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Article

Employee Volunteerism—Conceptual Study and the Current Situation

Institute of Enterprise Management, Obuda University, Tavaszmező utca 15-17, H-1084 Budapest, Hungary
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Author to whom correspondence should be addressed.
Sustainability 2020, 12(20), 8378; https://doi.org/10.3390/su12208378
Received: 31 August 2020 / Revised: 25 September 2020 / Accepted: 26 September 2020 / Published: 12 October 2020
(This article belongs to the Special Issue CSR and Business Ethics for Sustainable Development)

Abstract

The purpose of the study is to analyze employee volunteerism. This issue had not been studied on a broader international level earlier. This research firstly discovers altruism and volunteerism values in the economy. Then, based on the third-party model, observes each part, where participants are the (1) volunteer (employee) (2) company (and its CSR activity) and (3) an external organization, which manages this type of formal volunteerism. Each participant was analyzed through comprehensive analysis using descriptive and inference statistics and classification methods on complex, extensive secondary databases. Altogether, more than 10,000 respondents’ answers are examined from two worldwide surveys, and further ten international statistical indicators and indices are explored. These methods result in volunteer characteristics on a personal level, afterwards in country classification, which provides a cultural comparison of the employee volunteerism. Our findings prove that demographical differences do not, but company-level actions influence the intensity of formal volunteerism. Moreover, three main clusters (formed from 43 countries) show different values. This diversity might partly be caused by measurement fragmentations and lack of internationally accepted definitions and theories. This paper aims to provide a broader overview of the topic, which might be a useful starting point for the forthcoming aggregated conceptualization. Employee volunteers’ behavior arises from the personal value of volunteerism. However, the attendance and intensity of voluntary activity are primarily influenced by the environment (e.g., life period, living and working situation). Employee volunteerism programs are an important and essential part of CSR at the company level, and strongly frames this activity, where employee volunteerism could associate each participant’s interests and improve their values. However, the practices may differ in each country and in each sector. The current pandemic rewrote the traditional volunteerism model and our projection. The last chapter provides a preliminary study about how employee volunteerism could work in this extraordinary, COVID-19 situation.
Keywords: altruism; volunteerism; CSR; employee volunteerism; third-party model of volunteerism; COVID-19 altruism; volunteerism; CSR; employee volunteerism; third-party model of volunteerism; COVID-19

1. Introduction

“The good news is that volunteers, perhaps more than ever before, are demonstrating the critical importance of acting together to tackle the challenges of our time. … The full picture of volunteering remains complex and often hidden. Most volunteering happens in conditions that can be difficult to capture: actions beyond the confines of formal organizations; spontaneous, sometimes highly individual actions in response to a need, and in humanitarian contexts that are dangerous and fastpaced. These forms of participation are driving change and shifting the dynamics in ways that we are only just beginning to recognize and measure.” (Oliver Adam, UNV & Jagan Chapagain, IFRC, 2020) [1].
Volunteerism is a crucial part of CSR on the corporate level and an essential part of the wider voluntary sector. However, from an economic point of view, the selfish actor model and the profit-oriented business theory do not match with free giving. This means free giving must arise from a more profound value. At the same time, the expression of voluntary activity is determined by the environment, especially by the economic environment.
Many authors emphasized volunteerism as a driving force of this sphere. Volunteerism stems from altruism, which is a basic value on a personal level. Volunteerism is an expression of altruism. Altruism is widely studied basic value in economics, mainly related to volunteerism. Although these two definitions cannot exist without each other, as Haski-Leventhal [2] underlined, not every act of volunteering is altruistic and not every altruistic act is volunteering. Moreover, she underlined that altruism is basically selfish. Similarly, CSR and employee volunteerism are also driven by profit. As Holt [3] defined, the model of a selfish “homo economicus” actor will free ride on every free offered good; in this sense, altruism depends on the price of helping others, so not every actor is entirely selfish. On the other hand, a volunteer’s per capita value of the benefit must be compared with the cost of volunteering. This so-called volunteer’s dilemma is a social problem. As experiments showed when similar volunteers’ actions met, and a larger group formed, it ended in a reduction of volunteerism’s price. This means that the institutionalized form of volunteerism is rewarding. Indeed, the individualistic view of ethical behavior considers ethical behavior as that advances long-term self-interest [4]. Moreover, motivations related to volunteering can be altruistic, value-based and utilitarian [5]. A broader international study found that some selfish motivations regarding volunteerism are utilitarian; for example, university the student population is highly motivated by career-enhancing and job prospects when they take part in voluntary activities, however, the forms of student volunteering varied by countries. That said, employee volunteerism is motivated by egoistic, altruistic and organizational citizenship motives. Moreover, a study [6] suggested that volunteer opportunities that fulfil egoistic and organizational citizenship motives will be adequate, rather than a simple altruistic motive.
This self-interest characterizes corporate needs, as well [7]. Simon described [8,9] altruism as a unique form of loyalty to (or identification with) groups to which the individual belongs, mainly concerning volunteering. Indeed, 50 years of literature in social responsibility shows that the widely studied subtopics are significantly related to altruism, ethics, sustainable development and voluntary activities [10]. Volunteerism is broadly studied and measured at different levels and on various fields. Here we began from the personal level, and traced back volunteerism to its main economic drivers, selfishness and altruism. However, volunteerism exists beyond personal traits and characteristics. At this level, volunteerism is handled as a utilitarian value, a kind of behavioral expression of altruism. On the other hand, this issue can be handled as social, as well as economic behavior. Indeed, volunteers themselves [11] go through different socialization development—the five phases considered a career ladder for volunteers—from the nominee to the retiring stages. It means volunteer activity should be treated and managed like employment. This activity needs clear a vision and mission, punctual responsibilities and rights, adequate resources and motivation, and all of these components should suit the different stages; and this is not a one-man show. Consequently, volunteerism is an essential issue of economics.
We briefly discuss the relevant literature on volunteerism—when we emphasize the economic viewpoint; therefore, employee volunteerism as part of CSR can be described. Relying on the third-party model, our research questions and methodology are argued respectively in the next two sections. In the following section, we first analyze volunteerism on a personal level. Second, we examine internationally measured statistical indicators of formal volunteerism; and third, we classify selected countries regarding their voluntary activity. In the discussion section, we assess our findings’ managerial implications and our research’s limitations. Finally, we outline how COVID-19 has rewritten volunteerism. Here we predict the possible benefits of virtual volunteerism in this extraordinary situation, and we reflect on the contribution of our results to the further employee volunteerism agenda. The contribution of this paper has changed during this research, as it happened in real life. The pandemic rewrote all aspects of our life. Before the COVID-19 pandemic, a clear clustered map, based on our recent findings which are detailed in the discussion part, showed how employee volunteerism can and may work properly and how all participants of the third-party model can and may facilitate each other. Best practices are listed in leading countries, where volunteerism has a deeper and longer heritage. These case studies would stand as examples for the countries where employee volunteerism is not so well known. Our findings suggested that the main differences among these countries arise from the situation and role of the government and non-profit sector, because, as our results showed, all people on a personal level are ready to help. Altruism works regardless of the geographical or political circumstances. Firms, governments and nonprofits are going to tailor the way, the form and the frequencies of volunteerism but now these members are faced with a daunting challenge of COVID-19. In this extraordinary situation, the measured harmony crashed. Each country must apply different tools for how to win the battle against the pandemic, so the topic of volunteerism moves into the background. As preliminary research shows, so-called self-regulated voluntary activities are coming slowly into the light. Hopefully, all these bottom-up activities will lead us back to the previous model of employee volunteerism, which might become a new normal.

2. Literature Review

Many authors have argued that while plenty of studies and measurements are about the core characteristics of volunteerism, we still do not have a single, simple, objective definition. Rochester and her colleagues [12] broadly examined volunteerism in their book. According to them, volunteering can be described through a three-perspectives model, where volunteering is seen as (1) a gift of time or “unpaid” work or service, because of this the volunteer represents an additional resource for the whole society; (2) serious leisure, when volunteers sacrifice their free time and effort in order to satisfy intrinsic needs and spend their time in a meaningful and joyful way (intrinsic and extrinsic motivation); (3) activism as a force for social change. Some other experts kept the last characteristic as crucial. This means that social activism arises from strong motivations for volunteering in order to understand ecosystems, express and propagate certain values or interact socially [13,14]. We would extend this definition with (4) free will. However, the cited authors questioned free will. They stated that some forms of activities may involve a certain level of coercion, e.g., compulsory student volunteerism at high schools or employee-supported volunteering might also be listed here. They have not specified volunteerism straightly with the “unpaid” marker, because volunteers should not be out of pocket, but volunteers should not receive any remuneration (or monetary incentives) for their effort. That means that a certain level of payment (covering the costs or a kind of small material reward) always will be present. Later, further classifications of volunteerism are described; here, we selected those definitions which might be related to CSR (Corporate Social Responsibility) and employee volunteerism. Employee-supported volunteering [15] is described as episodic, common activities to enhance teambuilding or to provide expert advice (later we call this skill-based volunteerism). In this study, we try to measure each characteristic of employee volunteerism.
There are also various typologies of volunteerism in the literature. The main typology divides volunteerism into two main types and is mainly used by statistical enumerations. These are respectively: (1) formal/organization-based, and (2) informal/direct volunteerism. While the first one is undertaken through an organization or group of clubs, the second one covers a more spontaneous, direct, individual type of help. Furthermore, in some countries, there are not exact qualitative differences between formal (organizational) and informal (non-organizational) volunteerism in term of statistical measurement [16]. We also realized and described this problem in our study. Apart from this, our focus was wider, so we have extended the microeconomic view to a broader macro level. This paper intents to observe employee volunteerism—that means formal volunteerism where active and professional support arrives from the non-profit sector.
The question is given of why a company would be interested in a common project without any profit. Baines [17] listed the flow-on benefits to business of engaging in the non-profit sector: (1) at the internal level, this relationship will facilitate employee attraction, staff retention and employee engagement; (2) it is assigned with company purpose and values; (3) it will enhance customer loyalty and brand enhancement and open new markets. Millora [18] extended this typology and suggested a new agenda for the four types of volunteering practices. These ‘traditional’ practices are (1) mutual aid/self-help which is based on reciprocity, mostly informally, so many active individuals do not call themselves volunteers. (2) Philanthropy and service work through organizations and associations, (3) Civic participation which also involves political decision-makers and social audits. (4) Finally, advocacy or campaigning is the broadest form, where “pressure groups” may also be active members in order to achieve a collective action or to lobby for change. A new form of volunteering is “leisure” or serious leisure volunteerism.
From our viewpoint, the second form (2) relates to CSR, where greater recognition of the organizations’ diversity is involved (e.g., universities or companies). Therefore, if a volunteering activity is supported and/or sponsored by a company, it is a kind of Corporate Social Responsibility. Some authors detailed further dimensions of volunteerism, for example, Cnaan et al. [19] conceptualized volunteerism and placed volunteerism between different dimensions based on the combination of the above factors. As a result of (a) the free choice lies between free will and obligation to volunteer; (b) remuneration ranges from none at all, not expected, to fully expenses-covered and offering a low pay or stipend; (c) the structure can be formal or informal; the final dimension is that (d) the intended beneficiaries of volunteerism can range from helping a stranger to helping friends or relatives to benefit oneself.
All abovementioned theories and findings go far beyond the simple helping and giving charitability. Every study reflected a broader field. It can be referred to as the market of volunteerism, where different actors are making an effort and cooperating. Our goal is to achieve a well-structured, comprehensive overview of this field. That is why the paper relies on the so-called third-party model.
Haski-Leventhal et al. [20] introduced the Social Responsibility Matrix, which is based on the market model of volunteerism. Earlier, she suggested [21] this so-called third-party market model, where the three participants are government, corporations and educational institutes. The current study also operates in this conceptualization. However, the three main areas and participants are the following: (1) a person, who is not just a donor in this model, but at the same time is an employee in a (2) company which is in a frame of CSR action cooperation with a (3) non-profit charitable organization. Together they frame employee volunteerism. Moreover, the overlapping of the three perspectives results in additional combinations. Initially, the Social Responsibility Matrix shows the connection between employees and organizations concerning social responsibility at the organizational (CSR) and individual levels. Accordingly, this model covers the relationship between (1) first and (2) second participants. Both participants have their own particular values and attitudes regarding social responsibility. Moreover, employees can engage in private forms of social responsibility out of their workplace (i.e., identity-based volunteerism without behavior). An organization can pretend (behavior-based) CSR without value. The win-win situation is when the employee’s identity matches an organization’s values and together they can reach social responsibility. The authors listed the main factors which motivate social responsibility. Based on their findings, our literature review follows their structure. At the heart of this model is the volunteer. The volunteer is active in doing the work/service, enhancing social capital, strengthening the community. They are vital members/resources of society and the company or university. The volunteer is a strong, active link between organization, the community and society. As a result, they represent and form employee volunteerism. According to the aforementioned authors, the government, educational institutes, organizations and business entities add a frame to volunteering. As our focus, we replaced the government with the non-profit sector, i.e., charity organizations.
The authors also listed the most critical factors which count in volunteerism. Firstly, on a personal or volunteer level, two things are highlighted: (1) volunteerability covers the willingness, capability and availability of individuals to volunteer. The concept is derived from employability because this term defines the ability to be employed. Secondly, from the organization’s side, (2) recruitability is involved, which refers to the ability of volunteer organizations to recruit volunteers and maintain them. This concept arises from the demand side and has four main components: accessibility, resources, networks and cooperation. Each participant influences the volunteerability of individuals and the recruitability of volunteer organizations and has their own interest in and motivation for volunteering. In this paper, the roles of corporations and non-profits are underlined, as we ignore the topic of university volunteerism, even though we agree with Vetitnev et al. that the most vital advantage of university volunteering is developing future, ethically minded leaders [22]. In addition, educational institutions and communities [23] are also involved in CSR activities. Reicher [24] presented this in a successful best practice where these relationships worked successfully among students, researchers as volunteers at universities and firms, as a part of University Social Responsibility—USR. Bowen et al. [25] compared employee volunteering with service learning. The latter is a special form of university student volunteerism whereby education and charity organizations can meet while benefiting the whole university. This activity significantly boosted students’ career through their gained communication and leadership experiences. That is why we will just briefly return to the new generation of volunteers in the last chapter. The main text concentrates on employee volunteerism.
The abovementioned third-party model [21] underlined the governments’ role, too. The legal system, laws and regulations influence each actor’s rights and responsibilities differently. Most countries have already implemented volunteering in their national development plans, but these programs remain isolated. Extended partnerships are still missing. Indeed, the measurement and comparison of national actions seem to be problematic due to the lack of widely accepted definitions, models and methodologies [1], since governments are the main drivers for achieving the goals. Those cannot be accomplished without many stakeholders and their proactive and effective public sector support [26]. In this study, politics and authority are not widely investigated because the study concerns the labor market from a business view. Instead of government, this study focuses on non-profits, as the main character of this model.
Businesses and organizations are also responsible for the environment (sustainability) and for the community in which they operate. Moreover, values can also be defined on the corporate level. Corporate values [4] are general beliefs about what is or is not appropriate behavior. This is similar to personal values, which are extended to ethical and moral questions on the corporate level, where instead of the individualistic view, the utilitarian view dominates. This reflects on ethical behavior which provides the greatest good to the largest number of people. Social responsibility is the related concept, but it refers to the overall way in which companies try to balance their resources to relevant groups and individuals in their social environment [27]. Business leaders should contribute through the activities of their firms to the welfare of their communities. This is a voluntary approach by which they may choose to meet or exceed stakeholders’ expectations by integrating social concerns with required revenue and legal obligations. This activity covers Corporate Social Responsibility, which can be briefly defined as the ways in which companies undertake their activities to have a positive impact on society [17]. Towards this shared value, a business creates economic value and value for society by addressing community needs and challenges, because it offers new opportunities in new markets. However, this extended responsibility arises from either the companies’ business activity or from ethical behavior. Therefore, four main aspects of business responsibility are legal, ethical, economic and philanthropic, the last of which refers to giving back to society and is generally considered as voluntary and charitable [4,28].
In this study, we accepted the following definition of CSR: “CSR is the obligation of an organization to act in ways that serve both its own interests and the interests of stakeholders, this includes employees and the public as well, i.e., anyone that will in some way be affected by the organization.” [4] p. 134.
However, CSR has been defined by various researchers in different ways. Halbusi and his colleague collected and compared different definitions [29]. They described CSR activities where employees are also committed to so-called personal social actions. Personal social action or individual action is supported or sponsored by the organization to help social issues and community well-being. This form can be measured in paid time off, special activities or personal caritative actions, but it does not include CSR activities without employee involvement such as grants or corporate-wide donations. It can be divided into further subclasses: (1) charitable donations, which could be automatically deducted from the employee’s salary, so the individual makes a minimum effort, therefore, has minimum involvement. (2) Volunteer days or special events in the company’s name, e.g., annual events sponsored by the company, which can be understood as episodic volunteering. (3) Employee Volunteer Programs when (a) from bottom to top employees inform their employer of off-site activities in the name of the company, (b) top-to-bottom ways when an employer provides a list of volunteer opportunities for their employees, (c) a side of a non-profit organization is also involved. This non-profit organization enquires after a firm’s help, so (d) a firm delegates employees to a non-profit organization. In any case, if the employees are not engaged with the firm’s values, they will not represent themselves as organizational representatives, so those actions cannot be defined as part of the CSR program.
Another ranking of CSR level was provided by Deresky and Christopher [27] where the lowest level means obstructionist stance or avoiding responsibility, then comes defensive stance by which a company carries out legal but not always ethical requirements. By taking an accommodative stance, firms carry out only small social requirements by a particular interest. Finally, the highest level is the proactive stance when companies actively seek opportunities to be a good member of the community.
Benedek and her colleagues [23] structured CSR definitions in chronological order. Hereby they suggested volunteerism itself is not CSR, but it is a part of it. According to them, the primary motivation for voluntariness and donation is altruism: mutual altruism (interest), empathy altruism (willingness to help) and docile altruism (expectation). The last one means to follow the social norms and expectations and is typically sourced from the lack of clear CSR strategy.
In sum, we agree that CSR frames volunteerism. As an essential part of CSR in the competitive sector, employee volunteerism represents the major part of this article. Additionally, the employee volunteerism term can be extended as corporate volunteerism [30]. Here we concentrated on the former, whereby the participants in an employee volunteering program reflect the third-party model. Respectively, the participants are the employee as a volunteer, the community partner (or non-profit organization), and the company [31]. On the other hand, it is highly important to underline that volunteer work is not the same as CSR. The former is more associated with formal volunteerism with its direct impact on the economy. The later one, the employee volunteerism, is rather an essential part of Corporate Social Responsibility which targets employee engagement and the company’s reputation [32]. Therefore, instead of the economic impact analyzation, its impact should be managed and measured at the organization level, where this impact can be expressed in financial, social and environmental terms. In our case, there might be overlapping among the definitions of employee volunteerism, CSR and formal volunteerism, because there are no direct global indicators which could clearly clarify employee volunteerism.
The most cited and best summary of employee volunteering literature was provided by Rodell and her colleagues [33], who adapted the behavioral approach. However, a lot of different definitions have been suggested in the current state of the art, and most of them contain the following elements: this activity is an essential part of CSR, where employee devotes time and effort freely in a frame of planned activity for an external non-profit or charitable organization. It is beneficial for employees and firms, as well. Therefore, employees, companies and either organization are involved, the activity covers doing something outside of the normal work behavior, in a planned and organized formal mode. A variety of factors influence employee volunteerism. (1) On the employee’s side: individual factors like demographic, personality and identity, and motives, (2) workplace characteristics, such as job design and work context; (3) at the company level: time, financial and logistical support, employer recognition and publicity of opportunities. It could happen in various ways (1) depending on the length and regularity of the volunteering, (2) depending on the direction and intensity of volunteering and, finally, (3) depending on persistence. Finally, the results or outcomes of voluntary activity inspire employees, employers, and outside of the company, stakeholders, the partner organizations, in sum, the whole society. To achieve these goals, the company should have a well-structured Employee Volunteer Program [34]. This is a planned, managed effort that seeks and encourages employees towards effective voluntary activity under the sponsorship of a certain company. Comparing this activity with cash-only charitable giving, it requires a more complex strategy, diverse contributions and more resource with a clear focus on addressing a serious social problem. It means that business priorities, employee interest and community must overlay each other. Cycyota et al. [35] completed these with employers who can also give time, energy, skills or talent to an organization without receiving the return. Moreover, leaders’ behavior serves as an example; in the discussion part, we recommend some ideas on how this can happen.
Companies can offer various types of employee volunteer programs at the same time. According to an American study [26], the number of commonly offered programs in 2018 was on average five. Nevertheless, the range is wide, from the episodic short voluntary activity to the long-term, regular volunteerism. A possible list of programs contains the following programs: the main types of volunteering are those in which the company offers free work. Respectively, (1) traditional volunteering, which does not involve applying the employee’s workplace skills. (2) Pro bono or skills-based volunteering, in which the employee’s professional skills are offered in service to a community partner. A unique, new type of volunteerism is (3) virtual volunteering, which allows employees to commit their services and time to an organization away from its physical site. This type of volunteering is executed over the internet via any electronic devices that allow employees to provide their skilled services virtually [26]. However, the most popular program belonged to traditional or in-hand volunteering in 2018, but 76% of the companies (N = 193) offered important skills-based volunteer programs, as well. Those were either pro bono services or board leadership [26].
The other types could be counted towards charitable activities because the donation is material. These include (4) Dollars-for-Doers Grants, which is a program in which the company contributes a grant to a non-profit partner where its employee volunteers; (5) in-kind volunteering, when the company donates to a non-profit partner, e.g., used computers, meeting rooms or commercial product, and offers training or service on how to use them. All these programs can be happening within or out of working hours. The companies can offer these programs in the following forms: paid release time, flexible scheduling, off-company time, employee volunteer awards, board leadership, company-wide day, team grants, virtual volunteering, volunteer sabbatical, which can be handled as leisure volunteerism, and finally, an incentive bonus. Besides, those, as mentioned earlier, can be interpreted as incentives. As results showed, volunteer participation rates increased when employees had access to more flexible volunteering opportunities, i.e., the volunteering program itself can be interpreted by the employees as a facilitator or incentive. It is relevant to analyze the impact that volunteer work has on the organization either in financial or in social and environmental terms.
According to the latest studies [36], the best, top companies directly implement their CSR and employee volunteering activities into their Reputation Quotient. Moreover, Fortune’s 100 best companies actively practice employee volunteerism [35]. According to many reports [26,37,38], most of the companies measured volunteerism as part of the company’s engagement score and company performance. Of course, it might be due to greater ease in tracking on-company-time efforts. Some of the firms not only measure social outcomes and impacts of community investments/grants but also handle employee volunteer programs as a massive part of their business value. Moreover, as a study reported [26], the percentage of companies measuring the business value of community investments through brand/customer metrics (33%) falls behind the measurement done through employee metrics (43%). It means the business outcome of employee volunteerism is counted rather to HR performance than to the competitive market value. Therefore, the overall CSR is being used as an HR tool to recruit, engage and motivate employees [39]. On the other hand, any actions were taken by employees in the corporation’s name, and towards their ability to learn and improve either the social or company performance, may be listed as a CSR activity. In contrary, unlike action taken in a firm’s name or in which employees are passive participants, it can have a wrong impact on a firm’s brand, as well. When an employee is not involved or aware of CSR strategy (does not believe in it or handles it ineffectively) then his or her personal social action will also be rare. Aguinis et al. [40] argued that the so-called peripheral CSR could cause many troubles when the employees do not find meaningfulness through their work (i.e., lack of sensemaking and integration of the CSR strategy into a firm’s routine and activities). The opposite of this and a kind of solution is embedded CSR, which relies on the company’s core competencies, and in this way results in positive outcomes for employees, as well.
Although the positive impacts of employee volunteerism exceed its negative impacts, as it is shown in Table 1, disadvantages should also be taken into consideration. The biggest issue might be the cost of employee volunteerism. Some calculations showed that there is an inflexion point for management and program costs when total cash contributions exceed 100 million USD. The expansion of cash contributions may hide more complexity in terms of operational processes of such grants, funds and programs. The analysis showed a statistically significant positive correlation between higher total cash contributions and the management and program costs. In other words, the higher the total cash giving, the higher the management and program costs will be. The median management and program cost per contribution of staff team member in 2018 was around 200,000 USD, and total median management and program costs were 1.4 million USD by the most prominent US companies (N = 86) [26].
These large numbers supposed that seemingly the large companies are interested and can afford employee volunteerism. Basil et al. [48] studied the relationship between company size and support for employee volunteering. The research suggested that larger over smaller companies demonstrate greater formalization and codification of their support for employee volunteering. Consequently, the larger companies use employee volunteering effort in a more formalized way. Additionally, large companies are more likely to tie other types of charitable activities to employee volunteering. The authors observed 990 randomly selected Canadian businesses and the results showed that large companies support employee volunteerism in a more strategical structure than small companies. This includes organizing formal policies and programs. Therefore, it results in greater influence over the causes which benefit from employee volunteering. As Li and his colleagues [49] underlined, firm size is one of the key variables in this area.
This does not mean that smaller companies would not have employee volunteering. Instead, it means that SME may not have and may not manage conscious social audit [4] at an organizational level, even if a systematic assessment of social performance can be used to measure and report all resources and costs of CSR, and its effectiveness on the firm’s social performance [27].
The firm’s reputation, or its marketing strategy, visibility and the structure of ownership, might play an important role. It drives results, as shown in Li’s work [50]. We would like to underline that in this study these factors are not directly examined due to the lack of reliable information (i.e., these indicators are not detailed in the used secondary macro datasets).
As Baines [17] suggested from his personal experience, the non-profit sector must also balance financial rewards (personal interest) and doing good. The main difference between the for-profit and the non-profit business view is that the latter helps back by its inability to match them for profit in the following spheres: compensations, marketing, tolerance of risk, time and use of capital. Overall, a positive relationship can be found among a firm’s total performance and CSR. However, these results do not necessarily reflect employees’ perceptions and opinions [29]. It is argued that whilst most of the CSR literature has concentrated on external stakeholders, just a few studies have dealt with internal stakeholders such as employees.
In the following section, we observed employee volunteerism by analyzing statistical databases and empirical findings. Following the third-party model, firstly, we focused on the volunteers at their personal level. In order to provide a complex overview, we examined the factors and values which describe (employee) volunteers. Later, we expanded the focus by targeting non-profit organizations and companies that offer and support employee volunteerism. Because of the lack of direct secondary data, here we analyzed formal volunteerism.

3. Hypotheses and Research Question

3.1. Personal Characteristics

CSR policies and strategy are created by organizations, but individual employees implement them. In the middle of employee volunteerism stands the employee who is volunteering. Our personality and identity drive our behavior. Accordingly, attendance and intensity of volunteerism can be observed through personal traits and values. Rodell et al. suggested that strong volunteering identity can be characterized [33]. Although the meaning or characteristics of “volunteering identity” were not defined in the cited article, here we tried to discover it. In the first stage, demographic variables were studied, namely age and gender. More importantly, some results suggest that the most effective recruitment strategies depend on the age of the employee [51].
Bostjancic et al. [30] also underlined that the members of Generation Y (Millennials) as jobseekers found more attractive the companies which run employee volunteer programs. Tyagi and Mallya [52] pointed out that young employees are more willing to participate in CSR activities than their older colleagues. We agree with generation studies and think that volunteerism as a value is born with but can be taught, so a level of caretaking follows our life. The amount of time spent volunteering, or undertaking a form of volunteerism significantly depends on life period/life spent [53]. Millennials are young and ambitious, they have more power and time. Even their elder retired colleagues with grown-up kids are energetic enough to volunteer more. Between these two generations, generation X seems to be less active.
However, millennials will be having young children and generation X (who remain inactive volunteers now) will be retired, so the roles change. Beyond formalized employee volunteering projects, new volunteering relationships build on a new learning process, when the younger generation could relate to volunteering with the help of elder, more experienced volunteers. In the frame of employee volunteering, the next generation can experience and learn to engage with the labor market, and the spirit of social change may foster work ethics and business values. Rodell and her colleagues deeply examined individual factors which influence employees’ decision to volunteer [33]. Among others, age and gender belonged to the most studied demographic factors. According to them, age as a variable appeared to have a U shape depending on the employees’ life period. These findings led us to our first hypotheses, where we observed how age influences volunteer activity. However, we premised that this variable does not influence volunteer activity.
Regarding the gender comparison, gender differences have also been broadly studied [12,54,55,56]. Some results indicated that job satisfaction was related to volunteerism among female employees, but not among male employees [57]. As argued, women are more likely to volunteer when forms of company support ease their schedule, e.g., part-time volunteering [35], but men tended to be more interested in volunteering activity if it targeted cultural or sports event. Evidence on gender comparison regarding volunteering intensity is mixed. Still, some studies tend to show that women are more likely to volunteer; others criticized it [33]. Consequently, we can hypothesize that neither gender nor age has a significant influence on volunteerism.
Hypothesis 1 (H1).
Gender and age will not affect the intensity or attendance of volunteerism.
Ethical behavior is influenced by many factors, namely, personal variables (e.g., personal values), organizational (e.g., policies, codes, corporate values), external environmental factors (e.g., government, norms and values of the society) and cultural values. However, some universal ethical standards (certain universally accepted truths) are applied across all cultures, but cultural issues in ethical behavior should also be taken into consideration.
Corporate social activities are also determined by cultural contexts, and local habits and heritage [4]. We agree that there are different interpretations of ethical values; apart from this, the best strategy is starting with the lowest level of CSR and obeying universal rules and regulations or the ‘law of the land’ (i.e., laws of the host country) [27]. This means that the free will of active participation can be described by universal personal values and beliefs as Schwartz [58] also suggested. Relying on his findings about values, we attempted to discover the volunteers’ values. We hypothesized that volunteers could be described through a unique pattern.
Hypothesis 2 (H2).
Active, inactive and non-volunteers have different value sets.
The abovementioned results (i.e., Schwartz’s values) are based on a personal-level observation where formal volunteering is not separated from the informal. Therefore, these drew a greater picture of voluntary activity than we targeted. In order to study employee volunteerism, we had to tighten our focus and concentrate on formal volunteering. One of the operational challenges was how to access special types of data and analytics. Employee volunteerism has not been often studied on an international level or been examined as value sets.

3.2. Formal Volunteerism

As said in the previous chapter, employee volunteerism can be identified as formal volunteerism. As Madison and his colleagues proved, employee volunteerism has a long-term effect on organizational commitment and a more positive attitude towards work compared with the impacts caused by informal, individual volunteerism [46]. On the contrary, there were no significant differences in organizational citizenship behavior, nor stronger intention to stay with the company [59]. Although formal volunteerism, and as a part of it, employee volunteerism, is assessed, the methodologies are diverse. Both terms may require a broader view fitted to a nicety definition and measurement methodology. That is why, before we would analyze employee volunteerism, a comprehensive overview is needed where we suggest that various metrics assume equivalent results.
Hypothesis 3 (H3).
Ranking numbers from different metrics are significantly related to each other.
Employee volunteerism and formal volunteerism are determined not just by company level factors, but even more by country-level variables. It means that countries can be ranked and classified regarding volunteerism. For example, List and Price [60] ranked countries’ charity and voluntary activities. In their study, they focused on the so-called Western World and used a similar CAF (Charities Aid Foundation) database to the one we used. The explored variables were giving money (in percentage), giving time (in percentage), helping a stranger (in percentage) in population rate. The authors calculated WGI (World Giving Index) score as a composite factor of the formers. According to them, Australia and New Zealand have the highest percentage of the population involved in charity giving. Both countries have a long and strong heritage, as a national value in caritative behavior. Unfortunately, the Central and Eastern European countries are less generous, as Benedek et al. [23] found. Seemingly, citizens in the Western countries allocate more time, gift and money giving related to the tax treatment or public good provisions. As the authors suggested the reasons, what drives regional differences, remains unknown; in answering that, our paper provides some thought-provoking ideas.
Hypothesis 4 (H4).
Countries can be grouped according to their volunteerism activity, measured on ranking ordinary scales from the various datasets.
Rodell et al. [33] supposed that cultural comparison might be a potential way to study employee volunteering. For example, Handy et al. [5] ran a worldwide project to examine student volunteerism, which could be handled as an entrance to employee volunteering. Perhaps the students’ population seems to be easier to target than employees. As they suggested, student volunteers were motivated by career and job prospects. Authors collected and analyzed data from 12 countries and studied students’ motivation regarding volunteerism. They found that student volunteerism varied by country. Episodic volunteerism (short periods on an occasional basis) was typical in India or China. In contrast, more regular and longer activity was common in Canada, the USA and Belgium. Comparing country effects on the intensity of student volunteering, significant differences were found. These fundamental differences between the clusters lead us to our conclusion regarding cultural differences. This study also aims to observe and merge indicators which identify the level of volunteerism and cultural background in case of more than 40 countries. Here we assumed that clusters could be described with intensity (i.e., average amount of volunteerism), and with other characteristics of volunteerism calculated from secondary datasets. The most important characteristics are the proportion and attendance of formal and informal volunteering because that may provide further information about employee volunteerism.
Hypothesis 5 (H5).
Clusters can be compared and described with voluntary indicators.
Cultural differences were found in a few studies [5,12]. Because national cultural profiles influence national institutions, cultural values are reflected in national rules and regulations. One significant and widely studied cultural value is altruism, of which a crucial aspect is volunteerism. The measurement of culture is as difficult as estimating volunteerism, and methods are firmly based on various definitions. There are several studies on the value and impact of volunteering and more cross-cultural theories compare trends in different countries. In addition, political regimes are also colored by cultures. This study remained with secondary statistical indicators and compared the results of different databases. This comparison ensured a reliable interpretation of employee volunteerism practices around the world. Here, observational methods with secondary empirical data sources from well-known and broadly used indexes and theories were used, which are selected from statistical databases about formal volunteerism. After a more in-depth comparison of different definitions and methods, we calculated correlations between the variables above. Finally, different tests of independence can be implemented. Consequently, the results of various countries can be observed by principal component analysis so that the countries may be clustered.
With this two-stage statistical procedure, three critical findings can be obtained. Firstly, it provides a deeper insight and understanding into voluntary behavior’s personal characteristics and values. Secondly, selected countries can be grouped depending on volunteerism indicators. Finally, each cluster can be described and typified. Consequently, similarities and differences among these clusters can be observed, and deeper understanding may be found in the selected countries’ employee volunteerism ‘systems’. These findings ensure further implications about employee volunteerism and provide a systematic analysis among countries.

4. Materials and Methods

Firstly, we collected and explored secondary statistical findings and estimations about employee volunteering. Some of them were also directly implemented in our research, but the lack of a universally accepted methodology still causes problems [26]. In this chapter, we examined how employee volunteerism can be and has been measured. Here, we list the definitions from which these metrics are sourced.
According to Points of Light’s definition, volunteer activities are a type of company investment when a company invests non-negligible resources of an employees’ time in order to effectively serve community needs or mobilize employees to engage in direct voluntary service (doing good and giving back). The whole process is a planned, managed effort and is treated as a component of the CSR program. The company does not pay the employees directly but pays intermediaries or community organizations to organize these activities [61] and covers the ongoing costs.
The CIVIC 50 Survey is measured by True Impact and Points of Light; it draws a distinction between company-sponsored volunteering and employee volunteerism. The survey is a kind of measuring instrument which estimates employee volunteerism in the USA. Because the central concept based on the before-mentioned theory and one of the sponsor organizations is the same, this survey provides a more detailed definition but using the same terms. Company-sponsored volunteerism means common forms of this voluntary activity, which can include but are not limited to painting, conducting environmental cleanup and mentoring students, among others. Apart from the different forms, each employee’s voluntary activity must be supported by company resources [31].
Many experts argued that [62] a standardized reporting metrics should be considered, which would make it easier to report employee volunteering performance. Therefore, best practices might be offered. Sometimes this methodological lack arises from the view that CSR is only a tick in the PR toolbox rather than a new way of doing business. Indeed, the local government might enforce mandatory reporting about the competitive markets’ volunteering activity [7]. We have found some measurements which directly targeted employee volunteerism, even if not on an international level. Simple descriptive statistics were applied here. This statistical summary gives an insight into the company and business direction regarding the third-party model.
As pointed out in the survey, employee volunteerism can be described and examined through the third-party model. We targeted two main directions here. On the micro, personal level, we relied on Schwartz’s value set [58] measured by the World Value Survey. Schwartz’s value research contains volunteering- and altruism-related questions. Therefore, many researchers implemented his findings and observed his database as an identity component into volunteering-relevant studies. Many authors agreed that Schwartz’s findings reflect employee volunteerism impacts [20,29,63].
As argued, values either on a personal level or on company level drive and modify behavior. Schwartz [58] studied basic human values from various countries. However, he also found geographical differences; here, we are more concerned about volunteerism-related values. As he found, these values are recognized in all cultures, but as a part of the basic value set. Those might conflict other values because values are ordered by importance (which could explain the abovementioned diverse theories regarding age or gender differences). Values are beliefs and they motivate actions. Although in specific situations they may be transcended, they always serve as standards. Volunteerism might be related to Schwartz’s benevolence and universalism categories. The former enhances the welfare of those with whom one is in frequent personal contact; it promotes cooperative and supportive social actions. Moreover, Schwartz keeps benevolence as the most important value. The latter is a kind of tolerance and protection for the welfare of all people and nature. These two values compose self-transcendence, and together harmonize welfare and interests of others like a “cherish power.” Values are measured with the Schwartz Value Survey. A lot of research that followed (such as this article) used and built on either Schwartz’s survey or results. Moreover, many studies and research relied on Schwartz’s theory and methodology, e.g., statistical measurements that we used as secondary data, OECD Index, Happiness Index, CAF Giving Index.
In order to test personal volunteerism, we turned to the newly released provisional version of EVS/WVS Values Survey 2017/2020—Joint Core [64,65] database, including data from over 129,000 worldwide respondents. We selected and used n = 69,578 answers from the original Wave 7 version part.
Previously, we also tested the World Value Wave 6 dataset [66]. Wave 6 contains Schwartz’s values and other values, opinions, believes, as well. Wave 6 measured almost 90,000 participants’ answers from more than 60 countries between 2010 and 2014. The findings served as a conceptual basement for Inglehart and Welzel’s [67] Cultural Map. In this paper, the empirical part deals with a dataset without this constructive theory. We examined the collected n = 89,565 responses from Wave 6, too. The Wave 7 (2017–2020) is more up-to-date but contains fewer questions related to volunteerism or altruism. That is why we examined the EVS (European Values Study)/WVS (World Values Survey) joint survey, which was expanded with further questions about values. In addition, these two surveys overlap. For the final conclusion, we stayed with the Wave 7 survey where scales are more detailed and up-to-date.
Due to this large sample size, we used parametric techniques, and where the variables were measured on an ordinal scale, we relied on non-parametric methods, using SPSS23 and RStudio software. Because the results are sourced from controlled and supervised methodology and based on well-structured, stabile conceptualization and operationalization, here reliability and variability were not checked, we took them for granted. We preselected those questions from the lengthy questionnaire which were related to volunteerism. As this survey targets people’s opinion on the micro-level, volunteerism was observed by statements about values, beliefs and motivation mainly measured on an ordinal scale. Unfortunately, the small answer options range is a problematic weakness of the survey. The intensity and direction of volunteerism were questioned, which allowed us, after a data transformation, to divide the answerers’ group depending on the attendance or regularity of their voluntary activity. The questionnaire contains general volunteerism-targeted statements which are not directly related to employee volunteerism. That is why the formal and informal types of volunteerism were tested together.
The non-profit sector and government were described through secondary data, which aimed to estimate volunteerism in each country. Unfortunately, there is a regional and geographical imbalance in official measurement standard and effort due to the lack of universal conceptualization and definition. That is why our second empirical study aimed to discover a larger, international statistical database and measurements about volunteerism.
Here we observed ten different datasets, as it is detailed in Appendix A. These datasets can be ordered into various groups: (1) variables which marked intensity or frequency of voluntary activities; (2) variables which measured the amount (time) of volunteerism; (3) variables which focused on the voluntary activity’s type (direction). Each used different measurement units and was based on different methodological conceptualizations. Some of them are arranged in ranking order to examine gender or age differences. Here we selected ranking lists, where countries were ordered from the best achievement (1 = highest score), in descending order, measured on an ordinal scale. Some variables were adapted (i.e., tailored) to the population, some were not. Where it was possible, we preferred metrics adapted to the countries’ population number. According to our research questions, we tried to select those variables which directly measured formal volunteerism. Because of the forthcoming hypotheses, we assessed validity with Cronbach’s alpha for the relationship testing. We used Spearman’s rho test (in case of the ranking). Finally, for the model building, we used a classification method, hierarchical cluster analysis. Each method is broadly described respectively to the hypotheses. After a thoughtful selection and transmission, we choose 43 countries (European countries remained the majority).

5. Results

5.1. Secondary Findings

In this section, we list and organize secondary data about corporate volunteerism from the international literature, and statistical database. List and Price [60] calculated OLS regression to gain a deeper insight into cultural differences in volunteerism in the USA in 2004. Charitable giving was significantly sourced from individual donations. The second biggest source was foundations; finally, the corporates only represented 5.6% (13.46 billion USD) of that composition. According to the authors, this small amount can be explained from an economic point of view because profitability does not match with free giving. However, corporates’ social performance is significantly correlated with financial performance [27] and, as the authors agreed, ageing population and natural disasters would lead to higher levels of caritative actions in the forthcoming years.
The CAF [68] measures caritative activities for more than a decade. In 2016 [62], and later in 2018 [7], an update was provided. The organization published reports about Britain’s biggest companies and about how these companies deploy their corporate philanthropy. These are expressed in corporate giving in the form of cash or in-kind gifts (value of work hours donated towards employee volunteering) addressed to a charity or community organization. This methodology is also based on the third-party model, where businesses can help towards their partnership with the non-profit or charity sector.
A company can offer employee volunteering in various ways; for example, it can offer paid volunteering leave, which is one of the most preferred incentives for the employees. According to CAF’s findings, the smallest form of the donation was giving-time, compared with PR exercise donations. Moreover, an impressive result was that the general public’s view on the corporate donation slightly differed from the reality of which was the most generous industry in the FTSE 100. Although 37% of the respondents thought consumer services lead the ranking of donation, the reality was only 12%. The opposite case was in the healthcare sector [7].
Another index that measures social responsibility is the MSCI KLD 400 Social Index [69] as part of the MSCI ESG (Social and Governance) indexes [70], which also take environmental, social and governance risks and opportunities into account. The MSCI KLD 400 Social Index ranks almost 400 companies in the USA according to their sustainable investing, socially responsible investing, mission-related investing, or screening. These metrics typically include issues such as climate change, human capital and labor management, corporate governance, gender diversity, privacy and data security, among others. Although these metrics fit CSR ideology and theory, they do not contain a direct volunteering factor. The ESG indexes [70,71] are composite metrics and also include other indicators like Sustainable Impact Index and the United Nations Sustainable Development Goals or Socially Responsible Investing (SRI) Index. The whole measurement is designed to identify listed companies whose core business addresses at least one of the world’s social and environmental challenges. Listed companies are ranked in ESG ratings. Unfortunately, none of these was focused on volunteering, even though it provides a ranking of top 10 constituents, where information technologies and communication services are the leading examples.
We have found some measurements which directly targeted employee volunteerism, even if not on an international level. Although Points of Light [72] is not a research institution, it mainly designs products and services that make it easier for volunteers to find opportunities to serve, and possibilities for businesses to share best practices and develop custom solutions, and for non-profits to collaborate and share resources. In sum, this organization joins each participants’ hand and coordinates their activities. Points of Light publishes The Civic 50, in order to rank the 50 most community-minded companies in the USA each year. The ranking order is determined by an annual survey administered by True Impact. It is not just a benchmarking (based on scores of its survey and narrative interview) but also a place for sharing best practices. According to its latest report [37], the leading 50 companies’ employees volunteered 10.5 million hours which means 7.1 h average per employee in 2018. From this significant amount, 28% was skills-based volunteering. The average ratio of employees participating in an externally directed company volunteering activity was 43%. Regarding its methodology [73], the population includes public and private companies with US operations and revenues of USD 1 billion or more. The survey instrument consisted of quantitative and multiple-choice questions, narrative questions (mini case story, as it is referred to) to capture best practices. Because the measurement techniques are based on large companies’ self-reported responses, and as we know, CSR can be handled as a PR tool, reliability and validity are questionable. The before-mentioned True Impact’s measurement service refers to the ROI Tracker [38] and computes traditional, skills-based, pro bono, board service, and green team volunteer programs. Data were directly collected from their volunteers and beneficiary organizations using web-based surveys. The sample number was only 29 in 2013 [45]. According to its 2013 report [45], employee volunteers preferred more traditional, hands-on volunteerism, e.g., food preparation, sorting, serving and painting or handiwork than skill-based volunteerism, e.g., office support, management of general operations, accounting. Even though the saved or avoided cost (free services provided by volunteers for which the non-profits would otherwise have to pay) in the second case was significantly higher, skill-based volunteer activities seemed to achieve more capacity gains and greater cost saving for non-profits than traditional volunteer activities.
A similar organization is the Chief Executives for Corporate Purpose (CECP) [74], that measures the so-called Giving in Numbers index. Giving in Numbers is a kind of benchmarking for corporate social investments. This organization is in partnership with companies, so its results are based on responses of its surveyed partners. The population is any U.S. company with a revenue of more than USD 2 billion. The targeted topics are cash-donating and in-kind/product giving, employee volunteerism, and other impact measurements.
According to its latest report [26], volunteer time off (how much time the participating companies allowed their employees to volunteer on company time) was on average 20 h in 2018. In sum, companies reported an average of 61,000 h of volunteering in company time and 193,000 h outside company time. The median number of pro bono hours in 2016 was approximately 3500 h, while in 2018 it was 5600 h, yielding a growth rate of 61%. Pro bono services’ median value was 833,000 USD in 2018. The Financial and Consumer Staples industries stand out as leaders when it comes to employee volunteer participation rates (41% and 39%, respectively).
It is important to underline that these numbers originated from the USA, so they describe only a part of worldwide volunteerism.

5.2. Empirical Study

5.2.1. On the Individual Level

Answering the research question, we tested each factor (Schwartz’s value set was either included) separately. However, we used many reliable statistical methods, but only the significant differences are explained in this section. Our first hypothesis was the following.
Hypothesis 1 (H1).
Gender and age will not affect the intensity or attendance of volunteerism.
Here we used two types of test. In the first case, where the data were sourced from the World Value Survey, we used the Mann–Whitney U test. In the second case, where the data were sourced from large statistical measurements, we used parametric techniques (Z test) due to the normal distribution. For the first comparison, the appropriate procedure is the non-parametric test because the variables were measured on an ordinal scale. We kept it granted that its requirements are met.
Wave 6 did not contain any sufficient evidence to infer that gender or age variable is different in many cases at a 5% significance level. However, we found very slight gender difference regarding the type of organization in Wave 7. Males were more actively volunteering in sport and recreational organizations (4915 active and 4825 inactive) than females (3117 active members and 4010 inactive). Contrary, in a church and religious organization, more females were active (7576) or inactive (6209) members > compared with male members (active 6611, inactive 5682). Small differences occurred about the important child qualities what the children should be encouraged to learn at home. Women were more concerned with using thrifting to save money and things (Mann-Whitney U non-parametric test p = 0.532), and unselfishness (p = 0.519) values. Satisfaction with the financial situation of households showed some small gender differences (p = 0.380), females rated it on a higher level. Gender and age comparison were also tested on the secondary datasets detailed in Appendix A. We found minimal differences in UNV (United Nations Volunteers) Volunteerism database, where comparing men and women activities (in percentage, altered to the population) p-value was 0.04506, so depending on the significance level, it could mean gender difference.
Hypothesis 2 (H2).
Active, inactive, and non-volunteers have different value sets.
Discovering the volunteers’ characteristics, firstly, we calculated the active and inactive memberships and used this transformed variable as an indicator of volunteer activism rate (activity rate measured on an ordinal scale). Afterwards, we measured the relationship between volunteer activism and selected variables using association techniques (Phi and Cramer’s V) because the variables were qualitative. Results from Wave 6 suggested that some small differences were between the active and non-active group in the case of satisfaction. Either “satisfaction with answerer’s life” or “satisfaction with the financial situation of household” or “state of health” aspects were slightly higher-ranked by active volunteers (non-significant differences). Moreover, these variables (the above-mentioned and voluntary activism) had a significant (p < 0.0001), moderately strong relationship (Cramer V values were between 0.4 and 0.6). The active volunteers kept the necessary action to transmit these values to the next generation. Values such as “not being selfish or unselfishness” were those qualities that children should be encouraged to learn at home. Super active and very active volunteers, who were active members of more various organizations, were averagely four years younger than the less active answerers.
Results from Wave 7 confirmed these findings. Moreover, here (Wave 7) further specialization may be drawn. Active volunteers were more interested in politics and religion than non-volunteers. The relationship between voluntary activism and interest was albeit significant, too small. We compared the volunteers with the non-volunteers, the only strong significant difference origins from that what is important in life because volunteers rated friends higher than non-volunteers (Mann-Whitney U, p = 0.998).
Comparing the two results (i.e., Wave 6 from 2010–2014 and Wave 7 from 2017–2020), the direction of voluntary activity changed a little bit. Although the first four places were the same in both cases, the self-help and mutual aid groups, as well as professional organizations stepped up on the ranking list. Perhaps, the current extraordinary situation modified the order. We also dealt with how the pandemic may influence employee volunteerism.
Other interesting findings were the correlation between a feeling of happiness and subjective state of health (Spearman’s rho = 0.381, p = 0.000) and satisfaction with respondents’ life (Spearman’s rho = 0.459, p = 0.000), but none of these factors had any significant correlation with volunteerism activity. This does not mean that these factors would be independent of voluntary activities.

5.2.2. On the Regional Level

Hypothesis 3 (H3).
Ranking numbers from different metrics are significantly related to each other.
Comprehensive metrics and index comparisons were carried out in two main stages. Firstly, we selected the ranking scales (rank 1 = the highest score) and where the data allowed, we implicated some additional order. Here we adopted the ranking values (helping strangers, donating money and volunteering time) from the Giving Index, the Gallup ranking value and the Philanthropic rank. Regarding the UNV database, firstly, the nominal numbers were corrected with the population of each country. Then formal volunteering and volunteer numbers were ordered in descending order (ranking). The relationship between these variables was tested with the Spearman rho correlation. This technique can be applied only on ordinal or ranked variables as it was in our case. Results are detailed in Table 2. Table 2 demonstrates significant evidence to maintain the H3 hypothesis. For the sake of reliability testing, we applied the Cronbach’s alpha test. When we kept all variables, Cronbach’s alpha was 0.927, which is a very strong, significant result, but the Philanthropic Rank did not show significant similarity with the other values (p = 0.12), so we decided to sort it out. The Cronbach’s alpha was still acceptable with 0.913 value. This method maintained the measurement of internal consistency, i.e., the set of items are closely related and can be handled as a group.
This finding led us to the next hypotheses and made it possible to classify countries.
Hypothesis 4 (H4).
Countries can be grouped according to their volunteerism activity, measured on ranking ordinary scales from the various datasets.
Answering this question, we applied hierarchical cluster analysis and we used the centroid method on the cases (items were the selected countries). This classification helps to classify countries into groups that are relatively homogeneous based on a defined set of variables (here volunteerism). Centroid method measures the distance between two clusters, which is defined as the difference between the centroids (cluster averages). We preferred hierarchical techniques because there was no previous decision about the number of clusters (country groups). Here we relied on the abovementioned set of variables, according to countries’ volunteerism characteristics and intensity. Our aim was to understand countries’ volunteerism practices and the way in which they attempt employee volunteerism inside their national borders.
The dendrogram in Figure 1 shows the closest relationships between countries; it means the similar data placed the similar items closer. After we applied cluster analysis, countries were grouped into two stabile clusters, plus a third cluster was formed for the rest. The first cluster includes countries, where formal volunteerism has tradition and works in a precise, official way. The list of these countries is the following in alphabetic order: Australia, Austria, Canada, Cyprus, Denmark, Finland, France, Germany, Ireland, Luxemburg, Netherlands, New Zealand, Sweden, Switzerland, United Kingdom, United States of America.
Those countries belong to the second cluster, where volunteerism is more informal, or less conscious, and it rather works through the neighbourhood and social bonds. Here are Belgium, Bulgaria, Czech Republic, Estonia, Greece, Hungary, Italy, Korea, Japan, Latvia, Lithuania, Poland, Portugal, Romania, Slovakia, Slovenia, Spain.
The third cluster covers the countries where the statistical databases about volunteerism were incomplete or only poor values were available. The Index of Philanthropic Freedom, measured by Hudson Institute, serves as evidence in this case because these countries had got fewer average points compared to other clusters’ values. This cluster’s members are Brazil, Chile, China, Croatia, Iceland, India, Mexico, Norway, Russian Federation, Turkey.
Three main clusters were formed, two can be compared with efficient statistical methods, because in the third case (Cluster 3) consequences are based on incomplete data, which could be misleading.
Before the cluster comparison, Figure 2 demonstrates an interesting visual comparison of the countries regarding the direction of volunteerism. The data sourced from an OECD database selected the values from the same WVS Wave 6 study as we did. However, we did not analyze cultural and country comparison on this dataset because of the methodological limitation. Figure 2 provides a preliminary insight into country comparison.
Hypothesis 5 (H5).
Clusters can be compared and described with voluntary indicators.
The question is whether there are differences between the countries in terms of volunteerism. Regarding the large representative sample sizes, and since the data are sourced from secondary data sources, as detailed in Appendix A, it can be granted that the required statistical conditions are satisfied. This allows performing ANOVA F-tests. The main differences between the clusters are detailed in Appendix B, where the statistical calculations are also provided. Here, we only arranged the main characteristics of each cluster found on the statistical comparison (ANOVA). In this way, we can have a deeper insight into the international tendencies on volunteerism.
Informal volunteerism is better accepted and more preferred everywhere compare with formal volunteerism, as the literature was confirmed, as well. It can be assumed that the intensity of formal, organized voluntary actions is more popular in Cluster 1 countries, comparing with Cluster 2. Here, the non-profits sector operates well, and special charitable organizations manage voluntary activities. The most popular field was social and health services, which may be very beneficial under these extraordinary circumstances. Donating money instead of time is a more attractive way to give help. Seemingly, the volunteer’s role is a long-term engagement with shorter but more regular actions.
In the case of the second cluster, it seems there are fewer “professional” volunteers and charitable organizations because informal volunteerism is more typical. The ratio between formal and informal volunteerism is greater, even more, spontaneous and informal actions seem to be classic. As the average time spending on volunteerism shows, the professional and super active volunteers are more engaged and work longer. Besides this, episodic volunteerism is supposed to be common. The direction of voluntary activities differs; because fields of education and culture, social volunteerism happened more frequently here.
Volunteerism is presented by the third group, as well. Although data are poor, we can assume that volunteerism occurs here, too. Mostly financial help provision was typical, but less recognized time and effort appeared. Nevertheless, poor data could also have caused these small numbers.
Based on the main conclusion drawn from the data, we can suggest that the amount and intensity of formal and informal volunteerism differ in each country, as seen in Figure 3.
The difference can be explained with methodological weaknesses (e.g., lack of reliable measurement) or with cultural differences. Taking the second reason, we can conclude that the level and intensity of employee volunteerism is not satisfying anywhere, but the countries are on the right track, and they easily can learn from each other’s experiences with active cooperation.

6. Conclusions and Limitation

The aim of this paper was to discover employee volunteerism. Our article was organized as follows: in the first chapter, the main literature on volunteerism and employee volunteerism, as an essential part of CSR, was introduced. Empirical research based on the third-party model conceptualization and five hypotheses were tested and discussed. Hypotheses covered the following topics. H1 hypotheses sought to compare male and female volunteers’ activity and the young and older generations’ volunteering. H2 aimed to describe volunteers through a unique pattern. In H3 we assumed that various metrics have equivalent results. In the case of H4, selected countries were clustered depending on their volunteerism. The last, H5 hypotheses identified and characterized each cluster. For the sake of hypotheses testing, we applied various statistical methods, which were presented in the third chapter. Except for the H2 hypotheses about volunteers’ personal characteristics, all hypotheses were accepted. H2 was rejected.
As managerial implications, firstly, we agree with the latest UNV Report, global framing of volunteering must evolve, and volunteer measurement should be integrated [1]. Secondly, we accept Schwartz’s theory and assume that voluntary activity as a behavioral attendance of altruism stems from personal values. Including any contract, volunteers might be employees who assist with the management. That is why the companies may frame volunteerism and manage it as employee volunteerism. However, this is not a single action and process. There is a need to meet outside infrastructure and experienced experts in order to have a dedicated manager of volunteers. Employee volunteer programs may differ among countries and cultures, but companies may learn from each other on how employees can be engaged with employee volunteerism. Best practices and case studies [57,75,76,77] have elaborated how to manage this program. Here we referred to the most effective advice. There are many incentives for employees to be motivated to join the program. Depending on the reason for participation those could be directly asked participation, feeling of pressure by colleagues or supervisors, loyalty to the firm, paid vacation, incentives, donations, grants, reference, career options, etc. [30]. The term of “no out of cash” should be taken into account so employees’ cost must be covered, in a form as follow: time-related benefits, e.g., flexible working hours, paid leave or financial benefits, e.g., gifts, event tickets, purchase of necessary materials, or ‘PR company brand tools’, logistical supports [30], etc.
According to Mirvis [39], there are three different ways how a company can engage their employees with CSR: (1) transactional approach when offered programs directly meet employees’ interests, needs and values; (2) relational approach, which relies on a psychological commitment between the employer and employees to emphasize social responsibility; (3) developmental approach when not just corporate CSR but also employees’ personal responsibilities are improved. Tyagi and Mallya [52] took one more step; they suggested that employees’ participation could be out of love, and sometimes it does not stem from inner generosity, rather than a compulsion to conformity (as they said, a moral obligation), which reflects the abovementioned Social Responsibility Matrix. According to them, employees need to be encouraged for active participation and continuous managerial supervision, even if we think their results might be reasoned with cultural values, as well.
In many firms, CSR is born from the lower levels (bottom-line) of employees [43], but it does not mean that a core strategy or a responsible leadership would not be necessarily needed. New leadership strategy [28] would become a model where a leader will hear the voices and recognize the needs of the poor and vulnerable. That is why senior leaders are responsible to express CSR [7] and employee volunteerism as an ethically and socially responsible goal in the company’s strategic plan. Leadership is taken in social initiatives, and the leader acts as an ethical role model, where the whole management must be fully committed to this program [4]. This requires a proactive social responsibility strategy, when legal, ethical, economic and discretionary responsibilities are successful. Business actions should be made with ethical consideration standing side by side with great performance objectives, and with the personal, organizational or greater social ones. “Indeed, the point that profits and social responsibility can go hand in hand is being confirmed in a new creative way.” [4] p. 141. Besides these, the outcome and effectivity of each program must be measured [31,34] and broadly communicated [30]. Unfortunately, this measurement or conceptualization of any employee volunteerism program at the company level is still imperfect and unfledged.

Limitations

Our empirical studies can be divided into two main parts. (1) Personal traits and interest regarding volunteerism were explored by analyzing WVS 6 and WVS 7 databases. (2) Third-party model and employee volunteerism, due to the missing direct measurement, were observed through the main formal volunteerism indices. We relied on secondary data analysis. Apart from the classic problems sourced from this method, the advantages rang the bell. Even so, in this chapter, we listed the issues which caused some limitations in our study.
The first used dataset (WVS) originates from a longer questionnaire, which examined values and beliefs. Its items were measured on an ordinal (Likert) scale. Black noted [78] that measuring attitudes, opinions and values involves a trial to measure how intensely people feel about the questioned issues, but researchers must handle carefully unwarranted conclusions drawn from these opinions, and extreme generalizations, or stereotyping of the respondents. Because of the attitude aspects, it does not mean that people would behave as they feel. In conclusion, it is better to understand the tendencies behind these opinions. On the other hand, qualitative variables, like in WV Surveys, are measured within the limits of a nominal or ordinal scale. These data types are on the lower level of the permissible mathematical calculation, so no other than determining frequencies are permitted. Accordingly, only non-parametric techniques are acceptable to apply, as we did. Therefore, only, proportion and ranking can be calculated, which restricted us from using nonparametric techniques. More sophisticated tests may be meaningless because of the lack of strong measurement level.
The second part targeted macro-level comparison. This time, the methodological diversification was challenging. We can find various datasets which aim to measure and compare volunteerism (these are detailed in Appendix A, where we listed the used datasets). This diversity partly arises from the lack of a universally accepted definition of volunteerism, and is partly caused by methodological diversifications. For example, UNV listed [79] the countries that have not introduced policies, legislation or other measures on volunteering. In our research, those countries were selected where this legislation was introduced before 2008. These countries’ metrics have appeared almost in each relevant database. In addition, measuring of volunteering may reinforce a holistic understanding of the engagement of participants in volunteerism. Broader but more appropriate and punctual conceptualization of volunteerism may make comparison and benchmark easier through a clear definition and metrics. In addition, the units of measurement were misleading. Taking the UNV dataset, if we rank countries regarding the absolute values (number of volunteers), the ranking is entirely different than when we use real numbers adapted to the population. For the sake of illustration, we enclosed these two different orders into Appendix C.
Originally, further regression analysis had also been applied. The regression analysis aims to make a prognosis about the future relying on the past. This new situation rewrote the main aim of our study, so we skipped the regression analysis. In the last section, we tried to explore how the pandemic has impacted formal and employee volunteerism.

7. Discussion

The recent extraordinary COVID-19 pandemic is not just the largest healthcare challenge of this century but it disrupts jobs (mass unemployment or reduced working hours on the labor market), the economy (some sectors are highly affected, e.g., tourism) and the educational system. It results in a development battle like poverty or inequality. Those who are the most vulnerable in this social and economic uncertainty need more help, and volunteering can be more crucial. Furthermore, due to the realignment of roles and participants in the volunteering sector, it requires stronger relationships and sectoral strategies among the government, competitive sector and non-profits. Volunteering during a pandemic may affect different demographic groups and may encourage people who would not usually volunteer to help [80]. Some may have more time and energy available to volunteer. On the contrary, other people, for example, with young children (unable to go to school) or older people who are at increased risk of illness, may have been unable to be engaged in certain volunteer activities. Finally, it seems that the ‘giants’ of the third-party volunteerism model have a slower reaction time than individual volunteers have had in this situation.
Most community volunteerism research has focused on and was done during non-emergency situations [80]. The UNV report in 2011 [81] contained a special chapter about volunteerism and disasters, where spontaneous volunteer responses and emergent groups are dedicated as the first responder following natural disasters. However, this informal volunteering seems to be fast reactions and rapid spread due to online connections and new technologies but cause mixed results. For instance, abrupt, not trained volunteers may cause harm on themselves. The lack of reliable information facilitates the spread of infodemics, as the authors of new research [82] call misleading online information or rumors; that is very risky nowadays. Researchers from 87 different countries followed and examined COVID-19-related rumors, stigma and conspiracy theories circulating on online platforms during the first wave of COVID-19 and as they found these myths decrease community trust in governments and international health agencies. Moreover, some lead to numbers of deaths, for example, following misinformation when hundreds of people died by the COVID-19. Spontaneous volunteer responses can revise them as it is happening now. Many young people provided examples of how they were fighting misinformation by raising public awareness of where to find accurate sources of information [83].
Governments alone cannot address the challenges arising from strong shocks. Governments must focus on the healthcare sector and must manage economics. The competitive sector must protect its employees and stabilize its business activities. Besides, the non-profit sector is waking up very slowly from the first hit. Over the half-year, demand for charity services increased. In contrast, non-profit organizations must handle strong restrictions and new regulations and adopt new social rules. According to the latest CAF reports [84,85,86], charity organizations are negatively impacted by the coronavirus global pandemic. In March, the most challenging impacts were: decreased funding, travel restrictions, increased cost, and the break in the whole supply chain. Besides the massive loss of donors and financial problems, organizations wrestled with technology challenges; almost the whole operation process had to be switched to online, which requires a lot of patience and flexibility from donors and volunteers. However, the number of organizations receiving donations from corporations has decreased significantly (approximately with 44%), which is an obvious outcome of economic recession. The lack of the necessary infrastructure and client-facing programs led to cancelling main events, hindering regular updates. Not mentioned the prompt implementation of new health and safety procedures. Nonetheless, here would be the perfect matching point where firms could lend a helping service in the form of pro bono or skilled volunteerism. Long-term donors would keep their reputations, and charity organizations would find new ways to engage with donors. Some nonprofits reported some innovative new solutions, like neighbors helping neighbors program, or job loss assistance, or COVID-19 testing programs.
The donation behavior has also changed, web and debit card giving has increased. The targets of donation are mainly hospitals and hospices. Unfortunately, some group donors like young or older people who are hit by COVID-19 harder, have stepped back and reduced their donations. Partly, this is because people’s income has become uncertain, and their long-term living stability has been affected by the recession. Those who were more likely to volunteer their time must face lockdown and restricted movement; social distancing has also disrupted these facilities. Parallel with these, charity organizations were not able to operate properly in their current form. Organizations expected only 12 months long operation time in the current form without any help. Almost a third of the organizations expected being forced to close in 12 months. The rest must start working remotely, to find a new alternative way of delivering their service with reduced service offers and find ways to reach beneficiaries and recruit volunteers. This dark outlook to the future lessened from March to June. Some organizations stood up, reopened or successfully have been adapted to the new normal.
After the spontaneous community-level volunteer actions, it can be expected [81] that organized volunteerism slowly returns back with associations, organizations and non-profits at the local and national level. Nevertheless, Mak and Fancourt [80] stated that the recently proved state of the art and well-known predictors had not been as clear cut as before the pandemic. Their findings regarding employment status and volunteering are inconsistently compering with previous literature. As they found, employment or other working responsibilities (e.g., university study) are strong predictors for social voluntary action. It is partly understandable and can be explained with sudden stops or slowdowns in working activities. Shorter working hours > being employed but not working and inactivity lead to loss of aim and essence of valued work. Fracture motivation and faith in meaningful effort appeared. Motivations for community volunteering may solve these problems [80]. It has a sense of purpose, enhances social capital (skills development), leads to mental and physical health improvement and meets needs and wants to feel empowered. Employee volunteerism may facilitate social recognition and approval, too. Not mentioned is that all of them are important factors to encourage volunteerism. ILO, as part of its COVID-19 monitoring [87,88], called experts’ attention to the so-called lockdown generation. ILO defined those young people (15–24 years old) as lockdown generation, who are facing multiple shocks from the pandemic and who are likely to suffer severe and long-lasting impacts of COVID-19. Moreover, their dark career prospects could be a long-lasting problem, which might lead to a long-term effect on the national level and scarring effect on (re)entering the labor market, because they lose their attachment to the labor market and lose their rights at work. Not mentioned is how lockdown restrictions impact their mental well-being. Apart from these issues, young people are ready to work and keen to satisfy their needs for feeling useful and helpful. They are ready to support vulnerable and hard-hit groups. Hereby, they could generate balanced labor market outcomes and secure international solidarity [89].
In sum, the pandemic may rewrite all volunteerism [90]. Before the pandemic, there were some typical barriers to volunteering which due to the lockdown and remote life disappeared, for example, time pressure from other activities. The way of communication and type of channels totally shifted from the personal level to the online and social media, so virtual volunteering may play an important part.
During the first quarter of the year [88], an estimated 5.4% of working hours were lost which is equal to 155 million full-time jobs, while in the second quarter this numbers was 14.0%, equivalent to 400 million full-time jobs (measured in 48 h/week). These values are higher on a regional level in the more affected countries; for example, in the USA, this was 18.3%. Regarding the volunteer sector, this country was the world’s most generous country over the last ten years (CAF). Unfortunately, this extraordinary situation might restructure the weights and roles, therefore may rearrange the ranking. New Zealand and Australia also had leading places. Both countries are noted as the most successful examples managing COVID crises (except Victoria state in Australia), but both countries pay a massive amount of COVID-19 costs (strict restrictions and closures, high cost of testing protection and supports). None of their governments can afford to concentrate on the volunteer sector. However, both have a long heritage, experiences and acceptable practices on how to manage natural diseases (e.g., seasonal bushfires in Australia or earthquakes in New Zealand). These countries have regularly faced disasters, and volunteerism has also been present in preparing and coping with them. These countries are supposed to be the first where citizens react immediately and proactively to COVID-19 disaster. If we rely on the previously cited report [81], the next step might be (and it is) spontaneous answers. Self-help organizations, local network and communities mobilize their resources to lend helping hands and wake up society. Still, these actions are taking place; the giant actors of volunteerism can recover and turn back to manage, contribute in other effective ways. As a final step, the attention of national authorities and donors can turn to rebuild essential physical infrastructures and services. Communities with more civic engagement and experiences have a better chance of recovering after the disaster, but the road is still long there.
Even the researchers have neglected this topic. When as branches of research have been published since the COVID-19 outbreak, until the final touch of publishing this article, just a few research and paper have dealt with employee volunteering during the COVID-19 pandemic. Zhang, Weng and Jia [91] just partly mentioned COVID-19 as a public health emergency which challenges regarding the implementation of new or ongoing volunteering strategies in practice. The authors presented Wuhan taxi drivers who helped to carry healthcare workers during the epidemic prevention of the COVID-19 period. However, they also emphasized the risk and side effects, such as volunteers’ compulsory self-isolation from their family.
Mak and Fancourt [80] analyzed data from 31,890 adults in the UK regarding the COVID-19 pandemic. They identified three types of volunteer activities: (1) formal volunteering, (2) social action volunteering and (3) neighborhood volunteering. The patterns behind them revealed demographic, socio-economic, personality and psychological factors. Voluntary work included shopping, packing, delivering food, medicines, driving healthcare staff around, helping food banks, homeless services, fundraising and making donations, providing emotional support through online or telephone helplines, taking part in research, providing free accommodations to people affected COVID-19, etc. Regarding their findings, employee volunteering may be equal to formal volunteering and/or social volunteering. The authors identified pro bono support as social volunteering. This type of volunteering often involved the internet and was not locally restricted. Formal volunteering was defined as volunteering with existing organizations within a formal structure. Here the targeted donors were not separated whether personal, individual or firms concern motivated them. Obviously, the formal volunteers were closer to the frontline and had direct connections with the hard-hit sphere. According to them, people who were currently employed were more likely to engage in social action volunteering.
Aguinis et al. [40] provided a theoretical work about CSR and employee volunteerism regarding the COVID-19 pandemic. Unfortunately, some companies began facing reduced commitment from workers as they questioned unsafe working conditions, for example, lack of adequate protective equipment or working with positively tested colleagues. The authors suggested various research topics and directions for the future. For example, the pandemic facilitates potential hybrid collaborations in different industries (e.g., health and fashion industry in order to create face masks), collaborations between governments and non-profits or in partnerships between private, public and competitive sector (e.g., researchers and practitioners) among others. All of these may be a successful response to the COVID-19 crises. These new collaborations may result in both private and public engagement and create new HRM routines, practices and measurement metrics (regarding recruitment) [91]. Companies have vast human resources, but innovatively, these opportunities might provide support to charitability [92] in a novel way. CSR is managed and created by firms, and individual entities, who are ready to help. The companies may implement them and might be more deeply involved in employee volunteerism.
We absolutely agree with these findings. Volunteer activities serve as the best field to practice, develop skills, increase motivation. Why could it not happen under the CRM’s umbrella? Why could not volunteer activity be the best reference and entrance ticket to the competitive sector when the market is ready to open and restart? In addition, volunteering provides a shielding effect on the volunteers from being isolated in hard times [55]. To achieve this, even a non-profit organization should be ready to accept a new way of time giving.
The UNV [18] projected a new model of volunteerism, where philanthropy or service to others should be extended with greater recognition of the diversity of organizations (companies or even universities). Action in which volunteering takes place, may invite new participants, where volunteers could also be leaders, decision-makers, planners and innovators. Finally, the serious leisure of volunteering should be added to the volunteerism’s definition, as well. Here we suggest that the so-called COVID volunteerism should also be counted to this. In sum, more participants, wider agencies, and novel, innovative forms and types of volunteerism might be widely accepted in the future. The new 2020 model comprises five dimensions of volunteer actions: mutual aid, service, campaigning participation and leisure. They overlap each diverse category, and ways of expressions are open for any volunteers. Here we must turn back to the COVID-19 pandemic because safe and secure work is significantly important. The ILO published and advised many guidelines and recommendations regarding safety and health at workplaces during the pandemic. In a nutshell, here we cited one from the ten key points [93], namely ‘Provide personal protective equipment (PPE)’, and inform workers of its correct use. This should be an essential part of workers’ fundamental right to safe and healthy work.
Abel and Willa [63] emphasized that the perception of how others act in a crisis can influence other citizens’ behavior. Besides, this COVID-19 pandemic may affect how people support and help social protection, as a result of this voluntary activity and as Weber [94] p. 3 suggested “The COVID-19 crisis serves as a cautionary tale about our societal and scientific ability to predict the future”, even the future of employee volunteerism.

Author Contributions

Conceptualization, methodology, software, validation and formal analysis; investigation, resources, data curation, writing—original draft preparation, A.K.D., writing—review and editing, A.K.D. visualization, A.K.D., supervision, A.K.D. project administration, A.K.D. & V.N.; funding acquisition, V.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

The authors are grateful to Włodzimierz Sroka for his valuable advice and kind support. The authors would like to express thanks to Tamás Mizik, whose review helped to make better the final version. The authors appreciate the reviewers’ suggestions and tried to implement them where it was possible.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A. Statistical Data Sources

Database NameIndicesDefinitionSample Size and CharacteristicsYearInstituteSource
COVID 19 data
CAF ReportsVariousThe Voice of Charities Facing COVID-19 WorldwideThe philanthropic sector from 99 countries Vol1 122 countries n = 544 Vol2 n = 880 Vol3 125 countries n = 4142020. Vol 1. 03 Vol 2. 04 Vol3 05.CAFhttps://www.cafonline.org/about-us/research/coronavirus-and-charitable-giving
Interactive COVID-19 Data by LocationReported data for cases, deaths and testing with data explorer (different time series). Government responses (various indices) we were working with Workplace closures: Stay-at-home restrictions, Internal movement restriction, International travel restriction, Testing policy, Contact tracing, Government Stringency Index. Using the same data from the European Centre for Disease Prevention and Control and governmental responses have also been tracked by Oxford University, by the Blavatnik School of Government.Worldwide or Selected regions2020. updated dailyInternational SOShttps://pandemic.internationalsos.com/2019-ncov/covid-19-data-visualisation
Savana Coronavirus data trackingThe tracker covers 5 key areas: concern & impact, home & work,out-of-home & retail, news sources and approval ratings. Here we focused on work.Tracking the variety of new working situations that UK adults find themselves in, including those who have been furloughed.Daily tracker, with 1000+ UK respondents every dayDaily reportSavantahttps://savanta.com/coronavirus-data-tracker/
Personal level
World Values Survey Wave 6. Selected questions from the survey (4 scales Likert and multiply choices)Memberships (Inactive/Active) of various voluntary organizations Personal values and opinions about voluntary organizations World wide (over 60 countries) n = 89,5652010–2014World Values Surveyhttps://www.worldvaluessurvey.org/WVSDocumentationWV6.jsp
World Values Survey Wave 7., EVS WVS Cross-National Wave 7 joint core Selected questions from the survey (focusing on values) World wide (48 countries/territories)2017–2020World Values Survey and European Values Studyhttp://www.worldvaluessurvey.org/WVSDocumentationWV7.jsp
Macroeconomical level
OECD1. OECD calculations based on data from the European Values Survey (2011), European Values Study 2008, Integrated Dataset (EVS 2008), and the World Values Survey Association (2009), World Values Survey, Wave 5 2005–2008, Official Aggregate v.20140429, Distribution of volunteers by field of activity Percentage of volunteers, 2008 or latest available yearSelected from Better Life Initiative: Measuring Well-Being and ProgressWorldwide selected from various databases2016–2018OECDhttps://www.oecd.org/statistics/better-life-initiative.htm
OECD2. OECD calculations based on data from OECD (2012), OECD Survey of Adult Skills (PIAAC database)Frequency of formal volunteering in months, 2012 2012
Source: OECD calculations based on the Harmonized European Time Use Survey web application, Eurostat Time Use database, survey micro-data; and tabulations from national statistical offices.Time spent in formal, 2013 or latest available year Average minutes of volunteering per day, by all respondents and by volunteers only, among people aged 15–642013 and latest
European Social Survey 2012.Proportion of people involved in work for voluntary or charitable organizations in the past yearEuropean Social Survey (ESS) 2012, which asks respondents whether, over the last 12 months, they have been involved in work for voluntary or charitable organizations28 country, in each with at least n = 20002012ESShttps://www.europeansocialsurvey.org/data/download.html?r=6
Gallup World Poll Citizen Engagement IndexProportion of people who volunteered time to an organization in the past month, “Have you done any of the following in the past month? How about volunteered your time to an organization?” In other words, data from Gallup World Poll reflect the proportion of people engaging in any kind of voluntary work roughly around the time of the survey. around 160 countries each with n = 10002015 or last year available1 Galluphttps://www.gallup.com/analytics/232838/world-poll.aspx
World Happiness ReportVolunteering is defined as helping another person with no expectation of monetary compensation. Percentage of respondents within the country who reported Donating Money/Time to a Charity in the Past Month.Database presents the percentage of respondents reporting that they donated money to charity or volunteered time to an organization within the past month within each country surveyed by the Gallup World Poll, Based on Gallup World Poll averaged across 2009–2017. https://worldhappiness.report/ed/2019/happiness-and-prosocial-behavior-an-evaluation-of-the-evidence/
CAF World Giving Index Helping PercentageThe survey asks questions on many different aspects of life today including giving behaviour: Helping a stranger, Donating money, Volunteering time the report is primarily based upon data from Gallup’s World View World Poll2018Charities Aid Foundationhttp://knoema.com/WDGIVIND2018/world-giving-index
ILO Unpaid Work - Volunteer work.Number of volunteers by type of volunteer work (thousands) Volunteer rate by type of volunteer work (%) -- Annual 1. Direct volunteer work, which is done to help other people directly (e.g., a neighbour, a friend, a stranger, nature); 2. Organization-based volunteer work, which is done through or for an organization, community or group.According to the latest international standards (see 19th ICLS, Resolution I), “volunteers” includes any person of working age who engages in unpaid, non-compulsory work for others, for at least one hour in a four week or one month reference period. Unpaid means that volunteers do not receive a remuneration in cash or in kind for the work done or hours worked. Nevertheless, volunteers may receive some small form of support or stipend in cash or in kind usually meant to enable their participation. ILOSTAT database is collected from official national reports or produced using published micro-data by national statistical offices.2016 or latestILOhttps://ilostat.ilo.org/topics/volunteer-work/
The Index of Philanthropic Freedomranking based on expert opinion survey 63 experts representing 64 different countriesTo compute the overall score, and by extension the overall
rankings, CGP staff had to first compute the scores of the
three indicators based on an expert survey.
64 countries in the study were selected to represent all regions of the world as equally as possible2015Hudson Institutehttps://www.hudson.org/research/11259-the-interactive-map-of-philanthropic-freedom
UNV Volunteering by countryFormal and informal volunteering (full-time equivalent)FORMAL VOLUNTEERING
Voluntary activity is undertaken through an organization, typified by volunteers
making an ongoing or sustained commitment to an organization and
contributing their time on a regular basis (UNV 2015a, p. xxv).
INFORMAL VOLUNTEERING
Voluntary activities have done directly, unmediated by any formal organization that
coordinates larger-scale volunteer efforts (UNV 2015a, p. xxv).
62 countries2018UN Volunteershttps://www.unv.org/sites/default/files/UNV_SWVR_2018_English_WEB.pdf

Appendix B. Empirical Findings

OrganizationIndexCluster 1.Cluster 2.Cluster 3.TotalEtaANOVA (df = 2)
MeanNStd. DeviationMedianMeanNStd. DeviationMedianMeanNStd. DeviationMedianMeanNStd. DeviationMedianEtaSum of SquaresFSig.
OECDFields of volunteering (Distribution of volunteers by field of activity %)Social and health services28.54126.8529.4426.39138.3926.4730.60711.9926.9428.12328.6326.890.1984.020.550.58
Education and culture27.72125.0927.8430.23135.2728.3029.60710.0233.2129.15326.3828.580.1841.180.490.62
Social movements10.56123.839.6513.02133.5212.609.7172.648.9311.38323.6610.710.3962.642.580.09
Sports22.01126.5723.7218.63134.4816.9621.9379.4320.9820.62326.5619.830.2686.981.010.38
Others11.17125.1210.0211.73135.4211.538.1677.525.1810.74325.809.810.2461.650.910.41
OECDParticipation rates in formal volunteering (Percentage)39.50128.0539.0724.6596.2323.3738.36319.1238.6233.792411.3434.480.641204.897.210.00
OECD3Frequency of formal volunteering (Percentage of formal volunteers, by frequency)Less than once a month44.14125.9446.2353.86910.5355.2054.4137.8351.0149.07249.2847.400.54583.324.380.03
Less than once a week but at least once a month24.79122.4524.9523.2393.0622.8921.5333.6321.5423.80242.9323.340.3930.221.900.17
At least once a week but not every day26.04124.5325.9017.8697.2613.9819.1236.3520.6822.11246.9324.260.58374.915.400.01
Every day5.02121.164.755.0593.135.264.9331.725.055.02242.084.970.020.030.001.00
EUSSAverage minutes of volunteering per dayVolunteers131.851321.16130.00145.601031.54151.0075.50254.4575.50132.842532.60131.000.578216.775.230.01
All respondents5.85133.444.001.90101.451.001.5020.711.503.92253.303.000.62100.756.880.00
Proportion of people involved in work for organizations15–29 years old46.87109.7750.5532.00129.9232.0549.901 49.9039.242312.1841.800.641324.826.830.01
30–49 years old47.96108.5647.4032.401211.4628.3055.201 55.2040.162312.9042.700.651557.217.400.00
GALLUP Proportion of people who volunteered time to an organization in the past monthTotal (All ages)32.06168.5731.0014.88178.3613.0016.0058.6616.0022.263811.8322.000.722658.6718.460.00
Men 30.94168.4729.0015.29179.5513.0016.0058.8014.0021.973811.7022.000.662222.5113.670.00
Women33.19168.9234.0014.47177.6113.0016.2058.9815.0022.583812.2623.000.753121.7922.360.00
15–29 year olds27.311610.8227.0016.241710.5714.0012.20510.7812.0020.373812.0919.500.511395.556.090.01
Happiness The percentage of respondents within each country within the last month Donating Money to a Charity0.57160.120.590.26140.080.260.3190.210.210.40390.200.380.740.8121.680.00
Volunteering Time to an Organization 0.31160.080.300.16140.080.140.1790.090.180.22390.110.240.670.2014.800.00
Giving IndexHelping a strangerPercentage (%) 54.94169.3853.0038.35176.7937.0036.5046.5634.5045.323711.5544.000.742616.2920.350.00
Donating moneyPercentage (%) 56.441612.0757.0024.59178.9923.0017.2546.7017.0037.573719.6034.000.8610,212.2848.050.00
Volunteering timePercentage Score(%)30.63167.6529.5014.71177.1014.0013.7546.0815.5021.493710.7420.000.752357.2122.310.00
ILONumber of volunteers by type of volunteer work (thousands)Organization-based5282.81146275.732442.701352.91151744.00530.20692.134881.01341.402940.04334649.431072.500.44134,837,181.053.630.04
Direct6192.66137016.192271.202488.25154110.53950.201268.7041294.37900.903840.72325559.381413.900.36125,810,086.292.190.13
Total14,879.90526,798.723059.304588.3842762.184596.103312.7733444.291527.308557.611217,227.622863.750.33345,401,204.940.530.60
Volunteer rate by type of volunteer work (%)Organization-based27.091410.4028.4511.50157.1710.7022.70421.7021.2519.473312.9316.400.581808.067.660.00
Direct35.741325.2630.3021.011516.0316.6039.38435.8041.0029.293223.4722.050.341976.611.900.17
Total36.95217.0436.9516.101 16.102.7522.192.7519.10519.2116.100.891180.894.000.20
HudsonOverall Score4.46120.224.474.1470.294.213.3070.463.184.06260.574.230.856.0030.640.00
CSO Score4.76120.224.754.4170.294.503.4770.943.534.32260.744.580.737.4313.370.00
Tax Score4.32120.484.303.8670.504.003.2470.573.103.90260.674.000.685.2310.170.00
Cross Border Score4.31120.424.234.1570.374.303.2170.553.503.97260.644.000.745.7114.180.00
UNVPopulation aged 15 or older (million)32.971661.967.2520.881728.128.94268.878441.8851.1773.9941213.069.250.46378,700.495.010.01
Formal volunteering (person)806,623.50161,522,462.99251,905.00172,321.8217273,249.0249,417.00966,845.0081,397,819.71349,956.00574,883.10411,167,086.32138,769.000.304,843,275,738,619.141.850.17
Informal volunteering (person)992,019.31161,930,224.26187,862.50393,925.1916427,965.53200,208.002,302,035.0082,649,893.091,399,274.501,014,784.80401,806,109.29213,028.500.3919,431,863,432,876.503.340.05
Total volunteering (person)1,798,642.69163,448,132.43439,767.00568,892.1316633,259.90266,192.503,268,879.8883,962,469.951,690,487.501,600,789.90402,927,286.48423,316.000.3539,923,533,214,707.502.510.10
Formal volunteering in population ratio (%)2.6916.000.832.460.7217.000.540.680.79100.980.541.4743.001.211.150.7838.0032.010.00
Informal volunteering in population ratio (5)2.7316.000.412.772.5517.001.392.951.93101.542.522.4743.001.192.760.274.191.530.23
Total volunteering in population ratio (%)5.4216.000.945.593.1917.001.403.412.71102.133.343.9143.001.863.990.6459.7014.030.00

Appendix C. The Ranking Anomaly

UNV Volunteerism Country Ranking Based on Raw Numbers (1 = Highest Number)UNV Volunteerism Country Ranking Based on Modified Real Numbers, Where Numbers Were Divided by Population before Ranking (1 = Highest Number)UNV Formal Volunteerism Country Ranking Based on Raw Numbers (1 = Highest Number)UNV Formal Volunteerism Country Ranking Based on Modified Real Numbers, Where Numbers Were Divided by Population before Ranking (1 = Highest Number)
United States of America1919
China238233
India340336
Mexico413928
Germany516415
France611714
United Kingdom714512
Canada8162
Japan937824
Brazil10241121
Turkey11343041
Italy12321023
Poland13171829
Spain14271631
Australia15151311
Netherlands166125
Romania17292935
Chile18252022
Sweden194143
Austria205177
Greece21191913
Czech Republic22283234
Korea23391532
Denmark2472410
Switzerland25232618
Norway268216
New Zealand272224
Hungary28353738
Portugal29362520
Bulgaria30313939
Finland31202716
Slovakia32304037
Croatia33213126
Ireland34262817
Lithuania35124140
Latvia36183525
Slovenia37333630
Estonia38223827
Cyprus3910338
Luxemburg403341
Belgium 2319

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Figure 1. Dendrogram, based on hierarchical cluster classification among selected countries’ value.
Figure 1. Dendrogram, based on hierarchical cluster classification among selected countries’ value.
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Figure 2. Visual comparison of the type of volunteerism among selected countries. Source: OECD.
Figure 2. Visual comparison of the type of volunteerism among selected countries. Source: OECD.
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Figure 3. Comparison of formal and informal volunteerism among selected countries.
Figure 3. Comparison of formal and informal volunteerism among selected countries.
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Table 1. Advantages and disadvantages of employee volunteerism with references.
Table 1. Advantages and disadvantages of employee volunteerism with references.
AdvantagesDisadvantages
Employee level
  • Stronger attitudes towards work, organizational commitment and job satisfaction trigger the form of reciprocity among employees [26,41].
  • New and positive perception of career [34].
  • It strengths team relationships and provides new opportunities to meet other members [26,41].
  • Provides more sense of belonging to a team [42].
  • A greater level of happiness and self-perception [28].
  • Volunteer’s job-relevant skills will be improved, including facilitated communication and other skills [26,41].
  • It facilitates time management and plan fullness thinking skill gains [43].
  • Lack of conscious and meaningful CSR strategy and helping role might trigger social apathy, social insensitivity (lack of responsible thinking and activity) and selfishness [23]. This might be a social risk, as well.
  • Nonlinear associations between frequency of volunteer activity and well-being were found on psychological well-being, so upper or lower levels (not optimal frequency) of engagement in a volunteer activity were not beneficial for well-being [42].
  • Volunteers might have a negative social aspect, a stereotype of the typical people with higher income, higher education who can afford to provide support for those in need [21].
  • The new environment might have a negative effect, such as mobbing or bullying, which is more prevalent in the public sector [41].
Company-level
  • It builds trust with the stakeholders to keep contact and share information, creates a positive reputation and image [23].
  • Commercial and social benefits, a positive halo effect [7]. Better engagement with the public, reputation. It improves reputation, brand perception for new customers and increases brand loyalty.
  • It clarifies the whole strategy and vision, ensures an effective strategy to recruit and retain talents who may have a positive influence on the bottom line [43].
  • It strengths social capital [44] through new opportunities for networking and relationship development (new sales options), even recruiting new employees [45].
  • Possibility to win market share from the competitors [43]. It secures broad media attention [35].
  • Teams may have a rising number of anecdotal and case examples of business impact coming from employees who are involved in service and social-good programs [26].
  • Better employee attendance, which reduces absenteeism [46].
  • It increases employee engagement and long term loyalty [35].
  • It helps to identify rising leaders and attract and recruit better potential candidates.
  • It causes a so-called preselection and schemes whereby an organization only selects those applicants who demonstrate shared organizational values on personal traits and fit into its voluntary and involuntary turnover [29].
  • Costly [47]; every CSR involvement requires ongoing investments in order to achieve value-creating activities.
Source: Authors’ collection.
Table 2. Results of independence calculation with Spearman’s rho among selected metrics.
Table 2. Results of independence calculation with Spearman’s rho among selected metrics.
Correlations
Gallup RankingGiving Helping StrangerGiving Donating MoneyGiving Volunteering TimePhilanthropic RankUNV Population RankUNV Formal Population
Spearman’s rhoGallup RankingCorrelation Coefficient1.0000.694 **0.807 **0.980 **0.617 **0.348 *0.699 **
Sig. (2-tailed) 0.0000.0000.0000.0020.0320.000
N38333333223837
Giving Helping
Stranger
Correlation Coefficient0.694 **1.0000.809 **0.686 **0.515 *0.577 **0.660 **
Sig. (2-tailed)0.000 0.0000.0000.0120.0000.000
N33373737233736
Giving Donating MoneyCorrelation Coefficient0.807 **0.809 **1.0000.824 **0.617 **0.585 **0.732 **
Sig. (2-tailed)0.0000.000 0.0000.0020.0000.000
N33373737233736
Giving Volunteering TimeCorrelation Coefficient0.980 **0.686 **0.824 **1.0000.545 **0.425 **0.647 **
Sig. (2-tailed)0.0000.0000.000 0.0070.0090.000
N33373737233736
Philanthropic
Rank
Correlation Coefficient0.617 **0.515 *0.617 **0.545 **1.0000.702 **0.717 **
Sig. (2-tailed)0.0020.0120.0020.007 0.0000.000
N22232323262625
UNV Population RankCorrelation Coefficient0.348 *0.577 **0.585 **0.425 **0.702 **1.0000.753 **
Sig. (2-tailed)0.0320.0000.0000.0090.000 0.000
N38373737264341
UNV Formal PopulationCorrelation Coefficient0.699 **0.660 **0.732 **0.647 **0.717 **0.753 **1.000
Sig. (2-tailed)0.0000.0000.0000.0000.0000.000
N37363636254141
**. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed).
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