Human capital continues to be a crucial factor in organizational success and a source of competitiveness for businesses (Jurík & Sakál, 2014). According to Espinosa Robert et al. (2022), the human resources (HR) department plays a vital role in contributing to the growth and development of an organization with a philosophy focused on well-being and people-first sustainability (Qamar et al., 2023). Jurík and Sakál (2014) state that competency-based HR management is considered the most advanced system for promoting healthy organizational development, with the aim to create a competitive company led by competent individuals. In order to design a competency-based model, it is necessary to define the essential competencies that differentiate the institution, based on the mission, vision, and strategy of the organization (Nardes et al., 2021). A competency profile outlines the essential knowledge, skills, and abilities required for job performance and is typically integrated into competency-based models and used by companies in employee selection (Jurík & Sakál, 2014).

Within their strategic role, the HR department must implement an effective personnel selection (PS) policy. This term is defined as the process of hiring individuals for a specific position within an organization. According to Espinosa Robert et al. (2022), PS includes all the phases of the process such as recruitment, selection, hiring, or onboarding. Recruitment and selection are closely related. Recruitment aims to attract qualified candidates who fulfil the requirements of the vacancy, while selection involves conducting a more refined screening to choose the best candidate fit for the organization. Therefore, as emphasized by Evertz and Siifê (2017), organizations must focus not only on efficient hiring tactics but also on reaching the individuals they aim to target. Selecting the ideal candidate for a job position can be an expensive and time-consuming process. Additionally, certain profiles, such as those related to Information Technologies (IT) and managerial roles, are highly in demand in the job market, leading to serious difficulties in finding suitable candidates.

According to Çelikbilek (2018), the PS process is complex for several reasons, including the need to integrate group decision-making, subjective judgments, various inputs from different sources and large-scale data to avoid bias or error. Additionally, interviewers' personality traits may increase the risk of introducing bias into the selection process (Wingate et al., 2024). When assessing a candidate in a PS process, there are numerous qualitative and quantitative judgments or factors to consider. Therefore, it is commonly considered as a Multi-Criteria Decision-Making (MCDM) problem (Afshari et al., 2013; Ding et al., 2019; Li et al., 2022; Mallick & Mukhopadhyay, 2023; Tuana, 2018) or a Multi-Actor Multi-Criteria Analysis (MAMCA) problem due to the opinions of the decision-makers. MCDM methods in the PS process help reduce subjectivity and enhance the robustness of the decision-making process, making it easier for decision-makers to identify the optimal candidate for the vacancy (Jasemi & Ahmadi, 2017; Romero et al., 2015; Zulfikar et al., 2018).

A literature review on fuzzy logic for decision-making was conducted by Ruvalcaba Coyaso and Vermonden (2015). The review focuses on how fuzzy logic enhances certainty in the decision-making process and the transition from PS processes to mathematical models. However, this review cannot be considered systematic for several reasons. It does not address specific research questions, lacks a clear selection protocol explaining inclusion or exclusion criteria, and only briefly mentions two inclusion criteria. Moreover, it uses the keywords "personnel selection," "fuzzy logic," and "fuzzy sets" without providing a defined search strategy or equation. In summary, this study provides a general overview of fuzzy logic in PS processes, rather than analysing the various MCDM methods applied to ps. Ahmed et al. (2020) conducted a Systematic Literature Review (SLR) on leadership competencies for a managerial position, particularly with a specific focus on the project manager role, based on empirical research studies. The authors aimed to identify the most prevalent leadership competencies required for this managerial position. Their study reveals that effective communication and developing teams are the most crucial competencies for managing engineering projects. Furthermore, this research highlights that competencies such as goal achieving, critical analysis, empowerment, and strategic planning improve the probability of project success. This contribution provides valuable insights into the leadership competencies required for this managerial position, which could aid in the PS of this profile.

The current study conducts a SLR, which is a scientific research method that analyses relevant literature on a specific topic through a clear and objective question to aim for valid and objective conclusions from the available evidence on the topic (Sánchez-Meca, 2010). The principal purpose of this SLR is to analyse how multi-criteria decision-making methods are applied in PS, focusing on their use in managerial positions, identifying which methods are used to rank candidates to determine the best fit, and which are used to assess each candidate's distance from the ideal profile, and subsequently to develop a further agenda based on the identified gaps.

Section 2 focuses on the methodology, aiming to identify studies related to PS that apply MCDM methods to improve the decision-making in these processes. We propose a general research question and two secondary questions. The secondary questions aim to narrow down the focus to managerial positions, which are of particular interest, and to concentrate on methods involving candidate ranking. The methodology is based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, which establishes a protocol as indicated by García-Peñalvo (2022). The protocol defines inclusion and exclusion criteria, search strategies for the selected databases, and a unique identifying code for the screening phase. Additionally, we include the PRISMA flow diagram, which provides a graphic representation of the selection phases of the review.

Section 3 presents the results of the selected publications in our SLR. Firstly, the analysis covers findings such as the distribution of research across the years studied and the countries of origin of the authors. The ranking of the most cited publications in the two databases used specifies the country of origin of the corresponding author and determines the relative contribution of each country based on citations counts. Secondly, the findings are provided in relation to the formulated research questions, along with other data of interest for the research. The discussion in Section 4 addresses the research questions based on the synthesis of data obtained from the selected publications, all of which are empirical studies.

According to the conclusions and future agenda presented in Section 5, this SLR addresses both research questions: it identifies gaps in the literature and sets directions for future work, including practical recommendations for practitioners and researchers. It concludes that the application of MCDM methods in PS helps to reduce uncertainty by transforming subjective judgments into numerical representations, thus providing transparency and efficiency in the decision-making process. The Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) and its variations are among the most widely applied methods in PS, as they assess the distance of each candidate from the ideal profile for a specific position and rank them to determine the optimal individual. The Analytic Hierarchy Process (AHP) is the second most used approach for candidate ranking. In addition, this study highlights the critical role of PS in managerial positions within private organizations, given the strategic importance of the decision-making process, which affects both revenues and competitive advantage.

As the introduction points out, the aim of this paper is to explore the gaps in the literature concerning ps, with a specific emphasis on the application of multi-criteria approaches for decision-making within selection processes. It also outlines a further agenda including practical recommendations for practitioners and researchers. The proposed methodology is a SLR based on the PRISMA framework (Moher et al., 2010), which is the most commonly used framework in SLR articles. It improves the information of reviews and critically evaluates those already published (García-Peñalvo, 2022). The research questions that the SLR aims to answer must be specific and concise in order to define the scope of the review (García-Peñalvo, 2022). Therefore, we define one main question, along with two secondary questions:

RQ1: What multi-criteria methods are applied in personnel selection?

The rigor and reliability of SLR rely on previous planning and documentation of methodology. Hence, a systematic review protocol is essential for several reasons: (i) it enables careful planning and anticipation of potential problems; (ii) it provides transparent documentation of planned methods, prevents the use of subjective decision-making in determining inclusion criteria and extracting data; and (iii) can reduce duplicated work (Shamseer et al., 2015). For these reasons, a systematic review protocol is required and should include, at a minimum, the finalized research questions, the scope of the review, the timeframe, the inclusion and exclusion criteria, the quality assessment criteria, the data sources, the search terms, and the search equation (García-Peñalvo, 2022). Our SLR protocol employed the following criteria:

According to Figure 2, scientific production fluctuates over the analysed years, although publications are consistently observed each year. The results of the SLR, based on the selected publications, reveal that 23.54% of the studies are concentrated in 2018, with 10 articles, 1 conference paper, and 1 proceedings paper. Following this peak, production decreases steadily until 2022, when an increase is observed, reaching 7 publications. Between 2018 and 2023, 66.67% of the scientific works were focused on this period, representing a significantly higher proportion than in the previous five years of the analysed period. Hence, an upward trend is observed over the last six years. Therefore, it can be concluded that research on the topic of multicriteria methods applied to personnel selection continues every year, reflecting the importance of this topic, with the most notable years being 2018 and 2022.

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Figure 3 shows the countries of origin of the corresponding authors. The countries highlighted in purple represent authors from that location with related publications. The darker the shade of purple, the higher the number of related publications in that country. Most authors are from Turkey with ten publications, representing 19.61% of the total. India has five publications representing 11.75%. The countries with four to three publications include Iran, Taiwan, China, the Czech Republic, and Serbia. Two publications were identified for each of the following countries: Azerbaijan, Egypt, Indonesia, and Vietnam. The remaining works are written by individuals from Brazil, Croatia, Cuba, Cyprus, Lithuania, Malaysia, Saudi Arabia, Slovakia, Spain, and Switzerland, with each country contributing one publication. Asian countries provide a significant contribution, accounting for 68.63% of the publications related to the topic, with Turkey and India standing out. On the other hand, European countries contribute less, representing 23.53% of the total, with the Czech Republic and Serbia at the forefront.

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According to quality standards, Table 4 and 5 show the 17 most cited publications without self-citations in the Scopus and WoS databases, respectively. In addition to these parameters, Table 4 includes the Field-Weighted Citation Impact (FWCI) from Scopus, according to Elsevier (n.d.), assesses the citation performance of a document relative to similar documents within its field. This metric considers factors such as publication year, document type, and associated disciplines. In Table 5, has been added the Category Normalized Citation Impact (CNCI), which is equivalent to the FWCI in WoS. CNCI measures the impact of a document by comparing its actual citation count to the expected citation rate for documents of a similar type, publication year, and subject area (Clarivate-Incites, n.d.). A value above 1.00 in both FWCI and CNCI indicates a higher citation frequency than would be expected in comparison to the average for similar publications in the same field.

Table 4

Publication	Citations	Self-citations	Citations without self-citations	FWCI
Abdel-Basset et al. (2020)	115	0	115	9.25
Nabeeh et al. (2019)	138	31	107	11.09
Sang et al. (2015)	93	4	89	4.16
Heidary Dahooie et al. (2018)	80	7	73	4.35
Karabasevic et al. (2016)	84	25	59	4.0
Samanlioglu et al. (2018)	63	6	57	3.28
Yalçin and Pehlivan (2019)	47	0	47	5.17
Krishankumar et al. (2020)	44	0	44	5.06
Karabasevic et al. (2018)	40	7	33	3.20
Ulutaş et al. (2020)	30	5	25	4.41
Afshari et al. (2013)	24	0	24	0.32
Çelikbilek (2018)	24	3	21	0.89
Efe and Kurt (2018)	21	0	21	1.27
Turskis et al. (2017)	23	5	18	1.32
Jasemi and Ahmadi (2017)	17	0	17	1.16
Chang (2015)	18	2	16	0.51
Bilgehan Erdem (2016)	15	0	15	3.50

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In Scopus, the highest cited articles, cited more than a hundred times, include Abdel-Basset et al. (2020), which proposes a hybrid method using Analytic Network Process (ANP) and TOPSIS based on neutrosophic bipolar numbers to address the Chief Executive Officer (CEO) in a private energy company in Egypt. In second place, Nabeeh et al. (2019) also uses the traditional TOPSIS method but integrate it with neutrosophic Analytic Hierarchy Process (AHP) to select a managerial position in a public organization in Egypt. Both case studies are conducted in Egypt and use similar techniques to address a manager selection process. These similarities are attributed to the participation of the same authors in both articles. In contrast, Nabeeh et al. (2019) have a lower number of citations than Abdel-Basset et al. (2020), but a greater impact than the global average in terms of document type, year of publication and field. They remain in the top two positions in Table 4, with values that are significantly above the average, 11.09 and 9.25, respectively. With regard to Yalçin & Pehlivan (2019), it should be noted that although it does not occupy a position at the forefront in terms of number of citations, ranking at number eight, it has a greater impact than Sang et al. (2015) despite having a lower number of citations. This is indicated by its FWCI of 5.17, positioning it at the third highest impact level.

According to the citations in WoS, the highest cited publications with more than eighty citations are Nabeeh et al. (2019) in the first place, which is the second most cited paper in Scopus, and Karabasevic et al. (2018). In this study, they propose the Stepwise Weight Assessment Ratio Analysis (SWARA) to determine the weights of the criteria and the Evaluation based on Distance from Average Solution (EDAS) to rank and select the candidates in an it company for a non-managerial position in Serbia. It is noteworthy that the most cited article is not the one with the highest impact. Nabeeh et al. (2019) rank fourth in terms of citation impact, while Ulutaş et al. (2020) hold the top position with a CNCI of 7.09, despite being ranked tenth for the number of citations. Similarly, although Dockalíková & Kashi (2013b) is the least cited article in Table 5, it ranks according to citation impact with a value of 5.57.

Table 5

Publication	Citations	Self-citations	Citations without self-citations	CNCI
Nabeeh et al. (2019)	88	0	88	5.51
Karabasevic et al. (2016)	81	0	81	6.27
Sang et al. (2015)	79	0	79	2.58
Heidary Dahooie et al. (2018)	67	0	67	3.56
Samanlioglu et al. (2018)	54	0	54	2.47
Karabasevic et al. (2018)	39	0	39	2.97
Yalçin and Pehlivan (2019)	39	0	39	1.98
Krishankumar et al. (2020)	38	0	38	2.27
Abdel-Basset et al. (2020)	25	0	25	1.79
Ulutaş et al. (2020)	24	0	24	7.09
Afshari et al. (2013)	20	0	20	0.81
Çelikbilek (2018)	17	0	17	1.06
Efe and Kurt (2018)	17	0	17	0.9
Chang (2015)	17	0	17	1.23
Jasemi and Ahmadi (2017)	12	0	12	0.99
Bilgehan Erdem (2016)	11	0	11	0.55
Dockalíková and Kashi (2013b)	7	0	7	5.57

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In conclusion, considering both databases, the three highest cited publications correspond to the following papers: Abdel-Basset et al. (2020), Nabeeh et al. (2019), and Karabasevic et al. (2018). Two of these studies analyses the selection process for a managerial position, which addresses the first research secondary question of this systematic review. Based on the citation impact as determined by the FWCI, over 80% of the 17 most cited publications in this systematic review exceed the value of 1, indicating that they are above the expected global average. Regarding the CNCI, 76% are higher than the average. Combining the most cited publications from the two databases results in Table 6, which lists the eighteen top publications and their respective countries of origin. It is noteworthy that Turskis et al. (2017) are found exclusively in Scopus, while Dockalíková and Kashi (2013b) is only indexed in WoS.

Table 6

Publication	Country
Abdel-Basset et al. (2020)	Egypt
Nabeeh et al. (2019)	Egypt
Sang et al. (2015)	China
Heidary Dahooie et al. (2018)	Iran
Karabasevic et al. (2016)	Serbia
Samanlioglu et al. (2018)	Turkey
Yalçin and Pehlivan (2019)	Turkey
Krishankumar et al. (2020)	India
Karabasevic et al. (2018)	Serbia
Ulutaş et al. (2020)	Serbia
Afshari et al. (2013)	Iran
Çelikbilek (2018)	Turkey
Efe and Kurt (2018)	Turkey
Turskis et al. (2017)	Lithuania
Jasemi and Ahmadi (2017)	Iran
Chang (2015)	Taiwan
Bilgehan Erdem (2016)	Turkey
Dockalíková and Kashi (2013b)	Czech Republic

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Figure 3 shows that Turkey stands out as the country that has published the most studies on the topic. Table 7 also highlights that half of its publications are among the most cited, representing 27.78% of the highest cited publications. In contrast, India, the second country with the most contributions according to Figure 3, has only one study on the list of the most cited studies. Iran and Serbia each account for 16.67% of the most cited scientific works. In the case of Iran, three out of the four papers published are listed in Table 6. As regard Serbia, 100% of its contributions are among the most cited. Egypt is in a similar situation. Both contributions are listed in Table 6 and, as mentioned above, are among the three most cited studies.

Table 7

Country	Number of publications included in Table 6	Percentage
Turkey	5	27.78
Iran	3	16.67
Serbia	3	16.67
Egypt	2	11.11
China	1	5.56
Czech Republic	1	5.56
India	1	5.56
Lithuania	1	5.56
Taiwan	1	5.56

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In response to the first research question, drawing on the results of the review summarized in Table 8, the findings demonstrate the significance of PS in private organizations, 56.86% of the studies are concentrated on this type, among which 72.73% of the publications have been conducted on the selection of managerial roles, emphasizing the importance of investing in the selection of a leader. Since it is a strategic decision-making process that will affect the performance of the organization in terms of customer satisfaction, quality, innovation, profitability, and competitiveness, as indicate by Dwivedi et al. (2020), who propose a model for selecting a team of managers to launch a new business line in a supply chain company. Within the managerial position, the Project Manager role is the most analysed position, accounting for 18.18%. This is because project management competencies are crucial to ensure the growth and sustainability of an organization. Therefore, selecting candidates for this position is a challenge. In addition, project management involves a high level of risk due to the nature of projects. Lima and Gomes (2022) propose a behavioural TOPSIS that enables the categorization of the candidates' risk profiles for decision-makers, assessing whether they tend to accept risks or show risk aversion.

In terms of sectors, the it industry is the most predominant in managerial vacancies and ranks second for non-managerial positions, indicating a high demand for qualified personnel with managerial skills in it companies. The Education sector stands out in non-managerial vacancies in comparison with the it sector. Among the studies focusing on the selection of academic staff, approximately 80% relate to Higher Education, such as universities or faculties. Redep et al. (2015) emphasize the challenge of evaluating candidates for academic positions in Higher Education due to the intense competition for qualified teaching staff with doctoral degrees and the limited number of available positions. The large pool of candidates, who meet the minimum legal requirements, increases the complexity of the selection process. Consequently, this study proposes a model that incorporates additional criteria and sub-criteria and weights them using the AHP. This method involves a pairwise comparison of criteria to determine their relative importance. Based on the relevance of these criteria, assessments can be conducted, and this approach enhances decision-makers' efficiency by facilitating a faster, more objective, and transparent selection of the best candidate for a faculty position. Other authors, such as Paraskevas et al. (2022) and Nallakaruppan and Kumaran (2018), have utilized AHP in combination with different variants to address faculty member selection in Higher Education. Despite the significance of these roles in Higher Education, the analysis of the publications does not identify any vacancies related to managerial skills. Consequently, this could be identified as a gap in the literature.

On the other hand, as indicated in Table 8, most publications selected for this systematic review (72.55%) lack an exhaustive description of each criterion or competency. Such information is essential for decision-makers to assess candidates, as well as the competency level that each candidate must attain for the specific job position. Wang et al. (2022) propose the establishment of a competency library aligned with departmental goals. This library provides a brief definition of the main criteria and sub-criteria. Afterward, qualitative levels are described, allowing the interviewer to assign a generic level to each candidate for each competency: no expertise, emerging, developing, intermediate, advanced, very advanced, or expert. However, these studies do not include a rating scale for each competency, such as a scale from 1 to 5 which defines the meanings for each level. Regarding the test conducted to assess the competencies of each candidate, the publications do not demonstrate how the interview is structured to evaluate the competencies of each candidate. However, Wang et al. (2022) briefly explain the selection process without going into detail about the interview or examination they present to them. In conclusion, the absence of the rating scale, which includes the meaning of each level for each competency and the method of assessment, represents two additional gaps in the literature reviewed.

The competencies or criteria associated with positions are often derived from the literature, as seen in the study by Heidary Dahooie et al. (2018). Therefore, it is understood that prior analysis and design of the position (job description) have not been conducted or shown in the publication specifically in each organization. This means there is a lack of the analysis of functions, tasks, responsibilities, and competencies needed to meet the requirements, leading to the adoption of generic competencies. On the other hand, Altuntas and Yildirim (2022) conducted a study on the competencies required in job postings for the vacancy to be filled but they do not develop or provide the job description. Turskis et al. (2017), Paraskevas et al. (2022), and Chang (2015), use the Delphi method with experts to establish the criteria for evaluating candidates for a specific position, but they do not provide details on the procedure followed, corresponding this another gap in the reviewed publications.

Addressing the second research question, various MCDM methods are used for ranking candidates to identify the most suitable individual and to calculate each candidate's distance from the ideal profile. TOPSIS method and its variants, based on the premise that the optimal candidate, has the highest similarity to the positive ideal alternative and the lowest similarity to the negative ideal alternative is present in almost half of the publications (47.06%). Table 9 shows some variants of the TOPSIS method found in the analysed publications and their contributions. Most variations of TOPSIS are used to model uncertainty and data imprecision, including evaluations from decision-makers in PS (Ramdania et al., 2020; Ş enel et al., 2018). Typically, the TOPSIS method is combined with another technique prior to candidate ranking to assign importance to criteria (Dockalíková & Kashi, 2013a; Mediouni & Cheikhrouhou, 2019). For example, Samanlioglu et al. (2018) and Òzdemir (2013) suggest using the AHP for the selecting it personnel and in the textile sector, respectively. Similarly, Chang (2015) suggests the employment of the ANP to derive the weights of the criteria and consider the interdependencies among them in the selection of managerial positions. Table 10 shows the additional relevant methods used to rank candidates and identify the optimal fit for the position, some of which compare each candidate with an ideal profile. Finally, there are other candidate sorting methods applied to PS that are not as relevant in this study because they only appear in one publication, and they are also combined with AHP, such as the Weighted Sum Approach (WSA) (Dockalíková & Kashi, 2013a) or Grey Relational Analysis (GRA), which calculates the distance between the candidate and the ideal profile (Kucuk & Atilgan, 2019). Methods that also involve the ranking of candidates, but whose authors combine them with other methods different from AHP, are combinative Distance-based Assesment (CODAS) (Yalçin & Pehlivan, 2019) and viseKriterijumska Optimizacija I Kompromisno Resenje (vikor) (Krishankumar et al., 2020). The latter also measures the candidate's distance from the ideal profile for a given vacancy and organization, specifically in the it sector.

Table 9

TOPSIS variants	What does it contribute in relation to TOPSIS?
Neutrosophic TOPSIS	The use of the neutrosophic set aim to improve the accuracy of the evaluation process for decision-makers. According to Abdel-Basset et al. (2020), the neutrosophic approach facilitates the characterization of uncertainty across multiple factors and simplifies the complex judgment phase. This could enable leaders or managers to deal with uncertain information and address the selection of managerial positions in private and public organizations, as suggests Nabeeh et al. (2019).
Fuzzy TOPSIS	To deal with the uncertainty and ambiguity inherent in the decision-makers judgements, fuzzy TOPSIS uses fuzzy sets to express the decision-makers information and preferences. First, the distance to the fuzzy positive ideal solution, the distance to the fuzzy negative ideal solution, and the closeness coefficients (CC) are calculated. Then fuzzy TOPSIS determines the ranking of the candidates based on the CC. The difference is that TOPSIS works with real and deterministic values, while fuzzy TOPSIS considers the uncertainty and imprecision of the data to calculate the distances to the ideal solution. Several selected publications of this review use this variant of TOPSIS or with fuzzy numbers (Efe & Kurt, 2018), in particular some authors such as Baharin et al. (2021), Jabbarova and Jabbarova (2023), and Sang et al. (2015) apply these methods to address managerial position selection processes. On the other hand, this variant also applies to the education sector, where selecting high-quality teachers is of considerable importance, as it is related to the success of students both in university (Behera & Sarkar, 2013; Dung et al., 2018) and secondary school (Zaganjori et al., 2020).
Behavioral TOPSIS	In the case of Project Manager vacancies, the risk profile of the candidates has been the subject of evaluation. In TOPSIS, the candidate ranking is determined based on the results of the decision-makers candidate evaluations and the subsequent calculation of the CC proximity index. Behavioural TOPSIS, in addition to calculating the ranking, incorporates the loos aversion rate A into the value function Vof each alternative (candidate). This results in different A values and thus different rankings for the three risk perspectives V aggressive, V neutral and V conservative (Lima & Gomes, 2022).
Multi-objective optimization based on TOPSIS	This method is a modification that concerns only certain aspects of the HR management task. To include additional elements in TOPSIS, consider the following: decision-makers group, hierarchical structuring of criteria, assigning significance weights to criteria, and the experience of experts involved in assessing candidates. Mammadova and Jabrayilova (2018)) suggest the consideration of scientific expertise in the algorithmic factors related to the evaluating alternatives. TOPSIS based multi-objective optimization improves decision-making accuracy by prioritising based on proximity to the ideal solution, thus ensuring objectivity and transparency of managerial decisions.
TOPSIS-LP	Dwivedi et al. (2020) propose TOPSIS with Linear Programming (LP) to improve the assessment of the decision-makers by considering the restrictions imposed by the business, such as salary, maximum annual budget per employee, and limitations on the number of positions for each vacancy. The use of LP makes it possible to optimise both the cost and efficiency of the selection process, identifying the key positions to fill to build an efficient team at minimum cost.

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Table 10

MCDM methods that involve candidate ranking or comparing each alternative with an ideal solution	What does it contribute?
AHP	Some authors use AHP as an evaluation system model without using a ranking method to select the best candidate (Bahurmoz et al., 2015; Bilgehan Erdem, 2016; Lele, 2015). Chen et al. (2015) establish an assessment model for recruiting dual-qualified nursing teachers. The model uses AHP p to provide a quantitative analysis approach, determining the weight of criteria such as biographical analysis, theoretical knowledge examination, clinical nursing skills assessment, and interview and lecture evaluations. After the evaluation by experts, a table is generated with the scores assigned to each candidate for each analysed criteria, obtaining an average of each expert's opinion for all criteria. These scores are determined based on the previously assigned weights, and the result is obtained for each candidate. This method could be useful for the selection of the dual-qualification nursing teacher. Selecting this profile can be challenging because qualified candidates may not be readily available. However, it is a crucial role in the nursing profession as it bridges the gap between theory and practice in these studies (Chen et al., 2015).
ARAS	The role of Director for Estates and Economy Office, as presented in the real case study by Turskis et al. (2017)), is a challenging managerial position due the multidisciplinary nature, making it particularly difficult to assess the criteria. The authors describe the competencies and scales used to determine the criteria values. Criteria are ranked by experts from most to least important, and each expert constructed a pairwise comparison matrix. Subsequently, the criteria weights are then calculated based on the opinions of all experts. The Additive Ratio Assessment (ARAS) is then used to address the problem. ARAS is a method that compares pairs of alternatives and assigns preference values to each pair, rather than comparing each alternative with an ideal solution and anti-ideal solution as TOPSIS does. After constructing the normalized-weighted decision-making matrix, it is obtained the candidate ranking by calculating the weighted sum of preference values for each alternative. This determines the best performance assessment and solves the PS problem. This method can be applied to select other managerial positions, such as a sales director at a manufacturing company (Karabasevic et al., 2016), or to address other types of vacancies in the it sector, as demonstrate by Heidary Dahooie et al. (2018).
EDAS	The EDAS method calculates the distance between each alternative and the average solution, evaluates their relative performance and provides a ranking of alternatives based on their relative distance to the average solution. Turskis et al. (2017) use this method in the same case study, resulting in identical candidate rankings, demonstrating its effectiveness in addressing complex PS problems. Similarly, Karabasevic et al. (2018) propose a model based on EDAS to assist decision-makers in identifying the most suitable candidates effortlessly. The model is flexible and can incorporate additional criteria or sub-critera to align with specific objectives in the it business.
PROMETHEE	The Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) method relies on pairwise comparisons of decision points based on evaluation factors. Importance weights reflect the relationship level between evaluation factors, and each evaluation factor also considers its internal relationship. Daniçan et al. (2022) apply this method in a PS at a high-quality textile factory, where the position plays a crucial role in the functioning of the sewing line. The weights for the selection criteria were calculated using AHP and then utilized in the PROMETHEE method to rank the five candidates. The results were compared with TOPSIS, and the same raking was obtained. PROMETHEE is a valuable instrument for ensuring effective PS in all sectors and fields. It has been noted by authors such as Chen and Hung (2020) and Anisseh et al. (2016) use it in their case studies to select a marketing manager and a project manager respectively, in different sectors.

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PS becomes a challenge in a company or organization, decision-makers make decisions based on qualitative methods such as interviews or group activities. These methods could use ambiguous expressions and imprecise terms throughout the process, leading to uncertain judgments and reducing the effectiveness of investments in human capital (Abdel-Basset et al., 2020). In terms of the impact, the metrics used in the databases demonstrate that including quantitative measures, such as multi-criteria methods applied to the PS, improves the decision-making process. This is evidenced by the high impact of the publications selected in this SLR, with over 80% of the most cited works exceeding the established average.

The SLR presented in this paper addresses two research questions, one based on selecting managerial positions and the other based on MCMD methods applied to selection processes, both widely discussed in Section 3.3 and leading us to identify gaps for researchers and practitioners in candidates' selection. This paper builds upon the existing review by Ruvalcaba Coyaso and Vermonden (2015) on a related topic in several ways. First, it adapts the PRISMA procedure to the context of this investigation. Second, our review establishes inclusion and exclusion criteria that align with the research questions and develops a specific systematic review protocol for selecting publications. This process improves the information provided in the previously published reviews on the topic, while also enhancing the rigor and reliability of our review. It avoids subjective decisions and reduces duplicated work.

Following a comprehensive examination of the 51 selected publications and the subsequent analysis, this systematic review addresses two research questions. Regarding the first research question, the findings emphasize the significance of ps within private sector entities, with more than half of the publications focusing on this area. Specifically, over 70% of these studies concentrate on managerial positions. This fact highlights the importance of investing in the selection process of these vacancies, as it is regarded as a strategic decision-making process. It can be concluded that the application of MCMD methods in PS problem enables the handling of both quantitative and qualitative judgments, transforming linguistic values into quantitative data to reduce subjectivity, and identifying the optimal candidate for the vacancy, particularly relevant to managerial positions. Addressing the second research question, among the MCMD methods used for candidate ranking to determine the ideal fit for the position, TOPIS and its variations are one of the most utilized in PS, as they determine the distance of each candidate from the ideal profile for a given job position. In contrast, AHP is the second most applied method for ranking candidates. It is worth noting that in almost all the publications reviewed in this systematic review, multiple MCMD methods are often combined to solve the PS problems.

Regarding the founded gaps, it can be observed that the reviewed publications do not address the selection of leadership roles, such as deans, associate deans, program directors, department chairs or faculty responsible for national and international accreditation among others in Higher Education. In addition, a later study by Izar Landeta et al. (2023) apply five MCMD, including TOPSIS, to address a case of faculty selection, though not for managerial positions. This is even though managerial positions are significant within this context. Therefore, we recommend as further research agenda to investigate the criteria and processes employed in selecting academic leadership positions, to identify the competencies and soft skills that should be considered in the candidates for such roles. While some competencies may be common with those of professors, others will be specific to the managerial role. This information would be highly valuable to Chief Human Resources Officers (CHRO) in educational institutions, who must integrate these managerial competencies into their institution's information systems. A further gap related to the selection process is the absence of a comprehensive methodology for analysing and designing specific job vacancies. To address this gap, further research is recommended to demonstrate the entire process of analysing responsibilities and tasks, indicating the competencies or criteria to design a specific job description. It is also necessary to specify the required level for each criterion applicable to each position. We suggest that the CHRO may implement MCMD methods to analyse, design, and select job positions. This fact leads to facilitate the description of more accurate job positions, thereby enabling to attract suitable candidates and implement a more rigorous and objective selection process.

This review identifies two gaps in the literature related to competencies. The first is the lack of a rating scale that includes comprehensive descriptions of each level for each competency in most publications selected for this SLR. The researchers may study new models that incorporate a rating scale when integrating mcmd methods into selection processes. As future agenda for CHRO or selection professionals will be the creation of a comprehensive and detailed dictionary of competencies aligned with the organization, outlining both general and specific competencies or criteria for each position, including a detailed definition of each competency, as indicated by Wang et al. (2022). Additionally, we recommend establishing scales (e.g. from 1 to 5) for each competency and defining the meaning of each scale. This framework would facilitate a more comprehensive understanding of the assessment criteria for each vacancy. The second gap is the lack of clarity regarding the candidate assessment methodology. The reviewed studies do not explicitly demonstrate structure of the interviews, or the techniques employed to analyse the competencies of each candidate. It is therefore recommended as further research agenda to include details of the evaluation techniques in their investigations, as it is essential for personnel selection professionals to have a guide for designing assessment tests or the structure of the interview based on criteria or competencies.

Table 11 provides a summary of the gaps identified in this SLR, specifying whether they are related to researchers or practitioners, whether they pertain to the methodology, and outlining the proposed future agenda for researchers and practitioners.

Table 11

gap	Related to researchers	Related to practitioners	Related to methodology	Future agenda for researchers	Future agenda for practitioners
Lack of selection of managerial roles in Higher Education when integrating MCMD methods.	(	(	(	To investigate the criteria and processes employed in selecting academic leadership positions. To identify the competencies and soft skills to managerial role in Higher Education.	To integrate the competencies and soft skills required for managerial roles into the information systems of institutions.
Absence of a methodology for job vacancy analysis and design specifically when integrating MCMD methods.	(	(	(	To model and monitor the process for analysing and designing job positions by identifying competencies and required level including MCMD methods.	To implement MCMD methods to analyse, design and select job positions. To integrate competency-based job positions into the recruitment and selection process.
Lack of a rating scale that defines each level for each competency when integrating MCMD methods.	(	(	(	To propose how to incorporate a rating scale when integrating MCMD methods into selection process.	To determine the general and specific competencies or criteria aligned with the organization. To define each competency elaborating a detailed dictionary of competencies. To establish scales for each competency and define the meaning of each scale level.
Insufficient clarity regarding the candidate assessment when integrating MCMD methods.	(	(	(	To describe how to incorporate evaluation techniques into the models.	To design assessment test and structure of the interview base on criteria or competencies.

Contribution Roles (CRediT taxonomy)

Ana López-González: conceptualization; methodology; formal analysis; visualization; data curation; writing-original draft; writing-review/editing; investigation.

Eugenia Babiloni: conceptualization; methodology; formal analysis; writing-review/ editing; supervision.

Lourdes Canós-Darós: conceptualization; methodology; formal analysis; writing-review/ editing; supervision.

All authors read and approved the final manuscript.

Conflict of interest: The authors declare that they have no conflict of interest.