Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1287/isre.1110.0410 | Information Systems Research |
Keywords | Field | DocType |
electronic markets,channel acceptance increase,channel inertia,empirical analysis,channel usage,improved channel allocation,drive channel usage,electronic channel,buyer heterogeneity,channel usage behavior,traditional sales channel,channel choice,new channel,electronic channels,ushering buyers,e-channel adoption decision,information systems | Revenue,Panel data,Information system,Response model,Economics,Consumer behaviour,Microeconomics,Communication channel,Discrete choice,Channel allocation schemes,Marketing | Journal |
Volume | Issue | ISSN |
23 | 4 | 1047-7047 |
Citations | PageRank | References |
7 | 0.48 | 32 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nishtha Langer | 1 | 46 | 4.13 |
| Chris Forman | 2 | 600 | 34.93 |
| Sunder Kekre | 3 | 619 | 62.00 |
| Baohong Sun | 4 | 68 | 13.16 |