Index
ISBN: 978-1-78756-340-7, eISBN: 978-1-78756-339-1
ISSN: 1548-6435
Publication date: 19 September 2019
This content is currently only available as a PDF
Citation
(2019), "Index", Marketing in a Digital World (Review of Marketing Research, Vol. 16), Emerald Publishing Limited, Leeds, pp. 209-217. https://doi.org/10.1108/S1548-643520190000016022
Publisher
:Emerald Publishing Limited
Copyright © 2019 Emerald Publishing Limited
INDEX
A/B testing, 71–72
Ability, 150
Academic marketers, 92–93
Academic researchers, 128
Adverse technology–consumer interaction (ATCI), 123–126
examples, 126
pathways of technology optimism and, 124
response rates declining to customer surveys, 128–132
significance, 127–128
Agency, 92
AirBnB, 88–89
Alexa, 86–87
Alibaba, 88–89
Alphabet (Google), 51
AlphaGo Zero program, 22–23
Amazon, 2–3, 36, 51, 88–89, 93
current business model, 3–4
reviews, 47
Amazon Alexa app, 108
Amazon Echo, 86, 92–93, 108
Amazon Go, 6–7
Amazon.com, 182
American Association for Public Opinion Research (AAPOR), 129
Antecedents of perceived deception, 148–154
elaboration ability, 151–154
elaboration motivation, 150–151
initial expectations, 148–150
Anthropomorphism, 93
AOL, 3–4
Apple, 51, 88–89, 106–107
Apple Watch, 17
Apps, 107–108
age, 105–106
App Store, 108
AR in, 105
monetization, 105–107
retailers, 106–107
Argument quality, 154–155
ARPANET, 36
Artificial intelligence (AI), 4, 15, 92, 109–110, 113
competency, 123
programs, 22–23
Augmented reality (AR), 107, 112
in apps, 105
AR View, 107
Autonomous cars, 108
Autonomy software, 91–92
“Autopilot” technologies, 6
Aversion to cashless payment transactions, 126
B2B platform, 51
Banner advertising, 57
Biased search & analysis, 68–69
Big Data, 8–9, 38–41, 63–64, 70
A/B testing, 71–72
benefits in marketing management, 65–66
blindness to and falsification of hypotheses, 72–73
combining Big Data with lean start-up methodology, 77–79
communication, 70
confidence, 70–71
confirmation, 68–69
control, 69–70
deceived by Big Data, 66–71
hubris, 67–68
mitigating learning challenges of, 71–76
and privacy, 45–46
regularly updating analyses to reveal shifts and trends, 73
statistical literacy and risk intelligence, 76
3Vs of, 69
transparent presentation of statistical insights, 74–76
Bionic eye, 25
Bitcoin, 91–92
Black Swans event, 69
Blind spots, 127
Blockchains, 91–92
Blurring (see Line tightening)
Brick and mortar, 52–56
Build-measure-learn loop, 64, 78
Business model evolution, 64
Buyer inputs, Internet on, 44–45
Buyer search, 44–45
California consumer privacy act (2018), 107–108
Central routes of persuasion, 154–158
Channel contracting, 180
Chi-square analysis, 176
Cloud-based services, 22–23
CMO Survey, 65
Co-locational targeting, 101
Code, 86
Cognitive dissonance theory (CDT), 146
Commercial 3D printers, 171
Commercialization, 36
Communication, 16–17
of Big Data, 74
networks, 36–37
Commuters, 101
Company strategy, research on, 92–93
Competitive locational targeting, 101
Complexity of market, 88–90
Computer-aided design program (CAD program), 170
Computer-mediated environments, 2
Computer numeric control (CNC) machines, 179
Computers, 18
Confirmation, control, communication, and confidence (4Cs), 67
lean start-up methodology and, 77–79
Connected knowledge economy, 3–4
“Connecting” concept, 25
Consumer reactance to frequent price changes, 126, 132–136
ATCI, 133–135
reasons for, 133
research opportunities, 135–136
Consumer Reports
, 47
Consumer-to-consumer interactions, 4
Consumer-to-firm interactions (C2B interactions), 4
Consumer(s), 1–2, 8
data, 123
decision process, 37
perception of non-deception, 144
research on consumer behavior, 93
role of, 179–180
Consumers’ Perceptions Ethics of Online Retailers (CPEOR), 144
Content, 48–49
Contextual targeting, 101
Conventional econometric model, 39–40
Coping with digital, 5–8
Copy machine, 17
Creations, 175, 176, 181–182
Criticality, 161
Customers, 101
facing technology, 86–87
relationship management, 180
Cybersecurity, 1–2, 5, 6
Data
data-sensitive age, 115
privacy, 107–108
Data-based learning
benefiting from Big Data in marketing management, 65–66
combining Big Data with lean start-up methodology, 77–79
mitigating learning challenges of Big Data, 71–76
Decentralized autonomous organizations (DAOs), 93
Deception, 143–144
online, 144
perception of, 146
Decision-making, 63–64, 77
Deep learning, 23–24
Desktop 3D printers, 168, 170, 172
Digital
attributes, 44, 52–53
cameras, 5
connectivity capabilities, 17
innovations, 1–2, 4
machine communication, 22
manufacturing tools, 168
marketplace, 19
revolution, 2
technologies, 1, 5
transformation, 1–2, 4–5
world, 1
Digital, social media and mobile (DSMM), 4
Digital Age, 14
digital dyads in marketplace, 20–29
information in, 19–20
Digital dyads in marketplace of Digital Age, 20–29
human–human digital dyad, 26–29
human–machine digital dyad, 24–26
machine–machine digital dyad, 21–24
Digital innovations on marketing and consumers
Big Data and privacy, 45–46
buyer search, 44–45
impact on seller inputs, 38–41
impact on seller outputs, 41–43
innovations relating to interactive marketing, 36
Internet on retail markets, 52–56
platforms, 51–52
structure of online interactions between seller, platform and buyer, 38
topics for further research, 39
use of online devices, 37
user generated content, 46–51
Digitalization, 1–2
blindsided by digital, 3–5
in blink of eye, 2–9
coping with digital, 5–8
marketing in digital world, 8–9
Digitization, 5
Direct-to-customer model, 115
Disconfirming analysis, 72–73
Disembodied software, 93
“Driver assist”, 6
DuploBrio adapter, 183–184
E-commerce, 2
sales, 52–53
e-Trade, 3–4
East Asian strategy game “Go”, 22–23
eBay, 38, 51, 88, 104
Economic institutions, nature of, 180–181
Education, 1–2
Elaboration
ability, 151–154
motivation, 150–151
Elaboration Likelihood Model (ELM), 145–146
Electronic word-of-mouth (eWOM), 27–28, 164
Employment, 1–2
Enlightenment, 14–15
Enterprising retailers, 184
Entrepreneurs, 1, 78
Environmental context, 41–42
Esthetic idealism, 14–15
Ethical ideology, 146, 148
Ethical orientations, 149
European Union (EU), 45
Executive leadership, 26
Expertise, 151
Experts, 152
Exploitation, 23–24
Exploration, 23–24
exploration-based algorithms, 23–24
Eye-tracking technology, 102
FabStores, 174
Facebook, 2–3, 18–19, 23, 28, 51, 88–89
Fair value line, 73
Fake or cursory responses to online surveys, 126
Familiarity, 151
Firm-to-consumer interactions (B2C interactions), 4
Firm-to-firm (B2B interactions), 4
Fitbit (smart watches), 108
Fitness trackers, 99
Flattening (see Line steepening)
Follow-up actions, 164
Forecasting model, 39–40
Fourth Industrial Revolution, 15–16
Fraudulent negative review, 126
Fused-deposition modeling, 170
General Data Protection Regulation (GDPR), 46, 107–108
General skepticism, 146, 148, 149–150
Geoconquesting, 101
Ghost Ads, 71–72
Google, 2–3, 15–16, 36, 51, 88–89, 106–107
search engine, 51–52
Google Assistant, 86–87
Google Play, 108
Google Sketchup, 170
Gothic cathedrals, 14–15
GPS navigation, 2–3
Hash, 91–92
Hedonic purchase, 161
Hilton hotels, 93, 115
Hosts value exchange, 88–89
Human behavior, 8
Human computers, 22–23
Human–human connectivity, 14
Human–human digital dyad, 26–29
Human–human social communication, 27
Human–machine communication, 25
Human–machine connectivity, 14
Human–machine digital dyad, 24–26
Idealism, 148–149
IKEA, 107
Illinois MakerLab, 184
In-app advertisements (IAA), 103, 106–107
In-app purchases (IAP), 106–107
In-vitro fertilization, 72
Independent companies, 163
Industrial Revolution, 14–15
Information (see also Artificial intelligence (AI))
in Digital Age, 19–20
evolution, 18
in marketplace, 17–19
products, 87
technology, 16–17, 86–87
Informative advertising, 42
Initial expectations, 146, 148–150
Innovative firms, 72–73
Instagram, 18–19
Intelligence, 90–91
Internet, 2, 17, 36
advertising, 41
algorithms, 23
expertise, 153, 154
on retail markets, 52–56
Internet of Services (IoS), 109
Internet of Things (IoT), 2–3, 98, 109, 113
Internet on buyer inputs, 44–45
Big Data and privacy, 45–46
buyer search, 44–45
user generated content, 46–51
Involvement, 151
iPhone (Apple), 2–3, 15–16, 17
Islamic Golden Age, 14–15
“Jailbreak”, 25
Journal of Marketing (JM), 3
Kiosks, 105
Knowledge, 151, 153
KONE, 109
Laser cutters, 179
Lathing, 170–171
Lean start-up methodology, combining Big Data with, 77–79
and communication, 79
and confidence, 79
and confirmations, 77–78
and control, 78
Learning setting, 66
Legacy firms, 64
Leverage-salience theory, 131
Line steepening, 73
Line tightening, 73
Location targeting leverages, 101
Logistic regression, 40
Low attention spans and distraction of Smartphone use, 126
Machine learning (see also Artificial intelligence (AI)), 23–24
algorithms, 8–9
methods, 39–40
models, 109–110
Machine–machine communication, 24
Machine–machine connectivity, 14
Machine–machine digital dyad, 21–24
Machine–machine dyad, 20–21
MakerBot, 170, 171, 174–175
Manufacturer Recommended Price Range (MSRP), 135
Market, 18, 88
complexity, 90
disruptions, 1
Marketers, 1, 105, 122, 127, 135
Marketing (see also Mobile marketing 2.0)
analytics, 64, 65
applications, 38–39
and consumer behavior, 4
digital dyads in marketplace of digital age, 20–29
in digital world, 8–9
evolution of information in marketplace, 17–19
information in Digital Age, 19–20
and Internet, 3
literature, 169–170
manager, 66–67
professionals, 76
scholars, 8, 179
scholarship, 2, 167–168
spotlight on information, 16–20
stages of ages, 14–16
Marketing management
benefiting from Big Data in, 65–66
combining Big Data with lean start-up methodology in, 77–79
Marketing Science Institute (MSI), 3
Marketplace
information in, 17–19
phenomena, 14
revolution, 18
Marketplace of Digital Age, digital dyads in, 20–29
MasterCard, 89
Materialism theory, 178
Medical Expenditure Panel Survey, 129
Menu costs, 133
Mere-measurement effects, 131
mHealth platform, 106–107
Microsoft, 51, 88–89
Milling, 170–171
Minecraft, 184
Minimum viable product (MVP), 78
Miskol (see Missed Call Marketing (MCM))
Missed Call Marketing (MCM), 103–104
Mobile, 113–115
AR, 107, 112
attributes and related marketing advantages, 100
devices, 99, 100–101, 103
marketers, 100–101
marketing, 98, 105–106
promotions, 98, 99
retailing, 99
technologies, 105, 107
user experience, 107–108
Mobile advertising, 102–103
revenues, 41–42
strategies, 103–104
Mobile apps, 97–98, 99, 104, 105
monetization, 105–107, 112
Mobile marketing 2.0 (see also Marketing), 98
AI, 109–110
data privacy and mobile user experience, 107–108
emerging trends, 105–110
IoT, 109
key issues in mobile marketing, 106
mobile app monetization, 105–107
mobile AR, 107
mobile marketing practice, 113–116
mobile-led cross-channel effects, 104–105
personalized mobile advertising, 102–104
research agenda based on emerging trends, 111–113
research agenda based on gaps in extant literature, 110–111
review of mobile marketing research, 99–105
self-driving vehicles, 108–109
targeted mobile promotions, 100–102
wearables and other smart devices, 108
Mobile-led cross-channel effects, 99, 104–105, 111
Moderators, 162
variables, 159–161
Money-back guarantees, 163
Motivation, 48–49, 150, 151
Motorola Moto X cellphone, 25
Moveable Feast, 14, 19–20, 22
Multi-purpose AI platforms, 123
Multiplayer online battle arenas (MOBA), 28–29
National Health Interview Survey, 129
Nervous System, 182
Netflix, 2–3, 23
Network structure, 48–49
Neural Network Processor (NNP), 22–23
Non-deception, consumers’ perception of, 144
Non-proximal mobile users, 101–102
Non-retail settings, 104
Not-yet-imagined digital technology, 1
NVivo11 qualitative software program, 148
Object
archetypes, 175
notion of, 178–179
Office Max, 182
Offline retailers, 57
Omnichannel retailing, 104, 122
Online
advertising, 41–43
deception, 144
expertise, 153
interactions, 38
purchasing, 142
retailers, 182
reviews, 46–48
search, 45
services, 142
sources, 40–41
Online consumer reviews (OCR), 142, 143, 147
Online word-of-mouth (eWOM), 46
Opportunity network, 3–4
Opt-in, get customers to, 115
“Optimal experience” of psychological flow, 2
Optimism, 122
Outsourcing, 135
Paid apps, 106–107
Paperclip AI, 92
Parrot Pot, 25
Pay Pal, 51
Perceived deception
antecedents of, 148–154
consequences, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR), 142, 143, 162, 163
data analysis, 147–148
data collection and sample, 147
findings and conceptual model, 148–161
literature review, 143–146
method, 147–148
theoretical and managerial implications, 162–164
Perceived homophily, 155, 156, 163–164
Perceived riskiness of purchase, 159–160
Peripheral cues, 157
Peripheral routes of persuasion, 154–158
Personalization, 103, 115
Personalized mobile advertising, 99, 102–104, 110–111
Persuasion
central and peripheral routes of, 154–158
persuasive advertising, 42
Pet grooming, 133–134
Pew Research Center, 48
“Plant Sitter” mode, 25
Platforms, 51–52
Positive-NPV marketing program, 131
Potential negativity, 161
Practitioners, 8
Pre-Internet, 88
Price, 92
fluctuation, 133
volatility, 134
Privacy, 45–46
Product
knowledge, 151
and services, 159–160
Public policy, 92–93
Purchase involvement, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
A/B testing
, 71–72
Ability
, 150
Academic marketers
, 92–93
Academic researchers
, 128
Adverse technology–consumer interaction (ATCI)
, 123–126
examples
, 126
pathways of technology optimism and
, 124
response rates declining to customer surveys
, 128–132
significance
, 127–128
Agency
, 92
AirBnB
, 88–89
Alexa
, 86–87
Alibaba
, 88–89
Alphabet (Google)
, 51
AlphaGo Zero program
, 22–23
Amazon
, 2–3, 36, 51, 88–89, 93
current business model
, 3–4
reviews
, 47
Amazon Alexa app
, 108
Amazon Echo
, 86, 92–93, 108
Amazon Go
, 6–7
Amazon.com
, 182
American Association for Public Opinion Research (AAPOR)
, 129
Antecedents of perceived deception
, 148–154
elaboration ability
, 151–154
elaboration motivation
, 150–151
initial expectations
, 148–150
Anthropomorphism
, 93
AOL
, 3–4
Apple
, 51, 88–89, 106–107
Apple Watch
, 17
Apps
, 107–108
age
, 105–106
App Store
, 108
AR in
, 105
monetization
, 105–107
retailers
, 106–107
Argument quality
, 154–155
ARPANET
, 36
Artificial intelligence (AI)
, 4, 15, 92, 109–110, 113
competency
, 123
programs
, 22–23
Augmented reality (AR)
, 107, 112
in apps
, 105
AR View
, 107
Autonomous cars
, 108
Autonomy software
, 91–92
“Autopilot” technologies
, 6
Aversion to cashless payment transactions
, 126
B2B platform
, 51
Banner advertising
, 57
Biased search & analysis
, 68–69
Big Data
, 8–9, 38–41, 63–64, 70
A/B testing
, 71–72
benefits in marketing management
, 65–66
blindness to and falsification of hypotheses
, 72–73
combining Big Data with lean start-up methodology
, 77–79
communication
, 70
confidence
, 70–71
confirmation
, 68–69
control
, 69–70
deceived by Big Data
, 66–71
hubris
, 67–68
mitigating learning challenges of
, 71–76
and privacy
, 45–46
regularly updating analyses to reveal shifts and trends
, 73
statistical literacy and risk intelligence
, 76
3Vs of
, 69
transparent presentation of statistical insights
, 74–76
Bionic eye
, 25
Bitcoin
, 91–92
Black Swans event
, 69
Blind spots
, 127
Blockchains
, 91–92
Blurring (see Line tightening)
Brick and mortar
, 52–56
Build-measure-learn loop
, 64, 78
Business model evolution
, 64
Buyer inputs, Internet on
, 44–45
Buyer search
, 44–45
California consumer privacy act (2018), 107–108
Central routes of persuasion, 154–158
Channel contracting, 180
Chi-square analysis, 176
Cloud-based services, 22–23
CMO Survey, 65
Co-locational targeting, 101
Code, 86
Cognitive dissonance theory (CDT), 146
Commercial 3D printers, 171
Commercialization, 36
Communication, 16–17
of Big Data, 74
networks, 36–37
Commuters, 101
Company strategy, research on, 92–93
Competitive locational targeting, 101
Complexity of market, 88–90
Computer-aided design program (CAD program), 170
Computer-mediated environments, 2
Computer numeric control (CNC) machines, 179
Computers, 18
Confirmation, control, communication, and confidence (4Cs), 67
lean start-up methodology and, 77–79
Connected knowledge economy, 3–4
“Connecting” concept, 25
Consumer reactance to frequent price changes, 126, 132–136
ATCI, 133–135
reasons for, 133
research opportunities, 135–136
Consumer Reports
, 47
Consumer-to-consumer interactions, 4
Consumer-to-firm interactions (C2B interactions), 4
Consumer(s), 1–2, 8
data, 123
decision process, 37
perception of non-deception, 144
research on consumer behavior, 93
role of, 179–180
Consumers’ Perceptions Ethics of Online Retailers (CPEOR), 144
Content, 48–49
Contextual targeting, 101
Conventional econometric model, 39–40
Coping with digital, 5–8
Copy machine, 17
Creations, 175, 176, 181–182
Criticality, 161
Customers, 101
facing technology, 86–87
relationship management, 180
Cybersecurity, 1–2, 5, 6
Data
data-sensitive age, 115
privacy, 107–108
Data-based learning
benefiting from Big Data in marketing management, 65–66
combining Big Data with lean start-up methodology, 77–79
mitigating learning challenges of Big Data, 71–76
Decentralized autonomous organizations (DAOs), 93
Deception, 143–144
online, 144
perception of, 146
Decision-making, 63–64, 77
Deep learning, 23–24
Desktop 3D printers, 168, 170, 172
Digital
attributes, 44, 52–53
cameras, 5
connectivity capabilities, 17
innovations, 1–2, 4
machine communication, 22
manufacturing tools, 168
marketplace, 19
revolution, 2
technologies, 1, 5
transformation, 1–2, 4–5
world, 1
Digital, social media and mobile (DSMM), 4
Digital Age, 14
digital dyads in marketplace, 20–29
information in, 19–20
Digital dyads in marketplace of Digital Age, 20–29
human–human digital dyad, 26–29
human–machine digital dyad, 24–26
machine–machine digital dyad, 21–24
Digital innovations on marketing and consumers
Big Data and privacy, 45–46
buyer search, 44–45
impact on seller inputs, 38–41
impact on seller outputs, 41–43
innovations relating to interactive marketing, 36
Internet on retail markets, 52–56
platforms, 51–52
structure of online interactions between seller, platform and buyer, 38
topics for further research, 39
use of online devices, 37
user generated content, 46–51
Digitalization, 1–2
blindsided by digital, 3–5
in blink of eye, 2–9
coping with digital, 5–8
marketing in digital world, 8–9
Digitization, 5
Direct-to-customer model, 115
Disconfirming analysis, 72–73
Disembodied software, 93
“Driver assist”, 6
DuploBrio adapter, 183–184
E-commerce, 2
sales, 52–53
e-Trade, 3–4
East Asian strategy game “Go”, 22–23
eBay, 38, 51, 88, 104
Economic institutions, nature of, 180–181
Education, 1–2
Elaboration
ability, 151–154
motivation, 150–151
Elaboration Likelihood Model (ELM), 145–146
Electronic word-of-mouth (eWOM), 27–28, 164
Employment, 1–2
Enlightenment, 14–15
Enterprising retailers, 184
Entrepreneurs, 1, 78
Environmental context, 41–42
Esthetic idealism, 14–15
Ethical ideology, 146, 148
Ethical orientations, 149
European Union (EU), 45
Executive leadership, 26
Expertise, 151
Experts, 152
Exploitation, 23–24
Exploration, 23–24
exploration-based algorithms, 23–24
Eye-tracking technology, 102
FabStores, 174
Facebook, 2–3, 18–19, 23, 28, 51, 88–89
Fair value line, 73
Fake or cursory responses to online surveys, 126
Familiarity, 151
Firm-to-consumer interactions (B2C interactions), 4
Firm-to-firm (B2B interactions), 4
Fitbit (smart watches), 108
Fitness trackers, 99
Flattening (see Line steepening)
Follow-up actions, 164
Forecasting model, 39–40
Fourth Industrial Revolution, 15–16
Fraudulent negative review, 126
Fused-deposition modeling, 170
General Data Protection Regulation (GDPR), 46, 107–108
General skepticism, 146, 148, 149–150
Geoconquesting, 101
Ghost Ads, 71–72
Google, 2–3, 15–16, 36, 51, 88–89, 106–107
search engine, 51–52
Google Assistant, 86–87
Google Play, 108
Google Sketchup, 170
Gothic cathedrals, 14–15
GPS navigation, 2–3
Hash, 91–92
Hedonic purchase, 161
Hilton hotels, 93, 115
Hosts value exchange, 88–89
Human behavior, 8
Human computers, 22–23
Human–human connectivity, 14
Human–human digital dyad, 26–29
Human–human social communication, 27
Human–machine communication, 25
Human–machine connectivity, 14
Human–machine digital dyad, 24–26
Idealism, 148–149
IKEA, 107
Illinois MakerLab, 184
In-app advertisements (IAA), 103, 106–107
In-app purchases (IAP), 106–107
In-vitro fertilization, 72
Independent companies, 163
Industrial Revolution, 14–15
Information (see also Artificial intelligence (AI))
in Digital Age, 19–20
evolution, 18
in marketplace, 17–19
products, 87
technology, 16–17, 86–87
Informative advertising, 42
Initial expectations, 146, 148–150
Innovative firms, 72–73
Instagram, 18–19
Intelligence, 90–91
Internet, 2, 17, 36
advertising, 41
algorithms, 23
expertise, 153, 154
on retail markets, 52–56
Internet of Services (IoS), 109
Internet of Things (IoT), 2–3, 98, 109, 113
Internet on buyer inputs, 44–45
Big Data and privacy, 45–46
buyer search, 44–45
user generated content, 46–51
Involvement, 151
iPhone (Apple), 2–3, 15–16, 17
Islamic Golden Age, 14–15
“Jailbreak”, 25
Journal of Marketing (JM), 3
Kiosks, 105
Knowledge, 151, 153
KONE, 109
Laser cutters, 179
Lathing, 170–171
Lean start-up methodology, combining Big Data with, 77–79
and communication, 79
and confidence, 79
and confirmations, 77–78
and control, 78
Learning setting, 66
Legacy firms, 64
Leverage-salience theory, 131
Line steepening, 73
Line tightening, 73
Location targeting leverages, 101
Logistic regression, 40
Low attention spans and distraction of Smartphone use, 126
Machine learning (see also Artificial intelligence (AI)), 23–24
algorithms, 8–9
methods, 39–40
models, 109–110
Machine–machine communication, 24
Machine–machine connectivity, 14
Machine–machine digital dyad, 21–24
Machine–machine dyad, 20–21
MakerBot, 170, 171, 174–175
Manufacturer Recommended Price Range (MSRP), 135
Market, 18, 88
complexity, 90
disruptions, 1
Marketers, 1, 105, 122, 127, 135
Marketing (see also Mobile marketing 2.0)
analytics, 64, 65
applications, 38–39
and consumer behavior, 4
digital dyads in marketplace of digital age, 20–29
in digital world, 8–9
evolution of information in marketplace, 17–19
information in Digital Age, 19–20
and Internet, 3
literature, 169–170
manager, 66–67
professionals, 76
scholars, 8, 179
scholarship, 2, 167–168
spotlight on information, 16–20
stages of ages, 14–16
Marketing management
benefiting from Big Data in, 65–66
combining Big Data with lean start-up methodology in, 77–79
Marketing Science Institute (MSI), 3
Marketplace
information in, 17–19
phenomena, 14
revolution, 18
Marketplace of Digital Age, digital dyads in, 20–29
MasterCard, 89
Materialism theory, 178
Medical Expenditure Panel Survey, 129
Menu costs, 133
Mere-measurement effects, 131
mHealth platform, 106–107
Microsoft, 51, 88–89
Milling, 170–171
Minecraft, 184
Minimum viable product (MVP), 78
Miskol (see Missed Call Marketing (MCM))
Missed Call Marketing (MCM), 103–104
Mobile, 113–115
AR, 107, 112
attributes and related marketing advantages, 100
devices, 99, 100–101, 103
marketers, 100–101
marketing, 98, 105–106
promotions, 98, 99
retailing, 99
technologies, 105, 107
user experience, 107–108
Mobile advertising, 102–103
revenues, 41–42
strategies, 103–104
Mobile apps, 97–98, 99, 104, 105
monetization, 105–107, 112
Mobile marketing 2.0 (see also Marketing), 98
AI, 109–110
data privacy and mobile user experience, 107–108
emerging trends, 105–110
IoT, 109
key issues in mobile marketing, 106
mobile app monetization, 105–107
mobile AR, 107
mobile marketing practice, 113–116
mobile-led cross-channel effects, 104–105
personalized mobile advertising, 102–104
research agenda based on emerging trends, 111–113
research agenda based on gaps in extant literature, 110–111
review of mobile marketing research, 99–105
self-driving vehicles, 108–109
targeted mobile promotions, 100–102
wearables and other smart devices, 108
Mobile-led cross-channel effects, 99, 104–105, 111
Moderators, 162
variables, 159–161
Money-back guarantees, 163
Motivation, 48–49, 150, 151
Motorola Moto X cellphone, 25
Moveable Feast, 14, 19–20, 22
Multi-purpose AI platforms, 123
Multiplayer online battle arenas (MOBA), 28–29
National Health Interview Survey, 129
Nervous System, 182
Netflix, 2–3, 23
Network structure, 48–49
Neural Network Processor (NNP), 22–23
Non-deception, consumers’ perception of, 144
Non-proximal mobile users, 101–102
Non-retail settings, 104
Not-yet-imagined digital technology, 1
NVivo11 qualitative software program, 148
Object
archetypes, 175
notion of, 178–179
Office Max, 182
Offline retailers, 57
Omnichannel retailing, 104, 122
Online
advertising, 41–43
deception, 144
expertise, 153
interactions, 38
purchasing, 142
retailers, 182
reviews, 46–48
search, 45
services, 142
sources, 40–41
Online consumer reviews (OCR), 142, 143, 147
Online word-of-mouth (eWOM), 46
Opportunity network, 3–4
Opt-in, get customers to, 115
“Optimal experience” of psychological flow, 2
Optimism, 122
Outsourcing, 135
Paid apps, 106–107
Paperclip AI, 92
Parrot Pot, 25
Pay Pal, 51
Perceived deception
antecedents of, 148–154
consequences, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR), 142, 143, 162, 163
data analysis, 147–148
data collection and sample, 147
findings and conceptual model, 148–161
literature review, 143–146
method, 147–148
theoretical and managerial implications, 162–164
Perceived homophily, 155, 156, 163–164
Perceived riskiness of purchase, 159–160
Peripheral cues, 157
Peripheral routes of persuasion, 154–158
Personalization, 103, 115
Personalized mobile advertising, 99, 102–104, 110–111
Persuasion
central and peripheral routes of, 154–158
persuasive advertising, 42
Pet grooming, 133–134
Pew Research Center, 48
“Plant Sitter” mode, 25
Platforms, 51–52
Positive-NPV marketing program, 131
Potential negativity, 161
Practitioners, 8
Pre-Internet, 88
Price, 92
fluctuation, 133
volatility, 134
Privacy, 45–46
Product
knowledge, 151
and services, 159–160
Public policy, 92–93
Purchase involvement, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
California consumer privacy act (2018)
, 107–108
Central routes of persuasion
, 154–158
Channel contracting
, 180
Chi-square analysis
, 176
Cloud-based services
, 22–23
CMO Survey
, 65
Co-locational targeting
, 101
Code
, 86
Cognitive dissonance theory (CDT)
, 146
Commercial 3D printers
, 171
Commercialization
, 36
Communication
, 16–17
of Big Data
, 74
networks
, 36–37
Commuters
, 101
Company strategy, research on
, 92–93
Competitive locational targeting
, 101
Complexity of market
, 88–90
Computer-aided design program (CAD program)
, 170
Computer-mediated environments
, 2
Computer numeric control (CNC) machines
, 179
Computers
, 18
Confirmation, control, communication, and confidence (4Cs)
, 67
lean start-up methodology and
, 77–79
Connected knowledge economy
, 3–4
“Connecting” concept
, 25
Consumer reactance to frequent price changes
, 126, 132–136
ATCI
, 133–135
reasons for
, 133
research opportunities
, 135–136
Consumer Reports
, 47
Consumer-to-consumer interactions
, 4
Consumer-to-firm interactions (C2B interactions)
, 4
Consumer(s)
, 1–2, 8
data
, 123
decision process
, 37
perception of non-deception
, 144
research on consumer behavior
, 93
role of
, 179–180
Consumers’ Perceptions Ethics of Online Retailers (CPEOR)
, 144
Content
, 48–49
Contextual targeting
, 101
Conventional econometric model
, 39–40
Coping with digital
, 5–8
Copy machine
, 17
Creations
, 175, 176, 181–182
Criticality
, 161
Customers
, 101
facing technology
, 86–87
relationship management
, 180
Cybersecurity
, 1–2, 5, 6
Data
data-sensitive age
, 115
privacy
, 107–108
Data-based learning
benefiting from Big Data in marketing management
, 65–66
combining Big Data with lean start-up methodology
, 77–79
mitigating learning challenges of Big Data
, 71–76
Decentralized autonomous organizations (DAOs)
, 93
Deception
, 143–144
online
, 144
perception of
, 146
Decision-making
, 63–64, 77
Deep learning
, 23–24
Desktop 3D printers
, 168, 170, 172
Digital
attributes
, 44, 52–53
cameras
, 5
connectivity capabilities
, 17
innovations
, 1–2, 4
machine communication
, 22
manufacturing tools
, 168
marketplace
, 19
revolution
, 2
technologies
, 1, 5
transformation
, 1–2, 4–5
world
, 1
Digital, social media and mobile (DSMM)
, 4
Digital Age
, 14
digital dyads in marketplace
, 20–29
information in
, 19–20
Digital dyads in marketplace of Digital Age
, 20–29
human–human digital dyad
, 26–29
human–machine digital dyad
, 24–26
machine–machine digital dyad
, 21–24
Digital innovations on marketing and consumers
Big Data and privacy
, 45–46
buyer search
, 44–45
impact on seller inputs
, 38–41
impact on seller outputs
, 41–43
innovations relating to interactive marketing
, 36
Internet on retail markets
, 52–56
platforms
, 51–52
structure of online interactions between seller, platform and buyer
, 38
topics for further research
, 39
use of online devices
, 37
user generated content
, 46–51
Digitalization
, 1–2
blindsided by digital
, 3–5
in blink of eye
, 2–9
coping with digital
, 5–8
marketing in digital world
, 8–9
Digitization
, 5
Direct-to-customer model
, 115
Disconfirming analysis
, 72–73
Disembodied software
, 93
“Driver assist”
, 6
DuploBrio adapter
, 183–184
E-commerce, 2
sales, 52–53
e-Trade, 3–4
East Asian strategy game “Go”, 22–23
eBay, 38, 51, 88, 104
Economic institutions, nature of, 180–181
Education, 1–2
Elaboration
ability, 151–154
motivation, 150–151
Elaboration Likelihood Model (ELM), 145–146
Electronic word-of-mouth (eWOM), 27–28, 164
Employment, 1–2
Enlightenment, 14–15
Enterprising retailers, 184
Entrepreneurs, 1, 78
Environmental context, 41–42
Esthetic idealism, 14–15
Ethical ideology, 146, 148
Ethical orientations, 149
European Union (EU), 45
Executive leadership, 26
Expertise, 151
Experts, 152
Exploitation, 23–24
Exploration, 23–24
exploration-based algorithms, 23–24
Eye-tracking technology, 102
FabStores, 174
Facebook, 2–3, 18–19, 23, 28, 51, 88–89
Fair value line, 73
Fake or cursory responses to online surveys, 126
Familiarity, 151
Firm-to-consumer interactions (B2C interactions), 4
Firm-to-firm (B2B interactions), 4
Fitbit (smart watches), 108
Fitness trackers, 99
Flattening (see Line steepening)
Follow-up actions, 164
Forecasting model, 39–40
Fourth Industrial Revolution, 15–16
Fraudulent negative review, 126
Fused-deposition modeling, 170
General Data Protection Regulation (GDPR), 46, 107–108
General skepticism, 146, 148, 149–150
Geoconquesting, 101
Ghost Ads, 71–72
Google, 2–3, 15–16, 36, 51, 88–89, 106–107
search engine, 51–52
Google Assistant, 86–87
Google Play, 108
Google Sketchup, 170
Gothic cathedrals, 14–15
GPS navigation, 2–3
Hash, 91–92
Hedonic purchase, 161
Hilton hotels, 93, 115
Hosts value exchange, 88–89
Human behavior, 8
Human computers, 22–23
Human–human connectivity, 14
Human–human digital dyad, 26–29
Human–human social communication, 27
Human–machine communication, 25
Human–machine connectivity, 14
Human–machine digital dyad, 24–26
Idealism, 148–149
IKEA, 107
Illinois MakerLab, 184
In-app advertisements (IAA), 103, 106–107
In-app purchases (IAP), 106–107
In-vitro fertilization, 72
Independent companies, 163
Industrial Revolution, 14–15
Information (see also Artificial intelligence (AI))
in Digital Age, 19–20
evolution, 18
in marketplace, 17–19
products, 87
technology, 16–17, 86–87
Informative advertising, 42
Initial expectations, 146, 148–150
Innovative firms, 72–73
Instagram, 18–19
Intelligence, 90–91
Internet, 2, 17, 36
advertising, 41
algorithms, 23
expertise, 153, 154
on retail markets, 52–56
Internet of Services (IoS), 109
Internet of Things (IoT), 2–3, 98, 109, 113
Internet on buyer inputs, 44–45
Big Data and privacy, 45–46
buyer search, 44–45
user generated content, 46–51
Involvement, 151
iPhone (Apple), 2–3, 15–16, 17
Islamic Golden Age, 14–15
“Jailbreak”, 25
Journal of Marketing (JM), 3
Kiosks, 105
Knowledge, 151, 153
KONE, 109
Laser cutters, 179
Lathing, 170–171
Lean start-up methodology, combining Big Data with, 77–79
and communication, 79
and confidence, 79
and confirmations, 77–78
and control, 78
Learning setting, 66
Legacy firms, 64
Leverage-salience theory, 131
Line steepening, 73
Line tightening, 73
Location targeting leverages, 101
Logistic regression, 40
Low attention spans and distraction of Smartphone use, 126
Machine learning (see also Artificial intelligence (AI)), 23–24
algorithms, 8–9
methods, 39–40
models, 109–110
Machine–machine communication, 24
Machine–machine connectivity, 14
Machine–machine digital dyad, 21–24
Machine–machine dyad, 20–21
MakerBot, 170, 171, 174–175
Manufacturer Recommended Price Range (MSRP), 135
Market, 18, 88
complexity, 90
disruptions, 1
Marketers, 1, 105, 122, 127, 135
Marketing (see also Mobile marketing 2.0)
analytics, 64, 65
applications, 38–39
and consumer behavior, 4
digital dyads in marketplace of digital age, 20–29
in digital world, 8–9
evolution of information in marketplace, 17–19
information in Digital Age, 19–20
and Internet, 3
literature, 169–170
manager, 66–67
professionals, 76
scholars, 8, 179
scholarship, 2, 167–168
spotlight on information, 16–20
stages of ages, 14–16
Marketing management
benefiting from Big Data in, 65–66
combining Big Data with lean start-up methodology in, 77–79
Marketing Science Institute (MSI), 3
Marketplace
information in, 17–19
phenomena, 14
revolution, 18
Marketplace of Digital Age, digital dyads in, 20–29
MasterCard, 89
Materialism theory, 178
Medical Expenditure Panel Survey, 129
Menu costs, 133
Mere-measurement effects, 131
mHealth platform, 106–107
Microsoft, 51, 88–89
Milling, 170–171
Minecraft, 184
Minimum viable product (MVP), 78
Miskol (see Missed Call Marketing (MCM))
Missed Call Marketing (MCM), 103–104
Mobile, 113–115
AR, 107, 112
attributes and related marketing advantages, 100
devices, 99, 100–101, 103
marketers, 100–101
marketing, 98, 105–106
promotions, 98, 99
retailing, 99
technologies, 105, 107
user experience, 107–108
Mobile advertising, 102–103
revenues, 41–42
strategies, 103–104
Mobile apps, 97–98, 99, 104, 105
monetization, 105–107, 112
Mobile marketing 2.0 (see also Marketing), 98
AI, 109–110
data privacy and mobile user experience, 107–108
emerging trends, 105–110
IoT, 109
key issues in mobile marketing, 106
mobile app monetization, 105–107
mobile AR, 107
mobile marketing practice, 113–116
mobile-led cross-channel effects, 104–105
personalized mobile advertising, 102–104
research agenda based on emerging trends, 111–113
research agenda based on gaps in extant literature, 110–111
review of mobile marketing research, 99–105
self-driving vehicles, 108–109
targeted mobile promotions, 100–102
wearables and other smart devices, 108
Mobile-led cross-channel effects, 99, 104–105, 111
Moderators, 162
variables, 159–161
Money-back guarantees, 163
Motivation, 48–49, 150, 151
Motorola Moto X cellphone, 25
Moveable Feast, 14, 19–20, 22
Multi-purpose AI platforms, 123
Multiplayer online battle arenas (MOBA), 28–29
National Health Interview Survey, 129
Nervous System, 182
Netflix, 2–3, 23
Network structure, 48–49
Neural Network Processor (NNP), 22–23
Non-deception, consumers’ perception of, 144
Non-proximal mobile users, 101–102
Non-retail settings, 104
Not-yet-imagined digital technology, 1
NVivo11 qualitative software program, 148
Object
archetypes, 175
notion of, 178–179
Office Max, 182
Offline retailers, 57
Omnichannel retailing, 104, 122
Online
advertising, 41–43
deception, 144
expertise, 153
interactions, 38
purchasing, 142
retailers, 182
reviews, 46–48
search, 45
services, 142
sources, 40–41
Online consumer reviews (OCR), 142, 143, 147
Online word-of-mouth (eWOM), 46
Opportunity network, 3–4
Opt-in, get customers to, 115
“Optimal experience” of psychological flow, 2
Optimism, 122
Outsourcing, 135
Paid apps, 106–107
Paperclip AI, 92
Parrot Pot, 25
Pay Pal, 51
Perceived deception
antecedents of, 148–154
consequences, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR), 142, 143, 162, 163
data analysis, 147–148
data collection and sample, 147
findings and conceptual model, 148–161
literature review, 143–146
method, 147–148
theoretical and managerial implications, 162–164
Perceived homophily, 155, 156, 163–164
Perceived riskiness of purchase, 159–160
Peripheral cues, 157
Peripheral routes of persuasion, 154–158
Personalization, 103, 115
Personalized mobile advertising, 99, 102–104, 110–111
Persuasion
central and peripheral routes of, 154–158
persuasive advertising, 42
Pet grooming, 133–134
Pew Research Center, 48
“Plant Sitter” mode, 25
Platforms, 51–52
Positive-NPV marketing program, 131
Potential negativity, 161
Practitioners, 8
Pre-Internet, 88
Price, 92
fluctuation, 133
volatility, 134
Privacy, 45–46
Product
knowledge, 151
and services, 159–160
Public policy, 92–93
Purchase involvement, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
E-commerce
, 2
sales
, 52–53
e-Trade
, 3–4
East Asian strategy game “Go”
, 22–23
eBay
, 38, 51, 88, 104
Economic institutions, nature of
, 180–181
Education
, 1–2
Elaboration
ability
, 151–154
motivation
, 150–151
Elaboration Likelihood Model (ELM)
, 145–146
Electronic word-of-mouth (eWOM)
, 27–28, 164
Employment
, 1–2
Enlightenment
, 14–15
Enterprising retailers
, 184
Entrepreneurs
, 1, 78
Environmental context
, 41–42
Esthetic idealism
, 14–15
Ethical ideology
, 146, 148
Ethical orientations
, 149
European Union (EU)
, 45
Executive leadership
, 26
Expertise
, 151
Experts
, 152
Exploitation
, 23–24
Exploration
, 23–24
exploration-based algorithms
, 23–24
Eye-tracking technology
, 102
FabStores
, 174
Facebook
, 2–3, 18–19, 23, 28, 51, 88–89
Fair value line
, 73
Fake or cursory responses to online surveys
, 126
Familiarity
, 151
Firm-to-consumer interactions (B2C interactions)
, 4
Firm-to-firm (B2B interactions)
, 4
Fitbit (smart watches)
, 108
Fitness trackers
, 99
Flattening (see Line steepening)
Follow-up actions
, 164
Forecasting model
, 39–40
Fourth Industrial Revolution
, 15–16
Fraudulent negative review
, 126
Fused-deposition modeling
, 170
General Data Protection Regulation (GDPR), 46, 107–108
General skepticism, 146, 148, 149–150
Geoconquesting, 101
Ghost Ads, 71–72
Google, 2–3, 15–16, 36, 51, 88–89, 106–107
search engine, 51–52
Google Assistant, 86–87
Google Play, 108
Google Sketchup, 170
Gothic cathedrals, 14–15
GPS navigation, 2–3
Hash, 91–92
Hedonic purchase, 161
Hilton hotels, 93, 115
Hosts value exchange, 88–89
Human behavior, 8
Human computers, 22–23
Human–human connectivity, 14
Human–human digital dyad, 26–29
Human–human social communication, 27
Human–machine communication, 25
Human–machine connectivity, 14
Human–machine digital dyad, 24–26
Idealism, 148–149
IKEA, 107
Illinois MakerLab, 184
In-app advertisements (IAA), 103, 106–107
In-app purchases (IAP), 106–107
In-vitro fertilization, 72
Independent companies, 163
Industrial Revolution, 14–15
Information (see also Artificial intelligence (AI))
in Digital Age, 19–20
evolution, 18
in marketplace, 17–19
products, 87
technology, 16–17, 86–87
Informative advertising, 42
Initial expectations, 146, 148–150
Innovative firms, 72–73
Instagram, 18–19
Intelligence, 90–91
Internet, 2, 17, 36
advertising, 41
algorithms, 23
expertise, 153, 154
on retail markets, 52–56
Internet of Services (IoS), 109
Internet of Things (IoT), 2–3, 98, 109, 113
Internet on buyer inputs, 44–45
Big Data and privacy, 45–46
buyer search, 44–45
user generated content, 46–51
Involvement, 151
iPhone (Apple), 2–3, 15–16, 17
Islamic Golden Age, 14–15
“Jailbreak”, 25
Journal of Marketing (JM), 3
Kiosks, 105
Knowledge, 151, 153
KONE, 109
Laser cutters, 179
Lathing, 170–171
Lean start-up methodology, combining Big Data with, 77–79
and communication, 79
and confidence, 79
and confirmations, 77–78
and control, 78
Learning setting, 66
Legacy firms, 64
Leverage-salience theory, 131
Line steepening, 73
Line tightening, 73
Location targeting leverages, 101
Logistic regression, 40
Low attention spans and distraction of Smartphone use, 126
Machine learning (see also Artificial intelligence (AI)), 23–24
algorithms, 8–9
methods, 39–40
models, 109–110
Machine–machine communication, 24
Machine–machine connectivity, 14
Machine–machine digital dyad, 21–24
Machine–machine dyad, 20–21
MakerBot, 170, 171, 174–175
Manufacturer Recommended Price Range (MSRP), 135
Market, 18, 88
complexity, 90
disruptions, 1
Marketers, 1, 105, 122, 127, 135
Marketing (see also Mobile marketing 2.0)
analytics, 64, 65
applications, 38–39
and consumer behavior, 4
digital dyads in marketplace of digital age, 20–29
in digital world, 8–9
evolution of information in marketplace, 17–19
information in Digital Age, 19–20
and Internet, 3
literature, 169–170
manager, 66–67
professionals, 76
scholars, 8, 179
scholarship, 2, 167–168
spotlight on information, 16–20
stages of ages, 14–16
Marketing management
benefiting from Big Data in, 65–66
combining Big Data with lean start-up methodology in, 77–79
Marketing Science Institute (MSI), 3
Marketplace
information in, 17–19
phenomena, 14
revolution, 18
Marketplace of Digital Age, digital dyads in, 20–29
MasterCard, 89
Materialism theory, 178
Medical Expenditure Panel Survey, 129
Menu costs, 133
Mere-measurement effects, 131
mHealth platform, 106–107
Microsoft, 51, 88–89
Milling, 170–171
Minecraft, 184
Minimum viable product (MVP), 78
Miskol (see Missed Call Marketing (MCM))
Missed Call Marketing (MCM), 103–104
Mobile, 113–115
AR, 107, 112
attributes and related marketing advantages, 100
devices, 99, 100–101, 103
marketers, 100–101
marketing, 98, 105–106
promotions, 98, 99
retailing, 99
technologies, 105, 107
user experience, 107–108
Mobile advertising, 102–103
revenues, 41–42
strategies, 103–104
Mobile apps, 97–98, 99, 104, 105
monetization, 105–107, 112
Mobile marketing 2.0 (see also Marketing), 98
AI, 109–110
data privacy and mobile user experience, 107–108
emerging trends, 105–110
IoT, 109
key issues in mobile marketing, 106
mobile app monetization, 105–107
mobile AR, 107
mobile marketing practice, 113–116
mobile-led cross-channel effects, 104–105
personalized mobile advertising, 102–104
research agenda based on emerging trends, 111–113
research agenda based on gaps in extant literature, 110–111
review of mobile marketing research, 99–105
self-driving vehicles, 108–109
targeted mobile promotions, 100–102
wearables and other smart devices, 108
Mobile-led cross-channel effects, 99, 104–105, 111
Moderators, 162
variables, 159–161
Money-back guarantees, 163
Motivation, 48–49, 150, 151
Motorola Moto X cellphone, 25
Moveable Feast, 14, 19–20, 22
Multi-purpose AI platforms, 123
Multiplayer online battle arenas (MOBA), 28–29
National Health Interview Survey, 129
Nervous System, 182
Netflix, 2–3, 23
Network structure, 48–49
Neural Network Processor (NNP), 22–23
Non-deception, consumers’ perception of, 144
Non-proximal mobile users, 101–102
Non-retail settings, 104
Not-yet-imagined digital technology, 1
NVivo11 qualitative software program, 148
Object
archetypes, 175
notion of, 178–179
Office Max, 182
Offline retailers, 57
Omnichannel retailing, 104, 122
Online
advertising, 41–43
deception, 144
expertise, 153
interactions, 38
purchasing, 142
retailers, 182
reviews, 46–48
search, 45
services, 142
sources, 40–41
Online consumer reviews (OCR), 142, 143, 147
Online word-of-mouth (eWOM), 46
Opportunity network, 3–4
Opt-in, get customers to, 115
“Optimal experience” of psychological flow, 2
Optimism, 122
Outsourcing, 135
Paid apps, 106–107
Paperclip AI, 92
Parrot Pot, 25
Pay Pal, 51
Perceived deception
antecedents of, 148–154
consequences, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR), 142, 143, 162, 163
data analysis, 147–148
data collection and sample, 147
findings and conceptual model, 148–161
literature review, 143–146
method, 147–148
theoretical and managerial implications, 162–164
Perceived homophily, 155, 156, 163–164
Perceived riskiness of purchase, 159–160
Peripheral cues, 157
Peripheral routes of persuasion, 154–158
Personalization, 103, 115
Personalized mobile advertising, 99, 102–104, 110–111
Persuasion
central and peripheral routes of, 154–158
persuasive advertising, 42
Pet grooming, 133–134
Pew Research Center, 48
“Plant Sitter” mode, 25
Platforms, 51–52
Positive-NPV marketing program, 131
Potential negativity, 161
Practitioners, 8
Pre-Internet, 88
Price, 92
fluctuation, 133
volatility, 134
Privacy, 45–46
Product
knowledge, 151
and services, 159–160
Public policy, 92–93
Purchase involvement, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
General Data Protection Regulation (GDPR)
, 46, 107–108
General skepticism
, 146, 148, 149–150
Geoconquesting
, 101
Ghost Ads
, 71–72
Google
, 2–3, 15–16, 36, 51, 88–89, 106–107
search engine
, 51–52
Google Assistant
, 86–87
Google Play
, 108
Google Sketchup
, 170
Gothic cathedrals
, 14–15
GPS navigation
, 2–3
Hash
, 91–92
Hedonic purchase
, 161
Hilton hotels
, 93, 115
Hosts value exchange
, 88–89
Human behavior
, 8
Human computers
, 22–23
Human–human connectivity
, 14
Human–human digital dyad
, 26–29
Human–human social communication
, 27
Human–machine communication
, 25
Human–machine connectivity
, 14
Human–machine digital dyad
, 24–26
Idealism, 148–149
IKEA, 107
Illinois MakerLab, 184
In-app advertisements (IAA), 103, 106–107
In-app purchases (IAP), 106–107
In-vitro fertilization, 72
Independent companies, 163
Industrial Revolution, 14–15
Information (see also Artificial intelligence (AI))
in Digital Age, 19–20
evolution, 18
in marketplace, 17–19
products, 87
technology, 16–17, 86–87
Informative advertising, 42
Initial expectations, 146, 148–150
Innovative firms, 72–73
Instagram, 18–19
Intelligence, 90–91
Internet, 2, 17, 36
advertising, 41
algorithms, 23
expertise, 153, 154
on retail markets, 52–56
Internet of Services (IoS), 109
Internet of Things (IoT), 2–3, 98, 109, 113
Internet on buyer inputs, 44–45
Big Data and privacy, 45–46
buyer search, 44–45
user generated content, 46–51
Involvement, 151
iPhone (Apple), 2–3, 15–16, 17
Islamic Golden Age, 14–15
“Jailbreak”, 25
Journal of Marketing (JM), 3
Kiosks, 105
Knowledge, 151, 153
KONE, 109
Laser cutters, 179
Lathing, 170–171
Lean start-up methodology, combining Big Data with, 77–79
and communication, 79
and confidence, 79
and confirmations, 77–78
and control, 78
Learning setting, 66
Legacy firms, 64
Leverage-salience theory, 131
Line steepening, 73
Line tightening, 73
Location targeting leverages, 101
Logistic regression, 40
Low attention spans and distraction of Smartphone use, 126
Machine learning (see also Artificial intelligence (AI)), 23–24
algorithms, 8–9
methods, 39–40
models, 109–110
Machine–machine communication, 24
Machine–machine connectivity, 14
Machine–machine digital dyad, 21–24
Machine–machine dyad, 20–21
MakerBot, 170, 171, 174–175
Manufacturer Recommended Price Range (MSRP), 135
Market, 18, 88
complexity, 90
disruptions, 1
Marketers, 1, 105, 122, 127, 135
Marketing (see also Mobile marketing 2.0)
analytics, 64, 65
applications, 38–39
and consumer behavior, 4
digital dyads in marketplace of digital age, 20–29
in digital world, 8–9
evolution of information in marketplace, 17–19
information in Digital Age, 19–20
and Internet, 3
literature, 169–170
manager, 66–67
professionals, 76
scholars, 8, 179
scholarship, 2, 167–168
spotlight on information, 16–20
stages of ages, 14–16
Marketing management
benefiting from Big Data in, 65–66
combining Big Data with lean start-up methodology in, 77–79
Marketing Science Institute (MSI), 3
Marketplace
information in, 17–19
phenomena, 14
revolution, 18
Marketplace of Digital Age, digital dyads in, 20–29
MasterCard, 89
Materialism theory, 178
Medical Expenditure Panel Survey, 129
Menu costs, 133
Mere-measurement effects, 131
mHealth platform, 106–107
Microsoft, 51, 88–89
Milling, 170–171
Minecraft, 184
Minimum viable product (MVP), 78
Miskol (see Missed Call Marketing (MCM))
Missed Call Marketing (MCM), 103–104
Mobile, 113–115
AR, 107, 112
attributes and related marketing advantages, 100
devices, 99, 100–101, 103
marketers, 100–101
marketing, 98, 105–106
promotions, 98, 99
retailing, 99
technologies, 105, 107
user experience, 107–108
Mobile advertising, 102–103
revenues, 41–42
strategies, 103–104
Mobile apps, 97–98, 99, 104, 105
monetization, 105–107, 112
Mobile marketing 2.0 (see also Marketing), 98
AI, 109–110
data privacy and mobile user experience, 107–108
emerging trends, 105–110
IoT, 109
key issues in mobile marketing, 106
mobile app monetization, 105–107
mobile AR, 107
mobile marketing practice, 113–116
mobile-led cross-channel effects, 104–105
personalized mobile advertising, 102–104
research agenda based on emerging trends, 111–113
research agenda based on gaps in extant literature, 110–111
review of mobile marketing research, 99–105
self-driving vehicles, 108–109
targeted mobile promotions, 100–102
wearables and other smart devices, 108
Mobile-led cross-channel effects, 99, 104–105, 111
Moderators, 162
variables, 159–161
Money-back guarantees, 163
Motivation, 48–49, 150, 151
Motorola Moto X cellphone, 25
Moveable Feast, 14, 19–20, 22
Multi-purpose AI platforms, 123
Multiplayer online battle arenas (MOBA), 28–29
National Health Interview Survey, 129
Nervous System, 182
Netflix, 2–3, 23
Network structure, 48–49
Neural Network Processor (NNP), 22–23
Non-deception, consumers’ perception of, 144
Non-proximal mobile users, 101–102
Non-retail settings, 104
Not-yet-imagined digital technology, 1
NVivo11 qualitative software program, 148
Object
archetypes, 175
notion of, 178–179
Office Max, 182
Offline retailers, 57
Omnichannel retailing, 104, 122
Online
advertising, 41–43
deception, 144
expertise, 153
interactions, 38
purchasing, 142
retailers, 182
reviews, 46–48
search, 45
services, 142
sources, 40–41
Online consumer reviews (OCR), 142, 143, 147
Online word-of-mouth (eWOM), 46
Opportunity network, 3–4
Opt-in, get customers to, 115
“Optimal experience” of psychological flow, 2
Optimism, 122
Outsourcing, 135
Paid apps, 106–107
Paperclip AI, 92
Parrot Pot, 25
Pay Pal, 51
Perceived deception
antecedents of, 148–154
consequences, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR), 142, 143, 162, 163
data analysis, 147–148
data collection and sample, 147
findings and conceptual model, 148–161
literature review, 143–146
method, 147–148
theoretical and managerial implications, 162–164
Perceived homophily, 155, 156, 163–164
Perceived riskiness of purchase, 159–160
Peripheral cues, 157
Peripheral routes of persuasion, 154–158
Personalization, 103, 115
Personalized mobile advertising, 99, 102–104, 110–111
Persuasion
central and peripheral routes of, 154–158
persuasive advertising, 42
Pet grooming, 133–134
Pew Research Center, 48
“Plant Sitter” mode, 25
Platforms, 51–52
Positive-NPV marketing program, 131
Potential negativity, 161
Practitioners, 8
Pre-Internet, 88
Price, 92
fluctuation, 133
volatility, 134
Privacy, 45–46
Product
knowledge, 151
and services, 159–160
Public policy, 92–93
Purchase involvement, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
Idealism
, 148–149
IKEA
, 107
Illinois MakerLab
, 184
In-app advertisements (IAA)
, 103, 106–107
In-app purchases (IAP)
, 106–107
In-vitro fertilization
, 72
Independent companies
, 163
Industrial Revolution
, 14–15
Information (see also Artificial intelligence (AI))
in Digital Age
, 19–20
evolution
, 18
in marketplace
, 17–19
products
, 87
technology
, 16–17, 86–87
Informative advertising
, 42
Initial expectations
, 146, 148–150
Innovative firms
, 72–73
Instagram
, 18–19
Intelligence
, 90–91
Internet
, 2, 17, 36
advertising
, 41
algorithms
, 23
expertise
, 153, 154
on retail markets
, 52–56
Internet of Services (IoS)
, 109
Internet of Things (IoT)
, 2–3, 98, 109, 113
Internet on buyer inputs
, 44–45
Big Data and privacy
, 45–46
buyer search
, 44–45
user generated content
, 46–51
Involvement
, 151
iPhone (Apple)
, 2–3, 15–16, 17
Islamic Golden Age
, 14–15
“Jailbreak”
, 25
Journal of Marketing (JM)
, 3
Kiosks, 105
Knowledge, 151, 153
KONE, 109
Laser cutters, 179
Lathing, 170–171
Lean start-up methodology, combining Big Data with, 77–79
and communication, 79
and confidence, 79
and confirmations, 77–78
and control, 78
Learning setting, 66
Legacy firms, 64
Leverage-salience theory, 131
Line steepening, 73
Line tightening, 73
Location targeting leverages, 101
Logistic regression, 40
Low attention spans and distraction of Smartphone use, 126
Machine learning (see also Artificial intelligence (AI)), 23–24
algorithms, 8–9
methods, 39–40
models, 109–110
Machine–machine communication, 24
Machine–machine connectivity, 14
Machine–machine digital dyad, 21–24
Machine–machine dyad, 20–21
MakerBot, 170, 171, 174–175
Manufacturer Recommended Price Range (MSRP), 135
Market, 18, 88
complexity, 90
disruptions, 1
Marketers, 1, 105, 122, 127, 135
Marketing (see also Mobile marketing 2.0)
analytics, 64, 65
applications, 38–39
and consumer behavior, 4
digital dyads in marketplace of digital age, 20–29
in digital world, 8–9
evolution of information in marketplace, 17–19
information in Digital Age, 19–20
and Internet, 3
literature, 169–170
manager, 66–67
professionals, 76
scholars, 8, 179
scholarship, 2, 167–168
spotlight on information, 16–20
stages of ages, 14–16
Marketing management
benefiting from Big Data in, 65–66
combining Big Data with lean start-up methodology in, 77–79
Marketing Science Institute (MSI), 3
Marketplace
information in, 17–19
phenomena, 14
revolution, 18
Marketplace of Digital Age, digital dyads in, 20–29
MasterCard, 89
Materialism theory, 178
Medical Expenditure Panel Survey, 129
Menu costs, 133
Mere-measurement effects, 131
mHealth platform, 106–107
Microsoft, 51, 88–89
Milling, 170–171
Minecraft, 184
Minimum viable product (MVP), 78
Miskol (see Missed Call Marketing (MCM))
Missed Call Marketing (MCM), 103–104
Mobile, 113–115
AR, 107, 112
attributes and related marketing advantages, 100
devices, 99, 100–101, 103
marketers, 100–101
marketing, 98, 105–106
promotions, 98, 99
retailing, 99
technologies, 105, 107
user experience, 107–108
Mobile advertising, 102–103
revenues, 41–42
strategies, 103–104
Mobile apps, 97–98, 99, 104, 105
monetization, 105–107, 112
Mobile marketing 2.0 (see also Marketing), 98
AI, 109–110
data privacy and mobile user experience, 107–108
emerging trends, 105–110
IoT, 109
key issues in mobile marketing, 106
mobile app monetization, 105–107
mobile AR, 107
mobile marketing practice, 113–116
mobile-led cross-channel effects, 104–105
personalized mobile advertising, 102–104
research agenda based on emerging trends, 111–113
research agenda based on gaps in extant literature, 110–111
review of mobile marketing research, 99–105
self-driving vehicles, 108–109
targeted mobile promotions, 100–102
wearables and other smart devices, 108
Mobile-led cross-channel effects, 99, 104–105, 111
Moderators, 162
variables, 159–161
Money-back guarantees, 163
Motivation, 48–49, 150, 151
Motorola Moto X cellphone, 25
Moveable Feast, 14, 19–20, 22
Multi-purpose AI platforms, 123
Multiplayer online battle arenas (MOBA), 28–29
National Health Interview Survey, 129
Nervous System, 182
Netflix, 2–3, 23
Network structure, 48–49
Neural Network Processor (NNP), 22–23
Non-deception, consumers’ perception of, 144
Non-proximal mobile users, 101–102
Non-retail settings, 104
Not-yet-imagined digital technology, 1
NVivo11 qualitative software program, 148
Object
archetypes, 175
notion of, 178–179
Office Max, 182
Offline retailers, 57
Omnichannel retailing, 104, 122
Online
advertising, 41–43
deception, 144
expertise, 153
interactions, 38
purchasing, 142
retailers, 182
reviews, 46–48
search, 45
services, 142
sources, 40–41
Online consumer reviews (OCR), 142, 143, 147
Online word-of-mouth (eWOM), 46
Opportunity network, 3–4
Opt-in, get customers to, 115
“Optimal experience” of psychological flow, 2
Optimism, 122
Outsourcing, 135
Paid apps, 106–107
Paperclip AI, 92
Parrot Pot, 25
Pay Pal, 51
Perceived deception
antecedents of, 148–154
consequences, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR), 142, 143, 162, 163
data analysis, 147–148
data collection and sample, 147
findings and conceptual model, 148–161
literature review, 143–146
method, 147–148
theoretical and managerial implications, 162–164
Perceived homophily, 155, 156, 163–164
Perceived riskiness of purchase, 159–160
Peripheral cues, 157
Peripheral routes of persuasion, 154–158
Personalization, 103, 115
Personalized mobile advertising, 99, 102–104, 110–111
Persuasion
central and peripheral routes of, 154–158
persuasive advertising, 42
Pet grooming, 133–134
Pew Research Center, 48
“Plant Sitter” mode, 25
Platforms, 51–52
Positive-NPV marketing program, 131
Potential negativity, 161
Practitioners, 8
Pre-Internet, 88
Price, 92
fluctuation, 133
volatility, 134
Privacy, 45–46
Product
knowledge, 151
and services, 159–160
Public policy, 92–93
Purchase involvement, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
Kiosks
, 105
Knowledge
, 151, 153
KONE
, 109
Laser cutters
, 179
Lathing
, 170–171
Lean start-up methodology, combining Big Data with
, 77–79
and communication
, 79
and confidence
, 79
and confirmations
, 77–78
and control
, 78
Learning setting
, 66
Legacy firms
, 64
Leverage-salience theory
, 131
Line steepening
, 73
Line tightening
, 73
Location targeting leverages
, 101
Logistic regression
, 40
Low attention spans and distraction of Smartphone use
, 126
Machine learning (see also Artificial intelligence (AI)), 23–24
algorithms, 8–9
methods, 39–40
models, 109–110
Machine–machine communication, 24
Machine–machine connectivity, 14
Machine–machine digital dyad, 21–24
Machine–machine dyad, 20–21
MakerBot, 170, 171, 174–175
Manufacturer Recommended Price Range (MSRP), 135
Market, 18, 88
complexity, 90
disruptions, 1
Marketers, 1, 105, 122, 127, 135
Marketing (see also Mobile marketing 2.0)
analytics, 64, 65
applications, 38–39
and consumer behavior, 4
digital dyads in marketplace of digital age, 20–29
in digital world, 8–9
evolution of information in marketplace, 17–19
information in Digital Age, 19–20
and Internet, 3
literature, 169–170
manager, 66–67
professionals, 76
scholars, 8, 179
scholarship, 2, 167–168
spotlight on information, 16–20
stages of ages, 14–16
Marketing management
benefiting from Big Data in, 65–66
combining Big Data with lean start-up methodology in, 77–79
Marketing Science Institute (MSI), 3
Marketplace
information in, 17–19
phenomena, 14
revolution, 18
Marketplace of Digital Age, digital dyads in, 20–29
MasterCard, 89
Materialism theory, 178
Medical Expenditure Panel Survey, 129
Menu costs, 133
Mere-measurement effects, 131
mHealth platform, 106–107
Microsoft, 51, 88–89
Milling, 170–171
Minecraft, 184
Minimum viable product (MVP), 78
Miskol (see Missed Call Marketing (MCM))
Missed Call Marketing (MCM), 103–104
Mobile, 113–115
AR, 107, 112
attributes and related marketing advantages, 100
devices, 99, 100–101, 103
marketers, 100–101
marketing, 98, 105–106
promotions, 98, 99
retailing, 99
technologies, 105, 107
user experience, 107–108
Mobile advertising, 102–103
revenues, 41–42
strategies, 103–104
Mobile apps, 97–98, 99, 104, 105
monetization, 105–107, 112
Mobile marketing 2.0 (see also Marketing), 98
AI, 109–110
data privacy and mobile user experience, 107–108
emerging trends, 105–110
IoT, 109
key issues in mobile marketing, 106
mobile app monetization, 105–107
mobile AR, 107
mobile marketing practice, 113–116
mobile-led cross-channel effects, 104–105
personalized mobile advertising, 102–104
research agenda based on emerging trends, 111–113
research agenda based on gaps in extant literature, 110–111
review of mobile marketing research, 99–105
self-driving vehicles, 108–109
targeted mobile promotions, 100–102
wearables and other smart devices, 108
Mobile-led cross-channel effects, 99, 104–105, 111
Moderators, 162
variables, 159–161
Money-back guarantees, 163
Motivation, 48–49, 150, 151
Motorola Moto X cellphone, 25
Moveable Feast, 14, 19–20, 22
Multi-purpose AI platforms, 123
Multiplayer online battle arenas (MOBA), 28–29
National Health Interview Survey, 129
Nervous System, 182
Netflix, 2–3, 23
Network structure, 48–49
Neural Network Processor (NNP), 22–23
Non-deception, consumers’ perception of, 144
Non-proximal mobile users, 101–102
Non-retail settings, 104
Not-yet-imagined digital technology, 1
NVivo11 qualitative software program, 148
Object
archetypes, 175
notion of, 178–179
Office Max, 182
Offline retailers, 57
Omnichannel retailing, 104, 122
Online
advertising, 41–43
deception, 144
expertise, 153
interactions, 38
purchasing, 142
retailers, 182
reviews, 46–48
search, 45
services, 142
sources, 40–41
Online consumer reviews (OCR), 142, 143, 147
Online word-of-mouth (eWOM), 46
Opportunity network, 3–4
Opt-in, get customers to, 115
“Optimal experience” of psychological flow, 2
Optimism, 122
Outsourcing, 135
Paid apps, 106–107
Paperclip AI, 92
Parrot Pot, 25
Pay Pal, 51
Perceived deception
antecedents of, 148–154
consequences, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR), 142, 143, 162, 163
data analysis, 147–148
data collection and sample, 147
findings and conceptual model, 148–161
literature review, 143–146
method, 147–148
theoretical and managerial implications, 162–164
Perceived homophily, 155, 156, 163–164
Perceived riskiness of purchase, 159–160
Peripheral cues, 157
Peripheral routes of persuasion, 154–158
Personalization, 103, 115
Personalized mobile advertising, 99, 102–104, 110–111
Persuasion
central and peripheral routes of, 154–158
persuasive advertising, 42
Pet grooming, 133–134
Pew Research Center, 48
“Plant Sitter” mode, 25
Platforms, 51–52
Positive-NPV marketing program, 131
Potential negativity, 161
Practitioners, 8
Pre-Internet, 88
Price, 92
fluctuation, 133
volatility, 134
Privacy, 45–46
Product
knowledge, 151
and services, 159–160
Public policy, 92–93
Purchase involvement, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
Machine learning (see also Artificial intelligence (AI))
, 23–24
algorithms
, 8–9
methods
, 39–40
models
, 109–110
Machine–machine communication
, 24
Machine–machine connectivity
, 14
Machine–machine digital dyad
, 21–24
Machine–machine dyad
, 20–21
MakerBot
, 170, 171, 174–175
Manufacturer Recommended Price Range (MSRP)
, 135
Market
, 18, 88
complexity
, 90
disruptions
, 1
Marketers
, 1, 105, 122, 127, 135
Marketing (see also Mobile marketing 2.0)
analytics
, 64, 65
applications
, 38–39
and consumer behavior
, 4
digital dyads in marketplace of digital age
, 20–29
in digital world
, 8–9
evolution of information in marketplace
, 17–19
information in Digital Age
, 19–20
and Internet
, 3
literature
, 169–170
manager
, 66–67
professionals
, 76
scholars
, 8, 179
scholarship
, 2, 167–168
spotlight on information
, 16–20
stages of ages
, 14–16
Marketing management
benefiting from Big Data in
, 65–66
combining Big Data with lean start-up methodology in
, 77–79
Marketing Science Institute (MSI)
, 3
Marketplace
information in
, 17–19
phenomena
, 14
revolution
, 18
Marketplace of Digital Age, digital dyads in
, 20–29
MasterCard
, 89
Materialism theory
, 178
Medical Expenditure Panel Survey
, 129
Menu costs
, 133
Mere-measurement effects
, 131
mHealth platform
, 106–107
Microsoft
, 51, 88–89
Milling
, 170–171
Minecraft
, 184
Minimum viable product (MVP)
, 78
Miskol (see Missed Call Marketing (MCM))
Missed Call Marketing (MCM)
, 103–104
Mobile
, 113–115
AR
, 107, 112
attributes and related marketing advantages
, 100
devices
, 99, 100–101, 103
marketers
, 100–101
marketing
, 98, 105–106
promotions
, 98, 99
retailing
, 99
technologies
, 105, 107
user experience
, 107–108
Mobile advertising
, 102–103
revenues
, 41–42
strategies
, 103–104
Mobile apps
, 97–98, 99, 104, 105
monetization
, 105–107, 112
Mobile marketing 2.0 (see also Marketing)
, 98
AI
, 109–110
data privacy and mobile user experience
, 107–108
emerging trends
, 105–110
IoT
, 109
key issues in mobile marketing
, 106
mobile app monetization
, 105–107
mobile AR
, 107
mobile marketing practice
, 113–116
mobile-led cross-channel effects
, 104–105
personalized mobile advertising
, 102–104
research agenda based on emerging trends
, 111–113
research agenda based on gaps in extant literature
, 110–111
review of mobile marketing research
, 99–105
self-driving vehicles
, 108–109
targeted mobile promotions
, 100–102
wearables and other smart devices
, 108
Mobile-led cross-channel effects
, 99, 104–105, 111
Moderators
, 162
variables
, 159–161
Money-back guarantees
, 163
Motivation
, 48–49, 150, 151
Motorola Moto X cellphone
, 25
Moveable Feast
, 14, 19–20, 22
Multi-purpose AI platforms
, 123
Multiplayer online battle arenas (MOBA)
, 28–29
National Health Interview Survey
, 129
Nervous System
, 182
Netflix
, 2–3, 23
Network structure
, 48–49
Neural Network Processor (NNP)
, 22–23
Non-deception, consumers’ perception of
, 144
Non-proximal mobile users
, 101–102
Non-retail settings
, 104
Not-yet-imagined digital technology
, 1
NVivo11 qualitative software program
, 148
Object
archetypes, 175
notion of, 178–179
Office Max, 182
Offline retailers, 57
Omnichannel retailing, 104, 122
Online
advertising, 41–43
deception, 144
expertise, 153
interactions, 38
purchasing, 142
retailers, 182
reviews, 46–48
search, 45
services, 142
sources, 40–41
Online consumer reviews (OCR), 142, 143, 147
Online word-of-mouth (eWOM), 46
Opportunity network, 3–4
Opt-in, get customers to, 115
“Optimal experience” of psychological flow, 2
Optimism, 122
Outsourcing, 135
Paid apps, 106–107
Paperclip AI, 92
Parrot Pot, 25
Pay Pal, 51
Perceived deception
antecedents of, 148–154
consequences, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR), 142, 143, 162, 163
data analysis, 147–148
data collection and sample, 147
findings and conceptual model, 148–161
literature review, 143–146
method, 147–148
theoretical and managerial implications, 162–164
Perceived homophily, 155, 156, 163–164
Perceived riskiness of purchase, 159–160
Peripheral cues, 157
Peripheral routes of persuasion, 154–158
Personalization, 103, 115
Personalized mobile advertising, 99, 102–104, 110–111
Persuasion
central and peripheral routes of, 154–158
persuasive advertising, 42
Pet grooming, 133–134
Pew Research Center, 48
“Plant Sitter” mode, 25
Platforms, 51–52
Positive-NPV marketing program, 131
Potential negativity, 161
Practitioners, 8
Pre-Internet, 88
Price, 92
fluctuation, 133
volatility, 134
Privacy, 45–46
Product
knowledge, 151
and services, 159–160
Public policy, 92–93
Purchase involvement, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
Object
archetypes
, 175
notion of
, 178–179
Office Max
, 182
Offline retailers
, 57
Omnichannel retailing
, 104, 122
Online
advertising
, 41–43
deception
, 144
expertise
, 153
interactions
, 38
purchasing
, 142
retailers
, 182
reviews
, 46–48
search
, 45
services
, 142
sources
, 40–41
Online consumer reviews (OCR)
, 142, 143, 147
Online word-of-mouth (eWOM)
, 46
Opportunity network
, 3–4
Opt-in, get customers to
, 115
“Optimal experience” of psychological flow
, 2
Optimism
, 122
Outsourcing
, 135
Paid apps
, 106–107
Paperclip AI
, 92
Parrot Pot
, 25
Pay Pal
, 51
Perceived deception
antecedents of
, 148–154
consequences
, 158–159
Perceived Deception in Online Consumer Reviews (PDOCR)
, 142, 143, 162, 163
data analysis
, 147–148
data collection and sample
, 147
findings and conceptual model
, 148–161
literature review
, 143–146
method
, 147–148
theoretical and managerial implications
, 162–164
Perceived homophily
, 155, 156, 163–164
Perceived riskiness of purchase
, 159–160
Peripheral cues
, 157
Peripheral routes of persuasion
, 154–158
Personalization
, 103, 115
Personalized mobile advertising
, 99, 102–104, 110–111
Persuasion
central and peripheral routes of
, 154–158
persuasive advertising
, 42
Pet grooming
, 133–134
Pew Research Center
, 48
“Plant Sitter” mode
, 25
Platforms
, 51–52
Positive-NPV marketing program
, 131
Potential negativity
, 161
Practitioners
, 8
Pre-Internet
, 88
Price
, 92
fluctuation
, 133
volatility
, 134
Privacy
, 45–46
Product
knowledge
, 151
and services
, 159–160
Public policy
, 92–93
Purchase involvement
, 150–151
Rapid prototyping, 170
Re-evaluate targeting strategy, 115
Reformation, 14–15, 18–19
Renaissance, 18–19
Era, 14–15
Replacements, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project), 171, 176
Research questions (RQ), 148, 149
Resistance to using self-service technologies, 126
Response rates declining to customer surveys, 126, 128–132
consequences, 131
evidence for, 129
research opportunities, 131–132
technology-based reasons for, 129–131
Retail markets, Internet on, 52–56
Retailing research, 167–168
Retailing thought and practice, implications for, 177–184
nature of economic institutions, 180–181
notion of objects, 178–179
role of consumers, 179–180
Retailing-related issues, 180
Review
consistency, 155, 156
number of, 154–155
platform, 160–161
quantity, 155
Revolutionary technologies, 15–16
Risk intelligence, 76
Robotics, 4, 91
Savvy marketers, 122
Selective laser sintering, 170
Self-driving
technologies, 6
vehicles, 108–109
Self-esteem, 28
Self-manufactured objects, typology of, 174–177
Self-manufacturers, 169–170, 180
Self-manufacturing, 169–174
3D printing, 170–171
3D printing literature, 171–174
Self-protecting behaviors, 158, 162
Self-service technology, 86–87, 93
by consumers, 122
Seller inputs, impact on, 38–41
research needs, 40–41
Seller outputs, impact on, 41–43
shares of U.S. advertising spending by medium, 41
U.S. online advertising revenues, 42
Service Dominant Logic theory (SDL theory), 178
Shapeways.com, 170, 182
Shopping
AR View, 107
IoT and, 109
journey archetypes, 133–134
mobile apps offer, 105–106
mobile influences, 102
Short messaging service (SMS), 103
Showrooming, 57
practices, 126
Silicon Valley, 15–16
Simultaneous platform response functions, 89
Siri (Apple), 86–87
Smart devices, 98, 108, 112
Smart speakers, 109–110
Smarter mobile technologies, 105
Smartphone, 13–14, 98, 103
virtual assistants, 109–110
Social
manufacturing ecosystem, 174
networking sites, 27–28
networks, 48–49
production, 180–181
roles and interactions, 48–49
Social media, 2–3, 28, 37, 48–50
advertising, 57
Social Science Citation Index, 46–47
Software, 3–4, 85–87
agency, 92
autonomy, 91–92
complexity, 88–90
intelligence, 90–91
product, 87–92
regulation and public policy, 93
research directions, 92–93
research on company strategy, 92–93
research on consumer behavior, 93
Solidworks, 170
Solutions, 175, 176, 183–184
Staples, 182
Statistical analyses, 68–69
Statistical literacy, 76
Stereo-lithography, 170
Substitutes, 175, 176, 182–183
Super Bowl (2019), 6–7
Survey-based research, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
Rapid prototyping
, 170
Re-evaluate targeting strategy
, 115
Reformation
, 14–15, 18–19
Renaissance
, 18–19
Era
, 14–15
Replacements
, 175, 176, 183
Replicator Rapid Prototype project (RepRap Prototype project)
, 171, 176
Research questions (RQ)
, 148, 149
Resistance to using self-service technologies
, 126
Response rates declining to customer surveys
, 126, 128–132
consequences
, 131
evidence for
, 129
research opportunities
, 131–132
technology-based reasons for
, 129–131
Retail markets, Internet on
, 52–56
Retailing research
, 167–168
Retailing thought and practice, implications for
, 177–184
nature of economic institutions
, 180–181
notion of objects
, 178–179
role of consumers
, 179–180
Retailing-related issues
, 180
Review
consistency
, 155, 156
number of
, 154–155
platform
, 160–161
quantity
, 155
Revolutionary technologies
, 15–16
Risk intelligence
, 76
Robotics
, 4, 91
Savvy marketers
, 122
Selective laser sintering
, 170
Self-driving
technologies
, 6
vehicles
, 108–109
Self-esteem
, 28
Self-manufactured objects, typology of
, 174–177
Self-manufacturers
, 169–170, 180
Self-manufacturing
, 169–174
3D printing
, 170–171
3D printing literature
, 171–174
Self-protecting behaviors
, 158, 162
Self-service technology
, 86–87, 93
by consumers
, 122
Seller inputs, impact on
, 38–41
research needs
, 40–41
Seller outputs, impact on
, 41–43
shares of U.S. advertising spending by medium
, 41
U.S. online advertising revenues
, 42
Service Dominant Logic theory (SDL theory)
, 178
Shapeways.com
, 170, 182
Shopping
AR View
, 107
IoT and
, 109
journey archetypes
, 133–134
mobile apps offer
, 105–106
mobile influences
, 102
Short messaging service (SMS)
, 103
Showrooming
, 57
practices
, 126
Silicon Valley
, 15–16
Simultaneous platform response functions
, 89
Siri (Apple)
, 86–87
Smart devices
, 98, 108, 112
Smart speakers
, 109–110
Smarter mobile technologies
, 105
Smartphone
, 13–14, 98, 103
virtual assistants
, 109–110
Social
manufacturing ecosystem
, 174
networking sites
, 27–28
networks
, 48–49
production
, 180–181
roles and interactions
, 48–49
Social media
, 2–3, 28, 37, 48–50
advertising
, 57
Social Science Citation Index
, 46–47
Software
, 3–4, 85–87
agency
, 92
autonomy
, 91–92
complexity
, 88–90
intelligence
, 90–91
product
, 87–92
regulation and public policy
, 93
research directions
, 92–93
research on company strategy
, 92–93
research on consumer behavior
, 93
Solidworks
, 170
Solutions
, 175, 176, 183–184
Staples
, 182
Statistical analyses
, 68–69
Statistical literacy
, 76
Stereo-lithography
, 170
Substitutes
, 175, 176, 182–183
Super Bowl (2019)
, 6–7
Survey-based research
, 129
Tablets, 103
Tangible goods, 86
Target setting, 66
Targeted mobile promotions, 99–102, 110
Tech-expert, 152
Technology, 122
orientation, 123
technology-enabled dynamic pricing methods, 134
technology-enabled retail fraud by consumers, 126
Technology Acceptance Model, 7
Teenage Engineering, 183
Telecom, 3–4
Telecommunicators, 18
Temporal targeting, 101–102
Tencent, 88–89
Text mining methods, 40
Thank God It’s Friday (TGIF), 110
Thingiverse.com, 168, 174–175
3D printers, 168, 170, 179
3D printing, 170–171, 183
of existing objects and new creations, 172–173
literature, 169, 171–174
technology, 4
threat and opportunity for retailers, 173–174
Time series analysis, 50
Tinkercad, 170
Traditional non-platform firms, 89
Transaction cost theory, 180
Transformation, 76
Transparent presentation of statistical insights, 74–76
Travelocity, 3–4, 38
TripAdvisor, 142
Trust, 93
TrustedShops.com, 163
Turing Machine, 86
Twitter, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”, 6
Uber, 93
Ultimaker, 170, 171
University of Illinois, 184
US Ninth Circuit, 93
User generated content, 46–51
online reviews, 46–48
research, 48, 50–51
social media, 48–50
Utilitarian purchase, 161
Utility function, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
Tablets
, 103
Tangible goods
, 86
Target setting
, 66
Targeted mobile promotions
, 99–102, 110
Tech-expert
, 152
Technology
, 122
orientation
, 123
technology-enabled dynamic pricing methods
, 134
technology-enabled retail fraud by consumers
, 126
Technology Acceptance Model
, 7
Teenage Engineering
, 183
Telecom
, 3–4
Telecommunicators
, 18
Temporal targeting
, 101–102
Tencent
, 88–89
Text mining methods
, 40
Thank God It’s Friday (TGIF)
, 110
Thingiverse.com
, 168, 174–175
3D printers
, 168, 170, 179
3D printing
, 170–171, 183
of existing objects and new creations
, 172–173
literature
, 169, 171–174
technology
, 4
threat and opportunity for retailers
, 173–174
Time series analysis
, 50
Tinkercad
, 170
Traditional non-platform firms
, 89
Transaction cost theory
, 180
Transformation
, 76
Transparent presentation of statistical insights
, 74–76
Travelocity
, 3–4, 38
TripAdvisor
, 142
Trust
, 93
TrustedShops.com
, 163
Turing Machine
, 86
Twitter
, 18–19, 39–40
U.S. adults on “Automation in Everyday Life”
, 6
Uber
, 93
Ultimaker
, 170, 171
University of Illinois
, 184
US Ninth Circuit
, 93
User generated content
, 46–51
online reviews
, 46–48
research
, 48, 50–51
social media
, 48–50
Utilitarian purchase
, 161
Utility function
, 92
Value exchange, 86, 88
Virtual reality (VR), 99
Virtual social interaction, 18–19
Visualizations, 74, 76
Voice-based devices, 108
Volume, velocity, and variety (3Vs), 64, 65, 67–68
of Big Data, 69
Volume, velocity, variety and veracity (4Vs), 63–64, 65, 67, 68
W-Fi, 2–3, 36
Wearable devices, 99, 108, 112
Web browser, 36
Webrooming practices, 126
Windows, 51
Word of mouth (WOM), 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
Value exchange
, 86, 88
Virtual reality (VR)
, 99
Virtual social interaction
, 18–19
Visualizations
, 74, 76
Voice-based devices
, 108
Volume, velocity, and variety (3Vs)
, 64, 65, 67–68
of Big Data
, 69
Volume, velocity, variety and veracity (4Vs)
, 63–64, 65, 67, 68
W-Fi
, 2–3, 36
Wearable devices
, 99, 108, 112
Web browser
, 36
Webrooming practices
, 126
Windows
, 51
Word of mouth (WOM)
, 27–28
Yahoo, 3–4
Zero marginal costs of software businesses, 92
ZocDoc app, 108
Yahoo
, 3–4
Zero marginal costs of software businesses
, 92
ZocDoc app
, 108
- Prelims
- Transitioning to a Digital World
- Marketing in the Digital Age: A Moveable Feast of Information
- The Impact of Digital Innovations on Marketing and Consumers
- Big and Lean is Beautiful: A Conceptual Framework for Data-based Learning in Marketing Management
- The Growing Importance of Software as a Driver of Value Exchange
- Mobile Marketing 2.0: State of the Art and Research Agenda
- All’s Not Well on the Marketing Frontlines: Understanding the Challenges of Adverse Technology–Consumer Interactions
- Perceived Deception in Online Consumer Reviews: Antecedents, Consequences, and Moderators
- Self-manufacturing via 3D Printing: Implications for Retailing Thought and Practice
- Previous Volume Contents
- Index