Index
2019; Emerald Publishing Limited; Linguagem: Inglês
10.1108/s1548-643520190000016022
ISSN1944-7035
Tópico(s)Impact of AI and Big Data on Business and Society
ResumoCitation (2019), "Index", Marketing in a Digital World (Review of Marketing Research, Vol. 16), Emerald Publishing Limited, Bingley, 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 Book Chapters 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
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