• Journal of Distribution Research
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• v.15 no.3
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• pp.111-137
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• 2010

The basic purpose of this study is to investigate perceived quality and service personal value affecting the result of long-term relationship between service buyers and suppliers. This research presented a constructive model(perceived quality affecting the service personal value and the moderate effect of NFC) in the on off line and then propose the research model base on prior researches and studies about relationships among components of service. Data were gathered from respondents who visit at the education service market. For this study, Data were analyzed by AMOS 7.0. We integrate the literature on services marketing with researches on personal values and perceived quality. The SERPVAL scale presented here allows for the creation of a common ground for assessing service personal values, giving a clear understanding of the key value dimensions behind service choice and usage. It will lead to a focus of future research in services marketing, extending knowledge in the field and stimulating further empirical research on service personal values. At the managerial level, as a tool the SERPVAL scale should allow practitioners to evaluate and improve the value of a service, and consequently, to define strategies and actions to address services for customers based on their fundamental personal values. Through qualitative and empirical research, we find that the service quality construct conforms to the structure of a second-order factor model that ties service quality perceptions to distinct and actionable dimensions: outcome, interaction, and environmental quality. In turn, each has two subdimensions that define the basis of service quality perceptions. The authors further suggest that for each of these subdimensions to contribute to improved service quality perceptions, the quality received by consumers must be perceived to be reliable, responsive, and empathetic. Although the service personal value may be found in researches that explore individual values and their consequences for consumer behavior, there is no established operationalization of a SERPVAL scale. The inexistence of an established scale, duly adapted in order to understand and analyze personal values behind services usage, exposes the need of a measurement scale with such a purpose. This need has to be rooted, however, in a conceptualization of the construct being scaled. Service personal values can be defined as a customer's overall assessment of the use of a service based on the perception of what is achieved in terms of his own personal values. As consumer behaviors serve to show an individual's values, the use of a service can also be a way to fulfill and demonstrate consumers'personal values. In this sense, a service can provide more to the customer than its concrete and abstract attributes at both the attribute and the quality levels, and more than its functional consequences at the value level. Both values and services literatures agree, that personal value is the highest-level concept, followed by instrumental values, attitudes and finally by product attributes. Purchasing behaviors are agreed to be the end result of these concepts' interaction, with personal values taking a major role in the final decision process. From both consumers' and practitioners' perspectives, values are extremely relevant, as they are desirable goals that serve as guiding principles in people's lives. While building on previous research, we propose to assess service personal values through three broad groups of individual dimensions; at the self-oriented level, we use (1) service value to peaceful life (SVPL) and, at the social-oriented level, we use (2) service value to social recognition (SVSR), and (3) service value to social integration (SVSI). Service value to peaceful life is our first dimension. This dimension emerged as a combination of values coming from the RVS scale, a scale built specifically to assess general individual values. If a service promotes a pleasurable life, brings or improves tranquility, safety and harmony, then its user recognizes the value of this service. Generally, this service can improve the user's pleasure of life, since it protects or defends the consumer from threats to life or pressures on it. While building upon both the LOV scale, a scale built specifically to assess consumer values, and the RVS scale for individual values, we develop the other two dimensions: SVSR and SVSI. The roles of social recognition and social integration to improve service personal value have been seriously neglected. Social recognition derives its outcome utility from its predictive utility. When applying this underlying belief to our second dimension, SVSR, we assume that people use a service while taking into consideration the content of what is delivered. Individuals consider whether the service aids in gaining respect from others, social recognition and status, as well as whether it allows achieving a more fulfilled and stimulating life, which might then be revealed to others. People also tend to engage in behavior that receives social recognition and to avoid behavior that leads to social disapproval, and this contributes to an individual's social integration. This leads us to the third dimension, SVSI, which is based on the fact that if the consumer perceives that a service strengthens friendships, provides the possibility of becoming more integrated in the group, or promotes better relationships at the social, professional or family levels, then the service will contribute to social integration, and naturally the individual will recognize personal value in the service. Most of the research in business values deals with individual values. However, to our knowledge, no study has dealt with assessing overall personal values as well as their dimensions in a service context. Our final results show that the scales adapted from the Schwartz list were excluded. A possible explanation is that although Schwartz builds on Rokeach work in order to explore individual values, its dimensions might be especially focused on analyzing societal values. As we are looking for individual dimensions, this might explain why the values inspired by the Schwartz list were excluded from the model. The hierarchical structure of the final scale presented in this paper also presents theoretical implications. Although we cannot claim to definitively capture the dimensions of service personal values, we believe that we come close to capturing these overall evaluations because the second-order factor extracts the underlying commonality among dimensions. In addition to obtaining respondents' evaluations of the dimensions, the second-order factor model captures the common variance among these dimensions, reflecting the respondents' overall assessment of service personal values. Towards this fact, we expect that the service personal values conceptualization and measurement scale presented here contributes to both business values literature and the service marketing field, allowing for the delineation of strategies for adding value to services. This new scale also presents managerial implications. The SERPVAL dimensions give some guidance on how to better pursue a highly service-oriented business strategy. Indeed, the SERPVAL scale can be used for benchmarking purposes, as this scale can be used to identify whether or not a firms' marketing strategies are consistent with consumers' expectations. Managerial assessment of the personal values of a service might be extremely important because it allows managers to better understand what customers want or value. Thus, this scale allows us to identify what services are really valuable to the final consumer; providing knowledge for making choices regarding which services to include. Traditional approaches have focused their attention on service attributes (as quality) and service consequences(as service value), but personal values may be an important set of variables to be considered in understanding what attracts consumers to a certain service. By using the SERPVAL scale to assess the personal values associated with a services usage, managers may better understand the reasons behind services' usage, so that they may handle them more efficiently. While testing nomological validity, our empirical findings demonstrate that the three SERPVAL dimensions are positively and significantly associated with satisfaction. Additionally, while service value to social integration is related only with loyalty, service value to peaceful life is associated with both loyalty and repurchase intent. It is also interesting and surprising that service value to social recognition appears not to be significantly linked with loyalty and repurchase intent. A possible explanation is that no mobile service provider has yet emerged in the market as a luxury provider. All of the Portuguese providers are still trying to capture market share by means of low-end pricing. This research has implications for consumers as well. As more companies seek to build relationships with their customers, consumers are easily able to examine whether these relationships provide real value or not to their own lives. The selection of a strategy for a particular service depends on its customers' personal values. Being highly customer-oriented means having a strong commitment to customers, trying to create customer value and understanding customer needs. Enhancing service distinctiveness in order to provide a peaceful life, increase social recognition and gain a better social integration are all possible strategies that companies may pursue, but the one to pursue depends on the outstanding personal values held by the service customers. Data were gathered from 284 respondents in the korean discount store and online shopping mall market. This research proposed 3 hypotheses on 6 latent variables and tested through structural equation modeling. 6 alternative measurements were compared through statistical significance test of the 6 paths of research model and the overall fitting level of structural equation model. and the result was successful. and Perceived quality more positively influences service personal value when NFC is high than when no NFC is low in the off-line market. The results of the study indicate that service quality is properly modeled as an antecedent of service personal value. We consider the research and managerial implications of the study and its limitations. In sum, by knowing the dimensions a consumer takes into account when choosing a service, a better understanding of purchasing behaviors may be realized, guiding managers toward customers expectations. By defining strategies and actions that address potential problems with the service personal values, managers might ultimately influence their firm's performance. we expect to contribute to both business values and service marketing literatures through the development of the service personal value. At a time when marketing researchers are challenged to provide research with practical implications, it is also believed that this framework may be used by managers to pursue service-oriented business strategies while taking into consideration what customers value.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Asia Marketing Journal
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• v.12 no.4
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• pp.55-78
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• 2011

Recently strategic alliance between business firms has become prevalent to overcome increasing competitive threats and to supplement resource limitation of individual firms. As one of allianced sales promotion activities, a new type of discount program, so called "Alliance Card Discount", is introduced with the partnership of credit cards and loyalty cards. The program mainly pursues short-term sales growth by larger discount scheme while spends less through cost share among alliance partners. Thus this program can be regarded as cost efficient discount promotion. But because there is no solid evidence that it can really deliver profitable sales growth, an empirical study for its effects on sales and profit should be conducted. This study has two basic research questions concerning the effects of allianced discount program ; 1)the possibility of sales increase 2) the profitability of the discount driven sales. In F&B industry, sales increase mainly comes from increased guest count. Especially in family restaurants, to increase the number of guests we need to enlarge the size of visitor group (number of visitors for one group) because customers visit by group in a special occasion. And because they pay the bill by group(table), the increase of sales per table is a key measure for sales improvement. The past researches for price & discount sensitivity and reference discount rate explain that price sensitive consumers have narrow reference discount zone and make rational purchase decision. Differently from all time discount scheme of regular sales promotions, the alliance card discount program only provides the right to get discount like discount coupon. And because it is usually once a month opportunity given by the past month usage level, customers tend to perceive alliance card discount as a rare chance to get. So that we can expect customers try to maximize the discount effect when they use the limited discount opportunity. Considering group visiting practice and low visit frequency of family restaurants, the way to maximize discount effect should be the increase the size of visit group. And their sensitivity to discount and rational consumption behavior defer the additional spending for ordering high price menu, even though they get considerable amount of savings from the discount. From the analysis of sales data paid by alliance discount cards for four months, we found the below. 1) The relation between discount rate and number of guest per table is positive : 25% discount results one additional guest 2) The relation between discount rate and the spending per guest is negative. 3) However, total profit amount per table is increased when discount rate is increased. 4) Reward point accumulation & redemption did not show any significant relationship with the increase of number of guests. These results suggest that the allianced discount program substantially contributes to sales increase and profit improvement by increasing the number of guests per table. Though the spending per guest is decreased by discount rate increase, the total amount of profit per table is improved. It seems the incremental profit by increased guest count offsets the profit decrease. Additional intriguing finding is the point reward system does not have any significant impact on the increase of number of guest, even if the point accumulation & redemption of loyalty program are usually regarded as another saving offers by customers. In sum, because it is proved that allianced discount program with credit cards and loyalty cards is effective to both sales drive and profit increase, the alliance card program could be recommended as strategically buyable program.