K.Bulut and G. Kayakutlu

Transcription

1 , July 6-8, 20, London, U.K. Analysng the Impact of Unverstes on Regonal Development: A Case Study Usng Fuzzy Cogntve Maps K.Bulut and G. Kayakutlu Abstract The mpact of nnovaton n ndustral development s contnuously ncreasng. Unverstes have the major roles n nnovaton. The postve nfluence of hgh educaton n regonal development s requred and recognzed by the authortes. Researchers contnue to nvestgate the subject usng a varety of methods. Ths paper analyses the contrbuton of unverstes to the regonal development by usng the Fuzzy Cogntve Mappng (FCM) technque. FCM s used n modellng the crtcal factors and the relatons between them. In ths paper several factors are detected from lterature. A model s desgned on the detected crtera on whch ntervews wth experts of economy are conducted. As a result seventeen crtera are used to construct FCM. Most mportant factors are detected and accordngly some suggestons are presented to mprove Unversty contrbuton n regonal development. Index terms: Fuzzy Cogntve Maps, Regonal Development, Unverstes. I. INTRODUCTION Unverstes are publc nsttutons wth mportant socal roles. They are assgned the msson to educate and render expertse. The unversty graduates desgn and shape the socety. Hence, the nfluence of educaton and research run n a Unversty s not lmted to the technologcal capabltes or development of human sklls n the regon they serve. Therefore, a Unversty establshed n a cty nfluences the technologcal development, socal development, economcal development and cultural development of the cty and ts vcnty [7]. Moreover, a unversty s an mportant resource of nformaton and contnuous educaton whch would support the sustanablty n busness and socal servces for the regon. Unverstes can be seen as multfaceted economc actors that are embedded n regons, and not only produce codfed knowledge and human captal, but also partcpate actvely as mportant nsttutonal actors n buldng and sustanng local networks and flows of knowledge, and n lnkng them wth global ones [2].Unverstes are anchor tenants n ther regons, whch helps stablze regonal economes over the long term, especally n smaller regonal economes. Poltcans are embracng strateges that te unverstes to regonal economc development through the mpacts of academc research on technologcal advances used by companes, the recrutment of graduates nto the regonal labour force, and the actve role of unverstes n settng the regonal economc development agenda [20]. In lterature, there are numerous researches that provde evdence for unverstes to become drvng forces n the regonal development [7]. That s why a lterature survey was run to defne the nfluental factors. More than forty factors are pcked. After ntervewng the experts of economy the research s realzed on seventeen of them. Fuzzy Cogntve Map (FCM) s useful n modellng complex systems [7]. Ths research ams to rank and relate the factors that make a Unversty nfluental n regonal development. Our paper s organsed n four sectons. The next secton presents the selected crtera followed by the clarfcaton of Fuzzy Cogntve Mappng method. Secton 4 focuses on the applcaton. The fnal chapter gves nformaton about the study fndngs and concludes ths paper. II. UNIVERSITY DRIVEN DEVELOPMENT We select the crtera from the lterature about the effects of the unverstes on regonal development. Table I presents the descrpton of all the concepts and the source of these concepts. TABLE I Crtera of the FCM Model and the Descrptons Concept Descrpton Lterature C: The number of unversty-owned research centres. Vught F.v., (2006) C2: C3: C4: Qualty and sze of research canter. Vught F.v., (2006) Number of researchers that unversty has. Vught F.v., (2006) The amount of the regon's workforce. Vught F.v., (2006) K.Bulut s wth the Industral Engneerng Department, Unversty of Krkkale,Krkkale,Turkey. (correspondng author wth moble phone: ; e-mal: kezbanbulut@yahoo.com.) G.Kayakutlu s wth the Industral Engneerng Department, Istanbul Techncal Unversty, Macka Istanbul, Turkey.(e-mal: kayakutlu@tu.edu.tr) C5: C6: Sklls level of regonal labour force. The ncluson level of regonal work force on research and projects. Drucker J.&Goldsteın H.,(2007)

2 , July 6-8, 20, London, U.K. Concept Descrpton Lterature Beng open to change and the atttude of the people of the regon C7: response. C8: Teachng and research potental of the regon to be addressed as an ssue. C9: Unversty-ndustry cooperaton level. Vught F.v., (2006) C0: C: Number of projects whch are developed by the unversty. Applcablty level of the developed projects. C2: The budget volume. Calıskan S., (200) C3: C4: Number of graduates from the unversty. Vught F.v., (2006) The qualty of the professor employed n unversty. for events, goals, nputs, outputs, states, varables and trends of the complex system been modelled. Ths graphc dsplay shows clearly whch concepts nfluences wth other concepts and what ths degree of nfluence s [6]. Exstng knowledge on the behavour of the system s stored n the structure of nodes and nterconnectons of the map. Relatonshps between concepts have three possble types; a) Ether Express postve causalty between two concepts (W j 0); b) Negatve causalty (W j 0); c) No relatonshp (W j 0). The value of W j ndcates how strongly concept C nfluences concept C j. The sgn of W j ndcates whether the relatonshp between concepts C and C j s drect or nverse. A new formulaton for calculatng the values of concepts at each tme step, of a Fuzzy Cogntve Map, s proposed: C5: C6: The amount of the unversty's support for projects. The number and qualty of the socal actvtes organzed by the unversty. n t t t ( j j ) j j A f A W A () C7: Graduate student's desre to work n the regon. III. FUZZY COGNITIVE MAPS (FCM) Cogntve Mappng technque was frst used for modellng decson-makng processes related to socal and poltcal systems by Axelord [].Cogntve Maps are based on tradtonal logc system. Tradtonal bnary logc requres that a statement must be ether true or false [9].But n fuzzy logc there are ntermedate values and also Fuzzy cogntve mappng s based on fuzzy logc. FCM s a powerful tool for modellng and controllng complex systems wth hgh dmenson and a varety of varables and factors. FCM s a soft system methodology that conssts of a number of varable concepts and connectons whch llustrate the cause and effect relatons between the concepts [4].FCM conssts of concepts, that llustrate dfferent aspects n the behavour of the system and these concepts nteract wth each other showng the dynamcs of the system. The human experence and knowledge of the operaton of the system s used to develop Fuzzy Cogntve Map (FCM), as a result of the method by whch t s constructed,.e., usng human experts that know the operaton of system and ts behavour n dfferent crcumstances. An FCM llustrates the system by a graph showng the cause and effect along concepts, and t s a smple way to descrbe the system s behavour n a symbolc manner, explotng the accumulated knowledge of the complex system [6]. Fuzzy Cogntve Maps consst of concept nodes and weghted arcs, whch are graphcally llustrated as a sgned weghted graph wth feedback. Sgned weghed arcs, connectng the concept nodes, represent the causal relatonshp that exsts among concepts. In general, concepts of a FCM, represent key-factors and characterstcs of the modelled complex system and stand Two knds of threshold functons are used n the Fuzzy Cogntve Map framework, the unpolar sgmod functon, where >0 determnes the steepness of the contnuous functon: f( x) (2) x e When nature of concepts can be negatve, ther values belong to the nterval [-, ], the followng functon s used [2]: f ( x) tanh( x) (3) These varables are defned by ther out degree [od (v j )] and n degree [d (v j )].Out degree s the row sum of absolute values of a varables n the adjacency matrx and shows the cumulatve strengths of connectons (a j ) extng the varable [2]. N od( v ) w (4) j k Indegree s the column sum of absolute values of a varable and shows the cumulatve strength of varables enterng the unt [2]. N d( v ) w (5) j k The mmedate doman of a varable s the summaton of ts ndegree (narrows) and outdegree (outarrows) also called centralty. jk kj

3 , July 6-8, 20, London, U.K. Fg..Fuzzy Cogntve Map Desgned The contrbuton of a varable n a cogntve map can be depcted by calculatng ts centralty (c) to fnde whether t s a transmtter, recever or ordnary varable. The centralty (c) of a varable s also called ts total degree [td(v)][2]: c = td(v ) = od(v ) + d(v ) (6) FCMs have these specfc advantageous characterstcs: FCMs capture more nformaton n the relatonshps between concepts. FCMs are dynamc. FCMs express hdden relatonshps. FCMs are combnable. FCMs are tuneable [9]. In lterature FCMs are used n dfferent areas. Peláez and Bowles [5] provde a new strategy for predctng falure effects n a complex system by usng FCM. Kardaras and Mentzas [5] propose a FCM to model and analyse the busness performance. Tseng et al.[9]developed a two-step fuzzy cogntve mappng method n ther study. Chen et al. [4] work on academc papers to apply text mnng, and then formed a fuzzy cogntve map. Dmtrs [6] extends the exstng fuzzy cogntve map (FCM) for medcal decson makng process. IV. CASE STUDY In ths secton, we use the expert-based methods for developng FCM. These methods usually consst of three steps [2]:. Identfcaton of mportant concepts; 2. Identfcaton of causal relatonshps among the concepts; 3. Estmaton of the strength of the causal relatonshps. In order to descrbe the relatonshp between a unversty and the regon n whch the Unversty s located, t s necessary to apply ndcators. Furthermore, the ntensty of the relaton s measured through ths ndcator. In the frst step, the concepts affectng the unversty's contrbuton to regonal development are determned. In determnng concepts, a lterature survey s run and valdated through ntervews wth the experts. Each relatonshp between these consepts s expressed by a real number I= [-, ] [2] nterval. The value of 0 denotes no relatonshp and s mplctly assgned at the end of the second step. Hgher absolute values represent stronger relatonshps, whereas the sgn defnes the type: promotng (postve numbers) or nhbtng (negatve numbers). [8] In second step; causal relatonshps among these concepts are dentfed through ntervews. We ran the survey wth four experts. They descrbe each relatonshp by means of lngustc terms, e.g. weak, medum, strong and very strong. Then we map the lngustc terms to numercal values, e.g. weak to 0.25, medum to 0.5, strong to 0.75, and very strong to.0. Assumng no addtonal nformaton on the credblty of ndvdual experts or assumng that all experts are equally credble, the smplest method for combnng the maps s to calculate average of each relatonshp weght across all experts [8].Therefore, for k experts, the connecton matrx of the fnal FCM s establshed by the followng expresson [3]: (... ) (7) k E E E2 E k Ths basc formula can be easly modfed to accommodate credblty of dfferent experts by assgned a weght w that quantfes credblty of the th expert. These weghts take value from [0, ] range and ther sum

4 , July 6-8, 20, London, U.K. s usually normalzed, that s. The fnal, combned model s calculated usng the followng weghted average [8]: E ( we w2e2... wkek) k w For combnng the maps, we calculate the average of each relatonshp weght across all experts who have the same credblty. We use formula (8). After calculatons mportance measure of the concepts can be seen n Table II. TABLE II Rank of The Concepts Concept Centralty C 2,25 C2 2,5 C3 3,75 C4 2,88 C5 4,38 C6: 4 C7 0,25 C8 4,25 C9 6,3 C0 5,63 C 4,25 C2 7,5 C3 9,5 C4,75 C5 4,38 C6 7,75 C7,63 From Table II, the most mportant concept s found as C9 (Unversty-Industry Cooperaton level) and the second one s C0 (Number of projects whch are developed by the unversty). The sequence of concepts n mportance shows us the most mportant factors for desgnng the model. These concepts are C3( number of researchers that unversty has.), C5( sklls level of regonal labour force), C6 (the ncluson level of regonal work force on research and projects), C8 (Teachng and research potental of the regon to be addressed as an ssue), C9 (unverstyndustry cooperaton level), C0( number of projects whch are developed by the unversty), C( applcablty level of the developed projects), and C5 (the amount of the unversty's support for projects). Fuzzy Cogntve Map s drawn from these mportant concepts and t can be seen n Fg.. It s shown n the map that unversty-busness cooperaton s the most mportant factor causng effects on the others. (8) V. CONCLUSION Ths study s realzed to evaluate the mportance and relatons of crtera nfluencng the Unversty contrbutons n regonal development of ts vcnty. The case study s run n Krkkale and t s found that collaboraton wth the busness world, ncluson of the regonal workforce n research projects, teachng proportons are mportant factors for Krkkale regon. Krkkale Unversty should focus on the cooperaton wth the regonal busness n order to have some postve nfluence. Ths s a regon where the Unversty can contrbute a lot as long as they can collaborate wth the regonal busness centres. The Unversty- Busness collaboraton wll be the centre of focus for further studes. Polcy desgns are to be handled both sded: from the ndustry and from the Unversty. Ths research wll be contnued to work on scenaros for regonal development wth the collaboratve effort. REFERENCES [] Axelrod, R. (976). Structure of decson: the cogntve maps of poltcaleltes, Prnceton Unversty Press. [2] Bramwell A., Wolfe D. A., (2008) Unverstes and regonal economc development: The entrepreneural Unversty of Waterloo, Research Polcy,Vol 37,pp [3] Calışkan S., (200), Contrıbutıon of Unıversıty Student Expendıtures to Local Economy: Case Of Usak Unıversıty, Electronc Journal of Socal Scences, V.9 Is.3 (69 79). [4] Chen N.S., Knshuk, We, C.W., Chen, H.J.(2008) Mnng e-learnng Doman Concept Map from Academc Artcles, Computers & Educaton [5] C. Enrque Peláez and John B. Bowles, (996), Usng fuzzy cogntve maps as a system model for falure modes and effects analyss,informaton Scences Volume 88, Issues -4, January, Pages [6] Dmtrs k. Iakovds, member, ıeee, and Elpnk Papageorgou,(20), Intutonstc Fuzzy Cogntve Maps for Medcal Decson Makng, IEEE Transactons on Informaton Technology n Bomedcne, Vol. 5, No.. [7] Drucker J.,Goldsteın H.,(2007) Assessıng The Regıonal Economıc Development Impacts Of Unıversıtıes: A Revıew Of Current Approaches Internatıonal Regıonal Scıence Revıew. Vol.30, : [8] F. v. Vught, (2006), The Regonal Impact of Unverstes, EUA Autumn Conference Brno, 9 20 October. [9] Jason, R.C. Perschtte, K. A. (2000). Fuzzy Cogntve Mappng: Applcatons n Educaton, Internatonal Journal of Intellgent System, Vol, 5,, 25. [0] Karlsson C., Zhang W.B.,(200) The role of unverstes n regonal development Endogenous human captal and a growth n a two regon model, The Annals of Regonal Scence.Vol.35.pp [] Khan, M., Quaddus, M. (2004) Group decson support usng fuzzy cogntve maps for causal reasonng. Group Decs. Negotaton J. 3(5), [2] Kosko B. (986) Fuzzy cogntve maps. Int J Man-Mach Stud; [24.65]75. [3] Kosko, B. (988) Hdden patterns n combned and adaptve knowledge Networks. Int. J. Approxmate Reasonng 2, [4] Krsten Grovermann Qvst Isak,( 2008), Investgatng Fuzzy Cogntve Mappng as a partcpatory tool for conceptual landscape modellng, MSc Thess n Landscape Management, Faculty of Lfe Scences, Unversty of Copenhagen.

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