The present research demonstrates how consumer responses to negative and positive offers are influenced by whether the administering marketing agent is an artificial intelligence (AI) or a human. In the case of a product or service offer that is worse than expected, consumers respond better when dealing with an AI agent in the form of increased purchase likelihood and satisfaction. In contrast, for an offer that is better than expected, consumers respond more positively to a human agent. The authors demonstrate that AI agents, compared with human agents, are perceived to have weaker intentions when administering offers, which accounts for this effect. That is, consumers infer that AI agents lack selfish intentions in the case of an offer that favors the agent and lack benevolent intentions in the case of an offer that favors the customer, thereby dampening the extremity of consumer responses. Moreover, the authors demonstrate a moderating effect, such that marketers may anthropomorphize AI agents to strengthen perceived intentions, providing an avenue to receive due credit from consumers when the agent provides a better offer and mitigate blame when it provides a worse offer. Potential ethical concerns with the use of AI to bypass consumer resistance to negative offers are discussed.
AakerJenniferVohsKathleen D.MogilnerCassie (2010), “Nonprofits Are Seen as Warm and For-Profits as Competent: Firm Stereotypes Matter,” Journal of Consumer Research, 37 (2), 224–37.
2.
AbeleAndrea E.WojciszkeBogdan (2007), “Agency and Communion from the Perspective of Self Versus Others,” Journal of Personality and Social Psychology, 93 (5), 751–63.
3.
AggarwalPankajMcGillAnn L. (2007), “Is That Car Smiling at Me? Schema Congruity as a Basis for Evaluating Anthropomorphized Products,” Journal of Consumer Research, 34 (4), 468–79.
4.
AndersonRonald D.EngledowJack L.BeckerHelmut (1979), “Evaluating the Relationships Among Attitude Toward Business, Product Satisfaction, Experience, and Search Effort,” Journal of Marketing Research, 16 (3), 394–400.
5.
AwadEdmondDsouzaSohanKimRichardSchulzJonathanHenrichJosephShariffAzim, et al. (2018), “The Moral Machine Experiment,” Nature, 563 (7729), 59–64.
6.
BaraschAlixandraLevineEmma E.BermanJonathan Z.SmallDeborah A. (2014), “Selfish or Selfless? On the Signal Value of Emotion in Altruistic Behavior,” Journal of Personality and Social Psychology, 107 (3), 393–413.
7.
BausellR. BarkerLiYu-Fang (2002), Power Analysis for Experimental Research: A Practical Guide for the Biological, Medical and Social Sciences. Cambridge, UK: Cambridge University Press.
8.
BoltonLisa E.MattilaAnna S. (2015), “How Does Corporate Social Responsibility Affect Consumer Response to Service Failure in Buyer–Seller Relationships?” Journal of Retailing, 91 (1), 140–53.
9.
BrandMyles (1984), Intending and Acting: Toward a Naturalized Action Theory. Cambridge, MA: MIT Press.
10.
BratmanMichael E. (1987), Intention, Plans, and Practical Reason. Cambridge, MA: Harvard University Press.
11.
ChandlerJesseSchwarzNorbert (2010), “Use Does Not Wear Ragged the Fabric of Friendship: Thinking of Objects as Alive Makes People Less Willing to Replace Them,” Journal of Consumer Psychology, 20 (2), 138–45.
12.
ChenRockyPengEcho Wen WanLevyEric (2017), “The Effect of Social Exclusion on Consumer Preference for Anthropomorphized Brands,” Journal of Consumer Psychology, 27 (1), 23–34.
13.
DarkePeter R.AshworthLaurenceMainKelley J. (2010), “Great Expectations and Broken Promises: Misleading Claims, Product Failure, Expectancy Disconfirmation and Consumer Distrust,” Journal of the Academy of Marketing Science, 38 (3), 347–62.
14.
DavenportThomasGuhaAbhijitGrewalDhruvBressgottTimna (2020), “How Artificial Intelligence Will Change the Future of Marketing,” Journal of the Academy of Marketing Science, 48 (1), 24–42.
15.
DietvorstBerkeley J.SimmonsJoseph P.MasseyCade (2015), “Algorithm Aversion: People Erroneously Avoid Algorithms After Seeing Them Err,” Journal of Experimental Psychology: General, 144 (1), 114–26.
16.
DuShuiliBhattacharyaChitrabhan B.SenSankar (2007), “Reaping Relational Rewards from Corporate Social Responsibility: The Role of Competitive Positioning,” International Journal of Research in Marketing, 24 (3), 224–41.
17.
EstevaAndreKuprelBrettNovoaRoberto A.KoJustinSwetterSusan M.BlauHelen M., et al. (2017), “Dermatologist-Level Classification of Skin Cancer with Deep Neural Networks,” Nature, 542 (7639), 115–18.
18.
EvangelidisIoannisVan OsselaerStijn M.J. (2018), “Points of (Dis)Parity: Expectation Disconfirmation from Common Attributes in Consumer Choice,” Journal of Marketing Research, 55 (1), 1–13.
19.
FiskRaymond P.YoungClifford E. (1985), “Disconfirmation of Equity Expectations: Effects on Consumer Satisfaction with Services,” NA – Advances in Consumer Research, Vol. 12, Elizabeth C. Hirschman and Moris B. Holbrook, eds. Provo, UT: Association for Consumer Research, 340–45.
20.
GrayHeather M.GrayKurtWegnerDaniel M. (2007), “Dimensions of Mind Perception,” Science, 315 (5812), 619–19.
21.
GrayKurt (2012), “The Power of Good Intentions: Perceived Benevolence Soothes Pain, Increases Pleasure, and Improves Taste,” Social Psychological and Personality Science, 3 (5), 639–45.
22.
GrayKurtWegnerDaniel M. (2008), “The Sting of Intentional Pain,” Psychological Science, 19 (12), 1260–62.
23.
GrayKurtYoungLianeWaytzAdam (2012), “Mind Perception Is the Essence of Morality,” Psychological Inquiry, 23 (2), 101–24.
GüroğluBernavan den BosWouterCroneEveline A. (2009), “Fairness Considerations: Increasing Understanding of Intentionality During Adolescence,” Journal of Experimental Child Psychology, 104 (4), 398–409.
HayesAndrew F. (2017), Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. New York: Guilford Publications.
28.
HilbigBenjamin E.ThielmannIsabelHeppJohannaKleinSina A.ZettlerIngo (2015), “From Personality to Altruistic Behavior (and Back): Evidence from a Double-Blind Dictator Game,” Journal of Research in Personality, 55 (April), 46–50.
29.
HuangSzu-chiChenFangyuan (2019), “When Robots Come to Our Rescue: Why Professional Service Robots Aren’t Inspiring and Can Demotivate Consumers’ Pro-Social Behaviors,” in NA – Advances in Consumer Research Volume 47, BagchiRajeshBlockLaurenLeeLeonard, eds. Duluth, MN: Association for Consumer Research, 93–98.
30.
HuangMing-HuiRustRoland T. (2018), “Artificial Intelligence in Service,” Journal of Service Research, 21 (2), 155–72.
31.
HughesClarethaRobertLionelFradyKristinArroyosAdam (2019), “Artificial Intelligence, Employee Engagement, Fairness, and Job Outcomes,” in Managing Technology and Middle-and Low-Skilled Employees. Bingley, UK: Emerald Publishing, 61–68.
32.
KimTaeWooDuhachekAdam (2020), “Artificial Intelligence and Persuasion: A Construal Level Account,” Psychological Science, 31 (4), 364–80.
33.
KimSaraMcGillAnn L. (2011), “Gaming with Mr. Slot or Gaming the Slot Machine? Power, Anthropomorphism, and Risk Perception,” Journal of Consumer Research, 38 (1), 94–107.
34.
KimSeo YoungSchmittBernd H.ThalmannNadia M. (2019), “Eliza in the Uncanny Valley: Anthropomorphizing Consumer Robots Increases Their Perceived Warmth but Decreases Liking,” Marketing Letters, 30 (1), 1–12.
35.
KumarV.DixitAshutoshJavalgiRajshekar Raj G.DassMayukh (2016), “Research Framework, Strategies, and Applications of Intelligent Agent Technologies (IATs) in Marketing,” Journal of the Academy of Marketing Science, 44 (1), 24–45.
36.
LandwehrJan R.McGillAnn L.HerrmannAndreas (2011), “It's Got the Look: The Effect of Friendly and Aggressive ‘Facial’ Expressions on Product Liking and Sales,” Journal of Marketing, 75 (3), 132–46.
37.
LinChien-HuangChenMing (2017), “Follow Your Heart: How Is Willingness to Pay Formed Under Multiple Anchors?” Frontiers in Psychology, 8 (2269), 1–9.
38.
LongoniChiaraBonezziAndreaMorewedgeCarey (2019), “Resistance to Medical Artificial Intelligence,” Journal of Consumer Research, 46 (4), 629–50.
39.
MacDormanKarl F.VasudevanSandosh K.HoChin-Chang (2009), “Does Japan Really Have Robot Mania? Comparing Attitudes by Implicit and Explicit Measures,” AI & Society, 23, 485–510.
40.
MalleBertram F.MosesLouis J.BaldwinDare A. (2001), “Introduction: The Significance of Intentionality,” Intentions and Intentionality: Foundations of Social Cognition, 4 (1), 1–26.
41.
MayserSabineWangenheimFlorian von (2013), “Perceived Fairness of Differential Customer Treatment: Consumers’ Understanding of Distributive Justice Really Matters,” Journal of Service Research, 16 (1), 99–113.
42.
MendeMartinScottMaura L.van DoornJennyGrewalDhruvShanksIlana (2019), “Service Robots Rising: How Humanoid Robots Influence Service Experiences and Elicit Compensatory Consumer Responses,” Journal of Marketing Research, 56 (4), 535–56.
43.
MorewedgeCarey. K. (2009), “Negativity Bias in Attribution of External Agency,” Journal of Experimental Psychology: General, 138 (4), 535–45.
OliverRichard L. (1980), “A Cognitive Model of the Antecedents and Consequences of Satisfaction Decisions,” Journal of Marketing Research, 17 (4), 460–69.
47.
OliverRichard L.BalakrishnanP.V. SundarBarryBruce (1994), “Outcome Satisfaction in Negotiation: A Test of Expectancy Disconfirmation,” Organizational Behavior and Human Decision Processes, 60 (2), 252–75.
48.
OliverRichard L.DeSarboWayne S. (1988), “Response Determinants in Satisfaction Judgments,” Journal of Consumer Research, 14 (4), 495–507.
RadkeSinaGüroğluBernade BruijnEllen R.A. (2012), “There’s Something About a Fair Split: Intentionality Moderates Context-Based Fairness Considerations in Social Decision-Making,” PLoS One, 7 (2).
51.
RandDavid G.NewmanGeorge E.WurzbacherOwen M. (2015), “Social Context and the Dynamics of Cooperative Choice,” Journal of Behavioral Decision Making, 28 (2), 159–66.
52.
RozinPaulNemeroffCarol (2002), “Sympathetic Magical Thinking: The Contagion and Similarity ‘Heuristics’,” in Heuristic and Biases: The Psychology of Intuitive Judgment, GilovichThomasGriffinDaleKahnemanDaniel, eds. New York: Cambridge University Press, 201–16.
53.
RussellStuart J.NorvigPeter (2010), Artificial Intelligence: A Modern Approach. Hoboken, NJ: Pearson Education.
54.
SanfeyAlan G.RillingJames K.AronsonJessica A.NystromLeigh E.CohenJonathan D. (2003), “The Neural Basis of Economic Decision-Making in the Ultimatum Game,” Science, 300 (5626), 1755–58.
55.
SprengRichard A.MacKenzieScott B.OlshavskyRichard W. (1996), “A Reexamination of the Determinants of Consumer Satisfaction,” Journal of Marketing, 60 (3), 15–32.
56.
SrinivasanRajiAbiGülen Sarial (2021), “When Algorithms Fail: Consumers’ Responses to Brand Harm Crises Caused by Algorithm Errors,” Journal of Marketing, 85 (5), 74–91.
57.
SuleimanRamzi (1996), “Expectations and Fairness in a Modified Ultimatum Game,” Journal of Economic Psychology, 17 (5), 531–54.
58.
ThalerRichard H. (1988), “Anomalies: The Ultimatum Game,” Journal of Economic Perspectives, 2 (4), 195–206.
59.
TsirosMichaelMittalVikasRossWilliam T.Jr. (2004), “The Role of Attributions in Customer Satisfaction: A Reexamination,” Journal of Consumer Research, 31 (2), 476–83.
WaytzAdamCacioppoJohnEpleyNicholas (2010), “Who Sees Human? The Stability and Importance of Individual Differences in Anthropomorphism,” Perspectives on Psychological Science, 5 (3), 219–32.
62.
WaytzAdamHeafnerJoyEpleyNicholas (2014), “The Mind in the Machine: Anthropomorphism Increases Trust in an Autonomous Vehicle,” Journal of Experimental Social Psychology, 52 (May), 113–17.
63.
WilliamsPaulNaumannEarl (2011), “Customer Satisfaction and Business Performance: A Firm-Level Analysis,” Journal of Services Marketing, 25 (1),20–32.
64.
WirtzJochenPattersonPaul G.KunzWerner H.GruberThorstenLuVinh NhatPaluchStefanie, et al. (2018), “Brave New World: Service Robots in the Frontline,” Journal of Service Management, 29 (5), 907–31.
65.
WojciszkeBogdanAbeleAndrea E.BarylaWiesław (2009), “Two Dimensions of Interpersonal Attitudes: Liking Depends on Communion, Respect Depends on Agency,” European Journal of Social Psychology, 39 (6), 973–90.
66.
ZłotowskiJakubProudfootDianeYogeeswaranKumarBartneckChristoph (2015), “Anthropomorphism: Opportunities and Challenges in Human–Robot Interaction,” International Journal of Social Robotics, 7 (3), 347–60.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
