The Innovative Human Resource Management Framework: Impact of Green Competencies on Organisational Performance

Abstract

Scholars have emphasised the importance of green settings in today’s business paradigms. Studies on green behaviour have produced a plethora of noteworthy discoveries, whether focused on financial success, individual capabilities, or development. However, despite significant growth in interest in green business practices, the relationship between individuals’ willingness and green competencies has received little attention. This article used the customised green competencies conceptual model to investigate how green skills influence organisational performance and their relationship with the willingness moment. This article developed an innovative human resource management approach to address these difficulties. A questionnaire was used to perform empirical statistical research with 516 respondents from Serbian universities. Different mathematical and statistical methodologies were used to analyse the results. The findings corroborate the suggested theoretical model, and they suggest that green competencies will influence people’s willingness to participate in green activities. This article gives new information on human behaviour and organisational effectiveness in a green atmosphere. It includes managerial and practical consequences and recommendations for businesses looking to improve their social responsibility and environmental sustainability.

1. Introduction

Rapid development as a result of technology and scientific developments and many social, health, and financial crises in recent decades and worldwide trends have had a significant impact on business and the environment [1,2]. In today’s global business climate, the only certainty is uncertainty. Many ongoing modern concerns have prompted changes in how organisations think about their objectives. Due to the ever-changing business environment in the age of globalisation, businesses face numerous challenges [3]. Recent difficulties and globalisation have a catalytic effect in all aspects of contemporary life and business [4], driving organisations to grow resiliently and sustainably. To preserve and acquire a competitive edge, organisations must adapt their business models to be more inclusive, pro-environmental, and innovative. Innovation for more significant influence entails developing innovative products or procedures to assist the organisations’ beneficiaries and effectively address critical challenges [5]. The growing need for sustainable techniques can be seen in all industries [6], and there has recently been a slew of studies on sustainability and financial performance [7].

Bibi and Li [8] emphasized that numerous authors have indicated that implementing new legislation and economic policies will increase environmental efficiency. Rasche and Waddock [9] emphasise that numerous methods of industry regulations regarding the different trending aspects, including environmental protection, emerged in the last two decades. However, the future should be in incorporating sustainability for the sustainable and more resilient future, not only because of the legal obligations. Furthermore, the modern global business ecosystem triggered a new wave of corporate social responsibility activities that do not include only the regulatory requirement of the country [10,11,12]. Sustainability is a long-term goal [13], and it should be an integral part of every aspect of society. Organisations are becoming increasingly cognizant of the necessity to accomplish ethical, social, and environmental objectives [14].

In their research, Tornjanski and Čudanov [15] emphasised the need for organisational empowerment for a sustainable future. Environmentally concerned organisations must communicate their pro-environmental viewpoints to their personnel. Employees are an essential component of implementing pro-environmental procedures in businesses [16], and researchers [17,18] point out that there has been a lot of research done on the impact of human capital on long-term development. Employees who integrate innovative processes and embrace new pro-environmental practices are more likely to achieve long-term goals [14]. Individuals are more engaged in goal-relevant activities [19]; as a result, organisations must embrace global environmental trends, incorporate sustainable goals into organisational objectives, and support individuals in becoming more environmentally conscious and helping others in this way, thereby constructing a new, more inclusive society.

A pro-environmentally conscious individual with green abilities and a commitment to help the environment and others comprehend and embrace modern difficulties and work on creative methods to improve organisational performance is described as having a new viewpoint on the environment. Furthermore, ecologically conscious and willing individuals will direct their green performance toward long-term growth, innovation, and financial performance.

Several academics discussed green segments in a variety of theoretical disciplines. Green behaviour analyses have previously revealed many important conclusions. Despite the growing interest among academics in green corporate practices, there remains a considerable gap in the understudied relationship between personal willingness and green competencies. This study intends to address a gap in the literature by looking into the relationship between green competencies and willingness.

This article contributes to the literature by analysing, synthesising, and providing an extensive and comprehensive review of published studies in this area, empirically re-searching the relationship between green competencies and organisational performance, and identifying future research directions.

2. Sustainability and Human Resource Management

Past studies [20,21] have highlighted that human activities are causing about two-fifths of all environmental problems, but recently, it can be assumed that direct and indirect human impacts are even more significant than previously described. The challenges organisations face have made them shift their business paradigms towards resilient and sustainable development and growth.

Mandip [22] considers that sustainable development should fulfil today’s needs without compromising the chances of future generations to meet their needs. Sustainability is a dynamic and evolving concept [23], usually associated with stable systems, and it is of primary importance to organisations [24]. Zaugg [25] emphasises that employees, companies, and society should benefit from sustainability. It should be seen as a possibility to enhance competitiveness [26,27]. There are three dimensions of sustainability [28]: protection of the natural environment, maintenance of economic vitality, and observance of particular social considerations about human development, which is the most important for this study. Human resource management plays an essential role in implementing sustainable organisational practices with the aim of promoting environmental sustainability [29]. Additionally, incorporating sustainability into human resource management could bring humanity back to the management of human resources [30].

2.1. Theoretical Background of Sustainable Human Resource Management

Ehnert [31] noted the diversity of theoretical terminology explaining the relationship between sustainability and human resource management. For example, some authors use the term “sustainable human resource management” (e.g., [14,25,32]), others prefer “green human resource management” (e.g., [33]) and some emphasise the differences between these two terms. Vraňaková et al. [34] observe sustainability in the context of human resource management as twofold: supporting the implementation of a sustainable strategy and sustainable development, and sustainable work and sustainably performing human resource management.

Green human resource management offers a functional method for organisations to develop human capital and enhance their green performance and sustainable development [35,36,37,38]. Jabbour [39] supports the opinion that green human resource management practices positively influence organisations’ green performance through various activities, while Kramar [40] defines it as human resource management activities with positive environmental results. In addition, some authors [41] consider it part of environmental management, and many authors [42,43] agree that improving employees’ green behaviour will enhance an organisation’s performance based on willingness.

Piwowar-Sulej [44] points out that sustainability has recently become more influential in developing an approach to employees and refers to it as sustainable HRM. Ehnert [32] defines sustainable human resource management as “the pattern of planned or emerging human resource management strategies and practices intended to enable organisational goal achievement while simultaneously reproducing the HR base over a long-lasting calendar time and controlling for self-induced side and feedback effects of HR systems on the HR base and thus on the company itself”. The function of sustainable management is to facilitate the development of employees and human resource management practices for today and to meet forthcoming needs [31]. Thom and Zaugg [45] consider it to comprise “those long-term oriented conceptual approaches and activities aimed at socially responsible and economically appropriate recruitment and selection, development, deployment, and downsizing of employees”.

Building on the integrative model of strategic human resource management [46], Ehnert [32] developed a model of sustainable management.

Compared to prior sustainable human resource management models, this model concentrates on the origin of human resources, such as family, schools, and universities, and adds socio-economic drivers, such as demographic trends and social, political, and legislative systems. In addition, the model provides possible short-term and long-term effects of sustainable human resource management:

• Individual: employee well-being, work–life balance, health, employability;
• Social: viability of sources of human resources, quality of life, good employer brand;
• Organisational: long-term supply of workforce, healthy employees.

There are key tensions and paradoxes between efficiency and substance-oriented rationality and between social responsibility and efficiency-oriented rationality.

2.2. Conceptual Model of Green Competencies and Adapted Green Competencies

Competencies have a considerable influence on career success [47,48,49]. Some authors [50,51,52] consider that competencies represent the behaviours and attitudes employees need to perform their assignments effectively. Personal characteristics and circumstances, behaviours, knowledge, skills, attitudes, values, and beliefs are some professional competencies [48].

Organisations should take a proactive and systematic approach to modern challenges and have a variety of green strategies to increase employees’ pro-environment awareness and competencies [29]. In addition, individual attitudes and values are fundamental elements that influence green competencies [53,54].

Roberts [55] classified competencies into four categories: natural, acquired, adaptive, and performance. Cousins [56] adapted this competency framework to the green setting. Individuals who have developed green competencies remain motivated through performance measures and reward methods that provide green performance development possibilities [41,57]. Authors [58,59] conducted various studies considering employees’ motivation factors in different working environments.

Table 1. Definitions of constructs.

Construct	Definition	Source
Natural green competencies	An individual’s underlying traits and personality dimensions, derived from observations and mentoring received at formative stages, regarding dominant green behaviour of their immediate social groups.	[55,60,61]
Acquired green competencies	Green knowledge and skills that an individual accumulates through experience regarding environmental issues that lead to strong convictions and feelings about acting in an environmentally friendly manner.	[55,56,62]
Effective green competencies	Combination of natural and acquired green competencies.	[55]
Green performance	Final output or observable behaviour resulting from combination of natural, acquired, and adaptive competencies.	[63,64,65,66]

Source: [67].

shows the definitions of different types of green competencies and performance.

Natural green competencies (NGCs) are attributes and opinions formed in an individual’s formative stages, while acquired green competencies (AGCs) represent green knowledge accumulated through experience. Pellegrini et al. [68] consider that employees’ acquired green competencies support the integration of pro-environmental reasoning into the human resource activities of organisations. Combining natural and acquired green competencies produces effective green competencies essential for green performance.

Human resource management could benefit from measuring green behaviour to determine employees’ green performance, which is the result of combined natural, acquired, and adaptive competencies. Someone can have green competencies, but it is also essential to want to help the environment to achieve green performance. Ivanović and Mirčetić [29] built on the green competencies conceptual model, and Subramanian et al. [67] introduced the willingness moment as a vital part of an individual’s green performance and developed an adapted green competencies model (Figure 1).

As seen in the previous figure, both natural green competencies and acquired green competencies are prerequisites for effective green performance. The offered model is essential for this paper because it adds a new component to achieve green performance, the willing moment. For example, an individual can have excellent natural green competencies and advanced levels of acquired green competencies. However, Ivanović and Mirčetić [29] consider that green performance cannot be attained if an individual is unwilling to employ their effective green competencies, and because of that, the willingness moment is observed as an essential part of this model. The willingness moment can also predict an employee’s attitude toward the environment or their ability to acquire green skills.

2.3. Impact of Pro-Environment Behaviour on Financial Performance

Since the Industrial Revolution, finance has been a powerful enabler of human progress [69]. Levine [70] highlights finance as a key element in economic development. Finance represents a diverse ecosystem, with a function that can appear complex and opaque in the broader economy and the environment [71]. Noh [72] considers green finance as future-oriented, aiming to develop the financial industry, improve the environment, and enhance economic growth. Despite the importance of green finance and the significant increase in the number of scholars using this and similar terms, there is still no single agreed-upon definition that clearly explains it [72]. Independent of the differences in terminology in the literature, modern observation of finance has to be more inclusive and include pro-environment behaviour because it has direct and indirect implications for financial performance.

There is a significant interdependence between green behaviour and the financial performance of organisations. Recently, the green setting has been more visible in all business segments, and more organisations are shifting their business paradigms towards pro-environment and responsible activities. Environmental sustainability can have diverse impacts on organisational competitiveness [73,74]. Many scholars [75,76,77] have examined environmental performance in sustainable organisations and the relationship between environmental management and financial performance. Numerous studies have been conducted examining the impact of pro-environment human resource management activities on the green performance or organisations [78,79].

Sustainability has become a vital segment in many types of organisations. Petrović et al. [80] emphasised that scholars endeavour to define the term “sustainable entrepreneurship”, which incorporates business, economic, ecological, and social aspects, while Aničić et al. [81] consider small and medium enterprises the carriers of development and innovative activities. Noh [82] points out that green growth provides both economic development and environmental enhancement. Rakić and Mitić [83] emphasise that green finance should include new technologies, financial products, industries, and services to support green growth.

As possible motives for the increased importance of green finance recently, Noh [82] considers increased risk due to environmental destruction and the insufficiency of natural resources, and the fact that the seriousness of the problem has been exaggerated, so stakeholders demand social responsibility. However, Schillebeeckx et al. [83] point out that organisations not only react to stakeholder preferences, but also consider how their reactions may affect the organisation’s ability to create value. Organisations and stakeholders working together to add value in sustainable and mutually desirable ways leads to responsible innovation [84,85], which is crucial to address contemporary challenges and achieve desired financial performance.

2.4. Theoretical Research Model

For this research, a theoretical research model was created. The initial model (Figure 2) consisted of a dependent variable, green performance, and an independent variable, relationship to natural and acquired green competencies.

Further elaboration of the initial model led to a new theoretical research model (Figure 3), consisting of three independent variables, attitude towards the environment, natural green competencies, and acquired green competencies, and a dependent variable, willingness. Lorincová et al. [86] point out that corporate culture firmly contributes to the employees’ willingness to achieve the organisation’s objectives.

2.5. Hypotheses

Based on the new theoretical model, the following research sub-models with relationships between independent variables and dependent variable were developed, which also propose hypotheses as follows:

(a)

Willingness sub-model in attitude towards the environment function (Figure 4), which proposes hypothesis H1: Attitude towards the environment affects willingness.

(b)

Willingness sub-model in natural green competencies function (Figure 5), which proposes hypothesis H2: Green competencies affect willingness.

(c)

Willingness sub-model in acquired green competencies function (Figure 6), which proposes hypothesis H3: Acquired green competencies affect willingness.

(d)

Multiple willingness sub-models in attitude towards the environment, natural green competencies and acquired green competencies functions (Figure 7), which propose general hypothesis H0: Attitude towards the environment, natural green competencies, and acquired green competencies affect willingness.

3. Materials and Methods

In order to examine green competencies, the willingness moment, and their interdependency, empirical research was conducted with students, under the assumption that the activities of university studies are similar to those of employees [87,88]. The online questionnaire was distributed among students at universities in Serbia in October 2020.

In the empirical part of the paper, the survey method was used with a questionnaire. The results obtained by empirical statistical research were processed by the following mathematical and statistical methods: Cronbach’s alpha coefficient, descriptive statistics, correlation and regression analysis, ANOVA, linear regression, and multiple linear correlation. The collected data were analysed using SAS JMP v.14 statistical software and were processed and presented textually, tabularly, and graphically.

The questionnaire on attitudes towards the environment and green competencies was designed in September 2020 and carried out in October 2020. It was formed by combining existing questionnaires on in-role and extra-role behaviour [89] and natural and acquired green competences [55].

The survey was structured in five major sections. The first part focused on the respondents’ demographic profile. In the other four segments, respondents were asked to indicate how often they engage in specific pro-environment behaviours on a 5-point Likert scale (1 = never, 5 = always). One segment related to in-role and extra-role green behaviours (4 items), which was measured by a scale adapted from Bissing-Olson et al. [89], with 2 items for each type of behaviour. Three parts were measured by a scale adapted from Roberts [55], and covered attitudes towards the environment (4 items), natural green competences (5 items) and acquired green competencies (5 items). The instrument was pilot tested for reliability of the research statements and variables.

A total of 516 respondents formed the sample for the research, 342 women (66.3%) and 174 men (33.7%), students at universities in Serbia. The majority of respondents were born between 1999 and 2001. A main finding of the research shows that characteristics of respondents can also be observed through their daily activities. For example, 78.4% of respondents said they carry out their daily activities in an environmentally friendly way. In addition, most respondents (83.5%) agreed that they carry out their study-related activities in a manner that does not harm the environment. On the other hand, only 25.1% of respondents said they were actively involved in environmental protection outside of their job, while 64.8% said they took the initiative often or always to perform their daily activities in an environmentally friendly manner. The results of analysing students’ green behaviour in terms of in-role and extra-role green behaviour revealed a difference in students’ green behaviour, with more students engaging in in-role green behaviour than extra-role green behaviour. The research findings are in accordance with the findings of Bissing-Olson et al. [89] and Zhang et al. [90], implying that students are less likely to engage in proactive environmental conservation than adults.

In terms of natural green competencies, 61.2% of respondents said their parents had stressed the importance of environmental protection during their childhood; 65.8% said they had listened to a lot about the importance of environmental protection during their childhood; 43.8% said they frequently watched educational programs about environmental protection or read/listened about the issue while growing up. In addition, 39.3% of respondents said that their friends impacted their attitudes toward environmental protection in a favourable way, while 38.75% said that their university colleagues cared about the environment and positively influenced their attitudes. In terms of acquired green competencies, 57.4% of respondents said their prior experience had a significant impact on their environmental knowledge and skills; 35.8% of respondents had courses in their previous education that provided them with knowledge about environmental protection, and 23.6% of respondents have actively studied environmental issues. Overall, 96.1% of respondents believe they must protect the environment, while 89.7% of respondents are disturbed when they witness someone or something polluting the environment.

Students’ opinions regarding environmental conservation were used to investigate the willing moment. Regarding their environmental attitudes, 44.1% of respondents believe they took better care of the environment under the state of emergency than they did previously. On the other hand, fewer students, 42.2% of respondents, believe they are more environmentally conscious after the state of emergency than before it, and 43.85% believe that e-learning is more environmentally friendly than classroom learning. Finally, 92.2% of respondents believe it is critical to protect the environment when conducting business.

Based on the recommendations for identifying factor limitations, the obtained Cronbach’s alpha coefficient should be higher than recommended or ≥0.6 [91]. Based on the rules and guidelines of internal consistency, the obtained value should be within 0.6 ≤ α ≤ 1.0 because this represents acceptable consistency, thus reliability of the research sample. In this research, all Cronbach’s coefficients were acceptable for all set statements (

Table 2. Reliability of research statements.

Statement	Cronbach’s Coefficient	Reliability
WILL 1	0.84	(0.7 ≤ α < 0.9) sample is remarkably reliable.
WILL 2	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
WILL 3	0.82	(0.7 ≤ α < 0.9) sample is remarkably reliable.
WILL 4	0.82	(0.7 ≤ α < 0.9) sample is remarkably reliable.
ATT 1	0.84	(0.7 ≤ α < 0.9) sample is remarkably reliable.
ATT 2	0.84	(0.7 ≤ α < 0.9) sample is remarkably reliable.
ATT 3	0.85	(0.7 ≤ α < 0.9) sample is remarkably reliable.
ATT 4	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
NGC 1	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
NGC 2	0.82	(0.7 ≤ α < 0.9) sample is remarkably reliable.
NGC 3	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
NGC 4	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
NGC 5	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
AGC 1	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
AGC 2	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
AGC 3	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
AGC 4	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.
AGC 5	0.83	(0.7 ≤ α < 0.9) sample is remarkably reliable.

Source: Authors.

) and variables (

Table 3. Reliability of variables.

Variable	Cronbach’s Coefficient	Reliability
Willingness	0.66	(0.6 ≤ α < 0.7) sample is reasonably reliable.
Attitude towards environment	0.79	(0.7 ≤ α < 0.9) sample is remarkably reliable.
Natural green competencies	0.64	(0.6 ≤ α < 0.7) sample is reasonably reliable.
Acquired green competencies	0.60	(0.6 ≤ α < 0.7) sample is reasonably reliable.

Source: Authors.

).

Table 2 and Table 3 show that the sample was reasonably reliable, therefore the questionnaire had acceptable construction for this research.

4. Results and Discussion

4.1. Descriptive Statistics of Statements

In this section of the paper, the values of descriptive statistics of respondents’ answers to the set statements for all variables are given separately as mean value and standard deviation.

Table 4. Descriptive statistics of variables.

Variable	Mean	Std Dev
Willingness moment	3.7200772	0.6870397
Attitude towards environment	3.4995174	0.7621516
Natural green competencies	3.4664093	0.7463069
Acquired green competencies	3.7181467	0.5979485

Source: Authors.

shows the mean values of the estimates for the variables and their standard deviations.

The variable WILL has the highest mean value at 3.7200772 and the variable NGC has the lowest mean value at 3.4664093. The variable ATT has the largest standard deviation at 0.7621516 and the variable AGC has the smallest standard deviation at 0.5979485.

The frequency and percentage of attitudes according to the ratings are given in

Table A1. Frequency and percentage of attitudes according to claims.

Attitude
Claim	1 = Totally Disagree	2 = Partially Disagree	3 = Neither Agree nor Disagree	4 = Partially Agree	5 = Totally Agree	Total
WILL 1	19 3.7%	20 3.9%	46 8.9%	165 31.9%	268 51.7%	518
WILL 2	5 1.0%	17 3.3%	89 17.2%	280 54.1%	127 24.5%
WILL 3	42 8.1%	138 26.6%	208 40.2%	100 19.3%	30 5.8%
WILL 4	16 3.1%	34 6.6%	133 25.7%	200 38.6%	135 26.1%
ATT 1	69 13.3%	92 17.8%	127 24.5%	142 27.4%	88 17.0%
ATT 2	73 14.1%	93 18.0%	133 25.7%	131 25.3%	88 17.0%
ATT 3	80 15.4%	73 14.1%	137 26.4%	140 27.0%	88 17.0%
ATT 4	2 0.4%	3 0.6%	35 6.8%	153 29.5%	325 62.7%
NGC 1	11 2.1%	49 9.5%	117 22.6%	169 32.6%	172 33.2%
NGC 2	18 3.5%	49 9.5%	133 25.7%	177 34.2%	141 27.2%
NGC 3	26 5.0%	98 18.9%	168 32.4%	152 29.3%	74 14.3%
NGC 4	27 5.2%	102 19.7%	185 35.7%	134 25.9%	70 13.5%
NGC 5	21 4.1%	82 15.8%	215 41.5%	152 29.3%	48 9.3%
AGC 1	8 1.5%	40 7.7%	172 33.2%	208 40.2%	90 17.4%
AGC 2	36 6.9%	122 23.6%	175 33.8%	133 25.7%	52 10.0%
AGC 3	77 14.9%	156 30.1%	163 31.5%	96 18.5%	26 5.0%
AGC 4	2 0.4%	1 0.2%	17 3.3%	112 21.6%	386 74.5%
AGC 5	4 0.8%	7 1.4%	43 8.3%	145 28.0%	319 61.6%

in the Appendix A. For example, AGC 4 was scored 5 by the most respondents (386, 74.5%) and AGC 3 was scored 5 by the fewest respondents (26, 5.0%). On the other hand, ATT 3 was scored 1 by the most respondents (80, 15.4%) and ATT 4 was scored 1 by the fewest respondents (2, 0.4%). Finally, WILL 3 was scored 3 by the most respondents (208, 40.2%), while AGC 4 was scored 3 by the fewest respondents (17, 3.3%).

4.2. Correlation and Regression Analysis of the Model

Figure 8 displays the values of Pearson’s correlation. The directions of all possible relationships between variables are positive, which means there is a positive correlation between variables.

The highest correlation coefficient is between NGC and AGC, at 0.6577, or medium strong. That means that NGC can explain AGC with 0.43256929 or 43.25%. The lowest correlation coefficient is between WILL ATT, at 0.2530, or relatively weak. That means that WILL can explain ATT with only 0.064009 or 6.4%.

Based on the theoretical sub-models (Figure 4, Figure 5 and Figure 6), estimates of the statistical significance of influences are given for single linear dependencies (

Table 5. Regression data for dependent variable WILL.

Independent Variable	ANOVA	Std Beta	RSquare (%)	Connectedness	Hypothesis	Regression Equation
Attitude towards environment	F(1516) = 35.2889, p < 000001	0.3	6.4	Relatively weak	H1 is not confirmed	y = 2.9219391 + 0.2280709∙x_1 WILL = 2.9219391 + 0.2280709∙ATT
	Table A2	Table A3
Natural green competencies	F(1516) = 163.9849, p < 0.0001	0.5	24.11	Medium strong	H2 is confirmed	y = 2.152978 + 0.4520814∙x_1 WILL = 2.152978 + 0.4520814∙NGC
	Table A4	Table A5
Acquired green competencies	F(1516) = 236.8614, p < 0.0001	0.6	31.46	Medium strong	H3 is confirmed	y = 1.3238157 + 0.6444774∙x_1 WILL = 1.3238157 + 0.6444774∙AGC
	Table A6	Table A7

Source: Authors.

): independent variables ATT, NGC, and AGC on dependent variable WILL (ANOVA and interpretations for Std Beta, RSquare (%), component connections, hypotheses, and regression equations).

Based on Figure 4, Figure 5 and Figure 6 and

Table A2. ANOVA for WILL and ATT variables.

Source	DF	Sum of Squares	Mean Square	F Ratio
Model	1	15.62115	15.6212	35.2889
Error	516	228.41505	0.4427	Prob > F
C. Total	517	244.03620		<0.0001

,

Table A3. Coefficients for WILL and ATT variables.

Term	Estimate	Std Error	t Ratio	Prob > |t|	Std Beta	VIF
Intercept	2.9219391	0.1375	21.25	<0.0001	0
ATT	0.2280709	0.038393	5.94	<0.0001	0.253005	1

,

Table A4. ANOVA for WILL and NGT variables.

Source	DF	Sum of Squares	Mean Square	F Ratio
Model	1	58.85166	58.8517	163.9849
Error	516	185.18453	0.3589	Prob > F
C. Total	517	244.03620		<0.0001

,

Table A5. Coefficients for WILL and ATT variables.

Term	Estimate	Std Error	t Ratio	Prob > |t|	Std Beta	VIF
Intercept	2.152978	0.125174	17.20	<0.0001	0
NGC	0.4520814	0.035303	12.81	<0.0001	0.49108	1

,

Table A6. ANOVA for WILL and NGT variables.

Source	DF	Sum of Squares	Mean Square	F Ratio
Model	1	76.77741	76.7774	236.8614
Error	516	167.25878	0.3241	Prob > F
C. Total	517	244.03620		<0.0001

and

Table A7. Coefficients for WILL and ATT variables.

Term	Estimate	Std Error	t Ratio	Prob > |t|	Std Beta	VIF
Intercept	1.3238157	0.157696	8.39	<0.0001	0
AGC	0.6444774	0.041876	15.39	<0.0001	0.560905	1

in the Appendix A, graphs of three single linear regression equations for WILL as a function of the variables were projected: attitude towards the environment, natural green competencies, and acquired green competencies (Figure 9).

Hypothesis H1, which states that ATT affects WILL, is not confirmed. Hypothesis H2 is confirmed, implying that NGC affects WILL. Hypothesis H3 is confirmed, indicating that AGC affects WILL.

Estimates, of the statistical significance of the influence of independent components ATT, NGC and AGC on dependent component WILL for multiple linear dependency (ANOVA and interpretations of Std Beta, RSquare (%), component connections, hypothesis, and multiple regression equation) are given in

Table 6. Multiple regression analysis data for dependent variable WILL.

Independent Variables	ANOVA	Std Beta	RSquare (%)	Connectedness	Hypothesis	Regression Equation
ATT, NGC and AGC	F(3514) = 89.9948, p < 0.0001	0.6	34.43	Medium-strong	H0 is confirmed	y = 1.1368655 + 0.056402∙x_1 + 0.1953311∙x_2 + 0.4595662∙x_3 WILL = 1.1368655 + 0.056402∙ATT + 0.1953311∙NGC + 0.4595662∙AGC
	Table A8	Table A9

Source: Authors.

. The obtained data (

Table A8. ANOVA for WILL, ATT, NGT, and AGT variables.

Source	DF	Sum of Squares	Mean Square	F Ratio
Model	3	84.03989	28.0133	89.9948
Error	514	159.99631	0.3113	Prob > F
C. Total	517	244.03620		<0.0001

and

Table A9. Coefficients for WILL, ATT, NGT, and AGT variables.

Term	Estimate	Std Error	t Ratio	Prob > |t|	Std Beta	VIF
Intercept	1.1368655	0.168131	6.76	<0.0001	0
ATT	0.056402	0.034286	1.65	0.1006	0.062568	1.1341029
NGC	0.1953311	0.043681	4.47	<0.0001	0.212181	1.765106
AGC	0.4595662	0.056122	8.19	<0.0001	0.399972	1.8704231

in the Appendix A) show that the contributions of the independent variables differ in multiple linear regression.

The most significant contribution to the dependent variable WILL is the independent variable AGC (39.99%), followed by NGC (21.21%) and ATT (6.25%). Therefore, the general hypothesis H0 is confirmed, indicating that ATT, NGC, and AGC affect WILL. The graph of the multiple linear regression equation of WILL as a function of ATT, NGC, and AGC shown in Figure 10 was projected based on Table 4.

Based on the presented results, the multiple regression equation can be fitted, which means that the independent variable ATT can be excluded from the analysis, because its influence on the dependent variable WILL is insignificant for further research. Consequently, a new hypothesis H01 is set, showing that NGC and AGC affect WILL.

Table 7. Multiple regression analysis data for dependent variable WILL.

Independent Variables	ANOVA	Std Beta	RSquare (%)	Connectedness	Hypothesis	Regression Equation
NGC and AGC	F(2515) = 133.1978, p < 0.0001	0.6	34.09	Medium strong	H01 is confirmed	y = 1.2416889 + 0.1982178∙x_2 + 0.4817681∙x_3 WILL = 1.2416889 + 0.1982178∙NGC + 0.4817681∙AGC
	Table A10	Table A11

Source: Authors.

shows the statistical significance of the influence of independent components NGC and AGC on the dependent component WILL for multiple linear dependence (ANOVA and interpretations of Std Beta, RSquare (%), component connectivity, hypothesis, and multiple regression equation).

Based on the obtained data (

Table A10. ANOVA for WILL, NGT, and AGT variables.

Source	DF	Sum of Squares	Mean Square	F Ratio
Model	2	83.19750	41.5988	133.1978
Error	515	160.83869	0.3123	Prob > F
C. Total	517	244.03620		<0.0001

and

Table A11. Coefficients for WILL, NGT, and AGT variables.

Term	Estimate	Std Error	t Ratio	Prob > |t|	Std Beta	VIF
Intercept	1.2416889	0.155846	7.97	<0.0001	0
NGC	0.1982178	0.043718	4.53	<0.0001	0.215317	1.7622575
AGC	0.4817681	0.054565	8.83	<0.0001	0.419295	1.7622575

in the Appendix A), it can be seen that the contributions of the independent variables differ in the multiple linear regression equation. The independent variable AGC makes the largest contribution to the dependent variable WILL (41.92%), followed by NGC (21.53%). The total coefficient of multiple determination is 0.340923. Related to the previous multiple regression equation that included independent variable ATT, the total ratio decreased by only 0.003, which is insignificant. Therefore, hypothesis H01 is accepted, meaning that NGC and AGC affect WILL.

Based on the obtained data considering hypothesis H01 (Table 4), a graph of the multiple linear regression equation of WILL as a function of NGC and AGC was projected (Figure 11).

Based on the presented research, it can be concluded that the dependent component WILL can be explained by the independent component ATT with 6.4%. Therefore, hypothesis H1, which states that ATT affects WILL, is not confirmed. The dependent component WILL can be explained by the independent component NGC with 24.11%. Consequently, hypothesis H2 is confirmed, implying that NGC affects WILL. The dependent component WILL can be explained by the independent component AGC with 31.46%. Accordingly, hypothesis H3 is confirmed, indicating that AGC affects WILL. The dependent component WILL can be explained by the independent components NGC, ATT, and AGC with 34.43%. Therefore, hypothesis H0 is confirmed, meaning that NGC, ATT, and AGC affect WILL. Finally, the dependent component WILL can be explained by the independent components NGC and AGC with 34.09%, implying that hypothesis H01 is confirmed and that NGC and AGC affect WILL.

5. Conclusions

According to the findings, the aim of the paper was fulfilled. Natural green competencies, acquired green competencies, and attitudes toward green behaviour of an individual affect the willingness of the same individual. Furthermore, university students are involved in environmental protection, although their attitudes and understanding about environmental preservation vary. However, much more can be done to raise student understanding of this critical issue. In this regard, both students and universities should work harder to promote environmentally friendly behaviour and green competencies, leading to improved green performance.

Green settings have become an essential part of the contemporary business environments, and it forces organisations to shift business paradigms to be more inclusive, pro-environmental, and innovative to maintain and gain a competitive edge. Furthermore, every forward-thinking organisation should consider incorporating sustainability into its processes to build future growth strategies. Green competencies of individuals are an essential part of this process. This paper endeavoured to examine how organisational performance is influenced by green competencies and willingness of individuals, and their interdependence and mutual relations. As a result, it can be concluded that a more inclusive and pro-environmental approach will have direct and indirect impacts on organisational growth, financial performance, and the environment. Accordingly, it means that embracing modern pro-environmental trends and nurturing green competencies benefit organisations in many ways.

This study is not exempt from some limitations and should be addressed in future research. The survey was undertaken for the first time in this article, and in a particular context, during the specific conditions regarding the global health pandemic that could influence the final results. The COVID-19 pandemic has had a detrimental impact on many aspects of human existence [92], including human resource management [93]. The poll solely pertains to students from universities in Serbia. Even though this research benefits from getting crucial information about students’ attitudes toward green behaviour, it is also a limitation because it is uncertain if findings can be applied to students of different nations. There are also certain limitations regarding setting up the theoretical model. Firstly, there is a time lag between acquiring green competencies and developing willingness, which can be a limitation. Moreover, causation should be observed carefully because there can be collinearity if the analysis is observed only cross-sectionally.

Accordingly, these limitations give recommendations for future research paths. Future research can be undertaken after the COVID-19 pandemic to determine the impact of the pandemic on the results. The same survey should be undertaken in other countries to make a comparative analysis. The recommendation is to conduct the same research periodically to examine trends and make a comparative analysis. Finally, before the future research, scholars could set up a new theoretical model with stronger causation between variables.

The paper has practical, managerial, and theoretical implications. The main practical contributions are related to the new cognitions associated with green competencies’ impact on organisational performance. Managerial implications emerge from the need to observe the green environment differently by including pro-environmental and innovative premises, demonstrating the importance of a paradigm shift. The implied need to maintain and gain a competitive advantage necessitates considering the individual’s green competencies and willingness. The article contributes to the existing literature providing a comprehensive literature review and, building on the existing theoretical model, adds willingness moment and proposes a new theoretical model. As a result, evaluating the impact of analysed parameters on performance can be considered a contribution of this paper and the Innovative Human Resource Management Framework can be used as a guideline for managers.