Impact of Strategic Changes on the Performance of Trucking Firms in the Agricultural Commodity Transportation Market

Transcription

1 Impac of Sraegc Changes on he Performance of Truckng Frms n he Agrculural Commody Transporaon Marke Alber J. Allen Deparmen of Agrculural Economcs Msssspp Sae Unversy Msssspp Sae, MS Emal: allen@agecon.mssae.edu Hayuan Wang Deparmen of Indusral Engneerng Msssspp Sae Unversy Msssspp Sae, MS Safdar Muhammad Cooperave Agrculural Research Program Tennessee Sae Unversy Nashvlle, Tennessee Gerald Mumma Cener for Dsease Conrol and Prevenon Alana, Georga A.A. Farhad Chowdhury Deparmen of Busness Admnsraon Msssspp Valley Sae Unversy Seleced Paper prepared for presenaon a he Souhern Agrculural Economcs Assocaon Annual Meeng, Alabama, February 1-5, 2003 Copyrgh 2003 by Alber J. Allen, Hayuan Wang, Safdar Muhammad, Gerald Mumma, and A.A. Farhad Chowdhury. All rghs reserved. Readers may make verbam copes of hs documen for non-commercal purposes by any means, provded ha hs copyrgh noce appears on all such copes.

2 Absrac Economerc models were developed o esmae facors ha nfluence sraegc changes and evaluae he mpacs ha sraegc changes wll have on he subsequen performance of agrculural commody ruckng frms. Resuls reveal ha GDP and change n frm sze wll have posve mpacs on sraegc changes made by frms. Inroducon For-hre agrculural commody ruckng frms are consanly forced o ac and reac n response o changes n her exernal and nernal envronmens. I s her choce as o wha acons o ake, f any. Those acons, or choces of nacon, connually have performance mplcaons for sakeholders. Sraegc changes can be defned as hose aleraons a frm makes n s busness approach o beer algn self wh s envronmen n s effors o manan and/or mprove performance. For-hre agrculural commody ruckng frms do have he ably o make sraegc changes and do make hose changes usng a varey of sraegc resources, when faced wh srong changes n her envronmens. Agrculural ruckng frms do no make all he same changes, do no change a he same me, nor gan he same performance mpacs from her acons Ths sudy wll enrch our undersandng of he lnks beween he exernal and nernal forces ha mpel an agrculural commody-ruckng frm o aler and adap s sraegc focus over me. Ths research conrbues o he feld of sraegc managemen n s me seres perspecve and s ndvdual frm-level analyss of sraegc changes. Objecves of he Sudy The objecves of hs sudy are as follows: 1

3 1. To develop frm sraegc change ndces on an ndvdual frm level over he perod for agrculural commody ruckng frms. 2. To evaluae he exernal and nernal facors ha nfluences an agrculural commody-ruckng frm o change or no change s sraegc focus over me. 3. To evaluae he performance mplcaons of an agrculural commody ruckng frm s decson o aler s sraegc focus over me. Daa, Mehods, and Models The process of obanng he objecves of hs sudy s wofold. Frs, a caegorzaon of carrer decsons no key dmensons s done. Second, a model of sraegc change s developed. The key dmensons ha bes summarze he range of managemen decsons n he ruckng ndusry for hs analyss nclude Cos, Prce, Rsk, Servce, and Sze. For each of hese denfed dmensons, a key fnancal and/or operang performance measure was used as represenave ndcaors of managemen decsons ha consue he essence of sraegy. Daa for he fnancal and operang performance measures were obaned from TTS Blue Book of Truckng Companes, publshed by Techncal Transporaon Servces. Table 1 provdes deals on how each key dmenson was measured. Table 1: Type of Sraegc Change Dmensons and Represenave Fnancal Measures Used for Sudy Type of Dmenson Cos Dmenson Prce Dmenson Rsk Dmenson Servce Dmenson Sze Dmenson Source: Feler e al. Represenave Fnancal Measure Operang Expenses/Mles Toal Revenues/Toal Tons Toal Deb/Toal Equy Toal Salary, Wages and Frnge Benefs/Toal Number of Employees Toal Operaon Revenues 2

4 In hs sudy he cos dmenson measure capures he specrum of he agrculural commody frm s cos ncludng salares, wages, axes, and oher expenses. The prce dmenson provdes nformaon on prces ha he frm charged for s servces. The rsk dmenson capures nformaon on how well he agrculural commody frm s manager/owner handles s capal resources. The servce dmenson capures nformaon on cusomer servces and he employee coss n provdng ha servce for compensaon by he frm. The sze dmenson s used o ndcae how he sraegc focus of dfferen sze frms s affeced by acons/nacon by s managemen. The ndvdual frm s varable dmenson score sars wh he general ledger accoun balance or rao for each frm n each year. In he begnnng, for each year, all agrculural commody- ruckng frms n he daa se were used. Those frms wh mssng daa on any sngle dmenson were elmnaed for ha specfc year. Based on prevous sudes by Boeker (1989) and Feler (1995) concernng sraegc change, wo models of ndvdual frm sraegc change were developed. In Model One, a sraegc change ndex was calculaed for each frm n each year usng he sum of he yearly changes n he absolue values of he above dmensons. Usng he base year and hen for each year afer, he changes n sandardzed scores on ndvdual dmensons, aken n erms of absolue values, were compued as he sraegc change ndex. The sraegc change ndex was used o provde an ndcaon of how an ndvdual frm changed s poson relave o ndusry averages as well as changes on each ndvdual dmenson, and how exernal and nernal facors nfluenced ndvdual frm sraegc changes. The proposed regresson Model One s as follows. 3

5 D D Y ε = Where, Y : The h observaon of SCINDE from year o year 1 0 : Inercep k : Coeffcens for ndependen varables. k=1, 2, 3 9, 10. j : The h observaon of jh ndependen varable relaed o year. =1,2,3 194,195 n he model, j=1,2,3 7,8 n he model. 1 : The h observaon of LN ( CFIRMSIZE ) from year o year 1 2 : The h observaon of LN (SIZE) for year 3 : The h observaon of PREY-ORS for year -1 4 : The h observaon of PIRATES for year 5 : The h observaon of CPI for year 6 : The h observaon of AAUR for year 7 : The h observaon of DFUELPRS for year 8 : The h observaon of GDP for year D 2 : The h observaon of LAW1. =1, f he year s 1995, 0 oherwse D 2 D 3 : The h observaon of LAW2. =1, f he year s 1998, 0 oherwse D 3 : The years ,1999. The dependen varable SCINDE n Model One s he year-o-year change n he sraegc change ndex and ndependen varables are nernal and exernal facors. 4

6 Inernal facors affecng a frm s sraegc change for hs sudy conss of sze of he frm, pror performance, and change n sze of frm. Accordng o Feler (1995), frm sze s assocaed wh ressance o change. As he sze of he frm ncreases, frm behavor becomes more predcable and conrolled as becomes more formalzed. As a resul, he lkelhood of change n sraegc focus declnes as frm sze ncreases. Thus, s expeced ha he sze of he frm wll have a negave mpac on sraegc change. In hs sudy he varable s measured by ln(toal Operang Revenues) due o he large values of hs varable. Ths ndependen varable s represened n Model One by LN (SIZE). The change n he sze of he frm s expeced o have a posve mpac on sraegc change. For example, f a frm s merged wh anoher frm, sraegc changes wll lkely come abou. In hs sudy, he change n frm sze s measured by ln ( Re venue 1 Re venue ). Ths ndependen varable s represened n Model One by LN ( CFIRMSIZE ). Performance for each frm s measured by each frm s Operang Rao (Toal Operang Expenses/Toal Operang Revenues). Therefore, pror performance for each frm was measured by he prevous year s operang rao fgures for each frm. Ths ndependen varable s represened n Model One by PREY-ORS. Exernal facors nclude envronmenal change and legslave change. The envronmenal facors nclude gross domesc produc, desel fuel prces, prme neres raes, unemploymen raes, and consumer prce ndex. Legslave changes nclude varous federal ruckng laws ha have been passed durng he sudy perod. The ruckng laws seleced for hs analyss nclude he Naonal Hghway Sysem Desgnaon Ac of 1995 (November 28, 1995), and he Transporaon Equy Ac for he 5

7 21 s Cenury, TEA-21 (June 9, 1998). They are represened n Model One by LAW1 and LAW2. The envronmenal facors were consdered o have some mpac on sraegc changes. Federal legslaon a he naonal level s expeced o have a posve mpac on sraegc changes. The exernal facors are represened by AAUR, CPI, PIRATES DFUELPRS, and GDP n he model. They were obaned elecroncally from he followng secondary sources. The average annual unemploymen raes (AAUR) for he U.S. were obaned from he Oregon Employmen Deparmen webse. The consumer prce ndex values (CPI) for hs analyss were obaned from he U.S. Deparmen of Labor, Bureau of Labor Sascs, Washngon, D.C. webse. Desel fuel prces (DFUELPRS) were obaned from Naonal Transporaon Sascs 2001, Bureau of Transporaon Sascs, Washngon D.C. webse. Gross domesc produc (GDP) values for he U.S. were obaned from he Bureau of Economc Analyss webse. Prme neres raes (PIRATES) were obaned from he Federal Reserve Bank of New York webse. Informaon on federal legslaon affecng he ruckng ndusry was obaned from he Federal Hghway Admnsraon, U.S. Deparmen of Transporaon webse. The webse addresses for all of he elecroncally sources used for he exernal facors are found n he References. Model Two nvesgaes he mpac of sraegc change on a frm s subsequen performance. Sraegc change s expeced o have a posve mpac on a frm s subsequen performance. In hs model, he frm s sraegc change ndex s used as an ndcaor of sraegc change. Performance s measured as he Operang Rao 2, 6

8 measurng performance n he year subsequen o sraegc changes. Thus, hs model looks a sraegc change n year one and performance mpacs n he followng year. The proposed regresson Model Two s as follows. Y = D D 10 D ε D 3 3 D 4 4 D 5 5 D 6 6 D 7 7 D 8 8 Where, Y : The h observaon of POSTOR for year 2 0 : Inercep k : Coeffcens for ndependen varables. k=1, 2, 3 9,10 j : The h observaon of jh ndependen varable relaed o year. =1,2,3 116,117 n he model, j=1 n he model 1 : The h observaon of SCINDE from year o 1 D j : The h observaon of jh ndependen varable relaed o year. =1,2,3 116,117 n he model, j=2 9,10 n he model D 2 : The h observaon of INDE2. D 2 =1, f frm s sraegc change ndex s n he range of , 0 oherwse D 3 : The h observaon of INDE3. D 3 =1, f frm s sraegc change ndex s n he range of , 0 oherwse D 4 : The h observaon of INDE4. D 4 =1, f frm s sraegc change ndex s n he range of , 0 oherwse D 5 : The h observaon of INDE5. D 5 =1, f frm s sraegc change ndex s 2.04 or greaer, 0 oherwse 7

9 D 6 : The h observaon of he year. D 6 =1, f he year s 1994, 0 oherwse D 7 : The h observaon of he year. D 7 =1, f he year s 1995, 0 oherwse D 8 : The h observaon of he year. D 8 =1, f he year s 1996, 0 oherwse D 9 : The h observaon of he year. =1, f he year s 1997, 0 oherwse D 9 D 10 : The h observaon of 1998 he year. =1, f he year s 1998, 0 oherwse D 10 : The years , In Model Two, Operang Rao 2 s he dependen varable. The dependen varable s represened by POSTOR n he model. The ndependen varables are he sraegc change ndex (SCINDE). Dfferen frm dsrbuon caegores were se up based on he breakdown of he sraegc change ndex usng fve dummy varables. Ths caegorzaon allowed for a closer analyss of ndvdual frm sraegc changes. Also ncluded n hs model were dummy varables for each year ( ) o conrol he effecs of a me rend and performance rends over me. The regresson models were run n he STATISTICA package usng sandard regresson mehod. Afer runnng he economerc models usng sandard mehod, he auhors found ha he models can be mproved by usng forward sepwse varable selecon mehod. Accordng o Rawlngs e al, he forward sepwse varable selecon mehod chooses he subse models by addng one varable a a me o he prevously chosen subse. The varable n he subse of varables no already n he model ha causes he larges decrease n he resdual sum of squares s added o he subse. Informaon on resuls and analyses of orgnal models can be found n appendx. Therefore, he resuls of revsed models are presened n hs paper. 8

10 Resuls The model selecon procedure resuled n varables LN ( CFIRMSIZE ), LN (SIZE), PREY-ORS, PIRATES, GDP and LAW2 beng seleced. The mproved model s as follows. Y = D3 ε Where, All he parameers denoe he same meanng as menoned above. Regresson resul summary for he mproved model s n able 2. Table 2: Model One regresson summary N=195 Regresson summary for Dependen Varable: Y - SCINDE R= , R 2 = , Adjused R 2 = F (6,188)= , P <0.0000, Sandard Error of Esmae: Varable Parameer Sandard Errors -sasc p-value Esmaes Inercep LN ( CFIRMSIZE ) LN (SIZE) PREY-ORS GDP PIRATES LAW Sgnfcan a α = Sgnfcan a α = The resuls show ha f here s one un ncrease of frm sze, wll resul n un mprovemen of sraegc change ndex. Also f here s one un ncrease of prme neres rae, wll resul n uns declne of sraegc change ndex. Ths mples ha hese frms over hs me perod may no have expanded he operaons because of he addonal cos resuled by he ncrease of neres rae. 9

11 The resuls also show ha as he law was enaced n 1998, resuled n uns declne of sraegc change ndex. Alhough a negave value of he coeffcen of LAW2 was no expeced, hs could mply ha he nermodal ransporaon ac may have had an adverse nfluence on sraegc decsons made by hose agrculural frms durng ha me perod. The coeffcen of varable GDP s posve as expeced. Ths mples ha he ncrease n GDP by one un wll resul favorable mpac on sraegc ndex change of he frm by uns. As before, he model resuls also urns ou ha F es shows ha he regresson model s overall sgnfcan wh F value= and p= (when α = 0. 01, α = 0.05 or α = 0.10). The ANOVA able of he analyss s n able 3. Table 3: Model One ANOVA able ANOVA able for dependen varable: Y - SCINDE Source Sums of df Mean F P-Value Squares Square Regresson Resdual Toal Based on he forward varable selecon procedure, he varables seleced were SCINDE, INDE4, INDE5, 1995, 1996, and 1998 for Model Two. The regresson model s n equaon as follows. Y = D4 5 D5 7 D7 8 D8 10 D 10 ε Where, All he parameers denoe he same meanng as menoned above. 10

12 Regresson resul summary for he mproved model s n able 4. The resuls ndcae ha one un ncrease of sraegc ndex change resuled n un decrease of he pos-operang rao as desred. Ths means ha he sraegc changes made by he frms n prevous me perod has a posve effec on he subsequen performance of he frms. The resuls also show ha one un change of me varable 1996 resuled n un ncrease of POSTOR and one un change of INDE 4 caegory resuled n un of ncrease of POSTOR. The means ha he me varable and he INDE4 caegory had a negave mpac on he performance of he ruckng frms durng he sudy perod. Table 4: Model Two regresson summary N=117 Regresson summary for Dependen Varable: Y - POSTOR R= , R 2 = , Adjused R 2 = F (6,100)=3.2660, P < , Sandard Error of Esmae: Varable Parameer Esmaes Sandard Errors -sasc p-value Inercep SCINDE INDE INDE Sgnfcan a α = Sgnfcan a α = As before, he model resuls also urn ou ha F es shows ha he regresson model s overall sgnfcan wh F value= and p= (when α = 0. 01, α = 0.05 or α = 0.10). Ths shows grea mprovemen of he orgnal model. The ANOVA able of he analyss s n able 5. 11

13 Table 5: Model Two ANOVA able ANOVA able for dependen varable: Y - POSTOR Source Sums of df Mean F P-Value Squares Square Regresson Resdual Toal Summary and Conclusons One of he objecves of hs sudy was o evaluae he mpac of nernal and exernal facors on sraegc changes made by agrculural commody ruckng frms over he sudy perod. Anoher objecve was o measure he nfluence ha sraegc changes wll have on he performance of agrculural commody ruckng frms n subsequen years. Two economerc models accomplshed he objecves of hs sudy. The resuls n Model One show ha GDP and change n frm sze wll have posve mpacs on sraegc changes made by frms. Resuls also show ha he prme neres rae and LAW2 have negave mpacs on sraegc changes made by frms. The resuls n Model Two show ha SCINDE has a posve mpac on pos operang raos of he frms. Resuls also show ha me varable and he INDE4 caegory had a negave mpac on he performance of he ruckng frms durng he sudy perod. 12

14 References Boeker, W., Sraegc Change: The Effecs of Foundng and Hsory. Academy of Managemen Journal Vol.32/No.3 (1989): Bureau of Economc Analyss, Naonal Income and Produc Accouns Tables. Inerne se hp:// (Accessed November 2002) Feler, J. N. Measurng Frm Sraegc Change n he Regulaed and Deregulaed Moor Carrer Indusry: An Egheen-Year Evaluaon. Ph.D. Dsseraon, The Unversy of Maryland, Feler, J.N., T. M. Cors and C. M. Grmm. Sraegc and Performance Canges Among LTL Moor Carrers: Transporaon Journal Vol.37/No. 4 (Summer 1998): Naonal Transporaon Sascs Inerne se hp:// (Accessed November 2002) Rawlngs, J.O., S. G. Panula and D.A. Dckey. Appled Regresson Analyss Sprnger-Verlag New York, Inc. Sae of Oregon, Oregon Employmen Deparmen, Annual Average Unemploymen Raes. Inerne se: hp://olms.emp.sae.or.us/pubs/sngle/annualraes.pdf (Accessed November 2002) STATISTICA and SaSof, 2300 E. 14h S. Tulsa, OK 74104, USA. TTS Blue Book of Truckng Companes, Transporaon Techncal Servces, Inc., New York, years. U.S. Deparmen of Labor, Bureau of Labor Sascs. Inerne se fp://fp.bls.gov/pub/specal.reques/cpi/cpiai.x (Accessed November 2002) U.S. Deparmen of Transporaon, Federal Hghway Admnsraon, Legslaon and Regulaons. Inerne se hp:// (Accessed November 2002) 13

15 Appendx Table 1: Orgnal Model One regresson summary N=195 Regresson summary for Dependen Varable: Y - SCINDE R= , R 2 = , Adjused R 2 = F (10,184)=4.6659, P < , Sandard Error of Esmae: Varable Parameer Sandard Errors -sasc p-value Esmaes Inercep LN ( CFIRMSIZE ) LN (SIZE) PREY-ORS PIRATES CPI AAUR DFUELPRS GDP LAW LAW Sgnfcan a α = Sgnfcan a α = Table 2: Orgnal Model One ANOVA able ANOVA able for dependen varable: Y - SCINDE Source Sums of DF Mean F P-Value Squares Square Regresson Resdual Toal

16 Table 3: Orgnal Model Two regresson summary N=117 Regresson summary for Dependen Varable: Y - POSTOR R= , R 2 = , Adjused R 2 = F (10,106)=1.9923, P < , Sandard Error of Esmae: Varable Parameer Esmaes Sandard Errors -sasc p-value Inercep SCINDE INDE INDE INDE INDE Sgnfcan a α = Table 4: Orgnal Model Two ANOVA able ANOVA able for dependen varable: Y - POSTOR Source Sums of DF Mean F P-Value Squares Square Regresson Resdual Toal