Amsterdam Business School | University of Amsterdam
Master Thesis
The motivating determinants for customers to engage in
Customer Participation and their effect on
Satisfaction as service outcome
Name : David van Dongen
Student number : 10681906
Supervisor : Drs. Frank Slisser
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Statement of Originality
This document is written by David van Dongen who declares to take full responsibility for the contents of this document. I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.
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Abstract
Prior empirical evidence on the driving motives for customers to engage in customer participation activities is still limited. The author aimed to contribute to the literature by identifying these motives and study their influence on satisfaction through customer participation, including the moderating role customer participation readiness factors play between customer participation and satisfaction. A conceptual framework which included motives as antecedents was researched, testing several hypotheses. Based on data from 573 SkyPriority Panel members, the learning benefit motives appear to have a positive effect on customer participation. This study revealed that customer participation has a negative effect on satisfaction, and the customer participation readiness factors ‘perceived ability’ and ‘role
identification’ do not have any moderating effects on the relation between customer participation and satisfaction. The outcome of this study suggests that companies planning to adopt, or having adopted, customer participation into their business activities should focus their resources on learning benefit motives, both in the design of the customer participation activities, as well as in their recruitment efforts. Furthermore, firms need to question whether, other than the general theoretical understanding in the literature implies, customer participation is the right strategy to use when enhancing customer satisfaction of these participants is the main goal. However one can assume that these customer participation activities can generate useful information for businesses to contribute to service and/or product improvement efforts that may enhance the customer satisfaction in general. Nevertheless more research is needed to understand the complex phenomena of customer participation.
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Table of Contents
1. Introduction ... 5
1.1. Satisfaction and Perceived Service Quality ... 5
1.2. Customer Participation ... 6
1.3. Motives ... 7
1.4. Customer Participation Readiness Factors ... 8
1.5. Objective and Relevance ... 10
2. Literature review ... 13
2.1. Satisfaction ... 13
2.2. Customer Participation ... 14
2.3. Customer Participation Readiness Factors ... 16
2.4. Motives for taking part in customer participation activities ... 18
3. Research design ... 22 3.1. Research method ... 22 3.2. Participants ... 22 3.3. Materials ... 24 3.4. Procedure ... 25 3.5. Statistical analysis ... 26 4. Research results ... 27 4.1. Validity of scales ... 27
4.2. Demographic profile of the sample ... 28
4.3. Regression analyses and testing hypotheses ... 29
5. Discussion ... 36
5.1. Significance and theoretical implications ... 36
5.2. Managerial implications ... 39
5.3. Limitations and directions for future research ... 40
6. Conclusions ... 43
7. References ... 44
5 1. Introduction
A cornerstone of marketing is the focus on the needs,wishes and preferences of customers. Market orientation literature has demonstrated that firms which are more focused on customer needs, in terms of both their company culture and behavioral components, outperform their competitors (Narver and Slater, 1990; Kohli and Jaworski, 1990). The exchange of information between firm and consumer therefore is of vital importance for companies to effectively learn about the needs, wishes and preferences of their customers (Sinkula, Baker and Noordewier, 1997). Current literature emphasizes how indispensable it is for companies nowadays to involve customers in activities like co-creation and quality assurance for achieving a competitive edge (Constantinides et al., 2015). A recent development in the exchange of information between consumers and firms pertains to the partaking of the customer in this process (Haumann et al., 2015), also referred to as customer participation. Integrating customer participation leads to the development and delivery of better products and services (Fuchs and Schreier, 2011; Prahalad and Ramaswamy, 2004), which on its turn leads to an increased perceived service quality and satisfaction. Highly satisfied customers drive growth and profitability (Heskett and Schlesinger, 1994).
1.1. Satisfaction and Perceived Service Quality
Satisfaction and perceived service quality are widely established constructs to determine the comparison that consumers make between the performance of a product or service and some standard (Bitner, 1990; Parasuraman et al., 1988; Zeithaml et al., 1993). A large-scale global empirical study clearly shows that companies that really care about the satisfaction and the perceived service quality of their customers perform better (Simon et al., 2016). Companies with
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a customer centric business model in which insights and analytics plays a pivotal role, are more likely to excel in their performance and generate strong revenue growth (Simon et al., 2016). High satisfaction and perceived service quality leads to positive behavioral intentions from customers, which eventually generates increased market share, sales and profitability (Dagger & Sweeney, 2007).
1.2. Customer Participation
Customer participation is defined as the level to which a customer concurs labor, preference, cognition, or other inputs to service production and delivery (Dabholkar, 1990; Chan et al., 2010).
In the literature there is a common academic understanding that customer participation induces augmented productivity, incremented customer satisfaction, and improved service quality (Bitner et al., 1997; Kelley et al., 1990; Chan et al., 2010; Cermak et al., 1994). A higher customer satisfaction will subsequently lead to a higher repurchase intention (RPI) which in turn contributes to an increase in revenue. In order to achieve the desired perceived service quality and satisfaction, companies nowadays are more and more involving their customers in their day-to-day business. Companies ask their customers to give their opinion and to share feedback about products and services. Customer participation is a recent development in the exchange of
information between firm and consumer (Haumann et al., 2015).Technology advances have allowed firms to design new ways for customers to share feedback about products and services. This important development enables firms to become more customer oriented. Integrating customers into the organizations' process improves service quality, and market success, (Chan et al., 2010; Cermak et al., 1994; Prahalad and Ramaswamy, 2004) and as such this topic has been among one of the top research priorities of the Marketing Science Institute (Hoyer, Chandy, Dorotic, Krafft, & Singh, 2010). By adopting customer participation strategies, organizations in
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service industries intend to achieve superior quality as this is of paramount importance as high quality leads, via positive behavioral intentions from customers, to improved market share, sales and greater profitability (Dagger & Sweeney, 2007). According to Woojung Chang (2016), who conducted a recent meta-analysis on the effectiveness and benefits of customer participation in new product development, the involvement of customers in the ideation and launch stages improves the new product financial performance directly and indirectly through acceleration of time to market.
1.3. Motives
Whether a customer is willing to participate is believed to be determined by his or her motive and/or motivation. Motive is defined by Kotler and Armstrong (2004, p. 191) as: "a need that is sufficiently pressing to direct the person to seek satisfaction". Although theoretically the
underlying concepts are different, both words “motive” and “motivation” can often function as synonyms, meaning e.g. incentive or drive (Wells, 2011). The Longman Dictionary of
Contemporary English describes it as “a cause of or reason for action; that which urges a person to act in a certain way”. Based on this description, in this study the auditor refers to “motive” as a specific cause for one's actions.
Although the effectiveness of customer participation on perceived service quality and satisfaction is generally supported in literature, customer participation can still be a real challenge for companies to administer. The reason resides in the fact that customers are not always willing and motivated to cooperate. Participation is mainly on voluntary basis and customers are requested to spend their valuable time, share their valuable knowledge and effort in evaluating and increasing the quality of existing products and services, just as providing valuable proposals for innovating products and services (Constantinides et al., 2015). Recent literature examined the moderating effect of motives between customer participation and service
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outcomes - service quality and satisfaction - (Dong et al., 2015). It is interesting to see however how motives on the whole encourage people to take part in customer participation, as antecedent predictors. Surprisingly, knowledge about the motives for customers to take part in customer participation activities and how these motives influence their satisfaction is still limited and suggestions are made for further research (Sigala, 2014; Dong et al., 2008; Dong et al., 2015).
1.4. Customer Participation Readiness Factors
Customer participation readiness is defined as the extent to which a customer is prepared to participate in service production and delivery consisting of three factors: perceived ability, role identification, and perceived benefit of participation (Dong et al., 2015; Meuter et al., 2005).
The perceived ability factor pertains to the perceived cognition and competence of customers empowering them to take part successfully or efficiently (Dong et al., 2015; Meuter et al., 2005).
The role identification factor pertains to the degree to which participants receive and internalize their roles in service participation (Dong et al., 2015; Lengnick-Hall, 1996; Zeithaml, Berry, and Parasuraman 1993).
The perceived benefit of participation factor pertains to the customers assessment of the partaking compensation andis according to Dong et al., close to ‘‘motives’’ (Dong et al., 2015; Meuter et al. 2005). However, Dong et al. does indicate an important difference between motives and perceived benefit, by stating,
perceived benefits of participation serves our research better because it captures the essence of needs-supply fit by assessing the rewards of participation; while motivation by definition evaluates the desire to receive the rewards which is a psychological outcome of the needs-supply fit (e.g., Meuter et al., 2005) and value contains a wide variety of
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meanings and thus not as specific as benefit (e.g., Chan, Yim, and Lam, 2010). (2015, p. 162).
Dong et al. states that these perceived benefits can either comprise extrinsic rewards like a reduced fare and commodity (Dong et al., 2015; Meuter et al. 2005) or intrinsic rewards like gratification and sense of accomplishment (Lusch, Brown, and Brunswick 1992).
Dong et al. (2015) found a moderating effect of the three customer participation readiness factors on the relation between customer participation and service outcomes (perceived service quality and satisfaction). Dong et al. (2015) concluded from their investigation that customer participation could have both positive and negative effects on service outcomes (satisfaction and perceived service quality), depending on whether customer participation readiness is high or low. Dong et al. used these three customer participation readiness factors as moderators, including the perceived benefit of participation factor which reflects motives in her model.
However it is important to notice that there is an ongoing debate on the differences and similarities of the constructs of perceived benefits and motives. Shortly after the publication by Dong et al. (2015), Constantinides et al. (2015) contributed to this debate by publishing a paper in which he suggests that motives are not a moderator in the relationship between customer participation and service outcomes, but an antecedent for customer participation. Inspired by this new conceptual approach by Constantinides, in this paper the perceived benefits of participation are treated as an aspect of the construct motives, rather than an aspect of customer participation readiness factors. As such, in the current research the author uses motives as a separate
predictor, ensuring that the constructs customer participation readiness and motives do not have any areas of overlap.
It is possible that besides motives, other customer participation readiness factors should also be seen as antecedents rather than moderators. However, until this moment, no specific prior
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research points in this direction and therefore the current study uses the two remaining customer participation readiness factors as moderators.
1.5. Objective and Relevance
The limited knowledge about the motives for customers to engage in customer participation activities and how these motives influence their satisfaction is leading to the following research question:
What motives influence, through customer participation, the degree of the service
outcome “satisfaction”, and what moderating role customer participation readiness factors play in this effect?
Hence the objective of this paper is:
1. to identify which customer motives enhance the willingness to participate in customer participation activities
2. to study whether customers who strongly participate show a positive appraisal of satisfaction 3. to outline the extent to which these identified motives influence satisfaction
4. to study the moderating effect of customer participation readiness factors on the relationship between customer participation and satisfaction
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Figure 1. Conceptual framework of the current study.
The practical relevance. The practical relevance of customer participation to companies has become clear from its introduction. If companies know better how to encourage customers to get engaged, they can ensure that more customer participation occurs, which might positively enhance the service outcome satisfaction. For example, if a particular motive is very strong, companies can focus on that specific motive. Insights helps companies to effectively recruit and engage participants into customer participation activities.
The scientific relevance. The scientific relevance and contribution to the existing literature on this subject is the case for the following three reasons:
1. This research is conducted in a more real-life setting than previous surveys (Constantinides et al., 2015; Dong et al., 2015)
2. Dong et al.'s research focused on the moderating effect of motives between customer participation and service outcomes. The author of the current study however, suggests that the motive factor of customer participation readiness can better be seen as a loose predictor of customer participation, rather than as a moderator for the customer participation - service
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outcomes relationship. This suggestion is based on the fact that knowledge about the motives for customers to take part in customer participation activities is still limited and suggestions are made for further research (Constantinides et al., 2015; Sigala, 2014; Dong et al., 2008; Dong et al., 2015). It is interesting however to see how motives on the whole encourage people to take part in customer participation, as antecedent predictors. This suggestion is followed in this research.
3. Research has been done based on scenario-based experiments by Dong et al., but it is suggested and good to replicate this research with field experiments so that evidence of the effects becomes stronger.
4. Constantinides et al. (2015) contributed to the existing literature by identifying customer motives increasing the readiness to participate in online co-creation activities. However, the identified motives were only studied in an unnatural pilot setting as the purpose of their study was to mainly identify which data could be deduced from the pilot questionnaire to test its practical applicability. This opens the gap for further research and study these identified motives for customer participation in a real-life setting.
13 2. Literature review
This literature review is structured in the same fashion as in the introduction, but gives a more extensive description of the definitions and previous research on the relationship between constructs.
2.1. Satisfaction
Even though there is no obvious concurrence concerning the definition of satisfaction, most definitions include “an evaluative, affective, or emotional response” (Oliver et al., 1989, p., 1).
In the literature, a distinction between satisfaction and perceived service quality is outlined. Satisfaction literature has emphasized the idea that consumers make a comparison between the performance of the product or service and some standard. The service quality literature argues that the distinction between perceived service quality and satisfaction is that they use different standards of comparison (Bitner, 1990; Parasuraman et al., 1988; Zeithaml et al., 1993). Bitner (1990) states “The theory underlying the disconfirmation paradigm is that consumers reach satisfaction decisions by comparing product or service performance with prior expectations about how the product or service would or should perform”. Concerning perceived service quality, Bitner (1990) states “Parasuraman, Zeithaml, and Berry (1988) define "perceived [service] quality" as the consumer's judgment about a firm's overall excellence or superiority. This definition suggests that perceived quality is similar to an individual's general attitude toward the firm (see also Zeithaml 1988)”.
Spreng and Mackoy (1996) empirically examined the distinction. Results indicate that the twoconstructs are, in the present case, distinct. Dong et al. (2015) included this distinction in her model by scrutinizing the moderating effect of customer participation readiness factors on the
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relation between customer participation and service outcomes, consisting of both perceived service quality and satisfaction.
In the current study the author will only focus on the construct satisfaction as the
dependent variable for service outcome, rather than both satisfaction and perceived quality. The reason for this choice is that in this research the service outcome is seen as a balance between perception of the expected performance and actual performance of a company by the client, instead of a general attitude of the client towards the company.
2.2. Customer Participation
Customer participation is an important predictor of satisfaction (Bitner et al., 1997; Kelley et al., 1990; Bendapudi et al., 2003; Chan et al., 2010; Cermak et al., 1994).
Customer participation is referred to by Chan et al. (2010) and Dabholkar (1990) as the extent to which a customer concurs labor, preference, cognition, or other inputs to service production and delivery. Customer participation in current paper entails a broad conceptual domain, described by Dong et al. as: “covering various customer roles and behaviors such as sharing information/preferences and providing labor, and its wide coverage of customer participation spectrum consisting of firm, joint, and customer production (Lovelock and Young, 1979; Mustak, Jaakkola, and Halinen, 2013)” (Dong et al., 2015, p. 161).
Closely associated to customer participation is innovation capability of companies (Ngo & O'Cass, 2013). Companies emphasizing on innovation are more likely to improve the fit between their innovative offerings and their customer needs. Service innovations with greater customer participation in successful propositions perform better compared to those that were unsuccessful. Literature shows a significant dissimilarity between these successes and failures (Martin & Horne, 1993; Martin, Horne, & Schultz, 1999).
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Marketing literature has largely focused on the economic implications of customer participation. The studies predominantly focused on customer participation in co-production processes, thus customers participating in the performance of various activities within the production process including all cooperation formats between the customer and the service provider, as described by Etgar (2008). These studies offer vital documentation of the beneficial aspects of active customer participation in the production of goods and services in contrast to traditional firm production, without the active engagement of customers in co-production (e.g., Bendapudi and Leone, 2003; Bitner et al., 1997; Etgar, 2008; Mochon,
Norton, and Ariely, 2012; Troye and Supphellen, 2012). They show that customer participation in co-production processes improves customer’s evaluation of the resulting product or service (Atakan, Bagozzi, and Yoon, 2014; Mochon, Norton, and Ariely 2012; Troye and Supphellen, 2012) and changes their assessment of the co-production offering firm (Bendapudi and Leone, 2003; Meuter et al., 2000).
In the literature, the general theoretical understanding is that customer participation leads to increased satisfaction. Bitner et al. (1997) argues that customer participation increases the likelihood that customers their needs are fulfilled and their pursued benefits are accomplished, since customers contribute to their own satisfaction and the ultimate quality of the services they receive. Bendapudi et al. (2003) cites a positive relationship between customer participation and satisfaction when service outcome excels expectations.
Hypothesis related to the effect of customer participation on satisfaction:
H1 There is a positive effect of customer participation on satisfaction, where people who participate in customer participation show higher satisfaction than customers who do not participate.
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2.3. Customer Participation Readiness Factors
The relationship between customer participation and satisfaction depends on various factors, also referred to as the customer participation readiness factors.
Customer participation readiness is initially defined and introduced by Meuter et al. (2005) as the condition or state in which a consumer is prepared and likely to use an innovation for the first time. He established three key factors as dimensions for constructing customer participation readiness. These are customers their role clarity, their motivation, and their ability. Role clarity stands for the customer knowledge and understanding of what to do. Motivation refers to a desire to receive the rewards associated with participating. And ability stands for having the required skills and confidence to complete the task.
These customer participation readiness factors are used by Dong et al. (2015) as
moderators in the model of her recent study. Though, she slightly modified its definition into: the extent to which a customer is prepared to participate in service production and delivery consists of three factors: perceived ability, perceived benefits of participation and role identification (Dong et al., 2015). Her rationale for using “perceived benefits of participation” is that it
embosoms both “motives” (Meuter et al., 2005) and “perceived value” (Chan et al., 2010). In her model these variables serve as moderators between customer participation and service outcomes (service quality and satisfaction).
In the current research, in contrast to Dong et al., the author treats “perceived benefits of participation” as an aspect of the construct motives, rather than an aspect of customer
participation readiness factors. The author does not support the suggestion of motives being subject to the all-embracing customer participation readiness construct but sees motives as a separate entity and as an antecedent for customer participation. As such, in the current research,
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the author uses motives as a separate predictor, ensuring that the constructs customer
participation readiness and motives do not have any area of overlap. This results in excluding “perceived benefits of participation” -factor as a moderator from the model.
One might wonder whether besides motives, other customer participation readiness factors should also be seen as antecedents rather than moderators. However, until this moment, no specific prior research points in this direction and therefore the current study uses them as moderators. In conclusion, the moderating customer participation readiness factors in this study are ability and role identification.
The moderating effects of ability and role identification between customer participation and satisfaction recently examined (Dong et al., 2015) show conclusive evidence that when the ability factor is high, increasing customer participation augments customer satisfaction.
Concurrently, it shows that when the ability factor is low, the effect of customer participation on satisfaction declines or results in a negative ramification. The same effects occur with the role identification factor. The results highlight the contingent nature of customer participation its effect, demonstrate that customer participation could indeed be a double-edged sword, and provide managerial guidelines to enhance customer participation’s benefits through appropriate targeting and service design.
Hypotheses related to the moderating effect of customer participation readiness factors on the relation between customer participation and satisfaction:
H2a The perceived ability to participate, moderates the effect between customer participation and satisfaction where customers with a high perceived ability show a stronger relation between customer participation and satisfaction.
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H2b The extent to which a customer identifies with the participation role, moderates the effect between customer participation and satisfaction, where customers with a high role identification show a stronger relation between customer participation and satisfaction.
2.4. Motives for taking part in customer participation activities
The third readiness factor related to motives that in the current study is perceived as an antecedent of customer participation.
In both the Cambridge and Oxford Dictionaries the meaning of the word motive is
described as “a reason for doing something”. The Longman Dictionary of Contemporary English describes it as “a cause of or reason for action; that which urges a person to act in a certain way”. As indicated earlier in this paper, current literature provides limited empirical research
information on the reasons why people take part in customer participation. Since customer participation is mainly on voluntary basis customers are not always willing and motivated to cooperate (Constantinides et al., 2015). A resume of the most relevant articles found in literature with regard to motives in relation to customer participation will be given in this chapter.
Several articles have related various motives to customer participation. For example, Holland and Baker (2001) proposed that the drivers for customer participation are limited to “experiential vs. task orientation” and “other personal factors”. As extensions they proposed to seek to sketch other factors that would influence customers partaking in customer participation.
Sigala (2014) proposes a more extensive framework for the relation between motives and customer participation. In her paper, she proposes a holistic framework identifying four
dimensions and issues for researching customer involvement (based on customer participation) in implementing sustainable supply chain management in tourism. In her model she uses the following three factors motivating customer involvement: customer factors (e.g.: functional,
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emotional, cognitive benefits, and sociodemographic factors), environmental factors (e.g.:
technology push, and social trends) and firm factors (e.g.: sustainable culture values, and flexible organizational structures to support and integrate customers in co-creation and innovation). As direction for future research, she proposed to investigate these factors more in depth.
An additional paper that discusses motives for customer participation is Hennig-Thurau et al. (2004). In his proposal for word-of-mouth communication behavior, the author researched virtual communities and traditional word-of-mouth literature, which led him to suggest 11 distinct motives which consumers may have in engaging in web-based consumer opinion platforms. The following limitations, however, were reasons for not adopting this source in current research: (1) the study only focused on motives for writing online opinions which does not cover the full broad conceptual domain of customer participation, in particular the interactive nature of customer participation activities (e.g. co-creation and in quality assurance), and (2) the validity of the empirical results are to be questioned (Hennig-Thurau et al., 2004).
The most recent and relevant source applicable to customer participation, however, is the model of customers’ motives used in the recent study on customer motives and benefits for participating in online co-creation activities (Constantinides et al., 2015). The authors
Constantinides et al. (2015) identified four benefits as relevant motives: learning benefits, social integrative benefits, personal integrative benefits and hedonic benefits. The basis of these motives derive from the uses and gratifications approach which explains two basic dimensions (cognitive and affective) on which the benefits are deduced by customers (Constantinides et al., 2015).
The motive ‘learning benefit’ is described as a benefit which delivers the customer acquisition of knowledge, insight of the product and an understanding of the environment (Constantinides et al., 2015, Hoyer et al., 2010, Nambisan et al., 2007).
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The motive ‘social integrative benefit’ refers to a benefit perceived by the customer, arising from relational and social developed ties while working together or interacting with relevant other customers or company staff, creating a sense of belongingness and social identity (Constantinides et al., 2015, Hoyer et al., 2010, Nambisan et al., 2007).
The motive ‘personal integrative benefit’ relates to a benefit which enhances the customer’s own status, influence, self-confidence and self-efficacy when participating (Constantinides et al., 2015, Nambisan et al., 2007).
The motive ‘hedonic benefit’ is a benefit that enhances the customer’s pleasurable experience, by perceiving it as being interesting, entertaining and exciting (Constantinides et al., 2015, Hoyer et al., 2010, Nambisan et al., 2007).
Constantinides et al. found that all four benefits are positively related with the likeliness of customers to engage in customer participation activities.
Hypotheses related to the effect of motives on customer participation:
H3a There is a positive effect of the motive ‘learning benefit’ on customer participation, where people with a strong learning benefit motive are more likely to participate in customer participation than people with a weak learning benefit motive.
H3b There is a positive effect of the motive ‘social integrative benefit’ on customer
participation, where people with a strong social integrative benefit motive are more likely to participate in customer participation than people with a weak social integrative
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H3c There is a positive effect of the motive ‘personal integrative benefit’ on customer participation, where people with a strong personal integrative benefit motive are more likely to participate in customer participation than people with a weak personal integrative motive.
H3d There is a positive effect of the motive ‘hedonic benefit’ on customer participation, where people with a strong hedonic benefit motive are more likely to participate in customer participation than people with a weak hedonic motive.
22 3. Research design
This paper aims to study what motives influence, through customer participation, the degree of the service outcome “satisfaction”, and what role customer participation readiness factors play in this effect.
3.1. Research method
The analysis of this research is mainly quantitative, highlighting patterns. The findings are compared to theory in order to delineate the patterns which exist. The structure of this research is based on academic literature. The research is effectuated using online questionnaires, hence this method is commonly used for collecting data and questionnaires are well known and easy to comprehend for respondents (Saunders and Lewis, 2012). For this research the author used the SkyPriority Panel of SkyTeam Alliance.
3.2. Participants
To carry out the empirical study, this study used the data drawn from an online survey among SkyPriority Panel participants. The SkyPriority Panel is a customer panel who regularly provide feedback on their travel experiences. More specifically, they provide feedback on SkyPriority product/services implementation such as signage, line priority and baggage pickup. All panelists underwent thorough screening before being selected and invited by SkyTeam to take part in customer participation activities and serve as a model customer participation population. In order to become a SkyPriority Panel member, candidates had to fill in an online intake survey (see Appendix 1). These intake surveys were distributed in the following languages: English, Simplified Chinese, Traditional Chinese, Spanish, French, German, Russian, Italian, Czech, Arabic, Romanian, Korean, Dutch, Japanese, Vietnamese, and Indonesian. Only applicants with
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a fully completed in-take survey were admitted for recruitment and no incentives were used. The following rules were used for the screening of the panelist:
- Planned at least 2 trips with a SkyTeam member airline in the coming 12 months - Owner of an Android or iOS mobile device (smartphone or tablet)
- Member of at least one of the frequent flyer programs (FFP) from a SkyTeam member airline - SkyPriority eligible, hence profiled as a High Value Customer (HVC):
IF [(travel class=Business/First)] OR [(travel class=Economy) AND (FFP status=Elite+)] - Opt-in to become a SkyPriority Panel member: indicated to have interest in joining the panel
(after having seen an infographic, explaining about the program)
As this study is intended to reflect customers in general, the population comprises all potential customers for SkyPriority. For this field research the SkyPriority Panel was used consisting of 24,337 participants who are considered eligible to use SkyPriority services. During their initial intake for becoming a panelist, they indicated their language of preference.
The inclusion criteria for the prospective subjects was the English language, as the
questionnaire was only available in English. Hence, the invitation emails containing a survey link were sent to English speakers only (see Appendix 2). The subgroup to which an invitation to fill the questionnaire was sent consisted of 3,513 panelists. The sample on which the analyses were based consisted of 573 respondents with fully completed surveys. The response rate was 16.31%.
A total number of 369 incomplete surveys were excluded from this study, people who clicked on the link but did not finish the survey. The largest amount of dropout was with the first question.
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3.3. Materials
Quantitative questionnaire. The survey was distributed to the total population and was conducted by means of an online quantitative questionnaire which consisted of five modules, structured around the research model:
1. Socio-demographic profile 2. Customer Participation 3. Motives
4. Satisfaction
5. Customer Participation Readiness Factors
Socio-demographic profile. This module is used for descriptive and weighting purposes. Data is weighted based on the known demographic profile of the panel participants.
Customer Participation. This module consists of 1 single response question with 7 selectable answers to assess the level of the self-reported customer participation for our
participants (from 1 to 6 of where low scores indicated a low level of customer participation and high scores indicated a high level of customer participation, whereas a 7 score meant that
customers had no possibility to participate as they did not receive the opportunity to download the app needed for customer participation), adapted from Verhaeghe et al. (2016).
Motives. Motives were measured on a 4-item scale (Cronbach’s alpha: .843 for learning benefits, .812 for social integrative benefits, .878 for personal integrative benefits and .914 for hedonic benefits), adapted from Constantinides et al.( 2015), some example items included: “I take part in customer participation activities when such activities enhance my knowledge about the product and its usage” and “I take part in customer participation activities when such
activities offer me satisfaction from influencing product design and development.” This measure contained 14 statements to be answered on a seven point Likert-scale (ranging from 1= strongly
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disagree to 7= strongly agree) to assess the self-reported customer participation motives for our participants. During analysis these motives were ranked, but more importantly, they were correlated with variables on satisfaction.
Satisfaction. Satisfaction was measured by using three, seven-point Likert-type
statements (Cronbach’s alpha: .830), adapted from Voss, G. B., Parasuraman, A., & Grewal, D. (1998), an example item included: “I was satisfied with the service provided”. Each item had a seven-point scale with a midpoint labeled “neither agree nor disagree” and anchored with “disagree very strongly” and “agree very strongly”. This scale is used as it is intended to measure the degree to which a customer is satisfied with a service that has been experienced or received.
Customer Participation Readiness Factors. Customer participation readiness factors were measured on a 2-item scale (Cronbach’s alpha: .934 for perceived ability and .880 for role identification), adapted from Dong et al. (2015), some example items included: “I am fully capable of reviewing SkyPriority products/services myself” and “I am glad to perform some service roles that would normally be provided by the company”. This measure contained 7 statements to be answered on a seven point Likert-scale (ranging from 1= strongly disagree to 7= strongly agree). Here the author used a regression analysis to test for the moderation effect from customer participation readiness factors on the already established relationship between
customer participation motives and satisfaction, should one exist.
3.4. Procedure
The panel participants were invited for this research via email (see Appendix 2). Before the invitations were sent duplicate email addresses were removed. For the sake of cost and
convenience, only an English-language questionnaire was used (see Appendix 3). Each of these panelists received one invitation email on 28 July 2017, the date the survey was made available.
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The fieldwork period for data collection lasted for eight days. After 4 August 2017, the online survey was closed and no more submissions were accepted. A market research agency was used for collecting data. However, conducting statistical analysis, interpretation and analysis for the model as described in this paper was done by the author. No rewards or incentives were provided to the respondents.
3.5. Statistical analysis
The Refined conceptual framework including hypothesis (Figure 2) is divided into two parts for statistical analysis.
Statistical analysis part one relates to the effect of customer participation on satisfaction (H1) and the moderating effect of customer participation readiness factors on the relation between customer participation and satisfaction (H2a and H2b). For answering H1, H2a and H2b, a multiple linear regression model is used, with satisfaction as the dependent variable, customer participation as independent variable and with perceived ability and role identification as moderators.
Statistical analysis part two relates to the effects of the four motives on customer participation (H3a, H3b, H3c and H3d). For answering H3a, H3b, H3c and H3d, likewise, a multiple linear regression model is used. In this model customer participation serves as the dependent variable, and the four motives ‘learning benefit’, ‘social integrative benefit’, ‘personal integrative benefit’ and ‘hedonic benefit’ as independent variables.
27 4. Research results
4.1. Validity of scales
Motives. An exploratory factorial analysis was conducted. The validity for conducting an exploratory factorial analysis is commendable and allowable since KMO (Kaiser-Meyer-Olkin measure of sampling adequacy) showed a higher value than .800 (KMO = .954), proving the sample size to be sufficient (Mitrea et al., 2009), and Bartlett’s test showed to be highly significant (p < .001), meaning there is significant correlation between the items in order to perform a factor analysis (Barlett, 1954; Kaiser, 1970). The factor analysis resulted in showing two factors seemingly corresponding with internal and external motives. Because it was the goal of current study to address the influence of the four motives ‘learning benefit’, ‘social integrative benefit’, ‘personal integrative benefit’ and ‘hedonic benefit’ on customer participation, the author decided to maintain the original four constructs with the items as proposed by Constantinides et al.( 2015). This is supported by the reliability analysis as the Cronbach’s alpha values of each of these four motives showed a higher value than .700 for the given survey, which means a strong inner reliability (Cronbach, 1951). The Cronbach’s alpha value for ‘learning benefit’ motive was .877, for ‘social integrative benefit’ motive .834, for ‘personal integrative benefit’ motive .844, and for ‘hedonic benefit’ motive .886.
Customer Participation Readiness Factors. An exploratory factorial analysis was conducted. KMO showed a higher value than .800 (KMO = .871) and the Bartlett’s test showed a high significant (p < .001). The outcome of the factor analysis was in line with the scale as proposed in literature by Dong et al. (2015). Furthermore the Cronbach’s alpha analysis indicated strong inner reliability. The Cronbach’s alpha values were .904 for perceived ability, and .900 for role identification. The author could conclude that these customer participation readiness factor scales were suitable for the further analyses.
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Satisfaction. In accordance with literature (Voss et al., 1998) the scale used to measure satisfaction was based on three statements of which the last one was a reversed statement: “I was unhappy with the level of SkyPriority service provided”. However, the reliability statistics
including all three statements turned out too low (Cronbach’s alpha: .513). A correlation analyses indicated that of the three statements, the reversed statement was not correlating with the other statements. For that reason, the author decided to drop the reversed statement and only continue with statements one and two. The internal reliability on these two statements only improved accordingly to an acceptable level (Cronbach’s alpha: .853).
4.2. Demographic profile of the sample
The study is based on a total of 573 respondents who fully completed their questionnaire. From these respondents, 91% were males and 9% females with an average age of 45.5 years. The sample studied enclosed 146 Asians, 202 Europeans, 33 Middle Easterners, 129 North Americans, 23 South Americans and 40 respondents from other parts of the world. Out of all participants, 87% were Elite+ members, with their FFP (frequent flyer program) tier level they are automatically eligible for SkyPriority services, regardless their travel class on SkyTeam member airlines. Furthermore out of all participants, 60% actively take part in customer participation activities (Table 1).
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Table 1. Sample demographics.
4.3. Regression analyses and testing hypotheses
Statistical analysis part one
Assumptions assessment. For the use of multiple linear regression analysis, five
underlying assumptions were checked (Gelman and Hill, 2007; Field, 2013). The assumption of no multicollinearity was tested by the variance inflation factor statistic (VIF < 5.00; Tolerance > .20), which ensured that the independent variables were not highly correlated with each other
Overall Active CP Inactive CP
N= 573 N= 341 N= 232 Male 522 (91) 318 (93) 204 (88) Female 51 (9) 23 (7) 28 (12) 45.5 (± 11.11) 44.0 (± 10.72) 47.80 (± 11.32) Asian 146 (25) 74 (22) 72 (31) European 202 (35) 123 (36) 79 (34) Middle Eastern 33 (6) 19 (6) 14 (6) North American 129 (22) 80 (23) 49 (21) South American 23 (5) 18 (5) 5 (2) Other 40 (7) 27 (8) 13 (6) Elite+ 499 (87) 300 (88) 199 (86) Elite 50 (9) 29 (8) 21 (9) Base 24 (4) 12 (4) 12 (5) Gender N (%) Age in years M (± SD) Characteristics Nationality N (%)
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(Hutcheson and Sofroniou, 1999). The assumption that the residuals were not linearly auto-correlated was checked with the Durbin-Watson test (d = 1.884), which valued around 2
indicating no autocorrelation, thus meeting the assumption of independence (Durbin and Watson, 1951). The assessment of the assumption for normally distributed residuals showed a distribution slightly skewed to the left. It should be noted however that this deviation was minimal and not deemed problematic for conducting the analysis (Lumley et al., 2002). And finally the
assumptions of linearity and homoscedasticity were checked, showing a linear relationship between the outcome variable and the independent variables, and similar variance of error terms across the independent variables. The dataset was checked for outliers and no significant outliers were found considering the fitted Gaussian distribution of the data.
Hierarchical multiple linear regression analysis. For the first part of the statistical analysis a hierarchical multiple linear regression analysis was performed aiming to understand the effect of customer participation (independent variable) on satisfaction (dependent variable) and the moderating effect of customer participation readiness factors (moderators) on the relation between customer participation and satisfaction. The descriptive statistics with a summary of the data used in the study is provided in Table 2.
Table 2. Means (M), Standard Deviations (SD), and Correlations among the study Variables.
M SD 1 2 3 4 Customer Participation 4.13 1.79 _ Perceived ability 5.90 1.13 .169** _ Role identification 5.57 1.31 .149** .590** _ Satisfaction 4.83 1.48 -.079* .208** .216** _ *significance p < .05; **significance p < .01 Note.
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The regression model showed an R-squared value of 8% (R² = .078), the percentage of the satisfaction variable variation that is explained by the regression. The regression model was significant which was tested by means of the ANOVA (p < .001). The results of this hierarchical multiple linear regression analysis are demonstrated in Table 3.
Table 3. Hierarchical Multiple Regression Analysis on Satisfaction unstandardized coefficients.
The analysis of this hierarchical regression model is to be based on the most comprehensive model which in this case is model 3.
The result shows a significant (p = .003) but negative relationship between customer participation and satisfaction. The predictor ‘customer participation’ has a negative b-value (b = - .105) which indicates that if customer participation increases by one unit the satisfaction will decrease by .105 units. This interpretation is only true if the effects of the other predictors
Model 1 Model 2 Model 3
Variable B B B
-.065 -.105** -.105**
Perceived ability .163* .165*
Role identification .206** .210***
Customer participation x Perceived ability -.008
.021
R² .006 .077*** .078***
F 3.402 14.961*** 9.034***
ΔR ² .006 .071*** .001
*significance p < .05; **significance p < .01; ***significance p < .001 Customer participation
Customer participation x Role identification
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are held constant. Nevertheless, since the effect turns out to be negative instead of positive, contrary to what the alternative hypothesis suggests, hypothesis H1 is not supported.
The regression analysis shows that moderation influence from the predictor ‘perceived ability’ between customer participation and satisfaction was not significant (p > .05). Hypothesis H2a is therefore not supported.
Equally, it shows no significant moderation by the predictor ‘role identification’ between customer participation and satisfaction (p > .05). Hypothesis H2b is therefore not supported.
In addition, to support the conclusion and discussion of these results, an overview was conducted on how the scores for satisfaction are distributed among the respondents based on their level of customer participation, which appears in Table 4. Accordingly to the outcome the level of customer participation does not appear to have an impact on satisfaction. The mean satisfaction shows similar values per customer participation group level.
Tabel 4. Means (M) and Standard Deviations (SD) of the scores for Satisfaction among the Customer participation group levels.
Statistical analysis part two
Assumptions assessment. The second part of the statistical analysis required the use of multiple linear regression analysis. The assessment of the five assumptions was also performed
N (%) M SD
No customer participation 200 (37) 4.94 1.58
Low customer participation 74 (14) 4.80 1.37
Medium customer participation 79 (14) 4.82 1.33
High customer participation 188 (35) 4.67 1.48
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prior to this analysis (Gelman and Hill, 2007; Field, 2013). The assumption of no
multicollinearity has been met (VIF < 5.00; Tolerance > .20). Likewise the assumption of independent errors has been met (d = 2.053). The assumption for normally distributed residuals was checked, but the histogram showed a deviation, skewed to the left. This seems to be caused due to the customer participation scale used, which is most likely too limited. However as neither transformation, apart from being discussible in this case, nor removal of outliers were expected to have led to an improvement of normality, the author decided to continue (Lumley et al., 2002). Lastly the assumptions of linearity and homoscedasticity have been met. Dataset was checked on outliers and no significant outliers were found.
Multiple linear regression analysis. For the second part of the statistical analysis a multiple linear regression analysis was performed to investigate the effects of the four motives (independent variables) on customer participation (dependent variable). The descriptive statistics with a summary of the data is provided in Table 5.
Table 5. Means (M), Standard Deviations (SD), and Correlations among the study Variables
M SD 1 2 3 4 5
Learning benefit 5.05 1.40 _
Social integrative benefit 4.37 1.50 .660** _
Personal integrative benefit 4.86 1.33 .804** .699** _
Hedonic benefit 4.75 1.45 .733** .687** .786** _
Customer Participation 4.13 1.79 .045 -.074* .005 -.054 _
*significance p < .05; **significance p < .01 Note.
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The regression model showed an R-squared value of 3% (R² = .028), the percentage of the customer participation variable variation that is explained by the regression. The regression model was significant, which was tested by means of the ANOVA (p = .004). The results of this multiple linear regression analysis are demonstrated in Table 5.
Table 5. Summary of Multiple Regression Analysis for Customer Participation (N= 573)
The result shows that there is a positive effect of the motive ‘learning benefit’ on customer participation, where people with a strong learning benefit motive are more likely to participate in customer participation than people with a weak learning benefit motive (p < .05; β = .197). This means that the alternative hypothesis H3a is supported.
The result shows a negative influence from the motive ‘social integrative benefit’ on customer participation rather than a positive influence (p < .05; β = -.152). Contrary to what the alternative hypothesis H3b suggested and therefore the hypothesis is not supported.
The regression analysis shows that there was no significant influence from the motive ‘personal integrative benefit’ on customer participation (p > .05). Hypothesis H3c is therefore not supported.
Variable B SE(B) β t Sig. (p)
.254 .10 .197 2.643 .008
Social integrative benefit -.182 .08 -.152 -2.387 .017
Personal integrative benefit .089 .11 .066 0.795 .427
-.180 .09 -.144 -1.977 .049
R² = .028. Learning benefit
Hedonic benefit Note.
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Also in the case of ‘hedonic benefit’, the coefficient shows a negative influence from hedonic benefit motive on customer participation (p < .05; β = -.144) rather than a positive one. Conflicting with the hypothesis H3d suggestion, this hypothesis is therefore not supported.
36 5. Discussion
This chapter addresses the significance of the findings of this research, elaborates on the
theoretical implications, and the managerial implications. Subsequently it outlines the limitations of this study accompanied with directions for future research.
5.1. Significance and theoretical implications
Knowledge about the motives for customers to take part in customer participation is a relatively untapped subject in the literature (Constantinides et al., 2015; Sigala, 2014; Dong et al., 2008; Dong et al., 2015). Insight in which motives serve as predictors for people to successfully take part in customer participation and how these motives influence their satisfaction can help companies to effectively recruit and engage participants into their customer participation activities and positively enhance satisfaction.
This study aimed to identify these driving motives for customers to engage in customer participation activities, how these motives influence their satisfaction through customer
participation, and what moderating role customer participation readiness factors play on the relationship between customer participation and satisfaction.
A key implication of the results is that of the proposed antecedent constructs, only the motive ‘learning benefit’ appears to have a positive effect on customer participation. However the results reveal that there is a negative effect from customer participation on satisfaction, and the customer participation readiness factors ‘perceived ability’ and ‘role identification’ do not have any moderating effects on the relation between customer participation and satisfaction.
The study explored the effect of customer participation on satisfaction. The effect found was negative. As a result, the first hypothesis (H1) is not confirmed. To the contrary, this result suggests a significant effect in the opposite direction. The total score for satisfaction by the
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respondents was slightly above average based on a 7-point scale and the level of customer
participation does not appear to have an impact on satisfaction. Nevertheless, the respondents not active in customer participation showed slightly higher satisfaction scores, whereas respondents engaged in high customer participation showed slightly lower satisfaction scores (see Table 4). The main factor assumed to be causing this inconsistent finding is the specific conditions of the SkyPriority panel, used as sample for this research. These participants are high value customers, very knowledgeable about the premium service, auditing a premium service repeatedly, and when they report problems they perceive little is done in response. Furthermore it could still be that, regardless the above average satisfaction scores, negative service experience to be the cause for customer participation within this sample. Another more general reason which could partly explain the inconsistent finding of this empirical study is that the general academic
understanding that customer participation leads to increased customer satisfaction is mainly theoretically based (Bitner et al., 1997; Kelley et al., 1990; Chan et al., 2010; Cermak et al., 1994).
The moderating effects of perceived ability and role identification on the relationship between customer participation and satisfaction were not established. Regarding the related hypotheses (H2a and H2b), it was expected to find similar moderating effects of these customer participation readiness factors as identified in the literature by Dong et al. (2015). The
hypotheses H2a and H2b therefore do not hold true.
Not within the scope of this study to research but interestingly enough, results showed a positive direct effect of both perceived ability and role identification on satisfaction, but with no moderating effects of these constructs in the relation between customer participation and
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satisfaction, but are not relevant in the relationship between CP and satisfaction which is contrary to the findings by Dong et al. (2015) in her research.
From the four suggested motives, this study found that the motive ‘learning benefit’ is positively associated with customer participation, where people who have strong learning benefits are more likely to take part in customer participation than people with low learning benefits. The hypothesis H3a therefore holds true. This outcome is in line with one of the four motives suggested by Constantinides et al. (2015).
In contrast to the author’s expectation, this study found a negative effect for the motives ‘social integrative benefit’ and ‘hedonic benefit’ rather than the expected positive effects, suggesting that people with high social integrative and hedonic benefits are less likely to take part in customer participation than people with low social integrative and hedonic benefits. The hypotheses H3b and H3d therefore do not hold true. This outcome is contradictory to the suggested motive constructs by Constantinides et al. (2015) and could have two possible explanations: (1) Constantinides based his suggested motive constructs solely on literature review findings and used an unnatural setting, whereas in this study these suggested motive constructs are tested in a real life setting and it shows that there are other effects; (2) the outcome measure is different as Constantinides his motive constructs were based on online co-creation activities as a form of customer participation, whereas in this study these motive constructs are researched on customer audit activities as a form of customer participation. Perhaps the motive benefits differ between these two activities of customer participation and other constructs, which could have an impact on customers their intention to take part in customer participation, need to be considered.
Finally, in this study the motive ‘personal integrative benefit’ could not be established as one of the antecedents for customer participation. As a result, hypothesis H3 is not confirmed.
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This construct is one of the suggested motive constructs by Constantinides et al. (2015) which was expected to show a positive effect on customer participation. The explanation for this deviation is equal to the two possible ones given in the previous paragraph.
5.2. Managerial implications
The findings of this research are particularly useful for businesses which actively integrated customer participation in their business activities or intend to adopt customer participation strategies.
First, this study provides insights to managers about the motives affecting customer participation engagement. This information can be particularly interesting for managers involved in recruitment of new volunteers as participants or involved in participant-retention activities. With the knowledge that there is a positive effect of the motive ‘learning benefit’ on customer participation, managers can now concentrate their resources specifically on people with a strong learning benefit motive and tailor their recruitment program and communication accordingly. Furthermore, managers can sophistically incorporate or embed learning benefit motive elements into the design of their customer participation activities or propositions. To think of elements like related to the acquisition of knowledge or environmental insights. With the insight that both the motives ‘social integrative benefit’ and ‘hedonic benefit’ cause a negative effect on customer participation instead of a positive one, it is recommended for managers to avoid customers who are strongly inclined to have a preference for one of these motives.
Second, another finding with managerial implications in this empirical study is the fact that the effect of customer participation on satisfaction turns out to be negative. The assumption is that the more conscious about the business the participants are, the more critical they become. Managers should reconsider the purpose of their customer participation strategy. If it is solely
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with the idea of enhancing satisfaction among these participants, than it is recommended for companies not to assume that it will naturally lead to improved satisfaction, but rather test it first. Or it is recommended to consider other types of activities than customer participation.
Furthermore, when recruiting customers for customer participation activities, managers should also evaluate if highly satisfied customers are the right target group to focus on, with the knowledge that there is a high probability that this will reduce their satisfaction level. These customer participation activities can however generate useful information for businesses which can be converted to service and/or product improvement efforts that may enhance the general customer satisfaction.
5.3. Limitations and directions for future research
The findings of this study are subject to a number of limitations. While there is an effect with an apparent causal relationship between all of these factors as identified in the literature and research data, the suggested model does not sufficiently explain the interaction. It could be that there are confounding variables such as the number of interactions a customer has with the service, the type of service, the perceived or actual impact their participation is having on the service etc. These confounding variables may have prevented validating the model.
The reason some of these relationships failed to show up in this study as they did in some of the literature reviewed (Constantinides et al., 2015; Dong et al., 2015) is that in those studies the services were one-off interactions, whereas SkyPriority Panel members use the service regularly.
It could also be that the relationships between these variables are weak and as such, difficult to test for. It is quite common for findings in social sciences to be difficult to replicate, leading to the possibility that some published findings are in reality type I errors.
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The proposed model was relatively complex and it could be that the study was not accurately isolating and measuring the right variables (Box, 1979). Such models can be hard to validate in a single study, even with a solid literature review and relying on validated
instruments. The nuances of this particular set of customers, this particular service, and the history of the panel could all be confounding the measures used in this study.
Self-selection of sample in which it is likely to have a degree of self-selection bias. For example, the decision to participate in the study may reflect some inherent bias in the traits of the participants which can either direct to the sample not being representative of the population being researched, or exaggerating some specific finding from the research.
The sample showed a disproportionate distribution among men (91%) and women (9%). A different ratio among men and women may have led to a different outcome. This distribution however is in accordance with the ratio represented in the SkyPriority panel.
No extreme effects were observed but one can argue that low R-squared values can be expected in a field that attempts to predict human behavior as humans are simply harder to predict.
In order to get a better understanding of the phenomena of customer participation, more research is required. Direction for future research is to use an experimental design research. Given the complexity, perhaps several iterative studies could be used to more carefully
understand how best to isolate and measure each of these variables and then identify if and how these variables are interacting with each other. It would be possible, for example, to conduct one study just on the interaction between customer participation and customer satisfaction. And then step-by-step build a model.
Another avenue for further research to get a more fine-tuned understanding is by adding other variables to the model. Apart from control variables like e.g. education and age, one could
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think of adding the “Big Five” personality traits, which by many contemporary personality psychologist are believed to be the five basic dimensions of personality. The five personality traits described in the literature are extraversion, agreeableness, conscientiousness, neuroticism, and openness to experience. Matzler et al. (2005) for example, researched relationships between the concept of customer satisfaction in relation to some of these personality traits and emotions in settings with high customer participation.
Furthermore, there are numerous other motives customers might have when engaging in customer participation activities which were not taken into account in the proposed model. Future research examining other motives for customer participation could be a promising extension to this study.
Depending on the customer participation activities, a lack of impact, feedback or
recognition for participation to the customer, may cause a negative impact on satisfaction. Future research should take these predictor variables into account.
Lastly in future experimental design the researcher can secure randomization of the sample by using a controlled experimental design to eliminate self-selection bias. The shortcoming of this method however is that it is an artificial setting rather than a real world situation.
43 6. Conclusions
This study aimed to identify the driving motives for customers to engage in customer participation activities, how these motives influence their satisfaction through customer participation, and what moderating role customer participation readiness factors play on the relationship between customer participation and satisfaction.
This study employed an online survey among SkyPriority Panel participants. Based on data from 573 respondents, several hypotheses were tested.
The outcome of this study indicates that, according to proposed model, only the motive ‘learning benefit’ has a positive effect on customer participation. Furthermore, the results show a negative effect from customer participation on satisfaction, and that customer participation readiness factors ‘perceived ability’ and ‘role identification’ do not have any moderating effects on the relation between customer participation and satisfaction.
As pointed out in the introduction, an increasing number of companies understand that, in order to achieve a competitive edge nowadays, customers should be at the center of a
company. In this context, customer participation activities have become instrumental to several companies in their daily business. This research provides insights for companies that contribute to effectively recruit and engage customers into customer participation activities which can lead to a better business performance. Nevertheless more research is needed to understand the complex phenomena of customer participation and satisfaction.
