An Empirical Study of the Effect of Internet Services on the Preferential Adoption of Mobile Internet

The revolution in wireless and cellular communications has led to a remarkable growth in smart mobile cellular devices capable of Internet access and mobile web browsing. This study empirically examined the emerging role of the mobile Internet as an alternative access channel for a growing list of applications and services. Based on a survey of 220 undergraduate students in a major university in the Middle East, we developed and tested a model where the mobile advantage of e-communication, e-transactions, e-entertainment, and e-learning were posited to influence the choice of Internet access channel, mobile or stationary. The results indicated that e-communication, e-transactions, and e-entertainment significantly influenced the choice of Internet channel, whereas access to online learning resources and services did not have such an effect. Moreover, the study did not find any significant effect of gender in this preference, pointing to the declining relevance of the gender digital divide. Some theoretical and practical implications of the results are discussed.

[1]  Sertan Kabadayi,et al.  Consumer acceptance of SMS advertising: a study of American and Turkish consumers , 2010, Int. J. Mob. Commun..

[2]  Vinton G. Cerf,et al.  The Future of the Internet: Implications for Managers an Interview with Vinton G. Cerf , 2011 .

[3]  Ibrahim M. Al-Jabri,et al.  Mobile Banking Adoption: Application of Diffusion of Innovation Theory , 2012 .

[4]  Eric B. Weiser,et al.  Gender Differences in Internet Use Patterns and Internet Application Preferences: A Two-Sample Comparison , 2000, Cyberpsychology Behav. Soc. Netw..

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

[6]  C. Anthony Di Benedetto,et al.  Diffusion of Innovation , 2015 .

[7]  Jeffrey M. Voas,et al.  Mobile Applications: The Fifth Cycle , 2010, IT Professional.

[8]  Detmar W. Straub,et al.  Specifying Formative Constructs in Information Systems Research , 2007, MIS Q..

[9]  Matti J. Haverila,et al.  Cell phone feature preferences and gender differences among college students , 2011, Int. J. Mob. Commun..

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

[11]  A. Palmer,et al.  Predicting young consumers' take up of mobile banking services , 2010 .

[12]  Gary Garrison,et al.  Investigating mobile wireless technology adoption: An extension of the technology acceptance model , 2009, Inf. Syst. Frontiers.

[13]  Harry Bouwman,et al.  Mobile services put in context: A Q-sort analysis , 2012, Telematics Informatics.

[14]  Icek Ajzen,et al.  From Intentions to Actions: A Theory of Planned Behavior , 1985 .

[15]  Anastasios A. Economides,et al.  Use of mobile phones by male and female Greek students , 2008, Int. J. Mob. Commun..

[16]  Ronald T. Cenfetelli,et al.  Interpretation of Formative Measurement in Information Systems Research , 2009, MIS Q..

[17]  Al Alak B.A.M.,et al.  MOBILE MARKETING: EXAMINING THE IMPACT OF TRUST, PRIVACY CONCERN AND CONSUMERS' ATTITUDES ON INTENTION TO PURCHASE , 2010 .

[18]  Kaan Varnali,et al.  Predictors of attitudinal and behavioral outcomes in mobile advertising: A field experiment , 2012, Electron. Commer. Res. Appl..

[19]  Shintaro Okazaki,et al.  Exploring convenience in mobile commerce: Moderating effects of gender , 2013, Comput. Hum. Behav..

[20]  Jeffrey J. Johnson,et al.  Gender Differences in Email and Instant Messaging: A Study of Undergraduate Business Information Systems Students , 2008, J. Comput. Inf. Syst..

[21]  Bill N. Schilit Mobile Computing: Looking to the Future , 2011, Computer.

[22]  Upkar Varshney,et al.  Issues in Emerging 4G Wireless Networks , 2001, Computer.

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

[24]  Ibrahim Alnawas,et al.  Examining The Impact Of Mobile Marketing On Consumers' Attitudes and Purchase Intentions. , 2010 .

[25]  Upkar Varshney,et al.  The wireless internet decision: a multi-method investigation of decision drivers , 2012, Int. J. Mob. Commun..

[26]  Pirkko Walden,et al.  Reconsidering the actual and future use of mobile services , 2009, Inf. Syst. E Bus. Manag..

[27]  Filippo Renga,et al.  Mobile Applications and Their Delivery Platforms , 2011, IT Professional.

[28]  Mohamed Khalifa,et al.  Adoption of Mobile Commerce: A Confidence Model , 2012, J. Comput. Inf. Syst..

[29]  Mark de Reuver,et al.  Should mobile Internet be an extension to the fixed web? Fixed-mobile reinforcement as mediator between context of use and future use , 2013, Telematics Informatics.

[30]  Marco Ronchetti,et al.  Hoarding content for mobile learning , 2006, Int. J. Mob. Commun..

[31]  Maro Vlachopoulou,et al.  Modeling users’ acceptance of mobile services , 2012, Electronic Commerce Research.

[32]  I. Ajzen,et al.  Understanding Attitudes and Predicting Social Behavior , 1980 .

[33]  A. Ant Ozok,et al.  An empirical comparison of consumer usability preferences in online shopping using stationary and mobile devices: results from a college student population , 2010, Electron. Commer. Res..

[34]  Steve Jones,et al.  U.S. College Students' Internet Use: Race, Gender and Digital Divides , 2009, J. Comput. Mediat. Commun..

[35]  L. Cronbach Essentials of psychological testing , 1960 .

[36]  Bill Anckar,et al.  VALUE CREATION IN MOBILE COMMERCE: FINDINGS FROM A CONSUMER SURVEY , 2002 .

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

[38]  Jen-Her Wu,et al.  What drives mobile commerce?: An empirical evaluation of the revised technology acceptance model , 2005, Inf. Manag..

[39]  Taeyong Yang,et al.  CONSUMER PREFERENCES FOR MOBILE INTERNET: A COMPARATIVE CROSS-NATIONAL MIXED METHODS STUDY , 2012 .

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

[41]  Erik Bohlin,et al.  An analysis of mobile Internet access in Thailand: Implications for bridging the digital divide , 2012, Telematics Informatics.

[42]  J. Cooper,et al.  The digital divide: the special case of gender , 2006, J. Comput. Assist. Learn..

[43]  S. Barnes,et al.  Driving consumer acceptance of mobile marketing: a theoretical framework and empirical study , 2005 .

[44]  Kin Keung Lai,et al.  An empirical analysis of mobile internet acceptance from a value-based view , 2012, Int. J. Mob. Commun..

[45]  Wynne W. Chin Issues and Opinion on Structural Equation Modeling by , 2009 .

[46]  Sunil Jose Gregory,et al.  Role of Mobile Based Applications in India's Social and Economic Transformation , 2011, Int. J. E Bus. Res..

[47]  Mohamed Khalifa,et al.  Explaining the adoption of transactional B2C mobile commerce , 2008, J. Enterp. Inf. Manag..

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

[49]  Po-Chien Chang,et al.  Drivers and moderators of consumer behaviour in the multiple use of mobile phones , 2010, Int. J. Mob. Commun..

[50]  Alain Yee-Loong Chong,et al.  An empirical analysis of the adoption of m-learning in Malaysia , 2011, Int. J. Mob. Commun..

[51]  Ralph L. Rosnow,et al.  Essentials of Behavioral Research: Methods and Data Analysis , 1984 .

[52]  Alain Yee-Loong Chong,et al.  Determinants of 3G Adoption in Malaysia: A Structural Analysis , 2010, J. Comput. Inf. Syst..

[53]  Wei-Tsong Wang,et al.  Factors influencing mobile services adoption: A brand-equity perspective , 2012, Internet Res..

[54]  Alain Yee-Loong Chong,et al.  A two-staged SEM-neural network approach for understanding and predicting the determinants of m-commerce adoption , 2013, Expert Syst. Appl..

[55]  Jacob Cohen Statistical Power Analysis for the Behavioral Sciences , 1969, The SAGE Encyclopedia of Research Design.

[56]  Mikko V. J. Heikkinen,et al.  Modeling Intention to Use Novel Mobile Peer-To-Peer Services , 2011, Int. J. E Bus. Res..

[57]  Pingjun Jiang,et al.  Adopting mobile internet: a demographic and usage perspective , 2008, Int. J. Electron. Bus..

[58]  Sandra Thomas,et al.  Characteristics and mobile Internet use intensity of consumers with different types of advanced handsets: An exploratory empirical study of iPhone, Android and other web-enabled mobile users in Germany , 2013 .

[59]  Torsten J. Gerpott,et al.  Attribute Perceptions as Factors Explaining Mobile Internet Acceptance of Cellular Customers in Germany: An Empirical Study Comparing Actual and Potential Adopters with Distinct Categories of Access Appliances , 2011, Int. J. E Bus. Res..

[60]  Brian Regan,et al.  Diffusion of innovation: analysis of internet cellular phone adoption by users in Jordan , 2011, Int. J. Electron. Bus..

[61]  Joo-Young Jung,et al.  Where do you go online? A comparison of internet connectedness via personal computers and mobile phones in Japan , 2009, Int. J. Mob. Commun..

[62]  Chang Liu,et al.  Facilitating Conditions, Wireless Trust and Adoption Intention , 2005, J. Comput. Inf. Syst..

[63]  Upkar Varshney,et al.  Evolution and emerging issues in mobile wireless networks , 2007, CACM.

[64]  Judy Drennan,et al.  An investigation of consumer acceptance of M-Banking in Australia , 2010 .