A Liquid Approach to Consumption: how liquid consumption and regulatory focus affect consumer brand attitude and purchase intention

A Liquid Approach to Consumption:

How liquid consumption and regulatory focus affect consumer

brand attitude and purchase intention

Liis Milk

Student number: 11354143

Master’s Thesis

Supervisor: dr. S.F. Bernritter Graduate School of Communication

Master’s programme Communication Science, Persuasive Communication

Abstract

The popularity of social media is continuously increasing and brands use this in their

advantage to persuade consumers. However, as consumers are moving away from ownership and prefer ephemerality and flexibility in their consumption, brands need to understand which products and services yield the greatest engagement in consumers. Therefore, this research aims to fill a gap in existing consumer behaviour literature by investigating whether a new theory of liquid consumption may provide a greater understanding about the way different services affect consumer brand attitude and purchase intention on social media. More specifically, this research investigated whether user-generated content (UGC) on Instagram promoting a service with more liquid properties would have a stronger impact on consumer attitude and purchase intention than UGC promoting a service with more solid properties. In addition, this study also expected individuals’ regulatory focus to have an influence on this relationship. An online survey experiment with a 2 x 2 between subject factorial design was conducted among 92 participants. The results indicate that exposure to UGC promoting more liquid service had a significantly stronger effect on consumer attitude and purchase intention than exposure to UGC promoting more solid service. However, regulatory focus did not have a significant influence on this relationship. This research implies that in order to persuade consumers, brands should focus on products and services that facilitate liquid lifestyle of consumers. As one of the first studies to empirically test out the theory of liquid consumption, this study provides a good starting point for discussion and further research.

Keywords: liquid consumption, regulatory focus, user-generated content, consumer

Introduction

In the last century there has been a rapid increase of Internet-based messages transmitted through social media (Mangold & Faulds, 2009). Consequently, consumers are turning away from traditional media (e.g., television and newspapers), and prefer Internet and social media in their search for information (Casaló, Flavián & Ibáñez-Sánchez, 2017;

Mangold & Faulds, 2009). Due to the increase of consumers on the Internet it is important for marketers to have a better understanding of their online behaviour (Schivinski & Dabrowski, 2016). The importance becomes pertinent in the light that social media advertising is

changing traditional marketing communication. While marketing determines the success of newly released products, peer-to-peer communication is more crucial in determining the product success in the long run (Gaikar & Marakarkandy, 2015).

Peer-to-peer communication, also referred to as electronic word-of-mouth (eWOM) communication, has become an important source of product information with considerable influence on consumers’ purchase behaviour (Tsao, 2014). It has been found to influence consumer awareness, attitude and purchase intention (Mangold & Faulds, 2009). Instead of seeing it as a threat, brands and companies are assigning greater importance to eWOM management and use it as a tool in developing new marketing strategies (Tsao & Hsieh, 2015). Brands know the power consumers have and therefore encourage them to create brand-related content (Arnhold, 2008; Geurin & Burch, 2017). They then use this user-generated content (UGC) on their own social media page to persuade consumers, as information coming from other consumers is believed to increase the credibility of the message.

UGC plays an especially important role in promoting products that are harder to evaluate prior to the purchase. These kind of products may be categorized as experience goods, and as the name suggests are related more to experiences and services (e.g., club

memberships). Senecal and Nantel (2004) argue that consumers are more likely to rely on other consumers’ product recommendations about experience products. This is important as we are heading towards an economy that values experiences over possessions (Pine & Gilmore, 1998). And while preference for non-ownership consumption is continuously growing, the aim of this research is not to suggest that ownership and possession will loose their value for consumers. Rather, the focus of this research is to extend the current

knowledge of the way ownership and non-ownership consumption differ from one another. A framework for comparison is offered in liquid consumption theory by Bardhi and Eckhardt (2017), where ownership and non-ownership consumption are seen as two ends of the same consumption scale.

Bardhi and Eckhardt (2017) argue that the nature of consumers’ relationship to

consumption and value derived from objects, services and experiences may be temporary and context specific. Consumers are more detached from possessions, and they value objects for the functionality and immateriality (Bardhi, Eckhardt & Arnould, 2012). Further, products that provide access are valued over possessions as they facilitate variety seeking (Bardhi & Eckhardt, 2017). For example, variety achieved through accessing many different cars (e.g., car sharing companies) instead of owning a car or by getting a membership to clubs or organizations (Bardhi et al., 2012; Botsman & Rogers, 2010). While it is argued that this liquefied relationship to object is different from solid relationship, there is currently not enough empirical evidence to support this line of argumentation. Therefore, this research aims to fill the gap in the literature by investigating the way consumer behaviour differs in the context of services that either facilitate solid or liquid consumption.

The impact different products and services have on consumer attitude and purchase intention is also dependent on individuals’ personal characteristics. One important

different information and how they make decisions (Kumashiro, Rusbult, Finkenauer & Stocker, 2007). People with promotion focus choose to put emphasis on the positive outcomes without considering the losses (Fan & Zhang, 2015). They are more open to new opportunities and prefer a variety when making a decision. On the other hand, people with prevention focus put emphasis on the possible negative consequences and prefer stability over variety and new opportunities (Fan & Zhang, 2015). This means that even when presented with a similar situation, different people will make different decisions based on their regulatory focus. As such, regulatory focus should also be considered when trying to understand the way different services affect consumer’s attitude and purchase behaviour.

This research contributes to the literature in several ways. As marketing scholars have recognized non-ownership consumption as an important research direction, this study will fill a gap in the literature by testing out the concept of liquid consumption within consumer behaviour research (Akbar, Mai & Hoffmann, 2016). Secondly, this research will add to the literature by testing the interplay of liquid consumption and individuals’ regulatory focus on consumer brand attitude and purchase intention. Finally, as this research is the first to empirically test the liquid consumption theory, this study also contributes to the literature by creating an initial scale that serves as a starting point in making liquid and solid consumption measureable.

The societal relevance of this study becomes evident in the light that brands and marketers and continuously trying to understand how to best persuade consumers on social media. This can be especially difficult now that consumers are turning away from more traditional ownership consumption and look for alternatives that would provide them with more fluidity and mobility. This research can therefore help brands to have a better idea about strategies that would lead to stronger brand attitude and greater purchase intention in consumers.

In conclusion, the aim of this research is to understand the role liquid consumption and regulatory focus play on shaping consumer behaviour on social media. Based on this, a research question is formulated:

RQ: What is the effect of user-generated content on Instagram promoting either liquid

consumption service or solid consumption service on consumers’ brand attitude and purchase intention, and is this influenced by people’s regulatory focus?

Theoretical framework Social media advertising and user-generated content

An early research by Burnkrant and Cousineau (1975) found individuals’ behaviour to be most commonly determined by the influence of other people. As such, it is not surprising that social media advertising is changing traditional marketing communication. More specifically, brand communications previously controlled by marketing managers are now being shaped by consumers (Schivinski & Dabrowski, 2016). Fan and Miao (2012) argue that during a purchase decision, consumers often turn to other consumer reviews found online. These reviews, also referred to as eWOM communication, are recognized as a dominant factor in consumer purchase behaviour forming today (East, Hammond & Wright, 2007). This finds support in the research by Wang, Yu and Wei (2012) concluding that peer communication in social media has a positive influence on consumers purchase intention.

Peer communications is found to have an even bigger impact on consumers than store reputation or assurance seals (Utz, Kerkhof & Van Den Bos, 2012). Therefore, in order to persuade consumers, brands have adapted a new kind of marketing technique where they choose to share user-generated content (UGC) on their social media page. UGC refers to a newer type of brand promotion created and shared by users on their social network page. It is

often accompanied by a hashtag (#BrandX), making it easy for brands to monitor the shared content. This kind of posts have gained increased popularity because research shows that UGC (compared to brand content) masks the persuasive intent of a message. In turn, if the advertising is not perceived as persuasive, it is believed to have a stronger affect on consumer behaviour (Van Noort, Antheunis & Van Reijmersdal, 2012).

Consumers also feel that UGC is more objective, reliable and credible than information coming from companies (Tsao & Hsieh, 2015). They prefer other consumers’ information because in addition to the general product information it also includes other users’ experience with the product or service (Utz et al., 2012). Therefore, UGC becomes relevant in situations, where consumers use social media to make a decision about products or services that are harder to evaluate. This is important in the light that we are moving towards an experience economy where consumers prefer experiences over products (Pine & Gilmore, 2013).

Liquid consumption

For many decades’ consumer research has seen material possessions as an expression and extension of self-hood (Bardhi et al., 2012). Ownership of material possessions has commonly been associated with adulthood and it is believed to be superior because it

provides people with independency and security (Baumeister, 2014). However, ownership is no longer the only desired solution to consumers’ needs (Baumeister, 2014). Due to the constant changes taking place in the global marketplace we are now seeing a rise of a

competing consumption mode called non-ownership consumption (Lawson, 2011). Younger population plays especially important role in this shift as they choose to organize their lives around travelling (Richards, 2015). To better understand this new kind of relationship that

consumers form with the material world, Bardhi and Echkardt (2017) developed a framework that focuses on a consumption mode described as liquid consumption.

Liquid consumption theory (LCT) by Bardhi and Eckhardt (2017) is used to describe a new dimension of consumption along a solid-to-liquid spectrum. They describe liquid consumption as “ephemeral, access based and dematerialized”, and contrast it with more “enduring, ownership-based and material” form of solid consumption (Bardhi & Eckhardt, 2017, p. 585). LCT is an extension of a theory of liquid modernity introduced by Bauman (2000), who sees fluidity and liquidity as fitting metaphors when understanding the way life has changed from being stable to being more uncertain and rapidly changing (Bardhi & Eckhardt, 2017; Bauman, 2013). This also applies to social structures that used to serve as frames of reference, but have become weakened and ephemeral with time (Bauman, 2013). Therefore, people have to find new ways to organize their lives in this liquefied society (Bardhi & Eckhardt, 2017). Bardhi and Eckhardt see liquid consumption as a way for

consumers to facilitate an appropriate lifestyle. Whether this also has an impact on consumer decision making process has not yet been empirically testes, however there are reasons to believe that ephemerality, access and dematerialization all play a role in persuading consumers.

Ephemerality refers to the temporal nature of consumption encompassing the duration of a transaction between the consumer and the provider, as well as the length of the product use (Baumeister, 2014). Ephemerality is especially prevalent among younger population, also referred to as global nomads, who move from place to place and value possessions only temporarily in each locale (Bardhi et al., 2012; Bardhi & Eckhardt, 2017). They often seek convenience and prefer non-ownership consumption over the burdens of ownership as it enables fluidity in their lifestyle (Bardhi & Eckhardt, 2017). As such, it may be argued that in a decision making process consumers would prefer products and services that provide them

with more convenience. This is in line with previous research on non-ownership consumption that has established a link between consumers’ convenience orientation and buying decisions (Berry, Seiders & Grewal, 2002). Researches by Moeller and Wittkowski (2012), and

Baumeister (2014) are two of the more recent examples of that.

Moeller and Wittkowski (2012) were set out to understand the reasons behind consumers’ growing preference for non-ownership consumption. They found that

convenience has a positive influence on consumers’ preference orientation. The second study by Baumeister (2014) compared the differences between access (one type of non-ownership consumption) and ownership, and investigated how the success of an access offering depends on the service convenience. He found that service convenience has a significant role on consumer attitude. He also found this to be important in the case of behavioural intention, however the results were narrowly not significant (Baumeister, 2014). This shows that consumers have a preference for non-ownership consumption as it allows them to enjoy the convenience of the service and avoid the responsibility and commitment that comes with ownership (Lawson, 2011).

One of the most common non-ownership consumption types is access. Access refers to a situation, where users pay temporarily for a right to enjoy the benefits of a good owned by a third party that provides access (e.g., Netflix account or gym membership) (Baumeister, 2014). In liquid consumption access is valued over ownership because it can facilitate variety seeking (Bardhi & Eckhardt, 2017). Estrella-Ramón’s meta-analysis (2014) of studies

examining the relationship between the variety size and consumer behaviour provides confirmation that bigger variety size has a stronger impact on consumer behaviour. Kahn’s research (1995) supports this line of argumentation. His research focusing on the variety-seeking of consumers highlights that one motivation for choosing variety in purchase situation is related to the uncertainty that one feels about the future preferences. Thus,

consumers wish to preserve as many future options as possible. This is relevant for brands who could use bigger variety size to make their product more appealing and therefore increase consumer attitude towards the brand and consumer purchase intention.

Variety size is also relevant as consumers may perceive the different options as a chance to gain new experiences. Research by Lawson, Gleim, Perren and Hwang (2016) investigating consumers’ motivations to engage in access-based consumption found that the ability to experience something new and different was indeed important to consumers. This is in line with LCT, where emphasis has shifted from object attachment to experiences (Bardhi & Eckhardt, 2017). Furthermore, experiential purchases are found to make consumer happier than material purchases (Nicolao, Irwin, and Goodman 2009; Van Boven & Gilovich, 2003). Van Boven and Gilovich (2003) tested this by looking whether investing their money in life experiences would make people happier than investing it on material possessions. In a series of surveys and experiments they concluded that people gained more happiness from

experiences than from material goods. Similar findings were reported in a follow-up study by Nicolao et al. (2009). Based on the assumption that consumers have started to value

experiences over material possessions it may be argued that we are moving towards a market economy where consumers look for products and services that are less material or

dematerialized.

Dematerialized products and services are valued for the intangibility and functionality as this can help facilitate liquid lifestyle of consumers (Bardhi et al., 2012). However, in the light that immaterial object and services can be difficult to evaluate, dematerialization will also have an impact on consumer decision making (Bardhi & Eckhardt, 2017). One way to evaluate this impact is through product categorization. And as dematerialization of products has many similarities with the classification of products into search and experience

material products would yield similar results. The product is considered a search good, when the information about the product is easy to acquire and can be assessed using external information (Hsu, Yu & Chang 2017; Lu, Chang & Chang, 2014). On the contrary, experience goods are more difficult to evaluate prior to the purchase (Mudambi & Schuff, 2010). Furthermore, it is found that when the product characteristics cannot be assessed directly by observation and contact, consumers will view the reaction of others as evidence about the true quality of the product (Burnkrant and Cousineau, 1975). Bei, Chen and

Widdows (2004) compared the importance of online information sources between search and experience products, and found that for the experience goods the online information sources were used more frequently and the information from other consumers was considered more important. Senecal and Nantel (2004) compared in their study experience goods with search goods and concluded that consumers are more influenced by recommendations for experience goods than for search goods. These results give grounds to argue that consumers would pay more attention to recommendations about dematerialized products and services and the information found would have a direct affect on their attitude and purchase intention.

The framework above indicates that consumer preference has changed in time and consumers are more likely to prefer products which facilitate liquid lifestyle. Especially younger consumers, whose life is filled with more uncertainty. They prefer to travel from place to place and experience new things. As younger consumers are also the main users of social media, then brands should offer products that facilitate this type of mobile lifestyle. Therefore, it is proposed that services and products that have more liquid properties, such as convenience, flexibility and variety, would have a stronger influence on consumers on social media than products and services that have more solid properties. The main hypotheses (H1) and (H2) are formulated:

H1: Exposure to user-generated content promoting a service with more liquid properties

leads to a more positive attitude towards the brand than a user-generated content promoting a service with more solid properties.

H2: Exposure to user-generated content promoting a service with more liquid properties

leads to greater purchase intentions in users than a user-generated content promoting a service with more solid properties.

The influence of regulatory focus

There are many different external factors, such as aforementioned product properties and advertising types, that have an affect on consumer decision making process. However, the way consumer come to a decision about a product and service is more dependent on the internal factors. It is believed that due to people’s unique control system different people produce different reaction in the same situation (Higgins, 1997). Some people focus more on the positive outcomes and tend to achieve positive results, while other focus more on the negative outcomes and therefore minimize the negative consequences (Fan & Zhang, 2015). These differences of focus are referred to in the literature as people’s regulatory focus, and they help us understand how and why advertising persuasion works (Micu, 2010).

The framework of regulatory focus theory (RFT) was first proposed by Higgins (1997). According to the theory, the focus-specific orientations are a major source for difference in people’s behaviour and information processing (Higgins, 2002; Florack, Friese & Scarabis, 2010). More specifically, people with different regulatory focus have different information processing patterns (Kumashiro et al., 2007). People with promotion focus target their attention towards the achievement of ideals and aspirations, while people with

prevention focus target their attention towards fulfilments of duties and responsibilities (Higgins, 1997; Werth & Foerster, 2007).

Regulatory focus also influences which information attracts more attention among people (Werth and Foerster, 2007). Information that highlights the presence and absence of positive outcome is more compatible with promotion focus, while information that focuses on the presence and absence of negative outcome is more compatible with prevention focus (Florack et al., 2010; Higgins, 2002; Hsu et al., 2017). If the information processed is

matched with people’s regulatory focus, a regulatory fit occurs. This in turn has been related to stronger persuasive effects (Aaker & Lee, 2001).

Hsu et al. (2017) research provides support for this positive relationship between consumer’s regulatory focus and message focus. Their findings show that purchase intention is significantly higher when regulatory fit occurs. More specifically, consumers with

promotion focus have a higher purchase intention when exposed to positive (vs. negative) messages (Hsu et al., 2017). This is in line with research by Werth and Foerster (2007). The results of their study confirmed that in the promotion focus, participants had a higher level of satisfaction for a product with a promotion slogan than for a product with a prevention slogan (Werth & Foerster, 2007). As UGC on brand’s pages on Instagram is promoting the products and services, then exposure to this kind of content should be more effective for people with promotion focus (vs. prevention focus) and result in higher purchase intention. Therefore, a main hypotheses (H3) is formulated:

H3: People with promotion focus will have a greater purchase intention when exposed to

either user-generated content than people with prevention focus.

In addition to the direct effect that regulatory focus has on consumer decision making process, regulatory focus may also have an influence on the relationship between liquid consumption and consumers purchase intention. Werth and Foerster (2007) argue in their

research that consumers evaluate product alternatives differently depending on their regulatory focus. People with promotion focus are found to be more open to change and prefer variety in their choices, as variety offers a way of capturing more opportunities (Pham & Higgins, 2005). On the contrast, people with prevention focus have a preference for

stability, thus they see variety of options as a potential mistake (Pham & Higgins, 2005). This is in line with the Werth and Foerster (2007) argumentation suggesting that prevention

focused consumers seek products that are safe and reliable while promotion focused consumers prefer products that are related to comfort and variety. This difference becomes relevant in the case of LCT, where liquid consumption is more related to convenience and variety. This gives grounds to argue that regulatory focus is an important factor when trying to understand how liquid consumption affects consumer purchase intention. More

specifically, exposure to liquid service promotion should lead to greater purchase intention in people with promotion focus than exposure to solid service promotion. Based on this line of argumentation, moderator hypothesis (H3a) is formulated:

H3a: User-generated content promoting a service with more liquid properties will lead to

greater purchase intention in people with promotion focus than user-generated content promoting a service with more solid properties.

Methods Design and participants

To answer the proposed research question and hypotheses (H1-H3a), a 2 (multi-gym membership vs. single gym membership) x 2 (promotion focus vs. prevention focus)

between-subjects factorial design was conducted (Table 1). This enables to compare the effects of Instagram posts depending on the consumer focus and service features (Werth & Foerster, 2007).

Table 1. 2 x 2 between-subjects factorial design

A self-administered online experiment was designed using a Qualtrics online platform. Online experiment was opted for in order to reach a more heterogeneous sample and maintain the anonymity of respondents. A convenience sample was used to recruit participants through Facebook and Instagram over the time period of 21 days, and no incentive was given. All the participants were asked to share the questionnaire with their friends and family. Participants who had never used Instagram were excluded from the study.

Facebook was used next to Instagram to distribute the survey because the

demographics of Facebook users are similar to demographics of Instagram users. According to the latest statistics, the biggest group of users are between 18-35 years old (Hutchinson, 2017; York, 2017). This age group is also the most relevant for this study, as they buy more and do more research online compared to Generation X and baby boomers (Hall, 2018).

questionnaire. Participants who did not finish the survey were excluded from the further analyses. In addition, 6 participants were excluded because they had never used Instagram. Of the final sample (N = 92), 66.7% were females. Participants ranged from 19 to 65 years of age (M = 27.26, SD = 6.63), and most had at least a bachelor’s degree (17.5%) or master’s degree (16.5%). The biggest percentage on participants were either from Estonia (26.9%) or the Netherlands (16.3%). However, as the country or origin did not have a normal

distribution, it was excluded from the further analyses.

Procedure and stimuli

The survey was comprised of five different sections. In the first section of the study participants were briefed with clear instructions and asked to confirm that they agree to voluntarily participate in the study. In addition, participants indicated whether they have ever used and/or are currently using Instagram.

In the second section of the survey, regulatory focus was manipulated. All the participants were randomly assigned either into primed-ideal condition or primed-oughts conditions. Participants in the primed-ideal condition were asked to list their past and current hopes, dreams and aspirations (promotion focus), and participants in the primed-oughts condition were asked to list their past and current duties, obligations and responsibilities (prevention focus) (Florack et al., 2010).

Following section focused on the liquid consumption. Participants were asked to imagine a certain situation where they are scrolling around Instagram and come across an Instagram post featuring a new gym membership. Thereafter, participants were again randomly assigned into one of two conditions. In both conditions, participants were first introduced to the kind of gym membership that was featured on the Instagram post. These descriptions included the benefits and possibilities that a membership would offer.

Participants in the first manipulation group saw a description and an Instagram post that featured a multi-gym membership (liquid consumption service) (Figure 1, Appendix A), and participants in the second manipulation group saw a description and an Instagram post that featured a single gym membership (solid consumption service) (Figure 2, Appendix A). To rule out any alternative explanations of the results, both posts featured the same picture and a text of the same length. The only difference between the stimuli were the names of the two different gyms, and the description. It was clearly indicated that the post was a UGC and a repost from a regular user (@move_eat_lift).

The fourth section of the survey measured the dependent variables. First, participants purchase intention was measured with three questions, and thereafter they were asked to indicate their attitude toward the membership on a 7-point semantic scale with four items.

The last section of the survey measured the solid and liquid consumption services on a 7-point scale comprised of 6 items (Appendix B). In addition, demographic data, such as gender, age, country of origin, level of education and gym membership status were gathered. In the end, participants were debriefed and the aim of the study was revealed.

Manipulation checks for regulatory focus and liquid consumption

For regulatory focus, participants saw three pairs of statements anchoring the opposite ends of 7-point scales meant to capture the conflict between ideal self and ought self (Pham & Avnet, 2004; Roy & Ng, 2012). For each pair, participants were asked to indicate whether they would prefer to: 1) “do what is right” (ought) or “do whatever I want” (ideal); 2) “take a trip around the world” (ideal) or “pay back my loans” (ought); 3) “go wherever my heart takes me” (ideal) or “do whatever it takes to keep my promise” (ought).

To measure whether participants perceived a difference between the solid

degree they agree with the statement “The Instagram post was focusing on one specific gym” (1- Strongly disagree, 7 - Strongly agree).

Scale construction for liquid consumption

Since the theory of liquid consumption has not yet been tested and measured in research, then based on the differences of solid and liquid consumption highlighted by Bardhi and Eckhardt (2017), a 6-item liquid consumption scale was created. For all six items, the answer categories ranged from 1 to 7 (1- strongly disagree, 7 - strongly agree). All six items allowed participants to indicate whether the Instagram post they saw earlier featured a membership that had more qualities of a liquid consumption service or a membership that had more qualities of a solid consumption service (Appendix B). Three of the statements highlighted the qualities that are in line with liquid consumption (flexibility, mobility, variety), and the other three focused on the qualities that are more common for solid consumption (single gym membership, feeling of belonging, strong relationships).

A principal axis analysis revealed that the 6 items form two scales: both had an eigenvalue above 1 (eigenvalue factor 1 is 2.70 and factor 2 is 1.73). Initially, the first scale had four items but one of them had a low factor loading of 0.44 and was excluded. Therefore, the first scale includes three items that focus on the liquid consumption. The second scale includes two items that focus on the solid consumption. Reliability for both scales was good: for scale 1 Chronbach’s alpha = 0.87 and for scale 2 Chronbach’s alpha = 0.77.

Measures of the constructs

Brand attitude. The dependent variable for hypotheses H1 (main effect), which reflects participants overall feeling about a brand, was measured by using items from

semantic differential items. Participants were asked to indicate how they feel about the brand (bad/good, unappealing/appealing, unattractive/attractive and dislike/like). Reliability

resulted in good Chronbach’s alpha = 0.92.

Purchase intention. The dependent variable for main hypotheses H2 and H3, and moderator hypothesis H3a, which is used to evaluate the possibility of buying a product, was measured with a three item scale with 7 answer options. Participants were asked to indicate to what extent they agree with the following statements (1 - Strongly disagree, 7 - Strongly agree): 1) I plan to join the membership in the future; 2) Given the chance, I intend to join this kind of membership in the future; 3) Given the chance, I would join this kind of membership in the future (Chen & Barnes, 2007; Hsu et al., 2017). Reliability resulted in good Chronbach’s alpha = 0.92.

Regulatory focus. The independent variable for hypothesis H3 and a moderator variable for hypothesis H3a, which is concerned with the regulatory focus that people have, posits that people can either have a promotion focus or a prevention focus. In this study, the promotion and prevention focus were induced by a manipulation adapted from previous research (Florack et al., 2010; Pham & Avnet, 2004; Roy & Ng, 2012). As stated in the regulatory focus theory, the regulation of behaviour according to duties obligations and responsibilities should activate prevention focus, and regulation of behaviour according to aspirations and hopes should activate promotion focus (Higgins, 1998; Florack et al., 2010). Therefore, participants in the promotion focus group were asked to list two of their past and current aspirations and hopes. In contrast, participants in the prevention focus group were asked to list two of their past and current obligations, duties and responsibilities. Reliability resulted in Chronbach’s alpha = 0.65.

Control variables. Five control variables (sex, age, country of origin, level of education and gym membership status) were included to rule out any alternative

explanations. Sex of the participants was determined by asking participants to indicate whether they are male, female or other, and age by asking participants to write down their age in number. In order to understand the behavioural difference between participants from different countries, a country of origin was included and measured by asking participants to choose their country of origin from a list. The level of education was measured by asking participants to indicate their highest level of school they have finished or the highest degree they had obtained (1- less than a high school degree, 2 - high school degree, 3 - bachelor’s degree, 4 - master’s degree, 5 - doctoral degree, 6 - other). Gym membership status was measured by asking participants whether they are already members of any gym.

Results Randomisation check

To see, whether randomisation of participants to the groups (promotion focus vs. prevention focus) and (liquid service vs. solid service) was successful, a cross tabulation with chi-square test was conducted for sex, gym membership status and level of education, and an independent sample T-test was conducted for age.

Regulatory focus. No statistically significant difference between groups was found for sex, X2(1, N = 90) = 1.10, p = 0.29, gym membership status, X2(1, N = 92) < 0.001, p = 0.99, and level of education, X2(4, N = 92) = 4.28, p = 0.37. After conducting an independent sample T-test, the results showed no statistically significant difference of age between the promotion (M = 26.41, SD = 3.59) and prevention (M = 25.40, SD = 3.46) groups, t(84) = 1.33, p = 0.19), 95% CI[-0.50, 2.53]. As no statistically significant difference between groups was revealed, the randomisation of participants was successful.

Liquid consumption. No statistically significant difference between groups were found for sex, X2(1, N = 90) = 0.56, p = 0.46, gym membership status, X2(1, N = 92) = 0.83, p

= 0.36, and level of education, X2(4, N = 92) = 4.28, p = 0.37. With regards to age, the results showed no statistically significant difference between the liquid service (M = 25.69, SD = 3.57) and solid service (M = 26.22, SD = 3.55) group, t(84) = -0.69, p = 0.49, 95% CI[-2.06, 1]. As no statistically significant difference between groups was revealed, the randomisation of participants was successful.

Manipulation check

To assess whether the manipulation materials worked for regulatory focus and liquid consumption manipulations, two manipulation checks were performed.

Regulatory focus. To test whether participants in the promotion focus group would place greater emphasis on ideals versus oughts, and participants in the prevention focus group on oughts versus ideals, an independent sample T-test was conducted. The results revealed that there was no statistically significant difference between the promotion focus (M = 3.59,

SD = 1.39) and prevention focus (M = 3.77, SD = 1.56) group, t(96) = -0.60, p = 0.55, 95%

CI[-0.77, 0.41]. Furthermore, both groups place greater emphasis on ideals. Therefore, the manipulation was not successful, and all further results concerning regulatory focus should be treated with caution.

Liquid consumption. To test whether participants in the solid group would agree more with the statement “This Instagram post was focusing on one specific gym” than participants in the liquid group, an independent sample T-test was conducted. The results revealed that participants in the solid group did agree more with the statement (M = 4.96, SD = 1.65) than participants in the liquid group (M = 2.47, SD = 1.69) group, t(91) = -7.19, p < 0.001, 95% CI[-3.18, 1.80]. Since a statistically significant difference between groups was revealed, the manipulation was successful.

Covariates

To assess whether any of the control variables (sex, age, level of education and gym membership status) are significantly related to the dependent variables (purchase intention for H1, H3 and H3a, and brand attitude for H2), a correlation analysis with Pearson’s r was conducted. The results revealed that gym membership status has a positive correlation with brand attitude (r = 0.34, p = 0.001) and purchase intention (r = 0.22, p = 0.03) (Table 2). Therefore, gym membership status will be included in the further analyses.

Table 2. Correlations and descriptive statistics for brand attitude and purchase intention

Main analysis

Brand attitude. With the first main hypothesis (H1) it was tested whether exposure to liquid consumption service would lead to more positive brand attitude than exposure to solid consumption service. Based on the correlation results, gym membership status was included as a covariate. A two-factor analysis of variance (ANOVA) revealed that

participants in the liquid group had a significantly higher attitude towards the brand (M = 4.97, SD = 1.29) than participants in the solid group (M = 4.19, SD = 1.23), F(1, 88) = 4.35, p = 0.04, ² = 0.05. Therefore, the first main hypothesis (H1) is supported.

Purchase intention. With the second main hypothesis (H2) it was tested whether exposure to liquid consumption service would lead to greater purchase intention than exposure to solid consumption service. Once again, based on the correlation results, gym membership status was included as a covariate. A two-factor analysis of variance (ANOVA) revealed that participants in the liquid group had a significantly greater purchase intention (M = 4.08, SD = 1.47) than participants in the solid group (M = 3.42, SD = 1.47), F(1, 87) = 4.05,

p = 0.047, ² = 0.05. Therefore, the second main hypothesis (H2) is supported as well.

With the third main hypothesis (H3) it was tested whether people with promotion focus would have a greater purchase intention than people with prevention focus when exposed to either service promotion. The results reveal an opposite but not significant difference between purchase intention for people with promotion (M = 3.57, SD = 1.40) and prevention focus (M = 3.98, SD = 1.59), F(1, 87) = 2.30, p = 0.13, ² = 0.03. Therefore, the third main hypothesis (H3) is not supported.

With the moderator hypothesis (H3a) it was tested whether regulatory focus would influence a relationship between service type and purchase intention. More specifically, it was tested whether exposure to promotion of liquid consumption service (vs. solid

consumption service) would yield a greater purchase intention in people with promotion focus. While exposure to liquid service promotion (M = 3.57, SD = 1.40) did result in greater purchase intention in people with promotion focus than exposure to solid service promotion (M = 3.57, SD = 1.40), the interaction effect was not significant, F(1, 87) = 0.26, p = 0.61, ² = 0.003. As such, the moderator hypothesis (H3a) is not supported.

Conclusion and discussion

This research aimed to find an answer to a research question whether exposure to UGC on Instagram promoting service with more liquid properties would have a stronger impact on consumer attitude towards the brand and purchase intention than exposure to UGC promoting service with more solid consumption properties. The results reveal that exposure to promotion of liquid service and promotion of solid service on Instagram do yield a different result on consumer attitude and purchase intention. However, regulatory focus appeared to not have an impact on this relationship.

The first two main hypotheses focused on the liquid consumption theory and it was expected that exposure to an Instagram post promoting liquid service would have a more positive affect on consumer behaviour than exposure to Instagram post promoting solid service. The results reveal that exposure to liquid service promotion did lead to a more positive attitude (H1) and greater purchase intention (H2) than exposure to solid service promotion. This means that consumers are more interested in a service that provides

flexibility, access and variety. These findings are in line with the results of Estrella-Ramón’s meta-analysis (2014) that found variety size to be an important factor in consumer behaviour. These findings also confirm the results of Baumeister (2014) study, who found that service convenience is an important factor in non-ownership consumption. While his study only found significant support for consumer attitude, it did not find significant support for

behavioural intention. This research adds to his findings by showing that service convenience does appear to have a significant role on both consumer attitude and purchase intention.

With regards to regulatory focus, it was expected that individuals’ regulatory focus would have an affect on the relationship between the service type and purchase intention. With the main hypothesis (H3) it was hypothesised that exposure to either UGC would lead to a greater purchase intention in people with promotion focus. The results provided no

support for the hypothesis, as exposure to either service promotion lead to stronger purchase intention in people with prevention focus. This is not in line with previous regulatory focus and regulatory fit research by Hsu et al. (2017) which showed that consumer with promotion focus have a higher purchase intention when exposed to a positive message. Our results may be explained by the fact that the manipulation for regulatory focus was not successful.

Manipulation check revealed that participants in both primed-ideals and primed-oughts group appeared to lean towards the ideals (vs. oughts), which would mean that regardless of the manipulation their focus was more compatible with promotion focus.

With the moderator hypothesis (H3a) it was expected that exposure to UGC

promoting a service with more liquid properties would lead to stronger purchase intention in people with promotion focus than exposure to UGC promoting a service with more solid properties. The results revealed that people with promotion focus did have a greater purchase intention when exposed to a liquid service promotion (vs. solid service promotion), however the difference was not significant. Therefore, further research on regulatory focus is

warranted.

Limitations and future research

The current study has three limitations that should be addressed. Firstly, initial analysis of the data revealed that this survey experiment resulted in a very high dropout rate. Out of 212 participants who started the survey, only 98 completed the full questionnaire. Most of the participants quit during the first section of the study focusing on regulatory focus. As this section included two open questions, one possible explanations may be that participants were put off by the prospect of having to write extensively (Bryman, 2012). Regardless of the high dropout rate, the randomization of participants to manipulation groups still assured that both groups had equal number of participants. Furthermore, the

randomization check assured that the groups are comparable in terms of the demographic variables (sex, age, level of education and gym membership status).

The second limitation of this study is related to the regulatory focus manipulation. As stated in the previous section, the results of the manipulation check revealed no difference between the two groups. One important aspect that should be considered is that the manipulation of regulatory focus was based on previous research, however the reliability of the scales was not reported in these studies (Florack et al., 2010; Pham & Avnet, 2004; Roy & Ng, 2012). In this study, the reliability of the scale was found to be low. As this study only focus on the participants’ induced regulatory focus and did not measure their chronic regulatory focus, no conclusion in regards to the regulatory focus can be drawn. Therefore, future research is needed that in addition to manipulating participants’ regulatory focus also measures it.

Thirdly, this study focused on only one product category (different gym memberships). This raises a question whether the findings of this study may be extended to other product categories. Therefore, more research is needed to understand how liquid consumption theory applies to different products. This kind of future research is especially important in the light that neither of the services introduced had only liquid or solid qualities. Products and services that are at the ends of the solid-liquid spectrum may produce different results.

Theoretical and practical implications

The contribution of this research to the consumer behaviour literature is twofold. Firstly, it is the first study to provide empirical evidence of the effects of liquid consumption on consumer behaviour. The results indicate that the theory of liquid consumption is relevant in understanding which services are preferred by online consumers and how to best persuade

consumers. Secondly, this study was the first to quantify the concepts of liquid consumption. By focusing on the ways liquid and solid consumption differ in their nature, an initial scale was constructed. The results revealed that the scales resulted in good reliability. As such, these results serve as a good starting point for future research on this topic.

The main practical implication of this study is that services with different properties induce different reactions from consumers on social media. Specifically, consumers on social media appear to have a more positive attitude towards a service that has more liquid qualities than service with more solid properties. This means that when brands and marketers are creating advertising for their products and services, they should take into account that consumers on social media prefer services that provide them with flexibility, mobility and variety.

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Appendix A

Manipulation material for liquid consumption

Figure 2. Multi-gym membership

Appendix B

Solid/ Liquid consumption scale

To what extent do you agree with the following statements (1 - strongly disagree, 7 - strongly agree):

1. The Instagram post was focusing on one specific gym. 2. This kind of membership gives me a lot of flexibility. 3. This kind of membership gives me a sense of belonging. 4. This kind of membership gives me freedom and mobility.

5. This kind of membership allows me to build strong relationship with other members. 6. This kind of membership is good for people who are seeking variety.