Understanding the intention to donate online in the Chinese context: The influence of norms and trust
Vol.16,No.1(2022)
Due to the advancement of information and communication technologies, online donations have become unprecedentedly convenient, making money received from individual online donations an important form of revenue for many charitable organizations in China. However, factors contributing to people’s online donation intentions, in turn impacting donating behavior, have been under-examined. The current study aims to understand factors influencing online donation intention in the Chinese cultural context by combining constructs from the extended Theory of Planned Behavior (TPB; including the original TPB constructs and moral norm) and trust-related constructs (i.e., trust in charity organizations and trust in technology). The moderation effect of past donation behavior on the relationship between trust and donation intention was also explored. A total of 721 Chinese participants completed the online survey. SPSS was used to perform hierarchical multiple regressions. The results showed that attitude, perceived behavioral control, moral norm, and subjective norm were all positively related to online donation intention. Moral norm was found to be a stronger predictor than subjective norm, raising the amount of explained variance of the original TPB model. Trust in charity organizations was found to positively predict donation intention while trust in technology was not. The results also revealed that past donation behavior moderated the effect of trust in charity organizations on donation intention. This study not only adds to the body of knowledge on charitable donation in the online context by incorporating two trust-related constructs into the extended TPB model, but also highlights the different roles moral and subjective norms play in predicting people’s prosocial behavior in the context of Chinese culture.
online donation; theory of planned behavior; moral norm; subjective norm; trust; past donation behavior; Chinese online philanthropy
Wu Li
School of Media and Communication, Shanghai Jiao Tong University, Shanghai, China
Wu Li, Ph.D., is a professor at the School of Media and Communication of Shanghai Jiao Tong University, China. His research interests cover new media and media psychology. He recently investigates research topics on psychological effects and social impacts of social media use.
Yuanyi Mao
Department of Media and Communication, City University of Hong Kong, Hong Kong SAR, China
Yuanyi Mao, M.A., is a doctoral student in media and communication at City University of Hong Kong, China. His research interests include human-computer interaction and moral psychology, especially the psychological processes and consequences related to the interaction with emerging technologies.
Cong Liu
School of Media and Communication, Shanghai Jiao Tong University, Shanghai, China
Cong Liu, Ph.D., is an associate professor at the School of Media and Communication of Shanghai Jiao Tong University, China. Her research interest lies in quantitative studies in computer-mediated communication, media psychology, and health communication. This is the corresponding author for the article (lcong26@sjtu.edu.cn).
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First submission received:
August 8, 2020
Revisions received:
August 17, 2021
November 20, 2021
Accepted for publication:
January 3, 2022
Editor in charge:
Michel Walrave
Introduction
The development of information and communication technologies (ICT) has promoted the dissemination of information in healthcare, and made online donation more convenient (Hou et al., 2021). Online donation, which refers to an open call for monetary donations through online platforms, has become an increasingly important channel for both donors and beneficiaries in China (Liu et al., 2018). On the one hand, a majority of Chinese charitable organizations have set up online donation channels on their official websites to attract more potential donors. On the other hand, beneficiaries, also known as donation requesters, usually turn to social media platforms such as Sina Micro charities and Shuidichou for help. According to Chaoxi Gu, the vice minister of the Ministry of Civil Affairs of China, money from individuals online can comprise up to 80% of the total revenue for some charitable organizations (Zhang, 2017).
Despite the advancement opportunities the Internet and social media holds for online donation in China, several serious challenges remain. For instance, although the Internet has become an indispensable channel for nonprofit organizations to run fundraising campaigns (Hooper & Stobart, 2003), there is a digital gap among various charitable organizations in terms of Internet use. Due to their limited knowledge about the Internet and its users, many organizations are not proficient in running successful online fundraising campaigns to maintain or attract more people to participate (Ma & Xie, 2015; Pan, 2017). In recent years, there are more and more online charity projects in China that fail to achieve their financing goals within a stipulated period (Chen et al., 2019). Therefore, it is of vital importance to explore and identify the factors which influence people’s online donation intention and provide practical implications regarding how to encourage and maintain their continued online donations in the future as well.
However, factors predicting people’s online donation intention have been under-examined in previous research. The extant literature on donations mainly focus on the traditional offline context, with the Theory of Planned Behavior model (TBP) used as the main theoretical foundation to identify factors affecting individual donation intention or behaviors (Kashif et al., 2015; Knowles et al., 2012; Smith & McSweeney, 2007; van der Linden, 2011). Amongst the limited published literature that explore factors influencing online donation, most lack theoretical guides such as the TPB model, and few touch on trust towards charitable organizations and Internet technology (Ahn et al., 2018; Sura et al., 2017; Treiblmaier & Pollach, 2006). Furthermore, most charity studies have been conducted in the context of Western countries, with fairy little attention given to Asian countries (Choi et al., 2019; Li et al., 2018).
To fill the research gap, the current study combines constructs from the extended TPB model (i.e., the original TPB components and moral norm) and trust-related constructs (i.e., trust in charity organizations and trust in technology) to develop an integrated conceptual model to predict people’s online donation intention. Moreover, to enrich the extant research on donations which has been limited to Western countries, we conducted the current study using Chinese case and samples. Taking into account the potential impact of collectivistic Chinese culture, we compare the different contributions from two types of norms (i.e., subjective norm and moral norm). Furthermore, in order to address the scarcity of research on online donation, two forms of trust (i.e., trust in charity organization and trust in technology) were incorporated into the extended TPB model to gain a holistic understanding of factors influencing people’s donation in the online context. Beyond that, we explore the moderation effect of past donation behavior on the effect of trust in predicting Chinese intentions to donate online, so as to provide more nuanced knowledge on individual decision-making mechanisms concerning online donations.
Literature Review
Extended Theory of Planned Behavior (TPB)
As one of the most frequently cited theories, the TPB (Ajzen, 1991) has been extensively applied to understand and predict human behavior. In its original formulation, the TPB claims that people’s behavioral intention—the immediate proxy of actual behavior—is jointly determined by attitude, subjective norm, and perceived behavioral control (PBC). Several meta-analyses identified that the TPB generally explains about 40% to 50% of the variance in behavioral intention (Armitage & Conner, 2001; Sutton, 1998). To better understand human behavior, especially prosocial behavior, moral norm was incorporated into the original TPB model. A meta-analysis revealed that moral norm predicted an additional 4% of the variance in donation intention after controlling for the original TPB variables (Conner & Armitage, 1998).
Unlike attitude and PBC in the TPB model, subjective norm’s contribution to the TPB model has been debated among researchers, especially when in combination with moral norm in the extended TPB. To some extent, the contributions of subjective and moral norms may largely depend on specific contexts such as the different cultural backgrounds of respondents. Distinguished from that of Western countries, the value of philanthropic giving in China is deeply rooted in Confucian ethics and collectivistic cultural values (Zhou & Zeng, 2006). Therefore, it is necessary to examine the influences of different norms on Chinese prosocial behavior, considering extant studies were mainly conducted among Western people.
Attitude and PBC
According to Ajzen (1991), attitude refers to the degree to which a person has a favorable or unfavorable evaluation of a certain behavior, and PBC concerns the perceived ease or difficulty of performing the behavior. These two variables were repeatedly confirmed to have a consistently positive effect on people’s intention in different types of donation contexts, such as blood donation (France et al., 2014), organ donation (Rocheleau, 2013), and monetary donation (Kashif et al., 2015; Kashif & De Run, 2015; Knowles et al., 2012; Oosterhof & Peters, 2009; Smith & McSweeney, 2007; van der Linden, 2011). In the case of monetary donation, a more recent study among 432 Saudi participants (Veludo-de-Oliveira et al., 2017), attitude and PBC were also found to be significant factors positively influencing individuals’ intention to give monetary donations.
When it comes to online donation, there are at least two crucial differences that distinguish it from offline donations: more potential risks and greater anonymity (Gefen et al., 2003; Postmes et al., 2001). It is thereby necessary to examine whether the effect of attitude and PBC on offline donation would still hold true in the online context. Thus, we hypothesize the following:
H1: Attitude positively predicts individuals’ intention to donate online.
H2: PBC positively predicts individuals’ intention to donate online.
Subjective Norm Versus Moral Norm
Subjective norm emphasizes the perceived social pressure to perform or not to perform a behavior (Ajzen, 1991), whereas moral norm refers to the individual’s personal belief about what is inherently right or wrong to do (Parker et al., 1995). Despite the similarity of subjective norm and moral norm, the two constructs are distinct from several theoretical perspectives.
First, self-determination theory posits that there are two types of motivation, namely, internal (or autonomous) motivation and external (or controlled) motivation (Ryan et al., 1996). By and large, moral norms can be considered an internal motivation, where an individual’s behavioral decisions are self-chosen and completely originate from themselves. In contrast, subjective norms can be regarded as an external motivation, where individuals perform behaviors based on the potential social benefits and consequences from significant others (Sheeran et al., 1999). Second, according to theories on social learning, individuals usually acquire moral standards through interactions with social reference groups and choose certain norms as their own value principles and expectations that guide their behaviors (Krebs & Janicki, 2004; van der Linden, 2011). Although moral norms may have their origin in social or group norms, once becoming internalized and autonomous, they exert influence on an individual’s feelings, intentions, and behaviors independently from social contexts (Manstead, 2000). In short, moral norm focuses on the individual’s intrinsic moral responsibilities, whereas subjective norm resorts to extrinsic motives, such as rewards or punishment from social groups.
Many prominent social-psychological theories are based on the premise that moral norms are the main driver behind prosocial behavior. For instance, both the Norm-Activation Model (Schwartz, 1977) and the Value-Belief Norm (Stern et al., 1999) propose that feelings of personal obligation and moral responsibility lead to the formation of prosocial behavior. To date, support for the use of moral norms in predicting prosocial behavior has been widespread (see Manstead, 2000, for a review). Indeed, the findings of previous studies indicate that moral norms result in the behavioral intention to engage in such prosocial behaviors as donating and volunteering (Burgoyne et al., 2005; Warburton & Terry, 2000). Developing further, some researchers argued that the inclusion of moral norms can even crowd out the significance of subjective norms (e.g., Kurland, 1995). This argument was also well empirically supported. When entering these two types of norms into the same model, studies conducted by van der Linden (2011) in European countries and Knowles et al. (2012) in Australia revealed that moral norm is a powerful predictor of donating intentions while social norm does not play a significant role in the formation of charitable intent.
However, considering the fact that the extant studies were mainly conducted in the context of Western countries, we argued that subject norm cannot be ignored when examining Chinese prosocial behavioral intention due to cultural differences. One of the most frequently documented individual traits is a person’s cultural orientation, which is defined as patterns of assumptions, beliefs, and perceptions that drive people’s attitudes and behavior in society (Hofstede et al., 2010). Among various cultural factors, individualism and collectivism are probably the most useful constructs to assess culture in different countries or areas. Individualism emphasizes self-reliance and places more importance on personal attitudes than on social norms, whereas collectivism emphasizes interdependence and places more importance on social norms than personal attitudes (Triandis & Gelfand, 1998). According to the social norm theory (Schwartz, 1977), people’ performance of prosocial behavior, to some extent, are driven by social norms (such as helping people in need) which are approved, shared and expected by the group or the society. At the same time, prior research indicates that people with a collectivistic orientation have a greater susceptibility to interpersonal influences (Bearden et al., 1989), and are more likely to obey social norms compared to those from Western individualistic societies (Fischer et al., 2009).
Several observations were yielded from the above literature review on the contribution of moral norms and subjective norms in predicting prosocial behavior. On the one hand, moral norm plays an important role in the formation of charitable intentions and adds to the explanatory power of the original TPB model as an independent predictor. On the other hand, the role of subjective norm may vary across cultural contexts. Due to their collectivistic cultural orientation, the prosocial behavioral intention of Chinese people may be positively predicted by subjective norms even when combined with moral norms. In sum, we propose the following three hypotheses:
H3: Subjective norm positively predicts individuals’ intention to donate online among Chinese participants.
H4: Moral norm positively predicts individuals’ intention to donate online among Chinese participants.
H5: Moral norm makes a unique contribution to the original TPB, that is, moral norm significantly increases online donation intention after controlling for the effect of the original TPB variables (i.e., attitude, PBC, and subjective norm).
Trust
Trust is a psychological state that accepts vulnerability based upon positive expectations of the intention or behavior of another (Rousseau et al., 1998). McKnight et al. (2002) extended the concept of trust into the
e-commerce context, and it was divided into trust in vendors and trust in technology (Pavlou, 2003; Siau & Shen, 2003). Similarly, in the context of online government or e-government, researchers conceptualized e-government trust as the trust of the government and technology (Bélanger & Carter, 2008; Teo et al., 2008). In line with the above classifications of trust, Treiblmaier and Pollach (2006) proposed a new framework by claiming that people’s trust in an organization and the Internet would have a bearing on their general attitudes and intention to donate online. We adopt this framework and the classification of trust in our study— that is, trust in charity organizations and trust in (the Internet) technology.
Trust in Charity Organizations
Trust in charity organizations refers to donor perception of the beneficial attributes of charitable service providers (Bélanger & Carter, 2008), such as competence, benevolence, and integrity (Bhattacherjee, 2002). These attributes are key antecedent factors in building initial user trust towards online commercial vendors, which, in turn, affect their transaction intentions (Lu et al., 2016). In the context of donation, Tonkiss and Passey (1999) argued that the extent to which potential donors trust charity organizations are driven by their perception of how wisely an organization has used their donations in the past, an assertion strongly supported by several empirical studies. For instance, Sargeant et al. (2006) analyzed perceptual determinants that influence individual nonprofit giving behavior, and their results showed that trust in charity organizations determined people’s commitment to the organizations, which stimulated their giving behavior. Furthermore, Shier and Handy (2012) found that there was a significantly positive relationship between people’s trust towards nonprofit organizations and their willingness to donate online.
In addition to the findings of the empirical studies mentioned above, we also argue that trust in charity organizations plays an important role in predicting Chinese people’s intention to donate online for two other reasons. First, public trust in charity organizations has been under great pressure in the last decade due to a number of scandals. The media has uncovered several well-known charities, such as the Red Cross of China and the China Youth Development Foundation, misusing their donations (Bannister, 2013; Wang, 2011). These scandals have had a major influence on public trust towards the organizations involved (Y. Yang et al., 2016), decreasing Chinese people’s donation intentions. Second, in line with the tradition of Confucian culture and the moral system, philanthropy in China has been greatly influenced by “familism” (Y. Yang et al., 2020). As a result, when making the donation decisions, Chinese people are inclined to trust those who have a personal relationship (kinship or quasi kinship) rather than strangers, in contrast to the spirit of the “stranger ethic” of modern Western philanthropy (Weber & Gerth, 1953). Given that, in most cases, online donors are not familiar with the recipients, the role of charity organizations is particularly important since they function as a base on which donors can build their trust, especially in the context of collectivist Chinese culture. In light of the above discussion, we propose the sixth hypothesis:
H6: Trust in charity organizations positively predicts individuals’ intention to donate online.
Trust in Technology
Trust in technology is the extent to which the donors trust the competence and security of the Internet (Teo et al., 2008). Although the speed and the convenience of payment transactions over the Internet may seem appealing to the donors, the nature of the medium has potential negative ramifications that could deter them from donating online. In the e-service environment, users may feel threatened by potential risks—such as intangible service providers, loss of money, transaction security, and the leaking of personal information (Gefen et al., 2003; Yousafzai et al., 2003) which, in turn, could make them reluctant to complete e-commerce transactions or even reject using e-services (Kuisma et al., 2007). Among the scarce studies about online donation, Treiblmaier and Pollach (2006) argued that besides trust in charity organizations, trust in Internet technology was another major factor determining people’s intention to donate online. An empirical study by Sura et al. (2017) concluded that Internet technology significantly influenced users’ general attitude toward online donation.
According to McCole et al. (2010) and Yousafzai et al. (2003), security and privacy are the major barriers for people to build trust in an online transaction. However, being members of a collectivist society where people’s self-image is largely defined in terms of “we” rather than “I” (Hofstede et al., 2010), Chinese people are less concerned about privacy issues compared with their Western counterparts. As shown in Rose et al.’s (2014) survey of 10,000 consumers from different countries, the percentage of Chinese who are cautious about the possible leaking of personal information on the Internet is only 50%, which is largely below the global average (76%). In addition, online payment technology in China is very mature, deeply penetrating the daily life of Chinese people. Unlike in earlier stages where only after evaluating the risks of online payment would users start to build up their confidence towards the new technology, Chinese internet users nowadays are much more familiar with online payment and already place a higher degree of trust in it (Q. Yang et al., 2015). Therefore, we are curious whether trust in technology still plays a significant role in predicting Chinese intention to donate online, and propose the following hypothesis:
H7: Trust in technology positively predicts individuals’ intention to donate online.
Moderation Effect of Past Donation Behavior on Trust
Research revealed that perceived uncertainty creates a need for trust-based interaction (Kramer, 2001). In the context of online consumption, trust was found to be an important factor that is capable of deceasing people’s uncertainty (such as perceived information asymmetry, fears of seller opportunism, and information security concerns), which in turn, increase consumers’ purchasing intention (Kramer, 2001; Pavlou et al., 2007). Furthermore, existing studies also showed that previous online shopping experience further promotes people’s intention to purchase online in the future (Pavlou, et al., 2007). In specific, the accumulated online-shopping experience will help reduce the perceived uncertainty about the vendors and increase future purchase intention and behaviors (Grabner-Kräuter, 2004; Park & Stoel, 2005).
In other words, trust and past behavior are two important factors that alleviate uncertainty and promote online purchasing. Therefore, for the consumers who lack previous purchasing experience, their future intention to purchase online would be largely determined by their trust in the online platform and the vendor. Similarly, compared to those who have already experienced online donation, it is plausible that people without past online donating experience will rely more heavily on their trust in the charity organization as well as their trust in technology when making the decisions to donate online. Based on the above, it is hypothesized that:
H8a: The influence of trust in charity organizations on intention to donate online is moderated by past donation behavior.
H8b: The influence of trust in technology on intention to donate online is moderated by past donation behavior.
Based on the above hypotheses, the conceptual framework of this study is depicted in Figure 1.
Figure 1. Research Conceptual Model.
Method
Participants and Procedures
The target population of this study is Chinese Internet users, including those who have no experience with online donation and those who have already engaged in online monetary donation activities. An online survey method was adopted for the present study. The pre-test with a convenience sample of 83 users showed that all the core constructs achieved a satisfactory reliability score (all above .80). Principal component analysis of the seven key variables was conducted using SPSS 23.0. Seven factors were extracted with varimax rotation. The cutoff factor loading score was 0.50. Results showed that the items clearly loaded to the seven constructs and the total variance explained by the seven factors was 87.14%.
Then, the formal online survey was released on WenJuanXing, the most widely used online questionnaire platform in China, in September 2019. The survey link was posted and distributed on the most popular Chinese social network sites, such as Baidu Tieba and Tencent Weibo. At the beginning of the questionnaire, a screening question was used to filter out ineligible respondents who were under 18 years old, as the target group of this study is adults with disposable income.
Table 1. Participants’ Demographic Profiles and Past Donating Behaviors (n = 721).
Gender |
|
Male |
272 (37.7%) |
Female |
449 (62.3%) |
Age |
|
18–25 |
336 (46.6%) |
26–35 |
181 (25.1%) |
36–45 |
142 (19.7%) |
46–55 |
62 (8.6%) |
Education level |
|
Below Undergraduate |
102 (14.7%) |
Undergraduate |
439 (60.5%) |
Graduate |
180 (24.8%) |
Religious affiliation |
|
No |
580 (80.4%) |
Yes |
141 (19.6%) |
Disposable monthly income (in RMB) |
|
≤1800 |
195 (27.0%) |
1801–3000 |
116 (16.1%) |
3001–5000 |
139 (19.3%) |
5001–8000 |
118 (16.4%) |
8001–12000 |
64 (8.9%) |
≥12001 |
89 (12.3%) |
Past donating behaviors |
|
No |
387 (53.4%) |
Yes |
338 (46.6%) |
Payment channels (among those who had past donating behaviors) |
|
Alipay |
218 (65.3%) |
|
218 (65.3%) |
Online Banking |
42 (12.6%) |
Fast payment with bank cards |
24 (7.2%) |
Other |
28 (8.4%) |
Amount of money donated (in RMB; among those who had past donating behaviors) |
|
<10 |
70 (20.0%) |
11–50 |
142 (42.5%) |
51–99 |
61 (18.3%) |
100–200 |
47 (14.1%) |
>200 |
14 (4.2%) |
Note. Payment channels and the amount of money donated were calculated among the experienced donors (n = 334). |
A total of 721 valid respondents participated in this survey over four weeks. Statisticians have suggested that a researcher would have better power (0.8) to detect a small effect size with approximately 30 participants per variable for regression equations using six or more predictors, if the circumstances allow (Cohen & Cohen, 1975; Wilson et al., 2007). In this study, 14 predictors were included in the regression model, so a minimum sample size of 420 is required to achieve a power of 0.8. Therefore, we can claim that the sample size of 721 yields enough power to draw reliable inferences from the performed hierarchical regression analysis.
As is shown in Table 1, among the 721 respondents, the majority were female (62.3%), young (71.7%; between 18 and 35), had or were pursuing a bachelor’s degree (60.5%), and had no religious affiliation (80.4%). About 62.4% reported that they had less than 5000 yuan of monthly disposable income. Nearly half of the participants (46.3%) responded that they had previous online donation experience. Among these experienced donors, more than half used Alipay (65.3%) and WeChat (65.3%) as payment channels. When being asked the total amount he/she had donated online in the past three months, 42.5% of the respondents reported to have donated 11–50 Yuan while 20.0% have donated less than 10 Yuan and 36.6% have donated more than 50 Yuan.
Measures
Dependent Variable
To measure behavioral intention, participants were asked to self-report on a 5-point scale (1 = strongly disagree, 5 = strongly agree) with two items regarding their intention to donate online in the next three months. Cronbach’s alpha of this scale was 0.90.
Independent Variables
The independent variables included the original TPB variables (i.e., attitude to online donation, PBC, and subjective norm), one extended TPB variable (i.e., moral norm), and trust (including trust in charity organizations and trust in technology). Attitude towards online donation was assessed with a semantic differential scale (e.g., 1 bad – 5 good, 1 unpleasant – 5 pleasant, 1 worthless – 5 valuable), while other constructs were measured on 5-point Likert scales (1 = strongly disagree to 5 = strongly agree). All the scales obtained high reliabilities (Cronbach’s Alphas ranged from 0.83 to 0.91).
Moderator Variable
Past donation behavior was treated as a moderator between the variables of trust and the dependent variable. It is a single item question (Have you ever donated online before?), and participants were asked to choose Yes or No.
Detailed items, statistics, and sources of all constructs are shown in Table 2.
Table 2. Construct Scales, Cronbach’s Alphas and Sources.
Measures |
α |
Source |
Attitude to online donation |
.91 |
Ajzen (2002) |
I believe that participation in online donation would be bad – good |
||
I believe that participation in online donation would be unpleasant – pleasant |
||
I believe that participation in online donation would be worthless – valuable |
||
Perceived behavioral control (PBC) |
.83 |
Ajzen (2002) |
It is entirely up to me whether I participate in online donation or not |
||
I am confident that I am able to easily use the technologies involved when donating online |
||
The money required for online donation is affordable for me |
||
Overall speaking, donating online is completely within my control |
||
Subjective norm |
.86 |
Ajzen (2002); Smith and McSweeney (2007) |
People closest to me think that I should participate in online donation |
||
People who are important to me think that I should participate in online donation |
||
Moral norm |
.87 |
|
I am the kind of person who donates money online |
|
|
I would feel guilty if I didn’t participate in online donation |
|
|
I believe I have a moral obligation to donate money online |
|
|
Not participating in online donation goes against my principles |
|
|
Trust in charity organizations |
.91 |
Sargeant et al. (2006) |
I would trust the charity organizations to always act in the best interest of the causes |
|
|
I would trust the charity organization to use donated funds appropriately |
|
|
I would trust the charity organization to use fundraising techniques that are appropriate and sensitive |
|
|
Trust in technology |
.81 |
Bélanger and Carter (2008); Teo et al. (2008) |
The technology has enough safeguards to make me feel comfortable using platform to transact personal information |
|
|
I feel assured that legal and technological structures adequately protect me from problems that could arise from the transaction |
|
|
Behavioral intention |
.90 |
Ajzen (2002) |
I intend to donate money online in the next three months |
|
|
I plan to donate money online in the next three months |
|
|
Results
Before performing the hierarchical multiple regression, we conducted the Pearson correlation analysis on all the key constructs in our study. As Table 3 shows, behavioral intention was positively and significantly correlated with other independent variables, except trust in technology. The correlation coefficients amongst the independent variables and the moderator were between 0.10 and 0.60, suggesting that all the variables are suitable to be entered into the same regression model.
Table 3. Pearson Correlation Matrix and Descriptive Statistics on All Measured Variables.
Variables |
M |
SD |
1 |
2 |
3 |
4 |
5 |
6 |
7 |
1. Attitude |
3.74 |
0.79 |
1 |
|
|||||
2. PBC |
3.84 |
0.65 |
.34** |
1 |
|
||||
3. Subjective norm |
3.14 |
0.76 |
.44** |
.17** |
1 |
|
|||
4. Moral norm |
3.10 |
0.83 |
.50** |
.17** |
.59** |
1 |
|
||
5. Trust in charity organizations |
2.03 |
0.82 |
−.07 |
−.25** |
.04 |
−.01 |
1 |
|
|
6. Trust in technology |
2.47 |
0.90 |
.03 |
−.03 |
−.01 |
.02 |
.57** |
1 |
|
7. Behavioral intention |
3.31 |
0.90 |
.56** |
.34** |
.48** |
.59** |
.05 |
.10** |
1 |
8. Past donation behaviora |
0.46 |
0.50 |
.24** |
.27** |
.19** |
.26** |
.12** |
.16** |
.48** |
Note. **p < .01; N = 721. a 0 = no, 1 = yes. |
Hierarchical multiple regression was conducted to examine the influence of the original TPB variables, moral norm, and two types of trusts on individuals’ intention to donate online in the future. Specifically, demographics (i.e., gender, age, education, income, and religious affiliation) were entered into the first block as control variables, the variables of the original TPB model (i.e., attitude to online donation, PBC, and subjective norm) were entered into the second block, moral norm was entered into the third block, and two trust-related variables, past behavior, and their interaction terms were entered into the fourth block. We standardized the variables of trust in charity organizations, trust in technology, and past behavior, multiplied the corresponding standardized values to create the interaction terms, and then added these new variables to the last block of regression model. The results of the regression analysis for each block were summarized in Table 4, and only the coefficients for the variables that were first entered to the model were presented.
As Table 4 shows, demographic variables accounted for 6.1% of the variance in the intention to donate in the future. Among them, gender (β = .077, p = .039), educational level (β = .080, p = .035), monthly disposable income (β = .126, p = .007), and religious affiliation (β = .138, p < .001) were the significant predictors. However, age had no significant impact on their intention to donate online (β = .067, p = .134). That is, the results indicated that participants of male gender, higher educational level, higher monthly disposable income, and those with religious affiliations were more likely to donate online than their counterparts.
In the second block, attitude (β = .373, p < .001), PBC (β = .150, p < .001) and subjective norm (β = .271, p < .001) were significantly and positively related to the intention to donate online after controlling for the effect of the demographic variables. Thus, H1, H2 and H3 were supported.
In the third block, moral norm (β = .348, p < .001) was found to be a significant predictor of intention to donate online. Furthermore, three variables in the original TPB model jointly explained 36.4% of the variance in people’s intention, and the addition of moral norm significantly increased the variance explained (ΔR2 = 6.8%, ΔF = 96.18, p < .001). H4 and H5, therefore, were also supported.
Results of the last block showed that trust in charity organizations (β = .067, p = .039) positively predicted people’s donating intention, whereas trust in technology did not have any significant effect on their intention to donate online (β = .010, p = .754), after controlling for all the variables in the above blocks. Regarding the moderation effect of past behavior, the interaction term of trust in charity organizations and past behavior (β = −.066, p = .031) negatively and significantly predicated people’s donating intention. In contrast, the interaction term of trust in technology and past behavior (β = .008, p = .782) did not predicate their intention. Hence, H6 and H8a were supported, yet neither H7 nor H8b was supported.
Table 4. Hierarchical Regression Predicting Online Donating Intention.
Predictor |
∆R2 |
β |
p |
95% CI |
Demographics (in Block 1) |
.061 |
|
|
|
Gendera |
.077 |
.039 |
[.007, .277] |
|
Age |
.067 |
.134 |
[−.019, .139] |
|
Education |
|
.080 |
.035 |
[.006, .174] |
Disposable monthly income |
.126 |
.007 |
[.018, .115] |
|
Religious affiliationb |
|
.138 |
< .001 |
[.146, .478] |
Original TPB (in Block 2) |
.364 |
|
|
|
Attitude |
.373 |
< .001 |
[.349, .499] |
|
PBC |
.150 |
< .001 |
[.124, .290] |
|
Subjective norm |
.271 |
< .001 |
[.245, .395] |
|
Extended Variable (in Block 3) |
.068 |
|
|
|
Moral norm |
.348 |
< .001 |
[.300, .450] |
|
Trust and Past Behavior (in Block 4) |
.073 |
|
|
|
Trust in charity organizations |
.067 |
.039 |
[.003, .118] |
|
Trust in technology |
.010 |
.754 |
[−.046, .063] |
|
Past donation behavior |
|
.266 |
< .001 |
[.190, .288] |
Trust in charity organizations × past behavior |
|
−.066 |
.031 |
[−.113, −.005] |
Trust in technology × past behavior |
|
.008 |
.782 |
[−.047, .062] |
Total Adjusted R2 |
.558 |
|
|
|
Note. N = 721; a 0 = male, 1 = female; b 0 = no, 1 = yes; all the coefficients were standardized. |
In sum, the influence of the extended TPB variables (original TPB variables with moral norm) and the trust-related variables of online donation intention, as well as the moderation effect of past donation behavior, is depicted in Figure 2.
Figure 2. Influence of TPB Variables, Two Types of Trust, and the Moderation Effect of Past Behavior on Online Donation Intention.
Note. *p < .05, **p < .01; ***p < .001.
To illustrate the moderation effect of past donation behavior and trust in charity organizations on individuals’ intention to donate online, post-hoc simple slope tests were conducted and the interactive effects were plotted. The simple slope tests indicated that trust in charity organization was positively related to intention to donate online (slope = 0.136, p = .004, 95% CI [0.044, 0.227]) for people without previous donation experience, whereas it had no significant effect on online donation intention (slope = 0.002, p = .969, 95% CI [−0.084, −0.087]) for those with donation experiences. See Figure 3 for the illustrations for the simple slope tests.
Figure 3. Relationship Between Trust in Charity Organizations and Behavioral Intention Among People With and Without Past Donating Experience.
Discussion
Drawing upon the extended TPB and trust-related constructs, this study empirically explored the factors affecting Chinese people’s intention to donate online. The results showed that attitude, PBC, subjective norm, and moral norm were positively related to intent to donate online. Particularly, moral norm was found to be a more important factor than subjective norm in predicting intentions to donate online among respondents. Trust in charity organizations was found to positively predict donation intention, while trust in technology was not. The results also revealed that past donation experience moderated the effects of trust in charity organizations on individuals’ intention to donate online. People with no donation experience tended to rely more on their trust in the organizations compared to those who had donated before.
Contributions of Moral Norm and its Comparisons to Subjective Norm
In line with the previous studies (e.g., Bamberg & Möser, 2007; Conner & Armitage, 1998), the present study confirmed that moral norm significantly influences people’s intention to donate online and increased the amount of explained variance of the original TPB model in predicting people’s behavioral intentions. Also, this study revealed that moral norm was a stronger predictor in explaining people’s intention to donate online compared to subjective norm. These results could be explained by the fact that monetary donation is a typical prosocial behavior, which is mainly driven by people’s intrinsic moral responsibilities rather than the rewards or punishment from social groups. In other words, online donation could be regarded as a prosocial behavior that is much more morally loaded than merely being promoted by one’s social/group identity. Another possible explanation for this finding is the context of online channels. Different from the traditional offline donation behaviors featuring high visibility and group membership (Christian & Abrams, 2003; Davies et al., 2002), online donation is usually conducted by Internet users in relatively private or invisible settings. In such cases, the absence of pressure from social expectations and group membership weakens the impact of subjective norm to some extent.
Nevertheless, departing from previous findings which showed subjective norm did not yield significant influence when moral norm was included simultaneously as a predictor (Knowles et al., 2012; van der Linden, 2011), our study indicates that subjective norm is still significant even after the inclusion of moral norm. This conflicting finding may originate from the cultural differences between Chinese and Western people, as we argued previously. Due to their collectivist cultural background, Chinese people highly value being part of a social circuit and take responsibility for the actions and behaviors of people within their group (Hofstede et al., 2010). According to Fischer et al. (2009), individuals within a collectivistic culture are also more strongly guided by group norms, duties, and obligations, in contrast to those who have grown up in an individualistic culture. In this sense, although the influence of subjective norm is weakened in combination with moral norm, it is still a significant predictor of online donation considering the collectivistic mindset of Chinese participants. In addition, there is another explanation for the reason why subjective norm still matters when controlling for moral norm. As a special form of online transaction, online donation involves potential risks (Gefen et al., 2003; Yousafzai et al., 2003), people thereby are inclined to refer to others’ behavior for guidance. Thus, the more they think others engage in online donation, the more likely they are to take the same action.
Influences of Trust in Charity Organizations and Trust in Technology
First of all, the findings show that trust in charity organizations does significantly predict the donation intention but the effect only exists among people who have never donated online before. The non-significant effect of trust in charity organizations among those with past donation experience can be attributed to the transparency and accessibility of information provided by online donation platforms. Compared with the donors in the offline environment, online donors can easily access the status of the donation progress and the distribution of the collected money, which could help to largely reduce their concerns about monetary abuse. In addition, as previous studies have indicated, trust can be obtained and developed gradually over time based on positive outcomes from repeated behaviors (Chiu et al., 2012; Hsu et al., 2007). Consequently, when people donate online and have a positive experience, such as the easy accessibility of information and timely feedback, their perceived uncertainty is reduced, which weakens the impact of trust in charity organizations on future donation intention. That is, trust in charity organizations is no longer a predominant cause of changes in donation intentions for people who have experienced positive online donations.
Another finding on trust worth discussing is the non-significant effect of trust in technology. This result is inconsistent with Sura et al.’s (2017) research which showed that only factors related to Internet technology (other than charity organizations) influenced people’s general attitude toward online donations. As mentioned before, Chinese people usually have a weaker sense of privacy due to their collectivistic orientation and are trusting of online payment methods because of the technology’s maturity in China. These are the possible explanations of the discrepancy between our findings and the previous research results. To be specific, trust in technology is no longer a significant determinant of the online donation intention of Chinese participants due to low levels of privacy concern and the low levels of uncertainty in online payment technologies. Another possible reason why trust in technology was not a significant predictor of intention to donate online is that most scandals in China about online donation (at least those exposed to the public) were caused by the bad management of organizations instead of technology (Bannister, 2013; Wang, 2011). Hence, Chinese people may be less cautious of technology than they are of organizations when it comes to their decision-making of online donation.
Implications and Limitations
Combining the extended TPB model with the trust perspective, the current study sheds light on factors related to Chinese participants’ intentions to donate online. It adds to the body of knowledge on charitable donation in the online context by incorporating two forms of trust into the extended TPB model, and highlights the different contributions of two types of norms in predicting people’s prosocial behavior within the Chinese cultural background. Furthermore, findings on the moderation effect of past donation behavior on trust provides us a deeper understanding of Chinese people’s decision-making process when making online donations.
Apart from its theoretical contributions, this study also provides some practical implications regarding how to increase individuals’ willingness to donate online. For instance, given the importance of moral norm in predicting people’s donating intention, it is of vital importance to show moral recognition for online donation and foster people’s sense of personal responsibility to participate in the charitable activity. Meanwhile, since subjective norm was still found to be a significant predictor after controlling for moral norm, it is also necessary therefore to encourage online donors to share their charitable giving behaviors on social media which can provide a source of invisible social pressure for other potential donors (Zhong, 2015).
Beyond that, there are at least two measures that charitable organizations can employ based on the result that trust in charity organizations significantly predicts behavioral intention only among the people without any previous experience of online donation. On the one hand, charitable organizations should always engage themselves in maintaining a positive image and building their credibility among the public. Specifically, besides conducting external audits, which are generally seen as an efficient means of monitoring (Duncan, 2004), organizations can also make full use of Internet technology to make donation activities (including the amount of money collected and use of the money) more transparent to decease potential donors’ concerns of monetary abuse. On the other hand, charitable organizations can initially appeal to donors by allowing them to donate small amounts money, a lower barrier to entry, and help them to get familiar with the online donation process (including its transparency regarding the use of collected money), which will further enhance their trust in charitable organizations and their online donating intention as well.
Despite the above theoretical and practical contributions, this study has several limitations. First, participants in our study may have varying levels of knowledge of different charity organizations and they may have a certain organization in mind when filling the questionnaire. It could be a confounding factor that is not controlled for in the current study. Although the forms of the third-party charitable crowdfunding platforms in China are rich and diverse, those hosted by major Chinese corporations like Alibaba, Tencent, and Sina were reported to account for more than 86% of the total amount of fund-raising on the third-party platforms, which has become the driving force for the development of China’s online donation (China Association of Fundraising Professionals, 2015). These most popular third-party charitable platforms share many aspects in common in terms of their social media nature and the supported projects. In specific, they all rely on the huge user base from social media services, and are most popular in medical projects for vulnerable groups. Thus, it is believed that the evidence provided by this study is still generalizable to the mainstream charitable industry in China. Nevertheless, future studies should also consider including more variables regarding the specific types of channels/platforms and projects when designing their study measures. Second, our study focuses on individuals’ donation intention in the online context as well as the influence of Chinese culture, which offers us an insightful look into factors influencing online donation among Chinese people. However, such a research endeavor, to some extent, also limits the generalizability of the results. Third, considering the intention-behavior gap, longitudinal studies are needed in the future to better link the relationship between predictors and actual online donation behavior. Finally, the potential dynamic relationship between moral norm and subjective norm remained un-examined in our study, which is worthy of being further explored in future studies.
Acknowledgement
This work was supported by the National Social Science Fund of China [19BXW090]. The authors also thank the financial support from Qixing Charitable Communication Research Project [2021-2022-A06].
Conflict of Interest
The Author(s) declare(s) that there is no conflict of interest.
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Copyright © 2022 Wu Li, Yuanyi Mao, and Cong Liu.