Despite the growing importance of video-based social media content, such as vlogs, as a marketing tool in the travel industry, there is limited research on the characteristics that enhance engagement among potential travelers. This study explores the influence of emotional valence in YouTube travel content on viewer engagement, specifically likes and comments. We analyzed 4,619 travel-related YouTube videos from eight popular tourist cities. Using negative binomial regression analysis, we found that both positive and negative emotions significantly influence the number of likes received. Videos with higher positive emotions as well as negative emotions receive more likes. However, when it comes to the number of comments, only negative emotions showed a significant positive influence, while positive emotions had no significant impact. These findings offer valuable insights for marketers seeking to optimize engagement strategies on YouTube, considering the unique nature of travel products. Further research into the effects of specific emotions on engagement is warranted to improve marketing strategies. This study highlights the powerful impact of emotions on viewer engagement in the context of social media, particularly on YouTube.
This study has examined the effect of cognitive resource on purchase intention of scarcity products according to the level of need for cognitive closure. In order to find out the effect on purchase intention for products that are presented a shopping environment is supposed, where various timing of consumer promotion reward exist, and where consumers can easily access and experience a lot of cognitive changes. the effect of how these two influences are adjusted according to the level of need for cognitive closure (NFCC). The study divide into two experiments. Research analyzes the behavioral differences of consumers for scarcity message products according to cognitive resource level with a moderating effect of NFCC. As a result of the study, Research according to the level of cognitive resource, when applied scarcity message product showed a negative effect of the cognitive resource (self-regulating resource) depletion level on the purchase intention of high-involvement product with scarcity message (Hypothesis 1). Consumers' purchase intention for limited products was higher at the non-depleted level than at the cognitive resource depletion level, and this difference was found statistically significant. Next, as a result of examining the difference according to the level of NFCC, the difference in the influence of cognitive resource level on purchase intention of scarcity products was found to be statistically significant where the NFCC was low (Hypothesis 2).
As the aversion to advertising grows, native advertising has gained significant attention as a means to counteract this rejection. Native advertising is designed to seamlessly blend with other content on the page where they are displayed. They mimic the overall design and presentation of the platform, providing a natural exposure to consumers. Many companies utilize native advertising, but there is not much academic research on this topic. Therefore this study aims to examine the effectiveness of native advertising for social issues. The study looked at two types of native advertising: ads created by a company and ads sponsored by a company. Results suggested that consumers showed more positive attitudes towards a company's ads if they were sponsored by the company rather than created by the company. This study argued that this effect would be more pronounced for consumers who tended to buy ethically. To verify these hypotheses an online experiment was conducted revealing that on average consumers displayed the same attitude toward a company whether the native advertising was created or sponsored by a company. However, it was also discovered that consumers with a tendency for ethical consumerism formed more positive attitudes toward companies when the company sponsored native advertising as opposed to having created it. In practice, this study suggests how companies can improve the effectiveness of native advertising, such as implementing native advertising as a sponsor and being transparent about their advertising to appeal to consumers with high ethical consumption tendencies. This study expands the scope of research in areas related to native adverting and corporate social responsibilities.
Currently, the domestic traditional market has not escaped the swamp of stagnation that began in the early 2000s despite various projects promoted by many related players such as the central government and local governments. In order to overcome the crisis faced by the traditional market, various R&Ds have recently been conducted on how to build a smart traditional market that combines information and communication technologies such as big data analysis, artificial intelligence, and the Internet of Things. This study analyzes various previous studies, users of traditional markets, and application cases of ICT technology in foreign traditional markets since 2012 and proposes a model to build a smart traditional market using ICT technology based on the analysis. The model proposed in this study includes building a traditional market metaverse that can interact with visitors, certifying visits to traditional markets through digital signage with NFC technology, improving accuracy of fire detection functions using IoT and AI technology, developing smartphone apps for market launch information and event notification, and an e-commerce system. If a smart traditional market platform is implemented and operated based on the smart traditional market platform model presented in this study, it will not only draw interest in the traditional market to MZ generation and foreigners, but also contribute to revitalizing the traditional market in the future.
In a customer-based industry, customer retention is the competitiveness of a company, and improving customer retention improves the competitiveness of the company. Therefore, accurate prediction and management of potential dormant customers is paramount to increasing the competitiveness of the enterprise. In particular, there are numerous competitors in the domestic card industry, and the government is introducing an automatic closing system for dormant card management. As a result of these social changes, the card industry must focus on better predicting and managing potential dormant cards, and better predicting dormant customers is emerging as an important challenge. In this study, the Recurrent Neural Network (RNN) methodology was used to predict potential dormant customers in the card industry, and in particular, Long-Short Term Memory (LSTM) was used to efficiently learn data for a long time. In addition, to redefine the variables needed to predict dormant customers in the card industry, Unified Theory of Technology (UTAUT), an integrated technology acceptance theory, was applied to redefine and group the variables used in the model. As a result, stable model accuracy and F-1 score were obtained, and Hit-Ratio proved that models using LSTM can produce stable results compared to other algorithms. It was also found that there was no moderating effect of demographic information that could occur in UTAUT, which was pointed out in previous studies. Therefore, among variable selection models using UTAUT, dormant customer prediction models using LSTM are proven to have non-biased stable results. This study revealed that there may be academic contributions to the prediction of dormant customers using LSTM algorithms that can learn well from previously untried time series data. In addition, it is a good example to show that it is possible to respond to customers who are preemptively dormant in terms of customer management because it is predicted at a time difference with the actual dormant capture, and it is expected to contribute greatly to the industry.
Seonghun, Kim;Suelki, Do;Sangeun, Han;Jayhoon, Kim;Seokjong, Lim;Jinho, Park
Journal of the Korean Society for information Management
/
v.39
no.4
/
pp.269-306
/
2022
This study aimed to develop indicators that can measure the digital transformation performance of science and technology information construction and sharing systems by utilizing the Digital Curation Maturity Models. For digital transformation, it is necessary to consider not only simple service improvement but also organizational and business changes. In this study, we aimed to develop a model for measuring the digital transformation of KISTI, Korea's representative science and technology information service organization. KISTI has already carried out BPR work for digital transformation and borrowed the concept of a maturity model. However, in BPR, there is no method to measure the result. Therefore, in this paper, we developed an index to measure digital transformation based on the maturity model. Indicator development was carried out in two ways: model development and evaluation. Cases for model construction were made through a comprehensive review of existing KISTI and various domestic and foreign cases. The models before verification were technology (37), data (45), strategy (18), organization (36), and (social)influence (14) based on the major categories. After verification using confirmatory factor analysis, the model is classified as technology (20 / 17 indicators dropped), data (36 / 9 indicators dropped), strategy (18 / maintenance), organization(30 / 6 indicators dropped), and (social) influence (13 indicators / 1 indicator dropped).
The size of the domestic art market has increased 21.9% over the past five years as of 2018 to KRW 448.2 billion and the number of transactions has also increased 31.6% to 39,367 points maintaining growth for the fifth consecutive year. Art distribution platforms are diversifying from galleries and auction-style offline to online auctions. The art market consists of three areas: production (creation), distribution (trade), and consumption (buying) of works and as the perception of artistic value as well as economic value spreads interest is also increasing as a means of investment. Consumers who purchase works and think of them as a means of investment technology have an increased need for objective information about their works, but there is a limit to collecting and analyzing objective and reliable statistics because information provision in the art market distribution area is closed and unbalanced. This paper identifies objective and reliable art distribution status and status through big data collection and structured and unstructured data analysis on art market distribution areas. Through this, we want to implement a system that can objectively provide analysis of authors in the current market. This study collected author information from art distribution sites and calculated the frequency of associated words by writer by collecting and analyzing the author's articles from Maeil Business, a daily newspaper. It aims to provide consumers with objective and reliable information.
The net function of the domestic medical insurance system is highly regarded, but due to the problem of incomplete coverage, the public wants to secure coverage through private medical insurance subscription. As a result, the subscription rate of private medical insurance has recently increased, and the billing rate has also increased. As the number of people seeking private medical insurance increased, workers at private medical insurance companies are experiencing increased job stress and side effects, especially for insurance reviewers who are in charge of paying insurance, such as communicating with customers who claimed insurance and contributing to the company's profit. In response, this study analyzed the effects of job stress on mental health of insurance reviewers and conducted a descriptive survey study to reduce job stress of insurance reviewers and promote mental health. The analysis shows that job stress for insurance reviewers has a significant impact on mental health (+). In detail, job stress has a significant impact on all four factors: social performance and self-confidence, depression, sleeping disturbance and anxiety, and general well-being and vitality. This study showed that job stress in insurance reviewers has a significant (+) impact on mental health. Job stress can cause side effects in organizational aspects, such as reducing enthusiasm for job performance and increasing turnover and resignation rates, but it can also worsen individual physical health and cause diseases such as depression and anxiety, causing mental health to be impoverished. Therefore, in order to prevent this, appropriate work stress prevention methods and countermeasures should be provided to help reduce work stress and improve mental health.
This study investigated the means-end chain theory more concretely through the APT hard laddering technique. This is carrying out a questionnaire survey targeting users by hair salon type, and the items drawn from the qualitative laddering technique are applied. The technique is a comparative analysis of each attribute, consequences, and value item by analyzing each step's questions. The results are as follows. First, hairdresser's ability, acceptance of individual-customized opinions, and cheap price were the most mentioned items in the selection attributes. As for the consequences items, image transformation, neatness, novelty, and psychological stability were drawn in order. The items indicated as important among the value items were satisfaction, followed by happiness, confidence, beauty, and bond. Second, the remarkable selection attributes, irrelevant of hair salon type, was revealed as hairdresser's ability and the key values pursued when using a hair salon were drawn as satisfaction, confidence, and beauty. From this result, it was found that meeting the desire of consumers using hair salons can be linked with ultimately pursued values. It was also verified that partial differences were shown by hair salon type and this meant that consumers' desire and expected benefits were different by hair salon type. Although this study drew value perception through comparison with hair salon types based on the means-end chain theory, it was confirmed that the most important selection attribute was hairdresser's ability and they select and use hair salons to gain satisfaction and confidence.
This study is a descriptive survey study using a self-reported survey method to find out the job value and intention of career choice of college students in the medical management field. This study was conducted on university students in medical management at three four-year universities located in Busan Metropolitan City. A total of 139 effective questionnaires were used as statistical analysis data. As a result of the analysis, social dedication and stability were significantly displayed in the selection of jobs for hospital administration and administrative positions, and social dedication and stability were significantly displayed in the selection of jobs as medical recorders. In choosing a career as an international medical tourism coordinator, the focus on human relations, maintaining face, and pursuing stability have been significant. Only social commitment was significantly shown in the choice of occupation as a health educator. A comparison of job values according to general characteristics showed that there was a difference in the pursuit of knowledge and social commitment. In the case of grades, there was a difference in social dedication and stability. There was no significant difference in the case of religious or non-religious matters. In the case of economic level, only economic priorities differed. Through this study, we would like to present basic data so that college students in medical management who prepare to take the first step into a professional medical management society can recognize the need for recognition of job value and move in a better direction in choosing a job.
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