Future research agenda
| Themes | Research questions |
|---|---|
| Consumers in the era of PA* | |
| Consumer behaviour | What benefits/sacrifices do consumer experience with PA? What factors influence these benefits/sacrifices? |
| What is the impact of PA on consumer behaviour, such as buying, loyalty, trust, engagement, word of mouth (WOM), user-generated content (UGC), or satisfaction? | |
| What emotions (e.g. happiness, disgust, surprise, anger, shame, or excitement) does PA evoke among consumers? Are there mixed (ambivalent) emotions? How do the emotions affect the behaviour? How do cognitions, emotions, and behaviours interact compared to traditional ads? | |
| Under what circumstances will consumers respond favourably to PA in the long term? | |
| When do consumers perceive problematic clashes between the context (e.g. website or mobile app content) and PA? | |
| What kinds of different “forced exposures” are there? What are their significance and consumer reactions? | |
| Are there different consumer reactions to the use of first-, second-, and third-party data use for PA? | |
| Are there differences between generations/cultures and their attitudes towards PA? What can explain the differences? | |
| What kinds of PA do the consumers find annoying/intrusive? | |
| What kinds of PA make the consumers feel vulnerable? When do they feel forced exposure? | |
| Does PA frequency make a difference? What is the relative impact and significance in different situations of multiple advertisement forms? | |
| How will consumers react to PA in new technologies and platforms such as virtual reality (VR), augmented reality (AR), wearable technologies, and robots? | |
| Consumer counter-behaviour to PA | Will consumers increase their ad blocker use if/when PA increases? Under what conditions will they do so? |
| What kinds of self-defence processing and negative evaluations can consumers engage in? | |
| What kinds of new sabotage/coping methods could be possible in addition to providing false data or creating multiple online user profiles? | |
| When and/or what types of consumers try to sabotage PA? What are the reasons for doing so? | |
| Meaning of AI | How do consumers understand AI, and what is their extent of knowledge of it? Is AI as cryptic for consumers to understand as is typically assumed? |
| What do consumers think can be done with AI today and in the future? | |
| In what ways do consumers perceive AI and related technologies to be destructive/harmful? | |
| What types of environmental impacts do consumers associate with AI? | |
| What impact do beliefs about AI have on their reactions to PA and behaviour in general? | |
| When do consumers perceive that the personalisation is problematic? E.g. when is online usage public, and are there ways that AI can detect this? | |
| Do consumers understand that personal information that they volunteered to give/gave consent to can be turned into new information about them (e.g. with AI) that they have no control over? | |
| Increasing data collection and use in society | Are people willing to proactively trade or sell their personal data to gain benefits/products? To whom? Under what circumstances? |
| In what situations and why do they volunteer/refuse to give data? What factors and incidents have significant impact on the attitudes? | |
| What is the attitude among consumers and citizens towards the increasing amount of data being collected about and from them? In what situations are they exceptionally positive/exceptionally negative? | |
| How do consumers and citizens feel about datafication? What emotions does it evoke? Do they have fears? | |
| How do the attitudes change over time as datafication increases (longitudinal approach)? | |
| How do consumers and citizens think about data being stolen, bought, hacked, or manipulated? What are the effects on their behaviour as a result? | |
| How familiar are consumers and citizens with their rights and how data about them is collected, stored, and used? | |
| Privacy and risk beliefs | In what ways do consumers (try to) protect their personal information by restricting or limiting others from accessing it? What do consumers do when their privacy has been violated? |
| What makes consumers suspect misuse of their data? What kind of websites do consumers suspect misuse their data? | |
| How do consumers perceive the “personalisation-privacy paradox” in different situations? | |
| In what situations and for what services do consumers care exceptionally more/less about privacy? | |
| How do consumers think about the processing of data about them to generate new information and knowledge? | |
| What data types (e.g. personal information, behavioural data, location data) in general and subtypes (e.g. sexual orientation, race, health data) do consumers feel comfortable giving? | |
| How do consumers feel about predictions about them that are made using AI predictive analysis? When are they more/less comfortable with them? | |
| AI-driven advertising and PA for retailers | |
| Strategies | What is the suitability of PA for different service types and for different products? |
| How does PA/AI use interact with different brand personalities (i.e. are there retailer brands that benefit more/less from PA/AI use)? | |
| How can PA/AI be aligned with brand strategies? | |
| What are the alternative methods of PA in specific and personalisation in general if legislation prevents retailers from collecting data across channels? What are the consequences of the implementation of the General Data Protection Regulation (GDPR)? | |
| What kind of potential do new technologies and platform such as VR, AR, wearable technologies, and robots offer in terms of PA and AI use? | |
| Impacts | How does the use of PA affect retailer–customer relationships in the short/long term? |
| How does customer trust affect the efficiency and effectiveness of PA in retailing? | |
| How does retailer trust interact with PA ad relevance? In particular, does consumer trust towards the retailer ameliorate the possibly negative impacts of ad relevance for consumers with high data risk profile? | |
| What new measures should/could advertisers use to determine the impact of PA? | |
| Under what circumstances can it be a competitive advantage for retailers to not use data and/or allow consumers to remain anonymous? | |
| Ethical issues | How should retailers consider vulnerable consumers (e.g. children, elderly) when advertising online? |
| When can and should consumer data be purchased from, sold to, or distributed among other actors? | |
| How can policy, regulation, and legislation be updated to cover consumer privacy and ethical issues when AI is used in digital advertising? | |
| How are offerings related to sensitive matters (e.g. sexuality, religion, health) conveyed in a manner that is unobtrusive? | |
| What is the role of data and privacy policies, such as consent and GDPR, and how can retailers ensure ethical PA/AI use? | |
| Who owns and can monetise the new information generated with AI? How can retailers deploy it without acting unethically? | |
| Ecosystem development | What kind of ecosystems of companies and platforms emerge for future AI-driven advertising? What media trading, content creation, business intelligence, data brokers, analytics, and data management platforms are needed? |
| How can retailers deploy systems utilising unstructured data that are increasingly available online (e.g. user-generated content related to the retailer) to predict consumer behavioural trends? | |
| How can retailers build an ecosystem to track and address consumer preferences and behaviour (e.g. through aps, payment systems)? | |
| How can retailers solve the struggles between short- and long-term goals for different ecosystem partners? | |
| How are positive financial outcomes shared among ecosystem partners (e.g. models from data sales to provisions)? | |
| How can retailers avoid a loss of power to walled gardens and emerging (large) ecosystem actors who own customer data? | |
| Themes | Research questions |
|---|---|
| Consumer behaviour | What benefits/sacrifices do consumer experience with PA? What factors influence these benefits/sacrifices? |
| What is the impact of PA on consumer behaviour, such as buying, loyalty, trust, engagement, word of mouth (WOM), user-generated content (UGC), or satisfaction? | |
| What emotions (e.g. happiness, disgust, surprise, anger, shame, or excitement) does PA evoke among consumers? Are there mixed (ambivalent) emotions? How do the emotions affect the behaviour? How do cognitions, emotions, and behaviours interact compared to traditional ads? | |
| Under what circumstances will consumers respond favourably to PA in the long term? | |
| When do consumers perceive problematic clashes between the context (e.g. website or mobile app content) and PA? | |
| What kinds of different “forced exposures” are there? What are their significance and consumer reactions? | |
| Are there different consumer reactions to the use of first-, second-, and third-party data use for PA? | |
| Are there differences between generations/cultures and their attitudes towards PA? What can explain the differences? | |
| What kinds of PA do the consumers find annoying/intrusive? | |
| What kinds of PA make the consumers feel vulnerable? When do they feel forced exposure? | |
| Does PA frequency make a difference? What is the relative impact and significance in different situations of multiple advertisement forms? | |
| How will consumers react to PA in new technologies and platforms such as virtual reality (VR), augmented reality (AR), wearable technologies, and robots? | |
| Consumer counter-behaviour to PA | Will consumers increase their ad blocker use if/when PA increases? Under what conditions will they do so? |
| What kinds of self-defence processing and negative evaluations can consumers engage in? | |
| What kinds of new sabotage/coping methods could be possible in addition to providing false data or creating multiple online user profiles? | |
| When and/or what types of consumers try to sabotage PA? What are the reasons for doing so? | |
| Meaning of AI | How do consumers understand AI, and what is their extent of knowledge of it? Is AI as cryptic for consumers to understand as is typically assumed? |
| What do consumers think can be done with AI today and in the future? | |
| In what ways do consumers perceive AI and related technologies to be destructive/harmful? | |
| What types of environmental impacts do consumers associate with AI? | |
| What impact do beliefs about AI have on their reactions to PA and behaviour in general? | |
| When do consumers perceive that the personalisation is problematic? E.g. when is online usage public, and are there ways that AI can detect this? | |
| Do consumers understand that personal information that they volunteered to give/gave consent to can be turned into new information about them (e.g. with AI) that they have no control over? | |
| Increasing data collection and use in society | Are people willing to proactively trade or sell their personal data to gain benefits/products? To whom? Under what circumstances? |
| In what situations and why do they volunteer/refuse to give data? What factors and incidents have significant impact on the attitudes? | |
| What is the attitude among consumers and citizens towards the increasing amount of data being collected about and from them? In what situations are they exceptionally positive/exceptionally negative? | |
| How do consumers and citizens feel about datafication? What emotions does it evoke? Do they have fears? | |
| How do the attitudes change over time as datafication increases (longitudinal approach)? | |
| How do consumers and citizens think about data being stolen, bought, hacked, or manipulated? What are the effects on their behaviour as a result? | |
| How familiar are consumers and citizens with their rights and how data about them is collected, stored, and used? | |
| Privacy and risk beliefs | In what ways do consumers (try to) protect their personal information by restricting or limiting others from accessing it? What do consumers do when their privacy has been violated? |
| What makes consumers suspect misuse of their data? What kind of websites do consumers suspect misuse their data? | |
| How do consumers perceive the “personalisation-privacy paradox” in different situations? | |
| In what situations and for what services do consumers care exceptionally more/less about privacy? | |
| How do consumers think about the processing of data about them to generate new information and knowledge? | |
| What data types (e.g. personal information, behavioural data, location data) in general and subtypes (e.g. sexual orientation, race, health data) do consumers feel comfortable giving? | |
| How do consumers feel about predictions about them that are made using AI predictive analysis? When are they more/less comfortable with them? | |
| Strategies | What is the suitability of PA for different service types and for different products? |
| How does PA/AI use interact with different brand personalities (i.e. are there retailer brands that benefit more/less from PA/AI use)? | |
| How can PA/AI be aligned with brand strategies? | |
| What are the alternative methods of PA in specific and personalisation in general if legislation prevents retailers from collecting data across channels? What are the consequences of the implementation of the General Data Protection Regulation (GDPR)? | |
| What kind of potential do new technologies and platform such as VR, AR, wearable technologies, and robots offer in terms of PA and AI use? | |
| Impacts | How does the use of PA affect retailer–customer relationships in the short/long term? |
| How does customer trust affect the efficiency and effectiveness of PA in retailing? | |
| How does retailer trust interact with PA ad relevance? In particular, does consumer trust towards the retailer ameliorate the possibly negative impacts of ad relevance for consumers with high data risk profile? | |
| What new measures should/could advertisers use to determine the impact of PA? | |
| Under what circumstances can it be a competitive advantage for retailers to not use data and/or allow consumers to remain anonymous? | |
| Ethical issues | How should retailers consider vulnerable consumers (e.g. children, elderly) when advertising online? |
| When can and should consumer data be purchased from, sold to, or distributed among other actors? | |
| How can policy, regulation, and legislation be updated to cover consumer privacy and ethical issues when AI is used in digital advertising? | |
| How are offerings related to sensitive matters (e.g. sexuality, religion, health) conveyed in a manner that is unobtrusive? | |
| What is the role of data and privacy policies, such as consent and GDPR, and how can retailers ensure ethical PA/AI use? | |
| Who owns and can monetise the new information generated with AI? How can retailers deploy it without acting unethically? | |
| Ecosystem development | What kind of ecosystems of companies and platforms emerge for future AI-driven advertising? What media trading, content creation, business intelligence, data brokers, analytics, and data management platforms are needed? |
| How can retailers deploy systems utilising unstructured data that are increasingly available online (e.g. user-generated content related to the retailer) to predict consumer behavioural trends? | |
| How can retailers build an ecosystem to track and address consumer preferences and behaviour (e.g. through aps, payment systems)? | |
| How can retailers solve the struggles between short- and long-term goals for different ecosystem partners? | |
| How are positive financial outcomes shared among ecosystem partners (e.g. models from data sales to provisions)? | |
| How can retailers avoid a loss of power to walled gardens and emerging (large) ecosystem actors who own customer data? | |
Note(s): *Although we here refer to PA, we propose similar questions are relevant for all types of new advertising techniques and/or use of customer data