Enhancing Credibility in Programmatic Advertising: A Conceptual Model of Transparency,Optimality,and Safety Surveillance

Abstract

Programmatic advertising (PA) has revolutionized the digital marketing landscape, providing automated and data-driven solutions for advertisers. However, concerns regarding the credibility of PA platforms have emerged, necessitating a comprehensive understanding of the factors that influence credibility. This paper aims to explore the key drivers that enhance the credibility of PA platforms and propose a conceptual model for their evaluation. Drawing upon a review of existing literature, the study identifies three essential drivers: transparency, optimality, and safety surveillance. Each driver is considered a two-layer construct with distinct sub-components, emphasizing the complexity and interplay between various elements.

Keywords

digital advertising programmatic advertising credibility transparency optimality safety surveillance brand safety audience safety

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References

Ada

Nabout

N. A.

Feit

E. M.

(2022). Context information can increase revenue in online display advertising auctions: Evidence from a policy change. Journal of Marketing Research, 59(5), 1–19.

Afshar

R. R.

Zhang

Kaymak

(2022). Dynamic ad network ordering method using reinforcement learning. International Journal of Computational Intelligence Systems, 15, Article 27.

Aguirre

Mahr

Grewal

De Ruyter

Wetzels

(2015). Unraveling the personalization paradox: The effect of information collection and trust-building strategies on online advertisement effectiveness. Journal of Retailing, 91(1), 34–49.

Alaimo

Kallinikos

(2018). Objects, metrics and practices: An inquiry into the programmatic advertising ecosystem. Proceedings of the Working Conference on Information Systems and Organizations (pp. 110–123). Springer.

Andreou

(2019). Auditing, measuring, and bringing transparency to social media advertising ecosystems [Doctoral dissertation]. Sorbonne Université.

Andreou

Silva

Benevenuto

Goga

Loiseau

(2019). Measuring the Facebook advertising ecosystem. Proceedings of the Network and Distributed System Security (NDSS) Symposium, San Diego, CA, USA, 2019 February (pp. 1–15).

Araujo

Copulsky

J. R.

Hayes

J. L.

Kim

S. J.

Srivastava

(2020). From purchasing exposure to fostering engagement: Brand-consumer experiences in the emerging computational advertising landscape. Journal of Advertising, 49(4), 428–445.

Bapna

Goes

Wei

Xiang

(2017). Sequential targeting of display advertising. Management Science, 63(11), 3582–3602.

Benedicktus

R. L.

Brady

M. K.

Darke

P. R.

Voorhees

C. M.

(2010). Conveying trustworthiness to online consumers: Reactions to consensus, physical store presence, brand familiarity, and generalized suspicion. Journal of Retailing, 86(4), 322–335.

10.

Bleier

Eisenbeiss

(2015). Personalized online advertising effectiveness: The interplay of what, when, and where. Marketing Science, 34(5), 669–688.

11.

Brunton

Nissenbaum

(2011). Vernacular resistance to data collection and analysis: A political theory of obfuscation. First Monday, 16(5).

12.

Cespedes

F. V.

Dougherty

J. P.

Kates

S. M.

(2016). Sales management: A global perspective. Springer.

13.

Chen

Xie

Dong

Wang

(2019). Understanding programmatic creative: The role of AI. Journal of Advertising, 48(4), 347–355.

14.

Cheong

Kim

Combs

(2016). Advertising agency operating efficiency. Journal of Marketing Communications, 22(1), 83–99.

15.

Choi

S. M.

Rifon

N. J.

(2002). Antecedents and consequences of web advertising credibility: A study of consumer response to banner ads. Journal of Interactive Advertising, 3(1), 12–24.

16.

Ciuchita

Gummerus

J. K.

Holmlund

Linhart

E. L.

(2022). Programmatic advertising in online retailing: Consumer perceptions and future avenues. Journal of Service Management, 34(2), 231–255.

17.

Cooper

D. A.

Yalcin

Nistor

Macrini

Pehlivan

(2023). Privacy considerations for online advertising: A stakeholder’s perspective to programmatic advertising. Journal of Consumer Marketing, 40(2), 235–247.

18.

Cozzolino

Corbo

Aversa

(2021). Digital platform-based ecosystems: The evolution of collaboration and competition between incumbent producers and entrant platforms. Journal of Business Research, 126, 385–400.

19.

Crovitz

L. G.

(2020, January 21). How Amazon, Geico and Walmart fund propaganda. The New York Times. https://www.nytimes.com/2020/01/21/opinion/fake-news-russia-ads.html

20.

Drèze

Hussherr

F. X.

(2003). Internet advertising: Is anybody watching? Journal of Interactive Marketing, 17(4), 8–23.

21.

Eberwein

Fengler

Karmasin

(2018). The European handbook of media accountability. Routledge.

22.

eMarketer. (2018). The state of programmatic advertising. Inside Intelligence. https://www.insiderintelligence.com/content/what-concerns-ad-buyers-about-programmatic-advertising

23.

Flanagin

A. J.

Metzger

M. J.

(2000). Perceptions of internet information credibility. Journalism & Mass Communication Quarterly, 77(3), 515–540.

24.

Frick

T. W.

Belo

Telang

(2022). Incentive misalignments in programmatic advertising: Evidence from a randomized field experiment. Management Science, 69(3), 1–22.

25.

Fulgoni

G. M.

(2016). Fraud in digital advertising: A multibillion dollar black hole: How marketers can minimise losses caused by bogus web traffic. Journal of Advertising Research, 56(2), 122–125.

26.

Funk

Nabout

N. A.

(2016). Cross-channel real-time response analysis. In Bush

(Ed.), Programmatic advertising the successful transformation to automated, data-driven marketing in real-time (pp. 141–152). Springer.

27.

Gertz

McGrath

(2016). The effect of transaction transparency on programmatic media buying. Journal of Advertising Research, 56(4), 412–421.

28.

Ghanbarpour

Sahabeh

Gustafsson

(2022). Consumer response to online behavioral advertising in a social media context: The role of perceived ad complicity. Psychology & Marketing, 39(10), 1–18.

29.

Goldsmith

R. E.

Lafferty

B. A.

Newell

S. J.

(2000). The impact of corporate credibility and celebrity credibility on consumer reaction to advertisements and brands. Journal of Advertising, 29(3), 43–54.

30.

Hasri

M. N.

Silva

Susanto

Y. B.

Winarno

P. M.

(2022). The attitude toward the programmatic advertising on click-through intention. Proceedings of the 4th International Conference of Economics, Business, and Entrepreneurship, ICEBE 2021, 7 October 2021. Lampung, Indonesia: European Alliance for Innovation.

31.

Helberger

Huh

Milne

Strycharz

Sundaram

(2020). Macro and exogenous factors in computational advertising: Key issues and new research directions. Journal of Advertising, 49(4), 377–393.

32.

IAB Europe. (n.d.). Programmatic advertising. Retrieved February 17, 2025, from https://iabeurope.eu/programmatic-advertising/

33.

Johnson

G. A.

Lewis

R. A.

Nubbemeyer

E. I.

(2017). Ghost ads: Improving the economics of measuring online ad effectiveness. Journal of Marketing Research, 54(6), 867–884.

34.

Johnson

T. J.

Kaye

B. K.

(2009). In blog we trust? Deciphering credibility of components of the internet among politically interested internet users. Computers in Human Behavior, 25, 175–182.

35.

Jung

A. R.

(2017). The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 70, 303–309.

36.

Karlsson

(2020). Feedback control in programmatic advertising: The frontier of optimization in real-time bidding. IEEE Control Systems Magazine, 40(5), 40–77.

37.

Kietzmann

Paschen

Treen

(2018). Artificial intelligence in advertising: How marketers can leverage artificial intelligence along the consumer journey. Journal of Advertising Research, 58(3), 263–267.

38.

Kim

Y. J.

Han

J. Y.

(2014). Why smartphone advertising attracts customers: A model of web advertising, flow, and personalization. Computers in Human Behavior, 33, 256–269.

39.

Kiran

K. U.

Arumugam

(2020). Role of programmatic advertising on effective digital promotion strategy: A conceptual framework [Conference session]. Journal of Physics, Engineering and Technology.

40.

Latham

Hervé

Bizet

(2021). Antitrust concerns in ad-tech: Formalizing the combined effect of multiple conducts and behaviours. European Competition Journal, 17(2), 353–390.

41.

Lee

Cho

(2020). Digital advertising: Present and future prospects. International Journal of Advertising, 39(3), 332–341.

42.

Yuan

Wang

(2018). A hierarchical framework for ad inventory allocation in programmatic advertising markets. Electronic Commerce Research and Applications, 31, 40–51.

43.

Yuan

Zhao

Wang

(2017, July). Research on information structure of programmatic advertising markets. Proceedings of the 20th World Congress of the International Federation of Automatic Control, IFAC-PapersOnLine, (Vol. 50., No. 1, pp. 13587–13592).

44.

Malloy

McNamara

Cahn

Barford

(2016). Ad blockers: Global prevalence and impact. Proceedings of the 2016 Internet Measurement Conference, Santa Monica, CA, USA (pp. 4–6). ACM.

45.

Malthouse

E. C.

Hessary

Y. K.

Vakeel

K. A.

Burke

Fudurić

(2019). An algorithm for allocating sponsored recommendations and content: Unifying programmatic advertising and recommender systems. Journal of Advertising, 48(4), 366–379.

46.

Malthouse

E. C.

(2017). Opportunities for and pitfalls of using big data in advertising research. Journal of Advertising, 46(2), 227–235.

47.

Malthouse

E. C.

Maslowska

Franks

J. U.

(2018). Understanding programmatic TV advertising. International Journal of Advertising, 37(5), 769–784.

48.

Markham

Gatlin-Watts

Bounds

(2001). Internet advertising vs. traditional advertising. Journal of Promotion Management, 6(1), 3–17.

49.

Martínez-Martínez

I. J.

Aguado

Boeykens

(2017). Ethical implications of digital advertising automation: The case of programmatic advertising in Spain. El profesional de la información, 26(2), 201–210.

50.

Nabout

A. N.

Clement

Shehu

(2015). The risk of advertising on non-premium websites. EMAC 2015 Conference Proceedings, Baltimore, Maryland, USA.

51.

Newell

S. J.

Goldsmith

R. E.

(2001). The development of a scale to measure perceived corporate credibility. Journal of Business Research, 52(3), 235–247.

52.

Nuara

Trovò

Gatti

Restelli

(2022). Online joint bid/daily budget optimization of Internet advertising campaigns. Artificial Intelligence, 305, Article 103682.

53.

Palos-Sanchez

Saura

J. R.

Martin-Velicia

(2019). A study of the effects of programmatic advertising on users’ concerns about privacy overtime. Journal of Business Research, 96, 61–72.

54.

Pavlou

P. A.

Gefen

(2004). Building effective online marketplaces with institution-based trust. Information Systems Research, 15(1), 37–59.

55.

Pavlou

P. A.

Stewart

D. W.

(2000). Measuring the effects and effectiveness of interactive advertising. Journal of Interactive Advertising, 1(1), 61–77.

56.

Pawlata

Cakir

(2020). The impact of the transparency consent framework on current programmatic advertising practices (Vol. 1). Proceedings of the 4th International Conference on Computer-Human Interaction Research and Applications (CHIRA) 2020 Virtual Event, (pp. 331–336).

57.

Pintado

P. G.

Mateo

R. C.

Huertas

J. G.

(2018). Delphi study on the evolution and prospects of the advertising programmatic buying in Spain. Doxa Comunicación, 27, 253–271.

58.

Qin

Jiang

(2019). The impact of AI on the advertising process: The Chinese experience. Journal of Advertising, 48(4), 338–346.

59.

Rappaport

S. D.

(2014). Lessons learned from 197 metrics, 150 studies, and 12 essays: A field guide to digital metrics. Journal of Advertising Research, 54(1), 110–118.

60.

Richet

(2022). How cybercriminal communities grow and change: An investigation of ad-fraud communities. Technological Forecasting and Social Change, 174, Article 121279.

61.

Rodgers

Nguyen

(2022). Advertising benefits from ethical artificial intelligence algorithmic purchase decision pathways. Journal of Business Ethics, 178, 1043–1061.

62.

Rus-Arias

Palos-Sanchez

P. R.

Reyes-Menendez

(2021). The influence of sociological variables on users’ feelings about programmatic advertising and the use of ad-blockers. Informatics, 8(1), Article 5.

63.

Samuel

Gareth

R. T.

White

R. T.

Paul

(2021). Programmatic advertising: An exegesis of consumer concerns. Computers in Human Behavior, 116, Article 106657.

64.

Saurwein

(2022). Algorithms on the internet: Factor of media change and challenge for change management. In Karmasin

Diehl

Koinig

(Eds.), Media and change management (pp. 419–442). Springer.

65.

Segijn

C. M.

Opree

S. J.

van Ooijen

(2022). The validation of the perceived surveillance scale. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 16(3), Article 9.

66.

Segijn

C. M.

Strycharz

Riegelman

Hennesy

(2021). A literature review of personalization transparency and control: Introducing the transparency–awareness–control framework. Media and Communication, 9(4), 120–133.

67.

Semerádová

Weinlich

(2022, May 18). Effectiveness of automatic retargeting in programmatic advertising. SSRN. https://ssrn.com/abstract=4113049

68.

Statista. (2023a). Programmatic advertising worldwide—Statistics & facts. https://www.statista.com/topics/2498/programmatic-advertising/#topicOverview

69.

Statista. (2023b). Estimated cost of digital ad fraud worldwide from 2018 to 2023. https://www.statista.com/statistics/677466/digital-ad-fraud-cost/

70.

Strycharz

Kim

Segijn

C. M.

(2022). Why people would (not) change their media use in response to perceived corporate surveillance. Telematics and Informatics, 71, Article 101838.

71.

Taylor

C. R.

(2009). Editorial. International Journal of Advertising, 28(3), 411–418.

72.

Thorson

(2023). 100 years of advertising studies in JMCQ. Journalism & Mass Communication Quarterly, 100(4), 958–978.

73.

Trusov

Jamal

(2016). Crumbs of the cookie: User profiling in customer-base analysis and behavioral targeting. Marketing Science, 35(3), 405–426.

74.

Van den Broeck

Poels

Walrave

(2020). How do users evaluate personalized Facebook advertising? An analysis of consumer- and advertiser-controlled factors. Qualitative Market Research, 23(2), 309–327.

75.

Van den Broeck

Zaroualia

Poels

(2019). Chatbot advertising effectiveness: When does the message get through? Computers in Human Behavior, 98, 150–157.

76.

Van Doorn

Hoekstra

J. C.

(2013). Customization of online advertising: The role of intrusiveness. Marketing Letters, 24(4), 339–351.

77.

van Ooijen

(2022). When disclosures backfire: Aversive source effects for personalization disclosures on less trusted platforms. Journal of Interactive Marketing, 57(2), 178–197.

78.

Walker

Kent

(2013). The roles of credibility and social consciousness in the corporate philanthropy-consumer behavior relationship. Journal of Business Ethics, 116(2), 341–353.

79.

Wang

Xiong

Yang

(2019). Serial position effects on native advertising effectiveness: Differential results across publisher and advertiser metrics. Journal of Marketing, 83(2), 82–97.

80.

White

Samuel

(2019). Programmatic advertising: Forewarning and avoiding hype-cycle failure. Technological Forecasting and Social Change, 144, 157–168.

81.

Wicker

S. B.

Karlsson

(2017). Internet advertising: Technology, ethics, and a serious difference of opinion. Communications of the ACM, 60, 70–79.

82.

(2021). The role and influence of artificial intelligence on advertising industry. Proceedings of the 2021 International Conference on Social Development and Media Communication, Sanya, China.

83.

Yun

J. T.

Segijn

Pearson

Malthouse

Konstan

J. A.

Shankar

(2020). Challenges and future directions of computational advertising measurement systems. Journal of Advertising, 49(4), 446–458.

84.

Yun

J. T.

Strycharz

(2022). Building the future of digital advertising one block at a time: How blockchain technology can change advertising practice and research. Journal of Current Issues & Research in Advertising, 44(1), 24–37.