• Title/Summary/Keyword: Statistical modeling

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Environmental Health Surveillance of Low Birth Weight in Seoul using Air Monitoring and Birth Data (2002년 서울시 대기오염과 출생 자료를 이용한 저체중아 환경보건감시체계 연구)

  • Seo, Ju-Hee;Kim, Ok-Jin;Kim, Byung-Mi;Park, Hye-Sook;Leem, Jong-Han;Hong, Yun-Chul;Kim, Young-Ju;Ha, Eun-Hee
    • Journal of Preventive Medicine and Public Health
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    • v.40 no.5
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    • pp.363-370
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    • 2007
  • Objectives: The principal objective of this study was to determine the relationship between maternal exposure to air pollution and low birth weight and to propose a possible environmental health surveillance system for low birth weight. Methods: We acquired air monitoring data for Seoul from the Ministry of Environment, the meteorological data from the Korean Meteorological Administration, the exposure assessments from the National Institute of Environmental Research, and the birth data from the Korean National Statistical Office between January 1, 2002 and December 31, 2003. The final birth data were limited to singletons within $37{\sim}44$ weeks of gestational age. We defined the Low Birth Weight (LBW) group as infants with birth weights of less than 2500g and calculated the annual LBW rate by district. The air monitoring data were measured for $CO,\;SO_2,\;NO_2,\;and\;PM_{10}$ concentrations at 27 monitoring stations in Seoul. We utilized two models to evaluate the effects of air pollution on low birth weight: the first was the relationship between the annual concentration of air pollution and low birth weight (LBW) by individual and district, and the second involved a GIS exposure model constructed by Arc View 3.1. Results: LBW risk (by Gu, or district) was significantly increased to $1.113(95%\;CI=1.111{\sim}1.116)\;for\;CO,\;1.004(95%\;CI=1.003{\sim}1.005)\;for\;NO_2,\;1.202(95%\;CI=1.199{\sim}1.206\;for\;SO_2,\;and\;1.077(95%\;CI=1.075{\sim}1.078)\;\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was significantly increased to $1.081(95%\;CI=1.002{\sim}1.166)\;for\;CO,\;1.145(95%\;CI=1.036{\sim}1.267)\;for\;SO_2,\;and\;1.053(95%\;CI=1.002{\sim}1.108)\;for\;PM_{10}$ with each interquartile range change. Personal LBW risk was increased to $1.003(95%\;CI=0.954{\sim}1.055)\;for\;NO_2$, but this was not statistically significant. The air pollution concentrations predicted by GIS positively correlated with the numbers of low birth weights, particularly in highly polluted regions. Conclusions: Environmental health surveillance is a systemic, ongoing collection effort including the analysis of data correlated with environmentally-associated diseases and exposures. In addition. environmental health surveillance allows for a timely dissemination of information to those who require that information in order to take effective action. GIS modeling is crucially important for this purpose, and thus we attempted to develop a GIS-based environmental surveillance system for low birth weight.

Estimating the Yield of Marketable Potato of Mulch Culture using Climatic Elements (시기별 기상값 활용 피복재배 감자 상서수량 예측)

  • Lee, An-Soo;Choi, Seong-Jin;Jeon, Shin-Jae;Maeng, Jin-Hee;Kim, Jong-Hwan;Kim, In-Jong
    • KOREAN JOURNAL OF CROP SCIENCE
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    • v.61 no.1
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    • pp.70-77
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    • 2016
  • The object of this study was to evaluate the effects of climatic elements on potato yield and create a model for estimating the potato yield. We used 35 yield data of Sumi variety produced in mulching cultivation from 17 regions over 11 years. According to the results, some climatic elements showed significant level of correlation coefficient with marketable yield of potato. Totally 22 items of climatic elements appeared to be significant. Especially precipitation for 20 days after planting (Prec_1 & 2), relative humidity during 11~20 days after planting (RH_2), precipitation for 20 days before harvest (Prec_9 & 10), sunshine hours during 50~41 days before harvest (SH_6) and 20 days before harvest (SH_9 & 10), and days of rain during 10 days before harvest (DR_10) were highly significant in quadratic regression analysis. 22 items of predicted yield ($Y_i=aX_i{^2}+bX_i+c$) were induced from the 22 items of climatic elements (step 1). The correlations between the predicted yields and marketable yield were stepwised using SPSS, statistical program, and we selected a model (step 2), in which 4 items of independent variables ($Y_i$) were used. Subsequently the $Y_i$ were replaced with the equation in step 1, $aX_i{^2}+bX_i+c$. Finally we derived the model to predict the marketable yield of potato as below. $$Y=-336{\times}DR_-10^2+854{\times}DR_-10-0.422{\times}Prec_-9^2+43.3{\times}Prec_-9\\-0.0414{\times}RH_-2^2+46.2{\times}RH_-2-0.0102{\times}Prec_-2^2-7.00{\times}Prec_-2-10039$$.

Product Recommender Systems using Multi-Model Ensemble Techniques (다중모형조합기법을 이용한 상품추천시스템)

  • Lee, Yeonjeong;Kim, Kyoung-Jae
    • Journal of Intelligence and Information Systems
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    • v.19 no.2
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    • pp.39-54
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    • 2013
  • Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

Evaluation of Myocardial Oxygen Consumption with $^{11}C$-Acetate and 3D PET/CT: By Applying Recirculation Correction Method and Modified One-Compartmental Tracer Kinetic Modeling ($^{11}C$-Acetate와 3차원 PET/CT를 이용한 심근의 산소 소모량 평가: 재순환 교정법 및 수정 단일구획 추적자 동적 모델 적용)

  • Chun, In-Kook;Hwang, Kyung-Hoon;Lee, Sang-Yoon;Kim, Jin-Su;Lee, Jae-Sung;Shin, Hee-Won;Lee, Min-Kyung;Yoon, Min-Ki;Choe, Won-Sick
    • Nuclear Medicine and Molecular Imaging
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    • v.42 no.4
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    • pp.275-284
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    • 2008
  • Purpose: We intended to evaluate myocardial oxygen consumption ($MVO_2)$ by applying recirculation correction and modified one-compartment model to have a reference range of $MVO_2$ in normal young population and to reveal the effect of recirculation on time-activity curve (TAC). Materials and Methods: In nine normal male volunteers with mean age of $26.3{\pm}4.0$, $MVO_2$ was estimated with 925 MBq (25mCi) of $^{11}C$-Acetate (Neuroscience Research Institute, Gachon University of Medicine and Science, Incheon, Korea) and PET/CT (Biograph 6, Siemens Medical Solution, Germany). Analysis software such as $MATLAB^{(R)}$ v7.1 (Mathworks, Inc., United States), $Excel^{(R)}$ 2007 (Microsoft, United States), and $SPSS^{(R)}$ v12.0 (Apache Software Foundation, United States) were used. Twenty three frames were of $12{\times}10$, $5{\times}60$, $3{\times}120$, $2{\times}300's$ duration, respectively. The modified one-compartmental model and the recirculation correction method were applied. Statistical analysis was performed by using Test of Normality, ANOVA and Post-Hoc (Scheffe's) analysis, and p-value less than 0.05 was considered as significant. Results: The normal reference ranges of $MVO_2$ were presented as $3.18-4.64\;{\times}\;10^{-4}\;ml/g/sec$, $1.91-3.94\;{\times}\;10^{-4}\;ml/g/sec$, $4.31-6.40\;{\times}\;10^{-4}\;ml/g/sec$, $2.84-4.53\;{\times}\;10^{-4}\;ml/g/sec$ and $3.42-5.00\;{\times}\;10^{-4}\;ml/g/sec$ in the septum, the inferior wall, the lateral wall, the anterior wall and the entire wall, respectively. In addition, it was noted that the dual exponentiality of the clearance curve is due to the recirculation effect and that the characteristic of the curve is essentially mono-exponential. Conclusion: $^{11}C$-Acetate is a radiotracer worthwhile to assess $MVO_2$. Re-circulated $^{11}C$ can influence TAC of $^{11}C$ in myocadia and so the recirculation correction must be considered when measuring $MVO_2$.

Predicting Forest Gross Primary Production Using Machine Learning Algorithms (머신러닝 기법의 산림 총일차생산성 예측 모델 비교)

  • Lee, Bora;Jang, Keunchang;Kim, Eunsook;Kang, Minseok;Chun, Jung-Hwa;Lim, Jong-Hwan
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.21 no.1
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    • pp.29-41
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    • 2019
  • Terrestrial Gross Primary Production (GPP) is the largest global carbon flux, and forest ecosystems are important because of the ability to store much more significant amounts of carbon than other terrestrial ecosystems. There have been several attempts to estimate GPP using mechanism-based models. However, mechanism-based models including biological, chemical, and physical processes are limited due to a lack of flexibility in predicting non-stationary ecological processes, which are caused by a local and global change. Instead mechanism-free methods are strongly recommended to estimate nonlinear dynamics that occur in nature like GPP. Therefore, we used the mechanism-free machine learning techniques to estimate the daily GPP. In this study, support vector machine (SVM), random forest (RF) and artificial neural network (ANN) were used and compared with the traditional multiple linear regression model (LM). MODIS products and meteorological parameters from eddy covariance data were employed to train the machine learning and LM models from 2006 to 2013. GPP prediction models were compared with daily GPP from eddy covariance measurement in a deciduous forest in South Korea in 2014 and 2015. Statistical analysis including correlation coefficient (R), root mean square error (RMSE) and mean squared error (MSE) were used to evaluate the performance of models. In general, the models from machine-learning algorithms (R = 0.85 - 0.93, MSE = 1.00 - 2.05, p < 0.001) showed better performance than linear regression model (R = 0.82 - 0.92, MSE = 1.24 - 2.45, p < 0.001). These results provide insight into high predictability and the possibility of expansion through the use of the mechanism-free machine-learning models and remote sensing for predicting non-stationary ecological processes such as seasonal GPP.

A Study on the Determinants of Blockchain-oriented Supply Chain Management (SCM) Services (블록체인 기반 공급사슬관리 서비스 활용의 결정요인 연구)

  • Kwon, Youngsig;Ahn, Hyunchul
    • Knowledge Management Research
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    • v.22 no.2
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    • pp.119-144
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    • 2021
  • Recently, as competition in the market evolves from the competition among companies to the competition among their supply chains, companies are struggling to enhance their supply chain management (hereinafter SCM). In particular, as blockchain technology with various technical advantages is combined with SCM, a lot of domestic manufacturing and distribution companies are considering the adoption of blockchain-oriented SCM (BOSCM) services today. Thus, it is an important academic topic to examine the factors affecting the use of blockchain-oriented SCM. However, most prior studies on blockchain and SCMs have designed their research models based on Technology Acceptance Model (TAM) or the Unified Theory of Acceptance and Use of Technology (UTAUT), which are suitable for explaining individual's acceptance of information technology rather than companies'. Under this background, this study presents a novel model of blockchain-oriented SCM acceptance model based on the Technology-Organization-Environment (TOE) framework to consider companies as the unit of analysis. In addition, Value-based Adoption Model (VAM) is applied to the research model in order to consider the benefits and the sacrifices caused by a new information system comprehensively. To validate the proposed research model, a survey of 126 companies were collected. Among them, by applying PLS-SEM (Partial Least Squares Structural Equation Modeling) with data of 122 companies, the research model was verified. As a result, 'business innovation', 'tracking and tracing', 'security enhancement' and 'cost' from technology viewpoint are found to significantly affect 'perceived value', which in turn affects 'intention to use blockchain-oriented SCM'. Also, 'organization readiness' is found to affect 'intention to use' with statistical significance. However, it is found that 'complexity' and 'regulation environment' have little impact on 'perceived value' and 'intention to use', respectively. It is expected that the findings of this study contribute to preparing practical and policy alternatives for facilitating blockchain-oriented SCM adoption in Korean firms.

Structural relationship among justice of non-face-to-face exam, trust, and satisfaction with university (치위생(학)과 학생이 지각한 비대면 시험의 공정성, 시험 불안 및 학교 신뢰 간의 구조적 관계)

  • Hyeong-Mi Kim;Chang-Hee Kim;Jeong-Hee Kim
    • Journal of Korean Dental Hygiene Science
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    • v.6 no.1
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    • pp.37-50
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    • 2023
  • Background: This study investigated the structural relationships among justice, test anxiety, and school reliability s non-face-to-face tests of dental hygiene students. Methods: A survey was conducted with 267 dental hygiene students. The survey items included general characteristics, opinions on evaluation, the fairness of non-face-to-face tests (distributive, procedural, and interactional justice), school satisfaction, and school reliability. For statistical analysis, independent-sample t-tests, one-way ANOVA, and structural modeling analyses were performed. Results: Among factors that directly affected distributive justice and reliability towards non-face-to-face tests, the higher the interactional justice (β=0.401, p<0.001) and distributive justice (β=0.232, p=0.002) levels, the higher the school satisfaction. The higher the school satisfaction (β=0.606, p<0.001) and procedural justice (β=0.299, p<0.001) levels, the higher the perceived reliability of the school. Factors that indirectly affected school reliability included interactional justice (β=0.243, p=0.010) and distributive justice (β=0.141, p=0.010). Interactional justice (β=0.592, p=0.010) and distributive justice (β=0.208, p=0.010) were the factors affecting school satisfaction. Moreover, factors that influenced school reliability were distributive justice (β=0.56, p=0.010), interactional justice (β=0.332, p=0.010), procedural justice (β=0.229, p=0.010), and distributive justice (β=0.116, p=0.010). Conclusions: Students will trust and be satisfied with schools when schools and professors sufficiently provide information on face-to-face tests and ensure proper procedures to achieve reasonable grades as rewards for exerted time and effort. Furthermore, this study provides a reference base for developing a variety of content for fair, non-face-to-face tests, thereby allowing students to trust their schools.

The Influences of Chinese Interpersonal Culture on Counterfeit Brand (중국인의 타인의식형 집단문화와 위조명품 브랜드 구매행동)

  • Kim, Joo-Ho
    • Asia Marketing Journal
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    • v.13 no.2
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    • pp.27-48
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    • 2011
  • The Chinese counterfeits has begun to gain great attention recently because of the drastic increase in its volume. The consumption of counterfeit harms to manufacturer who spend millions of dollars to create and develop new product. The counterfeits in Chinese can cause international dispute and lower national reputation. The purpose of this study were to examine if the buyers of counterfeits tend to care more about interpersonal relationship than non-buyers among Chinese. Data were gathered by surveying Chinese consumer living in Beijing, Shanghai, and Guangzhou metropolitan area using convenient sampling, and 480 questionnaires were used in the statistical analysis. In analyzing data, descriptive statistics, factor analysis, structural equation modeling with AMOS were conducted. The results of this study were follows, first, attitude toward counterfeits was classified into three factors such as interpersonal relationship, perception, and involvement. It is general belief that attitudes toward counterfeits were correlated with on brand attachment, however this study show that the buyers of counterfeits tended to purchase counterfeit goods as more alternatives of genuine(original) product than non-buyers. Perhaps, the buyers of counterfeits tended to have lower consumer ethics than non-buyers because they value counterfeit high. It is generally accepted that both a producer and a buyer violate the laws, but they are rather generous for buyer. The results of this study suggest consumers' attitude towards counterfeit need to be changed, following consumer education and strict law enforcement. Based on these results, global brand marketing strategies for luxury goods were suggested.

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Self-Regulatory Mode Effects on Emotion and Customer's Response in Failed Services - Focusing on the moderate effect of attribution processing - (고객의 자기조절성향이 서비스 실패에 따른 부정적 감정과 고객반응에 미치는 영향 - 귀인과정에 따른 조정적 역할을 중심으로 -)

  • Sung, Hyung-Suk;Han, Sang-Lin
    • Asia Marketing Journal
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    • v.12 no.2
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    • pp.83-110
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    • 2010
  • Dissatisfied customers may express their dissatisfaction behaviorally. These behavioral responses may impact the firms' profitability. How do we model the impact of self regulatory orientation on emotions and subsequent customer behaviors? Obviously, the positive and negative emotions experienced in these situations will influence the overall degree of satisfaction or dissatisfaction with the service(Zeelenberg and Pieters 1999). Most likely, these specific emotions will also partly determine the subsequent behavior in relation to the service and service provider, such as the likelihood of complaining, the degree to which customers will switch or repurchase, and the extent of word of mouth communication they will engage in(Zeelenberg and Pieters 2004). This study investigates the antecedents, consequences of negative consumption emotion and the moderate effect of attribution processing in an integrated model(self regulatory mode → specific emotions → behavioral responses). We focused on the fact that regret and disappointment have effects on consumer behavior. Especially, There are essentially two approaches in this research: the valence based approach and the specific emotions approach. The authors indicate theoretically and show empirically that it matters to distinguish these approaches in services research. and The present studies examined the influence of two regulatory mode concerns(Locomotion orientation and Assessment orientation) with making comparisons on experiencing post decisional regret and disappointment(Pierro, Kruglanski, and Higgins 2006; Pierro et al. 2008). When contemplating a decision with a negative outcome, it was predicted that high (vs low) locomotion would induce more disappointment than regret, whereas high (vs low) assessment would induce more regret than disappointment. The validity of the measurement scales was also confirmed by evaluations provided by the participating respondents and an independent advisory panel; samples provided recommendations throughout the primary, exploratory phases of the study. The resulting goodness of fit statistics were RMR or RMSEA of 0.05, GFI and AGFI greater than 0.9, and a chi-square with a 175.11. The indicators of the each constructs were very good measures of variables and had high convergent validity as evidenced by the reliability with a more than 0.9. Some items were deleted leaving those that reflected the cognitive dimension of importance rather than the dimension. The indicators were very good measures and had convergent validity as evidenced by the reliability of 0.9. These results for all constructs indicate the measurement fits the sample data well and is adequate for use. The scale for each factor was set by fixing the factor loading to one of its indicator variables and then applying the maximum likelihood estimation method. The results of the analysis showed that directions of the effects in the model are ultimately supported by the theory underpinning the causal linkages of the model. This research proposed 6 hypotheses on 6 latent variables and tested through structural equation modeling. 6 alternative measurements were compared through statistical significance test of the paths of research model and the overall fitting level of structural equation model and the result was successful. Also, Locomotion orientation more positively influences disappointment when internal attribution is high than low and Assessment orientation more positively influences regret when external attribution is high than low. In sum, The results of our studies suggest that assessment and locomotion concerns, both as chronic individual predispositions and as situationally induced states, influence the amount of people's experienced regret and disappointment. These findings contribute to our understanding of regulatory mode, regret, and disappointment. In previous studies of regulatory mode, relatively little attention has been paid to the post actional evaluative phase of self regulation. The present findings indicate that assessment concerns and locomotion concerns are clearly distinct in this phase, with individuals higher in assessment delving more into possible alternatives to past actions and individuals higher in locomotion engaging less in such reflective thought. What this suggests is that, separate from decreasing the amount of counterfactual thinking per se, individuals with locomotion concerns want to move on, to get on with it. Regret is about the past and not the future. Thus, individuals with locomotion concerns are less likely to experience regret. The results supported our predictions. We discuss the implications of these findings for the nature of regret and disappointment from the perspective of their relation to regulatory mode. Also, self regulatory mode and the specific emotions(disappointment and regret) were assessed and their influence on customers' behavioral responses(inaction, word of mouth) was examined, using a sample of 275 customers. It was found that emotions have a direct impact on behavior over and above the effects of negative emotions and customer behavior. Hence, We argue against incorporating emotions such as regret and disappointment into a specific response measure and in favor of a specific emotions approach on self regulation. Implications for services marketing practice and theory are discussed.

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A Study on Perceived Quality affecting the Service Personal Value in the On-off line Channel - Focusing on the moderate effect of the need for cognition - (온.오프라인 채널에서 지각된 품질이 서비스의 개인가치에 미치는 영향에 관한 연구 -인지욕구의 조정효과를 중심으로-)

  • Sung, Hyung-Suk
    • 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.

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