Can Talent Management Improve Training, Sustainability and Excellence in the Labor Market?

Abstract

The objective of this article is to analyze the characteristics of the most attractive companies in the labor market, which each year maintained their position in the ranking published by the Spanish business magazine Actualidad Económica (AE) for the period 2013–2020. The research study will focus on permanence in ranking, global valuation, and training. To do this, control variables were added: business management gender, geo-cultural areas, regional areas, economic activity, size and stock market membership. This is a quantitative work, where statistics such as partial correlations, Pearson coefficients and independent sample means were used with the Levene test; in modeling, multiple regressions of ordinary least squares (OLS) and panel data were used. It is concluded that the permanence in the ranking significantly increases the total value and training, which leads companies to excellence, along with the fact that they are in the capital of the country and that they focus on the commerce, professional, scientific and technical, and finance and insurance sectors. On the other hand, assessment of training is explained by employee valuation, the work environment and talent management. On the contrary, factors such as the gender variable in the business direction, nationality, size and stock market membership do not significantly influence the overall valuation.

1. Introduction

Successive economic crises around the world have resulted in job losses for millions of workers, many of whom will struggle to re-enter the labor market. The present COVID-19 crisis, which is impacting at the health, social and economic levels, has only aggravated the situation in the labor market, with an unemployment rate of 16% in the last quarter of 2020 in Spain. Therefore, if having a stable job in the current situation is a great asset, it is even more valuable if it is performed in one of the 100 most valued organizations in the labor market, sustaining itself throughout the period of analysis (2013–2020) in the ranking published by the business magazine Actualidad Económica, hereinafter AE, even during the COVID-19 pandemic.

The objective of this article is to study the factors that can influence the valuation obtained both in training, and the total valuation of the companies that persist every year (2013–2020) in the ranking of the 100 best companies to work for in Spain. Sustainability in the ranking will be shown to be synonymous with excellence and attributes that may explain this fact will be also analyzed, such as: the gender in business management, nationality, geo-cultural areas, regional areas, economic activity, size and stock market membership.

2. Theoretical Framework

Markets are evolving towards globalization, in which the importance of information technologies increases, which allows business competitiveness to increase [1]. This phenomenon has been reinforced with the COVID-19 pandemic, as telework spreads in companies and society at large. In this context, the knowledge economy and business training have become more relevant thanks to information and communication technologies (ICT), so that companies have more tools to compete in a globalized market [2]. The intangible assets of companies, including the training and skills of workers, knowledge and technological integration, and knowledge about the functioning of the market and business management in a global economy [3], increase productivity and the efficient management of resources. Investment in business training is essential to maintaining the competitiveness of companies [4] and human capital is a great asset that, through investment in business training, increases the productive capacity of the organization [5].

Conversely, there is an existential crisis in business education driven by the conflict between social and financial objectives. A paradigm shift in business education requires leaders to learn how to incorporate new competencies. It leads companies to continuous innovation and highly sustainable performance [6]. The misalignment between the education system and companies hinders the job market [7]. Business education should contribute to companies’ members generating social value and demonstrating sustainable performance [8,9].

The existence of rankings that categorize companies according to job performance, such as Fortune 100 in the USA or Great Place to Work in Europe, adds corporate value contributing to generating an image of a good organization [10]. There are, in this regard, studies that refer to human resources rankings, including that of the Spanish magazine Actualidad Económica [11].

It is worth noting the importance of innovation for companies, markets and society [12], since it is fundamental to long-term profitability and sustainability [13]. Innovation leads to commercial and financial success, but society demands that innovation be carried out in a responsible and ethical manner [14]. If change and doing things differently was already important in Schumpeter’s time, the market is now evolving into one based on innovation and ICT [15], it being essential for most companies to adopt this approach. Business digitalization consists of the implementation of digital tools and technologies as well as data, which together can make business processes more efficient and effective [16]. Digitalization is also improving the sustainability of companies [17].

A study on the integration of responsible innovation (RI), a concept integral to companies’ practice, obtained results that link responsible innovation (RI) practices in the context of corporate social responsibility (CSR), sustainability and ethics [18]. In order to better adapt to change, organizations must have some essential attributes, and nowadays the buzzwords have become sustainability, digitization, resilience and agility [19].

A few years after Schumpeter’s theories were published in the 1960s, the role of education and how profitable investments in human capital were in increasing the productivity and motivation of professionals [20] were highlighted. Thus, economies that base their productive model on low-value-added activities, using low-skilled labor, become more vulnerable in periods of recession (such as that being lived through due to COVID-19), destroying many jobs, as they are the easiest and cheapest to destroy [21]. The absence of skilled human capital, training, and knowledge harms the economic development of an organization [22], and this prevents sustainable development over time of companies and economies. High professional qualification entails the need to manage talent, provide constant business training, provide higher remuneration, and engage in permanent recruitment. All this contributes to improving the working environment and an increasing identification of the employee with the organization, which results in greater business productivity [23].

It also highlights the importance of people’s overall ability (work ethic, assimilation of experience, natural intelligence, commitment, etc.), which means that people tend to extract higher performance from training [5]. Talent management is related to training and companies, which in order to thrive need to develop a talent recruitment strategy through investment in incentives and training programs [24]. Commitment to leadership, as well as the autonomy, competence, and relationship between employees, is a good strategy of attracting and retaining talent positively related to labor commitment [25]. In addition, job satisfaction largely determines organizational success, as dissatisfaction has negative effects on productivity [26].

The basic competitive advantage of companies lies in the level of training and management of human talent or human resources [27]. In the same line, it is established that the systemic interrelationship between knowledge, competencies, innovation, and competitiveness is a tool for the management of human talent by skills, which allows organizations to increase their productivity and competitiveness [28]. Companies that develop strategies capable of attracting talent, with sustained training over time, will promote innovation, productivity and competitiveness in the market [29]. The satisfaction of professionals increases with human resources policies that promote talent management and training [30]. The conclusion therefore drawn is that training is a key element for attracting and retaining talent, as investment in training is a resource that benefits both businesses and workers [31]. A responsible company is one that allows professional development according to the worker’s needs [32]. Training helps to improve the skills of professionals by increasing their intentions to remain in the company, productivity and the position of the company in the market [33,34]. Adopting a global approach to talent management can create long-term sustainable organizational success [35].

On the other hand, competitiveness lies in adapting and regenerating the assets of training, knowledge, and competencies, as well as developing and strengthening the organizational capacities that translate this knowledge into effective actions [36]. Research on talent management shows that management strategies promote companies’ transformation and growth processes and increase their competitiveness in the global market [29]. Education is the preparation by and for life, the purpose of which is to prepare the person both within and outside the working environment [37].

Financial capital ceases to be the most important resource and gives its place to knowledge, as applying knowledge profitably is more important than money [38]. People, from the caretaker services to senior management, bring organizations to life with their dynamism, creativity, and rationality [39]. This implies that all people need training to carry out their tasks efficiently so as to be able to contribute to the development of the company. In the Information Age, employment has shifted from the industrial sector to the services sector and manual labor has been replaced by intellectual work, which marks the path of the post-industrialization era, based on knowledge and the tertiary sector [40]. The trend of the labor market is innovation and technology, the globalization of markets, the virtual economy and an emphasis on services and knowledge sectors [41]. Companies, in order to compete sustainably over time, will have to boost the knowledge economy, which implies good talent management and continued business training [42].

3. Materials and Hypothesis

The following hypotheses have been raised to achieve the objectives of this research.

Hypothesis 1.

“Adequate talent-management improvestraining in the company”.

The talent management of a company has a positive impact on the productivity and motivation of professionals, and the more talent there is in an organization, the more training is demanded to maintain the level of excellence, as can be seen in the works of [24,35,43].

Hypothesis 2.

“For training efforts to take effect, an adequate working environment is needed”.

A bad working environment can cause irreparable damage to businesses. For talent management and training to generate added value, a good working environment [44] is required. Satisfied workers increase the value of companies [45].

Hypothesis 3.

“High levels of corporate social responsibility (CSR) influence a company’s sustainability in the ranking”.

Companies with a good corporate reputation have a sustainable competitive advantage [46]. CSR is seen as an important element that influences the good perception of companies and their professional attractiveness [47].

Table 1. Variables used by AE.

Variable	Description	Maximum Score	% o/Total
Talent Management	Projection, performance and unwanted rotation	240	24%
Remuneration	Combination of fixed, variable wage, remuneration in kind and social benefits	225	22.5%
Work Environment	Working hours, telework, family reconciliation and working conditions	205	20.5%
Corporate Social Responsibility (CSR)	Social and volunteer policies involving staff	50	5%
Training	Educational Investment received by the employee	220	22%
Employees Perception	Valuation of the professionals of the company in which they work	60	6%
TOTAL	Sum of scores	1000	100%

Source: Own elaboration.

describes the variables used by AE, which make up the six pillars used in the preparation of the annual ranking, based on a questionnaire containing 100 questions. Next to each variable is the maximum score that each company can obtain for it. The questionnaire was completed out by human resources experts from more than 500 companies. Companies that can participated and qualified for the ranking of the 100 best companies to work for in Spain had to meet the following requirements: operating in Spain, having more than five years of operation and having a workforce of more than 100 employees.

The variable under study (training) had a maximum value of 220 points, similar to the other two characteristics that are most important in determining the total valuation of the company, namely remuneration and talent management (a variable that relates to training). The total scores amount to 1000 points. In 2020, AE changed the scale to 1375 points, and these scores were adapted to the scale used in the first seven years (2013–2019), with a maximum of points being 1000 points.

Table 2. Control variables, added to the study, of AE’s ranking companies.

Variables	Justification
Number of years in the ranking	This is measured by the number of years that companies have remained in the ranking. Companies remaining in the ranking throughout the 8-year period are considered the most excellent from the point of view of the labor market.
Gender management	Classifies companies according to whether management is exercised by men or women.
Geo-cultural areas	They are grouped by countries and cultural areas, such as Anglo-Saxon, Central-North European or Mediterranean European and Asian areas.
Regional areas	Companies are grouped according to the tax domicile by regional areas that group regions (Autonomous Communities). Madrid, the Mediterranean and Northern Spain are identified
Economic activity	Analyses what the economic sectors of companies are, and, for this, they are classified according to the CNAE code and grouped by the first digit.
Size	Calculates the number of workers in the companies that work in Spain.
Trading in the stock market	Classifies companies according to whether they issue its shares on financial markets admitted to trading.

Source: Own elaboration.

shows the objective control variables added for conducting the study. The first variable, the number of years that companies have remained in the ranking, focuses the analysis on the excellent companies, which are defined as the companies that are included in the ranking every year. The second variable ranks companies according to the gender of the company’s management. No studies have been found that have linked management according to gender and management excellence through sustainability in a ranking of the companies which are best to work for. Geo-cultural areas bring companies together by country, classifying them in Anglo-Saxon; North-Central European, Mediterranean and Asian areas. The regional areas correspond to the locations of companies in the three most important areas of Spain (Madrid, the Mediterranean and Northern Spain). The following variables, such as the economic sector in which companies are engaged, are classified by the first digit of the National Classification of Economic Activities (CNAE) code. The size is measured according to the number of workers working in Spain. Finally, the variable of being listed on the stock market will be used.

Table 3. Number of companies and records according to number of years in the ranking.

Number of Years in the Rankings	NO. Companies	%o/Total	NO. Records
1	115	40.64%	115
2	54	19.08%	108
3	34	12.01%	102
4	22	7.77%	88
5	15	5.30%	75
6	12	4.24%	72
7	14	4.95%	98
8	17	6.01%	136
Grand Total	283	100.00%	794

Source: Own elaboration from the data published in Economic News (2013–2020).

shows the 794 records corresponding to the ranking during the 8-year period of 2013–2020. Only 6% of companies managed to be in the ranking every year, and it is that group of companies that the research in this article will focus on. The objective is to analyze whether the permanence in the ranking influences a higher valuation obtained by companies in a significant way, as well as to analyze whether there are external variables that can influence the results obtained, such as gender in management, geo-cultural area, regional area, type of activity, size or stock market membership.

4. Quantitative Analysis

To achieve the objectives described above, different analysis techniques will be used: unifactorial variances with the Levene test, statistical analysis, as well as a model with different specifications of minimum ordinary least squares (OLS) and panel data, that will try to measure empirically whether there are certain dichotomous or numerical variables that have some kind of significant effect on the total valuation of companies in 2020, in the first type of model, or on what affects the valuation of training, throughout the period of the preparation of the ranking (2013–2020), in the second type of model.

4.1. Descriptive Statistical Analysis

Table 4. Average valuations of companies sorted by years in the ranking.

N0 Years in Ranking	Talent	Remuneration	Environment	CRS	Training	Employees	Total
1	165.3	141.7	140.7	37.2	155.3	54.2	694.4
2	171.0	155.4	150.2	38.7	165.7	55.0	736.1
3	172.6	155.9	154.5	40.1	165.2	55.9	744.3
4	176.9	162.8	152.6	40.4	178.6	53.5	764.5
5	185.4	166.7	163.0	42.5	180.3	57.2	795.1
6	184.4	156.7	155.6	43.1	183.0	58.4	781.3
7	179.5	169.5	161.5	44.3	177.8	59.3	791.8
8	190.1	183.6	172.0	43.6	188.1	59.2	836.7
TOTAL	177.9	162.1	156.5	41.2	173.9	56.6	768.0
% 8 years/1 year	115.0%	129.5%	122.3%	117.1%	121.2%	109.2%	120.5%
% 8 years/potential value	79.2%	81.6%	83.9%	87.2%	85.5%	98.6%	83.7%

Source: Own elaboration from AE data (2013–2020).

shows an upward trend in the valuation of all items as the number of years of companies remaining in the ranking increases. There is a 20.5% increase in total value and a 21.2% increase in training valuation reached by organizations that remain in the ranking for eight years compared to the ones which stay in the ranking for a single year. In turn, when compared to the potential value, training is the most valued item (85.5% over potential value), scoring above talent management, remuneration, and work environment. The conclusions obtained in a previous study that referred to the period 2013–2016 did not show the permanence in the ranking to be a factor that influenced the valuation of the items [48]. However, in this article, the conclusions differ, since it is appreciated that sustainability in the ranking influences total valuation and training.

It can be seen in

Table 5. Testing independent samples of average values classified according to permanence in the ranking (2013–2020).

Variables	Years in the Ranking	N	Media	F.	Sig.	Test Levene	Sig. (Bilateral)
Talent	8 years old	136	190.5	0.117	0.732	Equal variances are assumed	0.000
	7 years	98	179.47
Remuneration	8 years old	136	183.56	12.594	0.000	No equal variances are assumed	0.000
	7 years	98	169.51
Environment	8 years old	136	172.04	0.246	0.621	No equal variances are assumed	0.000
	7 years	98	161.45
CSR	8 years old	136	43.61	1.386	0.240	Equal variances are assumed	0.334
	7 years	98	44.27
Training	8 years old	136	188.13	0.242	0.623	Equal variances are assumed	0.000
	7 years	98	177.84
Employee rating	8 years old	136	59.18	0.402	0.526	Equal variances are assumed	0.935
	7 years	98	59.29
Total	8 years old	136	836.74	0.132	0.717	Equal variances are assumed	0.000
	7 years	98	791.83

Source: Own elaboration from AE data (2013–2020).

that companies that have been in the ranking for eight years (excellent company) in relation to those that have been in the ranking for seven years obtain a higher and significant valuation in four of the six items, including training, in addition to total. Therefore, the mere fact of being in the rankings for one more year makes their ratings superior in a revealing way. This confirms that permanence in the ranking generates an increase in value and those companies listed every year in the ranking reach the highest level of valuation excellence, compared to those that are there for fewer years.

Since excellent companies are those that are in the ranking every year, the following analyses will focus on this group of companies, studying whether the gender of the presidency or maximum management responsibility of the company influence the valuation within this group of excellence.

In

Table 6. Testing independent samples of average values classified by gender for companies that remain in the ranking every year (2013–2020).

Variables	Gender	N	Media	F.	Sig.	Test Levene	Sig. (Bilateral)
Talent	man	120	189.91	2.611	0.108	Equal variances are assumed	0.706
	women	16	191.89
Remuneration	man	120	182.78	3.357	0.069	Equal variances are assumed	0.193
	women	16	189.36
Environment	man	120	170.41	7.302	0.008	No equal variances are assumed	0.000
	women	16	184.33
CSR	man	120	43.19	0.530	0.468	Equal variances are assumed	0.010
	women	16	46.77
Training	man	120	188.07	2.089	0.151	Equal variances are assumed	0.921
	women	16	188.61
Employee rating	man	120	58.90	0.070	0.792	Equal variances are assumed	0.411
	women	16	61.25
Total	man	120	833.35	3.266	0.073	Equal variances are assumed	0.045
	women	16	862.19

Source: Own elaboration from AE data (2013–2020).

, in all items, women-led companies achieve a higher valuation in a significant way: in working environment, in CSR and in total valuation.

The following section discusses the possible influence of the nationality and geo-cultural area variables on the assessment of training and the total score. In an earlier study, the authors found no influence of nationality on human resources policies in Malaysian companies [49]. On the contrary, another work presented a list of systematic differences in human resources management in multinational enterprises depending on the country of origin [50]. Some more recent empirical research supported findings in the same direction [51,52].

Companies from 19 countries are present in the ranking during the period 2013–2020, but this number is reduced to less than half (seven countries) for those that are included in the ranking every year (

Table 7. Valuations items sorted by international areas of companies that are held in the ranking every year.

Areas/Countries	Nº Records	%	Talent	Remuneration	Environment	CSR	Training	Employees	Total
Saxon	40	29.4%	189.3	182.1	172.7	43.1	186.5	60.2	833.9
USA	24	17.6%	194.8	178.9	175.3	43.9	198.2	59.5	850.7
UK	16	11.8%	180.9	186.9	168.8	41.9	169.0	61.2	808.7
North Central Europe	16	11.8%	204.8	175.3	170.0	43.1	181.3	56.6	831.8
Germany	8	5.9%	202.7	175.0	153.8	41.2	175.9	58.1	806.8
Netherlands	8	5.9%	206.9	175.5	186.3	45.0	186.6	55.1	856.8
Mediterranean Europe	80	58.8%	187.7	185.9	172.1	44.0	190.3	59.2	839.1
Spain	56	41.2%	186.5	187.3	178.4	44.5	188.9	59.4	845.1
France	16	11.8%	192.5	173.1	155.4	43.5	198.9	58.4	821.7
Italy	8	5.9%	186.0	202.2	161.5	40.8	182.6	59.6	832.6
TOTAL	136	100.0%	190.1	183.6	172.0	43.6	188.1	59.2	836.7

Source: Own elaboration from AE data (2013–2020).

). The most prevalent are those from Mediterranean Europe, which account for 58.8%, and Anglo-Saxon countries, who account for 29.4%, thus increasing their participation over the total population that have been included for just a few years. By contrast, those in Central-North Europe have a reduced presence in the most excellent companies list, and Asian companies are not even represented.

Another noteworthy fact is that the highest rated companies in total are those in Mediterranean Europe (839.1), followed by the Anglo-Saxon companies (833.9) and those in Northern-Central Europe (831.8), although these differences are not noticeable. While focusing attention on the valuation of the training, the same order is found. However, when considering the total sample, the most valued companies are the Anglo-Saxon companies, with significant differences from those from Mediterranean countries with a bilateral sig of (0.037) [53]. The explanation for this is that the companies that remain in the ranking are the most outstanding, with no differences between them depending on their nationality, their total value, or training.

By making the comparison according to specific items, it can be seen (

Table 8. Testing independent samples of significant average values by international areas.

Variable	Areas	N	Media	F.	Sig.	Test Levene	Sig. (Bilateral)
Talent	Saxon	40	189.26	4.831	0.032	No equal variances are assumed	0.001
	North Central Europe	16	204.78
Talent	Mediterranean Europe	80	187.66	4.740	0.032	No equal variances are assumed	0.000
	North Central Europe	16	204.78

Source: Own elaboration from AE data (2013–2020).

) that companies in North-Central Europe have significantly higher values in talent management, highlighting companies in both the Netherlands and Germany. In all other items, the differences do not reach statistical relevance.

There are certain differences between human resources practices in different regions, detected by comparative research using econometric techniques [54,55,56,57,58]. Another study, which focused on companies that were in the ranking at some point during the period 2013–2016, did not reflect the fact that the regions with the highest GDP per capita in Spain had significantly better data, compared to other areas of the territory [59].

Table 9. Valuations of items sorted by geographical areas of companies included in the ranking every year.

Autonomous -Regions Grouping	Nº Records	%	Talent	Remuneration	Environment	CSR	Training	Employees	Total
Madrid	107	78.7%	193.3	182.0	170.2	43.4	188.7	59.3	837.0
Mediterranean	21	15.4%	176.1	190.0	176.7	43.6	187.0	57.5	830.8
North	8	5.9%	184.9	187.8	183.9	46.4	183.8	61.4	848.2
TOTAL	136	100.0%	190.1	183.6	172.0	43.6	188.1	59.2	836.7

Source: Own elaboration from AE data (2013–2020).

shows that companies appearing on AE’s ranking every year (2013–2020) are mainly located in Madrid (78.8%), the country’s capital, achieving the highest valuation in talent management and training. Considering that only one company is in the north and that part of its operational headquarters is in Madrid, this increases the total value and the relative importance of the capital of Spain, being the reference place for the most outstanding companies.

Some authors include, among the contextual factors influential in human resources practices, the characteristics of the sector of activity [60]. The sector can also be categorized in several ways: services, industry, construction [55]. A previous study considering all companies concluded that the energy, financial and professional, scientific and technical sectors had higher values in a relevant manner compared to the remaining 16 economic sectors in which the companies operated [53].

In

Table 10. Valuations items of companies classified by activities.

Description CNAE	Nº Records	% 0/Total	Talent	Remuneration	Environment Agency	CSR	Training	Employees	Total
Commerce	8	5.9%	198.8	190.9	184.8	47.1	193.4	61.1	876.2
construction	8	5.9%	189,4	161.5	134.7	43.0	197.4	55.4	781.3
Financial and insurance companies	48	35.3%	183.2	192.9	172.9	44.7	187.0	59.2	839.9
Manufacturing industry	16	11.8%	179.3	183.8	164.5	40.3	172.4	61.3	801.7
Information and communication	8	5.9%	202.7	175.0	153.8	41.2	175.9	58.1	806.8
Professionals, scientific and technical	32	23.5%	202.8	174.5	184.1	44.4	196.8	59.6	862.6
Supply of energy	16	11.8%	186.3	184.9	174.3	41.9	188.7	57.5	833.7
TOTAL	136	100.0%	190.1	183.6	172.0	43.6	188.1	59.2	836.7

Source: Own elaboration from AE data (2013–2020).

, seven economic sectors can be seen, with the most valuable regarding the total score and in the variable training being the commerce sector (876.2/193.4), forming 5.9% of the companies in the ranking, the professional, scientific and technical sector, with a valuation of (862.6/196.8), making up 23.5% of companies, and the financial and insurance sector, with a valuation of (839.9/187).

Size is one of the most potentially influential factors in human resources practices [56], but there does not appear to be a consensus on the positive or negative signs of its effects. On the one hand, there can be a noticeable positive impact of small/medium size on employee behaviors (commitment or job satisfaction) and a negative impact of the same size on an operational performance indicator (absence and sick leave) [61]. On the other hand, there can be an association between increasing the size of businesses and formalizing human resources practices [62]. One study suggests that small businesses have several advantages, such as flexibility of roles, a close entrepreneur–worker relationship, among others [63]. On the other hand, another study stated that small businesses lack the resources to adopt progressive human resources management practices [49]. Small businesses have several advantages, such as a flexibility of roles, and a close employer–worker relationship, [63]. Ref. [59] showed in a clear and meaningful way that large organizations have better training ratios than small ones.

It can be seen in

Table 11. Nº workers and valuation according to years spent in the ranking.

Nº of Years in the Rankings	Nº Records	%	Average Workers	Total Rating	Training Rating
1	115	14.48%	3,211	694.4	155.3
2	108	13.60%	2,369	736.1	165.7
3	102	12.85%	4,093	744.3	165.2
4	88	11.08%	2,127	764.5	178.6
5	75	9.45%	4,370	795.1	180.3
6	72	9.07%	5,097	781.3	183.0
7	98	12.34%	6,249	791.8	177.8
8	136	17.13%	6,484	836.7	188.1
TOTAL	794	100.00%	4,306	768.0	173.9

Source: Own elaboration from AE data (2013–2020).

that, as the number of years spent in the ranking increases, so do company size, total rating and training rating.

Table 12. Correlations between training, number of employees and total valuation between companies in the ranking.

	Descriptive	Training	Total	Workers	Ranking Years
Training	Pearson correlation	1	0.621 **	0.092**	0.395 **
	Sig. (bilateral)		0.000	0.009	0.000
	n	794	794	794	794
Total	Pearson correlation	0.621**	1	0.081*	0.310 **
	Sig. (Bilateral)	0.000		0.022	0.000
	n	794	794	794	794
Workers	Pearson correlation	0.092 **	0.081 *	1	0.182 **
	Sig. (Bilateral)	0.009	0.022		0.000
	n	794	794	794	794
Years in the Ranking	Pearson correlation	0.395 **	0.310 **	0.182 **	1
	Sig. (Bilateral)	0.000	0.000	0.000
	n	794	794	794	794

Source: Own elaboration from AE data (2013–2020). **. Correlation is significant at level 0.01 (bilateral). * Correlation is significant at level 0.05 (bilateral).

calculated Pearson’s correlation between the variables training, total score, workers and years in the ranking, there being a positive and significant relationship among them all.

Companies listed on the stock market bear a higher degree of demand, as they are controlled by the National Securities Market Commission, by shareholders and by the market itself. Unlike those that are not publicly traded, a higher valuation of such companies could be expected. A previous study concluded that publicly traded companies achieve significantly better results in training management [59]. On the other hand, when considering the total sample of the companies that are listed in the ranking on occasion for the period 2013–2020, 63% of the companies in the total sample are listed on the stock market and have a valuation of 782.1***, higher and of significant difference from the non-listed stock market. However, when compared to the most excellent companies, striking differences occur. On the one hand, the relative weight of companies listed on the stock market increases (76.5%), and those listed in ibex-35 (29.4%). However, in terms of total valuation and training, it is those that are not publicly traded that reach the highest value, although the % decreases (

Table 13. Companies that remain for 8 years according to stock market membership (2013–2020).

	Nº Records	%	Total	Training
Listed	104	76.5%	829.3	186.6
Ibex35	40	29.4%	832.2	186.5
No Ibex	64	47.1%	827.4	186.6
Not Listed	32	23.5%	861.0	193.1
TOTAL	136	100.0%	836.7	188.1

Source: Own elaboration from AE data (2013–2020).

). Therefore, the few companies that are not listed on the stock market and that remain in the rankings every year are very well valued and achieve high values in training, corresponding to companies in the world of consulting, professional and technical advice.

4.2. Regression Analysis

This section establishes global models that seek to measure empirically whether there are certain dichotomous or numerical variables that have a significant effect on the total valuation of the companies in 2020. For this purpose, a multiple regression model (OLS) is used, since it is a technique that allows us to explain the relationship between the total valuation and the independent variables [64]. We choose the linear specification from the former estimation, since it fits better than other specifications that are more complex to interpret. The following equation would be a standard equation [65] for the estimation of a multiple regression analysis, where Xs would be explanatory variables, including intercept, while the ε would be the error term:

$$Total Valuatio{n}_i={\beta }_i*X_i+{\epsilon }_i$$

In the first specification (

Table 14. OLS method of the total variable relative to the control variables.

Dependent Variable	Total Valuation
Specification	Specification 1	Specification 2
Variables	Coefficient (Std. Error)	Coefficient (Std. Error)
Constant	766.826 (22.395) ***	724.673 (22.945) ***
Male presidency	−0.998 (19.241)	4.080 (19.386)
Central-North European	6.074 (18.232)	0.908 (18.197)
Mediterranean	5.836 (14.670)	−0.656 (14.784)
Number of employees	−16.214 (13.284)	−7.383 (13.082)
Stock market listing	16.066 (12.484)	5.828 (13.384)
Excellent company	69.988 (15.794) ***	-
Number of years being an excellent company	-	11.248 (2.616) ***
Mediterranean region	−9.656 (16.278)	−7.282 (16.421)
Northern region	−41.071 (23.533) *	−33.500 (23.665)
Other regions	−60.059 (26.379) **	−53.567 (26.762) **
Finance and insurance (K)	57.220 (14.759) ***	54.466 (14.968) ***
Commerce (G)	34.944 (18.448) *	40.083 (18.697) **
Professional, scientific and technical (M).	31.078 (16.928) ***	27.562 (17.177)
Adjusted R-squared	0.343	0.336
N	100 (t = 1, i = 100)	100 (t = 1, i = 100)
F-statistic	5.311	5.177

Source: Own elaboration from AE 2020 data. Sig.*** = 0.01, ** = 0.05, * = 0.

), there is a positive and significant value of the dichotomous variable that identifies companies that spent 8 years in the ranking (Excellent company), compared to those that spent less time, and the valuation of these companies is 69,988 points higher than the others. In the second specification, it can be seen how every passing year for companies in the ranking causes their total value to increase by 11,248 units. These results are as expected, given the rejection of most bilateral sigma in Table 5 as well as confirming the analysis of the data in Table 4. This would be the only noteworthy difference between the three specifications, so only the specification that we consider to best explain the relationship will be discussed, which would be the first.

A difference is found in the significance of the presidency’s gender variable among the average tests in Table 6 and linear regression. This is because in a multiple linear regression, it is possible to control by more than one variable at the same time, making the explanatory power of the variable gender of the presidency disappear. Although Table 6 shows that certain differences in valuation (total, working environment and CSR) were due to the gender of the presidency, this variable is not relevant in the overall model.

As noted by the descriptive statistics in Table 7, the origin of the company or geo-cultural area do not affect the total valuation of the company, since it does not have a different valuation from that of the Anglo-Saxon companies, meaning that it should be omitted to avoid falling into the trap of the fictitious variables [65].

Unlike the geo-cultural area of the company (Table 9), the Spanish region in which the company is headquartered significantly affects the valuation, with all regions having a lower valuation than that omitted, which would be Madrid, while the regions with the least valued companies would be those that are part of other regions.

As shown in Table 10, the sector to which the companies belong significantly affects the total valuation of the companies, with the financial sector having the most positive effect, followed by commerce and professional, scientific and technical companies, relative to the omitted variable that would be made up of all companies that are not part of any of these three sectors.

Although Table 12 shows a weak positive correlation between total valuation and worker numbers, this is not manifested in the overall model, with no significant relationship between number of employees and this variable. This could be related to the fact that larger companies are those that remained in the ranking for the longest, as seen in Table 11.

In line with Table 13, the membership of companies in the stock market positively, but not significantly, affects the valuation of companies. This may be due to the presence of professional, scientific and technical companies which are highly valued but not publicly traded.

To try to explain the relationships between the valuation of the training of the 17 companies that spent 8 years in the ranking of the most valued companies, a model of panel data is used; that is, a combination of temporary data with cross-section data, which would be each of the companies, while the temporal variable would be the year.

The regression estimation with panel data has certain advantages over linear models, such as allowing one to control individual heterogeneity, as well as introducing a greater number of degrees of freedom and, in general, reducing multicollinearity [64]. The individual heterogeneity can be assumed to be random or fixed [66]; the choice between the two types of heterogeneity depends on the nature of the data. As data come from companies chosen by a valuation process, the choice of fixed effects on the cross-section seems more advisable [67]. A fixed-effects dashboard data model, where αi is a non-random and company-specific element, would be written as follows:

$$Valuation of Trainin{g}_{it}={\beta }_i*X_{it}+{\alpha }_i+{\mu }_{it}$$

Based on the partial correlations of

Table 15. Partial correlations of companies’ business valuations that are ranked every year.

	Talent	CSR	Remuneration	Training	Employees	Environment
Talent	1	0.158	0.079	0.352	0.041	0.135
CSR	0.158	1	0.167	0.283	0.065	0.37
Remuneration	0.079	0.167	1	0.014	0.192	0.168
Training	0.352	0.283	0.014	1	0.366	0.245
Employees	0,.041	0.065	0.192	0.367	1	0.034
Environment	0.135	0.37	0.168	0.245	0.034	1

Source: Own elaboration from AE data (2013–2020).

, together with selection criteria, we develop three specifications, which examine the relationships between the individual valuations of each of the characteristics of the companies, upon the valuation of training.

The first specification in

Table 16. Panel data model, with training being the dependent variable for the period 2013–2020.

Dependent Variable	Valuation of Training	2013–2020
Specification	Specification 1	Specification 2	Specification 3
Variables	Coefficient (Std. Error)	Coefficient (Std. Error)	Coefficient (Std. Error)
Constant	72.463 (23.474) ***	66.847 (25.025) ***	75.355 (24.694) ***
Val. Employees	0.740 (0.116) ***	0.738 (0.116) ***	0.749 (0.119) ***
Val. Environment	0.198 (0.090) **	0.186 (0.092) **	0.203 (0.091) **
Val. Talent	0.198 (0.081) **	0.197 (0.082) **	0.207 (0.085) **
Val. CSR	-	0.186 (0.282)	-
Val. Remuneration	-	-	−0.003 (0.081)
Adjusted R-squared	0.529	0.527	0.526
N	136 (t = 8, i = 17)	136 (t = 8, i = 17)	136 (t = 8, i = 17)
F-statistic	8.980	8.511	8.476

Source: Own elaboration from AE data 2013–2020. Sig.*** = 0.01, ** = 0.05.

includes three explanatory variables: employees, environment and talent assessment [25,27,29]. The other two specifications include the CSR and remuneration variables, with the aim of evaluating different alternatives, although the best regression would be that of specification 1, which will be the one we will discuss. Since all the variables, both explanatory and those to be explained, are strictly positive, a logarithmic transformation can be made to them, to interpret the coefficients as elasticities. It is concluded that the variable that would be most positively related to the assessment of training would be the valuation of Employees, this being significant. A 1% increase in employee valuation would increase training valuation by 0.25%. The other variables would also be positive and significant.

Research reveals that H1 and H2 are confirmed. However, the results of the analysis in the Levene tests show that, in relation to H3, the difference is not significant, nor does it appear to influence the valuation of the company’s training, as can be seen in Table 16.

5. Conclusions

Being present in the ranking of the most valued companies in the labor market developed by AE is exceedingly difficult, and only 6% of the companies remained in the ranking for every year during the period 2013–2020, as can be seen in Table 3.

Companies that hold their position in the ranking longer achieve more value in all items (Table 4). The training variable reaches the highest value relative to its potential (85.5%) among most representative variables (talent management, remuneration and work environment). By comparing the data of companies that are in the ranking over the eight-year period and those in the ranking for only seven, it can be observed that the result is higher in most cases and specifically in training, with a bilateral significance (0.000), as shown in Table 5. The OLS regression model (Table 14) also shows the relevance of permanence. This proves that sustainability in the ranking of the most valued companies in the labor market corresponds to value excellence, as well as attaching great importance to training.

Although it is appreciated that women-led companies that appear in the ranking every year achieve higher valuation in all items, including training, significantly in some cases (Table 6), the global regression model (Table 14) does not allow us to conclude that gender is a relevant variable.

Internationally, companies from 19 different countries can be observed for the period 2013–2020, this value being reduced to seven nations (36.8%) when referring to those that are included in the ranking every year. By focusing on the most excellent companies (Table 7), it is noticed that the value of talent management is higher with a sig 0.001 in favor of companies in Central Europe (Table 8). The global regression model (Table 14) confirms that nationality does not influence the results for total score or training.

The companies that are in the ranking every year operate in seven economic sectors, namely the commerce, professional, scientific and technical, and financial and insurance sectors, these being the most valued in general as well as in training (Table 10 and Table 14).

The most resilient and valued companies are mainly located in Madrid (Table 9), and their relevance can be seen in the regression model (Table 14).

Positive and significant correlations between sustainability in ranking, size, training and total valuation are seen through Pearson’s coefficient (Table 11 and Table 12). Yet, when submitting it to the overall model (Table 14), it cannot be concluded that size influences the overall outcome in the most excellent companies.

Overall, 76.5% of companies are listed on the stock market and 29.4% belong to IBEX35. By contrast, the highest valuations, both for total score and training, are achieved by companies that do not trade on the stock market, although the differences are not significant according to the regression model (Table 13 and Table 14).

In the panel data model (Table 16), it is appreciated that training as a dependent variable is significantly explained with employee valuation, work environment and talent management. We observe a global feedback effect, where investment in human capital improves the overall valuation of the company and its permanence in the ranking, given that maintaining high standards in training requires a high level of talent management, attracting and keeping the most excellent workers. On the other hand, it is not seen that CSR or remuneration influence the values acquired by training in the most excellent companies to work for.

It can be established that remaining in the ranking significantly increases total valuation and training, which leads to business excellence. These companies are in the capital of the country, and focus on the commerce; professional, scientific and technical; and financial and insurance sectors. It is also appreciated that the value of training is explained by employee valuation, work environment and talent management. This last result is consistent with human capital theories, where investment in this resource by firms and workers improves productivity and motivation, due to the identification that the skilled workers feel with the firm. On the contrary, the variable gender in the business direction does not influence the total valuation, nationality, size, or stock market membership.

In summary, for the most outstanding companies in the country, where the salary of their workers is already higher than the national average, improvements in pay do not necessarily lead to business excellence. However, guiding the organization’s efforts to make the working day more flexible, to welcome teleworking or to improve talent management, will perpetuate the good management of the company by maximizing the retention of their most qualified personnel, guaranteeing their permanence in the ranking of the best companies to work for.

It should be mentioned as a limitation of this research that the recommendations provided are limited as to the level of disaggregation of the valuations offered by AE magazine. Future research should introduce new variables, expand the number of years, and extend the analysis to other countries in order to be able to perform comparative international analyses.