This study critically analyzed the user experience (UX) of mobile applications, focusing on the advertising platforms of mobile applications for culture and arts content. This study aims to examine the direction for growth of the related mobile applications and propose alternative approaches to improve usability. In this study, a mobile app named 'Moviepre' was selected, and a heuristic evaluation was performed for in-depth exploration. For the selected case, the UX Honeycomb model was reconstructed to analyze useful, usable, desirable, findable, accessible, and credible elements of the case. First, since the users' preference for the price factor did not show a significant correlation with the usefulness of the content and the interface, it is necessary to make sure that the mobile application has unique values to gain a competitive advantage in the market. Second, by adopting customer path stages for analysis, the result indicated that users continuously interact with the service from the first moment they are aware of the mobile application. Third, if the user feels uncomfortable, it is likely that these factors hinder the establishment of a long-term relationship between the users and the mobile application. Finally, brand identity should be clearly established, and brand image strategy needs to be developed to satisfy users' expectations that high-quality culture and arts content will be available through the mobile application.
As relationship between buyer and seller has been brought closer and long-term relationship has been more important in B2B markets, the importance of service and service convenience increases as well as product. In homogeneous markets, where service offerings are similar and therefore not key competitive differentiator, providing greater convenience may enable a competitive advantage. Service convenience, as conceptualized by Berry et al. (2002), is defined as the consumers' time and effort perceptions related to buying or using a service. For this reason, B2B customers are interested in how fast the service is provided and how much save non-monetary cost like time or effort by the service convenience along with service quality. Therefore, this study attempts to investigate the impact of service convenience on relationship factors such as relationship satisfaction, relationship commitment, and relationship performance. The purpose of this study is to find out whether service convenience can be a new antecedent of relationship quality and relationship performance. In addition, this study tries to examine how five-dimensional service convenience constructs (decision convenience, access convenience, transaction convenience, benefit convenience, post-benefit convenience) affect customers' relationship satisfaction, relationship commitment, and relationship performance. The service convenience comprises five fundamental components - decision convenience (the perceived time and effort costs associated with service purchase or use decisions), access convenience(the perceived time and effort costs associated with initiating service delivery), transaction convenience(the perceived time and effort costs associated with finalizing the transaction), benefit convenience(the perceived time and effort costs associated with experiencing the core benefits of the offering) and post-benefit convenience (the perceived time and effort costs associated with reestablishing subsequent contact with the firm). Earlier studies of perceived service convenience in the industrial market are none. The conventional studies that have dealt with service convenience have usually been made in the consumer market, or they have dealt with convenience aspects in the service process. This service convenience measure for consumer market can be useful tool to estimate service quality in B2B market. The conceptualization developed by Berry et al. (2002) reflects a multistage, experiential consumption process in which evaluations of convenience vary at each stage. For this reason, the service convenience measure is good for B2B service environment which has complex processes and various types. Especially when categorizing B2B service as sequential stage of service delivery like Kumar and Kumar (2004), the Berry's service convenience measure which reflect sequential flow of service deliveries suitable to establish B2B service convenience. For this study, data were gathered from respondents who often buy business service and analyzed by structural equation modeling. The sample size in the present study is 119. Composite reliability values and average variance extracted values were examined for each variable to have reliability. We determine whether the measurement model supports the convergent validity by CFA, and discriminant validity was assessed by examining the correlation matrix of the constructs. For each pair of constructs, the square root of the average variance extracted exceeded their correlations, thus supporting the discriminant validity of the constructs. Hypotheses were tested using the Smart PLS 2.0 and we calculated the PLS path values and followed with a bootstrap re-sampling method to test the hypotheses. Among the five dimensional service convenience constructs, four constructs (decision convenience, transaction convenience, benefit convenience, post-benefit convenience) affected customers' positive relationship satisfaction, relationship commitment, and relationship performance. This result means that service convenience is important cue to improve relationship between buyer and seller. One of the five service convenience dimensions, access convenience, does not affect relationship quality and performance, which implies that the dimension of service convenience is not important factor of cumulative satisfaction. The Cumulative satisfaction can be distinguished from transaction-specific customer satisfaction, which is an immediate post-purchase evaluative judgment or an affective reaction to the most recent transactional experience with the firm. Because access convenience minimizes the physical effort associated with initiating an exchange, the effect on relationship satisfaction similar to cumulative satisfaction may be relatively low in terms of importance than transaction-specific customer satisfaction. Also, B2B firms focus on service quality, price, benefit, follow-up service and so on than convenience of time or place in service because it is relatively difficult to change existing transaction partners in B2B market compared to consumer market. In addition, this study using partial least squares methods reveals that customers' satisfaction and commitment toward relationship has mediating role between the service convenience and relationship performance. The result shows that management and investment to improve service convenience make customers' positive relationship satisfaction, and then the positive relationship satisfaction can enhance the relationship commitment and relationship performance. And to conclude, service convenience management is an important part of successful relationship performance management, and the service convenience is an important antecedent of relationship between buyer and seller such as the relationship commitment and relationship performance. Therefore, it has more important to improve relationship performance that service providers enhance service convenience although competitive service development or service quality improvement is important. Given the pressure to provide increased convenience, it is not surprising that organizations have made significant investments in enhancing the convenience aspect of their product and service offering.
These days, the concept of creating shared value is drawn keen attentions to. This interest comes out of the expectation that Creating Shared Value(CSV) can offer an answer to some social issues by creating societal and economic values on the top of the achievements that existing Corporate Social Responsibility(CSR) has made. However, it is difficult to make a clear distinction between the achievements that the activities of CSR and CSV have made. In this regard, developing a methodology to make an actual proof analysis on the accomplishments of CSV and to verify customer's awareness of and attitude towards the CSV is necessarily required. A company needs to gain a competitive advantage in the marketplace as well as resolve a social issue by innovating value chain. The research has verified the cause and effect relationship between the CSV from the point of view of value chain and the purchase intention aroused by its economic, societal and cultural values through the company image and credibility with actual proof analysis and come up with following results. First, a societal and cultural value resulted in giving positive impact on a company's image, which implies that CSV activities can be the thin end of the wedge through which customers have a good image of the company involved in CSV. Second, a societal value makes a positive influence on the credibility of a company. In this regard, CSV should be recognized not just as a thing that generates a cost, but a way to win-win as well as future development. Third and last, the research results show that both company image and credibility influence on purchase intention. Considering that CSV generates a positive evaluation on a company that will ultimately cause continuous profit-making, the company's ultimate goal of activities, it should be approached from the perspective of making a mid-and-long term strategy.
In recent years, one of the major reasons for the fierce competition amongst firms is that they strive to increase their own market shares and customer acquisition rate in the same market with similar and apparently undifferentiated products in terms of quality and perceived benefit. Because of this change in recent marketing environment, the differentiated after-sales service and diversified promotion strategies have become more important to gain competitive advantage. Price promotion is the favorite strategy that most retailers use to achieve short-term sales increase, induce consumer's brand switch, in troduce new product into market, and so forth. However, if marketers apply or copy an identical price promotion strategy without considering the characteristic differences in product and consumer preference, it will cause serious problems because discounted price itself could make people skeptical about product quality, and the changes of perceived value might appear differently depending on other factors such as consumer involvement or brand attitude. Previous studies showed that price promotion would certainly increase sales, and the discounted price compared to regular price would enhance the consumer's perceived values. On the other hand, discounted price itself could make people depreciate or skeptical about product quality, and reduce the consumers' positivity bias because consumers might be unsure whether the current price promotion is the retailer's best price offer. Moreover, we cannot say that discounted price absolutely enhances the consumer's perceived values regardless of product category and purchase situations. That is, the factors that affect consumers' value perceptions and buying behavior are so diverse in reality that the results of studies on the same dependent variable come out differently depending on what variable was used or how experiment conditions were designed. Majority of previous researches on the effect of price-comparison advertising have used consumers' buying behavior as dependent variable. In order to figure out consumers' buying behavior theoretically, analysis of value perceptions which influence buying intentions is needed. In addition, they did not combined the independent variables such as brand loyalty and price discount rate together. For this reason, this paper tried to examine the moderating effect of brand loyalty on relationship between the different levels of discounting rate and buyers' value perception. And we provided with theoretical and managerial implications that marketers need to consider such variables as product attributes, brand loyalty, and consumer involvement at the same time, and then establish a differentiated pricing strategy case by case in order to enhance consumer's perceived values properl. Three research concepts were used in our study and each concept based on past researches was defined. The perceived acquisition value in this study was defined as the perceived net gains associated with the products or services acquired. That is, the perceived acquisition value of the product will be positively influenced by the benefits buyers believe they are getting by acquiring and using the product, and negatively influenced by the money given up to acquire the product. And the perceived transaction value was defined as the perception of psychological satisfaction or pleasure obtained from taking advantage of the financial terms of the price deal. Lastly, the brand loyalty was defined as favorable attitude towards a purchased product. Thus, a consumer loyal to a brand has an emotional attachment to the brand or firm. Repeat purchasers continue to buy the same brand even though they do not have an emotional attachment to it. We assumed that if the degree of brand loyalty is high, the perceived acquisition value and the perceived transaction value will increase when higher discount rate is provided. But we found that there are no significant differences in values between two different discount rates as a result of empirical analysis. It means that price reduction did not affect consumer's brand choice significantly because the perceived sacrifice decreased only a little, and customers are satisfied with product's benefits when brand loyalty is high. From the result, we confirmed that consumers with high degree of brand loyalty to a specific product are less sensitive to price change. Thus, using price promotion strategy to merely expect sale increase is not recommendable. Instead of discounting price, marketers need to strengthen consumers' brand loyalty and maintain the skimming strategy. On the contrary, when the degree of brand loyalty is low, the perceived acquisition value and the perceived transaction value decreased significantly when higher discount rate is provided. Generally brands that are considered inferior might be able to draw attention away from the quality of the product by making consumers focus more on the sacrifice component of price. But considering the fact that consumers with low degree of brand loyalty are known to be unsatisfied with product's benefits and have relatively negative brand attitude, bigger price reduction offered in experiment condition of this paper made consumers depreciate product's quality and benefit more and more, and consumer's psychological perceived sacrifice increased while perceived values decreased accordingly. We infer that, in the case of inferior brand, a drastic price-cut or frequent price promotion may increase consumers' uncertainty about overall components of product. Therefore, it appears that reinforcing the augmented product such as after-sale service, delivery and giving credit which is one of the levels consisting of product would be more effective in reality. This will be better rather than competing with product that holds high brand loyalty by reducing sale price. Although this study tried to examine the moderating effect of brand loyalty on relationship between the different levels of discounting rate and buyers' value perception, there are several limitations. This study was conducted in controlled conditions where the high involvement product and two different levels of discount rate were applied. Given the presence of low involvement product, when both pieces of information are available, it is likely that the results we have reported here may have been different. Thus, this research results explain only the specific situation. Second, the sample selected in this study was university students in their twenties, so we cannot say that the results are firmly effective to all generations. Future research that manipulates the level of discount along with the consumer involvement might lead to a more robust understanding of the effects various discount rate. And, we used a cellular phone as a product stimulus, so it would be very interesting to analyze the result when the product stimulus is an intangible product such as service. It could be also valuable to analyze whether the change of perceived value affects consumers' final buying behavior positively or negatively.
Recently, AlphaGo which is Bakuk (Go) artificial intelligence program by Google DeepMind, had a huge victory against Lee Sedol. Many people thought that machines would not be able to win a man in Go games because the number of paths to make a one move is more than the number of atoms in the universe unlike chess, but the result was the opposite to what people predicted. After the match, artificial intelligence technology was focused as a core technology of the fourth industrial revolution and attracted attentions from various application domains. Especially, deep learning technique have been attracted as a core artificial intelligence technology used in the AlphaGo algorithm. The deep learning technique is already being applied to many problems. Especially, it shows good performance in image recognition field. In addition, it shows good performance in high dimensional data area such as voice, image and natural language, which was difficult to get good performance using existing machine learning techniques. However, in contrast, it is difficult to find deep leaning researches on traditional business data and structured data analysis. In this study, we tried to find out whether the deep learning techniques have been studied so far can be used not only for the recognition of high dimensional data but also for the binary classification problem of traditional business data analysis such as customer churn analysis, marketing response prediction, and default prediction. And we compare the performance of the deep learning techniques with that of traditional artificial neural network models. The experimental data in the paper is the telemarketing response data of a bank in Portugal. It has input variables such as age, occupation, loan status, and the number of previous telemarketing and has a binary target variable that records whether the customer intends to open an account or not. In this study, to evaluate the possibility of utilization of deep learning algorithms and techniques in binary classification problem, we compared the performance of various models using CNN, LSTM algorithm and dropout, which are widely used algorithms and techniques in deep learning, with that of MLP models which is a traditional artificial neural network model. However, since all the network design alternatives can not be tested due to the nature of the artificial neural network, the experiment was conducted based on restricted settings on the number of hidden layers, the number of neurons in the hidden layer, the number of output data (filters), and the application conditions of the dropout technique. The F1 Score was used to evaluate the performance of models to show how well the models work to classify the interesting class instead of the overall accuracy. The detail methods for applying each deep learning technique in the experiment is as follows. The CNN algorithm is a method that reads adjacent values from a specific value and recognizes the features, but it does not matter how close the distance of each business data field is because each field is usually independent. In this experiment, we set the filter size of the CNN algorithm as the number of fields to learn the whole characteristics of the data at once, and added a hidden layer to make decision based on the additional features. For the model having two LSTM layers, the input direction of the second layer is put in reversed position with first layer in order to reduce the influence from the position of each field. In the case of the dropout technique, we set the neurons to disappear with a probability of 0.5 for each hidden layer. The experimental results show that the predicted model with the highest F1 score was the CNN model using the dropout technique, and the next best model was the MLP model with two hidden layers using the dropout technique. In this study, we were able to get some findings as the experiment had proceeded. First, models using dropout techniques have a slightly more conservative prediction than those without dropout techniques, and it generally shows better performance in classification. Second, CNN models show better classification performance than MLP models. This is interesting because it has shown good performance in binary classification problems which it rarely have been applied to, as well as in the fields where it's effectiveness has been proven. Third, the LSTM algorithm seems to be unsuitable for binary classification problems because the training time is too long compared to the performance improvement. From these results, we can confirm that some of the deep learning algorithms can be applied to solve business binary classification problems.
As the population, buying power, and intensity of self-expression of the elderly generation increase, its importance as a market segment is also growing. Therefore, the mass marketing strategy for the elderly generation must be changed to a micro-marketing strategy based on the results of sub-segmentation that suitably captures the characteristics of this generation. Furthermore, as a customer access strategy is decided by sub-segmentation, proper segmentation is one of the key success factors for micro-marketing. Segments or sub-segments are different from sectors, because segmentation or sub-segmentation for micro-marketing is based on the homogeneity of customer needs. Theoretically, complete segmentation would reveal a single voice. However, it is impossible to achieve complete segmentation because of economic factors, factors that affect effectiveness, etc. To obtain a single voice from a segment, we sometimes need to divide it into many individual cases. In such a case, there would be a many segments to deal with. On the other hand, to maximize market access performance, fewer segments are preferred. In this paper, we use the term "sub-segmentation" instead of "segmentation," because we divide a specific segment into more detailed segments. To sub-segment the elderly generation, this paper takes their lifestyles and life stages into consideration. In order to reflect these aspects, various surveys and several rounds of expert interviews and focused group interviews (FGIs) were performed. Using the results of these qualitative surveys, we can define six sub-segments of the elderly generation. This paper uses five rules to divide the elderly generation. The five rules are (1) mutually exclusive and collectively exhaustive (MECE) sub-segmentation, (2) important life stages, (3) notable lifestyles, (4) minimum number of and easy classifiable sub-segments, and (5) significant difference in voices among the sub-segments. The most critical point for dividing the elderly market is whether children are married. The other points are source of income, gender, and occupation. In this paper, the elderly market is divided into six sub-segments. As mentioned, the number of sub-segments is a very key point for a successful marketing approach. Too many sub-segments would lead to narrow substantiality or lack of actionability. On the other hand, too few sub-segments would have no effects. Therefore, the creation of the optimum number of sub-segments is a critical problem faced by marketers. This paper presents a method of evaluating the fitness of sub-segments that was deduced from the preceding surveys. The presented method uses the degree of homogeneity (DoH) to measure the adequacy of sub-segments. This measure uses quantitative survey questions to calculate adequacy. The ratio of significantly homogeneous questions to the total numbers of survey questions indicates the DoH. A significantly homogeneous question is defined as a question in which one case is selected significantly more often than others. To show whether a case is selected significantly more often than others, we use a hypothesis test. In this case, the null hypothesis (H0) would be that there is no significant difference between the selection of one case and that of the others. Thus, the total number of significantly homogeneous questions is the total number of cases in which the null hypothesis is rejected. To calculate the DoH, we conducted a quantitative survey (total sample size was 400, 60 questions, 4~5 cases for each question). The sample size of the first sub-segment-has no unmarried offspring and earns a living independently-is 113. The sample size of the second sub-segment-has no unmarried offspring and is economically supported by its offspring-is 57. The sample size of the third sub-segment-has unmarried offspring and is employed and male-is 70. The sample size of the fourth sub-segment-has unmarried offspring and is not employed and male-is 45. The sample size of the fifth sub-segment-has unmarried offspring and is female and employed (either the female herself or her husband)-is 63. The sample size of the last sub-segment-has unmarried offspring and is female and not employed (not even the husband)-is 52. Statistically, the sample size of each sub-segment is sufficiently large. Therefore, we use the z-test for testing hypotheses. When the significance level is 0.05, the DoHs of the six sub-segments are 1.00, 0.95, 0.95, 0.87, 0.93, and 1.00, respectively. When the significance level is 0.01, the DoHs of the six sub-segments are 0.95, 0.87, 0.85, 0.80, 0.88, and 0.87, respectively. These results show that the first sub-segment is the most homogeneous category, while the fourth has more variety in terms of its needs. If the sample size is sufficiently large, more segmentation would be better in a given sub-segment. However, as the fourth sub-segment is smaller than the others, more detailed segmentation is not proceeded. A very critical point for a successful micro-marketing strategy is measuring the fit of a sub-segment. However, until now, there have been no robust rules for measuring fit. This paper presents a method of evaluating the fit of sub-segments. This method will be very helpful for deciding the adequacy of sub-segmentation. However, it has some limitations that prevent it from being robust. These limitations include the following: (1) the method is restricted to only quantitative questions; (2) the type of questions that must be involved in calculation pose difficulties; (3) DoH values depend on content formation. Despite these limitations, this paper has presented a useful method for conducting adequate sub-segmentation. We believe that the present method can be applied widely in many areas. Furthermore, the results of the sub-segmentation of the elderly generation can serve as a reference for mature marketing.
Nowadays, it is common that most consumers are purchasing goods in e-stores. The e-stores eager to attract, revisit, retain, and finally convert them into loyal customers. The e-store marketers have planned and executed numerous marketing efforts. As one of the marketing activities, e-store managers attempt to build web sites that meet customers' functional and psychological needs. A wide array of studies has been done to identify factors that could affect customers' response of web sites. Majority of studies were conducted to verify technology-related and functional variables of the website which facilitate transactions and enhance customer responses such as purchase intention and website loyalty. However, there has been little research on the external cues of website and psychological variables of consumer that could have positive influences on customer response. The purpose of this study is to investigate the influence of e-store personality on e-store loyalty through mediating variables such as e-store identification, e-store trust, and e-store engagement. The authors of this study develop the model and set up the six main hypotheses and a set of sub-hypotheses based on a literature review, shown in
To support business decision making, interests and efforts to analyze and use transaction data in different perspectives are increasing. Such efforts are not only limited to customer management or marketing, but also used for monitoring and detecting fraud transactions. Fraud transactions are evolving into various patterns by taking advantage of information technology. To reflect the evolution of fraud transactions, there are many efforts on fraud detection methods and advanced application systems in order to improve the accuracy and ease of fraud detection. As a case of fraud detection, this study aims to provide effective fraud detection methods for auction exception agricultural products in the largest Korean agricultural wholesale market. Auction exception products policy exists to complement auction-based trades in agricultural wholesale market. That is, most trades on agricultural products are performed by auction; however, specific products are assigned as auction exception products when total volumes of products are relatively small, the number of wholesalers is small, or there are difficulties for wholesalers to purchase the products. However, auction exception products policy makes several problems on fairness and transparency of transaction, which requires help of fraud detection. In this study, to generate fraud detection rules, real huge agricultural products trade transaction data from 2008 to 2010 in the market are analyzed, which increase more than 1 million transactions and 1 billion US dollar in transaction volume. Agricultural transaction data has unique characteristics such as frequent changes in supply volumes and turbulent time-dependent changes in price. Since this was the first trial to identify fraud transactions in this domain, there was no training data set for supervised learning. So, fraud detection rules are generated using outlier detection approach. We assume that outlier transactions have more possibility of fraud transactions than normal transactions. The outlier transactions are identified to compare daily average unit price, weekly average unit price, and quarterly average unit price of product items. Also quarterly averages unit price of product items of the specific wholesalers are used to identify outlier transactions. The reliability of generated fraud detection rules are confirmed by domain experts. To determine whether a transaction is fraudulent or not, normal distribution and normalized Z-value concept are applied. That is, a unit price of a transaction is transformed to Z-value to calculate the occurrence probability when we approximate the distribution of unit prices to normal distribution. The modified Z-value of the unit price in the transaction is used rather than using the original Z-value of it. The reason is that in the case of auction exception agricultural products, Z-values are influenced by outlier fraud transactions themselves because the number of wholesalers is small. The modified Z-values are called Self-Eliminated Z-scores because they are calculated excluding the unit price of the specific transaction which is subject to check whether it is fraud transaction or not. To show the usefulness of the proposed approach, a prototype of fraud transaction detection system is developed using Delphi. The system consists of five main menus and related submenus. First functionalities of the system is to import transaction databases. Next important functions are to set up fraud detection parameters. By changing fraud detection parameters, system users can control the number of potential fraud transactions. Execution functions provide fraud detection results which are found based on fraud detection parameters. The potential fraud transactions can be viewed on screen or exported as files. The study is an initial trial to identify fraud transactions in Auction Exception Agricultural Products. There are still many remained research topics of the issue. First, the scope of analysis data was limited due to the availability of data. It is necessary to include more data on transactions, wholesalers, and producers to detect fraud transactions more accurately. Next, we need to extend the scope of fraud transaction detection to fishery products. Also there are many possibilities to apply different data mining techniques for fraud detection. For example, time series approach is a potential technique to apply the problem. Even though outlier transactions are detected based on unit prices of transactions, however it is possible to derive fraud detection rules based on transaction volumes.
The marketing environment has become competitive to an extent that requires firms to target their products at markets that span national boundaries. However, competitive clout cannot be achieved in global consumer markets unless firms thoroughly understand and adequately respond to the core values and needs of those consumers. Brand equity is one of the most important assets to a company. Especially in sportswear markets, brand equity is the crucial value added to a product by its brand name. Factors such as country of origin also influence customer's attitude towards brand equity. Therefore, this paper discusses the relationship between country of origin effect and brand equity, and how they influence consumers' loyalty for respective brands. This paper focused on the sports shoes market, because it is an increasing area of opportunity for world manufacturers. The objectives of this study were the following. (1) Test the effect of country of origin on brand equity. (2) Test how brand equity influences consumers' brand loyalty. (3) Find whether there are differences in the effects of country of origin and brand equity among the three countries. (4) Find whether there are differences in the effects of country of origin and brand equity among the different lifestyles. Based on the review of literature results, the hypotheses are concluded as the following: H1-a: Country image has positive influence on country of origin. H1-b: Product perception has positive influence on country of origin. H2-a: Perceived quality has positive effect on brand equity. H2-b: Perceived price has positive effect on brand equity. H3: Country of origin has positive effect on brand equity. H4: Brand equity has a positive impact on brand loyalty. Research model was constructed (see Fig. 1). After data analysis, the following results were concluded: sports shoes purchase behavior showed significant differences among Korean, Chinese, and American consumers for favorite brand, purchased brand, purchased place, information usage, and favorite sports games. The results of this study also extend the research of the relationship among country of origin, brand equity and brand loyalty to the sports shoes market. Brand equity was proven to have a significant relationship with brand loyalty for all countries. The factors which can influence brand equity are different for different countries. The third finding of this paper is that we identified different three lifestyles, adventurer, follower, and laggard, for Korean, Chinese and American consumers. Without the nationality boundary, seeing the emergence of a new group of consumers who have similar preferences and buy similar brands is more important. All of the consumers consider brand equity to keep their brand loyalty. Perceived price is the only factor which can influence brand equity for adventurers; brand is more important for them. The laggards were not influenced by any factor. All of the factors expect perceived price are important for the followers. Marketing managers should consider brand equity when introducing their brand into a new market. Also localization is the basic strategy that all the sports shoes companies should understand. But as a global brand, understanding the same characteristics for each country is more important to build global strategy.
Virtual community(VC) will increasingly be organized as commercial enterprises, with the objective of earning an attractive financial return by providing members with valuable resources and environment. For example, Cyworld.com in Korea uses several community services to enable customers of Cyworld to take control of their own value as potential purchasers of products and services. Although initial adoption is important for online network service success, it does not necessarily result in the desired managerial performance unless the initial usage is continuously related to the continuous usage and purchase. Particularly, the customer who receives relevant online services and is well equipped with online network services, will trust the online service provider and perceive less risk and experience more activities such as continuous usage and purchase. Thus, how to promote continued online service usage or, alternatively, how to prevent discontinuance is a critical issue for VC service providers to consider. By aggregating a wide range of information and online environments for customers and providing trust to its members, the service providers of virtual communities help to reduce the perceived risk of continuous usage and purchase. Drill down, online service managers realize that achieving strong and sustained customers who continuously use online service and purchase on it is crucial. Therefore, the research into this online service continuance will identify the relationship between the initial usage and the continuous usage and purchase. The research of continuous usage or post adoption has recently emerged as an important issue in the IS literature. Individuals' information systems(IS) continuous usage decisions are congruent with consumers' repeat purchase decisions. The TAM(Technology Acceptance Model) paradigm has been strongly confirmed across a wide range from product purchase on EC to online service usage contexts. The analysis of IS usage based on TAM has proven to be successful across almost online service contexts. However, most of previous studies have focused on only an area (i.e., VC or EC). Just little research has tried to analyze the relationship between VC and EC. The effect of some factors on user intention, captured through several theories such as TAM, has been demonstrated. Yet, few studies have explored the salient relationships of VC users' EC acceptance. To fill this gap between VC and EC research, this paper attempts to develop a research model that extends the TAM perspective in view of the additional contributions of trust in the service provider and trust in members on some factors that affect EC and VC adoption. In this extension, we applied the TAM-to-TAM(T2T) model, and analyzed the transfer effect of trust between these two TAMs. The research model was empirically tested on the context of a social network service. The model was to extend TAM with the trust concept for the virtual community environment from the perspective of tasks. By building an extended model of TAM and examining the relationships between trust and the existing variables of TAM, it is aimed to explain a user's continuous intention to use VC and purchase on EC. The unit of analysis in this paper is an individual user of a virtual community. The population of interest is the individual with the experiences in virtual community. The data for this paper was made available via a Web survey of VC users. In total, 281 cases were gathered for about one week, but there were some missing values in the sample and there were some inappropriate cases. Thus, only 248 cases were finally analyzed. We chose the structural equation analysis to test the hypotheses and it is better suited for explaining complex relationships than the other methods. In this test, AMOS was used to test the Structural Equation Model (SEM). Noticeable results have been found in the T2T model regarding the factors affecting the intention to use of virtual community and loyalty. Our result showed that trust transfer plays a key role in forming the two adoption beliefs. Overall, this study preliminarily confirms the salience of trust transfer in online service.
. This model is composed of four paths such as dimensions of e-store personality. First of all, hypothesis 1 is partially supported because sub-hypothesis 1-1 and 1-2 are supported, whereas sub-hypothesis 1-3, 1-4, and 1-5 are rejected. Specifically, it reveals that warmth and sophistication dimensions in e-store personality have positive influence on e-store identification, however, activity, progressiveness, and strictness does not have any significant relationship on e-store identification. Secondly, hypothesis 2 was supported. Therefore, it can be said that e-store identification has a positive impact on e-store trust. Thirdly, hypothesis 3 is also supported. Hence, there is a positive relationship between e-store identification and e-store engagement. Fourthly, hypothesis 4 is supported too. e-store identification has a positive influence on e-store loyalty. Fifthly, hypothesis 5 is also accepted. This indicates that e-store trust is a precedent variable which positively affects e-store loyalty. Lastly, it reveals that e-store engagement has a positive impact on e-store loyalty. Therefore, hypothesis 6 is supported. The findings of the study imply that some dimensions of e-store personality have a positive influence on e-store identification, and that e-store identification has direct and indirect influence on e-store loyalty through e-store trust and e-store engagement positively. These results also suggest that the e-store identification in e-store personality is a precedent variable which positively affects e-store loyalty directly and indirectly through e-store trust and engagement as a mediating variable. Therefore, e-store marketers need to implement website strategy based on e-store personality, e-store identification, e-store trust, and e-store engagement to meet customers' psychological needs and enhance e-store loyalty. Finally, the limitations and future study directions based on this study are discussed.
A Study on the Application of Outlier Analysis for Fraud Detection: Focused on Transactions of Auction Exception Agricultural Products
(부정 탐지를 위한 이상치 분석 활용방안 연구 : 농수산 상장예외품목 거래를 대상으로)
The Relationship among Country of Origin, Brand Equity and Brand Loyalty: Comparison among USA, China and Korea
(원산지효과, 상표자산 및 상표충성 간의 관계에 관한 연구: 미국, 중국, 한국의 비교분석)
A Study on EC Acceptance of Virtual Community Users
(가상 공동체 사용자의 전자상거래 수용에 대한 연구)
이메일무단수집거부
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