Search Cost/ Vendor Management by HC111211164657

VIEWS: 0 PAGES: 58

									 Search Cost/ Vendor
    Management
        By Johnny Lee
Department of Accounting and
    Information Systems
     University of Utah
                               1
 Why is Search Cost important?
1. Customer Attraction cost
2. Revenue generated by attracted customers
3. Profit= Revenue-cost




                                              2
                       Agenda
1.   Reducing Buyer Search Costs: Implications for
     Electronic Marketplaces (Bakos 1997)
2.   Comment on Bakos 1997 (Harrington 2001)
3.   An information Search cost Perspective for Designing
     Interface for Electronic Commerce (Hoque & Lohse
     1999)
4.   Measuring Switching Costs and the Determinants of
     Customer Retention in Internet-enabled Business: A
     study of the Online Brokerage Industry (Chen & Hitt
     2002)

                                                            3
   Reducing Buyer Search Costs:
      Implications for Electronic
            Marketplaces
• Bakos 1997
• Gap:
  – How might the “lowered” search cost in
    Electronic Market impact buyer and seller’s
    behaviors?
  – Non transaction cost perspective.



                                                  4
         Research Question:
• How do buyers trade between search cost
  and fit cost ?
• How do search cost impact buyer’s decision
  in a market place?
• How do different search cost structure
  impact the incentive of market provider?


                                               5
            Market Function
1. Commodity market:
  1. Existence of seller
  2. Price
2. Differentiated market:
  1. Product Characteristics
  2. Price


                               6
         Commodity Market
• Lower search cost
  – Electronic market place  move market toward
    Walresian auctioneer (Fully Informed)
  – Sway the market to Buyer’s market
  – Wipe out abnormal return for sellers Seller
    might try to delay the introduction of E-market



                                                  7
       Differentiated Markets
• Different products for Different buyers’
  demand
• Standardized rating system  Compare
  different products
• Buyers face an optimization problem.



                                             8
         Buyer Choice Model
• Spatial differentiation models: (Chamberlin
  1993)
  – Fit cost: the distance from buyers preference to
    product attributes.
  – Ex.: Red car vs. Orange car
     • Fit cost= U(Red)-U(Orange)




                                                       9
         Model: Search Cost
• Differentiated market
• Unit circle (pp.1679):
  – Products are offered along this circle
  – Buyers pay search cost to find location and
    price of product by seller
  – Buyers make decision on Buying or keep
    searching

                                                  10
          Model: Search Cost
• Unit circle (cont..):
   – Fit cost: Distance between buyers preference
     and actual product bought
• Electronic market provide low-cost search
  (search time)  Reduce fit cost Higher
  utility


                                                    11
                   Model 1
• Buyer:
  – Risk neutral
  – Identical demand subject to r (reservation utility
    )
  – Enter the market when expected Total Cost
    (TC) <= r



                                                     12
                     Model 1
•   Seller move first: decide where to locate product
•   Number of sellers=m
•   c= buyer search cost (constant)
•   f= buyers’ prior distribution for sellers prices
•   Assumption: search with replacement
•   Expect to have Perfect Bayesian Equilibria: satisfy
    the rational expectations constraint that f is the
    actual distribution of seller prices
                                                      13
                   Model 1
• If search cost (c)=0
  p*=t/2m
  t= the degree of differentiation
• If c<>0 and m>>0
  P* depends on t and c
Equilibrium: seller charge p*

                    p  ct
                      *



                                     14
                     Model 1
• Buyer’s reservation price
         R  p *  ct  2 ct

• Expected fit cost
       exp(fit cost)  3 ct
                       2

• Utility at price    ct
         r  2 ct

                               15
Electronic Market Prevent
   Market Breakdown




                            16
 Electronic Market Benefit Buyer

              p  ct
                *




• Promote price competition
• Reduce the market power of sellers

                                       17
         Investment Incentives
• To maximize total social surplus
• Invest X* that

           Min( x  n c( x)t )
             dc( x)    2 c( x)
                    
              dx        n t
                    Solve for x

                                     18
         Investment Incentives
• Seller: can expect to capture a certain proportion 
  of buyers’ efficiency gain

          dc( x)      2 c( x)
                 
           dx       (2  1)n t
    1 Convex: seller invests in socially optimal level
    1 Convex: seller will under-invest
   0.5 Convex: seller will resist
                                                           19
         Investment Incentives
• When convex, buyers will over-invest due to rent
  redistribution at the expense of sellers

             dc( x)    c( x)
                    
              dx       n t




                                                     20
         Investment Incentives
• Intermediary: can capture a certain proportion 
  of buyers’ efficiency gain


        min( x  2   n  c( x)t )
   0.5 Over invest
   0.5 Same a social optimal
   0.5 Under invest
                                                     21
Separating Search Cost for Price
          and Product
• c1 =cost to visit seller s
• c2 =cost to acquire price information from
  seller s
• c3 =cost to acquire product information
  from seller s



                                               22
                  Markets
• Market with low cost of Price information

               p  mc 2
                  *       1
                          2

• Market with low cost of Product information

            p  ( r  c3 )
              *       1
                      2
                                              23
              Contribution
• Formally establish search cost model for
  different type of markets
• Introduce the concept of investment
  incentive




                                             24
            Future Research
• Differences in buyers’ ability to obtain
  information on the web
• Distribution of the payoffs generated by e-
  market among Buyers, Sellers,
  intermediaries.
• Expansion of the separating model
• Multiperiod model

                                                25
       Comment on Bakos 1997
• Harrington 2001
• Research Question:
  – How valid the results found on Bakos 1997
    when separating search cost for price and
    product are?




                                                26
                Bakos 1997
• Result 1: When cost of product information
  is positive and cost of price is close to zero.
  The market is close to a perfectly
  competitive market. The equilibrium price
  is close to marginal cost




                                                    27
               Bakos 1997
• Result 2: When cost of price information is
  positive and cost of product is zero. The
  equilibrium price is decreasing with the cost
  of price information.




                                              28
        Validation of Results
• Result 1 is WRONG
• Result 2 is based on an unreasonable
  implicit assumption
 The analysis regarding the separation of
  search cost for price and product
  information is flawed


                                             29
                     Result 1
• The buyer’s utility from the entire searching
  processes is bounded above by
           r  p  td  c2  c3  0
                 *     *

   d*= the maxima distance(d) the customer will search until the
   distance between his/her location and a seller’s product is
   smaller or equal than d*.
   There is no Symmetric pure-strategy equilibrium in which
   buyer’s search
   Whether an equilibrium with searching exists remains an open
   question
                                                          30
                   Result 2
• The result from Bakos 1997 is only valid
  when   1
•Imply that if buyer search but does not buy then
the search cost will be refunded




                                                    31
      Conclusion/Contribution
The analysis regarding the separation of
 search cost for price and product
 information is invalid




                                           32
An information Search cost Perspective
        for Designing Interface for
           Electronic Commerce
• Hoque & Lohse 1999
• Gap:
  – How to implement prior knowledge on user
    interface design on Web Site design?
  – Does prior knowledge on user interface design
    still hold on Internet world?



                                                    33
   Consumer information search
• Research Question:
   How does subtle changes in the user interface design
     influence information search costs?
   – Reducing price information search cost  price
     sensitive (Alba et al 1997)
   – Design of on-line stores can alter information search
     costs(Ariely 1998)
• How do web developer build the user interface by
  applying the knowledge on information search
  cost?

                                                             34
               Hypothesis
• Serial position
• H1: Consumers using electronic directories
  will be more likely to choose to patronize a
  business near the beginning of the
  electronic listing than will consumers using
  traditional paper directories.


                                                 35
               Hypothesis
• Travel distance
• H2: Consumers using electronic directories
  will be more likely to choose to patronize a
  business nearby than will consumers using
  traditional paper directories.



                                                 36
               Hypothesis
• Display advertisements
• H3: Consumers using electronic directories
  will be less likely to choose a business with
  a display advertisement than will consumers
  using traditional paper directories.



                                              37
           Experimental design
•    1*3 design
•    Three versions of yellow pages
    1. Paper version
    2. GIF version (HTML version of #1)
    3. Hyperlink version
       present an alphabetical listing of businesses
       with hyperlink to ads.

                                                       38
     Experimental Procedures
1. Read instructions
2. Given a goal
3. Using yellow pages to decide which
   business
4. Repeat 2-3 for different headings
5. Questions on yellow page usage and
   business they typically patronize
                                        39
                  Subjects
• N=177
• Cell size
  – Paper:       54 (42% male)
  – Computer     123(70% male)
     • GIF:       61
     • Hyperlink: 62




                                 40
Summary Statistics




                     41
Result




         42
            Hypothesis test
• H1: Accepted
• H2: Accepted
• H3: Accepted
  – Ads on paper + effect on choice
  – Ads on Computer - effect on choice




                                          43
 Discussion and Implementation
• Expand the understanding on human-
  computer interface time parameters
• The more you require users to do, the less
  likely they are buying
• Display ads on electronic world has less
  impact than does in paper yellow pages.
  – Due to long download time
  – Is this still true?

                                               44
     Measuring Switching Costs and the
     Determinants of Customer Retention in
    Internet-enabled Business: A study of the
            Online Brokerage Industry
• Chen and Hitt 2002
• Gap:
  – Lacking of systems that can measure switching
    cost
  – Lack of systems that can measure Customer
    Retention


                                                    45
          Research question:
• How should the magnitudes of switching
  cost and brand loyalty for online service
  providers be measured?
• How system usage, service design, and
  other firms and individual factors affect
  switching and retention


                                              46
             Switching Cost
• Heavy investment to attract customers
• Lock-in customers
• Switching cost:
  – Transaction cost
  – Learning cost
  – Artificial or Contractual costs


                                          47
    Switching cost in E-market
• Higher/Lower than traditional market?
• Friedman 1999: lower switching cost
• Brenjolfsson&Smith 2000: Consumers are
  willing to pay higher price from familiar
  seller
• ?????


                                              48
               Hypothesis
• H1: There are no significant differences in
  measuring switching costs across firms.
• H2: There are no significant differences in
  measuring switching costs across firms after
  controlling for customer characteristics.



                                             49
               Hypothesis
• H3A: Use of multiple brokers is positively
  correlated with switching
• H3B: Changing in usage patterns is
  positively correlated with switching
• H3C: High volume of Web site usage is
  negatively correlated with switching


                                               50
                    Hypothesis
• H4A:Switching is negatively correlated with Web site
  personalization
• H4B: Switching is positively correlated with Web site ease
  of use
• H4C: Switching is negatively correlated with Web site
  quality
• H4D: Switching is negatively correlated with breadth of
  offering
• H4E: Switching is not correlated to cost (not testable but
  posited that coefficient should be indistinguishable from
  zero)
                                                           51
               Hypothesis
H5A: Use of multiple brokers is negatively
 correlated with attrition
H5B: High volume of Web site usage is
 negatively correlated with attrition




                                             52
                  Hypothesis
• H6A: Customer attrition is negatively correlated
  with Web personalization
• H6B: Customer attrition is negatively correlated
  with Web site quality
• H6C: Customer attrition is negatively correlated
  with breadth of offerings
• H6D: Customer attrition is negatively correlated
  with Web site ease of use
• H6E: Customer attrition is not correlated to cost
• H6F: Customer attrition is negatively correlated
  with account minimums

                                                      53
                     Method
• Switching cost: Random utility model
                                    M
  u   j  x j   rj  z  j   skW  
   i
   j
                             i
                                          k
                                           i   i
                                               j
                                   k 1

  i  1,2,...,N ,  j  1,2,...,M 
    firm - specified effect
    Custumer perference     s
  s  Switching costs
  r  Price index
                                                   54
                       Method
• Drivers of switching and attrition

          Pr( Attrit )
    log                    a   a x j   a rj  a z i   ij
        1  Pr( Attrit )
                             j



    firm - specified effect
    Custumer perference   s
   s  Switching costs
   r  Price index
                                                              55
Result




         56
              Contribution
• Utilize Web site traffic data to measure
  switching cost
• How system design variables as well as
  other customer and firm-specific
  characteristics affect switching, adoption,
  and attrition
• Applicable in the on-line brokerage context

                                                57
     Thanks!!

Question and comments




                        58

								
To top