Mentor: Dr. Selwyn Piramuthu
College of Warrington College of Business
"The usage of mobile applications has exploded within the past few years because it offers benefits such as convenience, entertainment, and social functions. More recently, the emergence of app development tools allow users to create their own mobile applications, and make a profit off of their creations. However, with the millions of apps already created, more than 99.99% of them fail according to Forbes (2014). What aspects should mobile app developers focus on even before developing their app to raise their chances of success? I'm conducting this research to answer this question. Upon completion, the results will not only contribute to this domain of research, but also provide meaningful implications that can be used in the mobile applications industry."
Information Systems and Operations Management
- Mobile Applications
- Technology Acceptance
- Information Systems
- Florida Bright Futures Academic Scholar
- President's Honor Roll
- Warrington College of Business Dean's List
- United Way Volunteer Income Tax Assistant
Hobbies and Interests
- Anything outdoors
Model of Acceptance and Use of Mobile Applications
The purposes of this study are to: (a) identify specific characteristics of mobile apps that influence consumer attitude, adopt intention, and adoption, and (b) examine the moderator role of product type (hedonic vs. functional products). For the purposes of the study, two research questions were developed: Which particular characteristics of mobile apps influence consumer attitude, adopt intention, and adoption? And is there any significant moderator role of product type in this relationship? I modified the Unified Theory of Acceptance and Use of Technology (UTAUT2) model to create a model that is more fitting to mobile app development, entitled as the Model of Acceptance and Use of Mobile Applications (MAUMA). “Behavioral Intention” was replaced with “Adopt Intention,” and “Use Behavior” was replaced with “Adopt” to better suit the mobile application context. Also, the original factors (Performance Expectancy, Effort Expectancy, etc.) were grouped into two categories: Consumer Characteristics and Mobile App Characteristics. “Hedonic vs. Utilitarian product” and “Intrinsic vs. Extrinsic Motivators” replaced “Age,” “Gender,” and “Experience” as moderators. Finally, “Attitude” was added in order to represent the consumer’s preconceived attitude toward the app before intending to use it. To test this research model, I plan to collect data using Amazon Mechanical Turk. The target sample size is 500. First, the descriptive statistics will be employed. The efficacy of the model will be tested through structure equation modelling. Psychometric property of the measures will be tested through confirmatory factor analysis.