This study analyzes convention tourism destination brand slogans focusing on the international convention cities. Data were collected from official tourism web sites of 190 cities which hosts more than ten international meetings in 2013. One hundred and six destination brand slogans were identified. Specifically, the researchers attempt to carry out content analysis of the linguistic and visual expressions of the slogans. Results indicated that in terms of linguistic expressions, most of slogans adopted word or phrase patterns pursuing brevity. In the brand slogan spectrum, nearly half of slogans are common type which didn't express destinations' specific attributes and benefits properly. And the most frequently used key words in the slogans are 'visit' and 'city'. While in terms of visual expressions, about 70% of slogans adopted typography for explicitness and 60% of them utilized human and natural resources as visual signs for building up unique images. Based on the results, implications for creating effective convention tourism destination brand slogans were also discussed.
Electronic commerce, commonly known as e-commerce or eCommerce, has become a major business trend in these days. The amount of trade conducted electronically has grown extraordinarily by developing the Internet technology. Most electronic commerce has being conducted between businesses to customers; therefore, the researches with respect to e-commerce are to find customer's needs, behaviors through statistical methods. However, the statistical researches, mostly based on a questionnaire, are the static researches, They can tell us the dynamic relationships between initial purchasing and repurchasing. Therefore, this study proposes dynamic research model for analyzing the cause of initial purchasing and repurchasing. This paper is based on the System-Dynamic theory, using the powerful simulation model with some restriction, The restrictions are based on the theory TAM(Technology Acceptance Model), PAM, and TPB(Theory of Planned Behavior). This article investigates not only the customer's purchasing and repurchasing behavior by passing of time but also the interactive effects to one another. This research model has six scenarios and three steps for analyzing customer behaviors. The first step is the research of purchasing situations. The second step is the research of repurchasing situations. Finally, the third step is to study the relationship between initial purchasing and repurchasing. The purpose of six scenarios is to find the customer's purchasing patterns according to the environmental changes. We set six variables in these scenarios by (1) changing the number of products; (2) changing the number of contents in on-line shopping malls; (3) having multimedia files or not in the shopping mall web sites; (4) grading on-line communities; (5) changing the qualities of products; (6) changing the customer's degree of confidence on products. First three variables are applied to study customer's purchasing behavior, and the other variables are applied to repurchasing behavior study. Through the simulation study, this paper presents some inter-relational result about customer purchasing behaviors, For example, Active community actions are not the increasing factor of purchasing but the increasing factor of word of mouth effect, Additionally. The higher products' quality, the more word of mouth effects increase. The number of products and contents on the web sites have same influence on people's buying behaviors. All simulation methods in this paper is not only display the result of each scenario but also find how to affect each other. Hence, electronic commerce firm can make more realistic marketing strategy about consumer behavior through this dynamic simulation research. Moreover, dynamic analysis method can predict the results which help the decision of marketing strategy by using the time-line graph. Consequently, this dynamic simulation analysis could be a useful research model to make firm's competitive advantage. However, this simulation model needs more further study. With respect to reality, this simulation model has some limitations. There are some missing factors which affect customer's buying behaviors in this model. The first missing factor is the customer's degree of recognition of brands. The second factor is the degree of customer satisfaction. The third factor is the power of word of mouth in the specific region. Generally, word of mouth affects significantly on a region's culture, even people's buying behaviors. The last missing factor is the user interface environment in the internet or other on-line shopping tools. In order to get more realistic result, these factors might be essential matters to make better research in the future studies.
Kim, Ja-Hyun;Seo, Jin-Won;Na, Young-Eun;An, Kwang-Guk
Korean Journal of Ecology and Environment
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v.40
no.1
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pp.130-142
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2007
This study was to examine impacts of turbid water on fish community in the downstream of Yongdam Dam during the period from June to October 2006. For the research, we selected six sampling sites in the field: two sites were controls with no influences of turbid water from the dam and other remaining four sites were the stations for an assessment of potential turbid effects. We evaluated integrative health conditions throughout applications of various models such as necropsy-based fish health assessment model (FHA), Index of Biological Integrity (IBI) using fish assemblages, and Qualitative Habitat Evaluation Index (QHEI). Laboratory tests on fish exposure under 400 NTU were performed to find out impact of turbid water using scanning electron microscope (SEM). Results showed that fine solid particles were clogging in the gill in the treatments, while particles were not found in the control. This results indicate that when inorganic turbidity increases abruptedly, fish may have a mechanical abrasion or respiratory blocking. The stream health condition, based on the IBI values, ranged between 38 and 48 (average: 42), indicating a "excellent" or "good" condition after the criteria of US EPA (1993). In the mean time, physical habitat condition, based on the QHEI, ranged 97 to 187 (average 154), indicating a "suboptimal condition". These biological outcomes were compared with chemical dataset: IBI values were more correlated (r=0.526, p<0.05, n=18) with QHEI rather than chemical water quality, based on turbidity (r=0.260, p>0.05, n=18). Analysis of the FHA showed that the individual health indicated "excellent condition", while QHEI showed no habitat disturbances (especially bottom substrate and embeddeness), food-web, and spawning place. Consequently, we concluded that the ecological health in downstream of Yongdam Dam was not impacted by the turbid water.
The spatial and temporal zooplankton dynamics were examined along ca. 100-km section of the middle to lower Seomjin River (without estuary dam in river mouth) and Youngsan River (with estuary dam in river mouth) systems during study periods (2004. Nov.${\sim}$2006. Aug.) based on a monthly sampling intervals. The spatial variation of zooplankton biomass at both river ecosystems was distinct. There was considerable longitudinal variation in total zooplankton abundance in Youngsan R. stretch. The increase in total zooplankton abundance were observed along the longitudinal stretch toward the estuary dam. In contrast, there were not statistically significant longitudinal differences in total zooplankton abundance in Seomjin R. stretch. In Youngsan R. stretch, average abundance of total zooplankton (average ranges: $199{\sim}817$ Ind. $L^{-1}$ at 3 sampling sites, n=20) were nearly $4{\sim}60$ fold higher than that of Seomjin R. stretch (average ranges: $12{\sim}43$ Ind. $L^{-1}$ at 4 sampling sites, n=20). Relative abundance of rotifers (over 80% of total zooplankton abundance) at the whole sampling sites in Youngsan R. stretch were Much higher than that of the Seomjin R. stretch. The most abundant rotifers were Polyarthra spp., Brachionus spp., Colurella spp., and Keratella spp. at the both river ecosystems. In Seomjin R. stretch, copepods carbon biomass sharply increased toward in river mouth (over 40% of total zooplankton carbon biomass). Average ranges of total zooplankton filtering rates for phytoplankton at both river ecosystems varied from 21.2 to 92.9 mL $L^{-1}\;D^{-1}$ in Youngsan R. stretch and from 2.1 to 2.6 mL $L^{-1}\;D^{-1}$ in Seomjin R. stretch. Considering the zooplankton filtering rates, zooplankton as grazers of phytoplankton in Youngsan R. stretch seemed to play the more important role in planktonic food web than that of the Seomjin R. stretch.
Planning a multi-day trip is a complex, yet time-consuming task. It usually starts with selecting a list of points of interest (POIs) worth visiting and then arranging them into an itinerary, taking into consideration various constraints and preferences. When choosing POIs to visit, one might ask friends to suggest them, search for information on the Web, or seek advice from travel agents; however, those options have their limitations. First, the knowledge of friends is limited to the places they have visited. Second, the tourism information on the internet may be vast, but at the same time, might cause one to invest a lot of time reading and filtering the information. Lastly, travel agents might be biased towards providers of certain travel products when suggesting itineraries. In recent years, many researchers have tried to deal with the huge amount of tourism information available on the internet. They explored the wisdom of the crowd through overwhelming images shared by people on social media sites. Furthermore, trip planning problems are usually formulated as 'Tourist Trip Design Problems', and are solved using various search algorithms with heuristics. Various recommendation systems with various techniques have been set up to cope with the overwhelming tourism information available on the internet. Prediction models of recommendation systems are typically built using a large dataset. However, sometimes such a dataset is not always available. For other models, especially those that require input from people, human computation has emerged as a powerful and inexpensive approach. This study proposes CYTRIP (Crowdsource Your TRIP), a multi-day trip itinerary planning system that draws on the collective intelligence of contributors in recommending POIs. In order to enable the crowd to collaboratively recommend POIs to users, CYTRIP provides a shared workspace. In the shared workspace, the crowd can recommend as many POIs to as many requesters as they can, and they can also vote on the POIs recommended by other people when they find them interesting. In CYTRIP, anyone can make a contribution by recommending POIs to requesters based on requesters' specified preferences. CYTRIP takes input on the recommended POIs to build a multi-day trip itinerary taking into account the user's preferences, the various time constraints, and the locations. The input then becomes a multi-day trip planning problem that is formulated in Planning Domain Definition Language 3 (PDDL3). A sequence of actions formulated in a domain file is used to achieve the goals in the planning problem, which are the recommended POIs to be visited. The multi-day trip planning problem is a highly constrained problem. Sometimes, it is not feasible to visit all the recommended POIs with the limited resources available, such as the time the user can spend. In order to cope with an unachievable goal that can result in no solution for the other goals, CYTRIP selects a set of feasible POIs prior to the planning process. The planning problem is created for the selected POIs and fed into the planner. The solution returned by the planner is then parsed into a multi-day trip itinerary and displayed to the user on a map. The proposed system is implemented as a web-based application built using PHP on a CodeIgniter Web Framework. In order to evaluate the proposed system, an online experiment was conducted. From the online experiment, results show that with the help of the contributors, CYTRIP can plan and generate a multi-day trip itinerary that is tailored to the users' preferences and bound by their constraints, such as location or time constraints. The contributors also find that CYTRIP is a useful tool for collecting POIs from the crowd and planning a multi-day trip.
Journal of Korean Home Economics Education Association
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v.19
no.2
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pp.1-12
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2007
This study analyzed the recognition and utilization regarding teacher's guidebook for middle school technology-home economics class in the 7th Educational Curriculum. The data were collected via e-mail to teachers teaching home economics in middle schools. These e-mail addresses were acquired from middle school web pages registered on the Educational Board. The 355 data were analyzed using the SPSS program. The results were as follows: First, teachers recognized highly the necessity of teacher's guidebook. However, as the actual guidebook was not adequately helpful, the overall degree of satisfaction was relatively low. Teachers utilizing guidebook had more positive recognition on teacher's guidebook than teachers who did not. And teachers majored in technology education thought teacher's guidebook more helpful compared with teachers majored in home economics education. Second, teachers referenced teacher's guidebook mostly for field practice guidance. Third, teachers who did not utilize teacher's guidebook used other reference materials such as Internet Web sites and audiovisual materials. They were most commonly used for the reason that the contents were ample and easy to access. Fourth, the followings were suggested to improve teacher's guidebook. The provision of learning contents that can be practically used in class, the various samples of teaching-learning method, the specified methods of planning and criteria for performance assessment, the adequate supplementations regarding textbook contents, and the improvement of the outward layout format of the guidebook.
In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.
BACKGROUND: Various culture media have been used for hydroponic cultures of horticultural plants under the smart greenhouses with natural and artificial light types. Management of the culture medium for the control of medium amounts and/or necessary components absorbed by plants during the cultivation period is performed with ICT (Information and Communication Technology) and/or IoT (Internet of Things) in a smart farm system. This study was conducted to develop the cloud-based data analysis system for effective management of culture medium applying to hydroponic culture and plant growth in smart greenhouses. METHODS AND RESULTS: Conventional inorganic Yamazaki and organic media derived from agricultural byproducts such as a immature fruit, leaf, or stem were used for hydroponic culture media. Component changes of the solutions according to the growth stage were monitored and plant growth was observed. Red and green lettuce seedlings (Lactuca sativa L.) which developed 2~3 true leaves were considered as plant materials. The seedlings were hydroponically grown in the smart greenhouse with fluorescent and light-emitting diodes (LEDs) lights of $150{\mu}mol/m^2/s$ light intensity for 35 days. Growth data of the seedlings were classified and stored to develop the relational database in the virtual machine which was generated from an open stack cloud system on the base of growth parameter. Relation of the plant growth and nutrient absorption pattern of 9 inorganic components inside the media during the cultivation period was investigated. The stored data associated with component changes and growth parameters were visualized on the web through the web framework and Node JS. CONCLUSION: Time-series changes of inorganic components in the culture media were observed. The increases of the unfolded leaves or fresh weight of the seedlings were mainly dependent on the macroelements such as a $NO_3-N$, and affected by the different inorganic and organic media. Though the data analysis system was developed, actual measurement data were offered by using the user smart device, and analysis and comparison of the data were visualized graphically in time series based on the cloud database. Agricultural management in data visualization and/or plant growth can be implemented by the data analysis system under whole agricultural sites regardless of various culture environmental changes.
The research conducted here focuses on the effect of factors that affect the behavior of UCC (User Created Content) website users, other than user's rational recognition of how useful a UCC website can be. Most discussions in the existing literature on information systems have focused on users' evaluation how a UCC website can help to attain the users' own goals. However, there are other factors and this research pays attention to an individual's 'personality,' which is stable and biological in nature. Specifically, I have noted here that 'extroversion' and 'neuroticism,' the two common personality factors presented in Eysenck's most representative 'EPQ Model' and 'Big Five Model,' are the two personality factors that affect a site's 'usefulness,' by this I mean how useful does the user consider the website and its content. How useful a site is considered by the user is the other factor that has been regarded as the antecedent factor that influences the adoption of information systems in the existing MIS (Management Information System) research. Secondly, as using or creating a UCC website does not guarantee the user's or the creator's extrinsic motivation, unlike when using the information system within an organization, there is a greater likelihood that the increase in user's activities in relation to a UCC website is motivated by emotional factors rather than rational factors. Thus, I have decided to include the relationship between an individual's personality and what they find pleasurable in the research model. Thirdly, when based on the S-O-R Paradigm of Mehrabian and Russell, the two cognitive factors and emotional factors are finally affected by stimulus, and thus these factors ultimately have an effect on an individual's respondent behavior. Therefore, this research has presented an assumption that the recognition of how useful the site and content is and what emotional pleasure it provides will finally affect the behavior of the UCC website users. Finally, the relationship between the recognition of how useful a site is and how pleasurable it is to useand UCC usage may differ depending on certain situational conditions. In other words, the relationship between the three factors may vary according to how much users are involved in the creation of the website content. Creation thus emerges as the keyword of UCC. I analyzed the above relationships through the moderating variable of the user's involvement in the creation of the site. The research result shows the following: When it comes to the relationship between an individual's personality and what they find pleasurable it is extroverted users who have a greater likelihood to feel pleasure when using a UCC website, as was expected in this research. This in turn leads to a more active usage of the UCC web site because a person who is an extrovert likes to spend time on activities with other people, is sensitive to new experiences and stimuli and thus actively responds to these. An extroverted person accepts new UCC activities as part of his/her social life, rather than getting away from this new UCC environment. This is represented by the term 'Foxonomy' where the users meet a variety of users from all over the world and contact new types of content created by these users. However, neuroticism creates the opposite situation to that created by extroversion. The representative symptoms of neuroticism are instability, stress, and tension. These dispositions are more closely related to stress caused by a new environment rather than this creatingcuriosity or pleasure. Thus, neurotic persons have an uneasy feeling and will eventually avoid the situation where their own or others' daily lives are frequently exposed to the open web environment, this eventually makes them have a negative attitude towards the web environment. When it comes to an individual's personality and how useful site is, the two personality factors of extroversion and neuroticism both have a positive relationship with the recognition of how useful the site and its content is. The positive, curious, and social dispositions of extroverted persons tend to make them consider the future usefulness and possibilities of a new type of information system, or website, based on their positive attitude, which has a significant influence on the recognition of how useful these UCC sites are. Neuroticism also favorably affects how useful a UCC website can be through a different mechanism from that of extroversion. As the neurotic persons tend to feel uneasy and have much doubt about a new type of information system, they actively explore its usefulness in order to relieve their uncomfortable feelings. In other words, neurotic persons seek out how useful a site can be in order to secure their own stable feelings. Meanwhile, extroverted persons explore how useful a site can be because of their positive attitude and curiosity. As a lot of MIS research has revealed that the recognition of how useful a site can be and how pleasurable it can be to use have been proven to have a significant effect on UCC activity. However, the relationship between these factors reveals different aspects based on the user's involvement in creation. This factor of creationgauges the interest of users in the creation of UCC contents. Involvement is a variable that shows the level of an individual's mental effort in creating UCC contents. When a user is highly involved in the creation process and makes an enormous effort to create UCC content (classed a part of a high-involvement group), their own pleasure and recognition of how useful the site is have a significantly higher effect on the future usage of the UCC contents, more significantly than the users who sit back and just retrieve the UCC content created by others. The cognitive and emotional response of those in the low-involvement group is unlikely to last long,even if they recognize the contents of a UCC website is pleasurable and useful to them. However, the high-involvement group tends to participate in the creation and the usage of UCC more favorably, connecting the experience with their own goals. In this respect, this research presents an answer to the question; why so many people are participating in the usage of UCC, the representative form of the Web 2.0 that has drastically involved more and more people in the creation of UCC, even if they cannot gain any monetary or social compensation. Neither information system nor a website can succeed unless it secures a certain level of user base. Moreover, it cannot be further developed when the reasons, or problems, for people's participation are not suitably explored, even if it has a certain user base. Thus, what is significant in this research is that it has studied users' respondent behavior based on an individual's innate personality, emotion, and cognitive interaction, unlike the existing research that has focused on 'compensation' to explain users' participation with the UCC website. There are also limitations in this research. Firstly, I divided an individual's personality into extroversion and neuroticism; however, there are many other personal factors such as neuro-psychiatricism, which also needs to be analyzed for its influence on UCC activities. Secondly, as a UCC website comes in many types such as multimedia, Wikis, and podcasting, these types need to be included as a sub-category of the UCC websites and their relationship with personality, emotion, cognition, and behavior also needs to be analyzed.
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
. This model is composed of four paths such as dimensions of e-store personality${\rightarrow}$e-store identification, e-store identification${\rightarrow}$e-store loyalty, e-store identification ${\rightarrow}$e-store trust${\rightarrow}$e-store loyalty, and e-store identification${\rightarrow}$e-store engagement${\rightarrow}$e-store loyalty. II. Research Method Ladies under 30s were the respondents of this survey. Data were collected from January 20th to February 26th in 2010. A total of 200 questionnaires were distributed and 169 respondents were analysed finally to test hypotheses because 31 questionnaires had incorrect or missing responses. SPSS 12.0 and LISREL 7.0 program were used to test frequency, reliability, factor, and structural equation modeling analysis. III. Result and Conclusion According to results from factor analysis, eigen value was over 1.0 and items which were below 0.6 were deleted. Consequently, 9 factors(% of total variance is 72.011%) were searched. All Cronbach's ${\alpha}$ values are over the recommended level(${\alpha}$ > 0.7). The overall fit indices are acceptable such as ${\chi}^2$=2028.36(p=0.00), GFI=0.87, AGFI=0.82, CFI=0.81, IFI=0.92, RMR=0.075. All factor loadings were over the recommended level. As the result of discriminant validity check with chi-square difference test between paired constructs, each construct has good discriminant validity. The overall fit indices of final model are acceptable such as ${\chi}^2$=340.73(df=36, p=0.00), GFI=0.92, AGFI=0.81, CFI=0.91, IFI=0.91, RMR=0.085. As test results, 5 out of 6 hypotheses are supported because there are statistically significant casual relationships in structural equation model, shown in
. 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.
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