• Journal of Distribution Science
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• v.10 no.2
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• pp.43-52
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• 2012

As experiential education services are growing, the need for proper management is increasing. Considering that adequate measures are an essential factor for achieving success in managing something, it is important for managers to use a proper system of metrics to measure the performance of experiential education services. However, in spite of this need, little research has been done to develop a valid and reliable set of metrics for assessing the quality of experiential education services. The current study aims to develop a multi-item instrument for assessing the service quality of experiential education. The specific procedure is as follows. First, we generated a pool of possible metrics based on diverse literature on service quality. We elicited possiblemetric items not only from general service quality metrics such as SERVQUAL and SERVPERF but also from educational service quality metrics such as HEdPERF and PESPERF. Second, specialist teachers in the experiential education area screened the initial metrics to boost face validity. Third, we proceeded with multiple rounds of empirical validation of those metrics. Based on this processes, we refined the metrics to determine the final metrics to be used. Fourth, we examined predictive validity by checking the well-established positive relationship between each dimension of metrics and customer satisfaction. In sum, starting with the initial pool of scale items elicited from the previous literature and purifying them empirically through the surveying method, we developed a four-dimensional systemized scale to measure the superiority of experiential education and named it "Experiential Education PERFormance" (EEPERF). Our findings indicate that students (consumers) perceive the superiority of the experiential education (EE) service in the following four dimensions: EE-empathy, EE-reliability, EE-outcome, and EE-landscape. EE-empathy is a judgment in response to the question, "How empathetically does the experiential educational service provider interact with me?" Principal measures are "How well does the service provider understand my needs?," and "How well does the service provider listen to my voice?" Next, EE-reliability is a judgment in response to the question, "How reliably does the experiential educational service provider interact with me?" Major measures are "How reliable is the schedule here?," and "How credible is the service provider?" EE-outcome is a judgmentin response to the question, "What results could I get from this experiential educational service encounter?" Representative measures are "How good is the information that I will acquire form this service encounter?," and "How useful is this service encounter in helping me develop creativity?" Finally, EE-landscape is a judgment about the physical environment. Essential measures are "How convenient is the access to the service encounter?,"and "How well managed are the facilities?" We showed the reliability and validity of the system of metrics. All four dimensions influence customer satisfaction significantly. Practitioners may use the results in planning experiential educational service programs and evaluating each service encounter. The current study isexpected to act as a stepping-stone for future scale improvement. In this case, researchers may use the experience quality paradigm that has recently arisen.

• Asia pacific journal of information systems
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• v.18 no.1
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• pp.97-115
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• 2008

Introduction The e-government is concerned with using Internet and Web technologies to exchange information and services with citizens, businesses and other related organizations, and it centers on three functions, namely informational, interactive, and transactional [UN, 2001]. Many developed countries like the U.S. have been actively involved in e-government projects, since they enable both more effective public services for citizens and more efficient internal operations. Korea is among these leading countries that are planning to leverage computer and communication technologies to provide for integration of work processes and information as well as convenient access to information and services. For this reason, evaluating e-government projects is becoming a crucial issue for both researchers and policy-makers. However, most research to date has primarily focused on a model of success of an e-government system designed for citizens, overlooking internal systems specifically created for employees working in a public organization. This paper is intended to propose a model to measure the success of a Web-based information system designed for use by internal users at Chungwadae, the executive branch of Korea's central government. The paper is also aimed at applying the model to the assessment of the present system being used at Chungwadae in comparison with the preceding system. Evaluating an e-Government System The most widely cited model of information systems success today is that of DeLone and McLean[1992, 2003, 2004]. The original model states that the success of an information system can be measured using six dimensions, including system quality, information quality, use, user satisfaction, individual impact, and organizational impact. Although the ultimate success of an information system may be reflected in the impact that the system has upon individuals as well as an organization, aspects of using the system such as system use and user satisfaction can play an important role in determining the system success, because the system would be a sheer failure if users don't like and use the system. As a response to criticisms given by numerous researchers, the authors adapted their model to fit the emerging Web-based environment. The revised model[DeLone and McLean, 2003] they offered included an additional quality dimension, namely service quality, and combined individual and organizational impacts into net benefits which can also influence user satisfaction. The e-government system success model can be built around this updated model. Our model incorporates information quality, system quality, and service quality as in the DeLone and McLean model. However, the 'system use' dimension has been replaced by perceived usefulness, as suggested by Seddon[1998]. In addition, because the e-government systems that this paper focuses on are internal public systems used in government agencies, the 'net benefits' dimension has been replaced by perceived work efficiency. Based on the proposed model, a total of nine hypotheses have been formulated which we tested using an empirical analysis. Methods A questionnaire form has been created with items that are designed to examine the relationships among the variables in the model. The questionnaire has been handed over, in person, to 65 members of Chungwadae staff who are now actively using the E-Support System, the present information system created to support internal work at Chungwadae. We made arrangements to meet with each individual who agreed to participate in our survey, and helped to fill out the survey form with explanations. Of the 65 copies that were delivered, only 33 were returned, and 30 responses of these have been adopted for our analysis, since three were not valid. The extremely small sample size was due to the limited number of staff members who had adequate experience required of this study. Results We gathered data from the questionnaire survey and analyzed them using a regression analysis to test the hypotheses. As shown in the table below, the results indicated that all three dimensions of an information system’s quality are positively related to user satisfaction. However, information quality and system quality were found to be positively related to perceived usefulness, while service quality was not. In addition, perceived usefulness is not positively related to user satisfaction, implying that a user may find a system useful, but may not be satisfied with it. Finally, user satisfaction and perceived usefulness both are positively related to perceived work efficiency. This suggests that workers' positive experience with the system is important to guarantee favorable work efficiency. Conclusions We conclude that the proposed model proved useful in measuring the success of an internal information system used by a government agency. To demonstrate the applicability and usefulness of the model in the paper, we applied the model to the assessment of the present internal system used at Chungwadae in comparison with the preceding system. The results showed that the present system outperforms the preceding one in a statistically significant way. Future research will have to focus on applying the model to Korea's governmental agencies other than Chungwadae and examine whether it proves applicable in different types of governmental organizations.

• Journal of Gifted/Talented Education
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• v.21 no.1
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• pp.57-81
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• 2011

The purpose of this study was to explore the quality of life of musically talented students as measured by their external experiences (e.g., activities, companions) and internal experiences (e.g., flow, emotion). The participants in this study were 33 musically talented students (10 males, 23 females) aged 13 to 19. Study data were collected for 7 consecutive days using the Experience Sampling Method (ESM), which employs a cellular-phone as a signaling device. The results were as follows: First, in response to the 1625 random signals, musically talented students reported that 40.9% of their time was spent on productive activities. An additional 33.4% of time was used for maintenance activities and the rest of their time was spent on leisure/social activities. Also, musically talented students reported that 48.5% of their time was spent alone. When they were alone, they spent a lot of time engaging in productive activities (44.3%). Second, in order to measure the flow of their life, two methods were used. One used a 4-channel flow model (i.e. apathy, boredom, flow, anxiety) and the other used 8 dimensions and conditions of the flow experience (i.e. concentration, self-consciousness disappears, action and awareness merge, distorted sense of time, freedom from worry about failure, clear goals, immediate feedback, balance between challenges and skills). According to the former, when engaged in music-related activities, musically talented students usually reported flow (54.0%), while they felt apathy (41.3%) for daily routines activities. According to the latter method, musically talented students experienced flow for most productive activities, while they experienced flow least for maintenance activities. Emotional variables of ESF are comprised of 10 semantic scales (i.e. happy-sad, strong-weak, active-passive, sociablelonely, proud-ashamed, involved-detached, excited-bored, clear-confused, relaxed-worried, cooperative-competitive). Musically talented students reported experiencing the most positive emotion for social activities and experiencing the most negative emotion for maintenance activities. Results of this study assert that musically talented students had to trade off immediate enjoyment for developing their special gifts. They could not afford as much time for socializing with friends, and they had to spend more time alone compared to their peers without such gifts. Consequently, they were found to deprive themselves of the spontaneous good times that teenagers usually thrive on. They were helped in this respect by their autotelic personality traits, especially their strong need for achievement and endurance. The downside, however, is that the moment-to-moment quality of their moods suffered. The argument concerning musically talented students applies for all adolescents. The choices that talented students must make between immediate gratification and long-term development, and between solitude and companionship, are the same choices every young person must make, regardless of her or his level of talent. All of us have gifts that are potentially useful and worthy of being appreciated. But to develop these latent talents we must cultivate them, and this takes time and the investment of mental energy. The lifestyle that musically talented students develop can show us some of the choices all of us must make in order to cultivate our gifts.

• Journal of Venture Innovation
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• v.6 no.4
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• pp.23-40
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• 2023

This study examines the customer value factors affecting the intention to continue using the mobile app of department stores, which are traditional offline retailers, in the retail industry that is rapidly digitalizing and becoming mobile. This study clarifies multidimensional customer value in three dimensions; functional, convenience, and social. Functional value refers to the integrated channel, and consistent customer experience provided between channels in the omnichannel retail environment, while convenience value is the convenience of saving time and effort save while customers use a mobile app. Social value refers to the improvement of social approval or social self-concept occurring due to the use of products or services related to green marketing within the mobile app of the department store. The influence of each on the dependent variable, the mobile app's continuous use intention, was analyzed by using the three dimensions of customer value as independent variables. Data was collected from customers who have a history of using the mobile app of Shinsegae Department Store in Korea, and a confirmatory analysis was conducted using Smart PLS 4.0. The analysis results showed that all three dimensions of customer value; functional value, convenience value, and social value, had a positive (+) influence on customers' intention to continue using the mobile app, and the influence of functional value had the greatest impact. As functional value appears to be the most important influencing factor due to the omnichannel retail trend by advancement of technology, it suggests that it is important for department stores, and offline retailers, to provide integrated channels. This provides insights into the direction of customer-centered strategy formulation for activating department store mobile apps and suggests basic analytical data for customized services and marketing activities that department stores can effectively meet the changing expectations and demands of customers through new mobile channels rather than existing offline channels.

• Journal of Global Scholars of Marketing Science
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• v.18 no.2
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• pp.89-111
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• 2008

Due to the development of digital technology, studies regarding smart wear integrating daily life have rapidly increased. However, consumer research about perception and attitude toward smart clothing hardly could find. The purpose of this study was to identify innovative characteristics and perceived risk of smart clothing and to analyze the influences of theses factors on product attitudes and intention to adopt. Specifically, five hypotheses were established. H1: Perceived attributes of smart clothing except for complexity would have positive relations to product attitude or purchase intention, while complexity would be opposite. H2: Product attitude would have positive relation to purchase intention. H3: Product attitude would have a mediating effect between perceived attributes and purchase intention. H4: Perceived risks of smart clothing would have negative relations to perceived attributes except for complexity, and positive relations to complexity. H5: Product attitude would have a mediating effect between perceived risks and purchase intention. A self-administered questionnaire was developed based on previous studies. After pretest, the data were collected during September, 2006, from university students in Korea who were relatively sensitive to innovative products. A total of 300 final useful questionnaire were analyzed by SPSS 13.0 program. About 60.3% were male with the mean age of 21.3 years old. About 59.3% reported that they were aware of smart clothing, but only 9 respondents purchased it. The mean of attitudes toward smart clothing and purchase intention was 2.96 (SD=.56) and 2.63 (SD=.65) respectively. Factor analysis using principal components with varimax rotation was conducted to identify perceived attribute and perceived risk dimensions. Perceived attributes of smart wear were categorized into relative advantage (including compatibility), observability (including triability), and complexity. Perceived risks were identified into physical/performance risk, social psychological risk, time loss risk, and economic risk. Regression analysis was conducted to test five hypotheses. Relative advantage and observability were significant predictors of product attitude (adj $R^2$=.223) and purchase intention (adj $R^2$=.221). Complexity showed negative influence on product attitude. Product attitude presented significant relation to purchase intention (adj $R^2$=.692) and partial mediating effect between perceived attributes and purchase intention (adj $R^2$=.698). Therefore hypothesis one to three were accepted. In order to test hypothesis four, four dimensions of perceived risk and demographic variables (age, gender, monthly household income, awareness of smart clothing, and purchase experience) were entered as independent variables in the regression models. Social psychological risk, economic risk, and gender (female) were significant to predict relative advantage (adj $R^2$=.276). When perceived observability was a dependent variable, social psychological risk, time loss risk, physical/performance risk, and age (younger) were significant in order (adj $R^2$=.144). However, physical/performance risk was positively related to observability. The more Koreans seemed to be observable of smart clothing, the more increased the probability of physical harm or performance problems received. Complexity was predicted by product awareness, social psychological risk, economic risk, and purchase experience in order (adj $R^2$=.114). Product awareness was negatively related to complexity, meaning high level of product awareness would reduce complexity of smart clothing. However, purchase experience presented positive relation with complexity. It appears that consumers can perceive high level of complexity when they are actually consuming smart clothing in real life. Risk variables were positively related with complexity. That is, in order to decrease complexity, it is also necessary to consider minimizing anxiety factors about social psychological wound or loss of money. Thus, hypothesis 4 was partially accepted. Finally, in testing hypothesis 5, social psychological risk and economic risk were significant predictors for product attitude (adj $R^2$=.122) and purchase intention (adj $R^2$=.099) respectively. When attitude variable was included with risk variables as independent variables in the regression model to predict purchase intention, only attitude variable was significant (adj $R^2$=.691). Thus attitude variable presented full mediating effect between perceived risks and purchase intention, and hypothesis 5 was accepted. Findings would provide guidelines for fashion and electronic businesses who aim to create and strengthen positive attitude toward smart clothing. Marketers need to consider not only functional feature of smart clothing, but also practical and aesthetic attributes, since appropriateness for social norm or self image would reduce uncertainty of psychological or social risk, which increase relative advantage of smart clothing. Actually social psychological risk was significantly associated to relative advantage. Economic risk is negatively associated with product attitudes as well as purchase intention, suggesting that smart-wear developers have to reflect on price ranges of potential adopters. It will be effective to utilize the findings associated with complexity when marketers in US plan communication strategy.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.57-78
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• 2020

With the development of the Internet, consumers have had an opportunity to check product information easily through E-Commerce. Product reviews used in the process of purchasing goods are based on user experience, allowing consumers to engage as producers of information as well as refer to information. This can be a way to increase the efficiency of purchasing decisions from the perspective of consumers, and from the seller's point of view, it can help develop products and strengthen their competitiveness. However, it takes a lot of time and effort to understand the overall assessment and assessment dimensions of the products that I think are important in reading the vast amount of product reviews offered by E-Commerce for the products consumers want to compare. This is because product reviews are unstructured information and it is difficult to read sentiment of reviews and assessment dimension immediately. For example, consumers who want to purchase a laptop would like to check the assessment of comparative products at each dimension, such as performance, weight, delivery, speed, and design. Therefore, in this paper, we would like to propose a method to automatically generate multi-dimensional product assessment scores in product reviews that we would like to compare. The methods presented in this study consist largely of two phases. One is the pre-preparation phase and the second is the individual product scoring phase. In the pre-preparation phase, a dimensioned classification model and a sentiment analysis model are created based on a review of the large category product group review. By combining word embedding and association analysis, the dimensioned classification model complements the limitation that word embedding methods for finding relevance between dimensions and words in existing studies see only the distance of words in sentences. Sentiment analysis models generate CNN models by organizing learning data tagged with positives and negatives on a phrase unit for accurate polarity detection. Through this, the individual product scoring phase applies the models pre-prepared for the phrase unit review. Multi-dimensional assessment scores can be obtained by aggregating them by assessment dimension according to the proportion of reviews organized like this, which are grouped among those that are judged to describe a specific dimension for each phrase. In the experiment of this paper, approximately 260,000 reviews of the large category product group are collected to form a dimensioned classification model and a sentiment analysis model. In addition, reviews of the laptops of S and L companies selling at E-Commerce are collected and used as experimental data, respectively. The dimensioned classification model classified individual product reviews broken down into phrases into six assessment dimensions and combined the existing word embedding method with an association analysis indicating frequency between words and dimensions. As a result of combining word embedding and association analysis, the accuracy of the model increased by 13.7%. The sentiment analysis models could be seen to closely analyze the assessment when they were taught in a phrase unit rather than in sentences. As a result, it was confirmed that the accuracy was 29.4% higher than the sentence-based model. Through this study, both sellers and consumers can expect efficient decision making in purchasing and product development, given that they can make multi-dimensional comparisons of products. In addition, text reviews, which are unstructured data, were transformed into objective values such as frequency and morpheme, and they were analysed together using word embedding and association analysis to improve the objectivity aspects of more precise multi-dimensional analysis and research. This will be an attractive analysis model in terms of not only enabling more effective service deployment during the evolving E-Commerce market and fierce competition, but also satisfying both customers.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.4
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• pp.1-20
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• 2023

This study attempted to identify the relationship between the investment determinants of accelerators and investment performance through empirical analysis. Through literature review, four dimensions and 12 measurement items were extracted for investment determinants, which are independent variables, and investment performance was adjusted to the cumulative amount of subsequent investment based on previous studies. Performance data from 594 companies selected by TIPS from 2017 to 2019, which are relatively reliable and easy to secure data, were collected, and the subsequent investment cumulative attraction amount, which is a dependent variable, was hypothesized through multiple regression analysis three years after the investment. As a result of the study, 'industrial experience years' in the characteristics of founders, 'market size', 'market growth', 'competitive strength', and 'number of patents' in the characteristics of products and services had a significant positive (+) effect. The impact of independent variables on dependent variables was most influenced by the competitive strength of market characteristics, followed by the number of years of industrial experience, the number of patents, the size of the market, and market growth. This was different from the results of previous studies conducted mainly on qualitative research methods, and in most previous studies, the characteristics of founders were the most important, but the empirical analysis results were market characteristics. As a sub-factor, the intensity of competition, which was the subordinate to the importance of previous studies, had the greatest influence in empirical analysis. The academic significance of this study is that it presented a specific methodology to collect and build 594 empirical samples in the absence of empirical research on accelerator investment determinants, and created an opportunity to expand the theoretical discussion of investment determinants through causal research. In practice, the information asymmetry and uncertainty of startups that accelerators have can help them make effective investment decisions by establishing a systematic model of experience-dependent investment determinants.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.47-73
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• 2020

KTX rolling stocks are a system consisting of several machines, electrical devices, and components. The maintenance of the rolling stocks requires considerable expertise and experience of maintenance workers. In the event of a rolling stock failure, the knowledge and experience of the maintainer will result in a difference in the quality of the time and work to solve the problem. So, the resulting availability of the vehicle will vary. Although problem solving is generally based on fault manuals, experienced and skilled professionals can quickly diagnose and take actions by applying personal know-how. Since this knowledge exists in a tacit form, it is difficult to pass it on completely to a successor, and there have been studies that have developed a case-based rolling stock expert system to turn it into a data-driven one. Nonetheless, research on the most commonly used KTX rolling stock on the main-line or the development of a system that extracts text meanings and searches for similar cases is still lacking. Therefore, this study proposes an intelligence supporting system that provides an action guide for emerging failures by using the know-how of these rolling stocks maintenance experts as an example of problem solving. For this purpose, the case base was constructed by collecting the rolling stocks failure data generated from 2015 to 2017, and the integrated dictionary was constructed separately through the case base to include the essential terminology and failure codes in consideration of the specialty of the railway rolling stock sector. Based on a deployed case base, a new failure was retrieved from past cases and the top three most similar failure cases were extracted to propose the actual actions of these cases as a diagnostic guide. In this study, various dimensionality reduction measures were applied to calculate similarity by taking into account the meaningful relationship of failure details in order to compensate for the limitations of the method of searching cases by keyword matching in rolling stock failure expert system studies using case-based reasoning in the precedent case-based expert system studies, and their usefulness was verified through experiments. Among the various dimensionality reduction techniques, similar cases were retrieved by applying three algorithms: Non-negative Matrix Factorization(NMF), Latent Semantic Analysis(LSA), and Doc2Vec to extract the characteristics of the failure and measure the cosine distance between the vectors. The precision, recall, and F-measure methods were used to assess the performance of the proposed actions. To compare the performance of dimensionality reduction techniques, the analysis of variance confirmed that the performance differences of the five algorithms were statistically significant, with a comparison between the algorithm that randomly extracts failure cases with identical failure codes and the algorithm that applies cosine similarity directly based on words. In addition, optimal techniques were derived for practical application by verifying differences in performance depending on the number of dimensions for dimensionality reduction. The analysis showed that the performance of the cosine similarity was higher than that of the dimension using Non-negative Matrix Factorization(NMF) and Latent Semantic Analysis(LSA) and the performance of algorithm using Doc2Vec was the highest. Furthermore, in terms of dimensionality reduction techniques, the larger the number of dimensions at the appropriate level, the better the performance was found. Through this study, we confirmed the usefulness of effective methods of extracting characteristics of data and converting unstructured data when applying case-based reasoning based on which most of the attributes are texted in the special field of KTX rolling stock. Text mining is a trend where studies are being conducted for use in many areas, but studies using such text data are still lacking in an environment where there are a number of specialized terms and limited access to data, such as the one we want to use in this study. In this regard, it is significant that the study first presented an intelligent diagnostic system that suggested action by searching for a case by applying text mining techniques to extract the characteristics of the failure to complement keyword-based case searches. It is expected that this will provide implications as basic study for developing diagnostic systems that can be used immediately on the site.

• Archives of design research
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• v.15 no.4
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• pp.97-110
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• 2002

As users environments change, users primary needs for homepages also change more complicatedly. Today, users do not only want usability for homepages, but also to feel appropriate emotional experiences. Despite users needs, users do not always experience appropriate emotions that are conveyed by designers through homepage. I In this research paper, we analyzed the related factors with the emotional quality, which means the degree that users feel target emotions intended by designers. For analyzing factors related with the emotional quality, three hypotheses were verified; the factor of an emotion, the factor of users and the factor of designers. As the factor of emotions, the first hypothesis is that unclear emotional dimensions in users minds are related with the emotional quality. The second hypothesis, as the factor of users, is that the diversity of users experiences by same homepage is related with the emotional quality. The third hypothesis, as the factor of designers, is that the appropriate selection of design elements is related with the emotional quality. In the previous research, we selected the basic 13 emotional dimensions and 30 representative emotional words based on the statistical results and evaluations by professional designers. For this research, we conducted an experiment and user survey. In the experiment, we asked 30 designers to design homepages focusing on the typical emotion that was presented by a researcher. Based on the designing process and user evaluation, we performed statistical analyses: ANOVA with Tukey post hoc method and Factor Analysis. We found the discrepancy between the emotions that designers intend and the actual emotions that users experienced from homepages. From the result of analysis, we know that the factor of users and the factor of designers related with the emotional qualities, but the factor of emotions did not. The definiteness of emotions did not relate with the emotional quality. However, the diversity of emotions that users feel seeing the same homepages and design elements that designers chose for conveying target emotion related with the emotional quality.

• Asia pacific journal of information systems
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• v.19 no.3
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• pp.99-124
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• 2009

Many firms in Korea have adopted and used advanced information technology in an effort to boost efficiency. The process of adapting to the new technology, at the same time, can vary from one firm to another. As such, this research focuses on several relevant factors, especially the roles of social interaction as a key variable that influences the technology adaptation process and the outcomes. Thus far, how a firm goes through the adaptation process to the new technology has not been yet fully explored. Previous studies on changes undergone by a firm or an organization due to information technology have been pursued from various theoretical points of views, evolved from technological and institutional views to an integrated social technology views. The technology adaptation process has been understood to be something that evolves over time and has been regarded as cycles between misalignments and alignments, gradually approaching the stable aligned state. The adaptation process of the new technology was defined as "appropriation" process according to Poole and DeSanctis (1994). They suggested that this process is not automatically determined by the technology design itself. Rather, people actively select how technology structures should be used; accordingly, adoption practices vary. But concepts of the appropriation process in these studies are not accurate while suggested propositions are not clear enough to apply in practice. Furthermore, these studies do not substantially suggest which factors are changed during the appropriation process and what should be done to bring about effective outcomes. Therefore, research objectives of this study lie in finding causes for the difference in ways in which advanced information technology has been used and adopted among organizations. The study also aims to explore how a firm's interaction with social as well as technological factors affects differently in resulting organizational changes. Detail objectives of this study are as follows. First, this paper primarily focuses on the appropriation process of advanced information technology in the long run, and we look into reasons for the diverse types of the usage. Second, this study is to categorize each phases in the appropriation process and make clear what changes occur and how they are evolved during each phase. Third, this study is to suggest the guidelines to determine which strategies are needed in an individual, group and organizational level. For this, a substantially grounded theory that can be applied to organizational practice has been developed from a longitudinal comparative case study. For these objectives, the technology appropriation process was explored based on Structuration Theory by Giddens (1984), Orlikoski and Robey (1991) and Adaptive Structuration Theory by Poole and DeSanctis (1994), which are examples of social technology views on organizational change by technology. Data have been obtained from interviews, observations of medical treatment task, and questionnaires administered to group members who use the technology. Data coding was executed in three steps following the grounded theory approach. First of all, concepts and categories were developed from interviews and observation data in open coding. Next, in axial coding, we related categories to subcategorize along the lines of their properties and dimensions through the paradigm model. Finally, the grounded theory about the appropriation process was developed through the conditional/consequential matrix in selective coding. In this study eight hypotheses about the adaptation process have been clearly articulated. Also, we found that the appropriation process involves through three phases, namely, "direct appropriation," "cooperate with related structures," and "interpret and make judgments." The higher phases of appropriation move, the more users represent various types of instrumental use and attitude. Moreover, the previous structures like "knowledge and experience," "belief that other members know and accept the use of technology," "horizontal communication," and "embodiment of opinion collection process" are evolved to higher degrees in their dimensions of property. Furthermore, users continuously create new spirits and structures, while removing some of the previous ones at the same time. Thus, from longitudinal view, faithful and unfaithful appropriation methods appear recursively, but gradually faithful appropriation takes over the other. In other words, the concept of spirits and structures has been changed in the adaptation process over time for the purpose of alignment between the task and other structures. These findings call for a revised or extended model of structural adaptation in IS (Information Systems) literature now that the vague adaptation process in previous studies has been clarified through the in-depth qualitative study, identifying each phrase with accuracy. In addition, based on these results some guidelines can be set up to help determine which strategies are needed in an individual, group, and organizational level for the purpose of effective technology appropriation. In practice, managers can focus on the changes of spirits and elevation of the structural dimension to achieve effective technology use.