Being at the cutting edge of online shopping: Role of recommendations and discounts on privacy perceptions. (August 2021)
- Record Type:
- Journal Article
- Title:
- Being at the cutting edge of online shopping: Role of recommendations and discounts on privacy perceptions. (August 2021)
- Main Title:
- Being at the cutting edge of online shopping: Role of recommendations and discounts on privacy perceptions
- Authors:
- Venkatesh, Viswanath
Hoehle, Hartmut
Aloysius, John A.
Nikkhah, Hamid Reza - Abstract:
- Abstract: Despite the explosion of selling online, customers continue to have privacy concerns about online purchases. To alleviate such concerns, shopping sites seek to employ interventions to encourage users to buy more online. Two common interventions used to promote online sales are: (1) recommendations that help customers choose the right product either based on historic purchase correlations or recommendations suggested by the retailer; and (2) discounts that increase the value of products. Building on privacy calculus, we theorize about how and why key, representative combinations of recommendations and discounts influence the effects of inhibitors and enablers on online purchase intention. Our research design incorporated recommendations coming from different sources for the recommendation (retailer and other customers' preferences) product relatedness (related products with historic purchases correlated to the focal product and unrelated products with no historic purchase correlation to the focal product) and two types of discounts (regular and bundle). Participants completed a browsing task in a controlled online shopping environment and completed a survey (n = 496). We found mixed results of moderating effects of recommendations and product relatedness on the effect of inhibitors and enablers on purchase intention. Although recommendations did not enhance the effects of inhibitors, they did enhance the effects of enablers on online purchase intention. We alsoAbstract: Despite the explosion of selling online, customers continue to have privacy concerns about online purchases. To alleviate such concerns, shopping sites seek to employ interventions to encourage users to buy more online. Two common interventions used to promote online sales are: (1) recommendations that help customers choose the right product either based on historic purchase correlations or recommendations suggested by the retailer; and (2) discounts that increase the value of products. Building on privacy calculus, we theorize about how and why key, representative combinations of recommendations and discounts influence the effects of inhibitors and enablers on online purchase intention. Our research design incorporated recommendations coming from different sources for the recommendation (retailer and other customers' preferences) product relatedness (related products with historic purchases correlated to the focal product and unrelated products with no historic purchase correlation to the focal product) and two types of discounts (regular and bundle). Participants completed a browsing task in a controlled online shopping environment and completed a survey (n = 496). We found mixed results of moderating effects of recommendations and product relatedness on the effect of inhibitors and enablers on purchase intention. Although recommendations did not enhance the effects of inhibitors, they did enhance the effects of enablers on online purchase intention. We also found that product relatedness did not enhance the effect of privacy enablers on online purchase intentions. The results also showed that discounts enhance the effects of enablers, and that discounts can counteract the moderating effect of recommendations on the relationship between inhibitors and purchase intention under certain circumstances. We discuss theoretical and practical implications. Highlights: Impact of recommendations on customer perceptions in retail sites. Impact of discounts on customer perceptions in retail sites. Recommendations, discounts, privacy and customer outcomes. … (more)
- Is Part Of:
- Computers in human behavior. Volume 121(2021)
- Journal:
- Computers in human behavior
- Issue:
- Volume 121(2021)
- Issue Display:
- Volume 121, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 121
- Issue:
- 2021
- Issue Sort Value:
- 2021-0121-2021-0000
- Page Start:
- Page End:
- Publication Date:
- 2021-08
- Subjects:
- Recommendation systems -- Recommendation agents -- Discounts -- Privacy calculus -- Privacy paradox
Interactive computer systems -- Periodicals
Man-machine systems -- Periodicals
004.019 - Journal URLs:
- http://www.sciencedirect.com/science/journal/07475632 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.chb.2021.106785 ↗
- Languages:
- English
- ISSNs:
- 0747-5632
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.921600
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25493.xml