Effects of adaptivity and other external variables on mobile service adoption

This paper explores user interface between user and information systems in system adoption. Acceptance of a system is defined as a function of perceived usefulness and perceived ease of use. There are several external variables that have an impact on perceived usefulness and perceived ease of use. Therefore the content and interface design of every single application should be addressed accordingly to enhance users intention to use the system. The paper proposes that adding adaptive features into systems may be one of the approaches to address this phenomenon. We identified external variables including adaptive behavior impacting acceptance of mobile reservation system through three prototypes.

[1]  Ken-ichi Matsumoto,et al.  Identifying Services in Procedural Programs for Migrating Legacy System to Service Oriented Architecture , 2011, Int. J. Inf. Syst. Serv. Sect..

[2]  Benjamin B. Bederson,et al.  Interfaces for staying in the flow , 2004, UBIQ.

[3]  Soe-Tsyr Yuan,et al.  Using System Dynamics to Analyze Customer Experience Design , 2010, Int. J. Serv. Sci. Manag. Eng. Technol..

[4]  Jesus Boticario,et al.  samap: An user-oriented adaptive system for planning tourist visits , 2008, Expert Syst. Appl..

[5]  Judy Kay,et al.  An intelligent interface for sorting electronic mail , 2002, IUI '02.

[6]  Mark A. Neerincx,et al.  Usability trade-offs for adaptive user interfaces: ease of use and learnability , 2004, IUI '04.

[7]  Shadi Aljawarneh,et al.  Cloud Security Engineering: Avoiding Security Threats the Right Way , 2011, Int. J. Cloud Appl. Comput..

[8]  James W. Bronson,et al.  Suboptimal technology adoption: The case of computer reservation systems in the travel industry , 2003 .

[9]  I Maglogiannis,et al.  EmerLoc: Location-based services for emergency medical incidents , 2007, Int. J. Medical Informatics.

[10]  Hyung Jun Ahn,et al.  Agent-based adaptive travel planning system in peak seasons , 2004, Expert Syst. Appl..

[11]  Settapong Malisuwan,et al.  A Study of Behavioral Intention for 3G Mobile Internet Technology: Preliminary Research on Mobile Learning , 2005 .

[12]  Maria Virvou,et al.  Evaluating an intelligent graphical user interface by comparison with human experts , 2004, Knowl. Based Syst..

[13]  Thorsten Joachims,et al.  Eye-tracking analysis of user behavior in WWW search , 2004, SIGIR '04.

[14]  James P. Turley,et al.  The significance of cognitive modeling in building healthcare interfaces , 2006, Int. J. Medical Informatics.

[15]  Olle Bälter,et al.  Bifrost inbox organizer: giving users control over the inbox , 2002, NordiCHI '02.

[16]  Bassam Hasan,et al.  Effects of interface style on user perceptions and behavioral intention to use computer systems , 2007, Comput. Hum. Behav..

[17]  B. Wildemuth,et al.  Development of an adaptive multimedia program to collect patient health data. , 2001, American journal of preventive medicine.

[18]  Adamantios Koumpis,et al.  Supporting Adaptivity in Intelligent User Interfaces : The case of Media and Modalities Allocation , 1995 .

[19]  Barin Nag,et al.  Intelligent Systems in Operations: Methods, Models and Applications in the Supply Chain , 2010 .

[20]  Patricia A. Chalmers,et al.  The role of cognitive theory in human-computer interface , 2003, Comput. Hum. Behav..

[21]  管郁君,et al.  Gender-Specific Websites: How Do Female Visitors Respond? , 2005 .

[22]  Shiow-yang Wu,et al.  Rule-based intelligent adaptation in mobile information systems , 2008, Expert Syst. Appl..

[23]  E. A. Edmonds,et al.  Flexibility in interface development , 1994 .

[24]  Markku Tukiainen,et al.  The expanding focus of HCI: case culture , 2006, NordiCHI '06.

[25]  Jungchul Park,et al.  Adaptable versus adaptive menus on the desktop : Performance and user satisfaction , 2007 .

[26]  Thorsten Joachims,et al.  The influence of task and gender on search and evaluation behavior using Google , 2006, Inf. Process. Manag..

[27]  Richard Cox,et al.  Attention design: Eight issues to consider , 2006, Comput. Hum. Behav..

[28]  Valeria Cardellini,et al.  Performance and Dependability in Service Computing : Concepts , Techniques and Research Directions , 2022 .

[29]  Mark A. Neerincx,et al.  Interaction design concepts for a mobile personal assistant , 2004 .

[30]  Jeffrey O. Kephart,et al.  MailCat: an intelligent assistant for organizing e-mail , 1999, AGENTS '99.

[31]  W. Wen,et al.  A knowledge-based intelligent electronic commerce system for selling agricultural products , 2007 .

[32]  Kristina Höök,et al.  Steps to take before intelligent user interfaces become real , 2000, Interact. Comput..

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

[34]  N. Basoglu,et al.  Exploring the Contribution of Information Systems User Interface Design Characteristics to Adoption Process , 2007, PICMET '07 - 2007 Portland International Conference on Management of Engineering & Technology.

[35]  Ying Liu,et al.  Service Composition Based Software Solution Design: A Case Study in Automobile Supply Chain , 2010, Int. J. Serv. Sci. Manag. Eng. Technol..

[36]  S. M. Alexander,et al.  A Study of the Cascading Effects of Ambulance Diversion among Hospitals , 2011, Int. J. Inf. Syst. Serv. Sect..

[37]  Shuk Ying Ho,et al.  The Attraction of Internet Personalization to Web Users , 2006, Electron. Mark..

[38]  B. Kargin,et al.  Factors Affecting the Adoption of Mobile Services , 2007, PICMET '07 - 2007 Portland International Conference on Management of Engineering & Technology.

[39]  Jadwiga Indulska,et al.  Adapting the Web interface: an adaptive Web browser , 2001, Proceedings Second Australasian User Interface Conference. AUIC 2001.