Show simple item record

dc.contributor.authorXu, David Jingjun
dc.contributor.authorBenbasat, Izak
dc.contributor.authorCenfetelli, Ronald T.
dc.date.accessioned2014-08-08T21:34:50Z
dc.date.available2014-08-08T21:34:50Z
dc.date.issued2014-06
dc.identifier.citationXu, Jingjun David; Benbasat, Izak; Cenfetelli, Ronald T. 2014. The influences of online service technologies and task complexity on efficiency and personalization. Information Systems Research, vol. 25:no. 2:ppg. 420-436en_US
dc.identifier.issn1047-7047
dc.identifier.otherWOS:000338701400012
dc.identifier.urihttp://dx.doi.org/10.1287/isre.2013.0503
dc.identifier.urihttp://hdl.handle.net/10057/10700
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractOnline retailers are increasingly providing service technologies, such as technology-based and human-based services, to assist customers with their shopping. Despite the prevalence of these service technologies and the scholarly recognition of their importance, surprisingly little empirical research has examined the fundamental differences among them. Consequently, little is known about the factors that may favor the use of one type of service technology over another. In this paper, we propose the Model of Online Service Technologies (MOST) to theorize that the capacity of a service provider to accommodate the variability of customer inputs into the service process is the key difference among various types of service technologies. We posit two types of input variability: Service Provider-Elicited Variability (SPEV), where variability is determined in advance by the service provider; and User-Initiated Variability (UIV), where customers determine variability in the service process. We also theorize about the role of task complexity in changing the effectiveness of service technologies. We then empirically investigate the impact of service technologies that possess different capacities to accommodate input variability on efficiency and personalization, the two competing goals of service adoption. Our empirical approach attempts to capture both the perspective of the vendor who may deploy such technologies, as well as the perspective of customers who might choose among service technology alternatives. Our findings reveal that SPEV technologies (i.e., technologies that can accommodate SPEV) are more efficient, but less personalized, than SPEUIV technologies (i.e., technologies that can accommodate both SPEV and UIV). However, when task complexity is high (vs. low), the superior efficiency of SPEV technologies is less prominent, while both SPEV and SPEUIV technologies have higher personalization. We also find that when given a choice, a majority of customers tend to choose to use both types of technologies. The results of this study further our understanding of the differences in efficiency and personalization experienced by customers when using various types of online service technologies. The results also inform practitioners when and how to implement these technologies in the online shopping environment to improve efficiency and personalization for customers.en_US
dc.language.isoen_USen_US
dc.publisherINFORMSen_US
dc.relation.ispartofseriesInformation Systems Research;v.25:no.2
dc.subjectInput variabilityen_US
dc.subjectOnline service technologiesen_US
dc.subjectSPEV technologiesen_US
dc.subjectSPEUIV technologiesen_US
dc.subjectTask complexityen_US
dc.subjectEfficiencyen_US
dc.subjectPersonalizationen_US
dc.titleThe influences of online service technologies and task complexity on efficiency and personalizationen_US
dc.typeArticleen_US
dc.rights.holderCopyright © 2014, INFORMS


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record