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ABSTRACT
Online retailers assume that customers expect speedy delivery. To ensure that customers receive at least part of the order sooner, they often split deliveries into smaller quantities, spread out over different dates. Yet split deliveries may increase customers’ hassle costs, such that they have to receive multiple deliveries, as well as their perceptions of environmental harms due to more packaging and transportation. Three experiments and a field study test how delivery speed and split (vs. consolidated) deliveries affect key customer outcomes. In the case of split deliveries, faster delivery does not affect customers’ order completion, satisfaction, and word of mouth (Study 1); only when the deliveries are consolidated does faster delivery enhance them, and then only partially. Split deliveries also negatively affect the three outcomes more powerfully when the deliveries are fast (vs. slow) (Study 2). Study 3 reveals that the effects are mediated by perceived hassle costs and environmental impacts. Study 4, using apparel sales transaction data from a U.S. online retailer, shows that split (vs. consolidated) deliveries decrease the number of repeat purchases. These results carry important theoretical implications, as they show that delivery speed matters only under certain conditions and that rather the delivery mode (split vs. consolidated) may be a key unexplored factor associated with customer hassle costs and environmental concerns. The results are practically relevant because they suggest that retailers should not split deliveries to increase delivery speed; instead, shipments of multi-item orders should be consolidated to make receiving them hassle-free with environmentally friendly delivery in order to achieve positive customer outcomes.
Disclosure Statement
No potential conflict of interest was reported by the authors.
Supplemental Material
Supplemental data for this article can be accessed online at https://doi.org/10.1080/10864415.2022.2123647
Notes
1 Although three days instead of one day might not seem a big difference, this time difference can be important with regard to the construal levels. The temporal distance and corresponding consequences seem to follow a logarithmic rather than linear relationship (e.g., same difference in concreteness between tomorrow and next month compared to next month and next decade [Citation92, Study 2c]). Moreover, while most studies consider tomorrow as near in time, what can be considered as distant in time depends, among other things, on the importance, the organizational scope, and the duration of the respective event. For example, one’s wedding next week will certainly be considered close in time, while a simple delivery next week will seem distant in time.
2 Split deliveries on the same day often happen in reality when products are shipped from different sellers (e.g., sellers using the same marketplace), warehouses, or stores (e.g., in the case of omnichannel fulfillment). In these cases, split deliveries can arrive on the same day at different times, with different courier services or transportation vehicles. We did not specify whether multiple courier services or transportation vehicles are involved, to keep the study setting realistic; online sellers such as Amazon or Target usually do not disclose this information to customers. In addition, we did not restrict or specify the delivery location and left it to participants’ imagination, because the use of certain delivery locations (e.g., parcel stations) is highly location dependent.
3 Purchase frequency (skewness = 4.63) and average return rate (skewness = 4.20) are heavily right skewed, so we applied square root transformations to both variables.
4 Using a boxplot method, in consultation with the online retailer that provided the data, we determine that customers with more than nine orders or who purchased more than 22 products in total represent extreme outliers. Accordingly, we removed 78,686 orders (48,874 multi-item orders) from the original data set (1,415,362 orders). Including these outliers in our analysis does not change the pattern of results.
5 Orders with split deliveries contain more products on average (M = 3.68) than consolidated deliveries (M = 1.92, t(1,336,674) = –264.5, p < .001). This disparity decreases when we include only multi-item orders (Msplit = 3.68, Mconsolidated = 2.75, t(717,159) = –136.09, p < .001).
6 A very small, negative interaction effect of delivery mode and number of prior purchases on repeat purchases, b = –.01, p < .01, disappears in Model 3. The negative interaction means that the negative effect of split deliveries slightly increases with each prior purchase; the finding does not change the nature of results.
7 A very small, negative interaction effect of both control variables appears, b = –.02, p < .001, which might indicate that the relationship between the control variables and the dependent variable is nonlinear.
8 Perceived delivery fulfillment “refers to the degree to which a consumer perceives that a product will be delivered properly and will meet the consumer’s expectations as promised” [Citation51, p. 21].
9 A posttest comparison of Studies 1 and 2 reveals that order completion (t(107) = 2.05, p < .05) and satisfaction (t(107) = 2.06, p < .05) are higher when two separate packages are dispatched together after 3 days versus when one of the two packages is dispatched after just 1 day (and the other after 3 days).
Additional information
Notes on contributors
Daniel Brylla
Daniel Brylla ([email protected]; corresponding author) is a Ph.D. candidate in the Faculty of Economics and Business Administration of Friedrich-Schiller University Jena,Germany. He holds a master’s degree in computer science and has 22 years of industry experience as a designer and programmer in the e-commerce domain. His research has been published in several journals and proceedings such as International Journal of Electronic Commerce, Electronic Markets, International Conference on Information Systems, and European Conference on Information Systems.
Gianfranco Walsh
Gianfranco Walsh ([email protected]) is a professor in the Faculty of Economics and Business Administration of Leibniz University Hannover, Germany. He received his Ph.D. and habilitation degrees from that university. Dr. Walsh’s research revolves around e-commerce and human behavior in services, and has been published in, among others, Academy of Management Journal, British Journal of Management, International Journal of Electronic Commerce, Journal of the Academy of Marketing Science, Journal of Interactive Marketing, and Journal of International Marketing. His work has been funded by the German Research Foundation and Federal Ministry of Education and Research. He serves on the editorial review boards of Journal of Business Research, Journal of Service Research, and others.