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Job involvement can be linked with important work outcomes. One way for organizations to increase job involvement is to use machine learning technology to predict employees’ job involvement, so that their leaders of human resource (HR) management can take proactive measures or plan succession for preservation. This paper aims to develop a reliable job involvement prediction model using machine learning technique.

This study used the data set, which is available at International Business Machines (IBM) Watson Analytics in IBM community and applied a generalized linear model (GLM) including linear regression and binomial classification. This study essentially had two primary approaches. First, this paper intends to understand the role of variables in job involvement prediction modeling better. Second, the study seeks to evaluate the predictive performance of GLM including linear regression and binomial classification.

In these results, first, employees’ job involvement with a lot of individual factors can be predicted. Second, for each model, this model showed the outstanding predictive performance.

The pre-access and modeling methodology used in this paper can be viewed as a roadmap for the reader to follow the steps taken in this study and to apply procedures to identify the causes of many other HR management problems.

This paper is the first one to attempt to come up with the best-performing model for predicting job involvement based on a limited set of features including employees’ demographics using machine learning technique.

This study examines the influence of developer experience between human resource management (HRM) practices and innovation in software (S/W) engineering. This study uses motivation theory and investigates how HRM practices influence the innovative behaviors of S/W developers by using a mediator of affective developer experience.

For this, this study used a survey of S/W developers working in Korea. Out of 431 responses collected from 35 companies, 352 responses from 34 companies were usable for analysis and takes structural equation modeling.

The results show that developmental appraisal, externally or internally equitable reward and comprehensive training increase their affective developer experience affecting innovative behaviors positively in turn. However, selective staffing has no effect.

The results show that S/W developers pursue individual growth rather than success in their organizations. The findings show the context of S/W engineering in Korea and provide universalistic perspective when top managers motivate their S/W engineers by HRM system.

本研究擬探討開發經驗會如何影響人力資源管理方法與軟件工程創新之間的關聯。具體來說，本研究以動機理論，並利用情感的開發經驗作為中介者，去探討人力資源管理方法會如何影響軟件開發人員的創新行為。

研究人員調查於韓國工作的軟件開發者; 他們收集來自35間公司共431個回應，其中來自34間公司共352個回應可用來分析; 分析以結構方程模型進行。

研究結果顯示，發展評估、 外在或內在的公平獎勵和綜合培訓，均能增加情感的開發經驗，繼而反過來會正面地影響創新行為; 唯選擇性人員配置則沒有作用。

研究結果顯示軟件開發人員於其機構內所追求的是個人成長，而不是個人成就。研究結果說明了韓國軟件工程有關的情況，而且，若高層管理人員欲以人力資源管理系統激勵其軟件工程師，研究結果為此亦提供了一個普遍性的觀點。

This study systematically assesses and empirically examines the research question: How do social skills influence resource acquisition and social performance? Specifically, this study applies RBV theory from strategy to link social skills, resource conditions and the performance of social enterprises.

For this, we surveyed social enterprises in Korea to collect data and used SPSS 18.0 for hierarchical regression analysis.

In the Korean context, first, the results show that all social skills of social entrepreneurs are positively related to social performance. Second, among independent variables, self-promotion is positively associated with financial support and expressiveness is positively associated with marketing support. However, the rest of the independent variables have no significance. Finally, obtaining financial support from their partner mediates the relationship between self-promotion and social ventures' social performance, and obtaining marketing support from their partner mediates the relationship between expressiveness and social ventures' social performance.

This study provides two contributions. First, this is the first study to apply and test the RBV systematically and empirically in the context of social enterprises. Second, the results suggest that social skills and support types are important to social value creation.

Based on the conservation of resource theory, this study aims to develop and test the relationship between workplace technostress and affective organizational commitment. It assumes that the direct relationship between workplace technostress and affective organizational commitment is moderated by perceived organizational support.

For this, this study used a survey method and multiple regression analyses with multisource data from 257 Korean employees.

The results suggest the following. First, workplace technostress was negatively associated with affective organizational commitment fully. Second, there was a stronger negative relationship between workplace technostress and affective organizational commitment for employees with low as opposed to those with high levels of leader–member exchange.

This study provides practical implications that are directly related to the performance management of employees under technostress.

To the best of the authors’ knowledge, this study is the first one to examine the moderating effect of leader–member exchange on the relationship between technostress and affective organizational commitment.

Based on the cognitive appraisal theory, the current research extended the content domain of sexual harassment research by examining the moderating effect of power distance orientation, a cultural value on the relationship between sexual harassment and organizational behavior.

For this, this study used a survey method and multiple regression analyses with 285 Korean employees.

As a result, first, the more unwanted sexual attention employees perceived from their leaders, the less likely they were to be affectively committed to their organization. Second, the more sexual coercion employees perceived from their leaders, the more likely they were to have turnover intention. Third, the negative relationship between unwanted sexual attention and affective commitment is stronger for the employees who are low rather than high in power distance orientation. Finally, the positive relationship between sexual coercion and turnover intention is stronger for the employees who are low rather than high in power distance orientation.

The study expanded the content area of sexual harassment research by showing the control effect of the power distance direction.

Based on the conservation of resources theory, this study aims to develop and test the relationship between workplace ostracism and the work-to-family conflict of a female employee. And, it assumes that the direct link between workplace ostracism and the work-to-family conflict of a female employee is moderated by perceived organizational support.

For this, this study used a survey method and multiple regression analyses with multi-source data from 226 Korean female employees.

The results suggest the following. First, workplace ostracism was positively associated with the work-to-family conflict of a female employee. Second, there was a stronger positive relationship between workplace ostracism and work-to-family conflict for female employees with low as opposed to those with high levels of perceived organizational support.

To the best of author’s knowledge, this study is the first one to examine the moderating effect of perceived organizational support on the relationship between workplace ostracism and the work-to-family conflict of a female employee.

This study aims to reveal the role of artificial intelligence (AI) in the context of a front-line service meeting to understand how users accept AI technology-enabled service.

This study collected 454 Korean employees through online survey methods and used hierarchical regression to test the hypothesis empirically.

In the results, first, clarity of user and AI's roles, user's motivation to adopt AI-based technology and user's ability in the context of the adoption of AI-based technology increases their willingness to accept AI technology. Second, privacy concerns related to the use of AI-based technology weakens the relationship between role clarity and user's willingness to accept AI technology. And, trust related to the use of AI-based technology strengthens the relationship between ability and user's willingness to accept AI technology.

This study is the first one to reveal the role of AI in the context of a front-line service meeting to understand how users accept AI technology-enabled service.

本研究旨在顯示在前線服務會議的情況下人工智能所扮演的角色，以便了解使用者如何接受人工智能科技化服務。

研究以網上問卷調查方式取得454名韓國僱員的數據，並使用層次迴歸分析，對假設進行以經驗為依據的測試。

研究結果首先顯示、增強使用者願意接受人工智能科技的因素包括使用者與人工智能兩者角色的清晰度、使用者使用基於人工智能的科技的積極性、以及在應用基於人工智能科技的情況下使用者的能力。其次，與使用基於人工智能的科技有關的私隱問題會削弱角色清晰度與使用者是否願意接受人工智能科技之間的關係。而且，對使用基於人工智能的科技的信任會強化有關的能力與使用者是否樂意使用基於人工智能的科技之間的關係。

這是首個研究、去顯示在前線服務會議的情況下人工智能所扮演的角色，以便了解使用者如何接受人工智能科技化服務。

Based on the conservation of resources theory, the purpose of this paper is to develop and test the relationship between workplace ostracism and psychological distress of male employees. And depending on the leader member exchange (LMX) theory, it assumes that the relationship between workplace ostracism and psychological distress of male employees is moderated by the LMX.

For this, this study used a survey method and multiple regression analyses with multi-source data from 226 male Korean employees and their supervisors.

The results suggest the following. First, workplace ostracism was positively associated with job tension, emotional exhaustion and depressed moods at work for male employees. Second, there was a stronger positive relationship between workplace ostracism and job tension, or emotional exhaustion for male employees with low, as opposed to those with high, levels of LMX.

This study is the first one to examine the moderating effect of LMX on the relationship between workplace ostracism and psychological distress of male employees.

Based on the conservation of resource theory, this study developed and tested the relationship between workplace ostracism and job performance. And it assumes that the direct link between workplace ostracism and supervisor-rated in-role performance/organizational citizenship behavior is moderated by perceived organizational support.

For this, this study used a survey method and multiple regression analyses with multisource data from 256 Korean employees and their supervisors.

The results suggest the following. First, workplace ostracism was negatively associated with supervisor-rated in-role performance and organizational citizenship behaviors. Second, there was a stronger negative relationship between workplace ostracism and supervisor-rated in-role performance/organizational citizenship behaviors for employees with low as opposed to those with high levels of perceived organizational support.

This study is the first one to examine the moderating effect of perceived organizational support on the relationship between workplace ostracism and supervisor-rated in-role performance/organizational citizenship behavior.

以資源守恆論為基礎，本研究發展並測試了工作場所排斥與工作表現的關係。本研究假設感知組織支持會緩和工作場所排斥與主管評價的角色中的表現／組織公民行為之間的直接聯繫。

就此而言，本研究採用了調查方法及多元回歸分析法。多源數據取自256名韓國人僱員及其主管。

研究結果有以下的顯示：第一、工作場所排斥與主管評價的角色中的表現及組織公民行為有負相關的關係。第二、就工作場所排斥與主管評價的角色中的表現／組織公民行為的反向關連的關係而言，感知組織支持水平低的僱員，相對於水平高的僱員，呈現更強的負相關。

這是首個研究、去探討感知組識支持在工作場所排斥與主管評價的角色中的表現／組織公民行為間之關係上所起的調節作用。﹞

Despite ongoing reports of insider-driven leakage of confidential data, both academic scholars and practitioners tend to focus on external threats and favour information technology (IT)-centric solutions to secure and strengthen their information security ecosystem. Unfortunately, they pay little attention to human resource management (HRM) solutions. This paper aims to address this gap and proposes an actionable human resource (HR)-centric and artificial intelligence (AI)-driven framework.

The paper highlights the dangers posed by insider threats and presents key findings from a Leximancer-based analysis of a rapid literature review on the role, nature and contribution of HRM for information security, especially in addressing insider threats. The study also discusses the limitations of these solutions and proposes an HR-in-the-loop model, driven by AI and machine learning to mitigate these limitations.

The paper argues that AI promises to offer many HRM-centric opportunities to fortify the information security architecture if used strategically and intelligently. The HR-in-the-loop model can ensure that the human factors are considered when designing information security solutions. By combining AI and machine learning with human expertise, this model can provide an effective and comprehensive approach to addressing insider threats.

The paper fills the research gap on the critical role of HR in securing and strengthening information security. It makes further contribution in identifying the limitations of HRM solutions in info security and how AI and machine learning can be leveraged to address these limitations to some extent.