This study developed a model to empirically investigate the effects of market orientation and relationship orientation with suppliers on business performance and examine the moderating effects of entrepreneur's characteristics (working tenure) and clinic's location. The data was collected from 200 animal clinics which belong to Korean Animal Hospital Association (KAHA)'s national conference in April, 2007. Descriptive statistic, factor analysis, reliability analysis, and regression analysis were conducted to analyze the data using SPSS/PC+ 12.0. The findings are as follows. First, the market orientation of animal clinics influences significantly both financial and non-financial performance. When the moderating effect of entrepreneur's working tenure is considered, market orientation has significant effect on animal clinic's financial and non-financial performance. However, when the moderating effect of animal clinic's location is considered, market orientation has not significant effect on animal clinic's financial and non-financial performance. Second, animal clinic's relationship orientation with suppliers mostly affects the financial and non-financial performance significantly. When entrepreneur's working tenure in the clinic is longer (above 4 years group), relationship orientation with suppliers significantly affects both financial and non-financial performance. Meanwhile, when the entrepreneur's working tenure in the clinic is shorter (less than 3 years group), relationship orientation with suppliers doesn't affect clinic's financial performance but affect non-financial performance partially. In other words, when entrepreneur's working tenure is shorter (less than 3 years group), market orientation more influences on clinic's financial and non-financial performance while relationship orientation with suppliers does less. It is thought that their relation with suppliers and relationship orientation activities with suppliers are less strongly established and maintained yet. So, they primarily focus on market orientation strategy when entrepreneur's working tenure is shorter. Third, when animal clinics are located in non-metropolitan area, relationship orientation with suppliers significantly affects financial and non-financial performance. However, when animal clinics are located in metropolitan area, it doesn't affect financial and non-financial performance either. It is thought that animal clinics which are located in non-metropolitan area need stronger relationship with suppliers and need support more from them as most of suppliers actively work in metropolitan area not in the non-metropolitan area and animal clinics in metropolitan area can easily get better market information than animal clinics in non-metropolitan area. Lastly, while the effect of the market orientation significantly influences animal clinic's business performance continuously, the effect of the relationship orientation differently influences business performance as it is moderated by entrepreneur's working tenure and animal clinic's location. So, relationship orientation with suppliers can be selectively applied to improve the clinic's financial and no-financial performance. In summary, both of animal clinic's marketing orientation and animal clinic's relationship orientation with suppliers positively influence their business performance. However, entrepreneur's working tenure and animal clinic location moderate the relationship between market orientation and relationship orientation and their business performance differently. This study is quite meaningful to empirically investigate the effects of both of market orientation and relationship orientation with suppliers on business performance and examine the moderating effects of entrepreneur's characteristics (working tenure) and clinic's location. And, as this kind of study has been very few in the context of animal clinic industry, it helps practically understand the effects of market orientation and relationship orientation with suppliers on the financial and non-financial performance in animal clinic industry. Furthermore, as the market conditions in animal clinic industry have been in difficulty for a few years, this study can help improve animal clinic's financial and non-financial business performance together with their suppliers as business partners. Lastly, this study can help find mid-term and long-term cooperation between animal clinics and their suppliers. This study has some limitations. So, care should be taken when generalizing the results of the study. First, our samples were collected from only the animal clinics industry. However, a comparison of the results presented here with those form other marketing contexts (e.g., general hospitals) would be worthwhile. Future comparative research will enhance the generality of our contingency theory cross industry context. Second, this study found that market orientation and relationship orientation affect business performance. However, there may be other antecedents, such as internal market orientation and relationship orientation with customers. Also, this research did not consider other moderators, such as overall market conditions, competitive situations, and power/conflict between suppliers and buyers in the relationship between market and relationship orientation and business performance.
This study attempted to contribute to the clinical application of implant operation by making a quantitative nerve examination using a neurometer for the evaluation of sensory disturbances that could be incurred after the implantation in the dental clinics, and it intended to establish an objective guideline in the evaluation of sensory nerve after the operation of implant. An inspection was performed with the frequencies of 2000Hz, 250 Hz and 5 Hz before and after the operations of tooth implant using
The rural problems which we are facing start from the extremely small sized population and the skewed population structure by age and sex. Thus we analyzed the change of the rural population. And we analyzed the recent return migration to the rural areas by comparing the recent in-migrants with out-migrants to rural areas. And by analyzing the rural village survey data which was to show the current characteristics of rural population, we found out the effects of the in-migrants to the rural areas and predicted the futures of rural villages by characteristics. The changes of rural population composition by age was very clear. As the out-migrants towards cities carried on, the population composition of young children aged 0~4 years was low and the aged became thick. The proportion of the population aged 0~4 years was 45.1% of the total population in 1970 and dropped down to 20.4% in 1995, which is predicted to become under 20% from now on. In the same period(1970~1995), the population aged 65 years and over rose from 4.2% to 11.9%. In 1960, before industrialization, the proportion of the population aged 0~4 years in rural areas was higher than that of cities. As the rural young population continuously moves to cities it became lower than that in urban areas from 1975 and the gap grew till 1990. But the proportion of rural population aged 0~4 years in 1995 became 6.2% and the gap reduced. We can say this is the change of the characteristics of in-migrants and out-migrants in the rural areas. Also considering the composition of the population by age group moving from urban to rural area in the late 1980s, 51.8% of the total migrants concentrates upon age group of 20~34 years and these people's educational level was higher than that of out-migrants to urban areas. This fact predicted the changes of the rural population, and the results will turn out as a change in the rural society. However, after comparing the population structure between the pure rural village of Boeun-gun and suburban village of Paju-gun which was agriculture centered village but recently changed rapidly, the recent change of the rural population structure which the in-migrants to rural areas becomes younger is just a phenomenon in the suburban rural areas, not the change of the total rural areas in general. From the characteristics of the population structure of rural village from the field survey on these villages, we can see that in the pure rural villages without any effects from cities the regidents are highly aged, while industrialization and urbanization are making a progress in suburban villages. Therefore, the recent partial change of the rural population structure and the change of characteristics of the in-migrants toward rural areas is effecting and being effected by the population change of areas like suburban rural villages. Although there are return migrants to rural areas to change their jobs into agriculture, this is too minor to appear as a statistic effect.
According to the Internet Usage Research performed in 2016, the number of internet users and the internet usage have been increasing. Smartphone, compared to the computer, is taking a more dominant role as an internet access device. As the number of smart devices have been increasing, some views that the demand on high-speed internet will decrease; however, Despite the increase in smart devices, the high-speed Internet market is expected to slightly increase for a while due to the speedup of Giga Internet and the growth of the IoT market. As the broadband Internet market saturates, telecom operators are over-competing to win new customers, but if they know the cause of customer exit, it is expected to reduce marketing costs by more effective marketing. In this study, we analyzed the relationship between the cancellation rates of telecommunication products and the factors affecting them by combining the data of 3 cities, Anyang, Gunpo, and Uiwang owned by a telecommunication company with the regional data from KOSIS(Korean Statistical Information Service). Especially, we focused on the assumption that the neighboring areas affect the distribution of the cancellation rates by coupling type, so we conducted spatial cluster analysis on the 3 types of cancellation rates of each region using the spatial analysis tool, SatScan, and analyzed the various relationships between the cancellation rates and the regional data. In the analysis phase, we first summarized the characteristics of the clusters derived by combining spatial information and the cancellation data. Next, based on the results of the cluster analysis, Variance analysis, Correlation analysis, and regression analysis were used to analyze the relationship between the cancellation rates data and regional data. Based on the results of analysis, we proposed appropriate marketing methods according to the region. Unlike previous studies on regional characteristics analysis, In this study has academic differentiation in that it performs clustering based on spatial information so that the regions with similar cancellation types on adjacent regions. In addition, there have been few studies considering the regional characteristics in the previous study on the determinants of subscription to high-speed Internet services, In this study, we tried to analyze the relationship between the clusters and the regional characteristics data, assuming that there are different factors depending on the region. In this study, we tried to get more efficient marketing method considering the characteristics of each region in the new subscription and customer management in high-speed internet. As a result of analysis of variance, it was confirmed that there were significant differences in regional characteristics among the clusters, Correlation analysis shows that there is a stronger correlation the clusters than all region. and Regression analysis was used to analyze the relationship between the cancellation rate and the regional characteristics. As a result, we found that there is a difference in the cancellation rate depending on the regional characteristics, and it is possible to target differentiated marketing each region. As the biggest limitation of this study and it was difficult to obtain enough data to carry out the analyze. In particular, it is difficult to find the variables that represent the regional characteristics in the Dong unit. In other words, most of the data was disclosed to the city rather than the Dong unit, so it was limited to analyze it in detail. The data such as income, card usage information and telecommunications company policies or characteristics that could affect its cause are not available at that time. The most urgent part for a more sophisticated analysis is to obtain the Dong unit data for the regional characteristics. Direction of the next studies be target marketing based on the results. It is also meaningful to analyze the effect of marketing by comparing and analyzing the difference of results before and after target marketing. It is also effective to use clusters based on new subscription data as well as cancellation data.
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.