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Article

Can Corporate Fairness towards Public Authorities Enhance Customer Loyalty? A Multi-Sectorial Investigation in a Developing Country

by
Ovidiu I. Moisescu
1,*,
Oana A. Gică
2,
Victor O. Müller
1 and
Camelia Ancuța Müller
1
1
Faculty of Economics and Business Administration, Babeș-Bolyai University, 400591 Cluj-Napoca, Romania
2
Faculty of Business, Babeș-Bolyai University, 400174 Cluj-Napoca, Romania
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(1), 187; https://doi.org/10.3390/su12010187
Submission received: 29 November 2019 / Revised: 15 December 2019 / Accepted: 24 December 2019 / Published: 25 December 2019
(This article belongs to the Special Issue Corporate Social Responsibility (CSR) in Developing Countries: Current Trends and Development)
Browse Figure
Versions Notes

Abstract

:
This paper investigates how customer loyalty can be enhanced by improving customers’ perceptions of corporate fairness towards public authorities, taking into account the mediating role of customer-company identification, in a multi-sectorial context, in a developing country in Central and Eastern Europe. The investigation is conducted comparatively within four main industries (telecom services, retail banking services, dairy products and personal care products) and depicts the particular impact these perceptions have on customer loyalty in each domain, with practical implications concerning corporate social responsibility (CSR) communications. A consumer survey was designed and implemented among a sample of 1464 customers from Romania. The collected data was analyzed by means of partial least squares structural equation modeling (PLS-SEM). We found that customers’ perception of corporate fairness towards public authorities has a significant and positive impact on customer loyalty in all investigated industries, both directly and indirectly via customer-company identification, with a higher impact for services, especially for retail banking services.

1. Introduction

According to the stakeholder-based framework, corporate social responsibility (CSR) encompasses responsibilities towards various stakeholders, among which public authorities play an important role [1,2]. Consequently, businesses should regard taxation, law compliance and any other aspect of their relationship with national, regional or local governments as part of CSR [3]. However, many companies are nowadays often criticized for not fully complying to the rules imposed by public authorities, trying to elude the law, cheating on taxes, or offering actual or disguised bribes to public officials [4,5]. For example, even though tax revenues are at the core of democratic societies, many companies, especially large ones, have figured out legally-framed ways to avoid taxes—at least partially—wherever they operate [3].
Previous studies have suggested that CSR, if it’s appropriately disseminated among customers, can have positive effects on the creation and maintenance of long-term relationships with customers [6,7]. Many customers expect companies to be good corporate citizens and to show fairness to their stakeholders. Repurchase decisions are often influenced by how customers perceive their suppliers from this point of view [6,8,9]. Thus, it can be stated that a good CSR image among customers can enhance customer loyalty. In addition, researchers have emphasized that customer loyalty has a positive impact on business performance [10,11].
With regard to the relationship between perceived CSR and customer loyalty, previous research conducted in various industries has suggested that the link between the two is significant, positive, and very often mediated by customer relationship attributes such as customer-company identification [12,13].
Considering the fact that companies’ social responsibilities regard all stakeholders and that public authorities represent an important stakeholder [1,2], it is essential to establish whether corporate fairness towards public authorities can enhance customer loyalty, and, if so, to emphasize the relevance of disseminating this facet of CSR among customers.
However, previous studies on the relationship between customer-based perceptual CSR and customer loyalty have generally ignored corporate responsibilities towards public authorities, being mostly focused on environmental or societal responsibilities. Moreover, the extant knowledge on the general relationship between CSR and customer loyalty is still rather scarce concerning the context of developing countries [14], particularly in the cases of Central and Eastern Europe [15].
Acknowledging the positive impact of CSR on their customers’ loyalty and, consequently, on their long-term profitability, many companies have reconsidered their CSR communication, placing it at the core of their overall marketing communications. Thus, in recent years, companies have been allocating significant resources to regularly disseminate how their activities are in accordance with CSR principles [16,17]. However, corporate responsibilities and fairness towards public authorities (i.e., fully complying with the law and regulations, always paying taxes fairly and honestly, striving to prevent and avoid bribery etc.) are rarely emphasized within CSR reports or other specific forms of CSR communication.
The goal of this paper is to investigate how customer loyalty can be enhanced by improving customers’ perceptions of corporate fairness towards public authorities, taking into account the mediating role of customer-company identification, in a multi-sectorial context, in Romania, one of the largest developing countries in Central and Eastern Europe.
The current research brings useful insights regarding a previously neglected facet of CSR—companies’ responsibilities towards public authorities—and its impact on customer loyalty, filling in an important literature gap. By investigating the mechanism behind this impact, more specifically the mediating role of customer-company identification, our findings push forward the current understanding of the relationship between CSR and customer loyalty, from the particular perspective of public authorities as important stakeholders of any business.
Moreover, the current paper contributes to reducing the scarcity of research in what concerns the relationship between CSR and customer loyalty, in general, within the context of developing countries, as most of the literature on the subject regards developed countries.
Our results convey practical implications for companies, showing how fostering customer loyalty can be done by means of appropriate CSR communication. More specifically, we suggest that CSR communications should not omit relevant aspects concerning corporate responsibilities and fairness towards public authorities (i.e., fully complying with the law and regulations, always paying taxes fairly and honestly, striving to prevent and avoid bribery etc.), as they may significantly influence customer-company identification and customer loyalty.
In the following sections we will firstly present the theoretical foundations and issue our research hypotheses. More specifically, we will define the concepts of corporate social responsibility and corporate fairness towards public authorities, customer loyalty and customer-company identification, and we will briefly describe corporate tax non-compliance and corruption as reflections of corporate social irresponsibility. Furthermore, we will present the methodology employed for accomplishing our research objectives, followed by the presentations of our research results, accompanied by the discussion of these results. Finally, we will draw the research conclusions and present its limitations, as well as future research directions.

2. Theoretical Foundations and Hypotheses Development

2.1. Corporate Social Responsibility and Corporate Fairness towards Public Authorities

Even though CSR is currently an important and trendy topic in the literature, its definition is not universal [2]. Moreover, there is much confusion when it comes to systematizing the concept and identifying its main components [18].
One of the main approaches regarding CSR systematization is provided by Carroll [19] who states that CSR encompasses the economic, legal, ethical and discretionary expectations that a society has of organizations at a given point in time. According to this view, organizations have economic, legal, ethical, and philanthropic responsibilities. Among these, legal and ethical responsibilities can be emphasized as comprising those aspects which reflect companies’ responsibilities towards public authorities.
Another important development in what concerns CSR systematization is emphasized by Freeman et al. [2] who conceptualize CSR within the framework of stakeholder theory. Thus, CSR encompasses specific responsibilities towards each stakeholder—among which public authorities play an important role—alongside stakeholders, employees, customers, business partners (including suppliers), the environment, and the society must be considered. From a stakeholder perspective, one of the most appropriate definitions of CSR was outlined by the European Commission, which sees it as the voluntarily integration of social and environmental concerns in business operations as well as in interactions with stakeholders [13].
If we scrutinize the most relevant methodologies regarding the measurement of customers’ perceptions of CSR, we can observe that most of these are based on either Carroll’s approach of CSR, or on the stakeholder-based perspective of the concept. Thus, many researchers have quantified customers’ perceptions of CSR focusing on economic, legal, ethical, and philanthropic dimensions [20,21,22,23]. However, studies assessing customer-based perceptual CSR are becoming more focused on a stakeholder-based perspective, considering organizational responsibilities towards specific stakeholder categories [1,13,24,25,26].
Both researchers and business practitioners regard corporate responsibilities and fairness towards public authorities as an important element of CSR [1,2,3]. Always acknowledging and adhering to laws and regulations when carrying out activities represents an important element of CSR [21,23]. From this perspective, a responsible company follows all regulations carefully and promptly, submitting to the principles established by the regulatory system and keeping away from bending the law, even when this would improve business results [1,20]. Paying taxes in a fair and timely manner is also comprised among corporate responsibilities [1,4], while, on the other hand, cheating on taxes (or avoiding them), as well as corruption represent facets of corporate social irresponsibility [4].

2.2. Corporate Tax Non-Compliance and Corruption as Reflections of Corporate Social Irresponsibility

Corporate tax non-compliance refers to the phenomenon where companies do not pay the right tax at the right time, for any reason. It has various forms of manifestation, comprising tax evasion, tax avoidance and other tax-noncompliance behaviors, such as making careless errors/mistakes on the company tax return, or not making tax payments on time.
Tax evasion is when a company deliberately and unlawfully does not declare or account for what it owes, by hiding income or information from the tax authorities. It represents an intentional falsification of tax-relevant information through the non-declaration of taxable income and trade mispricing [27]. Tax fraud is the most severe form of tax evasion which is largely punishable under criminal law. It involves deliberately submitting false statements (for example, fiscal fraud in the value added tax area) or producing fake documents (such as invoices and receipts). Tax evasion includes the hidden economy, which is when a company hides taxable activity from tax authorities/administrations completely.
While tax evasion means breaking the rules, tax avoidance refers to bending the rules of the tax system (i.e., exploiting loopholes and mismatches within the law) to gain a tax advantage the legislator (state) never intended. Companies that engage in tax avoidance schemes, operate within the letter but not within the spirit of the law. Tax avoidance often involves fictitious artificial transactions that have little or no purpose other than to produce this advantage. Widespread forms of tax avoidance are aggressive tax planning arrangements, where multinational companies, often using transfer pricing mechanisms, look to relocate their tax base to other jurisdictions (tax havens and lower tax jurisdictions) in order to have items of income untaxed or taxed at a lower rate.
According to the European Commission, estimates regarding the sums being lost by the EU member states due to tax evasion and avoidance go up to one trillion euros. Companies who engage in tax non-compliance, depriving public budgets of huge amounts, exert an important negative impact on the rest of society. Therefore, such behavior should be considered contrary to the principles of corporate social responsibility.
In addition to tax evasion/avoidance, corporate corruption is another phenomenon which has a negative impact on society. It is when a company (or an employee of a company) pays a sum of money or performs a service in exchange for an illicit act by a public official [28]. According to Argandona [29], corruption to the company’s benefit is “when managers or employees accept extortion or make a bribe to obtain beneficial effects for the company or prevent it from suffering harm”. Although studies show that corporate bribery is counterproductive (leading to lower profit margins and employee morale as well as poverty and poor governance in the countries where it is practiced), according to the World Bank, approximately one-third of companies worldwide use kickbacks, paying an estimated total of 400 billion US dollars a year [30].

2.3. Customer Loyalty

Despite the fact that customer loyalty has been at the core of many scientific endeavors, its meaning has been a debated for many years, without a full consensus yet.
One of the first definitions that gained worldwide support was issued by Jacoby and Chesnut [31], who described customer loyalty as consisting in the biased behavioral response expressed over time by consumers with respect to one or more alternative brands out of a set of brands, as a result of psychological processes.
Another important development in what concerns the systematization of customer loyalty is provided by Oliver [32], who developed a framework in which he integrated cognitive, affective, conative and behavioral dimensions. His definition of customer loyalty (which later received worldwide support) regarded it as a deeply held commitment to rebuy a preferred product/service consistently in the future, thereby causing repetitive same-brand or same brand-set purchasing, despite situational influences and marketing efforts having the potential to cause switching behavior.
Currently, most researchers agree that customer loyalty has a dual nature. On one hand, customer loyalty can be attitudinal, including cognitive, affective and conative (behavioral intent) dimensions, while, on the other hand, it can be behavioral, reflecting the actual repeat purchase behavior. As Dick and Basu [33] state, repeat purchase behavior alone can be deceiving as it can suggest spurious loyalty (based on inertia, lack of options etc.), true loyalty implying also attitudinal loyalty, materialized in psychological commitment and positive company/brand attitude.
Previous studies have suggested that there is a direct positive relationship between customers’ perceptions of a company’s CSR and their loyalty to that company. This finding is applicable to various industries, such as banking services (e.g., [12,13,34]), telecom services [21,35], personal care products [36,37], food products [38,39,40] and other sectors. Moreover, recent studies have suggested that in particular, customers’ perceptions regarding corporate responsibilities towards public authorities, directly impact customer loyalty. Environmental or societal responsibilities impact customer loyalty to a lesser extent [41]. Considering these arguments, we propose the following hypothesis:
Hypothesis 1.
Corporate fairness towards public authorities positively influences customer loyalty.

2.4. Customer-Company Identification

Ashforth and Mael [42] were the first to conceptualize organizational identification as a person’s perception of “oneness or belongingness” with an organization. Customer-company identification is a concept derived from organizational identification, and is defined as the degree to which a member of an organization defines him/herself by the same attributes that he or she believes define the organization [43]. Drawing on the social identity theory and organizational identification, Bhattacharya and Sen [44] define customer-company identification as “the primary psychological substrate for the kind of deep, committed, and meaningful relationships that marketers are increasingly seeking to build with their customers”.
In what concerns the measurement of customer-company identification, even though it has been suggested that the concept might be viewed as multidimensional [44], most researchers have approached it in a parsimonious manner, as a mono-dimensional construct, based on the measurement scale proposed by Ashforth and Mael [42], taking into account the extent to which a company’s customers are preoccupied with the way others refer to the company.
Customer-company identification explains the reasons and motivations which encourage individuals to relate to companies, while the feelings of belonging and connection to an organization help individuals to achieve a positive social identity [45]. Customer-company identification make customers more psychologically attached to companies [44], further having the potential to enhance customer loyalty [12,46]. Considering these ideas and arguments, we propose the following hypothesis:
Hypothesis 2.
Customer-company identification positively influences customer loyalty.
Previous research has suggested that CSR practices, policies and initiatives represent antecedents of customer-company identification, inducing customers to identify and develop a sense of connection with companies [12,13,45]. Specifically, “the way that CSR initiatives create benefits for companies appears to be by increasing consumers’ identification with the company” [47]. Conceptualizing CSR within the framework of the stakeholder theory—in which context companies’ responsibilities towards public authorities play an important role in the overall CSR architecture—we posit the following hypothesis:
Hypothesis 3.
Corporate fairness towards public authorities positively influences customer-company identification.

3. Materials and Methods

The research objective was to investigate how customer loyalty can be enhanced by improving customers’ perceptions of corporate fairness towards public authorities, taking into account the mediating role of customer-company identification. The investigation was conducted comparatively within four industries (telecom services, retail banking services, dairy products and personal care products), and depicts the specific impacts that these perceptions have on customer loyalty in each sector, with practical implications concerning CSR communication.
The four industries were targeted mainly because of their main competitors’ significant visibility in the mainstream media, as well as their CSR practices dissemination to the general public. Thus, consumers’ perceptions regarding companies’ CSR policies, including their fairness towards public authorities, were formed and could be measured. Moreover, these sectors refer to products or services with a large penetration among consumers and therefore the main competitors’ customers can be easily found among the overall population. Other industries with similar characteristics related to CSR practices dissemination and market penetration could have been included in the research (e.g., retail services or the automotive industry). However, targeting more sectors would have increased the questionnaire length and, consequently, would have generated respondent fatigue, which reduces response rates and would have probably generated many missing values.
Data were collected by conducting a self-administered paper and pencil questionnaire-based survey among a large sample of urban Romanian customers of companies from the four targeted industries. In order to measure customer loyalty, customer-company identification and the perceptual corporate fairness of companies towards public authorities, the questionnaire included a set of 10 specific items drawn from the literature (Table 1). Thus, customer loyalty was measured using 4 items based on the scale developed and validated by Zeithaml et al. [48], customer-company identification was assessed employing a 3 item scale adapted from Mael and Ashforth [49], while corporate fairness towards public authorities was evaluated using a 3 item scale adapted from Wagner et al. [4]. All three latent variables were conceptualized as reflective.
The questionnaire comprised four main sections, one for each investigated sector, respondents were asked to name a specific company of which they were customers for each section, and to refer to it by rating their perceptions regarding its corporate fairness towards public authorities, as well as their identification with the company and their loyalty towards that company. All answers were recorded on a Likert scale ranging from 1 = “strongly disagree” to 7 = “strongly agree”, with a middle neutral point.
The sampling procedure was non-probabilistic consisting in quota sampling by gender and age, capitalizing on a significant snowball sampling effect due to the large number of survey operators involved in data collection (more than one hundred bachelor and master students). In order to minimize sample selection bias, each survey operator was instructed to apply the questionnaire to a group with a predefined demographics-based structure, more specifically, to a certain number of men and women, as well as to a certain number of respondents from each age group. Furthermore, survey operators were instructed to ask for personal contact data of respondents so that the researchers could remove fake respondents. The data was collected in the 2015–2016 academic year, right before the adoption of the EU’s General Data Protection Regulation (GDPR).
After removing full straight-liners from the sample, the final investigated sample included 1464 respondents, among which 1449 were customers of and referred to a telecom company, 1409 to a banking company, 1414 to a dairy products company, and 1415 to a personal care products company. The demographics of the sample for each industry is outlined in Table 2.

4. Results and Discussion

Collected data was analyzed by means of partial least squares structural equation modeling (PLS-SEM), using the SmartPLS 3 software [50]. The same PLS-SEM model was assessed separately for each investigated industry.
As our research was focused on prediction, trying to estimate the impact of corporate responsibility to public authorities on customer loyalty (and to emphasize both theoretical and practical implications), PLS-SEM was employed for our data analyses because, as compared to covariance-based SEM methods, it is generally better suited for exploring relationships, as it is focused on prediction [51].
The first step of our PLS-SEM analyses was to assess the employed measurements. As in this case, all measures were reflective, we tested our constructs for convergent validity and internal consistency. The results in Table 3 show that all three latent variables exhibit very good internal consistency, the values of Cronbach’s alpha and composite reliability being above the recommended threshold of 0.7, without exceeding 0.95, as suggested by Hair et al. [51]. As for convergent validity, both outer loading values (which exceed the threshold of 0.7), and average variance extracted values (above 0.5) indicate that the three constructs are convergent.
Assessing reflective measurements also involves discriminant validity or, more specifically, verifying whether the constructs are truly distinct from each other. Recent research [52,53] has shown that the Fornell–Larcker criterion is not as good of an option for assessing discriminant validity, as compared to the heterotrait-monotrait ratio of correlations (HTMT) criterion. Hence, we assessed discriminant validity exclusively using the former method. As shown in Table 4, the three latent reflective variables are conceptually distinct, HTMT values were way under the threshold of 0.85, as suggested by Henseler et al. [54].
The second step of our PLS-SEM investigation consisted of the structural model assessment. Firstly, collinearity issues were analyzed, and afterwards the hypothesized relationships were tested. As it can be seen in Table 5, no critical levels of collinearity were found between the two predictor variables (corporate fairness and customer-company identification), all variance inflation factors (VIF) values were below the threshold of 5, as suggested by Hair et al. [51].
In order to test the hypothesized relationships between corporate fairness towards public authorities, customer-company identification and customer loyalty, we used the bootstrapping procedure with 5000 subsamples. The results in Figure 1 confirm all three hypotheses in all four industries (p values < 0.001 for all tested relationships). Thus, it can be stated that the impact of perceived corporate fairness towards public authorities on customer loyalty is positive and significant, having both a direct and indirect (via customer-company identification) nature.
However, the direct impact is much higher than the indirect one in all cases. This indicates that, no matter if customers identify themselves with their companies or not, the perceived corporate fairness still has a relevant impact on their loyalty towards that company.
Our results are in line with those obtained by Choi and La [34], Pérez et al. [12] and Öberseder et al. [13] in the banking industry, Salmones et al. [21] and Vlachos et al. [35] in the case of telecom companies, He and Lai [36] and Suh and Yoo [37] for the personal care products industry, as well as with the research results outlined by Du et al. [38], Perrini et al. [39] and Anselmsson et al. [40] who investigated these issues in food product industries. Their results emphasized the impact of perceptual CSR on customer loyalty, even if the focus was not on companies’ responsibility towards public authorities. On the other hand, considering the stakeholder-based view of CSR, public authorities represent one of the main stakeholders to which a company needs to direct its CSR efforts. Therefore, our results support these previous findings, from a different perspective.
Nevertheless, even though the indirect effect (mediated by customer-company identification) is relatively lower, it is significant. Consequently, if companies manage to create a positive image among their customers in what concerns compliance with laws and regulations, payment of taxes and/or attitudes towards bribery, this will lead to an increase in the level of their customers’ identification with the company, which further enhances customer loyalty. Our results regarding the indirect effect of perceptual CSR—in our case corporate responsibility towards public authorities—on customer loyalty, via customer-company identification, is also in line with previous research outcomes, such as those obtained by Sen and Bhattacharya [6], Sen et al. [55] or Oberseder et al. [13].
Considering the coefficients of determination (R2) for our target dependent variable, it can be stated that between 20% and 30% of the variation in customer loyalty is explained by customers’ perceptions of corporate fairness to public authorities (including the mediating impact of customer-company identification). Still, a larger R2 can be observed in the service sectors (banking: R2 = 0.294; telecom: R2 = 0.246), as compared to the products related sectors (dairy products: R2 = 0.206; personal care products: R2 = 0.218). This can be explained by considering the particularities of banking and telecom sectors. Firstly, in these cases the players are few and large-sized, registering important earnings, so people expect and monitor them to a larger extent with respect to their relationship with the government. Secondly, both the banking and telecom sectors are heavily regulated, their compliance with laws and regulations are, to a larger extent, a subject of interest for both their customers and the media. Thirdly, especially in Romania (where the research sample originates from), customers pay more attention to the banking sector as compared to other industries when it comes to corporate ethical behavior, as the sector has been involved in scandals concerning abusive contractual terms and fraudulent practices for many years.
The third step of our PLS-SEM analyses was focused on model-fit and predictive relevance assessment. With respect to model fit, Table 6 indicates appropriate goodness of fit, as standardized root mean square residual (SRMR) values are below the threshold of 0.08, for both saturated and estimated models, as suggested by Hair et al. [51].
However, the notion of fit is not fully applicable to PLS-SEM, as it seeks a solution based on different statistical objectives than those related to prediction, which is the base of PLS-SEM [51]. Moreover, model-fit measures for PLS-SEM models are in their early stage of research and need further development. Instead of assessing goodness of fit, structural models should be assessed primarily on the basis of their predictive capabilities.
In order to assess the predictive relevance of our model, we used the blindfolding procedure with an omission distance of 8 (as the default value of 7, set in the SmartPLS software, was a divisor/factor for the number of respondents in the case of retail banking services). Table 7 suggests moderate prediction power for our model in the banking and telecom industries, Q2 values are between 0.15 and 0.35, suggesting borderline moderate prediction power in the case of the dairy and personal care products sectors, respectively [56].
This result supports our previous statement regarding the higher impact of corporate fairness on customer loyalty in the telecom industry and, especially, the banking sector, from the perspective of corporate responsibility towards public authorities. Overall, it can be stated that impact of the perceived corporate responsibility towards public authorities on customer loyalty is not high, but rather moderate. This could be a consequence of the communist past of Romania, a period in which bribery was considered normal, as one way in which citizens could obtain access to basic products or services. This habit continued in the democratic regime that followed, many people still accepting corruption in society, without really condemning it or taking any action against it.
To fully validate the applicability of the investigated relationships, we further checked for unobserved heterogeneity. This phenomenon occurs when the relationships in the model differ significantly between groups and these groups can’t be determined using observable characteristics [57]. For example, firm size represents an important grouping variable in CSR studies and results obtained in such contexts may not be consistent in various firm size groups [58]. However, in the current study, firm size is not an observable variable. Therefore, we ran the PLS finite mixture procedure (FIMIX) to assess unobserved heterogeneity for three scenarios: One, two, and three potentially relevant segments (using 1.0E-10 as stop criterion, 5000 as the maximum number of iterations, and 10 repetitions). The FIMIX-PLS results are shown in Table 8.
In such analyses, the consistent Akaike’s information criterion (CAIC), and the modified Akaike’s information criterion with factor 3 (AIC3) represent the most relevant fit measures, the optimal solution being the number of segments with the lowest fit measures value [57], provided that the normed entropy statistic (EN) is above the threshold of 0.5 [59]. Despite the fact that, at a first glance, our results suggest a two, or even three segment optimal solution for each industry, these scenarios exhibit an EN value below 0.50, showing that the two/three segments would not actually be well separated. Overall, these results indicate that there is no substantial heterogeneity in our data and, therefore, the investigation relationships do not significantly differ among various groups, including those based on firm size.

5. Conclusions

The main topics addressed by previous research related to CSR in Romania are mainly focused on companies’ practices and policies in this field, the influence of CSR on business competitiveness, and CSR reporting methods—usually from the perspective of employees and managers—with the financial, energy and agri-food industries being among the most investigated. Our paper complements current knowledge by tackling CSR from customers’ perspective, analyzing four industries comparatively, from both the services and products sectors. The paper outlines relevant findings for the theoretical knowledge regarding the relationship between customer loyalty and perceived corporate responsibility towards a relevant stakeholder of any organization, public authorities.
Our results showed that customers’ perception of corporate fairness towards public authorities has a significant and positive impact on customer loyalty, both directly and indirectly via customer-company identification, in all investigated industries, with a higher impact for services and especially for retail banking services. Also, our analyses revealed no substantial heterogeneity in the data and, therefore, we can state that the confirmed relationships are similarly applicable not only for various industries, but also for various sizes of companies. By investigating the mechanism behind the impact of CSR on customer loyalty, in particular, the mediating role of customer-company identification, our findings advance the current knowledge of CSR and its influence on customer loyalty, from the particular perspective of public authorities as important stakeholders of any business.
Our results convey practical implications for companies. Thus, we show that fostering customer loyalty can be done by means of appropriate CSR communication (besides other means companies have in their marketing arsenal). Furthermore, we suggest that CSR communications should include aspects concerning corporate fairness towards public authorities. The way these issues are disseminated must be carefully managed so as to generate positive customer perceptions, as these perceptions further influence customer-company identification and customer loyalty significantly. In other words, we show that being a good corporate citizen in relation to public authorities is not only ethical, but also beneficial from a customer loyalty point of view.
Starting from the premise that the potential benefits of positively perceived CSR, including perceived fairness towards public authorities, can only become relevant when customers are aware of a company’s attitude towards their stakeholders, the practical implications of our findings are related to customer relationship management and to CSR communication efficiency. Thus, companies which operate in Romania (and, to a limited extent, in most developing countries) can foster their customer loyalty by actively communicating their fair attitude towards public authorities, emphasizing that they fully comply with the legislation in conducting their activities, that they always pay taxes fairly and honestly, and that they strive to prevent and avoid corruption in their relation with the state.
Concerning research limitations, as the current study was conducted exclusively among customers from Romania, the results might not be fully extrapolated for other developing countries because of their different cultural and economic contexts. Also, the proposed mechanism behind the impact of CSR on customer loyalty did not include other customer-related mediating variables (e.g., brand trust, customer satisfaction), or potentially moderating variables related to customers such as their green attitude or their psychological traits.
As a future research direction, in order to increase the relevance of our findings, expanding the research in other developing countries, both from Europe and other continents, should be considered. Moreover, conducting such research in a comparative manner, between developed and developing countries, should be of future interest for CSR researchers. Last but not least, as a future research opportunity, our model should be revisited by taking into consideration other mediating variables (e.g., brand trust), as well as consumers’ green attitudes as moderators, and integrating them into the structural equation model.

Author Contributions

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

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 12 00187 g001 550
Figure 1. Structural model assessment: partial least squares algorithm and bootstrapping results Note: Path coefficients and p values shown on the inner model’s arrows (p values in parentheses).
Figure 1. Structural model assessment: partial least squares algorithm and bootstrapping results Note: Path coefficients and p values shown on the inner model’s arrows (p values in parentheses).
Sustainability 12 00187 g001
Table
Table 1. Latent variables measurement.
Table 1. Latent variables measurement.
Latent VariableCodingItem
Corporate fairness to public authorities [4]FAIR1I believe that this company fully complies with the law and regulations
FAIR2I believe that this company always pays its taxes fairly and honestly
FAIR3I believe that this company strives to prevent and avoid bribery
Customer-company identification [49]CCI1I am interested in what others think about this company
CCI2I feel angry when someone criticizes this company
CCI3I feel good when someone praises this company
Customer loyalty [48]LOY1This company is my first choice in its sector
LOY2I will continue to be a customer of this company
LOY3In the future I plan to do more business with this company
LOY4I would recommend this company to my friends/acquaintances
Table
Table 2. Sample demographics.
Table 2. Sample demographics.
IndustryGenderAge
MenWomen18–24 yrs25–34 yrs35–44 yrs>44 yrs
Telecom49.34%50.66%20.36%29.68%23.33%26.64%
Banking49.11%50.89%20.87%29.52%23.28%26.33%
Dairy49.43%50.57%20.65%29.77%22.91%26.66%
Personal care49.26%50.74%20.64%29.40%23.18%26.78%
Table
Table 3. Convergent validity and internal consistency assessment.
Table 3. Convergent validity and internal consistency assessment.
BankingTelecom
IndicatorOLCACRAVEIndicatorOLCACRAVE
FAIR10.8620.8590.9140.779FAIR10.80.8220.8950.739
FAIR20.891FAIR20.893
FAIR30.894FAIR30.883
CCI10.7990.8480.9080.767CCI10.7580.8180.8910.733
CCI20.905CCI20.91
CCI30.919CCI30.893
LOY10.8480.8820.9190.738LOY10.8140.8640.9060.708
LOY20.848LOY20.83
LOY30.843LOY30.83
LOY40.896LOY40.889
Dairy productsPersonal care products
IndicatorOLCACRAVEIndicatorOLCACRAVE
FAIR10.8650.8640.9170.787FAIR10.8870.8910.9320.821
FAIR20.912FAIR20.926
FAIR30.884FAIR30.905
CCI10.840.870.920.794CCI10.8440.8740.9220.798
CCI20.908CCI20.914
CCI30.923CCI30.92
LOY10.8250.8770.9160.731LOY10.8490.8860.9210.745
LOY20.883LOY20.887
LOY30.867LOY30.863
LOY40.844LOY40.852
OL = outer loadings; CA = Cronbach’s Alpha; CR = composite reliability; AVE = average variance extracted.
Table
Table 4. Discriminant validity assessment: heterotrait-monotrait ratio of correlations (HTMT) values.
Table 4. Discriminant validity assessment: heterotrait-monotrait ratio of correlations (HTMT) values.
BankingTelecomDairy ProductsPersonal Care Products
FAIRLOY FAIRLOY FAIRLOY FAIRLOY
LOY0.419N/ALOY0.391N/ALOY0.376N/ALOY0.371N/A
CCI0.2740.533CCI0.3240.507CCI0.2750.433CCI0.340.464
Table
Table 5. Collinearity assessment between corporate fairness to public authorities and customer-company identification: VIF (variance inflation factors) values.
Table 5. Collinearity assessment between corporate fairness to public authorities and customer-company identification: VIF (variance inflation factors) values.
BankingTelecomDairy ProductsPersonal Care Products
VIF = 1.102VIF = 1.079VIF = 1.061VIF = 1.102
Table
Table 6. Goodness of fit: standardized root mean square residual (SRMR) values.
Table 6. Goodness of fit: standardized root mean square residual (SRMR) values.
BankingTelecom
SaturatedEstimated SaturatedEstimated
SRMR0.0610.061SRMR0.0680.068
Dairy productsPersonal care products
SaturatedEstimated SaturatedEstimated
SRMR0.0540.054SRMR0.0520.052
Table
Table 7. Predictive relevance: Q2 values for customer loyal.
Table 7. Predictive relevance: Q2 values for customer loyal.
BankingTelecomDairy ProductsPersonal Care Products
Q2 = 0.203Q2 = 0.162Q2 = 0.144Q2 = 0.154
Table
Table 8. Unobserved heterogeneity: finite mixture (FIMIX) segmentation results.
Table 8. Unobserved heterogeneity: finite mixture (FIMIX) segmentation results.
BankingTelecomDairy ProductsPersonal Care Products
Number of SegmentsNumber of SegmentsNumber of SegmentsNumber of Segments
123123123123
AIC37438.47380.97347.47719.77694.77686.97629.87580.97572.97559.77508.17454.9
CAIC7464.67438.67436.77746.17752.87776.77656.17638.77662.37586.17565.97544.3
ENN/A0.2810.412N/A0.1970.21N/A0.4910.332N/A0.180.34
Note: AIC3 = modified Akaike’s information criterion with factor 3; CAIC = consistent Akaike’s information criterion; EN = entropy statistic normed.

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Moisescu, O.I.; Gică, O.A.; Müller, V.O.; Müller, C.A. Can Corporate Fairness towards Public Authorities Enhance Customer Loyalty? A Multi-Sectorial Investigation in a Developing Country. Sustainability 2020, 12, 187. https://doi.org/10.3390/su12010187

AMA Style

Moisescu OI, Gică OA, Müller VO, Müller CA. Can Corporate Fairness towards Public Authorities Enhance Customer Loyalty? A Multi-Sectorial Investigation in a Developing Country. Sustainability. 2020; 12(1):187. https://doi.org/10.3390/su12010187

Chicago/Turabian Style

Moisescu, Ovidiu I., Oana A. Gică, Victor O. Müller, and Camelia Ancuța Müller. 2020. "Can Corporate Fairness towards Public Authorities Enhance Customer Loyalty? A Multi-Sectorial Investigation in a Developing Country" Sustainability 12, no. 1: 187. https://doi.org/10.3390/su12010187

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