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How Does Digital Shadow Work Affect User Emotion and Behavior in Self-service Technologies Use?

원문정보

Huimin Shi, Joon Koh

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초록

영어

During the Covid-19 pandemic, social distance regulation calls for non-contact services, making self-service technologies gain much more attention. However, customers found they are pushed into more digital shadow work by employing Self-service technologies (SSTs). This research aims to examine how digital shadow work influences user emotions and behaviors during SSTs use. Based on the grounded theory method (GTM), this draft drives 128 codes and 7 categories to develop the theory of digital shadow work. Operations, consisting of pre-use, during use, and after use, along with the cognitions, including the perception of use-value and time efficiency, act as the trigger of digital shadow work. Achievement emotions, embodying happiness and satisfaction from technology use, result from the perception of high use-value and high time efficiency, while loss emotions, encompassing anger and disappointment from the user experience, generate from the perception of low use-value and low time efficiency, and finally, user responses from the digital shadow work - quitting, continuous and alternative behaviors are found as key factors. The interventing roles of a sense of control, system features, and compensation are also addressed. Examining users’ psychological mechanisms academically contributes to developing the theory of digital shadow work whereas it advances the development of SSTs on a practical side.

목차

ABSTRACT
Ⅰ. Introduction
Ⅱ. Theoretical Background
2.1. Self-service Technologies
2.2. Shadow Work
2.3. Emotions in IT Use
Ⅲ. Research Design and Methodology
3.1. Grounded Theory Methodology
3.2. Research Design
Ⅳ. Data Collection
4.1. Preliminary Interview
4.2. Main Interview
4.3. Focus Group Interview
4.4. Data Coding
Ⅴ. Findings
5.1. Self-service Technology Adoption at AH and Jumbo
Ⅵ. Discussion and Conclusion
6.1. Discussion of Findings
6.2. Implications for Research and Practice
6.3. Study Limitations and Future Research Directions
Acknowledgements

저자정보

  • Huimin Shi Research Assistant, Peking University-Wuhan Institute for Artificial Intelligence, China
  • Joon Koh Professor, Department of Business Administration, Chonnam National University, Korea

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