Integration DEA into Six Sigma Methodology for Performance Evaluation of Yazd Science and Technology Park Technological Companies

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1 J. Basc. Appl. Sc. Res., 3(7) , , TextRoad Publcaton ISSN Journal of Basc and Appled Scentfc Research Integraton DEA nto Sx Sgma Methodology for Performance Evaluaton of Yazd Scence and Technology Park Technologcal Companes Seyyed Heydar Mrfakhradn, Fatemeh Azz 2 Assocate Professor of Industral Management, Yazd Unversty 2 MA of Industral Management, Yazd Unversty ABSTRACT Evaluaton of performance wll enable an organzaton to reduce ts dependence on government assstance due to effcent use of ts resources and s one of the man problems n organzatons. Customer s satsfacton s the most mportant goal of organzaton. In order to acheve that, organzatons should perform effectvely and effcently. Integratng the DEA method nto Sx Sgma methodology used to enhance both the usefulness of Sx Sgma and the effectveness of DEA for assessng and mprovng effcency. Addng qualty tools to data envelopment analyss, the performance evaluaton s done n a more effectve manner. In order to mprove organzaton performance, t s crucal to establsh a constant and structured performance evaluaton system through the organzaton. Due to the mportance of performance evaluaton and role of Scence and Technology Park n country mprovement, ths paper s proposed to evaluate performance of 33 frms that are n Yazd Scence and Technology Park n Iran, usng ntegraton Data Envelopment Analyss nto Sx Sgma methodology. DMAIC crcle helps researcher to take a comprehensve vew on problems. In ths paper, an nclusve approach s suggested n order to evaluate performance, combnng DMAIC crcle of sx sgma and DEA. Results of solvng the output-orented BCC model of DEA show that among 33 Technologcal frms n Yazd Scence and Technology Park 7 companes are neffcent and 6 companes are effcent. The results of the senstvty analyss show that by elmnatng nputs Total assets, R&D expendture and Captal and output number of lcenses and number of the effcency scores have a greater mpact on performance than the other crtera and performance of frms are reduced by the elmnatng these crtera. KEYWORDS: Performance Evaluaton, DEA-Sx Sgma, Yazd Scence and Technology Park. INTRODUCTION Performance s one of the fundamental concepts of management, snce most of manageral tasks are formed on the bass of that, to put dfferently, the successfulness of each organzaton s closely depended on ther actvtes. In fact, performance covers all organzatonal requrements for achevng ther defned objectves. So based on what has been explaned above, the performances of each and every organzaton must be unque []. Most scholars defne performance as the degree of achevement towards the set goal [2]. Evaluatng the performance of organzatons s a process through whch we can evaluate the organzatons based on ther goals and msson and measure ther success rate n achevng those goals or ther devaton rate from them [3]. The performance evaluaton plays a more and more mportant role n the modern enterprse management, and the method of evaluaton system on enterprse performance s always an mportant queston n the theory and practce [4]. The evaluatng systems are very mportant mechansms of control over the man polces of the organzatons and gve the managers very mportant and vtal nformaton about the level of compatblty and approprateness of the branches wth the gven programs [3]. The hgh performance s the goal that an organzaton pursues. A ratonal and scentfc method of performance evaluaton, not only can carry out effectve measurement to the past organzaton s performance, but also t helps to offer decson support to mprove and optmze the performance for the future [5]. Performance evaluaton can make the enterprse to recognze ther advantages and dsadvantages and fnd that there s unreasonable phenomenon, so as to further mprove ther management level [4]. Therefore, Performance evaluaton wll enable an organzaton to reduce ts dependence on government assstance due to effcent use of ts resources [6]. The performance evaluaton s qute subjectve, snce t reles on the ndvdual judgment of the managers who have dfferent, varous and mult-factor assessment methods of a system s performance [7]. Data envelopments analyss s one of the accepted methods for evaluatng the performance of the organzatons. Ths method s used to Correspondng Author: Fatemeh Azz, MA of Industral Management, Yazd Unversty. Tel: , Fax: Emal: azz.fateme750@gmal.com 987

2 Khradn and Azz, 203 evaluate and compare the relatve effcency of decson makng unts lke schools, hosptals, unverstes, banks, etc, whch have several smlar nputs and outcomes [8]. Accordng to role of evaluaton n organzatons and the mportance of scence and technology parks n developng technology and economc growth n countres, ths study evaluated the performance of 33 technologcal companes n Yazd Scence and Technology Park n Iran apples ntegraton Data Envelopment Analyss nto Sx Sgma methodology. -- Performance Evaluaton Performance s a broad term because t depends upon how the organzaton defnes t. For some organzatons, performance refers to proftablty, for some t means reach, for others t may be translated to customer servce and satsfacton and yet, for others t can be defned as reputaton and credblty. Any organzaton strves hard to mprove ts performance. Ths helps the organzaton to acheve ts goals and objectves. The ablty to mprove performance les n the ablty to measure t [6]. The performance evaluaton s a systematc revew process carred out to help an organzaton reach a certan goal. Makng performance evaluaton part of the management and control system helps the organzaton to effectvely manage ts resources and measure ts performance relevant to ts goals [9]. Performance evaluaton s for achevng the entre target. It bases on the quantfcaton standard made n advance or usng subjectve judgment to assess the result of daly operaton; meanwhle, performance evaluaton also possesses the functon of amendng respondng polces and unfyng the target of ndvduals and organzatons [0]. 2-- Scence and Technology parks Scence parks are sources of entrepreneurshp, talent and economc compettveness for our naton and are key elements of the nfrastructure, supportng the growth of today s global knowledge economy. They enhance the development, transfer and commercalzaton of technology []. One of the objectves n establshng the scence park n most countres s to provde an nfrastructure of techncal, logstc and admnstratve support that a young frm s necessary n the process of strugglng to gan a foothold n a compettve market [2]. Dfferent crtera are used n order to evaluate the companes performance n Yazd Scence and Technology Park. They are shown n Table. Table Effectve Crtera n performance Evaluaton of companes n the Scence and Technology Park Crtera Total assets R&D Expendtures Total number of employees Number of patents Annual Sales Sales revenue Export volume Captal Current costs Number of lcenses Reference [3, 4, 5] [3, 6, 2, 5, 7, 8, 9, 20, 2] [3, 6, 7, 20, 22] [6, 3,, 7, 8, 9, 2, 23] [6, 5, 9, 2] [3, 24] [3, 5, 20, 22] [, 25] [26, 27] [27] Nosratabad, et al., (20) proposed a fuzzy expert system to evaluate the scence and technology parks. Present a system whch s able to compare ths hgh number of scence parks, wth many crtera, s one of the fndngs of ths paper []. Lu, et al., (200) utlzes an emprcal study to provde valuable manageral nsghts when measurng the mpact of R&D actvtes and performance representaton n the Tawanese technologcal ndustry. Ths study develops a two-stage sequental technque for ncorporatng envronmental effects nto a method for evaluatng R&D performance based data envelopment analyss (DEA) and ordnary least squares (OLS) regresson wth panel data to obtan an effcency measurement. The study data comprsed 94 technologcal frms analyzed from a multsource database. The nputs and outputs n DEA s Total Assets, R&D expendture, total number of employers, number of R&D, number of patents, export volume, return of nvestment and sales revenue [3]. Bglard, et al., (2006) have provded a sound and theory-grounded methodologcal framework to scence parks performance measurement and some practcal suggestons useful for the desgn and the mplementaton of a Scence Park s (SPs) performance evaluaton. Based on the analyss of four Italan case studes, the emprcal fndngs partly lend support to prevous research output and partly add new elements of dscusson to the debate. More specfcally, major results are that the evaluaton crtera should be algned wth scence park (a) actual 988

3 J. Basc. Appl. Sc. Res., 3(7) , 203 msson, (b) major stakeholders commtment, (c) economc regonal condtons, (d) legal forms, (e) nature of the scentfc competence base avalable wthn research centers and (f) SP s lfe-cycle stage [23]. Sun & Ln, (2009) have analyzed effcency and productvty growth of sx hgh-tech ndustres n Hsnchu Scence Park n Tawan for perod In Ths paper DEA was appled to analyze the relatve performance. In order to fnd out the long-term effectveness n productvty, the wndow analyss s adapted to seek the most recommended set of ndustres for Hsnchu Scence Tawan by measurng the performance changes over tme. Inputs and outputs are consdered n ths study nclude R&D expendtures, number of employees, workng captal, number of patents and annual sales [6]. Jan, et al., (20) presents a data envelopment analyss (DEA) based approach for performance measurement and target settng of manufacturng systems. The approach s appled to two dfferent manufacturng envronments. The performance peer groups dentfed DEA utlzed to set performance targets and to gude performance mprovement efforts. The DEA scores are checked aganst past process modfcatons that led to dentfed performance changes [28]. Kakojoor, et al., (20) evaluate the performance of each branch of the Azad Islamc Unversty (IAU) n Mazandaran provnce, determnng the role model and reference branches to defne the neffcent branches by applyng envelopment analyss and rankng the effcent branches of AIU n Mazandaran provnce by applyng Anderson Peterson method [3]. 2- MATERIAL AND METHODS 2-- Data Envelopment Analyss DEA s a non-parametrc technque used to measure the effcency of DMUs. It consders that each DMU s engaged n a transformaton process, where by usng some nputs (resources) t s tryng to produce some outputs (goods or servces). DEA uses all the data avalable to construct a best practce emprcal fronter, to whch each neffcent DMU s compared [29]. The most frequently used DEA models are CCR and BCC wth constant and varable returns to scale, respectvely. Accordng to the objectve of a model, the DEA models can be categorzed nto two types: nputorented model and output-orented model. The nput-orented model ntends to mnmze nputs wth gven outputs, whereas the output-orented model does to maxmze outputs wth gven nputs [30]. The lnear program of the basc DEA model s as follows, whch can be solved relatvely easly and a complete DEA solves n lnear programs, one for each DMU. max s r m s. t. x s r rj 0 m u y x 0 j, 2,..., n r rj j r 0, 2,..., m u y ur 0 r, 2,..., s () Model (), often referred to as the CCR model, assumes that the producton functon exhbts constant returns-toscale. The BCC model adds an addtonal constant varable, W, n order to permt varable returns-to-scale: max s r m s. t. x Here, s r rj 0 m u y x W 0 j, 2,..., n r rj j r 0, 2,..., m u 0 r, 2,..., s (2) r u y W j x s the amount of th nput, y s the amount of r th output, v s the weght gven to the th nput, rj u r s the weght gven to the r th output, and k s the DMU beng measured [30]. It should be noted that the results of the CCR nput-mnmzed or output-maxmzed formulatons are the same, whch s not the case n the BCC model. Thus, n the output-orented BCC model, the formulaton maxmzes the outputs gven the nputs and vce versa [3]. 989

4 Khradn and Azz, Integraton of DEA nto Sx Sgma One of the advantages of the Sx Sgma methodology over other process mprovement programs s that the use of data analyss tools n Sx Sgma projects enables practtoners to accurately dentfy process hnderng problems and demonstrate the mprovement usng objectve data. Most of the exstng tools n Sx Sgma methodology are qualty management tools and statstcal methods, whch s qute natural because Sx Sgma was orgnated from statstcal concepts for qualty mprovement. Typcal qualty management tools are process mappng, cause-andeffect dagrams, Pareto charts, qualty functon deployment, and falure mode and effect analyss. Examples of the statstcal methods nclude statstcal process control, desgn of experments, analyss of varance, hypothess testng, regresson analyss and so forth. These qualty management and statstcal tools are effectve n fndng and elmnatng causes of defects n busness processes by focusng on the nputs, outputs, and/or the relatonshp between nputs and outputs. However, these methods for elmnatng defects are usually nsuffcent n handlng other types of process-mprovement problems, such as workforce schedulng, resource plannng and operatons management. Among many operatons research technques, the DEA method s well suted to dentfy the effcent and neffcent ndvduals that can further facltate resource plannng or performance assessment. The ntegraton of DEA nto the Sx Sgma framework wll result n a synergstc effect that outperforms what can be acheved by the ndvdual applcaton of DEA. To our best knowledge, DEA has not been ncluded nto the Sx Sgma toolbox that many Sx Sgma practtoners are famlar wth. The relatonshp of DEA wth other tools needs to be specfed n the DMAIC phases [32] METHODOLOGY In ths study 33 Technologcal companes were selected as DMUs of Data Envelopment Analyss n Yazd provnce Scence and Technology Park. To analyze data, DEA-Solver software has been used. The mplementaton procedure of DEA n each phase of DMAIC s llustrated n table2. Sx Sgma tools that can facltate the mplementaton of DEA are lsted n last column. Table 2 DEA n the DMAIC framework DMAIC phases Procedure for mplementng DEA Other tools facltatng DEA Defne Identfy the decson-makng unts (DMUs) Fuzzy Delph Defne nputs and outputs nvolved n assessng DMUs effcency Measure Develop data collecton plan Data collecton plan Collect nputs and outputs data Verfy data accuracy and relablty Analyss Apply approprate DEA models to obtan effcency scores for DMUs Summary statstcs Analyze relatvely effcent DMUs Analyze relatvely neffcent DMUs Improve Provde reference sets for neffcent unts Set performance targets for all unts Plannng to mprove the performance of neffcent frms Control Provde methods to ensure proper functonng n the future Provdng methods for Performance Evaluaton of companes Box Plot 4- RESULTS The mplementaton procedure of DEA n DMAIC crcle has been proposed n followng sectons. -4- Defne Phase In the Defne phase, the multple nputs and outputs of DMUs are dentfed. In ths study, The DMUs are Technologcal companes n Yazd Scence and Technology Park. By revewng researches that were conducted n frm s performance evaluaton n Scence and Technology Park, Effectve crtera were dentfed. In ths research Fuzzy Delph was used n defne phase to determne the most mportant crtera n evaluatng the performance of Technologcal frms n Yazd Scence and Technology Park and dentfyng nputs and outputs n DEA. In Delph Method the experts are provded wth an ntal questonnare and are requested to gve ther opnon separately and anonymously about the varables n queston. The ntal questonnares are returned to a coordnator, who analyses the responses. Based on the statstcal fndngs, a second questonnare s nterspersed to the partcpants, who are asked f they wsh to revse ther earler estmates. Ths process s followed agan and agan untl the outcome converges to a reasonable soluton from decson makers, vew pont a pre-determned number of teratons s completed or stablty n the results s obtaned [33]. Experts expressed ther agreement about effectve crtera n performance evaluaton of technologcal companes n Yazd Scence and Technology Park wth lngustc varable, such as low, medum and hgh. By 990

5 J. Basc. Appl. Sc. Res., 3(7) , 203 defnng the range lngustc varables, the experts wll answer questons wth the same mnd. Lngustc varables are descrbed as trapezodal fuzzy numbers. Low (0,0,2,4), medum (3,4,6,7) and hgh (6,8,0,0) [34]. In ths study After Experts were selected, the Delph was repeated four rounds. In the frst round, a lst of effectve Crtera n performance evaluaton of Scence and Technology Park was gven to experts. Also, they were asked to express the crtera that were effectve n performance evaluaton of frms but not n lst based on ther opnon or ther experence. Fnally, two crtera were added whch nclude total currency and number of. As regards the sgnfcance of vew n property value, the answers of the ntal round were collected and statstcally analyzed accordng to Eq. (2) A a, a, a, a,,2,3,..., n m m m m m A a, a, a, a a, a, a, a 2 n n n n At ths stage, the experts were asked to amount the mportance of crtera n performance evaluaton Technologcal companes of Scence and Technology Park n Yazd Provnce of Iran, as low, medum, and large. Then, for each expert the devaton between Average and her/hs ntal estmate (A) was computed followng Eq. (3) m, m2 2, m3 3, m4 4 a a, a2 a2, a3 a3, a4 a4 3 e a a a a a a a a n n n n The dstance between two fuzzy numbers was calculated by measurng the devaton between the average fuzzy evaluaton data and the experts evaluaton data (Eq. 4). In ths study, dfference that was calculated s less than the threshold value of 0.2 set by ths research and s thus acceptable for the group consensus [35]. S Am 2 Am am2 am22 am23 am24 am am 2 am 3 am 4 4 Fnally crtera selected that showed n table 3., 4 Inputs Outputs Table 3 Inputs and outputs for performance evaluaton of Technologcal companes Total assets, R&D Expendtures, Total number of employees, Captal, current costs Number of patents, Export volume, Sales revenue, number of lcenses, total currency, number of 2-4- Measure Phase The Measure phase quantfes and benchmarks the process usng actual collected data. The data collecton process nvolves developng a collecton plan, collectng data, and verfyng data accuracy and relablty that are mplemented n the Measure phase. In ths phase data collected n consderng the nput and output of the defne phase and exstng documents n each technologcal company n Yazd Scence and Technology Park. Table 4 shows nformaton about the nputs and outputs of each Technologcal company n Yazd Scence and Technology Park. Table 4 Values of nputs and outputs of Technologcal frms of Yazd Scence and Technology Park DMU Total assets (Mllon) R&D Expendtures (Mllon) Total number of employees current costs (Mllon) Captal (Mllon) Number of patents Export volume (Mllon) total currency (Mllon) number of number of lcenses Sales revenue (Mllon)

6 Khradn and Azz, Analyss Phase Data collected wll be analyzed n the Analyze phase. For a DEA, the formulaton and soluton of the DEA model are prmary outcomes of ths phase. A set of effcent DMUs and a set of neffcent DMUs are concurrently dentfed n the DEA s soluton. An approprate DEA model should be selected dependng on the nature of applcaton. By mplementng the BCC model of DEA, the effcency of each 33 companes (DMUs) are determned, based on the Varety returns-to-scale assumpton and they ranked consderng ther effcency. The results are shown n table 5. Table5 Results of BCC model DMU Effcency Score Rankng DMU Effcency Score Rankng DMU Effcency Score Rankng The results show that among the 33 Technologcal companes n Yazd Scence and Technology Park, 6 companes are effcent and 7 are neffcent. Summary statstcs were used n the Analyze phase. The Mean, mnmum, maxmum and the standard devaton for nputs, outputs and DEA scores lsted n Table 6. Table 6 Summary Statstcs Mean STD.Dev Mn Max Input Total assets R&D Expendture Total number of employees Captal Current Cost Output Number of patents Export volume Sales revenue total currency number of lcenses number of Effcency Score Improve The Improve phase determnes the best soluton usng optmzaton approaches. As a lnear programmng technque for optmzaton, DEA can naturally be ncorporated nto the Improve phase be planned for mprovng the performance of neffcent frms. Specfcally, the results from the DEA can provde reference sets for neffcent DMUs and set performance targets for all DMUs. Consderng the coeffcents of the reference sets wth combnaton effcent DMUs create a vrtual DMU. By comparng the nput and output of the vrtual DMU neffcent unts, optmal nputs and outputs are dentfed to neffcent unts acheve effcency.table 7 presents actual and target values and reference set for DMUs, as well as the DEA score. 992

7 J. Basc. Appl. Sc. Res., 3(7) , 203 Table7 Compare the actual and target values to mprove the performance of neffcency Technologcal located n Yazd Scence and Technology Park DMU Reference set Inputs Outputs I I2 I3 I4 I5 O O2 O3 O4 O5 O6 2 2,2,5, Target Actual ,8,26 Target Actual ,2,2,26,33 Target Actual ,,2,29,33 Target Actual ,2,27,29,30 Target Actual ,3,33 Target Actual , Target Actual ,26,2,0, Target Actual ,29,2, Target Actual ,2,27,33 Target Actual ,,26 Target Actual ,,2,27,30,33 Target Actual ,29,30 Target Actual ,30,27,2, Target Actual ,29 Target Actual ,4,,2,30 Target Actual ,26,29 Target Actual In table 7 for example companes,5,2 and 2 are reference set for company 2. The coeffcent of reference set s calculated by BCC output of DEA. It was clear the coeffcent of reference set for Effcent DMUs s one. Senstvty analyss of nputs and outputs Senstvty analyss of nputs and outputs were used to determne the effectve nputs and outputs of Technologcal companes. Thus, the output-orented BCC model s run agan, and each tme t s removed from the nput or output. Table 8 shows the results of senstvty analyss. 993

8 Khradn and Azz, 203 Table8 the results of senstvty analyss DMU Total assets R&D Expendture Total number of employees Captal Current Cost Number of patents Export volume Sales revenue total currency number of lcenses number of DMU Total assets R&D Expendture Total number of employees Captal Current Cost Number of patents Export volume Sales revenue total currency number of lcenses number of DMU Total assets R&D Expendture Total number of employees Captal Current Cost Number of patents Export volume Sales revenue total currency number of lcenses number of The results of the senstvty analyss relevant to the most mportant and least mportant nputs and outputs show that by elmnatng nputs Total assets, R&D expendture and Captal and output number of lcenses and number of the effcency scores compromse wth other nputs and outputs has the hghest rate of declne. Ths shows the mportance of these crtera n performance evaluatng of Technologcal companes. But by elmnatng nputs Total number of employees and Current Cost and outputs Export volume, the effcency scores were ncreased compromse wth other nputs and outputs. Ths shows the less mportance of these crtera n performance evaluaton of companes. 994

9 J. Basc. Appl. Sc. Res., 3(7) , Control Phase In the control phase, accordng to senstvty analyss of data envelopment analyss, the crtera nclude Total assets, R&D expendture and Captal and output number of lcenses and number of are mportant crtera. Box Plots were drawn, to evaluate status companes n these crtera. The results show that n Total assets and R&D expendture more companes are located n remote areas. About total assets crtera, the medan s the mddle, so the assumpton of symmetry s a powerful data dstrbuton. Fgure show the box plot of total assets Fg.. Box Plot of total assets 5- DISCUSSION AND CONCLUSION Performance evaluaton s the process of determnng effcency and productvty of the methods appled to acheve set objectves. Performance evaluaton system can also be expressed as all ndcators that measure productvty and effcency actvtes n a company [36]. Ths paper has presented the mplementaton of DEA nto each phase of the DMAIC process. 33 technologcal companes n Yazd Scence and Technology Park n Iran are selected to mplement proposed methodology. Most research about performance evaluaton used the basc model of data envelopment analyss and other technques used n ths feld, such as balanced scorecard [, 23, 27]. Also, research n the feld of scence and technology parks evaluated parks and ncubators, does not evaluated the frms n Scence and Technology parks. In comparson wth other exstng technques for performance evaluaton of organzatons, data envelopment analyss s the most approprate [37]. Integratng the DEA method nto Sx Sgma methodology used to enhance both the usefulness of Sx Sgma and the effectveness of DEA for assessng and mprovng effcency. Addng qualty tools to data envelopment analyss, the performance evaluaton s done n a more effectve manner. In ths research, wth survey of lterature revew and opnon from experts, the effectve crtera n performance evaluaton of Technologcal companes n Yazd Scence and Technology Park were dentfed and for performance evaluaton of them ntegratng DEA nto the sx sgma methodology was used. Results of solvng the output-orented BCC model of DEA show that among 33 Technologcal frms n Yazd Scence and Technology Park 7 companes are neffcent and 6 companes are effcent. The results of the senstvty analyss show that by elmnatng nputs Total assets, R&D expendture and Captal and output number of lcenses and number of the effcency scores have a greater mpact on performance than the other crtera and performance of frms are reduced by the elmnatng these crtera. So, Technologcal companes n Yazd Scence and Technology Park should be gven more attenton to these crtera. In future research recommend evaluaton of performance of the Scence and Technology Parks whch have used fuzzy approach. Also suggested ntegratng DEA was appled nto sx sgma methodology to evaluate sx sgma projects n the feld of performance evaluaton. REFERENCES 995

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