An Integrated Adoption Model of Mobile Cloud Services: Exploration of Key Determinants and Extension of Technology Acceptance Model

This study identifies and investigates a number of cognitive factors that contribute to shaping user perceptions of and attitude toward mobile cloud computing services by integrating these factors with the technology acceptance model. A structural equation modeling analysis is employed on data collected from 1099 survey samples, and results reveal that user acceptance of mobile cloud services is largely affected by perceived mobility, connectedness, security, quality of service and system, and satisfaction. Both theoretical and practical implications of the study's findings are discussed.

[1]  Kun Chang Lee,et al.  Understanding factors affecting trust in and satisfaction with mobile banking in Korea: A modified DeLone and McLean's model perspective , 2009, Interact. Comput..

[2]  Chaokun Wang,et al.  Phosphor: A Cloud Based DRM Scheme with Sim Card , 2010, 2010 12th International Asia-Pacific Web Conference.

[3]  P. Bentler,et al.  Significance Tests and Goodness of Fit in the Analysis of Covariance Structures , 1980 .

[4]  Angel P. del Pobil,et al.  Modeling the user acceptance of long-term evolution (LTE) services , 2013, Ann. des Télécommunications.

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

[6]  Dong-Hee Shin,et al.  Analysis of online social networks: a cross-national study , 2010, Online Inf. Rev..

[7]  Linda Dailey Paulson.  Low-Power Chips for High-Powered Handhelds , 2003, Computer.

[8]  Kaisa Väänänen,et al.  User experience of mobile photo sharing in the cloud , 2010, MUM.

[9]  Parthasarathy Ranganathan,et al.  Energy Consumption in Mobile Devices: Why Future Systems Need Requirements-Aware Energy Scale-Down , 2003, PACS.

[10]  Hyunseung Choo,et al.  Smartphones as smart pedagogical tools: Implications for smartphones as u-learning devices , 2011, Comput. Hum. Behav..

[11]  Jen-Her Wu,et al.  Mobile computing acceptance factors in the healthcare industry : A structural equation model , 2006 .

[12]  Geoffrey H. Kuenning,et al.  Saving portable computer battery power through remote process execution , 1998, MOCO.

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

[14]  I. Ajzen,et al.  Attitude-behavior relations: A theoretical analysis and review of empirical research. , 1977 .

[15]  J. Hair.  Multivariate data analysis , 1972 .

[16]  Chonho Lee,et al.  A survey of mobile cloud computing: architecture, applications, and approaches , 2013, Wirel. Commun. Mob. Comput..

[17]  Eunil Park,et al.  User acceptance of long-term evolution (LTE) services: An application of extended technology acceptance model , 2013, Program.

[18]  Eszter Hargittai,et al.  Whose Space? Differences Among Users and Non-Users of Social Network Sites , 2007, J. Comput. Mediat. Commun..

[19]  Danah Boyd,et al.  Social Network Sites: Definition, History, and Scholarship , 2007, J. Comput. Mediat. Commun..

[20]  Alec Wolman,et al.  MAUI: making smartphones last longer with code offload , 2010, MobiSys '10.

[21]  Keng Siau,et al.  Mobile communications and mobile services , 2003, Int. J. Mob. Commun..

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

[23]  Dong-Hee Shin,et al.  Why do people play social network games? , 2011, Comput. Hum. Behav..

[24]  Anol Bhattacherjee,et al.  Understanding Information Systems Continuance: An Expectation-Confirmation Model , 2001, MIS Q..

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

[26]  Fred D. Davis.  User Acceptance of Information Technology: System Characteristics, User Perceptions and Behavioral Impacts , 1993, Int. J. Man Mach. Stud..

[27]  Mahadev Satyanarayanan,et al.  Fundamental challenges in mobile computing , 1996, PODC '96.

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

[29]  Yoonmo Sang,et al.  Exploring Koreans' smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory , 2013, Comput. Hum. Behav..

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

[31]  J. W. Davis.  Power benchmark strategy for systems employing power management , 1993, Proceedings of the 1993 IEEE International Symposium on Electronics and the Environment.

[32]  Yu-Ru Lin,et al.  Elucidating user behavior of mobile learning: A perspective of the extended technology acceptance model , 2007, Electron. Libr..

[33]  Gavriel Salvendy,et al.  Perceived security determinants in e-commerce among Turkish university students , 2005, Behav. Inf. Technol..

[34]  Keith F Widaman,et al.  On specifying the null model for incremental fit indices in structural equation modeling. , 2003, Psychological methods.

[35]  Ephraim R. McLean,et al.  The DeLone and McLean Model of Information Systems Success: A Ten-Year Update , 2003, J. Manag. Inf. Syst..

[36]  Dong-Hee Shin,et al.  Applying the Technology Acceptance Model and Flow Theory to Cyworld User Behavior: Implication of the Web2.0 User Acceptance , 2008, Cyberpsychology Behav. Soc. Netw..

[37]  Mufajjul Ali,et al.  Green Cloud on the Horizon , 2009, CloudCom.

[38]  Ephraim R. McLean,et al.  Information Systems Success: The Quest for the Dependent Variable , 1992, Inf. Syst. Res..

[39]  Imsook Ha,et al.  Determinants of adoption of mobile games under mobile broadband wireless access environment , 2007, Inf. Manag..

[40]  Jengchung V. Chen,et al.  Acceptance and adoption of the innovative use of smartphone , 2007, Ind. Manag. Data Syst..

[41]  Jason Flinn,et al.  Virtualized in-cloud security services for mobile devices , 2008, MobiVirt '08.

[42]  Chih-Chien Wang,et al.  Extending the technology acceptance model to mobile telecommunication innovation: The existence of network externalities , 2008 .