Palm Oil 5

Palm Oil Variables

13/06/2026

This changes my recommendation quite a bit.

Because the mill has not implemented Industry 4.0 or smart mill technology yet, I would be very careful about adding automation adoption as a major dependent variable.

An examiner may ask:

"How can workers evaluate or adopt a technology that they have never used?"


That creates a validity problem.


What I like about your current framework

Your current model is actually quite practical:

Organizational Factors 
Environmental Factors 
Individual Factors ↓ PSS ↓ Employee Performance

This is a workplace performance model.

The mill manager's complaint about knowledge transfer can fit naturally into this model without changing the entire study.

Option 1 (My Preferred Option)

Treat Knowledge Transfer as a new organizational factor.

For example:

Organizational Factors

Training

Communication

Management Support

Knowledge Transfer


Then keep all your ROs and RQs exactly the same.

No new RO. No new RQ.

Only revise the literature review and conceptual framework.

The logic becomes:

Knowledge Transfer → PSS → Employee Performance

This fits perfectly with the manager's complaint.

Option 2

Add "Readiness for Automation" instead of "Automation Usage."

Because automation is not yet implemented.

Possible new objective:

RO5: To examine the influence of organizational, environmental, and individual factors on employee readiness for automation technologies.

Possible research question:

RQ5: How do organizational, environmental, and individual factors influence employee readiness for automation technologies?

This is defensible because workers can answer:

Am I willing to learn?

Am I ready to adapt?

Do I believe automation will help me?


They do not need actual experience with smart mills.


Option 3 (I would be cautious)

Add:

"Automation Usage"

The problem:

No automation exists yet.

An examiner may immediately challenge:

"Usage of what exactly?"

You would have to redefine it as intention or readiness.

Where PSS becomes interesting

I think you may be onto something here.

Suppose workers receive training about future automation.

Some workers think:
"My supervisor supports me and helps me learn."

Others think:
"My supervisor doesn't care."


The same training can produce different outcomes.

This suggests:

Knowledge Transfer → Readiness for Automation

Moderated by:

PSS

Meaning:

When PSS is high, knowledge transfer has a stronger effect.

When PSS is low, knowledge transfer has a weaker effect.

That is theoretically stronger than making PSS do everything.

The human-centricity issue you quoted

This is actually a gem.

Many Industry 4.0 studies focus on:

Technology

Cost

Productivity


Very few focus on:
"Will workers feel less valuable?"


The paper's discussion on craftsmanship loss points toward:

Meaningful work

Employee dignity

Job identity

Psychological ownership


For a DBA, this could become a future paper.

I would not put it into the main framework yet because your model is already becoming crowded.

The question I would ask you next

What exactly are your Organizational, Environmental, and Individual factors?

Right now they are broad categories.

For example:

Organizational

Training

Communication

Knowledge Transfer

Safety Culture


Environmental

Work Conditions

Technology Availability

Regulatory Pressure


Individual

Experience

Self-Efficacy

Motivation


If you show me the actual variables under each category, I can tell you whether Knowledge Transfer should:

1. Become a new organizational factor,

2. Replace an existing factor,

3. Become a separate construct, or

4. Become part of a future Industry 4.0 extension study.


At this stage, I would not add automation usage to the DBA. I would instead add knowledge transfer and possibly automation readiness because the smart mill has not yet been rolled out. That keeps your study grounded in the current reality of C- Island rather than a future system that workers have not experienced yet.

Norsanina.blogspot.com

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Daily food nutrients

Daily Nutrient Targets For you (52 years, 158 cm, 80 kg): Nutrient Target Protein 70–90 g Carbohydrates 180–250 g Fat 50–70 g Fiber 25–30 g ...