Every reference with a DOI in the deposited reference list resolved to a known
work in Crossref or DataCite at the dated check, and none carried a retraction,
withdrawal, or removal notice.
The 102 checked references that resolve
resolves10.1287/mnsc.35.8.982User Acceptance of Computer Technology: A Comparison of Two Theoretical Models
resolves10.1037/xge0000033Algorithm aversion: People erroneously avoid algorithms after seeing them err.
resolves10.1108/JCM-03-2019-3129Entertain me, I’ll stay longer! The influence of types of entertainment on mall shoppers' emotions and behavior
resolves10.1509/jm.13.0056Touch versus Tech: When Technology Functions as a Barrier or a Benefit to Service Encounters
resolves10.1002/jcpy.1181Preference for Human (vs. Robotic) Labor is Stronger in Symbolic Consumption Contexts
resolves10.1509/jm.14.0389Warm Glow or Extra Charge? The Ambivalent Effect of Corporate Social Responsibility Activities on Customers’ Perceived Price Fairness
resolves10.1016/j.jretai.2016.12.006Shopper-Facing Retail Technology: A Retailer Adoption Decision Framework Incorporating Shopper Attitudes and Privacy Concerns
resolves10.1016/j.bushor.2018.08.004Siri, Siri, in my hand: Who’s the fairest in the land? On the interpretations, illustrations, and implications of artificial intelligence
resolves10.1509/jmkg.67.2.19.18608Making Healthful Food Choices: The Influence of Health Claims and Nutrition Information on Consumers’ Evaluations of Packaged Food Products and Restaurant Menu Items
resolves10.1509/jmkg.74.5.104Why do Older Consumers Buy Older Brands? The Role of Attachment and Declining Innovativeness
resolves10.1002/mar.20000The effect of information overload on consumer choice quality in an on‐line environment
resolves10.5898/JHRI.6.3.LiTouching a Mechanical Body: Tactile Contact With Body Parts of a Humanoid Robot Is Physiologically Arousing
resolves10.1016/j.indmarman.2013.03.001Artificial intelligence-based systems applied in industrial marketing: An historical overview, current and future insights
resolves10.1509/jmkg.69.2.61.60759Choosing among Alternative Service Delivery Modes: An Investigation of Customer Trial of Self-Service Technologies
resolves10.1086/678301The Role of Arousal in Congruity-Based Product Evaluation
resolves10.1016/j.jretconser.2013.07.002Supermarket self-checkout service quality, customer satisfaction, and loyalty: Empirical evidence from an emerging market
resolves10.1016/j.bushor.2020.01.003Collaborative intelligence: How human and artificial intelligence create value along the B2B sales funnel
resolves10.1086/661551Influence via Comparison-Driven Self-Evaluation and Restoration: The Case of the Low-Status Influencer
resolves10.1016/j.bushor.2019.07.004Factors that influence new generation candidates to engage with and complete digital, AI-enabled recruiting
resolves10.1111/jcc4.12066Virtual Customer Service Agents: Using Social Presence and Personalization to Shape Online Service Encounters
resolves10.1037/a0018144How prevalent is wishful thinking? Misattribution of arousal causes optimism and pessimism in subjective probabilities.
resolves10.1093/jcr/ucx117How Long Did I Wait? The Effect of Construal Levels on Consumers’ Wait Duration Judgments
resolves10.2307/25148784E-Commerce Product Recommendation Agents: Use, Characteristics, and Impact1
resolves10.1086/346247Looking Back: Exploring the Psychology of Queuing and the Effect of the Number of People Behind
The 26 references without a DOI — listed, not checked
no DOI — not checkedHow AI will change strategy: a
thought experiment
no DOI — not checkedPrediction machines: the simple
economics of artificial intelligence
no DOI — not checkedBandoim,
L.
(2019), “Predicting the future of amazon
go stores”, available at: www.forbes.com/sites/lanabandoim/2019/11/27/predicting-the-future-of-amazon-go-stores/#4b7a07981896
(accessed 14 February
2020).
no DOI — not checkedA little bit about
love
no DOI — not checkedCheng,
A.
(2019), “New York proves amazon go works,
and an even bigger rollout is only a matter of time”,
available at: www.forbes.com/sites/andriacheng/2019/06/26/amazon-gos-even-bigger-rollout-is-not-a-matter-of-if-but-when/#7d53f2096f52
(accessed 19 February
2020).
no DOI — not checkedChui,
M.,
Manyika,
J.,
Miremadi,
M.,
Henke,
N.,
Chung,
R.,
Nel,
P. and
Malhotra,
S.
(2018), “Notes from the AI frontier:
applications and value of deep learning”, available
at www.mckinsey.com/featured-insights/artificial-intelligence/notes-from-the-ai-frontier-applications-and-value-of-deep-learning
(accessed 15 February
2020).
no DOI — not checkedBeyond
automation
no DOI — not checkedArtificial intelligence for the
real world
no DOI — not checkedDhar,
A.
(2020), “The future of service delivery:
humans, AI and automation”, available at: www.forbes.com/sites/forbestechcouncil/2019/05/03/the-future-of-service-delivery-humans-ai-and-automation/#7020858476f3
(accessed 30 July
2020).
no DOI — not checkedIntroduction to
mediation
no DOI — not checkedHeng,
M.
(2019), “Potential for wider retailer
sector to adopt unmanned store concept”,
available at: www.straitstimes.com/singapore/potential-for-wider-retail-sector-to-adopt-unmanned-store-concept
(accessed 14 February
2020).
no DOI — not checkedEngaged to a robot? The role of
AI in service
no DOI — not checkedIsidore,
C. and
Meyersohn,
N.
(2019), “What the retail apocalypse means
for the American economy”, available at:
https://edition.cnn.com/2019/09/30/economy/forever-21-retail-apocalypse/index.html
(accessed 18 February
2020).
no DOI — not checkedHumans Need Not Apply: A Guide to Wealth and
Work in the Age of Artificial Intelligence
no DOI — not checkedKestenbaum,
R.
(2018), “The impact of 3,000 amazon go
stores will be massive”, available at:
www.forbes.com/sites/richardkestenbaum/2018/09/23/3000-amazon-go-stores-ibm-cisco-ncr-fujitsu-toshiba-oracle/#6326af6b5147
(accessed 14 February
2020).
no DOI — not checkedFrontiers: Machines vs humans:
the impact of artificial intelligence chatbot disclosure on customer
purchases
no DOI — not checkedMarr,
B.
(2017), “How Walmart is using machine
learning AI, IoT and big data to boost retail
performance”, available at: www.forbes.com/sites/bernardmarr/2017/08/29/how-walmart-is-using-machine-learning-ai-iot-and-big-data-to-boost-retail-performance/#180a36756cb1
(accessed 12 February
2020).
no DOI — not checkedAn Approach to Environmental
Psychology
no DOI — not checkedPalmer,
M. Buontempo,
F. and
Abadi,
M.
(2020), “Malls across the US are trying
to survive the ‘retail apocalypse’ by adding rides, indoor ski
parks, and other entertainment options”,
available at: www.businessinsider.com/malls-closing-retail-apocalypse-entertainment-shopping-2019-11
(accessed 18 February
2020).
no DOI — not checkedDiffusion of innovations:
modifications of a model for telecommunications
no DOI — not checkedThélin,
L.
(2019), “The unmanned
store”, available at: www.designretailonline.com/projects/technology/the-unmanned-store/
(accessed 14 February
2020).
no DOI — not checkedAI-enabled promiscuity: wham bam
thank you mam
no DOI — not checkedJob candidates’ reactions
to AI-enabled job application processes
no DOI — not checkedAI-enabled biometrics in
recruiting: Insights from marketers for managers
no DOI — not checkedStimulating or intimidating: the
effect of aI-enabled in-store communication on consumer patronage
likelihood
no DOI — not checkedWalton,
C.
(2019), “Brick-and-mortar retail is not
dead, but department stores like Macy’s sure
are”, available at: www.forbes.com/sites/christopherwalton/2019/01/10/physical-retail-is-not-dead-but-department-stores-like-macys-sure-are/#5199cc67dd0e
(accessed 18 February
2020).
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