• Journal of Global Scholars of Marketing Science
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• v.18 no.4
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• pp.33-59
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• 2008

This paper aims to analyse the preference for German farm tourism among the German population. For this reason, we conducted an empirical study in Germany during summer 2007 and we applieda structural equation model based on partial leasts quares(PLS) to analyse the data. In the following chapters we will introduce the literature review and our conceptual frame work. We will then outline the procedures we adopted and the results of the empirical analysis. In the final part so me conclusions will be presented and a discussion will follow in order to draw the future directions of our research. According to our hypotheses, the possibility that agri-tourism enters in the evoked set of an individual is higher: H1: The higher the information degree about it. H2: The lower the influence of the social stimuli. H3: The higher the physical exposure to it (experience). H4: The higher the wellness image of agri-tourism. H5: The higher the traditional image of agri-tourism. H6: The higher the exciting image of agri-tourism. H7: The higher the perceived value for money. Our further hypotheses affirm that the possibility that agri-tourism enters in the evoked set of an individual is higher: H8: The lower the perceived risk. H9: The higher the motive to enjoy a holiday in the nature. H10: The higher the motive to enjoy a sport holiday. H11: The lower the motive to have an organized holiday. H12: The lower the motive to have a holiday abroad. H13: The lower the motive of action and night life. H14: The higher the motive to spend a holiday with the family. H15: The lower the motive to spend a city holiday. Finally, our model has some socio-demographics data. As we mentioned before, German agri-tourism has traditionally been the travel destination of large-size families, with low-to-middle income. For that reason, our final hypothesises are the following: the possibility that agri-tourism enters in the evoked-set of an individual is higher: H16: The higher the number of family members. H17: The lower the family income. Since in this study we use a path model with a PLS approach, we are able to state some interrelations among the exogenous latent variables: H18: The motive of sport holiday has a positive influence towards nature motives. H19: The physical exposition to agri-tourism has a positive influence toward information. H20: The motive of family holiday has a negative influence toward the motive of action and night life. H21: Social stimuli have a positive influence towards individuals risk perceptions. H22: Social stimuli have negative influence towards experience. Data for this study were gathered via administrated questionnaires during the summer 2007 within the frame of an academic "marketing research" course. The corresponding t-values are assessed using the bootstrapping method with 500 re-samples. In our model 61% of the degree of appreciation of German agri-tourism (evoked set) is explained by five independent variables: value for money ($0.335^{{\ast}{\ast}{\ast}}$) (H7) experience ($0.267^{{\ast}{\ast}}$) (H3), exciting image ($0.204^{\ast}$) (H6) organisation ($-0.162^{\ast}$) (H11) and holiday abroad ($-0.156^{\ast}$) (H12). The variance explained ($R^2$) for the other endogenous variables are the following: nature 24.3%, information 14.1%, action holiday 13.8%, risk perception 5.8% and experience 2.4%. An overview can be inferred from table 5. The results also allow us to test each of the proposed hypotheses. With exception of organization and abroad, none of the others travel style factors (H9 to H15) seem to have any significant impact towards evoked set which leads to the rejection of the respective hypotheses. As expected, social stimuli have a significant influence on individuals' risk perception (H21 accepted), however neither the former nor the latter have a valuable impact on evoked set (rejection of H2 and H8). Besides, since the influence of social stimuli towards experience is not significant, also H22 has to be rejected. Experience influences information (H19 accepted) but the latter does not affect significantly the evoked set (H1 rejected). Both H4 as well as H5, referring respectively to the perceived images of German agri-tourism as a wellness destination and the traditional image of the German farm tourism have to be rejected. Finally, none of the demographic data included in the model explains significantly the variance of the factor evoked set. Therefore neither H16 nor H17 has been accepted. As far as the interrelation between sport and nature (H18) and family and action (H20) are concerned, the stated relationship among these variables has been statistically confirmed. Our path model based on partial least squares shows the factors influencing the preference for farm tourism in Germany. Among others value for money and experience are the most significant ones. Practical implications are discussed.

• Korean Journal of Microbiology
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• v.51 no.2
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• pp.97-107
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• 2015

Wetlands constitute a transitional zone between terrestrial and aquatic ecosystems and have unique characteristics such as frequent inundation, inflow of nutrients from terrestrial ecosystems, presence of plants adapted to grow in water, and soil that is occasionally oxygen deficient due to saturation. These characteristics and the presence of vegetation determine physical and chemical properties that affect decomposition rates of organic matter (OM). Decomposition of OM is associated with activities of various extracellular enzymes (EE) produced by bacteria and fungi. Extracellular enzymes convert macromolecules to simple compounds such as labile organic carbon (C), nitrogen (N), phosphorus (P), and sulfur (S) that can be easily taken up by microbes and plants. Therefore, the enzymatic approach is helpful to understand the decomposition rates of OM and nutrient cycling in wetland soils. This paper reviews the physical and biogeochemical factors that regulate extracellular enzyme activities (EEa) in wetland soils, including those of ${\beta}$-glucosidase, ${\beta}$-N-acetylglucosaminidase, phosphatase, arylsulfatase, and phenol oxidase that decompose organic matter and release C, N, P, and S nutrients for microbial and plant growths. Effects of pH, water table, and particle size of OM on EEa were not significantly different among sites, whereas the influence of temperature on EEa varied depending on microbial acclimation to extreme temperatures. Addition of C, N, or P affected EEa differently depending on the nutrient state, C:N ratio, limiting factors, and types of enzymes of wetland soils. Substrate quality influenced EEa more significantly than did other factors. Also, drainage of wetland and increased temperature due to global climate change can stimulate phenol oxidase activity, and anthropogenic N deposition can enhance the hydrolytic EEa; these effects increase OM decomposition rates and emissions of $CO_2$ and $CH_4$ from wetland systems. The researches on the relationship between microbial structures and EE functions, and environmental factors controlling EEa can be helpful to manipulate wetland ecosystems for treating pollutants and to monitor wetland ecosystem services.

• Magazine of the Korean Society of Agricultural Engineers
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• v.19 no.1
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• pp.4279-4295
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• 1977

Two types of model were established in order to product the soil moisture content by which information on irrigation could be obtained. Model-I was to represent the soil moisture depletion and was established based on the concept of water balance in a given soil profile. Model-II was a mathematical model derived from the analysis of soil moisture variation curves which were drawn from the observed data. In establishing the Model-I, the method and procedure to estimate parameters for the determination of the variables such as evapotranspirations, effective rainfalls, and drainage amounts were discussed. Empirical equations representing soil moisture variation curves were derived from the observed data as the Model-II. The procedure for forecasting timing and amounts of irrigation under the given soil moisture content was discussed. The established models were checked by comparing the observed data with those predicted by the model. Obtained results are summarized as follows: 1. As a water balance model of a given soil profile, the soil moisture depletion D, could be represented as the equation(2). 2. Among the various empirical formulae for potential evapotranspiration (Etp), Penman's formula was best fit to the data observed with the evaporation pans and tanks in Suweon area. High degree of positive correlation between Penman's predicted data and observed data with a large evaporation pan was confirmed. and the regression enquation was Y=0.7436X+17.2918, where Y represents evaporation rate from large evaporation pan, in mm/10days, and X represents potential evapotranspiration rate estimated by use of Penman's formula. 3. Evapotranspiration, Et, could be estimated from the potential evapotranspiration, Etp, by introducing the consumptive use coefficient, Kc, which was repre sensed by the following relationship: Kc=Kco$.$Ka＋Ks‥‥‥(Eq. 6) where Kco : crop coefficient Ka : coefficient depending on the soil moisture content Ks : correction coefficient a. Crop coefficient. Kco. Crop coefficients of barley, bean, and wheat for each growth stage were found to be dependent on the crop. b. Coefficient depending on the soil moisture content, Ka. The values of Ka for clay loam, sandy loam, and loamy sand revealed a similar tendency to those of Pierce type. c. Correction coefficent, Ks. Following relationships were established to estimate Ks values: Ks=Kc-Kco$.$Ka, where Ks=0 if Kc,=Kco$.$K0$\geq$1.0, otherwise Ks=1-Kco$.$Ka 4. Effective rainfall, Re, was estimated by using following relationships : Re=D, if R-D$\geq$0, otherwise, Re=R 5. The difference between rainfall, R, and the soil moisture depletion D, was taken as drainage amount, Wd. {{{{D= SUM from { {i }=1} to n (Et-Re-I+Wd)}}}} if Wd=0, otherwise, {{{{D= SUM from { {i }=tf} to n (Et-Re-I+Wd)}}}} where tf=2∼3 days. 6. The curves and their corresponding empirical equations for the variation of soil moisture depending on the soil types, soil depths are shown on Fig. 8 (a,b.c,d). The general mathematical model on soil moisture variation depending on seasons, weather, and soil types were as follow: {{{{SMC= SUM ( { C}_{i }Exp( { - lambda }_{i } { t}_{i } )+ { Re}_{i } - { Excess}_{i } )}}}} where SMC : soil moisture content C : constant depending on an initial soil moisture content $\lambda$ : constant depending on season t : time Re : effective rainfall Excess : drainage and excess soil moisture other than drainage. The values of $\lambda$ are shown on Table 1. 7. The timing and amount of irrigation could be predicted by the equation (9-a) and (9-b,c), respectively. 8. Under the given conditions, the model for scheduling irrigation was completed. Fig. 9 show computer flow charts of the model. a. To estimate a potential evapotranspiration, Penman's equation was used if a complete observed meteorological data were available, and Jensen-Haise's equation was used if a forecasted meteorological data were available, However none of the observed or forecasted data were available, the equation (15) was used. b. As an input time data, a crop carlender was used, which was made based on the time when the growth stage of the crop shows it's maximum effective leaf coverage. 9. For the purpose of validation of the models, observed data of soil moiture content under various conditions from May, 1975 to July, 1975 were compared to the data predicted by Model-I and Model-II. Model-I shows the relative error of 4.6 to 14.3 percent which is an acceptable range of error in view of engineering purpose. Model-II shows 3 to 16.7 percent of relative error which is a little larger than the one from the Model-I. 10. Comparing two models, the followings are concluded: Model-I established on the theoretical background can predict with a satisfiable reliability far practical use provided that forecasted meteorological data are available. On the other hand, Model-II was superior to Model-I in it's simplicity, but it needs long period and wide scope of observed data to predict acceptable soil moisture content. Further studies are needed on the Model-II to make it acceptable in practical use.

• Journal of Elementary Mathematics Education in Korea
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• v.9 no.2
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• pp.85-110
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• 2005

The purpose of this study is to examine the characteristics of visual representation used in problem solving process and examine the representation types the students used to successfully solve the problem and focus on systematizing the visual representation method using the condition students suggest in the problems. To achieve the goal of this study, following questions have been raised. (1) what characteristic does the representation the elementary school students used in the process of solving a math problem possess? (2) what types of representation did students use in order to successfully solve elementary math problem? 240 4th graders attending J Elementary School located in Seoul participated in this study. Qualitative methodology was used for data analysis, and the analysis suggested representation method the students use in problem solving process and then suggested the representation that can successfully solve five different problems. The results of the study as follow. First, the students are not familiar with representing with various methods in the problem solving process. Students tend to solve the problem using equations rather than drawing a diagram when they can not find a word that gives a hint to draw a diagram. The method students used to restate the problem was mostly rewriting the problem, and they could not utilize a table that is essential in solving the problem. Thus, various errors were found. Students did not simplify the complicated problem to find the pattern to solve the problem. Second, the image and strategy created as the problem was read and the affected greatly in solving the problem. The first image created as the problem was read made students to draw different diagram and make them choose different strategies. The study showed the importance of first image by most of the students who do not pass the trial and error step and use the strategy they chose first. Third, the students who successfully solved the problems do not solely depend on the equation but put them in the form which information are decoded. They do not write difficult equation that they can not solve, but put them into a simplified equation that know to solve the problem. On fraction problems, they draw a diagram to solve the problem without calculation, Fourth, the students who. successfully solved the problem drew clear diagram that can be understood with intuition. By representing visually, unnecessary information were omitted and used simple image were drawn using symbol or lines, and to clarify the relationship between the information, numeric explanation was added. In addition, they restricted use of complicated motion line and dividing line, proper noun in the word problems were not changed into abbreviation or symbols to clearly restate the problem. Adding additional information was useful source in solving the problem.

• Korean Journal of Agricultural and Forest Meteorology
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• v.1 no.1
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• pp.41-51
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• 1999

This study was conducted to investigate the effects of local climatic conditions on the annual increment of Korean white pine planted in Gapyung and Yaungdong. For this, stand variables such as mean DBH, mean height, basal area per hectare, and volume per hectare by stand age were measured and summarized for each locality. Based on these statistics, annual increments for 8 years from stand age 10 to 18 were calculated for each of stand variables. A topoclimatological technique which makes use of empirical relationships between the topography and the weather in study sites was applied to produce normal estimates of monthly mean, maximum, minimum temperatures, relative humidity, precipitation, and hours of sunshine. Then, the yearly climatic variables from 1990 to 1997 for each study site were derived from the spatial interpolation procedures based on inverse- distance weighting of the observed deviation from the climatic normals at the nearest 11 standard weather stations. From these estimates, 17 weather variables such as warmth index, coldness index, index of aridity etc., which affect the tree growth, were computed on yearly base for each locality. The deviations of measured annual increments from the expected annual increments for 8 years based on yield table of Korean white pine were then correlated with and regressed on the yearly weather variables to examine effects of local climatic conditions on the growth. Gapyung area provides better conditions for the growth of Korean white pine in the early stage than Youngdong area. This indicates that the conditions such as low temperature, high relative humidity, and large amount of precipitation provide favor environment for the early growth of Korean white pine. A ccording to the correlation and regression an analysis using local climatic conditions and annual increments, the growth pattern of Gapyung area corresponds to this tendency. However, it was found that the relationship between annual increments and local climatic conditions in Youngdong area shows different tendency from Gapyung. These results mean that the yearly growth pattern could not sufficiently be explained by climatic conditions with high variance in yearly weather variables. In addition, the poor growth in Youngdong area might not only be affected by climatic conditions, but also by other environmental factors such as site quality.

• Korean Journal of Heritage: History & Science
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• v.42 no.3
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• pp.26-47
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• 2009

This study examined dwelling site from among the sites of the Neolithic age found in the Asan Bay(牙山灣) area, and the temporal-spatial location and meaning of the dwelling site (settlement). The majority of the settlements in the area are of a square style but some coexist with rectangular-style settlements, which is noteworthy. The dwelling sites of the Neolithic age found in Asan Bay area are mostly located in a ridge of hilly areas, divided into gentle, low areas (20~50 meters above sea level) and relatively high areas (50~80 meters above the sea level). Although location strongly corresponded to the residents' subsistence and the technical levels within the culture, it likely was greatly affected by natural environment where they lived, as well. In examining radiocarbon dating results and the excavated artifacts, the settlements found in Asan Bay were determined to belong to the period II(3,500~3,000 B.C.) stated in the Relative Chronological table of Dwelling sites in the Neolithic age, written by the author. Said Dwelling sites are proven to have a close relationship with those found on the coast of Gyeonggi Province(京畿道) and in the Geum River(錦江) valley. This is deemed to be the result of expansion and interchange between Gyeonggi Province(京畿道) group and Geum River(錦江) valley group, who constituted the large settlements. Additionally, the Daecheon-ri type dwelling sites in the Geum River valley were verified to be the result of exchange, and spread to the Asan Bay area in the same era. Two forms of Dwelling sites coexisted dynamically in the Asan Bay area around 3,500 B.C. Such a phenomenon resulted primarily from the expansion of the dwelling site due to the introduction of primitive agriculture, as well as environmental (temperature), biological and social changes at those times.

• Magazine of the Korean Society of Agricultural Engineers
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• v.11 no.1
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• pp.1534-1548
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• 1969

This experiment was conducted, making use of the 'NONG-RIM6' arecommended variety of rice for the year of 1968. Main purposes of the experiment are to explore possibilities of; a) ways and means of saving irringation water and, b) overcoming drought at the same time so that an increased yield in rice could be resulted in. Specifically, it was tried to determine the effects of the Rotation irrigation method combined with differentiated thickness of lining upon the growth and yield of rice. Some of the major findings are summarized in the following. 1) The different thicknesses show a significant relationship with the weight of 1,000 grains. In the case of 9cm lined plot, the grain weight is 23.5grams, the heaviest. Next in order is 3cm lined plot, 6cm lined plot, control plot, and wheat straw lined-plot. 2) In rice yield, it is found that there is a considerably moderate significant relationship with both the different thickness of lining and the number of irrigation, as shown in the table. 3) There is little or no difference among different plots in terms of a) physical and chemical properties of soil, b) quality of irrigation water, c) climatic conditions, and rainfalls. 4) It is found that there is a significant relationship between differences in the method of rotation irrigation and the number of ears per hill. The plot irrigated at an interval of 7 days shows 17.4 ears and plot irrigated at an interval of 6 days, 16.3 5) In vinyl-treated plots, it is shown that both yield and component elements are greatest in the case of the plot ith whole of $3cm/m^2$ Next in order are the plot with a hole of $2cm/m^2$ the plot with a hole of $1cm/m^2$ In the case of the plot with no hole it is found that both yield and component elements are decreased as compared to the control plot. 6) The irrigation water reqirement is measured for the actual irrigation days of 72 which are the number subtracted the days of rainfall of 30 from the total irrigation days of 102. It is found that the irrigation water requirement for the uncontrol plot is 1,590mm as compared to 876mm(44.9% saved) for the 9cm-lined plot, 959mm(39.7% saved) for the 6cm-lined plot 1,010mm(36% saved) for the 3cm-lined plot and 1,082mm(32% saved) for the wheat straw lined plot. In the case of the Rotation irrigation method it is found that the water requirement for the plot irrigated at an interval of 8 days is 538mm(65% saved), as compared to 617mm(61.6% saved) for plot irrigated at an interval of 7 day 672mm(57.7% saved) for plot irrigated at an interval of 6day, 746mm(53.0% saved) for the plot irrigated at an interval of 5 days, 890mm 44.0% saved) for the plot irrigated at an interval of 4 days, and 975mm(38.6% saved) for the plot irrigated at an interval of 3 days. 7) The rate of evapotranspiration is found 2.8 around the end of month of July, as compared to 2.6 at the begining of August 3.4 around the end of August and 2.6 at the begining of August 3.4 around the end of August and 2.6 at the begining of September. 8) It is found that the saturation quantity of 30mm per day is decreased to 20mm per day though the use of vinyl covering. 9) The husking rate shows 75 per cent which is considered better.

• Magazine of the Korean Society of Agricultural Engineers
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• v.11 no.1
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• pp.1561-1579
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• 1969

In Korea, the duty of water in paddy fields was measured at the Agricultural Experimental Station in Suwon about 60 years ago. After that time some testing has been made in several places, but the key points in its experiment were the water depth of evapo-transpiration. Improved breeds, progress in cultivation and management techniques as well as development of measuring apparatus in recent years have necessitated the review of the duty of water in paddy fields. The necessity of reviewing the conventional methods has become even more important, as no source of information has been made available through survey of water utilization on a soil use basis which requires data on peculiar features of the water depth of evapo-transpiration. For example, the duty of water in paddy field is largely affected by the water depth of evapo-transpiration in connection with the wetted paddy field, whereas in connection with the normal paddy fields without this characteristic the vertical percolation become the predominant factor in measuring the decreasing depth of water. Therefore, it becomes important. that not only the water depth of evapotranspiration but also the vertical percolation process should also be observed in order to arrive at a realistic conclusion. As the vertical percolation has aclose relationship to the height of the underground water, the change of the latter can be measured. As the conclusion of this experiment, the following subjects are indicated. 1. In order to determine the economic duty of water in paddy fields on a basis of varying soil features, the varying soil features in the benifited area should be investigated thoroughly. The water depths of evapo-transpiration(ET) ratio to evaporation in the evaporator(V) on a basis of the varying soil features are as follows: clay loam ET/V = 1.11, loam ET/V = 1.64, sandy loam ET.V = 1.63 2. The decreasing depth of water consists of the water depth of evapotranspiration, the vertical per colation and the percolation of foot path. Among these three, the percolation of foot path can be utilized again. 3. As the result of this experiment, it shows the decreasing depth of water as follows. clay loam 9.3 mm/day, loam 13.5mm/daty, sandy loam 15.3mm/day 4. On a basis of the varying soil features and the height of the underground water, the vertical percolation varies. 5. The change of the vertical percolation on a basis of the varying soil features shows as follows: clay loam $1{\sim}2$ mm/day, loam $2{\sim}3$mm/day, sandy loam $3{\sim}4$mm/day 6. The level of the underground water changes sensibly by priority of clay loam, loam, sandy loam. When it rains, the level of the underground water rises fast and falls down slowly. 7. The level of the underground water changes within the scope of 25cm 8. The transpiration ratio is given in table 8 and their value are as follows: clay loam 168.8, loam 255.6, sandy loam 272.5

• Journal of Distribution Research
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• v.15 no.1
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• pp.1-24
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• 2010

I. Introduction The industry of domestic discount store was reorganized with 2 bigs and 1 middle, and then Home Plus took over Home Ever in 2008. In present, Oct, 2008, E-Mart has 118 outlets, Home Plus 112 outlets, and Lotte Mart 60 stores. With total number of 403 outlets, they are getting closer to a saturation point. We know that the industry of discount store has been getting through the mature stage in retail life cycle. There are many efforts to maintain existing customers rather than to get new customers. These competitions in this industry lead firms to acknowledge 'store loyalty' to be the first strategic tool for their sustainable competitiveness. In other words, the strategic goal of discount store is to boost up the repurchase rate of customers throughout increasing store loyalty. If owners of retail shops can figure out main factors for store loyalty, they can easily make more efficient and effective retail strategies which bring about more sales and profits. In this practical sense, there are many papers which are focusing on the antecedents of store loyalty. Many researchers have been inspecting causal relationships between antecedents and store loyalty; store characteristics, store image, atmosphere in store, sales promotion in store, service quality, customer characteristics, crowding, switching cost, trust, satisfaction, commitment, etc., In recent times, many academic researchers and practitioners have been interested in 'dual path model for service loyalty'. There are two paths in store loyalty. First path has an emphasis on symbolic and emotional dimension of service brand, and second path focuses on quality of product and service. We will call the former an extrinsic path and call the latter an intrinsic path. This means that consumers' cognitive path for store loyalty is not single but dual. Existing studies for dual path model are as follows; First, in extrinsic path, some papers in domestic settings show that there is 'store personality-identification-loyalty' path. Second, service quality has an effect on loyalty, which is a behavioral variable, in the mediation of customer satisfaction. But, it's very difficult to find out an empirical paper applied to domestic discount store based on this mediating model. The domestic research for store loyalty concentrates on not only intrinsic path but also extrinsic path. Relatively, an attention for intrinsic path is scarce. And then, we acknowledge that there should be a need for integrating extrinsic and intrinsic path. Also, in terms of retail industry, this study is meaningful because retailers want to achieve their competitiveness by using store loyalty. And so, the purpose of this paper is to integrate and complement two existing paths into one specific model, dual path model. This model includes both intrinsic and extrinsic path for store loyalty. With this research, we would expect to understand the full process of forming customers' store loyalty which had not been clearly explained. In other words, we propose the dual path model for discount store loyalty which has been originated from store personality and service quality. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. II. Research Model Dual path model integrates intrinsic path and extrinsic path into one specific model. Intrinsic path put an emphasis on quality characteristics and extrinsic path focuses on brand characteristics. Intrinsic path is based on information processing perspective, and extrinsic path emphasizes symbolic and emotional dimension of brand. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. Hypotheses are as follows; Hypothesis 1: Service quality perceived by customers in discount store has an positive effect on customer satisfaction Hypothesis 2: Store personality perceived by customers in discount store has an positive effect on store identification Hypothesis 3: Customer satisfaction in discount store has an positive effect on store loyalty. Hypothesis 4: Store identification has an positive effect on store loyalty. III. Results and Implications We examined consumers who patronize discount stores for samples of this study. With the structural equation model(SEM) analysis, we empirically tested the validity and fitness of the dual path model for store loyalty in discount stores. As results, the fitness indices of this model were well fitted to data obtained. In an intrinsic path, service quality(SQ) is positively related to customer satisfaction(CS), customer satisfaction(CS) has very significantly positive effect on store loyalty(SL). Also, in an extrinsic path, the store personality(SP) is positively related to store identification(SI), it shows significant effect on store loyalty. Table 1 shows the results as follows; There are some theoretical and practical implications. First, Many studies on discount store loyalty have been executed from various perspectives. But there has been no integrative view on this issue. And so, this research was theoretically designed to integrate various and controversial arguments into one systematic model. We empirically tested dual path model forming store loyalty, and brought up a systematic and integrative framework for future studies. We want to expect creative and aggressive research activities. Second, a few established papers are focused on the relationship between antecedents and store loyalty; store characteristics, atmosphere, sales promotion in store, service quality, trust, commitment, etc., There has been some limits in understanding thoroughly the formation process of store loyalty with a singular path, intrinsic or extrinsic. Beyond these limits in single path, we could propose the new path for store loyalty. This is meaningful. Third, discount store firms make and execute marketing strategies for increasing store loyalty. This research provides real practitioners with reference framework needed for actual strategy formation. Because this paper shows integrated and systematic path for store loyalty. A special feature of this study is to represent 6 sub dimensions of service quality in intrinsic path and 4 sub dimensions of store personality in extrinsic path. Marketers can make more analytic marketing planning with concrete sub dimensions of service quality and store personality. When marketers of discount stores make strategic planning like MPR, Ads, campaign, sales promotion, they can use many items which are more competitive than competitors.

• Proceedings of the KOR-KST Conference
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• 1995.02a
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• pp.101-113
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• 1995

The objective of this research is to test the feasibility of developing a statewide truck traffic forecasting methodology for Wisconsin by using Origin-Destination surveys, traffic counts, classification counts, and other data that are routinely collected by the Wisconsin Department of Transportation (WisDOT). Development of a feasible model will permit estimation of future truck traffic for every major link in the network. This will provide the basis for improved estimation of future pavement deterioration. Pavement damage rises exponentially as axle weight increases, and trucks are responsible for most of the traffic-induced damage to pavement. Consequently, forecasts of truck traffic are critical to pavement management systems. The pavement Management Decision Supporting System (PMDSS) prepared by WisDOT in May 1990 combines pavement inventory and performance data with a knowledge base consisting of rules for evaluation, problem identification and rehabilitation recommendation. Without a r.easonable truck traffic forecasting methodology, PMDSS is not able to project pavement performance trends in order to make assessment and recommendations in the future years. However, none of WisDOT's existing forecasting methodologies has been designed specifically for predicting truck movements on a statewide highway network. For this research, the Origin-Destination survey data avaiiable from WisDOT, including two stateline areas, one county, and five cities, are analyzed and the zone-to'||'&'||'not;zone truck trip tables are developed. The resulting Origin-Destination Trip Length Frequency (00 TLF) distributions by trip type are applied to the Gravity Model (GM) for comparison with comparable TLFs from the GM. The gravity model is calibrated to obtain friction factor curves for the three trip types, Internal-Internal (I-I), Internal-External (I-E), and External-External (E-E). ~oth "macro-scale" calibration and "micro-scale" calibration are performed. The comparison of the statewide GM TLF with the 00 TLF for the macro-scale calibration does not provide suitable results because the available 00 survey data do not represent an unbiased sample of statewide truck trips. For the "micro-scale" calibration, "partial" GM trip tables that correspond to the 00 survey trip tables are extracted from the full statewide GM trip table. These "partial" GM trip tables are then merged and a partial GM TLF is created. The GM friction factor curves are adjusted until the partial GM TLF matches the 00 TLF. Three friction factor curves, one for each trip type, resulting from the micro-scale calibration produce a reasonable GM truck trip model. A key methodological issue for GM. calibration involves the use of multiple friction factor curves versus a single friction factor curve for each trip type in order to estimate truck trips with reasonable accuracy. A single friction factor curve for each of the three trip types was found to reproduce the 00 TLFs from the calibration data base. Given the very limited trip generation data available for this research, additional refinement of the gravity model using multiple mction factor curves for each trip type was not warranted. In the traditional urban transportation planning studies, the zonal trip productions and attractions and region-wide OD TLFs are available. However, for this research, the information available for the development .of the GM model is limited to Ground Counts (GC) and a limited set ofOD TLFs. The GM is calibrated using the limited OD data, but the OD data are not adequate to obtain good estimates of truck trip productions and attractions .. Consequently, zonal productions and attractions are estimated using zonal population as a first approximation. Then, Selected Link based (SELINK) analyses are used to adjust the productions and attractions and possibly recalibrate the GM. The SELINK adjustment process involves identifying the origins and destinations of all truck trips that are assigned to a specified "selected link" as the result of a standard traffic assignment. A link adjustment factor is computed as the ratio of the actual volume for the link (ground count) to the total assigned volume. This link adjustment factor is then applied to all of the origin and destination zones of the trips using that "selected link". Selected link based analyses are conducted by using both 16 selected links and 32 selected links. The result of SELINK analysis by u~ing 32 selected links provides the least %RMSE in the screenline volume analysis. In addition, the stability of the GM truck estimating model is preserved by using 32 selected links with three SELINK adjustments, that is, the GM remains calibrated despite substantial changes in the input productions and attractions. The coverage of zones provided by 32 selected links is satisfactory. Increasing the number of repetitions beyond four is not reasonable because the stability of GM model in reproducing the OD TLF reaches its limits. The total volume of truck traffic captured by 32 selected links is 107% of total trip productions. But more importantly, ~ELINK adjustment factors for all of the zones can be computed. Evaluation of the travel demand model resulting from the SELINK adjustments is conducted by using screenline volume analysis, functional class and route specific volume analysis, area specific volume analysis, production and attraction analysis, and Vehicle Miles of Travel (VMT) analysis. Screenline volume analysis by using four screenlines with 28 check points are used for evaluation of the adequacy of the overall model. The total trucks crossing the screenlines are compared to the ground count totals. L V/GC ratios of 0.958 by using 32 selected links and 1.001 by using 16 selected links are obtained. The %RM:SE for the four screenlines is inversely proportional to the average ground count totals by screenline .. The magnitude of %RM:SE for the four screenlines resulting from the fourth and last GM run by using 32 and 16 selected links is 22% and 31 % respectively. These results are similar to the overall %RMSE achieved for the 32 and 16 selected links themselves of 19% and 33% respectively. This implies that the SELINICanalysis results are reasonable for all sections of the state.Functional class and route specific volume analysis is possible by using the available 154 classification count check points. The truck traffic crossing the Interstate highways (ISH) with 37 check points, the US highways (USH) with 50 check points, and the State highways (STH) with 67 check points is compared to the actual ground count totals. The magnitude of the overall link volume to ground count ratio by route does not provide any specific pattern of over or underestimate. However, the %R11SE for the ISH shows the least value while that for the STH shows the largest value. This pattern is consistent with the screenline analysis and the overall relationship between %RMSE and ground count volume groups. Area specific volume analysis provides another broad statewide measure of the performance of the overall model. The truck traffic in the North area with 26 check points, the West area with 36 check points, the East area with 29 check points, and the South area with 64 check points are compared to the actual ground count totals. The four areas show similar results. No specific patterns in the L V/GC ratio by area are found. In addition, the %RMSE is computed for each of the four areas. The %RMSEs for the North, West, East, and South areas are 92%, 49%, 27%, and 35% respectively, whereas, the average ground counts are 481, 1383, 1532, and 3154 respectively. As for the screenline and volume range analyses, the %RMSE is inversely related to average link volume. 'The SELINK adjustments of productions and attractions resulted in a very substantial reduction in the total in-state zonal productions and attractions. The initial in-state zonal trip generation model can now be revised with a new trip production's trip rate (total adjusted productions/total population) and a new trip attraction's trip rate. Revised zonal production and attraction adjustment factors can then be developed that only reflect the impact of the SELINK adjustments that cause mcreases or , decreases from the revised zonal estimate of productions and attractions. Analysis of the revised production adjustment factors is conducted by plotting the factors on the state map. The east area of the state including the counties of Brown, Outagamie, Shawano, Wmnebago, Fond du Lac, Marathon shows comparatively large values of the revised adjustment factors. Overall, both small and large values of the revised adjustment factors are scattered around Wisconsin. This suggests that more independent variables beyond just 226; population are needed for the development of the heavy truck trip generation model. More independent variables including zonal employment data (office employees and manufacturing employees) by industry type, zonal private trucks 226; owned and zonal income data which are not available currently should be considered. A plot of frequency distribution of the in-state zones as a function of the revised production and attraction adjustment factors shows the overall " adjustment resulting from the SELINK analysis process. Overall, the revised SELINK adjustments show that the productions for many zones are reduced by, a factor of 0.5 to 0.8 while the productions for ~ relatively few zones are increased by factors from 1.1 to 4 with most of the factors in the 3.0 range. No obvious explanation for the frequency distribution could be found. The revised SELINK adjustments overall appear to be reasonable. The heavy truck VMT analysis is conducted by comparing the 1990 heavy truck VMT that is forecasted by the GM truck forecasting model, 2.975 billions, with the WisDOT computed data. This gives an estimate that is 18.3% less than the WisDOT computation of 3.642 billions of VMT. The WisDOT estimates are based on the sampling the link volumes for USH, 8TH, and CTH. This implies potential error in sampling the average link volume. The WisDOT estimate of heavy truck VMT cannot be tabulated by the three trip types, I-I, I-E ('||'&'||'pound;-I), and E-E. In contrast, the GM forecasting model shows that the proportion ofE-E VMT out of total VMT is 21.24%. In addition, tabulation of heavy truck VMT by route functional class shows that the proportion of truck traffic traversing the freeways and expressways is 76.5%. Only 14.1% of total freeway truck traffic is I-I trips, while 80% of total collector truck traffic is I-I trips. This implies that freeways are traversed mainly by I-E and E-E truck traffic while collectors are used mainly by I-I truck traffic. Other tabulations such as average heavy truck speed by trip type, average travel distance by trip type and the VMT distribution by trip type, route functional class and travel speed are useful information for highway planners to understand the characteristics of statewide heavy truck trip patternS. Heavy truck volumes for the target year 2010 are forecasted by using the GM truck forecasting model. Four scenarios are used. Fo~ better forecasting, ground count- based segment adjustment factors are developed and applied. ISH 90 '||'&'||' 94 and USH 41 are used as example routes. The forecasting results by using the ground count-based segment adjustment factors are satisfactory for long range planning purposes, but additional ground counts would be useful for USH 41. Sensitivity analysis provides estimates of the impacts of the alternative growth rates including information about changes in the trip types using key routes. The network'||'&'||'not;based GMcan easily model scenarios with different rates of growth in rural versus . . urban areas, small versus large cities, and in-state zones versus external stations. cities, and in-state zones versus external stations.