Co-Creation with Bandwagon Effects

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Co-Creation with Bandwagon Effects
Niladri Syam*
Department of Marketing and Entrepreneurship
University of Houston
Houston, TX 77204
Email: nbsyam@uh.edu
Phone: 713-743-4568
Rambod Dargahi
Department of Marketing and Entrepreneurship
University of Houston
Houston, TX 77204
Email: rdargahi@bauer.uh.edu
Phone: 713-743-4734
James D. Hess
Department of Marketing and Entrepreneurship
University of Houston
Houston, TX 77204
Email: jhess@uh.edu
Phone: 713-743-4175
* Corresponding author
Please do not cite without permission
August 15, 2013
Co-Creation with Bandwagon Effects
Abstract
We study the behavior of consumers who co-create products with a firm and ask how
bandwagon effects (social preferences) on the consumers affect their co-creation choices.
Consumers have to make three related decisions: (1) Should they just buy the standard, off-theshelf product or should they buy the customized product? (2) If they choose customization, what
is the optimal design of the customized product (customized design) and how should they split
the design task between themselves and the firm (extent-of-co-creation)? (3) In deciding on the
above, how should they take into account the preferences of other customers (bandwagon
effects)?
Our model allows us to ask how bandwagon effects determine how the market is endogenously
segmented among customers who choose the standard product, those who do the entire
customization task themselves (DIY-ers), and those who co-create the customized product with
the firm. We also analyze how bandwagon effects determine the optimal customized design and
the optimal extent-of-co-creation.
We find that for low levels of bandwagon intensity all co-creators will choose the customized
product at their ideal locations. Interestingly, our main result in this case finds that an increase in
the bandwagon intensity can either increase or decrease the mass of co-creators. When the fixed
setup cost of the customized product is large (small), then an increase in the bandwagon intensity
causes a decrease (increase) in the mass of co-creators. We have experimentally tested our main
result and found support for it.
For higher levels of bandwagon intensity co-creators may choose to customize at a location other
than their ideal location. Thus, bandwagon effects can explain why consumers may opt for lessthan-perfect customization even when they do choose customization over standardization.
We contribute by (1) developing an analytical model of how consumers co-create their ideal
products in the presence of social preferences, and (2) experimentally testing our model.
Keywords: Co-creation; Product Design; Social Preferences; Rational Expectations Equilibrium
1. Introduction
1
Consider the following scenario: Bob, an avid dirt-biker and an amateur videographer
always wanted to combine his two hobbies on weekends. Some of the off-road trails he often
rides on are very scenic and Bob would like to share these sights with his friends. The major
problem is that he has to stop to capture the videos since the trails are very bumpy, making it
very difficult shoot the videos while riding. Calling on all his ingenuity, Bob has been able to
come up with an idea for a steadicam stabilizing mount that makes it easier to shoot videos while
on his dirt-bike. Now Bob is faced with the problem of finding a way to get his steadicam
produced. He recently heard of eMachineShop.com, an online vendor that allows people to
design and buy custom engineering products. eMachineShop.com’s user interface requires Bob
to translate his idea to an engineering design, and moreover allows buyers like Bob, who are not
completely familiar with manufacturing, to let the company build or partially build their designs.
At this point, Bob has to make some hard decisions.
Though eMachineShop.com offers custom designs they also offer standard designs in
their ‘Store Buyers’ webpage. Bob could easily buy a product with a standard design similar to
his requirements even though it may not fully meet his exact requirements. Depending on their
skills, dirt-bikers ride on trails of wildly varying topographical features and the amount of
bumpiness they experience is an important consideration in the design of the steady-cam.
Bob could instead opt for a custom design. Some aspects of design are more demanding
than others so Bob would have to figure out how much of the design task he would complete and
how much he would ask eMachineShop’s experts to do. If he is willing to devote considerable
time and effort, which in turn will depend on his cost of time and effort, he could do the entire
design task as a do-it-yourself (DIY) project.
2
Finally, what about being able to sell the steadicam he creates? He noticed that in
eMachineShop’s ‘Store Sellers’ webpage the company features designs created by people like
Bob and these designs are available for sale to others who might have similar needs. If Bob ever
wanted to sell his co-created steadicam, clearly the demand would be higher if Bob is able to
reflect the preferences of others in his design. Since the sale to others has the potential for
considerable earnings, to the extent of even defraying his total cost of obtaining the steadicam,
this is an important consideration for Bob.
In light of what has been said above, consumers who consider a customized product have
to make three cognate decisions. First, should they co-create a custom design according to their
specific preferences or should they just get the standard, off-the-shelf design? Second, if they
choose to co-create, how much of the co-creation should be done by them and how much should
be offloaded to the firm? Third, in developing their product design how should they account for
the preferences of other customers in order to be fashionable or to enhance resale value?
Advances in information technology and manufacturing increasingly facilitate the
participation of the customer in the production of goods and services (Syam and Pazgal 2013). A
practical manifestation of co-creation is user design of products (Griffin and Hauser 1993; von
Hippel and Katz 2002; Randall, Terweisch and Ulrich 2007). Powered by the internet, instances
of user design of products continue to increase. Dahan and Hauser (2002) report how web-based
interfaces have been used for user-design of cameras, copier finishers, laptop bags, laundry
products, etc. Lulu.com allows everyone to become their own publisher and provides individuals
with printing and fulfillment infrastructure that, in the past, was the province of large publishing
houses. In this research, co-creation is conceptualized as a division of the production task
3
between the firm and the consumer. So the provision of customized products to the consumer is
the end which is achieved through various levels of co-creation between firm and customer.
From the consumer’s point of view the co-creation of many customized products,
especially high ticket items, have an emotional or social aspect to them. For firms offering cocreated products and for academics seeking to understand them, it is important to understand the
personal and social motivation of the customer who co-creates a product that she will later
consume. Our focus is on the behavior of the consumer who co-creates a customized ideal
product when social factors influence the attractiveness of the product.
Consider a potential homeowner jointly designing her home with a builder. On the one
hand the homeowner will want to personalize her home to her specific tastes, but on the other
hand she will also keep an eye on the likely tastes of other people. This could be for many
reasons. She may want to resell the home at some point in the future and this is likely to induce
her to reflect the preferences of others in her own design. More generally, she may change her
personalization decisions for the sake of fitting in with what she perceives are the preferences of
other people whose opinions she values. This is Leibenstein’s (1950) bandwagon effect that
“represents the desire of people to purchase a commodity in order to get into ‘the swim of
things’; in order to conform with the people they wish to be associated with; in order to
be fashionable or stylish; or, in order to appear to be ‘one of the boys.’” (page 189).
One can easily see this in the case of apparel where our desire to get uniquely customized
clothes may be tempered by our desire to fit in with our peer group. When social phenomena are
incorporated then each economic agent is required to account for the behavior of all other
economic agents in her decision making, and in our case the behavior in question is the product
choice of others. Since all consumers in the market are making a similar prediction about others’
behavior, consistency requires analysis in the spirit of rational expectations equilibrium models.
4
Moreau and Herd (2010) and Moreau and Bonney and Herd (2011) have empirically
investigated some of the social forces in co-creation. However many aspects of how social
influences affect consumer’s co-creation decisions remain under-researched especially in terms
of building economic models of this phenomenon. Our model adds to the recent spate of work
that incorporates psychological and social forces in analytical models of marketing phenomena
(Amaldoss and Jain 2005). Syam et. al. (2008) have investigated how consumers’ feelings of
regret and miswanting can affect their design of the customized product, though the authors did
not explicitly model the division of the design task between firm and customer. Godes’ (2013)
investigation of how the extent of word-of-mouth communication among consumers affects the
optimal quality offered by the firm is similar in spirit, although the focal actor in our paper is the
consumer.
In this research we adopt the consumer’s point of view and ask how she co-creates
products taking the firm’s decisions, like prices, as given. We address the following research
questions: (1) How do consumers decide whether they should just buy the standard, off-the-shelf,
product or the customized product? (2) If they choose customization, what is the optimal design
of the customized product (customized design) and how should they split the design task
between themselves and the firm (extent-of-co-creation)? (3) In deciding on the above, how
should they take into account the preferences of other customers (bandwagon effects)? The last
question is important. As already mentioned, at eMachineShop.com drill bits and other machine
tools co-created by the firm and a consumer can then be sold to other consumers via the firm’s
store. These now become the off-the-shelf or default standard products for others, and new
consumers visiting the site can co-create their own machine tools or merely buy one of the
standard tools on sale. At Threadless.com which co-creates customized T-shirts with consumers,
5
a shirt designed by a given consumer is then made available for sale to others. In both cases the
amateur designers whose designs of drill bits or T-shirts are sold get part of the proceeds from
the sale, and so their utility from co-creation can be greatly enhanced if they are able to reflect
the choices of other consumers in their co-created designs.
We have two kinds of results pertaining to the segment of co-creators in the market and
their design of the co-created product. First, our most interesting result finds that, as the
bandwagon intensity increases the mass of co-creators can either decrease or increase. When the
setup cost for customization is large then an increase in the bandwagon intensity causes a
decrease in the mass of co-creators. When the setup cost for customization is large there is a
large segment of standardizers and the standard design serves as a focal point which becomes
more attractive as bandwagon intensity increases. On the contrary, when the setup cost for
customization is small then an increase in the bandwagon intensity causes an increase in the
mass of co-creators. This latter result is non-intuitive because, though a small setup cost implies
a large group of customizers, by definition there is large heterogeneity in the designs of the
various customized products and consumers cannot focus on any one design. We have
experimentally tested our main result and found support for it. Second, an increase in the
bandwagon intensity affects the design of the co-created (customized) product in a complex
manner. When bandwagon effects are absent and even for low levels of bandwagon intensity
consumers always choose the customized product at their ideal locations. Interestingly, for high
levels of bandwagon intensity consumers may choose to customize at a location other than their
ideal. Thus, we may see less-than-perfect customization because of bandwagon effects even in
situations where consumers would always choose perfect customization absent such bandwagon
effects. This result is similar to that in Syam et al. (2008) who find that consumers’ feelings of
6
regret could cause them to optimally choose less-than-perfect customization. Regret of losing out
on a better alternative is an individual-level emotion whereas the current paper incorporates
social aspects of attending to the choices of other people in the market.
Our main contribution lies in (1) providing an analytical model of product co-creation in
the presence of social preferences on the part of consumers, and (2) experimentally testing the
main predictions of our analytical model. Our analytical model endogenizes the decision of the
customer to opt for the standard or the customized product. In the latter case, we endogenize the
optimal design of the customized product and the extent of co-creation of the customized
product. Incorporating social preferences in co-creation is important because of the increasing
role of consumers in designing their ideal products, and since consumers are social beings, the
role of social forces in their design choices is important to understand.
2. Co-Creation Model
Some of the forces at work may best be seen by first ignoring the social aspect of cocreation. This will serve as a benchmark case, to be contrasted with a situation where we
introduce bandwagon effects which are social preferences or other-regarding preferences. In
what follows, when we refer to the non-standard product we will use the terms customized
product and co-created product interchangeably. In both cases the product that is finally
consumed is customized to the customer’s preference but it may or may not be co-created with
the firm depending on whether or not it is optimal for the customer to do some of the design task
herself. Our focus is on investigating the behavior of customers who take the firm’s prices as
given and decide whether and how to co-create with the firm.
7
2.1 Co-creation without Bandwagon Effects
In the current section we analyze the base case where consumers have only self-regarding
preferences, that is, there are no bandwagon effects. Consider a market where a monopolist
firm’s product has attribute level 0, and where a unit mass of consumers have preferences for
ideal products distributed uniformly on [0, 1] . The monopolist sells two types of products, a
standard product and a customized product that differs from the standard one. The consumption
utility of the self-focused consumer whose ideal is at x from buying the standard product is
USelf
Std  V  x  P .
(1)
Here V is the consumer’s valuation for his ideal product, but the standard product at 0 is less
than ideal by an amount x, and P is the price of the standard product.
Consider the customized product. Ignoring the social aspect for the time being, the
consumption utility of consumer x from buying a customized product z is
2
USelf
Custom  V  ( x  z)  (P  PS  PC k )  (z  k ) .
(2)
The meanings of the variables will be explained subsequently. We allow the customer to
optimally choose the amount of customization she desires. She can get a customized product at
point z (≤ x), where z denotes the ‘customized design’ desired by her. Depending on parameters
the buyer at x may optimally choose to get her customized product exactly at her ideal location x,
in which case z=x. Said differently, the ‘customized design’ z is the consumer’s optimal design
of the product. Since a consumer’s social preferences are incorporated (Section 2.2) the optimal
design of the customized product may not be at her ideal location x.
In the spirit of co-creation the customized product at z can be produced collaboratively by
the firm and customer. The ‘extent-of-co-creation’ will be denoted by k, 0≤ k ≤ z, where the
‘extent-of-co-creation’ is just the division of the manufacturing task between customer and firm
8
(see Anderson 2002). The firm will partially co-create the customized product’s design from 0 to
k and the customer x will complete the customized design from k to z. The extent-of-co-creation
k will be determined optimally depending on the price changed by the firm for its share of cocreation and the customer’s own cost of co-creating. In many instances, for example at
eMachineShop.com, it is the customer who decides to what extent she would need the firm to
step in to help co-create the product. To summarize, there are two aspects of customization
choices for the consumer at x: she will optimally choose both the ‘customized design’ z and the
‘extent-of-co-creation’ k. The former determines her optimal design of the customized product
and the latter determines the division of the design task between the firm and the consumer.
Since the manufacture of customized products involves a separate setup for different
customers, most sellers of customized products charge a setup price for them. This is true in the
case of eMachineShop.com where the vendor charges a setup price which is independent of the
amount of custom work that needs to be done. Indeed, the following quote from their website
makes this point abundantly clear:
“In custom manufacturing - whether for machine parts from eMachineShop, printed
brochures from a printer or stuffed teddy bears, setup costs are often the main factor in
the price when ordering just one or a few parts…The reason is that a custom
manufacturer has to go through several steps whether you order one or many parts”
The setup price, PS, is charged to the customers regardless of the extent of customization
they require the firm to do and is added onto the standard price. Additionally, if the consumer
requires the firm’s help with customization then the firm changes a price of PC per unit of
customization, so that the total price to customize from 0 to k is P+PS+PC k. As an illustration,
eMachineShop’s pricing link specifies the following about its pricing:
“Have eMachineShop staff make a CAD drawing (or convert from another format) for
you for a small fee.” [our italics]
or,
9
“Draw your part yourself in the free CAD Download (or use the import feature) to get an
instant price.”[our italics]
Of course, if the customer rationally chooses to do all the customization herself (k =0),
then she will not incur either the setup price or the unit price for customization. The customer
completes the product by bringing it from k, where the firm delivers it, to z at a cost that is
quadratic in the distance. The cost of product completion borne by the customer is (z  k ) 2 .
The following result specifies the customization choices for the typical consumer whose
ideal product is located at x. Notice that not all consumers will want to customize and we will
return to this below.
Proposition 1: Let 0<PC<1. If the consumer whose ideal is located at x chooses a
customized product, the customized design and extent of co-creation are
P
 P 
P 
a) z*=x and k*=0 when x  0, C  or b) z*=x and k*= x  C when x   C , 1 .
2
 2 
 2 
Proof: See Appendix.
Proposition 1 gives the customization choices of consumer x. This consumer has to make
two related decisions regarding her choice of customization. First, she has to determine the
customized design, in other words, the product design given by z*. Second, she has to determine
the extent-of-co-creation, in other words, the division of labor specifying how much she wants
the firm to build, k*, and how much she will do herself, z* k*.
In the absence of social influences the typical consumer would optimally choose a
product customized to her ideal location, that is at z*=x. The consumers located further away
from the standard product at 0 will choose to co-create their ideal product such that the firm does
P
an amount of production given by k *  x  C , and the consumer at x then completes the
2
product by customizing the rest of the way from k* to x. It makes sense that the extent of co10
creation done by the firm decreases in the price PC and increases in the customer’s marginal cost
of self-production δ. Consumers who are located closer to the standard product at 0 will do all of
the production themselves. This is because, being located close to the standard product, their cost
of customization is not very large and they would like to avoid the setup cost of co-production.
We call these consumers the Do-It-Yourself (DIY) types.
The above analysis assumed that the customer was buying a customized product.
However, the customer could choose to avoid customization altogether and merely buy the
standard product, although there is an opportunity cost of not having the ideal design. The
following proposition shows how the market is divided between the customized and the standard
products.
Proposition 2: Let 0<PC<1 and
PC
< x̂ <1 where
2
2

 PC  

x̂  PS  
 /(1  PC ) .

2  



 P 
a. For x  0, C  the consumer at x chooses a customized product over the standard
 2 
product. Her customization choices are k*=0 and z*=x. These consumers are Do-ItYourself (DIY) consumers who get the perfectly ideal product at x, but do all the
customization themselves by choosing the firm’s portion of customization k* to be
zero.
P

b. For x   C , x̂  the consumer at x chooses the standard product 0.
 2 
c. For x  x̂, 1 the customer at x chooses a customized product over the standard
P
product. Her customization choices are k*= x  C and z*=x. These consumers are co2
creators. They get their perfectly ideal product at x, but ask the firm to do part of the
customization, k*>0, and then complete the product by bringing it to their ideal
location x.
Proof: See Appendix.
11
(3)
Figure 1 shows how the market is segmented between the customers who prefer the
standard product and the customized product. Among those who prefer the customized product,
some choose to do all the customization themselves and are the DIYers. Other customers who
prefer the customized product over the standard product are the co-creators who will jointly
design the customized product with the firm.
Choose
Standard
Product
DIY
0
Co-Create
^x
PC
2
1
Figure 1: Market segmentation between DIYers, standardizers and co-creators
The market segmentation in Proposition 2 shows that there are two distinct, non P 
connected segments of consumers who purchase the customized product. Those in 0, C 
 2 
customize the product without any help from the firm. On the other hand, those in x̂, 1
 P 
customize the product with the help of the firm. The segment of DIYers in 0, C  has a very
 2 
small cost of customization since their design are very close to the standard and they will just
P

customize their ideal product themselves. The customers in segment  C , x̂  are farther away
 2 
from the standard product and so have a higher cost of customizing the product all by
themselves. If they chose to customize they would do it jointly in collaboration with the firm.
However, the misfit of their ideal product from the standard product is not very large and so they
cannot justify paying the setup price charged by the firm for the customized product. These
12
consumers then opt for the standard product. The customers in segment x̂, 1 have ideals very far
away from the standard product and so have a very large marginal cost of customizing the
product all by themselves. They therefore prefer to have the firm co-create the customized
product. Moreover, since they have high misfit they are also willing to pay the setup price to get
an ideal product.
Note the role of the setup price in creating the mass of standard product purchasers. If the
P
P 
P 
setup price is very small, x̂  C or Ps  C 1  C  , then all consumers purchase a
2
2 
2 
customized product. Those closer to the firm will be DIYers and those further away are coP 

creators. On the other hand if the setup price is very large, x̂  1 or Ps  1  PC 1  C  , then
4 

there will be no co-creators in the market. Those closer to the firm will be DIYers and those
further away will just purchase the standard product. Throughout, we assume setup costs are
neither very small nor very large.
2.2 Co-creation with Bandwagon Effects
The valuation of many products has a social aspect. We assume that a person who
consumes design x gets additional utility if this product reflects the preferences of other
consumers in the market. In addition to wanting a fashionable product, the consumer may also
want to sell the product at some point in the future. This is the bandwagon effect, which we
model by computing the aggregate distinction of the chosen design from the products chosen by
others.
Consider the standard product. The other-regarding or social utility from buying the
standard product for consumer x when there are bandwagon effects is
13
Bandwagon
UStd
 V  P  x   - Expected distance from 0 to what others choose ) .
(4)
In the above  is the bandwagon intensity parameter. It the degree to which consumers care
about reflecting the design choices of others in their own design.  is the value that consumer
derives when her choice of product is maximally fashionable in the sense that it is perfectly
consistent with that of others. Her happiness is diminished if there is some misfit between her
product at 0 and what others choose, and in that case gives additional utility “(- Expected
distance from 0 to what others choose).” Seen through the lens of the resale metaphor, “Expected distance from 0 to what others choose” can be thought of as the resale price adjusted
by the less fashionable product at 0. When the standard product is exactly the product desired by
others, then the consumer that buys design 0 is perfectly fashionable and gets the maximum
possible price of  from a resale. Of course, what others would choose is endogenously
determined and the typical consumer x calculates her utility based on how she expects the others
to behave. In a Rational Expectations Nash Equilibrium her expectation of others behavior has to
be consistent with the others’ true behavior.
Similar to the case of the standard product, the social utility from buying the co-created
customized product for consumer x when there are bandwagon effects is
Bandwagon
U Custom
 V  ( x  z)  P  (PS  PC k )  (z  k ) 2
 ( - Expected distance from z to what others choose ).
(5)
Note that here the distance is from z to what others chose. As in Section 2.1 we allow
consumers to choose their customized design at a location which is different than their ideal. We
assume that the customer at x wants to get the customized product at z≤ x, where the ‘customized
design’ will be optimally determined as in Section 2.1. The customized design z can be cocreated by the firm and customer, and the ‘extent-of-co-creation’ will be denoted by k, 0≤ k ≤ z.
14
When there are bandwagon effects, the optimal ‘customized design’ z and the ‘extent-ofco-creation’ k could depend on the bandwagon intensity . As with the case of choosing the
standard product, the term “ Expected distance from z to what others choose” can be thought
of as the resale price adjusted by the misfit of the owned product at z and others’ desired product.
When the customized product at z is exactly the product desired by others, there is no misfit and
consumer x gets the maximum possible price from a resale.
The rational expectations Nash equilibrium calculation is complicated because consumers
have to form rational expectations of others’ behaviors along two dimensions: (1) The designs of
the customized product chosen by these other consumers who choose to customize and, (2) The
mass of the other consumers who choose to customize or to buy the standard product.
Consider the following market segmentation when consumers have social preferences,
that is, they experience bandwagon effects. In the rational expectations Nash equilibrium
framework we proceed under the assumption that every consumer believes that all those
consumers who lie to the right of a product design  (ideal points higher than  ) will choose an
ideally customized product while those to the left of  (ideal points lower than  ) but above
PC/2 will choose the standard product. This belief will be shown to be consistent in equilibrium.
Choose
Standard
Product
DIY
0
Co-Create

PC
2

Figure 2: Market segmentation with bandwagon effects
15
1
P

Customers x   c ,   will purchase the standard product. For the focal standardizing
 2 
consumer x who chooses the standard product at 0, we have
“Expected distance from 0 to what others choose” =
PC
2
0

 2 1 1  PC 
( y  0)dy  PC (0  0)dy   ( y  0)dy       .

2 2 2  2 
2

2
1
(6)
The first integral on the right hand side is for all the other customers who have ideal points y
below
PC
, and who choose to DIY customized products at y. Their distance from the focal
2
standardizing consumer who gets the standard product at 0 is y-0 and the segment of such
 P 
consumers is 0, C  . The second integral is for all the other customers who have ideal points y
 2 
P

in  C ,   , and who are believed to choose the standard products at 0. Their distance from the
 2 
focal standardizing consumer who gets the standard product at 0 is (0-0). The third integral is for
all other customers who have ideal points y in [  , 1], and who are believed to get customized
products at y. Their distance from the focal standardizing consumer who gets the standard
product at 0 is equal to y-0.
Customers x  [  , 1] will purchase the customized product at z. For the focal customizing
consumer who chooses the customized product at z we have
“Expected distance from z to what others choose” =
PC

z
1
2 (z( x )  y)dy 
(
z
(
x
)

0
)
dy

(
z

y
)
dy

( y  z)dy.
PC
0

z
2




(7)
P
The first integral on the right hand side is for customers y who have ideal points below C , and
2
who DIY to get customized products at y. Their distance from the focal customizing consumer
16
 P 
who gets the customized product at z is z-y and the segment of such consumers is 0, C  . The
 2 
P

second integral is for all the other customers who have ideal points in  C ,   and who choose
 2 
the standard product at 0. Their distance from the focal customizing consumer who gets the
customized product at z is z-0. The third and fourth integrals are for all other customers who
have ideal points y in [  , 1], and who choose to get customized products at y. Their distance
from the focal customizing consumer who gets the customized product at z depends on whether
y is less than z (third integral) or larger than it (fourth integral).
For consumers with ideals in [ , 1] what is the best product design z? The consumer at x
will either choose her co-created customized product at her ideal location x or at a point z < x.
We will denote the former situation as ‘Ideal’ co-creation and the latter as ‘Non-Ideal’ cocreation. It is not rational for her to choose customization at a point z > x because she will get a
non-ideal product and at a higher customization cost. The following lemma determines the
optimal design of the customized product for consumers with ideals in [ , 1] when there are
moderate levels of social bandwagon preferences.
Proposition 3: Let the bandwagon intensity be small,  < 1  PC , then in a rational
expectations Nash equilibrium the customized design chosen by consumers at x  [  , 1] is
z*=x. Thus, there is Ideal co-creation.
Proof: See Appendix.
Notice the force of Proposition 3 in ensuring that a consumer’s expectations of other
consumers’ behavior with respect to product design are rational. The consumer at x  [  , 1]
expects that all other consumers at y  [  , 1] will choose z(y)=y. Given these beliefs, she then
finds it optimal to design her customized product at z=x. Since x is just a generic consumer who
17
is designing her optimal customized product, the design given in proposition 3, z*=x, is a rational
expectations Nash equilibrium design.
Proposition 3 also states that when the bandwagon intensity is low then the co-creation is
of the ‘Ideal’ co-creation type. The condition that bandwagon intensity is small has bite. We will
show in Section 4 that when bandwagon effects are higher, then it is possible to have equilibria
with Non-Ideal co-creation. Of course DIY consumers also get the customized products at their
ideal locations, but they are not co-creators since they do all the production themselves.
Using z=x in (6), for the focal co-creating consumer we have
“Expected distance from z=x to what others choose” =
PC

02 (x  y)dy  P
C
x
1

x
( x  0)dy   ( x  y)dy   ( y  x )dy 
2
(8)
2
x2  x 
 2 1 1  PC 
  
 .
2
2 2  2 
Substituting (6) and (8) into (4) and (5), and upon using z=x, we obtain the social utilities
from buying the standard and customized products:
2

 2 1 1  PC  
Bandwagon
and
U Std
( x )  V  P  x    
  


2 2 2  2  


Bandwagon
U Custom
(x)
2

 2 1 1  PC  
2

 V  P  PS  PC k  ( x  k )    - x  x 
  
 .

2 2 2  2  


2
(9)
(10)
We must derive the optimal extent-of-co-creation k that the consumers in [,1] will choose by
maximizing utility given in (10). Taking the derivative of (10) with respect to k we can find the
optimal k, in other words, the ‘extent-of-co-creation’ that customer x desires:
18
Bandwagon
U Custom
k
 PC  2( x  k )  0
(11)
P
or k *  x  C
2
As a result, the optimal utility of consumers in [ , 1] is
2
2

 2 1 1  PC  
P 
Bandwagon
U Custom
( x )  V  P  PS  PC x   C     - x 2  x 
  
 .

2 2 2  2  
 2 


(12)
One can quickly check that in the limit without bandwagon effects (→0), upon
substituting k *  x  PC /( 2) into (10) and equating with (9), the consumer who is indifferent

P2 
between the standard and co-created products is given by x  x̂   Ps  c  /(1  PC ) . Thus, the

4 

identity of the indifferent customer in the limit without bandwagon effects is the same as that in
Proposition 2 in section 2.1, as is reasonable to expect. From the above discussion, when the
bandwagon intensity is low, that is when 0     , then the customer at x  [  , 1] will
P 

choose z* ( x )  x; k * ( x )  x  C  .
2 

The utilities in (9) and (12) depend upon . We now consider how this threshold that
defines the number of co-creators is determined. It is clearly related to the bandwagon intensity
parameter . Solve for the consumer who is indifferent between the standard product and the
ideal co-created product. For consistency of our rational expectations Nash equilibrium the
consumer at x=  should be indifferent between buying the co-created product and the standard
Bandwagon
one, that is UStd
Bandwagon
()  U Custom
() . Consider the consumer at x=  . Substituting
x=  in (9) gives the optimal utility of choosing the standard product in terms of  :
19
  2 1 1  P 2 
 V  P     
   C  .
(13)
 2 2 2  2  



Substituting x= in (12) gives the optimal utility of choosing the customized co-created product
Bandwagon
U Std
( )
in terms of  :
2

P 2
3 2 1 1  PC  
Bandwagon
U Custom
( )  V  P  PS  PC   C      
  
 .

4
2
2 2  2  


(14)
The rationality condition gives us an implicit equation which defines the equilibrium threshold of
co-creating, denoted * . If we set (13) and (14) equal we obtain a quadratic equation in :
P P
 P 
22  (1  PC  )  C  C   C    PS  0 .
2  2
 2  
(15)
Equation (15) can be solved to find the marginal consumer * who is indifferent between buying
the co-created (customized) product and the standard product, when consumers take into account
the product choices of other consumers in the market. Equation (15) has two roots and the
following result rules out the larger one,
Proposition 4: In a rational expectations Nash equilibrium with small bandwagon
intensity   (0,  ),   1  PC , the consumer who is indifferent between standardization
and co-creation is given by


2
1  PC 
 PC 

x̂

 

1  PC 
2 


* 1
  1 
1  1  8
(16)
.
2
4
 

 1  PC 
1 








Proof: See Appendix.
20
Economic forces help determine * and therefore the proportion of consumers that chose
to co-create. It is easy to see, for example, if the setup cost of co-production, PS, increases, then
there is less co-creation: * increases in x̂ which from (3) is positively related to setup cost, PS.
More interestingly, social forces also affect which consumers choose to co-create. How
do the proportions of co-creators and standardizers change when the bandwagon intensity 
increases? Intuitively one might expect that as the bandwagon intensity grows more consumers
will want to imitate the cohort of customers that are buying the standard product. This intuition
can be mistaken, as seen in our principal theorem.
Theorem 1: Let bandwagon intensity be   (0,  ) . There is a setup cost P̂S such that
 *
 0 : when the setup cost is high then an increase in bandwagon
a. If PS  P̂S then

intensity decreases the number of co-creators;
 *
 0 : when the setup cost is low then an increase in bandwagon
b. If PS  P̂S then

intensity increases the number of co-creators.
Proof: See Appendix.
This result is intriguing because it shows that as the bandwagon intensity increases the
number of co-creators may either increase or decrease; this differential effect is determined by
the magnitude of the setup costs of co-production. Why? As the bandwagon intensity increases,
a typical consumer would increasingly like in her own product to reflect the preferences of
others. Since a large PS implies that * is also large, many consumers will naturally choose the
standard product to avoid the setup costs. The typical consumer then leans even more towards
the standard product when her bandwagon intensity increases because it is fashionable. Thus, the
segment of customers who choose the standard product increases as the bandwagon intensity
increases. On the other hand, when PS is small then * is also small, implying that many
21
consumers choose a co-created, customized product. A consumer who wishes to reflect others’
choices in her own will opt for a customized product over the standard one. Thus, the segment of
customers who choose the co-created customized products increases as bandwagon intensity
increases.
Two aspects of Theorem 1 are important to note. First, the insight offered in Theorem 1b
would be difficult to guess without careful analysis. Theorem 1a says that as the bandwagon
intensity increases, more consumers will buy the standard product. Since there is one fixed
design for the standard product (at 0), one might guess that if enough people are buying the
standard product and the social preference (bandwagon intensity) increases then the attraction for
the standard product further increases. However, unlike the standard product, there is no fixed or
focal design of customized products, which by definition are different for different consumers.
Part 1b analyzes the case where a large proportion of the market is buying customized products
and the bandwagon intensity increases. The heterogeneity of custom designs means that there is
no fixed custom design for a customer to focus on as she decides whether to customize or
standardize. In this case consumers have to mentally do a rather complex calculation of how
close their customized design will be to the ‘average’ of all the custom designs of all the other
customizers in the market. As the social preference (bandwagon intensity) increases, more cocreated products are chosen. In Section 3, we find empirical support for this non-intuitive result.
Second, we haven’t assumed an exogenous group of consumers of fixed size that
absolutely prefers the standard product. If the mass of standardizers is exogenously fixed, then it
is a forgone conclusion that this group, and its choice of product, becomes more and more
important as the intensity of social preference increases. In that case, as the bandwagon intensity
increases more consumers would like to purchase the standard product in order to be more
22
fashionable. In our model the segment of customers choosing the standard product is
endogenously derived, so as the bandwagon intensity increases either more or fewer customers
will buy the standard product as detailed in Theorem 1. All consumers form rational expectations
of other consumers’ behaviors and make optimal choices based on maximizing their own
utilities, although these utilities have social components.
Theorem 1 has a clear managerial implication for firms that wish to increase the number
of people that co-create products with them. Part (b) of the proposition states that the number of
 *
 0 ) when the setup cost of customization, PS, is small and
co-creators will increase (that is

the firm is able to induce higher intensity of social preference among its customers. One obvious
manner in which the firm can influence a higher intensity of social preference is to encourage the
customers to focus on the resale value of their customized product. When the resale value is high
then consumers will want to attend to the preference of others in the market. Of course, the firm
usually gets a part of the resale price of custom designs created by consumers since the firm
usually displays these designs in their ‘buyer’s section’, as in the case of eMachineShop.com.
Thus, a combination of low setup cost of customization but a high resale price, part of whose
proceeds the firm will get, will lead to an increase in the mass of co-creators for the firm.
Below, we will test the main implication of our model given in Theorem 1.
3. Experimental Study
The theory is tested in a 2×2 design experiment. One factor was setup cost (low versus high) and
the other was bandwagon intensity (absent versus present). Thirty-six students participants were
recruited from a major public university by providing extra credit in a course, as well as having
the opportunity to win $5 or $10 based on their performance in the experiment.
23
3.1 Procedure
The experiment was done in a computer lab using z-Tree (Fischbacher 2007).
Participants designed a bicycle that they would buy for a niece, where the design attribute was its
color. The standard bicycle was a very pale green color (shade #0), but it could be customized to
darker shades of green, as shown in Figure 3. Participants were told the shade of green that their
niece found ideal, and were asked to make choices on behalf of the niece, regardless of their
personal tastes.
Figure 3: Shades of Green to Customize Bike Color
The participants could either buy the standard bike for their niece, or incur the cost to add
layers of paint to bring the bike’s color closer to their niece’s ideal. Adding additional layers to
the bike could be done either by the local bike store or by themselves. The standard bike cost
$100, and the bike store charged a setup cost (low =$14 and high=$20) plus $7 for every layer
added by the store. They could also chose to paint layers by themselves at a cost; a cost table
was provided telling the total cost of DIY or co-creation. When setup costs are low, the theory
predicts a midrange threshold color for co-creation, so participants were told their niece preferred
a shade # 3 green (which is below the threshold). When setup costs were high, the niece wanted
a shade #7 green that is above the corresponding threshold. Participants needed to make three
decisions: (1) Will they choose the standard bike color or a customized color? (2) In the case
they choose the customized bike, how many layers of paint did they want to add to the standard
24
bike color? (3) Of the number of total layers that they want, how many will they paint
themselves (given that the store will paint the rest)? Each scenario was repeated three times in
order for the participants to have an opportunity to correct mistakes.
After these decisions were recorded, participants were told that because their niece was
likely to outgrow her bike, they would also have to consider the resale value of the bike (the
niece could use the resale price for other things she wanted). The resale price depended upon
how different the bike is from the color of bikes chosen by others. They were told that every
shade of green from 0 to 10 was equally likely to be the ideal for someone else’s niece. Resale
value sheets were provided and the decisions were repeated for low and high setup cost.
Decisions were repeated for low and high setup costs, only now when resale value of the bike
was relevant. The theory predicts that for low setup costs, the threshold between standardization
and co-creation should diminish and the participant should switch to now wanting to co-create a
customized bike. On the other hand, for high setup costs, the resale value should motivate the
participant to buy a “popular” standard bike.
The theory developed above implies the following hypotheses.
H1: When setup costs are low, stronger bandwagon intensity increases the probability that a
consumer co-creates.
H2: When setup costs are high, stronger bandwagon intensity decreases the probability that a
consumer co-creates.
As a consequence of these, we can also hypothesize:
H3: Higher setup cost negatively moderates the effect of bandwagon intensity on probability
of co-creators.
3.2 Logit Model of Co-Create or Standardize
Experimental design predicts that the probability that co-creation is chosen depends upon
whether the setup cost is small or large and whether the bandwagon effect is absent or present,
25
along with a moderated effect. The logit model of choice expresses the log odds of co-creation in
terms of a factor  0  1dum   2 PSdum   3dum  PSdum , where dum and PSdum are the
dummy coded variables represent low and high values of bandwagon intensity and setup cost.
The coefficients i represent the effects of variables on log-odds, but our theory-driven
hypotheses are about probabilities. For example, the moderation effect on probabilities is not the
logit coefficient 3 of the interaction term ×PS on , but the difference in differences in

 

1
1
1
1
probabilities, 



. These
 ( 0  1   2   3 )
 ( 0   2 )  
 ( 0  1 )
 ( 0 ) 
1 e
1 e
1  e
 1  e

are a nonlinear functions of all the parameters, but can be computed along with its standard
errors via bootstrapping (see Ai and Norton 2003, and Hess, Hu, Blair 2013).
Table 1
Logit Regression of Co-Creation versus Standard Product
as a function of Bandwagon Intensity  and Setup Cost PS
Incremental effect
on probability of
co-creation
Hypothesis

PS=0

PS=1

0.203*
(0.095)
-0.501*
(0.089)
-0.705*
(0.130)
p-value
Logit Coefficients
i
0.0322
0.000
-4.964*
(1.245)
2.772*
PS
(1.076)
1.299*

(0.643)
0.779*
Intercept
(0.364)
Notes: Setup Cost PS and Bandwagon Intensity  are dummy coded {0,1}
Standard error in parentheses; Number of observations=144
Value of the log-likelihood= -64.505
Number of bootstrap resamples for Incremental Effects on Probability=5,000.
×PS
0.000
The estimated logit coefficients and resulting incremental effects on the probability of cocreating are found in Table 1. Figure 4 illustrates the findings.
26
0.972
0.888
Probability of Co-Creating Product
Setup Cost PS
High
0.685
Low
0.472
Low
High
Bandwagon Intensity 
Figure 4: The Effect of Bandwagon intensity on Co-Creating
According to hypothesis H1, when setup costs are low then many customers choose to cocreate a customized product, although a wide variety of different designs are chosen (between *
and 1). If the bandwagon intensity increases, customers who previously chose the standard
product are drawn to co-creation because there are so many other co-created products being
used. In the experiment with setup costs low ($14), the person whose ideal is shade #3 green
tends to switch from the standard green to a co-created customized green when the bandwagon
effect is increased. The probability of co-creating rises by 0.203 (p=0.03) supporting H1.
On the other hand, when setup costs are large, very few consumers want to co-create and
many choose the standard product to avoid the setup costs. Hypothesis H2 states that as the
bandwagon intensity increases, customers who previously co-created will be drawn toward the
large number of people choosing the standard product. In the experiment, when setup costs are
high ($20), the person whose ideal is shade #7 green tends to switch from a customized green
color to the standard color when the bandwagon effect is increased. The probability of co-
27
creating falls by 0.501 with p=0.00, thus supporting H2. The difference-in-difference in
incremental effects of bandwagon intensity for low and high setup costs, -0.705, is also highly
statistically significant, in line with the moderation hypothesis H3.
4. Higher Bandwagon Intensity
The analysis in Section 2 was carried out when the bandwagon intensity of consumers is
low (<1-PC). In that case we saw that consumers always rationally choose Ideal co-creation
where the customized design is at their ideal location. In the current section we show that when
the bandwagon intensity is high then consumers may choose Non-Ideal co-creation. Since the cocreation without bandwagon effects is always ideal co-creation, this shows that bandwagon
effects are the reason for Non-Ideal co-creation.
We will construct an equilibrium where all co-creating consumers are doing Non-Ideal
co-creation, and demonstrate that, unlike the case with low bandwagon intensity, such an
equilibrium can be rational when bandwagon intensity is higher. Consider the market
segmentation in Figure 5 where all consumers located in [χ, 1] are Non-Ideal co-creators who
buy the imperfectly customized design at χ.
Choose
Standard
Product
DIY
0
Pc
Co-Create
to Non-Ideal

1
2
Figure 5: Market segmentation with non-ideal co-creators
Consider the consumer located at x, ≤x≤1. She could have the following alternate belief
about how the market is segmented:
28
Belief NIC (Non-Ideal Co-creation): Consumer x expects that all other consumers y in [, 1] are
non-ideal co-creators who customize their product at 
The following result shows that for higher bandwagon intensity this can be rational.
Proposition 5: There exists a * such that 1-PC< * where there exists a rational
expectations Nash equilibrium with the following characteristics:
 P 
1. Consumers in 0, C  are DIYers who customize the product at their ideal locations
 2 
P

but do not co-create with the firm, consumers in  C , *  are standardizers and
 2

*
consumers in [ ,1] are co-creators.
2. All co-creators choose the customized product at *, that is, they are Non-Ideal coP 

creators. The optimal choices for the co-creators are z* ( x )  * ; k * ( x )  *  C .
2 

Proof: See Appendix.
Proposition 5 states that Non-Ideal co-creation can be an equilibrium when the
bandwagon intensity exceeds 1-PC (although it may not be the unique one). This contrasts with
the case of low bandwagon intensity, β<1-PC, where Non-Ideal co-creation is not possible.
It is important to note the difference between  * in section 2.2 and  * in the current
section. In section 2.2 all consumers x in [  * , 1] are Ideal co-creators who get the perfectly
designed customized product at their ideal locations x. In the current section all consumers in
[  * , 1] are Non-Ideal co-creators who get the imperfectly designed customized product
at  *  x . The critical difference between low and high bandwagon intensity lies in the optimal
design of the co-created product. When the bandwagon intensity is low (section 2.2) consumers
always choose the co-created customized product at their ideal location and therefore the design
of the co-created product does not vary with . In contrast when the bandwagon intensity is high,
the optimal design of the co-created product, given by * , depends on .
29
5. Conclusion
Co-creation of goods and services jointly by the firm and consumers is growing in
popularity owing to increases in information technology and user interfaces. This research
focuses on the behavior of consumers who co-create custom designs with the firm when social
influences are important.
We develop an analytical model of how social influences, specifically bandwagon
effects, determine the market segmentation among customers who choose the standard product,
customers who design their ideal customized product entirely by themselves (DIYers), and
customers who co-create their product with the firm. Our model also allows us to investigate
how social influences determine the optimal design of the customized product, that is, the
customized design, and the optimal extent-of-co-creation.
We find that those who buy the standard product are sandwiched on either side by
customers who do all the customization by themselves (DIYers) and customers who will cocreate with the firm. Thus, there are two distinct, non-connected segments of consumers who
purchase the customized product. Our main result finds that, as the bandwagon intensity
increases the mass of co-creators can either decrease or increase. When the proportion of the
market that chooses the standard product is fairly large, then an increase in the bandwagon
intensity causes a decrease in the mass of co-creators. On the contrary, when the proportion of
the market that chooses the standard product is small, then an increase in the bandwagon
intensity causes an increase in the mass of co-creators. This result has been experimentally tested
and we have found support for it. Finally, we find that for high levels of bandwagon intensity
consumers may rationally choose to customize the product at a location other than their ideal.
This contrasts with the case without bandwagon effects or when the bandwagon intensity is low,
30
in which case consumers will optimally design their customized products at their ideal locations.
Our contribution lies in developing an analytical model of product co-creation when consumer’s
social preferences are important, and secondly we experimentally test the main predictions of our
model.
This paper focuses on co-production, leaving aside the process by which the product
design is created by an interaction of buyer and seller. For complex, multidimensional products,
consumers may not have the expertise to know what constitutes a feasible bundle of product
attributes and may require assistance from the seller on co-designing the customized product.
Since our focus is on the behavior of co-creating customers we also set aside the issue of how the
prices are determined by the seller. These and other issues are left for future research.
31
References
Ai C, Norton EC (2003) Interaction terms in logit and probit models. Econ Lett. 80(1): 123-29.
Amaldoss W, Jain S (2005) Pricing of conspicuous goods: a competitive analysis of social
effects. J. Marketing Res. 42(1): 30-42.
Anderson, ET (2002). Sharing the wealth: when should firms treat customers as partners?
Management Sci. 48(8): 955–971.
Bendapudi N, Leone R (2003) Psychological implications of customer participation in coproduction. J. Marketing 67(1): 14-28.
Dahan E, Hauser JR (2002) The virtual customer. J. Prod. Innov. Management. 19(5): 332-353.
Fay S, Mitra D, Wang Q (2009) Ask or Infer? strategic implications of alternative learning
approaches in customization. Internat. J. Res.Marketing. 26(2): 136-152.
Fischbacher U (2007) z-Tree: Zurich toolbox for ready-made economic experiments,
Experimental Econom 10(2): 171-178.
Franke N, Keinz P, Steger C (2009) Testing the value of customization: when do customers
really prefer products tailored to their preferences? J. Marketing. 73(5): 103-121.
Franke N, Schreier M, Kaiser U (2010) The "I Designed It Myself" effect in mass customization.
Management Sci. 56(1): 125-140.
Godes, D (2013) Product policy in markets with word-of-mouth communication. Working paper.
University of Maryland, College Park, MD.
Hess, JD, Hu Y, Blair E (2013) On testing moderation effects in experiments using logistic
regression. Working paper, University of Houston, Houston, TX.
Kramer T, Spolter-Weisfeld S, Thakkar M (2007) The effect of cultural orientation on customer
responses to personalization. Marketing Sci. 26(2): 246-258.
Leibenstein, H (1950), Bandwagon, snob, and veblen effects in the theory of consumers'
demand. Quarterly J. Econom. 64(2): 183-207.
Moreau P, Bonney L, Herd KB (2011) It’s the thought (and the effort) that counts: how
customizing for others differs from customizing for oneself. J. Marketing. 75(5): 120-133.
Moreau P, Herd KB (2010) To each his own? how comparisons with others influence
consumers’ evaluations of their self-designed products. J. Consumer Res. 36(5): 806-819.
32
Randall T, Terwiesch C, Ulrich K (2005) Principles for user design of customized products.
Calif. Management Rev. 47(4): 68-85.
Randall T, Terwiesch C, Ulrich K (2007) User design of customized products. Marketing Sci.
26(2): 268-280.
Redstrom J (2006) Towards user design? on the shift from object to user as the subject of design.
Design Studies 27(2): 123-139.
Sawhney M, Verona G, Prandelli E (2005) Collaborating to create: The Internet as a platform for
customer engagement in product innovation. J. of Interactive Marketing. 19(4): 4-17.
Simonson I, (2005) Determinants of customers' responses to customized offers: conceptual
framework and research propositions: J. Marketing 69(1): 32-45.
Syam N, Ruan R, Hess JD (2005) Customized products: a competitive analysis. Marketing Sci.
24(4): 569-584.
Syam N, Krishnamurthy P, Hess JD (2008) That’s what i thought i wanted? miswanting and
regret for a standard good in a mass-customized world. Marketing Sci. 27(3): 379-397.
Syam N, Pazgal A (2013) Co-creation with production externalities. Marketing Sci. forthcoming.
Thomke S, von Hippel E (2002) Customers as innovators: a new way to create value. Harvard
Bus. Rev. 80(4): 74-81.
Terwiesch C, Loch C (2004) Collaborative prototyping and the pricing of custom designed
products. Management Sci. 50(2): 145-158.
Fischbacher U (2007), Z-Tree: Zurich toolbox for ready-made economic experiments.
Experimental Econom. 10(2): 171-178.
von Hippel E (1994) “Sticky Information” and the locus of problem solving: implications for
innovation. Management Sci. 40(4): 429-439.
von Hippel E (1998) Economics of product development by users: the impact of “sticky” local
information. Management Sci. 44(4): 629-644.
von Hippel E, Katz R (2002) Shifting innovation to users via toolkits. Management Sci. 48(7):
821-833.
33
Appendix
Proof of Proposition 1:
 P 
Case a: Let x  0, C  . First, fix a z ≤x and determine the optimal k given z. From (2), the first
 2 
order condition for an interior solution gives,
U Self
Custom
k
=  PC  2(z  k) =0, which implies
P
P
that k(z)  z  C . But z ≤x< C , therefore k(z) is negative. Since k is the amount of
2
2
customization to be done by the firm, it has to be non-negative and so an interior solution is
inadmissible. At a corner solution, we will either have k * (z) =0 or k * (z) =z. What is rational for
the consumer to do? From the consumer surplus (2), the consumer’s total cost of customization is
C(z, k)= PS  PC k  (z  k ) 2 . If we set k=0 the cost is C(z,0)   z 2 , recalling setup cost is
avoidable. On the other hand, if we set k  z the cost is C(z, z)= PS  PC z . Clearly, since z ≤
PC
P
by assumption, therefore  z 2 ≤ C z ≤ PC z < PS  PC z .Thus, we have C(z, 0)≤ C(z, z),
2
2
and the consumer is better off DIYing, k*=0. Substituting this value into (2)
2
gives CSSelf
Custom  V  P  ( x  z)   z . Second, optimizing now with respect to design z, the
first order condition for an interior solution of z gives z=
P
1
1
. Given that z ≤x< C <
, the
2
2 2 
interior solution is inadmissible, so the consumer will choose the largest possible z, z*=x.
P 
Case b: Let x   C , 1 . First, fix a z ≤x and determine the optimal k given z:
 2 
34
P

if z  C ,
0
2
k (z)  
z  PC if z  PC .
2
2

We analyze two subcases.
P
Case b.i: If z ≤ C then k (z)  0 . Substituting this in the consumer’s surplus and following a
2
logic similar to above, we can see that she will choose the maximum possible z consistent with
PC PC2
P

V

P

x


all constraints: z= C . Optimized consumer surplus is CSSelf
.
Custom
2 4
2
P
P
Case b.ii: Suppose z > C . Substituting k(z)  z  C the consumer surplus results in
2
2
PC2
CSSelf

V

P

x

(
1

P
)
z

P

. This is linear in z, and because 1-PC >0 the
C
S
Custom
4
consumer will choose the largest possible z consistent with all constraints, z  x . Optimized
PC2

V

P

P
x

P

consumer surplus is CSSelf
.
C
S
Custom
4
P
P
Will the consumer choose { k (z)  0 ; z = C } or { k (z)  x  C ; z  x }? Case b.i is
2
2
P
P
preferred if PS  (1  PC )( x  C ) . Since PC<1 and by assumption x  C , the right hand side
2
2
is positive. Thus, as along as the setup cost is not too high, the optimal customization choice for
P
the consumer is { k * (z)  x  C ; z *  x }. 
2
 P 
Proof of Proposition 2: Let x  0, C  . If the consumer chooses customization, she will choose
 2 
2
k * (z)  0 and z *  x and the optimal consumer surplus is CSSelf
Custom  V  P   x . Notice that
35
since the consumer does not ask for any customization from the firm, she also does not pay the
Self
setup costs. CSSelf
Custom > CSstd if x<
P
. This is true since x< C and PC<1.

2
1
P 
Now consider x   C , 1 . If the consumer chooses customization, she will
 2 
P
choose k * (z)  x  C and z*=x, so optimal consumer surplus is
2
PC2
PC2
Self
Self
CS
CSSelf

V

P

P
x

P

V

P

P
x

P

CS
.
>
or
>VPx
Custom
C
S
C
S
Custom
std
4
4
if x> x̂ . Thus, if x> x̂ the consumer will buy the customized product, and if
will buy the standard product. Finally we need to ensure that
PC
<x< x̂ then she
2
PC
< x̂ <1. This reduces to
2
PC  PC 
P  PC 
 P 
 PC 
1 
  PS  1  PC 1  C  . It can be checked that C 1 
 as
  1  PC 1 
2 
2 
4 
2 
2 
4 


long as PC  min{ 1, 2} .

Proof of Proposition 3:
We determine the equilibrium product design chosen by consumer x when she has social
preferences and takes other people’s designs into account. Because the cost of customization
increases with the distance of a consumer’s location from the location of the firm’s default
product at 0, it is conceivable that a given consumer x very distant from 0 will choose an
imperfectly customized product which lies to the left of her ideal location x. Of course, because
bandwagon effects matter, consumer x will take into account the co-creation choices of others in
designing her co-created product. Suppose consumer x has the following belief about other
consumers y in [  , 1].
36
Belief IC (Ideal Co-creation): Consumer x expects that all other consumers y in [  , 1]
perfectly customize their products at y
We will show that this belief is rational by showing that, given this belief of others
behaviors, consumer x will also optimally choose to customize at her ideal location x. Since x is
a generic consumer in [,1], this will establish the rationality of this belief. Let customer x
customize her product at z, where z is in the interval [,1], that is  ≤ z≤ x. We will determine
the optimal z and k with the above segmentation. From equation (6) the expected distance from
her product at z(x) to what others choose is obtained by substituting z(y)=y because all other
customers y (≠x) are ideal co-creators who get the product at their ideal locations y.
“Expected distance from z to what others choose”=
Pc

z
1
2

z
 IC   2 (z  y)dy  Pc (z  0)dy   (z  y)dy   ( y  z)dy .
0
Computing the integrals and simplifying gives
P
c
z
1

2
 IC  (zy  1 y 2 )  zy Pc  (zy  1 y 2 )  ( 1 y 2  zy )
2
2
2
0

z
2
2
P 
  1  C   z2  z  1 2  1
2  2 
2
2
The utility of the consumer is
2


 PC 
1
U  V  x  z  P  PS  PC k  (z  k )    
  z2  z  1 2  1  .
2  2 
2
2


2
Maximize this with respect to k and z. First, the optimal value of k, given z, is
k z
PC
2
. Back substituting gives
37
(17)
2


Pc2
1  PC 
U  V  x  z  P  PS  PC z 
   
  z2  z  1 2  1  .
2
2
4
2  2 


The marginal utility with respect to product location z is
U
 1  PC  (2z  1) . Setting it
z
equal to zero and solving gives the interior optimal solution z  (1  (1  PC ) / ) / 2 . By
assumption   1  PC , and therefore this interior solution exceeds 1 and is inadmissible. Simple
re-arrangement gives
U
 (1  PC  )  2(1  z)  0 . The value of z will be increased until the
z
constraint z ≤ x is binding. The equilibrium solution is
z*  x ; k *  x  PC 

2 


(18)
This solution is consistent in equilibrium since consumer x’s Belief IC, that everyone in [,1] is
perfectly customizing, is correct. Given this supposition about others’ behaviors, she too finds it
optimal to customize perfectly at z*(x)=x.
We will now show that it is not rational to expect that a sub-segment of [,1] will do nonideal co-creation when   1  PC . Nor is the belief that all consumers in [,1] will do non-ideal
co-creation. Consider the following market segmentation where consumers located at the farthest
right choose to buy the imperfectly customized product at χ. This is the sub-segment of non-ideal
co-creators. Consumers in [,] are ideal co-creators who buy the perfectly customized product.
That is, consumers in x  [,] buy the customized product at their ideal locations x.
38
DIY
0
Non-Ideal
Co-Creation
Ideal
Co-Creation
Standardize
Pc
2


1
Figure 6: Market segmentation with ideal and non-ideal co-creators
Consider the consumer located at x  ,1 in Figure 6. She could have the following
alternate belief about how the market is segmented.
Belief M (Mixed Co-creation): Consumer x expects that all other consumers y in [, 1]
are non-ideal co-creators who customize their product at while those in [, χ] are ideal
co-creators who buy the perfectly customized product.
Suppose customer x in [] has Belief M, and customize her product at z, ≤ z≤ x. What is the
expected distance from her product at z to what others choose?
“Expected distance from z to what others choose”=
Pc
2


1
2


 M   (z  y)dy  Pc (z  0)dy   (z  y)dy  
0
(z  )dy .
The first and third integrals follow because the DIY consumer y in [0,
(19)
Pc
] and also consumer y
2
in [  , χ] choose ideal co-creation at their ideal locations y. The fourth integral follows because
the all other customers in the interval [, 1] choose non-ideal co-creation at . Computing the
integrals and simplifying gives
P
c


1
2
 M  (zy  1 y 2 )  zy Pc  (zy  1 y 2 )  (z  ) y 
2
2
0

2
2
P 
  1  C   1  2    1  2  z.
2  2 
2
2
39
(20)
The utility of the consumer in this segment ≤x≤1 is
2


P 


2
2
1
1
1
U  V  x  z  P  PS  PC k )  (z  k )             z .
2 2
2
2
 




2
Maximize this with respect to k and z. First, the optimal value of k given z is
k z
PC
2
. That is, the customer produces
Pc
and asks the firm to do the rest. Back
2
substituting gives utility as a function of only z:
2


P2
P 
U  V  x  z  P  PS  PC z  C      1  C   1  2    1  2  z  .
2  2 
2
2


4


To determine the optimal z, the marginal utility with respect to product location z is
(21)
U
 1  PC   >0,
(22)
z
which is positive, implying that consumer x will choose z*=x. Thus her choice is in contradiction
to her belief that all consumers in [, 1] will choose non-ideal co-creation at 
What about non-ideal co-creation for all consumers in the segment farthest from the standard
product at 0? Consider the following market segmentation where = and all consumers located
in [χ, 1] are non-ideal co-creators who buy the imperfectly customized product at χ. Consider
Figure 5 and suppose the consumer located at x, ≤x≤1. She could have the following alternate
belief about how the market is segmented.
Belief NIC (Non-Ideal Co-creation): Consumer x expects that all other consumers y in [, 1] are
non-ideal co-creators who customize their product at 
Let customer x customize her product at z, ≤ z≤ x. What is the expected distance from her
product at z to what others choose?
40
“Expected distance from z to what others choose”=
Pc

1
2
 NIC  (zy  1 y 2 )  zy Pc  (z  ) y 
2
0
2
2
 PC 
1
 
  2    z
2  2 
(23)
.
The utility of the consumer in this segment ≤x≤1 is
2


P 
U  V  x  z  P  PS  PC k  (z  k ) 2     1  C    2    z  .
2  2 


The optimal value of k is k  z 
PC
2
. Back substituting gives utility as a function of only z:
2


P2
P 
U  V  x  z  P  PS  PC z  C     1  c    2    z  .
2  2 
4


(24)
The marginal utility with respect to product location z is
U
 1  PC   .
z
(25)
For   1  PC this derivative is positive implying that consumer x will choose z*=x. Thus her
choice is in contradiction to her belief that all consumers in [, 1] will choose non-ideal cocreation at 
Finally, since the above derivation with Belief IC was carried out under the assumption
that all DIY consumers are perfectly customizing at their ideal locations, we need to confirm that
this is indeed rational for them to do. Consider the segmentation in Figure 6 above. Consider
 P 
customer x in 0, C  who takes the behavior of the standardizing consumers in
 2 
 PC 
 2 ,   and the


ideally co-creating consumers in [  , 1] as given. Further x believes that all others DIY
41
 P 
consumers y in 0, C  are getting the perfectly customized product at their ideal locations y.
 2 
Suppose consumer x gets the customized product at z≤ x≤
PC
. What is her optimal choice of z?
2
“Expected distance from z to what others choose”=
Pc
z

1
2

   (z  y)dy   2 ( y  z)dy  Pc (z  0)dy   ( y  z)dy .
0
z
(26)
Computing the integrals and simplifying gives
2
P
1 1
 PC 
1
 
  2z C  z 2  z(2  1)    2 .
2  2 
2
2 2
(27)
P
The utility of the consumer in this segment ≤x≤ C is
2
2

P 
1 1 
 PC 

1
U  V  x  z  P  z    
  z 2  1  2 C   z 2    2  .
2  2 
2 
2 2 



2
(28)
Note that in (28) because the consumer x is DIYing, she can avoid setup cost. The marginal
utility with respect to product location z is
interior solution as ẑ 
P
U
 1  2z  (1  2 C  2  2z) . This gives the
z
2
P
1
 
1

   C   . Notice that at z=0,
2(  )    
2 2 
P
U
1
 1  2(  C  ) >0 for  small. So the utility U increases at z=0. Clearly, if the
z z  0
2 2
interior maximum ẑ lies to the right of
P
that ẑ ≥ c is equivalent to  
2
PC
then the optimal z is z*=x. Simple algebra shows
2
1 1  1  PC  . Because
2
 


  1  PC the right hand side exceeds 1,
so the optimal z for consumer x in the DIY segment is z*=x, and we thus we have shown that it is
rational for the DIY consumers to perfectly customize at the ideal locations. 
42
Proof of Proposition 4:
P P
 P 
From equation (15) the equilibrium  * solves 2 2  (1    PC )  C  C   C    PS  0 .
2  2
 2  
There are two roots of this quadratic equation given by,
1  1  PC  1

  1 
4
  4
2
4P  P
P  8P
 1  PC 
1 
  C  C  C   S
 
  2
2  


P 2
Using x̂   PS  C  /(1  PC ), the above becomes

4 



2
1  PC 
 PC 

x̂

 

1  1  PC 
2 


  1 
1  1  8
.
2
4
 

 1  PC 
1 



 



(29)
Since the analysis without bandwagon effects is the boundary case of the analysis with
bandwagon effects, as  approaches 0, the correct root for  should approach x̂ . Notice the term
1
1  PC
on the right hand side of (29) goes to infinity as →0. Also, using L’Hopital’s rule on

the term under the radical gives
lim   0
  P  2 (1  P ) x̂ 
C 
 C  
  2 




 1  PC
1 





2
= lim   0
 4 x̂
=0.
 1  PC 
1 

 

If we consider the larger root in (29) (with the + sign) then the entire term inside the curly braces
approaches 2, so the larger root approaches  as →0, a contradiction. On the other hand, for the
smaller root, the term in curly braces on right hand side of (29) approaches 0 as →0. Combined
43
 1  PC 
with the fact that the multiplier 1 
 goes to infinity as →0, so the smaller root tends to
 

a finite limit. Thus, the smaller root is the correct one. Now for the root to be valid we need the
 PC  1  PC
xˆ
  
2 


expression under the square root sign to be positive, 1  8
>0. It can be checked
2
 1  PC 
1 

 

2
that is will be the case for small β. Combining this with the requirement that β< 1-PC we can find
a critical value of β , say  , such that the smaller root in (29) identifies the consumer that is
indifferent between standardization and co-creation in equilibrium. 
Proof of Theorem 1:
From equation (15) the implicit equation defining the equilibrium  * is

P 2
P P
 P 
2 2  (1    PC )  C  C   C    PS  0 . Using x̂   PS  C  /(1  PC ), the

2  2
4 
 2  

dividing line between standardizing and co-creation when =0, the above can be expressed as
2
P 
2  (1  PC  )  x̂ (1  PC )    C   0 .
 2 
2
P
Notice that, by assumption, x̂  C , which implies that setup cost PS is sufficiently large that
2
some customers want to avoid co-creation if  is near zero. For algebraic simplicity, let


, where   [0, 1] . The implicit equation defining the equilibrium  can be expressed
1  PC
as
44
 P 2

x̂      C     2 2   F( ) .
  2 



(30)
Equation (30) implies that the equilibrium  is given by the intersection of a line x̂   and a
2
parabola F() which has two roots,
1 1
P 

1  2 C  , one positive and one negative. Note
4 4
  
2
P
P
that because x̂   C    C  , so the left hand side of (30), x̂   , exceeds F() at =0 for ≤1.
 2   2 
It is easy to see that F() is upward sloping at zero and is maximized at  = ¼ . See Figure 7.
For the graph to look precisely like Figure 7 the positive root of parabola, where the
function F() meets the -axis, exceeds x̂ or
P 2
PS  C
1 1
P 
4 .

1  2 C   x̂ 
4 4

(
1

P


C)
2
This is equivalent to
PS  P̂S 

2
2
1  PC 
 PC    PC 
1

1

8

.





4 
 2    2 


45
(31)
F(z )
x̂
x̂ - z
b
æçè P
ö
÷
2d ø
æ
æ PC ö
÷
è 2d ø
f çç -2z 2 + z + ç
2
è
C
2
ö
÷÷
ø
a
x̂
1
4
z
Figure 7: Graphs of F(  ) and x̂   when x̂ is smaller than root of F(  )
Let us investigate what happens when  increases from 0 given (31). The curvature of
F() sharpens and we move from the bold curve to the dashed curve in Figure 7. Note that the
parabola’s root where the function F()=0 is independent of the value of f whereas its intercept
increases in . The equilibrium  is given by the intersection of curve corresponding to F() and
the line x̂   . As  (equivalently ) increases the point of intersection moves from point ‘a’ to
‘b.’ In other words, the equilibrium  decreases:

 0.

Now consider the case where inequality (31) is not satisfied as in Figure 8 where the
positive root of parabola, where the function F()=0, is smaller than x̂ .
46
F
x̂
x̂ - z
2
æ
æP ö ö
f çç -2z 2 + z + ç C ÷ ÷÷
è 2d ø ø
è
 æç PC ö÷
2
è 2d ø
x̂

c
1
4
d
Figure 8: Graphs of F() and x̂   when x̂ is larger than root of F()
Again, when  increases from 0 (increasing ), the curvature of F() sharpens and we move from
the bold curve to the dashed curve. Now the intersection of F() and the line x̂   moves from
point ‘c’ to ‘d.’ Here the equilibrium increases:

 0.

P 
Notice that when =0, point a in Figure 7 and point c in Figure 8 are at x̂   C ,1 .
 2 
When  increases, we need the location of * (either point a or c) to remain in the interval
47
 PC 
,1 and this will be true so long as  is not too large. That is, there is an open interval of

 2 
's, 0,  ,   0 , so that * is neither too large nor too small. 
Proof of Proposition 5: Consider the market segmentation given in Figure 5. Consider the
consumer located at x, ≤x≤1 who has Belief NIC about all other consumers in [1]. Let
customer x customize her product at z, where z is in the interval [, 1], that is ≤ z≤ x.
Following the logic given in the proof of Proposition 3, the utility of this consumer is
2


PC2
 Pc 
1
U  V  x  z  P  PS  PC z 
        2    z  and the marginal utility of
2  2 
4


consumer x with respect to her customized choice of z is
U
 1  PC   . This is by assumption
z
negative and so she will choose z*=χ, so her Belief NIC is rational when   1  PC .
 P 
The above analysis was carried out under the assumption that DIY consumers in 0, C 
 2 
will choose their customized product at their ideal locations. Is this rational given the behavior of
 P 
the co-creators in [, 1]? Consider consumer x in 0, C  who expects all other consumers y in
 2 
this interval to choose the customized product at y. Suppose x chooses her customized product at
z ≤ x. What is her optimal choice of z?
“Expected distance from z to what others choose”=
Pc
2
z
0 (z  y)dy  z

1
2

( y  z)dy  Pc (z  0)dy   (  z)dy
2
1
P 
P
 1  C   2 C    z  z 2  (1  ) .
2  2 
2
 2
The utility of this consumer is
48
(32)
2


1
 PC 
P
1
U  V  x  z  P  z     
  2z C      z 2  (1  ) .
2  2 
2
 2


2
(33)
Note that in (33) since the consumer x is doing DIY she does not incur the setup cost nor does
she have to choose k. The marginal utility with respect to product location z is
P
U
 1  2z  (1  C  2  2z) . This gives the interior solution as
z

~z 
P
1
 
1 
P




. Again, following the logic of Proposition 3, ~z > C is


2(  )   
2 2 
2
 1  PC 
 . If this is true then a consumer x in
equivalent to   1 1 
2
 

 PC 
0, 2  will optimally


choose z*=x. We thus we have shown that it is rational for the DIY consumers to perfectly
customize at the ideal locations if bandwagon intensity is not too high. To summarize, if


2 1 
2
1  PC
 1 then we can have a situation where consumers in

 PC 
0, 2  are DIYers and


consumers in [χ, 1] are non-ideal co-creators.
What determines the threshold * that defines the number of co-creators? After making
appropriate substitutions for z* and k* from Proposition 5 the utility of the consumer x in the cocreation segment [, 1] is
2


P2
P 
Bandwagon
U Custom
 V  x    P  PS  PC   C    1  c    2  .
2  2 
4


Similarly, the utility of consumer x in the standardization segment
Bandwagon
U Std
PC
 x   is
2
2


 PC 
1
 V  x  P    
   2  
2  2 


49
(34)
(35)
The consumer at x   must be indifferent between standardization and non-ideal co-creation
and therefore we can equate (34) and (35) after substituting x   . This gives the following
equation which implicitly defines *:
P P
 P 
2 2  (1  PC  )  C  C   C    PS  0 .
2  2
 2  
(36)
This equation is identical to that analyzed in the proof of Theorem 1, only here >1-PC. * is the
smaller of the two roots. 
50
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