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1. Introduction
Human resource management has become a fundamental management role (García, 2016) since human talent management must be aligned with corporate objectives and be an input towards their fulfillment. Such a task requires adopting a comprehensive and inclusive strategic direction to drive the actions and aspirations of employees within the organization (Jaramillo, 2011; Kusse et al., 2020; Lechuga et al., 2018). A construct that has also gained strength within organizations given such a context is Corporate Social Responsibility (CSR), understood as the response organizations give to the environment from which they draw the resources to perform their activities. Much has been written about the CSR-human talent relationship, and the notion of Internal Social Responsibility (ISR), companies’ commitment to their employees, has even been posited.
As such, it turns out relevant to study social responsibility within the organization and through the eyes of the closest internal stakeholder of any organization, i.e., its workers (at the managerial, tactical, and operational levels). This approach to studying CSR is innovative, as most studies focus outside the organization (external stakeholders). It is crucial to analyze how responsible medium and large companies are towards their workers through management and human talent practices, considering that human resource management is a positive or hostile manifestation of corporate social responsibility (Blanco-Ariza and Vera-Barbosa, 2019; Vesga, 2020).
The exercise of corporate social responsibility is centered on the satisfaction of its stakeholders, both external and internal; inside this second category, the organization’s human talent and how the administration manages it are fundamental. Thus, it is essential to question how human talent management contributes to exercising corporate social responsibility towards internal stakeholders, namely, workers (Guzmán, 2016; López et al., 2019).
Under this perspective, ISR should consider aspects such as improving the quality of working life, generating an excellent working environment, promoting more outstanding worker commitment and development and integral company performance and company-family relationship programs, leading to greater productivity and competitiveness in the organization (Lechuga et al., 2018; Jaramillo, 2011). Regrettably, Colombian companies still hold a reductionist view of the role of social responsibility in human management (Calderón et al., 2011).
The purpose of this paper is to present the design of a social responsibility perspective-based human resource management model, specifically focused on Internal Social Responsibility. Multivariate analysis tools were employed, including Factor Analysis (FA) and Structural Equations (SEM), which will allow finding the latent and observable variables that will make up the ISR-based human resource management model for the companies studied.
These results will be an input to enrich the academic discussion on the incorporation of CSR into human talent management practices as a strategic personnel development factor. Likewise, it will serve as a roadmap for companies to lead themselves to strengthen their CSR actions based on human talent by implementing the proposed model. For the researchers, the results will shed light on the development of new research on the topic.
This paper is structured as follows: introductory statements that allow us to understand how Internal Social Responsibility is intertwined with human talent actions and practices. Then, the theoretical structure that supports the research results, which includes a body of knowledge about human management and internal social responsibility, is presented. The third section illustrates the methodology used to achieve the objectives, followed by a discussion of the results and, finally, the conclusions.
2. Theoretical framework
2.1. Human talent and organization
Throughout history, people have forged the remarkable institutions that society has today (Astudillo et al., 2017), including those of the State and, of course, all organizations and their various dimensions. Such social institutionalization has led to different mechanisms aimed at making employees more productive, ranging from extrinsic to intrinsic rewards (Mejía et al., 2013; Di Miceli, 2019; Bianchi, 2018). This formally appeared with the emergence of motivation models and empowerment postulates, and quality management theory, which among other things, proposed teamwork and people’s participation in company decision-making. More recently, other topics, such as 360-degree motivation (López, 2021), happiness at work, and emotional salary (Rubio et al., 2020), have come into the spotlight.
All these approaches become nuanced in what is known as human talent management. This connotation has bestowed a new meaning and importance on people’s management in consideration of their role in productivity (Chova, 2015 and Fernández, 2010, cited by Ganga and Villacís, 2018) and competitiveness (Montoya and Boyero, 2016; Danvila-del Valle and Sastre-Castillo, 2007; Zenteno-Hidalgo and Durán, 2016, cited by Pedraza, 2020). Proper management of human talent generates synergy in terms of creativity and innovation, which in turn impacts products and services (Farrukh et al., 2019) with high differentiating value and consistency with the needs of consumers.
According to Bianchi (2018), the relationship between employees’ adaptation and training and their organizations is mediated by shared intrinsic and extrinsic values at work. In the same perspective, Nientied and Toska’s (2019), study on motivational factors and organizational commitment of knowledge workers in Albania concludes that “organizations need to pay attention to the relationship between motivation improvement and productivity improvement. The current transactional leadership style stimulates employees based on their innate drive to increase productivity (Jaramillo, 2011, p. 33). Similarly, Terlato’s (2018) research on motivation, intrinsic factors, and performance in companies in the metropolitan area of Buenos Aires shed evidence that “the use of extrinsic factors is little mobilizing, and companies seem to use them in the face of ignorance of the essence of the motivational process” (p. 28) (Nientied and Toska, 2019). This author insists that if companies “want to have people who perform, who improve their tasks, serve customers better, communicate better, and innovate, they must learn to develop the internal drivers for virtuous behavior” (p. 28).
López (2021), in a study on 360-degree motivation and its influence on the work climate of companies in the city of Ambato (Ecuador), identified motivational factors as those related to personal, economic, training and recognition, professional development, psychological needs, security, salary, stability, promotions, responsibility and, to a lesser extent, the involvement of employees in the attainment of objectives.
2.2. Internal social responsibility
According to Barrena et al. (2019), implementing socially responsible behaviors has become a priority strategy for companies in recent years, and it is mirrored in comprehensive and inclusive strategic direction exercises (López et al., 2019). In this vein, the merger of CSR and human resource management (HRM) has expanded, “displaying a wide range of benefits that are reflected in higher levels of employee engagement, motivation and performance” (p. 2544) (Tarigan et al., 2020). Internal social responsibility (ISR) arose within this context, explicitly regarding workers’ job satisfaction (Tarigan et al., 2020; Farrukh et al., 2019; Franco et al., 2017). In this vein, per ISR, “companies cannot call themselves socially responsible if their actions are not reflected firstly mirrored in their employees and families by providing the best working conditions and an effective win-win relationship” (Jaramillo, 2011, p. 168). According to Gaete et al. (2009), ISR in the area of human resource management should be understood as “the voluntary implementation of good practices by the organization to enable the adequate development of its human capital, in accordance with institutional values and principles, and in accordance with the needs and desires of the organization’s human resources” (p. 41).
In the same vein, Gaete et al. (2009) considered the following dimensions: (a) Diversity management, which comprises cultural aspects (religious beliefs, cultures and convictions, racial origins, physically handicapped and gender diversity), (b) Work-life balance dimension (work flexibility, flexible working hours, telecommuting and social benefits), c) Labor harassment (work climate, occupational health, staff turnover rates, absenteeism, and organizational structure), d) Internal communication (procedures, ICTs, integration of hierarchical levels and staff participation in decision making).
Likewise, Franco et al. (2017) conclude that there is a tight relationship between CSR and human talent as concerns staff performance (Lechuga et al., 2018), increased motivation, and improved job satisfaction (Farrukh et al., 2019; Franco et al., 2017) and a strengthened sense of belonging towards the company.
For Jaramillo (2011), factors associated with induction or socialization, training, development, and promotion of higher education and career plans are essential from an ISR perspective (Kusse et al., 2020). Some companies fail to pay due attention to these as they “do not allow the time, budget or support so that employees can improve their skillset and thus achieve greater personal, professional and work development” (p. 193). This assessment coincides with Calderón et al. (2011), cited by Saldarriaga (2013), in concluding that Colombian companies still hold the role of social responsibility to a reductionist view about human resource management” (p. 116).
The study by Obrad and Gherhes (2018) on the implementation of socially responsible human talent management practices in multinational companies in Romania offers evidence of significant concern for providing good working conditions and training (Kusse et al., 2020; Lechuga et al., 2018), health (Lopez, 2021), safety, professional development opportunities (Lopez, 2021), fairness, efficient and transparent communication, employee promotions in the company hierarchy (Lopez, 2021), promotion of women to leadership positions and employee ethnic, cultural and social diversity. On the other hand, regarding people with a disability, Kin (2019) evidenced that companies play an irreplaceable role in improving their employability through “workplace adaptations, business-oriented environments, a supportive attitude, and work requirements” (p. 6).
Along these lines, Barrena et al. (2019), regarding what would be a socially responsible array of human resources, put forward the following policies: attraction and retention of employees (Kusse et al., 2020), training and continuous development (López, 2021), employee relations management, communication (Lechuga et al., 2018), transparency (Lechuga et al., 2018) and social dialogue, diversity and equal opportunities, fair remuneration and social benefits, prevention, occupational health and safety (López, 2021), and work-family balance (Kusse et al., 2020; Lechuga et al., 2018).
For Kusse et al. (2020), another concept associated with CSR is sustainable development (SD), which implies a balance between the three sustainability pillars: financial, social, and environmental. SD offers a new way of thinking about and managing human impacts, creating longer-lasting positive outcomes for more significant benefits to human societies (economic, human, social, and ecological), ensuring long-term resource availability and quality. Along these lines, Unsworth et al. (2021) posit that employees’ green behavior contributes to environmental sustainability (Malik et al., 2021), which agrees with Tsymbaliuk et al. (2021) when they argue that green human resource management practices should be implemented across all human resource management functions: organizational design and workforce planning, job analysis and design, recruitment, onboarding and matching, human resource accounting, performance appraisal and management, training and professional development, corporate culture, compensation and benefits, and employee relations.
2.3. Human talent management and social responsibility models
A management model is a theoretical construct aimed at representing reality. It is a mental model underlying practice and a set of concepts that materialize through a management methodology comprising crucial factors that lead to a value proposition made up of strategic, structural, operational, and managerial aspects in an environment that connects it to society and its stakeholders (Uribe, 2018, p. 63).
Rentería and Vesga (2019) and Vesga (2020) argue that management models should reflect company-worker relations in an economic context in which responsibility for labor performance is centered on the individual, seeking to improve the internal processes of the organization (Blanco-Ariza and Vera-Barbosa, 2019). “The challenge for companies, at present, is to implement a human talent management model deeply oriented to productive work, in which the development of organizations is made more efficient” (Reinoso et al., 2019, p. 39).
Duque et al. (2020) propose a model in which human management processes are grouped into four moments or categories that describe organizations’ needs in terms of the preparation of the human management area, personnel recruitment, selection and onboarding, retention of people, and employment relationship termination. Reinoso et al. (2019) base their model on recognizing personal capabilities involving contents linked to a person and a human management model by competencies. Uribe (2020) proposes a social responsibility management model that intertwines strategy and structure, stakeholder relations, and monitoring and continuous improvement. Araque et al. (2016) also analyze the interests of organizations’ different stakeholders in their model and consider five processes: research, dissemination, and social development; social and environmental sensitivity; environmental policy; work climate; and socially responsible communication and marketing.
Human talent management models concerning social responsibility exercises could improve customer satisfaction, quality management, workplace well-being, safety and health management, quality of life, and labor welfare (Solano, 2010; López et al., 2019). These models should ensure the monitoring of the internal processes carried out by the company’s personnel towards constantly establishing their contribution to the goals set forth by the organization (Blanco-Ariza and Vera-Barbosa, 2019).
Human talent management is fundamental to endorse socially responsible behavior internally (Guzmán, 2016), grounded in the quality of work life (Fernández, 2005). The relationship between human resources management and corporate social responsibility can be identified by analyzing the practices an organization implements, how it does so, and the strategies it uses for such purposes (García and Duque, 2012; López et al., 2019).
Within this conceptual framework and background analysis, the following hypotheses are posited in order to empirically contrast the structure proposed for the internal social responsibility-based human resources management model, “MGHRSEI,” for medium and large companies in Ibagué, Tolima, Colombia:
H1: The population variance-covariance matrix (∑) is equal to the variance-covariance matrix associated with the theoretical model (∑ [Ɵ]).
H2: The Corporate Social Responsibility- based Human Resources Management Model, “MGHRSEI,” is in direct connection to the latent variables of “Quality of life at work” (CAVITRA) and Internal Social Responsibility (RSEI).
H3: There is a direct relationship between the latent variable of “CAVITRA” and the observable variables that make up this construct.
H4: There is a direct relationship between the “RSEI” latent variable and the observable variables that make up this construct.
3. Methodology
The research that paved the way for this paper was quantitative. The techniques implemented to meet its objective were factor analysis (FA), a method that allows reducing dimensionality with minimal loss of information (Valderrey, 2010; Pérez, 2009), and the structural equation model (SEM). The latter is represented by a path diagram and a system of equations that simultaneously examine a series of dependency relationships or “analyze the causal and non-causal relationships between variables held as measurement indicators of the constructs, excluding measurement error from the analysis” (Casas, 2002, p. 3). In the first case, the aim is to establish the dimensions and the variables that make up each factor and identify the items that will make up the CSR-based human talent management model in the organization studied using the SEM model as a confirmatory analysis tool, thus fulfilling the research objective and determining some impact and association relationships between variables. The information was obtained through a structured questionnaire with a Likert scale, which was initially designed with four dimensions or factors: Human talent development, reconciliation and equality, CSR and business management, and CSR and human talent, derived from the literature review and subsequently adjusted to only two based on a pilot sampling that yielded a Cronbach’s Alpha of 0.844 for all its items, and 0.811 and 0.718 for the dimensions “Quality of life at work” and “Corporate Social Responsibility” respectively. Likewise, these findings were corroborated through convergent validity through Spearman’s correlation matrices, which yielded relationship levels between pairs of variables of 95% and 99%. After completing this process, the instrument was applied to the sample of 70 companies out of a population of 85 medium and large manufacturing and services organizations in the city of Ibagué, Tolima, Colombia, considering a 5% sampling error and 95% reliability.
4. Results
The Principal Components (PC) technique of Factor Analysis (FA) was used as an exploratory tool to design the internal social responsibility-based human resource management model in medium and large companies in Ibagué (RSEI), followed by the Structural Equation Model (SEM) on a confirmatory level. Table 1 shows the variables that were analyzed to build this model.
Table 1 Description of the variables studied
| Cod. | Description | Cod. | Description |
|---|---|---|---|
| Pro | Career Advancement | EdU | Promotion of university higher education |
| InF | Investment in human talent training | CSR | Organization knows the meaning of CSR |
| CaT | Quality at work | MiV | CSR mission and vision are essential to the company |
| PlC | Career plan | InT | The company provides transparent information |
| MuD | Women in management positions | EnC | The company offers training and education |
| EqV | Work-life balance | CCo | Company implements code of conduct |
| Dis | Jobs for the disabled | Med | The company makes extra-legal efforts to reduce environmental impacts |
Source: Authors’ own elaboration.
According to Table 2, the PCs yielded only nine variables out of 14 initial variables, using a saturation level higher than 0.5, which were grouped into two dimensions or latent variables: the first one took the name of “quality of life at work” (CAVITRA) which comprised the attributes of Pro, InF, EdU, PlC, CaT, EqV; the second one, “internal corporate social responsibility” (RSEI), included the items MiV, InT and CSR.
Table 2 Matrix of rotating components
| Component | ||
|---|---|---|
| 1 | 2 | |
| Pro | 0.819 | |
| InF | 0.804 | |
| EdU | 0.763 | |
| PlC | 0.638 | |
| CaT | 0.605 | |
| EqV | 0.545 | |
| EnC | ||
| Med | ||
| Dis | ||
| MiV | 0.849 | |
| InT | 0.840 | |
| CSR | 0.791 | |
| CCo | ||
| MuD | ||
Note: Extraction method: a principal component analysis.
Rotation method: Varimax with Kaiser normalization.
Source: Authors’ own elaboration.
Concerning the SEM confirmatory factor analysis, Figure 1 shows the initial model’s outline using the Maximum Likelihood (ML) method with all the study variables, the statistics of which Table 3 presents. These do not show a good fit (absolute, incremental, and parsimony). Additionally, most of its items’ factor loadings are < 0.7 and should not be included in the model to remove collinearity between variables as much as possible (Jöreskog, 1969; Garson, 2013; Raubenheimer, 2004; Widaman, 1993; Blume, 1976; Barclay et al., 1995).
Table 3 presents the estimation of the parameters of the initial model and its goodness-of-fit evaluation, finding that most of them fail to meet the required thresholds, such is the case of the P-value of the Chi-square (ꭕ2), which was 0.000 and should be > 0.08. The same happened with the Non-Centrality Parameter (NCP), as its value must be <2 instead of 49.573. The root mean square error of approximation (RMSEA) was 0.097, while it must be <0.08. All account for absolute fit measures that determine the degree to which the general model predicts the correlation matrix. The incremental fit measures, tasked with comparing the proposed model against some other existing models, find that the Normed Fit Index (NFI), the Tucker and Lewis index (TLI), and the comparative Fit Index (CFI) took values of 0.724, 0.837 and 0.864, respectively, failing to reach the minimum required value of >0.90.
Table 3 Initial model goodness-of-fit measures
| Goodness-of-fit measures | Acceptable fit measures levels | Values obtained | Criteria |
|---|---|---|---|
| Absolute fit measures | |||
| Chi-square ꭕ2 | The smaller, the better | 125.573 | Acceptable |
| D.f | 76 | ||
| P-value | > 0,05 | 0.000 | Unacceptable |
| ꭕ2 /d.f. | < 5 | 1.652 | Acceptable |
| NCP | < 2 | 49.573 | Unacceptable |
| GFI | > 0,80 | 0 | Unacceptable |
| RMSEA | < 0,08 | 0.097 | Unacceptable |
| RMR | Close to 0 | Unacceptable | |
| ECVI | Close to 1 high correlation | 3.066 | Unacceptable |
| Incremental fit measures | |||
| NFI | > 0,90 | 0.724 | Unacceptable |
| TLI | > 0,90 | 0.837 | Unacceptable |
| CFI | > 0,90 | 0.864 | Unacceptable |
| AGFI | >= 0,90 | Unacceptable | |
| Parsimony fit measures | |||
| PGFI | > 0,50 | Unacceptable | |
| PNFI | > 0,50 | 0.604 | Unacceptable |
| PCFI | > 0,50 | 0.721 | Unacceptable |
| AIC | Small value | 211.573 | Unacceptable |
Source: Authors’ own elaboration.
As for the parsimony fit measures, tasked with relating model fit quality with the number of estimated coefficients necessary to achieve the level of fit, the Parsimony Norm Fit Index (PNFI) and the parsimony comparative fit index (PCFI) yielded values of 0.604 and 0.721, above 0.50, thus satisfying the necessary standard. Concerning the Akaike Information Criterion (AIC), its value came at 211.573, which is considered high; therefore, it does not meet the required threshold.
Based on these results, we proceeded to rethink the model by removing those items with the lowest saturations (Figure 2), the fit measures of which appear in Table 4.
Table 4 Rival model goodness-of-fit measures
| Goodness-of-fit measures | Acceptable fit measures levels | Values obtained | Criteria |
|---|---|---|---|
| Absolute fit measures | |||
| Chi-square ꭕ2 | The smaller, the better | 14.643 | Acceptable |
| D.f | 12 | ||
| P-value | > 0,05 | 0.262 | Acceptable |
| ꭕ2 /d.f. | < 5 | 1.22 | Acceptable |
| NCP | < 2 | 2.643 | Unacceptable |
| GFI | > 0,80 | 0.929 | Acceptable |
| RMSEA | < 0,08 | 0.056 | Acceptable |
| RMR | Close to 0 | 0.097 | Acceptable |
| ECVI | Close to 1 high correlation | 0.473 | Acceptable |
| Incremental fit measures | |||
| NFI | > 0,90 | 0.930 | Acceptable |
| TLI | > 0,90 | 0.983 | Acceptable |
| CFI | > 0,90 | 0.986 | Acceptable |
| AGFI | >= 0,90 | 0.876 | Acceptable |
| Parsimony fit measures | |||
| PGFI | > 0,50 | 0.531 | Acceptable |
| PNFI | > 0,50 | 0.744 | Acceptable |
| PCFI | > 0,50 | 0.789 | Acceptable |
| AIC | Small value | 32.643 | Acceptable |
Source: Authors’ own elaboration.
As Figure 3 and Table 4 show the model improved ostensibly once re-designed compared to the initial model’s absolute fit, incremental fit, and parsimony statistics. According to Boomsma (2000) and McDonald and Ho (2002), a model’s efficient fit may be given by combining the measures χ2, RMSEA, ECVI, SRMR, GFI, and CFI, which had a good evaluation in the alternative model. Furthermore, as seen in Table 4, many more statistics came out well-adjusted to the data studied, which allows us to corroborate that the population variance and covariance matrix (∑) is equal to the variance and covariance matrix associated with the theoretical model (∑) as stated in hypothesis (1).
Source: Authors’ own elaboration.
Figure 3 RSI-based Human Resource Management Model for medium and large companies in Ibagué (MGHRSEI - per its acronym in Spanish)
These findings demonstrate that the variables Cat, Edu, InF, and Pro, represent the human management construct in organizations. At the same time, the items MiV and CSR account for the philosophy of social responsibility. Thus, these aspects gave life to the Internal Social Responsibility-based Human Resource Management Model for medium and large companies in Ibagué, satisfying the core research objective (Figure 3).
4.1. Solution of the hypothesis system
The first hypothesis was tested using the p-value, χ2 /d.f, GFI, CFI, and RMSEA statistics (Table 4), all of which were found to be significant, wherefore, the H1 hypothesis was accepted.
Figure 2 (“rival sequence diagram”) and Table 4 (“rival model goodness-of-fit measures”) show the direct relationship between the “MGHRSEI” and the “CAVITRA” and “RSEI” constructs with estimated values of 0.90 and 0.65, respectively; thus, hypothesisH2 is not rejected.
According to figure 2 (“rival sequence diagram”), there is a direct relationship between the latent variable “CAVITRA” and its observable variables. In this context, the CaT, EdU, InF and Pro items present 0.76, 0.65, 0.80, and 0.76 values, respectively, which means that hypothesis H3 is not rejected.
Based on Figure 2 (“rival sequence diagram”), there is a direct relationship between the latent variable “RSEI” and its observable variables. As such, the MiV and RSE items present estimated values of 0.93 and 0.88, respectively, which means that hypothesis H4 is not rejected.
5. Discussion
The empirical findings tell us that the companies that took part in the study have in common that they identify with the factors related to human talent management and internal social responsibility (ISR). Within this context, as shown in Figure 3, the Internal Social Responsibility-Human Management Model for Medium and Large Companies in Ibagué is made up of six variables: the first of which refers to the promotion of quality at work through fair wages and compensation (CaT), held as a significant factor in 360-degree motivation and work climate-influential (López, 2021; Gaete et al., 2009). Following this perspective, internal social responsibility (ISR) pursues workers’ job satisfaction (Tarigan et al., 2020; Farrukh et al., 2019; Franco et al., 2017); companies cannot be socially responsible if their actions do not impact their employees and their families (Jaramillo, 2011).
Regarding organizations’ (EdU) fostering of scenarios for formal university education, this is a fundamental aspect in the formation and training of human talent towards the improvement of their labor competencies (Jaramillo, 2011; Calderón et al., 2011 cited by Saldarriaga, 2013; Kusse et al., 2020; Lechuga et al., 2018). Another factor that makes up the human management model is companies’ investment in human talent (InF) training, development, and welfare. Under this perspective, Obrad and Gherhes (2018) mention socially responsible human talent practices in multinational companies in Romania, in which good working conditions, training (Kusse et al., 2020; Lechuga et al., 2018), healthcare (Lopez, 2021), safety, professional development opportunities (Lopez, 2021), fairness, efficient and transparent communication, employee promotions up the company ladder stand out (Lopez, 2021).
On the other hand, employees’ professional development opportunities (Pro) are a critical factor in job satisfaction (Tarigan et al., 2020; Farrukh et al., 2019; Franco et al., 2017) in agreement with Lopez (2021). Likewise, the conflation of CSR and human talent management has proven to be a fundamental philosophy that results in higher levels of employee engagement, motivation, and performance (Tarigan et al., 2020). This conflation must be based on establishing a management model that allows performing CSR actions systemically (Araque et al., 2016; Uribe, 2018; Uribe, 2020), in this case, through the organization’s human talent management.
Finally, companies’ knowledge and attitude toward teleological aspects (mission, vision, and corporate values) become fundamental elements in defining the criteria of internal social responsibility (Tarigan, 2020; Farrukh et al., 2019; Franco et al., 2017).
6. Conclusions
Internal social responsibility and human management are multidimensional constructs incapable of being explained from a single perspective. ISR is a complex phenomenon home to many interpretations: for some, it is merely a matter of satisfying labor legislation provisions, while others believe that it should be further reaching, seeking employees’ complete satisfaction regardless of the legislation. The multivariate analysis, concerning factor analysis and structural equations, indicated that the managers of the organizations studied agree that the quality of life at work is essential, represented in fair salaries and compensation, the promotion of higher education, investments in training, development, and human talent welfare, the existence of criteria for employee promotion, the organization’s knowledge about its mission, vision and values towards the implementation of CSR principles and the organization’s knowledge of the meaning of CSR (Tarigan et al., 2020; Farrukh et al., 2019; Franco et al., 2017). Furthermore, their implementation constitutes the fundamental pillars on which the internal Corporate Social Responsibility- Human Resource Management Model approach would have to be cemented.
The study’s findings confirmed the importance of internal social responsibility-based human resources management as a driver of productivity and organizational competitiveness.
