Strategy in practice: a quantitative approach to target setting

Transcription

1 MPRA Muich Peral RePEc Archive Strategy i practice: a quatitative apprach t target ettig Iree Fafaliu ad Paagiti Zervpul Uiverity f Piraeu, Ope Uiverity f Cypru 4. Jauary 2014 Olie at MPRA Paper N , pted 3. March :12 UTC

2 STRATEGY IN PRACTICE: A QUANTITATIVE APPROACH TO TARGET SETTING Iree Fafaliu Departmet f Ecmic, Uiverity f Piraeu, 80 Karali & Dimitriu St, Piraeu, Greece Tel. : fafaliu@uipi.gr Paagiti D. Zervpul Faculty f Ecmic ad Maagemet, Ope Uiverity f Cypru, Latia, 2252 Nicia, Cypru Tel.: paagiti.zervpul@uc.ac.cy ABSTRACT A exteded quality-drive efficiecy-aduted data evelpmet aalyi (QE-DEA) methd i develped t meaure the perfrmace f ervice uit. Perfrmace i meaured baed efficiecy ad uer atifacti. The exteded QE-DEA methd idetifie a bechmark ly uit that are qualified bth i efficiecy ad atifacti ad eure that all f the uit will be qualified i bth dimei f perfrmace whe their perfrmace becme maximal. If there are efficiet uit which fail t prvide atifactry ervice, a adutmet prcedure i applied t their utput befre the aemet f the uit perfrmace. Optimal utput target that lead every uit t maximal perfrmace are defied by the exteded QE-DEA. The preeted exprei relaxe the mai aumpti f the rigial QE-DEA methd that i the fixed weight betwee rigial ad aduted utput. The exteded exprei i applied t fifty public e-tp hp. Keywrd: Data evelpmet aalyi, Perfrmace maagemet, Efficiecy, Satifacti, Target ettig, Trade-ff 1

3 STRATEGY IN PRACTICE: A QUANTITATIVE APPROACH TO TARGET SETTING 1. INTRODUCTION I thi tudy, a exteded quality-drive efficiecy-aduted data evelpmet aalyi (QE-DEA) exprei i develped fr target ettig ad i applied t fifty public etp hp. The bective f the exteded exprei i t idetify utput that lead the uit uder evaluati t achieve ptimal perfrmace, ecurig at the ame time deirable level f uer atifacti with the ervice prvided by every uit. The peculiarity that the applied methd maage t deal with i the determiati f the ptimal balace betwee tw iverely related variable: efficiecy ad uer atifacti, which are icrprated i the aalyi. The exteded QE-DEA methd draw DEA ad algebraic aalyi. DEA i a liear prgrammig methd put frth by Chare et al. (1978). DEA meaure the efficiecy f peratial uit by frmig a prducti frtier which cit f bet-practice uit. Iput r/ad utput target are the defied fr the remaiig uit i rder t be prected t the prducti frtier. Ulike tchatic methd, DEA require a aumpti fr a prducti fucti a it i implicitly defied by the available empirical data. Sice the emial paper f Chare et al. (1978), DEA ha bee widely exteded ad applied t umeru area (Emruzead et al., 2008). DEA ha becme a mar techique fr perfrmace meauremet ad target ettig. Li (2011) ad Amirteimri ad Mhaghegh Tabar (2010) exteded DEA, facilitatig target ettig uder the ctrait f a fixed reurce fr the iput f all f the uit uder evaluati. Kx Lvell ad Patr (1997) develped a mdified DEA exprei fr perfrmace meauremet ad target ettig fr the prduced utput f the uit. The tw chlar ued a ctat iput i their prgram a the iput ifrmati wa icrprated i the utput. Lim ad Zhu (2013) mdified three DEA exprei (i.e. radial, lack-baed ad Nerlve-Lueberger) i rder t attai uer-determied target fr iput ad utput variable. The exteded QE-DEA methd idetifie ptimal utput r iput by ettig a bae target fr uer atifacti which applie t all ample uit. I additi t the bae target, the trade-ff betwee the dimei f perfrmace i a ctrait that huld al be cidered. The exteded QE-DEA methd relaxe a mar aumpti f the rigial methd regardig the flexibility f weight whe a mdificati i applied t utput f partially qualified uit (i.e. efficiet uit that d t meet the bae target fr uer atifacti). Thi tudy ufld a fllw. Secti 2 aalyze the exteded QE-DEA methd. Secti 3 preet a applicati f the exteded methd t fifty public e-tp hp, ad Secti 4 cclude. 2

4 2. FOUNDATIONS OF THE APPLIED TARGET-SETTING METHOD The applied target-ettig methd i a extei f the QE-DEA methd, put frth by Zervpul ad Palaka (2011). The cpe f the latter methd wa the perfrmace meauremet ad the peratial retructurig f rgaizatial uit while the frmer methd fcue perfrmace meauremet ad target ettig. I ther wrd, the QE- DEA algrithm i mdified i rder t accmmdate a utput-rieted aalyi. I additi, the mdified algrithm relaxe the aumpti f fixed weight betwee rigial ad aduted variable, which wa itrduced by Zervpul ad Palaka (2011). The exteded QE-DEA methd meaure perfrmace cre fr every peratial uit uder evaluati ad al target utput level which atify bth efficiecy ad uer (e.g. cutmer r citize ) atifacti attaimet. The QE-DEA methd idetifie bechmark uit which are regarded a relatively efficiet (i.e. efficiecy cre = 1.000) ad al uer reprt high level f atifacti frm their prvided ervice (i.e. atifacti cre 4, Table 1). Ay uit that atifie e f the tw criteria cat be a bechmark fr the uit that are diqualified i bth criteria. Hece, the frmer uit cat ifluece the prcedure fr determiig target utput level fr the latter uit. A velty f the QE-DEA methd i that partially qualified uit are either excluded frm the aalyi r cidered a fully diqualified. Itead, their iput r utput level are aduted apprpriately (i.e. the iput are icreaed whe a iput-rieted apprach i elected, ad the utput are decreaed i the cae f the utput rietati) t meet high uer atifacti tadard. The applied adutmet implie a trade-ff betwee efficiecy ad uer atifacti. I the ctext f target ettig (e.g. utput-rieted aalyi), maximal utput level fr a partially diqualified uit cat be attaied withut deterirati f uer atifacti (Gutaf ad Jh, 2002; Kamakura et al., 2002; Lau, 2000; Zeithaml, 2000; Ader et al., 1997) hldig the amut ad ct r reurce, ad techlgy ued by every peratial uit fixed. The QE-DEA algrithm de t require ay aumpti abut the magitude f trade-ff betwee the tw variable. Uer atifacti i meaured a five-pit Likert cale, which e repreet very diatified ad five tad fr very atified. The five-pit cale i trafrmed it a percetage cale i rder t be cmparable with the efficiecy cale which rage frm 0.0 t 1.0 (Table 1). Table 1. Trafrmati f atifacti cre Five-pit cale Equivalet percetage cale (0.2, 0.4) [0.4, 0.6) [0.6, 0.8) [0.8, 1.0] A uit i deemed qualified frm a uer perpective whe it cre at leat fur ut f five r 80%. Prir t the aalyi f the exteded QE-DEA algrithm, a lit f ymbl i prvided. 3

5 Nmeclature efficiecy cre ( 1) x i x y i r y r p S 1 1 ' ith iput f the th uit ith iput f the th referece uit rth utput f the th uit rth utput f the th referece uit -egative calar perfrmace cre uer atifacti cre f the th uit uer atifacti cre f the th referece uit average uer atifacti cre f the uit that are qualified i efficiecy ad uer atifacti ivere aduted efficiecy cre ivere efficiecy cre lwer bud A rigial uer atifacti cre uer atifacti cre lwer bud A ' aduted uer atifacti cre vi, u r -egative multiplier * v free i ig calar The firt tep fr applyig the target-ettig methd i t ru a utput-rieted variable retur t cale (VRS) DEA prgram (Baker et al. 1984). max. t. x x i 1,..., m i i y y r 1,..., t r r 1 0 (1) The efficiecy cre which are btaied frm prgram (1) are evaluated tgether with the cutmer r citize atifacti cre. If the efficiecy uit al meet high uer atifacti tadard, the there i eed fr adutmet f the prducti prce. The perfrmace cre f the uit are btaied frm prgram (2), which eure the atifacti f the tw criteria fr every uit that perate at ptimal level. 4

6 max p. t. x x i 1,..., m i i y py r 1,..., t r r 1 0 (2) ad S if S therwie If a efficiet uit that de t meet the high uer atifacti tadard i preet, the the utput huld be limited t eure a high atifacti cre fr thi uit. The ctrl ver the utput will have egative impact the efficiecy cre f the uit. The ew efficiecy cre i defied frm frmula (3) (Zervpul ad Palaka, 2011): ' [( A ) ( 1) ]( A ) ' [( A ) ( 1) ]( A ) ( A ) ( 1) 1 1 where 1. 1 ' ' 1/2 (3) Ulike the rigial QE-DEA mdel, it mdified exprei draw the multiplier VRS DEA prgram t determie the aduted utput f the partially qualified uit. T be mre precie: mi m vi xi i1 t r1 v. t. u y 1 r r * t m * ur yr v ixi v (4) r1 i1 vu, 0 ad * v i free i ig ad the mdified exprei i a fllw: 5

7 mi t uy r rc r1 t. t. u y 1 r1 r rc t m 1 ' * ur y c rc vi xic v r 1 i 1 (5) where c, y ad rc ad 1 ' yrc, yrc 2 c y rc, vu, 0 ad * v i free i ig The btaied utput ad weight are the aduted utput ( weight ( u ). ad r ad y rc ) ad their aiged The adutmet prce ecure that all f the efficiet uit will al prvide high uer atifacti level. Subequet t the adutmet prce, the perfrmace f the uit uder evaluati i meaured by applyig the fllwig prgram: max p. t. x x i 1,..., m i i y py r 1,..., t; y y y t t t ad r r r r, c rc t t t, c c 1 0 (6) where c ad t S if S therwie 6

8 3. APPLICATION OF THE TARGET-SETTING METHOD 3.1 Preetati f the data The applicability f the prped target-ettig methd will be explicit thrugh a umerical example. I the fllwig example, we ued data frm the Greek Citize Service Ceter (CSC) which are public e-tp hp appited t the prvii f admiitrative ervice t citize (uer). I particular, the ample cit f 50 CSC. There are ix iput variable (i.e. emplyee, weekly wrkig hur, PC, fax machie, priter, ad urface area) ad tw utput variable (i.e. e-ervice ad maual ervice prvided t citize). I additi, 764 citize atifacti quetiaire were cllected frm all f the ample CSC. The umber f atifacti quetiaire that were awered by citize fr every ample CSC rage frm 20 t 30. The deig f the atifacti urvey drew the SERVQUAL methdlgy develped by Paraurama et al. (1988). 3.2 Numerical example Prir t the applicati f the exteded QE-DEA algrithm, the liear prgram (1) i ued t claify the uit ad particularly t idetify the uit that are efficiet but are t qualified i atifacti (i.e. atifacti cre < 0.800). I Table 2, five ut f fifty ample uit (i.e. uit 31, 32, 41, 49, ad 50) are regarded a partially qualified a they are efficiet but they fail t deliver atifactry ervice t uer. Table 2. Uit claificati Uit Efficiecy (φ -1 ) Satifacti Claificati Uit Efficiecy (φ -1 ) Satifacti Claificati HE-HS HE-HS LE-HS HE-HS HE-HS HE-HS LE-HS HE-HS LE-HS HE-HS LE-HS HE-LS LE-HS HE-LS LE-HS LE-LS LE-HS LE-HS HE-HS HE-HS LE-LS LE-HS LE-HS HE-HS LE-LS HE-HS LE-HS LE-HS HE-HS HE-HS LE-HS HE-LS HE-HS LE-LS LE-HS LE-HS HE-HS LE-HS HE-HS LE-HS LE-HS LE-HS 7

9 LE-HS LE-HS HE-HS LE-HS HE-HS HE-LS HE-HS HE-LS HE: high efficiecy (efficiecy cre = 1.000); LE: lw efficiecy (efficiecy cre < 1.000); HS: high atifacti (atifacti cre 0.800); LS: lw atifacti (atifacti cre < 0.800) I thi ctext, the utput f the five partially qualified uit huld be aduted t eure that all f the bechmark uit f the ample bth are efficiet ad deliver atifactry ervice t uer. Drawig frmula (3), which i applied t every partially qualified uit, a atifacti cre i arbitrarily elected (e.g. ' A= 0.800). Thi cre huld be at a miimum equal t the lwer-atifacti bud (i.e , Table 1). The btaied efficiecy cre frm frmula (3) i t a relative meaure but rather a tadale. I ther wrd, the aduted efficiecy cre f a uit de t take it accut the mvemet f the remaiig uit tward the prducti frtier. Thi mvemet i prbable, due t the mdificati f the utput f the partially qualified uit. I additi, 1 i frmula (3), ad are et equal t Accrdig t Paradi et al. (2004), whe efficiecy cre lwer tha are preet, the dataet huld be reviewed fr faulty etrie. The lwer uer atifacti bud i defied by the percetage trafrmati f the uer atifacti cre which are meaured i a five-pit cale (Table 1). The ivere relatihip betwee efficiecy ad atifacti i preeted i the aduted efficiecy cre (Table 3). The aduted efficiecy cre are lwer tha the rigial efficiecy cre after the icreae f the level f atifacti. Table 3. Efficiecy adutmet Uit Origial cre Aduted cre Efficiecy Satifacti Claificati Efficiecy Satifacti Claificati (φ -1 ) (φ -1 ) HE-LS LE-HS HE-LS LE-HS HE-LS LE-HS HE-LS LE-HS HE-LS LE-HS The aduted utput f the five uit are illutrated i Table 4. The aduted utput were defied by liear prgram (4) ad (5). The aduted utput are alway lwer tha their rigial cuterpart. The decreae i the utput level f the uit that iitially did t meet the criteria fr bth efficiecy ad high atifacti i required i rder t imprve uer atifacti while iput ad techlgy are fixed. 8

10 Table 4. Aduted utput Uit Origial utput Aduted utput E-ervice Service E-ervice Service The aduted utput replace the rigial utput i the dataet, ad the liear prgram (6) i applied. The cre diplayed i clum tw ad eve f Table 5 repreet the perfrmace f the ample uit. Fr defiig perfrmace, atifacti wa icrprated i the ptimizati tgether with iput ad utput variable. Ulike the latter tw variable, uer atifacti i t fully ctrlled by the uit. Hwever, a wa tated i the previu ecti, there i a uderlyig relatihip betwee the activity f the uit, which i expreed i term f efficiecy ad uer atifacti. Clum 3-5 ad 8-10 f Table 5 diplay the target level fr atifacti ad the tw utput which are ptimal luti fr the ptimizati prblem. All f the uit which were partially qualified (i.e. uit 31, 32, 41, 49, ad 50) are regarded a bechmark after the adutmet f their utput accrdig t the exteded QE-DEA algrithm. Thee uit, hwever, eed t decreae their utput level cmpared t their rigial utput level. The gal f the preeted target-ettig methd i t defie utput target which ecure ychru ptimal perati ad high uer atifacti level. I may cae (e.g. uit 5, 6, 16), the attaimet f ptimal (target) utput i aciated with the acrifice f uer atifacti, which ever becme uacceptable. Table 5. Target-ettig reult Uit Perfrmace Target Uit Perfrmace Target Satifacti E-ervice Service Satifacti E-ervice Service (Chage) (Chage) (Chage) (Chage) % 0.0% % 0.0% % 0.0% % 0.0% % 0.0% % 0.0% % 103.1% % 0.0% % 301.4% % 0.0% % 55.6% % -11.7% % 57.3% % -11.9% % 287.2% % 282.0% % 155.7% % 594.6% % 0.0% % 0.0% % 237.5% % 282.8% % 88.7% % 0.0% % % % 0.0% % 0.0% % 64.7% % 0.0% % 0.0% 9

11 % % % -12.0% % 0.0% % 186.0% % 64.4% % 86.2% % 0.0% % 345.7% % 0.0% % 199.0% % 124.2% % 42.0% % % % 274.9% % 0.0% % 54.4% % 0.0% % -9.3% % 0.0% % -10.2% 4. CONCLUSIONS The prped target-ettig methd i a extei f the QE-DEA methd. I particular, the algrithm f the QE-DEA methd wa mdified apprpriately t relax it mar aumpti regardig the fixed weight betwee the rigial ad the aduted variable ad al t eable utput-rieted aalyi. The exteded QE-DEA methd applie twfld perfrmace meauremet, icrpratig i the aalyi bth efficiecy ad uer atifacti. The idetified bechmark uit alway are efficiet ad deliver highatifacti ervice t uer. I additi, ulike the rigial QE-DEA methd, it exteded exprei eure that all f the ample uit will attai efficiecy ad high uer atifacti whe perfrmace becme maximal. The maagerial implicati f the exteded QE-DEA methd were preeted i the applicati t fifty public e-tp hp. Hwever, the applicability f the methd i t limited t public rgaizati. REFERENCES Amirteimri, A. ad Mhaghegh Tabar, M. (2010), Reurce allcati ad target ettig i data evelpmet aalyi, Expert Sytem with Applicati 37: Ader, E.W., Frell, C. ad Rut, R.T. (1997), Cutmer atifacti, prductivity, ad prfitability: differece betwee gd ad ervice, Marketig Sciece 16 (2): Baker, R.D., Chare, A. ad Cper, W.W. (1984), Sme mdel fr etimatig techical ad cale iefficiecie i data evelpmet aalyi, Maagemet Sciece 30 (9): Chare, A., Cper, W.W. ad Rhde, E. (1978), Meaurig the efficiecy f decii makig uit, Eurpea Jural f Operatial Reearch 2 (6): Emruzead, A., Parker, B.R. ad Tavare, G. (2008), Evaluati f reearch i efficiecy ad prductivity: a urvey ad aalyi f the firt 30 year f chlarly literature i DEA, Sci-Ecmic Plaig Sciece 42:

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