Mobile advertising: The changing landscape of the advertising industry

The study explores the factors of m-advertising by proposing an extension of UTAUT.The constructs of UTAUT, FC and PEJ have positive and significant effect on BI.MS is a significant predictor for PE, EE and PEJ.EE has significant effect on PE.The control variables (gender and experience) have no confounding effects on BI. As mobile technologies continued to advance, a new platform of advertising known as mobile advertising (m-advertising) has emerged. This study explores factors that influence consumers' behavioral intention (BI) to use m-advertising by proposing an extension of Unified Theory of Acceptance and Use of Technology (UTAUT) model with personal innovativeness in information technology (PIIT), perceived enjoyment (PEJ) and mobile skillfulness (MS). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) to examine a sample size of 271 respondents, the findings reveal that all the constructs in UTAUT have positive and significant effect on BI. Additionally, the results also support MS as a major determinant of performance expectancy (PE), effort expectancy (EE) and PEJ. In terms of control variables, gender and experience were found to have no confounding effects on the BI to use m-advertising. The research model can provide useful insights for scholars and mobile marketers to facilitate the growth of m-advertising in the mobile market environment. Practical contribution of the study will provide useful information for scholars and mobile marketers to facilitate m-advertising growth in the mobile market environment.

[1]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[2]  Jijie Wang,et al.  Information technology (IT) in Saudi Arabia: Culture and the acceptance and use of IT , 2007, Inf. Manag..

[3]  Jian-Liang Chen,et al.  The effects of education compatibility and technological expectancy on e-learning acceptance , 2011, Comput. Educ..

[4]  Young-Gul Kim,et al.  Extending the TAM for a World-Wide-Web context , 2000, Inf. Manag..

[5]  E. Turban,et al.  Electronic Commerce: A Managerial Perspective , 1999 .

[6]  Efraim Turban,et al.  Electronic Commerce 2002: A Managerial Perspective , 2002 .

[7]  W. F. V. Raaij,et al.  Consumer Behaviour: A European Perspective , 1999 .

[8]  M. Decker,et al.  Comparison of Different Approaches for Mobile Advertising , 2005, Second IEEE International Workshop on Mobile Commerce and Services.

[9]  Moez Limayem,et al.  What makes consumers buy from Internet? A longitudinal study of online shopping , 2000, IEEE Trans. Syst. Man Cybern. Part A.

[10]  Garry Wei-Han Tan,et al.  Predicting the determinants of the NFC-enabled mobile credit card acceptance: A neural networks approach , 2013, Expert Syst. Appl..

[11]  Samer Barakat.  TRUST AND USER ACCEPTANCE OF MOBILE ADVERTISING , 2010 .

[12]  KENNETH C.C. YANG.  Exploring Factors Affecting Consumer Intention to Use Mobile Advertising in Taiwan , 2007 .

[13]  Alain Yee-Loong Chong,et al.  What drives Malaysian m-commerce adoption? An empirical analysis , 2009, Ind. Manag. Data Syst..

[14]  Beng Hui Chua,et al.  Predicting the Consumers' Intention to Adopt Mobile Shopping: An Emerging Market Perspective , 2012 .

[15]  Peng-Ting Chen,et al.  Personalized mobile advertising: Its key attributes, trends, and social impact , 2012 .

[16]  Suzanne Altobello Nasco,et al.  Comparing consumer responses to advertising and non‐advertising mobile communications , 2008 .

[17]  Y. Tao,et al.  Using UTAUT to explore the behavior of 3G mobile communication users , 2007, 2007 IEEE International Conference on Industrial Engineering and Engineering Management.

[18]  Gordon B. Davis,et al.  User Acceptance of Information Technology: Toward a Unified View , 2003, MIS Q..

[19]  Fred D. Davis,et al.  User Acceptance of Computer Technology: A Comparison of Two Theoretical Models , 1989 .

[20]  Tao Zhou,et al.  Integrating TTF and UTAUT to explain mobile banking user adoption , 2010, Comput. Hum. Behav..

[21]  I. Ajzen.  The theory of planned behavior , 1991 .

[22]  Li-Wei Mai,et al.  Consumer adoption of online music services: the influence of perceived risks and risk relief strategies , 2007 .

[23]  Pruthikrai Mahatanankoon,et al.  The Effects of Personality Traits and Optimum Stimulation Level on Text-Messaging Activities and M-commerce Intention , 2007, Int. J. Electron. Commer..

[24]  Marko Sarstedt,et al.  An assessment of the use of partial least squares structural equation modeling in marketing research , 2012 .

[25]  Gillian Sullivan Mort,et al.  Mobile Communications: A Study of Factors Influencing Consumer Use of m-Services , 2007, Journal of Advertising Research.

[26]  Garry Wei-Han Tan,et al.  Predicting the drivers of behavioral intention to use mobile learning: A hybrid SEM-Neural Networks approach , 2014, Comput. Hum. Behav..

[27]  Il Im,et al.  An international comparison of technology adoption: Testing the UTAUT model , 2011, Inf. Manag..

[28]  James B. Orlin.  A Faster Strongly Polynomial Minimum Cost Flow Algorithm , 1993, Oper. Res..

[29]  Christer Carlsson,et al.  Adoption of Mobile Devices/Services — Searching for Answers with the UTAUT , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[30]  Marko Sarstedt,et al.  Partial least squares structural equation modeling (PLS-SEM): A useful tool for family business researchers , 2014 .

[31]  Alain Yee-Loong Chong,et al.  Modeling the stimulators of the behavioral intention to use mobile entertainment: Does gender really matter? , 2013, Comput. Hum. Behav..

[32]  Masood H. Siddiqui,et al.  Effectiveness of Mobile Advertising: The Indian Scenario , 2008 .

[33]  Choy-Har Wong,et al.  Mobile TV: a new form of entertainment? , 2014, Ind. Manag. Data Syst..

[34]  Chelliah Sriskandarajah,et al.  Demand-supply optimization in mobile advertising , 2014 .

[35]  Ravindra K. Ahuja,et al.  Network Flows: Theory, Algorithms, and Applications , 1993 .

[36]  Mary Jo Bitner,et al.  Choosing among Alternative Service Delivery Modes: An Investigation of Customer Trial of Self-Service Technologies , 2005 .

[37]  Mary Helen Fagan,et al.  An Empirical Investigation into the Relationship between Computer Self-Efficacy, Anxiety, Experience, Support and Usage , 2003, J. Comput. Inf. Syst..

[38]  Soe-Tsyr Yuan,et al.  A recommendation mechanism for contextualized mobile advertising , 2003, Expert Syst. Appl..

[39]  Alain Yee-Loong Chong,et al.  Adoption of 3G services among Malaysian consumers: an empirical analysis , 2010, Int. J. Mob. Commun..

[40]  Rex B. Kline,et al.  Principles and Practice of Structural Equation Modeling , 1998 .

[41]  Timo Koivumäki,et al.  The perceptions towards mobile services: an empirical analysis of the role of use facilitators , 2006, Personal and Ubiquitous Computing.

[42]  Mikko T. Siponen,et al.  Integrating Habit into UTAUT: The Chinese eBay Case , 2011, Pac. Asia J. Assoc. Inf. Syst..

[43]  Sudip Bhattacharjee,et al.  Digital music and online sharing: software piracy 2.0? , 2003, CACM.

[44]  Ritu Agarwal,et al.  A Conceptual and Operational Definition of Personal Innovativeness in the Domain of Information Technology , 1998, Inf. Syst. Res..

[45]  Heikki Karjaluoto,et al.  Consumer acceptance of online banking: an extension of the technology acceptance model , 2004, Internet Res..

[46]  Richard P. Bagozzi,et al.  The Legacy of the Technology Acceptance Model and a Proposal for a Paradigm Shift , 2007, J. Assoc. Inf. Syst..

[47]  Alain Yee-Loong Chong,et al.  The adoption of PDA for future healthcare system: an emerging market perspective , 2014, Int. J. Mob. Commun..

[48]  Pin Luarn,et al.  AIS Electronic Library (AISeL) , 2017 .

[49]  Kenneth C. C. Yang,et al.  Exploring factors affecting the adoption of mobile commerce in Singapore , 2005, Telematics Informatics.

[50]  Chang Liu,et al.  An Application of the UTAUT Model for Understanding Student Perceptions Using Course Management Software , 2007, Communications of the IIMA.

[51]  Hélène Delerue,et al.  Job mobility restriction mechanisms and appropriability in organizations: The mediating role of secrecy and lead time , 2010 .

[52]  Su-Fang Lee,et al.  An Empirical Examination of Customer Perceptions of Mobile Advertising , 2006, Inf. Resour. Manag. J..

[53]  Garry Wei-Han Tan,et al.  Can the demographic and subjective norms influence the adoption of mobile banking? , 2012, Int. J. Mob. Commun..

[54]  Banjo Roxas,et al.  Effects of formal institutions on the performance of the tourism sector in the Philippines: The mediating role of entrepreneurial orientation , 2013 .

[55]  George M. Giaglis,et al.  Mobile Advertising Effectiveness: an Exploratory Study , 2006, 2006 International Conference on Mobile Business.

[56]  R. Bagozzi,et al.  On the evaluation of structural equation models , 1988 .

[57]  Thompson S. H. Teo.  Demographic and motivation variables associated with Internet usage activities , 2001, Internet Res..

[58]  Garry Wei-Han Tan,et al.  Understanding and predicting the motivators of mobile music acceptance - A multi-stage MRA-artificial neural network approach , 2014, Telematics Informatics.

[59]  Gillian Sullivan Mort,et al.  Mobile digital technology: Emerging issue for marketing , 2002 .

[60]  Kiseol Yang.  Consumer technology traits in determining mobile shopping adoption: An application of the extended theory of planned behavior , 2012 .

[61]  Marko Sarstedt,et al.  PLS-SEM: Indeed a Silver Bullet , 2011 .

[62]  Garry Wei-Han Tan,et al.  Determining factors affecting broadband services adoption: an empirical analysis of Malaysian consumers , 2012 .

[63]  G. Lekakos,et al.  Determinants of Effective SMS Advertising: An Experimental Study , 2007 .

[64]  S. Barnes.  Wireless digital advertising: nature and implications , 2002 .

[65]  Christina Spurgeon.  Losers and Lovers , 2005 .

[66]  Fred D. Davis,et al.  A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies , 2000, Management Science.

[67]  Fujun Lai,et al.  Using Partial Least Squares in Operations Management Research: A Practical Guideline and Summary of Past Research , 2012 .

[68]  Per E. Pedersen,et al.  Explaining intention to use mobile chat services: moderating effects of gender , 2005 .

[69]  Harry Bouwman,et al.  Ubiquitous use of mobile social network services , 2014, Telematics Informatics.

[70]  Kenneth C. C. Yang,et al.  Factors affecting consumers' responses to mobile advertising from a social norm theoretical perspective , 2010, Telematics Informatics.

[71]  Huaping Chen,et al.  An Empirical Study of What Drives Consumers to Use Mobile Advertising in China , 2008, 2008 The 3rd International Conference on Grid and Pervasive Computing - Workshops.

[72]  Felix B. Tan,et al.  Antecedents of perceived playfulness: an exploratory study on user acceptance of general information-searching websites , 2004, Inf. Manag..

[73]  Amy Carroll,et al.  Consumer perceptions and attitudes towards SMS advertising: recent evidence from New Zealand , 2007 .

[74]  David S. Johnson,et al.  Computers and Intractability: A Guide to the Theory of NP-Completeness , 1978 .

[75]  Kamla Ali Al-Busaidi,et al.  An empirical investigation linking learners’ adoption of blended learning to their intention of full e-learning , 2013, Behav. Inf. Technol..

[76]  Byeng-Hee Chang,et al.  Audience knowledge, perceptions and factors affecting the adoption intent of terrestrial digital television , 2006, New Media Soc..

[77]  June Lu,et al.  Are personal innovativeness and social influence critical to continue with mobile commerce? , 2014, Internet Res..

[78]  Garry Wei-Han Tan,et al.  Determinants of Mobile Learning Adoption: An Empirical Analysis , 2012, J. Comput. Inf. Syst..

[79]  Xiao Shuang.  A Conceptual Framework for Consumer Adoption of Mobile Advertising in China , 2010, 2010 International Conference on E-Business and E-Government.

[80]  E. Rogers.  Diffusion of Innovations , 1962 .

[81]  A. Bandura.  Social Foundations of Thought and Action , 1986 .

[82]  Xiao-yi Zhang,et al.  A Conceptual Model of User Adoption of Mobile Advertising , 2012, 2012 International Conference on Computer Science and Electronics Engineering.

[83]  LeeSungjoon.  An integrated adoption model for e-books in a mobile environment , 2013 .

[84]  Kenneth L. Kraemer,et al.  Innovation diffusion in global contexts: determinants of post-adoption digital transformation of European companies , 2006, Eur. J. Inf. Syst..

[85]  Kiseol Yang.  Determinants of US consumer mobile shopping services adoption: implications for designing mobile shopping services , 2010 .

[86]  Fred D. Davis,et al.  Extrinsic and Intrinsic Motivation to Use Computers in the Workplace1 , 1992 .

[87]  António Soares Aguiar,et al.  Why Do Firms Adopt E-Procurement Systems? Using Logistic Regression to Empirically Test a Conceptual Model , 2008, IEEE Transactions on Engineering Management.

[88]  Viswanath Venkatesh,et al.  Determinants of Perceived Ease of Use: Integrating Control, Intrinsic Motivation, and Emotion into the Technology Acceptance Model , 2000, Inf. Syst. Res..

[89]  Ting-Peng Liang,et al.  Consumer Attitudes Toward Mobile Advertising: An Empirical Study , 2004, Int. J. Electron. Commer..

[90]  Hsi-Peng Lu,et al.  Factors affecting purchase intention on mobile shopping web sites , 2009, Internet Res..

[91]  Alain Yee-Loong Chong,et al.  Predicting m-commerce adoption determinants: A neural network approach , 2013, Expert Syst. Appl..

[92]  Stuart M. Speedie,et al.  Factors influencing health information technology adoption in Thailand's community health centers: Applying the UTAUT model , 2009, Int. J. Medical Informatics.

[93]  Minjoon Jun,et al.  Measuring consumer perceptions of online shopping convenience , 2013 .

[94]  Chang Liu,et al.  Technology acceptance model for wireless Internet , 2003, Internet Res..

[95]  Hengdong Yang,et al.  The Role of Personality Traits in UTAUT Model under Online Stocking , 2005 .

[96]  Choy-Har Wong,et al.  Mobile shopping: the next frontier of the shopping industry? An emerging market perspective , 2014, Int. J. Mob. Commun..

[97]  C. Yu.  Factors Affecting Individuals to Adopt Mobile Banking: Empirical Evidence from the Utaut Model , 2012 .

[98]  Eunil Park,et al.  Factors influencing users' employment of mobile map services , 2014, Telematics Informatics.

[99]  Shin-Yuan Hung,et al.  Knowledge-sharing motivations affecting R&D employees' acceptance of electronic knowledge repository , 2011, Behav. Inf. Technol..

[100]  I. Ajzen,et al.  Belief, Attitude, Intention, and Behavior: An Introduction to Theory and Research , 1977 .

[101]  Elena Karahanna,et al.  Time Flies When You're Having Fun: Cognitive Absorption and Beliefs About Information Technology Usage , 2000, MIS Q..

[102]  M. Conner,et al.  The Theory of Planned Behaviour , 2004 .

[103]  R. Bagozzi.  Attitudes, intentions, and behavior: A test of some key hypotheses. , 1981 .

[104]  Patrick Y. K. Chau,et al.  Understanding Individual Adoption of Instant Messaging: An Empirical Investigation , 2005, J. Assoc. Inf. Syst..

[105]  Viswanath Venkatesh,et al.  Consumer Acceptance and Use of Information Technology: Extending the Unified Theory of Acceptance and Use of Technology , 2012, MIS Q..

[106]  Chris Higgins,et al.  Charismatic leadership and user acceptance of information technology , 2007, Eur. J. Inf. Syst..

[107]  G. Pope,et al.  A New Conceptual Model for Understanding Geographical Variations in Weathering , 1995 .

[108]  Hans van der Heijden,et al.  User Acceptance of Hedonic Information Systems , 2004, MIS Q..

[109]  Wen-Lung Shiau,et al.  Continuance intention of blog users: the impact of perceived enjoyment, habit, user involvement and blogging time , 2013, Behav. Inf. Technol..

[110]  Jong Woo Jun,et al.  A case study of mobile advertising in South Korea: Personalisation and digital multimedia broadcasting (DMB) , 2008 .

[111]  JungKun Park,et al.  Digital music services: consumer intention and adoption , 2008 .

[112]  Kar Yan Tam,et al.  Understanding the behavior of mobile data services consumers , 2008, Inf. Syst. Frontiers.

[113]  Jim Ryan,et al.  Faculty Use of Established and Emerging Technologies in Higher Education: A Unified Theory of Acceptance and Use of Technology Perspective , 2013 .

[114]  D. DavisFred,et al.  User Acceptance of Computer Technology , 1989 .

[115]  Fred D. Davis.  Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology , 1989, MIS Q..

[116]  Wei Wang,et al.  The contingent effect of personal IT innovativeness and IT self-efficacy on innovative use of complex IT , 2013, Behav. Inf. Technol..

[117]  Harry Bouwman,et al.  An assessment of advanced mobile services acceptance: Contributions from TAM and diffusion theory models , 2008, Inf. Manag..

[118]  Garry Wei-Han Tan,et al.  NFC mobile credit card: The next frontier of mobile payment? , 2014, Telematics Informatics.

[119]  Shin-Yuan Hung,et al.  Critical factors of WAP services adoption: an empirical study , 2003, Electron. Commer. Res. Appl..

[120]  Sungjoon Lee,et al.  An integrated adoption model for e-books in a mobile environment: Evidence from South Korea , 2013, Telematics Informatics.

[121]  Xinran Y. Lehto,et al.  Adoption of Mobile Technologies for Chinese Consumers , 2007 .

[122]  Kevin D. Wayne.  A Polynomial Combinatorial Algorithm for Generalized Minimum Cost Flow , 2002, Math. Oper. Res..

[123]  Zhaohua Deng,et al.  Comparison of the middle-aged and older users' adoption of mobile health services in China , 2014, Int. J. Medical Informatics.

[124]  Sylvia M. Chan-Olmsted,et al.  Perceived Effectiveness and Business Structure among Advertising Agencies: A Case Study of Mobile Advertising in South Korea , 2010 .

[125]  Dothang Truong,et al.  Computer self-efficacy in an ongoing use context , 2004, Behav. Inf. Technol..

[126]  J. Thong.  Resource Constraints and Information Systems Implementation in Singaporean Small Businesses , 2001 .

[127]  I-Chiu Chang,et al.  Physicians' acceptance of pharmacokinetics-based clinical decision support systems , 2007, Expert Syst. Appl..