Application of fuzzy TOPSIS method in analyzing a construction company

Transcription

1 Extensve Journal of Appled Scences Avalable onlne at EJAS Journal ISSN Applcaton of fuzzy TOPSIS method n analyzng a constructon company E. Najaf 1 M.A Amr Bandeh 2 * 1. Department of ndustal engneerng scence and research branchislamc azad unverstytehran 2. MA Student n Ayandeghan Hgher Educaton Insttuton of Tonekabon Correspondng author: Mohammad Alrahm Amr Bandeh ABSTRACT: Numerous methods can be used to analyze strategc cases n strategc management process. Among them analyss of strengths weaknesses opportuntes and threats (SWOT) s the most commonly used method whch assesses the opportuntes threats strengths and weaknesses of an organzaton. SWOT analyss s a crucal support tool for decson makng whch often used as a tool for systematcally analyss of an organzaton's nternal and external envronments. The purpose of analyzng external opportuntes and threats s to assess whether an organzaton can take advantage of opportuntes and defeat the threats when faced wth an uncontrollable external envronment such as prce changes poltcal nstablty socal transfers and foregn markets or not. Snce plannng processes wth multple varables are often complex the use of SWOT s not enough. In other words SWOT analyss cannot provde an analytcal tool for achevng the rankng and effcency of each SWOT factor. Therefore SWOT analyss cannot measure the approprateness of decson-makng alternatves based on these factors. The purpose of present study was to analyze a constructon company usng the fuzzy TOPSIS method. Keywords: fuzzy TOPSIS SWOT analyss INTRODUCTION A'WOT s the frst quanttatve SWOT method whch leads to AHP ntegraton and has been provded by (Cortla et al. 2000). There are also other artcles have demonstrated the uses of A-WOT (Shno and et al. 2006; Cajanos et al. 2004; Stersta et al. 2004). (Uxel and Daqduyern 2007) proposed Network Analyss Process (ANP) as a developed method of SWOT-AHP aggregaton to ntegrate t wth SWOT analyss. Other quanttatve SWOT technques have been suggested wth or wthout uncertanty consderatons. However the applcaton of the quanttatve SWOT method n energy desgn topcs s relatvely rare (Dyudo and Alau Alapat 2007). The SWOT-TOPSIS ntegraton method has also rarely been used n related lterature (Chalk 2009). In present study a SWOT-Fuzzy TOPSIS approach combned wth AHP has been proposed to use n structurng and prortzng SWOT factors for electrcty power supply chan. AHP method s used to determne relatve mportance of factors n each SWOT group as well as relatve mportance of factors among SWOT groups whle Fuzzy TOPSIS s used to assess electrcty power supply chan n presence of SWOT factors. Some of the basc features of AHP would be explaned based on the content of (Wnston 2004) and wth respect to AHP wthn each SWOT group. Accordngly SWOT factors n a group were evaluated usng bnary comparson matrx. It s mportant to note that the upper part of comparson matrx s trangles and ts lower part s symmetrc trangle. Then each column of comparson matrx was normalzed two by two through dvdng each element of that column nto sum of the elements. The mean arthmetc of elements n each normalzed matrx lne can be used to approxmately calculate the relatve mportance weght of each SWOT factor n the SWOT group. Constancy of results must be nvestgated and the constancy ndex (CI) should not exceed 0.1 (Wnston 2004). Cortla et al have suggested that AHP should nvolve an agent factor representng each SWOT group among SWOT groups n a way that the agent factor must have the hghest score of mportance. A quanttatve method of SWOT analyss provdes more detaled data for SWOT analyss. Ths approach adapts tself wth MADM decson-makng method whch uses mult-layered plans to smplfy complex ssues and thus t s enable to smultaneously mplement SWOT analyss on several organzatons (Saat and Vargasaral 2001). Plannng processes can be complcated by multple crtera due the napproprate utlzaton of SWOT. The matter ndcates that an unspecfed qualtatve and ncomplete lst of nfluental factors of nternal and external envronment has been used n the organzaton.

2 Ext J App Sc. 5 (2): Among methods utlzng from SWOT analyss one can refer to External Factor Evaluaton Matrx (EFE) Internal Factor Evaluaton Matrx (IFE) and Compettve Plan Matrx (CPM). However the followng shortcomngs are unavodable n all of them. The rankng of key factors s done objectvely. Therefore some troubles may be found n the quanttatve data ratng such as the volume of trade. 1. In objectve ratng of the data the evaluators group rate data wthout testng whch can lead to data ntegrty. To overcome these problems Cartla et al. and Stewart et al. combned AHP herarchy process analyss wth SWOT analyss and created a new combned method for mprovng envronmental analyss n the SWOT approach. Also n some cases SWOT analyss has been developed based on the GSM strategy matrx. Integraton of BSC's Balanced Scorecard SWOT Matrx leads to creaton of an ntegrated and holstc strategc management system. SWOT matrx can clearly determne the success factors used to dentfy the Balanced Scorecard (Ipp and Co 2006) and accordngly dentfy a structural approach to formulate adjust and develop opportuntes and threats as lke all compettors. An organzaton can balance ts strengths aganst weaknesses of compettors by lnkng SWOT and BSC analyss (Ipp and Co 2006) and try to optmal and effcent use of market opportuntes. 2. The man problem SWOT was frstly ntroduced n 1950 by two graduates of Harvard Busness School named George Albert Smth and Rowland Chrstensen (Chang and Huang 2006). At the tme ths analyss was recognzed as a useful management tool an addton to gan ncreasng successes. But perhaps the most vsble success of ths analyss was acheved when Jack Welch from General Electrc used t n the 1980s to examne GE's strateges and ncrease the productvty of hs organzaton. The steps of carryng out the analyss nclude: 1. Conductng a meetng of analyss. 2. Provdng a bref overvew from the purposes of sesson and the nvolved steps. 3. Utlzng from branstorm method to dentfy the strengths and weaknesses and opportuntes and threats. 4. Prortzng nternal and external factors. 5. Formaton of matrx. 6. Comparng nternal and external factors wth each other and determnng strateges 7. Determnng the requred measurements of carryng out specfed strateges 8. Performng measurements and nvestgatng ther results. 9. Updatng matrx at approprate ntervals. Dsplay the matrces used n the analyss method Prorty matrx of nternal factors Effect on compettve performance and capablty of the company Low Medum Hgh Medum prorty top prorty top prorty hgh Low prorty Medum prorty top prorty medum Low prorty Low prorty Medum prorty low Level of Importance Prorty matrx for external factors Possble effect on the company Low Medum hgh Medum prorty top prorty top prorty hgh Low prorty Medum prorty top prorty Medum Low prorty Low prorty Medum prorty Low Probablty of occurrence weakness Lst of weaknesses WO strateges Use opportuntes to elmnate weaknesses WT strateges Reduce weaknesses and avod threats SWOT matrx strength Lst of strengths SO strateges Take benefts of opportuntes wth the strengths ST strategy Use strength to avod threats. SWOT Opportuntes Lst of opportuntes Threats Lst of threats 3. Importance and necessty Fnancal frms especally constructon companes are very mportant due to ther drect and sgnfcant mpact on economc and socal development of countres. Because one of the success factors of advanced countres s payng attenton to the effcency of economc unts especally constructon companes. In ths analyss nsttutes are one of the effectve tools of management. In present study a quanttatve framework was proposed to develop a strategy for analyzng an actve constructon company n the feld of dam constructon 50

3 Ext J App Sc. 5 (2): buldng and road constructon. Accordng to the strategc management topcs questonnares should be desgned and data prepared to wegh Fuzzy models. In ths framework SWOT factors were extracted from suggested qualtatve framework elements. SWOT analyss s a structured approach to evaluate a structure n comparson wth nternal and external envronments. By dentfyng the factors n the SWOT matrx a functonal plan can be developed wth added strength as well as weaknesses can be elmnated or mnmzed opportuntes can be deployed and threats can be dentfed. However SWOT qualtatve matrx s nadequate and neffcent n many cases due to the lack of prortzaton of SWOT factors. Therefore dentfyng strength-weakness- opportunty and threat of a constructon company and ts analyss are absolutely necessary to mprove ts performance Rankng SWOT Groups The most mportant factors of each group have been dentfed based on tables presented n the prevous secton. In ths secton a pared comparson was performed by the experts between the same factors as agent of four SWOT groups based on AHP method. Ths analyss was based on data obtaned from the questonnare number (2) whch has been completed by experts n second step. In ths secton the scores and weghts of dfferent groups of SWOTs were specfed whch ts fnal results have been represented n Table (3-1). Table (3-1) AHP analyss results on quartet groups of SWOT S K=S 1 W K=W 5 O K=O 4 T K=T 1 WG S K=S W K=W O K=O T K=T CI As t can be seen the commtment factor and long-term safety of structure have been recognzed as the most mportant factor n all groups wth hgh prorty accordng to the data from questonnare number(2).the reason of ths matter can be the fact that the most mportant factor for the development and promoton of a constructon company n vewpont of experts and drectors s to ensure about carryng out the work correctly and f the qualty of a company's work s so hgh that employers have enough trust n a company t can have hgh effcency. Accordng to the table factors of sudden prce changes n housng market and materals fnancal problems and lack of the tmely collecton of clams are placed n next rank of mportance. In addton accordng to ths rankng experts beleve that among four groups of SWOT analyss ncludng strengths weaknesses opportuntes and threats the strength group s the most mportant one and t means that constructon companes need to focus on ther strength to acheve the most postve outcomes. After ths group the threat group has the hghest degree of mportance whch ndcates the need of addressng threats facng each constructon company so that they can take approprate actons for each of the threats. In addton to the results mentoned above the score of each group was also determned based on ths table. Accordngly the prorty order of these groups s as follow: S > T > W > O Strengths > Threats > Weaknesses > Opportuntes The specfed scores are used as a prorty factor of groups Calculatng the relatve mportance or weght of each factor In ths secton of study the prorty and mportance of factors have been ntroduced based on a coeffcent. Ths coeffcent s the result of multplcaton of factors' number n each group n the number from rankng of the groups whch s calculated accordng to equaton (4-1). w = w (SWOT) w G (3-2) As a result the weght of factors would be as followng table: 51

4 Ext J App Sc. 5 (2): Table (3-2) Weght of SWOT factors based on AHP analyss Factors w (SWOT) w G w S S W W W W W W O O O O T T T The crcular dagram of factors' weght has been shown n Fgure (4-1) to compare them wth each other calculatng the value vector (matrx of values) The matrx of values was prepared based on questonnare number (3). In ths secton as n the prevous sectons whch t was needed to nterpret the questonnare data obtaned from questonnare were nvestgated and dstorted data were removed from calculatons and rest of them were averaged and rounded. The matrx of values calculated from questonnare and fuzzy numbers correspondng to the qualtatve scorng have been presented n Table (4-9) separately. The correspondng fuzzy numbers have been allocated to factors accordng to Deng Feng's artcle (2007) whch has studed fuzzy numbers wth qualtatve varables. Factors Table (3-3) Matrx of values or value vector of factors Average numbers Value or quantty of calculated form the factors(qualtatve) questonnares The correspondng fuzzy number S medum S medum W medum W Farly poor 52

5 Ext J App Sc. 5 (2): W Farly poor W medum W Farly poor W medum O medum O very strong ( ) O Farly strong ( ) O Very strong ( ) T poor ( ) T poor ( ) T Very poor ( ) As t can be seen the factors of Iranan companes enterng nto countres of the regon to carry out great projects and approprate locaton of the company (proxmty to captal) are the most effectve and mportant factor n the vew pont of experts of under study company. In fact ths factor s very evdent n the company and most of ts engneers and executves feel that ths factor s hghly felt n the company. It means that the experts of Iranan companes beleve that enterng to foregn projects and good locaton are a great opportunty for companes to progress and feel that attenton and plannng for these two factors wth regard to power and staffs are the best optons for companes and the most approprate decson to ncrease profts and effcency. In contrast the factors of ncrease n the number of cvl engneers and consequently ncrease n the number of cvl engneerng companes and nstablty of domestc and foregn polces of the country and sudden decsons n macro dmensons are rarely felt n the company or n the other words they are not effectve parameters n ths company. The reason for ths judgment by engneers and company executves s that the actvtes of ths company are not affected by these threats or t s felt that the severty of these threats s low n the country. Consderng the nternal and external ssues related to the company and ts strength and hstory experts and drectors of the company beleve that they should pay attenton to opportuntes frst of all and then plan to use these opportuntes n order to enhance the company. Then they can use ther strength and try to strengthen them. The next step s to plan for solvng weaknesses and reducng them and fnally puttng n place optons to deal wth threats. 3-4 normalzng the amounts of value vector At ths step of analyss the vector values of e factors became dmensonless for the possblty of comparng two factors of dfferent values wth dfferent dmensons. Ths acton n fuzzy TOPSIS method s n two dfferent modes as follows: If the factor n s cost.e. ts lower value s more favorable then: n = ( mn {e 1 } e 4 mn {e 1 } e 3 mn {e 1 } e 2 mn {e 1 } e 1 ) If the n factor s proft.e. ts greater value s more favorable then: n = ( e 1 max {e 4 } e 2 max {e 4 } e 3 max {e 4 } e 4 max {e 4 } ) The normalzed amount of value vector of each factor was calculated usng equatons and whch the results of the calculatons have been presented n Table (4-10). 53

6 Ext J App Sc. 5 (2): Table 3-4 Normalzed amounts of value vector of factors Factors Intal value vector Type of factor Normalzed value vector S 1 proft ( ) S 2 proft ( ) W 1 ( ) W 2 ( ) W 3 ( ) W 4 ( ) W 5 ( ) W 6 ( ) O 1 proft ( ) O 2 ( ) proft ( ) O 3 ( ) proft ( ) O 4 ( ) proft ( ) T 1 ( ) T 2 ( ) T 3 ( ) As t can be seen strengths and opportuntes are from proft type and t means that ther strength s more desrable. In contrast weaknesses and threats are from cost type and t means that ther weaknesses and the low effectveness are more desrable. The clusterng was completely expected takng nto account relatve mportance n value vector (amounts' vector) To ncrease the accuracy and effcency of present study before carryng out fnal steps of fuzzy TOPSIS method values vector was weghted usng coeffcents obtaned n the AHP analyss. In fact the effect of each factor on decson-makng was modfed based on ts relatve mportance to other factors. To apply ths effect value vector of each factor was multpled n ts relatve mportance (weghtng coeffcent) whch has been presented n Table (4-8). As a result: n w = n w 3-5 Accordng to equaton (3-5) the vector value of factors would be as Table (3-5). Table 5-3 weghted amounts of value vector of factors based on mportance of coeffcent Factors S 1 Normal value vector ( ) Weghted value vector ( ) S 2 ( ) ( ) W 1 ( ) ( ) W 2 ( ) ( ) 54

7 Ext J App Sc. 5 (2): W 3 ( ) ( ) W 4 ( ) ( ) W 5 ( ) ( ) W 6 ( ) ( ) O 1 ( ) ( ) O 2 ( ) ( ) O 3 ( ) ( ) O 4 ( ) ( ) T 1 ( ) T 2 ( ) T 3 ( ) Table 5-3 shows the weghted vector values. These numbers ndcate the matter that both of relatve mportance to each of the other factors and the mportance of quartet groups of SWOT have been taken nto account n value of each factor dentfyng the most deal and most unfavorable opton Accordng to the fuzzy TOPSIS method the most deal opton and the most unfavorable opton are defned as follow: The most deal mode: n p = (1111) The most unfavorable mode: n n = (0000) The maxmum deal opton s a fuzzy number n the fuzzy doman (accordng to the defnton of the fuzzy number [0 and 1]) sgned wth n pand the mnmum unfavorable opton s a fuzzy number n the fuzzy doman sgned wth n n 4. Results In the rankng based on AHP analyss for each of the strengths weaknesses opportuntes and threat groups followng factors were evaluated as the most mportant and superor factor n each group. In the strengths group: long-term commtment and long-term safety of the structure In the weaknesses group: fnancal problems and lack of tmely collecton of clams In the opportuntes group: enterng of Iranan companes to countres of the regon to carry out great projects In the group of threats: sudden prce changes n the housng market and materals 2. In rankng groups wth AHP prorty order of groups was obtaned as follow by pared comparson of the most mportant factors of each group as agent of that group. Strengths Threats Weaknesses Opportuntes 3. Based on combnng the coeffcent of mportance of each factor wth the mportance of ts group hghmportance factors would be as follow: 1. Long-term commtment and long-term safety of the structure 2. Prce changes n the housng and materal market 3. The nstablty of domestc and foregn polces of the country and sudden decsons on macro dmensons 4. Use of equpment regulatons desgn methods and up-to-date cvl engneerng software 4. In the survey for the extent of effect and beng clear of factor n the company three of the factors earned the hghest score respectvely (.e. drectors and experts of Aradze Alborz Company consdered these optons as mportant factors for the company). 1. Enterng of Iranan companes to countres of the regon to carry out great projects 2. Approprate locaton of the company (Proxmty to the captal) 55

8 Ext J App Sc. 5 (2): Frequency and varety n materals and methods of constructon 5. In rankng based on fuzzy TOPSIS method and usng CC coeffcent four mportant factors were places n mportance levels of 1 to 4 as follow: 1. Long-term commtment and long-term safety of the structure 2. Prce changes n the housng market and materals 3. Use of equpment regulatons desgn methods and up-to-date cvl engneerng software 4. Enterng of Iranan companes to countres of the regon to carry out great projects 6. In both rankngs based on fuzzy AHP and TOPSIS commtment factors and long-term guarantee of structural safety and sudden prce changes n housng market and materals were placed the hghest level of mportance. 7. Except than factors mentoned n the precedng paragraph the remanng of factors used n two methods had no same rank. 8. In AHP method the most emphass s on groups of strengths and then on threats and weaknesses whle n fuzzy TOPSIS method the most emphass s agan on strengths opportuntes and threats wth almost equal mportance are n the next place and after them the emphass s on weaknesses. REFERENCES AndersenT.J. (2004) Integratng the strategy formaton process Internatonal Perspectve; European Management JournalVol.22pp: Arslan O. & Er I. D. (2008). SWOT analyss for safer carrage of bulk lqud chemcals n tankers. Journal of Hazardous Materals 154(1) Bates A. W. (2000). Managng Technologcal Change: Strateges for College and Unversty Leaders.The Jossey-Bass Hgher and Adult Educaton Seres Jossey-Bass Publshers 350 Sansome St San Francsco CA Baumgarten H. (2000). Termnologe der Logstk und de herarchsche Enordnung n das Unternehmen. Logstk-Management Strategen- Konzepte- Praxsbespele Beggs C. Utlty companes and energy supply. Energy Manage Conserv Bowersox DJ Closs DJ Cooper MB. Supply chan logstcs management. 3rd ed. Boston: McGraw-Hll/Irwn; Bryson JM. [Strategc plannng for publc and non proft organzaton] (Trans by Monavaran A) 2nd ed. Tehran: State Management Tranng Center; [Persan] Bujs P Bekaert D Cole S Hertem DV Belmans R. Transmsson nvestment problems n Europe: gong beyond standard solutons. Energy Polcy 2011; Büyüközkan G. & şakr Ersoy M. (2009). Applyng fuzzy decson makng approach to IT outsourcng suppler selecton system 2 2 Byars L. L. (1991). Strategc management: formulaton and mplementaton; concepts and cases. Harper Collns Celk M Ceb S Kahraman C Er ID. Applcaton of axomatc desgn and TOPSIS methodologes under fuzzy envronment for proposng compettve strateges on Turksh contaner ports n martme transportaton network Expert Syst Appl 2009;36: Chang HH Huang WC. Applcaton of a quantfcaton SWOT analytcal method.math Comput Model 2006;43: Chang H. H. & Huang W. C. (2006). Applcaton of a quantfcaton SWOT analytcal method Mathematcal and computer modellng 43(1) Chang Hsu- Hs- Huang Wen-chn. Applcaton of a quantfcaton SWOT analytcal method (2005) Chen C. B. & Klen C. M. (1997). An effcent approach to solvng fuzzy MADM problems Fuzzy Sets and Systems 88(1) ChenL.H. and WengM.C.(2006) An evaluaton approach to engneerng desgn n QFD processes usng fuzzy goal programmng models European Journal of Operatonal ResearchVol 172 pp: Councl S. C. (2008). Supply-chan operatons reference-model Overvew of SCOR verson 5(0) Davd F. R. (2011). Strategc management: Concepts and cases. Peaeson/Prentce Hall Davd F. R. (2011). Strategc management: Concepts and cases. Peaeson/Prentce Hall Davd M. E. Davd F. R. & Davd F. R. (2009). The Quanttatve Strategc Plannng Matrx (QSPM) appled to a retal computer store. The Coastal Busness Journal 8(1)