ERP Quality and the Organizational Performance: Technical Characteristics vs. Information and Service

Comment

Answer

Figures 1 & 3 must be changed.

These images have been redrawn and are now of higher resolution.

References should be up to date; including old references is not necessary only if it is the sentimental study or for a theoretical aspect.

i.e., Ref 10, 17, 18, 21, 22, 24,25, 29, 30, 31,  & 34.

Why do you even mention references from 1987? I think it is better to update references from 2010 and above.

The literature review has been revised to incorporate more recent research.

However, it is important to note that several older references used as part of this paper's methodology remain relevant because they represent the origin of the field itself (e.g., Fornell and Larcker, after whom the criterion for checking discriminative validity is named - 92,959 citations on Google Scholar.). These are mostly references from 30 onwards.

Other than that, the study is ok, the contribution is good.

Thank you very much. We appreciate your time, comments and opinion.

Comment

Answer

I have reviewed the submission entitled "ERP Quality and the Organizational Performance: Technical Characteristics vs Information and Service." The authors present a model that connects the ERP (Enterprise Resource Planning) quality with organisational business performance. The model was generated using SEM (Structural Equation Modelling) on primary data collected from 217 companies in Bosnia and Herzegovina. The paper has merit: It is well written, the motivations are well exposed, the results are presented, it is well directed to the target audience of Information, and the references are appropriate and up to date.

I have a few remarks for the authors to strengthen the paper before publication:

(1) I suggest you add a subtitle. Here, you should indicate the scope of your study, something like "ERP Quality and the Organizational Performance: Technical Characteristics vs Information and Service — A study in Bosnia and Herzegovina."

Thank you very much. We appreciate your time and comments.

1) The title seems to already have a subtitle (after the colon). If you and the editor consider that the suggested addition would not make the title too complicated, we agree.

(2) In most sentences, you used the British style (e.g., "organisational"); however, in a few sentences, you used the American style (e.g., "organisational").  Please, be consistent.

2) We proofread the text and used the British version of the writing.

(3) In line 69, the reference style is inconsistent.

(4) In Table 3, you should provide additional model evaluation indices besides X², RMSEA and CFI. I mean the goodness-of-fit index (GFI), the normed fit index (NFI), the Tucker-Lewis index (TLI), and the Akaike information criterion (AIC) / Bayesian information criterion (BIC). From a scientific perspective, this is the only severe drawback of the study.

3) We did proofreading and all references.

4) While reporting GoFs, we followed the instruction of Hair et al.. (2018, page 642): »Thus, reporting the x2 value and degrees of freedom, the CFI, and the RMSEA will often provide sufficient unique information to evaluate a model.«

However, following your suggestion, we have added SRMR and TLI. Mplus doesn't calculate NFI.

On the other side, AIC and BIC were not reported since we didn't compare any models (»Akaike’s information criterion (AIC) and the Bayesian information criterion (BIC) are commonly used for selecting an optimal model from the alternatives.«)

(5) Please improve the quality of Figures 1 and 3 (they are blurred). Also, there is a typo ("Organisational").

5) These images have been redrawn and are now of higher resolution.

(6) In lines 135–136, there is an apparent contradiction. Check and revise.

6) We revised that.

(7) I attached a PDF file with some minor remarks.

7) Thank you very much. We checked and revised all comments.

Comment

Answer

With great interest, I have read this article. However, I would recommend the following changes:

Thank you very much. We appreciate your time, comments and opinion.

- the literature review should be expanded - The introduction section can be shortened, then the literature review section, then Methodology with Hypothesis Development. 

We have restructured the paper following your suggestion.

- Also, the Methodology section is far too short,

The Methodology section is split into three subsections that discuss the research instrument, the data, and the statistical analysis. Thus, the fundamental aspects of the methodology are covered without greatly expanding the length of the study.

- data were acquired from 217 companies; I think that this amount is not a representative sample size. Authors should explain this,

We have added the following explanation to the study:

Following the recommendations for minimal sample sizes based on the model's complexity and the measurement model's basic characteristics, the sample size was established. In particular, (Hair et al., 2018) suggest a minimum sample size of 150 for models with seven or fewer components and no unidentified constructs (page 633). Five constructs were evaluated in our model, and none of them was underidentified. In other words, a sample size of 217 is considered sufficient for this model.

- I am missing some descriptive statistics; information about companies can be presented in tables,

We added the table of sample demographics.

- conclusion section can be divided into the Discussion section (which is missing now) and the Conclusion without citations, but with the study's limitations and further research directions.

Due to the length of the paper, the discussion is merged with the Results section. Thank you.