The Effect of Corporate Philanthropy on Consumer Behavior: Open Innovation in the Operating Mechanism

Abstract

The aim of this study was to highlight the effect of corporate philanthropy (CP) on consumer patronage behavior. For this purpose, reciprocity was taken as the key mechanism which determines consumers’ willingness to participate in and buy goods or services of a company performing philanthropic activities. The moderating effect of trust and vicarious licensing was also studied. Considering the importance of CP to society and its residents, it is essential to recognize its effect on consumer patronage behavior. To accomplish this objective, data were collected from 340 respondents via a questionnaire. The results of this research revealed that reciprocity shows a statistically significantly positive association with both participation intention (R = 0.729, R² = 0.531, p = 0.000, b = 0.740) and purchasing intention (R = 0.71, R² = 0.534, p = 0.000, b = 0.878). Similarly, trust strengthens the relationship of reciprocity with both participation intention (b = 0.250) and purchasing intention (b = 0.310). However, vicarious licensing weakens the relationship of reciprocity with both participation intention (b = −0.175) and purchasing intention (b = −0.187). The mediation effect of participation intention was also examined in this study. The results of this research will contribute to the benefit of society, since philanthropy plays a vital role in society’s progress. The greater response of consumers towards companies performing philanthropic activities justifies the importance of CP.

1. Introduction

Corporate philanthropy (CP) refers to the voluntary donation of assets of a profit earning company to promote the welfare of its society. This voluntary donation creates a positive social impact of the company on society [1]. CP also affects the market value of that company positively [2]. Many organizations have adopted various social causes for the welfare of society. There is an assumption that if companies perform philanthropic activities, consumers will reward those companies [3]. However, consumers do not blindly accept these philanthropic activities. Hence, they may or may not reward a company that conducts them [4]. How much a company can benefit from conducting philanthropic activities, depends upon how positively these activities are received by consumers [5]. Zlatev [6] proposes that companies should also consider the welfare effects of an activity while deciding how widely it can be implemented. It has also been noted that companies involved in CP obtain a positive impact on their product market competitiveness compared to their rivals [7]. The objectives of this study were to examine the effect of CP on consumer patronage behavior through the mechanism of reciprocity, to study the effect of trust as a moderating variable between reciprocity and consumer patronage behavior, and to study the effect of vicarious licensing as a moderator between reciprocity and consumer patronage behavior.

Cho and Lee [8] previously conducted research in South Korea, a developed country. They studied how CP affected consumer patronage behavior through the mechanism of reciprocity in that geography [9].

For the current study, this research was conducted in an emerging economy to examine how cross-cultural differences can affect the association between philanthropic activities and consumer patronage behavior. In developing countries, the importance of CP is manifold [10]. Like Cho and Lee [8], this study also uses reciprocity as a key mechanism which manifests the effect of CP on patronage behavior. The conceptual framework of Cho and Lee’s study [8] was also extended by scrutinizing the previous literature, and a couple more variables were added which can enhance and contribute more towards the relevant body of knowledge.

CP can affect consumer patronage behavior in two different forms: (1) How much a consumer is willing to support a company’s philanthropic activities (referred to as participation intention), and (2) the degree to which a consumer is willing to buy a company’s products or services (referred to as purchasing intention) [8]. To determine the effect of philanthropy on consumer behavior, Cho and Lee [8] showed that philanthropic activities strengthened consumer patronage behavior through the mechanism of reciprocity (i.e., “feeling of responsibility to reply to the positive act of one party with another positive act” [8], p. 2). Studies have shown that there are various other measures and variables which act as moderators between reciprocity and consumer patronage behavior, such as vicarious licensing (i.e., to what degree consumers decide that a company had donated to society on their behalf [8], p. 2) and trust (i.e., to what degree a consumer believes that philanthropic activities implemented by a company were conducted just for society’s welfare) [11].

This research reports on the gap in the literature about how CP affects consumer patronage behavior. An inconsistency is shown in previous literature related to philanthropic activities and consumer behavior. Some studies support the fact that CP improves brand loyalty [12], enhances reputation, or is undoubtedly marginally beneficial for firms [13]. On the other hand, others have argued that CP has a limited effect on a company’s bottom line [14]. The cause of this discrepancy in the previous literature arises from the fact that effect of CP on consumer behavior depends upon various moderating factors [15]. This research addresses this gap and studies the effect of CP on consumer behavior by introducing a couple of moderating variables.

Philanthropic activities are not only beneficial for society, but also for both the company and its employees as well [16]. It also helps a company to improve its brand and make a reputation for its customers, employees, and broader society. A study conducted by Unilever highlighted that 33% of global consumers preferred to buy from companies that were contributing to any social cause [17]. CP also provides a competitive edge to the companies performing philanthropic activities over the companies which are not involved in any social cause [18].

The results of this research will contribute to the benefit of society because philanthropy plays a vital role in social improvements. The greater response of consumers towards companies performing philanthropic activities justifies the perceived importance of CP. This study also indicates that when companies develop trust with its consumers, then the relation between reciprocity and consumer behavior would also be enhanced. For researchers, this study will help them to uncover the effect of certain moderating variables (such as trust), that many researchers were not previously able to explore. Thus, an enhanced conceptual framework can be developed.

2. Literature Review and Hypothesis Development

2.1. Corporate Philanthropy

It is a general belief that corporate social responsibility (CSR) has many forms out of which CP is known as one of the most important forms [19]. CP not only improves a firm’s performance, but also develops a better corporate image [20]. Kotler and Lee [21], p. 91, described CP as the subdivision of CSR and defined it as, “the direct giving by a company to a charity or cause, in the form of cash, donations and/or in- kind services”. CP is now acquiring a much better position in business strategies among all the CSR activities [22], generating positive benefits by changing the behavior of internal stakeholders of a company [23]. In fact, during COVID-19, pandemic several firms have opted for CP, not only to alleviate its consequences, but also to protect the interest of their shareholders [24]. Philanthropy also reduces the costs of formal controls [23].

2.2. Reciprocity

Reciprocity is generally accepted as one of the most important principles of the moral codes [25]. It can be defined as a sense of obligation in return to a positive action, i.e., to respond to one positive action with another positive action [26]. Drazena [27] believes that non-selfish behavior is the reflection of reciprocity. Reciprocity is generally viewed like a social norm, which govern the conduct of society that the person who receive a favor should be obligated to repay the favor [28]. Mark and Carrolyn [29] demonstrate that people who receive favor from others show reciprocity. Mathwick and Wiertz [30] described reciprocity as a form of social capital. If a person is more motivated to behave ethically, then his pro-social behavior to behave well will be more powerfully guided [31].

Hypothesis 1 (H1).

Reciprocity has significant positive relationship with participation intention.

Hypothesis 2 (H2).

Reciprocity has significant positive relationship with purchasing intention.

Hypothesis 3 (H3).

Participation intention mediates the path from reciprocity to purchasing intention.

2.3. Benevolence Trust

Forehand and Grier [32] suggested that people usually evaluate one another‘s motives, and these motives affect their succeeding behavior. They [32] found out that this process of evaluation can be addressed by attribution theory. This is explained as the process in which consumers assess a company’s motives and how they ultimately affect their behavior. Individuals usually attribute two types of motives: Focused on individuals or society’s benefit and motives focused on the company’s benefit. Consumers always evaluate philanthropic activities performed by a company. Therefore, companies constantly strive to improve their reputation and trust [33] by engaging in CP and CSR.

Park [11] suggested that philanthropic activities conducted by companies will drive more results, if consumers firmly believe that these philanthropic activities are conducted solely for the benefit of society and it’s pure volunteer work. On the other hand, if consumers believe that philanthropic activities are conducted for the company’s own benefit, they will fail to participate, as the company’s practices do not correspond to their expectations [34].

Hypothesis 4 (H4).

Trust will strengthen the relationship between reciprocity to participation intention.

Hypothesis 5 (H5).

Trust will strengthen the relationship between reciprocity to purchasing intention.

2.4. Vicarious Licensing

The licensing effect is described as a subconscious phenomenon, where a behavior taking place prior to a specific choice is presented as the justification and explanation for the decision after that [35]. Observation or inferences can also generate the licensing effect, i.e., vicarious licensing. For instance, Kouchaki [36] proposed that a person would behave less ethically if he watched another person performing an ethical activity. Later, the empirical results of his experiment showed that if a person realized that someone had already performed good deeds or behaved ethically or morally on his behalf, he would afterwards seem to act less ethically and morally and more indulgently.

Hypothesis 6 (H6).

Vicarious licensing will weaken the relationship between reciprocity to participation intention.

Hypothesis 7 (H7).

Vicarious licensing will weaken the relationship between reciprocity to purchasing intention.

2.5. Consumer Patronage Behavior

Patronage behavior involves the mechanism of identifying various factors and elements that are used by consumers for the selection of products or services from a number of available alternatives. CP also helps to build the company’s reputation. When a company succeeds in building its positive reputation, this fact will also help to increase consumer’s patronage behavior [37]. Boccia [38] suggested that as time goes by, a stronger relationship will develop between the consumer’s behavior and CP and have an influence upon the management of companies. There exists a positive association between philanthropic activities of companies and consumers’ behavior and responses towards those companies and their products [39].

Figure 1 above shows the conceptual framework that is used in this study. Reciprocity measures the effect of CP on consumer patronage behavior and is identified as an independent variable. In contrast, consumer patronage behavior is measured by participation intention and purchasing intention [8]. Both variables are taken as dependent variables. This study will also examine the mediation effect of participation intention and the moderating role of trust and vicarious licensing.

3. Materials and Methods

This study focuses on response and behavior of consumers towards philanthropic activities regulated by a company. The unit of analysis is individual in this study. The target population of this study comprises general consumers, such as employees, housewives, and university students.

Different measures were adapted from the existing literature to inspect the effect of variables used in this study. A comprehensive questionnaire designed by [8] was used for collecting data. The statements used to measure trust have been adapted from [11,32]. Yaakop et al. [40] suggest that it is much better to use previous instruments for measurements because previous scales were prepared carefully. They are more mature and robust than the newly developed ones. As previous scales have also been used frequently before, they seem to be more authentic. For a better understanding of consumers, a scenario of an anonymous company performing certain philanthropic activities was also developed at the beginning of the questionnaire. Respondents’ demographics details were also added.

The sample size has been estimated with the help of minimum requirements under CFA (Confirmatory Factor Analysis). It says that “ratio of cases to free parameters N: q is from 10:1 to 20:1” [41], p. 129. So, considering 17 parameters of our questionnaire and 20 cases for each of the parameter, a sample size of 17 ∗ 20 = 340 is acceptable. A self-administered questionnaire was distributed through online and in person surveys. Online questionnaires were developed using Google forms. One hundred questionnaires were distributed online, while 280 questionnaires were distributed physically. After collecting data, careful scrutiny was undertaken. Twenty-three incomplete responses from online survey and 7 incomplete responses from physical survey were excluded. The response rate from the online survey was 77% [42], while the response rate from the physical survey was 97.5% [42]. So, the number of responses collected from both the online and physical surveys was 67 and 273, respectively. The overall response rate for both the online and physical surveys was 89.4% [42].

A multistage random sampling technique was used to study the behavior of consumers as it allows for unbiased data collection [43]. Employees were divided into four categories based on their income, i.e., people with an income above US$ 1500, people with an income from US$ 1500 to US$ 1000, and a third category consisting of people earning from US$ 1000 to US$ 500. The last category belongs to employees earning less than US$ 500. Similarly, the students were also broadly classified into two categories, i.e., students studying in public universities and students studying in private universities. Two public and two private universities were randomly selected for data collection. 50% of responses were collected from students studying in public universities, while 50% of responses were collected from students studying in private universities. In addition, questionnaires were distributed equally among housewives, students, and employed persons from the target population. The final sample was comprised of approximately 34% housewives, 32% students, and 34% employed persons. There were 60% female respondents, while 40% were male respondents.

The questionnaire developed for this study comprised of close-ended questions. The variables used were measured using 5-point Likert Scale (1 was used for respondent’s response to strongly disagree, while 5 gave the option on strongly agree to the respondent).

4. Data Analysis and Results

4.1. Measurement Test

In this study, CFA was used in performing measurement tests in terms of construct validity (CV) and reliability. To determine the reliability of constructs, Cronbach’s alpha and composite reliability (CR) tests were used. The results shown in

Table 1. CFA (Confirmatory Factor Analysis) outputs.

Variables	Statements	Factor Loading	Cronbach’s α	CR	AVE
Reciprocity	1	0.799	0.850	0.707	0.607
	2	0.77
	3	0.841
Participation Intention	4	0.826	0.878	0.870	0.690
	5	0.845
	6	0.821
Purchasing Intention	7	0.827	0.920	0.821	0.742
	8	0.858
	9	0.896
	10	0.864
Vicarious Licensing	11	0.783	0.913	0.722	0.565
	12	0.719
Trust	13	0.786	0.758	0.914	0.679
	14	0.832
	15	0.868
	16	0.829
	17	0.804

indicate that Cronbach’s alpha values for every construct were above the suggested value of 0.6, while CR of each variable was greater than 0.7 [44]. Similarly, the value of AVE for each factor was greater than the standard value, i.e., 0.5 which confirms the existence of convergent validity [44]. The AVE estimates of all the constructs were larger than the corresponding squared inter-construct correlation estimates. This ensures the presence of discriminant validity as well as the convergent construct validity of the scale [44].

Gaskin [45] suggests that it is always important to assess the model fitness whenever the model is changed. The value of CMIN/df (X²/df) should be less than 5 [46], while the values of CFI, GFI, and NFI should be equal to 1 for excellent model fit [30,32]. Model fitness results (X²/df = 2.087, CFI = 0.965, GFI = 0.902, NFI = 0.927 and RMSEA = 0.057) of CFA showed that it is a good model fit [46].

4.2. Model Testing

In order to examine Hypotheses 1 and 2, the linear regression in SPSS was used [47]. The results are shown in

Table 2. Regression results.

Path	R	Adj R2	B	ρ
Reciprocity→Participation Intention	0.729	0.530	0.740	0.000
Reciprocity→Purchasing Intention	0.731	0.532	0.878	0.000

.

The values of adj R², 0.530 and 0.532, described the variance in reciprocity due to participation intention and purchasing intention, respectively. In other words, almost 53.0% of the variance in reciprocity was due to participation intention. In contrast, 53.2% of the variance in reciprocity was due to purchasing intention. While the values of p for both relationships were 0.000 (p < 0.05), the regression model significantly forecasted the outcome variable, i.e., there exists a significant positive relationship between independent and dependent variables [48]. So, H1 and H2 are confirmed.

4.3. Model Testing through SEM to Study Mediation Effect

To examine the mediation effect of participation intention, a structural equation model (SEM) in AMOS was used [49]. SEM framework has many advantages in the context of mediation analysis. When a model contains latent variables (as in this study, reciprocity, participation intention, purchasing intention, trust, and vicarious licensing are latent variables), SEM allows for ease of interpretation and estimation [50]. Two structural models, i.e., Direct Structural Model and Indirect Structural Model were developed. Maximum likelihood estimation method was used in both direct and indirect structural models [44]. Baron and Kenny [51] stated three necessary conditions to claim whether mediation has taken place or not.

• X should have significant relationship with M;
• Y should have significant relationship with M;
• on introducing M in the model, the relationship between X and Y should diminish.

To examine the relationship between X and M (Condition 1), a direct structural model was developed. Where X is an independent variable, i.e., reciprocity, M is a mediating variable, i.e., participation intention.

Table 3. Regression weights.

	S.R.W.	Estimate	S.E.	C.R.	p
Par-Int←Rec	0.900	0.891	0.060	14.89	0.000 ***

Note ‘***’ 1% significance level.

above shows the results of this direct structural model. The value of Standardized Regression Weights (SRW) was 0.900, which predicted that reciprocity has positive impact on consumer’s participation intention. Likewise, significant value (p-value = 0.000 < 0.05) highlighted a significant association between reciprocity and participation intention [44]. Moreover, model fitness results (X²/df = 3.485, CFI = 0.985, GFI = 0.973, NFI = 0.979 and RMSEA = 0.047) of CFA show that it is a good model fit [44,46]. These results show that the first condition stated by Barron and Kenny has been fulfilled.

The results of direct structural model to measure the relationship between Y and M (Condition 2) given in

Table 4. Regression weights.

	S.R.W.	Estimate	S.E.	C.R.	p
Pur-Int←Par-Int	0.911	0.971	0.056	17.37	0.000 ***

Note ‘***’ 1% significance level.

show that there exists a significant relationship between Y and M, i.e., purchasing intention and participation intention.

Model fitness results (X²/df = 2.923, CFI = 0.987, GFI = 0.970, NFI = 0.981, and RMSEA = 0.046) of CFA showed that it is a good model fit [44,46]. The results of direct structural model to measure the relationship between X and Y (Condition 3, part 1) are given in

Table 5. Regression weights.

	S.R.W.	Estimate	S.E.	C.R.	p
Pur-In←Rec	0.851	0.826	0.055	15.01	0.000 ***

Note ‘***’ 1% significance level.

. These results show that there exists a significant relationship between X and Y.

Model fitness results (X²/df = 2.062, CFI = 1.000, GFI = 0.990, NFI = 0.993, and RMSEA = 0.013) of CFA show that it is a good model fit [46]. While the relationship between X and Y diminished when M was introduced in the model (Condition 3, Part 2) as shown in

Table 6. Regression weights.

	S.R.W.	Estimate	S.E.	C.R.	p
Par-Int←Rec	0.900	0.804	0.052	15.39	0.000 ***
Pur-Int←Rec	0.164	0.159	0.115	1.38	0.168
Pur-Int←Par-Int	0.763	0.830	0.134	6.18	0.000 ***

Note ‘***’ 1% significance level.

below.

Model fitness results (X²/df = 2.432, CFI = 0.983, GFI = 0.956, and RMSEA = 0.066) of CFA show that it is a good model fit [46]. The p-value 0.168 shows the diminishing relation between X and Y after introducing M in the model. This confirms H3, i.e., participation intention mediates the path between reciprocity and purchasing intention.

4.4. Moderation Effect

To examine the effect of moderating variable, stepwise multiple moderated regression analysis in SPSS was used [8,52]. Model a represents the effect of reciprocity on participation intention. Model b represents both reciprocity and trust as separate exogenous variables, whereas Model c studies the impact of reciprocity and the interaction effect of trust on participation intention.

Table 7. The results of moderating effect of trust on participation intention.

	Adjusted R2	F Change	Sig Level of F Change
(a) Reciprocity→participation intention	0.531	374	0.000
(b) Reciprocity and trust→participation intention	0.547	43.42	0.035
(c) Reciprocity, trust effect, and reciprocity × trust→participation intention.	0.559	29.21	0.041

illustrates that the value of adj R² of Model c is greater than both Model a and Model b. It confirms that trust has moderated the relationship. The increase in value of adjusted R² from 0.531 to 0.559 shows that the proportion of variance in dependent variable increases when the moderating variable is introduced in the model [53]. Moreover, the beta value for this interaction is 0.250. The positive sign with beta value shows that trust strengthens the relationship between reciprocity and participation intention [8]. H4 is confirmed.

In the same way the moderated effect of trust on purchasing intention and the effect of vicarious licensing as a moderated variable is also given in

Table 8. The results of moderating effect of trust on purchasing intention.

	Adjusted R2	F Change	Sig Level of F Change
(a) Reciprocity→purchasing intention	0.534	378	0.000
(b) Reciprocity and trust→purchasing intention	0.593	98.65	0.030
(c) Reciprocity, trust effect, and reciprocity × trust→purchasing intention.	0.681	42.43	0.041

,

Table 9. The results of moderating effect of vicarious licensing on participation intention.

	Adjusted R2	F Change	Sig Level of F Change
(a) Reciprocity→participation intention	0.531	374	0.000
(b) Reciprocity and vicarious licensing→participation intention	0.638	76.65	0.013
(c) Reciprocity, licensing effect, and reciprocity × vicarious licensing→participation intention.	0.773	29.43	0.032

, and

Table 10. The results of moderating effect of vicarious licensing on purchasing intention.

	Adjusted R2	F Change	Sig Level of F Change
(a) Reciprocity→purchasing intention	0.534	378	0.000
(b) Reciprocity and vicarious licensing→purchasing intention	0.638	76.65	0.011
(c) Reciprocity, licensing effect, and reciprocity × vicarious licensing→purchasing intention.	0.781	32.43	0.003

, respectively.

From Table 8, it can be concluded that the value of adj R² of Model c is greater than both Model a and b, confirming trust has moderated the relationship [53]. The beta value for this interaction is 0.310 which shows that trust has strengthened the relationship between reciprocity and purchasing intention. Thus, accepting H5.

In the above Table 9, Model a represents the effect of reciprocity on participation intention. While Model b represents both reciprocity and vicarious licensing as separate exogenous variables, Model c studies the impact of reciprocity and the interaction effect of licensing on participation intention. In Table 9, the value of adj R² of Model c is greater than both Model a and b, which confirms vicarious licensing has moderated the relationship. However, the beta value for this interaction is −0.175. The negative sign with beta value shows that vicarious licensing has diminished the relationship between reciprocity and participation intention [8]. H6 is confirmed.

Value of Adjusted R² in Model c is greater compared to Model a and Model b. This shows that vicarious licensing has moderated the relationship between reciprocity and purchasing intention. The beta value −0.187 shows that vicarious licensing has dampens the relationship between reciprocity and purchasing intention [8]. So, H7 is accepted.

5. Discussion

This study examined behavioral and social mechanism concerning the impact of CP on consumer behavior. For this purpose, like Cho and Lee’s [8] study, reciprocity was identified as the key mechanism to determine consumers’ participation intention and purchasing intention towards a company’s philanthropic activities. Moreover, in this study the role of trust and vicarious licensing as moderating variables was also investigated. The model which has been proposed for this research study was examined in the context of an anonymous company performing certain philanthropic activities for the well-being of society and its residents. The practical and theoretical implications for this study are discussed below:

5.1. Philanthropy and Open Innovation

Open innovation promotes collaboration with people and organizations outside the company [54]. Open innovation has the great virtue of freedom [55]. In the past few decades, the emergence of open innovation as a phenomenon has dramatically increased [56]. Recently, some companies are following a new trend of open innovation in philanthropy. A significant minority of funders are working to explore new ideas, to adopt new methods, and act in the most accountable ways to receive their grants. As a result, it is now possible to see how philanthropy may become a lot more data-driven and a better learning area [55].

There are various ways of interrelating philanthropy and open innovation. For example, a company can be involved in alleviating poverty by doing philanthropy. Philanthropy and innovation together may generate business models which will give access to reasonably priced products or services and ultimately solve their problems. Philanthropy seems to have the most modest societal benefits [57]. Open innovation leads to the development and maintenance of successful business models [58].

5.2. Reciprocity and Open Innovation

The main belief behind this study is the degree up to which a person feels indebted or responsible to pay back the kindness they receive (i.e., reciprocity). So, it (reciprocity) is described as the mechanism of CP which increases a consumer’s behavior. Moreover, the outcome of this research study also confirms the significant and positive impact of reciprocity on consumer behavior. These results show that philanthropic activities conducted by companies for the benefit of their society could also improve a company’s bottom line or at least build a positive reputation for its consumers. This is in line with the findings by Mark and Carrolyn [29] that people who receive favor or kind behavior from others show reciprocity and display helpful behavior in society. In the same way, Dahl and Honea [59] also found similar results in their study, as they proposed that the person who receives any kind of favor or positive action feels a sense of obligation or indebtedness which can only be reduced by showing reciprocity. A company’s collaboration with its customers also results in open innovation [56]. Monika [56] further stated that a customer’s participation in the open innovation process increases with the level of innovation openness in the firm. During the innovation process, customers actively take part in new products’ innovation [60].

Kuthan and Hutter [61] highlighted an interesting relationship between reciprocity and open innovation. They considered that reciprocity should be a substantial behavioral element of innovation. Their research has also evolved the theory of cooperation by elaborating a relation between reciprocity and open innovation. Researchers have also shown that not only open innovation, but also the user innovation lead to social and economic development [58,62].

In this study, how participation intention acts as a mediator in the path from reciprocity to purchasing intention was also examined. The results of this study showed that the more a consumer is willing to participate in a company’s philanthropic activities, the more he/she is willing to purchase the products of the company. In this way, a consumer’s perception is developed that he is an agent supporting company’s philanthropy and in enhancing its business mission. As a result, the in-group identification of the consumer with the company is enhanced [63]. This ultimately leads to the consumers’ stronger willingness to support philanthropic activities of a company by purchasing its products. Similar propositions have been made by [64], as they suggested that consumers will more strongly support the market offerings of firms which are involved in CP. Although it is generally presented by companies that philanthropic activities are carried out without any monetary benefits, somehow these activities result in the improvement of a company’s bottom line.

This study also identifies other variables, such as trust and vicarious licensing, which could affect the strength of the relationship between consumers’ patronage behavior and reciprocity. Firstly, we have discussed the effect of trust on the strength of the relationship. Results shown in Table 7 and Table 8 tell us that trust increases the strength of the relation within reciprocity and patronage behavior. This is in line with the findings by Park [11], and Forehand and Grier [32]. They stated that philanthropic activities conducted by a company will generate more results if the consumer places trust in a company. Finally, this study also identified that vicarious licensing decreased the obligation of the consumer to return kindness. Consequently, the effect of reciprocity on consumers’ patronage behavior will decrease, i.e., both participation intention and purchasing intention as shown in Table 9 and Table 10. The same proposition was made by Kouchaki [36] in his research: The effect of licensing is not restricted to an individual’s own performance. When a person sees others behaving more ethically on his behalf, this will lead a customer to behave less ethically.

6. Conclusions

6.1. Implication

The results of this research highlight that philanthropy plays a vital role in the improvement of society. If a company is more actively working for the welfare of a particular society, the more favorable opinions are generated about that company by the consumers. This study also recommends that if companies develop trust in its consumers, then the relation between reciprocity and consumer behavior is also enhanced. Goodwill develops trust, and trust attracts more consumers towards a company. The goal of any company is to maximize its sales and profit, no matter how much they beat about the bush. Here is where CP’s importance lies. For the researchers, this study will help them to uncover the effect of certain moderating variables (such as trust) that many researchers were not able to explore. Thus, an enhanced conceptual framework can be developed.

6.2. Limitations and Future Recommendations

This study was useful in the context that how CP effects consumer’s patronage behavior. However, there are several limitations in this study. First, it was a cross-sectional study that analyzed data collected from consumers at a specific point in time. Moreover, responses were collected from consumers of a particular geographical area. So the findings of this study did not involve the perceptions of different consumers from different geographical regions. Every consumer was given the same scenario of an anonymous company performing certain philanthropic activities. In the future, instead of using a single scenario, this study can also be conducted by creating different philanthropic scenarios, and the responses of a single consumer towards each scenario can be examined. This study can also be conducted in any other part of the world to analyze how cultural and social values of other countries will affect the results of variables. The conceptual framework of this research can also be enhanced and examined by introducing a couple of more moderating variables. Lastly, future researchers can use time series data instead of cross-sectional data. Since time series analysis corresponds to data in a series of a particular period or interval [65], different seasons can be covered. There are certain times which are associated with peak time of philanthropy and giving like Christmas [66] and Ramazan (holy month of Muslims) [67], and time series analysis will help us study their effects as well.