• Journal of Preventive Medicine and Public Health
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• v.54 no.5
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• pp.330-339
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• 2021

Objectives: Tobacco control in Indonesia is very lenient compared to international standards. This study explored the perspectives of tobacco control stakeholders (TCSs) on the likelihood of advancing tobacco marketing regulation in Indonesia. Methods: Data were collected from TCSs who were members of the Indonesia Tobacco Control Network group in a modified Delphi study. We collected the data in 2 waves using a questionnaire that comprised a set of closed and open-ended questions. For this paper, we analysed 2 of the 3 sections of the questionnaire: (1) tobacco advertising, promotions, and sponsorship (TAPS) bans, and (2) marketing and retailing regulations. We conducted a descriptive analysis of the scores using Stata/IC.13 and summarised the comments for each item. Results: The TCSs viewed the measures/strategies across all aspects of TAPS and tobacco marketing regulation as highly desirable, but provided varied responses on their feasibility. They rated political feasibility lower than technical feasibility for most measures. Advancing TAPS measures and prohibition of selling to minors were considered more attainable by sub-national governments, while prohibition of tobacco corporate social responsibility was considered as the least feasible measure in the next 5 years. Conclusions: Despite little optimism for substantial national-level change, there is a positive expectation that sub-national governments will strengthen their tobacco control regulation. It is paramount that the government reduce tobacco industry leverage by implementing Article 5.3 of the World Health Organization Framework Convention on Tobacco Control. Extending advocacy networks beyond tobacco control groups and framing tobacco control more effectively are necessary steps.

• The Journal of the Convergence on Culture Technology
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• v.8 no.5
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• pp.229-234
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• 2022

This study conducted a preliminary survey to study humanities healing methods for college students. Based on the student survey, we would like to present the research direction of humanities healing and find an appropriate humanities healing method. For quantitative analysis, 10 questions were constructed, focusing on BPS-Modell, Bio, Psycho, and Sozio of life. In the question of the Bio, 50% of the students said they understood their body, mind, and will and acted accordingly, but 20% of the students showed that their actions according to their body, mind, and will did not fit. In the question of Psycho, more than 50% of students said they communicated well with their inner selves, but less than 20% of students did not. In the question of Sozio of life, more than 60% of students form a social network well, but about 10% of students have very low attitudes or meanings toward life. The ultimate purpose of humanities is 'happiness', and the purpose of human life is also 'happiness'. We hope that the power of positivity to realize a stable future society and improve the quality of life will be expanded through humanities healing.

• Journal of Global Scholars of Marketing Science
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• v.18 no.3
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• pp.59-88
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• 2008

Digital Convergence means integration between industry, technology, and contents, and in marketing, it usually comes with creation of new types of product and service under the base of digital technology as digitalization progress in electro-communication industries including telecommunication, home appliance, and computer industries. One can see digital convergence not only in instruments such as PC, AV appliances, cellular phone, but also in contents, network, service that are required in production, modification, distribution, re-production of information. Convergence in contents started around 1990. Convergence in network and service begins as broadcasting and telecommunication integrates and DMB(digital multimedia broadcasting), born in May, 2005 is the symbolic icon in this trend. There are some positive and negative expectations about DMB. The reason why two opposite expectations exist is that DMB does not come out from customer's need but from technology development. Therefore, customers might have hard time to interpret the real meaning of DMB. Time is quite critical to a high tech product, like DMB because another product with same function from different technology can replace the existing product within short period of time. If DMB does not positioning well to customer's mind quickly, another products like Wibro, IPTV, or HSPDA could replace it before it even spreads out. Therefore, positioning strategy is critical for success of DMB product. To make correct positioning strategy, one needs to understand how consumer interprets DMB and how consumer's interpretation can be changed via communication strategy. In this study, we try to investigate how consumer perceives a new product, like DMB and how AD strategy change consumer's perception. More specifically, the paper segment consumers into sub-groups based on their DMB perceptions and compare their characteristics in order to understand how they perceive DMB. And, expose them different printed ADs that have messages guiding consumer think DMB in specific ways, either cellular phone or personal TV. Research Question 1: Segment consumers according to perceptions about DMB and compare characteristics of segmentations. Research Question 2: Compare perceptions about DMB after AD that induces categorization of DMB in direction for each segment. If one understand and predict a direction in which consumer perceive a new product, firm can select target customers easily. We segment consumers according to their perception and analyze characteristics in order to find some variables that can influence perceptions, like prior experience, usage, or habit. And then, marketing people can use this variables to identify target customers and predict their perceptions. If one knows how customer's perception is changed via AD message, communication strategy could be constructed properly. Specially, information from segmented customers helps to develop efficient AD strategy for segment who has prior perception. Research framework consists of two measurements and one treatment, O1 X O2. First observation is for collecting information about consumer's perception and their characteristics. Based on first observation, the paper segment consumers into two groups, one group perceives DMB similar to Cellular phone and the other group perceives DMB similar to TV. And compare characteristics of two segments in order to find reason why they perceive DMB differently. Next, we expose two kinds of AD to subjects. One AD describes DMB as Cellular phone and the other Ad describes DMB as personal TV. When two ADs are exposed to subjects, consumers don't know their prior perception of DMB, in other words, which subject belongs 'similar-to-Cellular phone' segment or 'similar-to-TV' segment? However, we analyze the AD's effect differently for each segment. In research design, final observation is for investigating AD effect. Perception before AD is compared with perception after AD. Comparisons are made for each segment and for each AD. For the segment who perceives DMB similar to TV, AD that describes DMB as cellular phone could change the prior perception. And AD that describes DMB as personal TV, could enforce the prior perception. For data collection, subjects are selected from undergraduate students because they have basic knowledge about most digital equipments and have open attitude about a new product and media. Total number of subjects is 240. In order to measure perception about DMB, we use indirect measurement, comparison with other similar digital products. To select similar digital products, we pre-survey students and then finally select PDA, Car-TV, Cellular Phone, MP3 player, TV, and PSP. Quasi experiment is done at several classes under instructor's allowance. After brief introduction, prior knowledge, awareness, and usage about DMB as well as other digital instruments is asked and their similarities and perceived characteristics are measured. And then, two kinds of manipulated color-printed AD are distributed and similarities and perceived characteristics for DMB are re-measured. Finally purchase intension, AD attitude, manipulation check, and demographic variables are asked. Subjects are given small gift for participation. Stimuli are color-printed advertising. Their actual size is A4 and made after several pre-test from AD professionals and students. As results, consumers are segmented into two subgroups based on their perceptions of DMB. Similarity measure between DMB and cellular phone and similarity measure between DMB and TV are used to classify consumers. If subject whose first measure is less than the second measure, she is classified into segment A and segment A is characterized as they perceive DMB like TV. Otherwise, they are classified as segment B, who perceives DMB like cellular phone. Discriminant analysis on these groups with their characteristics of usage and attitude shows that Segment A knows much about DMB and uses a lot of digital instrument. Segment B, who thinks DMB as cellular phone doesn't know well about DMB and not familiar with other digital instruments. So, consumers with higher knowledge perceive DMB similar to TV because launching DMB advertising lead consumer think DMB as TV. Consumers with less interest on digital products don't know well about DMB AD and then think DMB as cellular phone. In order to investigate perceptions of DMB as well as other digital instruments, we apply Proxscal analysis, Multidimensional Scaling technique at SPSS statistical package. At first step, subjects are presented 21 pairs of 7 digital instruments and evaluate similarity judgments on 7 point scale. And for each segment, their similarity judgments are averaged and similarity matrix is made. Secondly, Proxscal analysis of segment A and B are done. At third stage, get similarity judgment between DMB and other digital instruments after AD exposure. Lastly, similarity judgments of group A-1, A-2, B-1, and B-2 are named as 'after DMB' and put them into matrix made at the first stage. Then apply Proxscal analysis on these matrixes and check the positional difference of DMB and after DMB. The results show that map of segment A, who perceives DMB similar as TV, shows that DMB position closer to TV than to Cellular phone as expected. Map of segment B, who perceive DMB similar as cellular phone shows that DMB position closer to Cellular phone than to TV as expected. Stress value and R-square is acceptable. And, change results after stimuli, manipulated Advertising show that AD makes DMB perception bent toward Cellular phone when Cellular phone-like AD is exposed, and that DMB positioning move towards Car-TV which is more personalized one when TV-like AD is exposed. It is true for both segment, A and B, consistently. Furthermore, the paper apply correspondence analysis to the same data and find almost the same results. The paper answers two main research questions. The first one is that perception about a new product is made mainly from prior experience. And the second one is that AD is effective in changing and enforcing perception. In addition to above, we extend perception change to purchase intention. Purchase intention is high when AD enforces original perception. AD that shows DMB like TV makes worst intention. This paper has limitations and issues to be pursed in near future. Methodologically, current methodology can't provide statistical test on the perceptual change, since classical MDS models, like Proxscal and correspondence analysis are not probability models. So, a new probability MDS model for testing hypothesis about configuration needs to be developed. Next, advertising message needs to be developed more rigorously from theoretical and managerial perspective. Also experimental procedure could be improved for more realistic data collection. For example, web-based experiment and real product stimuli and multimedia presentation could be employed. Or, one can display products together in simulated shop. In addition, demand and social desirability threats of internal validity could influence on the results. In order to handle the threats, results of the model-intended advertising and other "pseudo" advertising could be compared. Furthermore, one can try various level of innovativeness in order to check whether it make any different results (cf. Moon 2006). In addition, if one can create hypothetical product that is really innovative and new for research, it helps to make a vacant impression status and then to study how to form impression in more rigorous way.

• Information Systems Review
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• v.15 no.3
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• pp.89-110
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• 2013

Affiliate marketing is classified as a type of online advertising, where merchants share a percentage of sales revenue generated by each customer, who visited the company's website via a content provider. Content provider, referred to as an affiliate, usually places an online advertisement at its website. For the past few years, there have been a lot of companies or individuals who participate in affiliate marketing. Generally speaking, most of them have websites and post the merchant's ads on their own websites. However, building and maintaining websites have some technology requirements. The widespread use of Social Network Service (SNS), especially microblog-based SNS such as Twitter and Sina Weibo, provides opportunities for individuals who want to be content providers of affiliate marketing. Since information spreads quickly on microblog-based SNS and the easy in targeting customers, it is both an effective and an efficient tool to do affiliate marketing. The relationship between a content provider and the potential customer, which is referred as "tie strength", is quite an important issue in such situation. This paper proved that service characteristics of the microblog-based SNS (security, community drivenness and navigability) and content quality all had positive influence on click-through intention, while tie strength played a moderating role. For the group with strong tie, tie strength is crucial in influencing click-through intention. While for the weak tie group, content quality was very important. Finally, we proposed some implications for both academics and practitioners.

• Management & Information Systems Review
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• v.35 no.1
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• pp.69-84
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• 2016

This study set the research model to examine the correlation between Word-of-Mouth constraint factors, efforts to negotiate pertaining to these, Flow and Word-of-Mouth intent based on the theory of leisure constrain when it comes to the correlation between consumers' Word-of-Mouth constraint factors and Word-of-Mouth. Correlation among the variables were verified in an empirical manner. Results of this study are summarized as follows. After verifying the hypotheses, all the hypotheses were adopted excluding the hypotheses of two results (Hypothesis 1, hypotheses 5). Detailed results regarding this are as follows. First, the following is the effect of the Intrapersonal Constraint and Word-of-Mouth constraint factors on the Word-of-Mouth constraint negotiation effort. Interpersonal Constraint and Structural Constraint exert positive (-) effect on the Word-of-Mouth constraint negotiation effort. In case of Intrapersonal Constraint, negative (-) effect was demonstrated. Thus, this was statistically significant although dismissed from hypothesis verification. Second, the following is the result of examining the structural correlation between Word-of-Mouth constraint negotiation effort, Flow and Word-of-Mouth. Word-of-Mouth constraint negotiation effort exerts positive (-) effect on the Flow, but it was not statistically effective in case of the Word-of-Mouth. Lastly, it is possible to see that the Flow plays the role of a medium since it exerted positive (-) effect on the Word-of-Mouth. Results of this study are expected to provide key theoretical and working level implications as well as general understanding of the Word-of-Mouth constraint factors, consumers' Flow and Word-of-Mouth.

• Journal of the Korean Society of Safety
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• v.35 no.5
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• pp.74-85
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• 2020

Smart phone zombie or Smombie means pedestrians who walk without attention to their surroundings because they are focused upon their smart phone. Because the traffic accidents and injuries caused by Smombie have been increased rapidly in recent years, the social attention and policies are needed to prevent it. This study was conducted to analyze Smombie's current status and some solutions used before and to propose new improved method through the latest ICT trend. In this study, we did the field survey to check Smombies at several places in Seoul through people counting, and found that a lot of pedestrians still use the smart phone while walking. And we analyzed many case studies about some solutions to prevent Smombies previously. The case studies include legal regulations, government policies, smart phone app services and facilities that are used before. We studied them through internet searches and reference studies and we also checked the current operating situation as visiting several places that the solutions actually has been operated. Therefore, we found there are some limitations in previous solutions in terms of effectiveness and management. To consider new solution that can be expected to overcome the limitations, we analyzed the latest ICT trends focused on features to utilize the Smombie prevention, especially video recognition and digital signage. In these days, video recognition has been developed rapidly with assistance of AI technology and it can recognize the specific pedestrian's characteristics such as holding smart phone as well as hair style, clothes, backpack and etc. On the other hands, the digital signage is the convergence device that includes big display, network connection and various IoT sensors. It can be used as public media in many places for public services as well as advertising. Through these analysis results, we show the requirements and the user scenario for the improved method to prevent Smombie. Finally, we propose to develop R&D technology to recognize Smombie exactly as pedestrian attributes and to spread creative contents to increase pedestrian's interest and engagement for Smombie prevention through digital signage.

• Journal of Intelligence and Information Systems
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• v.22 no.2
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• pp.81-96
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• 2016

As the internet has become widespread and easy to access everywhere, it is common for people to search information via online search engines such as Google and Naver in everyday life. Recent studies have used online search volume of specific keyword as a measure of the internet users' attention in order to predict disease outbreaks such as flu and cancer, an unemployment rate, and an index of a nation's economic condition, and etc. For stock traders, web search is also one of major information resources to obtain data about individual stock items. Therefore, search volume of a stock item can reflect the amount of investors' attention on it. The investor attention has been regarded as a crucial factor influencing on stock price but it has been measured by indirect proxies such as market capitalization, trading volume, advertising expense, and etc. It has been theoretically and empirically proved that an increase of investors' attention on a stock item brings temporary increase of the stock price and the price recovers in the long run. Recent development of internet environment enables to measure the investor attention directly by the internet search volume of individual stock item, which has been used to show the attention-induced price pressure. Previous studies focus mainly on Dow Jones and NASDAQ market in the United States. In this paper, we investigate the relationship between the individual investors' attention measured by the internet search volumes and stock price changes of individual stock items in the KOSDAQ market in Korea, where the proportion of the trades by individual investors are about 90% of the total. In addition, we examine the difference between industries in the influence of investors' attention on stock return. The internet search volume of stocks were gathered from "Naver Trend" service weekly between January 2007 and June 2015. The regression model with the error term with AR(1) covariance structure is used to analyze the data since the weekly prices in a stock item are systematically correlated. The market capitalization, trading volume, the increment of trading volume, and the month in which each trade occurs are included in the model as control variables. The fitted model shows that an abnormal increase of search volume of a stock item has a positive influence on the stock return and the amount of the influence varies among the industry. The stock items in IT software, construction, and distribution industries have shown to be more influenced by the abnormally large internet search volume than the average across the industries. On the other hand, the stock items in IT hardware, manufacturing, entertainment, finance, and communication industries are less influenced by the abnormal search volume than the average. In order to verify price pressure caused by investors' attention in KOSDAQ, the stock return of the current week is modelled using the abnormal search volume observed one to four weeks ahead. On average, the abnormally large increment of the search volume increased the stock return of the current week and one week later, and it decreased the stock return in two and three weeks later. There is no significant relationship with the stock return after 4 weeks. This relationship differs among the industries. An abnormal search volume brings particularly severe price reversal on the stocks in the IT software industry, which are often to be targets of irrational investments by individual investors. An abnormal search volume caused less severe price reversal on the stocks in the manufacturing and IT hardware industries than on average across the industries. The price reversal was not observed in the communication, finance, entertainment, and transportation industries, which are known to be influenced largely by macro-economic factors such as oil price and currency exchange rate. The result of this study can be utilized to construct an intelligent trading system based on the big data gathered from web search engines, social network services, and internet communities. Particularly, the difference of price reversal effect between industries may provide useful information to make a portfolio and build an investment strategy.