Analysis of a Teleworking Technology Adoption Case: An Agent-Based Model
Round 1
Reviewer 1 Report
Thank you for the opportunity to read the paper. It is an interesting toping and I consider it fits to the journal.
I have just some suggestions:
In the abstract it is recommended not to pass bibliographic resources.
Part of the literature review was treated superficially and was not highlighted separately.
Figure 2. The screenshot of the computer model interface is hard to read. Maybe it would be good to divide it into several parts (for example 2a, 2b, .....)
Figure 3 has no title.
The conclusions part are missing. There is Discussion but it is recommended that there be conclusions
Bibliography reduced in number. It's out of date. There are sources from 2020, 3 from 2021 and one from 2022. We recommend updating.
Author Response
First, I would like to thank you for taking to time to read the paper, and for your valuable suggestions. As required by MDPI, I allow myself to provide a point-by-point response.
- In the abstract it is recommended not to pass bibliographic resources.
Response: The bibliographic references were from the abstract.
- Part of the literature review was treated superficially and was not highlighted separately.
Response: The referred literature was checked, and no relevant references were eliminated, for instance, original 5, 6, 7 and 8. Also, new relevant and updated literature was added. In addition, the most important literature was highlighted separately, especially which is related to teleworking and innovation diffusion theory.
- Figure 2. The screenshot of the computer model interface is hard to read. Maybe it would be good to divide it into several parts (for example 2a, 2b, .....)
Response: The figure was divided into 3 sections: netlogo world, set of controls and accumulative adoption plots.
- Figure 3 has no title.
Response: All figures were checked to have a title and corrections were applied.
- The conclusions part are missing. There is Discussion but it is recommended that there be conclusions
Response: The conclusions were integrated within the Discussion section, since it no a large text, following the sustainability template available on
https://www.mdpi.com/files/word-templates/sustainability-template.dot
this is:
“5. Conclusions
This section is not mandatory but can be added to the manuscript if the discussion is unusually long or complex.”
- Bibliography reduced in number. It's out of date. There are sources from 2020, 3 from 2021 and one from 2022. We recommend updating.
Response: The bibliography was updated by replacing some old literature and including some new ones in the case where it was possible.
Reviewer 2 Report
The topic of this article is relevant, since at present there is a
constant search for new models of behavior in the context of
organizational innovative transformations.
From the standpoint of mathematical modeling, the tasks posed in the
article have been solved.
I would like answers to the following questions:
Are there analogues of this model? And what exactly is its advantage?
What are the limitations and conditions for applying this model in
practice?
Has the model been tested on specific cases?
What are the possible scenarios for working with this model for decision
makers?
Author Response
First, I would like to thank you for taking to time to read the paper, and for your valuable suggestions. As required by MDPI, I allow myself to provide a point-by-point response.
- Are there analogues of this model? And what exactly is its advantage?
Response: There are analogues models specially applied to climate friend technology, such as green energy or electric cars. A good examples can be found in reference 30
“Kiesling, E. Planning the Market Introduction of New Products: An Agent-Based Simulation of Innovation Diffusion, Uni-versität Wien, 2011”
We believe that our model has a differential advantage in its capacity to reflect changes in environment, and affect agents using rules supported by theory and observation.
- What are the limitations and conditions for applying this model in practice?
Response: We think that model’s main limitations are:
It requires an in-deep knowledge of the characteristics that divide heterogeneous populations to be adequately configured.
It does not cover the final stages of the adoption decision process, and thus cannot be used to simulate the daily usage of teleworking technology. The phenomenon that occurred when an individual adopt telework and a few days ago stop teleworking and return to the office, cannot be simulated.
- Has the model been tested on specific cases?
Response: Yes, it was tested on a specific case of the adoption of a teleworking technology named SAROFI. Its backcasting and explicative capabilities were tested.
- What are the possible scenarios for working with this model for decision makers?
Response: It is expected that decision makers can use a correctly configured model simulate hypothetical adoption scenarios, for instance:
What happens if I spend more money on initial promotional events of a teleworking technology, does it reduces the adoption time?, is it worth?
What happens if I increase the external influence on individuals for teleworking, does it increase the adoption rate?, is it worth?
Reviewer 3 Report
Comments for author File: 
Comments.pdf
Author Response
First, I would like to thank you for taking to time to read the paper, and for your valuable suggestions. As required by MDPI, I allow myself to provide a point-by-point response.
- First, I would want to thank the author(s) for their hard work. The idea of this paper is very unique. In the introduction part, authors need to justify the more things such as teleworking and diffusion of innovation. This is very important to discuss in the introduction part. Overall, the idea is very interesting
Response: The discussion about teleworking, diffusion of innovation theory and its relationship was improved.
- Literature review part, authors need to more explain about the diffusion of innovation theory. In Rogers’s theory, the accumulated number of innovation adopters over time typically describes an s-shaped curve (s-curve) with four growing stages related to five groups of adopters. I also needed a more information of Rogers theory with the teleworking context
Response: The description of roger´s diffusion of innovation theory was improved, some important definitions were added, the descriptions of adopters groups were corrected and also the description of innovation attributes was also improved.
- Results, The simulation results are nearly perfect. However, the author(s) should double-check the values of the simulations of the outcomes
Response: The paper was improved to show that model´s verification and validation tasks did not use a single simulation result, but the model is run 2500 times to generate an average outcome which is used to compare and check de model outcomes. This approach is used on two different types of model outcome checks:
On model verification, when we check if the model can reproduce the outcome of an existing recognized model, this is the Bass model.
On model validation, when we check if the model´s outcome can reproduce a real data, this is the SAROFI’s diffusion data.
- Authors are advised to use recent and relevant references. Furthermore, authors are encouraged to properly edit their manuscripts to eliminate any potential grammatical errors or linguistic concerns.
Response: The referred literature was checked, and no relevant references were eliminated, for instance, original 5, 6, 7 and 8. Also, new relevant and updated literature was added. In addition, the most important literature was highlighted separately, especially which is related to teleworking and innovation diffusion theory.
In regard to manuscript edit, a general revision was applied, but a new native English revision will be applied if necessary for new revisions.
