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  4. Mobile Decision Support vs. Interpersonal Sales Communication: Predictors of Buying Intentions for Price Bundles
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Mobile Decision Support vs. Interpersonal Sales Communication: Predictors of Buying Intentions for Price Bundles

Type
conference paper
Date Issued
2008-06-15
Author(s)
Maass, Wolfgang
;
Kowatsch, Tobias  
Abstract
Mobile recommendation agents (MRA) are a new class of decision support systems that provide consumers with product information during purchase situations in stores. They allow merging of local information with global information provided by online content sources. Currently design criteria for MRA are missing. Studies on purchase decision support systems indicate the importance of price, single product quality, and attitude on buying intentions. It is assumed that purchase decision tasks on price bundles increase utility effects of MRA. We present an empirical study that investigates the impact of cues on price, bundle quality, and discount provided by MRA on consumer's buying intentions in comparison with interpersonal sales communication between consumer and sales personnel. Our results show that MRA can be used to inform consumers about bundle qualities under best-value strategy conditions, which will be used for future MRA designs
Language
English
Keywords
Mobile decision support systems
product bundling
retailing
HSG Classification
contribution to scientific community
Refereed
Yes
Book title
21st Bled eConference "eCollaboration: Overcoming Boundaries Through Multi-Channel Interaction" Proceedings
Publisher
Bled eCommerce Conference
Start page
25
End page
37
Pages
13
Event Title
21st Bled eConference "eCollaboration: Overcoming Boundaries Through Multi-Channel Interaction"
Event Location
Bled
Event Date
15.-18.06.2008
Official URL
http://aisel.aisnet.org/bled2008/43
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/78206
Subject(s)

business studies

Division(s)

ITEM - Institute of T...

Eprints ID
51329
File(s)
Thumbnail Image
Name

Maass Kowatsch 2008 Mobile Decision Support.pdf

Size

306.99 KB

Format

Adobe PDF

Checksum (MD5)

67ef275e9371168db3dbd4c8aec0946a

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