Grey Model for Evaluation and Analysis of Competitiveness in the Packaging and Testing Industry

Transcription

1 Interntionl Journl of Mngement, Economics nd Socil Sciences 2016, Vol.5(3), pp ISSN Grey Model for Evlution nd Anlysis of Competitiveness in the Pckging nd Testing Industry Chong-Rong Hung Kuo-Wei Lin* Dept. of Business Administrtion, Hsun Chung University, Hsinchu City, Tiwn The integrted circuit (IC) pckging nd testing industry is n importnt link in the semiconductor industril chin tht my decide the success or filure of the foundry industry. The purpose of this study ws to compre the competitiveness of the pckging nd testing industry in the rer section of the foundry process in Tiwn. Strting from the finncil dt of si listed compnies nd using Grey theory, this study summrizes their five fctors of competition: scle, growth, profit, efficiency nd risks. The study confirmed tht the model is ble to effectively compre the competitiveness of corportions in the sme industry. Keywords: Competitiveness, foundry, outsourced ssembly nd test, finncil nlysis, grey theory JEL: C02, C60 Semiconductor refers to substnce tht cn conduct electric current under some circumstnces, while it cn be used s n insultor under other circumstnces (Bouguezzi et l., 2016; Tirkel, 2013). An integrted circuit (IC) mens tht on semiconductor substrte, mny electronic circuits re combined into vrious electronic components, such s diodes nd trnsistors through oidtion, etching, nd diffusion, nd lminted onto smll re to complete certin logic functions (AND, OR, NAND etc.) nd to further chieve pre-set circuit functions (Wng nd Pn, 2016; Zho nd Wu, 2016). The rw mteril of semiconductor is silicon of snd. Silicon itself is n insultor, but if we dd smll mount of impurity toms, it will become little conductive, but not too conductive, semiconductor (Li nd Schlichtmnn, 2015). If we further divide smll silicon into severl res nd dd different impurity toms into ech re, the semiconductor turns into very smll volume of current switch through this specil design. After combining different kinds of switches, firm cn produce chip used for mobile phones or computers with vrious zoom nd control functions. The semiconductor industry chin includes the IP (Intellectul Property) design industry nd the IC design industry in the upstrem; IC mnufcturing, wfer fbriction nd relted production processes nd testing equipment, photo msk, nd other businesses in the midstrem; nd the IC pckging nd testing industry Mnuscript received June, 4, 2016; revised September 5, 2016; ccepted September 11, The Authors; CC BY-NC; Licensee IJMESS *Corresponding uthor: scholrte@gmil.com in the downstrem (Cesroni nd Picclug, 2013). The most importnt industry here is IC

2 Interntionl Journl of Mngement, Economics nd Socil Sciences 88 pckging nd testing, becuse it ultimtely my decide the success or filure of semiconductor product. IC pckging uses plstic, cermic, or metl substnce to cot the grin of finished wfer so tht the grin cn void contmintion nd be esily ssembled. This industry lso helps to design for chieving better effects of electricl connection nd het rdition from the wfer nd electronic system. IC testing cn be divided into two stges. One is the wfer testing before pckging, which minly tests the electric properties. The other is the IC finished product test, which minly tests IC functions nd whether the electric properties nd het rdition re norml so s to ensure product qulity. The IC pckging nd testing industry in Tiwn is the globl industry leder. Its yerly output vlue of over $10 billion mkes gret contribution to the economic development of Tiwn. Therefore, this study estblishes Grey theory model to compre the competitiveness of Tiwn s IC pckging nd testing industry. Grey Competitive Model Prior reserch indictes tht Grey theory cn be effectively pplied to overcome unpredictbility problems in cses of discrete dt nd deficient generte stisfctory consequence utilizing reltively smll mount of dt or with gret fctors vribility (Thkur nd Anbnndm, 2015). Lin et l. (2012) used the TOPSIS model to nlyze the competitiveness of five utomkers in Tiwn. Following tht, Lin et l. (2013) employed Grey theory model to compre the competitiveness of ten semiconductor mnufcturing firms in Tiwn. Both models obtined good results. Thus, this study once more utilizes Deng s (1989) Grey theory to nlyze the competitiveness of the pckging nd testing industry in the rer section of foundry process in Tiwn. The study steps re given below: - Construction of Decision Mtri A decision mtri is list of vlues tht helps decision mkers to identify nd nlyze sets of informtion nd further develops list of options (Co et l., 2015; Gul nd Guneri, 2016). A list of weighted criteri were estblished in this study nd ech option ginst those criteri ws evluted. After evluting ech lterntive, performnce vlues of ech ttribute were obtined nd with them we construct decision mtri shown in Tble 1. Alterntive C 1 C 2 C 3 C n A n A n A 3 A m informtion (Resh et l., 2015). The key n : : : : : : m1 m2 m3 Tble 1: Decision Mtri mn Ech lterntive hs n pprisl inde nd could dvntge of grey theory is tht it is relible to be written s:

3 89 Hung nd Lin A,,,...,,..., ] (1) i [ i1 i2 i3 in re ble to obtin the normlized vlue of the In the A i study, is the i th corportion th competitiveness inde of the i th corportion. tht ws pprised nd compred, C is the th Here, is the competition comprison inde competitiveness indictor, nd is the performnce vlue of the th indictor of the i th corportion. - Normlized Decision Mtri competitiveness Becuse the mgnitude order of ech comprison inde is different, if we put them on the sme stndrd for comprison, then it is not fir nd ustified. Hence, we hve to first normlize the vlues. In this study, we mke reference to the method introduced by Jing et l. (1988) nd seprtely use the higher the better nd the lower the better models to process ech element of vrious comprison indices ccording to the ttribute of the inde. The trget model of the higher the better is: min i m min i i (2) The trget model of the lower the better is: m i m min i i (3) In this study, ecept for the equity multiplier tht is the trget model of the lower the better, ll the other comprison indices re trget models of the higher the better. Therefore, we vlue fter the normliztion process. - Determine the Obect Weight Becuse the importnce of ech comprison inde is different, we hve to give ech inde weight w nd hve to stisfy the rule tht the totl vlue of ll weights should be equl to 1. n 1 w 1 (4) Dikoulki et l. (1995) rgued tht when the looser the results mesured by group of indices re, the higher the importnce will be for the group of mesurement indices, nd so when the stndrd devition is higher, the greter the weight will be. Therefore, when determining the weight vlue, one must first obtin the stndrd devition of ech mesurement inde. The weight vlue of ech mesurement inde cn then be obtined with the following formul. w n 1 - Estblish Stndrd Alterntive A 0 (5) The stndrd lterntive is the lterntive with the vlues of the best condition picked from ech comprison inde. It is defined s: A,,,..., ] (6) 0 [ n In this study, the best inde vlue is the mimum vlue of ech competitiveness

4 Interntionl Journl of Mngement, Economics nd Socil Sciences 90 comprison inde fter the normliztion process - tht is: 0 i 1,2,3,..., m m i (7) - Estblish Difference Mtri We now clculte the difference between ech inde nd stndrd lterntive inde to the following difference mtri: Note tht m m m n 2n 3n is the difference between the th competitiveness comprison inde of the i th corportion nd the stndrd lterntive inde fter the normliztion process - tht is: (9) 0. mn Here, m is the mimum vlue of the difference mtri. Note tht [ 0,1 ] is the identifiction coefficient designed to dust the difference between the vlues of the individul Grey reltion coefficients. It usully tkes the vlue of Obtin Grey Reltionl Grde The correltion between ech lterntive nd stndrd lterntive is obtined through the following formul: Here, i th n R i w (13) 1 R i is the Grey reltionl grde between the corportion nd the stndrd lterntive. A greter vlue represents tht the corportion is closer to the stndrd lterntive, nd the performnce vlue of their competitiveness comprison will be higher. - Clculte Grey Reltionl Coefficient The Grey reltionl coefficient of the competitiveness inde of the i th corportion nd stndrd lterntive inde is obtined by following formul: min m (10) In which: min Here, minmin i m i 1,2,3,..., m, 1,2,3,..., n (11) min is the minimum vlue of the difference mtri. m mm i i 1,2,3,..., m, 1,2,3,..., n (12) th Selection for Competitiveness Indictors Evlution Jin (2004) pointed out tht the comprisons of enterprise competitiveness in Chin should include four fctors: scle, growth, profit, nd brnd. However, becuse the mesurement vlue of the indictor of brnd fctor does not esily estblish n obective stndrd mesurement, this study therefore mkes reference to the model of Lin et l. (2012, 2013), who divided the comprison inde into five fctors: scle, growth, profit, efficiency, nd risks. Tble 2 shows the evlution indictors of ech fctor nd clcultion.

5 91 Hung nd Lin According to the trget methods of the higher Ctegory Rtio Formul Scle Fctor Fctor Fctor Efficiency Fctor Risk Fctor Revenue Scle 2014 Revenue / Totl 2014 Revenue of ll Enterprises Scle 2014 / Totl 2014 of ll Enterprises Scle 2014 / Totl 2014 of ll Enterprises Revenue (2014 Revenue / 2013 Revenue) - 1 (2014 / 2013 ) 1 (2014 / 2013 Equ ity) - 1 ROA 2014 Net / 2014 Averge Asset ROE 2014 Net / 2014 Averge Mrgin 2014 Net / 2014 Revenue Asset 2014 Revenue / 2014 Averge Asset Accounts Receivble 2014 Revenue / 2014 Averge Accounts Receivble Inventory 2014 Cost / 2014 Averge Inventory Mu ltiplier 2014 Assets / 2014 Current Rtio 2014 Current Assets / 2014 Current Libility Tble 2: Definitions of Evlution Indictors for the Five Fctors Appliction of Grey Competitiveness Model In this study we selected si listed pckging nd testing firms from the foundry industry of Tiwn. They re Advnced Semiconductor Mnufcturing Co. (ASE), Siliconwre Precision Industry Co., Ltd. (SPIL), Powertech Technology Co., Ltd. (PTI), ChipMos Technologies Ltd. (Chip MOS), Chipbond Science nd Technology Co., Ltd. (Chipbond), nd King Yun Electronics Co., Ltd. (KYEC Group). We etrcted dt from their public finncil sttements (see Tble 3) to eplore ech corportion s competitiveness. the better nd the lower the better s shown in formul (2) nd formul (3), we net normlized the dt s shown in Tble 4. Ecept for the equity multiplier evlution indictor in the risk fctor tht hs to be clculted ccording to the trget method of the lower the better s given in formul (3), the rest of the evlution indictors re the greter the more competitive, which hve to be clculted ccording to the trget method of the higher the better. Thus we obtined the normlized dt s shown in Tble 5. We further clculted the stndrd Enterprise Revenue Asset Cost Accounts Current Current Inventory Receivble Assets Libilities ASE Group 8,465, ,153 11,018,630 5,227,239 6,699,230 1,746,002 1,456,615 5,277,358 3,668,774 SPIL 2,740, ,044 4,280,860 2,379,179 2,048, , ,546 1,821, ,901 PTI 1,321, ,048 2,291,449 1,304,597 1,101, ,633 85, , ,779 Chip MOS 726, ,302 1,142, , , ,872 56, , ,284 Chipbond 583,412 87,210 1,322, , , ,561 33, , ,269 KYEC Group 537,048 84,453 1,310, , , ,308 9, , ,143 Tble3: Dt on Enterprises Opertionl Performnces in 2014 (US$ thousnd) Clculting the finncil dt of the si listed compnies in Tble 3 ccording to the methods shown in Tble 2, we obtined the decision mtri shown in Tble 4. devition of ech evlution indictor from the normlized dt nd then substitute them into formul (5) to obtin the weight vlue of ech evlution indictor.

6 92 Interntionl Journl of Mngement, Economics nd Socil Sciences Becuse the optiml vlue fter normliztion Scle Fctor Fctor Fctor Efficiency Fctor Risk Fctor Revenue Enterprise Revenue Scle Scle Scle ROA ROE Mrgin Asset Accounts Inventory Receivble Multiplier ASE Group SPIL PTI Chip MOS Chipbond KYEC Group Tble 4: Decision Mtri of Business Competitiveness Comprison Indices Current Rtio Scle Fctor Fctor Fctor Efficiency Fctor Risk Fctor Revenue Enterprise Revenue ROA ROE Scle Scle Scle Mrgin Accounts Asset Inventory Current Receivble Multiplier Rtio ASE Group SPIL PTI Chip MOS Chipbond KYEC Group Stndrd Devition Weighting Tble 5: Normlized Compring Indices should be 1, the vlue of ech element in stndrd lterntive A 0, which ws estblished by formul (6), is 1. We now substitute them into formul (8) nd formul (9) nd estblish the difference mtri s shown in Tble 6. in Tble 7. We then multiply the Grey reltionl coefficient by the weight vlue in Tble 1 nd sum them up through formul (13) to figure out the Grey reltionl grde given in Tble 7. A higher vlue represents being closer to the Enterprise Revenue Scle Scle Fctor Fctor Fctor Efficiency Fctor Risk Fctor Scle Scle Revenue From Tble 6, we cn see tht min 0 nd ROA ROE Mrgin Asset Accounts Receivble Inventory Multiplier ASE Group SPIL PTI Chip MOS Chipbond KYEC Group Tble 6: Difference Mtri with Stndrd Inde Difference Current Rtio stndrd lterntive nd denotes corportion 1 m. Substituting ech vlue into formul (10), we net obtin the Grey reltionl coefficient with higher competitiveness. From Tble 7, we note tht the top one is ASE, followed in order by

7 93 Hung nd Lin Chip MOS, SPIL, KYEC, PTI, nd Chipbond. fctor being rnked in lst plce, it hs Scle Fctor Fctor Fctor Efficiency Fctor Risk Fctor Grey Revenue Accounts Enterprise Revenue Asset Inventory Current Reltionl Rnk ROA ROE Receivble Scle Scle Scle Mrgin Multiplier Rtio Grde ASE Group SPIL PTI Chip MOS Chipbond KYEC Group Tble 7: Mtri of Grey Reltionl Coefficient nd Grey Reltionl Grde DISCUSSION ASE, rnked top on the list, hs been ggressive in the globl IC pckging nd testing industry by epnding cpcity. The firm is rnked number one on four fctors: scle, growth, efficiency nd risks. Although ASE s fctor of profit is not the highest, it is ble to rpidly respond to chnges in the eternl operting environment, llowing them keep the number title in the globl pckging nd testing industry. Therefore, this reserch rnks ASE s being No. 1 in comprehensive competitiveness. In second plce is Chip MOS, with scle fctor of four. However, becuse Chip MOS is ble to precisely foresee investment plnning nd strictly control costs, its profit fctor is the best mong the si firms. Becuse it mintins stedy profit growth, its overll competitiveness is in second plce. Third plce is for SPIL. It hs rpidly epnded its cpcity nd rnks t the top for three fctors: scle, growth, nd profit. Its risk fctor is rnked in the middle. SPIL s opertion strtegy is stedy growth, nd hence its comprehensive competitiveness is rnked third. In fourth plce is for KYEC. Despite its scle continuously invested in the epnsion of new plnts to increse the production of CMOS sensors, consumer electronic components, MEMS, nd the cpcity of prt logic IC testing. Hence, KYEC s growth, profit, efficiency, nd risk fctors re rnked in the middle. It hs lso dopted n opertion strtegy of stedy growth. Therefore, its comprehensive competitiveness is in fourth plce. PTI is on fifth number. Due to over-relince on orders from Jpnese DRAM gint Elpid, when Elpid shocked the DRAM industry nd unepectedly filed for bnkruptcy on Februry 27, 2012, ll of PTI s scle, growth, nd profit fctors slid to lst plce. As result, its overll competitiveness slid to fifth plce. Lst plce is for Chipbond, s its four fctors of scle, growth, profit, nd efficiency re ll t the bottom. This shows tht Chipbond hs been unble to rpidly respond to chnges in the eternl operting environment. As result, its pce of cpcity epnsion nd verticl technology integrtion is slower compred to the other firms. Thus, Chipbond s overll competitiveness is rnked lst.

8 Interntionl Journl of Mngement, Economics nd Socil Sciences 94 CONCLUSION Etrcting dt from the public finncil sttements issued by si listed pckging nd testing corportions in 2013 nd 2014, this study employed the chrcteristics of Grey theory to nlyze their competitiveness. The results were then compred with their ctul operting sitution in the first hlf of We re ble to confirm tht using Grey theory to estblish competitiveness comprison model cn truly reflect corportion s future competitiveness. REFERENCES Bouguezzi, S., Aydi, M. & Ghrini, M. (2016). Developing simple nlyticl therml model for discrete semiconductor in operting condition. Applied Therml Engineering, 100, Co, Q., Wu, J. & Ling, C. (2015). An intuitionistic fuzzy udgement mtri nd TOPSIS integrted multi-criteri decision mking method for green supplier selection. Journl of Intelligent nd Fuzzy Systems, 28(1): Cesroni, F. & Picclug, A. (2013). Opertionl chllenges nd ST's proposed solutions to improve collbortion between IP nd R&D in innovtion processes. Cliforni Mngement Review, 55(4): Deng J.L. (1989). Introduction to Grey system theory. The Journl of Grey Systems, 1, Dikoulki, D., Mvrots, G. & Ppynnkis, L. (1995). Determining obect weights in multiple criteri problem: The CRITIC method. Computers nd Opertions Reserch, 22, Gul, M. & Guneri, A. F. (2016). A fuzzy multi criteri risk ssessment bsed on decision mtri technique: A cse study for luminum industry. Journl of Loss Prevention in the Process Industries, 40, Jing, J.S., Wu, P.L., Zhng, X.D., Chng, T.H., Chn, S.F., Chng, H.T. & Wen, K.L. (1988). Introduction to Grey Theory, Gu-li Book Co., Tiwn. Jin, P. (2004). The Report on Chin s Enterprises Competitiveness. 1 st Ed., Socil Sciences Acdemic Press, Chin. Li, B. & Schlichtmnn, U. (2015). Sttisticl timing nlysis nd criticlity computtion for circuits with post-silicon clock tuning elements. IEEE Trnsctions on Computer- Aided Design of Integrted Circuits nd Systems, 34(11): Lin, K.W. (2013). The pprisl model of competitiveness for the foundry industry in Tiwn. Pkistn Journl of Sttistics, 29(5): Lin, K.W., Kun, C.M. & Ni, M.H. (2012). The rting of operting performnce of domestic uto industry. Journl of Computer Science, 8(11): Resh, R., Rvi, V. & Venkt, R. R. (2015). Selection of risk mitigtion strtegy in electronic supply chins using grey theory nd digrph-mtri pproches. Interntionl Journl of Production Reserch, 53(1): Thkur, V. & Anbnndm, R. (2015). Supplier selection using grey theory: A cse study from Indin bnking industry. Journl of Enterprise Informtion Mngement, 28(6): Tirkel, I. (2013). Forecsting flow time in semiconductor mnufcturing using knowledge discovery in dtbses. Interntionl Journl of Production Reserch, 51(18): Wng, K. & Pn, Z. (2016). An nlyticl model for stedystte nd trnsient temperture fields in 3-D integrted circuits. IEEE Trnsctions on Components, Pckging nd Mnufcturing Technology, 6(7): Zho, P. & Wu, K.I. (2016). Model-bsed vector-fitting method for circuit model etrction of coupled-resontor dipleers. IEEE Trnsctions on Microwve Theory nd Techniques, 64(6):