Multi-Channel Conflict Analysis While Using Banks as Distributors - An Evidence of Insurance Marketing

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1 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com Mult-Channel Conflct Analyss Whle Usng Banks as Dstrbutors - An Evdence of Insurance Marketng Chang Ku Fan 1, Hung-Chh La 2 and Yu-Nng Tan 3 1 Professor, Department of Rsk Management and Insurance, Shh Chen Unversty. 2 Assstant Professor, Department of Rsk Management and Insurance, Shh Chen Unversty. 3 Graduate Student, Department of Fnance and Bankng, Shh Chen Unversty Abstract Insurers have adopted multple channels of dstrbuton to sell nsurance products durng the past decade. Although multple channel dstrbuton strateges provde tremendous benefts to nsurers, but there are many causes whch lead to mult-channel conflct. The queston of how to dentfy the factors that cause dstrbuton channel conflcts has receved scant attenton n the lterature and has not been approprately nvestgated n pror studes. Ths study employed methods of Delph study, TOPSIS, and C.A. to dentfy the factors that cause dstrbuton channel conflcts n the nsurance ndustry and to assess the frequency of factors that cause nsurance dstrbuton channel conflct. Accordng to result of ths study the most mportant three causes leadng to mult-channel conflct are dfferences n percepton of realty used n jont decson makng, usng coercve powers, and ncompatblty of goals. Thus, admnstrators of banks or nsurance companes wll redesgn ther organzaton dscplnes or management polces accordngly whch can mprove the performance of multple channel strategy. Keywords: Mult-channel conflct, Technque for Order Preference by Smlarty to Ideal Soluton (TOPSIS), Conjont Analyss (CA). 1. INTRODUCTION As a result of changes n purchasng behavor, the nature of products and servces, nformaton technques, and the cost of dstrbuton, ncreasngly dverse and complex dstrbuton strateges have emerged. Employng varous channels to serve a gven market s becomng a major part of the marketng plans of product and servce supplers [9, 17, 30]. In ths context, to ncrease market coverage, decrease dstrbuton costs, and target the approprate segments, nsurers have adopted multple channels of dstrbuton to sell polces durng the past decade. The popular channels that have been employed by provders nclude Internet-led channels, company-led channels, bank-led channels, agent-led channels, broker-led channels, and other cybermedares (e.g., telephone and TV statons) [22, 28, 38]. Competton n the nsurance ndustry s at an all-tme hgh, whch challenges provders to retan exstng customers whle attractng new ones. Most banks and nsurers are lookng for the same thngs better ways to retan customers and to ncrease ncome. Although multple channel dstrbuton strateges provde tremendous benefts to nsurers, they also trgger certan challenges. Interestngly, many pror studes (e.g., [17, 28]) have found that both ntrachannel and nterchannel conflct may have postve and negatve effects on dstrbuton performance. Webb and Hogan (2002) [17] also found that channel performance s sgnfcantly affected by the frequency of channel conflct. Mnmzng the occurrence of channel conflct s a means of mprovng channel performance. Unfortunately, pror studes have provded few nsghts for nsurance decson makers related to multple channel conflct. Objectve and scentfc approaches to academc research are lmted, especally n terms of explorng the causes of multple channel conflct n an nsurance sector and nvestgatng the frequency of causes of channel conflct. The purpose of ths research s to dentfy the factors that cause dstrbuton channel conflcts n the nsurance ndustry. Ths study also contrbutes to both the nsurance marketng lterature and the nsurance marketng management lterature by assessng the frequency of the factors that cause nsurance dstrbuton channel conflct. 2. LITERATURE REVIEW 2.1. Motvatons of Employng Multple Dstrbuton Channels The prncpal ncentves for frms to develop multple dstrbuton channels are to ncrease market share, to reduce costs [8, 14, 21], to reach target markets [13, 26], to reach new market segments [10, 21], and to share nformaton and knowledge about customers [21]. Thus, many frms worldwde have adopted multple channel marketng strateges. Ths ncreasngly prevalent trend, whch s also known as multple dstrbuton strategy, has dramatcally changed the demands that are placed on channel managers [17, 24]. Volume 3, Issue 2, February 2014 Page 199

2 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com 2.2. Conflcts of Employng Multple Dstrbuton Channels Channel conflct between channel members tends to be a very negatve force whch may lower profts for all partes [32]. Many studes have shown channel conflct s nevtable, but not all conflcts are equally dangerous. The adopton of a multple channel strategy yelds both benefts and drawbacks for frms. Many pror studes have argued that the performance of marketng dstrbuton s affected by channel conflcts. Coelho et al. (2003) [5] evaluated 62 U.K. fnancal servce frms and found that mult-dstrbuton channels were assocated wth hgher sales performance but lower channel proftablty. Sngh (2006) [31] also found that a channel s effcency and ts conflct were negatvely correlated. Smlarly, a study by Chen and Chang (2010) [24] found that nsurers that adopted a drect dstrbuton system were more effcent than those that employed a mult-dstrbuton system. Although a multple channel strategy provdes many advantages for frms, t also presents certan dsadvantages. The adopton of a multple channel may create conflct n the demand for nternal company resources and conflctng objectves for varous channels, and such conflcts ncrease the potental for customer confuson and dssatsfacton [13, 17, 18, 21]. Poorly ntegrated multple-channels may engender n customer dssatsfacton wth the frm's multchannel strategy resultng n loss of customers to compettors [1]. Moreover, channel conflct may also stems from goal ncompatblty, clashes over doman, and dfferng perceptons whch lead to poor channel performance as well [39] The Factors Causng Dstrbuton Channel Conflct To manage channel conflct, t s necessary for marketng dstrbuton managers to dentfy the causes of channel conflct and to mnmze ths conflct. Many channel conflct studes (e.g., [17, 39]) agree that there are two types of channel conflct. The frst type s ntrachannel conflct, whch s also termed vertcal conflct and refers to the frcton between a frm and the members of ts dstrbuton channels. It often arses when actons that may be good for an nsurance company also result n ncreased competton for ts current dstrbuton channel [39]. The second type s nterchannel conflct, whch s also termed horzontal conflct and refers to the frcton between two or more channels at the same level. Horzontal conflct stems prmarly from competton between channel partcpants and the fear of channel cannbalsm [39]. Unfortunately, horzontal conflct, f not controlled, wll turn nto vertcal conflct [39]. Interchannel conflct s dstnct from ntrachannel conflct, whch has been the focus of most studes. Interchannel conflct occurs when one coalton beleves that another coalton s seekng to gan scarce resource at ts expense [15]. Therefore, marketng management expects multple channel conflct to be a common occurrence when frms have multple channels and lmted resources. A lack of channel management on the suppler s part s also a cause of nterchannel conflct because t s lkely to produce a confusng stuaton n whch nterchannel competton becomes nterchannel conflct [17]. Many other studes have observed that poorly desgned channel structures, poor algnment wth customer segments, communcaton dffcultes, and the use of coercve powers consttute addtonal causes of nterchannel conflct. Conflct between authorty and responsblty occurs when an unsutable channel structure desgn s used. As a result, channel mplementaton and performance suffer [23]. In addton to napproprate channel structure desgn, targetng the same customers s also a cause of channel conflct. Because most producers sell through several channels smultaneously, channels typcally compete to reach the same consumer segments. Another cause of channel conflct, n addton to relyng on poorly desgned channel structures, targetng the same customer segments, and experencng communcaton dffcultes, s the use of coercve powers. Cather and Howe (1989) [4] found that conflct was postvely correlated wth the use of coercve power for both ndependent and exclusve agency nsurers; ths result suggests that puntve agency management strateges are assocated wth ncreased tenson between nsurers and agency channels. In the context of multple channels, t s clearly necessary to dentfy the causes of ntrachannel conflcts [39]. The studes by Rosenberg and Stern (1970) [19] and Rosenberg (1974) [20] ndcated that goals, domans (roles), and perceptons are causes of ntrachannel conflct. The authors explaned that goals between and among vertcally lnked frms often dffer and may be ncompatble and even mutually exclusve. In the nterdependent arrangement of frms n a sngle channel system, one frm s goals may comprse another frm s constrants, resultng n conflct. Smlarly, the channel system features role nterdependence n whch one frm depends on another frm for work nputs and decson premses [34] Relatonshp between Channel Conflct and Performance The relatonshp between channel conflct and ts performance has been explored n prevous studes. Rosenberg (1974) [20] found that channel conflct may affect a dstrbutor s performance. Webb (2002) [16] and Chen and Chang (2010) [24] obtaned smlar fndngs and showed that multple channels enable frms to capture customers n dfferent market segments and yeld hgher sale volumes, although such channels also pose many challenges, such as channel conflcts. Therefore, the management or resoluton of channel conflcts largely determnes the actual consequences n terms of fnancal ndcators of performance. However, merely dentfyng the causes of multple channel conflct cannot decrease channel conflct or mprove the performance of dstrbutors. Webb and Hogan (2002) [17] found that channel performance s sgnfcantly affected by the frequency of channel conflct. In other words, dstrbuton admnstrators who want to mprove a channel s performance must dentfy and manage the most frequent causes of channel conflct. Volume 3, Issue 2, February 2014 Page 200

3 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com 3. METHODOLOGY The methodology n ths study conssts of two phases (see Fgure 1). In the frst phase, ths study employed the modfed Delph study to dentfy the causes of nsurance mult-channel conflct. In the second phase, the relatve frequency of cause leadng to mult-channel conflct was assessed by employng a conjont analyss (C.A.). However, Har et al., (1998) [12] suggested and fgured out the C.A. s useful for measurng up to about sx attrbutes. Before conductng C.A. to calculate the relatve frequency of cause trggerng off mult-channel conflct, ths study employed Technque for Order Preference by Smlarty to Ideal Soluton (TOPSIS) prevously to shortlst the causes dentfed by modfed Delph study. Fan (2007) [3] have even used TOPSIS successfully for the shortlst selecton of nputs before conductng Data Envelopment Analyss (DEA). Wthout adopt, TOPSIS s an dea method to select approprate attrbutes n the C.A. The Delph method, TOPSIS method and the C.A. are descrbed as follows: Fgure 1. The Structure of the Methodology 3.1. TOPSIS Developed by Hwang and Yoon (1981) [2], TOPSIS attempts to defne the deal soluton and the negatve deal soluton. The deal soluton maxmzes the beneft crtera and mnmzes the cost crtera, whereas the negatve deal soluton maxmzes the cost crtera and mnmzes the beneft crtera. The optmal alternatve s the closest to the deal soluton and the farthest from the negatve deal soluton. Alternatves n TOPSIS are ranked based on the relatve smlarty to the deal soluton, whch avods havng the same smlarty for both deal and negatve deal solutons. The method s calculated as follows: Establshng the performance matrx A j 1n j A 2n D, A 1 2 j n A m m1 m2 mj mn Where j s the performance of attrbute j for alternatve A, for =1, 2,..., m, j=1, 2,..., n. (1) Normalze the performance matrx. Normalzng the performance matrx s an attempt to unfy the unt of matrx entres. ( ), j, (2) j Where j s the performance of attrbute to crteron j Create the weghted normalzed performance matrx TOPSIS defnes the weghted normalzed performance matrx as V ( V j ), j, (3) Where w s the weght of crteron j. V j wj r j, j Determne the deal soluton and negatve deal soluton The deal soluton s computed based on the followng equatons: V {( max V jj), (max V jj '), 1,2,..., m} (4) j Volume 3, Issue 2, February 2014 Page 201 j V {(mn V jj), (mn V jj '), 1,2,..., m} (5) j j

4 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com where j { j 1, 2,..., n j belongs to beneft crtera}, j ' { j 1, 2,..., n j belongs to cost crtera} Calculate the dstance between dea soluton and negatve deal soluton for each alternatve, usng the n- dmensonal Eucldean dstance. n 2 ( j j..., m j1 S V V ) 1, 2,, (6) n 2 ( j j..., m j1 S V V ) 1, 2,, (7) Calculate the relatve closeness to the deal soluton of each alternatve * S C 1, 2,..., m. * S S Where 0 C 1. That s, an alternatve s closer to A as C approaches to Rank the preference order A set of alternatves can be preferentally ranked accordng to the descendng order of C Conjont Analyss The second purpose of ths study was to explore the relatve frequency of each cause leadng to mult-channel conflct. The concept of conjont analyss s ntroduced n ths secton, as well as the determned formula of the utlty wth the conjont analyss. The fnal part n ths secton dscusses the process of data analyss wth conjont analyss. Conjont analyss (CA) has been employed n research for many years. Panda and Panda (2001) [37] have descrbed CA as a what f experment n whch buyers are presented wth dfferent possbltes and asked whch product they would buy. In other words, CA s a multvarate technque used specfcally to understand how respondents develop preferences for products or servces [12]. Sudman and Blar (1998) [36] emphaszed that CA s not a data analyss process, such as cluster analyss or factor analyss; t can be regarded as a type of thought experment, desgned to dsplay how varous elements, such as prce, brand, and style, can be used to predct customer preferences for a product or servce. The basc CA model was computed wth the ordnary least squares (OLS) regresson parametrc mathematc algorthm [11] usng dummy varable regresson. Ths basc model can be represented as follows [25, 35]. Where m k U () = j j (9) 1 j1 U() = Overall utlty (mportance) of an attrbute α j = Overall utlty of the j level of the attrbute = 1, 2,., m j= 1, 2,..k j = 1, f the j th level of the th attrbute s present = 0, otherwse. Accordng to the CA basc model, Churchll and Iacobucc (2002) [6] presented a sx-stage model that s based on the more crtcal decson ponts n a conjont experment Select attrbutes The attrbutes are those nsurance companes can do somethng about and whch lead to mult-channel conflct. In other words, the company has the technology to make changes that mght be ndcated by frequency of cause leadng to multchannel conflct Determne Attrbute Levels The number of levels for each attrbute has a drect bearng on the number of stmul that the respondents wll be asked to judge Determne Attrbute Combnatons Ths wll determne what the full set of stmul wll look lke Select Form of Presentaton of Stmul and Nature of Judgments Typcally, three approaches can be used: a verbal descrpton, a paragraph descrpton, and a pctoral representaton. One method for characterzng judgments s to ask respondents to rank the alternatves accordng to frequency of cause Volume 3, Issue 2, February 2014 Page 202 (8)

5 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com leadng to mult-channel conflct. Another method that s ganng popularty among researchers s to use ratng scales Decde on Aggregaton of Judgments Ths step bascally nvolves the decson as to whether the responses from respondents or groups of respondents wll be aggregated Select Analyss Technque The fnal step s to select the technque that wll be used to analyze the data. The choce depends largely on the method that was used to secure the nput judgments from the respondents. 4. RESULTS 4.1. Result of Delph Study In order to dentfy the causes of nsurance dstrbuton mult-channel conflct, ths study apples a purposve samplng technque and select 10 experts who are employed by dfferent model banks and nsurance companes wth a known nvolvement or expertse n bancassurance. The ntervews were conducted through e-mal, or face to face. The am of Delph study s to dentfy the causes of mult-channel conflct. Delph panelsts were asked to justfy ther answers to ntervew questons and to rate ther level of agreement toward the causes of mult-channel conflct, rangng from strongly agree (SA) (5) to strongly dsagree (SD) (1). The ntervew protocol was developed based on the lterature revew. The ntervew explored more fully the perceptons of experts about the causes of mult-channel conflct. Descrptve statstcs of atttude toward each cause of mult-channel conflct at ntervew were showed as Table 1. In the fnal round, nne Delph panelsts strongly agreed that dfferences n percepton of realty used n jont decson makng and usng coercve powers were the causes of bank and nsurance mult-channel conflct. Moreover, eght Delph panelsts strongly agreed that, communcaton dffcultes, ncompatblty of goals, poor channel management and resource scarfy, were the causes of mult-channel conflct. Last, seven Delph panelsts strongly agreed that, poorly desgned channel structure and relatonshp wth lower nterdependence were the causes of mult-channel conflct. There were no undecded (UD) (3), dsagree (D) (2) and strongly dsagree (SD) (1) answers for the causes of multchannel conflct tem at round 3. Table 1. Descrptve Statstcs of Atttude toward Each Cause of Mult-Channel Conflct at Intervew Round 2 and Round 3 Atttude toward the Causes of Mult-Channel Conflct The Causes of Mult-Channel Conflct SA A UD D SD R2 R3 R2 R3 R2 R3 R2 R3 R2 R3 Communcaton Dffcultes Dfferences n Percepton of Realty Used n Jont Decson Makng Incompatblty of Goals Poor Channel Management Poorly Desgned Channel Structure Relatonshp wth Lower Interdependence Resource Scarcty Usng Coercve Powers *Fve Atttudes toward Necessary Competences: Strongly Agree (SA), Agree (A) Undecded (UD), Dsagree (D), and Strongly Dsagree (SD) Result of TOPSIS Based on the result of a Wlcoxon Sgned Rank test, no sgnfcant atttude dfference toward each cause of mult-channel conflct was found between R2 and R3. Thus, the 8 tems proposed by ths study can be dentfed as the causes of multchannel conflct. Table 2. Summary of the TOPSIS * C * The Causes of Mult-Channel Conflct C Rank Communcaton Dffcultes Dfferences n Percepton of Realty Used n Jont Decson Makng Incompatblty of Goals Poor Channel Management Poorly Desgned Channel Structure Relatonshp wth Lower Interdependence Resource Scarcty Usng Coercve Powers Volume 3, Issue 2, February 2014 Page 203

6 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com After conductng the TOPSIS, ths research showed the experts atttude tendency toward the 8 the causes lead to multchannel conflct (see Table 2) from the most mportant to the least mportant as followngs: (1) Dfferences n Percepton of Realty Used n Jont Decson Makng, (2) Usng Coercve Powers, (3) Incompatblty of Goals, (4) Communcaton Dffcultes, (5) Resource Scarcty, (6) Poor Channel Management, (7) Poorly Desgned Channel Structure, and (8) Relatonshp wth Lower Interdependence. Thus, t s mpossble to select all causes of mult-channel conflct, Har et al. (1998) [12] fgure out the conjont analyss s useful for measurng up to about sx attrbutes. Based on the result of TOPSIS, ths study decdes to choose top sx the causes lead to mult-channel conflct ncludng: Dfferences n Percepton of Realty Used n Jont Decson Makng (1.000), Usng Coercve Powers (0.842), Incompatblty of Goals (0.809), Communcaton Dffcultes (0.632), Resource Scarcty (0.620), and Poor Channel Management (0.559) as the causes lead to mult-channel conflct. The adjusted the causes lead to mult-channel conflct by TOPSIS used n ths study are reported n Fgure 2. Fgure 2. Affect of the Causes Lead to Mult-Channel Conflct n nsurance For a formal analyss, the dfferent attrbute levels have to be dummy-encoded n a bnary manner. The lowest attrbute level serves as a reference pont and gets a bnary code of 0 [29]. For any other attrbute level, a bnary dgt of 1 s gven f the level s present, and 0 s gven f t s not. Due to havng two levels for each attrbute, the total number of possble combnatons s 2 6 = 64 alternatves (stmul). Ths s far too many possble combnatons to be evaluated by any decson maker. Therefore, ths study had to construct a desgn of the nqury that defned a restrcted set of stmul to be consdered and the pars of these stmul to be compared Result of C.A. Startng wth a basc orthogonal plan generated by Addelman (1962) [33], 6 stmul were determned (see Table 3). Usng the stmul of the orthogonal array, a dfference desgn was constructed by a randomzed procedure followng the prncples gven by Hausrucknger and Herker (1992) [7]. Table 3. Attrbute Level and Orthogonal Plan Card of the Causes Leadng to Mult-Channel Conflct The Causes of Mult-Channel Conflct Attrbute Level Card No Communcaton Dffcultes 1 Yes 0 No Dfferences n Percepton of Realty Used n Jont Decson Makng 1 Yes 0 No Incompatblty of Goals 1 Yes 0 No Poor Channel Management 1 Yes 0 No Resource Scarcty 1 Yes 0 No Usng Coercve Powers 1 Yes 0 No The C.A. questonnare was developed on the bass of some of the lterature and shortlsted by TOPSIS methodology, planned wth an orthogonal desgn, and dstrbuted to 30 employees who are workng n nsurance companes or banks. 30 questonnares were completed n the survey. There were sxteen male and fourteen female n the panelst. The age group wth the hghest frequency was that had ffty-three percent; and the domnant educatonal level of C.A. panelsts was master s degrees that had forty-seven percent. Moreover, the bancassurance workng experence of 30 C.A. panelsts wth the hghest frequency was 6-10 that had sxty-seven percent n the bank, and ffty-three percent n the nsurance company. Accordng to the CA report (see Table 4), the most mportant factor was Dfferences n Percepton of Realty Used n Jont Decson Makng (relatve mportance = %), the second most mportant factor was Usng Coercve Powers (relatve mportance = %) and the thrd most mportant factor was Incompatblty of Goals (relatve mportance = %). Volume 3, Issue 2, February 2014 Page 204

7 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com Table 4. Relatve Affect of the Causes Lead to Mult-Channel Conflct n Insurance The Causes of Mult-Channel Conflct Varable Part-Worth Utlty Communcaton Dffcultes 1 Yes Dfferences n Percepton of Realty Used n Jont Decson Makng 1 Yes Incompatblty of Goals 1 Yes Poor Channel Management 1 Yes Resource Scarcty 1 Yes Usng Coercve Powers 1 Yes Total Utlty Relatve Importance CONCLUSION AND MANAGERIAL IMPLICATIONS There are many causes whch lead to mult-channel conflct. Due to the lmtaton of resources n lfe nsurance companes, try to deal wth the most mportant causes s an acceptable approach to mprove the effcency of multchannel desgn. Accordng to result of ths study the most mportant three causes leadng to mult-channel conflct are dfferences n percepton of realty used n jont decson makng, usng coercve powers, and ncompatblty of goals. Snce 1964, conjont analyss study are ssued frstly by conjont measure study of Luce and Tukey (1964) [27], and used many years. Snce 1998, Har et al. (1998) [12] suggest the conjont analyss s useful for measurng up to about 6 attrbutes, but no research provdes the method of shortlst selectons, ths study fnd the TOPSIS s an useful method to help ths study to shortlst these attrbutes. In order to deal wth the channel conflct of dfferences n percepton of realty used n jont decson makng, marketng managers must spend tme understandng how each dstrbutor nterprets realty and, where there s a sgnfcant dfference between what s seen and what exsts, try to elmnate the dstortons. Falure to deal wth the dfferences when dstrbutors perceve the job n negatve terms wll result n ncreased absenteesm and turnover and lower job satsfacton. Coercve power s a common method of nfluencng employee behavor. About the deal wth the channel conflct of usng coercve powers, marketng managers must balance the leadershp power usng. An essental component of management s to nfluence the people or unts admnsters manage so that they do what admnsters want them to do. The nfluence of a manager over hs followers s often referred to as power such as reward power, coercve power, legtmate power, referent power and expert power. As can be seen each of the powers s created by the follower s belef, f the follower does not hold the requste belef then the leader s not able to nfluence them. Each of the leadershp powers can be used by themselves or combned so that the nsurance marketng admnstrators have maxmum nfluence. The nsurance marketng admnstrators wll therefore need to thnk carefully about whch power to use. To face the problem of ncompatblty of goals among the dstrbutors, marketng managers must reframng goals to resolve ncompatblty. In many cases provders and dstrbutors are absolutely convnced they have opposng goals and cannot agree on anythng to pursue together. However, f goals are reframed or put n a dfferent context, the partes can agree. In a jont dscusson wth the nsurers and dstrbutors, the nsurance marketng admnstrators can fnd that both are able to affrm that they value feedback about postve and negatve experences. Trust s bult through a dscusson of goals. Perceptons of the ncompatblty of the goals changed through clear communcaton. REFERENCE [1] B. Rosenbloom, Mult-channel strategy n busness-to-busness markets: Prospects and problems, Industral Marketng Management, Vol.36, pp. 4-9, [2] C. Hwang, K. Yoon, Multple Attrbute Decson Makng: Methods and Applcaton. New York: Sprnger, [3] C. K. Fan, Apply Delph and TOPSIS Methods to Identfy Turnover Determnants of Lfe Insurance Sales Representatves, The Busness Revew, Cambrdege, Vol.8, No.2, pp , [4] D. A. Cather, V. Howe, Conflct and Channel Management n Property-Lablty Dstrbuton Systems, The Journal of Rsk and Insurance, Vol.56, No.3, pp , [5] F. Coelho, C. Easngwood, A. Coellho, Exploratory Evdence of Channel Performance n Sngle vs Multple Channel Strateges, Internatonal Journal of Retal and Dstrbuton Mangement, Vol.31, No.11, pp , [6] G. Churchll, D. Iacobucc, Marketng Research, Methodologcal Foundatons, 8 th edton, London: Harcourt Volume 3, Issue 2, February 2014 Page 205

8 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com Publshng, [7] G. Hausrucknger, A. Herker, De konstrukton von schätzdesgnsfür conjont - analysen auf der bass von paarverglechen, Marketng etschrftfürforschung und Praxs, Vol.14, No.2, pp , 1992 [8] G. L. Frazer, K. D. Anta, Exchange Relatonshps and Interfrm Power n Channels of Dstrbuton, Journal of the Academy of Marketng Scence, Vol.23, No.4, pp , [9] G. L. Frazer, Organzng and Managng Channels of Dstrbuton, Journal of the Academy of Marketng Scence, Vol.27, No.2, pp , [10] H. H. Fredman, Channel Polcy and Physcal Dstrbuton, Brooklyn College of Cty Unversty of New York, Retreved July 15, 2013, from [11] J. Fox, Appled Regresson Analyss, Lnear Models, and Related Methods, Thousand Oaks, CA: Sage Publcatons, [12] J. F. Har, R. E. Anderson, R. L. Tatham, W. C. Black, Multvarate Data Analyss. 5 th Edton., New Jersey: Prentce-Hall Internatonal, [13] J. M. Gallaugher, E-Commerce and the Undulatng Dstrbuton Channel, Communcatons of the Assocaton for Computng Machnery, Vol.45, No.7, pp , [14] K. Nothofer, D. Remy, The Role of Mult-Channel Management n the Hosptalty Industry, Les Roches Internatonal School of Hotel Management, Crans-Montana: Swtzerland, [15] K. L. Webb, N. M. Ddow, Understandng Hybrd Channel Conflct: a Conceptual Model and Propostons for Research, Journal of Busness-to- Busness Marketng, Vol. 4, No.1, pp , [16] K. L. Webb, Managng Channels of Dstrbuton n the Age of Electronc Commerce, Industral Marketng Management, Vol.31, No.2, pp , [17] K. L. Webb, J. E. Hogan, Hybrd Channel Conflct: Causes and Effects on Channel Performance, Journal of Busness and Industral Marketng, Vol.17, No.5, pp , [18] L. Goldkuhl, Multple Marketng Channel Conflct wth a Focus on the Internet: A Dual Perspectve, Thess of Lulea Unversty of Technology, Sweden, [19] L. J. Rosenberg, L. W. Stern, Toward the Analyss of Conflct n Dstrbuton Channels: A Descrptve Model, Journal of Marketng, Vol. 34, No.4, pp , [20] L. J. Rosenberg, A New Approach to Dstrbuton Conflct Management, Busness Horzons, Vol.17, No.5, pp , [21] L. T. Gamarra, C. Growtsch, Sngle-versus Mult-Channel Dstrbuton Strateges n German Lfe Insurance Market, The European Workshop on Effcency and Productvty Analyss, Bad Honnef: Germany, [22] M. B. Sarkar, B. Butler, C. Stenfeld, Intermedares and Cybermedares: A Contnung Role for Medatng Players n the Electronc Marketplace, Journal of Computer Medated communcaton, Vol.1, No.3, pp. 1-14, [23] M. J. Valos, Structure, People and Process Challenges of Multchannel Marketng: Insghts from Marketers, Journal of Database Marketng and Customer Strategy Management, Vol.16, No.3, pp , [24] M. S. Chen, P. L. Chang, Dstrbuton Channel Strategy and Effcency Performance of the Lfe Insurance Industry n Tawan, Journal of Fnancal Servces Marketng, Vol.15, No.1, pp , [25] M. Wedel, W. Kamakura, U. Böckenholt, Marketng data, models and decsons, Internatonal Journal of Research n Marketng, Vol.17, pp , [26] P. O Connor, J. Murphy, Hotel Yeld Management Practces Across Multple Electronc Dstrbuton Channels, Informaton Technology and Toursm, Vol. 10, No. 2, pp , [27] R. D. Luce, J. W. Tukey, Smultaneous conjont measurement: a new type of fundamental measurement, Journal of Mathematcal Psychology, Vol.1, No.1, pp. 1-27, [28] R. E. Dumm, R. E. Hoyt, Insurance Dstrbuton Channels: Markets n Transton, Journal of Insurance Regulaton, Vol.22, No.1, pp , [29] R. Helm, L. Manthey, A. Scholl, M. Stener, Emprcal Evaluaton of Preference Elctaton Technques from Marketng and Decson Analyss, Jenaer Schrften zur Wrtschaftswssenschaft, No.2, [30] R. T. Morarty, U. Moran, Managng Hybrd Marketng Systems, Harvard Busness Revew, November-December, pp , [31] R. Sngh, An Assessment of the Impact of dstrbuton Channel Conflct on Channel Effcency-Few Improvsed Conceptual Models, Indan Insttute of Management. Ahmedabad: Inda, [32] R. Yan, P. Guo, J. Wang, N. Amrouche, Product dstrbuton and coordnaton strateges n a mult-channel context, Journal of Retalng and Consumer Servces, Vol.18, pp , [33] S. Addelman, Orthogonal Man-Effect Plans for Asymmetrcal Factoral Experments, Technometrcs, Vol.4, No.1, pp , [34] S. Hogarth-Scott, S. T. Parknson, Retaler-Suppler Relatonshps n the Food Channel: A suppler Perspectve, Internatonal Journal of Retal and Dstrbuton Management, Vol. 21, No.8, pp , [35] S. N. Trpath, M. H. Sddqu, An emprcal study of tourst preferences usng conjont analyss, Internatonal Volume 3, Issue 2, February 2014 Page 206

9 Internatonal Journal of Applcaton or Innovaton n Engneerng & Management (IJAIEM) Web Ste: Emal: edtor@jaem.org, edtorjaem@gmal.com Journal of Busness Scence and Appled Management, Vol.5, No.2, pp. 1-16, [36] S. Sudman, E. Blar, Marketng Research, Boston: McGraw Hll, [37] T. K. Panda, S. Panda, An Alternatve Method for Developng New Toursm Products, Natonal Journal (SIDDHANT) of Regonal College of Management, Bhubaneswar, [38] T. W. Malone, J. Yates, R. I. Benjamn, Electronc Markets and Electronc Herarches, Communcatons of the ACM, Vol. 30, No.6, pp , [39] W. N. Seung, Managng Channel Conflct: From a Korean Lfe Insurance Industry Perspectve, LIMRA s Market Facts Quarterly, Vol. 29, No.3, pp , Volume 3, Issue 2, February 2014 Page 207