Young-myeong Kim
Sungkyunkwan University · Business, Management and Accounting
About the Lab
Professor Young-myeong Kim's research lab focuses on the intersection of human resource management, organizational behavior, and emerging technologies, particularly artificial intelligence in the workplace. The lab investigates how strategic HR practices—such as staffing, training, and performance evaluation systems—affect firm performance and employee outcomes under varying economic and competitive conditions. It also explores the psychological and social dynamics of workplace phenomena, including gossip, power, and perceptions of algorithmic fairness. Additionally, the lab examines cross-cultural differences in human-AI interaction, especially in the context of autonomous vehicles and AI agent design.
Research Overview
Research Output Trend
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Selected Papers
15This study integrates research from strategy, economics, and applied psychology to examine how organizations may leverage their human resources to enhance firm performance and competitive advantage. Staffing and training are key human resource management practices used to achieve firm performance through acquiring and developing human capital resources. However, little research has examined whether and why staffing and training influence firm-level financial performance (profit) growth under dif
The expectation that selection practices contribute to organizational performance has been long assumed; however, research on personnel selection has neglected to consider why firms differ in their use of selection practices and whether selection practices relate to organizational performance under different competitive environments. Based on strategic human resource management research, we introduce contingency theory to examine whether external (industry characteristics) and internal (prior fi
Although workplace gossip is ubiquitous, more scholarship is needed to determine how employees may use gossip to attain valuable social resources at work—namely, their experience of power. Drawing from the gossip literature and research on power in the workplace, we identify proximal (i.e., increased power accrual) and distal (i.e., diminished voluntary turnover) positive outcomes for employees enacting negative and positive gossip about the organization at work. Using a sample of 338 nurses, we
As firms increasingly depend on artificial intelligence to evaluate people across various contexts (e.g., job interviews, performance reviews), research has explored the specific impact of algorithmic evaluations in the workplace. In particular, the extant body of work focuses on the possibility that employees may perceive biases from algorithmic evaluations. We show that although perceptions of biases are indeed a notable outcome of AI-driven assessments (vs. those performed by humans), a cruci
Abstract Prior studies have suggested that downsizing events can lead to a contagion of voluntary turnover among employees. In the current study, drawing on the turnover event theory, we propose that the relationship between downsizing and turnover can be nonlinear. We also propose that the presence of collective pay‐for‐performance (PFP) practices is an important but overlooked contingency that moderates the effects of downsizing. By analyzing a dataset collected from 317 firms with 634 firm‐ye
We analyzed international differences in preferences related to the two dimensional (2D) versus three dimensional (3D) and male versus female external appearance of artificial intelligence (AI) agents for use in self-driving automobiles. We recruited 823 participants in five countries (South Korea, United States, China, Russia, and Brazil), who completed a survey. South Korean, Chinese, and North American respondents preferred a 2D appearance of the AI agent, which appears to result from the rel
In this paper, we investigate and analyze the expected per-node throughput in a wireless sensor network under a randomized sleep scheduling framework with a connectivity constraint. The unique optimal sleep probability maximizing the per-node throughput in the network is found. A sleep probability range in which the throughput monotonically increases along the sleep probability does exist, and it becomes a large portion of the total range when a network is heavy-traffic. This finding contradicts
This paper shows what kind of influence the learning motivation factors have on the effectiveness of Flipped Learning Model through the case of operating a JAVA programming subject. The Flipped Learning Approach consisting of Before Class, Before or At Start of Class, and In Class provides the students with learning motivation as well as satisfies Keller's ARCS(Attention, Relevance, Confidence, Satisfaction) to keep them studying steadily. This research conducts the operation of Flipped Learning
Research Areas
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