Elsevier

Computers in Human Behavior

Volume 28, Issue 6, November 2012, Pages 2055-2066
Computers in Human Behavior

Virtual agents in retail web sites: Benefits of simulated social interaction for older users

https://doi.org/10.1016/j.chb.2012.06.009Get rights and content

Abstract

This study investigates the benefits of simulated social interaction (social presence) through virtual agents for older users’ experience in retail Web sites, particularly with respect to age-related barriers to the adoption of online retailing. In Study 1, through four focus group interviews, we identified six social–psychological barriers to the adoption of online shopping among older users (mean age of 73 years). These included barriers relating to perceived risks, trust, social support, familiarity, experience, and search. In Study 2, a laboratory experiment with older users (mean age of 69 years) demonstrated that embedding a virtual agent that serves search and navigational/procedural support functions in the online store leads to increased perceived social support, trust, and patronage intention for the online store. Mediational analyses further revealed that the effect of virtual agents: (1) on trust is mediated by perceived social support; and (2) on patronage intentions is mediated in part by trust and perceived risks. The study provides important implications on the design of virtual agents for older users of e-commerce applications, and on building online trust and e-service patronage through virtual agents.

Highlights

► We investigated virtual agent benefits for older users’ experience in e-commerce. ► Focus group interviews revealed six barriers to online shopping adoption. ► Key barriers include perceived risks, and lack of trust and social support. ► Laboratory experiment tested the effects of virtual agents on key barriers. ► Virtual agents led to increased social support, trust, and patronage intent.

Introduction

Virtual agents, representing animated embodiments that respond to users through verbal and non-verbal communication (Cassell, Sullivan, Prevost, & Churchill, 2000), have been increasingly implemented on various online retail and service Web sites in recent years. For example, Ikea.com, a Swedish furniture and home goods retailer, features an automated virtual assistant named Anna who dons the company uniform and answers customer queries on Ikea’s products and services. Similarly, Alaska Airlines features Jenn, a virtual assistant who dons the company uniform and answers questions about airline reservations. Virtual agents on e-commerce and online retail Web sites most often serve a search support function by presenting product and service information based on user specified criteria. A few virtual agents serve a basic decision support function where they compare alternatives to assist the buyer with a choice decision (Sproule & Archer, 2000). However, an important aspect missed by online retail agent implementations is the navigational/procedural support function.

Navigational and procedural support in e-commerce interfaces, defined as assisting the buyer through the online transaction process, is important to low experience users and those who experience continuing challenges in online tasks despite repetitive usage, such as older users. Recent national surveys on Internet use continue to indicate the existence of an age-based digital divide. In 2011, 41% of adults aged 65 and over were Internet users, as compared to 74% of those aged 50–64, 87% of those aged 30–49, and 94% of those aged 18–29 (Pew Internet, 2011). These distinctions become greater when comparing the use of the Internet for specific functions such as searching product information and purchasing products online, ranked as the top 4–6 online activities performed by the American population as a whole (Pew Internet, 2009). Findings from the Pew Survey from September 2007 revealed that only 23% of Internet users 50–64 years old and 6% of Internet users 65 years old and older, have ever made an online purchase (Horrigan, 2008). This report revealed that attitudes towards online shopping do differ by age and that consumers over 50 years of age perceive the online shopping process to be more complicated, time-consuming, and less convenient than those under the age of 50, which may be an important deterrent to their adoption of online shopping (Horrigan, 2008). Due to the complexity of the online purchasing process, older users face barriers in adopting online shopping although access to goods and services online becomes critical as out-of-home mobility declines with age (McMellon & Schiffman, 2000).

This paper presents two studies. Study 1 inductively investigates and explains current barriers to the adoption of online shopping among the older population, and Study 2 puts forth a novel approach to address these barriers through the evaluation of a virtual agent serving both search and navigational/procedural support on a retail interface. In spite of the growing evidence documenting the merits of virtual agents in e-learning environments, there is a lack of research on how virtual agents can benefit older users and increase their adoption of specific e-commerce applications such as retail Web sites. This study proposes and tests a conceptual model that delineates the effects of virtual agents in an online store on the main barriers to online shopping among older users.

Section snippets

Study 1

In Study 1, focus group interviews (FGIs) were employed in answering the research question “What factors inhibit the adoption of online shopping among older users?”

Study 2

The goal of Study 2 was to test whether virtual agents in an online retail interface can address barriers identified through Study 1. Specifically, the scope of Study 2 is limited to the first three barriers (perceived risks, trust, and social support) that are conceptually related. The main thesis of Study 2 is that (1) social presence through virtual agents in an online store will enhance older users’ perceptions of social support from the online store; (2) this enhanced perceived social

Discussion

The two-phased approach employed in Studies 1 and 2 allowed for the systematic investigation of factors that influenced older users’ adoption of online shopping, using both inductive qualitative and deductive quantitative methods. Through FGIs, Study 1 revealed six main barriers to online shopping adoption among older users, which were further differentiated into specific dimensions. The broad categories included perceived risk barriers, trust barriers, social support barriers, familiarity

Implications

Employing a combination of inductive and deductive approaches, this study helps to create an in-depth understanding of the problems older users face in adopting online shopping, and how virtual agents in retail Web sites can benefit older users by alleviating some of the barriers experienced. This study examines the theory behind a new model for trust building and online retail patronage among older users, by specifying the perceived social support-trust-perceived risk linkage that enhances

Acknowledgments

This material is based in part upon work supported by the National Science Foundation under Grant Number IIS-0955763. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.

References (76)

  • R.E. Hostler et al.

    Assessing the impact of internet agent on end users’ performance

    Decision Support Systems

    (2005)
  • S.A.A. Jin

    The effects of incorporating a virtual agent in a computer-aided test designed for stress management education: The mediating role of enjoyment

    Computers in Human Behavior

    (2010)
  • J. Kim et al.

    Influences of online store perception, shopping enjoyment, and shopping involvement on consumer patronage behavior towards an online retailer

    Journal of Retailing and Consumer Services

    (2007)
  • H.H. Kuan et al.

    Trust transference in brick and click retailers: An investigation of the before-online-visit phase

    Information & Management

    (2007)
  • C. Liu et al.

    Beyond concern – A privacy-trust-behavioral intention model of electronic commerce

    Information & Management

    (2005)
  • J. Mumm et al.

    Designing motivational agents: The role of praise, social comparison, and embodiment in computer feedback

    Computers in Human Behavior

    (2011)
  • A.M. von der Pütten et al.

    “It doesn’t matter what you are!” Explaining social effects of agents and avatars

    Computers in Human Behavior

    (2010)
  • N. Adams et al.

    Psychological barriers to Internet usage among older adults in the UK

    Informatics for Health and Social Care

    (2005)
  • A.L. Baylor

    Intelligent agents as cognitive tools for education

    Educational Technology

    (1999)
  • A. Bhatnagar et al.

    On risk, convenience, and Internet shopping behavior

    Communications of the ACM

    (2000)
  • Campbell, R.J., & Wabby, J. (2003). The elderly and the Internet: A case study. The Internet Journal of Health, 3(1)....
  • J. Cassell et al.

    External manifestations of trustworthiness in the interface

    Communications of the ACM

    (2000)
  • J. Cassell et al.

    Embodied conversational agents

    (2000)
  • N. Charness et al.

    Word-processing training and retraining: Effects of adult age, experience, and interface

    Psychology and Aging

    (2001)
  • D.F. Cox et al.

    Perceived risk and consumer decision-making – The case of the telephone shopping

    Journal of Marketing Research (JMR)

    (1964)
  • S. Czaja et al.

    The impact of aging on access to technology

    Universal Access in the Information Society

    (2007)
  • S. Dash et al.

    The role of consumer self-efficacy and website social-presence in customers’ adoption of B2C online shopping

    Journal of International Consumer Marketing

    (2008)
  • P.M. Doney et al.

    An examination of the nature of trust in buyer–seller relationships

    Journal of Marketing

    (1997)
  • B. Doolin et al.

    Perceived risk, the Internet shopping experience and online purchasing behavior: A New Zealand perspective

    Journal of Global Information Management

    (2005)
  • J.K. Eastman et al.

    The elderly’s uses and attitudes towards the Internet

    Journal of Consumer Marketing

    (2004)
  • A.D. Fisk et al.

    Designing for older adults: Principles and creative human factors approaches

    (2004)
  • S. Ganesan

    Determinants of long-term orientation in buyer–seller relationships

    Journal of Marketing

    (1994)
  • D. Gefen et al.

    Managing user trust in B2C e-services

    E-Service Journal

    (2003)
  • J. Gilbert et al.

    Arthur: A personalized instructional system

    Journal of Computing in Higher Education

    (2002)
  • B.G. Glaser

    Basics of grounded theory analysis: Emergence vs forcing

    (1992)
  • B.G. Glaser et al.

    The discovery of grounded theory: Strategies for qualitative research

    (1967)
  • C. Goulding

    Grounded theory methodology and consumer behaviour, procedures, practice and pitfalls

    Advances in Consumer Research

    (2000)
  • S. Harridge-March

    Can the building of trust overcome consumer perceived risk online?

    Marketing Intelligence & Planning

    (2006)
  • Cited by (0)

    View full text