PRICING MODEL FOR COMPETING ONLINE AND RETAIL CHANNEL WITH ONLINE BUYING RISK

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1 PRICING MODEL FOR COMPETING ONLINE AND RETAIL CHANNEL WITH ONLINE BUYING RISK Vaanya Vaanyuwatana Chutikan Anunyavanit Manoat Pinthong Puthapon Jaupash Aussaavut Dumongsii Siinhon Intenational Institute of Technology, Thammasat Univesity Pathum Thani, 1000, THAILAND , Abstact This eseach stuies the ual-channel supply chain une ecentalize setting whee thee ae two competing fims offeing customes the same poucts. One fim sells though a taitional etaile stoe while the othe fim sells though the Intenet. The objective of this pape is to analyze how to impove the total supply chain pofit with the competing taitional etail channel an online etail channel. Geneally these two channels will compete against each othe to get the sales. To stuy the effects, we have evelope the ecentalize moel whee customes will make puchasing ecision with the channel that gives them the highest utility. Howeve, the customes buying online ae expose to the isk that the poucts ae not as expecte ue to lack of the oppotunity to ty o inspect the poucts. In this moel, each channel ties to maximize the total supply chain pofits by ajusting the pice on each channel. The analytical expessions fo the optimal pices an Nash equilibium ae foun. The numeical esult shows the analytical expessions towa the pice, eman, an pofit of each channel. Aitionally, we foun that in the case when the pouct has high penalty cost, thee is a geat iffeence in the pice an pofit between the two channels. On the othe han, thee is a geat iffeence between emans of the two channels when the pouct has low penalty cost. Keywos: Supply chain, Online, Retail, Online Risk, Nash equilibium, Game theoy 1. MOTIVATION AND LITERATURE REVIEW With moe Intenet uses eveyay, many fims have ealize that selling though the Intenet is anothe way to o the business an ceate moe pofits besies selling though a taitional physical stoe. In 011, U.S. online etail sales incease 16.1% fom 010 an e-commece was accounte fo 8.6% of total etail sales, inceasing fom 7.6% in 010 (Enight, 01). We can see that the impotance of e-commece has got a significant potion of oveall etail sales in the Unite States ove time. The benefits of shopping online ae such as convenience, time an effot savings, accessibility, seach capabilities, an lack of lines, salespeople an cows (Wolfinbage an Gilly, 001). Accoing to the eseach, 78% of Intenet uses agee that shopping online is

2 convenient (Hoigan, 008). Howeve, the awbacks of shopping online ae uneliability, lack of the oppotunity to inspect the poucts at the point of puchase, an elivey lags (Liebe an Syveson, 011). While having iect intepesonal communication an the ability to examine the poucts ae the upsie of shopping fom taitional etail stoes. The ownsies ae such as expensive pice ue to highe cost, having exact opeating hous, moe time an effot use, an sometimes shotage of mechanise. In eality, consumes may use the two channels iffeently. Some may pefe buying fom physical stoes an some may pefe the online stoes. Consequently, when the two channels, offline an online, compete against each othe, some total supply chain pofits will be lost. This pape povies the unestanings of how to solve such poblem when the taitional etail fim an online etail fim compete with each othe an still get the maximize total supply chain pofit. To accomplish this stuy, we have establishe the ecentalize moel base on the customes puchasing ecision. Then, we have evelope the optimal solution expession an one the numeical expeiment to see the moel esponse. Finally, we conclue the key finings of this stuy an povie some manageial insights fo etail maketes an futue eseaches. Most of the eseaches elate to this aea have stuie about the two channels consume esponse an picing stategies/competition. One eseach has foun that the iffeent Intenet uses base on income eanings, eucation, age, an ace have a significant impact on the numbe of Intenet usage while gene oes not (Liebe an Syveson, 011). Anothe eseach points out that high-shae bans enjoy geate ban loyalty in the online stoe than small-shae bans (Danahe, Wilson, an Davis, 003). Also, one stuy has foun that online customes ae less pice sensitive because customes place moe impotance on convenience, an pefe buying poucts in lage sizes to euce the numbe of oes (Anews an Cuim, 004). One eseach has inicate that the incease in competition woul esult in the lowe picing an less pice ispesion (Gube, 008). Moeove, anothe eseach suggeste that online etailes chage lowe pices than offline etailes. Offline etailes will fin it inceasingly ifficult to compete on pice. Also, online etailes make pice changes in smalle incements than offline etailes because the competition in the online maket is highe (Bynjolfsson an Smith, 000). Puchasing online often comes with isks accoing to pevious papes. Peceive isks fom shopping online ae suggeste to have 6 imensions: pefomance, financial, oppotunity/time, safety isk, social isk an psychological isks (Cunningham, 1967). Fo example, pefomance isk efes to the pobability that the puchase pouct oes not meet the buye expectation ue to its function failue. The main contibution of ou eseach is that while most elate papes iscusse on consume behavio, ban competition, picing stategies o the isk of puchasing fom online channel, ou eseach woul athe focus on how to obtain the optimal solution on the

3 conflicts between offline an online channels with online puchasing isk. Afte this section, the emaining pat of this pape is ivie as follows. Section intouces the assumptions an moel of the poblem we iscuss. Section 3 epesents the outcomes of the numeical expeiment. An conclusion an guiance fo futue eseaches ae inclue in section 4.. MODEL In this section, we will iscuss the ecentalize moel whee the offline an online channels focus on maximizing its own pofits. Fist, we pesent the moel an explain the elationship between each paty. Afte that, we eclae the elate vaiables use in the functions. Finally we evelop the optimal pice function that gives the highest total supply chain pofit..1 Decentalize Supply Chain Moel The ecentalize moel pesents two fims, etaile an online, offeing the same poucts fom the same supplies. Each channel ties to maximize the pofit iniviually. Customes can puchase eithe fom the etaile o online channel. The ecentalize supply chain consists of supplies, etaile channel, online channel, an customes. Supplies Retaile Fim Online Fim Customes Figue 1: The elationship of supply in ecentalize moel. Membe in the Moel Thee ae mainly 4 membes in the ecentalize moel. They ae supplies, etaile fim, online fim, an customes. The esciption of each membe is expesse below...1 Supplie The supplies ae the paty that povies the poucts in a supply chain. The supplies sell it to the next link in the chain, which ae the etaile fim an the online fim. Thee is no ecision vaiable at the supplie... Retaile Fim The etaile fim puchases the poucts fom supplies in wholesale pice, then sell to

4 customes in the etaile pice ( P ). The etaile pice efes to the amount of money customes have to give up to acquie the poucts in the etaile channel. The etaile channel is a iect competito with the online channel. The cost of the etaile channel is notate asc while the pofit of the etaile channel is notate asπ...3 Online Fim Simila to the etaile fim, the online fim puchases poucts fom supplies in the wholesale pice an sell to customes in online pice ( P ). The online pice efes to the amount of money customes have to give up to acquie a pouct in the online channel. The online channel is a iect competito with the etaile channel. The cost of the online channel is notate as C while the pofit of the online channel is notate asπ...4 Customes Customes ecie which channel to puchase the poucts by compaing the utility gaine between the etaile ( U ) an online ( U ) fims. When customes ecie to buy a pouct, they will set the value of that paticula pouct in thei mins (v ). If customes ae not fully satisfie with that pouct afte buying fom online channel, the v ecease by the popotion β. value will be.3 Function.3.1 Notation = Retaile channel = Online channel v = The custome s valuation of the pouct α = Pobability of ba incient happene ( 0 α < 1) β = The popotion of v the custome eceives afte mishap happens ( 0 β < 1) P = Retaile pice P = Online pice U = Utility gaine fom puchasing the etaile channel

5 U = A utility gaine fom puchasing the online channel D = Deman in the etaile channel D = Deman in the online channel π = Retaile pofit π = Online pofit C = Retaile cost C = Online cost.3. Utility Function Utility function is use to calculate the utility that customes will gain fom thei selecte channel. The utility function is evelope base on the customes puchasing ecisions. The custome can ecie eithe to puchase fom the etaile channel o the online channel. Utility function of etaile channel U = v P (1) Fom (1), the utility gaine fom puchasing in the etaile channel comes fom the iffeence between the custome s valuation of the pouct an the etaile pice. We assume that P must be less than v because if the etaile sets the pice of thei poucts moe than what customes have thought in thei mins, then customes will not puchase that poucts. Since puchasing fom the online channel is consiee to have some peceive isks (i.e. financial isk, safety isk,), α an β ae use to epesent these isks. A custome has a self-estimate pobability of ba incient, α, an when the ba incient happene, the value of pouct euces fom peceive value v to only βv whee 0 β < 1. Fo example, the quality o pouct chaacteistics might not be as expecte because the custome cannot examine the pouct befoe buying. The customes iffe in value of self-estimate pobability of ba incient α. We assume that self-estimate pobability of ba incient α is unifomly istibute between 0 an 1. If the ba incient happens, the custome will peceive the gaine utility of (β v P ) with pobability α. If the ba incient oes not happen, the

6 custome will peceive the gaine utility of (v P ) with pobability 1 α. The expecte utility gaine is then U = α(β v P ) + (1 α )(v P ). The utility when puchasing fom the online channel is shown in (). Utility function of online channel U = α(β v P ) + (1 α )(v P ) () Customes will always buy fom the channel that gives them the highest utility. Theefoe, if U > U, customes will buy fom the etaile channel. But if U > U, customes will buy fom the online channel. In oe to illustate the situation when customes will choose the etaile channel, we have to set up the equation as following: U > U v P > αβ ( v P ) + (1 α)( v P ) (3) Afte solving (3), we will get (4). P P α > = α* v(1 β ) (4) In (4), we set α * as if the pobability of the mishap that customes can take is moe than α *, customes will puchase fom the etaile channel. Similaly, to illustate the situation when customes will choose the online channel, we have to set up the equation as following: U > U αβ ( v P ) + (1 α)( v P ) > v P (5) Also, as α inceases, U eceases. To ensue that all customes buying fom online channel gets positive utility, we a anothe conition that U > 0 an that is equivalent to

7 v P v(1 β) > α = α (6) Using (4), we can split the online an etaile emans at α * whee all customes with α < α * buying fom online channel an all customes with α α * buying fom etaile channel. Please note that fom (4) an (6), α ' > α *, as a esult, all custome buying fom online channel has positive utility an enfocing U > 0 oes not change the eman function. Population = 1 Online Retaile 0 1 Figue : The utility between online an etaile channels.3.3 Deman Function Deman function is elaboate fom the custome buying behavio. Accoing to Figue, eman functions of the etaile an online channels ae as follows: D D = 1 (1 α*) = 1 α * = 1 ( α * 0) = α * (7) (8) Poposition 1: Deman function of etaile an online channels D = 1 P P v(1 β) (9) D = P P v 1 β ( ) (10) When substituting the value of α * fom (4) into the eman function (7) an (8), the esult of the eman function is as in (9) an (10)..3.4 Pofit Function The pofit of etaile an online channels ae as shown in (11) an (1). Please note that C > C ue to setup cost an cost of hiing employees.

8 π = ( P C ) D = ( P C ) (1 α*) π = ( P C ) D = ( P C ) α * (11) (1) Poposition : Pofit function of etaile an online channels P P π = ( P C) 1 v (1 β ) P P π = ( P C) v (1 β) (13) (14) The supply chain pofit function gives the maximum pofit fo each channel. Afte we substitute (9) into (11), we can get (13). Afte we substitute (10) into (1), we can get (14)..3.5 Retaile Pice an Online Pice Development We can fin the caniates of optimal etaile an online pices by applying the fist π π oe conition, = 0 an = 0, we can solve fo the optimal pice function as follows: P P Poposition 3: Optimal pice of etaile an online channels 1 P = ( v vβ + C + P) (15) 1 P = ( C + P) (16) The fist eivative function of the etaile an online pofits ae as in (15) an (16). Then, we etemine the secon oe conition of pofit with espect to the pice function an get the following: π = (17) P v vβ π = (18) P v vβ

9 π π Fom (17) an (18), it can be conclue that < 0 an < 0 because 0 β < 1. As a esult, the pofit function is stictly concave in the two pices. The secon oe conitions of global maximum point fo both etail an online pofits ae satisfie an (15) an (16) leas to the unique maximum pofit in each channel given the ecision of the othe playe. (15) an (16) can be calle the best esponse function fo etail channel an online channel espectively. By solving (15) an (16) simultaneously, we get: 1 P = ( C + ( v vβ + C ) (19) 3 1 P = ( v vβ + C + C) (0) 3 P P The function (19) an (0) etemines the outcome of the etaile an online pices that can attain the maximum pofit given that both playes ty to maximize thei pofit. Using only the paametes of moel, function (19) an (0) povies the peicte outcome of the game o Nash equilibium. 3. NUMERICAL EXPERIMENT In this section, we use the functions obtaine fom the pevious section to analyze the moel esponse. We use the ata in the following table to illustate the gaph of the pice competition between the etaile an online channels. Also, the Nash equilibium an the impacts towa each channel s pice, eman, an pofit ae analytically pove. Table 1: The input ata fo the numeical expeiment v β C C Pice Competition Fom Figue 3, the best esponse of the etaile channel epens upon the online channel while the best esponse of the online channel epens upon the etaile channel accoing to the optimal pice function obtaine fom the pevious section. Theefoe, if one channel ajusts the pice, the othe channel will have to ajust the pice linealy. In game theoy, the concept of Nash equilibium can escibe the metho of peicting the outcome of the pice setting inteaction between these two channels. The online channel is making the best ecision it can, taking into account the etaile channel s ecision, an vice vesa. In this case, we can peict the outcome of the competition fom both channels when the two function lines intesect at a cetain point (0.4, 0.3).

10 1 Online pice Retaile pice Online pice Retaile pice Figue 3: Pice competition between etaile an online channels 3. The Effects When Changing β In Figue 4, when β is low (the pouct has high penalty cost; ex. fashion appaels o shoes (unpeictable actual size), the iffeence in pice between the two channels is high. This is because the value of the pouct will emain vey low afte the mishap happens. But with high β (the pouct has low penalty cost; ex. books etc.), both channels cannot set the pice so iffeently. The eman fom Figue 5 is esulte fom the pice in Figue 4. When β is low, the eman in the etaile channel is highe than the online channel. But with high β, the eman of in the online channel will be highe than the etaile channel. In Figue 6 the pofit is esulte fom the eman in Figue 5. The pofit of the etaile channel is highe than the online channel when β is low. As β inceases, the pofit of the online channel will get highe, an ultimately beat the etaile channel Pice Retaile pice Online pice Beta Figue 4: Pice (when the β value is change)

11 1 Deman Retaile channel eman Online channel eman Beta Figue 5: Deman (when the β value is change) 0.4 Pofit Retaile pofit Online pofit Beta Figue 6: Pofit (when the β value is change) 4. CONCLUSION In this pape, we stuy the ual-channel supply chain une ecentalize setting. The objective of the eseach is to fin the optimal picing ecisions on both channels to maximize the total supply chain pofit an to gain manageial insights fom the moel. In this moel, the etaile fim an online fim offe customes the same pouct. A custome ecies to buy the pouct fom the channel giving them the highest utility. The two fims ty to maximize the total supply chain pofits by ajusting the pice on each channel. By the eseach, we foun the optimal pice of etaile channel an online channel in the ecentalize moel. The Nash equilibium is also foun. The analytical expessions fo the optimal pices ae pove analytically. The numeical esult shows the effects in pice, eman, an pofit of the etaile an online channels. We foun that when the pouct has high penalty cost, the etaile an online channels can set the pice vey iffeently an thee is a geat iffeence between the etaile an online pofit. But when the pouct has low penalty cost, the eman in etaile an online channels will be vey iffeent.

12 REFERENCES Anews, R. L., an I. S. Cuim (004). Behavioal Diffeences between Consumes Attacte to Shopping Online vs. Taitional Supemakets: Implications fo Entepise Design an Stategy, Intenational Jounal of Maketing an Avetising, 1(1), 38 61, woking pape. Bynjolfsson, Eik, Michael D. Smith Fictionless commece? A compaison of Intenet an conventional etailes. Management Science 46(4) Cunningham, Scott M. (1967), "The Majo Dimensions of Peceive Risk," In Donal F. Cox (es.), Risk Taking an Infomation Hanling in Consume Behavio, Boston, MA: Hava Univesity Pess, pp Danahe, P. J., Wilson, I. W., & Davis, R. A. (003). A compaison of online an offline consume ban loyalty. Maketing Science Fall, (003), Duehl, C. an E.L. Poteus Online vesus Offline Pice Competition: Maket Outcomes an the Effect of Intenet Shopping Penetation. Woking Pape, Smith School of Business, Univesity of Maylan. Enight, A. (01). E-commece sales jump 16% in 01. Retieve fom Gube, G. (008). Picing stategies in online & offline etailing. Retieve fom Hoffman, D., Novak, T., & Pealta, M. (1999). Builing con tust online. COMMUNICATIONS OF THE ACM, 4(4), Hoigan, J. B. (008, Febuay 13). Online shopping. PEW INTERNET&AMERICAN LIFE PROJECT, Retieve fom Liebe, E., an C. Syveson (011): Online vs. Offline Competition, in Oxfo Han- book of the Digital Economy, e. by M. Peitz, an J. Walfogel. Oxfo Univesity Pess, fothcoming. Wolfinbage, M. an M.C. Gilly (001). Shopping Online fo Feeom, Contol, an Fun. Califonia Management Review. Vol. 43, No.,

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