Tài liệu Phân tích, khảo sát và xác định mô hình dự báo bán hàng cho công ty bán lẻ trang sức

ĈҤ,+Ӑ&48Ӕ&*,$73+&0 75ѬӠ1*ĈҤ,+Ӑ&%È&+.+2$ -------------------- 1*8<ӈ17+8ǣ'ѬѪ1* 3+Æ17Ë&+.+Ҧ26È79¬;È&Ĉӎ1+ 0Ð+Î1+'Ӵ%È2%È1+¬1*&+2 &Ð1*7<%È1/Ҿ75$1*6Ӭ& Chuyên ngành: Kӻ TKXұWCông NJKLӋS 0mVӕ: 8.52.01.17 /8Ұ19Ă17+Ҥ&6Ƭ 73+Ӗ&+Ë0,1+WKiQJ08 QăP2021 1 &Ð1*75Î1+ĈѬӦ&+2¬17+¬1+7Ҥ, 75ѬӠ1*ĈҤ,+Ӑ&%È&+.+2$ ±Ĉ+4*-HCM &iQEӝKѭӟQJGүQNKRDKӑF PGS.TS Ĉӛ1JӑF+LӅQ ............................. 3*676/r1JӑF4XǤQK/DP .................. &iQEӝFKҩPQKұQ[pW1: 76'ѭѫQJ4XӕF%ӱX ........................................ &iQEӝFKҩPQKұQ[pW2: 761JX\ӉQ9ҥQJ3K~F1JX\rQ ....................... /XұQYăQWKҥFVƭÿѭӧFEҧRYӋWҥLTrѭӡng Ĉҥi hӑc Bách Khoa, ĈHQG Tp. HCM ngày 15 tháng 8 QăP2027UӵFWX\ӃQ Thành phҫn Hӝi ÿӗng ÿinh giá luұn văn thҥc sƭ gӗm: 1. 76/r6RQJ7KDQK4XǤQK ...................- &KӫWӏFK 2. 761JX\ӉQ9ăQ7KjQK ........................- 7KѭNê 3. 76'ѭѫQJ4XӕF%ӱX ...........................- 3KҧQELӋQ 4. 761JX\ӉQ9ҥQJ3K~F1JX\rQ ..........- 3KҧQELӋQ 5. 3*676Ĉӛ1JӑF+LӅQ .......................- Ӫ\YLrQ Xác nhұn cӫa Chӫ tӏch Hӝi ÿӗng ÿiQh giá LV và 7UѭӣQJ.KRDTXҧQ lý chuyên ngành sau khi luұn văn ÿã ÿѭӧc sӱa chӳa (nӃu có). &+Ӫ7ӎ&++Ӝ,ĈӖ1* 75ѬӢ1*.+2$ &Ѫ.+Ë i ĈҤ,+Ӑ&48Ӕ&*,$73+&0 75ѬӠ1*ĈҤ,+Ӑ&%È&+.+2$ &Ӝ1*+Ñ$;­+Ӝ,&+Ӫ1*+Ƭ$9,ӊ71$0 ĈӝFOұS- 7ӵGR- +ҥQKSK~F NHIӊM VӨ LUҰ19Ă17+Ҥ&6Ƭ +ӑWrQKӑFYLrQ1*8<ӈ1 7+8ǣ'ѬѪ1* .......................... MSHV: 1970237 ............. 1Jj\WKiQJQăPVLQK04/09/1996 ........................................... 1ѫLVLQKBình 7KXұQ ...... Chuyên ngành: .ӻ 7KXұW&{QJ1JKLӋS .................................... 0mVӕ : 8520117............. I. 7Ç1ĈӄTÀI : Phân WtFKNKҧRViWYj[iFÿӏQKP{KuQKGӵEiREiQKjQJFKRF{QJ W\EiQOҿWUDQJVӭF ............................................................................................................................................. II. 1+,ӊ09Ө9¬1Ӝ,DUNG : ................................................................................... 0өF WLrXFӫDÿӅWjLOjWuPKLӇXYӅTX\WuQKGӵEiRFӫDF{QJW\EiQOҿWUDQJVӭFYjSKkQ WtFKKLӋQWUҥQJWuPUDYҩQÿӅ7ӯÿyÿӅ[XҩW[k\GӵQJOҥLFiFEѭӟFWURQJTX\WUuQKGӵEiR ÿӇWuPUDP{KuQKGӵEiRSKKӧSFKRWӯQJQKyPWUDQJVӭFWKHRWӯQJWKӡLÿLӇPGӵbáo. ĈӇWKӵFKLӋQPөFWLrXQKLӋPYөFӫDÿӅWjLOj - 7uPKLӇXFiFOêWKX\ӃWYjFiFQJKLrQFӭXOLrQTXDQÿӃQÿӅWjL 3KkQWtFKÿӕLWѭӧQJ[iFÿӏQKYҩQÿӅSKkQWtFKKLӋQWUҥQJYjQJX\rQQKkQJk\UD FiFYҩQÿӅ ;k\GӵQJTX\WUuQKGӵEiRÿӇWuPUDP{KuQKGӵEiRSKKӧS 3KkQWtFKNӃWTXҧFӫDQJKLrQFӭXYjÿӅ[XҩWÿӏQKKѭӟQJ ........................................ III. 1*¬<*,$21+,ӊ09Ө : 22/02/2021 .................................................................. IV. 1*¬<+2¬17+¬1+1+,ӊ09Ө: 13/6/2021 .................................................... V. &È1%Ӝ+ѬӞ1*'Ү1 .......................................................................................... PGS76Ĉӛ1JӑF+LӅQ PGS76/r1JӑF4XǤQK/DP Tp. HCM, ngày « tháng « QăP21 &È1%Ӝ+ѬӞ1*'Ү1 PGS.TS Ĉӛ1JӑF+LӅQ &È1%Ӝ+ѬӞ1*'Ү1 &+Ӫ1+,ӊ0%Ӝ0Ð1 PGS76/r1JӑF4XǤQK/DP 75ѬӢ1*.+2$&Ѫ.+Ë ii LӠI &È0Ѫ1 ChҷQJPҩ\FKӕFPj KӑFNǤ FXӕLVҳSNӃWWK~c, nhuQOҥLTXmQJWKӡLJLDQÿmTXDHPFҧPWKҩ\ UҩW WUkQWUӑQJYj ELӃWѫQ. QăPNK{QJSKҧLFKһQJÿѭӡQJGjLQKѭQJQKӳQJÿLӅXÿmKӑF ÿѭӧFQKӳQJQJѭӡLFyFѫKӝLJһSJӥVӁOX{QOjNӹQLӋPÿiQJNKҳFJKLQăPJҳQEyFQJ QJ{LWUѭӡQJQj\%iFK.KRDVӁOjQLӅPWӵKjRYuOѭXJLӳQKLӅXNKyNKăQNLrQWUuYjFӕ JҳQJ EP[LQFiPѫQFiF WKҫ\F{EӝP{Q.ӻWKXұW&{QJQJKLӋSÿmKӛWUӧFiFNLӃQWKӵFFKX\rQ QJjQKEәtFK, OjPQӅQWҧQJFKRYLӋFWKӵFKLӋQOXұQYăQFNJQJQKѭiSGөQJKӳXtFKvào công YLӋF /ӡLFiPѫQVkXVҳFÿӃQWKҫ\Ĉӛ 1JӑF+LӅQ vj cô Lê 1JӑF4XǤQK/DPÿmÿӏQKKѭӟQJÿӅ tji. CiPѫQWKҫ\ cô ÿmNLrQQKүn giҧLÿiSPӑLWKҳFPҳFWұQWunh chӍ dүQÿӇHPFy WKӇKRjn thjnh OXұQYăQ. CiPѫQWҩWFҧ DQKFKӏ và các EҥQÿDQJKӑFWұSYjQJKLrQFӭXWҥLEӝ môn, PӑLQJѭӡLOX{QJL~Sÿӥ vj ÿӗng hành cQJHPWURQJVXӕWTXi trunh. Mһc d ÿmKӃWVӭFFӕJҳQJOXұQYăQYүQNK{QJWKӇWUiQKNKӓLQKӳQJWKLӃXVyW 0RQJQKұQ ÿѭӧFQKӳQJÿyQJJySTXêJLiWӯPӑLQJѭӡL Tp. HCM, ngày 31 tháng 7 QăP21 +͕FYLrQ 1JX\͍Q7KXǤ'˱˯QJ iii TÓM TҲT LUҰ19Ă1 1JKLrQFӭXQj\VӁWUuQKEj\PӝWTX\WUuQKGӵEiRÿѭӧFVӱGөQJWURQJPӝWF{QJW\EiQOҿ ÿӗWUDQJVӭF 1KyPKjQJ76&=ӣ+ӗ&Kt0LQKÿѭӧFOӵDFKӑQÿӇWKӵFKLӋQNKҧRViWYuWӹ WUӑQJFDRQKҩWYӅVӕOѭӧQJEiQKjQJ 'RÿһFÿLӇPFӫDFKXӛLWKӡLJLDQFiFP{KuQKGӵEiRVӁÿѭӧFNKҧRViWWKHRTX\WUuQKÿӇ OӵDFKӑQSKKӧSYjVӱGөQJ6RViQKSKѭѫQJSKiSGӵEiR6$5,0$Yj+ROW-Exponential :LQWHU VÿӇÿѭDUDP{KuQKGӵEiRFyÿӝFKtQK[iFFDR. VLӋFOӵDFKӑQÿѭӧFWKӵFKLӋQEҵQJ FiFKVRViQKÿӝFKtQK[iFFӫDGӵEiRÿӇWuPUDP{KuQKGӵEiRWӕWQKҩWFKRQJKLrQFӭX 6DXNKLiSGөQJJLҧLSKiSWURQJÿӅWjLÿӝFKtQK[iFFӫDGӵEiRÿmWăQJOrQ.ӃWTXҧ FӫDQJKLrQFӭXQj\FyWKӇÿѭӧFiSGөQJFKRFiFQKyPKjQJWUDQJVӭFNKiFYӟLPӝWVӕVӱD ÿәLFҫQWKLӃW ĈLӅXQj\VӁJL~SQKjEiQOҿFKXҭQ EӏÿӫQăQJOӵFQJXӗQOӵF WURQJYLӋFOұS NӃKRҥFKKjQJKRiYjWjLFKtQK iv ABSTRACT This study would present an enhancement of the forecast process that has been used in a jewelry retailer. Group is TSCZ in Ho Chi Minh area which is the highest proportion. Thus, TSCZ is chosen in this study. Due to basic characteristics of historical time series, appropriate theoretical forecast models are used. Comparing SARIMA and Holt-Exponential Winter's Smoothing techniques in order to provide high-accuracy customer transaction forecasts. They would be ranked by comparing forecast accuracy and forecast bias to find out which one is the best forecast model for the case study. After applying the solution, the forecast accuracy was increased by 10%. The results of this study could be applied to other group with some necessary modifications. The findings would assist in more accurate financial planning and budgeting when the demand forecast was done better. v LӠI &$0Ĉ2$1 Tôi [LQFDPÿRDQÿӅWjLOXұQYăQ³Phân WtFKNKҧRViWYj[iFÿӏQKP{KuQKGӵEiR EiQKjQJFKRF{QJW\EiQOҿWUDQJVӭF´ OjF{QJWUuQKQJKLrQFӭXFiQKkQFӫDW{L WURQJWKӡLJLDQTXD0ӑLVӕOLӋXVӱGөQJYjNӃWTXҧQWKXÿѭӧFOjGRW{LWKӵFKLӋQWuP KLӇXYjQJKLrQFӭXNKiFKTXDQFyQJXӗQJӕFYj FKѭDÿѭӧFF{QJEӕ7{L[LQFKӏX KRjQWRjQWUiFKQKLӋPYӟLWK{QJWLQÿѭӧFVӱGөQJWURQJÿӅWjLQj\ Tp. HCM, ngày 31 tháng 7 QăP21 +͕FYLrQ 1JX\͍Q7KXǤ'˱˯QJ vi MӨC LӨC 1+,͎09ͬ/8̴19Ă17+̨&6Ƭ ....................................................................................ii /ͤ, &È0ˮ1 ..................................................................................................................... iii TÓM 7̶7/8̴19Ă1....................................................................................................... iv ABSTRACT .......................................................................................................................... v /ͤ, &$0Ĉ2$1 ................................................................................................................ vi 0ͬ&/ͬ& .......................................................................................................................... vii '$1+6È&+%̪1*%,͊8 ............................................................................................... ix '$1+6È&++Î1+̪1+.................................................................................................. x '$1+6È&+9,͆77̶7± 7+8̴71*Ͷ........................................................................ xi &+˰ˮ1* 1: *,͢,7+,͎8 Ĉ͈7¬, .................................................................................. 1 1.1 ĈӕLWѭӧQJQJKLrQFӭX .......................................................................................... 1 1.2 0өFWLrXOXұQYăQ ................................................................................................ 2 1.3 3KҥPYLYjJLӟLKҥQ ............................................................................................. 2 1.4 &ҩXWU~FFӫDOXұQYăQ ......................................................................................... 2 &+˰ˮ1* &ˮ 6ͦ/é7+8<͆73+˰ˮ1*3+È3/8̴1 ....................................... 3 2.1 &ѫVӣOêWKX\ӃW ..................................................................................................... 3 2.1.1 ĈӏQKQJKƭD .......................................................................................................... 3 2.1.2 Phân ORҥL ............................................................................................................. 3 2.1.3 0{KuQKWӵKӗLTX\$XWRUHJUHVVLYHPRGHO-AR) .............................................. 4 2.1.4 0{KuQKWUXQJEuQKÿӝQJ0RYLQJDYHUDJHPRGHO- MA) ................................ 5 2.1.5 Mô hình ARMA ( Autoregressive - Moving average) ...................................... 5 2.1.6 7ӏQKKRiGӳOLӋX ................................................................................................. 6 2.1.7 Mô hình ARIMA (Autoregressive Intergrated Moving Average) ..................... 6 2.1.8 0{KuQKKjPPNJ:LQWHUV .................................................................................. 7 2.1.9 6DLVӕGӵEiR ...................................................................................................... 8 2.1.10 ĈӝFKtQK[iFGӵEiR± IRUHFDVWDFFXUDQF\)$Yj[XKѭӟQJGӵEiR± forecast bias FB ........................................................................................................... 10 2.1.11 1J{QQJӳOұSWUuQK3\WKRQ ........................................................................... 10 2.1.12 4X\WUuQKGӵEiR........................................................................................... 11 2.2 3KѭѫQJ SKiSOXұQ .............................................................................................. 11 2.2.1 *LDLÿRҥQ7LӃSFұQYҩQÿӅ ........................................................................... 13 2.2.2 *LDLÿRҥQ;iFÿӏQKFiF\ӃXWӕҧQKKѭӣQJ ................................................... 13 2.2.3 *LDLÿRҥQĈӅ[XҩWP{KuQKGӵEiR .............................................................. 13 2.2.4 *LDLÿRҥQ3KkQWtFKNӃWTXҧ ......................................................................... 14 2.2.5 &iFQJKLrQFӭXOLrQTXDQ ................................................................................. 14 &+˰ˮ1* Ĉ͘,7˰ͪ1*1*+,Ç1&Ͱ8 ................................................................. 15 vii 3.1 7әQJTXDQ ........................................................................................................... 15 3.1.1 7әQJTXDQYӅF{QJW\ ....................................................................................... 15 3.1.2 7әQJTXDQYӅVҧQSKҭP ................................................................................... 16 3.1.3 7әQJTXDQYӅTX\WUuQKGӵEiR ........................................................................ 17 3.1.4 7KXWKұSVӕOLӋX ................................................................................................ 20 3.1.5 ;ӱOêVӕOLӋXYj[iFÿӏQKYҩQÿӅ ...................................................................... 20 3.1.6 ;iFÿӏQKQJX\rQQKkQ...................................................................................... 22 &+˰ˮ1* 7+,͆7.͆9¬;Æ<'͸1*48<75Î1+ ............................................. 24 4.1 ;k\GӵQJP{KuQKJLҧLSKiS............................................................................. 24 4.1.1 - 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