ඒߛઔߒႃע
รնԼᙀรԲཚʳ 2004 ڣ 6 ִʳ 119-145
ၥਟѓϷݙӵଽϛᏰ!
ఀىᅿࡾفಛϞᔖҢ
Ҕ އ ྀ ဢ ! ࡌ
ᇷறץ։࣫ΰData Envelopment Analysis, DEAαኙ్խᖂඒߛ൳ਐᑑ ߓอऱᚨشΔڇ࣍ܓشኔᎾױᨠኘࠩऱދԵขנᇷறΔڇլᏁቃسขࠤᑇ ऱݮڤՀΔޣ࠷ٺެۯΰDecision Making Unit, DMUαسขயऱֺለଖΖ ڼլႛױش࣍ԫދԵ֗ԫขנऱႚอֺ։࣫Δٍױش࣍ڍႈދԵፖڍႈข נऱᓤᠧणउΖءઔߒאඒߛຝઔߒࡡᄎ 87 ᖂڣ৫్խᖂउᓳᇷறၞ۩
ֆمխඒߛ൳ኔᢞ։࣫Δ࿇ڕՀΚ
1.٤ഏֆمխᖂீऱᖞ᧯ய։࣫ሒࠩઌኙڶயऱᖂீ٥ 34 ࢬΔ٤ ຝᖂீऱ 16.19%Ζ
2.٤ഏֆمխᖂீࠠڶݾயऱᖂீ٥ 66 ࢬΔ٤ຝᖂீऱ 31.43%Ζ 3.٤ഏֆمխᖂீࠠڶᑓயऱᖂீ٥ 37 ࢬΔ٤ຝᖂீऱ 17.62%Ζ 4.ەႃٽ։࣫ঞಾኙڶயᖂீၞԫޡᙃࠡயඈټΔطඈټࠐΔֆ مխᖂீཏሙֺֆمᖂீ।ᚌฆΖ
5.ྤயऱֆمխڇᖞ᧯யፖݾயֱ૿ႊޏऱႈؾΔڇขנ
ႈ֒ᖂא֗խຜᔗᖂΙދԵႈΔאᇷء॰ᚌ٣Ζ
ᜢᗖຒǺၗх๎ϩǵᅱࡰسǵਏǵ،ൂՏ
ֆࡹၲǴԢεᏢ௲ػࡹᆶሦᏤࣴز܌ୋ௲
ႝηແҹࣁǺ[email protected]
ዺВයǺ2004 ԃ 1 Д 15 ВǹঅुВයǺ2004 ԃ 5 Д 7 Вǹ௦ҔВයǺ2004 ԃ 5 Д 21 В
Bulletin of Educational Research June, 2004, Vol. 50 No. 2 pp. 119-145
The Application of Data Envelopment Analysis to Senior High and Vocational School
Monitoring Indicator Systems
Cheng-Ta Wu A b s t r a c t
In order to know the comparative value of the output efficiency of each deci- sion-making unit without calculating output function, the Data Envelopment Analysis (DEA) of senior high and vocational school monitoring indicator systems must use the observable input and output data. Such an analysis not only serves the purposes of the traditional analysis of single input and output; it also fits the complex conditions of multiple input and output. Using data from the Ministry of Education for the 1998 academic year, this study conducted an empirical analysis of educational monitoring systems in public senior high and vocational schools in Taiwan. The main findings are as follows: 1. About 34 schools achieved a relative degree efficiency; these comprised 16.19% of all public senior high and vocational schools; 2. About 66 schools (com- prising 31.43% of all public senior high and vocational schools) achieved technical efficiency; 3. About 37 schools (17.62%) achieved scale efficiency; 4. In general, pub- lic senior high schools were more efficient than public vocational schools; 5. If ineffi- cient public senior high and vocational schools wanted to achieve greater over-all effi- ciency, the output items needing to be first improved were promotion rate (65.88%) and dropout rate (30.74%).
Keywords: Data Envelopment Analysis, monitoring indicator systems, efficiency, decision-making unit
Cheng-Ta Wu, Associate Professor, Graduate Institute of Educational Policy and Lead- ership, Tamkang University
E-mail: [email protected]
Manuscript received: Jan. 15, 2004; Modified: May 7, 2004; Accepted: May 21, 2004
ಥă݈! ֏
ඒߛਙ։࣫ऱ່ึؾऱਢ౨ಾኙඒߛਙᤜᠲ༼נݔᔞऱඒߛਙ৬ᤜ ΰeducational policy recommendationsαΔඒߛਙ৬ᤜԫᆖආشঁݮګඒߛਙ۩
೯Ιۖڶඒߛਙ۩೯۞ྥ༉ᄎขسඒߛਙ࣠Ζױਢኙ࣍ඒߛਙ։࣫ृۖ
ߢΔૹऱਢڇ࣍ڕ۶वඒߛਙ࣠ऱᐙΔڂڼ൳ΰmonitoringαඒߛਙ
ኔਜא৵ࢬ࿇سऱ࣠ΔࠀᨠኘኔᎾ࣠ፖቃཚ࣠հၴऱ၏Δঁਢඒߛ ਙ࣠൳ऱഗءრොΖ൳ڇඒߛਙေ۷࿓ݧխԯਢԫႈૹऱᛩᆏΔࠡ
ಾኙඒߛਙᜎயΰeducational policy performanceαၞ۩ߓอ֏ऱေ۷Δאਐנ ඒߛਙሒګؾᑑऱᒤࡉ࿓৫Ζط࣍ඒߛߓอᓤᠧۖڍ᧢Δڶૻऱଡܑਐᑑࢬ
༼ࠎऱᇷಛլ֊ኔᎾΖᖕ Johnsonΰ1999αਐנΔٚ۶ᖲዌิ៣ࢨଡԳڇ
ԫႈެছ݁ᏁܓشᇷಛΔᇷಛڇਙࠫࡳऱመ࿓խਢլױࢨऱΖڂڼΔ࿇
୶נਐᑑߓอᨃԫऱਐᑑၴขسᜤٽऱ܂شΔঁਢඒߛ൳ߓอࢬլױࢨऱΖ ء֮ᚵ٣൶ಘ൳ߓอऱઌᣂᄗ࢚Δ٦ܓشᇷறץ։࣫ᛵᇞඒߛ൳ߓอ ऱᇷಛΔא܂ඒߛ۩ਙᅝݝհەΖ
෮ăႾଠᇾր۞࠹ᙯໄه
Husénፖ Tuijnmanΰ1994αᎁ൳ഏ୮ඒߛߓอऱפ౨ڶնΚ(1)ᜎயຂٚ
ΰaccountabilityαΚຘመඒߛ൳ᄗउܫᛵᇞࠡᚌאየߩֆ٥ಘᓵᏁޣΔڂۖ
ᖿᚐඒߛؾᑑሒګፖᜎயຂٚΙ(2)ඔ፞ΰenlightenmentαΚআၞᛵᇞඒߛऱפ౨Δ व൜ٺഏඒߛߓอऱઌۿፖฆΙ(3)ެΚ៶طඒߛߓอ؈ऱᛵᇞΔআࠌඒ ߛ۩ਙፖጥऱޏΔ壆ڕᇷᄭऱլᅝ։ΕԳऱྤய౨ტΕᖂس।լࠋΔ
݁ױᆖط൳ਐᑑᛵᇞޏֱூኔਜছ৵ऱ᧢֏Δאܓ࣍۩ਙެΙ(4)ᖂ॰ऱޏ
ၞΚԱאڍցᨠរྒྷၦඒߛߓอ࣠Δۖس࿇୶ऱᓵፖֱऄڶܓ࣍ඒߛਙ
ᖂ॰ऱ࿇୶Ι(5)۩ਙ൳ࠫΚᇠ൳ߓอᄎၞۖᐙඒߛߓอऱዌΕრᆠፖ
࣠Δڶܗ࣍ඒߛਙऱေ۷Ζࠡඒߛਙ൳ऱᣊীΔᖕ Willmsΰ1992αऱ
ऄױא։ԿᣊΚ
ʙă؛ؒၿૡĞcompliance monitoringğ!
൳ߓอ։࣫ᖂீඒߛऱᙁԵΔܑਢඒஃࡉತਙऱᇷᄭΖຍጟߓอٞቹᒔ
ࡳਬጟඒߛࠎऱᑑᄷ౨የߩΖԫଡࢭᘭࢤऱ൳ߓอױ౨ץܶྒྷၦఄ్ऱؓ
݁ᑓΕᖂسፖඒஃऱֺࠏΕڇඒޗՂऱ֭נΕቹ塢ऱᑓΕඒஃऱᇷΕ᎖
ܗԳऱᑇၦΕࢨਢᖂس൷࠹ܑࠩඒߛऱֺࠏΖ
ʠăඨᔞؒၿૡĞdiagnostic monitoringğ!
်ឰࢤ൳ߓอൎᓳᙁԵᙁנᑓڤխᙁנֱ૿ऱംᠲΔܑਢᖂऱ
࣠Ζהଚऱؾऱਢဪࡳԫࠄࡳऱᓰ࿓ਢܡՕڍᑇऱᖂسࢬᑵ൜ΖٵᑌऱֱڤΔ ඒஃଚܓشඒփऱྒྷ᧭װބנୌࠄᖂسᏁޓၞԫޡऱඒᖄፖᛶإΔ်ឰऱ
൳ߓอ༈ޣބנऱݾ౨ࡉᄗ࢚ΔڇਬᖂீᇙຍᏁޓՕऱૹီΖ်ឰ൳ߓ อऱ࣠ྒྷၦז।ऱਢψயᑑᅃྒྷ᧭ωΰcriterion-referenced testsαΔࠀലྡྷរႃ
խڇᖂ࣠ፖᓰ࿓փ୲ጹയٽऱૻࡳᒤՂΖᇠ൳ߓอለ֟ൎᓳᖂீඒߛ ऱᙁԵΔڂהଚऱشრਢބנڇᖂݾ౨Ղऱ९ፖរΔྤᣂᖂس ऱᔆΖڂڼΔኙ࣍ڇᖂீࢨᖂհၴ܂ֺለΔਢڶشऱΖ
ʭăᑼझؒၿૡĞperformance monitoringğ!
รԿጟ൳ߓอݮኪጠᜎயࢤ൳ΔᇠߓอץܶԱᖂீඒߛऱᙁԵፖᙁנ հၴऱေၦΖഗءՂΔ࣠ऱေၦਢᑑᄷ֏ګ༉ऱྒྷ᧭Δࠀڇᜎயऱ࣠ՂΔ
൳ߓอጐױ౨ऱڇᖂீፖᖂհၴ܂ֺለΖڇਬጟൣउՂΔຍࠄֺለץܶԱኙ
࣍ᖂீඒߛᙁԵऱᓳᖞΖຍࠄߓอࣔᒔऱؾऱਢࠌᖂீᆖطؑեቃױֆၲچ
ေᓵΖຍ࢚ਢᖂீհၴࢨᖂհၴऱֺለല֧ದᤁञא֗ࠨᖿඒஃ༼ࠎޓړऱ ඒߛΖ
ඒߛਙ൳ֱऄڶڍֱڤΔ༉อૠऱᨠរΔڶאՀԿጟֱऄΰEngert, 1995αΚ1.ګءѧய墿։࣫ΰcost-benefit analysisαΔএشࠐ܂ਙֱூհګءፖ ᆖᛎய墿ֺለऱေ۷Δࠡؾऱڇေ۷ދᇷૠऱᆖᛎܓ墿Ζࠡயऱྒྷၦመ࿓ࠌ ش၀ݾΰdiscounting techniquesαΔֺለګءፖܓ墿ऱ၀ຄኞଖΖګءய
墿։࣫ೈԱױࠌެۯૠጩٺᙇᖗֱூऱଖΔٍױຘመૠጩٺᙇᖗֱூऱ ګءய墿ֺΔࠐֺለࠡઌኙயΖګءய墿։࣫բᐖऑሎشڇֆ٥ຝ॰ऱತ ਙቃጩߓอΔڕሿഗቃጩΔ܀ڕ࣠ᚨش࣍ඒߛՂΔսژڇڍംᠲΔڂګء
ய墿։࣫ழΔࠡދԵፖขנઃႊ᠏ངאຄኞݮڤࢨؑᏝ।قΔ܀ڇඒߛऱመ
࿓խΔࠡขנፖ࣠ਢৰᣄ᠏ངګؑᏝۖףאૠጩΖ2.ګءயش։࣫
ΰcost-utility analysisαΔڼጟ։ֱ࣫ऄࠡഗءਢࢬڶଡ᧯ኙਬԫࡳขנऱየ რ৫ઃױၦ֏Δۖലެृଡ᧯ࡳࢤΰqualitativeαፖᨠΰsubjectiveαऱڂైΔ
Եࠡה։࣫ऱݮڤհխ։࣫Ζ3.ګء࣠ΰcost-outcomeαፖګءய౨։
࣫ΰcost-effectiveness analysisαΔڇඒߛދԵױኞଖ֏Δ܀ඒߛขנࢨ࣠ྤऄኞ ଖ֏հൣउழΔঞᔞش࣍ګءய౨։࣫Δګءய౨ΰcost effectivenessαਢਐޢ ขנऱۯګءΔࠡױ܂ઌኙயऱ।قΔڇދԵፖขנհၴऱᣂএլࣔᒔΔ ࢨਢေ۷ृኙ֟ᑇऱขנႈڶᘋᔊழΔګءய౨ऱྒྷၦਢઌᅝڶشऱΖ܀ਢຍ ጟԫኞଖ֏ऱދԵኙԫขנᣂএऱྒྷၦΔڇඒߛऱᚨشՂڶࠡࣔ᧩ऱૻࠫΔ ڂඒߛऱٺႈขנΔਢطڍጟլٵऱދԵࢬขسऱΖ
Postlethwaiteΰ1994αਐנ൳ױא։ګԿᣊΚᖂீऱᙁԵΕᖂீऱመ࿓֗ᖂ
ீऱඒߛ࣠ΖՀ। 1 ࢬ।قऱ༓ଡਐᑑࠏਢඒߛᅝݝᆖൄᣂ֨ऱΔլਢޢଡ ഏ୮ऱඒߛᅝݝຟᄎᖕՀ।ၞ۩൳ඒߛߓอΔຏൄᄎࠉᅃኔᎾՂऱᏁᙇᖗ ࢬ൳ऱਐᑑΖངߢհΔլٵऱඒߛᅝݝኙ࣍൳ߓอᄎڶլٵऱەၦΔᇠ।
ࢬຫ٨ऱਐᑑլਢኙऱΔᄎڂඒߛ᧯ࠫऱګᑵ৫ΕತਙणउΕՕฒኙ࣍ඒߛ ګ࣠ऱየრ৫א֗ඒߛਙެृኙඒߛംᠲऱઔߒፖᨠኘۖڶࢬฆΖ
؆ΔOddenΰ1990αਐנഏ୮֗ڠऱඒߛਐᑑߓอᚨᇠො።אՀᒤᡱΚ1.
ඒߛᙁԵΔץਔΚᆖ၄Εढᇷ֗ࠡהᇷᄭΕඒஃᔆΕᖂسહནᇷறΙ2.ඒߛመ
࿓ΔץਔΚᖂீᔆΕᓰ࿓ΕඒᖂᔆΕඒߛᔆΙ3.ඒߛᙁנΔץਔΚᖂسګ
༉ΕፖΕኪ৫ፖࣄΖFitz-Gibbonΰ1996αՈᎁૠԫଡ൳ᜎயऱਐᑑ ߓอᏁץਔᙁԵΕመ࿓ፖᙁנΔࠀᙃܑᙁנΰoutputsαፖ࣠ΰoutcomesαऱ
ฆڇ࣍ᙁנຏൄش࣍ऴ൷ܘԺګ࣠ΰᤝڕΔီەᇢګᜎਬႈᓰ࿓ऱᙁנαΔۖ
࣠ຏൄਐ९ழၴऱګயΰᤝڕΔ࠹ඒߛ৵ऱ༉ᄐणउαΖឈྥ९ழཚऱګயለૹ
Δ܀ਢࠡ࠹ࠩऱڂైመڍլ࣐ᢞࣔ۶ृඒߛऱᐙڂైΔڂڼለᣄګ൳
ਐᑑऱᙇᖗኙွΖጵՂࢬ૪Δߩߠ൳ਐᑑ᧯ߓՕ᧯Ղፖ Johnstoneΰ1981αΙOakes ΰ1986αΙShavelsonΕMcDomnnellΕOakes ፖ Careyΰ1987αΙWindhamΕChapman ࡉ Walbergΰ1990αԳࢬ৬ዌऱਐᑑߓอᨠរઌฤΔઃආ۩ᙁԵΕመ࿓Εᙁנߓ อᑓڤΖ
ے1 Չ໋Ӌᘰ٧ڟՉݾᆿ˱࣠
ݾᆿᘸܮ ݾᆿΰս
ᙁԵ
ᖂீ৬ᗰढऱणኪ ඒஃമॐऱणኪ ᖂீऱᙄֆໂ ᖂீऱ༼ࠎ ᖂீऱኔ᧭
ᖂسऱ᜔Գᑇ
ᖂسऱڣΕڣ్ࡉࢤܑ
ٽ٤ඒஃऱᑇၦ ஃسֺ ఄ్ᑓ
መ࿓
ඒஃՠ܂๛ၦΰඒஃޢၜᓰழᑇα ඒஃࢬᨠኘࠩᐙඒᖂऱڂై
ᓰ࿓ڜඈΰ٤ഏࢤऱΕࢤऱΕᇠᖂீࡳऱα ᖂᖲᄎ
ޢԫڣ్ΔޢԫઝؾऱՂᓰழᑇ ޢԫڣ్ΔޢԫઝؾऱՂᓰᖂسԳᑇ ᅮᖂޢᖂཚࠩீီᖄڻᑇ
࣠
ઝؾऱᖂګ࣠
ٵڣᐋऱฅᄐԳᑇۍ։ֺ
ᖂس࠷ྒྷ᧭ຏመऱۍ։ֺ
ᖂسऱཚඨࡉኪ৫ ᖂسᡛᓰൣݮ ᑊԺംᠲ ᢐढᛒشംᠲ ጥඒംᠲ
ၗٰྍǺTuijnman, A. C., & Postlethwaite, T. N. (1994). Monitoring the standards of education (p.25). New York: Pergrmon.
ણăྤफ़Βඛ̶ژሀёᄃିֈᅳા۞၁ᙋᑕϡ
ᇷறץ։࣫ਢط CharnesΕCooper ፖ Rhodes ࣍ 1978 ڣࢬ༼נΔࠡᨠ࢚ᄭ
࣍ M. J. Farrell ऱྤᑇسขছᒴΔಾኙॺᛜܓࢤᔆิ៣ڇࡐࡳᑓሟයٙՀΔ ᘝၦڍႈދԵፖڍႈขנհެۯऱઌኙسขயऱԫጟֱऄΔࢬᘯެۯ ਐऱਢࠠڶ٥ٵދԵፖขנႈऱ࠹ေۯΔᑓڤڶאՀԲጟΚ
ʙăCCR ᇁВ!
CharnesΕCooper ፖ Rhodesΰ1978αࢬ༼נऱயေ۷ᑓڤጠ CCR ᑓڤΔ
এലࢬڶެۯऱٺႈขנፖދԵऱسขڂऱֺᄗ࢚ࢬ৬مऱᑇᖂᑓ ڤΔ٦᠏ངګ։ᑇᒵࢤቤᑓڤޣᇞΔٍܛലࢬڶެۯऱٺႈขנፖދԵႈ
։ܑאᒵࢤิٽऱֱڤףאۭຑΔޢԫଡެۯऱயଖขנհᒵࢤิٽೈ
אދԵհᒵࢤิٽΔࠀૻ່ࠫࠡՕயଖ 1Δז।ઌኙڶயհۯΔ֘հ ঞઌኙྤயΖ
ʠăBCC ᇁВ!
CCR ᑓڤࢬᘝၦऱயਢڇࡐࡳᑓሟΰConstant Return to scale, CRSαऱයٙՀΔ܀ਢᅝᑓሟױ᧢೯ழΔਬԫެۯྤயऱڂΔױ ౨ڶຝ։ڂਢࠐ۞࣍ሎ܂ᑓऱլᅝΔڂڼԱઔߒྤயݮګऱڂైΔ BankerΕCharnes ፖ Cooperΰ1984αല᜔யΰaggregate efficiencyα։ᇞګొݾ
யΰpure technical efficiencyαፖᑓயΰscale efficiencyαࠐ൶ಘΔشאᘝ ၦயΔጠ BCC ᑓڤΖ᜔யΰaggregate efficiencyαΕొݾயΰpure technical efficiencyαፖᑓயΰscale efficiency, SEαԿृհၴऱᣂএΔঞאቹ 1 ףאᎅ
ࣔΚ
X سขױ౨
ႃٽ
E
VRS Y CRS
R
M
0 ขנ
XN XB XA XE ދԵ
ၗٰྍǺBanker, R. D., Charnes, A., & Cooper, W. W. (1984). Some medels for estimat- ing technical and scale in efficiencies in data envelopment analysis. Manage- ment Science, 30(9), 1089.
1! ᒂझăসӬझჄᇁझ˞ᘰ۽
Xၗז।ދԵΔY ၗז।ขנΔBEC سขױ౨ႃٽऱছᒴΔࢬڶسขױ౨
ႃٽ BEC ڴᒵࢬץΔA ז।ေ۷ऱެۯΔࠡދԵၦ XAΔขנၦ
YBΖڇ᧢೯ᑓሟΰVariable Return to Scale, VRSαՀΔኙ A ۖߢΔB ऱขנ
ֽᄷፖ A ઌٵΔٵᑌسข OMΰYAΔYBαऱขၦΔA ऱދԵၦႊ MAΰXAαΔ܀
BऱދԵၦႊ MBΰXBαΔڂڼΔڇᘝၦ A ऱྤய࿓৫ழΔא B ەរΔ ױव A א MAΰXAαऱދԵၦسข OM ऱขၦਢྤயΔۖ A ऱొݾய
MB/MAΰXB/XAαΔڼܛ BCC ᑓڤࢬᘝၦऱயଖΖE រז।ڇ᧢೯ᑓ
ሟՀΔދԵፖขנऱิٽΰXΔYαխΔሒࠩݾயृΔٍܛٵழࠠڶొݾ
யፖᑓயΔࠡؓ݁سขԺ YE/XEΔਢسขױ౨ႃٽփΔࢬڶދԵขנิ
ٽऱؓ݁سขԺ່ՕऱΔՈ༉ਢᎅ່ࠠڶயऱΔڂڼ A រ᜔யհᘝၦႊፖ E រ܂ֺለΔۖ N ऱؓ݁سขԺፖ E ઌٵΰขנፖދԵհֺଖઌٵαΔਚۖא N
ەរΔA ऱ᜔ய MN/MAΰXN/XAαΔڼܛ CCR ᑓڤࢬᘝၦհயଖΖ
طቹ 1 ױवΔ᜔யଖొݾயଖፖᑓயଖऱଊᗨΔٍܛ MN/MAЈ ΰMB/MAαͪ SEΔڂڼ A ऱᑓய MN/MBΰXN/XBαΖངߢհΔא CCR ᑓ ڤऱயଖೈא BCC ᑓڤऱயଖΔױެۯऱᑓயଖΖ؆طቹ 1 ױवΔᅝᑓயଖ࣍ 1Δ।قᇠެۯ࣍ࡐࡳᑓሟΔࠠڶᑓயΔ ᅝᑓயଖլ࣍ 1 ழΔ।قᇠެۯ࣍ᑓᎠᏺࢨᎠ྇ऱྤᑓயၸ
ΖڼԫᇷಛΔױ༼ࠎެृ܂ᓳᖞسขᑓऱەΖ
طאՂऱᨠ࢚ΔBankerΕCharnes ፖ Cooperΰ1984αല CCR ᑓڤڍףԱԫס ࢤࢤᔆΰconvexityαऱૻࠫΔࠀޣӢӳj Ј 1ΰ।قᇠެۯ࣍ࡐࡳᑓ
ሟၸΔڼழݾயፖسขயઌΖૉ՛࣍ 1 ঞ।قެۯ࣍ᑓሟ ᎠᏺၸΙ֘հΔૉՕ࣍ 1 ঞ।قެۯ࣍ᑓሟᎠ྇ၸαΔٵழ֧ၞԫ ଡᄅऱ᧢ᑇ UoΔشאᘝၦ᧢೯ᑓሟՀऱొݾயଖΖڼ BCC ᑓڤխֺ CCR ᑓڤڍףԱԫסࢤࢤᔆऱૻࠫΔࠀޣӢӳj Ј 1Δڼԫૻࠫ।قެۯڇسข ࠤᑇՂհەរؘႊਢڶயެۯհסࢤิٽΰconvexity combinationαΔۖ
ૻࠫေ۷ۯፖࠡࢬەެۯհิٽऱᑓଖઌٵΰଖઌٵαऱය
ٙՀ܂ొݾயᘝၦհֺለΖ؆ BCC ᑓڤڇ CCR ᑓڤڍףԱԫଡ᧢ᑇ UoΔUo Ӣӳj Ј 1 ૻࠫڤઌኙᚨऱ᧢ᑇΔז।ᑓሟΰreturn to scaleαऱਐ ᑑΖط࣍ BCC ᑓڤհயছᒴਢڇ᧢೯ሟᑓՀࢬެࡳऱΔۖࠡסࢤࢤᔆ Ӣӳj Ј 1 ऱૻࠫΔࠌயছᒴ૿լຏመរΔՈ༉ਢᎅΔڇ᧢೯ሟᑓՀΔ
ࠡயছᒴऱऴᒵࠀլຏመរΔፖ Y ၗڶԫൄᑇኲ၏Δڼԫኲ၏ܛ UoΔ ڂڼΔBCC ᑓڤױຘመ Uo ࠐܒឰ࠹ေެۯհᑓሟणउΔᅝ UoЇ0 ழΔ ঞ।قᇠެۯ࣍ᑓሟᎠ྇Ιᅝ UoІ0 ழΔঞ।قᇠެۯ࣍ᑓ
ሟᎠᏺΙᅝ UoЈ0 ழΔঞᇠެۯࡐࡳᑓሟΖ
དྷăྤफ़Βඛ̶ژдିֈ˯̝ᑕϡ
ᇷறץ։࣫ᚨش࣍ඒߛᏆऱઔߒΔױאូᣊᚨش CCR ᑓڤΕBCC ᑓ ڤא֗ᜤٽࠡהᑓڤΔ։૪ڕՀΚ
ʙăպ CCR ᇁВఋ˷!
BessentΕBessentΕKennington ፖ Reaganΰ1981, 1982αא CCR ᑓڤေ۷ʳ
Houstonچ 167 ࢬ՛ᖂհઌኙயΔࠡխ 89 ࢬઌኙڶயΔ78 ࢬઌኙྤயΖ
FareΕGrosskopf ፖ Weberΰ1989αא CCR ᑓڤΔಾኙભഏ Missouri ڠࣟຝऱ 40 ଡᖂေ۷ઌኙ।Δ࿇षᆖࢤΰ୮அگԵα။ऱᖂΔࠡய।။ړΖ Rayΰ1991αᚨشᇷறץ։࣫ऱ CCR ᑓڤေ۷ભഏ Connecticut ڠٺֆمխᖂ ऱઌኙயΔ࿇ٺᇷᄭࠌشயឈڶৰՕլٵΔ܀Օຝ։ڂএࠐ۞࣍षᄎ ᆖᛎહནΔۖຟؑچயܑ܅ऱᖂீΔႛޏၞጥயսਢլߩऱΔࡸႊە ᐞ։ለڍऱᇷᄭࢨޏ᧢षᄎᆖᛎڂైऱૻࠫΖAndersonΕWalberg ፖ Weinstein ΰ1998αܓش CCR ᑓڤေ۷॒ףୂֆمॣᖂீ 1989Ε1991 ፖ 1993 ڣԿଡၸ
ऱᖂீயፖய౨Δ࿇ٵழࠠڶயፖய౨ऱᐛࡳऱڇᖂԳᑇΕԵᖂ
Εڍᑇᖂسॺຆᒡᖂسፖለ܅ᖂسक़၄Ζ
ʠăϫցպ BCC ᇁВ!
Zomorrodianΰ1990αא CCR ፖ BCC ᑓڤઔߒભഏ Massachusetts ڠ۫ຝ 81 ࢬ՛ᖂऱޏயΔ37 ࢬڶயΔ44 ࢬྤயΔࠀ࿇ᖂسᖜ֑塊ऱक़၄Ε
֟ᑇاගᖂسֺࠏΕஃسֺፖඒஃؓ݁ᜲᇷኙᖂீயڶ᧩ထࢤऱᐙΖ
ʭăᒒϫ֏͂ᇁВ!
Kirjavainenፖ Loikkanenΰ1998αٽᇷறץ։࣫ڇ᧢೯ᑓሟፖࡐࡳ
ᑓሟᑓڤፖ Tobit ։࣫ख़ᥞ 291 ࢬխᖂ 1989-1991 ڣऱயฆΔ࿇׀ئඒߛ
࿓৫ᄎ༼ઌኙயऱؓ݁ଖΔۖఄ్ᑇࢨᖂسᑇ֟ऱྤயᖂீΔࠡᖂீՕ՛
ࠀլᐙயଖΔۖֆمᖂீऱய।ֺߏمᖂீᚌฆΖ
Ёăࡁտ͞ڱ
ေ۷ᆖᛜᜎய່ᣂऱڂై༉ਢދԵፖขנڂհઌኙૹࢤΔ៶طઌኙૹ
ࢤലٺڂᖞٽԫਐᑑΔאေֺΖެࡳڂऱૹࢤΔႚอऄԯאಱ
ូ։࣫ެࡳٺڂឆܶऱᦞૹΔྥۖᇠऄႛᔞش࣍ԫขנΔྤऄڍขנհ
ൣउΖޏᇠૻࠫΔᆠՕܓᆖᛎᖂ୮ V. Pareto ڇ 20 ધॣ༼נॺରᕏᇞ ΰnon-dominance solutionαऱᄗ࢚Δءઔߒࢬආ࠷ऱᇷறץ։࣫ऄ༉ਢආشᇠ ᨠ࢚אေ۷ԫᆢ᧯ެۯհઌኙயΔ։࣫ຌ᧯ආش Frontier Analysis ၞ۩ૠ ጩΖ
ౙăྤफ़ֽ̈́ᇾᄲځ
ءઔߒאॵᙕԫࢬ٨հፕچ్խᖂ։࣫ᑌءΔ፦ႃຍࠄᖂீ 87 ᖂڣ ৫ഗءᇷறΔૠڶދԵႈΚᖂس᜔ԳᑇΕఄ్ᑇΕٽඒஃΕඒஃᖂᖵΕᆖൄ
॰Εᇷء॰Ιא֗ขנႈΚ֒ᖂΕխຜᠦீΕฅᄐਐᑑΖאՂٺਐᑑհ ᇷறࠐᄭඒߛຝઔߒࡡᄎ 87 ᖂڣ৫్խᖂउᓳΔٺਐᑑࡳᆠڕ। 2Κ
ے2 Ϩݾᆿ˞ጇѰܮס༎
ݾᆿ ጇ Ѱ ܮ ס ༎
ᖂس᜔Գᑇ ᇠீᖂس᜔ԳᑇΰץܶإఄΕᇖீΕኔشݾ౨ఄፖ৬ඒٽ܂ఄհᒳࠫփᖂ سԳᑇΔլץਔഏխݾᢌఄፖറ९ఄα
ᖂீఄ్ᑇ ᖂீఄ్᜔ᑇΰץܶإఄΕᇖீΕኔشݾ౨ఄፖ৬ඒٽ܂ఄհᒳࠫփఄᑇΔ լץਔഏխݾᢌఄፖറ९ఄα
ٽඒஃ ࠷ٽඒஃᢞհᒳࠫփإڤඒஃԳᑇ᜔ඒஃᠰᒳֺࠫհଙᑇΖ ඒஃᖂᖵ ࠠڶጚՓΰܶԼᖂ։ఄαᖂᖵאՂհඒஃԳᑇᠰᒳࠫඒஃԳᑇհֺ
ᆖൄ॰ 87ᖂڣ৫ࢨᄎૠڣ৫հᄎૠެጩᆖൄ॰᜔ᠰΰאשցૠα ᇷء॰ 87ᖂڣ৫ࢨᄎૠڣ৫հᄎૠެጩᇷء॰᜔ᠰΰאשցૠα
֒ᖂ ฅᄐسΰץਔەՂԫֆΰߏαمՕᖂΕݾᖂೃΕઝݾՕᖂΕݾΕԲറΕ
ၞറΕ૨ᤞᖂீֲ࡙ၴຝαऱٺ֒ᖂጥሐᖂسֺ
խຜᠦீ ᅝڣ৫ᇠீխຜᔗᖂΕٖΕಯᖂΕ᠏ᖂհᖂسֺΰץܶإఄΕᇖீΕኔ شݾ౨ఄፖ৬ඒٽ܂ఄα
ฅᄐ ᇠீᚨࡻฅᄐᖂس᜔ԳᑇࢬᇠࡻԵᖂԳᑇհֺΰץܶإఄΕᇖீΕኔ شݾ౨ఄፖ৬ඒٽ܂ఄα
߭ăࡁտඕڍᄃኢ
ءઔߒଈ٣א CCR ᑓڤ։࣫ᖂீऱᖞ᧯ઌኙயΔ٦א BCC ᑓڤ։࣫ࠡઌ ኙऱݾயΔࠀطڼԲृऱֺଖޣᑓயଖΰᖞ᧯யΕݾயፖᑓ யऱ։࣫࣠ڕॵ।ԲαΔא൶ಘඒߛ൳ਐᑑߓอऱ࣠Ζ౿։૪ڕՀΚ
ʙăጌझ˷ٙ!
ᖕ CCR ᑓڤေ۷ᖞ᧯யழΔૉࢬޣயଖ 1 ழΔז।ᇠެۯሒઌ ኙڶயΔૉࠡଖ՛࣍ 1 ழΔঞז।ᇠެۯઌኙྤயΖݾயঞਢਐ אڶऱދԵิٽΔسข່ՕขנิٽऱၦΔࢨਢڇڇਝࡳऱขנิٽၦՀΔ ࢬދԵ່֟ऱދԵิٽၦΔא BCC ᑓڤޣ࠷ڇਝࡳऱขנิٽၦՀΔࢬދԵ່֟
ऱދԵิٽၦऱݾயΔۖ։࣫ݾயז।ऱრᆠܛਢᨠኘٺխᖂீࢬ ދԵᇷᄭऱᆜิٽਢܡ່ࠋิٽऱൣݮΔࠡൎᓳऱਢᇷᄭᆜऱ৾ᅝ࿓৫Ζ ٵᑌऱΔૉࢬயଖ 1 ழΔז।ᇠެۯሒݾயΔ֘հΔঞז।ᇠެ
ۯྤݾயΖ
ᖕ। 3 ࿇٤ഏֆمխᖂீऱᖞ᧯ய։࣫ሒࠩઌኙڶயΰCCR ய
ଖ 1 ृαऱᖂீ٥ 34 ࢬΔ٤ຝᖂீऱ 16.19%Δࠡխֆم 13 ࢬΔֆ مᖂீ 13.4%Ιֆمխ 21 ࢬΔֆمխᖂீ 18.58%Ζயଖڇ 1 ۟ 0.9հၴऱᖂீ٥ 57 ࢬΔ٤ຝᖂீऱ 27.14%Δֆم 25 ࢬ 25.77%Δֆم
խ 32 ࢬΔ 28.32%Ζயଖڇ 0.9 ۟ 0.8 հၴऱᖂீ٥ 64 ࢬΔ٤ຝᖂீऱ
30.48%Δֆم 26 ࢬ 26.8%Δֆمխ 38 ࢬΔ 33.63%ΖངߢհΔயଖ
0.8 אՂࢬڶֆمխᖂீᑇհ 73.81%Ζࠡהآሒயଖ 0.8 ृΔֆم
33ࢬΔֆمխ 22 ࢬΔࢬڶֆمխᖂீᑇհ 26.19%Ζطڼױߠڇሒࠩڶ யऱᖂீֱ૿Δֆمխᖂீཏሙऱ।ֺֆمᖂீړΖ
ے3! ጌझĞCCRğࢄЩᆵ˷ࡎے झࢄ
ĞEğ ደमᆵ л˷̨
Ğ%ğ
˛ᕛϫࡎ
л˷̨Ğ%ğ ணፖл˷̨
Ğ%ğ ˛ᕛϫࡎணፖ л˷̨Ğ%ğ
13 13.4 13.40 E=1 խ 21 18.58 16.19
18.58 16.19
25 25.77 39.17 0.9<E< 1
խ 32 28.32 27.14
46.90 43.33
26 26.80 65.97 0.8<E<0.9
խ 38 33.63 30.48
80.53 73.81
25 25.77 91.74 0.7<E<0.8
խ 18 15.93 20.48
96.46 94.29
5 5.15 96.89 0.6<E<0.7
խ 2 1.77 3.33
98.23 97.62
2 2.06 98.97 0.5<E<0.6
խ 2 1.77 1.91
100 99.52
1 1.03 100 0.4<E<0.5
խ 0 0.00 0.48
100 100
ʠăӬझ˷ٙ!
Ղ૪ CCR ᑓڤਢشࠐᘝၦᖞ᧯யΔۖ BCC ᑓڤঞ៶طૠጩנڶᑓհ ՀऱొጰݾயଖΖءઔߒࠌش Frontier Analyst ຌ᧯ലࡐࡳᑓሟޏش᧢೯
ᑓሟᑓڤΔૠጩנ BCC ขנᖄٻհొጰݾயଖΰڕ। 4 ࢬقαΔ࿇٤ ഏֆمխᖂீࠠڶݾயऱᖂீ٥ 66 ࢬΔ٤ຝᖂீऱ 31.43%Δࠡխֆ م 24 ࢬΔֆمᖂீ 24.74%Ιֆمխ 42 ࢬΔֆمխᖂீ
37.17%Ζயଖڇ 1 ۟ 0.9 հၴऱᖂீ٥ 71 ࢬΔ٤ຝᖂீऱ 33.81%Δֆم
32 ࢬ 32.99%Δֆمխ 39 ࢬΔ 34.51%Ζயଖڇ 0.9 ۟ 0.8 հၴऱᖂீ
٥ 58 ࢬΔ٤ຝᖂீऱ 27.62%Δֆم 32 ࢬ 32.99%Δֆمխ 26 ࢬΔ
23.01%ΖངߢհΔயଖ 0.8 אՂࢬڶֆمխᖂீᑇհ 92.86%Ζࠡהآሒ
யଖ 0.8 ृΔֆم 9 ࢬΔֆمխ 6 ࢬΔࢬڶֆمխᖂீᑇհ 7.14%Ζ طڼױߠڇొጰݾயֱ૿Δֆمխᖂீսྥཏሙऱ।ֺֆمᖂீʳ ړΖ
ے4! ӬझĞBCCğЩᆵ˷ࡎے झࢄ
ĞEğ ደमᆵ л˷̨
Ğ%ğ
˛ᕛϫࡎ
л˷̨Ğ%ğ ணፖл˷̨
Ğ%ğ
˛ᕛϫࡎணፖ л˷̨Ğ%ğ
24 24.74 24.74 E=1 խ 42 37.17 31.43
37.17 31.43
32 32.99 57.73 0.9<E<1
խ 39 34.51 33.81
71.68 65.24
32 32.99 90.72 0.8<E<0.9
խ 26 23.01 27.62
94.69 92.86
6 6.19 96.91 0.7<E<0.8
խ 5 4.42 5.24
99.12 98.1
2 2.06 98.97 0.6<E<0.7
խ 0 0 0.95
99.12 99.05
1 1.03 100
0.5<E<0.6
խ 1 0.88 0.95
100 100
ʭăᇁझ˷ٙ!
۟࣍ᑓயএਐࢬسขऱขၦፖᇷᄭދԵၦऱֺࠏൣݮΔᅝࢬᛧऱขၦ ፖࢬދԵᇷᄭऱၦګֺࠏᏺףழΔঞࠠڶᑓயΔૉᅝլګֺࠏᏺףழΰᎠ ᏺࢨᎠ྇αΔঞז।լࠠᑓயΖᑓயፖݾயऱܑڇ࣍ᑓயࢬᣂ
֨ऱਢࢬᛧऱขၦፖࢬދԵᇷᄭၦऱֺࠏൣݮΔۖݾயঞਢᣂ֨ᇷᄭᆜ
ิٽਢܡ৾ᅝऱ࿓৫Δۖᑓயऱᘝၦঞױطᖞ᧯யፖݾயऱֺଖޣ
Δૉயଖ 1 ழΔז।ᇠެۯࠠڶᑓயΔܛขၦᙟދԵၦऱᏺףۖ
ګֺࠏᏺףΔጠհࡐࡳᑓሟΔૉࠡଖ՛࣍ 1 ழΔঞז।ᇠެۯྤ
ᑓயΔᑓሟױ౨ᎠᏺࢨᎠ྇Ζᖕ। 5 ࢬقΔ࿇٤ഏֆمխᖂ
ீࠠڶᑓயऱᖂீ٥ 37 ࢬΔ٤ຝᖂீऱ 17.62%Δࠡխֆم 15 ࢬΔ
ֆمᖂீ 15.46%Ιֆمխ 22 ࢬΔֆمխᖂீ 19.47%Ζயଖڇ 1
۟ 0.9 հၴऱᖂீ٥ 135 ࢬΔ٤ຝᖂீऱ 64.29%Δֆم 63 ࢬ 64.95%Δ ֆمխ 72 ࢬΔ 63.72%Ζயଖڇ 0.9 ۟ 0.8 հၴऱᖂீ٥ 28 ࢬΔ٤ຝᖂ
ீऱ 13.33%Δֆم 14 ࢬ 14.43%Δֆمխ 14 ࢬΔ 12.39%ΖངߢհΔ
யଖ 0.8 אՂࢬڶֆمխᖂீᑇհ 95.24%Ζࠡהآሒயଖ 0.8 ृΔֆ م 5 ࢬΔֆمխ 5 ࢬΔࢬڶֆمխᖂீᑇհ 4.76%Ζطڼױवᑓ யֱ૿Δֆمխᖂீ।սᚌ࣍ֆمᖂீΖ
ے5! ᇁझЩᆵ˷ࡎے झࢄ
ĞEğ ደमᆵ л˷̨
Ğ%ğ
˛ᕛϫࡎ
л˷̨Ğ%ğ ணፖл˷̨
Ğ%ğ
˛ᕛϫࡎணፖ л˷̨Ğ%ğ
15 15.46 15.46 E=1 խ 22 19.47 17.62
19.47 17.62
63 64.95 80.41 0.9<E< 1
խ 72 63.72 64.29
83.19 81.91
14 14.43 94.84 0.8<E<0.9
խ 14 12.39 13.33
95.58 95.24
4 4.12 98.97 0.7<E<0.8
խ 4 3.54 3.81
99.12 99.05
1 1.03 100 0.6<E<0.7
խ 1 0.88 0.95
100 100
Ͳăуϫ˷ٙ!
ᅝԫଡެۯऱயଖ 1 ழΔז।ڼެۯᆵڇயছᒴՂΔڂۖګ
ࠡהઌኙྤயެۯऱەኙွΔ៶א։࣫ࠡயଖא֗ࠡދԵፖขנऱ ޏ़ၴΔط࣍ CCR ᑓڤآ౨ಾኙઌኙڶயऱެۯၞԫޡ։ࠡயൎ ৫ΔڂڼΔࠉᅃ Doyle ፖ Greenΰ1993αऱऄΔאઌኙڶயऱެۯ
ەڻᑇऱڍኒΔ܂ၞԫޡൕຍࠄઌኙڶயऱެۯ։נటإڶயऱެ
ۯΖᅝԫڶயᖂீەऱڻᑇ။ڍΔܛז।ࠡ။ࠠڶటإயΔٍܛګ
ࠡהڍᑇᖂீࢬەऱࠉᖕΔڂڼΔࠡய।ګຍࠄᖂீऱᄒᑓΖط। 6 ױवΔ᠆խΰᒳᇆ 149αࠡהઌኙྤயհᖂீەऱڻᑇ 162 ڻ່ڍΔ
ࠡڻᄅࢋխΰᒳᇆ 121α121 ڻΕኦ֏խΰᒳᇆ 111α113 ڻΕፕஃᒤՕ ᖂॵխΰᒳᇆ 147α70 ڻΕႂஃᒤՕᖂॵխΰᒳᇆ 160α66 ڻΕፕতᥨΰᒳ ᇆ 83α58 ڻΕխࡉխΰᒳᇆ 166α27 ڻΕতދխΰᒳᇆ 107α21 ڻΔאڼ
ᣊංΔ٥ૠխ 21 ࢬΕ 13 ࢬΖطڼอૠױवΔֆمխઌኙڶய 1 ऱ ᖂீխΔսאֆمխ।ለֆمࠋΖ
ے6! уϫЩᆵࡎ
Щᆵ DMU Щᆵ DMU Щᆵ DMU
162 149 20 45 7 120 121 121 19 51 6 68Δ153
113 111 17 214 5 90Δ54Δ212Δ211 70 147 13 101 4 115 66 160 12 187 3 84Δ111Δ135 58 83 11 220 2 95Δ86 27 166 10 73 1 70Δ182Δ171 21 107 9 118
طՂ૪࣠ၞ۩ಘᓵवΔֆمխլᓵڇᖞ᧯யΕݾயΕᑓய
ઃᚌ࣍ֆمऱ।Ζ൶ߒࠡڂΔױၞԫޡܓشᠰ᧢ᑇ։࣫אᛵᇞࠡދԵ ፖขנႈޏऱ़ၴΖᖕቹ 2Εቹ 3 ᧩قΔᅝ᧢ႈࢬᏁޏีᗨۍ։ֺࢬڶ ઌኙֺࠏ။ՕृΔঞ।قᇠႈؾਢທګᖂீઌኙྤயऱױ౨ڂైհԫΔՈ
༉ਢᖂீᚨૹီᇠ᧢ႈऱᆖᛜጥΖངߢհΔྤயऱֆمխሒᖞ᧯ய
ΰCCR ᑓڤαႊޏऱႈؾڇขנႈֱ૿ᚌ٣ڻݧא֒ᖂ 65.88%א֗խຜ ᔗᖂ 30.74%Ι۟࣍ދԵႈֱ૿אᇷء॰ 1.06%ᚌ٣Ζ۟࣍ڇݾயΰBCC ᑓڤαֱ૿Δႊޏऱႈؾڇขנႈֱ૿ᚌ٣ڻݧאխຜᔗᖂ 62.04%א֗
֒ᖂ 36.39%Ι۟࣍ދԵႈֱ૿אᇷء॰ 0.55%ᚌ٣Ζ
ုΚa.ދԵႈΚᖂس᜔ᑇΰinput4αΕᖂீఄ్ᑇΰinput1αΕٽඒஃΰinput2αΕ ඒஃᖂᖵΰinput3αΕᆖൄ॰ΰinput5αΕᇷء॰ΰinput6α
b.ขנႈΚ֒ᖂΰoutput1αΕխຜᔗᖂΰoutput2αΕฅᄐΰoutput3α
2 ˴γ˛ᕛഒझደम˞࣯ᖞᝐᆵ˷ٙ˞CCRᇁВఋ˷
3 ˴γ˛ᕛഒझደम˞࣯ᖞᝐᆵ˷ٙ˞BCCᇁВఋ˷
ज़ăඕ ᄬ
ءઔߒᚨشᇷறץ։࣫ᚨش࣍൳ਐᑑߓอऱயေ۷ՂΔݦඨ៶طᇷற ץ։࣫հٺႈࢤ৬ዌԫݙᖞΕױ۩֗༼ࠎඒߛਙެ৬ᤜऱᜎயࢤ൳ ᑓীΔۖءઔߒຘመֆمխኔᢞᇷறऱ։࣫࣠Δ࿇լᓵڇᖞ᧯யΕݾ
யא֗ᑓயٻ৫ऱ।Δֆمխઃᚌ࣍ֆمΔࠀवྤயऱ ֆمխڇᖞ᧯யΰCCR ᑓڤαֱ૿Δႊޏऱႈؾڇขנႈֱ૿ᚌ٣ڻ ݧא֒ᖂא֗խຜᔗᖂΙ۟࣍ދԵႈֱ૿אᇷء॰ᚌ٣Ζ۟࣍ڇݾய
ΰBCC ᑓڤαֱ૿Δႊޏऱႈؾڇขנႈֱ૿ᚌ٣ڻݧאխຜᔗᖂא֗֒
ᖂΙ۟࣍ދԵႈֱ૿אᇷء॰ᚌ٣Ζ
ءઔߒኙ࣍൳ਐᑑߓอऱ৬ዌፖᚨش༼נאՀ৬ᤜΔࠌشᇷறץ։࣫ေ
۷ᑓڤೈԱױ։ઌኙயհ؆Δઌኙྤயᖂீऱઌኙயଖױ܂ᖂீඈټ ऱࠉᖕΔۖઌኙڶயऱᖂீឈྥࠡயଖ 1Δ܀ױ៶طەႃٽ։࣫խΔڶ யᖂீەऱڻᑇΔၞԫޡലઌኙڶயᖂீඈټΖڂڼΔױܓشᇷறץ
։࣫ᑓڤ܂ᖂீᜎயေ۷ऱᑇၦ֏൳ᑓীΖࠀױܓشᇷறץ։࣫ऱ်ឰ ࢤפ౨ΔބנᖂீྤயऱڂైΔൕۖᓳᖞᖂீᇷᄭऱᆜൣݮࢨᆖᛜᑓऱՕ
՛Δא܂ᖂீޏᜎயऱਙەΖᇷறץ։࣫ᑓڤױၞԫޡಾኙྤயհ ᖂீ༼ࠎᒔ֊ऱޏ༏৫ፖֱٻհઌᣂᇷಛΔຘመᠰ᧢ᑇऱ։࣫᧩قΔઌኙྤ
யऱᖂீઃڶؘࠡႊޏऱ़ၴΔڂڼྤயऱᖂீױࠉᖕࠡٺ۞ऱؾᑑଖΔ ᓳᖞࠡٺދԵፖขנႈؾऱ༏৫Δא܂ᖂீᆖᛜጥፖᇷᄭᆜऱޏࠉᖕΔ ࠀᓳᖞᖂீጥऱֱٻΖኙ࣍ઌኙޏ༏৫ለՕऱႈؾΔᖂீᚨܑղאૹီΔ ᆖᛜጥृᚨᔞழᓳᖞᖂீऱጥֱٻΔאޏᖂீऱጥயΔ༼ࣙᖂீᜎயΖ ٵழਙࢌኙ࣍ඒߛ൳ؘႊ৬مࠨᖿඒߛጥயऱቃጩࠫ৫ፖᇖܗࠫ৫Δאݮ ګኙᖂீᆖᛜጥऱ؆ຝᚘԺΖ
ણ҂͛ᚥ
Anderson, L., Walberg, H. J., & Weinstein, T. (1998). Efficiency and effectiveness analysis of Chicago public elementary school: 1989, 1991, 1993. Educational Administration Quar- terly, 34(4), 484-504.
Banker, R. D., Charnes, A., & Cooper, W. W. (1984). Some models for estimating technical and scale inefficiencies in data envelopment analysis. Management Science, 30 (9), 1078-1092.
Bessent, A., Bessent, W., Kennington, J., & Reagan, B. (1981). A fractional programming model for determining the efficiency of decision making units. (ERIC Document Reproduction Service No. ED 203535)
Bessent, A., Bessent, W., Kennington, J., & Reagan, B. (1982). An application of mathematical programming to assess productivity in the Houston independent school district. Manage- ment Science, 28(12), 1355-1367.
Charnes, A., Cooper, W. W., & Rhodes, E. (1978). Measuring the efficiency of decision making units. European Journal of Operational Research, 2(6), 429-444.
Doyle, J., & Green, R. (1993). Data envelopment analysis and multiple criteria decision making.
Omega, 21(6), 713-715.
Engert, F. M. (1995). A study of school district efficiency in New York State using data envel- opment analysis. Dissertation Abstracts International, 56(7), 2502A. (UMI No. 9538079) Fare, R., Geosskopf, S., & Weber, W. L. (1989). Measuring school district performance. Public
Finance Quarterly, 17(4), 409- 428.
Fitz-Gibbon, C. T. (1996). Monitoring education: Indicators, quality and effectiveness. London:
Cassell.
Husén, T., & Tuijnman, A. C. (1994). Monitoring standards in education: Why and how it came about. In A. C. Tuijnman & T. N. Postlethwaite (Eds.), Monitoring the standards of educa- tion (pp. 1-21). New York: Pergrmon.
Johnson, B. L. (1999). The politics of research: Information use in the education policy arena.
Educational Policy, 13(1), 23-36.
Johnstone, J. N. (1981). Indicators of education system. Paris: UNESCO.
Kirjavainen, T., & Loikkanen, H. A. (1998). Efficiency differences of finnish senior secondary schools: An application of DEA and Tobit analysis. Economics of Education Review, 17(4),
377-394.
Oakes, J. (1986). Educational indicators: A guide for policy makers. New Brunswich, NJ: Cen- ter for Policy Research in Education.
Odden, A. (1990). Educational indicators in the United States: The need for analysis. Educa- tional Researcher, 19(5), 24-29.
Postlethwaite, T. N. (1994). Monitoring and evaluation in different systems. In A. C. Tuijnman
& T. N. Postlethwaite (Eds.), Monitoring the standards of education (pp. 23-46). New York:
Pergrmon.
Ray, S. C. (1991). Resource-use efficiency in public school: A study of Connecticut data. Man- agement Science, 37(12), 1620-1628.
Shavelson, R., McDomnnell, L., Oakes, J., & Carey, N. (1987). Indicator systems for monitoring mathematics and science education. Santa Monica, CA: RAND.
Willms, J. D. (1992). Monitoring school performance: A guide for educators. London: The Fal- mer Press.
Windham, D. M., Chapman, D. W., & Walberg, H. J. (1990). Evaluation of educational efficiency: Constraints, issues, and policies. New York: JAI Press.
Zomorrodian, M. R. (1990). Guidelines for improving efficiency in elementary schools in West- ern Massachusetts: A data envelopment analysis approach. Dissertation Abstracts Interna- tional, 51(7), 2264A. (UMI No. 9035426)
ܢᐂ˘
˴γ˛ᕛሡ༴ʙᛔےĞᕛఋ˷ğ
ሡ༴ म Ϫ ሡ༴ म Ϫ ሡ༴ म Ϫ 1 ᅗ॑ՠ 2 Կૹՠ 3 ௧՞ՠ 4 ֽՠ 5 ࡵᥞ 6 ᢅࣟ
7 ᤕᖾ௧ࠃ 8 ᢅࣟՠ 9 ᙰৄ୮
10 ഏمࡵᥞݾᖂೃॵՠ 11 ᚊᑧልՠ 12 Ⴜልՠ 13 խᡑ 14 խᡑ୮ 15 ᣂ۫ል 16 Օྋልՠ 17 ્ொልՠ 18 ્ொ
19 ᠆ 20 Օظՠ 21 ࣟႨՠ 22 ޥຼՠ 23 ᣆልՠ 24 ഏمኦஃՕॵՠ 25 ة壃ՠ 26 Բࣥՠ 27 ߐֽՠ 28 ኦ֏ 29 ࣥልՠ 30 ശኔՠ 31 ࣥ୮ 32 ק֯୮ 33 ոფል 34 ୕ߺՠ 35 তދ 36 ౻֢ՠ 37 ֽߺՠ 38 ॡݠልՠ 39 ۫ᝅልՠ 40 ֯ք୮ 41 קཽልՠ 42 Ւՠ 43 اႂልՠ 44 ᄅ֏ՠ 45 ػࣾՠ 46 ק॰ልՠ 47 མ֮୮ 48 ᄅᛜՠ 49 دմՠ 50 ፕতል 51 ፕতՠ 52 མ֮ልՠ 53 ՞ልՠ 54 ࡽ՞ልՠ 55 Ꮥ՞ՠ 56 փ୕ልՠ 57 ৠࣟՠ 58 ࠋמል 59 ཽࣟ௧ࠃ 60 ਁਞՠ
61 ፕࣟልՠ 62 ᣂ՞ՠ 63 ፕࣟ
64 ګפᄐֽข 65 क़ᓊል 66 क़ᓊՠ 67 क़ᓊ 68 ٠༚ՠ 69 ᑫྋ௧ࠃ
70 ഗၼ௧ࠃ 71 ഗၼՠ 72 ᄅێ
73 ᄅێՠ 74 ፕխ୮ 75 ፕխል 76 ፕխՠ 77 ፕխᥨ 78 ဎত
79 ቯᆠՠ 80 ቯᆠ 81 ቯᆠ୮
82 ፕত 83 ፕতᥨ 84 ፕত௧ࠃ 85 ؑم࣪՞୮ 86 ؑم࣪՞ՠል 87 ؑمՕڜՠ 88 ؑمֵਰՠ 89 ؑمতཽՠ 90 ؑمփྋՠ 91 ؑمՓࣥ 92 ؑم௧ॹՠ 93 ؑمԿا୮
94 ؑمႂՠ 95 ؑمႂ 96 ؑمխإՠ 97 ഏم८॰ልՠ
Ğᛉğ˴γ˛ᕛሡ༴ʙᛔےĞ˛ఋ˷ğ
ሡ༴ म Ϫ ሡ༴ म Ϫ ሡ༴ म Ϫ ሡ༴ म Ϫ 98 ୮ᏘՖխ 99 ቯᆠխ 100 Ⴜխ 101 ຼཽխ 102 ፕতԲխ 103 ᄅᛜխ 104 Օظխ 105 ק॰խ 106 ࣥխ 107 তދխ 108 ᄅێՖխ 109 ࡽ՞խ 110 ્ொխ 111 ኦ֏խ 112 խᘋխ 113 ՞խ 114 ፕխԫխ 115 ᧯ߛኔխ 116 क़ᓊՖխ 117 ፕխՖխ 118 קཽխ 119 Ꮥᄅխ 120 ್లխ 121 ᄅࢋխ 122 ᄅ๗խ 123 ࡵᥞխ 124 ᢅࣟխ 125 ୕ߺխ 126 ፕতԲխ 127 ፕতՖխ 128 ৠࣟՖխ 129 ֏խ 130 ࣟفխ 131 ᄅ᠆խ 132 ᄅᛜխ 133 ێতխ 134 ࠱ᥞኔխ 135 क़ᓊխ 136 խᡑխ 137 ഗၼխ 138 ֯քխ 139 ᄅێխ 140 ֮ဎխ 141 ቯᆠՖ
142 ࣳສխ 143 ᑪڠխ 144 ᄅ֏խ 145 ್ֆխ 146 ભխ 147 ፕஃՕॵխ 148 ࣨᖯխ 149 ᠆խ 150 ፕতԫխ 151 ᄘමխ 152 ৠࣟխ 153 ፕࣟՖ
154 ፕࣟխ 155 ৵ᕻխ 156 ኦ֏Ֆխ 157 ێקխ 158 ഗၼՖխ 159 دߺխ 160 ஃՕॵխ 161 ፕխԲխ 162 ॡݠխ 163 ဎխ 164 ᄻྋխ 165 Ꮥ՞խ 166 խࡉխ 167 堚ֽխ 168 Կૹխ 169 ێࣟխ 170 دߺխ 171 ᥞၺՖխ 172 ၺࣔխ 173 ८॰խ 174 ێ՞խ 175 ێઝኔխ 176 Օխᖂ 177 ոࣳխᖂ 178 ᘋဎխᖂ 179 ةؓխᖂ 180 ᇙխᖂ 181 Կૹխᖂ 182 ᠨᄻխᖂ 183 堚ֽխᖂ 184 ᄅषխᖂ 185 ८՞խᖂ 186 ࣔᐚխᖂ 187 ᥞᚡխᖂ 188 ف➧խ 189 ڜൈխᖂ 190 ߐխ 191 ௧՞խᖂ *192 ᖫࣥխᖂ 193 ࡉؓխ 194 ဎۂխ 195 ནભՖ 196 ګפխ 197 ࣪՞խ 198 Օٵխ 199 Կاխ 200 Կاխᖂ 201 փྋխ 202 խ՞խ 203 ႂՖխ 204 Օխ 205 ۫࣪խ 206 ࣔխ 207 ةਞխ 208 խإխ 209 ՛ཽխ 210 ႂխᖂ 211 קԫՖխ 212 ᄅ๗խ 213 ༚ᘋխ 214 խ՞Ֆ 215 ၺࣔխᖂ 216 ছխ 217 ᅗ壁խ ʽ218 ৬ഏխᖂ 219 ؐᛜխ 220 ګᐚխᖂ
ຏǺځύѺ*ޣǴӢΓኧ҂༤เȐ192 ᆶ 218ȑǴࡺаલѨॶೀǴ҂ӈΕϩǶ
ܢᐂ˟
˴γ˛ᕛϨᇁВᆵᆵࢄے
DMU CCRझࢄ BCCझࢄ ᇁझ
1 80.25 91 0.88186813 2 81.02 86.29 0.93892687 3 90.47 96.74 0.9351871 4 82.92 83.9 0.98831943 5 68.42 74.5 0.91838926 6 82.8 83.49 0.99173554 7 75.92 87.84 0.86429872 8 72.6 80.84 0.89807026 9 75.39 80.07 0.94155114 10 91.47 99.63 0.91809696 11 94.8 96.9 0.97832817 12 94.15 96.86 0.97202147 13 95.15 96.1 0.99011446
14 84.04 100 0.8404
15 90.92 100 0.9092
16 87.97 95.02 0.92580509 17 88.73 93.03 0.95377835 18 68.78 84.02 0.81861462 19 76.18 77.86 0.97842281 20 89.61 90.34 0.99191942
21 97.03 100 0.9703
22 75.9 85.54 0.88730419 23 77.94 90.18 0.86427146
24 89.72 89.72 1
25 97.44 100 0.9744
26 88.31 90.75 0.97311295 27 64.44 64.7 0.99598145 28 80.28 80.35 0.99912881 29 76.66 86.8 0.88317972 30 92.95 96.49 0.96331226 31 58.75 66.65 0.88147037 32 71.51 77.01 0.9285807
33 100 100 1
34 88.39 88.89 0.99437507 35 74.86 84.43 0.88665166 36 84.55 87.59 0.96529284 37 70.58 95.98 0.73536153 38 70.18 71.94 0.97553517 39 78.86 85.52 0.92212348 40 75.97 80.92 0.93882847
41 92.25 95.07 0.97033765 42 78.05 86.16 0.90587279 43 94.68 97.23 0.97377353 44 79.65 85.92 0.92702514
45 100 100 1
46 65.77 85.8 0.76655012 47 94.8 95.75 0.99007833 48 83.9 90.74 0.92461979 49 93.88 97.73 0.96060575 50 80.8 87.5 0.92342857
51 100 100 1
52 91.91 94.64 0.97115385
53 92.77 92.77 1
54 100 100 1
55 81.81 86.56 0.94512477 56 82.33 93.05 0.88479312
57 98.99 100 0.9899
58 74.8 86.85 0.86125504 59 83.83 89.07 0.94116987
60 97.35 100 0.9735
61 97.06 100 0.9706
62 91.08 92.24 0.98742411 63 79.63 85.53 0.93101836
64 100 100 1
65 73.09 93.29 0.7834709 66 83.34 93.85 0.88801279 67 78.84 82.73 0.95297957
68 100 100 1
69 85.61 93.32 0.91738105
70 100 100 1
71 83.96 87.02 0.96483567 72 86.99 90.45 0.96174682
73 100 100 1
74 79.87 81.4 0.98120393 75 78.86 87.37 0.90259815 76 98.83 98.84 0.99989883
77 93.64 100 0.9364
78 76.26 79.79 0.95575887 79 83.56 91.01 0.91814086 80 68.62 75.02 0.91468942
81 95.02 100 0.9502
82 79.21 80.86 0.97959436
83 100 100 1
84 100 100 1
85 78.98 84.57 0.93390091
86 100 100 1 87 83.94 93.23 0.90035396 88 96.71 99.35 0.97342728 89 74.63 95.41 0.78220312
90 100 100 1
91 46.08 51.67 0.89181343 92 56.63 81.64 0.69365507 93 85.89 86.77 0.98985825 94 89.23 92.62 0.96339883
95 100 100 1
96 95.01 100 0.9501
97 90.6 100 0.906
98 78.25 84.67 0.92417621 99 89.83 90.5 0.99259669 100 78.79 80.99 0.97283615
101 100 100 1
102 91.2 100 0.912
103 82.53 87.5 0.9432 104 79.89 92.46 0.86404932 105 91.75 94.32 0.97275233 106 85.39 88.63 0.96344353
107 100 100 1
108 87.21 87.58 0.99577529 109 90.15 93.71 0.96201046 110 87.23 93.41 0.93384006
111 100 100 1
112 83.43 93.98 0.88774207 113 83.25 92.38 0.90116908 114 93.48 93.63 0.99839795
115 100 100 1
116 79.21 100 0.7921 117 95.67 98.61 0.97018558
118 100 100 1
119 89.21 91.85 0.97125749
120 100 100 1
121 100 100 1
122 82.89 86.76 0.95539419 123 85.94 100 0.8594 124 86.12 89.72 0.95987517 125 99.77 100 0.9977
126 91.2 100 0.912
127 69.44 100 0.6944 128 85.85 88.65 0.96841512 129 93.1 96 0.96979167 130 84.86 89.75 0.94551532
131 90.46 93.21 0.97049673 132 82.53 87.5 0.9432 133 92.77 95.21 0.97437244 134 84.69 96.99 0.8731828
135 100 100 1
136 85.22 90.34 0.94332522 137 84.56 93 0.90924731 138 94.36 100 0.9436 139 89.03 94.91 0.93804657 140 92.6 93.75 0.98773333 141 95.69 100 0.9569 142 89.44 96.28 0.92895721 143 78.17 84.68 0.92312234 144 81.14 85.83 0.9453571 145 83.49 84.04 0.9934555 146 94.31 95.31 0.98950792
147 100 100 1
148 88.91 92.56 0.96056612
149 100 100 1
150 89.82 90.69 0.99040688 151 83.14 93.76 0.88673208 152 79.15 82.95 0.95418927
153 100 100 1
154 79.18 91.18 0.86839219 155 88.55 91.1 0.97200878 156 92.59 96.79 0.95660709
157 86.6 100 0.866
158 81.33 90.87 0.89501486 159 96.78 100 0.9678
160 100 100 1
161 100 100 1
162 88.74 89.22 0.99462004 163 96.69 100 0.9669 165 93.26 100 0.9326
166 100 100 1
167 98.04 98.14 0.99898105 169 74.75 84.25 0.88724036 170 96.78 100 0.9678
171 100 100 1
172 83.38 86.26 0.96661257 173 94.35 96.52 0.97751761 174 70.51 100 0.7051 175 79.88 82.36 0.9698883 176 97.15 100 0.9715 177 99.06 100 0.9906
179 58.55 59.14 0.99002367 181 78.15 79.58 0.98203066
182 100 100 1
183 78.07 89.38 0.87346162 185 86.69 100 0.8669 186 77.65 98.37 0.78936668
187 100 100 1
190 74.44 74.44 1
191 88.92 89.78 0.99042103 193 92.64 96.41 0.96089617 194 82.16 92 0.89304348 195 94.59 94.92 0.99652339 196 65.1 73.72 0.88307108 197 99.02 99.96 0.99059624 198 83.26 91.02 0.91474401 199 79.94 86.85 0.92043754 200 71 79.87 0.88894453 201 90.34 94.69 0.95406062 202 85.75 88 0.97443182 203 96.24 100 0.9624 204 53.13 74.46 0.71353747 206 98.87 100 0.9887 207 77.7 86.18 0.9016013 208 94.32 100 0.9432 209 74.95 82.12 0.91268875 210 84.15 84.34 0.99774721
211 100 100 1
212 100 100 1
213 87.88 92.68 0.94820889
214 100 100 1
215 85.51 85.74 0.99731747 216 84.86 90.78 0.9347874 217 93.28 100 0.9328 219 93.93 94.4 0.99502119
220 100 100 1
DMU CCRயଖ BCC யଖ ᑓய
ؓ݁ଖ 87.040381 92.0587619 0.94451752 ሒயଡᑇ 13
խ 21 ٥ૠ 34
24
խ 42 ٥ૠ 66
15
խ 22 ٥ૠ 37
