–preference share dividend ReturnonequityAverage ordinary shareholders’ equity

Tobinq (TOBINQ) plays a crucial role in various financial interactions, helping to explain the connections between managerial equity ownership and firm value, as well as the relationship between managerial performance and tender offer gains In contemporary finance literature, Tobinq is recognized as a vital and widely accepted measure of corporate finance, offering a forward-looking perspective compared to traditional backward-looking accounting profit metrics This is due to a better understanding of market constraints by investors, as highlighted by Demsetz and Villalonga (2001) Tobinq is calculated as the ratio of a firm's market value to the replacement cost of its assets To simplify this calculation, this study utilizes the approximate Tobinq recommended by Chung and Pruitt (1994), which assumes that the replacement values of a firm’s assets are equal to their book values.

Marketvalueo f equityisfirmi’ssharepricemultipliedb y thenumberofc ommonshares

PS: Theliquidatingvalue of firm i’s outstanding preferredsharesNWC:

Thevalueoffirmi’sshort-termliabilitiesnetofitsshort- termassetsLDEBT: Thebookvalueoffirmi’s long-termliabilities

Followingpreviousstudies(GaryC.Biddle&Gilles,2006;Cadez,2006;F.Chenetal.,2011

;Seaman&Williams, 2011),thisstudy introducesseveral controlvariablesin allo f these regressionequations.

GRWvariable,aproxyoffirmgrowth,ismeasuredbysaleschangesscalesbypriorsales.Hig herrateo f salesgrowthindicatesa firm’sbetterwealthcreation.Thus,salesgrowthisusedasacont rolvariableinfluencingcorporateperformance.Thecorrelationbetweenfirmgrowthandcorpora teperformanceisoftenaccompaniedwitha positiverelationship (Dorestani, 2009).

Firmgrowth (GRW)= Net Sales t – Net Sales t-

1Net Sales t-1 (4.23) Thisstudyalsocontrolsforfirmage(AGE)becauseolderfirmshavegreater advantageousconditionssuchaseconomiesofscale,betterinfrastructureormoreinternally- generatedintangibleassetstohavesuperiorperformances.Coad,Segarra,andTeruel(2013)indic atethatageingfirmsareobservedtohavesteadilyincreasinglevelsofproductivity,profitability,la rgersizeandhigherequityratios.However,theyalsodiscoverthatfirmperformancedeteriorates withagebecauseolderfirmsappeartobelesscapabletoconvert employmentgrowthintosales growth, productivityand profits.

Firmage (AGE)=Logarithm(Yeart–Establishment Year)(4.24)

Firmsize(SIZE),asmeasuredbynaturallogarithmoftotalassets,isusedtocontroltheimpac tofsizeonwealthcreationthrougheconomiesofscales,bargainingpowerorearningspersistenc ebasedonthescope(Nazari,2010;Riahi-

Belkaoui,2003;Wang,2011).Largeorganizationsaremorelikelytohavetheresourcesneededto adoptnewinnovations(Luca& Atuahene-Gima,2007)andtoexploitexistingknowledge(Yli‐ Renko,Autio,&Sapienza, 2001).

Firmsize(SIZE)=Logarithm(Total Assets)(4.25)

Debtstructureorfinancialleverage(LEV)asmeasuredbytotallong- termdebtovertotalequity,isusedtocontroltheimpacto f debtservicingo n profitabilityandwealt h(Nazari,2010;Riahi-

Belkaoui,2003;Wang,2011).Inaddition,theroleofdebtistoreducemanagers’discretionanddisc ipliningtheirinvestmentdecisions(Jensen& Meckling,1976).Asregardsinvestmentefficiency ,debtholdersmaymonitorborrowersbetterandthusreducetheagencyconflictbetweencreditorsa ndborrowersthatarisesfrominvestmentopportunitiestomitigateover-investmentandunder- investmentproblems(JuanPedroSánchez&Gomariz, 2012).

Financial leverage (LEV)= Total long- termdebtTotal equity (4.26)

Chapter4presentsthereasonstochoosePLS-SEMapproach,theresearchprocess,howto determineunitofanalysis and samplesize,aswellashowtomeasureallvariablesinbothofresearchmodels.

ThisstudyappliesPLS-SEM,insteadofcovariance- basedSEM,becausetheauthorisnotlikelytohavealargesamplesizewithnormaldistribution.Ad ditionally,thisstudyalsouses bothreflective andformative measurement models, arefavour toPLS-SEM.

Intermsofdatacollection,thisstudycollectsresearchdatathroughtwophases.Thefirstphas eistosendquestionnairesurveytoobtainprimarydataaboutSMApractices.Thesecondphase,fin ancialdataaboutintellectualcapitalandcorporateperformanceareminedfromeachorganization o f everyrespondent.Sinceitisextremelydifficulttomatchbetweenprimarydataandsecondaryd ataofanorganization,thetargetminimumsamplesizeissmall,withexpected127observationsasb eingcalculatedbytheG*Powersoftware.

ThisstudyappliestheVAICmodeltomeasureICbecauseofeasy-to- calculation,theabilityofhighercomparisonacrossthefirmsandinputdataauditedbyprofessional publicaccountants.TomeasureeachconstructrelatedtothegroupofSMAtechniques,five- pointLikertscalesareusedtoassesswhatextentanorganizationdeployseachofSMAtechniques. AllthequestionsinthesurveyformareamendedfromthestudiesofCravensandGuilding(2001)a ndGuildingandMcManus(2002).Lastly,corporateperformanceismeasuredbyfourfinancialin dicatorswhichrepresentforthreeoverfourassesseddimensions,exceptfornon- financialdimension.Assetturnoverand investmentefficiencyaretheperformancesoftheproductivitydrivingtoafirm’svalueadded.Ret urnonequityassessesafirm’s profitabilityand Tobinqisaproxytoevaluateafirm’smarket value.

Thenextchapterisgoingtointroducedataanalysisandtheempiricaloutcomesofmeasurem entandstructuralmodels.Italsoincludesnotonlytestingthereliability,discriminantvalidity,con vergenceofmeasurementscalesbutalsoexaminingthefitnesso f structural models.

Thischapterpresentstheassessmentandrefinemento f themeasurementscales.Section5. 1presentshowtocollectdatatoconstructthevariablesofSMApracticesandthepilottesttoexami netheattributesoftheindicatorsofSMApracticesbeforecollectingmaindata.Section5.2discuss esthecharacteristicsofthefinalsampleinthemainstudy.Sections5.3and5.4discusstheoutcome so f reflectiveandconfirmativemeasurementscalesassessment.ThefinalSection

5.5providesdescriptivestatisticsoftheresearch dataandanevaluationofcollinearityissue inthe inner structural models.

Data collectionto construct the variablesofSMApractices

Thisworkisbuiltonthecombinationofprimarydata(viasurveys)andsecondarydata(finan cialdatacollectedinfinancialstatements).T o investigateS M A practicesappliedinabusinesso rganization,thedataiscollectedthroughquestionnairesurveywhichissenttoSMApractitioners;i e.managersormembersoftopmanagementwithknowledgeaboutaccounting,planningorfinanc eandatleasttwoyearsofworkingexperienceinthecurrentorganization.Thissectiondemonstrate sh o w tocollectprimarydatao f SMApracticesviaquestionnaire survey.

The questionnaire was initially created in English and consists of three sections: Part A gathers demographic information about respondents, including their job titles, responsibilities, and years of experience Part B focuses on the organization's Strategic Management Accounting (SMA) practices, incorporating 18 techniques related to strategic cost management, competitor accounting, strategic accounting, and customer accounting Part C collects optional contact information from the respondents To measure the extent of usage of these techniques, respondents are asked, "To what extent does your organization use the following techniques?" This is followed by a list of the 18 SMA techniques, rated on a five-point Likert scale from 1 (not at all) to 5 (to a great extent), where a score of 1 indicates minimal usage and a score of 5 indicates maximum usage For further details, please refer to Appendices 13 and 14 for the survey forms in English.

5.1.2.Translating and pilot testingofthe questionnaire

ThequestionnairewastranslatedintoVietnamesewiththeprocessasfollows.ThedraftEng lishversionofthequestionnairewassubmittedtothreeprofessorswithmanyyearso f experiencei nlecturingo n managementaccounting.Subsequently,therevisedquestionnairewastranslatedi ntoVietnameseviathetranslationprocessproposedbyBrislin(1970).Thetranslationprocesshad threesteps:(1)translatingtheoriginalquestionnaireintoVietnamese,

(2)translatingthetranslatedVietnameseversionbacktotheEnglishversion,and(3)comparingth ebackwardversionwiththeoriginalquestionnairetoensuretheconsistencyofmeaningbetweent heoriginalquestionnaireandits translatedVietnamese version.

Subsequently,therevisedVietnameseversionwasre- checkedbythreemanagersandtwoacademicstaffinordertoenhancethecompetenceofthequest ionnaireintermsofclarity,wording,understandabilityandconfiguration.Someminormodificat ionstothisversion(allbecausethewordingisappropriatewithVietnameserespondents’culturea ndlanguage)wereundertakenwithoutaffectingthemeaningo f thequestionnaireitems.Detailed informationonthe Vietnamesefinalquestionnaire is showninAppendix14.

Todopilottestingofthequestionnaire,thefinalVietnamesequestionnaireinpaperwassentt othestudentswhohavebeenstudyingtheCIMAprogramsatthemanagementandstrategiclevelso rtheACCAattheprofessionallevel.Thosearetheindividualswhohaveknowledgeofstrategicm anagementaccountingaswellworkingexperiences.Therefore,theyareeligibleinformantstod o pilottestingo f thequestionnaire.Aftercollectingsurveypapersandchoosing80completedrespo nses,thestatisticaltechniqueso f CronbachAlphaandExplanatoryFactorAnalysis(EFA)foralls caleswasthenperformedtoassessthereliability,convergent anddiscriminant validitiesofmeasurementscalesthroughapilotstudywith80samples.Inthisstudy,theapplicatio nsofCronbachAlphaandEFAwereconductedusingthesoftwarepackageSPSS20.0.Cronbach Alphacoefficientsare0.887–

The reliability of the measurement scales used for exploratory factor analysis (EFA) is confirmed, with a Cronbach's alpha greater than 0.60 and all item-total correlation coefficients exceeding 0.3 (Nunnally & Burnstein, 1994) EFA was conducted using principal component analysis (PCA) with Varimax rotation, revealing that all factor loadings above the cutoff value of 0.50 were statistically significant The analysis identified four factors with an Eigenvalue greater than 1.5, accounting for 77.841% of the variance Additionally, to ensure the appropriateness of the analysis, Bartlett’s test of sphericity and the Kaiser-Meyer-Olkin measure were utilized.

Olkin(KMO)measureswereexamined.TheK M O valueof0.930andtheverysmallSig.valuep rovedthatEFAresultswerereliable(χ 2= 1,215.546,df=153andp=0.000).Hence,thesemeasures wereconceivedappropriatelyforfurtheranalysisbecausetheyrevealedanacceptedvalidityandr eliabilityinthisstudy.InrelationtoEFAtesting,observedvariableswerearrangedandnamedinac cordancewithaprinciplethatonewithitsfactorloadinginfavourofadimensionwillb e transferre dtothat dimensionas illustratedinAppendix 15.

AsmentionedinChapter4,thisstudymainlyusesquantitativeresearchmethodbyusingem piricalsurveydataandfinancialdataobtainedfroma sampleo f atleast1 2 7 publiclytradedenterp risesinVietnamfortheyearof2016.Althoughtherearenow356companieslistedo n HoSEand3 87companieslistedo n HNX(statisticsi n 2016athttp:// vietstock.finance.vn),emailswitha surveylinkweresentt o only250potentialinformantsfrom2

50 listed firms which werechosen toattend thefinalroundoftheawardelectingVietnameselistedenterpriseswiththebestannualreports.Sin ceitisextremelydifficulttoobtaintheemailandinformationo f theseniormanagerssatisfiedwith allconditionsintermso f havingknowledgeaboutaccounting,planningo r financeandworkingf orlistedcompanies,t h e sourceo f individualinformationissupportedbytheglobalbodiesofprof essionalaccountantssuchastheAssociationofCharteredCertifiedAccountants(ACCA)andthe CharteredInstituteofManagementAccountants(CIMA),whichare the sponsorsofthe yearlyawardelectingthe best annual reports.

E- mailsurveywasoneofthemostsuitabledatacollectiontechniquesforabroadsurveyofbusinesso rganizationsinVietnam.Thistechniquehasbeenusedforitstimeliness andcost effectiveness It could aimat potential informants, was inconspicuous,andpotentialinformantscoulddecidetoanswerornot.E- mailswithsurveylinksweresenttotheemailaddresso f 2 5 0 potentialinformantsviatheSurvey Monkeysoftware.Follow-upemailsweresenttonon-respondentstore- explainthepurposeoftheresearch

Sixmonthsafterthefirstemailstherewere192completedrepliesreceived.Inthisstudy,thec ompleteresponseisdefinedasaresponsewithoutmissingdata.Theinformantshadtoanswerallth emandatoryquestionsinthesurveysection,andthenproceedingtothenextpart.Thisprocedurewa sprogrammedinSurveyMonkeysoftwareandwasperformedtosolve theissueofmissingdata insome surveyresponses.

Careless responses can skew survey results, particularly when response times are unusually short In this study, 9 responses with completion times under 10 minutes were removed from a total of 192, representing a 5% elimination rate This is consistent with findings by Meade and Craig (2012), which suggest that 5% to 15% of participants may respond inadvertently in lengthy surveys No responses were discarded based on financial literacy or experience, as all eligible informants were contacted Additionally, 4 responses indicating "No" to whether their organization analyzes management accounting data were excluded, suggesting a lack of understanding of strategic management accounting Lastly, 5 responses were retained where financial information was insufficient to support the research models.

Thefinalsamplewascomprisedof174validresponses,asshowninTable5.1.The174respo nsespassingthroughtheeliminatingprocesswereconsideredeligibleforthedataanalysis.Datafr omtheseresponseswereexportedfromSurveyMonkeytoaspreadsheettoaddmore financial informationfor furtheranalysis.

Table 5.1.Developmentofthe final sampleinthe mainstudy

-with“No” responses tothe questionofSMAconcept 4

Sample characteristics

Asillustratedin thepart 5.1.3, theemails withsurvey linkwere sentto 250 potentialinformants,b u t only192completedresponseso f thecorrespondingnumbero f listed companieswerereceived.Aftereliminating18inappropriateresponses,thesampleconsistso f 1 74satisfactoryobservations.Thesebelowpartsdescribethemaincharacteristicsofthe researchsample.

The manufacturing sector is the dominant industry in Vietnam, comprising 35.63% of the total sample, followed by real estate and construction at 18.39%, and mining and energy at 12.64% The study analyzed 174 selected firms, representing 20% of the 743 publicly traded companies on the Ho Chi Minh and Hanoi Stock Exchanges According to Krejcie and Morgan's sample size formula, a representative sample for 750 firms is 154, making the selection of 174 firms appropriate for generalizing the population Public enterprises play a significant role in the Vietnamese economy, with the market capitalization of listed companies accounting for 26.8% of GDP in 2015 As per the General Statistics Office of Vietnam, in 2016, the economic structure comprised 16.32% agriculture, forestry, and fishing, 32.72% industry and construction, and 40.92% services, indicating that the findings may be more applicable to manufacturing and construction firms than to those in the service and agriculture sectors.

Table5.3presentsthesamplecharacteristicstotalassetsandthelevelo f SMAimplementati onassessedbytherespondents.AccordingtotheDecree39/2018/ND-

CPrelatedtothecriteriatocategoriseintosmallandmediumenterprises,thesmallenterpriseshast otalequitylessthanVND20,000millionwhilethemediumenterpriseshastotalequityintherange ofVND20,000–

100,000millionandtotalequityhigherthanVND100,000millionarethelargeenterprises.Thetab le5.3showsthat89.66%ofthesampledorganisationshadtotalequityofmorethanVND100,000 million,namedbylargeenterprises.T h e authorbelievesthatwouldb e theappropriatesampleto investigateintellectualcapitalandstrategicmanagementaccountingbecausethemajorityo f the sample arepubliclytradedlarge enterprises.

The study investigates 18 SMA techniques, each assessed with a maximum score of 5, resulting in a total potential score of 90 for SMA practices A threshold value of 45 is established to categorize the sample into two groups: those with high SMA practices (scores above 45) and those with lower levels According to Table 5.3, 70.11% of the organizations sampled fall into the high SMA practices category, with 92.62% of large enterprises achieving higher levels of SMA implementation To evaluate the appropriateness of the organizations for SMA implementation, the author utilized a question derived from the definition of SMA: "Does your organization analyze management accounting data about the business, competitors, and customers for developing and monitoring the business strategy?" Responses indicating "No" were excluded, ensuring that the remaining organizations were suitable for investigating the correlations between SMA practices and intellectual capital.

Table 5.3.Thenumberofrespondents by OrganizationsizeandSMApractices type

Arespondentrepresentingeachorganizationtoanswerthequestionsinthesurveyaretheexe cutiveusinginformationobtainedfromthefinanceoraccountingdepartmentandthosedirectlyin teractwithfinanceoraccountingdepartment.Therespondentscomefromavarietyofsectors(co mmercialfinance,costmanagement,budgeting,accounting,planningandprocurement).Inthes urvey,theauthorusedthetestingquestion“Whatisyourcurrenthighestpositioniny o u r compan y?”withthethreeoptionsrelatedtotopmanagement,middlemanagementandnon- managementstaffsoastochecktheappropriatenessoftherespondentsbeforecontinuingwiththe followingquestions.

However,theauthorcategorisesinto7 groups(seeTable5.4).Statisticalresultso f thesamplebyp ositionandworkingyearsinthecurrentpositionshowthattheinformantsarefinancemanagers(27 01%),followedbyreportingmanagers(20.11%),thenbytheheado f thedepartment(14.36%)a ndgeneralmanagers(14.36%).Allrespondentsarefromseniormanagersormembersoftopmana gementteamwithknowledgeaboutaccounting,planningorfinanceandatleast2yearsofworking experienceinthecurrentorganizations.

Table 5.4.NumberofRespondentsbyPositions typeandWorking Years type inthecurrent organization

Theoutcomesofreflective measurement scalesassessment

TheSMApracticesvariableisbuiltbyreflectivemeasurementscales.Therefore,asbeingpr esentedinthePart4.2.1,theyareassessedontheirinternalconsistencyreliability,indicatorreliabil ity,convergentvalidityanddiscriminantvalidity(Kline,1998),asfollows:

 Internal consistencyreliability:thecriterionfor internal consistencyevaluationis composite reliability Composite reliabilityvalueofhigher than0.60andnotabove0.95areacceptableinexploratoryresearch(Nunnally& Burnstein,1994).Appendix16showsthatthecompositereliabilitiesoftheselatent variablesrangebetween0.860and0.950.Theseresultsindicateahighlevelofreliabilit yofthe measurement scales inthe outer models.

 Indicatorreliability:Thischaracteristicismeasuredb y outerloadingso n a construct ,indicatingthattheassociatedindicatorshavemuchincommon.Appendix16showst hattheouterloadingsofallobservedvariablesofalltheconstructsrangebetween0.57 7and0.881andhigherthanthecut-offvalueof

0.5(HairJr& Hult,2016).Allthecorrespondingt-bootstrapvaluearewellabove 1.96 tobestatisticallysignificant (rangedbetween 10.493and 50.343).

 Convergentvalidity:Thischaracteristicismeasuredbyaveragevarianceextractedcr iterionwhichisdefinedasthesumofthesquaredloadingsdividedb y thenumberofind icators(Nunnally&Burnstein,

 Discriminant validity: o Onemethodforassessingdiscriminantvalidityisb y examiningFornell-Larcker criterion Appendix18presents that the square rootofAVEofeachconstruct rangedbetween0.746and0.835, whichare higher thanits highestcorrelationwithanyotherconstruct;thus,indicatingthediscriminantvalid ityo f themeasurements.Ascanbeseen in Appendix

The analysis reveals that the squared root of the Average Variance Extracted (AVE) for the SMA variable is lower than its correlations with other variables such as COM, CUS, SCM, and STR Despite this, the author acknowledges the limitations indicated in Appendix 18, as the SMA variable is part of a hierarchical component model Discriminant validity is confirmed when an indicator's loading on its assigned construct exceeds its cross-loadings with other constructs, as outlined by Hair Jr & Hult (2016) Appendix 17 illustrates the loadings and cross-loadings for each indicator, showing that the indicator COM1 has the highest loading value of 0.745 with its corresponding construct COM, while all cross-loadings with other constructs, such as CUS, are lower (0.566) This overall cross-loadings criterion supports the discriminant validity of the constructs Additionally, the study utilized the Heterotrait-Monotrait ratio to further assess validity.

Monotrait(HTMT)test,whichismorestringentthanthato f (Fornell& Larcker,1981)toevaluatediscriminantvalidity(Henseleretal.,2015).Appendix18indicate sthattheHTMTvaluesofconstructsmeasuredbyreflectiveindicatorsrangedbet ween0.466and0.785,whicharesignificantlybelow0.85,providingevidence for discriminant validity.

Theoutcomesofformative measurement scalesassessment

Thestructuralcapital(SCE)variableisbuiltbyformativemeasurementscales,thoseareinn ovationcapitalefficiency(RDCE)andorganizationalcapitalefficiency(ORGCE).Thissectionf irstlypresentsthecalculationsoftheRDCEandORGCEvariablesandthen,asbeingpresentedint hePart4.2.2,theyareassessedontheirconvergentvalidity,collinearityissue, statisticallysignificant andrelevanceofthe formative indicators.

The efficiency of innovation is determined by dividing the cumulative research and development (R&D) investment by the value added, as outlined in Section 4.4.1.3 The cumulative R&D investment is calculated based on the sum of prior years’ R&D investments, depreciated over a three-year economic life This study adopts a straight-line depreciation approach due to the limited data availability in Vietnam's young stock exchange market, which has only been fully operational since 2010 For instance, if a manufacturing firm invests in R&D amounts of 3,408 million VND in 2016, 5,658 million VND in 2015, and 1,307 million VND in 2014, the cumulative R&D investment for 2016 would be 7,617.12 million VND Consequently, the firm's innovation efficiency is calculated as 0.0503 by dividing the cumulative R&D investment by the value added of 151,395 million VND.

AsdemonstratedinthePart4.4.1.3,theempiricalresultsfromthesimplecorrelationsandmu ltivariateregressionsdonotcontrolforthepotentialendogeneityofSGAi,tandEi,t(Shangguan,200 5).Inthepresenceo f endogeneity,ordinary-least- squaresestimationyieldsbiasedandinconsistentcoefficientestimate.Forthisreason,theauthorc onductsthe

This article discusses a two-step regression analysis of the equation 4.15, incorporating firm-specific fixed effects and year-specific random effects across various industries The first step involves estimating a regression to predict Selling, General, and Administrative (SGA) expenditures based on exogenous variables like total assets and profitability The second stage employs Ordinary Least Squares (OLS) regression to derive consistent estimates of the relationship between SGA expenditures and annual earnings Coefficient estimates across years and industries reveal that while δ1 and δ2 are significant for all industries, δ3 lacks significance in sectors such as mining, energy, and real estate This indicates that SGA expenditures have a useful life of two to three years, with the most substantial impact on earnings occurring in the current year, followed by rapid depreciation.

TocalculatetheamortizationratesofSGAexpenditures,theauthoronlyconsidersthosestat isticallysignificantδk’sinPanelA.Eachofthesecoefficientestimatesrepresentsthe benefits contributedbythe associatedSGA expenditures toearnings, while the sumofsignificantδ’srepresentsthetotalbenefitsofSGAexpendituresforoneyear.Forexample,f ortheManufacturingsector,δ1=1.694representsthecontributiontoearningsbythecurrentSGAe xpenditures,δ 2= 0.651representsthecontributiontoearningsb y theprevious- yearSGAexpenditures,δ3=0.204 representsthecontribution to earningsby theSGAexpendituresoftheyearbeforethepreviousyear.(δ 1 ,δ 2 ,δ 3 )=2.549representsthetotalea rningsinyeartcontributedbySGAexpendituresovert,t-1,t-

2years,while,forthecommercialsindustry,onlythesumofδ1andδ1=1.493representsthetotalearni ngsinyeartcontributedbySGAexpendituresovert,t-

2.Accordingly,formanufacturingsector,0.665=[1.694/2.549];0.255and0.080aretheamortiza tionrateofSGAexpendituresintheyeart,t-1andt-

Afterdeterminingthevalueoftheamortizationrates,firm- specificleveloforganizationalcapitalismeasuredbytheequation4.17.Forinstances,supposeift hefirstfirminthemanufacturingindustryspendsSGA 1,2016= 49,854millionVND,SGA 1,2015= 40,122millionVND,SGA 1,2014= 19,158millionVND,thecumulativeorganizational capitalinvestmentinyear2016is:ORGC1,2016=49,854x(1–0.665)+40,122x(1–

0.255–0.655)+19,158x(1–0.080–0.255–0.665),910.85.Then,theefficiencyof organizationalcapitalofthisfirm(0.131516)iscalculatedbythecumulativeorganizationalcapita l investment (19,910.85)dividedbythevalue added(151,395).

TheRDCEandORGCEindicatorsareformativemeasurementscaleso f t h e SCEvariable. AsillustratedinthePart4.2.2,theyareassessedontheirconvergentvalidity,collinearityissue,stat isticallysignificantandrelevanceo f theformativeindicators,a s follows:

 Convergentvalidity:Thischaracteristicismeasuredbycorrelatingbetweentheforma tivelymeasuredconstructwithareflectivelymeasuredconstructofthesameconstruc t.However,establishedreflectivemeasurementinstrumentscouldnotb e available,a ndconstructinga newscaleisdifficultandtime- consuming(HairJr&Hult,2016).Analternativeistoapplyageneralitemthatsummari zestheessenceo f theconstructtheformativeindicatorspurporttomeasure(Hair,Rin gle,& Sarstedt,2013).F o r thePLS-

SEMonstructuralcapital,anadditionalquestion,“Pleaseassesstheextenttowhichyo urcompany’sstructuralcapitalperformsinlastthreeyears,comparedwithyourmajor competitors”,eachrespondentcirclesthevaluemeasuringonascaleof1 (extremelyp oor)to7(excellent).Thisquestioncanbeusedasanendogenoussingle- itemconstructtovalidatetheformativemeasurementofstructuralcapital.

Figure 5.1.Assessmentofconvergent validityofformative indicators relative tostructural capital

Figure 5.1 shows the results for the redundancyanalysis for the SCEconstruct.T h e originalformativeconstructislabelledwithSCE_F,whereasth egeneralassessmentofthecompany’sstructuralcapitalefficiencyusingasingle- itemconstructislabelledwithSCE_G.Ascanbeseen,thisanalysisyieldsapathcoeffi cientof0.885,whichisabovetherecommendedthresholdof0.70,thusprovidingsupp ort for the formative construct’s convergent validity.

 Collinearityissue:Unlikereflectiveindicators,whichareessentiallyinterchangeabl e,highcorrelationsarenotexpectedbetweenitemsinformativemeasurementmodels AscanbeseeninTable5.5,thereisnotanycollinearityproblembetweenformativein dicatorsduetothefactthateachindicator’sVIFvalue (1.203) is lower than5.0(Hair Jr&Hult, 2016).

 Significanceandrelevanceofformativeindicators:Anotherimportantcriterionforev aluatingthecontributionofaformativeindicator,andtherebyitsrelevance,isitsouter weight.Theouterweightistheoutcomeo f themulti- regressionbetweenthelatentvariableandtheformativeindicators.TheresultsinTabl e5.5showthattheouterweightsaresignificantandhighenough(i.e.above

Table 5.5.VIF, Significance and relevanceofformative indicators

Models withendogenous construct RDCE ORGCE

Note:Significantat:*10,**5and***1percent levels(two-tailed),tvalue (showninbrackets)

Calculationofthevariableofinvestment efficiency

The study analyzes the equation using three regression methods: Pooled Ordinary Least Squares (OLS), Fixed Effects Model (FEM), and Random Effects Model (REM) through the Generalized Least Squares (GLS) method to address heteroskedasticity issues The Likelihood test indicates that FEM is more appropriate than Pooled OLS To determine whether to use fixed or random effects, the Hausman test is applied, revealing that the p-value for cross-section random effects is less than 5%, leading to the rejection of the null hypothesis in favor of the fixed effects model Consequently, the model incorporating firm-specific and year-specific fixed effects is preferred for all estimations Additionally, Durbin-Watson ratios between 1.5 and 2.5 suggest a good fit without autocorrelation Finally, the dependent variable for investment efficiency is defined as the absolute value of the standardized residuals multiplied by -1, indicating that a higher value corresponds to greater efficiency.

Total investment (INVEST) Pooled OLS

Note:Significantat:*10,**5and***1percent levels(two-tailed)

Descriptive statistics andcollinearityassessment

Thedescriptivestatisticsprovidesimplesummariesaboutthesampledataandmeasures.De scriptivestatisticssummarizethedataandformedthebasisofquantitativeanalysisofdata.Inaddi tion,toanalysetheassociationbetweenthedependentandindependentvariables,acorrelationan alysis(Pearson)isalsoundertaken.Movingforward,theissueofpotentialcollinearityproblemisa lsotestedtoconsiderremovingoneo f the correspondingindicators before conductingthe further regressions.

Appendix22containsdescriptivestatisticsforallthevariablesusedinthisstudy.Ascanbeob servedfromTable 5.2, the validnumberofobservations for eachvariable is174samples.Mean,median,maximum,minimum,standard deviation,SkewnessandKurtosisarereportedforeachvariableusedinthecurrentstudy.Skewnes sandKurtosisstatisticsallsuggestthatthevariablesarenotnormallydistributed.Toreducethehete roskedasticityproblemarisingoutofthenon- normaldistributions,regressionsareestimatedbythePLS-

Appendix2 2 alsopresentsPearson’scorrelationcoefficientanalysisforthedependentandi ndependentvariables.Correlationcoefficientsummarizesthelinearrelationshipbetweentwova riableshavingranked andprovidesufficientinformation fromthisstudy’spointofview.UnderthePearson’scorrelation,ofparticularnoteisthatthecorrel ationcoefficientsaren o t o f highmagnitudebetweenanytwoo f theindependentvariables tocause concernaboutmulticollinearityproblems.

TherelationshipsofHCE-SMA(0.551);SCE-SMA(0.514);RCE-SMA(0.829)aresignificantlypositive,roughlysupportingthesecondhypothesisthateacho f IC componentsispositivelyassociatedwiththepracticesofstrategicmanagementaccounting.

Thecorrelationanalysesshowthat,underthePearson’scorrelation,allICcomponentsarep ositivelyrelatedwithallofthecorporateperformanceindicatorsatthe significantlevel.TheresultsforICcomponentsdemonstratethatincreaseinvaluecreationefficie ncywillincreaseinmarketvalue,profitabilityandoperationefficiency.Thissupportsthethirdhyp othesisthattherearesignificantpositiveassociationsbetweeneacho f ICcomponents and eachofcorporate performance indicators.

TherelationshipsofSMA-ATO(0.713);SMA-INVEFF(0.776);SMA-ROE(0.930); SMA-

Furthermore,Appendix22alsoindicatesthateachgroupofSMApracticeshasthesignifica ntlypositiverelationshipwitheacho f ICcomponents,exceptfortheoutcomerelatedtot h e relati onshipbetweencustomeraccountingandstructuralcapital(0.011insignificantly).Thismeansth ateachgroupo f SMApracticesislikelytopositivelyassociatewithmostoftheICcomponentsast heinitialbasisoftheresultpredictionbeforeconducting regressionmodels.

AccordingtotheresultsinAppendix23,VIFvaluesallareuniformlybelowthethresholdval ueo f 2 , exceptforS M A variableunderthevalueof5 Itisconcluded,therefore,thatcollinearity doesnotreachcriticallevelsinanyofconstructsandisnotanissue for the estimationofthepartial least square pathmodels.

Chapter5presentsdatacollectiontoconstructthevariablesofSMApractices,theassessme nto f reflectiveandformativemeasurementscales,descriptivestatisticsandcollinearityassessm ent.

Thefinalsamplew a s composedo f 174validresponseswiththedominanceofmanufactur ingsector.70.11%ofthesampledorganisationsiscategorisedintothegroupo f highlevelofSM Apractices.92.62%ofthelargeenterpriseshasthehigherlevelofS M A implementation.Statisti calresultsofthesamplebypositionandworkingyearsinthe currentpositionshowthat theinformants are finance managers (27.01%), followedbyreportingmanagers(20.11%),thenbytheheadofthedepartment(14.36%)andgener almanagers(14.36%).Allrespondentsarefromseniormanagersormembersoftopmanagementt eamwithknowledgeaboutaccounting,planningorfinanceandatleast2yearsofworkingexperie nce inthe current organizations.

Thischapteralsodemonstratestheassessmentoutcomesofreflectiveandformativemeasur ementscalesintermsofstrategicmanagementaccountingpractices,followedtheresearchproces sillustratedinChapter4 T h e reliability,convergentvalidityanddiscriminantvalidityofthemea surementscalesrelatedSMApracticesaresupportedbythedataset.The18finalindicatorsfor4co nstructsofSMApracticesaresatisfactoryforfurtheranalyses.Theresultsindicatethatthereisnom easurementscaleforexception.Theissueofcollinearityalsodoes not reachcritical levels inanyofinner constructs.

Thenextchapterisgoingtointroducedataanalysisandtheempiricaloutcomesofmeasurem entandstructuralmodels.Italsoincludesnotonlytestingthedirectregressionandthemediatedpat hregressionsintherelationshipbetweenICandcorporateperformanceviathemediationofSMA practicesbutalsothetestingtheimpactofSMApracticesonICmanagement.

Chapter6 presentsandanalysesthedatausedinthisstudy.Itisstartedattheevaluationo f th efitnesso f theoreticalmodels.T h e nextsectionspresenttheempiricalresultsofexaminingthehy pothesesdevelopedinChapter3.Itincludestheoutcomesofthedirectregressionsandthemediate dpathregressionsthatareprocessedbythetoolofSmartPLS3.1.Theempiricalresultsarearranged inorderfromthefirsttosixthhypothesisandfinallythetestingresultso f controlvariables.N o t onl yistheanalysiso f thedatadescribedb u t correspondingtoeachsignificantpropositionitisalsoex plainedinthemanagerialcontext.

Evaluationofthe fitnessoftheoretical models

Toevaluatethefitnessofbothinnerstructuralandoutermeasurementmodelstothedatasim ultaneously,theclassicalgoodness-of-fitindex(GoF)associatedwithcovariance- basedSEMisnotappropriatetoPLS-

SEMapproach(HairJr&Hult,2016;Henseleretal.,2015;Nitzl,2016).Anotherpromisinggoodn ess-of-fitstatisticforuseinPLS-

SEMapproachisthestandardizedrootmeansquareresidual(SRMR).AsshowninTable6.1,thec omputedSRMRforallfivemodelsare0.048–0.073lowerthanthe0.08threshold,demonstrating goodfitofallproposedmodels tothe data.

Table 6.1.Summaryofthe SRMRresultsof5-testing models

SRMR values tvalue pvalue Conclusion

Note:Significantat:*10,**5and***1percent levels(2-tailed)

Empirical results–testingofreciprocal correlations betweenintellectual

H 1cfor theintellectualcapitalvariablesinthefirstmodel.Theseresultsshowhowhumancapitallink torelationalcapital(=0.552;pvalue