As platforms become primary decision making tools, platforms for decision have been introduced to improve quality of decision results. Because, decision platforms applied augmented decision-making process which uses experiences and feedback of users. This process creates a variety of alternatives tailored for users’ abilities and characteristics. However, platform users choose alternatives before considering significant quality factors based on securing decision quality. In real world, platform managers use an algorithm that distorts appropriate alternatives for their commercial benefits. For improving quality of decision-making, preceding researches approach trying to increase rational decision -making ability based on experiences and feedback. In order to overcome bounded rationality, users interact with the machine to approach the optional situation. Differentiated from previous studies, our study focused more on characteristics of users while they use decision platforms. This study investigated the impact of quality factors on decision-making using platforms, the dimensions of systematic factors and user characteristics. Systematic factors such as platform reliability, data quality, and user characteristics such as user abilities and biases were selected, and measuring variables which trust, satisfaction, and loyalty of decision platforms were selected. Based on these quality factors, a structural equation research model was created. A survey was conducted with 391 participants using a 7-point Likert scale. The hypothesis that quality factors affect trust was proved to be valid through path analysis of the structural equation model. The key findings indicate that platform reliability, data quality, user abilities, and biases affect the trust, satisfaction and loyalty. Among the quality factors, group bias of users affects significantly trust of decision platforms. We suggest that quality factors of decision platform consist of experience-based and feedback-based decision-making with the platform's network effect. Through this study, the theories of decision-making are empirically tested and the academic scope of platform-based decision-making has been further developed.

There has been a steady rate of accident in Coal Thermal Power Plants which have relatively higher chance of mortality. However, neither the systematic view of safety management nor the methodology such as safety factors or system requirements are yet to be studied in detail. Therefore, this study aims to propose a methodology to preemptively deal with safety issues and to secure fact focused responsibility in safety. It consists of two main parts. First, the Safety Measurement Index(SMI) with total 50 factors is proposed by analyzing the key factors that contribute to safety accidents based on failure mode and effect analysis (FMEA) and quality function deployment (QFD). To analyze the safety requirements, index presented by major countries and organizations are discussed. Second, main features of intelligent CCTV are studied to determine their relative importance for the framework of Smart Safety Management System (SSMS). Main features are discussed with four technological steps. Also, QFD was held to analyze to analyze how key technologies deal with Quality Measurement Index(QMI). The research results of this study reveal that scientific approaches could be utilized in integrating CCTV technologies into a smart safety management system in the era of Industry 4.0. Moreover, this reasearch provides an specific approach or methodology for dealing with safety management in Coal Thermal Power Plant.

Competitiveness of small and medium companies often rely on the competency of their employees. Many employees however try to move to better environments if possible, which results in high uncertainty in maintaining solid human resources. The purpose of this paper is to investigate the influencing factors of turnover intention and organizational loyalty of the early experienced, especially three to five years experienced, employees in the small and medium enterprises. A survey had been conducted using both LMX (Leader Member eXchange) and TMX (Team Member eXchange) as an effort to test the impact of strategic human resource management factors on turnover intension and organizational loyalty. It has been observed that the level of LMX is critical on the turnover intension, while the levels of LMX and TMX are positively related to the organizational loyalty. Especially significant mediation effect affects on the organizational loyalty for TMX via LMX in the serial structure. The human resource management factors become effective under the circumstances where leader and team members exchange activities are activated. These findings can be used in reducing turnover intention and increasing organizational loyalty of early experienced employees by enhancing the leadership training of middle level managers of the small and medium enterprises organizations. Besides, a set of active communication channels should be provided for the young employees so that they can share their work experiences and difficulties within the organization. The key results of this study may help the practitioners set up a management plan to maintain a low turnover rate for their organizations.

The enterprise life cycle derived from the product life cycle consists of introduction, growth, maturity and decline. The enterprise tries to reach the growth stage early and stay at the maturity stage stably through expanding its businesses and investing for the new technology. The public enterprise is not different but its life cycle is more prone to be affected by the national development and policy. A typical example can be found in the case of the quasi market SOC public enterprise which spends massive amount of fund to provide social infrastructure. After the fulfillment of its mandated mission it is exposed to the pressure of a merger or a closure usually because large portion of the debt is directly linked to the national financial stability and credit ratings. This research is focused on the variables that influence the life cycle of the quasi market SOC public Enterprise for its future competitiveness is in connection with its normalization, advancement and rationalization. In this respect, categorical variables system centering on public characteristics and profitability drew eight categorical variables such as policy outcomes, public benefit, finance and business values etc.

The purpose of this research is to identify and develop technology protection plans for small and medium-sized enterprises (SMEs) by analyzing past technology leakage patterns which were experienced by SMEs. We identified factors which affect the technology leakage, and analyzed patterns of the influences using a data mining algorithms. A decision tree analysis showed several significant factors which lead to technology leakage, so we conclude that preemptive actions must be put in place for prevention. We expect that this research will contribute to determining the priority of activities necessary to prevent technology leakage accidents in Korean SMEs. We expect that this research will help SMEs to determine the priority of preemptive actions necessary to prevent technology leakage accidents within their respective companies.