• The Journal of Information Systems
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• v.32 no.2
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• pp.1-24
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• 2023

Purpose The aim of this study is to investigate how system quality, privacy concerns, and usefulness impact user satisfaction and word-of-mouth intention towards smart order services among Chinese consumers. The study also seeks to provide both theoretical and practical implications based on the findings. Design/methodology/approach This study conducted an empirical study on Chinese consumers through an online survey on 274 users of smart order service in China. To analyze the data, frequency analysis, reliability analysis, and confirmatory factor analysis were performed using SPSS 26.0 and AMOS 26.0 statistical programs, and structural equation model was used for hypothesis testing. Findings The study results are as follows. First, system quality was found to have a positive effect on usefulness and user satisfaction. Second, privacy concerns were found to have a positive effect on user satisfaction, but not on usefulness. Third, user satisfaction was found to have a positive effect on consumers' word-of-mouth intention of the smart order service. Finally, mediating effects were found between system quality and user satisfaction through usefulness, as well as between system quality, perceived privacy concern, and usefulness through user satisfaction.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.570-575
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• 2013

Enhancing utilization of buildings is gaining in importance in response to a challenging economy; thus, there is a need for a method that analyzes space, user, and user activity in an integrated way to provide project stakeholders with utilization information to support their decision-making about buildings. Conventional methods, such as architectural programming and post-occupancy evaluation, lack a formal relationship between user activity and other information, and therefore, are coarse-grained. This relationship has been formalized by two relatively new methods that provide fine-grained utilization information: workplace planning and space-use analysis. We characterize these two methods with focuses on their usage in different phases (i.e., planning, design, occupancy), required information that needs to be gathered, and the achievement and limitations in terms of three criteria, i.e., consistency, efficiency, and transparency. This characterization would not only help project stakeholders select and use a method that best meets their purposes for enhancing utilization of their buildings, but also provide researchers with promising research topics regarding enhancing utilization of buildings.

• Current Optics and Photonics
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• v.1 no.5
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• pp.440-455
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• 2017

In this paper, we carry out a performance analysis of a two-user free-space optical (FSO) communication system with photodetector multiplexing, in which the two users are defined as the primary user (PU) and secondary user (SU). Unlike common single-user FSO systems, our photodetector multiplexing FSO system deploys a shared detector at the receiver and enables PU and SU to send their own data synchronously. We conduct the performance analysis of this FSO system for two cases: (1) in the absence of background radiation, and (2) in the presence of background radiation. Decision strategies for PU and SU are presented according to the two scenarios above. Exact and approximate conditional symbol-error probability (SEP) expressions for both PU and SU are derived, in an ideal channel with no fading. Average SEP expressions are also presented in the no-background-radiation scenario. Additionally, in some particular cases where the power ratio tends to 0.5 or 1, approximate SEP expressions are also obtained. Finally, numerical simulations are presented under different conditions, to support the performance analysis.

• Korean Management Science Review
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• v.23 no.2
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• pp.59-74
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• 2006

In this paper, we investigated economic viability of UCA (Ubiquitous Contents Access) technologies from user adoption perspective. UCA technologies are expected to 9et embedded into media and telecom merging services. Embracing new technologies such as UCA technologies, forged through an industry convergence, means opting for a technological innovation that will have technological as well as economic and strategic implications. As such, we adopted user perspective innovation adoption theories to explore key antecedents affecting consumer acceptance of these emerging technologies. Subsequently. using QFD (Quality Function Deployment) method, the impacts of UCA technical functions on user's perceived value enhancements are estimated. The QFD analysis result indicates that the new UCA service technologies could achieve about 42% enhancement on user perceived adoption intention compared to existing digital contents service technologies. The proposed analysis framework and findings suggests significant insights for further research.

• Journal of the Ergonomics Society of Korea
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• v.13 no.2
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• pp.1-12
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• 1994

Many different types of computer user interfaces are used to perform office tasks. Although some guidelines are proposed for selecting user interfaces appropriate to perform differnet tasks, they have not been supported by empirical studies. This study examined five user interface styles and their combinations which were used to perform representative office tasks. A variety of analysis techniques such as brainstorming, analytic hierarchy process, prototyping, and expert opinions were employed to evaluate the usability of the interfaces. Also, a human factors experiment was conducted to validate empirically the analysis results. The analysis procedures and results are described along with guidelines for selecting user interfaces in terms of subjective preferences and performance measures.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.4908-4922
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• 2019

The popularization of smartphones in recent years has created a rich ground for online-to-offline (O2O) services based on location information. In the process of finding user locations in O2O services, BLE (Bluetooth Low Energy) beacons are widely used because the beacons are economical in many ways. The current BLE method does not specify the direction of user movement, but adding that information could enrich the user experience for various O2O services. This paper proposes a method that identifies the user movement direction through data analysis on data sets generated by a pair of BLE beacons. Also we demonstrate its implementation with examples of services that need the direction information of users in order to show the feasibility of the method proposed.

• Journal of Information Technology Applications and Management
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• v.19 no.4
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• pp.97-113
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• 2012

In order to implement the real-time enterprise (RTE) and smart work effectively, many companies have introduced a mobile office. A mobile office improves employee productivity and increases ability to respond to business opportunities by helping employee manage their business anytime and anywhere. However, it also raises the user's stress level. We conducted in-depth interviews with users to assess user's perception of a mobile office according to Saaty's BOCR model. Based on the results of the interviews, we set variables affecting user's perception of the mobile office using factor analysis. This study revealed that support for real-time business, support for communication and collaboration, and information processing quality were positively related to continuous intention to use mobile office. Further study demonstrated that three variables have mediating effect between the psychological stress and continuous intention to use. This result implies that the system quality and function are the key elements of mobile office and may contribute to the continuous use.

• The Journal of Information Systems
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• v.30 no.4
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• pp.227-245
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• 2021

Purpose The purpose of this study is to examine the variables affecting user satisfaction through previous studies and to examine the differences between apps. Differences are based on factors that determine the quality of real estate service apps and derived by the topic modeling results. Design/methodology/approach This study conducts topic modeling to find factors affecting user satisfaction of real estate service apps using user reviews. Sentiment analysis is additionally conduct on the derived topics to examine the user responses. Findings Users give high sentiment scores for services that can manage factors such as usefulness of information, false sales, and hype. In addition, managing the basic services of app is an important factor influencing user satisfaction.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.93-107
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• 2014

In this paper, we report what we have observed with regard to user-perspective issue clustering based on multi-layered two-mode network analysis. This work is significant in the context of data collection by companies about customer needs. Most companies have failed to uncover such needs for products or services properly in terms of demographic data such as age, income levels, and purchase history. Because of excessive reliance on limited internal data, most recommendation systems do not provide decision makers with appropriate business information for current business circumstances. However, part of the problem is the increasing regulation of personal data gathering and privacy. This makes demographic or transaction data collection more difficult, and is a significant hurdle for traditional recommendation approaches because these systems demand a great deal of personal data or transaction logs. Our motivation for presenting this paper to academia is our strong belief, and evidence, that most customers' requirements for products can be effectively and efficiently analyzed from unstructured textual data such as Internet news text. In order to derive users' requirements from textual data obtained online, the proposed approach in this paper attempts to construct double two-mode networks, such as a user-news network and news-issue network, and to integrate these into one quasi-network as the input for issue clustering. One of the contributions of this research is the development of a methodology utilizing enormous amounts of unstructured textual data for user-oriented issue clustering by leveraging existing text mining and social network analysis. In order to build multi-layered two-mode networks of news logs, we need some tools such as text mining and topic analysis. We used not only SAS Enterprise Miner 12.1, which provides a text miner module and cluster module for textual data analysis, but also NetMiner 4 for network visualization and analysis. Our approach for user-perspective issue clustering is composed of six main phases: crawling, topic analysis, access pattern analysis, network merging, network conversion, and clustering. In the first phase, we collect visit logs for news sites by crawler. After gathering unstructured news article data, the topic analysis phase extracts issues from each news article in order to build an article-news network. For simplicity, 100 topics are extracted from 13,652 articles. In the third phase, a user-article network is constructed with access patterns derived from web transaction logs. The double two-mode networks are then merged into a quasi-network of user-issue. Finally, in the user-oriented issue-clustering phase, we classify issues through structural equivalence, and compare these with the clustering results from statistical tools and network analysis. An experiment with a large dataset was performed to build a multi-layer two-mode network. After that, we compared the results of issue clustering from SAS with that of network analysis. The experimental dataset was from a web site ranking site, and the biggest portal site in Korea. The sample dataset contains 150 million transaction logs and 13,652 news articles of 5,000 panels over one year. User-article and article-issue networks are constructed and merged into a user-issue quasi-network using Netminer. Our issue-clustering results applied the Partitioning Around Medoids (PAM) algorithm and Multidimensional Scaling (MDS), and are consistent with the results from SAS clustering. In spite of extensive efforts to provide user information with recommendation systems, most projects are successful only when companies have sufficient data about users and transactions. Our proposed methodology, user-perspective issue clustering, can provide practical support to decision-making in companies because it enhances user-related data from unstructured textual data. To overcome the problem of insufficient data from traditional approaches, our methodology infers customers' real interests by utilizing web transaction logs. In addition, we suggest topic analysis and issue clustering as a practical means of issue identification.

• Journal of Environmental Science International
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• v.28 no.12
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• pp.1101-1110
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• 2019

This study investigated Post-Occupancy Evaluation (POE) of cherry blossom trails 'Cherry Road' in Daegu Catholic Univ. campus, at Gyeonsan-city, Korea. The evaluation focused on image preference and satisfaction of users i.e., students, using questionnaire surveys. A total 201 questionnaire samples were analyzed and most of the respondents were in the age group of 20. Frequency analysis was conducted on demographics, use behavior, reliability, and means. Factor analysis and multiple regression analysis were conducted for user satisfaction and image preference. Over 80% of visitors came with companions during daytime. The most common motives for use were strolling and walking, event and meeting, passing. For user satisfaction the mean scores were highest for landscape beauty (4.22), image improvement (4.14), campus image (4.08). Night lighting facility received the lowest score (3.32). Factor analysis concerning user satisfaction was categorized into environment-human behavior and physical factors. Multiple regression analysis showed that the overall satisfaction of user was significantly influenced by five independent variables: 'harmonious' (β=.214), 'night lighting facility' (β=.173), 'landscape beauty' (β=.208), 'lawn care' (β=.154), and 'walking trails' (β=.123). The mean scores of image variables were highest for 'beautiful' (5.81), 'bright' (5.67), and 'open' (5.64). The lowest scores was for 'quiet' (4.47). Exploratory factor analysis led to three factors being categorized: aesthetics, comforts, and simplicity. Result of multiple regression analysis indicated that the preference of space image was significantly influenced by five variables: 'bright' (β=.397), 'refreshing' (β=.211), 'cool' (β=.219), 'clean' (β=.182), and 'natural' (β=.-142). Hence, Cherry Road has a high level of user satisfaction and image evaluation, which is interpreted as having various cultural events and value for students on campus. To improve the satisfaction of Cherry Road in the future, it is necessary to secure night lighting, to manage trash cans, and to secure rest space.