NASB (ACTUALIZADO) TEXTO: 8:48-59

Information seeking has been defined as the “need to consult various sources prior to making a purchasing decision” (Moutinho, 1987: 12). This may consist of an internal search (information stored in memory), or an external search (seeking new information) (Galan et al., 2015). Research by Darley et al,. (2010) did not find any previous empirical research relating to internal search over a 7-year period, whereas external search has seen a great deal of empirical research, with at least 24 studies found over the same period. Internal search concerns use of memory or previous experiences, whereas external search concerns collecting new information (Simões and Soares, 2010; Blackwell et al., 2006).

Where services are involved (such as with education), there are higher levels of intangibility associated with this type of decision, with an associated higher level of risk (Cubillo et al., 2006; Maringe and Carter, 2007). Furthermore, higher involvement decisions generally have a higher level of perceived risk (Simões and Soares, 2010). Consumers compensate for this by increasing their level of knowledge through a higher degree of searching for information (Moutinho, 1987; Mourali et al., 2005; Choi and Lee, 2003). Applicant’s need to find adequate information to ensure their decision is well informed (Briggs and Wilson, 2007). Moreover, any information considered will be judged as to its usefulness, relevance and believability (cognitive domain) and also its attractiveness and likeability (affective domain) (Moutinho, 1987). Moreover, Moutinho (1987: 15) suggests that consumers use information: “(1) To evaluate alternatives in making a choice; (2) to reinforce past choices as a rationalisation process; (3) to resolve conflict between buying and postponing; (4) to remind when to buy; and (5) to acquire knowledge for epistemic purposes.” As previously discussed, it is also used to reduce levels of risk (Choi and Lee, 2003). Brooks (2010) identifies three main sources of information: social networks (e.g. friends, family), educational institutions (e.g. role played by teachers in schools and colleges), and written information (e.g. university prospectus, open days/visits).

There has been a substantial amount of research relating to the amount of search activity a consumer is engaged in (Furse et al., 1984; Darley et al., 2010). A number of

68 | P a g e relevant factors have been highlighted, for example: product knowledge, experience, satisfaction rates, individual differences, situational variables. Moreover, much of the older existing research looking at search strategies undertaken by consumers relates to high cost durables (Furse et al., 1984). Some older studies even disagree about the assumption that prepurchase behaviour actually occurs (for example see Olshavsky and Granbois (1979), Newman (1977), Granbois (1977)). However, Ursic (1980) suggests that due to use of memory to recall, rather than observation, consumers are likely to under estimate the amount of search that took place. More recently Darley et al., (2010) found that there was an increased interest in decisions concerning online shopping, but that almost half of empirical research involved using student samples, and almost three quarters used survey methodology. Moreover, Galan et al., (2015) state that there is more information available than ever before to facilitate information searching, and Jaffe (2010) and Galan et al., (2015) explore how search has changed, with more use of social media platforms and how the sharing of content and ideas has influenced the purchase decision.

Some research indicates that there are differing patterns in how consumers search for information. For example, Usher et al. (2010), researching applicants to Higher Education courses, proposed a fourfold typology. This was based upon types of decision path (conventional or unconventional), and intensity of information usage (how many sources accessed): Cruisers (conventional decision path, low level information usage); Perusers (conventional decision path, high level information usage); Snoozers (unconventional decision path, low level information usage); Choosers (unconventional decision path, high-level information usage). In their analysis of individual search strategies for new car buyers, Furse et al., (1984) identified six distinctive groups based upon external information search patterns, suggesting that within other contexts individuals do not approach information search as one homogeneous group. They identified a low search group (below average search on all factors); a purchase-pal- assisted group (least experienced, therefore involve another more experienced person); a high-search group (above average on a range of factors); a retail-shopper (with heavy involvement of a range of people); a moderate search group (the largest group with moderate activity on all search factors). More recent research by Wolny and Charoensuksai (2014) explored shopper journeys for cosmetics. This research identified

69 | P a g e three distinct shopper journeys (previously discussed in Chapter 2), demonstrating three very different patterns of searching for information both at the pre-shopping stage and information search stage. This suggests there is a need to contextualise any research that considers identifying patterns of consumer search behaviour.

Recent research also suggests that the online environment takes on a much larger role in the consumer decision process and as a source for information (Moe and Trusov, 2011; Wolny and Charoensuksai, 2014). For example, with online product rating and reviews, where many more consumers are contributing their opinions and potential buyers increasingly rely on this source of information to help them make a decision. The decision making models presented by Wolny and Charoensuksai (2014) refer to a range of online information sources such as product reviews, ratings, and blogs that are sought during the customer shopping journey. Darley et al., (2010) discuss the importance of the online environment and focus on websites, and Lemon and Verhoef (2016) refer to a variety of touch points. Moreover, there now exists many online sites that simplify not only the search for information, but also undertake some of the processing of the information presented. For example, online sites such as Moneysupermarket.com and Booking.com allow consumers to easily search through a vast range of providers for car insurance and accommodation respectively.

When considering searching for information within HE, a short list has already been made, and a variety of sources is used to help in the decision making process (Maringe, 2006). Whilst some students can visit universities at open days where they may speak to staff, have a tour of the building, and get a ‘feel’ for the university environment, they are unable to ‘test drive’ their future HE course (Moogan et al., 1999: 213). University open days also allow additional detailed information on specific courses to be obtained. Moogan et al (1999: 222) note “the open-days’ organisation, structure and personnel created the biggest impressions”. Overseas students however may collect information at educational fairs in their home country (Patton, 2000). In addition, university brochures may be used at various stages of the decision making process, and are a crucial form of information in the early search stage (Harket et al., 2001; Veloutsou et al., 2005). However, this more conventional source of information is seen as having very little influence in the final decision (Newell et al., 1996). Veloutsou et al., (2004: 164)

70 | P a g e highlight the top three themes university students collect information on as: “perceived university’s offering and reputation, the opportunities to develop a healthy social activity and the ability to find suitable accommodation”. A full list of information required can be seen in Table 4.2, shown ranked in order of importance. Further research by Briggs and Wilson (2007) also identified the main sources of information that influenced student choice. The top five they identified were Prospectus, Open day, Word-of- mouth, Website and League tables. They also found that the university website was becoming increasingly important, and Veloutsou et al., (2005) state one reason for this is that geographically remote students can access it. Furthermore, research has indicated that at undergraduate level students typically refer to five different sources of information about HE, with open days, university prospectuses and online (especially university and UCAS websites) being the most frequently cited (Usher et al., 2010), which contradicts some of the earlier information by Newell et al., (1996).

Bennet (2006) however, highlights that more traditional promotional tools such as the university web site, the prospectus and a variety of other written material is seen as either inadequate, misleading or untrustworthy and therefore not seen as a significant influencer in their decision making. The most recent PTES survey also demonstrates that around 20 per cent of students have either a neutral or negative impression regarding the information provided by the university being both sufficient and accurate (Soilemetzidis et al., 2014). Some students also question the reliability of university websites, as is borne out by the most recent PTES survey (Soilemetzidis et al., 2014). Web site adaptation may also need consideration, adapting to various cultural requirements received a positive response (Singh et al., 2006). Also relevant to this discussion is that situational and individual differences may influence the information search undertaken (Punj and Stewart, 1983). Maringe and Carter (2007) suggest that African students claim to not have sufficient information at various parts of the decision making process. Furthermore, other research suggests that Asian consumers have a different cognitive style for decision making (Usunier and Lee, 2005). For example, Chinese consumers relying more heavily on personal sources of information (Doran, 2002). They are also more likely to be information seekers than information givers (Fong and Burton, 2008). This suggests a possible need to meet different cultural requirements regarding information required. Further research by Veloutsou et al.,

71 | P a g e (2005) suggests that higher performing students (identified from UCAS entry points) are more likely to engage with universities and ask questions, and Brooks (2010) suggests that the factors that influence older students are likely to be different and they draw on a different range of factors to make their decision.

Table 4.2: Information required by university candidates (Veloutsou et al. 2004: 165) 1. Content of specific course 13. Title of the degree awarded 25. Shopping in the area 2. University’s reputation 14. Existence of private flats

nearby

26. Development of business contacts when studying 3. Department’s reputation 15. Opportunities to study

abroad

27. University’s age

4. University campus 16. computer facilities 28. Male/female ration in the university

5. Night life in the city 17. Safety in campus 29. Degree classification structure

6. Course as a learning experience

18. Companies recruiting the department’s graduates

30. Opportunity to find part- time jobs

7. Activities in the university 19. Friendliness of people living in the area

31. Library facilities 8. Accommodation provided

by the university

20. Contact with the lecturers 32. Opportunity to find summer jobs

9. University unions 21. Size of the area 33. Activities nearby 10. Percentage of graduates

gaining employment within 1 year

22. Transport in the area 34. Weather in the area

11. Cost of living in the area 23. Safety in the area 35. Contact with counselling services

12. Average earning of the graduate

24. Local sights and activities 36. Contact with doctors through the university

Most of the research relating to information sources used and related areas such as perceived reliability tend to be for decisions at undergraduate level. One might argue that at postgraduate level students are more experienced in this decision process, having previously gone through the process at undergraduate level. Indeed, experience may lead to decisions becoming more automatic, or being replaced by cognitive shortcuts (for example using fewer attributes) requiring less attention and thereby becoming more closely associated with heuristics (Punj and Stewart, 1983). Furthermore, prospective students may decide to undertake their postgraduate study in a different country, which may again present a different approach to their decision process and use of information. Moreover, older studies considering information sources may be far less relevant today due to the increasing use of on-line sources, which may completely change the mix of sources used (Wolny and Charoensuksai, 2014; Tuten and Solomon, 2013). The importance of different information sources is therefore

72 | P a g e subject to change (Foskett and Hemsley-Brown, 2001). For example, Bowden (2000) suggested that league tables published in many of the quality newspapers and magazines are increasingly likely to have a greater influence. Increasingly the internet is used to provide information, which is sometimes controllable (e.g. the university’s web site), but is often outside university’s control in other on-line places and may be inaccurate (Veloutsou et al., 2005). Therefore, up-to-date research is required to understand what impact digital and social media are having on the use of information sources and to also explore what digital and social media sources students think are attractive, likeable, useful, relevant and believable (Brooks, 2010).

An application and/or decision stage is present in many of the existing models (for example, Maringe (2006); Vrontis et al., (2004); Foskett and Hemsley-Brown (2001) ). This will now be considered.