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Author: 雲光榮
Kritsapas Kanjanamekanant
Thesis Title: 協同機器人流程自動化: 機器人流程自動化利用率對持續使用與工作倦怠的貢獻
Co-working with Robotic Process Automation: How RPA utilization contributes to continuance and burnout
Advisor: 朱宇倩
Yu-Qian Zhu
Committee: 謝俊霖
Choon-Ling Sia
許書瑋
Shu-Wei Hsu
柯冠州
Kuan-Chou Ko
邱議德
Yi-te Chiu
Degree: 博士
Doctor
Department: 管理學院 - 資訊管理系
Department of Information Management
Thesis Publication Year: 2022
Graduation Academic Year: 110
Language: 英文
Pages: 123
Keywords (in Chinese): 機器人流程自動化RPA人工智慧AI倦怠持續使用
Keywords (in other languages): Robotic Process Automation, RPA, artificial intelligence, AI, burnout, continuance intention
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Robotic Process Automation (RPA) is a novel technology that drastically improves the efficiency and accuracy of work by using software robots to perform tasks, with or without human interactions, without tiredness and fatigue but delivers 100% accuracy. RPA is a software robot that uses a user-predefined algorithm to process work inputs and produces desired work outputs, and does not require prior IT knowledge. Unlike most other IT software, it also has the function to imitate human interactions with the computer i.e., working in the foreground resembling a human user, thus provides a good backward compatibility with the organization’s existing or legacy IT infrastructure.

This study is the first to investigate how RPA implementation changes the evaluations of its users, by conducting an online survey to the RPA users that are working in various industries in Thailand. Based on the reasoning of motivation and job demand-job resource balance, the proposed research model identifies the positive side (job autonomy, RPA performance) and negative side (intensified learning demand, intensified planning and decision-making demand, and work intensification) of RPA implementation, and their consequences - burnout and RPA continuance intention. Further, the current study distinguishes the usage of RPA into RPA usage breadth and RPA usage depth, to explore the mechanisms of how RPA utilization affect the users in more detail. The results indicated an interesting finding that the degree of RPA usage breadth and RPA usage depth have different impact on the cognitions of the RPA users. Several moderators are discussed, and the model explains about 67% of continuance intention and 28% of burnout variances, accordingly. A suggestion on how to report the results from a PLS-SEM is also discussed.

Last, of theoretical implications, managerial implications, and avenues for future research are discussed in the final section of this research. RPA is a new and unresearched aspect of IS, but it has the potential to overturn the way we previously work due to its limitless potentials. The findings from this research signify the need for further investigation of this avant-garde technology.


Robotic Process Automation (RPA) is a novel technology that drastically improves the efficiency and accuracy of work by using software robots to perform tasks, with or without human interactions, without tiredness and fatigue but delivers 100% accuracy. RPA is a software robot that uses a user-predefined algorithm to process work inputs and produces desired work outputs, and does not require prior IT knowledge. Unlike most other IT software, it also has the function to imitate human interactions with the computer i.e., working in the foreground resembling a human user, thus provides a good backward compatibility with the organization’s existing or legacy IT infrastructure.

This study is the first to investigate how RPA implementation changes the evaluations of its users, by conducting an online survey to the RPA users that are working in various industries in Thailand. Based on the reasoning of motivation and job demand-job resource balance, the proposed research model identifies the positive side (job autonomy, RPA performance) and negative side (intensified learning demand, intensified planning and decision-making demand, and work intensification) of RPA implementation, and their consequences - burnout and RPA continuance intention. Further, the current study distinguishes the usage of RPA into RPA usage breadth and RPA usage depth, to explore the mechanisms of how RPA utilization affect the users in more detail. The results indicated an interesting finding that the degree of RPA usage breadth and RPA usage depth have different impact on the cognitions of the RPA users. Several moderators are discussed, and the model explains about 67% of continuance intention and 28% of burnout variances, accordingly. A suggestion on how to report the results from a PLS-SEM is also discussed.

Last, of theoretical implications, managerial implications, and avenues for future research are discussed in the final section of this research. RPA is a new and unresearched aspect of IS, but it has the potential to overturn the way we previously work due to its limitless potentials. The findings from this research signify the need for further investigation of this avant-garde technology.

Chapter 1 – Introduction 1 1.1 Research context 1 1.2 Co-working with artificial intelligence 5 1.3 Research motivation and objective 8 1.4 Related literature 11 1.5 Outline 12 Chapter 2 – Literature Review 13 2.1 Co-working with technologies 13 2.2 Extant empirical research on RPA 18 2.3 Theories used in explaining IS usage and IS impact to individuals 20 2.4 How a new change at the organization affects an individual 24 Chapter 3 – Theoretical Framework and Hypothesis 26 3.1 Proposed framework 27 3.2 Hypothesis development 31 Chapter 4 – Research Methodology 44 4.1 Procedures and participants 44 4.2 Measurement items 46 4.3 Modelling technique 47 Chapter 5 – Results and Data Analysis 50 5.1 Model analysis 50 5.2 Common method variance 53 5.3 Structural model assessment 53 5.4 Moderation analysis 56 5.5 Post-hoc analysis 59 5.5.1 Descriptive comparisons 59 5.5.2 Other possible moderators 60 5.5.3 Comparing PLS-SEM results with multiple linear regression results 63 5.5.4 Mediated moderation of the model 64 Chapter 6 – Conclusions and Recommendations 66 6.1 Theoretical implications 68 6.2 Managerial implications 71 6.3 Limitation and future research 74 Appendix A – Measurement items 78 Appendix B – Bibliographical database list 81 Reference 82

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