full text nomi 3

8/7/2019 Full Text Nomi 3

1/8

D o e s S a t i s f a c t i o n M o d e r a t eth e A s s o c i a t io n b e t w e e n A l t e rn a t iv eA t t r a c t i v e n e s s a n d E x i t I n t e n t i o ni n a M a r k e t i n g C h a n n e l ?R o b e r t A . P i n g , J r.Wright State Universi ty

Th i s s t udy i nve s t i ga ted t he pred i c t ed modera t ing e f fe c t o fsat i s fac t ion on the associat ion between the at t rac t ivenessof the al ternat ive re lat ionship a nd ex i t in tent ion in a ma r-ke t i ng channe l. The s tudy used a var ia t ion o f the Kennyand Judd s t ruc tura l equa t ion t e chn ique proposed by t heauthor. Th e resul ts sugg ested that fo r c hanne l customerswi th lower sat i s fac t ion, al ternat ive at t rac t iveness wasposi t ive ly a ssoc iated wi th ex i t in tent ion. Wh en sat i s fac t ionwa s higher, however, al ternat ive at t rac t iveness ha d noassoc iat ion w i th ex i t in tent ion. T he impl icat ions of theseresul ts are discussed.

ings by p rov id ing a deeper unders tand ing o f the majo ran teceden ts o f ex i t in ten t ion . They a l so p rov ide em pi r ica lsuppor t fo r the long - te rm buyer-se l le r re la t ionsh ip f rame-work proposed by Dwyer, Schurr, and Oh (1987) ando thers by showing an e f fec t p red ic ted by D wyer , Schurr ,and Oh (1987): that h igher sat is fact ion at tenuates the al-ternat ive at t ract iveness-exi t in tent ion associat ion .Af te r summ ariz ing the cu r ren t know ledge abou t chan -nel relat ionship exi t in tent ion, a sat is fact ion-al ternat iveat t ract iveness in teract ion is proposed and tes ted using af ie ld su rvey and the P ing t echn ique . The imp l ica t ions o fthe resul ts are then discussed.

Channel re la t ionsh ip t e rmina t ion has rece ived someattent ion in recent s tudies (Ping and Dwyer 1991; Ping1993a). The se s tudies gene ral ly contend that exi t in tent ionin a channel relat ionship has several antecedents , amongthem overal l sat is fact ion and the at t ract iveness of the besta l t e rna t ive re la t ionsh ip . The as soc ia t ions among thesevar iab les have been modeled us ing l inear e f fec t s , andnonlinear effects have been assumed to be absent . Thiss tudy inves t iga tes a p laus ib le non l inear e f fec t invo lv ingthese variables : the in teract ion of overal l sat is fact ion andal ternat ive at t ract iveness in the ir effect on exi t in tent ion.It uses a f ield survey and a s t ructural equat ion techniqueproposed by Ping (1993b) that es t imates in teract ion andquadra t ic effects for latent variables .T h e r e s u l t s f i l l a g a p i n t h e c h a n n e l r e a c t i o n s - t o -dissat isfact ion l i terature and extend Ping 's (1993a) f ind-J o u r n a l o f t h e A c a d e m y o f M a r k e t i n g S c i en c e .V o l u m e 2 2 , N o . 4 , p a g e s 3 6 4 - 3 7 1 .C o p y r i g h t 9 1 9 9 4 b y A c a d e m y o f M a r k e t i n g S c ie n c e .

C H A N N E L R E L A T IO N S H I P T E R M I N A T IO NIn an inves t iga t ion o f genera l i zed responses to channe lrelat ionship problems, Ping (1993a) observ ed that thein tent ion to exi t a channel relat ionship was negat ivelyassociated with o veral l relat ionship sat isfact ion and posi-t ively associated with the at t ract iveness o f the best avai l -able al ternat ive relat ionship . The specificat ion of these

relat ionships involved a s t ructural equat ion analysis of amodel tha t imp l ic i t ly pos i ted on ly l inear re la t ionsh ips .In a concep tua l iza t ion o f the h i s to ry o f a buyer-se l le rre la t ionsh ip , Dwyer , Schurr, and O h (1987) p roposed tha tthese relat ionships pass through several phases (see alsoFord 1980; Ga dde and Mattsson 1987). Both part ies to thebuyer-sel ler relat ionship , they argued, pass throu gh aware-ness , exp lo ra t ion , expans ion , commitmen t , and , u l t i -mate ly , d is so lu t ion phases o f the re la t ionsh ip . T hey no tedtha t exchange par tners in the comm it ted phase ach ieve aleve l o f sa t i s fac tion tha t p rec ludes o ther p r imary exchangepartners . They s tated that aware ness o f al ternat ive relat ion-sh ips is m ain ta ined , bu t wi thou t cons tan t compar i sons tothe current relat ionship . One plausib le resul t of th is pre-


2/8

P i ng / A L T E R N A T I V E A T T R A C T I V E N E S S & E X I T IN T E N T I O N 3 6 5

clusio nary sta te i s tha t for sa t i sf ied f i rms, increases in thea t t r ac t i veness o f a l t e rna t i ve r e la t i onsh ips wo u ld n o t a f f ec tr e l a t i onsh ip ex i t i n ten t i on . P ing (1993a ) obse rved a pos i -t i ve a ssoc i a t i on be tw een a l t e rna t i ve a t t rac t i veness and ex i tin tent ion, however; th is suggests tha t the associa t ion i scon t ingen t on t he l eve l o f ove ra l l r e l a t ionsh ip sa t is f ac ti on .In pa r ti cu l ar , i f Dw yer , Schur r , and Oh (1987) a re co r rec t ,when overa l l sa t i sfac t ion i s lower , changes in a l te rnat ivea t t r ac t i veness shou ld be pos i t i ve ly a ssoc i a t ed wi th ex i tin tent ion. At higher levels of sa t i sfac t ion, however , th isa ssoc i a t i on shou ld no t be s i gn if i can t . Accord ing ly ,

H I : Overa l l r e l a t i onsh ip sa t i s f ac t i on mode ra t e sthe a ssoc i a t i on be tween a l t e rna t i ve a t t r ac -t i veness and ex i t i n t en ti on .Speci f ica l ly ,

H2 a : At h ighe r l eve l s o f ov e ra l l r e la t i onsh ip sa t is -f ac t i on t he re i s no a ssoc i a ti on be tw een a l t e r-nat ive a t t rac t iveness and exi t in tent ion,

andH 2 b : At lower l eve l s o f ove ra l l r e l a t ionsh ip sa t i s -fac t ion a l te rnat ive a t t rac t iveness i s posi t iv e lyassocia ted wi th exi t in tent ion.

The rema ind e r o f t he a r t ic l e repor t s a t e s t o f t he se hypo the -se s us ing da t a p rov ided by a f i e ld su rvey .

M E A S U R E M E N TSat isfac t ion, the global evaluat ion of re la t ionship ful -

f i l lmen t by t he f i rm (Dw yer and Oh 1987) , was meas uredus ing a modi f i ca t i on o f t he Dwyer and Oh sa t i s f ac t i onsca l e in sp i red by Gask i and Nev in (1985) . The doma in o fsa t i sfac t ion inc ludes a l l the charac ter is t ics of the buyer-se l l e r r e l a t i onsh ip t ha t a f i rm deems " reward ing , p ro f i t -ab l e , o r i n s t rumen ta l " (Ruke r t and Church i l l 1984) , o rcost ly , unfa i r , or f rust ra t ing (Ping 1993a) . The f ive i temsin t he sa t i s fac t i on measure a sse ssed t he bu ye r f i rm ' s ove r -a l l sa t i sfac t ion wi th the re la t ionship ( two i tems) , fa i rnessin t he exchan ge re l a t ionsh ip ( two i t ems) , and t he degree t owhich t he se l l e r f i rm was a good co mpa ny wi th which t odo bus iness.The a t t r ac t i veness o f t he be s t a l t e rna t i ve r el a t ionsh ip , af i rm ' s e s t ima te o f t he sa t i s f ac t i on ava i l ab l e i n t he be s tavai lable a l te rnat ive re la t ionship, was opera t ional ized asthe buy e r f i rm ' s p e rcep t ion o f t he o ve ra l l fu l fi l lmen t avai l -able f rom the best a l te rnat ive suppl ier , in addi t ion to theove ra l l fu l f i l lmen t ava i l ab l e i n t he ex i s t i ng buye r - se l l e rr e l a t ionsh ip (P ing 1993a ). The concep tua l i za t i on encom-passe s a f i rm ' s gene ra l i zed pe rcep t ions o f t he r ewards andcos t s ava i l ab l e i n t he m os t sa l i en t ava i l ab l e r e l a ti onsh ipa l t e rna t i ve . The four i t ems in t h is m easure dea l t wi th t heb u y e r f i r m ' s e v a l u a ti o n o f h o w g o o d a s u p p li e r c o m p a n y

the a l te rnat ive would be (1) i t s fa i rness, (2) i t s productsand services, (3) i t s pol ic ies and, (4) in genera l , howsa t is f i ed t he f i rm w ould b e w i th t he a l t e rna t i ve supp li e r.Ex i t i n t en t i on , t he i n t en t i on t o phys i ca l l y l e ave t here l a ti onsh ip , was ope ra t i ona l i zed a s t he p rop ens i t y t o t e r -mina t e t he p r imary supp l i e r r e l a ti onsh ip (P ing 1993a ) . Theconcep tua l i za t i on taps t he d egree o f i n t en t i on t o d i scon-t i nue t he r e l a ti onsh ip wi th t he econo mic excha nge pa r tne r.The s ix i t ems in t he ex i t i n t en t ion measure conce rned t hebuye r f i rm ' s t h ink ing o f ex i ti ng , look ing fo r a r ep l acem entsupp l i e r , cons ide r ing a r ep l acement ( two i t ems) , and re -so lv ing t o end t he r e l a t i onsh ip ( two i t ems) .These measures were combined into a se l f -administeredques t i onna i re t ha t was ma i l ed t o a sample o f ha rdwarere t ai l er s . The ana lys is o f t he r e su lt i ng da t a was condu c t edusin g structural equation analysis w ith a satisfaction-alternativeat t rac t iveness la tent var iable in terac t ion speci f ied usingthe P ing t echn ique . Be f o re de sc r ib ing t he s t udy , howev e r ,some back ground on t he e s t ima t ion o f non l inea r e f fec ts inst ruc tura l equat ions i s appropria te .

N O N L I N E A R L A T E N T V A R I A B L E SKenny and Judd (1984) p roposed t ha t i n t e rac t i on andquadra t i c l a t en t va ri ab l e s cou ld be spec i f i ed us ing i nd i ca -to r s tha t a re p roduc t s o f obse rved va r i ab l e s . They p rop osedtha t p roduc t s o f t he i nd i ca to r s fo r t he l i nea r l a t en t va r i ab le sX and Z , fo r example , w ou ld spec i fy t he l a ten t i n t e rac ti onvar iable XZ. Speci f ica l ly , i f X ha d indica tors x~ and x2 andZ ha d indica tors z~ and z2, respect ive ly , XZ is speci f ied

using the indica tors XlZl, XlZ2, X2Zl, and x2z2.In add i t i on , they sho wed tha t unde r ce r t a in cond i t i ons ,t he va r i ance o f t he se i nd i ca to r p roduc t s i s de t e rmined bythe i r cons t i tuen t i nd ica to r s . They sh owe d tha t , fo r exam-p le , t he va r i ance o f t he i nd i ca to r x~zz depends on ~1, ~, ,1 ,Var(X), Var(Z), 0~xl, and 0~zl, wh ere V ar(X) an d V ar(Z) arethe va r i ances o f the l a t en t va r i ab le s X and Z , ~1 and ~ 1 a rethe loa dings of xl on X and z~ on Z, and 0~xl and 0~zl a re thevar iances of the err or te rms exl and ez~. Speci f ica l ly , assum-ing t he l a t en t var i ab le s X and Z a re i nd ependen t o f t he e r ro rt e rms ex l and ~1 ; t he e r ro r t e rms a re i nde penden t o f e achother ; and x~, Zl, ~1, an d e , l a re no rma l ly dist r ibuted, th eyshow ed the va r iance o f XlZl i s g iven by

Var(x lzl) = V ar[(k, lX + gxl)(~.zlZ+ ez0]= ~xl2 ~zl2 Var(XZ) + ~xl2 VaF(X)0ez1+ ~.,12 Var(Z )0exl + 0Exl0c,1.

(1 )

They then spec i f i ed l a t en t va r i ab l e s such a s XZ wi thindicators such as XlZl by const ra ining the indica tor loadingand e r ro r t e rm fo r XlZl (Xxlzl and 0~xlzl) to be the com bin a-t i ons o f t he pa rame te r s shown in equa t ion (1 ) , t ha t is ,

~ 'x lz l = ~x l~ 'z l (2 )and0 e x l z l = ~ x l 2 War(X)0ez1 + ~ 1 2 V a r ( Z ) 0 e x 1 + 0 e x l 0 e z l . ( 3 )


3/8

366 JOURNALOF TH E ACADEMYOF M ARKETINGSCIENCE FALL 1994

T h e y a l so u s e d C O S A N ( c u rr e n tl y a s u b p r o c e d u re o f t h eSAS p rocedure CALIS) , wh ich i s pa r t i cu l a r ly su i t ed t omode l ing s t ruc tu ra l equa t ions w i th non l inea r te rms suchas those in equat ions (2) and (3) .Al thoug h the Ken ny and Judd t echn ique is an impor t an tt heore t i ca l con t r i bu t ion , i t ha s p roven d i f f i cu l t fo r r e -sea rche r s to implem en t (Aiken and Wes t 1991). T he num-be r o f dum my va r i ab l e s r equ i red t o spec i fy each i nd i ca to ro f a non l inea r va r iab l e us ing t he Kenny and Jud d t echn ique(e .g . , one for each term in equat ions [2] and [3]) canbeco me t ed ious fo r mode l s wi th m any ind i ca to r s o r seve ra lnonl in ear la tent var iables (Ping 1993b) . 1Ha ydu k (1987) and o the r s have p roposed a va r i a ti on o fthe Kenny and Judd (1984) t e chn ique t ha t c an be imple -m e n t e d u s in g L I S R E L ( J t r e s k o g a n d S t r b o m 1 9 8 9) a n dEQS (Ben t l e r 1989) . The t echn ique i s d i f f i cu lt t o summ a-r i ze , howeve r , and t he i n t e re s t ed r eade r i s d i r ec t ed t ochap te r 7 o f Hay duk (1987) fo r de t a il s . Unfor tuna t e ly , t het echn ique a l so r equ i re s t he spec i f i ca t ion and e s t ima t ion o fm a n y d u m m y v a r i a bl e s.As a r e su lt , P ing (1993b) p ropos ed an add i t i ona l va ri -a t i on o f t he Kenny and Judd t echn ique t ha t r equ i re s nod u m m y v a r i a b l es a n d c a n b e i m p l e m e n t e d i n L I S R E L a n dEQS . T he t echn ique i s c a r r i ed ou t i n two s t eps , pa ra l le l i ngthe two-s t ep e s t ima t ion approach fo r s t ruc tu ra l equa t ions u g g e s te d b y A n d e r s o n a n d G e r b i n g ( 1 9 8 8 ) - - e s t i m a t e t h em e a s u r e m e n t m o d e l b e f o r e e s t i m a t i n g t h e s t r u c t u r a lmode l .The meas urem en t pa rame te r s fo r t he l i nea r la t en t va ri -ab l e s a re e s t ima ted i n a m easurem en t mode l . These e s t i -ma te s a re used t o ca l cu l a te t he l oad ings and e r ro r va r i ancesfo r t he i nd i ca to r s o f t he i n t e rac t i on va r i ab le s i n equa t ions(2) and (3) . The interac t ion var iables are added to themode l , and t he ca l cu l a t ed l oad ings and e r ro r va r i ances fo rthe i nd i ca to r p roduc t s a re sp ec i f i ed a s f i xed r a the r t han f r eevar iables in the st ruc tura l model .Und e r t he Kenn y and Judd norma l i t y a ssumpt ions , andassuming the un id im ens iona l i t y o f each l i nea r l a t en t va r i -ab l e , P ing sugg es t ed t ha t t he l oad ings and e r ro r va r i ancesfo r t he Kenn y and Jud d p rod uc t i nd i cato r s o f an i n t e rac t i onor quadra t i c l a t en t va r i ab le need no t be e s t ima ted i n t hes t ruc tu ra l mo de l .2 Spec i f i ca ll y , he p rop osed t ha t pa rame te re s ti m a t es f r o m t h e m e a s u r e m e n t m o d e l b e u s e d t o c o m p u t ethe l oad ing and e r ro r va r i ance fo r p rod uc t i nd i ca to r s suchas xlz~ us ing equa t ions (2 ) and (3 ) . Then a s t ruc tu ra l mode lwi th XZ can be e s t ima ted wi th t he se ca l cu l a ted i n t e rac ti onindica to r loadings and erro r var iances (e .g . , ~1zl and 0~xlz l)speci f ied as f ixe d values (se t equal to the equat ion [2] and[3] va lues f or ~ lz l and 0~xl~l). This i s p ossible b ecause wi thsu f f i c i en t un id imens iona l i t y , t he measu remen t pa ram e te r sfor a la tent var iable ' s indica tors (e .g . , ~1 , ~,~1, Var[X],Var[Z] , 0~xl , and 0 ~ ) are t r iv ia l ly var iant be tween themeas uremen t and st ruc tural mod els (Anderson and Gerbing1988) . In o the r words , t he measuremen t pa rame te r e s t i -ma te s fo r t he i nd i ca to r s o f a su f f i c i en t ly un id imens iona ll a t en t va r iab l e change ve ry l i t tl e be tween the measu remen tand s t ruc tu ra l mode l s ( f r equen t ly on ly i n t he th i rd dec ima lp l ace ) . As a cons equence , t he l oad ings and e r ro r va r i ances

of p roduc t i nd i ca to r s can be de t e rm ined us ing a m easure -men t mode l and equa t ions (2 ) and (3 ) , t hen spec i f i ed a sconstants in the st ruc tura l model .P ing a l so po in t ed ou t t ha t t he su f f i c i en t un id imens ion -a l i t y a ssumpt ion enab l e s t he omiss ion o f t he non l inea rl a t en t va r i ab l e s f rom the measuremen t mode l wi th noe f fec t on t he pa rame te r e s t ima te s fo r t he l i nea r l a t en tva r i ab le s . B y the de f in i t i on o f un id imens iona l i t y , un id i -mens iona l cons t ruc t s a re una f fec t ed by t he p re sence o rabsence o f o the r l a t en t va r i ab l e s i n t he measuremen tmode l . S imi l a r ly , add ing o r de l e t i ng un id imens iona l c on-s t ruct s i n t he s t ruc tu ral m ode l does no t a f f ec t t he measure -men t pa rame te r e s t ima te s fo r t he added o r o the r l a t en tvar iables in the st ruc tura l model .The P ing t echn ique i nvo lves

1. ve r i fying indica tor norm al i ty ,32 . a ssuming the l a t en t va r i ab l es a re i ndependen t o fthe e r ro r t e rms , and t he e r ro r t e rms a re i nde -penden t o f e ach o the r ( a s t anda rd s t ruc tu ra l equa -t i on a ssumpt ion) ,3 . un id imens iona l i z ing each l i nea r l a t en t va r i ab l e ,4 . c en t e r ing t he obse rved va r iab l e s a t z e ro by sub-t r ac t i ng t he mean o f a va r i ab l e f rom each ca seva lue fo r t ha t va r i ab le ( see Bo l l en 1989) ,5 . e s t ima t ing l oad ings and e r ro r va r i ances fo r t hel i nea r i ndependen t va r i ab l e i nd i ca to r s us ing am e a s u r e m e n t m o d e l ,6 . u s ing t he se e s t ima te s t o ca l cu l a t e equa t ion (2 )and (3 ) e s t ima te s o f t he l oad ings and e r ro r va r i -ances fo r t he non l inea r l a t en t va r i ab l e i nd i ca to r s,7 . spec i fy ing equa t ion (2 ) and (3 ) e s t ima te s a s f i xedvalues in a s t ruc tura l model , then est imat ing tha tmode l , and8. repeat ing steps 6 and 7 as requi red to obta inmin ima l change i n t he measuremen t pa rame te r sbe tween two s t ruc tu ra l mode l e s t ima te s ( f r e -quen t ly no t necessa ry fo r s t rong ly un id imen-sional la tent var iables) .

The ba l ance o f t h i s a r t i c l e de sc ribe s t he f i e ld su rvey .

ME THODTo test the hypotheses, sa t i sfac t ion, a l te rnat ive a t t rac-t i veness , and ex i t i n t en t ion we re measu red wi th ba l anced5-po in t L ike r t - t ype sca l e s . The su rvey popu la t i on washa rdware r e t a i l e r s , and t he sampl ing f r ame was t he sub-sc r ip t i on l i s t o f a popu la r ha rdware t r ade pub l i ca t i on .Sampl ing i nvo lved n th name se l ec t i ons o f 100 p re t e s tnames and 600 f i na l t es t names . The p re t e s t r e sponses we reused t o v e r i fy the psych ome t r i c p rope r t i e s o f t he measure s .The re su l t i ng measure s appea red t o be con t en t va l id , un i -d imens iona l , and i n t e rna ll y and ex t e rna l l y cons i s t en t ( seeGerb ing and An de rson 1984) ; t hey each had a coe f f i c i en ta lpha o f . 8 o r above . The f i na l t e s t ma i l i ng y i e lded 288re sponses by f i rms a f t e r two pos t ca rd fo l l ow-ups . Thepsycho me t r i c p rope r t i e s o f t he measure s we re r eexamined


4/8

P i ng / A L T E R N A T I V E A T T R A C T I V E N E S S & E X I T IN T E N T I O N 3 6 7

F I G U R E 1L i n e a r - T e r m s - O n l y M e a s u r e m e n t M o d e l

~' S ~ / ~ ~ ~ EXISAT~ ALT

t t I l t l I t ] \ \~ 5 1 ~ s 2 ~ s 3 ~ s 4 ~ s 5 ~ a l ~ a 2 ~ a 3 ~ a 4 ~ e l ~ e 2 ~ e 3 ~ e l ~ e 5 ~ e 6

N O T E : S A T = s a t i s f a c t i o n , A L T = a l t e r n a t i v e a t t r a c t i v e n e s s , E X I =e x i t i n g .u s i n g t h e s e r e s p o n s e s a n d i t e m - t o - t o t a l c o r r e l a t i o n s , c o e f -f i c i e n t a l p h a c a l c u l a t i o n s , o r d e r e d s i m i l a r i t y c o e f f i c i e n t s( H u n t e r 1 9 7 3 ) , m u l t i p l e g r o u p a n a l y s i s ( A n d e r s o n , G e r b i n g ,a n d H u n t e r 1 9 8 7 ), a n d L I S R E L s i n g le f a c to r a n a ly s i s( J 6 r e s k o g 1 9 9 3 , p p . 2 9 7 , 3 1 3 ) . T h e m e a s u r e s w e r e c o n t e n tv a l i d , u n i d i m e n s i o n a l , a n d i n t e r n a l l y a n d e x t e r n a l l y c o n -s i s te n t ; t h e y h a d l a t e n t v a r i a b l e r e l i a b il i ti e s o f . 9 o r a b o v ea n d a v e r a g e e x t r a c t e d v a r i a n c e s o f . 7 o r a b o v e ( F o r n e l l a n dL a r k e r 1 9 8 1 ).

T h e i n d i c a t o r s f o r s a t i s fa c t i o n a n d a l t e r n a t iv e a t t r a c -t i v e n e s s w e r e t h e n z e r o c e n t e r e d , t h e n o r m a l i t y o f a ll t h ei n d ic a t o rs w a s a s s e s se d , a n d t h e m e a s u r e m e n t m o d e l f o rt h e l in e a r - t e r m s - o n l y m o d e l s h o w n i n F ig u r e 1 w a s e s t i-m a t e d u s i n g E Q S a n d m a x i m u m l ik e l ih o o d . T h e r e su l ti n gm e a s u r e m e n t p a r a m e t e r e s t im a t e s f o r s a t is f a c ti o n a n d a l -t e r n a t i v e a t t r a c t iv e n e s s a r e s h o w n i n T a b l e 1 .

B e c a u s e t h e la t e n t v a r i a b l e in t e r c o r r e l a t io n s w e r e a b o v e. 5 , l a t e n t v a r i a b l e d i s c r i m i n a n t v a l i d i t y w a s t e s t e d u s i n gt w o - g r o u p m e a s u r e m e n t m o d e l s . I n t hi s te s t, a m e a s u r e -m e n t m o d e l w i t h , f o r e x a m p l e , t h e s a t i s f a c ti o n - e x i t in t e n -t i o n p a t h f i x e d a t 1 w a s n e s t e d i n a n id e n t i c a l m o d e l w i t ht h a t p a t h f r e e d . O n e d e g r e e o f f r e e d o m t e s t s o f t h e d if f e r -e n c e s b e t w e e n t h e s e n e s t e d m o d e l s s u g g e s t e d t h a t s a t i sf a c -t io n , a l t e r n a t i v e a t t r a c t i v e n e s s , a n d e x i t i n t e n ti o n w e r ed i s t i n c t .T h e m e a s u r e m e n t m o d e l p a r a m e t e r e s t i m a te s w e r ec o m b i n e d t o p r o d u c e e q u a t i o n ( 2 ) a n d ( 3) l o ad i n g s a n de r r o r v a r i a n c e s f o r t h e s a t i s f a c t i o n - a l t e r n a t i v e a t t r a c t i v e -n e s s i n t e r a c t i o n i n d i c a t o r s s h o w n i n t h e F i g u r e 2 s tr u c t u r a lm o d e l . T h i s s t r u c t u r a l m o d e l w a s t h e n e s t i m a t e d u s i n gE Q S a n d m a x i m u m l ik e l ih o o d b y f i x i n g th e lo a d i n g s a n de r r o r v a r i a n c e s f o r t h e p r o d u c t i n d i c a t o r s a t th e T a b l e 1v a l u e s .

B e c a u s e t h e r e w e r e s l i g h t d i f f e r e n c e s i n t h e m e a s u r e -m e n t a n d s t r u c tu r a l m o d e l e s t im a t e s f o r th e m e a s u r e m e n tp a r a m e t e r s o f s a t is f a c t i o n a n d a l t e r n a t i v e a t t r a c ti v e n e s s , a ni t e r a ti v e a p p r o a c h w a s u s e d t o p r o d u c e t h e T a b l e 2 r e s u l ts .T h i s w a s a c c o m p l i s h e d b y r e c o m p u t i n g e q u a t i o n ( 2 ) a n d( 3 ) v a l u e s u s i n g t h e s t r u c t u r a l e q u a t i o n e s t i m a t e s o f t h em e a s u r e m e n t p a r a m e t e r s f o r s a t i s f a c t i o n a n d a l t e r n a t i v ea t t r a c ti v e n e s s , t h e n r e e s t i m a t i n g t h e s t r u c t u r a l m o d e l w i t ht h e s e r e v i s e d e q u a t i o n ( 2 ) a n d ( 3 ) v a l u e s f i x e d . T a b l e 2, a s

T A B L E 1M e a s u r e m e n t M o d e l R e s u l t sParameter Estimate Parameter Estimate

~'sl 0.79 es4 0.12~'sz 0.88 es5 0.10~s3 1.00 Ca1 0.27~ ' s 4 0.87 Ca2 0.24~5 0,94 Ca3 0.07~ a l 0.92 Ca4 0.24Xa2 0.90 e~i 0.529~a3 1.0 0 s 0.1 9~ 'a4 0 .78 s 0 .11~ i 0 . 8 4 e e4 0 . 3 2~ z 0 . 8 3 e e5 0 . 0 9~ 'e3 1 .00 Ee6 0 .1 2~e4 0 ,94 ~$AT 0.51~'e5 0. 96 (PSAT,~LT - -0 .37~e6 0.9 2 qbSAT,E X l - 0 . 4 3esl 0.16 ~ALT 0.85es2 0.13 ~ALT,EX~ 0.51es3 0 .10 ~ x I 0 .78

E q u a t i o n 2 a n d 3 e s ti m a t e s~'slal .533 0eslaI .257~'sla2 .509 0esla2 ,239IsXa3 .625 0~Xa3 .18 0~'s144 .38 4 0~sxa4 .207~'s2al .669 0es2a1 .242~ L s Z a 2 .639 0esza2 .224~243 .784 0es2a3 .151~ ' s 2 a 4 .482 0~sza4 .198~'s3al .852 0~3al .251~s342 .81 5 0es3a2 .231ks3a3 1.000 0es3a3 .140~'s344 .61 5 0es3a4 .208ks4al .657 0es4al .231~'s442 .62 8 0es4a2 .213~'s443 .77 0 0e.s4a3 .14 2~ k s 4 a 4 .473 0es4a4 .189~5 al .755 0esSal .227~saZ .722 0essa2 .209~5a 3 .885 0esSa3 .128~'s5a4 .54 4 Oes5a4 .188

a re s u l t, c o n t a i n s t h e e s t i m a t e s f r o m t h e s e c o n d s t r u c tu r a lm o d e l e s t im a t i o n . T h e T a b l e 2 d e g r e e s o f f r e e d o m f o r th es t ru c tu r a l m o d e l h a s b e e n r e d u c e d b y t h e n u m b e r o f p r e -v i o u s l y e s t i m a t e d p r o d u c t i n d i c a to r l o a d i n g s a n d e r r o rv a r i a n c e s ( 4 0 ; s e e T a b l e 1 ). 4

B e c a u s e t h e u s e o f p r o d u c t i n d i c a t o r s i n a s tr u c t u r a le q u a t i o n m o d e l r e n d e r s th e m o d e l f o r m a l l y n o n n o r m a l a n dm a x i m u m l ik e l ih o o d e s t i m a t i o n a s s u m e s m u l t iv a r i a t e n o r-m a l i t y , m a x i m u m l i k e l ih o o d s t a n d a r d e r r o r s f o r t h e s tr u c -t u r a l e f f e c t c o e f f i c i e n t s a r e n o t f o r m a l l y a p p r o p r i a t e( B o l l e n 1 9 8 9 ; s e e H u , B e n t l e r , a n d K a n o 1 9 9 2 ) . T h e e f f e c te s t im a t e s a p p e a r t o b e r o b u s t t o d e p a r t u r e s f r o m n o r m a l it y ,


5/8

368 JOURNALOF TH E ACADEMYOF M ARKETINGSCIENCE FALL 1994

F I G U R E 2S t r u c t u r a l M o d e l

E e l ~=2 E.3 ~s4 ~ s 5

~ I $ 2 ~3 $ 4 ~ 5

S A T " . ..

AL T

a I a 2 a 3 a ~

~ a l ~ a 2 ~ a 3 ~ a 4

S A T * A L T

~ e i ! Sel 9 " ~ e l

= - E X I : . . . r ., ,e 3 " , , - - - - ~ . 3

es 9 ' eese6 .,L (~e6

s 1 a I S l a 2. . . s l a 4 s 2 a l . . . $ 5 a 4/ t t f t~ s l a l ~ s l a 2 " 9 " ~ s l a 4 ~ s 2 a l " 9 . ~ s 5 a 4

NO TE: SAT = satisfaction,ALT = alternativeattractiveness,SAT*ALT= satisfaction-alternativeattractivenessinteraction,EXI = exiting.

bu t i t i s unknown whe the r t he s t anda rd e r ro r s and ch i -square sta t i s t ics are robust to depar tures f rom normal i ty .The s t ruc tu ra l mod e l was t he re fo re ree s t ima ted us ing a l e ssd i s t r i bu t i ona l l y dependen t e s t ima to r , EQS ' s Robus t e s t i -m a t o r , t o p r o d u c e m o r e d i s t r i b u t i o n a l l y a p p r o p r i a t es t anda rd e r ro r s and ch i - squa re s t a t i s t i c s (Sa to r ra andBen t ler 1988; see Ben t ler 1989, p . 217 e t seq. ; Hu, Bent ler ,and Kano 1992) .The s t ruc tu ra l mode l w as t hen ree s t ima ted i n two s t epsto a sse ss t he im prove men t in f i t o f add ing t he i n t e rac t i ont e rm . The re su l t sugges t ed t ha t add ing t he i n t e rac t ion t e rmsign i f i can t ly improv ed m ode l f i t ( see t he i nc remen ta l f i ti ndex i n Tab le 2 ). The F igure 2 mod e l was a l so e s t ima tedu s i ng t h e K e n n y a n d J u d d / C O S A N a p p r o a c h fo r c o m p a ri -son . Because COSAN prov ides no d i s t r i bu t i on - f ree e s t i -m a t o r s , o n l y m a x i m u m l i k e l ih o o d e s t im a t e s w e r ep r o d u c e d .In add i t ion , Tab le 2 shows OL S reg re ss ion e s t ima te s fo rthe F igure 2 mode l a s a d i r ec t i ona l po in t o f r e fe rence . 5Regre ss ion e s t ima te s a re known to be b i a sed and i ne f f i -c i en t fo r va r i ab l e s measured wi th e r ro r (Busemeye r andJones 1983) . As a r e su l t , they p rov ide on ly an i nd i ca t ionof t he d i r ec t i on (pos i t i ve o r nega t ive ) o f t he F igure 2e f fec ts . These r eg re ss ion e s t ima te s we re p roduced by av -eraging the indica tors for sa t i sfac t ion, a l te rnat ive a t t rac-tiveness, and e xit intention, and crea ting the interaction termby fo rming the p roduc t va r i ab l e sa t i s f ac t i on -a l t e rna t i veat t rac t iveness in each case .

D I S C U S S I O NT h e P i n g , K e n n y a n d J u d d / C O S A N , a n d r e g r e s s i o nresul ts were di rec t ional ly s imi lar , and the t va lues for theP i n g t e c h n iq u e a n d th e K e n n y a n d J u d d / C O S A N a p p r o a c hgene ra l l y le ad t o t he same in fe rences . The max imum l ike-

l i hood and Robu s t s t anda rd e r ro r e s t ima te s w e re a l so s imi -l ar , whe reas t he ch i - squa re e s t ima te s w e re no t . Beca use t heRobu s t e s t ima to r does no t a ssume mu l t i va r i a te no rma l i t ya s t he max imum l ike l i hood e s t ima to r does , t he Robus test imato r resul t s wi l l be interpre ted.Based on t he Rob us t e s t ima to r , the mod e l f i t t he da ta ,and t he hypo th es i zed a ssoc i at i ons we re suppo r t ed . Sa t i s -f ac t i on mod e ra t ed t he a l t e rna t i ve a t t r ac t iveness -ex i t i n t en -t i o n a s s o c i a t i o n , a s s h o w n b y t h e s i g n i f i c a n t e f f e c tcoeff ic ient for the a l te rnat ive a t t rac t iveness -exi t in tent ioninterac t ion (see Table 2) . In addi t ion, sa t i sfac t ion a t tenu-a ted the a l te rnat ive a t t rac t iveness-exi t in tent ion associa-t i on a s t he l eve l o f sa t i s f ac t ion i nc rea sed . Tab le 3 showsthe a l t e rna t i ve a t t r ac t i veness -ex i t in t en t i on e f fec t coe f f i -c i en t a t se l ec ted l eve l s o f sa t i s f ac ti on . As show n in t h i st ab le , a t h ighe r l eve l s o f measured sa t is f ac t ion ( e .g . , above4 , wh ich co r re spo nded to "ag ree") , t he a l t e rna t ive a t t rac -t i veness -ex i t i n t en t ion a ssoc i a t i on w as no t s i gn i fi can t. A tlower levels of sa t i sfac t ion, the a l te rnat ive a t t rac t iveness-exi t in tent ion associa t ion w as sta t i s t ica l ly s igni f icant .Thes e r e su lt s ma y h ave impl i ca t i ons fo r p rac t i t ione r s .The obse rved l ack o f a ssoc i a t i on be tween ex i t i n t en t i onand a l te rnat ive a t t rac t iveness a t h igher levels of sa t i sfac-t ion in this s tudy suggests tha t increases in the a t t rac t ive-ness o f a l t e rna t i ve s ( compe t i t i on ) may no t necessa r i l yt empt sa t i s f i ed cus tomer f i rms t o cons ide r ex i t i ng t he i rcu r ren t buye r - se l l e r r e l a ti onsh ip . In o the r w ords , an a l t e r -na t i ve ' s e f fo r t s t o be m ore a t t r ac t i ve to a t a rge t se t o f f i rmsmay no t , by t hemse lves , i nc rea se ex i t i n t en ti ons i n t he sef i rms ; dec rea sed sa t i s f ac t i on i n t he t a rge t f i rms m ay a l sobe r equ i red . On ly fo r t he l e ss sa t is f i ed f i rms i n t h i s s t udywere changes i n a l t e rna t ive a t t r ac ti veness a ssoc i a t ed wi thchanges i n ex i t i n t en ti ons . For sa t i s f i ed f i rms , changes i na l t e rna t i ve a t t r ac t i veness we re no t a ssoc i a t ed wi th ex i tin tent ion.Th i s f i nd ing sugges t s t ha t l e ss sa t is f i ed f irms m ay bevu lne rab l e t o compe t i t i ve mov es a imed a t inc rea s ing com-pe t i t o r a t t r ac t i veness , whe reas more sa t i s f i ed f i rms mayno t be so vu lne rab l e . Th i s i n t u rn may p rov ide some ins igh tinto a basic tenet in the customer service l i te ra ture , tha tsupe r io r cus tom er se rv i ce c rea t e s sa t i s fac t i on , wh ich l eadsto a compe t i t i ve advan tage ( see Dav ido w and Ut t a l 1989) .These r e su l t s sugges t no t on ly t ha t sa t is f ac t ion m ay reduc eex i t i n t en ti on bu t a l so t ha t i t may reduce t he a t t r ac ti venesso f t h e c o m p e t i t io n . H e n c e s u p e r i o r c u s t o m e r s e r v i ce m a ya l so r educe ex i t i n t en t i on and t he a t t r ac t i veness o f t hecomp e t i t ion ' s sup e r io r se rv i ce .The m ode l exp l a ined 65 pe rcen t o f t he va r i ance i n ex i ti n t en t i on , wh ich i s no t ab l e fo r marke t i ng s tud i e s . Th i sre su l t sugges ts t ha t whe reas unm ode led an t eceden t s o f ex i ti n t en t i on may rema in t o be i den t i f i ed , t he i r combinedcon t r i bu t ion t o exp l a in ing va r i ance i n ex i t i n t en t i on i n t h i s


6/8

P i n g / A L T E R N A T I V E A T T R A C T I V E N E S S & E X I T I N T E N T I O N 3 6 9

T A B L E 2S t r u c t u r a l M o d e l E s t i m a t i o n R e s u l t s

S t r u c t u r a l E q u a t i o n A n a l y s i s E s t i m a t e sP a r a m e t e r E s t i m a t e P a r a m e t e r E s t i m a t e

t ValueM L a R O B U S T b

~ s l 0 . 7 9 e s 5 0 . 1 0~ s 2 0 . 8 8 E a l 0 . 2 7~s3 1 .00 Ea 2 0 .24~ b s 4 0 . 8 7 e a 3 0 . 0 8Xs5 0 .94 e a 4 0 .23~ L a l 0 . 9 2 E e l 0 . 5 3~ 'a 2 0 .90 e e 2 0 .19La 3 1 .00 e e 3 0 .11~a 4 0 .78 Ee 4 0 .32~ 'e] 0 .84 e e 5 0 .09Xe 2 0 .83 e e 6 0 .12Le 3 1 .00 ( ~ S A T 0 .51~ 4 0 . 9 4 ~ S A T ,A L T - 0 . 3 7~ 5 0 . 9 6 ( ~ A L T 0 . 8 4~ 6 0 . 9 2 ( ~ S A T ,A L r 1 7 . 9 5e s l 0 . 1 6 ~ E X I 0 . 3 4es 2 0.1 3 ~EXI, SAT --0.35Es3 0.10 [~EXI,ALT 0 .65e s4 0 .12 ~EXI , SAT,A L T - 0 . 0 5

F i t i n d i c e sC h i - s q u a r ep v a l u e o f c h i - s q u a r e v a l u eB e n d e r ( 1 9 8 9 ) c o m p a r a t iv e f i t i n d e xN u l l m o d e l Z 2C h i - s q u a r e d e g r e e s o f f r e e d o mS q u a r e d m u l t i p l e c o r r e l a t i o n f o r E X IT o t a l c o e f f i c ie n t o f d e t e r m i n a t i o nI n c r e m e n t a l f i t i n d e x : c h i - s q u a r e d i f fe r e n c e

p v a l u eK e n n y a n d J u d d / C O S A N e s t im a t e s

O L S r e g r e s si o n e s t i m a t esD e p e n d e n t v a r i a b le

E X I

~EXI, SAT~EXI, ALT[~EXI,SAT,AL T

In d ep en d en t va r i a b l e b co e f f i c i en t t ValueS A T - . 2 8 7 - 7 . 3A L T . 7 4 5 6 . 0

S A T A L T - . 1 0 0 - 1 . 8

- - 4 . 5 9 - 4 . 7 91 0 . 5 8 9 . 6 1- 5 . 6 4 - 5 . 4 5

8 8 , 2 4 8 3 8 0. 0 0 0 1.000. 0 0 0 1.000

2 5 , 8 8 4 1 8 , 8 3 15 5 5 5 5 5.6 5.6 5

3 . 9 1.0 4

- 0 . 3 4 4 . 4 20 . 6 7 1 0 . 6 7

- 0 . 0 4 5 . 4 1

F va l u e a n d p R 27 9 . 5 2 ( . 0 0 ) . 5 2

a . M L = m a x i m u m l i k e l i h o o d e s t im a t e .b . R O B U S T = M L e s t im a t e w i t h E Q S R o b u s t o p t io n .

c o n t e x t m a y n o t b e l a r g e . F o r t h e b u s y c h a n n e l m a n a g e r ,t h is i n t u rn sugges t s t ha t sa t i s f ac t i on mai n t ena nce m ay besu f f i c i en t fo r r e l a t i onsh i p ma i n t enance .T h e t v a l u e s f o r t h e m a x i m u m l ik e l i ho o d c o e f f i c ie n tes t i mat es and t hose fo r t he R obus t op t i on were s i mi l a r ,whereas t he ch i - square es t i mat es were no t ( see Tab l e 2 ) .Th i s sugges t s t ha t s t andard e r ro r s p roduced by t he P i ngt e c h n i q u e m a y b e r o b u s t t o p r o d u c t i n d i ca t o r n o n n o r m a l it ybu t t ha t t he ch i - square s t a ti s ti c i s no t , and es t i mat o r s t ha t

a r e l es s d i s tr i bu t i ona l ly depend en t shou l d be u se d fo r t hech i - square s t a t is t ic w i t h t he P i ng t echn i que .

S U M M A R YT h e s t u d y i n v e st i ga t e d a h y p o t h e s i z e d m o d e r a t i n g e f -f ec t o f overa l l r e l a t ionsh i p sa t i s f ac t i on on t he as soc i a t i onbe t we en ex i t in t en t i on and t he a t t r ac t i veness o f an a l t e rna-


7/8

3 7 0 J O U R N A L O F T H E A C A D E M Y O F M A R K E T I N G S C IE N C E F A L L 1 9 94

T A B L E 3S a t i s f a c ti o n M o d e r a t i o n o f t h e A l t e r n a t i v eA t t r a c t i v e n e s s - E x i t I n t e n t io n A s s o c i a t i o n

SAT Valuea A L T Coe f f ic i en tb SE of the Coefficient c t Value1 0.596 0.1239 4.802 0.539 0.1859 2.893 0.482 0.2510 1.914 0.425 0.3173 1.335 0.368 0.3841 0.95

a. Sat i sfact ion ranged from 1 (low) to 5 in the s tudy."b . The coeffic ien t of ALT is g iven by .65ALT - .05SAT*ALT =(.65 - .05SAT)ALT.c . Th e s t an d a rd e r ro r o f t h e A LT co e f f i c i en t i s g i v en b y"~Var(bALT-bsATSAT)

= ~/Var(bALT)+ SAT2VaI(bsAT)+ 2SA TCov(bALT,bsAT).

t ive relat ionship in a market ing channel . The resul ts sug-ges t tha t the hyp o thes ized modera t ing e f fec t i s p resen t inthe s tud y context , and th at at h igher levels of sat is fact ion ,there w as no a l t e rna tive a t t rac t iveness -ex i t in ten t ion e f fec tin the s tudy popu la t ion.The inves t iga t ion used the P ing t echn ique and EQS toes t imate non l inear l a ten t var iab le e f fec t s . The resu l ts weree q u i v a le n t to t h o s e o f K e n n y a n d J u d d / C O S A N a n d w e r egenera l ly p laus ib le when compared to OLS reg ress ionresu l t s . In add i t ion , max imum l ike l ihood and Robus ts tandard e r ro r es t imates u s ing the P ing t echn ique weres imi la r , sugges t ing tha t max imum l ike l ihood e s t ima t e sf rom the P ing techn ique may be robus t to the depar tu ref rom normal i ty inheren t when p roduc t ind ica to rs a re u sed .The max imum l ike l ihood and Robus t ch i -square es t i -mates , however , were very d i f fe ren t . Th is sugges t s tha tma x im um l ike l ihood ch i -square es timates a re a f fec ted byproduc t ind ica to r nonnormal i ty and tha t ch i -square es t i-mates based on l es s d i s t ribu t ionaUy dependen t es t imato rsshou ld be u sed wi th the P ing t echn ique .

A C K N O W L E D G M E N T ST h e a u t h o r w i s h e s t o t h a n k E R o b e r t D w y e r , L e o n a A i k e n ,

Le s l i e H a y d u k , R o b e r t P e t e rs o n , a n d t w o a n o n y m o u s r e v ie w e r sf o r t h e i r c o n t r i b u t i o n s t o t h i s a r ti c l e .

N O T E S1 . L I S R E L 8 r e d u c e s t h e s p e c i f i c a t i o n e f f o r t u s i n g e q u a t i o n s

b u t g e n e r a t e s t h e d m n m y v a r i a b l e s f or e q u a t io n s ( 2) a n d( 3 ) u s i n g p a r t i a l d e r i v a t i v e s . L a r g e r m o d e l s , h o w e v e r , s t i l lr e q u i r e c o n s i d e r a b l e s p e c i f i c a t i o n e f f o r t , a n d t h e m a n yd u m m y v a r i a b l e s t h a t r e s u lt p r o d u c e l a r g e m a t r i c e s th a tc a n c r e a t e e s t i m a t i o n p r o b l e m s ( P i n g 1 9 93 b) .2 . T h e K e n n y a n d J u d d n o r m a l i t y a s s u m p t i o n s w e r e s ta t e da b o v e e q u a t i o n ( 2) .3 . M a x i m u m l i k e l i h o o d a n d g e n e r a l i z e d l e a s t s q u a r e s e st i -m a t e s a r e r o b u s t t o d e p a r t u r e s f r o m n o r m a l i t y ( A n d e r s o na n d A m e m i y a 1 9 85 , 19 8 6; B o o m s m a 1 98 3; B r o w n e 1 98 7;

4 ,5.

H a r l o w 1 9 85 ; S h a r m a , D u r v a s u l a , a n d D i l l o n 1 9 89 ;T a n a k a 1 9 84 ), a n d s t r ic t m u l t i v a r i a t e n o r m a l i t y m a y n o t b er e q u i r e d .T h i s a d j u s t m e n t t o th e d e g r e e s o f f r e e d o m w a s s u g g e s t e db y L e s li e H a y d u k ( p e r s o n a l c o m m u n i c a t i o n ) .T h e K e n n y a n d J u d d a p p r o a c h a p p a r e n t l y h a s b e e n a c -c e p t e d w i t h o u t a n y e m p i r i c a l j u s ti f ic a t io n . K e n n y a n d J u d d( 19 8 4) r e p o r t e d e s t i m a t e s f o r o n e s y n t h e t i c d a t a s e t f o r a ni n t e r a c ti o n a n d o n e f o r a q u a d r a ti c . T h e r e h a v e b e e n n of u r t h e r i n v e s t i g a t i o n s t o ju s t i f y o r e v a l u a t e t h e i r t e c h n i q u e ,a n d i ts p e r f o r m a n c e u n d e r v a r y i n g c o n d i ti o n s i s u n k n o w n .

R E F E R E N C E SAiken, Leon a S. and Stephen G. West . 1991. Mu ltiple Regression: Testing

and Interpreting Interactions. Newbury Park , CA: Sage.Anderson, Jame s C. and David W. Gerbing . 1988. "St ructural Equat ion

Mo d e l i n g i n Pract ice : A Rev i ew an d R eco mm en d ed Tw o -Step A p -proach ." Psycholog ical Bul let in 103 (May): 411-423.

Anderson, James C. , David W. Gerbing , and John E. Hunter. 1987. "Ont h e A ssessmen t o f U n i d i men s i o n a l Measu remen t : In t e rn a l an d Ex te r -nal Consistency , and O veral l Consis tency Cri teria ." J o u r n a l o f M a r -ket ing Research 24 (N ovem ber): 432-437.

Anderson, T heodore W. and Yasuo Amem iya. 1985. "The Asym ptot icN o rma l D i s t r ib u t i o n o f Es t i ma t o rs i n Fac t o r A n a l y s i s u n d e r G en e ra lCondi tions." Technical Re port 12 . Econom etric Workshop. S tanfordUniversity.

. 1 9 8 6 . "A sy mp t o m a t i c D i s tr i b u t io n i n Fac t o r A n a l y s i s an d L i n -ear St ructural Rela t ions." Technical Report 18 . Econometric Work-shop. Stanford University.

Bentler, Peter M. 1989. EQ S Structural Equat ions Program Manual . L osAngeles: BMDP Statistical Software.Bol len , Ke nneth A. 1989. Structural Equat ions wi th Latent Var iables .

New York: Wiley.Bo o msm a , A n n e . 1 9 8 3 . On the R obus tnes s o f L I SR E L ( Maximum L ike l i -hood Es t imation) agains t Sma ll Sample Size and Nonnormali ty. D i s -

serta t ion . Univers i ty of Gron ingen.Brow ne, Michael W. 1987. "Rob ustness of Sta t i s t ica l Inferenc e in Factor

A n a l y s i s an d Re l a t ed Mo d e l s . " Biometrika 74 (Ju ne): 375-384.Busemeyer, Jerom e R. and Law rence E. Jones. 1983. "Analy sis of

Mu l t ip l icat ive Com binat ion Rules When the Caus al Variables AreMeas ured wi th Error." Psycholog ical Bul let in 93 (M ay): 549-562.

Davidow, W il l iam H. and Bro U t ta l . 1989. Total Cus tom er Service. N ewYork: Harper.

Dwyer, E Rob ert and Sejo Oh. 1987. "Outp ut Sector Munificen ce Effectson the In ternal Pol i tica l Econ omy of M arket ing Chan nels ." Jour na l o fMar ke t ing R es ear ch 24 (Novem ber): 347-358.

Dwyer, E Robert , Paul H. Schurr, and Sejo Oh. 1987. "DevelopingBuyer-Seller R ela t ionships." Jour na l o f M ar ke t ing 51 (Apri l ) : 11-27 .

Ford , David I . 1980. "The Development of Buyer-Sel ler Rela t ions inIndustria l M arkets ." E ur opean Jour na l o f M ar ke t ing 14(5/6): 339-353.

Fornell , Claes and D avid E Larker. 1981. "Evaluat ing St ructural Equa-t i o n Mo d e l s w i t h U n o b se rv ab l e V a ri ab l es an d M easu remen t Er ro r ."Jour na l o f M ar ke t ing R es ear ch 18 (February): 39-50.

G ad d e , L a rs -Er i k an d La rs -G u n n a r Ma t t s so n . 1 9 87 . "S t ab i l i t y an dCh an g e i n N e t w o rk Re l a t i on sh i p s . "Internat ional Journ al of Researchin Market ing 4(1): 29-41.

Gaski , John and John R. Nevin . 1985. " l 'he Different ia l Effects ofExercised an d Unex ercised Pow er Sources in a Ma rket ing Chann el ."Journal o f Market ing Research 12 (May): 130-142.

G arb i n g , D av i d W . an d James C . A n d e rson . 1 9 8 4. "A n U p d a t ed Pa rad i g mfo r Sca l e D ev e l o p men t In co rp o ra t i ng U n i d i men s i o n a l i t y an d I t s A s -se ssmen t . " Journal o f Market ing Research 25 (May): 186-192.


8/8

Pi n g / A LTERN A TIV E A TTRA CTIV EN ESS & EX IT IN TEN T IO N 3 7 1

Harlow, Lawrence L. 1985. Behav ior of Some El l ipt ical Theory Es t ima-tors with Nonnormal Data in a Covariance Structures Framework: AMonte Carlo Study. Dissertation. University of California, Los Angeles.

Hayduk, L esl ie A. 1987. Structural Equat ion Mod el ing wi th LISREL:E s s en t ia l and A dvances . Bal timore , M D: Johns Hopkins Universi tyPress.Hu, Li-tze, Pe ter M. Bentler, and Yutaka Kano. 199 2. "Can Test Statisticsi n Co v a r i an ce S t ru c t u re A n a l y s i s Be Tru s t ed ?" Psycholog ical Bul let in112 (Septem ber): 351-3629

Hunter, Jo hn E. 1973. "M ethods for Reordering the Correla t ion Matrixto Faci l i ta te Visual Inspect ion and Prel iminary Cluster Analysis ."Jour na l o f E duca t iona l Meas ur emen t 10 (Spring): 51-61.

Jt ireskog, Karl G. 1993. "Testing St ructural Equat ton M odels ." In TestingStructural Equat ion Models . Eds. Ke nneth A. B ol len and J . Scot t Long.New bury Park , CA: Sage, 294-3169

J/Sreskog, Karl G. and D ag S6rbom. 19899LISREL 7: A Guide to theProgram and Appl icat ions . Sec ond Edition. Chicago: SPSS Inc.

Kenny, David and C harles M. Judd. 1984. "Est im at ing the Nonl inea r andInteract ive Effects of Latent Variables ." Psycholog ical Bul let in 9 6(July): 201-210.

Ping , R obert A. , Jr . 1993a. "T he Effects of S at i sfact ion and St ructuralConst ra in ts on R etai ler Exi ting , Voice , Loyal ty , O pportunism, andN eg l ec t . " Jour na l o f R e ta i li ng 69 (Fail): 320-352.

9 1993b. "L atent Variable Interaction an d Quadratic Effect E stima-tion: A Suggested Approach." Technical Report. Wright State University.

Ping , Robert A. and E Robe rt Dwyer. 19919"A Pre l i mi n a ry Mo d e l o fRelat ionship Terminat ion in Market ing Channe ls 9 In A dvances i nDistribution Channel Research. Ed. Gary Frazier . Greenw ich , CT: JAI,215-233.

Rukert, Robe rt W. and G i lbert A. Churchi ll . 1984. "Rel iab i l i ty andV a li d it y o f A l t e rn a t iv e Measu re s o f C h an n e l M emb er Sa t i s fac t io n . "Journa l of Market ing Research 21 (May): 226-2339

Satorra , A lbert and Peter M. Bent ler. 1988. "Scal ing Correct ions forChi-squared Sta t is t ics in Covarianc e St ructure Analysis ." P r oceed ingsof the Ame rican Stat is t ical Associat ion. Alexandria, VA.

Sharma, S ubhash , Srin ivas Durvasula , and W il l iam R. Di llon . 1989."So m e Resu lt s o n t h e Beh av i o r o f A l t e rn a ti v e Co v a r i an ce S t ru c tu reEs t i ma t i o n Pro ced u re s i n t h e Pre sen ce o f N o n n o rma l D a t a . " Jour na lof Mar ket ing Research 26 (May): 214-221.

Tanaka, Jeffrey S. 1984. Some R esul ts on the Es t imat ion o f Covar ianceStructure Models. Disserta tion . Unive rsi ty of Cal i forn ia , Los Angeles.

A B O U T T H E A U T H O RR o b e r t A . P i n g , J r . is a n a s s is t a n t p r o f e s s o r i n th e D e p a r t m e n to f M a r k e t i n g a t W r i g h t S t a t e U n i v e r s it y , D a y t o n , O H . H e o b -t a i n e d h i s P h . D . a t t h e U n i v e r s i t y o f C i n c i n n a t i . H i s r e s e a r c hi n t e r e s ts i n c l u d e t h e p o l i ti c a l e c o n o m y o f m a r k e t i n g c h a n n e l s a n dn o n l i n e a r e s t i m a t i o n f o r l a t e n t v a r i a b le s .

full text nomi 3

Documents