• Journal of Global Scholars of Marketing Science
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• v.13
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• pp.71-88
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• 2004

Although the factors that affect the width of latitude of price acceptance is well documented, the attempt to develop a practice-oriented methodology to calibrate the region of price insensitivity (i.e., a latitude of price acceptance) for a given individual brand has been relatively rare. The researcher aims to try to full this gap by developing a conjoint analysis-based procedure that can be applied to many industries. Furthermore, we examine the difference in the latitude of price acceptance between on- and off-line transaction in stock industry in Korea. The conjoint analysis-based procedure was applied to measure the disaggregate price response curve for individual stock investment both on- and off line transaction channel. The curves from the samples enable us to estimate the individual choice probabilities corresponding to applied price points. Using t-test the differences in mean choice probabilities between the list price and another price point were tested, through which we can get the latitude of price acceptance for a given brand in stock market. These procedures were tested in on- and off-line stock market in South Korea. The results showed that investors on off-line channel have wider latitudes of price acceptance than the investors on on-line transaction system.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.301-313
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• 2022

This study aims to investigate the causal relationship between variables of UTAUT2 model and the acceptance intention by Netflix and Wavve intention to adopt and acceptance intent by plan package. The results indicate that (1)First, the intention of Netflix adoption was influenced by performance expectancy, effort expectancy, hedonic motivation, price value, and habit; (2) the intention of wave adoption was influenced by performance expectancy, social influence, price value, and habit. (3)in the acceptance intention of Netflix's acceptance intent by plan package, price value and habit, performance expectancy and habit influenced on the acceptance intent of premium plan, and did not affect the standard plan; (4) in the acceptance intention of the basic plan by the Wavve plan, the price value had a negative effect on the acceptance intention of the basic plan, and the habit had a positive effect.The social impact on the acceptance intention of the standard rate plan, the price value and habit of the acceptance intention of the premium rate plan were affected.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.43
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• pp.25-52
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• 2009

An acceptance is effected by a statement or other conduct of the offeree indicating assent. Silence or inactivity does not in itself amount to acceptance. An acceptance of an offer becomes effective at the moment the indication of assent reaches the offeror. It uses in stating rules on whether an acceptance is too late to form a contract and an offeree may withdraw an acceptance after transmission. The offeree may indicate assent by performing an act such as one relating to the dispatch of the goods or payment of the price without notice to the offeror. The acceptance by action also is to be performed within the time fixed between the parties or within a resonable time. However, an oral offer must be accepted immediately by an offeree. After an acceptance by action, the offeree avoid revocation of an offer by giving the offeror prompt notice to that effect. Even if a reply an offer contains additions, limitations or other modifications is a rejection of the offer and constitutes a counter offer, the reply to an offer contains additional and different terms which do not materially alter the terms of the offer constitutes an acceptance unless the offeror objects to the discrepancy or to that effect. Additional or different terms relating to the price, payment, quality & quantity of the goods, time & place of delivery, a party's liability or the settlement of disputes are considered to materially alter the terms of the offer.

• Fashion & Textile Research Journal
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• v.22 no.2
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• pp.209-221
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• 2020

Recently, following the commercialization and market entry of smart clothes with diverse functions, smart clothes have been changing from technology-centered products to user-centered products. However, the analysis of consumer demand centered on actual commercialized products is lacking. Therefore, this study classified commercialized smart clothes by function and analyzed the demand and requirements of smart clothes according to sports/outdoor clothes consumption behaviors. As a result, consumers were classified according to their sports/outdoor clothes consumption behaviors into an outdoor leading group with high consumption propensity, an outdoor pursuit group with medium consumption propensity, and an outdoor following group with low consumption propensity. Among the commercialized smart clothes, those with a heartbeat measuring function, those with a heating function, and those with a light-emitting function were presented and demand analysis was conducted. According to the results, the outdoor leading group and the outdoor pursuit group had higher levels of awareness, preference, and purchase intentions than the outdoor following group. In addition, the outdoor leading group showed the highest level of purchase price acceptance while the outdoor following group showed the lowest level of purchase price acceptance. However, this study has a limitation that the acceptance for smart clothes were analyzed with consumers who had experience in sports outdoor clothes consumption. Therefore, in future, studies will be conducted with a wide range of consumers.

• Journal of the Korean Society of Food Culture
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• v.36 no.3
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• pp.293-299
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• 2021

The purpose of this study was to investigate the perception of the quality of school meals by parents of kindergarten children in Seoul, analyze the acceptance price and the optimal school meal cost using PSM (price sensitivity measurement) techniques, and provide basic data for improving the quality of kindergarten meals. The survey was conducted using descriptive statistics and PSM analysis of the responses of 1,272 parents of 779 kindergarten children belonging to the Seoul Metropolitan Office of Education from April to May 2021 and prior research analysis related to kindergarten meals. 74.1% of the parents surveyed were women, with 61% of children attending kindergartens attached to elementary schools, followed by private kindergartens (28.9%) and public kindergartens (10.1%). According to a study of the quality of meals, private kindergarten parents are highly satisfied with all the quality attributes of meals, such as "sanitation of dining environment" and "nutritionally balanced food" (p<0.001, p<0.01). The analysis of the acceptance price range and the optimal price for school meals showed that there was no significant variation based on the type of kindergarten establishment, with parents' acceptance price range ranging from 3,596 won to 4,454 won with an optimal price of 3,948 won.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.103-128
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• 2021

Recently, investors' interest and the influence of stock-related information dissemination are being considered as significant factors that explain stock returns and volume. Besides, companies that develop, distribute, or utilize innovative new technologies such as artificial intelligence have a problem that it is difficult to accurately predict a company's future stock returns and volatility due to macro-environment and market uncertainty. Market uncertainty is recognized as an obstacle to the activation and spread of artificial intelligence technology, so research is needed to mitigate this. Hence, the purpose of this study is to propose a machine learning model that predicts the volatility of a company's stock price by using the internet search volume of artificial intelligence-related technology keywords as a measure of the interest of investors. To this end, for predicting the stock market, we using the VAR(Vector Auto Regression) and deep neural network LSTM (Long Short-Term Memory). And the stock price prediction performance using keyword search volume is compared according to the technology's social acceptance stage. In addition, we also conduct the analysis of sub-technology of artificial intelligence technology to examine the change in the search volume of detailed technology keywords according to the technology acceptance stage and the effect of interest in specific technology on the stock market forecast. To this end, in this study, the words artificial intelligence, deep learning, machine learning were selected as keywords. Next, we investigated how many keywords each week appeared in online documents for five years from January 1, 2015, to December 31, 2019. The stock price and transaction volume data of KOSDAQ listed companies were also collected and used for analysis. As a result, we found that the keyword search volume for artificial intelligence technology increased as the social acceptance of artificial intelligence technology increased. In particular, starting from AlphaGo Shock, the keyword search volume for artificial intelligence itself and detailed technologies such as machine learning and deep learning appeared to increase. Also, the keyword search volume for artificial intelligence technology increases as the social acceptance stage progresses. It showed high accuracy, and it was confirmed that the acceptance stages showing the best prediction performance were different for each keyword. As a result of stock price prediction based on keyword search volume for each social acceptance stage of artificial intelligence technologies classified in this study, the awareness stage's prediction accuracy was found to be the highest. The prediction accuracy was different according to the keywords used in the stock price prediction model for each social acceptance stage. Therefore, when constructing a stock price prediction model using technology keywords, it is necessary to consider social acceptance of the technology and sub-technology classification. The results of this study provide the following implications. First, to predict the return on investment for companies based on innovative technology, it is most important to capture the recognition stage in which public interest rapidly increases in social acceptance of the technology. Second, the change in keyword search volume and the accuracy of the prediction model varies according to the social acceptance of technology should be considered in developing a Decision Support System for investment such as the big data-based Robo-advisor recently introduced by the financial sector.

• Journal of Agricultural Extension & Community Development
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• v.31 no.2
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• pp.85-101
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• 2024

Globally, technologies and policies are being developed to reduce greenhouse gas emissions. In agriculture, there's increasing interest in reducing methane emissions from paddy fields by improving water management practices. While automated irrigation systems are being developed, research on farmers' adoption intentions is lacking. This study aims to examine factors influencing farmers' acceptance of these systems using the UTAUT2 model. Results show that effort expectancy, facilitating conditions, price value, and user innovativeness positively influence acceptance intention, while perceived risk and innovation resistance negatively impact it. User innovativeness partially mediates the effects of facilitating conditions, price value, perceived risk, and innovation resistance on acceptance intention. Policy implications are proposed to promote the adoption of automated irrigation systems.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.711-720
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• 2020

This research aims to analyze the factors affecting the acceptance of social commerce, including performance expectancy, effort expectancy, social support, facilitating conditions, hedonic motivation, habitability, price saving orientation, and privacy concerns using the Unified Theory of Acceptance and Use of Technology (UTAUT2). UTAUT2 has been examined and modified in various contexts. The research model studies the acceptance and use of technology in the context of customers. This study adopts a quantitative method using the partial least squares regression (PLS) approach involving 244 respondents. The respondents are users of social commerce in Indonesia. The result of this research indicates that social influence, facilitating conditions, hedonic motivation, habit, price value orientation, and privacy concerns have a significant effect on behavioral intention. On the other hand, performance expectancy and effort expectancy does not affect behavioral intention. Furthermore, price value has a significant effect on social commerce user behavior. Lastly, facilitating conditions and habits does not affect social commerce user behavior. This research contributes to the development of theory by examining an additional variable, which is privacy concern. This study is significant since social media and social commerce have grown exponentially nowadays. Implications of the results for the development of the theory (UTAUT2) and practice are discussed in the article.

• The Journal of Information Systems
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• v.14 no.1
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• pp.171-195
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• 2005

The current study investigates major factors which influence the consumer's selection of internet shopping malls. Based on the technology acceptance model(TAM)(Davis, 1989) and trust theory(McKnight & Chervany, 2001), consumer selection factors from marketing research(Burke, 1997;Dodds et al, 2001), perceived usefulness, perceived ease of use, trust, service quality, and product price were hypothesized as to affect the consumer's decision to choose one's specific internet shopping malls. The study developed a research model to explain the shopping mall selection and collected the survey responses from 312 internet shopping mall users. The results of the current research indicate that all the research variables employed in the study, perceived usefulness, perceived ease of use, trust, service quality, and product price, are found to significantly influence the consumer's shopping mall selection decision. Among the influencing factors, price, service quality, and trust showed a greater effect on the shopping mall selection than usefulness and ease of use. This result implies that purchase-related variables such as price and service quality may be more critical to attracting customers and thereby raising the sales volume of the shopping mall, than the web site's usefulness and ease of use.

• Journal of the military operations research society of Korea
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• v.11 no.2
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• pp.64-68
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• 1985

This paper considers the following case: (1) the product is paid by the right price for a lot accepted by a given consumer's acceptance sampling plan, and (2) the product is paid by the discounted price for a lot rejected by this plan. In such a case, the producer's sampling plan need not be the same as that of the consumer's. From the producer's view point, the producer need to determine the preliminary sample size which maximizes his revenue. This paper, therefore, determines an optimal preliminary sample size from the producer's view point. This preliminary sample size is affected by the consumer's acceptance sampling plan, percent defective, preliminary inspection cost and the discount rate of the price.