Skip to main content
Log in

The effect of exogenous product familiarity on endogenous consumer search

  • Published:
Quantitative Marketing and Economics Aims and scope Submit manuscript

Abstract

When a consumer is familiar with one product but not its competitor, she is faced with a decision: either buy what she knows, or engage in search to learn more. When search is costly, competing firms may attempt to encourage or discourage search by adjusting prices. In this paper we consider how competitive dynamics between two quality differentiated firms are affected if one product enjoys a familiarity advantage. Familiarity is defined as a consumer’s ex-ante knowledge of fit for a particular product. An increase in the level of familiarity for one product allows a firm to charge higher prices since there are more consumers with information on that product relative to the competition. We call this the direct effect of familiarity. However, an increase in familiarity also has an indirect effect, since it gives the rival firm a stronger incentive to decrease price in order to encourage searching, in turn increasing overall competition. The effect of familiarity on profits depends on the magnitudes of these effects, and it is moderated by the level of quality differentiation between products. For very high or very low levels of differentiation, the results are relatively straightforward. However, when the level of differentiation is moderate, the results are more nuanced, with the higher-quality firm realizing higher profits from more familiarity, even if it must lower prices due to the indirect effect. We also find that, contrary to conventional wisdom, overall competition may be higher when firms are more quality differentiated. This is driven by the fact that higher quality differences bolster the indirect effect, with a lower quality firm providing deeper price cuts to counter increased familiarity of a high quality rival. We conclude by examining how changes in the cost of searching impact equilibrium outcomes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

Notes

  1. Our assumption of the uniform distribution is consistent with prior studies in marketing and economics. Alternatively, one could assume some other distribution (such as logistic or truncated normal) for fit uncertainty. However, such peaked distributional assumptions presuppose knowledge that some fit values are more likely than others. We follow the larger literature by assuming that, without any a priori information on whether certain fit values are more likely than others, the uniform distribution assumption is reasonable.

  2. We remark that, in some contexts, match parameters might be correlated. One approach to modeling such correlation is to use a Hoteling framework, wherein consumers are distributed uniformly on the unit line. Firm 1 is located at point 0 on the unit line and firm 2 is located at 1. Therefore, a consumer who knows the value of v1 also knows that v2 = 1 − v1. In other words, if a consumer knows that she has a better fit with one product, then she also knows that her fit with the other product is lower (a negative correlation), reflecting the fact that the firms are located at the opposite ends of the Hoteling line. However, such a formulation precludes the possibility of endogenous search. Consider a consumer who is familiar with product 1 but not 2. The consumer will buy product 1 if 2v1 + Δ > 1 or product 2 if 2v1 + Δ < 1 for \({\Delta } \equiv p_{2}-p_{1}+\overline {v}\). Since v1 and Δ are known to the consumer, she does not need to engage in costly search. Of course, one can make other functional assumptions about the nature of relationship between the match parameters, but the need to engage in search ceases to exist when there is any function, known by the consumers, that defines a correlation in valuations. Since endogenous search is at the heart of our paper, our i.i.d. assumption fits with the goals of this research. Furthermore, in our context of interest the horizontal attributes of competing products are uncertain and experiential in nature, but may not be of the “if you like one more, you like the other less” variety captured by the Hoteling line.

  3. An important distinction is that, in Anderson and Renault (2000), consumers do not observe the price of the unfamiliar product. Instead, consumers make the search decision based on the expected price of the unfamiliar product, and since consumers are rational, the expected price is in fact the equilibrium price. In our paper, consumers directly observe the price of the unfamiliar product when deciding whether to search (they do not need to form expectations). In either case, the computation of the net benefit from search is similar, since \(p_{2}^{\ast }\) is not a source of uncertainty in either model.

  4. Notice that if we were to include a convex cost in Eq. 10 above (so that firm 1 pays higher cost for quality), the equilibrium defined by the fixed point condition in Eq. 13 would structurally remain the same.

References

  • Anderson, S.P., & Renault, R. (1999). Product diversity, and search costs: a Bertrand-Chamberlin-Diamond model. The Rand Journal of Economics, 30(4), 719–735.

    Google Scholar 

  • Anderson, S.P., & Renault, R. (2000). Consumer information and firm pricing: Negative externalities from improved information. International Economic Review, 41(3), 721–742.

    Google Scholar 

  • Anderson, S.P., & Renault, R. (2009). Comparative advertising: Disclosing horizontal match information. The Rand Journal of Economics, 40(3), 558–581.

    Google Scholar 

  • Armstrong, M., Vickers, J., Zhou, J. (2009). Prominence and consumer search. Rand Journal of Economics, 40(2), 209–233.

    Google Scholar 

  • Branco, F., Sun, M., Villas-Boas, J.M. (2012). Optimal search for product information. Management Science, 58(11), 2037–2056.

    Google Scholar 

  • Branco, F., Sun, M., Villas-Boas, J.M. (2016). Too much information? information provision and search costs. Marketing Science, 35(4), 605–618.

    Google Scholar 

  • Cachon, G.P., Terwiesch, C., Xu, Y. (2005). Retail assortment planning in the presence of consumer search. Manufacturing & Service Operations Management, 7(4), 330–346.

    Google Scholar 

  • Cachon, G.P., Terwiesch, C., Xu, Y. (2008). On the effects of consumer search and firm entry in a multiproduct competitive market. Marketing Science, 27 (3), 461–473.

    Google Scholar 

  • Diamond, P. (1971). A model of price adjustment. Journal of Economic Theory, 3, 156–168.

    Google Scholar 

  • Gabszewicz, J.J. (1986). P.Garella ‘Subjective’ Price search and price competition. International Journal of Industrial Organization, 4, 305–316.

    Google Scholar 

  • Ghosh, B., & Galbreth, M. (2013). Consumer inattentiveness, search and voluntary quality disclosure: a competitive analysis. Management Science, 59(11), 2602–2621.

    Google Scholar 

  • Gu, Z., & Liu, Y. (2013). Consumer fit search, retail shelf layout, and channel interaction. Marketing Science., 32(4), 652–668.

    Google Scholar 

  • Guo, L., & Zhao, Y. (2009). Quality disclosure and market interaction. Marketing Science, 28(3), 488–501.

    Google Scholar 

  • Kuksov, D., & Villas-Boas, J.M. (2010). When more alternatives lead to less choice. Marketing Science, 29(3), 507–524.

    Google Scholar 

  • Ke, T.T., Shen, Z.J.M., Villas-Boas, J.M. (2016). Search for information on multiple products. Management Science, 62(12), 3576–3603.

    Google Scholar 

  • Levin, D., Peck, J., Ye, L. (2009). Quality disclosure and competition. Journal of Industrial Economics, 57(1), 167–196.

    Google Scholar 

  • Mussa, M., & Rosen, S. (1978). Monopoly and product quality. Journal of Economic Theory, 18, 301–317.

    Google Scholar 

  • Pires, T. (2016). Costly search and consideration sets in storable goods markets. Quantitative Marketing and Economics, 14, 157–193.

    Google Scholar 

  • Robert, J., & Stahl, D. II. (1993). Informative price advertising in a sequential search model. Econometrica, 61(3), 657–686.

    Google Scholar 

  • Sieler, S. (2013). The impact of search costs on consumer behavior. a dynamic approach. Quantitative Marketing and Economics, 11, 155–203.

    Google Scholar 

  • Stahl, D. II. (1989). Oligopolistic pricing with sequential consumer search. American Economic Review, 79, 700–712.

    Google Scholar 

  • Verplanken, B., & Wood, W. (2006). Interventions to break and create consumer habits. Journal of Public Policy & Marketing, 25(1), 90–103.

    Google Scholar 

  • Villas-Boas, J.M. (2009). Product variety and endogenous pricing with evaluation costs. Management Science, 55(8), 1338–1346.

    Google Scholar 

  • Wood, W., & Neal, D. (2009). The habitual consumer. Journal of Consumer Psychology, 19, 579–592.

    Google Scholar 

  • Wolinsky, A. (1986). True monopolistic competition as a result of imperfect competition. Quarterly Journal of Economics, 101(3), 493–512.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Bikram Ghosh.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Appendix

Appendix

1.1 Derivation of demand function given in Eq. 9 of the paper

We provide the technical details of the derivation of the demand function following the threshold for search, \(\widehat {v}\). The analysis requires us to also outline which consumers will engage in costly search.

The demand that firm 1 faces from the segment of consumers who are ex-ante familiar with product 1 and not product 2 depends on \(\widehat {v}\). Given \( \widehat {v}\), some of these consumers will buy product 1 without search, some may buy product 2 without search, and some will engage in search get fully informed before making a purchase decision. First, we remark that since \(\overline {v}>p_{1},\) there cannot exist a segment of consumers who are ex ante familiar with product 1 and buy product 2 without engaging in costly search. For this segment of consumers to exist, it must be the case that even with the lowest possible match realization of product 2, post purchase, the consumer is better off buying product 2 (without search) rather than product 1. However, the lowest possible valuation of product 2 is 0 and the lowest possible surplus that consumer may get from buying product 2 is − p2, which is strictly less than \(\overline {v}-\)p1, i.e. the lowest possible surplus the consumers could get from buying product 1. In other words, if a consumer buys product 2 without search and post purchase realizes that its match is arbitrarily close to 0, the initial purchase decision of buying product 2 without search becomes sequentially irrational.

Next we consider consumers who buy product 1 without engaging in search. Given the threshold, firm 1 expects that consumers in this segment who have a match v1 such that \(v_{1}+{\Delta } >\widehat {v}\) will buy product 1 without searching. Note that, since v1 > 0, if \(\widehat {v}-{\Delta } <0\) then all these consumers will buy product 1 without engaging in search.

The rest of the consumers will pay the search cost c, engage in search, and become informed of their match for product 2. Note that, if \(\widehat {v} -{\Delta } >1\), then all consumers will engage in search. The threshold \( \underline {v_{1}}\) above which no consumers engage in search is given by

$$ \underline{v_{1}}\equiv \max [0,\min \{1,\widehat{v}-{\Delta} \}] $$
(18)

The above observations imply that all consumers with \(v_{1}>\underline {v_{1}} \) or v1 < −Δ will make a purchase without searching. On the other hand, all consumers with −Δ < v1 < HCode \(\underline {v_{1}}\) will engage in search to become fully informed before choosing a product. Firms 1 and 2 compete for this segment of consumers. There are no other segments of consumers to consider given that, from the above expression, \(\underline { v_{1}}>-{\Delta } \).

Firm 1 expects to derive demand from both segments of consumers – those who are familiar with product 1 but not product 2 (a segment of size κ), and those who are familiar with product 2 but not product 1 (size 1 − κ ). As mentioned above, all consumers in the first segment with match value \( v_{1}>\underline {v_{1}}\) will never search for information on product 2, and thus this entire segment purchases product 1. Since v1 is drawn from U[0, 1], the proportion of consumers who buy product 1 without engaging in search is \((1-\underline {v_{1}})\). The rest of the consumers, with −Δ < v1 < HCode \(\underline {v_{1}}\), do engage in search and thus become fully informed. Firm 1 competes with firm 2 for these consumers and gets the demand from those whose match for product 1 is such that \( v_{1}-p_{1}+\overline {v}\geq v_{2}-p_{2}^{\ast }\), or v2v1 + Δ for all −Δ < v1 < HCode \(\underline {v_{1}}\). In other words, firm 1 gets F(v1 + Δ) proportion of consumers for all v1 < HCode \(\underline {v_{1}}\) only if v1 + Δ > 0 where the F(.) is the cumulative density function of v2. Finally, as mentioned above, if v1 < −Δ, firm 1 does not derive any demand from this segment.

Summarizing the above information, therefore, firm 1 expects to get a proportion \({\int \limits }_{{\max \limits } [-{\Delta } ,0]}^{\underline {v_{1}}}F(v_{1}+{\Delta } )dG(v_{1})\) of these consumers, where G(.) is the cumulative density function of v1 (the domain of integration reflects the fact that, if v1 < −Δ, then firm 1 gets no demand from this segment of consumers). In other words, the total demand, D1/1, from this segment of κ consumers is the sum of the above two parts and is given by

$$ D_{1/1}=(1-\underline{v_{1}})+{\int}_{\max [-{\Delta} ,0]}^{\underline{v_{1}} }F(v_{1}+{\Delta} )dG(v_{1}) $$
(19)

Finally, given the assumption of complete market coverage Δ > 0 and that vi (i = 1, 2) are drawn from U[0, 1], the demand that firm 1 expects to derive from the segment of consumers who are ex-ante familiar with its product and is not familiar with product 2 therefore can be given by

$$ D_{1/1}=(1-\underline{v_{1}})+{\int}_{0}^{\underline{v_{1}}}(v_{1}+{\Delta})dG(v_{1}) $$
(20)

Next consider the set of consumers who are ex-ante familiar with product 2 and not product 1. In the following we outline the demand that firm 1 expects to derive from this segment of consumers given by D1/2. The segment is (1 − κ) of the market. As in the case of D1/1, given \(\widehat {v},\) some consumers may buy product 1 without search, some may buy product 2 without search, and some will engage in search become fully informed and make purchase decision. First, consider a consumer who buys product 1 without engaging in search. Those consumers who realized v2 sufficiently low such that \(\inf (v_{1})-p_{1}+\overline {v}>\)\(v_{2}-p_{2}^{\ast }\), or for whom v2 < Δ holds, are better off buying product 1 without engaging in search since the worst-case utility from the (higher quality) product 1 is higher than their known utility from product 2.

Next consider the consumers who buy product 2 without engaging in search. Those consumers whose realized v2 is such that \(v_{2}>\widehat {v} +{\Delta } \) holds will be better off buying product 2 without engaging in search provided \(\widehat {v}+{\Delta } \in (0,1)\). Firm 1 does not expect to derive any demand from these consumers. The remaining consumers will engage in search and become fully informed, and the two firms will compete for them. Firm 1 therefore expects demand from those consumers who, after search, find \(v_{1}-p_{1}+\overline {v}\geq v_{2}-p_{2}^{\ast }\) or v1 > v2 −Δ for all v2 < \(\underline {v_{2}}\) , where \( \underline {v_{2}}\) is given by

$$ \underline{v_{2}}\equiv \max [0,\min \{1,\widehat{v}+{\Delta} \}] $$
(21)

In other words, the expected demand from this group is (1 − G(v2 −Δ)) given that v1 is drawn from U[0,1].

Summarizing, the demand that firm 1 expects to face from this segment of consumers is

$$ D_{1/2}={\int}_{\max [{\Delta} ,0]}^{\underline{v_{2}}}(1-G(v_{2}-{\Delta} ))dF(v_{2})+\max [{\Delta} ,0] $$
(22)

Finally, again given the assumption of complete market coverage Δ > 0. Therefore the demand that firm 1 expects to derive from the segment of consumers who are ex-ante familiar with product 2 and is not familiar with its product is

$$ D_{1/2}={\int}_{\Delta }^{\underline{v_{2}}}(1-v_{2}+{\Delta} )dF(v_{2})+{\Delta} $$
(23)

The above demands for each of the segments from which firm 1 expects to derive demand are reported in the main text of the paper.

1.2 Derivation of equilibrium

In order to derive the equilibrium above we first ought to outline the demand function as a function of Δ. Since the demand is also a function of \(\underline {v_{i}}\)i = 1, 2, there are multiple scenarios which can evolve given Δ. Specifically, four different cases can evolve: (i) \(\widehat {v}-{\Delta } >0\) and \(\widehat {v}+{\Delta } <1\) (ii) \(\widehat {v} -{\Delta } <0\) and \(\widehat {v}+{\Delta } <1\) (iii) \(\widehat {v}-{\Delta } >0\) and \( \widehat {v}+{\Delta } >1\) and (iv) \(\widehat {v}-{\Delta } <0\) and \(\widehat {v} +{\Delta } >1\). These cases evolve primarily because the functional firm of vi changes depending on which of the four conditions hold. In other words, vi introduces discontinuities in the demand function. Given the above information, solving for the above integrals we can write the expected demand function by firm as follows:

$$ \begin{array}{@{}rcl@{}} D_{1}({\Delta} )&=&\left\{ \begin{array}{l} \left( \kappa (\widehat{v}-1)^{2}+\widehat{v}-\frac{\widehat{v}^{2}}{2} +{\Delta} -\kappa \frac{{\Delta}^{2}}{2}\text{ }\right) \text{ if }0<{\Delta} <\min [\widehat{v},1-\widehat{v}] \\ \left( \kappa +(1-\kappa )(\widehat{v}-\frac{\widehat{v}^{2}}{2}+{\Delta} )\right) \text{ if }{\Delta} >\widehat{v}\text{ and }{\Delta} <1-\widehat{v} \\ \left( \frac{1+\kappa (\widehat{v}-1)^{2}+(2-{\Delta} ){\Delta} }{2}\right) \text{ if }{\Delta} <\widehat{v}\text{ and }{\Delta} >1-\widehat{v} \\ \kappa +\frac{(\kappa -1)(({\Delta} -2){\Delta} -1)}{2}\text{ if }{\Delta} > \widehat{v}\text{ and }{\Delta} >1-\widehat{v}\text{ } \end{array} \right.\\ D_{2}({\Delta} )& =&1-D_{1}({\Delta} ) \end{array} $$
(24)

Differentiating the above demand function with respect to Δ gives \( D_{1}^{^{\prime }}({\Delta } )\) which again needs to be evaluated for all possible scenarios. Using the fact that in equilibrium Δ = Δ yields \(D_{i}({\Delta }^{\ast })\) and \(D_{i}^{^{\prime }}({\Delta }^{\ast })\) for i = 1, 2. There will be four possible values of Di) and \(D_{i}^{^{\prime }}({\Delta }^{\ast })\) depending on which of the four conditions mentioned above holds. To derive the equilibrium prices we use Eq. 12 above which is \(p_{1}^{\ast }({\Delta }^{\ast })=\frac { D_{1}({\Delta }^{\ast })}{D_{1}^{^{\prime }}({\Delta }^{\ast })}\); \( p_{2}^{\ast }({\Delta }^{\ast })=-\frac {D_{2}({\Delta }^{\ast })}{ D_{2}^{^{\prime }}({\Delta }^{\ast })}\). Notice since there are four possible \(D_{i}({\Delta }^{\ast })\) and \(D_{i}^{^{\prime }}({\Delta }^{\ast })\) we will have four candidate prices depending on the value of Δ.

Next, we solve for the equilibrium Δ using the equality \( {\Delta }^{\ast }=p_{2}^{\ast }({\Delta }^{\ast })-p_{1}^{\ast }({\Delta }^{\ast })+\overline {v}\) in equation (13). There will be four sets of Δ corresponding to four sets of prices. We check that in each of the cases the corresponding bound (given in conditions (i) -(iv) above) on Δ holds. For instance, Δ corresponding to the first case ought to satisfy \({\Delta }^{\ast }<1-\widehat {v}\) (which automatically means that Δ < \(\widehat {v})\). Only three of the candidates satisfy the boundary conditions outlined above, and they correspond to cases (i), (iii) and (iv). The conditions (i) stated in terms of \(\overline {v}\) is \(Max[0,(2\kappa -1)(1-\widehat {v})^{2}]<\overline {v}<\frac {2-\widehat {v}- \widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}\). This level of \(\overline {v} \) is termed as low \(\overline {v}\). Condition (iii) above stated in terms of \( \overline {v}\) turns out to be \(\frac {(1+\kappa (1-\widehat {v})+2\widehat {v} )(1-\widehat {v})}{\widehat {v}}\)\(<\overline {v}<\frac {\kappa (\widehat {v} -1)^{2}-\widehat {v}(3-2\widehat {v})}{1-\widehat {v}}\). This level of \( \overline {v}\) is termed as intermediate \(\overline {v}\). Finally, condition (iv) \({\Delta }^{\ast }>\widehat {v}\) holds for \(\overline {v}>\frac {(3-2 \widehat {v})\widehat {v}+\kappa (1-3\widehat {v}+2\widehat {v}^{2})}{(1-\kappa )(1-\widehat {v})}\). This level of \(\overline {v}\) is termed as high \( \overline {v}\). The Δ corresponding to low, medium and high \( \overline {v}\) are given in Table 1 in the paper.

Next, to ensure that the above candidate equilibrium actually exists, we need to make sure that the equilibrium in each of the regions is deviation proof. In the following we simply outline the deviation check for the case when \(0<{\Delta }^{\ast }<1-\widehat {v}\) which as mentioned above corresponds to \(Max[0,(2\kappa -1)(1-\widehat {v})^{2}]<\overline {v}<\frac {2-\widehat {v}- \widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}\). The deviation check for equilibrium in any of the other cases can be done in a similar fashion. While testing for unilateral deviations off the region \(0<{\Delta }^{\ast }<1- \widehat {v}\), each of the firms can change its price unilaterally so that the resulting Δ, say Δd, is an element of one of the other regions mentioned in the demand schedule above, or it can deviate to corner the whole market. In particular, firm 1 can unilaterally change prices post deviation if one of the following holds (a) \({\Delta }^{d}\in (1- \widehat {v},\widehat {v})\); (b) \({\Delta }^{d}\in (\widehat {v},1)\); (c) \({\Delta }^{d}\in (\widehat {v}-1,0)\); (d) \({\Delta }^{d}\in (-\widehat {v},\widehat {v} -1); \) (e) \({\Delta }^{d}\in (-1,-\widehat {v})\) and (f) Δd > 1, in which case it corners the whole market, foreclosing the market for firm 2. \( {\Delta }^{d}=p_{2}^{\ast }-{p_{1}^{d}}+\overline {v}\) and \({p_{1}^{d}}\) is firm 1’s deviating price.

To prove non-deviation, first notice that to have a deviation in the interior of the other regions it must be that \({\Delta }^{d}=p_{2}^{\ast }-{p_{1}^{d}}+\overline {v}\) or \(\overline {v}\)\(={\Delta }^{d}-p_{2}^{\ast }+{p_{1}^{d}}\) after deviation for all \(Max[0,(2\kappa -1)(1-\widehat {v})^{2}]< \overline {v}<\frac {2-\widehat {v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v }}\). Now, consider the deviation to (a) above by firm 1. In such a case, the deviating price by firm 1 will be of the form \({p_{1}^{d}}({\Delta }^{d})=\frac { 1+\kappa (\widehat {v}-1)^{2}-({\Delta }^{d}-2){\Delta }^{d}}{2({\Delta }^{d}-1)} \dot {.}\) The above expression for \({p_{1}^{d}}({\Delta }^{d})\) follows from \( {p_{1}^{d}}({\Delta }^{d})=\)\(\frac {D_{1}({\Delta }^{d})}{D_{1}^{^{\prime }}({\Delta }^{d})}\) for \({\Delta }^{d}\in (1-\widehat {v},\widehat {v})\). \(\frac { D_{1}({\Delta }^{d})}{D_{1}^{^{\prime }}({\Delta }^{d})}\) is taken from the demand schedule outlined above. Substituting \({p_{1}^{d}}({\Delta }^{d})\) in \({\Delta }^{d}-p_{2}^{\ast }+{p_{1}^{d}}\) and then differentiating the resulting expression with respect to Δd shows that \({\Delta }^{d}-p_{2}^{\ast }+{p_{1}^{d}}\) is a strictly increasing function of Δd. In other words, \({\Delta }^{d}-p_{2}^{\ast }+{p_{1}^{d}}\) strictly increases over all \( {\Delta }^{d}\in (1-\widehat {v},\widehat {v})\). Notice in the deviating region \( \overline {v}\) the appropriate condition is \(\frac {(1+\kappa (1-\widehat {v})+2 \widehat {v})(1-\widehat {v})}{\widehat {v}}\)\(<\overline {v}<\frac {\kappa (\widehat {v}-1)^{2}-\widehat {v}(3-2\widehat {v})}{1-\widehat {v}}\). Define \( \overline {v}^{d}\) as an element in \(\frac {(1+\kappa (1-\widehat {v})+2 \widehat {v})(1-\widehat {v})}{\widehat {v}}\)\(<\overline {v}<\frac {\kappa (\widehat {v}-1)^{2}-\widehat {v}(3-2\widehat {v})}{1-\widehat {v}}\) and \( \overline {v}^{\ast }\) as a element in \(Max[0,(2\kappa -1)(1-\widehat {v} )^{2}]<\overline {v}<\frac {2-\widehat {v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}\) which is the region for the equilibrium under consideration. Since \(\overline {v}^{d}>\)\(\overline {v}^{\ast }\), it automatically follows that after deviation \(\overline {v}^{d}\)\(>{\Delta }^{d}-p_{2}^{\ast }+{p_{1}^{d}} \) for all \(\overline {v}^{d}\in \left (\frac {(1+\kappa (1- \widehat {v})+2\widehat {v})(1-\widehat {v})}{\widehat {v}},\frac {\kappa (\widehat {v}-1)^{2}-\widehat {v}(3-2\widehat {v})}{1-\widehat {v}}\right ) \). This also means that there cannot exist a feasible deviation in the interior of \((1-\widehat {v},\widehat {v})\) including the end point \(\widehat {v}\) because at the end point \({\Delta }^{d}-p_{2}^{\ast }+{p_{1}^{d}}\) = \(\overline {v }^{\ast }\) for \(\overline {v}^{\ast }\in \left (Max[0,(2\kappa -1)(1-\widehat { v})^{2}],\frac {2-\widehat {v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}} \right ) \). This is because for possible \({\Delta }^{d}\in (1-\widehat {v}, \widehat {v}),\) firm 1 has an incentive to monotonically reduce its deviating price, in effect invalidating the fact that any pure deviation to this region is feasible. Following precisely the same approach, one can show that neither firm has a feasible deviation to any of the other regions. In each case, one can establish that with any deviation, \({\Delta }^{d}-p_{2}^{\ast }+{p_{1}^{d}}\) or \({\Delta }^{d}-{p_{2}^{d}}+p_{1}^{\ast }\) is strictly monotonic. This also means that the deviating firm will either monotonically increase or decrease its equilibrium price. A similar approach establishes the non-deviation to other regions outlined as well. This establishes that the equilibrium is deviation proof.

Having outlined the equilibrium result, we now provide the proofs of Propositions.

1.3 Proof of Proposition 1

To derive the equilibrium prices, we use Eq. 12, which is \( p_{1}^{\ast }({\Delta }^{\ast })=\frac {D_{1}({\Delta }^{\ast })}{D_{1}^{^{\prime }}({\Delta }^{\ast })}\) ; HCode \(p_{2}^{\ast }({\Delta }^{\ast })=-\frac { D_{2}({\Delta }^{\ast })}{D_{2}^{^{\prime }}({\Delta }^{\ast })}\). Such implicit prices are given in Table 3 below. Notice that \(p_{i}^{\ast }({\Delta }^{\ast })\) are stated for permissible Δ which corresponds to low, intermediate and high \(\overline {v}\).

Table 3 Equilibrium Prices Implicitly defined as a function of Δ

Substituting Δ which is given in Table 1 of the paper, we get equilibrium prices \(p_{i}^{\ast }\) as a function of Δ. Below we outline the price expressions

$$ p_{1}^{\ast }=\left\{ \begin{array}{l} \frac{\left( \begin{array}{c} (-3+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}- \\ \kappa (4+8\kappa (\widehat{v}-1)^{2}-4(\widehat{v}-2)\widehat{v}-\kappa \overline{v}^{2}+ \\ \overline{v}(2+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})}))) \end{array} \right) }{\left( 4\kappa (-1+\kappa \overline{v}-\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}))\right) } \text{ for low }\overline{v} \\ \frac{\left( \begin{array}{c} (11+4\kappa (\widehat{v}-1)^{2}-\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} \\ +\overline{v}(2-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v }-2)\overline{v}})) \end{array} \right) }{(4(1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v} -2)\overline{v}}))}\text{ for Intermediate }\overline{v} \\ \frac{1}{8}\left( -5+5\overline{v}-\frac{3\sqrt{(\kappa -1)(-9+\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v})}}{(\kappa -1)}\right) \text{ for High }\overline{v} \end{array} \right. $$
(25)
$$ p_{2}^{\ast }=\left\{ \begin{array}{l} \frac{\left( \begin{array}{c} (-3-\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})} \\ -\kappa (-12+8\kappa (\widehat{v}-1)^{2}-+4(\widehat{v}-2)\widehat{v}-\kappa \overline{v}^{2}+ \\ \overline{v}(2+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})}))) \end{array} \right) }{\left( 4\kappa (-1+\kappa \overline{v}-\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}))\right) } \text{ for low }\overline{v} \\ \\ \frac{2(\kappa (\widehat{v}-1)^{2}-\frac{1}{16}\left( 1-\overline{v}+\sqrt{ -9+8\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v}})\right)^{2}}{ \overline{v}-1+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{ v}}}\text{ for Intermediate }\overline{v} \\ \\ \frac{1}{8}-\frac{\overline{v}}{8}-\frac{\sqrt{(\kappa -1)(9+\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v)}}}{8(\kappa -1)}\text{ for High }\overline{v} \end{array} \right. $$
(26)

Differentiating the above expressions with respect to κ yields \( \frac {dp_{i}^{\ast }}{d\kappa }\). The expressions are quite cumbersome to report for case (i). For brevity we do not report the corresponding expressions on the comparative statics. First, consider the case when \( Max[0,(2\kappa -1)(1-\widehat {v})^{2}]<\overline {v}<\frac {2-\widehat {v}- \widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}\), one can evaluate that \( \frac {dp_{1}^{\ast }}{d\kappa }>0\). Moreover, \(\frac {dp_{2}^{\ast }}{d\kappa }<0\) for \(\overline {v}\) arbitrarily close to the lower limit \(Max[0,(2\kappa -1)(1-\widehat {v})^{2}]\) and \(\frac {dp_{2}^{\ast }}{d\kappa }>0\) for \( \overline {v}\rightarrow \frac {2-\widehat {v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}\). Since \(p_{2}^{\ast }\) is a continuous function of κ it must be that there is exist a \(\overline {v}\) in the interior of the interval \(\left [ Max[0,(2\kappa -1)(1-\widehat {v})^{2}],\frac {2-\widehat { v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}\right ] \) above which \( p_{2}^{\ast }\) is an increasing function of κ and below which it is a decreasing function of κ. This establishes the first part of the proposition which corresponds to low \(\overline {v}\).

For intermediate \(\overline {v},\)\(\frac {(1+\kappa (1-\widehat {v})+2\widehat {v })(1-\widehat {v})}{\widehat {v}}<\overline {v}<\frac {\kappa (\widehat {v} -1)^{2}-\widehat {v}(3-2\widehat {v})}{1-\widehat {v}},\)

$$ \frac{dp_{1}^{\ast }}{d\kappa }=\frac{\left( \begin{array}{c} (\widehat{v}-1)^{2}(-3+4\kappa (1-\widehat{v})^{2}+\widehat{v}^{2}+ \\ \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}- \\ \overline{v}(2+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{ v}}) \end{array} \right) }{ \begin{array}{c} \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} \\ (1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2) \overline{v}})^{2} \end{array} }<0 $$
(27)
$$ \frac{dp_{2}^{\ast }}{d\kappa }=-\frac{\left( \begin{array}{c} (\widehat{v}-1)^{2}(13+4\kappa (\widehat{v}-1)^{2}+\overline{v}^{2}+ \\ \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}- \\ v(2+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}) \end{array} \right) }{ \begin{array}{c} \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} \\ (1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2) \overline{v}})^{2} \end{array} }<0 $$
(28)

Finally, for high \(\overline {v},\)\(\overline {v}>\frac {(3-2\widehat {v}) \widehat {v}+\kappa (1-3\widehat {v}+2\widehat {v}^{2})}{(1-\kappa )(1-\widehat { v})},\)

$$ \frac{dp_{1}^{\ast }}{d\kappa }=\frac{3}{2(1-\kappa )(\sqrt{(\kappa -1)(-9+\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v})}}>0 $$
(29)
$$ \frac{dp_{2}^{\ast }}{d\kappa }=\frac{1}{2(1-\kappa )(\sqrt{(\kappa -1)(-9+\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v})}}>0 $$
(30)

This establishes all parts of Proposition 1.

1.4 Proof of Proposition 2

\({\Pi }_{i}({\Delta }^{\ast })=p_{i}^{\ast }({\Delta }^{\ast })D_{i}({\Delta }^{\ast })\) for \(i=1,2.D_{i}({\Delta }^{\ast })\) is the equilibrium demand that each firm faces given that in equilibrium Δ = Δ. \( D_{i}({\Delta }^{\ast })\) is given in the following table:

 

\(D_{1}({\Delta }^{\ast })\)

\(D_{2}({\Delta }^{\ast })\)

Low \(\overline {v}\)

\(\kappa (\widehat {v}-1)^{2}+\widehat {v}-\frac {\widehat {v }^{2}}{2}+{\Delta }^{\ast }-\frac {\kappa {\Delta }^{\ast ^{2}}}{2}\)

\(\frac {1}{2 }\left (2+(\widehat {v}-2\right ) \widehat {v}-2{\Delta }^{\ast }+\kappa \)

  

\((-2(\widehat {v}-1)^{2}+{\Delta }^{\ast 2}))\)

Intermediate \(\overline {v}\)

\(\frac {1}{2}\left (1+\kappa (\widehat {v} -1\right )^{2}-({\Delta }^{\ast }-2){\Delta }^{\ast })\)

\(\frac {1}{2}\left (-\kappa (\widehat {v}-1\right )^{2}+({\Delta }^{\ast }-1)^{2})\)

High \(\overline {v}\)

\(\kappa +\frac {1}{2}(\kappa -1)(-1+({\Delta }^{\ast }-2){\Delta }^{\ast })\)

\(\frac {1}{2}(1-\kappa )({\Delta }^{\ast }-1)^{2}\)

Given \(p_{i}^{\ast }({\Delta }^{\ast })\) in Table 3 and \(D_{i}({\Delta }^{\ast }) \) one can get \({\Pi }_{i}({\Delta }^{\ast })\). Substituting Δ given in Table 1 yields \({\Pi }_{i}^{\ast }\) as a function of market primitives (κ and c).

Next, we differentiate \({\Pi }_{i}^{\ast }\) with respect to κ to get \( \frac {d{\Pi }_{i}^{\ast }}{d\kappa }\) which again has three parts corresponding to low, intermediate, and high values of \(\overline {v}\).

For low \(\overline {v}\), or when \(Max[0,(2\kappa -1)(1-\widehat {v})^{2}]< \overline {v}<\frac {2-\widehat {v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v }}\), the comparative static expressions are again quite cumbersome. However, one can compute and show that \(\frac {d{\Pi }_{1}^{\ast }}{d\kappa }>0\). Moreover \(\frac {d{\Pi }_{2}^{\ast }}{d\kappa }|_{v\rightarrow Max[0,(2\kappa -1)(1-\widehat {v})^{2}]}<0\) and \(\frac {d{\Pi }_{2}^{\ast }}{d\kappa } |_{v\rightarrow \frac {2-\widehat {v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}}\) > 0. Since \({\Pi }_{2}^{\ast }\) is a continuous function of κ it must be that there is exist a \(\overline {v}\) in the interior of the interval \(\left [ Max[0,(2\kappa -1)(1-\widehat {v})^{2}],\frac {2-\widehat { v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}\right ] \) above which \({\Pi }_{2}^{\ast }\) is an increasing function of κ and below which it is a decreasing function of κ.

For intermediate \(\overline {v},\)\(\frac {(1+\kappa (1-\widehat {v})+2\widehat {v})(1-\widehat {v})}{\widehat {v}}<\overline {v}<\frac {\kappa (\widehat {v} -1)^{2}-\widehat {v}(3-2\widehat {v})}{1-\widehat {v}},\)

$$ \frac{d{\Pi}_{1}^{\ast }}{d\kappa }=\frac{\left( \begin{array}{c} (\widehat{v}-1)^{2}(5+ 12\kappa (\widehat{v}-1)^{2}+\overline{v}^{2}+ \\ \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}- \\ \overline{v}(2+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{ v}})(11+4\kappa (\widehat{v}-1)^{2} \\ -\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}+ \\ \overline{v}(2+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{ v}}) \end{array} \right) }{ \begin{array}{c} 16\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} \\ (1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2) \overline{v}})^{2} \end{array} }>0 $$
(31)
$$ \frac{d{\Pi}_{2}^{\ast }}{d\kappa }=\frac{\left( \begin{array}{c} (\widehat{v}-1)^{2}(21 + 12\kappa (\widehat{v}-1)^{2}+\overline{v}^{2}+ \\ \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}- \\ \overline{v}(2+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{ v}})(-5+4\kappa (\widehat{v}-1)^{2} \\ -\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}+ \\ \overline{v}(2+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{ v}}) \end{array} \right) }{ \begin{array}{c} 16\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} \\ (1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2) \overline{v}})^{2} \end{array} }<0 $$
(32)

Finally, for high \(\overline {v},\)\(\overline {v}>\frac {(3-2\widehat {v}) \widehat {v}+\kappa (1-3\widehat {v}+2\widehat {v}^{2})}{(1-\kappa )(1-\widehat { v})},\)

$$ \frac{d{\Pi}_{1}^{\ast }}{d\kappa }=\frac{\left( \begin{array}{c} (-67+\kappa^{2}(\overline{v}-1)^{4}+\sqrt{(\kappa -1)(-9+\kappa (\overline{v }-1)^{2}+(\overline{v}-2)\overline{v})} \\ -\kappa (\overline{v}-1)^{2}(6+\sqrt{(\kappa -1)(-9+\kappa (\overline{v} -1)^{2}+(\overline{v}-2)\overline{v})} \\ +\overline{v}(-4+2\overline{v}-\sqrt{(\kappa -1)(-9+\kappa (\overline{v} -1)^{2}+(\overline{v}-2)\overline{v})})) \\ +\overline{v}(-3(4+\sqrt{(\kappa -1)(-9+\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v})})+ \\ \overline{v}(-4+\overline{v}-\sqrt{(\kappa -1)(-9+\kappa (\overline{v} -1)^{2}+(\overline{v}-2)\overline{v})})))) \end{array} \right) }{64(\kappa -1)(\sqrt{(\kappa -1)(-9+\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v})}}>0 $$
(33)
$$ \frac{d{\Pi}_{2}^{\ast }}{d\kappa }=\frac{\left( \begin{array}{c} (1+\kappa (\overline{v}-1)-\overline{v}+ \\ \sqrt{(\kappa -1)(-9+\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v} )})(3+\kappa (\overline{v}-1)^{2}- \\ \sqrt{(\kappa -1)(-9+\kappa (\overline{v}-1)^{2}+(\overline{v}-2)\overline{v} )} \\ +\overline{v}(2-\overline{v}+\sqrt{(\kappa -1)(-9+\kappa (\overline{v} -1)^{2}+(\overline{v}-2)\overline{v})})) \end{array} \right) }{256(\kappa -1)^{2}(\sqrt{(\kappa -1)(-9+\kappa (\overline{v} -1)^{2}+(\overline{v}-2)\overline{v})}}>0 $$
(34)

This establishes all parts of Proposition 2.

1.5 Proof of Proposition 3

First, notice that when \(\overline {v}\) is high, \(\overline {v}>\frac {(3-2 \widehat {v})\widehat {v}+\kappa (1-3\widehat {v}+2\widehat {v}^{2})}{(1-\kappa )(1-\widehat {v})},\) equilibrium price \(p_{i}^{\ast }\) is not a function of c, establishing the last part of the proposition.

For \(\overline {v}\) sufficiently low or when \(\overline {v}\in \left [ Max[0,(2\kappa -1)(1-\widehat {v})^{2}],\frac {2-\widehat {v}-\widehat {v}^{2}}{ 1-\kappa -\kappa \widehat {v}}\right ]\),

$$ \begin{array}{@{}rcl@{}} \frac{dp_{1}^{\ast }}{d\widehat{v}} &=&\frac{ \begin{array}{c} 2(2\kappa -1)(\widehat{v}-1)(5+\kappa^{2}(8(\widehat{v}-1)^{2}+\overline{v} ^{2}) \\ (\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}- \\ \kappa (12+4(\widehat{v}-2)\widehat{v}+ \\ \overline{v}(2+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})}))) \end{array} }{ \begin{array}{c} \sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})} \\ (1-\kappa \overline{v}+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2 \overline{v}+\kappa \overline{v}^{2})} \end{array} }<0\text{ for }\kappa >1/2\text{ }\\ &\Longrightarrow &\text{ }\frac{dp_{1}^{\ast }}{dc}>0\text{ for }\kappa >1/2 \end{array} $$
(35)

The opposite holds true for \(\kappa <\frac {1}{2}\)

$$ \begin{array}{@{}rcl@{}} \frac{dp_{2}^{\ast }}{d\widehat{v}} &=&-\frac{ \begin{array}{c} 2(2\kappa -1)(\widehat{v}-1(5+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v} -1)^{2}-2\overline{v}+\kappa \overline{v}^{2})} \\ +\kappa (4-4(\widehat{v}-2)\widehat{v}+\kappa (8(\widehat{v}-1)^{2}+ \overline{v}^{2})- \\ \overline{v}(2+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})}))) \end{array} }{ \begin{array}{c} \sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})} \\ (1-\kappa \overline{v}+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2 \overline{v}+\kappa \overline{v}^{2})} \end{array} }\\ &&>0\text{ for }\kappa >1/2\text{ }\\ &\Longrightarrow &\text{ }\frac{dp_{2}^{\ast }}{dc}<0\text{ for }\kappa >1/2 \end{array} $$
(36)

The opposite holds true for \(\kappa <\frac {1}{2}\)

Finally, for intermediate \(\overline {v}\) or \(\frac {(1+\kappa (1-\widehat {v})+2\widehat {v})(1-\widehat {v})}{\widehat {v}}<\overline {v}<\frac {\kappa (\widehat {v}-1)^{2}-\widehat {v}(3-2\widehat {v})}{1-\widehat {v}}\)

$$ \begin{array}{@{}rcl@{}} \frac{dp_{1}^{\ast }}{d\widehat{v}} \!\!&=&\!\!\frac{\left( \begin{array}{c} 2\kappa (\widehat{v}-1)(-3+4\kappa (1-\widehat{v})^{2}+\overline{v}^{2}+ \\ \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}-\overline{v }(2+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}) \end{array} \right) }{\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} (1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2) \overline{v}})^{2}}\\ &&>0\text{ }\\ &\Longrightarrow &\text{ }\frac{dp_{1}^{\ast }}{dc}<0\text{ } \end{array} $$
(37)
$$ \begin{array}{@{}rcl@{}} \frac{dp_{2}^{\ast }}{d\widehat{v}} \!&=&\!\!-\frac{\left( \begin{array}{c} 2\kappa (\widehat{v}-1)(13+4\kappa (\widehat{v}-1)^{2}+\overline{v}^{2}+ \\ \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}-v(2+\sqrt{ 9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}) \end{array} \right) }{\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} (1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2) \overline{v}})^{2}}\\ &&>0\text{ }\\ &\Rightarrow &\text{ }\frac{dp_{2}^{\ast }}{dc}<0 \end{array} $$
(38)

This establishes all parts of Proposition 3.

1.6 Proof of Proposition 4

Akin to equilibrium prices, for high \(\overline {v},\) equilibrium profit is not a function of c. Hence equilibrium profit is invariant to changes in search cost c.

For \(\overline {v}\) sufficiently low or when \(\overline {v}\in \)\(\left [ Max[0,(2\kappa -1)(1-\widehat {v})^{2}],\frac {2-\widehat {v}-\widehat {v}^{2}}{ 1-\kappa -\kappa \widehat {v}}\right ]\),

$$ \begin{array}{@{}rcl@{}} \frac{d{\Pi}_{1}^{\ast }}{d\widehat{v}} \!\!&=&\!\!\frac{\left( \begin{array}{c} ((2\kappa -1)(\widehat{v}-1)(13+ \\ \kappa^{2}(24(\widehat{v}-1)^{2}+\overline{v}^{2})+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}- \\ \kappa (20 + 12(\widehat{v}-2)\widehat{v}+\overline{v}(2+ \\ \sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}))) \\ (3-\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}+\kappa (4+8\kappa (\widehat{v}-1)^{2}- \\ 4(\widehat{v}-2)\widehat{v}-\kappa \overline{v}^{2}+ \\ \overline{v}(2+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})})))) \end{array} \right) }{ \begin{array}{c} (8\kappa \sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})} \\ (1-\kappa \overline{v}+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2 \overline{v}+\kappa \overline{v}^{2})}^{2} \end{array} }\\ &&<0\text{ for }\kappa >1/2\text{ }\\ &\Longrightarrow &\text{ }\frac{d{\Pi}_{1}^{\ast }}{dc}>0\text{ for }\kappa >1/2 \end{array} $$
(39)

The opposite holds true for \(\kappa <\frac {1}{2}\)

$$ \begin{array}{@{}rcl@{}} \frac{d{\Pi}_{2}^{\ast }}{d\widehat{v}} &=&-=\frac{\left( \begin{array}{c} ((2\kappa -1)(\widehat{v}-1)(13+\kappa^{2}(24(\widehat{v}-1)^{2}+\overline{v }^{2})+ \\ \sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}- \\ \kappa (4+ 12(\widehat{v}-2)\widehat{v}+ \\ \overline{v}(2+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})}))) \\ (3-\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v}+\kappa \overline{v}^{2})}+ \\ \kappa (-12+8\kappa (\widehat{v}-1)^{2}- \\ 4(\widehat{v}-2)\widehat{v}-\kappa \overline{v}^{2}+ \\ \overline{v}(2+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})})))) \end{array} \right) }{ \begin{array}{c} (8\kappa \sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2\overline{v} +\kappa \overline{v}^{2})} \\ (1-\kappa \overline{v}+\sqrt{9+\kappa (8(2\kappa -1)(\widehat{v}-1)^{2}-2 \overline{v}+\kappa \overline{v}^{2})}^{2} \end{array} }\\ &&>0\text{ for }\kappa >1/2\text{ }\\ &\Longrightarrow &\text{ }\frac{d{\Pi}_{2}^{\ast }}{dc}<0\text{ for }\kappa >1/2 \end{array} $$
(40)

Finally, for intermediate \(\overline {v}\) or \(\frac {(1+\kappa (1-\widehat {v})+2\widehat {v})(1-\widehat {v})}{\widehat {v}}<\overline {v}<\frac {\kappa (\widehat {v}-1)^{2}-\widehat {v}(3-2\widehat {v})}{1-\widehat {v}}\)

$$ \begin{array}{@{}rcl@{}} \frac{d{\Pi}_{1}^{\ast }}{d\widehat{v}} &=&\frac{\left( \begin{array}{c} \kappa ((\widehat{v}-1)(5+ 12\kappa (\widehat{v}-1)^{2}-2\overline{v}+ \overline{v}^{2}+ \\ \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}-\overline{v }\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}) \\ +(11+4\kappa (\widehat{v}-1)^{2}+ \\ 2\overline{v}-\overline{v}^{2}-\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}+ \\ \overline{v}\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}) \end{array} \right) }{ \begin{array}{c} 8\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} \\ (1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2) \overline{v}})^{2} \end{array}}\\ &&<0\text{ or} \end{array} $$
(41)
$$ \begin{array}{@{}rcl@{}} \text{ }\frac{d{\Pi}_{1}^{\ast }}{dc} &>&0\text{ } \end{array} $$
(42)
$$ \begin{array}{@{}rcl@{}} \frac{d{\Pi}_{2}^{\ast }}{d\widehat{v}} &=&\frac{\left( \begin{array}{c} \kappa ((\widehat{v}-1)(21 + 12\kappa (\widehat{v}-1)^{2}-2\overline{v}+ \overline{v}^{2}+ \\ \sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}- \\ \overline{v}\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} )+(-5+4\kappa (\widehat{v}-1)^{2}+ \\ 2\overline{v}-\overline{v}^{2}-\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}}+ \\ \overline{v}\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} ) \end{array} \right) }{8\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2)\overline{v}} (1-\overline{v}+\sqrt{9+8\kappa (\widehat{v}-1)^{2}+(\overline{v}-2) \overline{v}})^{2}}\\ &&>0\text{ or} \end{array} $$
(43)
$$ \begin{array}{@{}rcl@{}} \text{ }\frac{d{\Pi}_{2}^{\ast }}{dc} &<&0 \end{array} $$
(44)

This establishes all parts of Proposition 4.

1.7 Proof of Proposition 5

For brevity, we provide a shorter version of the proof of Proposition 5. Specifically, we do not report all the expressions that are included in evaluating the comparative statics, but instead offer those complete expressions as available from the authors on request. For low \(\overline {v}, \overline {v}\in \left [ Max[0,(2\kappa -1)(1-\widehat {v})^{2}],\frac {2- \widehat {v}-\widehat {v}^{2}}{1-\kappa -\kappa \widehat {v}}\right ] ,\) we first compute the consumer surplus by substituting the equilibrium, \( p_{i}^{\ast }(i=1,2)\) and Δ. The expressions are provided in the tables above. Next, we differentiate the resulting expression with respect to κ and evaluating the resulting expression yields the result stated in the proposition. For intermediate \(\overline {v}\) or \(\frac { (1+\kappa (1-\widehat {v})+2\widehat {v})(1-\widehat {v})}{\widehat {v}}< \overline {v}<\frac {\kappa (\widehat {v}-1)^{2}-\widehat {v}(3-2\widehat {v})}{1- \widehat {v}}\), we use the appropriate \(p_{i}^{\ast }(i=1,2)\) and Δ that is provided in the tables above to compute the equilibrium consumer surplus. For \(\overline {v}\) we check the corners. In other words, we evaluate it for c = 0 and \(c=\frac {1}{8}\). Next, we verify that \(\frac {dCS}{d\kappa }<0\) for c = 0 and \(\overline {v}\) in the intermediate region. Furthermore, \(\frac {dCS}{d\kappa }>\) for \(c=\frac {1}{8}\) and \( \overline {v}\) in the intermediate region. Since CS is a continuous function of c and \(\overline {v}\) the result in Proposition 5 (part ii) follows. Finally, for high \(\overline {v}\) or \(\overline {v}>\frac {(3-2 \widehat {v})\widehat {v}+\kappa (1-3\widehat {v}+2\widehat {v}^{2})}{(1-\kappa )(1-\widehat {v})},\) again substitution of \(p_{i}^{\ast }(i=1,2)\) and Δ from table 1 and 2 yields the appropriate expression for the consumer surplus. Differentiating the resulting expression with respect to κ and evaluating the sign of \(\frac {dCS}{d\kappa }\) shows that the equilibrium consumer surplus monotonically declines with respect to κ

This establishes all parts of Proposition 5.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Galbreth, M.R., Ghosh, B. The effect of exogenous product familiarity on endogenous consumer search. Quant Mark Econ 18, 195–235 (2020). https://doi.org/10.1007/s11129-019-09220-8

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11129-019-09220-8

Keywords

JEL Classification

Navigation