Cited by 1,898Technology Adoption and User BehaviourCustomer Service Quality and LoyaltyHealth, Technology, Consumer Behavior

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An Attitudinal Model of Technology-Based Self-Service: Moderating Effects of Consumer Traits and Situational Factors

Dabholkar, P. A., Bagozzi, R. P.·2002·Journal of the Academy of Marketing Science

DOI 10.1177/0092070302303001

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The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations
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“As discussed above, scholars in IS research [23, 85, 88, 89] and media usage [21, 62] have investigated antecedents to technology and media use.”
Background
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Liu, C., & Forsythe, S. M. (2010) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2010.10.004 · Cited by 89
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“…& Diemen, 2011; Lin & Chang, 2011; Meuter, Bitner, Ostrom, & Brown, 2005), demographics (Dean, 2008; Lee, Cho, Xu, & Fairhurst, 2010), and technology characteristics (Meuter et al., 2005) to situational influences (Dabholkar & Bagozzi, 2002; Simon & Usunier, 2007; Wang, Harris, & Patterson, 2012).”
Self-service technology kiosk design for restaurants: An QFD application
Park, S., Lehto, X. Y., & Lehto, M. R. (2020) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2020.102757 · Cited by 94
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“PE, not originally being part of the TAM, was added to the model later on due to the need to consider the hedonic aspects of using a technology [20].”
Background
Contactless service encounters among Millennials and Generation Z: the effects of Millennials and Gen Z characteristics on technology self-efficacy and preference for contactless service
Kim, S., Jang, S., Choi, W., Youn, C., & Lee, Y. (2021) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-01-2021-0020 · Cited by 110
Faculty's acceptance of computer based technology: Cross-validation of an extended model
Ahmad, T. B. T., Madarsha, K. B., Zainuddin, A. M. H., Ismail, N. A. H., & Nordin, M. S. (2010) · Australasian Journal of Educational Technology · doi:10.14742/ajet.1095 · Cited by 88
Web site satisfaction and purchase intentions
Ranaweera, C., Bansal, H. S., & McDougall, G. H. G. (2008) · Managing Service Quality · doi:10.1108/09604520810885590 · Cited by 86
Effects of customer experience across service types, customer types and time
Roy, S. (2018) · Journal of Services Marketing · doi:10.1108/jsm-11-2016-0406 · Cited by 85
“In this case, a more rigorous approach to test for similarity across the two groups as suggested by Dabholkar and Bagozzi (2002) based on Joreskog and Sorbom (1993) was adopted.”
Method
Making the Wait Worthwhile: Experiments on the Effect of Queueing on Consumption
Ülkü, S., Hydock, C., & Cui, S. (2020) · Management Sciences · doi:10.1287/mnsc.2018.3277 · Cited by 64
“…as well as psychological costs such as boredom, frustration, and anxiety (Maister 1984, Larson 1987); it results in unpleasant negative emotions and cognitions (Maister 1984, Larson 1987, Taylor 1994, Carmon and Kahneman 1995, Hui and Tse 1996, Brady and Cronin 2001, Dabholkar and Bagozzi 2002).”
Background
Online anthropomorphism and consumers’ privacy concern: Moderating roles of need for interaction and social exclusion
Xie, Y., Chen, K., & Guo, X. (2020) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2020.102119 · Cited by 86
Untact: Customer’s Acceptance Intention toward Robot Barista in Coffee Shop
Sung, H. J., & Jeon, H.-M. (2020) · Sustainability · doi:10.3390/su12208598 · Cited by 84
“It must also be noted that human interaction is absent during the usage of a self-service technology (SST), and yet, this human interaction contributes to the understanding of the dynamics of service provision through SST [17].”
BackgroundInfluential
Self‐service with a smile?
Pujari, D. (2004) · International Journal of Service Industry Management · doi:10.1108/09564230410532510 · Cited by 86
Mobile advertising avoidance: exploring the role of ubiquity
Okazaki, S., Molina‐Castillo, F., & Hirose, M. (2012) · Electronic Markets · doi:10.1007/s12525-012-0087-1 · Cited by 84
Understanding the differences of public and private self-service technology
Collier, J. E., Sherrell, D. L., Babakus, E., & Horky, A. B. (2014) · Journal of Services Marketing · doi:10.1108/jsm-04-2012-0071 · Cited by 84
Are Self‐Service Customers Satisfied or Stuck?
Buell, R. W., Campbell, D., & Frei, F. X. (2010) · Production and Operations Management · doi:10.1111/j.1937-5956.2010.01151.x · Cited by 84
Acceptance of Mobile Mental Health Treatment Applications
Becker, D. (2016) · Procedia Computer Science · doi:10.1016/j.procs.2016.09.036 · Cited by 85
“The concept of ease of use is measured with 5 items and the questions are adapted from the original TAM 34 and further reﬁnements were taken from a study by Bagozzi and Richard (2002) 35 .”
Method
Extent and impact of response biases in cross-national survey research
Tellis, G. J., & Chandrasekaran, D. (2010) · International Journal of Research in Marketing · doi:10.1016/j.ijresmar.2010.08.003 · Cited by 83
The Influence of Technology Readiness on the Evaluation of Self-Service Technology Attributes and Resulting Attitude Toward Technology Usage
Elliott, K. M., Meng, G., & Hall, M. (2012) · Services Marketing Quarterly · doi:10.1080/15332969.2012.715049 · Cited by 82
Improving consumer commitment through the integration of self-service technologies: A transcendent consumer experience perspective
Wei, W., Torres, E. N., & Hua, N. (2016) · International Journal of Hospitality Management · doi:10.1016/j.ijhm.2016.09.004 · Cited by 82
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“Research suggests that some aspects of innovativeness influence attitudes towards technological products (Dabholkar & Bagozzi, 2002).”
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Corporate social performance and consumer‐retailer emotional attachment
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Determinants of perceived usefulness and perceived ease of use in the technology acceptance model: senior consumers' adoption of self-service banking technologies
Rose, J., & Fogarty, G. J. (2006) · University of Southern Queensland ePrints (University of Southern Queensland) · Cited by 81
Deploying Self-Service Technology in Luxury Hotel Brands: Perceptions of Business Travelers
Küçükusta, D., Heung, V. C. S., & Hui, S. S.-K. (2014) · Journal of Travel & Tourism Marketing · doi:10.1080/10548408.2014.861707 · Cited by 81
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Negative online reviews and webcare strategies in social media: effects on hotel attitude and booking intentions
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“Manipulation checks for valence of reviews, scenario realism and managerial responses were measured using 7-point scales as proposed by Dabholkar and Bagozzi (2002) and Lee and Cranage (2014).”
Method
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“Advancing this theme, and already using a chatbot, Ashfaq et al. (2020) appropriated the studies of Langeard et al. (1981), Dabholkar (1996),) and Dabholkar and Bagozzi (2002) and brought the perspective that NFI-SE would be able to moderate ease of use, perceived usefulness and perceived pleasure.”
Method
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Key influencers and inhibitors on adoption of the Internet for banking
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Designing mobile business applications for different age groups
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The Aha! Experience: Insight and Discontinuous Learning in Product Usage
Lakshmanan, A., & Krishnan, H. S. (2011) · Journal of Marketing · doi:10.1509/jm.10.0348 · Cited by 80
“I like it, but I don't use it”: Impact of carsharing business models on usage intentions in the sharing economy
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“Carsharing attitude, one of the dependent variables, was captured by the survey using a 7-point sematic differential scale (Dabholkar & Bagozzi, 2002; Reinders, Dabholkar, & Frambach, 2008; see Appendix A).”
Method
Improving service brand personality with augmented reality marketing
Plotkina, D., Dinsmore, J. B., & Racat, M. (2021) · Journal of Services Marketing · doi:10.1108/jsm-12-2020-0519 · Cited by 89
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Attracting Shoppers to Shop Online—Challenges and Opportunities for the Indian Retail Sector
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Understanding Markets as Online Public Places: Insights from Consumers with Visual Impairments
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The Effect of Airport Self-Service Characteristics on Passengers’ Perceived Value, Satisfaction, and Behavioral Intention: Based on the SOR Model
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“[51], Delroy and Mark [52], Schunk [47], Gist and Mitchell [48], Huebner [53], Gardner and Pierce [54], Dabholkar and Bagizzi [55], Shamdasani et al.”
BackgroundInfluential
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“Measurement items for the perceived performance, which included efficiency, ease of use, reliability, convenience, and control, were developed with four items each based on existing studies (e.g., Dabholkar [21]; Dabholkar and Bagozzi [53]; Yen [54]).”
Background
Factors influencing the adoption of sharing economy in B2B context in China: Findings from PLS-SEM and fsQCA
Chuah, S. H., Tseng, M., Wu, K., & Cheng, C.-F. (2021) · Resources Conservation and Recycling · doi:10.1016/j.resconrec.2021.105892 · Cited by 79
“Finally, adoption intention was measured using a 2-item 7-point semantic differential scale, with the words ‘unlikely/likely’ and ‘impossible/possible’ offered alongside each statement (Dabholkar and Bagozzi, 2002).”
Method
The moderating role of technology readiness, gender, and sex in consumer acceptance and actual use of Technology-based services
Tsourela, M., & Roumeliotis, Μ. (2015) · The Journal of High Technology Management Research · doi:10.1016/j.hitech.2015.09.003 · Cited by 85
The Effects of Perceived Fairness on Customer Responses to Retailer SST Push Policies
White, A., Breazeale, M. J., & Collier, J. E. (2012) · Journal of Retailing · doi:10.1016/j.jretai.2012.01.005 · Cited by 83
Effectiveness of corporate employment web sites
van Birgelen, M., Wetzels, M. G. M., & van Dolen, W. (2008) · International Journal of Manpower · doi:10.1108/01437720810919323 · Cited by 76
Exploring the Use of the Abbreviated Technology Readiness Index for Hotel Customer Segmentation
Victorino, L., Karniouchina, E. V., & Verma, R. (2009) · Cornell Hospitality Quarterly · doi:10.1177/1938965509336809 · Cited by 76
Investigating consumer acceptance of autonomous technologies: the case of self-driving automobiles
Baccarella, C. V., Wagner, T. F., Scheiner, C. W., Maier, L., & Voigt, K. (2020) · European Journal of Innovation Management · doi:10.1108/ejim-09-2019-0245 · Cited by 84
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Gharib, R. K., Philpott, E., & Duan, Y. (2016) · Information & Management · doi:10.1016/j.im.2016.11.004 · Cited by 76
“001) between the constrained and unconstrained models were detected [121].”
Background
When Do Large Product Assortments Benefit Consumers? An Information-Processing Perspective
Boyd, D. E., & Bahn, K. D. (2009) · Journal of Retailing · doi:10.1016/j.jretai.2009.05.008 · Cited by 75
Capturing Global Youth: Mobile Gaming in the U.S., Spain, and the Czech Republic
Okazaki, S., Škapa, R., & Grande, I. (2008) · Journal of Computer-Mediated Communication · doi:10.1111/j.1083-6101.2008.00421.x · Cited by 75
Shaping travelers’ attitude toward travel mobile applications
Im, J. Y., & Hançer, M. (2014) · Journal of Hospitality and Tourism Technology · doi:10.1108/jhtt-11-2013-0036 · Cited by 75
“Many studies started to discuss a “fun/enjoyment” aspect as a significant predictor of attitudes in using fast food touch screens (Dabholkar and Bagozzi, 2002) and mobile chat services (Nysveen et al.”
Background
Ventriculostomy Simulation Using Patient-Specific Ventricular Anatomy, 3D Printing, and Hydrogel Casting
Ryan, J. R., Chen, T., Nakaji, P., et al. (2015) · World Neurosurgery · doi:10.1016/j.wneu.2015.06.016 · Cited by 75
THE INTERNATIONAL JOURNAL OF ORGANIZATIONAL INNOVATION
Wu, W.-L., Lee, Y.-C., Shu, H.-S., Chang, H.-J., Hou, J.-J., Lin, S.-J., Huang, C., Liu, K.-N., Lin, C.-H., Tseng, J.-S., et al. (2015) · Cited by 75
Why did they do it? How customers’ self-service technology introduction attributions affect the customer-provider relationship
Nijssen, E. J., Schepers, J., & Belanche, D. (2016) · Journal of service management · doi:10.1108/josm-08-2015-0233 · Cited by 80
Strategies for technology-driven service encounters for patient experience satisfaction in hospitals
Lee, D. (2018) · Technological Forecasting and Social Change · doi:10.1016/j.techfore.2018.06.050 · Cited by 76
Are you a tech-savvy person? Exploring factors influencing customers using self-service technology
Guan, X., Xie, L., Shen, W., & Huan, T.-C. T. C. (2021) · Technology in Society · doi:10.1016/j.techsoc.2021.101564 · Cited by 74
Exploring consumers' adoption of highly technological fashion products
Watchravesringkan, K., Hodges, N. N., & Kim, Y. (2010) · Journal of Fashion Marketing and Management · doi:10.1108/13612021011046101 · Cited by 74
The Impact of Endogenous Motivations on Adoption of IT-Enabled Services
Wunderlich, P., Kranz, J. J., Totzek, D., Veit, D. J., & Picot, A. O. (2013) · Journal of Service Research · doi:10.1177/1094670512474841 · Cited by 78
A dual‐sequence framework for B2C relationship formation: Moderating effects of employee communication style in online group chat
Dabholkar, P. A., van Dolen, W., & de Ruyter, K. (2009) · Psychology and Marketing · doi:10.1002/mar.20265 · Cited by 75
Self-citation
Examining a Model of Mobile Healthcare Technology Acceptance by the Elderly in Taiwan
Hsiao, C., & Tang, K. (2015) · Journal of Global Information Technology Management · doi:10.1080/1097198x.2015.1108099 · Cited by 74
“This result is consistent with a previous study which found that PU is not relevant to the usage of technology-based self-service products (Dabholkar & Bagozzi, 2002).”
Result
The impact of perceived online service quality on swiftguanxi
Shi, S., Mu, R., Lin, L., Yang, C., Kou, G., & Chen, X. (2018) · Internet Research · doi:10.1108/intr-12-2016-0389 · Cited by 74
Stimulating or Intimidating: The Effect of AI-Enabled In-Store Communication on Consumer Patronage Likelihood
van Esch, P., Cui, Y. G., & Jain, S. P. (2020) · Journal of Advertising · doi:10.1080/00913367.2020.1832939 · Cited by 84
Computer-Mediated Customization Tendency (CMCT) and the Adaptive e-Service Experience
Mathwick, C., Wagner, J. D., & Unni, R. M. (2009) · Journal of Retailing · doi:10.1016/j.jretai.2009.11.001 · Cited by 73
Why do consumers with social phobia prefer anthropomorphic customer service chatbots? Evolutionary explanations of the moderating roles of social phobia
Jin, S. A., & Youn, S. (2021) · Telematics and Informatics · doi:10.1016/j.tele.2021.101644 · Cited by 75
Impacts of Virtual Reality on Tourism Experience and Behavioral Intentions: Moderating Role of Novelty Seeking
Yuan, A., & Hong, J. (2023) · Journal of Hospitality & Tourism Research · doi:10.1177/10963480231171301 · Cited by 72
“Moreover, novelty seekers tend to be positively predisposed to new technologies (Dabholkar & Bagozzi, 2002).”
Online purchase determinants
Broekhuizen, T., & Huizingh, K. R. E. (2009) · Management Research News · doi:10.1108/01409170910952949 · Cited by 75
Personality determinants of need for interaction with a retail employee and its impact on self-service technology (SST) usage intentions
Lee, H. (2017) · Journal of Research in Interactive Marketing · doi:10.1108/jrim-04-2016-0036 · Cited by 72
Enhancing consumer value of the co-design experience in mass customization
Turner, F., Merle, A., & Gotteland, D. (2020) · Journal of Business Research · doi:10.1016/j.jbusres.2020.05.052 · Cited by 79
RETRACTED: Innovation adoption across self-service banking technologies in India
Kaushik, A. K., & Rahman, Z. (2015) · International Journal of Bank Marketing · doi:10.1108/ijbm-01-2014-0006 · Cited by 77
Retracted
Merging task‐technology fit and technology acceptance models to assess guest empowerment technology usage in hotels
Schrier, T. R., Erdem, M., & Brewer, P. (2010) · Journal of Hospitality and Tourism Technology · doi:10.1108/17579881011078340 · Cited by 73
Retail Banking and Customer Behaviour: A Study of Self Concept, Satisfaction and Technology Usage
Jamal, A. (2004) · The International Review of Retail Distribution and Consumer Research · doi:10.1080/09593960410001678381 · Cited by 75
Customized logistics service and online shoppers’ satisfaction: an empirical study
Hu, M., Huang, F., Hou, H., Chen, Y., & Bulysheva, L. (2016) · Internet Research · doi:10.1108/intr-11-2014-0295 · Cited by 76
“…Fan, & Kohli, 2002; Mathwick, Malhotra, & Rigdon, 2001; Menon & Kahn, 2002), consumer traits (Brown, Ganesan, & Challagalla, 2001; Burke, 2002; Dabholkar & Bagozzi, 2002), situational factors (Wolfinbarger & Gilly, 2001), previous online shopping experiences (Eastlick & Lotz, 1999; Shim,…”
Consumer Acceptance and Adoption of AI Robo-Advisors in Fintech Industry
Sabir, A. A., Ahmad, I. A., Ahmad, H., Rafiq, M., Khan, M. A., & Noreen, N. (2023) · Mathematics · doi:10.3390/math11061311 · Cited by 92
Why wait? Impact of waiting lines on self-service technology use
Kokkinou, A., & Cranage, D. A. (2015) · International Journal of Contemporary Hospitality Management · doi:10.1108/ijchm-12-2013-0578 · Cited by 70
“Performance encompasses customers’ perception of the reliability and accuracy of an SST (Dabholkar and Bagozzi, 2002).”
BackgroundMethodInfluential
A comparison of consumer views of traditional services and self‐service technologies
Cunningham, L. F., Young, C. E., & Gerlach, J. H. (2009) · Journal of Services Marketing · doi:10.1108/08876040910933057 · Cited by 70
The Roles of Perceived Enjoyment and Price Perception in Determining Acceptance of Multimedia-on-Demand
Liao, C., Tsou, C., & Shu, Y.-C. (2008) · International journal of business and information/International journal of business & information · doi:10.6702/ijbi.2008.3.1.2 · Cited by 70
Consumer Behavioral Intentions towards Mobile Payment Services: An Empirical Analysis in Pakistan
Aslam, W., Ham, M., & Arif, I. (2017) · Market-Tržište · doi:10.22598/mt/2017.29.2.161 · Cited by 73
“This theory is applied extensively in diff erent studies, such as those on the usage of wireless LAN (Yoon & Kim, 2007), the acceptance of Internet-based fi nance (Lee, 2009), and attitudes towards self-service explanations (Dabholkar & Bagozzi, 2002).”
Method
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Tan, X., & Kim, Y.-B. (2015) · Journal of Enterprise Information Management · doi:10.1108/jeim-04-2014-0039 · Cited by 69
“Following similar procedures in existing literature (Dabholkar and Bagozzi, 2002), we used multi-group testing in SEM to run two analyses, one for free estimate across groups, the other for constraining equal path coefficients across groups.”
BackgroundMethod
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Okazaki, S., Bailón, M. Á. N., & Molina‐Castillo, F. (2012) · International Journal of Electronic Commerce · doi:10.2753/jec1086-4415160404 · Cited by 69
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“…4.91 ATT3: For my next online purchase, self-collection using APS would be Favorable - Unfavorable 5.47 4.94 Intention (Source: Collier et al., 2014; Dabholkar & Bagozzi, 2002) INT1: It would be Very likely-Very unlikely for me to use APS self-collection for my next online purchase 5.26…”
MethodInfluential
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Santouridis, I., & Kyritsi, M. A. (2014) · Procedia Economics and Finance · doi:10.1016/s2212-5671(14)00051-3 · Cited by 68
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Value cocreation at its peak: the asymmetric relationship between coproduction and loyalty
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“Similarly, need for interaction (INTER) was measured with three items considered from previous studies (Dabholkar & Bagozzi, 2002; Sarmah et al., 2017).”
BackgroundMethod
Consumer acceptance of RFID-enabled services: a model of multiple attitudes, perceived system characteristics and individual traits
Pramatari, K. C., & Theotokis, A. (2009) · European Journal of Information Systems · doi:10.1057/ejis.2009.40 · Cited by 76
The Role of Signaling Identity in the Adoption of Personal Technologies
Arbore, A., Soscia, I., & Bagozzi, R. P. (2014) · Journal of the Association for Information Systems · doi:10.17705/1jais.00352 · Cited by 72
Self-citation
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Deb, M., & Agrawal, A. (2017) · Journal of Asia Business Studies · doi:10.1108/jabs-11-2015-0191 · Cited by 67
Examining the factors influencing smartphone apps use at tourism destinations: a UTAUT model perspective
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All for one but does one strategy work for all?
Hsieh, Y.-C., Roan, J., Pant, A., Hsieh, J., Chen, W., Lee, M., & Chiu, H.-C. (2012) · Managing Service Quality · doi:10.1108/09604521211231003 · Cited by 66

Authors: Dabholkar, P. A., & Bagozzi, R. P.
Affiliations: University of Tennessee at Knoxville (US)
Rice University (US)
ORCID: Bagozzi, R. P.
Venue: Journal of the Academy of Marketing Science
Publisher: Springer Science and Business Media LLC
Published: 2002-07-01
Volume: 30
Issue: 3
Pages: 184-201
ISSN: 0092-0703 (ISSN-L)
DOI: 10.1177/0092070302303001
OpenAlex: W2029483732
Semantic Scholar: 8c613e2552ca1fa8b3bcc65cf8499fefed4f1ebf
Cited by: 1,898
References: 62
Citations by year: 2026: 50 · 2025: 86 · 2024: 90 · 2023: 79 · 2022: 92 · 2021: 112 · 2020: 105 · 2019: 100 · 2018: 84 · 2017: 77 · 2016: 93 · 2015: 104 · 2014: 130 · 2013: 100 · 2012: 100
FWCI: 49.98
Type: journal article
Language: en
Open access: closed
Locations: Journal of the Academy of Marketing Science (publishedVersion)
Topics: Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Social Sciences › Business, Management and Accounting › Marketing › Customer Service Quality and Loyalty
Health Sciences › Health Professions › Health Information Management › Health, Technology, Consumer Behavior
Keywords: self-service technology, consumer acceptance, attitudinal model, consumer characteristics, situational factors, perceived waiting time, social anxiety, perceived crowding, novelty seeking, technology self-efficacy, self-consciousness, service delivery

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An Attitudinal Model of Technology-Based Self-Service: Moderating Effects of Consumer Traits and Situational Factors

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