







































 Humanities and Social Science Research; Vol. 8, No. 6; 2025 

ISSN 2576-3024   E-ISSN 2576-3032 

https://doi.org/10.30560/hssr.v8n6p24 

 24 Published by IDEAS SPREAD 

 

The Role of Digital Transformation in the Occupational Well-being of 

Online Technology Workers: An Integrated Theoretical Perspective 

Xiao Han1 & Ke Huang1 

1 School of Business, Qingdao University, China 

Correspondence: Xiao Han, School of Business, Qingdao University, Qingdao, China. E-mail: 

xiaohan@qdu.edu.cn 

 

Received: November 20, 2025; Accepted: December 4, 2025; Published: December 5, 2025 

 

Abstract 

With the rapid development and integration of new technologies in the context of the digital economy, the work 

patterns and skill requirements of online technology workers have undergone fundamental changes, exerting a 

complex and far-reaching impact on their occupational well-being. This paper takes online technology workers as 

the research object and uses Self-determination Theory (SDT) and Conservation of Resources Theory (COR) as 

an integrated framework to analyze the internal mechanisms by which digital technology transformation affects 

their well-being through a dual path of "empowerment" and "challenge." The study finds that, on the one hand, 

digital technology empowers workers by improving work efficiency, expanding capability boundaries, and 

optimizing collaboration abilities, thereby enhancing their well-being; on the other hand, the iteration of digital 

technology also triggers challenges such as skills obsolescence anxiety, blurred work-life boundaries, and 

perceived algorithmic control, thus weakening their well-being. Additionally, multi-level characteristics will 

moderate this influence process. This research provides theoretical basis and practical insights for improving the 

occupational well-being of online technology workers in the digital age. 

Keywords: Digital Transformation, Online Technology Workers, Occupational Well-being, Self-determination 

Theory, Conservation of Resources Theory 

1. Introduction 

Driven by the swift evolution of digital technology and profound changes in the global economy, the gig economy, 

as an emerging economic paradigm, is reshaping the labor market and work patterns with unprecedented depth 

and breadth (Flinchbaugh et al., 2020). In this transformation, online technology workers, as a professional group 

highly reliant on digital platforms for knowledge creation and technological innovation, have become the core 

human capital driving the development of the digital economy. This new work model not only provides flexibility 

and efficiency for businesses and individuals but also creates employment opportunities for tech talent globally 

that transcend geographical limitations (Wu & Huang, 2024). 

Technological evolution has always been a double-edged sword. With the continuous development of digital 

technology, online technology workers, while enjoying its numerous conveniences, also face big challenges. On 

the one hand, digital technology has given online technology workers a completely new way of working, greatly 

improving work efficiency and liberating them from repetitive or mechanical labor, allowing them to focus more 

on core value-added activities (Hui et al., 2024). For example, by using AI-assisted programming and data analysis 

and processing tools, workers can complete tasks more efficiently, driving rapid project progress, which greatly 

optimizes workflows and improves individual and team productivity. On the other hand, the rapid iteration of 

digital technology has also brought challenges. The fast pace of skill updates has triggered widespread anxiety 

about obsolescence and job insecurity (McGuinness et al., 2023). A 2024 survey titled "State of Developer 

Wellness" (Developer Nation, 2024) reported that 83% of developers experienced burnout at some stage in their 

careers. With the rapid development of technologies such as artificial intelligence and big data, traditional technical 

skills may become obsolete in a short period of time. Online technology workers must constantly invest significant 

time and energy in re-education and skill updates to remain competitive. This pressure of skill updates not only 

affects workers' career development but also negatively impacts their mental health, increasing uncertainty and 

anxiety at work. At the same time, while the introduction of algorithm management systems optimizes processes, 

it may also erode the work autonomy and sense of control of online technology workers through precise task 



hssr.ideasspread.org   Humanities and Social Science Research Vol. 8, No. 6; 2025 

 25 Published by IDEAS SPREAD 

 

allocation, continuous performance monitoring and automated decision-making, thereby threatening their intrinsic 

work motivation (Liu & Yin, 2024). 

Occupational well-being, as an individual's positive perception and emotional evaluation of the quality and 

meaning of their work, is an important indicator for measuring occupational health and sustainable development 

(Wright & Cropanzano, 2004). For online technology workers, a group of highly skilled individuals whose 

workstations are digital interfaces and whose main output is knowledge products, occupational well-being is not 

only related to their personal well-being but also directly affects their innovation efficiency, work quality, and 

career persistence (Tarafdar et al., 2024). When the level of well-being is high, they are more likely to proactively 

share and propose breakthrough solutions at work, continuously releasing cognitive resources; conversely, they 

are more likely to reduce work quality and frequently change jobs, which may lead to the loss of core knowledge 

within the company. 

However, existing research on technology and occupational well-being has significant limitations: First, most 

studies focus on macro-level organizational performance or meso-level process changes, paying insufficient 

attention to the psychological experiences of micro-level individuals, especially highly skilled online technology 

workers, under continuous technological shocks (Liu et al.); Secondly, the research perspective is relatively 

singular, mostly emphasizing the enabling effect of technology or criticizing its negative consequences, lacking 

an integrated theoretical framework to explain its coexisting "bright side" and "dark side" (Manfreda & Mijač, 

2024; Gao et al., 2025); Thirdly, there is a lack of in-depth mechanistic analysis on the special characteristics of 

online technology workers, such as their emphasis on a sense of technical mastery and the constraints imposed by 

platform algorithms (Mattern et al., 2024). 

To fill the aforementioned research gaps, this study focuses on the core group of online technology workers, 

attempting to move beyond a single theoretical perspective and construct a systematic analytical framework by 

integrating self-determination theory (SDT) and conservation of resources theory (COR). SDT theory reveals that 

the pursuit of three basic psychological needs—autonomy, competence, and relatedness—is the root of intrinsic 

motivation and well-being (Ryan & Deci, 2000), while COR theory explains the dynamic process by which 

individuals strive to acquire valuable resources (such as time, energy, and skills) and experience stress due to 

resource depletion or threats (Hobfoll, 2001). Digital technology operates on both levels simultaneously: it can act 

as an enabler of key resource and need fulfilment, but it can also become a source of challenges leading to resource 

depletion and demand obstacles. Based on this, this study constructs an integrated model of "technological change 

- psychological mechanisms - occupational well-being" to analyze how digital technology change has different 

impacts on the well-being of online technology workers through the dual paths of "empowerment" and "challenge". 

Also, this study proposes strategies to promote the well-being of online technology workers in the process of digital 

technology change from the individual and organizational levels. 

2. Theoretical Basis 

2.1 Self-Determination Theory 

Self-determination theory (SDT), proposed by Ryan and Deci (2000), is a macro-level theory about human 

motivation and personality development. Its core assumption is that individuals possess three innate, fundamental 

psychological needs crucial for mental health and well-being: autonomy, competence, and relatedness. Autonomy 

refers to an individual's desire to experience a sense of will and choice in their actions, feeling that their behavior 

stems from personal will rather than external pressure. In the work context, this manifests as a sense of control 

over the content, methods, and goals of their work (Deci & Ryan, 2000). Competence refers to an individual's 

desire to feel capable in their interactions with the environment, effectively addressing challenges and achieving 

expected results. For online technology workers, mastering and skillfully applying new technologies to solve 

complex problems is a key way to satisfy this sense of competence. Relatedness refers to an individual's desire to 

establish close emotional connections with others, feeling cared for and accepted, and belonging to a group. Even 

in remote work, maintaining meaningful connections with team members, colleagues, or users is an important 

source of occupational well-being for online technology workers (Van den Broeck et al., 2016). SDT theory posits 

that when the external environment supports the satisfaction of these three basic needs, an individual's intrinsic 

motivation, physical and mental vitality, and occupational well-being reach their optimal state; conversely, if the 

environment hinders the satisfaction of these needs, it leads to decreased motivation, increased alienation, and 

decreased well-being (Ryan & Deci, 2018). Therefore, SDT theory provides a core psychological mechanism 

explanation for how digital technology change affects the occupational well-being of online technology workers 

by influencing basic psychological needs. 

 



hssr.ideasspread.org   Humanities and Social Science Research Vol. 8, No. 6; 2025 

 26 Published by IDEAS SPREAD 

 

2.2 Conservation of Resources Theory  

Proposed by Hobfoll (1989), conservation of resources theory (COR) is primarily used to explain the psychological 

and behavioural responses of individuals when facing stress. The core idea of COR theory is that individuals have 

a tendency to strive to acquire, retain, and protect the resources they value. These resources include material 

resources, conditional resources, personal resources, and energy resources. According to conservation of resources 

theory, psychological stress arises when individuals face the threat of resource loss or fail to obtain the expected 

return after investing resources (Hobfoll, 2001). Applying this theory to the context of this study, digital technology 

itself can be viewed as an important instrumental resource, helping online technology workers complete tasks more 

efficiently and create new value. However, the process of learning and adapting to new technologies requires a 

significant investment of time, energy, and cognitive resources (Ahmed et al., 2022). If technological iteration is 

too rapid, leading to a rapid devaluation of existing skills, or if the platform's algorithmic management system 

over-monitors and depletes psychological energy, it can trigger stress and burnout, thereby impairing occupational 

well-being (Röttgen et al., 2024). COR theory provides a powerful theoretical perspective for understanding how 

digital technology, while acting as a channel for resource gain, can also become a source of resource depletion and 

ultimately affect occupational well-being. 

2.3 Theory Integration 

SDT theory and COR theory are not mutually exclusive; they jointly provide complementary perspectives for 

understanding the impact of digital technologies on the occupational well-being of online technology workers. 

Applying SDT theory alone may be overly optimistic, underestimating the systematic constraints and depletion in 

digital work environments. Conversely, applying COR theory alone may be overly pessimistic, overlooking 

individual agency and intrinsic motivation in pursuing meaning and growth. Therefore, a more explanatory 

analytical framework requires dynamically integrating both theories: the impact of digital technologies on online 

technology workers' well-being is achieved through a dual-pathway process—it shapes the quality of well-being 

by influencing the satisfaction of basic psychological needs (SDT), while also setting the energy baseline of well-

being by triggering resource gains (COR). Meanwhile, resources in COR theory can be viewed as enabling factors 

for need satisfaction in SDT theory. Adequate resources create space for individuals to pursue autonomy, 

competence, and relatedness; conversely, resource scarcity limits the possibility of need satisfaction. 

3. Mechanism Analysis 

The impact of digital technology change on the occupational well-being of online technology workers is not linear, 

but rather a complex mechanism achieved through two coexisting and intertwined paths of empowerment and 

challenge. Meanwhile, characteristics at individual, organizational, and platform levels will moderate this 

influence process. The theoretical framework in this paper is shown in Figure 1. 

 
Figure 1. Theoretical Framework 



hssr.ideasspread.org   Humanities and Social Science Research Vol. 8, No. 6; 2025 

 27 Published by IDEAS SPREAD 

 

3.1 The Positive Impact of Digital Transformation on Occupational Well-Being 

First, digital technology directly enhances the occupational well-being of online technology workers by 

significantly improving work efficiency. Intelligent code assistants, cloud-based IDEs, and automated testing tools 

are continuously advancing. These technologies effectively reduce tedious repetitive tasks and debugging time, 

saving developers considerable energy. This change allows online technology workers to invest more time and 

cognitive resources in creative and strategic core tasks, rather than mechanical operational tasks (Waterman et al., 

2024). Digital technologies reduce low-value consumption, achieve resource gains as proposed by COR theory, 

and simultaneously create a supportive environment that better satisfies workers' autonomy and competence needs 

in SDT theory. This also frees up individual cognitive resources, enhancing the sense of meaning in work (Pap et 

al., 2022). Therefore, with the reduction of repetitive tasks, online technology workers can enjoy efficient work 

while also gaining deeper psychological satisfaction and occupational well-being. 

Secondly, digital technologies like generative AI have significantly lowered entry barriers in the technical field. 

This helps online tech workers break through traditional skill boundaries and expand their capabilities (Manresa 

et al., 2025). Generative AI enables workers to transcend traditional skill barriers, extending their reach and 

influence across a wider variety of tasks. Furthermore, technology communities, online course platforms, and AI-

driven personalized learning recommendation systems provide convenient learning channels for online technology 

workers, enabling them to continuously keep up with the latest technological advancements and alleviating the 

pressure of knowledge updates. According to SDT theory, these changes enhance individuals' sense of growth and 

professional achievement while effectively satisfying the psychological need for competence in the workplace, 

thereby improving occupational well-being (Tian et al., 2024). 

Finally, the emergence of technologies such as cloud computing, real-time collaborative documents, and virtual 

offices has optimized the level of collaboration in remote teams, further promoting the well-being of online 

technology workers. These digital tools enhance information synchronization and knowledge sharing among team 

members by simulating elements of face-to-face interaction (such as real-time editing, video conferencing, and 

instant messaging) (Fang et al., 2021). Team members can thus collaborate efficiently while building emotional 

connections and trust, enhancing belonging and fulfilling relationships. SDT theory posits that the satisfaction of 

relatedness needs is essential to individuals' psychological health and positive work experiences. When individuals 

feel supported and recognized by their team, their job satisfaction and occupational well-being are significantly 

improved (Rubin et al., 2019). 

In summary, digital technologies improve work efficiency, expand capability boundaries, and optimize team 

collaboration, thereby satisfying the multiple psychological needs of online technology workers and significantly 

boosting their occupational well-being. The widespread application of these digital technologies is creating a more 

efficient, flexible, and meaningful work environment for online technology workers. 

3.2 The Negative Impacts of Digital Transformation on Occupational Well-being 

First, the rapid development of digital technologies shortens the lifecycle of skills. Currently popular technological 

frameworks and tools may soon be replaced by newer technologies, leading online technology workers to face 

skill obsolescence anxiety and continuous learning pressure (Caselli et al., 2022). In the context of rapid 

technological updates, online technology workers often need to master new skills and tools in a short period, 

forcing them to continuously invest significant time and energy to keep pace with industry developments (Krutova 

et al., 2022). However, according to COR theory, when these investments of time and energy fail to translate into 

job security or economic rewards, an individual's psychological resources are depleted, leading to negative 

emotions such as burnout and anxiety, severely impacting occupational well-being. 

Secondly, while remote work and asynchronous collaboration offer flexibility and geographical independence, 

they also blur the boundaries between work and life, increasing the psychological burden on workers. Frequent 

notifications, cross-time zone meetings, and the requirement to be on call at all times have created a "always-on" 

culture (Duan et al., 2023). This requires workers to remain constantly online and responsive to work demands, 

making it difficult for individuals to fully detach from work and even hindering effective rest outside of work 

hours. According to SDT theory, the long-term blurring of work-life boundaries not only depletes energy resources 

but also prevents individuals from fulfilling their needs for autonomy and relationships, thus threatening 

occupational well-being. 

Furthermore, with the rise of platform-based work methods, many work platforms have begun using algorithms 

for task allocation, process monitoring, and performance evaluation, thereby depriving workers of their autonomy 

at work (Möhlmann et al., 2021). This algorithm-dependent management model pursues efficiency and 

quantifiable output, but it neglects the emotional and cognitive needs of knowledge workers. Digital tools and 



hssr.ideasspread.org   Humanities and Social Science Research Vol. 8, No. 6; 2025 

 28 Published by IDEAS SPREAD 

 

algorithmic systems transform complex intellectual labor into a series of quantifiable indicators, significantly 

weakening workers' creativity and autonomy (Savolainen & Ruckenstein, 2024). This erosion of work autonomy 

directly challenges the core elements of SDT theory and triggers emotional resource depletion caused by 

continuously coping with loss of control, as identified by COR theory. When work becomes the execution of 

algorithmic rules, workers' intrinsic motivation and work passion diminish accordingly, ultimately undermining 

occupational well-being. 

In conclusion, while the rapid development of digital technology has brought numerous conveniences and 

innovations to online technology workers, it has also been accompanied by a series of psychological pressures and 

challenges. The rapid iteration of technology, the blurring of work-life boundaries, and algorithm-driven 

management methods have all profoundly impacted the well-being of online technology workers. In coping with 

these challenges, online technology workers often face a loss of psychological resources and a decline in 

occupational well-being.  

3.3 Moderating Factors of the Influence Pathways 

The strength of digital technology's impact on occupational well-being is moderated by multi-level factors, 

encompassing three dimensions: individual, organizational, and platform levels. 

At the individual level, digital literacy and psychological resilience are key moderating variables. Higher digital 

literacy enables online technology workers to utilize technological tools more proactively and efficiently, 

maximizing technology's potential to enhance occupational well-being while reducing the sense of competence 

frustration caused by barriers in technology use (Cetindamar et al., 2021). Meanwhile, understanding algorithmic 

logic can alleviate the uncertainty and pressure from algorithmic black boxes, protecting cognitive resources. 

Individuals with strong psychological resilience, when facing the pressure of technological iteration and 

algorithmic control, are less susceptible to psychological resource depletion, can better maintain intrinsic 

motivation, and buffer the negative effects of the occupational well-being challenge pathway (Aydın et al., 2023). 

At the organizational level, leadership style and organizational support constitute important buffers. 

Transformational leadership, through creating vision, intellectual stimulation, and individualized consideration, 

helps online technology workers find meaning and control amid digital technology changes, thereby satisfying 

their autonomy and relatedness needs and enhancing their perception of occupational well-being (Oliveira et al., 

2025). Organizational support provides crucial external resource replenishment for online technology workers 

coping with challenges, directly mitigating the decline in occupational well-being caused by learning pressure and 

resource depletion (Altamimi & Hilmi, 2023). 

At the platform level, algorithmic fairness and technology affordance are fundamental moderators. Algorithmic 

fairness can greatly reduce autonomy deprivation and emotional exhaustion resulting from the sense of loss of 

control among online technology workers, thereby moderating the impact of digital transformation on occupational 

well-being (Zhang et al., 2022). Technology affordance determines whether it serves as a rigid control tool or an 

empowering partner that online technology workers can flexibly utilize. This directly affects whether digital 

technology primarily leads to resource depletion or promotes competence satisfaction, ultimately moderating its 

impact on occupational well-being. (Gibbs & Navick, 2023). 

4. Conclusions and Implications 

4.1 Research Conclusions 

This study explores the impact of digital transformation on the occupational well-being of online technology 

workers against the backdrop of the digital revolution in work patterns. The research indicates that this impact is 

not a simple linear promotion or inhibition, but a complex process interwoven with two paths: technology 

empowerment and technology challenge. While digital technology enhances well-being by improving work 

efficiency, expanding capability boundaries, and optimizing collaboration abilities to meet workers' needs for 

autonomy, competence, and relationships; it also reduces occupational well-being by triggering skills anxiety, 

blurring work boundaries, and bringing algorithmic control, through depleting their psychological resources and 

hindering the fulfilment of basic needs. At the same time, factors at multiple levels, including digital literacy and 

psychological resilience at the individual level, leadership style and organizational support at the organizational 

level, as well as algorithmic fairness and technology affordance at the platform level, can moderate the impact of 

digital transformation on occupational well-being of online technology workers. 

The main theoretical contributions of this study are: First, it expands the research focus from a broad group of gig 

workers or general knowledge workers to the more contemporary online technology workers, deepening the 

understanding of the psychological experiences of highly skilled personnel in the context of digital transformation. 



hssr.ideasspread.org   Humanities and Social Science Research Vol. 8, No. 6; 2025 

 29 Published by IDEAS SPREAD 

 

Second, it breaks through the single perspective of the mutually exclusive impact of digital technology by 

integrating theories to construct a double-edged sword model, systematically revealing how digital transformation 

affects occupational well-being through both empowering and challenging forces, while also identifying the key 

moderators in this influence process. 

4.2 Practical Implications 

Based on the above mechanism analysis, this study proposes the following practical implications for different 

stakeholders: 

For individual online technology workers, first, implement of strategic technology adaptation. Proactively select 

and learn technical tools that can empower their professional depth rather than simply replace them, consciously 

manage the boundaries of technology use; Second, reshape professional identity. In the AI era, redefine one's core 

value, transforming from "implementer" to "problem definer," "architect designer," and "human-machine 

collaboration planner," constructing a more resilient and forward-looking professional identity; Third, build a 

continuous learning system. Internalize learning as a way of working, focusing on underlying thinking and core 

principles rather than blindly pursuing them, to improve the efficiency and sustainability of skill adaptability. 

For enterprises and platform organizations, first, design a "human-centered" technology work system. When 

introducing efficiency tools and algorithm management systems, a "human-centered" evaluation must be 

conducted. It is crucial to protect the autonomy of online technology workers by preserving sufficient options for 

work methods, process control, and participation in results evaluation. This is becoming a regulatory focus 

internationally. For instance, the EU Platform Work Directive mandates human oversight of algorithmic 

management and transparency, offering companies a clear compliance framework. Second, it is essential to 

cultivate a supportive learning culture and a psychologically safe environment. This includes providing systematic 

skills training resources closely integrated with career development paths, encouraging trial and error and 

knowledge sharing, alleviating employees' learning anxiety and fear of failure, and creating an organizational 

atmosphere that meets their competence and relationship needs. Third, it is vital to implement a technology strategy 

of "intelligent enhancement" rather than "simple replacement." This involves clearly defining the auxiliary role of 

technologies such as AI, emphasizing human-machine collaboration, and ensuring that online technology workers 

feel that digital technology can amplify their intelligence rather than threaten their positions. This concept aligns 

closely with the global consensus on developing AI responsibly and ensuring technology serves humanity. 

4.3 Research Limitations and Future Prospects 

As a theoretical study, this research has certain limitations. First, the core constructs and relationships in the 

theoretical framework need to be tested and revised through empirical research. Future research could develop 

scales specifically for online technology workers, collect data through multi-wave questionnaires, and employ 

structural equation modeling (SEM) or regression analysis to empirically test the theoretical pathway. Additionally, 

work autonomy and job crafting could be incorporated into the testing framework as mediating variables. Second, 

this study has not yet empirically explored some important moderating variables. Future research could incorporate 

individual-level factors and organizational-level factors to more meticulously characterize the differences in 

influencing mechanisms under various conditions. Finally, research methods could be further diversified. In 

addition to quantitative research, in-depth case studies can help researchers better capture the complex 

psychological states of online technology workers during digital transformation, thereby enriching and deepening 

the theoretical implications. 

Acknowledgments 

Funding: This research was supported by the Shandong Provincial Natural Science Foundation, grant number 

ZR2020QG037. 

References 

[1] Ahmed, W., Hizam, S. M., & Sentosa, I. (2022). Digital dexterity: Employee as consumer approach towards 

organizational success. Human Resource Development International, 25(5), 631–641. 

https://doi.org/10.1080/13678868.2020.1835107 

[2] Altamimi, F., & Hilmi, M. F. (2023). The relationship between innovation, digital transformation, 

organizational learning, perceived organizational support, and employee performance. International Journal 

of Business and Technology Management, 5(3), 321–341. 

[3] Aydın, A. G., & Baykal, E. (2023). The impact of organizational strategic trends on individual-based resilience 

with a digital transformation perspective. Human Resources Management and Services, 5(1), Article 3359. 



hssr.ideasspread.org   Humanities and Social Science Research Vol. 8, No. 6; 2025 

 30 Published by IDEAS SPREAD 

 

https://doi.org/10.18282/hrms.v5i1.3359 

[4] Caselli, M., Fracasso, A., Marcolin, A., & Scicchitano, S. (2025). Technological innovations and workers' job 

insecurity: The moderating role of human resource strategies. Journal of Industrial and Business Economics, 

52(1), 153–176. https://doi.org/10.1007/s40812-024-00329-w 

[5] Cetindamar, D., Abedin, B., & Shirahada, K. (2021). The role of employees in digital transformation: A 

preliminary study on how employees' digital literacy impacts use of digital technologies. IEEE Transactions 

on Engineering Management, 71, 7837–7848. https://doi.org/10.1109/TEM.2021.3087724 

[6] Deci, E. L., & Ryan, R. M. (2000). The "what" and "why" of goal pursuits: Human needs and the self-

determination of behavior. Psychological Inquiry, 11(4), 227–268. 

https://doi.org/10.1207/S15327965PLI1104_01 

[7] Developer Nation. (2024). State of Developer Wellness Report. 

https://www.developernation.net/resources/reports/state-of-developer-wellness-report-2024 

[8] Dewi, S. R., Suryamarta, R., & Kurnia, D. (2020). Sense of belonging and job satisfaction on employee 

performance. In International Conference on Community Development (ICCD 2020) (pp. 634–638). Atlantis 

Press. https://doi.org/10.2991/assehr.k.201017.140 

[9] Duan, S. X., Deng, H., & Wibowo, S. (2023). Exploring the impact of digital work on work-life balance and 

job performance: A technology affordance perspective. Information Technology & People, 36(5), 2009–2029. 

https://doi.org/10.1108/ITP-01-2021-0013 

[10] Flinchbaugh, C., Zare, M., Chadwick, C., Li, P., & Essman, S. (2020). The influence of independent 

contractors on organizational effectiveness: A review. Human Resource Management Review, 30(2), Article 

100681. https://doi.org/10.1016/j.hrmr.2019.01.002 

[11] Fang, M., Jandigulov, A., Snezhko, Z., Volkov, L., & Dudnik, O. (2021). New technologies in educational 

solutions in the field of STEM: The use of online communication services to manage teamwork in project-

based learning activities. International Journal of Emerging Technologies in Learning (iJET), 16(24), 4–22. 

https://doi.org/10.3991/ijet.v16i24.25227 

[12] Gao, J., Guo, H., & Gong, S. (2025). Value co-creation practices in the service of innovative digital products 

and their effects on consumer eudaimonic well-being. International Journal of Information Management, 86, 

Article 102979. https://doi.org/10.1016/j.ijinfomgt.2025.102979 

[13] Gibbs, J. L., & Navick, N. (2023). Bringing technological affordances into virtual work. In Handbook of 

virtual work (pp. 3–20). Edward Elgar Publishing. https://doi.org/10.4337/9781802200508.00008 

[14] Hobfoll, S. E. (2001). The influence of culture, community, and the nested-self in the stress process: 

Advancing conservation of resources theory. Applied Psychology, 50(3), 337–421. 

https://doi.org/10.1111/1464-0597.00062 

[15] Hui, X., Reshef, O., & Zhou, L. (2024). The short-term effects of generative artificial intelligence on 

employment: Evidence from an online labor market. Organization Science, 35(6), 1977–1989. 

https://doi.org/10.1287/orsc.2023.18441 

[16] Krutova, O., Turja, T., Koistinen, P., Melin, H., & Särkikoski, T. (2022). Job insecurity and technology 

acceptance: An asymmetric dependence. Journal of Information, Communication and Ethics in Society, 20(1), 

110–133. https://doi.org/10.1108/JICES-03-2021-0036 

[17] Liu, Q., Cui, H., Yuan, P., Liu, J., Jin, Y., Xia, L., & Zhang, P. (2024). Distinction of mental health between 

salesman and R&D in high-tech enterprise: A fNIRS study. Scientific Reports, 14(1), Article 22371. 

https://doi.org/10.1038/s41598-024-74216-8 

[18] Liu, R., & Yin, H. (2024). How algorithmic management influences gig workers' job crafting. Behavioral 

Sciences, 14(10), Article 952. https://doi.org/10.3390/bs14100952 

[19] Manfreda, A., & Mijač, T. (2024). Highlighting gaps in technology acceptance research: A call for integrating 

happiness and well-being into smart city development. Journal of Innovation & Knowledge, 9(4), Article 

100585. https://doi.org/10.1016/j.jik.2024.100585 

[20] Manresa, A., Sammour, A., Mas-Machuca, M., Chen, W., & Botchie, D. (2025). Humanizing GenAI at work: 

Bridging the gap between technological innovation and employee engagement. Journal of Managerial 

Psychology, 40(5), 472–492. https://doi.org/10.1108/JMP-05-2024-0356 



hssr.ideasspread.org   Humanities and Social Science Research Vol. 8, No. 6; 2025 

 31 Published by IDEAS SPREAD 

 

[21] Mattern, J., Tarafdar, M., Klein, S., & Schellhammer, S. (2024). Thriving in a bruising job: How high 

achieving IT professionals can cope with occupational demands. Information Systems Journal, 34(6), 1902–

1934. https://doi.org/10.1111/isj.12513 

[22] McGuinness, S., Pouliakas, K., & Redmond, P. (2023). Skills-displacing technological change and its impact 

on jobs: Challenging technological alarmism? Economics of Innovation and New Technology, 32(3), 370–

392. https://doi.org/10.1080/10438599.2021.1919517 

[23] Möhlmann, M., Zalmanson, L., Henfridsson, O., & Gregory, R. W. (2021). Algorithmic management of work 

on online labor platforms: When matching meets control. MIS Quarterly, 45(4), 1999–2022. 

https://doi.org/10.25300/MISQ/2021/15333 

[24] Naveen, P., & Diwan, B. (2023). Meta-heuristic endured deep learning model for big data classification: 

Image analytics. Knowledge and Information Systems, 65(11), 4655–4685. https://doi.org/10.1007/s10115-

023-01888-5 

[25] Oliveira, C. M. A. M., & Favaretto, J. E. R. (2025). Leadership styles and digital transformation: A literature 

review. Observatorio de la Economía Latinoamericana, 23(4), Article e9544. 

https://doi.org/10.55905/oelv23n4-071 

[26] Pap, Z., Vîrgă, D., & Lupșa, D. (2022). Bringing our best selves to work: Proactive vitality management and 

strengths use predicting daily engagement in interaction. Frontiers in Psychology, 13, Article 1015397. 

https://doi.org/10.3389/fpsyg.2022.1015397 

[27] Röttgen, C., Herbig, B., Weinmann, T., & Müller, A. (2024). Algorithmic management and human-centered 

task design: A conceptual synthesis from the perspective of action regulation and sociomaterial systems theory. 

Frontiers in Artificial Intelligence, 7, Article 1441497. https://doi.org/10.3389/frai.2024.1441497 

[28] Rubin, M., Paolini, S., Subašić, E., & Giacomini, A. (2019). A confirmatory study of the relations between 

workplace sexism, sense of belonging, mental health, and job satisfaction among women in male‐dominated 

industries. Journal of Applied Social Psychology, 49(5), 267–282. https://doi.org/10.1111/jasp.12577 

[29] Ryan, R. M., & Deci, E. L. (2018). Basic psychological needs in motivation, development, and wellness. The 

Guilford Press. https://doi.org/10.1521/978.14625/28806 

[30] Savolainen, L., & Ruckenstein, M. (2024). Dimensions of autonomy in human-algorithm relations. New 

Media & Society, 26(6), 3472–3490. https://doi.org/10.1177/14614448221100802 

[31] Tarafdar, M., Stich, J. F., Maier, C., & Laumer, S. (2024). Techno‐eustress creators: Conceptualization and 

empirical validation. Information Systems Journal, 34(6), 2097–2131. https://doi.org/10.1111/isj.12515 

[32] Tian, K., & Xin, J. (2024). The role of AIGC simulation environments in enhancing e-commerce skills: A 

study based on cognitive load theory. Behaviour & Information Technology. 

[33] Van den Broeck, A., Ferris, D. L., Chang, C. H., & Rosen, C. C. (2016). A review of self-determination theory's 

basic psychological needs at work. Journal of Management, 42(5), 1195–1229. 

https://doi.org/10.1177/0149206316632058 

[34] Waterman, A. S., Schwartz, S. J., & Conti, R. (2024). Resolving the paradox of work: Generalization of the 

roles of self-determination, the balance of challenges and skills, and self-realization values in intrinsic 

motivation across activity domains. The Journal of Positive Psychology, 19(2), 356–368. 

https://doi.org/10.1080/17439760.2023.2179936 

[35] Wright, T. A., & Cropanzano, R. (2004). The role of psychological well-being in job performance: A fresh 

look at an age-old quest. Organizational Dynamics, 33(4), 338–351. 

https://doi.org/10.1016/j.orgdyn.2004.09.002 

[36] Wu, D., & Huang, J. L. (2024). Gig work and gig workers: An integrative review and agenda for future 

research. Journal of Organizational Behavior, 45(2), 183–208. https://doi.org/10.1002/job.2775 

[37] Zhang, A., Boltz, A., Wang, C. W., & Lee, M. K. (2022). Algorithmic management reimagined for workers 

and by workers: Centering worker well-being in gig work. In Proceedings of the 2022 CHI conference on 

human factors in computing systems (pp. 1–20). ACM. https://doi.org/10.1145/3491102.3501866 

 

Copyrights 

Copyright for this article is retained by the author(s), with first publication rights granted to the journal. 



hssr.ideasspread.org   Humanities and Social Science Research Vol. 8, No. 6; 2025 

 32 Published by IDEAS SPREAD 

 

This is an open-access article distributed under the terms and conditions of the Creative Commons Attribution 

license (http://creativecommons.org/licenses/by/4.0/). 


