• Korean Journal of Dental Materials
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• v.44 no.2
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• pp.187-195
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• 2017

TheraCal LC, a new light-cured, resin-modified calcium silicate-filled base/liner material, has been introduced as a pulpotomy agent. The aim of this study was to evaluate the capacity of hard tissue formation and pulpal response after pulpotomy with TheraCal LC. Twenty-two 9-week-old male rats were anesthetized, cavities were prepared in maxillary first molars and pulps were capped with formocresol (FC), mineral trioxide aggregate (MTA), and TheraCal LC. Specimens obtained from rats were scanned using a high-resolution micro CT system. The specimens were prepared and evaluated histologically, and immunofluorescence assay was performed to assess the dentin matrix protein-1 (DMP-1) expression. On micro CT analysis, the MTA and TheraCal LC groups showed thicker hard tissue formation than the FC group. On hematoxylin and eosin (H&E) staining, MTA and TheraCal LC groups showed dentine bridge formation with vital pulp beneath the materials. On immunofluorescence analysis, DMP-1 was highly expressed in the TheraCal LC group compared to the FC group. TheraCal LC showed similar capacity to form hard tissue as MTA when it was used as a pulpotomy agent. Because of its good manipulation and faster setting time compared to MTA, TheraCal LC could be considered as a good alternative to MTA.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.139-161
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• 2019

The utilization of the e-commerce market has become a common life style in today. It has become important part to know where and how to make reasonable purchases of good quality products for customers. This change in purchase psychology tends to make it difficult for customers to make purchasing decisions in vast amounts of information. In this case, the recommendation system has the effect of reducing the cost of information retrieval and improving the satisfaction by analyzing the purchasing behavior of the customer. Amazon and Netflix are considered to be the well-known examples of sales marketing using the recommendation system. In the case of Amazon, 60% of the recommendation is made by purchasing goods, and 35% of the sales increase was achieved. Netflix, on the other hand, found that 75% of movie recommendations were made using services. This personalization technique is considered to be one of the key strategies for one-to-one marketing that can be useful in online markets where salespeople do not exist. Recommendation techniques that are mainly used in recommendation systems today include collaborative filtering and content-based filtering. Furthermore, hybrid techniques and association rules that use these techniques in combination are also being used in various fields. Of these, collaborative filtering recommendation techniques are the most popular today. Collaborative filtering is a method of recommending products preferred by neighbors who have similar preferences or purchasing behavior, based on the assumption that users who have exhibited similar tendencies in purchasing or evaluating products in the past will have a similar tendency to other products. However, most of the existed systems are recommended only within the same category of products such as books and movies. This is because the recommendation system estimates the purchase satisfaction about new item which have never been bought yet using customer's purchase rating points of a similar commodity based on the transaction data. In addition, there is a problem about the reliability of purchase ratings used in the recommendation system. Reliability of customer purchase ratings is causing serious problems. In particular, 'Compensatory Review' refers to the intentional manipulation of a customer purchase rating by a company intervention. In fact, Amazon has been hard-pressed for these "compassionate reviews" since 2016 and has worked hard to reduce false information and increase credibility. The survey showed that the average rating for products with 'Compensated Review' was higher than those without 'Compensation Review'. And it turns out that 'Compensatory Review' is about 12 times less likely to give the lowest rating, and about 4 times less likely to leave a critical opinion. As such, customer purchase ratings are full of various noises. This problem is directly related to the performance of recommendation systems aimed at maximizing profits by attracting highly satisfied customers in most e-commerce transactions. In this study, we propose the possibility of using new indicators that can objectively substitute existing customer 's purchase ratings by using RFM multi-dimensional analysis technique to solve a series of problems. RFM multi-dimensional analysis technique is the most widely used analytical method in customer relationship management marketing(CRM), and is a data analysis method for selecting customers who are likely to purchase goods. As a result of verifying the actual purchase history data using the relevant index, the accuracy was as high as about 55%. This is a result of recommending a total of 4,386 different types of products that have never been bought before, thus the verification result means relatively high accuracy and utilization value. And this study suggests the possibility of general recommendation system that can be applied to various offline product data. If additional data is acquired in the future, the accuracy of the proposed recommendation system can be improved.

• Economic and Environmental Geology
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• v.54 no.2
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• pp.233-245
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• 2021

Many studies on the microstructures in rocks have been conducted using experimental methods with various equipment as well as natural rock studies to see the development of microstructures and understand their mechanisms. Grain boundary migration of mineral aggregates in rocks could cause grain growth or grain size changes during metamorphism or deformation as one of the main recrystallization mechanisms. This study suggests improved ways regarding the analog material experiments with reformed equipment to see sequential observations of these grain boundary migration. It can be more efficient than the existing techniques and carry out an appropriate microstructure analysis. This reformed equipment was implemented to enable optical manipulation by mounting polarizing plates capable of rotating operation on a stereoscopic microscope and a deformation rig capable of experimenting with analog materials. The equipment can automatically control the temperature and strain rate of the deformation rig by microcontrollers and programming and can take digital photomicrographs with constant time intervals during the experiment to observe any microstructure changes. The composite images synthesized using images by rotated polarizing plates enable us to see more accurate grain boundaries. As a rock analog material, norcamphor(C7H10O) was used, which has similar birefringence to quartz. Static grain growth and simple shear deformation experiments were performed using the norcamphor to verify the effectiveness of the equipment. The static grain growth experiments showed the characteristics of typical grain growth behavior. The number of grains decreases and the average grain size increases over time. These case experiments also showed a clear difference between the growth curves with three temperature conditions. The result of the simple shear deformation experiment under the medium temperature-low strain rate showed no significant change in the average grain size but presented the increased elongation of grain shapes in the direction of about 53° regarding the direction perpendicular to the shearing direction as the shear strain increases over time. These microstructures are interpreted as both the plastic deformation and the internal recovery process in grains are balanced by the deformation under the given experimental conditions. These experiments using the reformed equipment represent the ability to sequentially observe changing the microstructure during experiments as desired in the tests with the analog material during the entire process.

• Journal of the Korean Chemical Society
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• v.64 no.6
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• pp.416-428
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• 2020

This study analyzed the uses of external representations presented in the matter units of the 7th-grade science digital textbooks developed under the 2015 revised national curriculum. The level, form, presentation, and interactivity of external representations presented in 5 types of digital textbooks were analyzed. As for the level, the macroscopic level of representations was mainly presented. The macroscopic level and microscopic level of representations were presented together in the particle description. As for the form, visual-verbal and visual-nonverbal representations were usually presented across the board. Very few audial-verbal and audial-nonverbal representations were presented. Visual-verbal and audial-verbal representations were mostly presented in formal form, and visual-nonverbal representations were mostly presented in illustration without movement. The presentation of representations was analyzed in three aspects. First, visual-verbal and visual-nonverbal representations were mainly presented together and none of audial-verbal and visual-nonverbal representations were presented together. When the representations of the audial-verbal, visual-nonverbal, and visual-verbal were presented together, some of the information presented in audial-verbal representations was repeatedly presented in the visual-verbal representations. Second, audial-nonverbal representations not related to learning content were presented along with other representations. Third, there were few cases of arranging visual-verbal and visual-nonverbal representations on the next pages. Audialverbal and visual-nonverbal representations were always presented synchronized. As for the interactivity, the manipulation level was mainly presented in the main area, and the feedback level was mainly presented in the activity area. The adaptation level and the communication level of interactivity were presented very few. Based on the results, the implications for the direction of constructing digital textbooks were discussed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.2
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• pp.177-188
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• 2021

On December 2015, Financial Supervisory Service(FSS) announced the four key thematic audit review areas, one of them is an appropriation of unbilled revenue. Accounting of unbilled revenue is intertwined with a percentage of completion, that is concerned about discretionary decision by manager. Therefore, if manager motivated by income-increasing manipulation is exaggerating percentage of completion, unbilled revenue is excessively recognized. This problem is caused the serious accounting issues(e.g., shock at a loss for 2013 fiscal year by some construction firms, malpractice of accounting in order-made production industry). Distrust of accounting was grown because the shipbuilding and construction industries successively went poor management and bad accounting of them is revealed. Those accounting issues were the trigger for problem recognition of unbilled revenue, they were background for the designation of appropriation unbilled revenue as thematic audit review areas by FSS. Therefore, this study verified effectiveness of thematic audit review by empirically analyzing whether designation of thematic audit review makes the firm increases conservative behavior. Conservative accounting is estimated by using Basu(1997) model. We analyzed the effect of the thematic audit review on conservative accounting of unbilled revenue by comparing with reflecting unbilled revenue or not. The sample for test consists of firm-years the manufacturing and construction industries from 2012 to 2017. The test results of this study suggested that the conservative accounting of unbilled revenue after designation of the thematic audit review was significantly increased. We also tested again by classifying whether or not it is construction industry. We found that construction industry is more conservative than the other industry only for the designated year of the thematic audit review, otherwise there was not any evidence for significantly increasing conservatism. This study contributes to the literature by empirically analysing relationship of the unbilled revenue to the thematic audit review from the perspective of the conservatism and verifying effectiveness of the thematic audit review.

• Journal of Korea Entertainment Industry Association
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• v.15 no.8
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• pp.145-159
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• 2021

is a contemporary experimental film that forms ambiguity in the narrative and the psychological motivation of the characters, destroys linear temporality, and reminds of manipulation possibilities in digital images through varied techniques, and it carries implication by the fact that the transformation process of human subjects and self-awareness are connected to social trauma and makes way to infer by comparing it to the historical contexts of other nations or societies. centers on the space outside the screen, absent space, and the intrinsic meaning within the space and the frame and shares the information in the visible space and the space outside the screen and arouses an active perceptual process so that the audience can deduce the information that is not presented. The film visualized the historical meaning without describing the background of the times in detail and aimed to express the conflicts and worries between the god, a transcendental existence, with humans, which are marginal beings, within the conflicting structure among humans. Moreover, attempted to resolve the sadness of loss and absence through the spatial aesthetics and the film presented the progression of the situation through the contrast of the characters and also the comparison between light and darkness. This study intends to make an attempt of interpreting the realm involving personal (characters) stories and the social and historical backgrounds together with the religious sphere and discuss the visualization of the semantic context. In addition, this study analyzed the sequence of the scenes in , which reconstructs identity and historical cases and religious values to observe the meaning and characteristics and closely analyze the general meaning pursued by the film. discussed the issues of trauma that individuals, regions, and nations confront as a representation and interpretation of the trauma connoted in the film, and consideration can be provided about the implication concerning the situation and context in South Korea. Furthermore, the film placidly discusses the growth and agony in humans and the society without expressing it excessively, so it will be a valuable research result to inspire the trend of creating films that incorporate new imaging technology and original visualization techniques.

• Korean Journal of Animal Reproduction
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• v.23 no.2
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• pp.127-132
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• 1999

This study was carried out to investigate the general characteristics such as volume, sperm concentration, sperm motility, sperm abnormality on whole semen, removed seminal plasma(RSP) semen and fractional semen of small dogs, and the effect of temperature and preservatio time and cryopreservation on motility of whole and removed seminal plasma semen. Multiple ejaculates were collected from small dogs by the digital manipulation of penis. 1. Average sperm concentration, sperm motility and abnormal sperm rates of whole semen and RSP semen were 5.07$\pm$2.32$\times$10$^{6}$ cells/$m\ell$, 95.42$\pm$2.65%, 4.42$\pm$0.157% and 4.69$\pm$3.27~4.25$\pm$3.65$\times$10$^{6}$ cells/$m\ell$, 91.17$\pm$3.85~88.52$\pm$3.85%, 6.57$\pm$0.43~5.54$\pm$0.52%, respectively. 2. Average semen volume per ejaculate, sperm concentration, sperm motility and abnormal sperm rate of 1st fractional semen were 0.92$\pm$0.7$m\ell$, 4.57$\pm$0.78$\times$10$^{6}$ cells/$m\ell$, 10.72$\pm$3.21% and 5.50$\pm$0.70%. Average semen volume per ejaculate, sperm concentration, sperm motility and abnormal sperm rate of 2nd fractional semen were 2. 14$\pm$0.19$m\ell$, 2.01$\pm$0.12$\times$10$^{6}$ cells/$m\ell$, 95.44$\pm$4.21% and 4.31$\pm$0.53%. Average semen volume per ejaculate, sperm concentration, sperm motility and abnormal sperm rate of 3rd fractional semen were 2.66$\pm$0.23$m\ell$, 2.35$\pm$0.21$\times$10$^{6}$ cells/$m\ell$, 90.71$\pm$2.63%, 6.33$\pm$0.91%, respectively. 3. Motility of whole semen and RSP semen were higher at 2$0^{\circ}C$ than at 4$^{\circ}C$ or 37$^{\circ}C$. When preservation temperature was 2$0^{\circ}C$, sperm motility were 98.32% at 1 hr, 92.15% at 5 hrs, 90.23% at 10 hrs 82.08% at 15 hrs 70.07% at 20 hrs 60.02% at 20 hrs 37.19% at 40 hrs respectively. 4. Average sperm motility of frozen 2nd fraction semen and RSP semen were 33.3$\pm$8.7, 54.7$\pm$9.5%, respectively. Sperm motility was significantly higher in frozen 2nd fraction semen and RSP semen compared with control group.

• Asia pacific journal of information systems
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• v.17 no.4
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• pp.31-59
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• 2007

We frequently use search engines to find relevant information in the Web but still end up with too much information. In order to solve this problem of information overload, ranking algorithms have been applied to various domains. As more information will be available in the future, effectively and efficiently ranking search results will become more critical. In this paper, we propose a ranking algorithm for the Semantic Web resources, specifically RDF resources. Traditionally, the importance of a particular Web page is estimated based on the number of key words found in the page, which is subject to manipulation. In contrast, link analysis methods such as Google's PageRank capitalize on the information which is inherent in the link structure of the Web graph. PageRank considers a certain page highly important if it is referred to by many other pages. The degree of the importance also increases if the importance of the referring pages is high. Kleinberg's algorithm is another link-structure based ranking algorithm for Web pages. Unlike PageRank, Kleinberg's algorithm utilizes two kinds of scores: the authority score and the hub score. If a page has a high authority score, it is an authority on a given topic and many pages refer to it. A page with a high hub score links to many authoritative pages. As mentioned above, the link-structure based ranking method has been playing an essential role in World Wide Web(WWW), and nowadays, many people recognize the effectiveness and efficiency of it. On the other hand, as Resource Description Framework(RDF) data model forms the foundation of the Semantic Web, any information in the Semantic Web can be expressed with RDF graph, making the ranking algorithm for RDF knowledge bases greatly important. The RDF graph consists of nodes and directional links similar to the Web graph. As a result, the link-structure based ranking method seems to be highly applicable to ranking the Semantic Web resources. However, the information space of the Semantic Web is more complex than that of WWW. For instance, WWW can be considered as one huge class, i.e., a collection of Web pages, which has only a recursive property, i.e., a 'refers to' property corresponding to the hyperlinks. However, the Semantic Web encompasses various kinds of classes and properties, and consequently, ranking methods used in WWW should be modified to reflect the complexity of the information space in the Semantic Web. Previous research addressed the ranking problem of query results retrieved from RDF knowledge bases. Mukherjea and Bamba modified Kleinberg's algorithm in order to apply their algorithm to rank the Semantic Web resources. They defined the objectivity score and the subjectivity score of a resource, which correspond to the authority score and the hub score of Kleinberg's, respectively. They concentrated on the diversity of properties and introduced property weights to control the influence of a resource on another resource depending on the characteristic of the property linking the two resources. A node with a high objectivity score becomes the object of many RDF triples, and a node with a high subjectivity score becomes the subject of many RDF triples. They developed several kinds of Semantic Web systems in order to validate their technique and showed some experimental results verifying the applicability of their method to the Semantic Web. Despite their efforts, however, there remained some limitations which they reported in their paper. First, their algorithm is useful only when a Semantic Web system represents most of the knowledge pertaining to a certain domain. In other words, the ratio of links to nodes should be high, or overall resources should be described in detail, to a certain degree for their algorithm to properly work. Second, a Tightly-Knit Community(TKC) effect, the phenomenon that pages which are less important but yet densely connected have higher scores than the ones that are more important but sparsely connected, remains as problematic. Third, a resource may have a high score, not because it is actually important, but simply because it is very common and as a consequence it has many links pointing to it. In this paper, we examine such ranking problems from a novel perspective and propose a new algorithm which can solve the problems under the previous studies. Our proposed method is based on a class-oriented approach. In contrast to the predicate-oriented approach entertained by the previous research, a user, under our approach, determines the weights of a property by comparing its relative significance to the other properties when evaluating the importance of resources in a specific class. This approach stems from the idea that most queries are supposed to find resources belonging to the same class in the Semantic Web, which consists of many heterogeneous classes in RDF Schema. This approach closely reflects the way that people, in the real world, evaluate something, and will turn out to be superior to the predicate-oriented approach for the Semantic Web. Our proposed algorithm can resolve the TKC(Tightly Knit Community) effect, and further can shed lights on other limitations posed by the previous research. In addition, we propose two ways to incorporate data-type properties which have not been employed even in the case when they have some significance on the resource importance. We designed an experiment to show the effectiveness of our proposed algorithm and the validity of ranking results, which was not tried ever in previous research. We also conducted a comprehensive mathematical analysis, which was overlooked in previous research. The mathematical analysis enabled us to simplify the calculation procedure. Finally, we summarize our experimental results and discuss further research issues.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.89-105
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• 2014

After emergence of Internet, social media with highly interactive Web 2.0 applications has provided very user friendly means for consumers and companies to communicate with each other. Users have routinely published contents involving their opinions and interests in social media such as blogs, forums, chatting rooms, and discussion boards, and the contents are released real-time in the Internet. For that reason, many researchers and marketers regard social media contents as the source of information for business analytics to develop business insights, and many studies have reported results on mining business intelligence from Social media content. In particular, opinion mining and sentiment analysis, as a technique to extract, classify, understand, and assess the opinions implicit in text contents, are frequently applied into social media content analysis because it emphasizes determining sentiment polarity and extracting authors' opinions. A number of frameworks, methods, techniques and tools have been presented by these researchers. However, we have found some weaknesses from their methods which are often technically complicated and are not sufficiently user-friendly for helping business decisions and planning. In this study, we attempted to formulate a more comprehensive and practical approach to conduct opinion mining with visual deliverables. First, we described the entire cycle of practical opinion mining using Social media content from the initial data gathering stage to the final presentation session. Our proposed approach to opinion mining consists of four phases: collecting, qualifying, analyzing, and visualizing. In the first phase, analysts have to choose target social media. Each target media requires different ways for analysts to gain access. There are open-API, searching tools, DB2DB interface, purchasing contents, and so son. Second phase is pre-processing to generate useful materials for meaningful analysis. If we do not remove garbage data, results of social media analysis will not provide meaningful and useful business insights. To clean social media data, natural language processing techniques should be applied. The next step is the opinion mining phase where the cleansed social media content set is to be analyzed. The qualified data set includes not only user-generated contents but also content identification information such as creation date, author name, user id, content id, hit counts, review or reply, favorite, etc. Depending on the purpose of the analysis, researchers or data analysts can select a suitable mining tool. Topic extraction and buzz analysis are usually related to market trends analysis, while sentiment analysis is utilized to conduct reputation analysis. There are also various applications, such as stock prediction, product recommendation, sales forecasting, and so on. The last phase is visualization and presentation of analysis results. The major focus and purpose of this phase are to explain results of analysis and help users to comprehend its meaning. Therefore, to the extent possible, deliverables from this phase should be made simple, clear and easy to understand, rather than complex and flashy. To illustrate our approach, we conducted a case study on a leading Korean instant noodle company. We targeted the leading company, NS Food, with 66.5% of market share; the firm has kept No. 1 position in the Korean "Ramen" business for several decades. We collected a total of 11,869 pieces of contents including blogs, forum contents and news articles. After collecting social media content data, we generated instant noodle business specific language resources for data manipulation and analysis using natural language processing. In addition, we tried to classify contents in more detail categories such as marketing features, environment, reputation, etc. In those phase, we used free ware software programs such as TM, KoNLP, ggplot2 and plyr packages in R project. As the result, we presented several useful visualization outputs like domain specific lexicons, volume and sentiment graphs, topic word cloud, heat maps, valence tree map, and other visualized images to provide vivid, full-colored examples using open library software packages of the R project. Business actors can quickly detect areas by a swift glance that are weak, strong, positive, negative, quiet or loud. Heat map is able to explain movement of sentiment or volume in categories and time matrix which shows density of color on time periods. Valence tree map, one of the most comprehensive and holistic visualization models, should be very helpful for analysts and decision makers to quickly understand the "big picture" business situation with a hierarchical structure since tree-map can present buzz volume and sentiment with a visualized result in a certain period. This case study offers real-world business insights from market sensing which would demonstrate to practical-minded business users how they can use these types of results for timely decision making in response to on-going changes in the market. We believe our approach can provide practical and reliable guide to opinion mining with visualized results that are immediately useful, not just in food industry but in other industries as well.

• Journal of Global Scholars of Marketing Science
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• v.20 no.1
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• pp.89-97
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• 2010

This study researches the effects of common features on a no-choice option with respect to regulatory focus theory. The primary interest is in three factors and their interrelationship: common features, no-choice option, and regulatory focus. Prior studies have compiled vast body of research in these areas. First, the "common features effect" has been observed bymany noted marketing researchers. Tversky (1972) proposed the seminal theory, the EBA model: elimination by aspect. According to this theory, consumers are prone to focus only on unique features during comparison processing, thereby dismissing any common features as redundant information. Recently, however, more provocative ideas have attacked the EBA model by asserting that common features really do affect consumer judgment. Chernev (1997) first reported that adding common features mitigates the choice gap because of the increasing perception of similarity among alternatives. Later, however, Chernev (2001) published a critically developed study against his prior perspective with the proposition that common features may be a cognitive load to consumers, and thus consumers are possible that they are prone to prefer the heuristic processing to the systematic processing. This tends to bring one question to the forefront: Do "common features" affect consumer choice? If so, what are the concrete effects? This study tries to answer the question with respect to the "no-choice" option and regulatory focus. Second, some researchers hold that the no-choice option is another best alternative of consumers, who are likely to avoid having to choose in the context of knotty trade-off settings or mental conflicts. Hope for the future also may increase the no-choice option in the context of optimism or the expectancy of a more satisfactory alternative appearing later. Other issues reported in this domain are time pressure, consumer confidence, and alternative numbers (Dhar and Nowlis 1999; Lin and Wu 2005; Zakay and Tsal 1993). This study casts the no-choice option in yet another perspective: the interactive effects between common features and regulatory focus. Third, "regulatory focus theory" is a very popular theme in recent marketing research. It suggests that consumers have two focal goals facing each other: promotion vs. prevention. A promotion focus deals with the concepts of hope, inspiration, achievement, or gain, whereas prevention focus involves duty, responsibility, safety, or loss-aversion. Thus, while consumers with a promotion focus tend to take risks for gain, the same does not hold true for a prevention focus. Regulatory focus theory predicts consumers' emotions, creativity, attitudes, memory, performance, and judgment, as documented in a vast field of marketing and psychology articles. The perspective of the current study in exploring consumer choice and common features is a somewhat creative viewpoint in the area of regulatory focus. These reviews inspire this study of the interaction possibility between regulatory focus and common features with a no-choice option. Specifically, adding common features rather than omitting them may increase the no-choice option ratio in the choice setting only to prevention-focused consumers, but vice versa to promotion-focused consumers. The reasoning is that when prevention-focused consumers come in contact with common features, they may perceive higher similarity among the alternatives. This conflict among similar options would increase the no-choice ratio. Promotion-focused consumers, however, are possible that they perceive common features as a cue of confirmation bias. And thus their confirmation processing would make their prior preference more robust, then the no-choice ratio may shrink. This logic is verified in two experiments. The first is a $2{\times}2$ between-subject design (whether common features or not X regulatory focus) using a digital cameras as the relevant stimulus-a product very familiar to young subjects. Specifically, the regulatory focus variable is median split through a measure of eleven items. Common features included zoom, weight, memory, and battery, whereas the other two attributes (pixel and price) were unique features. Results supported our hypothesis that adding common features enhanced the no-choice ratio only to prevention-focus consumers, not to those with a promotion focus. These results confirm our hypothesis - the interactive effects between a regulatory focus and the common features. Prior research had suggested that including common features had a effect on consumer choice, but this study shows that common features affect choice by consumer segmentation. The second experiment was used to replicate the results of the first experiment. This experimental study is equal to the prior except only two - priming manipulation and another stimulus. For the promotion focus condition, subjects had to write an essay using words such as profit, inspiration, pleasure, achievement, development, hedonic, change, pursuit, etc. For prevention, however, they had to use the words persistence, safety, protection, aversion, loss, responsibility, stability etc. The room for rent had common features (sunshine, facility, ventilation) and unique features (distance time and building state). These attributes implied various levels and valence for replication of the prior experiment. Our hypothesis was supported repeatedly in the results, and the interaction effects were significant between regulatory focus and common features. Thus, these studies showed the dual effects of common features on consumer choice for a no-choice option. Adding common features may enhance or mitigate no-choice, contradictory as it may sound. Under a prevention focus, adding common features is likely to enhance the no-choice ratio because of increasing mental conflict; under the promotion focus, it is prone to shrink the ratio perhaps because of a "confirmation bias." The research has practical and theoretical implications for marketers, who may need to consider common features carefully in a practical display context according to consumer segmentation (i.e., promotion vs. prevention focus.) Theoretically, the results suggest some meaningful moderator variable between common features and no-choice in that the effect on no-choice option is partly dependent on a regulatory focus. This variable corresponds not only to a chronic perspective but also a situational perspective in our hypothesis domain. Finally, in light of some shortcomings in the research, such as overlooked attribute importance, low ratio of no-choice, or the external validity issue, we hope it influences future studies to explore the little-known world of the "no-choice option."