Strategic waiting in cross-border e-commerce when there exists future disruption in direct-shipping channel
Posted: 24 Oct 2019 Last revised: 27 Apr 2020
Date Written: October 15, 2019
The burgeoning business of cross-border e-commerce has brought about new opportunities as well as new challenges. For example, decision makers have to be frequently confronted with extreme weather events such as typhoon, which has become a major threat to the direct-shipping channel. Fortunately, weather service agencies start to alert the public of an incoming weather event and forecast the impact way before it makes landfall. It is thus a critical decision whether to respond to the forecast: The typhoon might eventually have no impact because of sudden recurvature. In this paper, we study a cross-border e-tailer (he) who operates two sales channels: a bonded-warehouse channel and a direct-shipping channel. In light of an extreme weather event that potentially disrupts the direct-shipping channel, the e-tailer can be risk averse by observing the forecast and balancing demand in two channels. Alternatively, he can disregard the forecast. We show that, if the e-tailer has a relatively small or a large market potential in the direct-shipping channel, he should always be serious by observing weather forecast and responding accordingly. Otherwise, he is suggested to disregard the forecast and not respond. We identify three important effects that contribute to the e-tailer’s decisions, namely, unit-cost effect, channel-cooperation effect, and marginal-profit effect. That is, under responding strategy, when the market potential in the direct-shipping channel increases, the overseas supplier’s wholesale prices will increase more quickly (referred to as “unit-cost effect”), the channel cooperation via demand reallocation will be strengthened (referred to as “channel-cooperation effect”), and the e-tailer’s marginal profit will increase more slowly (referred to as “marginal-profit effect”). We also study the impact of the e-tailer’s promised delivery time and channel substitutability to check the robustness of the main findings.
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