Author List: Langer, Nishtha; Forman, Chris; Kekre, Sunder; Sun, Baohong;
Information Systems Research, 2012, Volume 23, Issue 4, Page 1212-1231.
Despite many success stories, B2B e-commerce penetration remains low. Many firms introduce electronic channels in addition to their traditional sales channels but find that buyer usage of the e-channel over time does not keep up with initial expectations. Firms must understand the underlying factors that drive channel usage and how these factors change over time and across buyers. Using panel data pertaining to the purchase histories of 683 buyers over a 43-month period, we estimate a dynamic discrete choice model in a B2B setting that (i) recognizes how price, channel inertia, and inventory change over time; (ii) allows buyers to dynamically trade off these factors when making e-channel adoption decisions; and (iii) takes into account buyer heterogeneity. We find that channel usage is both heterogeneous and dynamic across buyers. Our findings reveal the dynamic tradeoff between channel inertia and the adverse price effect, which interact in opposing directions as the e-channel grows more popular over time: price increases resulting from more bids deter buyers, whereas channel inertia built from sampling experience helps retain repeat buyers for the new channel. Second, we find that the buyers' size and diversity influence purchase decisions, and the e-channel appears more attractive to small and/or diversified buyers. Based on our analysis, we postulate that the seller's allocation decisions of products across channels, if not aligned with buyer behavior, can alienate some buyers. Based on the parameter estimates from the buyer response model, we propose an improved channel allocation that enables firms to selectively attract more buyers to the e-channel and improve revenues. Channel acceptance increases as a result of smart allocation when firms understand and account for individual buyers' channel usage behavior.
Keywords: buyer heterogeneity; channel choice; electronic markets
Algorithm:

List of Topics

#62 0.202 price buyers sellers pricing market prices seller offer goods profits buyer two-sided preferences purchase intermediary traditional marketplace decisions intermediaries selling
#23 0.189 channel distribution demand channels sales products long travel tail new multichannel available product implications strategy allows internet revenue technologies times
#168 0.135 firms firm financial services firm's size examine new based result level including results industry important account does suggests characterize limited
#153 0.103 usage use self-efficacy social factors individual findings influence organizations beliefs individuals support anxiety technology workplace key outcome behavior contextual longitudinal
#128 0.090 dynamic time dynamics model change study data process different changes using longitudinal understanding decisions develop temporal reveal associated state identifies
#91 0.088 auctions auction bidding bidders bid combinatorial bids online bidder strategies sequential prices design price using outcomes behavior theoretical computational efficiency
#101 0.080 edi electronic data interchange b2b exchange exchanges interorganizational partners adoption transaction trading supplier factors business suppliers impact network commerce efficiency
#136 0.071 expectations expectation music disconfirmation sales analysis vector experiences modeling response polynomial surface discuss panel new nonlinear period understand paper dissonance