Evaluation of the Software Industry Competitiveness in Jilin Province Based on Factor Analysis

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1 BULGARIAN ACADEMY OF SCIENCES CYBERNETICS AND INFORMATION TECHNOLOGIES Volume 14, No 4 Sofia 2014 Prit ISSN: ; Olie ISSN: DOI: /cait Evaluatio of the Software Idustry Competitiveess i Jili Provice Based o Factor Aalysis Pichao Meg 1, Weishi Yi 1, Yazhog Li 2 1 College of Sciece, Chagchu Uiversity of Sciece ad Techology, Chagchu, Chia 2 Beihua Uiversity, Jili, Chia s: megpc@cust.edu.c yiweishi@foxmail.com lyz@cust.edu.c Abstract: I this paper 12 ecoomic idices of the software idustry i 30 cities/provices i Chia are used to set up a evaluatio system for the competitiveess of the regioal software idustry. By usig the statistical aalysis method of factor aalysis, a evaluatio model of the comprehesive competitiveess of the software idustry for each city/provice is built. Takig Beijig ad Shaghai as examples, the comprehesive competitiveess ad problems of the software idustry i Jili provice are compared ad aalyzed. Keywords: Software idustry, competitiveess, factor aalysis. 1. Itroductio As a strategic leadig idustry i 21-st cetury, the software idustry is crucial to the electroic iformatio idustry ad plays a decisive role i the iformatio idustry developmet, thus becomig oe of the measuremets to assess the Comprehesive Natioal Power. N o w a k ad G r a t h a m [1] characterized the major barriers to success for small market software etrepreeuiral vetures based o the software idustry i Califoria, Uited States, ad further built ad verified their ecoometric model. D e h u a J u [2] studied the software idustry i Irelad ad demostrated that the reaso for Irelad holdig a domiat positio i the software market lays i its high quality software ad the advatage of huma resources maagemet. D a y a s i dhu [3] has developed a dyamic theoretical framework for global competitiveess ad implied that the orgaizatios i the Idia software idustry have created trust ad ecouraged the iter-orgaizatioal 101

2 relatioships. D e e p e d r a [4] studied the developmet of the Idia software idustry comprehesively. C h e [5] proposed optios to ehace the software idustry developmet healthily with respect to the major existig problems of the software idustry i Chia. L i u [6] compared the software idustry i Chia to that i Idia based o Porter s The Competitive Advatage of Natios. The developmet of the software idustry i Jili Provice plays a pivotal role i developig old idustrial bases. I our research the competitiveess of the software idustry i Jili provice, Shaghai ad Beijig was compared. Moreover, the factor aalysis method was used to evaluate the comprehesive competitiveess of the software idustry i Jili Provice ad further the overall situatio ad curret problems were aalyzed. 2. The evaluatio idices of the competitiveess i the software idustry Startig from the formatio of the software idustry competitiveess, we have built our evaluatio system based o Porter s diamod model, IMD world competitiveess idex ad the evaluatio system of the Chiese Eterprise Cofederatio. Moreover, we have also cosidered a recet evaluatio system study o the software idustry competitiveess i Chia ad combied the features of the software idustry ad data acquisitio. Our evaluatio system for the competitiveess of the regioal software idustry icludes the three first level idices (idustry iput, idustry output ad market performace) ad 12 secod level idices. 102 Table 1. Evaluatio system for the competitiveess of the software idustry i Jili Provice Geeral objective First level idices Secod level idices Eterprise umber x 1 Number of employees x 2 Idustry iput R&D staff x 3 Bachelor degree ad above proportio x 4 R & D fuds x 5 R&D iput itesity x 6 The evaluatio system for the competitiveess of the software idustry i Jili Provice 3. Factor aalysis Idustry output Market performace Busiess icome x 7 Idustrial added value x 8 Total profit x 9 Market share x 10 Export ratio x 11 Product exports x 12 Factor aalysis is proposed by the British psychologist C. Speaa ad has bee widely applied i the field of ecoomics, maagemet sciece ad sociology. Based o the aalysis of a few factors, factor aalysis is a method to study the coectio ad quatity relatioship betwee the factors ad the origial variables ad to detect the iteral structure of the factors. Further factor aalysis ca be used to costruct

3 a comprehesive evaluatio fuctio ad perform evaluatio based o the scores obtaied via such fuctio. The steps are the followig: 3.1. Hypothesis test Geerate a correlatio coefficiet matrix ad perform a test of sigificace to determie whether it is feasible to perform factor aalysis for the origial variables Normalizatio Let the sample data matrix be Z = ( Zij ) m = { z1, z2, L, z}, where there are variables ad m observatios. Let X = ( Xij ) m = { x1, x2, L, x} be the matrix after ormalizatio, ad the mea ad stadard deviatio for each observatio be 0 ad 1, respectively. The trasformatio equatio for ormalizatio is Zij z j X ij =, i = 1, 2, 3, L,, j = 1, 2, 3, L, p, S j z j = Z ij, S j = ( Zij z j ). 1 i= Geeratig a sample correlatio matrix, eigevalues ad eigevectors Let the sample correlatio matrix be R=(r ij ) m, ad r ij =r ji ad r ii =1, the R is a symmetric matrix with oes i the mai diagoal. Let the eigevalues ad eigevectors for R be λ 1 λ 2 λ p ad u 1, u 2,, u p, respectively, ad ui = ( ui1, ui2, L, uip), i = 1, 2, L, p Extractig pricipal compoets Based o the eigevalues ad eigevectors, we compute the Variace Cotributio Rate (VCR) wi = λ i / λ j ad the factor loadig of X i o F i, aij = u ij λ j, ad extract k pricipal compoets accordig to the criteria that the accumulatio of VCR 85%. The we perform orthogoal rotatio of the loadig matrix, makig the matrix as close as possible to the directio of +1, 1 or 0, ad write dow the factor equatios: X1 = a11f1 + a12f2 + L+ a1k Fk, L, X = a1f1 + a2f2 + L+ ak Fk. The eigevalue λ i for the i-th compoet F i measures the variace of this compoet. The bigger the variace, the more cotributio it has to the overall variace. The cotributio rate w i is the percetage of the explaatory importace of the correspodig factor with respect to all variables. The k compoets of the correspodig eigevector u i with respect to the eigevalue λ i are the coefficiets i= 1 103

4 for the k ormalized variables of the correspodig F i, ad the absolute values ad sigs idicate the correlatio stregth ad directio betwee the pricipal compoet ad the correspodig variable The iterpretatio of the pricipal compoets The coefficiets a ij of the factor loadig matrix idicate that the relative high loadigs are distributed amog the compoets regularly. We iterpret the compoets accordig to their actual meaigs Calculatig the factor scores from the loadig matrix A ad buildig the factor evaluatio model Calculate the factor scores from the obtaied loadig matrix A: F i = aij xij. / aij j j Weighted with w i, the VCR of each pricipal compoet ad based o the above factor scores, the comprehesive evaluatio model is built: k F = w i F. i= 1 F is the comprehesive score for the competitiveess of the regioal software idustry; w i is the weight for the i-th compoet (VCR for the i-th compoet); F i is the factor score for the i-th compoet Establishig of the evaluatio model of the competitiveess of the regioal software idustry a) Kaiser-Meyer-Olki (KMO) test ad Bartlett s test of sphericity We performed KMO test ad Bartlett s test of sphericity after ormalizig the 12 ecoomic idices for 30 cities/provices i 2012 i Chia, ad the results are show i Table 2. Table 2. Kaiser-Meyer-Olki ad Bartlett s test i KMO measure of samplig adequacy Approx. Chi-Square Bartlett s test of sphericity df 66 Sig As it ca be see from the table, the first row shows that the KMO test value is 0.848, ad the secod row shows the Bartlett s test result rejectig the ull hypothesis, thus the factor aalysis is sigificat for the 12 idices ad it is feasible to perform the factor aalysis. 104

5 Table 3. Commualities Variable Iitial Extractio Variable Iitial Extractio x x x x x x x x x x x x Table 3 demostrates the iitial commuality ad the re-geerated commuality after extractig 2 factors for the 12 idices used i our aalysis. The commo factor aalysis exhibits that the majority of the idices shares more tha 90% commuality. The above evaluatio demostrates the tight iteral structural relatioship betwee the extracted pricipal compoets ad the idices ad thus it is suitable for factor aalysis. b) Extractig the pricipal compoets Calculate the eigevalues, VCRs ad accumulatio of VCR for the pricipal compoets before ad after rotatio (Table 4). Table 4. Total variace explaied No Extractio sums Rotatio sums Iitial eigevalues of squared loadigs of squared loadigs Variace, Cumulative, Total Total Variace, Cumulative, Total Variace, Cumulative, % % % % % % I Table 4, the first colum is a factor idex, ad startig from the secod colum, every three colums are grouped together. I each group, the colums are eigevalues, VCRs ad accumulatios of VCR i sequece. The three groups of data demostrate the iitial solutio, the solutio ad the fial solutio for factors after rotatio. We ca see that the eigevalues for the 2 pricipal compoets after rotatio are ad respectively, the VCRs are % ad % respectively, ad the accumulatio of VCR is %. The two compoets ca explai as much as % variace of the 12 idices, which meas that the two compoets cotai major iformatio of the origial variables ad are eligible to evaluate the competitiveess of the regioal software idustry, as mai factors. c) The aalysis of the factor loadig matrix ad iterpretatio of the pricipal compoets 105

6 Table 5. The factor loadig matrix after rotatio Variable Compoet Compoet Variable x x x x x x x x x x x x Table 5 demostrates the result of rotatig the factor loadig matrix with the maximum variace method. Usig the pricipal compoets aalysis to perform a rotatio with maximum variace method, we get a relatively high loadig o the first factor of X 1, X 2, X 3, X 5, X 7, X 8, X 9, X 10, X 11, X 12, where te variables could reflect the geeral competitiveess of idustry, ad defie the first pricipal compoet as a geeral stregth factor. We get a relatively high loadig o the secod factor of X 4, X 6 ad defie the secod factor as a iovatio stregth factor. Thus we have the factor equatio: X1 = 0.962F F2 X5 = 0.971F F2 X 9 = 0.953F F2 X2 = 0.986F F2 X6 = 0.346F F2 X10 = 0.976F F2,,. X3 = 0.917F F2 X7 = 0.976F F2 X11 = 0.880F F2 X4 = 0.125F F X8 = 0.968F F 2 X12 = 0.914F F2 d) Calculatig the factor scores ad set up the evaluatio model The factor score fuctio ca be deduced from Table 5: F1 = (0.962X X X X X X X X X X12 ) /( ), F2 = (0.895X X6) /( ). Accordig to the weight for each pricipal compoet ad the correspodig score, we have the evaluatio model of the competitiveess of the regioal software idustry: F = wf wf 2 2 = 0.873F F2, where wi = λi / λ j, λ i is the variace for i-th compoet, F is the comprehesive score for the competitiveess of the regioal software idustry, ad F 1, F 2 are the factor scores for the first ad secod pricipal compoets, respectively. 106

7 Evaluatio of the comprehesive competitiveess of the software idustry i Jili Give our ewly-built evaluatio model, we have chose two typical regios of Chia, Beijig ad Shaghai as compariso targets ad have compared them to Jili. Further o we have evaluated the comprehesive competitiveess of the software idustry ad studied the competitiveess stregth i Jili Provice. F 1, F 2 ad F values were calculated after ormalizig the raw data for 30 differet cities/provices ad are show i Fig. 6. Table 6. F 1, F 2 ad comprehesive competitiveess scores (F) for Beijig, Shaghai ad Jili Regio F 1 F 2 F Beijig Shaghai Jili Our results have oly demostrated the relative differeces rather tha the absolute values for the competitiveess of the software idustry for each city/provice. Altogether, the comprehesive competitiveess scores for the software idustry i Jili Provice, Beijig ad Shaghai are 0.31, 1.16 ad 0.81 respectively, exhibitig a big gap betwee Jili Provice ad Beijig/Shaghai. With respect to the two compoets, the VCRs for the first factor ad the secod factor are ad respectively, idicatig the leadig role of the first factor o the competitiveess of the regioal software idustry. As show i Fig. 6, the first factor score is 0.44 of Jili Provice, which is much smaller tha that of Beijig (1.49) ad Shaghai (0.98). This is due to the professioal persoel shortages ad isufficiet fudig, as well as the relative weak competitiveess i marketig performace ad techological iovatios. The score for the secod factor is 0.23 of Jili Provice, which is higher tha Beijig (0.18) ad lower tha Shaghai (0.60). This is the result of the advatages of IT persoel ad the emphasis o team buildig ad persoel traiig i Jili Provice, however still accompaied with isufficiet fudig. As a result, the relative weak comprehesive competitiveess of the software idustry i Jili Provice is due to the relative low score for the first factor, which acts as a leadig factor. 4. Coclusios A case study was performed for the competitiveess of the software idustry i Jili Provice, usig factor aalysis. By comparig ad aalyzig the related data for the software idustry i 30 cities/provices i Chia, the relative developmet level of the software idustry i Jili Provice was obtaied. After further comprehesive evaluatio, a gap was recogized betwee the software idustry i Jili ad i the developed cities/provices i Chia, ad light is shed o the govermet strategy for idustry developmet. 107

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