Online communities and enhancing customer loyalty in charity fundraising

2018

University of Amsterdam Ayoub Kaddouri

10901779

Master Thesis

Online communities and enhancing

customer loyalty in charity

Table of Contents

3. Hypotheses and research design ... 17

3.1 Hypotheses ...17 3.2 Research design ...18 4. Research results ... 24 4.1 Descriptive statistics ...24 4.2 Variables ...25 4.3 Data screening ...27

4.4 Scale construction and reliability ...28

4.4.1 Customer engagement ... 28

4.4.2 Customer trust ... 29

4.4.3 Customer loyalty ... 30

4.5 Correlation analysis ...30

4.6 Regression analysis ...32

4.7 Structural Equational Modelling ...33

4.8 Hypotheses conclusions ...35

5. Conclusions ... 37

Bibliography ... 41

Appendix 1: Accompanying letter survey ... 44

Appendix II: Questionnaire ... 45

1.

Introduction

The importance of customer loyalty has increased in recent years. Do to fierce competition and well-informed customers, organizations need to give customer loyalty a high priority. According to Kotler (2013) organizations need to customize their customer relation’s strategy in a way that customer loyalty is enhanced (Kotler & Armstrong, 2013).

Until the early years of this century, customer loyalty has been associated with profit organizations. In recent years the importance of customer loyalty for non-profit organizations has been recognized.

According to Sargent & Woodlife (2008) customer loyalty is also important to charity organizations (Sargeant & Woodliffe, 2008). Studies in the U.K. and the U.S. show that attrition rates are an increasing cause of concern in charity. Many organizations lose up to 60% of cash donors after their first donation. A key determinant of customer loyalty in the charity sector is trust (Sargeant, Ford, & West, 2006).

In this thesis the relationship between online communities and customer loyalty in the charity sector will be analysed. An online community is a virtual space where people who share common interest interact with each other (Bagozzi & Dholakia, 2002). Online communities are becoming more important in consumer lives. There is extensive research on the relation between online communities and the influence on consumer behaviour. There is however, and it is relevant, both from an academic and a managerial perspective, little knowledge regarding the influence of online communities on charity fundraising.

1.1 Research question

This paper aims to extend existing literature by studying the element(s) that could positively affect the relationship between online communities and customer loyalty in charity fundraising. In an online community trust plays a role that could enhance customer loyalty. This will be evaluated by answering the following question:

What is the effect of online communities on customer loyalty in charity fundraising?

1.2 Report design

This research report is designed as follows. In chapter 2 the theoretical framework is constructed and the conceptual model is formed. In chapter 3 the hypotheses are formed and the quantitative research design is accounted for. The results of the research are presented in chapter 4. In this chapter the answer is given if the hypotheses are being accepted or rejected. The conclusions of the research are presented in chapter 5.

2.

Theoretical framework

2.1 Online communities

There are three major criteria in order to explain communities, which can found in most of the definitions. The first characteristic is that members of a community tend to come to group together, in physical or virtual spaces around specific interests. The second characteristic is that there has to be some interaction in order to build relationship. The third feature is that community members bond through common characteristics, experiences or values (Jang, Offman, Ko, Koh, & Kim, 2008), (Koh & Kim, 2003).

According to Gusfield (1975) there are two different types of communities. The traditional geographic community and the relational community revolving around member relationships (Gusfield, 1975). Virtual communities can be regarded as relational communities without a physical place to meet. However, members can become attached to these virtual spaces, which eventually can become a substitute for a geographical place.

The term “Online Communities”, as the term “Communities”, comes with multiple definitions. What these definitions have in common is that online communities are regarded as a computer-mediated space. Bagozzi and Dholakia (2002), define virtual communities as follows: “We view virtual communities to be mediated social spaces in the digital environment that allow groups to form and be sustained primarily through on-going communication processes”. A virtual community can

serve as a supplement or substitution to physical communities (Bagozzi & Dholakia, 2002).

According to Bagozzi and Dholakia (2002) communities share several characteristics. 1) Communities often exist around a certain common interest. 2) Members from the community feel a certain belonging to this group, which separates them from other groups. 3) Most communities have written or unwritten rules and habits in expressing themselves. These are so called netiquettes. 4) Unlike traditional media, content is created and published by active participants. This concept is in line with the core concept behind Web 2.0. Web 2.0 applications have shifted online activities from browsing to interacting and contributing. 5) Nonverbal expressions and physical appearance is often filtered out. However, with the continuous technological developments, image supported communication becomes more easy.

Rheingold (2000) argues that although there are resemblances between online (virtual) communities and physical communities, a large difference lies in the way the interaction takes place. Outside the virtual world, people first meet face to face, get to know one another, and possible form relationships. Within online communities, people get to know one another, build relationships, and possible get face to face. Another difference is whether or not participation is voluntary or not. Participation in online communities is often a matter of choice, while in the physical world membership may be imposed by, for example, geographic location (Bagozzi & Dholakia, 2002). For that reason the entry and exit barriers are often

lower for virtual communities, which makes motivating participation more important (Sun, Youn, Wu, & Kuntaraporn, 2006).

The commercial value of online communities to companies and organizations is pointed out by Armstrong & Hagel (Armstrong & Hagel, 2000). Because online communities offer the opportunity to customers to interact with each other as well as with the company, organizations can foster deeper buyer relationships by customizing products and services to meet customers’ demand and interests. Companies for example can base their marketing efforts on what they hear in the community.

Rheingold (2000) states that online communities have a positive effect on trust. Within online communities the interaction is higher than in physical communities. Participants share specific interests and trust each other’s knowledge. Bagozzi & Dholakia point out that participation in online communities is often a matter of choice (Bagozzi & Dholakia, 2002). Sun et al. sees this characteristic as a key element for the highly motivated participation of members (Sun, Youn, Wu, & Kuntaraporn, 2006).

The positive effect of online communities on trust can also be explained using the higher customer engagement in online communities. Ul Islam et al. (2016) link customer engagement to trust and prove the importance of online communities in this process (Ul Islam & Rahman, 2016). According to Ul Islam a proxy for customer engagement is the customer participation in the online community.

From the above it can be stated that online communities have become more and more influential in customers choices. They do also influence directly the customer loyalty. Research by Szmigin et al. (2005) proved that online communities have a positive relation on the bonding of clients and therefore on the loyalty (Szmigin, Canning, & Reppel, 2005). Gummerus et al. researched the ways in which online communities can be used to enhance loyalty (Gummerus, Liljander, Weman, & Philstrom,, 2012). According to that research online communities lead to 3 relationship benefits 1) social benefits, 2) entertainment benefits and 3) economic benefits. Gummerus et al. conclude that the benefits received are determined by the customer engagement and this relation was mediated mainly through social and entertainment benefits.

Fro the literature it can be concluded that online communities influence the customer engagement and trust. Therefore in this research the variables measured are engagement and trust.

2.2 Charity fundraising

Intense competition in the non-profit or charity fundraising market and the near continuous need for charities to acquire new supporters, reactivate lapsed donors and encourage first time donors to make further gifts are leading charities to initiate novel fundraising campaigns. Bennet & Savani (2011) indicate that UK charities focus their activities more and more on virtual communities (Bennet & Savani, 2011). According to Quinton (2012) the use of online social networks by

skills and resources comparing with the ones that uses online communities frequently (Quinton, 2012). Hassay & Peloza (2009) see so-called brand communities as a unique form of relationship that can have a significant impact on charities (Hassay & Peloza, 2009). Waters et. Al (2009) identify a clear distinction for-profit organizations and charities in embracing online communities in their marketing strategy (Waters, Burnett,, Lamm, & Lucas, 2009).

The use of online communities by charities is a relative new phenomenon. Most research concentrates on the use of online communities. One of the aspects that earlier research neglected to study is the effect of online communities on the customer loyalty of charities. This thesis will add value to earlier literature by focusing on the Dutch charity sector and to what degree online communities have enhanced customer loyalty.

2.3 Customer engagement

According to Jacoby and Chestnut (1978), loyalty implies a repurchase of a brand resulting from a positive affinity or feeling of consumers towards the brand or the product (Jacoby & Chestnut, 1978). In this view, consumer loyalty has a cognitive (positive affinity) dimension and a behavioural one (repeating a purchase). It is the behavioural dimension where customer engagement plays a key role. According to Bowden (2014), the only way to achieve loyalty is through a deeper engagement (Bowden, 2009).

Brodie et al. (2011) define customer engagement as “psychological state that occurs by virtue of interactive, cocreative customer experiences with a focal agent/object (for example a brand or a company) (Brodie, Ilic, Juric, & Hollebeek, 2011). According to Brodie et al. customer engagement is a dynamic and interactive process between the customer and the brand or company that co-create value. In this process psychological aspects as well as behavioural participation plays a role. According to Dessart et al. also social aspects play a role (Dessart, Veloutsou, & Morgan-Thomas, 2015).

Fung So et al. (2014) state that customer engagement consists of five dimensions: enthusiasm (1), Attention (2), Absorption (3), Interaction (4) and identification (5) (Fung So, King, & Sparks, 2014).

Wirtz et al. state that online communities play an important role in enhancing consumer engagement (Wirtz, et al., 2013). They argument, that online community engagement will lead to consumer engagement. The online community engagement is determined by; 1) product factors like product involvement and complexity, 2) customer factors like customer expertise and membership duration and 3) situational online community factors like the size, the governance or the valence of the online community.

2.4 Trust

Earlier in this chapter it has been argued that online communities have a positive effect on trust. Ul Islam et al. (2016) links customer engagement to trust and prove the importance of online communities in this process (Ul Islam & Rahman, 2016). An important conclusion of this research is that customer participation in the online communities has a direct effect on customer engagement and customer engagement leads to rise in word of mouth activities. It leads to a higher trust. Ul Islam et al. conclude that customer engagement plays a critical role in relationship building through the reinforcement of positive word of mouth by the actively engaged customer. They advise companies to encourage customer engagement on online communities by providing timely and reliable information and by keeping track of customers’ conversations.

Trust is also a key determinant of customer loyalty. Nguyen et at. (2013) see a direct relation between customer trust and customer loyalty (Nguyen, Leclerc, & LeBlanc, 2013). Customer trust is a condition for customer loyalty.

According to Sargeant et al. (2006) trust is proved to have a predictable value on the level of the donations (Sargeant, Ford, & West, 2006). Trust leads to engagement or loyalty and therefore leads to donations.

Casaló et al. (2007) conclude that trust can be defined by three types of beliefs; competence (1), honesty (2) and benevolence (3) (Casalo, Flavian, & Guinaliu, 2007). They relate competence to the perception of the consumer that the other

party’s knowledge and skills will have a positive effect in satisfying their needs. Casaló et al. define honesty as the belief that the other party will keep their word, fulfil their promises and be sincere. Finally, benevolence is the belief that the other party is willing to make an effort to meet common objectives.

2.5 Loyalty

Jacoby et al. define customer loyalty as the intention to repeat a purchase (Jacoby & Chestnut, 1978). There are many studies that focus on the relationship between customer loyalty and the customer value. There is less research on the correlation between the mentioned variables in the non-profit or more specific the charity sector. Reichheld & Covey (2006) argue that customer loyalty increases the customer value (Reichheld & Covey, 2006). Prove for this relation has been given in numerous studies (Gruen, Osmonbekov, & Czapewski, 2006).

Loyal customers will have a higher value because they tend to repeat purchases and will do that with fewer efforts from the company. It can be argued that the will be less price sensitive. Johnson et al. (1998) argument that trust plays a key determinant in the customer loyalty (Johnson & Auh, 19989). Johnsons’ research has two important conclusions; 1) within a higher trust environment, the inflection point at which customers start drastically reducing their consideration set of alternative brands, occurs on a lower level of satisfaction and 2) within a higher trust environment, customers should move more rapidly from problem solving to routinized behaviour. This means that clients will accept more ‘negative’ aspects from the company.

Recent research by Capgemini Consulting among European telecom companies showed a positive relation between the revenue growth and the client loyalty measured by the NPS (Capgemini Consulting, 2016). This seems logical because it is assumed customer loyalty increases the customer value (Reichheld & Covey, 2006). In chapter 4 the methodology behind the Net Promoter Score will be discussed in detail.

Also Kumar et al. (2007) find word of mouth a key aspect that organizations have to focus upon. The most valuable customers are not the ones that buy the most, but are those whose word of mouth brings in the most profitable new customers, regardless of how much they themselves buy (Kumar, Petersen, & Leone, 2007). According to Kumar et al. the organization should not only focus on the customer lifetime value (CLV) but also on the customers referral value (CRV). The Customer Referral Value is more difficult to measure. The CRV of a customer is calculated using the following formula:

𝐶𝑅𝑉 =𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟𝑠 𝑤ℎ𝑜 𝑗𝑜𝑖𝑛𝑒𝑑 𝑏𝑒𝑐𝑎𝑢𝑠𝑒 𝑜𝑓 𝑟𝑒𝑓𝑒𝑟𝑟𝑎𝑙

𝑑𝑖𝑠𝑐𝑜𝑢𝑛𝑡 𝑟𝑎𝑡𝑒 +

𝑣𝑎𝑙𝑢𝑒 𝑜𝑓 𝑐𝑢𝑠𝑡𝑜𝑚𝑒𝑟𝑠 𝑡ℎ𝑎𝑡 𝑤𝑜𝑢𝑙𝑑 𝑗𝑜𝑖𝑛 𝑎𝑛𝑦𝑤𝑎𝑦 𝑑𝑖𝑠𝑐𝑜𝑢𝑛𝑡 𝑟𝑎𝑡𝑒

The formula consists of two parts. The first one is the value of clients that buy the product or service because of the referral. This part follows the NPS methodology with the important addition that the referral is being valuated. The second part of the formula consists of customers that would buy the product or service also without the referral. The sum of both parts is the CRV of the company.

In the formula the customer value is calculated subtracting the marketing costs from the contribution margin of the client. It can be argued that the value of the

customers who joined because of referral is higher than the value of the customers that joined without the referral. The explanation is that the referral is ‘free’ for the company and the marketing costs are not.

The model of Kumar et al. ads an interesting perspective to the Reichhelds’ theory. Kumar et al. uses the CRV to segment customers in four segments; (1) champions who are excellent buyers and marketers, (2) affluents who buy a lot but don’t market well, (3) advocates who don’t buy a lot but are strong marketers and (4) misers who neither buy much nor market well. Kumar et al. (2007) argument that the organizations need to develop different strategies for all segments except the champions.

The NPS can be used to emphasize the importance of word of mouth. There are important objections to the use of the NPS as a measure for customer loyalty. (1) The method is based on only 1 question and therefore highly simplifies customer loyalty, (2) The model assumes other customers only influence customers. But family, advertisements and own experiences can also influence customers. In other words others also influence customers. According to Reichheld the recommendation question is the best indicator for the intention to repeat a purchase (3) The used answer-scale makes an arbitrary distinction within the three ranges. A customer that answer with 2 is treated the same as a customer that answers 6.

Another way to measure customer loyalty is by measuring the retention. Kotler & Armstrong (2015) denominate retention as one of the core elements of the

marketing sales process (Kotler & Armstrong, 2015) Retention can be defined as the activities and actions companies and organizations take to reduce the number of customer defections. There are numerous ways to measure the retention; percentage of ‘lost clients’, number of orders, number of years of customer relation, etc.

Kumar and Renatz (2006) criticise the retention perspective in customer loyalty. They find retention being part of a defensive strategy. Companies should not focus on ‘keeping the customer’ but on customer relationship management in which the development of the customer relation and therefore customer value plays a central role (Kumar & Reinartz, 2006). It is about adding value to the customer and not maintaining value for as much time possible.

Customer loyalty is also important in the charity sector. Sargeant & Woodlife (2008) emphasises that in order to increase income from donations, charity organizations need to look not only ‘why’ people make donations but also at the of ‘how’ donations are made (Sargeant & Woodliffe, 2008). It is the insight in the decision making process that is central to the understanding of how customers behave.

According to Sargent (2008) donor loyalty is defined by 7 principles: 1) customer service, 2) shared belief, 3) customers are aware of the consequences of their donations, 4) donors are connected to the charity, 5) donors trust the charity, 6) donors are engaged and 7) donors are learning from the charity (Sargeant & Woodliffe, 2008). The seven principles can be divided in the two variables are

central in this research; engagement and trust. The donor engagement (principle 6) can be increased by the 1) customer service, 2) shared belief, 3) customers are aware of the consequences of their donations, 4) donors are connected to the charity, and 5) donors are learning from the charity. The other dimension is principle 5; trust.

The two dimensions have a direct relation with online communities. Therefore it can be argued that online communities will have a positive effect on the loyalty in charity fundraising.

2.6 Conceptual model

The conceptual model assumes that online communities have a positive effect on customer engagement and customer trust and therefore on customer loyalty. As was shown in paragraph 2.3 engagement is the interactive process between the customer and the brand or company that co-create value. In paragraph 2.4 it is stated that there is a link between customer engagement and customer trust. Engagement positively influences trust. Both trust and engagement directly have a positive impact on customer loyalty and therefore this research focuses on these two variables: engagement (1) and trust (2).

Figure 1: conceptual model

Online community Engagement Trust Customer Loyalty

3.

Hypotheses and research design

3.1 Hypotheses

According to the literature members of an online community are highly motivated and interact in order to build relationships. They bond through common characteristics, experiences or values. Through online communities companies or organizations can foster deeper buyer relationships with customers. Therefore the first hypothesis tests the relation between online communities and customer engagement.

H1: Online communities have a positive effect on customer engagement

Numerous research point out that that online communities have a positive effect on customer trust (Casalo, Flavian, & Guinaliu, 2007) (Brodie, Ilic, Juric, & Hollebeek, 2011). The higher customer engagement in online communities has a positive relation with customer trust. In the second hypothesis the relation between online communities and trust is evaluated.

H2: Online communities have a positive effect on trust

As described in the conceptual model and in the literature review it is assumed that customer engagement and customer trust have a positive effect on customer

loyalty. The third hypothesis tests the relationship between customer engagement and customer trust and customer loyalty.

H3: Customer trust and engagement have a positive effect on customer loyalty

3.2 Research design

The research is conducted as part of an Msc study at the University of Amsterdam. The aim of the research is to identify and measure the relationship between online communities, customer engagement, and trust and customer loyalty.

According to Burns et al., the research can be defined as exploratory testing (Burns & Bush, 2017). The objective is to answer the research question by clarifying three hypotheses. Burns et al. distinguish five different methods of exploratory research; secondary data analysis (1), experience probe research (2), case analysis (3), focus groups (4) and projection techniques (5). This research is designed as an experience probe research. Of the five methods it offers the best possibilities to collect data from the ones that are expert with the research problem. In this research the experts to the customer loyalty in online communities are the participants in the online communities. Contrary to focus groups, experience probe research can be designed easier to become representative.

Data can be collected using two methods; quantitative (1) or qualitative (2). The methods can also be combined. For this research a quantitative data collection

method has been chosen because it offers a effective manner to collect data from a large group and therefore has a positive effect on the representativeness of the results. The data collected using a quantitative method can be easier and quicker being collected.

In the survey the respondents received questions with answer scales with the denomination of the different answers. This method gives the respondent the possibility to express the intensity of his feeling or opinion. Another advantage of this type of answer scale is its simplicity in use.

The chosen answer scale to measure the dependent variables customer engagement and customer trust is an interval scale; the 7-point Likert-scale. It is a symmetric agree-not agree scale that is widely used in market research. The 7-point Likert-scale is also used in some of the discussed research in chapter 2. The used answer scale is synthetic and has 7 answer points. The scale measures the intensity of the feelings or opinions of the respondents. In the used answer scale a neutral option is included to give the respondents that have no opinion the possibility to show their ambivalence. Another reason to include the neutral option is to offer respondents a symmetric scale with positive and negative answer options.

The answer scale used tot measure customer loyalty is the one that is part of the Net Promoter Score method. The answers of the respondents are classified into three categories; ‘detractor’, ‘passive’ and ‘promotor’.

Wereld Natuur Fonds Groep (WNFG)

The online community chosen is the Wereld Natuur Fonds Groep (WNFG) in the specialized photograph community Zoom.nl. Zoom is an online (website) and offline (magazine) platform for amateur photographers. Within Zoom there is a special community for charity organization Wereld Natuur Fonds Groep (WNFG). The community has approximately 5,000 members. Member can upload photos and discuss with other members and with the WNFG.

There are various reasons to choose the WFNG community. 1) The characteristics of an online community that were discussed in the literature review are present in WFNG (common interest, feeling of belonging to the group, written and unwritten rules, content is created by active participants and emphasis on verbal expression). 2) The online community is clearly segmented towards one specific characteristic of the members; being amateur photographers interested in WNF. 4) WNFG is big enough and therefore it is easier to receive a representative sample during the quantitative data collection. 5) WNFG makes it possible to access its members for participation in the research.

The survey was distributed through an active post on the forum of WNFG. In this post the researcher and the objectives of the research were introduced and members were asked to participate in the survey. By clicking on a link, the respondents were redirected to the online survey. The platform used is SurveyMonkey. The survey took place in January 2018.

The data collection method that is used to test the hypotheses is quantitative and data is collected through the conduction of a survey. The research is cross sectional.

In order to define the representative sample the following formula is used:

𝑛= 𝑁 ∗ 𝑧

2_{∗ 𝑝(1 − 𝑝)} 𝑧2_{∗ 𝑝(1 − 𝑝)+(𝑁 − 1)∗ 𝐹}2

The total population (N) are the 4.992 members of WNFG. In this research standard values are being used. The standard deviation (z) used is 1,96. The reliability level is 95%, the error term (F) 5% and the chance (p) is 50%. The needed sample size for this research is calculated as follows;

𝑛 = 4,992 ∗ 1,962∗ 0,5 ∗ 0,5

1,962 _{∗ 0,50 ∗ 0,50 + 4,991 ∗ 0,05}2 = 357

The survey will be representative if the response is at least 357.

Respondents received some general questions about gender, age and education level. A nominal scale was used to measure the gender and a ratio scale for the age. The educational level is measured using the ordinal scale; high school, MBO, HBO, University.

The general questions are not essential to the research but can serve as an additional control mechanism in case the outcome of the survey shows inconsistencies.

Loyalty to the charity fund is measured with the NPS. Both, the NPS and the CRV measure customer loyalty. The NPS however is more users friendly. And because it is necessary to make numerous assumptions when using the CRV model, the results will not be accurate. In paragraph 2.5 it has been emphasized that to calculate the CRV it is necessary to know the contribution margin and the

Therefore the NPS is used in this research. The NPS question is derived from the original question from Reicheld’s model into: how likely are you to recommend WNFG to a friend, colleague or relative?

Consumer engagement is measured with 28 questions on a 7-point Likert scale. Consumer trust is measured with 12 questions on a 7-point Likert scale.

Customer loyalty

The Net Promoter Score (NPS) is used to measure customer loyalty. This measure developed by Reichheld (2003) assumes there is only one relevant question to ask to a client; are you going to recommend the product/service/company to your family or friends? Respondents can answer with in a scale of 0-10. Those respondents that answer the question with 0-6 are so-called detractors. The will actively speak negative about the product/service/company. They are ‘bad ambassadors’. The respondents that answer the question with 7-8 are so-called passives. They are happy, but not enough to be an ambassador for the product/service/company. The respondents that answer with 9-10 are so-called promoters. They will actively promote the product/service/company. The NPS is calculated as follows:

𝑁𝑃𝑆 = % 𝑝𝑟𝑜𝑚𝑜𝑡𝑒𝑟𝑠 − % 𝑑𝑒𝑡𝑟𝑎𝑐𝑡𝑜𝑟𝑠

Consumer engagement

The method of Fung So et al. (2014) is used to measure engagement Fung So et al. The five dimensions of their model (enthusiasm, attention, absorption, interaction

and identification) are measured using a questionnaire with 23 items and using a 7-point Likert type scale.

Consumer trust

The model of Casaló et al. (2007) is used to measure consumer trust (Casalo, Flavian, & Guinaliu, 2007). They developed a framework in which consumer trust is measured by three dimensions; honesty, (1) benevolence (2) and competence (3). 4 items measure each dimension and using a 7-point Likert type scale.

4.

Research results

In this chapter the research results are presented. In paragraph 4.1 some general descriptive statistics of the sample group are shown. In paragraph 4.2 the variables are described. The results of data screening are discussed in paragraph 4.3. The scales are constructed in paragraph 4.4. In paragraph 4.5 the results of the correlation analysis are presented. In paragraph 4.6 the regression analysis is discussed. The outcome of the structural equational model is explored in paragraph 4.7. In the last paragraph the hypothesis conclusions are presented.

4.1 Descriptive statistics

The survey was returned complete by 380 respondents or 7,6% of the total population. 65,3% (248) of the respondents is man and 34,7% (136) is woman. The members of the Wereld Natuurfonds online community are relatively old with an average age of 64,3 years. The age distribution is presented in Appendix III. In figure 2 the education level of the respondents is shown. The member of the online community of Wereld Natuurfonds is relatively high educated. Degrees in University of Applied Sciences (HBO) and University are the most named.

Figure 2: Education level (n=380)

0 10 20 30 40 50

High school MBO HBO University

%

Education level

4.2 Variables

The behaviour of the individual in the community is measured by; length of membership (1), intensity of use (2), intensity of reaction to posts (3), intensity of publication of posts (4) and self image with regard to being a reference to others (5). The five items used to measure the five dimensions of the independent variable ‘online community’ are shown in table 1.

Independent variable: Online community

Variable

name Measure Question

OC1 Length of

membership Hoe lang ben je actief op de Wereld Natuur Fonds Groep van Zoom.nl?

OC2 Intensity of use Hoe vaak gebruik je de Wereld Natuur Fonds

Groep van Zoom.nl?

OC3 Passive use Ik reageer vaak op berichten van anderen

OC4 Active use Ik publiceer regelmatig berichten

OC5 Reference for

others

Ik ben een referentie voor andere members

Table 1: Dimensions of independent variable

The dependent variable customer engagement is measured using the method of Fung So et. Al (2014) using 23 items distributed among five dimensions; enthusiasm, attention, absorption, interaction and identification. The different items are shown in table 2.

Dependent variable: Customer engagement

ENTHOU1 Ik ben enthousiast over het Wereld Natuurfonds ENTHOU2 Ik ben gepassioneerd over het Wereld Natuurfonds

ENTHOU3 Alles gerelateerd aan het Wereld Natuurfonds heeft mijn aandacht ENTHOU4 Ik voel me een met het Wereld Natuur Fonds

ATT1 Ik wil meer over het Wereld Natuur Fonds weten

ATT2 Ik schenk aandacht aan alles over het Wereld Natuur Fonds ATT3 Ik concentreer me erg op het Wereld Natuur Fonds

ATT4 Ik hou er van om meer te leren over het Wereld Natuur Fonds

ABSRP1 Wanneer ik contact heb met de Wereld Natuur Fonds Groep op Zoom.nl vergeet ik alles om me heen

ABSRP2 Tijd vliegt wanneer ik contact het met de Wereld Natuur Fonds Groep op Zoom.nl ABSRP3 Wanneer ik contact heb met de Wereld Natuur Fonds Groep op Zoom.nl laat ik me ik

me meeslepen

ABSRP5 In mijn contact met de Wereld Natuur Fonds Groep op Zoom.nl laat ik mij volledig onderdompelen

INTER1 In het algemeen hou ik ervan om deel te nemen aan discussies in de Wereld Natuur Fonds Groep op Zoom.nl

INTER2 Ik ben iemand die houdt van interactie met gelijkgestemden in de Wereld Natuur Fonds Groep op Zoom.nl

INTER3 Ik ben iemand die houd van actieve deelname aan discussies in de Wereld Natuur Fonds Groep op Zoom.nl

INTER4 In het algemeen hou ik er erg van om ideeën met andere mensen te delen in de Wereld Natuur Fonds Groep op Zoom.nl

INTER5 Ik neem dikwijls deel aan activiteiten in de Wereld Natuur Fonds Groep op Zoom.nl INTER6 Wanneer ik intensief contact heb met de Wereld Natuur Fonds Groep op Zoom.nl ben ik

blij

IDEN1 Als iemand het Wereld Natuur Fonds bekritiseert, voel ik mij persoonlijk aangesproken IDEN2 Wanneer ik over het Wereld Natuur Fonds praat, gebruik ik eerder ‘we’ dan ‘zij’ IDEN3 De successen van het Wereld Natuur Fonds zijn mijn successen

IDEN4 Als iemand positief is over het Wereld Natuur Fonds voelt het als een persoonlijk compliment.

Table 2: Items for measurement of customer engagement.

Customer trust is measured using the method of Casaló et al. (2007) using three dimensions; honesty (1), benevolence (2) and competence (3) (2007). (Casalo, Flavian, & Guinaliu, 2007). The different dimensions are measured with 10 questions. In table 3, these items are shown.

Dependent variable: Customer trust

HONEST1 Ik denk dat de leden van de Wereld Natuur Fonds Groep op Zoom.nl over het algemeen hun afspraken nakomen

HONEST2 Ik denk dat de informatie die de leden van de Wereld Natuur Fonds Groep op Zoom.nl geven, eerlijk en oprecht is

HONEST3 Ik denk dat ik vertrouwen kan hebben in de beloften die de leden van de Wereld Natuur Fonds Groep op Zoom.nl geven

BENEV1 Ik denk dat de leden van de Wereld Natuur Fonds Groep op Zoom.nl naar een gemeenschappelijk voordeel zoeken bij hun interactie met andere leden

BENEV2 Ik denk dat de meeste leden van de Wereld Natuur Fonds Groep op Zoom.nl oog hebben voor de interesses en doelen van andere leden

BENEV3 Ik denk dat de leden van de Wereld Natuur Fonds Groep op Zoom.nl rekening houden met de gevolgen waartoe hun acties kunnen leiden voor de nadere leden

COMP1 Over het algemeen denk ik dat de leden van de Wereld Natuur Fonds Groep op Zoom.nl veel kennis hebben over het Wereld Natuur Fonds

COMP2 Over het algemeen denk ik dat de leden van de Wereld Natuur Fonds Groep op Zoom.nl veel ervaring hebben met het Wereld Natuur Fonds

COMP3 Over het algemeen denk ik dat de leden van de Wereld Natuur Fonds Groep op Zoom.nl de middelen hebben om een goed oordeel te vormen over het Wereld Natuur Fonds COMP4 Over het algemeen denk ik dat de leden van de Wereld Natuur Fonds Groep op Zoom.nl

op de hoogte zijn van de interesses van de andere leden

Table 3: Items for measurement of customer trust

The dependent variable customer loyalty is measured using the Net Promoter score.

4.3 Data screening

From the frequency distribution no errors in data entry were found. The normality of distribution has been examined. The dataset is found to be normal distributed with values for skweness and kurtois between -1 and +1.

The data was check for outliers by running frequencies of the standardized variables. Univariate outliers were found in the following seven variables: ENTHOU2, ABSRP1, ABSRP4, INTER3, INTER5, IDEN2 and INDEN3. The outliers were removed using the procedure of list wise deletion.

The data set has been explored for negatively keyed items; items that are phrased so that an agreement with the item represent a low level of the construct being measured. There was one negatively keyed item in the dataset. This item has been recoded.

The Variation Inflation Factor has been calculated for the independent variables. In table 4 the VIF values are presented. All values are lower than 3 and therefore multicollinearity is no issue in this research.

Variable VIF value

OC1 1,02

OC2 1,01

OC3 1,01

OC4 1,01

OC5 1,02

4.4 Scale construction and reliability 4.4.1 Customer engagement

The scale reliability for consumer engagement for the 23 items of table 2 was examined using Cronbach’s Alpha. The reliability level is not acceptable as Cronbach’s Alpha is only 0,282. The maximum Cronbach’s Alpha if items are deleted is 0,334. This is below the 0,6-0,7 levels that literature sees as acceptable.

The next step was to run a factor analysis. It showed 9 dominant factors that lead to a cumulative variance explained of 56,182%. Thereafter the Cronbach’s Alpha was calculated for each. The Cronbach’s Alpha’s remain low to very low. The highest outcome is 0,49.

The aforementioned results could prove the existence of subgroups in the dataset. It is possible that the length of membership (independent variable OC1) and the intensity of use of the community (independent variable OC2) can lead to the existence of sub groups with their own behaviour. Based upon explorative analysis of frequency distribution or these variables, community behaviour is assumed to influence customer engagement. Respondents that are longer member will tend to be more engaged than those that are member for a shorter period. The same thought applies for the activity; more active members are more engaged. The first step was to select the data on length of membership. The data was divided into 2 sub groups. The first group consists of people which membership was shorter than 2 years and in the second group represents respondents that were member for a period of 2 years or more. After this division the sample size

is acceptable (n=183). If the data is also filtered for activity (use of online community more than 2-3 times a week), the sample size is too small (n=41).

A factor analysis was done with the data of the sub group ‘long members’. This analysis gave 2 dominant factors. The factors were labelled identification and interaction. For both factors the Cronbach’s Alpha were calculated. For the factor identification the Cronbach’s Alpha is 0,641 and for interaction it is 0,441. Because the validity of the factor interaction is not acceptable, only identification is used to measure consumer engagement. Only 40% of the original 23 items are used to measure customer engagement. This affects the content validity of the research. Not all the aspects of customer engagement discussed in the literature review are being measured. This is a shortcoming of the research that limits the scope of the conclusions. According to Segers (2002), the number of items increases the internal validity of the research (Segers, 2002). One of the findings from the literature review is that customer engagement is a multi-dimensional condition. The commented research in the literature review identifies up to five dimensions of customer engagement. Four of them are not being measured in the survey as only a limited items are used. This shortcoming leads to a limited predictable value of the research.

4.4.2 Customer trust

The factor analysis was performed on the 10 items of table 3 that were used to measure consumer trust. Two factors were dominant with Chronbach’s Alpha of 0,751 and 0,596. The factors were labelled respectively honesty and competence.

4.4.3 Customer loyalty

Consumer loyalty is measured using the item the Net Promoter Score.

4.5 Correlation analysis

In the correlation analysis the Pearson coefficients quantify the linear relation between two variables. According to Mertler & Vanatta Reinhart (2017) there is a small/weak correlation when the Pearson coefficients are between 0,1 and 0,3. If the figure is between 0,3 and 0,5 there is a medium/moderate correlation. A Pearson coefficient above 0,5 implies a large correlation (Mertler & Vannatta Reinhart, 2017). The results for the correlation analysis are shown in table 5.

Variable M SD OC1 OC2 OC3 OC4 OC5 Cronbach

OC1 3,47 0,500 - OC2 2,45 1,073 -0,02 - OC3 3,77 1,998 -0,07 -0,06 - OC4 3,26 1,787 -0,03 0,08 0,02 - OC5 2,75 1,559 0,03 0,10 0,09 0,05 - Consumer engagement 3,17 0,645 -0,01 0,03 0,17* _{0,09 0,37}** _0,64 Trust: Honesty 5,49 0,978 -0,06 0,04 0,17* _0,25** _0,24** _0,75 Trust: Competence 5,82 1,139 -0,05 -0,04 0,24** _0,17* _0,18* _0,60 NPS 7,58 1,178 0,00 0,03 -0,10 0,02 -0,08

Table 5: Correlation Analysis (n=183) * _{correlation is significant at the 0,05 level (2-tailed)}, ** _{correlation is significant at the 0,01 level (2 tailed)}

There is a tendency to a positive relation between the honesty dimension of trust and the independent variables OC4, active posting on the online community, and OC5, being a reference tot others. The Pearson correlation is higher than 0,20. The relation is significant (p<0,01). There is also a significant Pearson correlation

factor between the honesty dimension of customer trust and OC3, the passive use of the community. The correlation factors is significant (p<0,05) but too low to conclude there is a relation between the mentioned variables.

The analysis also shows a significant (p<0,01) positive Pearson correlation factor between the competence component of customer trust and OC3, the passive use of the community. The Pearson correlation factor is higher than 0,20. There is also a significant (p<0,05) positive correlation between the competence dimension of trust and the independent variables OC4 and OC5. The correlation factors however are too low as prove for a positive relation between the concerning variables.

The analysis also shows a tendency for a positive relation between the independent variable OC5, being a reference for other users, and consumer engagement. The correlation factor is 0,37 and is significant (p<0,01). There are also significant (p<0,01) positive Pearson correlation factors between consumer engagement and OC3. The value however is too low and do not prove a positive relation between the concerning factors.

The correlation analysis shows an absence of relation between all the dimensions of the independent variable online community and customer loyalty measured by the NPS.

4.6 Regression analysis

A multiple regression analysis was performed to investigate the ability of the independent variable online community to predict the dependent variables (Y) level of customer engagement, trust and loyalty. The predictors (X) entered are the length of membership to the online community (OC1), the intensity of use (OC2), the frequency of reactions to posts (OC3), the frequency of active posts (OC4) and the degree of being a reference to others (OC5). The results of the regression analysis are shown in table 6.

R R2 R2 Change B SE β t Engagement 0,399 0,16 0,13 OC1 _-0,004 0,09 -0,003 0,039 OC2 _-0,010 0,04 -0,016 -0,223 OC3 0,042 0,02 0,130 1,801 OC4 0,021 0,03 0,059 0,823 OC5 0,154 0,03 0,355** _4,932 Trust Honesty 0,397 0,16 0,13 OC1 _{-0,115 0,135 -0,059} -0,853 OC2 0,026 0,063 0,028 0,405 OC3 0,075 0,034 0,154 2,210 OC4 0,148 0,038 0,271** _3,916 OC5 0,150 0,044 0,239** _3,421 Trust Competence 0,345 0,12 0,09 OC1 _-0,102 0,161 -0,045 -0,630 OC2 _-0,041 0,075 -0,039 -0,548 OC3 0,126 0,041 0,222** _3,111 OC4 0,118 0,045 0,185* _2,611 OC5 0,125 0,052 0,171* _2,399

Table 6: Regression analysis (n=183) * _{significant at the 0,05 level}, ** _{significant at the 0,01}

level

The F-test shows that the model used for customer engagement is significant. The F-value is 6,302 (p <0,01). The model used for the honesty component of customer trust shows a F-value of 6,607 (p <0,01). The model used for the competence component of customer trust has a F-value of 4,77 (p <0,01).

The model used for customer engagement explained 40% of the variance in customer engagement. In this model one of the five dimensions of the independent variable online community is statically significant; OC5 (being a reference to others). The β-value of this dimension of online community is relatively high 0,36 (p<0,01).

In the model used for the honesty dimension of customer trust, almost 40% of the variance was explained. In the model two of the five predictor variables are statically significant; OC4 (active posting) has a β-value of 0,27 (p<0,01) and OC5

(being a reference to others has a β-value of 0,23 (p<0,01).

The model used for the competence dimension of customer trust almost 35% of the variance is explained. Three of the five dimensions of the independent variable online community are statistically significant. OC3 (reaction to posts) has a β-value of 0,22 (p<0,01), OC4 (active posting) has a β-value of 0,185 (p<0,05) and O5(being a reference to others) records a β-value of 0,17 (p<0,05).

4.7 Structural Equational Modelling

A structural equational model was constructed where customer engagement, and the two components of customer trust (honesty and competence) acted as moderators for the dependent variable customer loyalty. The absolute goodness of fit of the model was assessed and found acceptable. The Chi-Square and probability values, the root mean square error of approximation (RMSEA) and the

goodness of Fit Index (GFI) were consistent with literature (Blunch, 2015). The results of the regression analysis are shown in table 7.

Estimate S.E. C.R. P

Trust Honesty <--- OC2 ,029 ,038 ,761 ,447

Trust Competence <--- OC2 -077 ,047 1,650 ,099

Engagement <--- OC2 -,001 ,014 -,049 ,961

Engagement <--- OC1 ,001 ,014 ,088 ,930

Trust Honesty <--- OC1 -,064 ,038 -1,688 ,091

Trust Competence <--- OC1 -,067 ,046 -1,433 ,152

Engagement <--- OC3 ,027 ,008 3,539 ***

Trust Honesty <--- OC3 ,054 ,021 2,587 ,010

Trust Competence <--- OC3 ,078 ,026 3,060 ,002

Engagement <--- OC4 ,007 ,009 ,787 ,431

Trust Honesty <--- OC4 ,128 ,024 5,406 ***

Trust Competence <--- OC4 ,097 ,029 3,359 ***

Engagement <--- OC5 ,079 ,010 7,917 ***

Trust Honesty <--- OC5 ,121 ,028 4,395 ***

Trust Competence <--- OC5 ,127 ,034 3,767 ***

NPS <--- Engagement ,033 ,195 ,171 ,864

NPS <--- Trust Honesty ,166 ,073 2,290 ,022*

NPS <--- Trust Competence -,084 ,060 -1,389 ,165

Table 7: Regression analysis using Equational Modelling (n=183) *** _{significant at}

the 0,01 level, * _{significant at the 0,05 level.}

In table 7 the regression values are displayed between the independent variables OC1, OC2, OC3, OC4 and OC5 and the moderators customer engagement and customer trust. The last three rows of table 7 show the regression coefficients for the relation between the moderators customer engagement and customer trust

and the dependent variable customer loyalty. The relation between customer engagement, the dimension competence of trust and customer loyalty are both positive but not significant. There is however a significant positive relation between the honesty component of customer trust and customer loyalty.

4.8 Hypotheses conclusions

The effect of online communities on customer engagement and customer trust is not unambiguously. There are dimensions of online communities that have a positive effect on customer engagement and customer trust. The correlation and regression analysis show that a limited number of factors of online communities have a positive relation with customer engagement and customer trust.

Customer engagement is positively influenced by the independent variable OC5; the degree of being a reference to others.

The frequency of reactions to posts (OC3), the frequency of active posts (OC4) and the degree of being a reference to others (OC5) positively influence customer trust.

Because the influence is not unambiguously and the influence that is proved is not very strong, hypotheses 1 and 2 are rejected.

Hypothesis 3 has been tested using structural equational modelling where customer engagement and customer trust act as moderator variables. The analysis

customer loyalty. However only the relation between the honesty component of customer trust and customer loyalty was significant. This is interesting as it proves that stimulating member to be active in an online community can lead, through a higher customer trust, to a higher customer loyalty. However because the results from the structural equational model are not unambiguous, hypothesis 3 is rejected.

5.

Conclusions

The conclusions of this research are presented in this chapter. With the results the research question is answered.

What is the effect of online communities on customer loyalty in charity fundraising?

An online community is defined as virtual social space where people share specific interest. Online communities have become more and more influential in customers choices.

The literature review show the existence of a positive relation between online communities and customer engagement and trust. And customer loyalty is positively influenced by customer engagement and trust. Using the results of the literature review it is argued that online communities have a positive effect on the customer loyalty.

This relation has been tested investigated for the online community Wereld Natuurfonds Groep on Zoom.nl using three hypotheses.

H1: Online communities have a positive effect on customer engagement H2: Online communities have a positive effect on customer trust

H3: Customer engagement and customer trust have a positive effect on customer loyalty.

The online community acts as independent variable and is measured using five dimensions; length of membership (1), intensity of use (2), passive use (3), active use (4) and being a reference to others (5).

For the dependent variables customer engagement and customer trust scales were constructed. The starting point were a list of items which were defined using the literature.

It appears that there are two sub groups in the data set when customer engagement and customer trust is measured. Based upon explorative analysis of frequency distribution or these variables, the length membership is assumed to influence customer engagement and customer trust.. The customer engagement and trust of respondents that are longer member tend to be higher than those that are member for a shorter period. The same thought applies for the level activity; more active members tend to have a higher customer engagement and customer trust. The scale to measure customer engagement that results from the analysis only measures 1 dimension of customer engagement; identification. To reach an acceptable level of scale reliability items had to be removed. This affects the content validity of the research. This is a shortcoming of the research that limits the scope of the conclusions. A suggestion for future research is to use a online community that is more homogenous.

Two dominant factors are used tot measure customer trust; honesty and competence.

The correlation analysis show a significant positive relation between three dimensions of online communities and dependent variables customer engagement and customer trust. These dimensions are active posting, passive use and being a reference for other users. All dimensions relate to the intensity in which the online community is used.

The correlation analysis shows an absence of a direct relation between all the dimensions of the independent variable online community and customer loyalty measured by the NPS.

The regression analysis shows significant positive relations between three dimensions of online communities and the dependent variable customer trust. The dimensions are; passive use, active posting and being a reference to others. The regression analysis for customer engagement shows a positive relation with the independent variable being a reference to others.

The results from both the correlation and regression analysis prove that some dimensions of an online community have a positive influence on customer engagement and customer trust. However the results are not unambiguous and therefore do not support hypothesis 1 and 2. Both hypotheses are rejected. Future research that analyses online communities where the percentage of active members is high can give additional insights into the relation between active behaviour and customer engagement and customer trust.

To test the relation between customer trust, customer engagement and customer loyalty structural equational modelling has been used. The regression analysis shows small positive relations between engagement, trust and customer loyalty. The relation between the honesty component of trust and customer loyalty is significant. It appears that by stimulating members to be more active in online communities, customer trust is enhanced and this leads to a higher customer loyalty. To increase customer loyalty using online communities it is recommended to stimulate members activity in the community. Because the results from the structural equational model are not unambiguous, hypothesis 3 is rejected.

This does not mean that the results of this study are inconsistent with the literature. This study proves how important it is to build customer trust and specially the honesty component of that. To reach a higher customer trust, members need to be stimulate to be an active member of the community. To be more engaged. It is then, that members undergo how the community is and this will lead to a higher customer loyalty. This is the most important recommendation this study leads to.

This study focus on the subgroup active members of online communities. It is suggested for further research to focus on the subgroup that is formed by less active members.

Bibliography

Armstrong, A., & Hagel, J. (2000). The Real Value of Online Communities. In E. Lesser, M. Fontaine, & J. Slusher, Knowledge and Communities. London:

Routledge.

Bagozzi, R., & Dholakia, U. (2002). Inernational social action in virtual communities. Journal of Interactive Marketing , 16t (2), 2-21.

Bennet, R., & Savani, S. (2011). Sources of New Ideas for Charity Fundraising; an Empirical Study. Creativity and innovation management , 20 (2), 121-138.

Blunch, N. (2015). Introduction to Structural Equational Modeling. London: Sage Publications Ltd.

Bowden, J. (2009). The process of customer engagement; a conceptual framework. Journal of Marketing Theory and Practice , 17 (1), 63-74.

Brodie, R., Ilic, A., Juric, B., & Hollebeek, L. (2011). Consumer engagement in a virtual brand community; An exploratory analysis. Journal of Business Research . Burns, A., & Bush, R. (2017). Marketing Research. London: Peason .

Capgemini Consulting. (2016). Unlocking customer satisfaction; why digital holds the key for telcos. Paris: Capgemini Consulting.

Casalo, L., Flavian, C., & Guinaliu, M. (2007). The impact of participation in virtual brand communities on consumer trust and loyalty; the case of free software. Online Information Review , 31 (6), 775-792.

Dessart, L., Veloutsou, C., & Morgan-Thomas, A. (2015). Consumer engagement in online brand communities: a social media perspective. Journal of Product & Brand Management , 24 (1), 28-42.

Fung So, K., King, C., & Sparks, B. (2014). Customer Engagement with tourism brands; scale development and validation. Journal of Hospitality & Tourism Research , 38 (3), 304-329.

Gruen, T., Osmonbekov, T., & Czapewski, A. (2006). eWon: The impact of

customer-to-custoer onlien know-how exchange on customer value and loyalty. Journal of Business Research , 59 (4), 449-456.

Gummerus, J., Liljander, V., Weman, E., & P. M. (2012). Customer engagement in a Facebook brand community. Managemen Research Review , 35 (9), 857-877. Gusfield, J. (1975). The Community; A Critical Response. New York: Harper Colophon.

Hassay, D., & Peloza, J. (2009). Building the Charity Brand Community. Journal of Nonprofit & Public Sector Marketing , 21 (1), 24-55.

Jang, H., Offman, L., Ko, I., Koh, J., & Kim, K. (2008). The influence of On-Line Brand Community Characteristics on Community Commitment and Brand Loyalty. Journal of Electronic Commerce , 12 (3).

Johnson, M., & Auh, S. (19989). Customer Satisfaction, Loyalty and the Trust Environement. Advances in Consumer Research , 25, 15-20.

Koh, J., & Kim, Y. (2003). Knowledge sharing in virtual Communities; an e-business perspective. Expert Systems with Applications , 26.

Kotler, P., & Armstrong, G. (2013). Principes van Marketing. Amstrerdam: Pearson Benelux B.V.

Kotler, P., & Armstrong, G. (2015). Principles of Marketing. New Jersey: Pearson. Kumar, V., & Reinartz, W. (2006). Customer Relationship Management. New York: Wiley.

Kumar, V., Petersen, J., & Leone, R. (2007, October). How valuable is wordt of mouth. Harvard Business Week , 2-8.

Mertler, C., & Vannatta Reinhart, R. (2017). Advanced and Multivariate Statistical Methods. New York: Routledge.

Nguyen, N., Leclerc, A., & LeBlanc, G. (2013). The mediating role of customer trust on customer loyalty. Journal of Service and Management , 6, 96-109. Quinton, S. (2012). Missing a strategic marketing trick? The use of online social networks by UK charities. International Journal of Nonprofit and Voluntary Sector Marketing , 18 (1), 35-51.

Sargeant, A., & Woodliffe, L. (2008, September 8). Building donor loyalty: the antecedents and role of commitment in the context of charity giving. Journal of nonprofit and & public sector marketing , 47-68.

Sargeant, A., Ford, J., & West, D. (2006). Perceptuatl determinants of nonprofit giving behavior. Journal of Business Research , 59 (2), 155-165.

Segers, J. (2002). Methoden voor de maatschappij wetenschappen. Assen: Van Gorcum.

Sun, T., Youn, S., Wu, G., & Kuntaraporn, M. (2006). Online word-of-mouth (or mouose); An exploration of its antecedents and cosequences. Journal of Computer-mediated Communication , 11, 1104-1127.

Szmigin, I., Canning, L., & Reppel, A. (2005). Online community: enhancing the relationship marketing concept through customer bonding. International Journal of Service Industry Management , 16 (5), 480-496.

Ul Islam, J., & Rahman, Z. (2016). Linking customer engagement to Trust and word-of-mouth on Facebook Brand communites; An emperical Study. Journal of Internet Commerce , 15 (1), 40-58.

Waters, R., B. E., Lamm, A., & Lucas, J. (2009). Engaging stakeholders through social networking; How nonprofit organizations are using Facebook. Public Relations Review , 35 (2), 102-106.

Wirtz, J., d. A., Bloemer, J., Horvath, C., Ramaseshan, B., van de Klundert, J., et al. (2013). Managing brands and customer engagement in online brand

Appendix 1: Accompanying letter survey

Geachte heer, mevrouw,

Mijn naam is Ayoub Kaddouri. Ik ben een economiestudent aan de Universiteit van Amsterdam. Ter afronding van mijn studie voer ik een onderzoek uit naar de invloed van online communities op de klantloyaliteit van Goede Doelen organisaties.

De Wereld Natuur Fonds Groep binnen Zoom is een voorbeeld van een online community. Het is een virtuele plek waar mensen met gemeenschappelijke interesses regelmatig bij elkaar komen. Zoom is de grootste fotografie-community van Nederland en de Wereld Natuur Fonds Groep is binnen Zoom een aparte community.

Ik wil u vriendelijk vragen om deel te nemen aan een korte online enquête. Het onderzoek is volledig anoniem. Met uw deelname vergroot u de kans op een succesvol onderzoek. Een van de doelstelling van mijn onderzoek is om Goede Doelen organisaties inzicht te geven in de wisselwerking tussen online communites en klantloyaliteit. Dit inzicht zal de Goede Doelen helpen om efficiënter om te gaan met hun marketinginspanningen.

Mijn onderzoek is volledig onafhankelijk en ik heb met dit onderzoek geen winstoogmerk. Mocht u een kopie van mijn onderzoeksverslag willen ontvangen, dan kunt u dit via het onderstaande email adres aanvragen. Ik stuur het u met veel plezier toe.

Appendix II: Questionnaire

1. In welke mate zult u het Wereld Natuur Fonds als goede doel aan u familie en vrienden aanbevelen?

0 1 2 3 4 5 6 7 8 9 10

2. Hoe lang ben je actief op de Wereld Natuur Fonds Groep van Zoom.nl? o Korter dan 1 jaar

o Tussen de 1 en 2 jaar o Tussen de 2 en 3 jaar o Langer dan 3 jaar

3. Hoe vaak gebruikt u de online community Wereld Natuur Fonds Groep van Zoom.nl?

o Dagelijks

o 2-3 keer per week

o 1 keer per week

o Minder dan 1 keer per week

4. Geef aan in welke mate u het eens bent met de volgende stellingen wanneer u aan de community Wereld Natuurfonds Groep op Zoom.nl denkt:

a) Ik reageer vaak op berichten van anderen.

1 2 3 4 5 6 7

Zeer oneens Zeer eens

b) Ik publiceer regelmatig berichten.

Zeer oneens Zeer eens c) Ik ben een referentie voor andere members.

1 2 3 4 5 6 7

Zeer oneens Zeer eens

5. Geef aan in welke mate u het eens bent met de volgende stellingen wanneer u aan het Wereld Natuurfonds denkt:

a) Ik voel me een met het Wereld Natuur Fonds

1 2 3 4 5 6 7

Zeer oneens Zeer eens

b) Ik ben gepassioneerd over het Wereld Natuur Fonds

1 2 3 4 5 6 7

Zeer oneens Zeer eens

c) Ik ben enthousiast over het Wereld Natuur Fonds

1 2 3 4 5 6 7

Zeer oneens Zeer eens

6. Geef aan in welke mate u het eens bent met de volgende stellingen wanneer u aan het Wereld Natuurfonds denkt:

a) Ik wil meer over het Wereld Natuur Fonds weten

1 2 3 4 5 6 7

b) Ik schenk aandacht aan alles over het Wereld Natuur Fonds

1 2 3 4 5 6 7

Zeer oneens Zeer eens

c) Alles gerelateerd aan het Wereld Natuurfonds heeft mijn aandacht

1 2 3 4 5 6 7

Zeer oneens Zeer eens

d) Ik concentreer me erg op het Wereld Natuurfonds

1 2 3 4 5 6 7

Zeer oneens Zeer eens

e) Ik hou er van om meer te leren over het Wereld Natuurfonds

1 2 3 4 5 6 7

Zeer oneens Zeer eens

7. Geef aan in welke mate u het eens bent met de volgende stellingen wanneer u contact heeft met de Wereld Natuurfonds Groep op Zoom.nl:

a) Wanneer ik contact heb met de Wereld Natuur Fonds Groep op Zoom.nl vergeet ik alles om me heen.

1 2 3 4 5 6 7

Zeer oneens Zeer eens

b) Tijd vliegt wanneer ik contact het met de Wereld Natuur Fonds Groep op Zoom.nl.

1 2 3 4 5 6 7

Zeer oneens Zeer eens

c) Wanneer ik contact heb met de Wereld Natuur Fonds Groep op Zoom.nl laat ik me meeslepen

1 2 3 4 5 6 7

Zeer oneens Zeer eens

d) Wanneer ik contact heb met de Wereld Natuur Fonds Groep op Zoom.nl kan ik mij daar moeilijk van losmaken

1 2 3 4 5 6 7

Zeer oneens Zeer eens

e) In mijn contact met de Wereld Natuur Fonds Groep op Zoom.nl laat ik mij volledig onderdompelen.

1 2 3 4 5 6 7

Zeer oneens Zeer eens

f) Wanneer ik intensief contact heb met de Wereld Natuur Fonds Groep op Zoom.nl ben ik blij.

1 2 3 4 5 6 7

Zeer oneens Zeer eens

8. Geef aan in welke mate u het eens bent met de volgende stellingen wanneer u denkt aan het contact met de Wereld Natuurfonds Groep op Zoom.nl en andere leden van de Wereld Natuur Fonds Groep:

a) In het algemeen hou ik ervan om deel te nemen aan discussies in de WNF Groep op Zoom.nl.

1 2 3 4 5 6 7

Zeer oneens Zeer eens

b) Ik ben iemand die houdt van interactie met gelijkgestemde in de WNF Groep op Zoom.nl.

c) 1 2 3 4 5 6 7

Zeer oneens Zeer eens

d) Ik ben iemand die houdt van actieve deelname aan discussies in de WNF Groep op Zoom.nl.

1 2 3 4 5 6 7

Zeer oneens Zeer eens

e) In het algemeen hou ik er erg van om ideeën met andere mensen te delen in de WNF Groep op Zoom.nl.

1 2 3 4 5 6 7

Zeer oneens Zeer eens