• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.739-745
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• 2010

This paper computes the repurchase index based on statistical modeling. Using the transaction record of a certain product, the repurchase index is obtained by fitting the Poisson regression model. The customers are classified into 5 groups based on the index giving the information about the propensity to repurchase.

• Journal of Digital Convergence
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• v.9 no.6
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• pp.207-216
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• 2011

This paper is for the influence of consulting character how to affect on the word-of-mouth intention and repurchase. Consulting characters consist of expertise, reliability and application. The results of this study are as follows: Firstly, Application except expertise and reliability have a positive effect on word-of mouth intention influence. Secondly, expertise and application except reliability have a positive effect on repurchase intention influence. This study shows that the company marketing performance would be greatly improved by an application of consulting experience and an expertise of consulting need.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.535-546
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• 2010

There are two methods in grouping customers for micro marketing promotion. The one is based on how much they paid and the other is based on how many times they purchased. In this study we are interested in the repurchase probability of customers. By analysing the customer's transaction data and demographic data, we develop a forecasting model of repurchase and make epurchase indexes of them. As a modeling tool we use the logistic regression model. Finally we categorize the customers into five groups in according to their repurchase indexes so that we can control customers effectively and get higher profit.

• Journal of Navigation and Port Research
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• v.37 no.3
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• pp.299-307
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• 2013

The purpose of this study were to analyze the effects of a marine leisure exhibition event(MLEE)'s service quality dissatisfaction levels on complaining behaviors and repurchase intentions and thus to provide fundamental marketing information for the event to be more successful. In order to accomplish such study purposes, this study employed a survey method with a total of 350 visitors to a MLEE hosted by G Province in 2012. The data collected were analyzed using multiple regression analysis and following findings were derived from current study. First, levels of service quality dissatisfaction were ranged from 3.29 point to 3.85 point at 7 point Likert scale. Second, both environment and exhibition facility had a positive effect on visitors' complaining behaviors, and both employee and environment factors had a positive effect on non complaining behavior. Third, only exhibition facility had a negative effect on repurchase behaviors including revisit intention and recommendation intention. Finally, complaining behavior had a negative effect on recommendation intention as well as revisit intention. Such findings provide important marketing information for induce more visitors to a MLEE, which are an index for the event's performance.

• Management & Information Systems Review
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• v.3
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• pp.47-76
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• 1999

Management Information System(MIS) User satisfaction, which was introduced at the earlier 1990's, has become a core way of strategic method. But domestic companies have little experience toward this concept and the methodological knowledge was not cumulated yet. So the definition of User satisfaction, as well as the validity and objectivity toward the estimation, is being under discussion In this report we will contain the contents as follows, 1) investigate limitations of exposed theories about Methodology, 2) look into the situations and handicaps of User satisfaction estimation which is being used in practical domains on company, 3) search for the better way in application through comparative analysis between case study of customer satisfaction structure by structural equation model and by ordinary estimation model. We have conclusions through model that Index values like GFI AGFL RMR are accepted as within limited range for estimating validity of used model. so we can expect to use the results for deduce accurate User satisfaction index. Therefore satisfied Users became lesser at complaint behavior instead higher at repurchase likelihood, while unsatisfied Users became lower. Results as above are accordance with the previous studies, and that proves ACSI model to be applied toward local MIS Users' case. Even though the scopes of this research are restricted in domestic market of MIS Users, ACSI model itself has developed with the purpose for compatibility toward inter-company and inter-industry. So this model can be applied beneficially in the future study to analyse the extent that latent variables affect to User satisfaction.

• The Journal of Industrial Distribution & Business
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• v.9 no.5
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• pp.63-72
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• 2018

Purpose - This work analyzes, in detail, the specification of vector error correction model (VECM) and thus examines the relationships and impact among seven economic variables for USA - balance on current account (BCA), index of stock (STOCK), gross domestic product (GDP), housing price indices (HOUSING), a measure of the money supply that includes total currency as well as large time deposits, institutional money market funds, short-term repurchase agreements and other larger liquid assets (M3), real rate of interest (IR_REAL) and household credits (LOAN). In particular, we search for the main explanatory variables that have an effect on stock and real estate market, respectively and investigate the causal and dynamic associations between them. Research design, data, and methodology - We perform the time series vector error correction model to infer the dynamic relationships among seven variables above. This work employs the conventional augmented Dickey-Fuller (ADF) and Phillips-Perron (PP) unit root techniques to test for stationarity among seven variables under consideration, and Johansen cointegration test to specify the order or the number of cointegration relationship. Granger causality test is exploited to inspect for causal relationship and, at the same time, impulse response function and variance decomposition analysis are checked for both short-run and long-run association among the seven variables by EViews 9.0. The underlying model was analyzed by using 108 realizations from Q1 1990 to Q4 2016 for USA. Results - The results show that all the seven variables for USA have one unit root and they are cointegrated with at most five and three cointegrating equation for USA. The vector error correction model expresses a long-run relationship among variables. Both IR_REAL and M3 may influence real estate market, and GDP does stock market in USA. On the other hand, GDP, IR_REAL, M3, STOCK and LOAN may be considered as causal factors to affect real estate market. Conclusions - The findings indicate that both stock market and real estate market can be modelled as vector error correction specification for USA. In addition, we can detect causal relationships among variables and compare dynamic differences between countries in terms of stock market and real estate market.

• Asia Marketing Journal
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• v.10 no.2
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• pp.99-123
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• 2008

Consumer satisfaction/dissatisfaction is key determinant of brand loyalty and store patronage behavior. But the results of many customer satisfaction surveys implemented by department stores show that consumer satisfactions do not predict the actual patronage behaviors well. The main reason of these surprising results would be that the consumer satisfaction indexes do not include some important determinants of consumer satisfaction. Many customer satisfaction surveys mainly focus on the evaluation of functional benefits including product assortments, merchandise prices and locational convenience. Recent studies indicate that emotional/hedonic benefits strongly influence the consumer satisfaction, intention to repurchase and intention to revisit. Our study suggests that both functional values and hedonic values should be included in developing the index of consumer satisfactions. The purpose of our study is to investigate the relationship between shopping value and consumer satisfaction, and actual patronage behavior. Shopping values is defined as the difference between total benefits and total shopping costs. Total benefits include the dimensions of product quality, service quality, and hedonic benefits. Total costs are classified as the monetary costs and non-monetary cost. The conceptual framework developed for this empirical study is as follows.