• Journal of Venture Innovation
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• v.6 no.3
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• pp.185-202
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• 2023

The COVID-19 pandemic catalyzed major changes in our work environment, underscoring the critical role of workplace flexibility. While a wealth of research exists on specific flexible work strategies and schedules, a broader understanding of workplace flexibility has been somewhat overlooked. This study aimed to bridge this gap by examining the correlation between workplace flexibility and organizational commitment. Our sample consisted of 300 employees from foreign businesses in the ICT(information and communications technology) service sector and the manufacturing industry, along with those from the top 50 leading Korean enterprises. We bifurcated workplace flexibility into two distinct categories for this study: quantitative and qualitative. Our results revealed that within the quantitative category, the flexibility of continuity of work and flexible place significantly enhanced organizational commitment. Interestingly, the flexibility of work schedules didn't have a marked impact on commitment levels. On the qualitative side, job autonomy and teamwork emerged as significant drivers of organizational commitment. It's worth noting that qualitative aspects of workplace flexibility had a more pronounced effect on organizational commitment than the quantitative elements. These findings highlight the necessity of approaching workplace flexibility from a comprehensive perspective, embracing both its quantitative and qualitative dimensions. For businesses aiming to maximize the benefits of flexibility, it's essential to cultivate a culture of open communication, champion collaboration, and prioritize job autonomy and teamwork. Establishing a work environment that actively supports feedback-oriented communication stands as a key component in this endeavor.

• Knowledge Management Research
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• v.24 no.3
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• pp.149-172
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• 2023

With the development of information technology, new technologies to be introduced in each industry are continuously increasing. This study aims to verify the influence of ambivalent emotions experienced when encountering new technologies, the coping strategies they induce, and their impact on the decision-making process of technology adoption Specifically, this research investigates the emotions and responses to new technologies in the situational context where service providers must deliver services based on new technology in environments where no such services have been developed previously. Furthermore, it seeks to verify the influence of coping responses on the intention to use services based on new technologies. To this end, this study investigated the ambivalent emotions and coping responses of financial sector workers to new financial services based on metaverse technology. As a result of the analysis ambivalance had a significant effect on all four coping responses (disengagement-oriented coping, denial, indecision and compromise). Among them, denial, which is an inflexible response, and compromise, which is a flexible response, had a significant positive effect on the intention to use, and disengagement-oriented coping and indecision had a significant negative effect on the intention to use. The results of this study confirm the user's metaverse acceptance factor and user-centered influence, and are expected to provide guidelines for the introduction of services to practical workers with academic significance.

• Journal of the Korea Institute of Building Construction
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• v.23 no.6
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• pp.785-796
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• 2023

The adoption of Environmental, Social, and Governance(ESG) practices in domestic construction firms is predominantly driven by major corporations. These companies not only publish reports on their ESG management but also engage in a meticulous process of identifying key issues and setting priorities. This process entails an in-depth evaluation of the severity of various issues and the gathering of insights from experts in the field. Interestingly, a comparative analysis of ESG assessments for construction companies, both domestically and internationally, reveals significant discrepancies in outcomes. These differences stem from the varied evaluation methodologies and criteria employed by different assessing bodies. Addressing this gap, our study proposes a suite of strategies aimed at bolstering ESG management within the construction sector. We advocate for enhanced policy support and financial backing, especially targeting small and medium-sized enterprises(SMEs) to facilitate their engagement in ESG practices. A critical step forward involves the standardization and transparent disclosure of ESG evaluation criteria, tailored to reflect the unique aspects of the construction industry. Moreover, the standardization and publication of ESG assessments for subcontractors are essential, equipping them with the necessary tools for effective ESG management and evaluation. Given the global nature of construction projects, particularly those commissioned by the European Union in regions like Africa and East Asia, adherence to ESG standards is imperative. Our long-term vision includes the development of a comprehensive database detailing ESG regulations and their impacts, segmented by region and country. This repository will serve as a valuable resource for companies venturing into international construction projects.

• Journal of the Korean Applied Science and Technology
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• v.40 no.6
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• pp.1567-1579
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• 2023

Sucralose is used as a sucrose alternative in the food sector and is a globally approved pyrogenic, high-intensity artificial sweetener. However, due to the lack of studies on the effects of sweeteners on the brain, this study confirmed whether short-term consumption of sucralose has cognitive and memory protective effects in scopolamine-induced memory-injured animal models. After oral administration of sucralose 2, 5, and 10 mg/kg, scopolamine (1 mg/kg) was administered to the control group and the drug group 30 minutes later, and saline was administered intraperitoneally to the normal group, followed by behavioral experiments As a result of the experiment, Y-Maze, passive avoidance, and Morris WaterMaze recovered more than 10% of cognitive function compared to the control group. In addition, as a result of measuring proinflammatory cytokines, sucralose was found to inhibit IL-6 and TNF-α by more than 30%, and we observed that the expression level of ERK-CREB with intracellular signaling mechanisms increased in a concentration-dependent manner. Therefore, it suggests that sucralose is associated with functional foods for the prevention of functional food patients.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.97-108
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• 2024

This research delves into the escalating concerns of accidents and fatalities in the construction industry over the recent five-year period, focusing on the development of a Safety Perception Model to augment safety measures. Given the rising percentage of elderly workers and the concurrent drop in productivity within the sector, there is a pronounced need for leveraging Fourth Industrial Revolution technologies to bolster safety protocols. The study comprises an in-depth analysis of statistical data regarding construction-related fatalities, aiming to shed light on prevailing safety challenges. Central to this investigation is the formulation of a Safety Perception Model tailored for small-scale construction projects. This model facilitates the quantification of safety risks by evaluating safety grades across construction sites. Utilizing the DWM1000 module, among an array of wireless communication technologies, the model enables the real-time tracking of worker locations and the assessment of safety levels on-site. Furthermore, the deployment of a safety management system allows for the evaluation of risk levels associated with individual workers. Aggregating these data points, the Safety Climate Index(SCLI) is calculated to depict the daily, weekly, and monthly safety climate of the site, thereby offering insights into the effectiveness of implemented safety measures and identifying areas for continuous improvement. This study is anticipated to significantly contribute to the systematic enhancement of safety and the prevention of accidents on construction sites, fostering an environment of improved productivity and strengthened safety culture through the application of the Safety Perception Model.

• Industry Promotion Research
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• v.9 no.1
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• pp.39-45
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• 2024

Dangerous tasks that occur every day at industrial site manufacturing plants, which have recently been making rapid changes, were classified by type, and the effect of mobile circuit television (CCTV) on safety accidents among daily safety management methods was analyzed. The subject of the study is about 3,000 workers who manage the infrastructure facility sector to supply utilities such as gas, water, and electricity to the display manufacturing process located in Asan City, and the study was conducted based on the daily dangerous work from 2019 to 2022, and during this study period, many construction works such as new investment and expansion of construction and manufacturing processes were occurring at the site. As a result, the rate of safety accidents and exposure to risks are expanding, and most of the safety accidents occurred because the sectors that did not follow the basics and the safety measures on the site were not implemented. In this paper, it was confirmed that there is an accident reduction effect according to the relationship between the dangerous work classified according to the work importance and the mobile CCTV shooting rate. Considering the characteristics of the manufacturing plant site, it can be used to play the role of basic data for preventing safety accidents based on the expansion of the introduction of a new safety management culture in the future.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.135-144
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• 2024

In this study, we propose an automatic classification model for quantitative multidimensional analysis based on facet theory to understand public opinions and demands on major issues through big data analysis. Civil complaints, as a form of public feedback, are generated by various individuals on multiple topics repeatedly and continuously in real-time, which can be challenging for officials to read and analyze efficiently. Specifically, our research introduces a new classification framework that utilizes facet theory and political analysis models to analyze the characteristics of citizen complaints and apply them to the policy-making process. Furthermore, to reduce administrative tasks related to complaint analysis and processing and to facilitate citizen policy participation, we employ deep learning to automatically extract and classify attributes based on the facet analysis framework. The results of this study are expected to provide important insights into understanding and analyzing the characteristics of big data related to citizen complaints, which can pave the way for future research in various fields beyond the public sector, such as education, industry, and healthcare, for quantifying unstructured data and utilizing multidimensional analysis. In practical terms, improving the processing system for large-scale electronic complaints and automation through deep learning can enhance the efficiency and responsiveness of complaint handling, and this approach can also be applied to text data processing in other fields.

• Information Systems Review
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• v.19 no.3
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• pp.127-154
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• 2017

This study aims to identify various service innovation patterns in the service industry and understand the main differences among them. We attempt to create a new typology of service innovation by analyzing its patterns based on the four major dimensions of service innovation (i.e., service concept, service delivery, customer interaction, and technology). We then investigate whether firms pursuing different service innovation patterns significantly differ from one another in terms of their performance (high and low performance). Based on empirical data collected from 198 Korean firms in the knowledge-intensive business service sector, four major clusters composed of different service innovation dimensions are identified. These four clusters can be interpreted as specific service innovation patterns, including "technology based high customer interaction," "high technology based high service delivery," "service delivery and high customer interaction-integrated," and "strongly balanced" innovators. High firm performance does not depend on the individual service innovation dimension but on the specific configurations of such service dimensions. Customer interaction also has an important role in achieving innovation success and improving firm performance, while technology has a key role in enhancing firm performance. This study sheds new light on service innovation research by developing a new typology of service innovation, identifying four major clusters as service innovation patterns, and exploring the relationship between service innovation patterns and firm performance.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.3
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• pp.48-66
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• 2024

According to the three amended Laws of the Data Economy and the Data Industry Act of Korea, systems for pseudonymous data integration and Data Safe Zones have been operated separately by selected agencies, eventually causing a burden of use in SMEs, startups, and general users because of complicated and ineffective procedures. An over-stringent pseudonymization policy to prevent data breaches has also compromised data quality. Such trials should be improved to ensure the convenience of use and data quality. This paper proposes a prototype system of the Integrated Data Safe Zone based on redesigned and optimized pseudonymization workflows. Conventional workflows of pseudonymization were redesigned by applying the amended guidelines and selectively revising existing guidelines for business process redesign. The proposed prototype has been shown quantitatively to outperform the conventional one: 6-fold increase in time efficiency, 1.28-fold in cost reduction, and 1.3-fold improvement in data quality.

• Journal of Intelligence and Information Systems
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• v.27 no.2
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• pp.33-54
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• 2021

With the fourth industrial revolution and the arrival of the New Normal era due to Corona, the importance of Non-contact technologies such as artificial intelligence and big data research has been increasing. Convergent research is being conducted in earnest to keep up with these research trends, but not many studies have been conducted in the area of nuclear research using artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. This study was conducted to confirm the applicability of data science analysis techniques to the field of nuclear research. Furthermore, the study of identifying trends in nuclear spent fuel recognition is critical in terms of being able to determine directions to nuclear industry policies and respond in advance to changes in industrial policies. For those reasons, this study conducted a media trend analysis of pyroprocessing, a spent nuclear fuel treatment technology. We objectively analyze changes in media perception of spent nuclear fuel dry treatment techniques by applying text mining analysis techniques. Text data specializing in Naver's web news articles, including the keywords "Pyroprocessing" and "Sodium Cooled Reactor," were collected through Python code to identify changes in perception over time. The analysis period was set from 2007 to 2020, when the first article was published, and detailed and multi-layered analysis of text data was carried out through analysis methods such as word cloud writing based on frequency analysis, TF-IDF and degree centrality calculation. Analysis of the frequency of the keyword showed that there was a change in media perception of spent nuclear fuel dry treatment technology in the mid-2010s, which was influenced by the Gyeongju earthquake in 2016 and the implementation of the new government's energy conversion policy in 2017. Therefore, trend analysis was conducted based on the corresponding time period, and word frequency analysis, TF-IDF, degree centrality values, and semantic network graphs were derived. Studies show that before the 2010s, media perception of spent nuclear fuel dry treatment technology was diplomatic and positive. However, over time, the frequency of keywords such as "safety", "reexamination", "disposal", and "disassembly" has increased, indicating that the sustainability of spent nuclear fuel dry treatment technology is being seriously considered. It was confirmed that social awareness also changed as spent nuclear fuel dry treatment technology, which was recognized as a political and diplomatic technology, became ambiguous due to changes in domestic policy. This means that domestic policy changes such as nuclear power policy have a greater impact on media perceptions than issues of "spent nuclear fuel processing technology" itself. This seems to be because nuclear policy is a socially more discussed and public-friendly topic than spent nuclear fuel. Therefore, in order to improve social awareness of spent nuclear fuel processing technology, it would be necessary to provide sufficient information about this, and linking it to nuclear policy issues would also be a good idea. In addition, the study highlighted the importance of social science research in nuclear power. It is necessary to apply the social sciences sector widely to the nuclear engineering sector, and considering national policy changes, we could confirm that the nuclear industry would be sustainable. However, this study has limitations that it has applied big data analysis methods only to detailed research areas such as "Pyroprocessing," a spent nuclear fuel dry processing technology. Furthermore, there was no clear basis for the cause of the change in social perception, and only news articles were analyzed to determine social perception. Considering future comments, it is expected that more reliable results will be produced and efficiently used in the field of nuclear policy research if a media trend analysis study on nuclear power is conducted. Recently, the development of uncontact-related technologies such as artificial intelligence and big data research is accelerating in the wake of the recent arrival of the New Normal era caused by corona. Convergence research is being conducted in earnest in various research fields to follow these research trends, but not many studies have been conducted in the nuclear field with artificial intelligence and big data-related technologies such as natural language processing and text mining analysis. The academic significance of this study is that it was possible to confirm the applicability of data science analysis technology in the field of nuclear research. Furthermore, due to the impact of current government energy policies such as nuclear power plant reductions, re-evaluation of spent fuel treatment technology research is undertaken, and key keyword analysis in the field can contribute to future research orientation. It is important to consider the views of others outside, not just the safety technology and engineering integrity of nuclear power, and further reconsider whether it is appropriate to discuss nuclear engineering technology internally. In addition, if multidisciplinary research on nuclear power is carried out, reasonable alternatives can be prepared to maintain the nuclear industry.