Identify and evaluate factors affecting non-oil exports using FGDM. Iran

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1 Identfy and evaluate factors affectng non-ol exports usng FGDM Sudabeh Morshedan Rafee (Ph.D.) and Zahra Houshmand Neghab Assst. Prof. & Faculty Member, Department of Commercal Management, Islamshahr Branch, Islamc Azad Unversty (IAU), Iran. E-mal: Faculty member, Department of Commercal Management, Islamshahr Branch, Islamc Azad Unversty (IAU), Iran Abstract: Economc development s one of the man obectves of every socety n the world and economc growth s fundamental to economc development. Nowadays, the nternatonal trade polcy s deemed as a key strategy n most countres, n such a manner that the process moves forward wth a speed more than producton growth of the goods and servces rendered n developed countres. Non-ol export growth s one of the effectve factors n the development of the country's economy. The am of ths study s to evaluatng the effectve factors on non-ol exports, usng fuzzy mult crtera decson makng. We contrbute non-ol exports lterature by dentfy and evaluate seven crtcal factors. The fndngs show that foregn drect nvestment, technology and qualty of products are the most mportant factors that have sgnfcant mpact on non-ol exports. [Sudabeh Morshedan Rafee (Ph.D.) and Zahra Houshmand Neghab. Identfy and evaluate factors affectng non-ol exports usng FGDM. Lfe Sc J ;():-]. (ISSN:-).. Key word: Economc growth, Non-ol exports, Fuzzy AHP, Fuzzy Delph. Introducton Economc development s one of the man obectves of every socety n the world and economc growth s fundamental to economc development. There are many contrbutors to economc growth. Export s consdered as one of the very mportant contrbutors among them. Although there s no overall consensus that support the export led economc growth, there are some economsts such as Kavouss (), Ram (), and Salvatore and Hatcher () that argue export beneft economc growth. Nowadays, the nternatonal trade polcy s deemed as a key strategy n most countres, n such a manner that the process moves forward wth a speed more than producton growth of the goods and servces rendered n developed countres. Hence, one of the effectve elements n lne wth the advancement of export development polces s the producton of compettve products at the foregn markets. Wthn the framework of tradng strateges, reducng amount of mports and puttng emphass on the ncrease of domestc products and also n lne wth alternatve polces for the mports whch necesstate the admsson of the supportve and tarff polces, and also the exports development polces as a supplementary strategy whch seeks for elmnaton of tradng obstacles and lmtatons, both of these two strateges are used for foregn exchange earnngs whch causes the mprovement of nternatonal transactons and facltates; one of the mportant economc obectves. Non-ol export growth s one of the effectve factors n the development of the country's economy. For example n developng countres, export of the agrcultural products has been consdered n order to supply the foregn currency as requred for sectors of ndustry and consumpton of the socety (Nader, ). Non-ol goods are goods produced n rural producton cooperatves, ncludng agrcultural products and crafts that can be exported abroad. Because the Iranan economy s among the ol-relant economes, ths relance on ol revenue has gone so far that many economsts consder t as the man cause of nflaton and lqudty growth. Non-ol exports are the rural producton cooperatves mportant performances whch s effectve to reduce the dependence on ol. After the frst, second, and thrd development plans, the country has not completely acheved the antcpated obectves concernng the nonol exports and they stll have a lttle share of earnngs than ol exports. Serously revsng producton process n order to mprove export's chan has become nevtable (Tavassol, ). The am of ths research s to dentfy effectve factor that have the most mpact on

2 non-ol export growth. For ths reason we use fuzzy AHP to evaluate the weght of these factors. The organzaton of ths paper s as follows. Secton dscusses the lterature revew. In Secton, we explan the process of the research, fuzzy Delph and fuzzy AHP methods. Secton s data analyss and the paper ends wth concludng remarks n secton.. Lterature revew Accordng to Mehrz (), the factors that make our falure n nternatonal markets are: clear nformaton about the market of exported goods, havng no attenton on advantage of country n export, attenton to qualty standards, defnng goals and coordnaton. Farokhan et. al., (), presented the effectve factors on ncreasng the export from the standponts ofthe Iranan exporters under a model. They found that four man factors nfluenced exports whch were: Indvdual factor (educaton, experence, export knowledge, publc communcatons), economcal factor (export markets, governmental subsdes, export prcng, export marketng), envronmental factor (rules and regulatons, culture, technology, nformal communcatons, poltcal factor) and product margnal factor (desgn and packagng, qualty of products, guarantee and after-sell servces, dstrbuton canals, products brands). In Zargarzade desgned marketng strateges for agrcultural products exporters. Accordng to hs research long term nterest of export merchants s affected by proper selecton of exportable goods and target markets regardng varety of factors and the choosng of goods and target markets should take place by consderng these factors. accordng to Aghdae and Zarden (), Lack of attenton to world economc stuaton and havng no proper marketng plan are the causes of Persan carpet retardaton but the thng whch has made the most damage to Persan handmade carpet and puts ts Export n Danger s ts Identty n Foregn Markets whch s hdden versus take carpets of compettors, for example, sometmes t happens when a buyer goes to a carpet shop n hs or her country for buyng a Persan handmade carpet, The seller nadvertently or ntentonally ntroduced some carpet whch are not really Persan carpet and have only Persan desgn and woven by Iran's competng countres such as Pakstan and Inda In, large Brazlan companes had been consdered to dentfy effectve factors on export. The results showed that the external envronment, frm characterstcs and frm strategy have mportant effect on export (Carnero et. al., ). Samm and Pekan (), n ther study mentoned nternal and external effectve factors and non-ol export development obstacles, optmze producton weakness, export organzaton weakness and as non-ol export problems through a forecastng study pattern. Ghazzade n has studed the effect of four varables ncludng target market envronment, natonal and nternal envronment of the company and mxed marketng elements. Darvshkhan n has studed the role of packng, mxed marketng elements and hygenc and nutrtous standards and proved ther postve effects on ncreasng local and global sellng from producer s perspectve. On the other hand there are a number of ways through whch Trade flows and foregn drect nvestment (FDI) can be lnked. Goldberg and Klen, () asserted that FDI may encourage export promoton, mport substtuton, or greater trade n ntermedate nputs whch often exst between parent and afflate producers. The orentaton of most nvestments by multnatonal frms s towards exports and ths may most lkely serve as a catalyst for the ntegraton of the FDI host economy to a global producton network n sectors n whch t may formerly have had no ndustral experence (OECD, ). Rodrguez Clare (); Calderón, Mortmore and Peres () argue that the very nature of the actvtes of multnatonal enterprses n Mexco could encourage the expanson of ts ndustral exports. These studes clearly ndcate that FDI could be assocated wth export trade n goods, and the host country may enoy an FDI led export growth. Goldberg and Klen (, ) do not fnd evdence to support a sgnfcant lnk between FDI and aggregate exports n Latn Amerca. Accordng to them, the trade-promotng effects of FDI appear to be weak or nsgnfcant wth regard to Latn Amercan trade wth the Unted States and Japan. Ther results also faled to fnd a systematc lnkage between sectoral trade and FDI n Latn Amerca. So accordng to lterature these factors are extracted (see table ).

3 Table ; factor affectng the non-ol exports Row Factors Row Factors Educaton Culture Experence Informal communcatons Governmental subsdes Technology Publc Desgn and communcatons packagng Exports markets Qualty of products Foregn drect Guarantee and nvestment after-sell servces Export prcng Dstrbuton canals Export marketng Products brands Rules and export knowledge regulatons.. Fuzzy logc Fuzzy set theory frst was ntroduced by Zadeh () to map lngustc varables to numercal varables wthn decson makng processes. Then the defnton of fuzzy sets were manpulated to develop Fuzzy Mult-Factors Decson Makng (FMCDM) methodology by Bellman and Zadeh () to resolve the lack of precson n assgnng mportance weghts of factors and the ratngs of alternatves aganst evaluaton factors. A fuzzy set s characterzed by a membershp functon, whch assgns to each element a grade of membershp wthn the nterval[,], ndcatng to what degree that element s a member of the set (Bevlacqua, Carapca, & Gacchetta, ). As a result, n fuzzy logc general lngustc terms such as bad, good or far could be used to capture specfcally defned numercal ntervals. A tlde wll be placed above a symbol f the symbol represents a fuzzy set. A trangular fuzzy number (TFN) M s shown n Fg.. A TFN s denoted smply l, m, u. The parametersl, m and u denote the as ( ) smallest possble value, the most promsng value and the largest possble value that descrbe a fuzzy event (Kahraman, Cebec, & Ruan, ). When l = m = u, t s a non-fuzzy number by conventon (Chan & Kumar, ). Each TFN has lnear representatons on ts left and rght sde such that ts membershp functon can be defned as (Kahraman, Cebec, & Ruan, );, x < l ( x l) ( ), l x m m l µ = () M ( u x), m x u u m, x > u Fg : A trangular fuzzy number, Cebec, & Ruan, ) (Kahraman, : multply fuzzy numbers, e.g. assumng two trangular fuzzy numbers A = ( a, b, c ), B = ( a, b, c ) A B = a a, b b c c () ( ), : dvde fuzzy numbers, e.g.: assumng two trangular fuzzy numbers A = ( a, b, c ), B = ( a, b, c ) A / B = a / a, b / b, c c () ( ) /. Methodology Ths study proposes a process ntegratng fuzzy Delph and fuzzy AHP methods to engage the challenge of factors selecton and evaluaton. Our experts are ten people of Industry, Mnes and Trade organzaton wth over years of experence n ths organzaton. Frstly we defne factors that are extracted from lterature. Then the fuzzy Delph method effectvely gathers nformaton toward developng crtcal factors. In ths problem, the relatve mportance of dfferent decson factors nvolves a hgh degree of subectve udgment and ndvdual preferences. The lngustc assessment of human feelngs and udgments are vague and t s not reasonable to represent them n terms of precse numbers. It feels more confdent to gve nterval udgments. Therefore trangular fuzzy numbers were used n ths problem to decde the prorty of one decson factors over another. The trangular fuzzy numbers were determned from revewng lterature (Kahraman, C.; Cebec, U.; Ulukan, Z., ). In order to evaluate the weghts of factors that were obtaned by fuzzy Delph method, fuzzy AHP was used.

4 .. Fuzzy Delph method: Murry et al. () proposed the concept of ntegratng the tradtonal Delph Method and the fuzzy theory to mprove the vagueness of the Delph Method. Membershp degree s used to establsh the membershp functon of each partcpant. Ishkawa et al. () further ntroduced the fuzzy theory nto the Delph Method and developed max mn and fuzzy ntegraton algorthms to predct the prevalence of computers n the future. In ths study we used Fuzzy Delph Method was proposed by Ishkawa et al. (), and t was derved from the tradtonal Delph technque and fuzzy set theory. Noorderhaben () ndcated that applyng the Fuzzy Delph Method to group decson can solve the fuzzness of common understandng of expert opnons. In ths study we use eleven experts to extract the crtcal factors of Industry, Mnes and Trade organzaton. The FDM steps are as follows: ) Collect opnons of decson group: Fnd the evaluaton score of each alternate factor s sgnfcance gven by each expert by usng lngustc varables n questonnares. ) Set up trangular fuzzy numbers: Calculate the evaluaton value of trangular fuzzy number of each alternate factor gven by experts, fnd out the sgnfcance trangular fuzzy number of the alternate factor. Ths study used the geometrc mean model of mean general model proposed by Klr and Yuan () for FDM to fnd out the common understandng of group decson. The computng formula s llustrated as follows: Assumng the evaluaton value of the sgnfcance of No. element gven by No. expert of n experts s ( a, b c ) W =,, =,,..., n,,,..., m Then the fuzzy weghtng W of No W = a, b, c, =,,..., m. ( ) Among whch a mn{ } c { } = max. () c a =. Element s n =, b = n b = ) Defuzzfcaton : Use smple center of gravty method to defuzzfy the fuzzy weght of each alternate element to defnte value followngs are obtaned: S (),, the a + b + c =, =,,..., m If If ) Screen evaluaton ndexes: Fnally proper factors can be screened out from numerous factors by settng the threshold a. The prncple of screenng s as follows:, then No. factor s the evaluaton ndex. S α S < α, then delete No. factor. Table ; Lngustc varables for mportance of each factor Absolutely approprate (,,) Approprate (,,) Slghtly approprate (,,) Neutral (,,) Slghtly napproprate (,,) Inapproprate (,,) Absolutely napproprate (,,) For the threshold value r, the / rule was adopted wth r set as.. Ths ndcated that among the factors for selecton, % of the factors account for an % degree of mportance of all the factors. The selecton factors were: If MA If MA r =., ths apprasal ndcator s accepted. r =., ths apprasal ndcator s reected... Fuzzy Analytc Herarchy Process Laarhoven and Pedrycz () proposed the Fuzzy Analytc Herarchy Process n, whch was an applcaton of the combnaton of Analytc Herarchy Process (AHP) and Fuzzy Theory. The lngustc scale of tradtonal AHP method could express the fuzzy uncertanty when a decson maker s makng a decson. Therefore, FAHP converts the opnons of experts from prevous defnte values to fuzzy numbers and membershp functons, presents trangular fuzzy numbers n pared comparson of matrces to develop FAHP, thus the opnons of experts approach human thnkng model, so as to acheve more reasonable evaluaton factors. Laarhoven and Pedrycz () proposed the FAHP, whch s to show that many concepts n the real world have fuzzness. Therefore, the opnons of decson makers are converted from prevous defnte values to fuzzy numbers and membershp numbers n FAHP, so as to present n FAHP matrx.

5 Table ; Lngustc varables for weght of each factor Extremely strong (,,) Intermedate (,,) Very strong (,,) Intermedate (,,) Strong (,,) Intermedate (,,) Moderately strong (,,) Intermedate (,,) Equally strong (,,) The steps of ths study based on FAHP method are as follows: ) Determne problems: Determne the current decson problems to be solved, so as to ensure future analyses correct; ths study dscussed the evaluaton factors for verfcaton of suppler selecton factors. ) Set up herarchy archtecture: Determne the evaluaton factors havng ndexes to be the factors layer of FAHP, for the selecton of evaluaton factors, relevant factors and feasble schemes can be found out through readng lteratures. Ths study screened the mportant factors conformng to target problems through FDM nvestgatng experts opnons, to set up the herarchy archtecture. ) Construct parwse comparson matrces among all the elements/factors n the dmensons of the herarchy system. Assgn lngustc terms to the parwse comparsons by askng whch s the more mportant of each two dmensons, as followng matrx : A = a a Λ. Λ a a = a a Λ. Λ a a a a Λ a a Λ Where a,,,,,,,,,,,,,,,,, = ) To use geometrc mean technque to defne the fuzzy geometrc mean and fuzzy weghts of each factor by Hseh et al. (). () r = ( a a... a n )n... w r r r r () ( ) = n Where a s fuzzy comparson value of dmenson to factor, thus, r s a geometrc mean of fuzzy comparson value of factor to each factor, w s the fuzzy weght of the th factor, w = lw, mw, uw. can be ndcated by a TFN, ( ) The lw, mw and uw stand for the lower, mddle, and upper values of the fuzzy weght of the th dmenson.. Data analyss Stage one: revewng relevant lterature of non-ol export and proposng mportant factors: factors for non-ol export based on relevant lterature are proposed. Stage two: Screen mportant factors by fuzzy Delph Method: Frst a DM ntervew table s setup and second ntervew was done wth ten experts from Industry, Mnes and Trade organzaton.

6 Seven factors were extracted from ths stage (see table ). Table ; the extracted factors by FDM Row Factor F: Governmental subsdes F: Foregn drect nvestment F:Rules and regulatons F:Technology F:Qualty of products F: Dstrbuton canals F: Export knowledge Stage three: The weghts of evaluaton factors We adopt fuzzy AHP method to evaluate the weghts of dfferent factors affectng non-ol export. Followng the constructon of fuzzy AHP model, t s extremely mportant that experts fll the udgment matrx. Accordng to the commttee wth ten representatves about the relatve mportant of factors, the parwse comparson matrces of factors wll be obtaned. We apply the fuzzy numbers defned n Table. We transfer the lngustc scales to the correspondng fuzzy numbers. Computng the elements of synthetc parwse comparson matrx by usng the geometrc mean method suggested by Buckley () that s: % %% % a = ( a a... a ) For example a % = ((.,.,.) (.,.,.) (.,.,.) (,,) (.,.,) (.,.,.) (.,.,.) (.,.,.) (,,) (.,.,.)) = (.,.,.) It can be obtaned the other matrx elements by the same computatonal procedure, therefore, the synthetc parwse comparson matrces of the fve representatves wll be constructed as follows matrx A:

7 F F F F F F F Table ; Fuzzy comparson matrx for the relatve mportance of factors F F F F F F F To calculate the fuzzy weghts of factors, the computatonal procedures are dsplayed as followng parts: Table ; The fuzzy comparson value of each factor among other factors For the weght of each factor, they can be done as follows:

8 We also can calculate the remanngw, there are: Table ; the weghts and rank of factors W a b c Rank Factor W... governmental subsdes W... Foregn drect nvestment W... Rules and regulatons W... Technology W... Qualty of products W... dstrbuton canals W... export knowledge. Concluson The role of exports n economc performance of developng countres has become one of the more ntensvely studed topcs n recent years. The maor mpetus for most studes on ths relatonshp s the export-led economc growth whch nterestngly represents a domnant explanaton n ths context. The performance of non-ol export sector, as ponted out earler, has however been relatvely mpressve n recent tmes. We developed non-ol export lterature by extractng and evaluatng crtcal factors that affectng non-ol export. By ths work seven factors were extracted that are; governmental subsdes, foregn drect nvestment, rules and regulatons, technology, qualty of products, dstrbuton canals and export knowledge. As t s consder n table X foregn drect nvestment, technology and qualty of products are the most mportant factor that have sgnfcant mpact on non-ol export. Furthermore lst of factors that have mpact on non-ol export were extracted from non-ol export lterature. Ths study used MADM method for the frst tme n order to extract and evaluate factors affectng non-ol export. In general, selecton problems as well as any human decson makng are vague and uncertan, and so fuzzy set theory helps to convert DM preferences and experences nto meanngful results by applyng lngustc values to measure each factor. In ths paper, a mult-crtera group decson makng model has been used based on fuzzy set theory to effcently deal wth the

9 ambguty of the decson makng problems n practcal cases to evaluate the factors. Reference Aghdae, S. F. A. and Zarden, H. Z. (), A SWOT Analyss of Persan Handmade Carpet Exports Internatonal Journal of Busness and Management Vol., No., pp -. Bellman, R., and Zadeh, L. (). Decsonmakng n a fuzzy envronment management. Scence,,. Calderón, A.; Mortmore, M. and Peres (): Foregn Investment as a Source of Internatonal Compettveness. In Dunnng J.H. and Narula (eds.) Catalyst for Economc Restructurng. Routledge, -. Carnero, J.; Rocha, A. and Slva, J. F. (), Determnants of export performance: a study of large Brazlan manufacturng frms. BAR, Braz. Adm. Rev. vol., n., pp. -. Darvsh Khan, M. (), studyng the effect of marketng management on Sohan export local and global sales ncrease, thess, economy and offcal unversty of Isfahan, p. Farokhan, S., Sadegh, T., andesmal, HRK, (). The Effectve Factors on Increasng the Export from the Iranan Exporters' Standponts. Asan Journal of Busness Management Studes (): -,. GhazZade, Mostafa (); study and determnaton of effectve factors n export company success n Iran n Mddle east and representaton of strateges for non-ol export ncrease, thess, Tehran unversty. P. Goldberg, S. and Klen, W. (): Foregn Drect Investment, Trade, and Real Exchange Rate Lnkages n Developng Countres. In Reuven Glck (ed.) Managng Captal Flows and Exchange Rates: Lessons from the Pacfc Basn. Cambrdge Unversty Press. Goldberg, S. and Klen, W. (): Internatonal Trade and Factor Moblty: an Emprcal Investgaton, NBER Workng Paper No.. Hseh, T.-Y., Lu, S.-T., & Tzeng, G.-H. (). Fuzzy MCDM approach for plannng and desgn tenders selecton n publc offce buldngs. Internatonal Journal of Proect Management,,. Ishkawa, A., Amagasa, M., Shga, T., Tomzawa, G., Tatsuta, R., & Meno, H. (). The max mn Delph method and fuzzy Delph method va fuzzy ntegraton. Fuzzy Sets and Systems,,. Kahraman, C., Cebec, U., & Ruan, D. (). Mult-attrbute comparson of caterng servce companes usng fuzzy AHP: The case of Turkey. Internatonal Journal of Producton Economcs,,. Kahraman, C.; Cebec, U.; Ulukan, Z. (). Mult-crtera suppler selecton usng fuzzy AHP. Logstcs Informaton Management,,. Kavouss, R. M., (), Export Expanson and Economc Growth: Further Emprcal Evdence, Journal of Development Economcs, vol., pp. -. Klr, G., & Yuan, B. (). Fuzzy sets and fuzzy logc Theory and applcaton. New Jersey: Prentce-Hall Inc. Laarhoven, P., & Pedrycz, W. (). A fuzzy extenson of Sat s prorty theory. Fuzzy Sets and System,,. Murry, T., Ppno, L., & Ggch, J. (). A plot study of fuzzy set modfcaton of Delph. Human Systems Management,,. Nader, A. (), comparatve advantage and export development n Iran, Insttute of Busness and Research Studes, Tehran:, p. Noorderhaben, N. (). Strategc decson makng. UK: Addson-Wesley.

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