Jungwoo Shin

Strategic Management of Cloud Computing Services: Focusing on Consumer Adoption Behavior

The emergence of cloud computing services has led to an increased interest in the technology among the general public and enterprises marketing these services. Although there is a need for studies with a managerial relevance for this emerging market, the lack of market analysis hampers such investigations. Therefore, this study focuses on the end-user market for cloud computing in Korea. We conduct a quantitative analysis to show consumer adoption behavior for these services, particularly infrastructure as a service (IaaS). Bayesian mixed logit model and the multivariate probit model are used to analyze the data collected by a conjoint survey. From this analysis, we find that the service fee and stability are the most critical adoption factors. We also present an analysis on the relationship between terminal devices and IaaS, classified by core attributes such as price, stability, and storage capacity. From these relationships, we find that larger storage capacity is more important for mobile devices such as laptops than desktops. Based on the results of the analysis, this study also recommends useful strategies to enable enterprise managers to focus on more appropriate service attributes, and to target suitable terminal device markets matching the features of the service.

Strategic demand forecasts for the tablet PC market using the Bayesian mixed logit model and market share simulations

Since the release of the Apple iPad and the explosion of consumer demand for tablet PCs, a number of companies are entering into the tablet PC market, creating a situation that is becoming more fiercely competitive, complex, and difficult to predict. Under the singularity of the Korean tablet PC market, into which both the iPad and Galaxy Tab (with an Android operating system) were simultaneously released, this study closely analyses consumer preferences for tablet PCs. It uses the Bayesian mixed logit model, which can reflect consumers’ heterogeneous preferences based on data collected from a conjoint method, and using the estimates of the consumer utility function with model verification, it offers forecasts for the tablet PC market under six likely situations.

Model for studying commodity bundling with a focus on consumer preference

This research complements the demand-side analysis of previous commodity bundling studies. Most previous have researchers analyzed the effects of commodity bundling by focusing on firm behavior and have assumed a simple consumer utility that does not reflect the heterogeneity of consumer preference. However, to measure the results of competition with the bundling strategy, an analysis of commodity bundling based on consumer preference is useful. Unlike previous studies, this study proposes a model that directly analyzes consumer behavior for commodity bundling and incorporates consumer heterogeneity to measure the consumer utility derived from bundled commodities. To validate the model, we used data on service subscriptions and usage of information communication technology in Korea, including fixed phone service, mobile service, and Internet. The empirical results show that the proposed model is useful in analyzing the effects of bundling for various services and products.

Economic valuation of noise pollution control policy: does the type of noise matter?

As the average noise level and number of noise sources have increased, governments have taken various measures to make soundscapes sustainable. Wise policy decisions require information about the monetary value of noise-control policies. This study elicited people’s willingness to pay (WTP) for noise policies, separating traffic noise from residential noise to compare the value of controlling different types of noise. The contingent valuation method was used for the empirical analysis, with data from South Korea. The results show that the monthly mean WTP of respondents was KRW 3392.3 for residential noise reduction and KRW 3507.1 for transport noise reduction; thus, the WTP for the latter is slightly higher than that for the former. Moreover, about 80% of people are unwilling to pay for a noise policy at all, and that high ratio of people with zero WTP must be taken into consideration in the process of policy formulation and implementation. Respondents’ experiential and psychological factors were found to be more important than their demographics in explaining their WTP for a noise policy. Potential policy implications based on the analysis results are provided.