IStore Nig Co Academic Press

IStore Nig Co Academic Press IJMBA- International Journal of Management and Business Automation. Published by iStore Nig Academic Press. https://ijmba.org.ng

Peer-reviewed, open-access journal advancing research in management, business automation & related fields.

22/09/2026

Tip

Research Tip: Why Your Paper May Be Rejected

Most people state in their methodology that they used convenience sampling, but then explain that they could not retrieve all the questionnaires, which reduced the sample size.

Technically, this is problematic. It may expose an inconsistency in the methodology and raise questions about whether the stated sampling technique was actually deployed.

Convenience sampling means that you select respondents based on their accessibility and willingness to participate. Nobody is forced to respond. If a respondent is unwilling to participate, you simply move to the next available respondent.

On the other hand, when you state that you could not retrieve all the questionnaires, it may indicate that you left the questionnaires at the respondents’ offices or gave them to someone to administer on your behalf. That is different from the direct selection and administration process expected in convenience sampling.

So, in your next paper, if you use convenience sampling, make sure your sampling and questionnaire administration procedures are consistent with the technique you have reported.

Does it make sense?
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International Journal of Management and Business Automation (IJMBA)
📖 Vol. 1, No. 3
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📚 RESEARCH TIPTake Note!It is very wrong to state that p-value = 0.000, even when the SPSS output shows 0.000.The truth ...
14/09/2026

📚 RESEARCH TIP

Take Note!

It is very wrong to state that p-value = 0.000, even when the SPSS output shows 0.000.

The truth is that a probability value cannot be exactly 0.000. SPSS, due to its display precision, may show 0.000 when the actual p-value is extremely small.

Therefore, instead of reporting:
❌ p-value = 0.000
You should report:
✅ p-value < 0.01
Research is not just about copying what SPSS displays; you must understand what the output means.

📢 CALL FOR PAPERS
International Journal of Management and Business Automation (IJMBA)
📖 Vol. 1, No. 3
💰 Review & Publication Fee: ₦20,000
📞 Contact Managing Editor:
WhatsApp: https://wa.me/2348064617645
🌐 ijmba.org.ng

Wait... Does a research study really have 3, 4 or 5 objectives? 🤔 Read this before writing your next project.A Research ...
14/09/2026

Wait... Does a research study really have 3, 4 or 5 objectives? 🤔 Read this before writing your next project.

A Research Study Has One Main Objective, Not Many

In Management Sciences, a research study ordinarily has one main or general objective, which may be broken down into several specific objectives.
The specific objectives do not change the study into several unrelated objectives. Rather, they provide the specific areas through which the main objective is achieved.

The problem is that many researchers state the main objective at the beginning of the study and never return to it again throughout the research work.

This is where the conclusion becomes important. The conclusion should not merely repeat the findings of the individual specific objectives. It should bring those findings together and clearly establish whether the main objective of the study has been achieved.
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📚 RESEARCH TIPWhy Your Questionnaire Is Out of ContextOne of the biggest flaws in survey research is poor questionnaire ...
07/09/2026

📚 RESEARCH TIP
Why Your Questionnaire Is Out of Context

One of the biggest flaws in survey research is poor questionnaire item formulation.

I have seen many questionnaires developed out of context, where researchers formulate items that measure only the dependent variable while neglecting the independent variables.

The trick is simple:
Just as you develop specific objectives to dissect your main objective into measurable areas, the same principle applies to questionnaire development.
Develop 2 or more items for each independent variable and ensure they are measuring indices for independent variable d. Also develop items that directly measure the dependent variable.

Every questionnaire item must have a purpose and connect to what your study intends to measure.
I am Edem King, and I am your tutor on Research Skill Development. 🎓

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*Sponsored:*
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Volume 1, Issue 3 ends September 27th 2026

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Give your honest answer
28/08/2026

Give your honest answer

🔬 RESEARCH TIPI bet you never knew this.If you are testing more than one hypothesis, showing one Cronbach's Alpha value ...
27/08/2026

🔬 RESEARCH TIP
I bet you never knew this.
If you are testing more than one hypothesis, showing one Cronbach's Alpha value above 0.70 as the reliability result for the entire questionnaire is wrong.

Reliability testing must be conducted for each construct separately.
Each construct has its own questionnaire items, and those items should be tested together to determine the internal consistency of that particular construct.

For example:
H₁: Training has no effect on Staff Performance
Cronbach's Alpha for Training
Cronbach's Alpha for Staff Performance

❌ Do not combine all questionnaire items measuring different constructs and run one Cronbach's Alpha simply to obtain one figure above 0.70.

✅ Test the items belonging to each construct separately.
Remember: Cronbach's Alpha measures the internal consistency of items measuring a particular construct; it does not measure the reliability of your entire research questionnaire as one single construct.

Like 👍 Share 🔄 Comment 💬 and join our Researcher Forum for more research tips..

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Your honest answer
25/08/2026

Your honest answer

🔬 RESEARCH TIP *Don't Mistake a Control Variable or Construct for One of the Variables in Your Specific Objectives* A co...
24/08/2026

🔬 RESEARCH TIP
*Don't Mistake a Control Variable or Construct for One of the Variables in Your Specific Objectives*

A control variable is not necessarily one of the constructs or factors used to measure your independent variable.

It is a separate factor that may also influence the outcome and whose influence the researcher wants to account for in the analysis.

Example:
Research topic: Training and Staff Performance
Your independent variable may have:
• On-the-job training
• Off-the-job training

These are the variables reflected in your specific objectives.
But you may include Age as a control variable.

Age is not a dimension of training, but it may independently influence staff performance. Therefore, its influence can be accounted for while examining the relationship between training and performance.

👉 Remember:
Specific-objective variables = What you want to investigate.
Control variable = Another factor whose possible influence on the outcome you want to account for.

Don't force every control variable into your title, objectives, or hypotheses simply because it appears in your regression model.

Like 👍 Share 🔄 Comment 💬 and join our Researcher Forum for more research tips.


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*Sponsored:*
📢 *Publish Your Paper with International Journal of Management and Business Automation (IJMBA)*
Volume 1, Issue 3 is now ongoing for submissions and instant publication.

💬 👉 Chat Now with the Managing Editor
https://wa.me/2348064617645

https://ijmba.org.ng

🔬 RESEARCH TIPWhat you never knew about control variables and how to deal with them in empirical research.Common flaws1....
22/08/2026

🔬 RESEARCH TIP
What you never knew about control variables and how to deal with them in empirical research.

Common flaws
1. Most researchers think a control variable is a factor that is blocked from influencing the model.
2. Some try to force the control variable to reflect in the topic, objectives, and hypotheses.

Here is what you should know:
A control variable does not need to appear in your title or objective for it to be included in the study. However, its inclusion should be clearly defined and justified in the methodology.

A control variable means a factor whose influence is accounted for. It is included in the model; we do not block it from influencing the model.

In model specification
The control variable should be reflected in the model alongside the main independent variables.
For example:
Y = β₀ + β₁X₁ + β₂X₂ + β₃C + ε
Where:
Y = Dependent variable
X₁, X₂ = Main independent variables
C = Control variable
β₀ = Constant
β₁, β₂, β₃ = Regression coefficients
ε = Error term

Also, your questionnaire must collect data for the control variable just as you collect data for the main variables.
If the control variable is a construct, such as organizational culture, it can be measured using Likert-scale items, just like the main variables.

However, if you are using a demographic characteristic such as age, and you intend to use it as a numerical control variable in regression, it is better to collect the actual age rather than age categories such as 25–30, 31–40, etc.

Like, share, comment, and join our Researcher Forum for more research tips.
👉 Would you like a tutorial on control variables and how they can be handled in SPSS analysis?
IStore Nig Co Academic Press
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*Sponsored:*
📢 *Publish Your Paper with International Journal of Management and Business Automation (IJMBA)*
Volume 1, Issue 3 is now ongoing for submissions and instant publication.

💬 👉 Chat Now with the Managing Editor
💬 👉 Chat Now: https://wa.me/2348064617645

https://ijmba.org.ng

📌 Research Tip: Your Model Specification Should Not Stand AloneThe model specification function in research is not merel...
13/08/2026

📌 Research Tip: Your Model Specification Should Not Stand Alone

The model specification function in research is not merely included to explain the mathematical relationship among variables. Once the data have been analysed, the specified model can be estimated, computed, and interpreted.

I personally believe this section should be captured and integrated into the empirical analysis rather than allowed to stand alone.
Remember: No section of a research work should exist in isolation. Each section should connect with and support another section.

🔢 Example with Two Independent Variables
Suppose your model is:
Y = β₀ + β₁X₁ + β₂X₂ + ε
Where: • Y = Dependent variable
• X₁ and X₂ = Independent variables
• β₀ = Constant
• β₁ and β₂ = Regression coefficients
• ε = Error term

After SPSS analysis, go to the Coefficients table and take the Unstandardized B values.
Suppose:
• Constant = 1.250
• Technological Innovation (X₁) = 0.420
• Organizational Culture (X₂) = 0.310
Your estimated model becomes:
Ŷ = 1.250 + 0.420X₁ + 0.310X₂

The ε (error term) is not assigned a numerical value in this computation. It represents unexplained variation or the influence of factors outside the specified model.

📈 Now compute the predicted Y
From the Descriptive Statistics table, suppose:
• Technological Innovation (X₁) mean = 4.20
• Organizational Culture (X₂) mean = 3.80
Substitute the mean values:
Ŷ = 1.250 + 0.420(4.20) + 0.310(3.80)
Ŷ = 1.250 + 1.764 + 1.178
Ŷ = 4.192

📝 How do we interpret this?
4.192 is not the actual mean of Y. It is the predicted/expected value of the dependent variable when X₁ and X₂ are at their respective mean values.

In a research report, you can write:
“The estimated regression model produced a predicted value (Ŷ) of 4.192 for the dependent variable when Technological Innovation and Organizational Culture were held at their respective mean values. This indicates that, at the average levels of the two independent variables, the expected level of Organizational Performance was approximately 4.19 on the measurement scale.”

This is how the model specification moves from a mathematical expression in the methodology to an actual computed and interpretable result.

Edem king's taught.
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