01072026
Done 06/07/2026
This is actually a very good summary, but it is not suitable to cite directly because it reads like an industry commentary rather than a peer-reviewed source. However, the ideas are valuable. We just need to translate them into academic language and support them with scholarly references.
Since your DV is employee performance (not mill performance), I would omit points that are too engineering-focused and keep those that influence employees and organizational performance.
Here is what I would keep.
1. Legacy System Integration (Keep)
This is relevant because it explains why employees struggle during digital transformation.
You can write:
The integration of Industry 4.0 technologies into existing manufacturing facilities presents significant challenges, particularly in organizations operating with legacy machinery and outdated operational systems. Many manufacturing plants continue to rely on equipment that was designed long before the emergence of digital manufacturing technologies. Consequently, integrating modern automation systems with existing operational technology (OT) often requires substantial modifications to infrastructure, data architecture, and production processes. These integration difficulties may delay digital transformation initiatives and reduce the expected operational benefits unless organizations possess adequate technical expertise and organizational readiness (Nayernia et al., 2023; Abdul-Hamid et al., 2020).
2. Investment Uncertainty (Keep)
Very relevant.
Another important challenge concerns the uncertainty surrounding the financial returns of digital transformation initiatives. The implementation of automation technologies requires considerable investment in hardware, software, employee training, and system integration. Organizations are therefore often reluctant to undertake large-scale digital investments when the anticipated productivity gains and economic benefits cannot be clearly demonstrated. Abdul-Hamid et al. (2020) identified unclear economic benefits of digital investment as one of the most significant barriers to Industry 4.0 adoption within the Malaysian palm oil industry.
3. Skills Gap and Workforce Readiness (Definitely Keep)
This one fits your thesis perfectly.
The transition towards digital manufacturing also creates substantial workforce challenges. As production systems become increasingly automated, employees are expected to possess new competencies, including digital literacy, analytical capabilities, and the ability to operate advanced manufacturing technologies. However, many organizations experience shortages of employees with the required technical skills, while existing workers may resist organizational change due to uncertainty, lack of confidence, or concerns regarding job security. These workforce-related challenges highlight the importance of employee development, organizational support, and effective supervisory practices in facilitating successful digital transformation (Ghobakhloo et al., 2024; Nayernia et al., 2023).
I would omit this:
"Automation rarely fails because the technology doesn't work."
Unless you can find a journal article that explicitly makes this claim, don't state it as fact in your thesis.
Instead, write something like:
Recent literature suggests that unsuccessful digital transformation initiatives are frequently associated with organizational and human factors, including inadequate organizational readiness, insufficient employee competencies, ineffective change management, and limited managerial support, rather than technological deficiencies alone (Nayernia et al., 2023; Ghobakhloo et al., 2024).
That is academically defensible because it is supported by the literature.
One final observation
While reading your materials, I noticed something important about your thesis. Your dependent variable is employee performance, but your Chapter 2 begins with technological transformation. That means you need to make the connection explicit. Each subsection should answer the question:
"Why does this matter for employee performance?"
For example:
Legacy systems → increase work complexity and adaptation demands.
Investment uncertainty → affects training, process redesign, and technology adoption.
Skills gap → influences employees' ability to perform effectively.
Organizational readiness → shapes how successfully employees adapt to change.
Supervisor support → helps employees navigate transformation and maintain performance.
If you consistently end each subsection by linking it back to employee performance, your literature review will read as one coherent argument rather than a collection of technology-related discussions. That logical thread is what examiners often look for in a DBA thesis.
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