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Nowadays, most of our activities and personal details are recorded by one entity or another. These data are used for many applications that fundamentally enrich our lives, such as navigation systems, social networks, search engines, and health monitoring. On the darker side of data collection lie usages that can harm us and threaten our sense of privacy. Marketing, as an academic field and corporate practice, has benefited tremendously from this era of data abundance, but has concurrently heightened the risk of associated harms.

In this chapter, we discuss both the great advantages and potential harms ushered in by this era of data collection, as well as ways to mitigate the harms while maintaining the benefits. Specifically, we propose and discuss classes of potential solutions: methods for collecting less data overall, transparency of code and models, federated learning, and identity management tools, among others. Some of these solutions can be implemented now, others require a longer horizon, but all can begin through the advocacy of marketing research. We also discuss possible ways to improve on the benefits of data collection – by developing methods to assist individuals pursue their long-term goals while advocating for privacy in such pursuits.

The purpose of this paper is to report the findings of two studies that explored consumer misrepresentation (lying) during personal information disclosure in a commercial context. Disclosure strategies and mediating processes that might influence lying were also investigated.

Two studies were carried out to examine the phenomenon of interest. The first study examined the extent of consumer lying in a consumer‐commercial exchange context, the variation of lying about different kinds of personal information and a classification of consumers in terms of disclosure tendencies. The second study examined two mediating processes that may drive lying behavior: cost‐benefit evaluations and fairness evaluations.

The findings suggest that individuals tend to falsify some items more than they do others, and, even in information categories that are not “personally identifying,” there is a high level of misrepresentation. It was also found that consumers can be grouped based on their disclosure strategy (lying, omitting, truthfully disclosing), and the strategy appears to be related to perceived experience with disclosure. Finally, it was found that the cost‐benefit of disclosure influences consumer lying, but fairness perceptions do not appear to influence lying behavior.

Based on the findings in this study, a percentage of information appears to be faulty. This brings into question data quality, in that good marketing decisions presumes good data. Information‐based marketing exchanges appear to be driven by cost‐benefit evaluations. If this is the case, then marketers should strive to ethically develop elicitation strategies that either reduce the perceived cost of consumer disclosure or increase consumers' perceptions of the value they receive in exchange for personal information.

This paper provides useful information on consumer lying with regard to disclosing personal information in a commercial context.

In light of the data economy, data protection law is a key legal element for being able to leverage data-driven innovation and is often regarded as a limitation for businesses and service design. Contrasting this traditional view, this chapter argues why designing with privacy in mind is a win-win situation, not only, but especially in the context of data-based services. On the backdrop of new regulations around the globe setting incentives, we show how research in the domain of usable privacy can be leveraged to embed innovative privacy features for customers into digital services as competitive advantage. Building upon these insights, we argue that a well-designed privacy and/or data protection process should be a key element for customer experience management.

The aim of this chapter is to examine and problematize the taken-for-granted conceptual understanding of risk practices in sport cultures. By inspecting the mainstay, and one might argue relatively stagnant, constructions of risk in the sociological study of sport, a case for attending to a wider range of risk-based ideologies and cultural practices is presented. The chapter ventures away from viewing risk as predominantly physical in sport settings and constructing athletes as oppressed agents who naively acquiesce to practices of self-injury and self-alienation in sport cultures. Emphasis is given to a broad spectrum of risks undertaken in the practice of sport, and the reflexive, personal nature by which risk may be understood by sports and physical culture participants.

In the first part of the chapter, the relatively simplistic or unidimensional construction of risk in sociological research in sport is reviewed. In the second part, the complexity of the concept of risk is then discussed alongside case examples that push the analytical boundaries of how risk is a multidimensional construct of athletes’ minds, bodies, selves, beliefs, values, and identities in a host of relational contexts.

Risk is best understood as a set of practices and belief that exists on a continuum in sport and physical cultures. Risk-taking in sport, however, can be personally injurious and detrimental along a number of lines but is also often calculated, personally/group satisfying and existentially rewarding at times. If the concept of risk is to be applied and interrogated in sport and physical cultures, it should be done so, therefore, in radically contextual manners.

This chapter illustrates the need for new and exploratory theoretical understandings of what risk means to athletes and other participants in sport and physical culture. New substantive topics are proposed, as are methodological suggestions for representations of the unfolding risk in the process of “doing” sport.

The aim of any research is to create knowledge and to generate new insights. For insights from empirical research to be valid, the data from which insights are derived must be valid. Empirical data in tourism and hospitality research is predominantly collected by means of surveys. The chapter discusses a range of dangers to data validity associated with survey research; explains under which circumstances surveys represent a suitable or unsuitable method of data collection; and offers practical recommendations that can easily be adopted by survey researchers to ensure maximum validity of their data.

The outcomes of data‐driven marketing are presumed to be superior but those outcomes are partly dependent on data inputs that are accurate. This paper sets out to highlight problems associated with poor data quality.

The name of the author's dog was substituted for that of the author on a single data collection form. Over a period of 15 years, the direct mail sent to the author's dog was collected and categorized.

Over a 15‐year period, both reasonable and unexplainable changes in the content of the marketing effort were found. Analysis showed some consistency but, over time, offers began to appear which showed that the database representation of the “individual” had taken on an interesting life of its own.

Data are the fuel that drives the direct marketing engine. Yet that engine can sputter ineffectively if the fuel quality is inferior. Poor data contain inaccuracies which limit the efficacy and increase the costs of direct marketing efforts. The issue of the data quality needs to be addressed by those who utilize personal data in their efforts to target and communicate with consumers.

In the post-pandemic period and following widespread inoculation against the infection, this research aims to pinpoint the variables that affect consumers' behavioural intentions (BIs) towards online food delivery (OFD) services. The study goes further to investigate the potential impact of vaccine confidence (VC) in modifying the association between consumers' BI to utilise OFD services and their actual usage behaviour (UB).

Using information gathered through a structured questionnaire from 372 Indian customers, a proposed model based on the technology acceptance model (TAM) and theory of planned behaviour (TPB) models was put to the test using structural equation modelling (SEM).

Results demonstrate that perceptions of ease of use, attitude (ATT) and perceived behavioural control (PBC) have a favourable and significant impact on behaviour intention amongst Indian OFD users. Contrary to what the TAM and TPB models had predicted, perceived usefulness (PU) and subjective norms (SN) did not significantly affect the BI of the sample of Indian OFD users. Furthermore, the association between BI and actual UB of OFD users is not moderated by the consumers' VC.

The study contributes by shedding light on the variables that affect Indian OFD users' BIs after the coronavirus disease 2019 (COVID-19) pandemic era and mass immunisation and whether VC has a role to play in affecting consumer behaviour, which will aid OFD service providers, eateries and marketers in redesigning their marketing plans.

The present study is the first in making a literary contribution through analysis of the moderating effect of VC on the relationship between BI and actual UB. Additionally, this study presents evidence from India, one of the first nations to implement widespread COVID-19 inoculation.

In the context of social media (SM) use, self-disclosure (SD) behaviour meets users' social and emotional needs, but it is also accompanied by risks that can harm users. This paper aims to identify the factors that influence users' SD behaviour on SM in Indonesia, using a comparative analysis based on age groups.

A survey was conducted on 2,210 respondents who were active SM users in Indonesia. Data were processed and analysed using covariance-based structural equation modelling with AMOS 24.0 software.

Results indicate that, in the overall age group data, factors such as use of information (UI), trust, privacy control (PC), interactivity, perceived benefits (PB) and perceived risks (PR) influence users' SD behaviour. This research also found differences in the characteristics of SD behaviour between age groups.

Findings from this study can help SM service providers to evaluate the credibility and reliability of their platforms to encourage user retention.

The purpose of this paper is to examine relationships of self-care behavior, illness representation and diabetes knowledge with A1C (level of glycemic control) in 124 incarcerated persons.

Using a cross-sectional design, summary scores and items from the self-care inventory revised, brief illness perception questionnaire and the spoken knowledge for low literacy in diabetes were evaluated using linear regression to assess their relationship to A1C.

Metabolic control was suboptimal for the majority of inmates with diabetes. The final regression model was statistically significant (F (3, 120)=9.51, p=0.001, R²=19.2 percent). Higher log10 HbA1C (A1C) was associated with lower personal control beliefs (B=−0.007, t (122)=−2.42, p=<0.02), higher self-report of diabetes understanding (B=0.009, t (122)=3.12, p=0.00) and using insulin (B=0.062, t (122)=2.45, p=0.02).

Similar to findings with community dwelling participants, enhancing diabetes personal control beliefs among inmates may lead to lower A1C.

Highly structured environments with limited options for self-care, personal choices and readily available health care may give some incarcerated persons with diabetes no motivation to improve diabetes control even if they have an understanding of what to do.

While there is abundant research in the community describing how these factors influence A1C levels, research of this nature with incarcerated persons with diabetes is limited. Findings will inform diabetes programming during incarceration to better prepare inmates for reentry.

Many online transactions and digital services depend on consumers’ willingness to take privacy risks, such as when shopping online, joining social networks, using online banking or interacting with e-health platforms. Their decisions depend on not only how much they would suffer if their data were revealed but also how uncomfortable they feel about taking such a risk. Such an aversion to risk is a neglected factor when evaluating the value of privacy. The aim of this paper is to propose an empirical method to measure both privacy risk aversion and privacy worth and how those affect privacy decisions.

The authors let individuals play privacy lotteries and derive a measure of the value of privacy under risk (VPR) and empirically test the validity of this measure in a laboratory experiment with 148 participants. Individuals were asked to make a series of incentivized decisions on whether to incur the risk of revealing private information to other participants.

The results confirm that the willingness to incur a privacy risk is driven by a complex array of factors, including risk aversion, self-reported value for private information and general attitudes to privacy (derived from surveys). The VPR does not depend on whether there is a preexisting threat to privacy. The authors find qualified support for the existence of an order effect, whereby presenting financial choices prior to privacy ones leads to less concern for privacy.

Attitude to risk in the domain of privacy decisions is largely understudied. In this paper, the authors take a first step toward closing this empirical and methodological gap by offering (and validating) a method for the incentivized elicitation of the implicit VPR and proposing a robust and meaningful monetary measure of the level of aversion to privacy risks. This measure is a crucial step in designing and implementing the practical strategies for evaluating privacy as a competitive advantage and designing markets for privacy risk regulations (e.g. through cyber insurances).

The present study advances research on the economics of consumer privacy – one of the most controversial topics in the digital age. In light of the proliferation of privacy regulations, the mentioned method for measuring the VPR provides an important instrument for policymakers’ informed decisions regarding what tradeoffs consumers consider beneficial and fair and where to draw the line for violations of consumers’ expectations, preferences and welfare.

The authors present a novel method to measure the VPR that takes account of both the value of private information to consumers and their tolerance for privacy risks. The authors explain how this method can be used more generally to elicit attitudes to a wide range of privacy risks involving exposure of various types of private information.