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Introduction

Irrespective of the polarized debate around the benefits and consequences of the increasing commercialization of higher education, the reality across the higher education landscape in a number of countries is that educational institutions, particularly universities, operate in a market place where students are consumers of an educational service. This includes countries such as the UK, Canada, Australia, and New Zealand, where the export of education services is now big business (OECD 2004; Naidoo 2006; Naidoo and Wu 2011, 2014). A number of scholars have picked up on this increasing marketization of higher education, including how universities are becoming more and more promotionalized in their targeting of prospective students, particularly overseas students (e.g., Binsardi and Ekwulugo 2003; Hemsley-Brown and Oplatka 2006; Hayes 2007; Bennett 2007). Chief amongst those promotional tactics that universities use to brand themselves is the use of academic rankings (Bock et al. 2014; Bunzel 2007), with research versus applied universities often a common brand positioning differentiator used in the education marketing literature (de Haan 2015). An implicit assumption borne in that literature is that, ceteris paribus, the better the ranking of an institution, the more in demand that institution ought to be with prospective students (Nguyen and LeBlanc 2001; Hazelkorn 2007). But, is this assumption correct? While no one can doubt that academic rankings act as a pull factor to prospective students, we argue in this chapter that it is way too simplistic to assume that better ranked universities will always have the upper hand in the education marketplace. Were this to be the case, we would have to assume that all prospective students have the same attitudes and behavioural intentions towards highly ranked universities. And yet, from a rich literature on consumer behaviour, we know that this is not the case and that consumers (by extension, prospective students) make diverse purchase evaluations and ultimately, decisions. As such, the research question that we pose ourselves in this chapter is whether research-intensive universities, which often are better ranked institutions since academic ranking methodologies tend to assign a heavier weightage to research output, have a comparative advantage with prospective students over their more applied counterparts. Specifically, using consumer behaviour theory, we explore this question in the forthcoming sections by examining how the regulatory system of prospective students and word of mouth (WOM) communication can play an influential role in the selection process of universities.

Literature Review

The literature on regulatory focus , a key concept in consumer behaviour theory, postulates that a consumer’s regulatory orientation will have a large influence on their product evaluation and choices (Roy and Ng 2012; Chatterjee et al. 2011; Lee and Aaker 2004; Chernev 2004; Pham and Avnet 2004), in turn impacting on purchase intention [see Motyka et al. (2014) for a recent meta-analysis on the effect of regulatory focus on product evaluation and behavioural intentions]. Two types of regulatory orientation have been advanced in the literature: “promotion focus ” versus “prevention focus ”. The former refers to a state that involves self-regulation towards advancement, accomplishment, and aspirations in life (i.e., a concern with the presence or absence of a positive outcome), while the latter involves self-regulation towards protection, safety, and responsibility in life (i.e., a concern with the absence or presence of a negative outcome) (Higgins 1997; Lockwood et al. 2002). Put differently, a promotion-focused consumer typically focuses on approach-oriented strategies that rely on an eager form of exploration aimed at maximizing gains (Pham and Avnet 2009). In contrast, a prevention-focused consumer focuses on avoidance-oriented strategies that are characterized by vigilant forms of exploration aimed at loss prevention (Pham and Avnet 2009).

This focus on gains in promotion-focused individuals tends to encourage risk-seeking behaviour. This includes impulsive purchases as well as hedonic consumption (Sengupta and Zhou 2007; Chernev 2004), adoption of really new products (Herzenstein et al. 2007), and often relies on heuristics in decision making (Pham and Avnet 2004). On the other hand, prevention-focused individuals tend to exhibit more risk aversive behaviour such as the assessment of purchases in a careful, precise, and detailed fashion to avoid undesirable outcomes (Zhu and Meyers-Levy 2007; Friedman and Forster 2001). Prevention focus therefore, promotes a preference for functional products (Chernev 2004), avoidance of really new products (Herzenstein et al. 2007), and relies on substantive information in decision making (Pham and Avnet 2004).

Given how promotion- and prevention-focused individuals display reliance on different product features when undertaking product evaluations, purchase intentions can theoretically be maximized when products/services have features that sustain consumers’ regulatory orientation; a situation referred to as regulatory fit in the literature (Chatterjee et al. 2011). The link between regulatory fit and purchase persuasion is well supported in the marketing literature. For example, product features that support hedonic claims (e.g., great taste in yoghurt), emphasizes desirable outcome (e.g., fruit juice that helps to get energized), and are performance related (e.g., speed of a car), have been shown to appeal more to promotion-focused individuals given the appeal of advancement to the promotion system (Roy and Ng 2012; Lee and Aaker 2004; Chernev 2004). Similarly, it has been advanced that product features that support utilitarian claims (e.g., useful bacteria in yoghurt), counteracts undesirable outcomes (e.g., fruit juice that prevents clogging of arteries) and are safety related (e.g., ABS brakes in car), are influential on prevention-focused individuals given their appeal for security and loss prevention (Roy and Ng 2012; Lee and Aaker 2004; Chernev 2004).

Thus, it is evident from the current literature that the promotion system weighs hedonic values of a decision, higher in comparison to the perceived risks associated with the decision and vice versa for the prevention system. Building on this premise, we advocate in the next sections that the regulatory focus of a prospective student will also play an influential role in their evaluation and selection of universities. It is to be acknowledged though that our perspective is largely theoretically grounded since no studies have yet established a connection between regulatory focus and higher education. Consequently, the next sections ought to be considered an exploratory discussion that will benefit from additional empirical evaluation.

Regulatory Focus and University Evaluations

Universities have different brand identities and attributes that they use to position themselves to prospective students (Mazzarol and Soutar 2002). One of these attributes, as indicated in our introductory section, is academic ranking which universities, in turn, frequently use to position themselves into two distinct brand identities that is a common feature of the higher education landscape across many countries: research intensive versus applied universities. As a generic classification, research-intensive universities are typically more elite, prestigious and well-established universities given their strategic focus on knowledge creation through research (Marginson 1997). In contrast, applied universities are usually “younger” institutions, and focus on the practical, industry-oriented aspects of education (Marginson 1997; Gray et al. 2003).

As advocated in the previous section, the features that appeal to promotion-focused individuals will differ to their prevention-focused counterparts. Specifically in the context of higher education, we advocate that risk-averse prevention-focused students may find more value with research-intensive universities given their more established nature and longer history. Research has shown that prevention-focused people tend to react more positively to well established relative to new products in consumption decisions (Herzenstein et al. 2007). Additionally, given that prevention-focused students tend to be deliberate, careful, and analytical information processors (Pham and Avnet 2004), we suggest that these students may be more attracted to the theory-based learning approach of research-intensive universities relative to the more practical curriculum at applied universities. Finally, because research-intensive universities are perceived to provide a more elite university education, we anticipate that prevention-focused students should prefer research-intensive universitiesbecause these are deemed to provide more stability in their career (Liberman et al. 1999), and may be a more effective means to achieve their security-related goals (Keller 2006).

On the flip side, since promotion-focused students are more open to the experiential side of consumption (Keller 2006; Jia et al. 2012), we believe that these students may be more receptive to the practical and less theoretical approach to learning that is common at applied universities. Finally, we put forward that promotion-focused students should also relatively prefer applied universities since a promotion system has been shown to react positively to new product consumption decisions (Herzenstein et al. 2007) and applied universities, by default of their newer history, are akin to new “products” in the educational marketplace. In sum, we, therefore, suggest that prospective students’ preference towards either a research-intensive university or an applied one will be influenced by their regulatory focus . Specifically, we propose that:

  • Proposition 1 (P1): Promotion-focused prospective students will exhibit higher (a) attitudes (e.g., preference) and (b) behavioural intentions (e.g., enrolment) towards the applied university in comparison to the research-intensive university .

  • Proposition 2 (P2): Prevention-focused prospective students will exhibit higher (a) attitudes and (b) behavioural intentions towards the research-intensive university in comparison to the applied university .

Regulatory Focus and Word of Mouth Interaction

Extending the above propositions further, we also advocate that WOM communication will impact on the link between regulatory focus and both attitudinal as well as behavioural intensions. WOM has been identified in the marketing literature as having a significant influence on product choice and evaluations [see De Matos and Rossi (2008) for a recent meta-analysis]. In particular, it has been suggested that WOM assists consumers with decision making and risk reduction of purchase evaluations (De Matos and Rossi 2008; Bansal and Voyer 2000). The literature also identifies that the level of consumer satisfaction and commitment with a product/service, will result in both WOM activity (i.e., how often and the quantity of information passed), and WOM valence (i.e., whether the information passed is positive, negative, or neutral) (De Matos and Rossi 2008; Sweeney et al. 2005; Harrison-Walker 2001). The latter has been suggested to influence the impact of regulatory focus on product evaluation. For example, Chung and Tsai (2009) show that prevention-focused individuals are more likely to share WOM with a strong social tie (a friend) than with a weak social tie (a stranger). Zhang et al. (2010), highlight that in an online consumer product review context (i.e., electronic WOM), consumers who associate products with promotion goals prefer positive over negative WOM. In contrast, consumers who evaluated products in alignment with prevention consumption goals shared a greater preference for negative over positive WOM (Zhang et al. 2010).

We postulate in the current study, that the relationship posited under P1 and P2 will hold under positive WOM since the latter reinforces existing attitudes and behavioural intentions of both promotion and prevention-focused individuals. This premise builds on previous studies which highlights that positive WOM may represent opportunities to promotion-focused individuals who are more geared towards achieving positive decision outcomes (Zhang et al. 2010). Positive WOM may also appeal to prevention-focused individuals as these informal communications may help to reduce the risks associated with negative decision outcomes (Zhang et al. 2010). It is, therefore, posited that:

  • Proposition 3 (P3): Under positive WOM, promotion (prevention) focus’s preference for applied (research) universities as posited in P1 and P2 will be sustained.

However, we propose that a negative WOM will have a relatively more profound effect on prevention-focused individuals relative to their promotion-focused counterparts since the latter are known to be somewhat insensitive towards risk, especially when they are engaged in the pursuit of advancement goals. For example, Sengupta and Zhou (2007) have suggested that promotion-focused consumers have a preference for luxury-related attributes in a car over safety-related attributes. Similarly, they are more inclined towards newly launched products (Herzenstein et al. 2007). The risk-averse nature of a prevention-focused system on the other hand, points towards heightened sensitivity to negative outcomes in comparison to their promotion-focused counterparts (Herzenstein et al. 2007). Consequently, a negative WOM can be expected to magnify the negative consequences of a decision for prevention-focused individuals more so than promotion-focused subjects, since the former’s natural inclination is to prevent loss. Put differently, we propose that an exposure to a negative WOM will, therefore, cause prevention-focused individuals to more greatly reduce their existing attitude and behavioural intentions relative to their promotion-focused counterparts.

  • Proposition 4 (P4): Under negative WOM, prevention-focused individuals will demonstrate a higher reduction in their attitudes and behavioural intentions towards both research-intensive and applied universities in comparison to their promotion-focused counterparts.

Methodology

To test the above propositions, we employ a mixed method technique called qualitative experimentation (Fine and Elsbach 2000; Robinson and Mendelson 2012) by randomly assigning prospective students to a 2 (regulatory focus: promotion versus prevention) × 2 (university type: research intensive versus applied) × 2 (WOM : positive versus negative) between subject experimental design and then qualitatively considering their reactions to the experimental manipulations through one-on-one in-depth interviews. To develop both a representative and accessible sampling frame, prospective university students were sourced from three highly reputed higher education fairs (e.g., www.topmba.com/events) held in the Asia Pacific region. A total of 48 students were randomly selected to participate in our study and further randomly assigned to one of the eight above outlined experimental conditions (i.e., an even split of six students per group). Data collection was discontinued at the point of theoretical saturation when further data gathering ceased to produce any new insights (Strauss and Corbin 1998).

Following a procedure developed and widely used in the regulatory focus literature (Pham and Avnet 2009), we manipulated the students’ regulatory focus by asking the students to generally speak about their hopes and aspirations versus duties and obligations. As indicated by Higgins (1997), regulatory focus, as a motivational state, can be activated by priming a person’s “ideals” (for promotion focus ) or “oughts” (for prevention focus ). The former conditions subjects to focus on working towards their aspirations in life (i.e., be promotion focused), while the latter drives subjects to concern themselves with the absence or presence of a negative outcome (i.e., be prevention focused). To cross check the reliabilityof our manipulation, we asked the interviewees to fill in a short survey instrument using a well-established measure of regulatory focus, with end points using 1 = something I ought to do and 7 = something I want to do (Pham and Avnet 2009). The results were overwhelmingly conclusive with all the promotion-conditioned subjects focusing on something they wanted to do as against prevention-focused subjects who overwhelmingly leaned towards something they ought to do, thus providing conclusive evidence that our manipulation for regulatory focus was successful.

Next, we exposed the students to fictitious marketing materials about two hypothetical universities, using the generic terminology of University A to describe a university with an applied brand identity and University B for a research-intensive institution. Post this exposure, we asked the students their impression about whether they thought the presented university was applied in nature or research intensive as a cross check of our experimental manipulation. In all 48 cases (i.e., 100 % success rate), the students correctly identified the brand identity of the universities.

We further asked the students to imagine that they met a close friend who said positive (negative) things about the university they were exposed too. We developed a number of hypothetical scenarios to describe the friend’s WOM and included comments from the friend’s personal experience with the said university, as well as hearsays the friend picked up from both alumni and prospective employers. We then exposed our interviewees to these hypothetical WOM reviews, which among others included statements such as “I am (not) having a real good time at this university”, “an alumni I spoke to said he enjoyed (hated) his time at this university” and “I attended a career fair by well known firm, and they said they regularly hire (don’t hire) from this university”.

Following this exposure to our eight experimental conditions, we conducted one-on-one interviews with the students regarding their attitudes and intentions towards the hypothetical university they were introduced to. A semi-structured approach with open-ended questions was used during the interviews, each lasting 30–45 minutes. While the early stages of data collection was quite open-ended, subsequent stages were more structured as insights started to emerge from the data (Strauss and Corbin 1998). Next, the collected transcribed data was content analysed to test the afore-mentioned propositions. Using the inter-judge test (Wagner et al. 2010), two independent researchers conducted the data analysis and interpretation to allow for adequate triangulation and validation (Stöttinger 2001). In the next section, an overview of our key qualitative findings is presented. For confidentiality reasons, any reference to specific respondents is disguised.

Findings

The collected qualitative data from the 48 interviews were content analysed to evaluate the influence of the participants’ regulatory foci on their attitudes and intentions towards the two different types of universities, and under different conditions of WOM reviews. The concept of attitudes as dependent variable was coded to reflect the following illustrative statements captured during the interviews: “This university makes me interested”, “I perceive this university’s reputation to be favourable”, “I feel this university to be trustworthy”, “I trust this university to provide good quality education”. Similarly, the concept of intention as the other key dependent variable was coded to reflect the following qualitative data excerpts obtained from the interviews: “I would like to find out more about this university”, “I will probably consider this university for my studies” and “I would probably be influenced towards going to this university”.

Attitudes Towards the University

Overall, the evidence that resulted from the qualitative data suggests that subjects with a promotion focus tend to prefer applied universities more than their prevention-focused counterparts (i.e., P1a) while prevention-focused subjects showed a higher attitude towards the research-intensive university as compared to their promotion-focused counterparts (i.e., P2a). The following data excerpts are illustrative of this.

I feel good about this University A [the applied University]. It has a good vibe about it….it feels progressive, modern and current. I do find the other university quite traditional and focused on its heritage rather than forward looking.—Respondent 1 (exposed to promotion focus manipulation).

I am not sure about University A. I prefer a better ranked institution as it is more likely to get me a better job….University B [the research-intensive University] has a better ranking. It has a strong history, and a strong alumni network.—Respondent 17 (exposed to prevention focus manipulation).

Intention Towards the University

Similarly, the qualitative findings demonstrated a strong indication to suggest that promotion-focused subjects had higher behavioural intentions towards their prevention-focused counterparts (i.e., P1b), while the latter preferred the research-intensive over promotion-focused subjects (i.e., P2b). The below illustrative excerpts captured during the interviews demonstrate this.

If I had to choose between those two universities, I’d say that I would more likely enrol with University A [the applied University]. University B feels too traditional.—Respondent 19 (exposed to promotion focus manipulation).

I am quite excited about University A [the applied University]….I want to find out more. What really excites me is the applied nature of its engagement with industry….I am more likely to enrol with University A.—Respondent 25 (exposed to promotion focus manipulation).

It seems quite risky to enrol at University A [the applied University] as University B is better known. I want a good job when I graduate, so I think I will go for University B.—Respondent 5 (exposed to prevention focus manipulation).

Impact of Word of Mouth on University Choice

From our qualitative data, we further find evidence to suggest that under positive WOM, promotion-focused individuals preferred the applied university over their prevention-focused counterparts. On the flip side, we also find indications that prevention-focused subjects prefer the research-intensive university over their promotion-focused counterparts. This is reflected in the below excerpts.

Now that you’ve told me about those good reviews from my friend, I am even more convinced that I should attend University A [the applied University]. I really feel that this university is the right choice for me.—Respondent 25 (exposed to promotion focus manipulation).

My friend has just informed me that his employer speaks highly of University B [the research-intensive University]. They especially commented on the University’s prestige and high rankings. This is why I would prefer to attend University B over A. I feel that the positive comments from employers make it less risky to go to University B.—Respondent 5 (exposed to prevention focus manipulation).

Thus, the above commentaries and others captured across the collected qualitative data indicate broad support for P3 in terms of both attitudinal preferences and behavioural intentions. In contrast, however, interesting results emerged under the negative WOM stimuli. As per our preceding theoretical discussion, it was argued that prevention-focused individuals will experience higher reductions in their existing attitudes due to their higher sensitivity to negative outcomes in comparison to their promotion-focused counterparts. As a result, it is expected that under negative WOM, promotion subjects would end up showing a relatively higher attitude for both university types over their prevention-focused counterparts. In support of this, it was found that under a negative WOM condition, promotion-focused subjects showed less of a negative reaction to both the research-intensive and applied universities relative to their prevention-focused counterparts. Indeed, while both promotion- and prevention-focused subjects evaluated their attitude downwards under negative WOM, the impact appeared to be much higher in the latter as compared to the former. This is reflected below.

Well, I am not sure anymore. I thought University B [the research intensive University] would be a better choice for me. But this review is terrible. I am now concerned that neither options are best for me.—Respondent 17 (exposed to prevention focus manipulation).

I am not too worried about this negative review. It does mean that I need to do some more research into University A [the applied University], but everybody is entitled to their views and mine may be different to theirs. So, I am not completely disinterested in University A now that I have read this review. Respondent 1 (exposed to promotion focus manipulation).

As observed with attitudes, under negative WOM , promotion-focused subjects also showed higher intentions for both the applied and research-intensive universities over their prevention-focused counterparts.

I will probably still apply to University A [the applied University] and may consider University B now that I have read this negative review about A. However, this is just one view point. So, I’m happy to still consider both options. Respondent 33 (exposed to promotion focus manipulation).

I don’t think I’ll be enrolling in either university. This review in University B [the research-intensive University], my preferred option, concerns me. If this is how bad University B is, then I wonder how much worse University A is as well. This makes me want to go study in another country as I don’t think universities in [Country A—name withheld for anonymity] are any good, especially given this review. Respondent 23 (exposed to prevention focus manipulation).

The above findings indicate that promotion (prevention) focus preference for applied (research intensive) universities is sustained under the positive WOM (i.e., support for P3). However, exposure to a negative WOM is making prevention focused as compared to promotion-focused subjects, more sensitive to negative outcomes (i.e., support for P4). As a result, these prevention-focused individuals are undertaking a relatively higher downward evaluation of both their attitudes and intentions in comparison to their promotion-focused counterparts, as a result of which their evaluation of both universities seem to be lower than promotion-focused subjects.

Discussion and Conclusion

The above findings allow for some important managerial considerations. Firstly, we suggest that prevention-focused students are more likely to enrol at research-intensive universities than a more applied institution. Therefore, from a marketing effectiveness perspective, it may be more effective for a research-intensive university to target prevention-focused students as prospective applicants and for an applied university to focus on promotion-focused subjects. This does not mean that research-intensive universities cannot target promotion-focused students, but we argue that to be successful, they will need to extend their messaging beyond their prestige and research heritage to also focus on factors that promote advancement goals such as career success and aspirations post-graduation. Similarly, for an applied university to target prevention-focused students, we suggest that they will need to reinforce their brand positioning around more conservative identities such as the academic rigour of its educational mission. Already, signs of this in practice are emerging with applied universities highlighting non-research-focused rankings (e.g., teaching quality rankings) in their promotional materials. However, regardless of the promotional manipulations used by universities, education marketers need to ensure that the brand identities they are marketing remain authentic to the educational missions of their institutions, especially when targeting prevention-focused subjects. This is to minimize any likelihood of post-enrolment dissatisfaction, which in turn can result in frustration, anxiety, and ultimately negative WOM , which as we advocate in P4, will have a greater impact on prevention-focused subjects relative to promotion-focused subjects.

Additionally, although exploratory in nature, the above findings also point to three theoretical contributions. First, given that higher education is a service that appeals to both promotion (e.g., it assists with advancement goals such as having a successful career) and prevention systems (e.g., it provides career security by minimizing joblessness), this chapter is an introductory step to address the calls by researchers to study a product/service that speaks to both promotion and prevention goals (Zhang et al. 2010). Second, the regulatory literature has been calling for an enhanced understanding of service sectors (Jia et al. 2012), which we hopefully provide in this chapter. Third, the study also contributes to a limited body of literature that connects regulatory focus with WOM (e.g., Zhang et al. 2010; Chung and Tsai 2009). These studies to date have unfortunately left important gaps in the sense that they either do not consider the impact of WOM valence, or use dependent variables that may be less relevant from a consumption point of view (e.g., review persuasiveness as against intention). The current study theorizes how regulatory focus influences evaluation and intention towards a particular university type, which can then be further moderated by the valence of WOM.

However, in spite of these contributions, the current work is not without its limitations, which we hope provide scope for future work. For instance, as acknowledged previously, our findings are only exploratory in nature. As such, testing our propositions on a larger sample set would be a fruitful research endeavour worth taking forward. Secondly, an area which we don’t address in the current chapter is the distinction between situationally induced versus chronically salient regulatory focus (Higgins 1997, 1998). Getting a more nuanced understanding of these two regulatory systems while theorizing will be a worthwhile endeavour. Finally, we need to concede that our propositions is framed with our own Western culture biases such that a more in-depth understanding of whether/how cultural sensitivities influence our propositions would provide some very useful insights. Nevertheless, in spite of these limitations, we hope to have successfully made the case for why the assumption that better ranked universities tend to be more in demand with prospective students than their applied counterparts is too simplistic to be of any real value to education marketers. Rather, we propose that university selection is more closely linked with a prospective student’s regulatory focus and WOM communication, an area which to our knowledge has not been made explicit before.