ISSN 0253-2778

CN 34-1054/N

Open AccessOpen Access JUSTC Review 23 September 2024

An integrated theoretical framework based on the SOMR model

Cite this:
https://doi.org/10.52396/JUSTC-2022-0120
More Information
  • Author Bio:

    Shengliang Zhang is currently an Associate Professor at the University of Science and Technology of China. He received his master degree from Fudan University. His research mainly focuses on service marketing, robotics services, and brand management

    Jianhui Jin is currently a graduate student at the School of Management of the University of Science and Technology of China. His research mainly focuses on e-word of mouth and advertising avoidance

  • Corresponding author: E-mail: jh1593572684@mail.ustc.edu.cn
  • Received Date: 30 August 2022
  • Accepted Date: 04 May 2023
  • Available Online: 23 September 2024
  • Advertising avoidance is resistance to advertising intrusion. This issue has been the subject of much academic research in recent years. To guide future scholars to better carry out relevant research and promote enterprises to better implement advertising activities, this study intends to summarize the relevant research on advertising avoidance in recent years. The specific method is to use the core literature meta-analysis method to identify, filter and screen relevant literature published in core journals from 1997 to 2020 with the keywords advertising avoidance and advertising resistance. We review the collected articles from the perspectives of external stimulating factors of advertising avoidance, internal perception factors of advertising avoidance, and moderating factors of advertising avoidance. On this basis, the SOMR model of advertising avoidance is constructed according to the SOR model. Finally, some prospects for future related research are given.
    The influence mechanism of advertisement avoidance based on SOMR model.
    Advertising avoidance is resistance to advertising intrusion. This issue has been the subject of much academic research in recent years. To guide future scholars to better carry out relevant research and promote enterprises to better implement advertising activities, this study intends to summarize the relevant research on advertising avoidance in recent years. The specific method is to use the core literature meta-analysis method to identify, filter and screen relevant literature published in core journals from 1997 to 2020 with the keywords advertising avoidance and advertising resistance. We review the collected articles from the perspectives of external stimulating factors of advertising avoidance, internal perception factors of advertising avoidance, and moderating factors of advertising avoidance. On this basis, the SOMR model of advertising avoidance is constructed according to the SOR model. Finally, some prospects for future related research are given.
    • This study clarified the relationship among the various factors of advertising avoidance, that is the advertisement itself is the independent variable, the internal perception of the audience is the mediator variable, the advertising avoidance is the dependent variable, while the audience themselves, the scene and social culture factors are the moderating variables.
    • This study comprehensively reviews and summarizes the respective connotations of the relevant factors and their specific factors of advertising avoidance.
    • This study point out and analyze the differences of scholars' understanding of related issues and the differences of research conclusions.

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  • [1]
    Speck P S, Elliott M T. Predictors of advertising avoidance in print and broadcast media. Journal of Advertising, 1997, 26: 61–76. doi: 10.1080/00913367.1997.10673529
    [2]
    Makkar M, Yap S F C. Managing hearts and minds: Romanticizing Airbnb experiences. Current Issues in Tourism, 2020, 25: 3461–3480. doi: 10.1080/13683500.2020.1792855
    [3]
    Steward M D, Lewis B R. A comprehensive analysis of marketing journal rankings. Journal of Marketing Education, 2010, 32 (1): 75–92. doi: 10.1177/0273475309344804
    [4]
    Liao S Q, Liu C Y, Shen Q, et al. The current situation and development trend of international communication discipline: Taking the SSCI journal of communication studies from 2000 to 2011 as the research object. Journalism Research, 2013 (3): 77–89. (in Chinese)
    [5]
    Edwards S M, Li H, Lee J H. Forced exposure and psychological reactance: Antecedents and consequences of the perceived intrusiveness of pop-up ads. Journal of Advertising, 2002, 31 (3): 83–95. doi: 10.1080/00913367.2002.10673678
    [6]
    Cho C H, Cheon H J. Why do people avoid advertising on the Internet? Journal of Advertising, 2004, 33 (4): 89–97. doi: 10.1080/00913367.2004.10639175
    [7]
    Chinchanachokchai S, Duff B R L, Faber R J. Distracted mind: The effects of multitasking and mind wandering on consumer memory for ad content. International Journal of Advertising, 2020, 39 (5): 631–654. doi: 10.1080/02650487.2019.1670536
    [8]
    Speck P S, Elliott M T. Consumer perceptions of advertising clutter and its impact across various media. Journal of Advertising Research, 1998, 38 (1): 29–41.
    [9]
    Tse A C B, Lee R P W. Zapping behavior during commercial breaks. Journal of Advertising Research, 2001, 41 (3): 25–29. doi: 10.2501/jar-41-3-25-29
    [10]
    Rojas-Mendez J I, Davies G. Avoiding television advertising: Some explanations from time allocation theory. Journal of Advertising Research, 2005, 45 (1): 34–48. doi: 10.1017/s0021849905050154
    [11]
    Wilbur K C. How the digital video recorder (DVR) changes traditional television advertising. Journal of Advertising, 2008, 37 (1): 143–149. doi: 10.2753/joa0091-3367370111
    [12]
    Bellman S, Schweda A, Varan D. The residual impact of avoided television advertising. Journal of Advertising, 2010, 39 (1): 67–82. doi: 10.2753/joa0091-3367390105
    [13]
    Okazaki S, Molina F J, Hirose M. Mobile advertising avoidance: Exploring the role of ubiquity. Electronic Markets, 2012, 22 (3): 169–183. doi: 10.1007/s12525-012-0087-1
    [14]
    Rau P L P, Liao Q Z, Chen C L. Factors influencing mobile advertising avoidance. International Journal of Mobile Communications, 2013, 11 (2): 123–139. doi: 10.1504/ijmc.2013.052637
    [15]
    Siddarth S, Chattopadhyay A. To zap or not to zap: A study of the determinants of channel switching during commercials. Marketing Science, 1998, 17 (2): 124–138. doi: 10.1287/mksc.17.2.124
    [16]
    Dix S, Phau I. Television advertising avoidance: Advancing research methodology. Journal of Promotion Management, 2010, 16 (12): 114–133. doi: 10.1080/10496490903574013
    [17]
    Lo S K, Hsieh A Y, Chiu Y P. Keyword advertising is not what you think: Clicking and eye movement behaviors on keyword advertising. Electronic Commerce Research and Applications, 2014, 13 (4): 221–228. doi: 10.1016/j.elerap.2014.04.001
    [18]
    Soellner J, Dost F. Exploring the selective use of ad blockers and testing banner appeals to reduce ad blocking. Journal of Advertising, 2019, 48 (3): 302–312. doi: 10.1080/00913367.2019.1613699
    [19]
    Jin C H, Villegas J. Consumer responses to advertising on the Internet: The effect of individual difference on ambivalence and avoidance. CyberPsychology & Behavior, 2007, 10 (2): 258–266. doi: 10.1089/cpb.2006.9960
    [20]
    Baek T H, Morimoto M. Stay away from me: Examining the determinants of consumer avoidance of personalized advertising. Journal of Advertising, 2012, 41 (1): 59–76. doi: 10.2753/joa0091-3367410105
    [21]
    Bellman S, Murphy J, Treleaven-H S, et al. Using Internet behavior to deliver relevant television commercials. Journal of Interactive Marketing, 2013, 27 (2): 130–140. doi: 10.1016/j.intmar.2012.12.001
    [22]
    Tran T P. Personalized ads on Facebook: An effective marketing tool for online marketers. Journal of Retailing and Consumer Services, 2017, 39 (11): 230–242. doi: 10.1016/j.jretconser.2017.06.010
    [23]
    Chowdhury R M, Finn A, Olsen G D. Investigating the simultaneous presentation of advertising and television programming. Journal of Advertising, 2007, 36 (3): 85–96. doi: 10.2753/joa0091-3367360306
    [24]
    Jiyoon H, Minette D, Wongun G. Native advertising: Is deception an asset or a liability? Journal of Media Ethics, 2018, 33 (3): 102–119. doi: 10.1080/23736992.2018.1477048
    [25]
    Liu C W, Lo S K, et al. Effects of banner ad shape and the schema creating process on consumer Internet browsing behavior. Computers in Human Behavior, 2018, 86 (9): 9–17. doi: 10.1016/j.chb.2018.04.034
    [26]
    Van den Broeck E, Poels K, Walrave M. An experimental study on the effect of ad placement, product involvement and motives on Facebook ad avoidance. Telematics & Informatics, 2018, 35 (2): 470–479. doi: 10.1016/j.tele.2018.01.006
    [27]
    Biu T, Lee R. Zapping behavior during commercial breaks. Journal of Advertising Research, 2001, 41 (3): 25–29. doi: 10.2501/jar-41-3-25-29
    [28]
    Ha L, Litman B R. Does advertising clutter have diminishing and negative returns? Journal of Advertising, 1997, 26 (1): 31–42. doi: 10.1080/00913367.1997.10673516
    [29]
    Bob M F, Arnold B B. “Stay tuned—We will be back right after these messages”: Need to evaluate moderates the transfer of irritation in advertising. Journal of Advertising, 2001, 30 (3): 15–25. doi: 10.1080/00913367.2001.10673642
    [30]
    Zahra S, Hossein T, Matanda M J. Reinquiry into advertising avoidance on the Internet: A conceptual replication and extension. Journal of Advertising, 2016, 45 (1): 120–129. doi: 10.1080/00913367.2015.1085819
    [31]
    Reading N, Bellman S, Varan D, et al. Effectiveness of telescopic advertisements delivered via personal video recorders. Journal of Advertising Research, 2006, 46 (2): 217–227. doi: 10.2501/s0021849906060223
    [32]
    Li B, Yin S. How perceived control affects advertising avoidance intention in a skippable advertising context: A moderated mediation model. Chinese Journal of Communication, 2020, 14 (2): 157–175. doi: 10.1080/17544750.2020.1776743
    [33]
    Okazaki S. Social influence model and electronic word of mouth: PC versus mobile Internet. International Journal of Advertising, 2009, 28 (3): 439–472. doi: 10.2501/s0265048709200692
    [34]
    Shin W, Lin T C. Who avoids location-based advertising and why? Investigating the relationship between user perceptions and advertising avoidance. Computers in Human Behavior, 2016, 63: 444–452. doi: 10.1016/j.chb.2016.05.036
    [35]
    Huh J, Delorme D E, Reid L N. Do consumers avoid watching over-the-counter drug advertisements? An analysis of cognitive and affective factors that prompt advertising avoidance. Journal of Advertising Research, 2015, 55 (4): 401–415. doi: 10.2501/jar-2015-022
    [36]
    Johnston W J, Khalil S, Cheng J M S, et al. Behavioral implications of international social media advertising: An investigation of intervening and contingency factors. Journal of International Marketing, 2018, 26 (2): 43–61. doi: 10.1509/jim.16.0125
    [37]
    Miltgen C L, Cases A S, Russell C A. Consumers’ responses to Facebook advertising across PCs and mobile phones: A model for assessing the drivers of approach and avoidance of Facebook ads. Journal of Advertising Research, 2019, 59 (4): 414–432. doi: 10.2501/jar-2019-029
    [38]
    Li H, Lee E. Measuring the intrusiveness of advertisements: Scale development and validation. Journal of Advertising, 2002, 31 (2): 37–47. doi: 10.1080/00913367.2002.10673665
    [39]
    Duff B R L, Faber R J. Missing the mark: advertising avoidance and distractor devaluation. Journal of Advertising, 2011, 40 (2): 51–62. doi: 10.2753/joa0091-3367400204
    [40]
    Sweller J. Cognitive load during problem solving: Effects on learning. Cognitive Science, 2010, 12 (2): 257–285. doi: 10.1016/0364-0213(88)90023-7
    [41]
    Lee J W, Ahn J H. Attention to banner ads and their effectiveness: An eye-tracking approach. International. Journal of Electronic Commerce, 2012, 17 (1): 119–137. doi: 10.2753/jec1086-4415170105
    [42]
    Chinchanachokchai S, Duff B R L, Sar S. The effect of multitasking on time perception, enjoyment and ad evaluation. Computers in Human Behavior, 2015, 45 (4): 185–191. doi: 10.1016/j.chb.2014.11.087
    [43]
    Liang H G, Xue Y J. Avoidance of information technology threats: A theoretical perspective. MIS Quarterly, 2009, 33 (1): 71–90. doi: 10.5555/2017410.2017417
    [44]
    Jung A R. The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 2017, 70 (5): 303–309. doi: 10.1016/j.chb.2017.01.008
    [45]
    Brehm S, et al. Psychological reactance: A theory of freedom and control. Nurs Stand, 1981: 27.
    [46]
    Youn S, Kim S. Understanding ad avoidance on Facebook: Antecedents and outcomes of psychological reactance. Computers in Human Behavior, 2019, 98 (9): 232–244. doi: 10.1016/j.chb.2019.04.025
    [47]
    Rojas-Mendez J I, Davies G, Madran C. Universal differences in advertising avoidance behavior: A cross cultural study. Journal of Business Research, 2009, 62 (10): 947–954. doi: 10.1016/j.jbusres.2008.08.008
    [48]
    Van der Goot M J, Rozendaal E, Opree S J, et al. Media generations and their advertising attitudes and avoidance: A six-country comparison. International Journal of Advertising, 2018, 37 (2): 289–308. doi: 10.1080/02650487.2016.1240469
    [49]
    Jain S P, Mathur P, Maheswaran D. The influence of consumers’ Lay theories on approach/avoidance motivation. Journal of Marketing Research, 2009, 46 (1): 56–65. doi: 10.1509/jmkr.46.1.56
    [50]
    Belanche D, Flavin C, Prez-Rueda A. User adaptation to interactive advertising formats: The effect of previous exposure, habit and time urgency on ad skipping behaviors. Telematics and Informatics, 2017, 34 (7): 961–972. doi: 10.1016/j.tele.2017.04.006
    [51]
    Andrews M, Luo X, Fang Z, et al. Mobile ad effectiveness: Hyper-contextual targeting with crowdedness. Marketing Science, 2016, 35 (2): 218–233. doi: 10.1287/mksc.2015.0905
    [52]
    Hess N J, Kelley C M, Scott M L, et al. Getting personal in public!? How consumers respond to public personalized advertising in retail stores. Journal of Retailing, 2019, 96 (3): 344–361. doi: 10.1016/j.jretai.2019.11.005
    [53]
    Bang H, Kim J, Choi D. Exploring the effects of ad-task relevance and ad salience on ad avoidance: The moderating role of Internet use motivation. Computers in Human Behavior, 2018, 89 (12): 70–78. doi: 10.1016/j.chb.2018.07.020
    [54]
    Chu S C, Yoojung K. Determinants of consumer engagement in electronic word-of-mouth (eWOM) in social networking sites. International Journal of Advertising, 2011, 30 (1): 47–75. doi: 10.2501/ija-30-1-047-075
    [55]
    Li Y M, Lin L F, Chiu S W. Enhancing targeted advertising with social context endorsement. International Journal of Electronic Commerce, 2014, 19 (1): 99–128. doi: 10.2753/jec1086-4415190103
    [56]
    Miltgen C L, Cases A-S, Russell C A. Consumers’ responses to Facebook advertising across PCs and mobile phones: A model for assessing the drivers of approach and avoidance of Facebook ads. Journal of Advertising Research, 2019, 59 (4): 414–432.
    [57]
    Chinchanachokchai S, de Gregorio F. A consumer socialization approach to understanding advertising avoidance on social media. Journal of Business Research, 2020, 110 (3): 474–483. doi: 10.1016/j.jbusres.2020.01.062
    [58]
    Rumbo J D. Consumer resistance in a world of advertising clutter: The case of Adbusters. Psychology & Marketing, 2010, 19 (2): 127–148. doi: 10.1002/mar.10006
    [59]
    Möller J, Eisend M. A global investigation into the cultural and individual antecedents of banner advertising effectiveness. Journal of International Marketing, 2010, 18 (2): 80–98. doi: 10.1509/jimk.18.2.80
    [60]
    Ketelaar P E, Konig R, Smit E G, et al. In ads we trust. Religiousness as a predictor of advertising trustworthiness and avoidance. Journal of Consumer Marketing, 2015, 32 (3): 190–198. doi: 10.1108/jcm-09-2014-1149
  • 加载中

Catalog

    Figure  1.  Year distribution of the literature.

    Figure  2.  The SOMR model of advertising avoidance.

    Figure  3.  The influence mechanism of advertisement avoidance based on SOMR model.

    [1]
    Speck P S, Elliott M T. Predictors of advertising avoidance in print and broadcast media. Journal of Advertising, 1997, 26: 61–76. doi: 10.1080/00913367.1997.10673529
    [2]
    Makkar M, Yap S F C. Managing hearts and minds: Romanticizing Airbnb experiences. Current Issues in Tourism, 2020, 25: 3461–3480. doi: 10.1080/13683500.2020.1792855
    [3]
    Steward M D, Lewis B R. A comprehensive analysis of marketing journal rankings. Journal of Marketing Education, 2010, 32 (1): 75–92. doi: 10.1177/0273475309344804
    [4]
    Liao S Q, Liu C Y, Shen Q, et al. The current situation and development trend of international communication discipline: Taking the SSCI journal of communication studies from 2000 to 2011 as the research object. Journalism Research, 2013 (3): 77–89. (in Chinese)
    [5]
    Edwards S M, Li H, Lee J H. Forced exposure and psychological reactance: Antecedents and consequences of the perceived intrusiveness of pop-up ads. Journal of Advertising, 2002, 31 (3): 83–95. doi: 10.1080/00913367.2002.10673678
    [6]
    Cho C H, Cheon H J. Why do people avoid advertising on the Internet? Journal of Advertising, 2004, 33 (4): 89–97. doi: 10.1080/00913367.2004.10639175
    [7]
    Chinchanachokchai S, Duff B R L, Faber R J. Distracted mind: The effects of multitasking and mind wandering on consumer memory for ad content. International Journal of Advertising, 2020, 39 (5): 631–654. doi: 10.1080/02650487.2019.1670536
    [8]
    Speck P S, Elliott M T. Consumer perceptions of advertising clutter and its impact across various media. Journal of Advertising Research, 1998, 38 (1): 29–41.
    [9]
    Tse A C B, Lee R P W. Zapping behavior during commercial breaks. Journal of Advertising Research, 2001, 41 (3): 25–29. doi: 10.2501/jar-41-3-25-29
    [10]
    Rojas-Mendez J I, Davies G. Avoiding television advertising: Some explanations from time allocation theory. Journal of Advertising Research, 2005, 45 (1): 34–48. doi: 10.1017/s0021849905050154
    [11]
    Wilbur K C. How the digital video recorder (DVR) changes traditional television advertising. Journal of Advertising, 2008, 37 (1): 143–149. doi: 10.2753/joa0091-3367370111
    [12]
    Bellman S, Schweda A, Varan D. The residual impact of avoided television advertising. Journal of Advertising, 2010, 39 (1): 67–82. doi: 10.2753/joa0091-3367390105
    [13]
    Okazaki S, Molina F J, Hirose M. Mobile advertising avoidance: Exploring the role of ubiquity. Electronic Markets, 2012, 22 (3): 169–183. doi: 10.1007/s12525-012-0087-1
    [14]
    Rau P L P, Liao Q Z, Chen C L. Factors influencing mobile advertising avoidance. International Journal of Mobile Communications, 2013, 11 (2): 123–139. doi: 10.1504/ijmc.2013.052637
    [15]
    Siddarth S, Chattopadhyay A. To zap or not to zap: A study of the determinants of channel switching during commercials. Marketing Science, 1998, 17 (2): 124–138. doi: 10.1287/mksc.17.2.124
    [16]
    Dix S, Phau I. Television advertising avoidance: Advancing research methodology. Journal of Promotion Management, 2010, 16 (12): 114–133. doi: 10.1080/10496490903574013
    [17]
    Lo S K, Hsieh A Y, Chiu Y P. Keyword advertising is not what you think: Clicking and eye movement behaviors on keyword advertising. Electronic Commerce Research and Applications, 2014, 13 (4): 221–228. doi: 10.1016/j.elerap.2014.04.001
    [18]
    Soellner J, Dost F. Exploring the selective use of ad blockers and testing banner appeals to reduce ad blocking. Journal of Advertising, 2019, 48 (3): 302–312. doi: 10.1080/00913367.2019.1613699
    [19]
    Jin C H, Villegas J. Consumer responses to advertising on the Internet: The effect of individual difference on ambivalence and avoidance. CyberPsychology & Behavior, 2007, 10 (2): 258–266. doi: 10.1089/cpb.2006.9960
    [20]
    Baek T H, Morimoto M. Stay away from me: Examining the determinants of consumer avoidance of personalized advertising. Journal of Advertising, 2012, 41 (1): 59–76. doi: 10.2753/joa0091-3367410105
    [21]
    Bellman S, Murphy J, Treleaven-H S, et al. Using Internet behavior to deliver relevant television commercials. Journal of Interactive Marketing, 2013, 27 (2): 130–140. doi: 10.1016/j.intmar.2012.12.001
    [22]
    Tran T P. Personalized ads on Facebook: An effective marketing tool for online marketers. Journal of Retailing and Consumer Services, 2017, 39 (11): 230–242. doi: 10.1016/j.jretconser.2017.06.010
    [23]
    Chowdhury R M, Finn A, Olsen G D. Investigating the simultaneous presentation of advertising and television programming. Journal of Advertising, 2007, 36 (3): 85–96. doi: 10.2753/joa0091-3367360306
    [24]
    Jiyoon H, Minette D, Wongun G. Native advertising: Is deception an asset or a liability? Journal of Media Ethics, 2018, 33 (3): 102–119. doi: 10.1080/23736992.2018.1477048
    [25]
    Liu C W, Lo S K, et al. Effects of banner ad shape and the schema creating process on consumer Internet browsing behavior. Computers in Human Behavior, 2018, 86 (9): 9–17. doi: 10.1016/j.chb.2018.04.034
    [26]
    Van den Broeck E, Poels K, Walrave M. An experimental study on the effect of ad placement, product involvement and motives on Facebook ad avoidance. Telematics & Informatics, 2018, 35 (2): 470–479. doi: 10.1016/j.tele.2018.01.006
    [27]
    Biu T, Lee R. Zapping behavior during commercial breaks. Journal of Advertising Research, 2001, 41 (3): 25–29. doi: 10.2501/jar-41-3-25-29
    [28]
    Ha L, Litman B R. Does advertising clutter have diminishing and negative returns? Journal of Advertising, 1997, 26 (1): 31–42. doi: 10.1080/00913367.1997.10673516
    [29]
    Bob M F, Arnold B B. “Stay tuned—We will be back right after these messages”: Need to evaluate moderates the transfer of irritation in advertising. Journal of Advertising, 2001, 30 (3): 15–25. doi: 10.1080/00913367.2001.10673642
    [30]
    Zahra S, Hossein T, Matanda M J. Reinquiry into advertising avoidance on the Internet: A conceptual replication and extension. Journal of Advertising, 2016, 45 (1): 120–129. doi: 10.1080/00913367.2015.1085819
    [31]
    Reading N, Bellman S, Varan D, et al. Effectiveness of telescopic advertisements delivered via personal video recorders. Journal of Advertising Research, 2006, 46 (2): 217–227. doi: 10.2501/s0021849906060223
    [32]
    Li B, Yin S. How perceived control affects advertising avoidance intention in a skippable advertising context: A moderated mediation model. Chinese Journal of Communication, 2020, 14 (2): 157–175. doi: 10.1080/17544750.2020.1776743
    [33]
    Okazaki S. Social influence model and electronic word of mouth: PC versus mobile Internet. International Journal of Advertising, 2009, 28 (3): 439–472. doi: 10.2501/s0265048709200692
    [34]
    Shin W, Lin T C. Who avoids location-based advertising and why? Investigating the relationship between user perceptions and advertising avoidance. Computers in Human Behavior, 2016, 63: 444–452. doi: 10.1016/j.chb.2016.05.036
    [35]
    Huh J, Delorme D E, Reid L N. Do consumers avoid watching over-the-counter drug advertisements? An analysis of cognitive and affective factors that prompt advertising avoidance. Journal of Advertising Research, 2015, 55 (4): 401–415. doi: 10.2501/jar-2015-022
    [36]
    Johnston W J, Khalil S, Cheng J M S, et al. Behavioral implications of international social media advertising: An investigation of intervening and contingency factors. Journal of International Marketing, 2018, 26 (2): 43–61. doi: 10.1509/jim.16.0125
    [37]
    Miltgen C L, Cases A S, Russell C A. Consumers’ responses to Facebook advertising across PCs and mobile phones: A model for assessing the drivers of approach and avoidance of Facebook ads. Journal of Advertising Research, 2019, 59 (4): 414–432. doi: 10.2501/jar-2019-029
    [38]
    Li H, Lee E. Measuring the intrusiveness of advertisements: Scale development and validation. Journal of Advertising, 2002, 31 (2): 37–47. doi: 10.1080/00913367.2002.10673665
    [39]
    Duff B R L, Faber R J. Missing the mark: advertising avoidance and distractor devaluation. Journal of Advertising, 2011, 40 (2): 51–62. doi: 10.2753/joa0091-3367400204
    [40]
    Sweller J. Cognitive load during problem solving: Effects on learning. Cognitive Science, 2010, 12 (2): 257–285. doi: 10.1016/0364-0213(88)90023-7
    [41]
    Lee J W, Ahn J H. Attention to banner ads and their effectiveness: An eye-tracking approach. International. Journal of Electronic Commerce, 2012, 17 (1): 119–137. doi: 10.2753/jec1086-4415170105
    [42]
    Chinchanachokchai S, Duff B R L, Sar S. The effect of multitasking on time perception, enjoyment and ad evaluation. Computers in Human Behavior, 2015, 45 (4): 185–191. doi: 10.1016/j.chb.2014.11.087
    [43]
    Liang H G, Xue Y J. Avoidance of information technology threats: A theoretical perspective. MIS Quarterly, 2009, 33 (1): 71–90. doi: 10.5555/2017410.2017417
    [44]
    Jung A R. The influence of perceived ad relevance on social media advertising: An empirical examination of a mediating role of privacy concern. Computers in Human Behavior, 2017, 70 (5): 303–309. doi: 10.1016/j.chb.2017.01.008
    [45]
    Brehm S, et al. Psychological reactance: A theory of freedom and control. Nurs Stand, 1981: 27.
    [46]
    Youn S, Kim S. Understanding ad avoidance on Facebook: Antecedents and outcomes of psychological reactance. Computers in Human Behavior, 2019, 98 (9): 232–244. doi: 10.1016/j.chb.2019.04.025
    [47]
    Rojas-Mendez J I, Davies G, Madran C. Universal differences in advertising avoidance behavior: A cross cultural study. Journal of Business Research, 2009, 62 (10): 947–954. doi: 10.1016/j.jbusres.2008.08.008
    [48]
    Van der Goot M J, Rozendaal E, Opree S J, et al. Media generations and their advertising attitudes and avoidance: A six-country comparison. International Journal of Advertising, 2018, 37 (2): 289–308. doi: 10.1080/02650487.2016.1240469
    [49]
    Jain S P, Mathur P, Maheswaran D. The influence of consumers’ Lay theories on approach/avoidance motivation. Journal of Marketing Research, 2009, 46 (1): 56–65. doi: 10.1509/jmkr.46.1.56
    [50]
    Belanche D, Flavin C, Prez-Rueda A. User adaptation to interactive advertising formats: The effect of previous exposure, habit and time urgency on ad skipping behaviors. Telematics and Informatics, 2017, 34 (7): 961–972. doi: 10.1016/j.tele.2017.04.006
    [51]
    Andrews M, Luo X, Fang Z, et al. Mobile ad effectiveness: Hyper-contextual targeting with crowdedness. Marketing Science, 2016, 35 (2): 218–233. doi: 10.1287/mksc.2015.0905
    [52]
    Hess N J, Kelley C M, Scott M L, et al. Getting personal in public!? How consumers respond to public personalized advertising in retail stores. Journal of Retailing, 2019, 96 (3): 344–361. doi: 10.1016/j.jretai.2019.11.005
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