• Information Systems Review
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• v.20 no.1
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• pp.137-158
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• 2018

Online platforms recently expanded their connectivity through an authing service. The growth of authing services enabled consumers to enjoy easy log in access without exerting extra effort. However, multiple points of access increases the security vulnerability of platform ecosystems. Despite the importance of balancing authing service and security, only a few studies examined platform connectivity. This study examines the optimal level of authing service of a platform and how authing strategies impact participants in a platform ecosystem. We used a game-theoretic approach to analyze security problems associated with authing services provided by online platforms for consumers and other linked platforms. The main findings are as follows: 1) the decreased expected loss of consumers will increase the number of players who participate in the platform; 2) linked platforms offer strong benefits from consumers involved in an authing service; 3) the main platform will increase its effort level, which includes security cost and checking of linked platform's security if the expected loss of the consumers is low. Our study contributes to the literature on the relationship between technology convenience and security risk and provides guidelines on authing strategies to platform managers.

• Information Systems Review
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• v.20 no.2
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• pp.111-137
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• 2018

Considering the increase in health insurance benefits and the elderly population of the baby boomer generation, the amount consumed by health care in 2020 is expected to account for 20% of US GDP. As the healthcare industry develops, competition among the medical services of hospitals intensifies, and the need of hospitals to manage the quality of medical services increases. In addition, interest in online reviews of hospitals has increased as online reviews have become a tool to predict hospital quality. Consumers tend to refer to online reviews even when choosing healthcare service providers and after evaluating service quality online. This study aims to analyze the effect of sentiment score of healthcare service quality on hospital rating with Yelp hospital reviews. This study classifies large amount of text data collected online primarily into five service quality measurement indexes of SERVQUAL theory. The sentiment scores of reviews are then derived by SERVQUAL dimensions, and an econometric analysis is conducted to determine the sentiment score effects of the five service quality dimensions on hospital reviews. Results shed light on the means of managing online hospital reputation to benefit managers in the healthcare and medical industry.

• Information Systems Review
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• v.25 no.2
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• pp.181-203
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• 2023

With the fierce competition of companies for the attraction of outstanding individuals, job satisfaction of employees has been of importance. In this circumstance, many companies try to invest in job satisfaction improvement by finding employees' everyday experiences and difficulties. However, due to a lack of understanding of the employee experience, their investments are not paying off. This study examined the relationship between employee experience and job satisfaction using employee reviews and company ratings from Glassdoor, one of the largest employee communities worldwide. We use text mining techniques such as K-means clustering and LDA topic-based sentiment analysis to extract key experience factors by job level, and DistilBERT sentiment analysis to measure the sentiment score of each employee experience factor. The drawn employee experience factors and each sentiment score were analyzed quantitatively, and thereby relations between each employee experience factor and job satisfaction were analyzed. As a result, this study found that there is a significant difference between the workplace experiences of managers and general employees. In addition, employee experiences that affect job satisfaction also differed between positions, such as customer relationship and autonomy, which did not affect the satisfaction of managers. This study used text mining and quantitative modeling method based on theory of work adjustment so as to find and verify main factors of employee experience, and thus expanded research literature. In addition, the results of this study are applicable to the personnel management strategy for improving employees' job satisfaction, and are expected to improve corporate productivity ultimately.

• Information Systems Review
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• v.26 no.2
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• pp.23-43
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• 2024

Nowadays, online reviews have become a common word of mouth that many users produce and consume. Posting online reviews is a kind of job that consumers do themselves. Since posting online reviews is not mandatory, it entirely relies on the consumer's voluntary willingness. In this respect, this study aims to describe the motivation for posting online reviews and their behavior processes, such as why online reviewers generate reviews and what types of reviews they create. In this study, we have conducted an in-depth study with 18 participants who have experience in posting reviews. By analyzing interview manuscripts from the grounded theory method approach, we have ultimately presented motivating factors for review posting (mutual reciprocity, material rewards), determinants of review browsing (trust toward review contents, preference for review format), and shadow work (a job that must be done, voluntary data production, consumer's share). We have also proposed the dynamics between core dimensions for theorizing a cycle process of review production and consumption. Our findings could bridge the gap in the existing online review research and offer practical implications for platform companies that need review management.

• Information Systems Review
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• v.26 no.2
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• pp.1-22
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• 2024

This study aims to empirically analyze the usage behavior of metaverses, which have recently attracted attention in various fields. To date, research on metaverses has focused on the concept, direction of utilization, development prospects, and technical aspects. However, there is a lack of research on the characteristics of metaverses and the behavior of users. As the metaverse develops with new content, there is a need to understand user behavior and content characteristics. In this study, we surveyed 375 adult males and females who experienced metaverse, and analyzed the impact of metaverse usage behavior on brand loyalty and item purchase intention based on 350 samples after excluding non-responses. The collected data were cleaned and statistically analyzed using SPSS 25.0 and SmartPLS 4.0. The results showed that the usage behavior factors such as immersion, vicarious satisfaction, and avatar identification have a positive effect on brand loyalty and intention to purchase branded items. These findings help to understand the concept and development direction of metaverse, and are expected to make important contributions to the field of brand marketing strategy formulation and metaverse-related user behavior research.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.5
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• pp.69-94
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• 2024

In order to improve the security policy compliance performance of an organization, it is crucial for organizational members to have a strong intention to actively accept these policies. Accordingly, this study proposes a research model based on the Health Belief Model, a key theory in the field of health psychology, with the aim of seeking ways to enhance the acceptability of security policies among organizational members. Data were collected through surveys and analyzed using statistical methods. The results of the study revealed that the perceived security threats and the perception of support for security policy compliance at the organizational level significantly influence the acceptance of security policies through the mediating role of perceived benefits from security policy compliance. Additionally, the study demonstrated that the perceived burden of effort and work disruption associated with complying with security policies, i.e., perceived barriers, has a significant negative impact on the acceptance of security policies. This study holds academic significance as it presents a model that effectively analyzes the cognitive mechanisms influencing the acceptance of security policies by applying the Health Belief Model, originally rooted in healthcare. The analysis results and various implications discussed in this study are expected to provide useful information and insights for developing strategies to enhance the acceptance of security policies among organizational members in the future.

• Journal of Intelligence and Information Systems
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• v.22 no.1
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• pp.119-138
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• 2016

Since the Industrial Revolution, which made the mass production and mass distribution of standardized goods possible, machine-made (manufactured) products have accounted for the majority of the market. However, in recent years, the phenomenon of purchasing even more expensive handmade products has become a noticeable trend as consumers have started to acknowledge the value of handmade products, such as the craftsman's commitment, belief in their quality and scarcity, and the sense of self-esteem from having them,. Consumer interest in these handmade products has shown explosive growth and has been coupled with the recent development of three-dimensional (3D) printing technologies. Etsy.com is the world's largest online handmade platform. It is no different from any other online platform; it provides an online market where buyers and sellers virtually meet to share information and transact business. However, Etsy.com is different in that shops within this platform only deal with handmade products in a variety of categories, ranging from jewelry to toys. Since its establishment in 2005, despite being limited to handmade products, Etsy.com has enjoyed rapid growth in membership, transaction volume, and revenue. Most recently in April 2015, it raised funds through an initial public offering (IPO) of more than 1.8 billion USD, which demonstrates the huge potential of online handmade platforms. After the success of Etsy.com, various types of online handmade platforms such as Handmade at Amazon, ArtFire, DaWanda, and Craft is ART have emerged and are now competing with each other, at the same time, which has increased the size of the market. According to Deloitte's 2015 holiday survey on which types of gifts the respondents plan to buy during the holiday season, about 16% of U.S. consumers chose "homemade or craft items (e.g., Etsy purchase)," which was the same rate as those for the computer game and shoes categories. This indicates that consumer interests in online handmade platforms will continue to rise in the future. However, this high interest in the market for handmade products and their platforms has not yet led to academic research. Most extant studies have only focused on machine-made products and intelligent services for them. This indicates a lack of studies on handmade products and their intelligent services on virtual platforms. Therefore, this study used signaling theory and prior research on the effects of sellers' characteristics on their performance (e.g., total sales and price premiums) in the buyer-seller relationship to identify the key influencing e-Image factors (e.g., reputation, size, information sharing, and length of relationship). Then, their impacts on the performance of shops within the online handmade platform were empirically examined; the dataset was collected from Etsy.com through the application of web harvesting technology. The results from the structural equation modeling revealed that the reputation, size, and information sharing have significant effects on the total sales, while the reputation and length of relationship influence price premiums. This study extended the online platform research into online handmade platform research by identifying key influencing e-Image factors on within-platform shop's total sales and price premiums based on signaling theory and then performed a statistical investigation. These findings are expected to be a stepping stone for future studies on intelligent online handmade services as well as handmade products themselves. Furthermore, the findings of the study provide online handmade platform operators with practical guidelines on how to implement intelligent online handmade services. They should also help shop managers build their marketing strategies in a more specific and effective manner by suggesting key influencing e-Image factors. The results of this study should contribute to the vitalization of intelligent online handmade services by providing clues on how to maximize within-platform shops' total sales and price premiums.

• Archives of design research
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• v.19 no.4 s.66
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• pp.41-50
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• 2006

It is generally regarded a design system in post-industrial society, which products designed by in-house designers or design consultancy are manufactured in factory and distributed in market for the consumer. Although it is treated an old design system in traditional society, the traces of vernacular design has been remaining in the state of adopted to the periodical needs in these days, also proving the attribute of design culture to constitute human's material environment as well as existing design systems. There were discovered various design artifacts in daily surroundings vary from the established design in several manners, user modifications or manufactures in everyday lives formalized them. It was approached a case study that analyze the changes of artifact configuration and designer/user context and creation process of the non-professional design artifacts, Creativity Template Theory and ACM(Artifact Context Model) have been utilized for the analysis model. From the analysis result, It assume that the everyday artifacts may be ordinary but extra-ordinary including particular ideas and identity represented by everyday designers or users. Beside these characteristics induce the potentiality that reflect on creative motives for the designers or a complementary artifact generator filling up with drawbacks in established design system. The everyday design domain, various explorations and alternatives are made, is seems to be another design practice domain dissimilar to the one in the industry-based design. Moreover it provides an more easily accessability for the approaching user-friendly design, user customization because they conduct the reliable modeling of consumer and end-user. Finally, based on the exploratory study regarding interpretation of context and configuration in the everyday artifacts, new approach for the design process and design education through more detailed cognitive modeling of everyday designers will be a further study.

• Journal of Korean Academy of Nursing
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• v.23 no.3
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• pp.417-430
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• 1993

이 연구는 환경적 요소(간호사의 자율성, 조직의 표준화)와 개인의 특성(통제위, 나이, 경험. 간호역할개념, 도덕성), 직무 스트레스, 윤리적 의사결정 사이의 관계를 이론적 틀을 구성하여 테스트함으로써 그 인과관계를 탐구하였다. 본 연구를 위해 개발된 모형은 1) Katz와 Kahn의 조직에 대한 개방체계 이론(open systems theory of organization) ; 2) Kahn. Wolfe, Quinn, Snoek의 스트레스 이론 (theory of stress) : 3) Kohlberg의 도덕발달 이론(theory of moral develop-ment): 그리고 4) 여러 문헌고찰을 기초로 하였다. 본 연구의 모형은 2가지의 주요 종속변수(직무 스트레스, 윤리적 간호행위), 2가지 매개변수(간호 역할개념, 도덕성 발달정도) 그리고 여러 독립변수들(조직의 표준화, 자율성, 통제위, 교육, 나이, 경험 등)로 구성되었다. 간단히 말해, 간호사의 스트레스와 윤리적 간호행위 를 개인 자신과 환경이라는 두 요소의 결과로 간주한 것이다. 미국(2개주)의 여러 건강관리기관에 근무하는 224명의 정규 간호사를 대상으로 하였고. 가설 검증을 위하여 1) 변수간의 인과관계를 조사하기 위한 Linear Structural Relationships(LISREL)기법과 2) 나이, 경험, 교육이 변수간의 관계에 미치는 중간역할을 알아보기 위해 상관분석을 이용하였다. LISREL결과를 보면 제시된 모델이 각 내재 변수에 상당한 설명력을 가지면서 자료에 잘 맞는 것으로 나타났다. 이 연구에서 가장 뚜렷한 점으로 나타난 것은 개인의 특성보다 환경적 요소로서의 자율성이 직무스트레스와 윤리적 의사결정을 예견하는데 훨씬 중요한 변수로 부각되었다는 점이다. 또한 간호사의 전문적 역할개념과 봉사적 역할개념이 간호사의 윤리적 의사결정을 예견하는 가장 중요한 요소로 나타났다. 중간영향(moderation effect)을 보면, 젊고 경험이 적은 간호사일수록 나이가 많고 경험있는 간호사보다 환경적 요소(자율성)에 더 큰 영향을 받는다는 것을 암시하고 있다. 또한 4년제 대학 이상을 졸업한 간호사의 윤리 적 간호행 위 는 2, 3년제 를 졸업 한 간호사 보다 환경적 요소에 의해 덜 영향을 받는 것으로 나타났다. 한편 자율성의 부족은 2, 3년제 졸업 간호사보다 4년제 졸업 간호사에게 더 심한 스트레스가 되고 있음을 시사하였다. 이 연구의 결과로부터 적어도 다음과 같은 두 가지 실제적인 제언을 도출할 수 있다. 첫째, 이 연구는 환경적요소로서의 자율성이 다른 어떤 개인적인 요소보다 직무 스트레스를 예견하는 데 중요한 요소라는 것을 제시하였다. 이것은 간호행정가들에게, 간호사의 직무 스트레스를 감소시키기 위해선 “자율성”이 아주 중요히 다루어져야 한다는 것을 의미한다. 만일 간호사들의 직무스트레스가 그 개인의 복지에 큰 해가 되고 환자를 간호하는 데 직접적으로 관계된다면, 간호행정가는 그 조직의 직무체계를 다시 평가해서 일에 대한 새로운 설계가 필요한지를 파악해야 한다. 또한 이 연구는 직무를 다시 설계할 경우, 누구에게 먼저 촛점을 두고 시작해야 하는지를 밝혀주고 있다. 즉, 젊고 경험이 미숙한 간호사들에게 촛점을 두고 시작해야 하며, 작업환경의 가장 중요한 차원중의 하나인 사회적 지원(social support)을 조심스럽게 고려해 보아야 한다. 둘째, 간호사의 윤리적 간호행위를 높히기 위해 전문적 역할개념과 봉사적 역할개념이 재강조될 필요가 있다. 이 두 역할개념 들을 교육을 통하여 효과적으로 가르칠 필요가 있다고 본다. 이 두 개념들이 간호사의 바람직한 간호행 위에 영향을 미치는 가장 중요한 요소로 나타났기 때문이다. 또한, 본 연구결과에 따르면, 경험이 많을수록 일에 싫증을 느껴 바람직한 윤리적 간호행위가 감소되는 경향이 있었다. 따라서, 건강관리체제 (health care system) 안에서의 간호사의 역할이-전문직으로서의, 그리고 환자를 위한 옹호자로서의-학교와 임상에서 효과적으로 교육되어져야 한다고 본다. 간호사들의 역할에 대한 계속적인 교육이 학생은 물론 임상 간호사들에게도 실시되어져야 할 것이다. 미래연구의 방향을 제시해 보면 첫째로 연구의 일반화를 높히기 위해 더 많은 대상자를 포함시켜야 한다. 이는 여러 종류의 표본을 반드시 한번에 전부 포함시켜야 한다는 것을 의미하는 것이 아니고, 특정한 여러 표본들을 연속적으로 연구함으로서 이 목표를 성취할 수 있다고 생각한다. 둘째는 여러 construct들(윤리적 간호행위, 직무 스트레스, 간호 역할개념 등)에 대한 적절한 측정도구를 개발해야 한다. 측정도구를 개발하기 위해서는 풍부하고 세세한 통찰력을 제공하는 질적인 정보를 얻는 것이 선행되어야 한다. 셋째, 윤리적 간호행위와 직무 스트레스에 관한 연구를 증진시키기 위해 실험설계 및 종단적 연구(expel-imental, longitudinal design)가 시도될 필요가 있다. 마지막으로, 윤리적 간호행위와 직무 스트레스를 예견할 수 있는 이론적 탐구(theoretical exploration), 즉 이론정립을 위하여, 환경적 요소와 개인의 특성에 대한 자세한 정보를 제공해 줄 수 있는 질적 연구들이 요구된다.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.