• Journal of Korean Society for Quality Management
• /
• v.51 no.4
• /
• pp.691-700
• /
• 2023

Purpose: This study aims to analyze the diffusion pattern of the Mongolian mobile phone market. In particular, we used a generalized diffusion model to explore the factors affecting market potenial. Methods: We used three diffusion models to estimate the number of mobile subscribers in Mongolia. Based on the Logistic model with the best fitness, we introduced time-varying market potential and explored the influence of various independent variables such as GDP and inflation. Results: Among the basic diffusion models, the Logistic model was the best in terms of estimation performance and statistical significance. The estimation results of the Generalized Logistic model confirm that investment in the telecommunication sector has a significant positive effect on market potential. The estimation of the Generalized Logistic model effectively describes the continuous growth of the Mongolian telecommunications market until recently. Conclusion: We have analyzed the diffusion pattern of the Mongolian telecommunications market and found that the amount of investment in the sector leads to the growth of the market size. This study is original in terms of its subject - Mongolian telecommunications market and methodology - time-varying market potential.

• ETRI Journal
• /
• v.36 no.3
• /
• pp.490-497
• /
• 2014

The market performance of WiBro in Korea has not been as expected, and its rapid diffusion in the near future is unlikely owing to the existence of competing services. There has been little research on the factors affecting this low market diffusion. This study is based on an analytical framework in which a lack of service capability and the insufficiency of service-related activities have resulted in the current poor market performance. An expert survey was conducted on WiBro specialists and verified using the analytical hierarchy process method. The result of this analysis is as follows: underinvestment in network deployment and marketing, insufficient promotional policies, and a shortage of service capabilities are to be analyzed as the main causes of WiBro's low market diffusion.

• Journal of Korean Institute of Industrial Engineers
• /
• v.40 no.4
• /
• pp.415-423
• /
• 2014

In recent decades, RFID (Radio Frequency IDentification) technology has been recognized as one of the most core competencies in implementing ubiquitous society. However, Korea has not seen good success in diffusion of RFID even though Korean government continues funding many projects to diffuse the technology in industries. Most previous researches overestimate the growth of Korean RFID market in contrary to real market situation. This study aims to analyze the Korean RFID market and find a reasonable forecasting model for it. Our experimental results show that Bass forecasting model provides the more realistic estimates than any other models and the analyses of forecasting error provide useful information for the better forecasting. We also observed that government policy plays a crucial role in the diffusion of RFID technology in Korea.

• Journal of the Korea Society for Simulation
• /
• v.20 no.2
• /
• pp.29-40
• /
• 2011

This paper focuses on the sensitivity analysis for the calibration of an agent-based simulation that analyzes the brand-level diffusion dynamics of competing products in the domestic premium mid-sized car market. In this paper, we employ a consumer-agent model that imitates the purchasing characteristics and behaviors of the consumers. The group of consumer agents that are socially interconnected represents a virtual market. By spreading the product information from previous adopters to potential consumer agents in the virtual market, the word-of-mouth phenomenon emerges like in the real market. The phenomenon influences the product choice of potential consumer agents that causes the variation of the product diffusion dynamics. In this simulation model, it is important to calibrate the virtual market parameters(e.g., ratio of innovators, social network structure, purchase time decision method) so that the virtual market can simulate the real market. However, it is difficult to measure these parameters directly from the real market. In this paper, we analyze the diffusion dynamics of simulations under various conditions in comparison with real sales data to calibrate the parameters.

• Journal of Distribution Research
• /
• v.15 no.4
• /
• pp.61-85
• /
• 2010

Introduction: Diffusion is process by which an innovation is communicated through certain channel overtime among the members of a social system(Rogers 1983). Bass(1969) suggested the Bass model describing diffusion process. The Bass model assumes potential adopters of innovation are influenced by mass-media and word-of-mouth from communication with previous adopters. Various expansions of the Bass model have been conducted. Some of them proposed a third factor affecting diffusion. Others proposed multinational diffusion model and it stressed interactive effect on diffusion among several countries. We add a spatial factor in the Bass model as a third communication factor. Because of situation where we can not control the interaction between markets, we need to consider that diffusion within certain market can be influenced by diffusion in contiguous market. The process that certain type of retail extends is a result that particular market can be described by the retail life cycle. Diffusion of retail has pattern following three phases of spatial diffusion: adoption of innovation happens in near the diffusion center first, spreads to the vicinity of the diffusing center and then adoption of innovation is completed in peripheral areas in saturation stage. So we expect spatial effect to be important to describe diffusion of domestic discount store. We define a spatial diffusion model using multinational diffusion model and apply it to the diffusion of discount store. Modeling: In this paper, we define a spatial diffusion model and apply it to the diffusion of discount store. To define a spatial diffusion model, we expand learning model(Kumar and Krishnan 2002) and separate diffusion process in diffusion center(market A) from diffusion process in the vicinity of the diffusing center(market B). The proposed spatial diffusion model is shown in equation (1a) and (1b). Equation (1a) is the diffusion process in diffusion center and equation (1b) is one in the vicinity of the diffusing center. $$\array{{S_{i,t}=(p_i+q_i{\frac{Y_{i,t-1}}{m_i}})(m_i-Y_{i,t-1})\;i{\in}\{1,{\cdots},I\}\;(1a)}\\{S_{j,t}=(p_j+q_j{\frac{Y_{j,t-1}}{m_i}}+{\sum\limits_{i=1}^I}{\gamma}_{ij}{\frac{Y_{i,t-1}}{m_i}})(m_j-Y_{j,t-1})\;i{\in}\{1,{\cdots},I\},\;j{\in}\{I+1,{\cdots},I+J\}\;(1b)}}$$ We rise two research questions. (1) The proposed spatial diffusion model is more effective than the Bass model to describe the diffusion of discount stores. (2) The more similar retail environment of diffusing center with that of the vicinity of the contiguous market is, the larger spatial effect of diffusing center on diffusion of the vicinity of the contiguous market is. To examine above two questions, we adopt the Bass model to estimate diffusion of discount store first. Next spatial diffusion model where spatial factor is added to the Bass model is used to estimate it. Finally by comparing Bass model with spatial diffusion model, we try to find out which model describes diffusion of discount store better. In addition, we investigate the relationship between similarity of retail environment(conceptual distance) and spatial factor impact with correlation analysis. Result and Implication: We suggest spatial diffusion model to describe diffusion of discount stores. To examine the proposed spatial diffusion model, 347 domestic discount stores are used and we divide nation into 5 districts, Seoul-Gyeongin(SG), Busan-Gyeongnam(BG), Daegu-Gyeongbuk(DG), Gwan- gju-Jeonla(GJ), Daejeon-Chungcheong(DC), and the result is shown