Quantitative Emotional Salary and Talent Commitment in Universities: An Unsupervised Machine Learning Approach

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

General conclusions: The paper is interesting and important from the scientific and empirical point of view. It discusses talent commitment within the university environment, focusing on identifying key factors that influence the loyalty of professors and researchers.. The main strengths of the article are as follows:

1. The authors clarify the aim of the research, core definitions, literature review.
2. The authors presents the scientific gap and thus they justify the need to discuss the topic.
3. The authors use interesting and quite novel approach to HRM - People Analytics based on machine learning techniques.
4. The authors clarify the limitations of the article ant the need for the further research.

Nevertheless I have some suggestions  and questions to the authors:

1. The management of universities, and therefore of the employees of these universities, is very specific. It differs from the management of commercial units because it is subject to additional legal regulations. Not all the solutions of the business sector can be applied to the education sector. This emphasis on the differences in the education sector is missing from the article and is important for the overall discussion.
2. The research results presented in the article are based on an analysis of the science sector in Spain. This is important as the solutions differ from country to country, e.g. the career path - its stages and the requirements for employees at each stage. What is missing in the article is a background description of the specifics of the career of a scientist in Spain.
3. The results of the research concern one unit, so it is a case study and the results should not be generalized to the entire sector. However, in the conclusion the authors draw conclusions concerning the entire sector.

 

General conclusion – the text can be improved by adding some information as mentioned above.

Comments for author File: Comments.pdf

Author Response

Reviewer 1

Comment 1:  The management of universities, and therefore of the employees of these universities, is very specific. It differs from the management of commercial units because it is subject to additional legal regulations. Not all the solutions of the business sector can be applied to the education sector. This emphasis on the differences in the education sector is missing from the article and is important for the overall discussion.

Response 1: Thank you for pointing that out. We agree with this comment, and we have included the following text in the Discussion to emphasise this aspect at page number 11, paragraph 2, line number 4.

“One of the key aspects to consider when analysing talent commitment in higher education institutions is the specific nature of the university environment compared to other sectors, particularly the business sector. Unlike commercial organizations, universities are subject to additional legal and administrative regulations that significantly influence human resource management. These include public regulations governing recruitment, promotion, and job stability, externally determined salary scales, and an institutional framework in which non-monetary incentives carry considerable weight.

In this regard, although the present study draws on concepts such as Quantitative Emotional Salary (QES), which are partially inspired by practices from the business world, their application has been carefully contextualized. The aim is not to directly transfer private sector models, but rather to explore internal patterns within the university system that may serve as meaningful indicators of motivation and retention, based on their statistical behaviour resembling that of economic compensation.

Acknowledging these structural differences is essential for a proper interpretation of the results. So, the contribution of this study lies in offering a methodological framework that can be adapted to different institutional contexts, always considering the regulatory and organizational constraints inherent to the education sector.”

Comments 2: The research results presented in the article are based on an analysis of the science sector in Spain. This is important as the solutions differ from country to country, e.g. the career path - its stages and the requirements for employees at each stage. What is missing in the article is a background description of the specifics of the career of a scientist in Spain.

Responses 2: Thank you for pointing that out. We agree with this comment, and we have included the following text in the paragraph Introduction to emphasise this aspect at page number 2, paragraph 5, line number 32 .

“The scientific career in Spain is defined by a highly regulated and hierarchical structure, built around a sequence of temporary contracts, competitive calls, and stabilization processes that rely heavily on external evaluation criteria and the availability of public funding. Access to and progression within the national research and academic system are determined by programs promoted by national and regional government bodies. This career path—particularly during the postdoctoral stage—is marked by extended periods of contractual precariousness, during which researchers are expected to simultaneously manage teaching responsibilities, produce high-impact scientific work, and continuously apply for funding through highly competitive calls. Securing a permanent position within the university system can take a long time, even for candidates with internationally competitive research profiles and strong scientific credentials.

These structural characteristics have a profound impact on researchers’ professional experiences, influencing their sense of job security, institutional recognition, and long-term career prospects. Consequently, any attempt to understand the factors that drive academic talent engagement and loyalty in the Spanish context must begin with a critical examination of this regulatory and organisational framework, which differs significantly from other higher education and research systems across Europe.”

Comments 3: The results of the research concern one unit, so it is a case study and the results should not be generalized to the entire sector. However, in the conclusion the authors draw conclusions concerning the entire sector.

Response 3:  Thank you for pointing that out. We agree with this comment, and we have included the following text in the paragraph Conclusions to emphasise this aspect at page number 12, paragraph 3, line number 12

“Nevertheless, it is important to underscore that this research is based on a single institutional case study. As such, its findings are context-specific and should not be generalized across the entire higher education sector without further validation. Institutional structures, regulatory frameworks, and cultural contexts vary widely between universities and national systems, and these factors could significantly affect the relevance and replicability of the observed patterns.”

 

We look forward to having answered all the questions requested in the revision of the work. Thank you very much for your time and suggestions to improve our article.

 

Reviewer 2 Report

Comments and Suggestions for Authors

This research covers an important topic in HR and higher education management. The introduction provides background, the research design was conducted properly, and the application of machine learning is innovative. The data analysis provides valuable insight, but more analytical specifications for future research could be improved.

I would also suggest having an explanation about the concept of QES in the introduction

Comments on the Quality of English Language

This paper has a good structure and clear language. However, some grammatical errors could be improved.

Author Response

Reviewer 2

Comment 1: I would also suggest having an explanation about the concept of QES in the introduction

Response 1:  Thank you for pointing that out. We agree with this comment, and we have included the following text in the paragraph Introduction to emphasise this aspect at page number 3, paragraph 14, line number 90.

“Within the framework of this scientific research, the quantitative emotional salary (QES) sub-dataset refers to a specific set of quantitative variables that capture the non-monetary yet measurable aspects of the work experience that directly influence the satisfaction, motivation, and loyalty of university faculty. The QES sub-dataset serves as an empirical representation of the broader concept of emotional salary, which is traditionally associated with qualitative factors such as recognition, work-life balance, or professional development. However, by focusing exclusively on its quantifiable dimensions, this sub-dataset enables an aim, data-driven analysis that can support strategic decision-making in academic talent management.

By isolating and analysing such variables independently from direct salary measures, the QES subset allows for a deeper understanding of the hidden factors that influence academic talent commitment. Its application makes it possible to go beyond traditional financial incentives and to optimize retention strategies through a more holistic and evidence-based approach.”

 

The English has been revised to try to detect the grammatical errors mentioned.

We look forward to having answered all the questions requested in the revision of the work. Thank you very much for your time and suggestions to improve our article.