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A study of the effects of programmatic advertising on users' concerns about privacy overtime

Authors:
Pedro R. Palos-Sanchez at University of Seville
Pedro R. Palos-Sanchez
José Ramón Saura at Rey Juan Carlos University
José Ramón Saura
Félix A. Martín-Velicia at University of Seville
Félix A. Martín-Velicia
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Abstract

This research work has two objectives. On the one hand, to analyze the influence that Perceived Usefulness of Programmatic Advertising (PA) has on the user's Concern about Privacy, and on the other, to check whether this relationship changes over time. That is, to find out how improvements in the effectiveness of programmatic advertising might increase the users' concern for privacy. Today, programmatic advertising can be very invasive, not only because of the use of cookies and geolocation, but also because of using algorithms that analyze users' interests in order to offer related products at a later date when the user visits other different websites which are not at all related to the first. Secondly, this document investigates whether this relationship increases over time and if there are any time-related effects. In this study, data from of a very large sample of Internet users in Spain (n = 14,822) was analyzed at three different moments of time between 2013 and 2017. PLS-SEM was used for the analysis given its usefulness in social studies. Several groups were analyzed to test the difference between the path coefficients of the latent variables at different moments in time. Academics and professionals will benefit from this document by being able to see the importance of this relationship over time and how it changes. The use of a longitudinal study allowed for an investigation into, not only the existence of the relationship, but how it changed over the years.
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Contents lists available at ScienceDirect
Journal of Business Research
journal homepage: www.elsevier.com/locate/jbusres
A study of the effects of programmatic advertising on users' concerns about
privacy overtime
Pedro Palos-Sanchez
a
, Jose Ramon Saura
b,⁎
, Felix Martin-Velicia
a
a
Department of Business Administration and Marketing, University of Seville, Av. Ramon y Cajal, 1, Seville, Spain
b
Department of Business Economics, Rey Juan Carlos University, Paseo Artilleros s/n, Madrid 28027, Spain
ARTICLE INFO
Keywords:
Programmatic advertising
Perceived usefulness
Privacy concern
Longitudinal analysis
Multigroup analysis
PLS-SEM
ABSTRACT
This research work has two objectives. On the one hand, to analyze the influence that Perceived Usefulness of
Programmatic Advertising (PA) has on the user's Concern about Privacy, and on the other, to check whether this
relationship changes over time. That is, to find out how improvements in the effectiveness of programmatic
advertising might increase the users' concern for privacy. Today, programmatic advertising can be very invasive,
not only because of the use of cookies and geolocation, but also because of using algorithms that analyze users'
interests in order to offer related products at a later date when the user visits other different websites which are
not at all related to the first. Secondly, this document investigates whether this relationship increases over time
and if there are any time-related effects. In this study, data from of a very large sample of Internet users in Spain
(n = 14,822) was analyzed at three different moments of time between 2013 and 2017. PLS-SEM was used for
the analysis given its usefulness in social studies. Several groups were analyzed to test the difference between the
path coefficients of the latent variables at different moments in time. Academics and professionals will benefit
from this document by being able to see the importance of this relationship over time and how it changes. The
use of a longitudinal study allowed for an investigation into, not only the existence of the relationship, but how it
changed over the years.
1. Introduction
Digital marketing and online advertising have become one of the
main strategies used by companies to get worthwhile results from their
Internet marketing and communication strategies (Jung, Pawlowski, &
Kim, 2017). Consequently, the Internet has become the preferred
channel of millions of users around the world for daily tasks, the pur-
chase of basic products and services, as well as for paying for these
goods and services nationally and internationally using payment gate-
ways with the world's main banks (Hauser & Urban, 1993;Keith,
Maynes, Lowry, & Babb, 2013).
The transmission of information through systems that manage
Internet users' data has become a process that companies constantly
optimize (Taddicken, 2013) to increase the profitability of digital
marketing strategies and to improve the return on investment of pro-
grammatic advertising (Palos-Sanchez, Martin-Velicia, & Saura, 2018).
Studies such as those by Ning, Liu, and Yang (2013),Lee, Jalali, and
Dasdan (2013),Chen and Zahedi (2017),Belanche, Flavián, and Pérez-
Rueda (2017),Miralles-Pechuán, Ponce, and Martínez-Villaseñor
(2018) and Huang (2018) show the interest of researchers in
Programmatic Advertising (PA) as a new marketing technique applied
to the Internet and emerging technologies (Leal-Rodríguez, Eldridge,
Roldán, Leal-Millán, & Ortega-Gutiérrez, 2015).
PA is a novel technique which has been developed in recent years,
and uses large amounts of data, or big data (Cui, Zhang, Li, & Mao,
2011;Lee et al., 2013;Qin, Yuan, & Wang, 2017;Shan, Lin, Sun, &
Wang, 2016). PA has stimulated growth and investment in graphic
advertising on the Internet (Kireyev, Pauwels, & Gupta, 2016). PA,
when compared to traditional models of buying and selling advertising
space on the Internet, has led to models which use the number of user
impressions, the cost of banner clicks and creative advertising (Aslam &
Karjaluoto, 2017a, 2017b,Miralles-Pechuán et al., 2018). The tech-
nology that drives PA analyses millions of pieces of real time data,
which allow PA adverts to accurately reflect the precise interests of a
user at the exact moment at which they are most likely to make a
purchase or click on an ad (Huang, 2018;Belanche et al., 2017;
Oikarinen & Söderlund, 2016).
PA has the potential to ensure that the online audience is adequate
and adverts are shown whenever the audience is using their device
(Lee, Ahn, & Park, 2015). In addition, advertising can be targeted for
https://doi.org/10.1016/j.jbusres.2018.10.059
Received 7 April 2018; Received in revised form 26 October 2018; Accepted 29 October 2018
⁎
Corresponding author.
E-mail addresses: ppalos@us.es (P. Palos-Sanchez), joseramon.saura@urjc.es (J.R. Saura), velicia@us.es (F. Martin-Velicia).
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Pedro Palos-Sanchez PhD in Business Economics at University of Seville, Information
Systems Engineer and Market Techniques Research, MBA Business Administration from
ESERP and the Camilo José Cela University. Master's Degree in Education and ICTs from
the Open University of Catalonia. More than 20 years working in companies of the sector
of Information Technology in different management positions. He has been a member of
the Executive Committees of the Spanish Association of e-learning-CEOE companies, the
Confederation of Trade and Services Companies of Seville, Secretary of the Association of
Engineers in Andalusia and Secretary General of the Federation of Information
Technology Companies of Andalusia. He is Associate Professor in the Department of
Business Management and Marketing, teaching at the Faculty of Business Studies of the
University of Sevilla, Spain. He has participated with various lectures, courses and articles
in various congresses and programs on digital economy, entrepreneurship and manage-
ment both nationally and internationally, being his research lines Digital Marketing and
Information Systems.
Jose Ramon Saura currently works at Rey Juan Carlos University in the Business
Economics Department (Madrid, Spain). P.h.D in Business Economics with International
Mention at Harvard Business School (HBS) and London South Bank University (LSBU) in
the Ehrenberg Bass Institute for Research in Marketing Sciences. He works as a technical
Marketing Mentor at Google Developer since 2010. His expertise is Digital Marketing
(SEO, SEM and Social Media Marketing), Information Systems, Technology Acceptance
Models and Interactive Marketing. He is usually in contact with the academic and pro-
fessional environments. He helps develop Startups in the early-stage as a Marketing
mentor at Google Developers programmes such as Google Launchpad Week, Google
Campus Startups School or Google for Moms. He has participated in various lectures,
courses, and articles in international congresses and programs about digital economy,
entrepreneurship, management, startups and online reputation. He is a member of the
European Academy of Management and Business Economics (AEDEM) and Reviewer of
Internationals Journals and Congresses.
Felix Martin-Velicia is Professor at the University of Seville. PhD in Business Economics.
Professor of marketing and market research studies Internet and new technologies applied
to research. He is a reviewer in national and international scientific conferences as well as
in journals. He studies traditional marketing and its relationship with digital marketing
and new technologies.
P. Palos-Sanchez et al. 
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This study evaluated the sensitivity of maximum likelihood (ML)- generalized least squares (GLS) - and asymptotic distribution-free (ADF)-based fit indices to model misspecification under conditions that varied sample size and distribution. The effect of violating assumptions of asymptotic robustness theory also was examined. Standardized root-mean-square residual (SRMR) was the most sensitive index to models with misspecified factor covariance(s) and Tucker–Lewis Index (1973; TLI)Bollen's fit index (1989; BL89) relative noncentrality index (RNI) comparative fit index (CFI) and the ML- and GLS-based gamma hat McDonald's centrality index (1989; Mc) and root-mean-square error of approximation (RMSEA) were the most sensitive indices to models with misspecified factor loadings. With ML and GLS methods we recommend the use of SRMR supplemented by TLI BL89 RNI CFI gamma hat Mc or RMSEA (TLI Mc and RMSEA are less preferable at small sample sizes). With the ADF method we recommend the use of SRMR supplemented by TLI BL89 RNI or CFI. Finally most of the ML-based fit indices outperformed those obtained from GLS and ADF and are preferable for evaluating model fit.
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Complexity in the Acceptance of Sustainable Search Engines on the Internet: An Analysis of Unobserved Heterogeneity with FIMIX-PLS
Article
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This paper analyses the complexity of user behaviour when facing the challenge of using sustainable applications, such as Internet search engines. This paper analyses an acceptance model using extended TAM (Technology Acceptance Model) with Trust as an added external variable. It was suggested that Trust indirectly influences the final Intention to Use with the perceptions of Utility and Ease of Use. To test the proposed model, a survey was carried out with users from different geographical areas of Spain ( n=445 ). The second aim of this study was to understand the complexity of marketing segmentation by separating the application users into different user groups. Users were grouped by their preference of favorite Internet search engine. Unobserved heterogeneity was studied using FIMIX-PLS, and three different user behaviours with search engines were identified. These corresponded to the number of inhabitants who live in the user area. In this way, the impact that the environment has on user choice, acceptance, and use of this type of sustainable applications was shown. The results were checked using PLS-SEM and showed that the model for the adoption of sustainable search engines is explanatory and predictive because confidence and acceptance for this TAM were validated. The conclusions are interesting for developers of environmentally sustainable and responsible applications which want to coincide with current trends to ensure that users prefer them.
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Do Online Comments Affect Environmental Management? Identifying Factors Related to Environmental Management and Sustainability of Hotels
Article
Full-text available
  • Aug 2018
The main aim of this study was to identify the key indicators related to environmental management and sustainability of hotels as perceived by travelers during their trips. The methodology used was a sentiment analysis with an algorithm developed in Python trained with data mining and machine learning, with the MonkeyLearn library in the hotel industry sector under the eWOM model (e-Word of Mouth). The results with negative, positive and neutral feelings were submitted to a textual analysis with the qualitative analysis software Nvivo Pro 12. The sample consisted of the 25 best hotels in Switzerland according to Traveler’s Choice from TripAdvisor ranking 2018 that draws from more than 500,000 reviews. For data extraction, we connected to the TripAdvisor API, obtaining a sample of n = 8331 reviews of the hotels that made up the ranking. The results of the study highlight the key factors related to environmental management detected by travelers during their stay in hotels and can be meaningfully used by managers or hotel managers to improve their services and enhance the value provided by their policies of sustainability and respect for the environment. The limitations of the present study relate to the size of the sample and the number of hotels included in the present analysis.
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Attitudes Expressed in Online Comments about Environmental Factors in the Tourism Sector: An Exploratory Study
Article
Full-text available
The object of this exploratory study is to identify the positive, neutral and negativeenvironment factors that affect users who visit Spanish hotels in order to help the hotel managersdecide how to improve the quality of the services provided. To carry out the research a SentimentAnalysis was initially performed, grouping the sample of tweets (n= 14459) according to the feelingsshown and then a textual analysis was used to identify the key environment factors in these feelingsusing the qualitative analysis software Nvivo (QSR International, Melbourne, Australia). The resultsof the exploratory study present the key environment factors that affect the users experience whenvisiting hotels in Spain, such as actions that support local traditions and products, the maintenance ofrural areas respecting the local environment and nature, or respecting air quality in the areas wherehotels have facilities and offer services. The conclusions of the research can help hotels improve theirservices and the impact on the environment, as well as improving the visitors experience based onthe positive, neutral and negative environment factors which the visitors themselves identified.
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How Consumers Allocate Their Time When Searching for Information
Article
  • Nov 1993
The authors assume consumers maximize value subject to a constraint on their time. The value of positive information is the increase in the expected utility of the consideration set; the value of negative information is the utility of choosing on the basis of the information versus the utility of a potentially erroneous decision without information. They examine four rules consumers use to select the order in which to visit sources. They use a multimedia computer laboratory, which allows consumers free choice among showroom visits, word-of-mouth interviews, magazine articles, and advertising for a new automobile. They estimate source value, compare predictions of time allocations to actual allocations, examine the impact of time constraints on the use of negative information, and calculate the relative performance of the source-order decision rules. They close with suggestions for experiments.
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Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory
Article
  • Nov 1982
In marketing applications of structural equation models with unobservable variables, researchers have relied almost exclusively on LISREL for parameter estimation. Apparently they have been little concerned about the frequent inability of marketing data to meet the requirements for maximum likelihood estimation or the common occurrence of improper solutions in LISREL modeling. The authors demonstrate that partial least squares (PLS) can be used to overcome these two problems. PLS is somewhat less well-grounded than LISREL in traditional statistical and psychometric theory. The authors show, however, that under certain model specifications the two methods produce the same results. In more general cases, the methods provide results which diverge in certain systematic ways. These differences are analyzed and explained in terms of the underlying objectives of each method.
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Attribute-Level Performance, Satisfaction, and Behavioral Intentions over Time: A Consumption-System Approach
Article
  • Apr 1999
  • J MARKETING
Instead of offering products or services alone, increasingly, firms and their partners are offering consumption systems. Consumption systems are offerings characterized by a significant product and service subsystem, as well as a pattern of consumption in which consumption occurs in multiple episodes over time. The authors develop a theoretical model for conceptualizing satisfaction with consumption systems and empirically test it using longitudinal data from 5206 automobile owners. Results show that an intertemporal examination of attribute-level performance, satisfaction, and behavioral intentions can improve an understanding of their relationships because these relationships change as the consumption of the product unfolds. For example, on the basis of their salience, attribute weights in determining satisfaction shift over time. Furthermore, the crossover effect of product and service satisfaction in determining intentions toward the manufacturer and the service provider is asymmetric, and this asymmetry reverses over time. Service satisfaction initially has a much larger impact in determining intentions toward the manufacturer, but later, product satisfaction is more influential in generating intentions toward the service provider and manufacturer. The results show that there is no direct link between satisfaction and behavioral intentions. Rather, satisfaction affects behavioral intentions in the future through a dual-mediation route.
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Structural Equation Models with Unobservable Variables and Measurement Error: Algebra and Statistics
Article
  • Aug 1981
Several issues relating to goodness of fit in structural equations are examined. The convergence and differentiation criteria, as applied by Bagozzi, are shown not to stand up under mathematical or statistical analysis. The authors argue that the choice of interpretative statistic must be based on the research objective. They demonstrate that when this is done the Fornell-Larcker testing system is internally consistent and that it conforms to the rules of correspondence for relating data to abstract variables.
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"What Can I Really Do?" : Explaining the Privacy Paradox with Online Apathy
Article
  • Jan 2016
Based on focus group interviews, we considered how young adults’ attitudes about privacy can be reconciled with their online behavior. The “privacy paradox” suggests that young people claim to care about privacy while simultaneously providing a great deal of personal information through social media. Our interviews revealed that young adults do understand and care about the potential risks associated with disclosing information online and engage in at least some privacy-protective behaviors on social media. However, they feel that once information is shared, it is ultimately out of their control. They attribute this to the opaque practices of institutions, the technological affordances of social media, and the concept of networked privacy, which acknowledges that individuals exist in social contexts where others can and do violate their privacy.
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