Ronald Baganzi

Dr. Ronald Baganzi is a Financial Analyst and Researcher at the Central Bank of Uganda. He is also a Researcher at the Center for Global Innovation & Entrepreneurship, Kyung Hee University. He holds a Ph.D. in Business Administration from Kyung Hee University, Seoul, South Korea. He earned a Masters in Finance from KAIST University (Korea Advanced Institute of Science and Technology), Seoul, South Korea and a BCOM (Accounting) degree from Makerere University in Uganda. His research interests are in: Choice Modelling; Artificial Intelligence and Internet Fraud; Technology Management Research; Mobile Payments Research; Internet Banking Research; Marketing Research; Consumer Behavior; Financial Engineering; Econometrics; Accounting and Audit; Financial Stability (Macroprudential Policy Analysis, Fiscal Sustainability and Stress Testing).

During his studies, Ronald was awarded a Sawtooth Software Grant that helped him to design a quantitative, quasi-experiment using choice-based conjoint (CBC) analysis. He was able to publish an article entitled “Using Choice-Based Conjoint Analysis to Determine Smartphone Choice - a Student’s Perspective”.

Abstract

The ability of smartphones to facilitate various services like Mobile Banking, e-commerce and Mobile Payments has made them part of consumers’ lives. Conjoint analysis (CA) is a Marketing Research approach used to assess how consumers’ preferences for products or services develop. The potential applications of CA are numerous in consumer electronics, banking and insurance services, job selection and workplace loyalty, consumer packaged goods, and travel and tourism. Choice-Based Conjoint (CBC) analysis is the most commonly used CA approach in Marketing Research. The purpose of this study is to utilize CBC analysis to investigate the relative importance of smartphone attributes that influence consumer smartphone preference. An experiment was designed using the Sawtooth CBC Software. 326 students attempted the online survey. Utility values were derived by Hierarchical Bayes (HB) estimation and used to explain consumers’ smartphone preferences. All the six attributes used for the study were found to significantly influence smartphone preference. Smartphone brand was the most important, followed by the price, camera, RAM, battery life, and storage. This study is one of the first to use Sawtooth CBC analysis to assess consumer smartphone preference based on the six attributes. We provide implications for the development of new smartphones based on attributes.

Keywords: Conjoint Analysis, Consumer Preference, Hierarchical Bayes Model, Part-worth Utility, Smartphones