• Journal of Korean Society for Quality Management
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• v.45 no.1
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• pp.39-54
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• 2017

Purpose: This study evaluated the effect of customer relationship management (CRM) on customer's brand loyalty in the holistic perspective of relational benefits, relationship quality and relation value. This paper attempted to find out the psychological process that links the relational benefits and brand loyalty. Methods: The data was collected by using the structured questionnaires to VIP customers and general customers of major domestic banks. The proposed research model is empirically tested using 324 valid questionnaires using SPSS 23 and AMOS 23. Results: This research indicated the partially positive relationship between the relational benefits and relation values, and between relational benefits and relationship quality. The relation value and relationship quality positively affects the relation commitment and the relation commitment also positively affects brand loyalty. This study also shows that the relation value affects the brand loyalty through the mediation of relation commitment, but also the relationship quality affects the brand loyalty through the media of relation commitment. Conclusions: This study investigates the role of perceptional factors(relational value and relationship quality) and affective factors(relation commitment) to find the relationship between relational benefits and brand loyalty. It also suggest the relative influence of relational benefits on relation value.

• International journal of advanced smart convergence
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• v.9 no.3
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• pp.215-220
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• 2020

The purpose of this study is to analyze the structural relationship among expectation value(relational, hedonistic), brand image, brand attitude, continuance viewing intention. The survey subjects to achieve the purpose of this study were selected the 521 YouTube sports contents Viewer in the metropolitan area. Data processing was done with SPSS 23 for frequency analysis, Cronbach's α analysis. Also, AMOS 21 was used for confirmatory factor analysis and structural equation model analysis. The results of the analysis are as follows: First, both relational value and,, hedonistic value had a positive effect on the brand image. Second, both relational value and,, hedonistic value had a positive effect on the brand attitude. Third, both brand image and brand attitudee had a positive effect on the brand attitude.

• Journal of the Korean Society of Fashion and Beauty
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• v.2 no.2 s.2
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• pp.23-33
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• 2004

As we continue to enjoy economic growth, there is an abundance of disposable income for consumer to spend. Consumers are spending more and more of these income in beauty service. However, relatively little is known about which factors influence consumer' behavior intentions in this area. The purpose of this study is to investigate the relationships between the servicescape and relational benefits on customer value in beauty salon area. The Results are summarized as follows First, as the results of data analysis, among the composition factor of servicescape, spatiality, comfortableness, cleanness and convenience are shown to give positive effect on customer value. Second, among the composition factor of relational benefits, economic honest, functional benefit, private benefit, social benefit and psychological benefit are found to have a positive relationship with customer value.

• 한국데이터정보과학회:학술대회논문집
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• 2006.04a
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• pp.55-62
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the dong's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute a missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(wen's GRG & weighted mean) method is the best of my other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5888-5903
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• 2019

The Relational ranking method applies authority-based ranking in relational dataset that can be modeled as graphs considering also their tuples' values. Authority directions from tuples that contain the given keywords and transfer to their corresponding neighboring nodes in accordance with their values and semantic connections. From our previous work, ObjectRank extends to ValueRank that also takes into account the value of tuples in authority transfer flows. In a maked difference from ObjectRank, which only considers authority flows through relationships, it is only valid in the bibliographic databases e.g. DBLP dataset, ValueRank facilitates the estimation of importance for any databases, e.g. trading databases, etc. A relational keyword search paradigm Object Summary (denote as OS) is proposed recently, given a set of keywords, a group of Object Summaries as its query result. An OS is a multilevel-tree data structure, in which node (namely the tuple with keywords) is OS's root node, and the surrounding nodes are the summary of all data on the graph. But, some of these trees have a very large in total number of tuples, size-l OSs are the OS snippets, have also been investigated using ValueRank.We evaluated the real bibliographical dataset and Microsoft business databases to verify of our proposed approach.

• Journal of Korea Trade
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• v.27 no.4
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• pp.1-18
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• 2023

Purpose - The purpose of this paper is to study how flexibility and mutuality in determining trade terms impact logistics efficiency in the context of relational theory. Additionally, the effect of relational contracts on logistical efficiency relative to the value of the goods being traded is investigated. Design/methodology - According to the relational contract theory, we developed 17 factors utilizing a 7-point Likert scale to measure variables related to flexibility, mutuality, logistics efficiency, and the added value of goods. The survey occurred over four months, and was distributed directly, and via email, phone, and online Google surveys. A total of 403 surveys were collected out of 1,800 distributed, and 380 were analyzed. The principal respondents were import/export companies and members of the Korea International Trade Association and the Korea Small and Medium Business Export-Import Association. The collected data were analyzed using frequency analysis, exploratory factor analysis, and correlation analysis using SPSS ver. 26.0 statistical software, and hypothesis test results were derived using Process Macro ver. 3.5. Findings - This study provides evidence that negotiation flexibility for trade terms affects the efficiency of the logistics process, and the mutuality of such arrangements is shown to be associated with the flexibility and efficiency of logistics processes. Additionally, it has been established that companies whose trade goods possess a low degree of added value may experience increased efficiency in logistics operations if they agree to trade terms that are both flexible and mutually beneficial with their counterparts. Originality/value - This study suggests that in an environment of rapidly shifting global logistics and unpredictable related costs, trade companies may be able to improve logistics efficiency by establishing flexible, mutually beneficial trade terms when entering into contracts. Furthermore, it is suggested that companies dealing in low-value-added products may improve the logistical performance of approaching trade from a perspective of relational contracts.

• World Technopolis Review
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• v.5 no.1
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• pp.47-60
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• 2016

In today's digital non-linear global business environment, innovation initiatives are influenced by inter-organizational, political, economic, environmental, technological systems, as well as by decisions made individually by key actors in these systems. Network-based structures emerge from social linkages and collaborations among various actors, creating innovation ecosystems, complex adaptive systems in which entities co-create value. A shared vision of value co-creation allows people operating individually to arrive together at the same future. Yet, relationships are difficult to see, continually changing and challenging to manage. The Innovation Ecosystem Transformation Framework construct includes three core components to make innovation relationships visible and articulate networks of relational capital for the wellbeing, sustainability and business success of innovation ecosystems: data-driven visualizations, storytelling and shared vision. Access to data facilitates building evidence-based visualizations using relational data. This has dramatically altered the way leaders can use data-driven analysis to develop insights and provide ongoing feedback needed to orchestrate relational capital and build shared vision for high quality decisions about innovation. Enabled by a shared vision, relational capital can guide decisions that catalyze, support and sustain an ecosystemic milieu conducive to innovation for business growth.

• Journal of the Korea Fashion and Costume Design Association
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• v.11 no.1
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• pp.63-75
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• 2009

This study aims to find out the dimension of consumers' shopping values in internet clothing purchase, and the relation of their relational quality with shopping malls and their shopping behavior depending on the type of their shopping values. For this purpose, this study surveyed 343 male and female consumers in their 20s or 30s for empirical analysis who have ever purchased clothing through internet shopping malls. Respondents are selected using the convenience sampling through internet survey in July 2008. For statistical analysis, descriptive statistics, factor analysis, ANOVA analysis, Duncan test, and $X^2$-test are carried out using SPSS for Windows 12.0. The results are as follows. First, consumers' shopping value dimensions in internet shopping for clothes are found 4 factors of fun, economic utility, information, and shopping convenience. Second, based on shopping value dimensions, consumers are categorized into an practicality-seeking, an economic utility/fun-seeking, a fun-seeking, and an information/fun-seeking group. Third, there are significant differences in relational quality, customer loyalty, favorable word of mouth, and repurchase intention depending on shopping value-based consumer types. In particular, the economic utility/fun-seeking and information/fun-seeking group have higher values on relational quality and shopping behavior variables than other groups. Thus internet shopping mall businesses need to recognize these group of consumers as their core customers and develop programs to maintain a long-term relationship with them.

• Journal of the Korean Society of Food Science and Nutrition
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• v.42 no.1
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• pp.120-128
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• 2013

This study was conducted to investigate the effect of relational benefits on perceived value in order to enhance customer satisfaction and win customer loyalty in the specialty coffee shop business. Structural equation modeling was performed and the structural model estimated with AMOS (ver 5.0). A total of 329 valid responses were used for data analysis. The findings show that confidence benefits among the relational benefits have a direct effect on perceived value. In addition, confidence benefits also have an indirect effect on customer satisfaction and loyalty from this perceived value. However, social benefits and special treatment benefits of customers had no effect on functional and symbolic value. In conclusion, establishing confidence benefits with the customer at the specialty coffee shop significantly influenced their perceptions of value, customer satisfaction, and loyalty.

• Journal of the Korean Data and Information Science Society
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• v.17 no.2
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• pp.421-436
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• 2006

Huang proposed a grey-based nearest neighbor approach to predict accurately missing attribute value in 2004. Our study proposes which way to decide the number of nearest neighbors using not only the deng's grey relational grade but also the wen's grey relational grade. Besides, our study uses not an arithmetic(unweighted) mean but a weighted one. Also, GRG is used by a weighted value when we impute missing values. There are four different methods - DU, DW, WU, WW. The performance of WW(Wen's GRG & weighted mean) method is the best of any other methods. It had been proven by Huang that his method was much better than mean imputation method and multiple imputation method. The performance of our study is far superior to that of Huang.