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A Market Segmentation Approach for Higher Education Based on Rational and Emotional Factors

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Title: A Market Segmentation Approach for Higher Education Based on Rational and Emotional Factors
Language: English
Authors: Angulo, Fernando, Pergelova, Albena, Rialp, Josep
Source: Journal of Marketing for Higher Education. Jan 2010 20(1):1-17.
Availability: Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
Peer Reviewed: Y
Page Count: 17
Publication Date: 2010
Intended Audience: Administrators
Document Type: Journal Articles
Reports - Research
Education Level: High Schools
Higher Education
Descriptors: Foreign Countries, Higher Education, Marketing, Subcultures, Student Recruitment, High School Students, College Choice, Decision Making, Focus Groups, Values, Logical Thinking, Emotional Response
Geographic Terms: Peru
DOI: 10.1080/08841241003788029
ISSN: 0884-1241
Abstract: Market segmentation is an important topic for higher education administrators and researchers. For segmenting the higher education market, we have to understand what factors are important for high school students in selecting a university. Extant literature has probed the importance of rational factors such as teaching staff, campus facilities, and quality of education. Less attention has been devoted to the relevance of emotional factors such as personal values. The aim of this paper is to suggest a segmentation approach based on integrating rational and emotional factors that prospective students value when selecting a university. We gather information from 21 focus groups and develop a survey applied to a sample of high school students. We find six segments characterized by distinct rational and emotional underlying factors that lead to a particular composition for each segment. The factors discussed in this research can be used as a guide for higher education managers to develop segmentation and communication plans. (Contains 5 tables, 1 figure, and 1 note.)
Abstractor: As Provided
Number of References: 54
Entry Date: 2010
Accession Number: EJ892295
Database: ERIC
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  Value: <anid>AN0052237375;ii501jan.10;2019Feb27.08:57;v2.2.500</anid> <title id="AN0052237375-1">A market segmentation approach for higher education based on rational and emotional factors. </title> <p>Market segmentation is an important topic for higher education administrators and researchers. For segmenting the higher education market, we have to understand what factors are important for high school students in selecting a university. Extant literature has probed the importance of rational factors such as teaching staff, campus facilities, and quality of education. Less attention has been devoted to the relevance of emotional factors such as personal values. The aim of this paper is to suggest a segmentation approach based on integrating rational and emotional factors that prospective students value when selecting a university. We gather information from 21 focus groups and develop a survey applied to a sample of high school students. We find six segments characterized by distinct rational and emotional underlying factors that lead to a particular composition for each segment. The factors discussed in this research can be used as a guide for higher education managers to develop segmentation and communication plans.</p> <p>Keywords: market segmentation; higher education; rational and emotional factors</p> <hd id="AN0052237375-2">Introduction</hd> <p>As higher education (HE) is turning more competitive, it has become necessary for HE institutions to engage in strategic marketing. Strategic marketing involves more than just using promotion to draw students toward the HE institution; it should also include market segmentation and positioning (Cann & George, [<reflink idref="bib10" id="ref1">10</reflink>]; Shirley, [<reflink idref="bib43" id="ref2">43</reflink>]). The premise behind segmentation is that while some prospective students share similar characteristics (such as gender, age, or grade point average), not all students with similar characteristics have the same expectations, goals, and prospects for the future. Students with similar attributes can be grouped, yielding definable segments. This allows HE managers to understand the groups of prospective students better based on their current and evolving needs, backgrounds, and expectations (Rogers, Finley, & Patterson, [<reflink idref="bib41" id="ref3">41</reflink>]).</p> <p>The literature on HE segmentation and choice has examined a large number of variables that prospective students take into account when choosing a university. The majority of these variables can be defined as university-focused and based on the information seeking paradigm. Examples of relevant attributes investigated are academic excellence and career opportunities (e.g., Gray, Fam, & Llanes, [<reflink idref="bib22" id="ref4">22</reflink>]; Mai, [<reflink idref="bib31" id="ref5">31</reflink>]), quality of education (Chapman & Pyvis, [<reflink idref="bib11" id="ref6">11</reflink>]), cost and tuition fees (Langa & David, [<reflink idref="bib29" id="ref7">29</reflink>]), and reputation (Willis & Kennedy, [<reflink idref="bib47" id="ref8">47</reflink>]). In addition to these rational factors, researchers have recently called for a broader frame, including more emotional factors that are thought to have an influence on the HE selection behavior but are still not widely studied (Menon, Saiti, & Socratous, [<reflink idref="bib37" id="ref9">37</reflink>]). The purpose of this paper is to fill this research void in the literature by suggesting a segmentation approach based on the integration of rational and emotional factors that prospective students value when selecting a university. To the best of our knowledge, our research is a first approximation to this phenomenon in HE.</p> <p>Once the empirical research had been developed, we found six segments characterized by distinct rational and emotional underlying factors that lead to a particular composition for each segment. While some of the segments had characteristics that can be usefully extrapolated to diverse environments, others were embedded in the specific contextual market under analysis.</p> <p>This paper is organized as follows. The second section discusses the integrated conceptual framework of market segmentation based on rational and emotional attributes and briefly introduces the extant research. The third section tackles the research approach. The fourth section presents the results. The last section contains discussion, conclusions, future research lines, and implications for managers.</p> <hd id="AN0052237375-3">Integrating rational and emotional factors for higher education segmentation</hd> <p>A large number of conceptual models have been developed in the literature in order to explain the consumption behavior in general, and HE 'consumption' in particular. However, a simple typology can differentiate between two distinct schools of thought: rational and emotional (Bhat & Reddy, [<reflink idref="bib7" id="ref10">7</reflink>]; Holbrook & Hirschman, [<reflink idref="bib27" id="ref11">27</reflink>]).</p> <hd id="AN0052237375-4">The rational perspective</hd> <p>According to the rational school, consumers buy products based on objective criteria such as price or technical features (Ajzen & Fishbein, [<reflink idref="bib1" id="ref12">1</reflink>]; Schiffman & Kanuk, [<reflink idref="bib42" id="ref13">42</reflink>]). The process of choice within this school of thought usually involves the following stages: decide about the relevance of each attribute of a product, collect information about competing products' attributes, evaluate the levels of each attribute in competing products, and choose the optimal product (Bettman, [<reflink idref="bib6" id="ref14">6</reflink>]; Fishbein & Ajzen, [<reflink idref="bib20" id="ref15">20</reflink>]; McGuire, [<reflink idref="bib34" id="ref16">34</reflink>]). This competitive aspect of information processing is treated at various stages (McGuire, [<reflink idref="bib34" id="ref17">34</reflink>]). In the theory of college selection, Chapman [<reflink idref="bib12" id="ref18">12</reflink>] proposes a behavioral model as a process that consists of a sequence of five interrelated stages: (a) presearch behavior, (b) search behavior, (c) application decision, (d) choice decision, and (e) matriculation decision. Researchers and, by inference, college admissions decision makers could be misled by focusing only on the application and choice behavior of students. For example, students who perceive a college to be too expensive will not presumably apply to such a college in the first instance. Chapman suggests that much of the substance of the college selection process is still hidden behind the application decision. The present study is focused on the presearch and search stage according to the model of Chapman.</p> <p>The majority of the research in HE segmentation and choice examines attributes related to the rational perspective. We have grouped these attributes according to their focus on university-centered underlying factors and individual-centered factors. Within the university-centered stream most of the research concentrates on three groups of factors: academic excellence and subsequent career opportunities (e.g., Briggs, [<reflink idref="bib9" id="ref19">9</reflink>]; Gray et al., [<reflink idref="bib22" id="ref20">22</reflink>]; Mai, [<reflink idref="bib31" id="ref21">31</reflink>]; Menon, [<reflink idref="bib35" id="ref22">35</reflink>]; Young, [<reflink idref="bib50" id="ref23">50</reflink>]); quality of education, including teaching courses and high standards of the HE institution (e.g., Chapman & Pyvis, [<reflink idref="bib11" id="ref24">11</reflink>]; Conard & Conard, [<reflink idref="bib13" id="ref25">13</reflink>]; Hoverstad, Lamb, & Miller, [<reflink idref="bib28" id="ref26">28</reflink>]), and reputation and social activities (e.g., Hoverstad et al., [<reflink idref="bib28" id="ref27">28</reflink>]; Willis & Kennedy, [<reflink idref="bib47" id="ref28">47</reflink>]; Yogev, [<reflink idref="bib49" id="ref29">49</reflink>]). Other relevant factors investigated are infrastructure and physical facilities (Gray et al., [<reflink idref="bib22" id="ref30">22</reflink>]; Mai, [<reflink idref="bib31" id="ref31">31</reflink>]), cost and tuition fees (Hoverstad et al., [<reflink idref="bib28" id="ref32">28</reflink>]; Langa & David, [<reflink idref="bib29" id="ref33">29</reflink>]), availability of scholarships (Drewes & Michael, [<reflink idref="bib18" id="ref34">18</reflink>]), selectivity (Conard & Conard, [<reflink idref="bib13" id="ref35">13</reflink>]), and distance from home (Briggs, [<reflink idref="bib9" id="ref36">9</reflink>]; Drewes & Michael, [<reflink idref="bib18" id="ref37">18</reflink>]). Contrary to the richness of attributes investigated in relation to the university, the research on individual factors is rather scant. Relevant attributes here are the duration of the information search process (Dawes & Brown, [<reflink idref="bib16" id="ref38">16</reflink>]; Menon, [<reflink idref="bib36" id="ref39">36</reflink>]; Menon et al., [<reflink idref="bib37" id="ref40">37</reflink>]) and self-efficacy and vocational interest of the student (Cunningham et al., [<reflink idref="bib14" id="ref41">14</reflink>]). In terms of geographical scope, research in this stream has been conducted in Europe, the United States, Australia, and Asia. Table 1 summarizes extant research focused on studying the rational perspective of HE segmentation.</p> <p>Table 1. Rational perspective in HE segmentation and choice.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Perspective</td><td>Focus</td><td>Underlying Factor</td><td>Country</td><td>Representative Studies</td></tr></thead><tbody valign="top"><tr><td>Rational</td><td>University</td><td>Academic and career opportunities</td><td>US, UK</td><td>Mai (<xref ref-type="bibr" rid="bibr31">2005</xref>)</td></tr><tr><td>Hong Kong</td><td>Willis & Kennedy (<xref ref-type="bibr" rid="bibr47">2004</xref>)</td></tr><tr><td>Malaysia, Singapore, Hong Kong</td><td>Gray et al. (<xref ref-type="bibr" rid="bibr22">2003</xref>)</td></tr><tr><td>US</td><td>Young (<xref ref-type="bibr" rid="bibr50">2002</xref>)</td></tr><tr><td>Turkey</td><td>Aycan & Fikret-Pasa (<xref ref-type="bibr" rid="bibr4">2003</xref>)</td></tr><tr><td>Scotland</td><td>Briggs (<xref ref-type="bibr" rid="bibr9">2006</xref>)</td></tr><tr><td>Australia</td><td>Marginson (<xref ref-type="bibr" rid="bibr32">2006</xref>)</td></tr><tr><td>Cyprus</td><td>Menon (<xref ref-type="bibr" rid="bibr35">1998</xref>)</td></tr><tr><td>Israel</td><td>Yogev (<xref ref-type="bibr" rid="bibr49">2007</xref>)</td></tr><tr><td>Quality and high standard</td><td>US, UK</td><td>Mai (<xref ref-type="bibr" rid="bibr31">2005</xref>)</td></tr><tr><td>Hong Kong</td><td>Willis & Kennedy (<xref ref-type="bibr" rid="bibr47">2004</xref>)</td></tr><tr><td>Malaysia, Singapore, Hong Kong</td><td>Gray et al. (<xref ref-type="bibr" rid="bibr22">2003</xref>)Chapman & Pyvis (<xref ref-type="bibr" rid="bibr11">2006</xref>)</td></tr><tr><td>US</td><td>Hoverstad et al. (<xref ref-type="bibr" rid="bibr28">1989</xref>) Conard & Conard (<xref ref-type="bibr" rid="bibr13">2001</xref>) Epple, Romano, & Sieg (<xref ref-type="bibr" rid="bibr19">2006</xref>)</td></tr><tr><td>Canada</td><td>Drewes & Michael (<xref ref-type="bibr" rid="bibr18">2006</xref>)</td></tr><tr><td>Image</td><td>US, UK</td><td>Mai (<xref ref-type="bibr" rid="bibr31">2005</xref>)</td></tr><tr><td>Hong Kong</td><td>Willis & Kennedy (<xref ref-type="bibr" rid="bibr47">2004</xref>)</td></tr><tr><td>US</td><td>Hoverstad et al. (<xref ref-type="bibr" rid="bibr28">1989</xref>) Conard & Conard (<xref ref-type="bibr" rid="bibr13">2001</xref>)</td></tr><tr><td>Israel</td><td>Yogev (<xref ref-type="bibr" rid="bibr49">2007</xref>)</td></tr><tr><td>Infrastructure and physical facilities</td><td>US, UK</td><td>Mai (<xref ref-type="bibr" rid="bibr31">2005</xref>)</td></tr><tr><td>Malaysia, Singapore, Hong Kong</td><td>Gray et al. (<xref ref-type="bibr" rid="bibr22">2003</xref>)</td></tr><tr><td>Cost and tuition fees</td><td>US</td><td>Hoverstad et al. (<xref ref-type="bibr" rid="bibr28">1989</xref>)</td></tr><tr><td>Spain, UK</td><td>Langa & David (2006)</td></tr><tr><td>Scholarship</td><td>Canada</td><td>Drewes & Michael (<xref ref-type="bibr" rid="bibr18">2006</xref>)</td></tr><tr><td>Selectivity</td><td>US</td><td>Conard & Conard (<xref ref-type="bibr" rid="bibr13">2001</xref>)</td></tr><tr><td>Distance from home</td><td>Canada</td><td>Drewes & Michael (<xref ref-type="bibr" rid="bibr18">2006</xref>)</td></tr><tr><td>Scotland</td><td>Briggs (<xref ref-type="bibr" rid="bibr9">2006</xref>)</td></tr><tr><td>Individual</td><td>Duration of search, process/information seeker</td><td>UK</td><td>Dawes & Brown (<xref ref-type="bibr" rid="bibr16">2002</xref>)</td></tr><tr><td>Greece</td><td>Menon et al. (<xref ref-type="bibr" rid="bibr37">2007</xref>)</td></tr><tr><td>Cyprus</td><td>Menon (<xref ref-type="bibr" rid="bibr36">2004</xref>)</td></tr><tr><td>Self-efficacy, vocational interest, choice goals</td><td>US</td><td>Cunningham et al. (<xref ref-type="bibr" rid="bibr14">2005</xref>)</td></tr></tbody></table> </ephtml> </p> <hd id="AN0052237375-5">The emotional perspective</hd> <p>Another influential perspective contends that the rational model does not capture the multisensory imagery, fantasy, fun, and emotions associated with the consumption of some products (e.g., Hirschman & Holbrook, [<reflink idref="bib24" id="ref42">24</reflink>]). In contrast to the rational or information processing approach, the emotional or hedonic school holds that consumers' motives are emotional in nature. Under this perspective, individuals use personal or subjective criteria such as taste, pride, desire for expressing themselves, and attaining emotional goals in their consumption decisions (McGuire, [<reflink idref="bib34" id="ref43">34</reflink>]; Schiffman & Kanuk, [<reflink idref="bib42" id="ref44">42</reflink>]). In a similar vein, Zaltman [<reflink idref="bib54" id="ref45">54</reflink>] underlines that 'at least 95 percent of all cognition occurs below awareness, in the shadows of the mind while, at most, only 5 percent occurs in high order consciousness' (p. 50). The rational perspective represents only the tip of the mental iceberg, while the emotional one symbolizes the unsuspected depth (Damasio, [<reflink idref="bib15" id="ref46">15</reflink>]; LeDoux, [<reflink idref="bib30" id="ref47">30</reflink>]).</p> <p>The empirical research under the emotional perspective is underrepresented in HE. The individual-focused attributes investigated within this stream can be grouped within intrinsic (such as identity construction), personal values, wishes, and expectations (Aycan & Fikret-Pasa, [<reflink idref="bib4" id="ref48">4</reflink>]; Chapman & Pyvis, [<reflink idref="bib11" id="ref49">11</reflink>]; Langa & David, [<reflink idref="bib29" id="ref50">29</reflink>]; Menon, [<reflink idref="bib35" id="ref51">35</reflink>]) and sociocultural influence such as family, friends, and contextual barriers and supports (Avrahami & Dar, [<reflink idref="bib3" id="ref52">3</reflink>]; Cunningham et al., [<reflink idref="bib14" id="ref53">14</reflink>]; Young, [<reflink idref="bib50" id="ref54">50</reflink>]). At a university level, a recent study (Baker & Brown, [<reflink idref="bib5" id="ref55">5</reflink>]) suggests that the romantic or exotic quality of the sights, sounds, and smells of traditional institutions can be an emotional influencer in university choice. Research in this stream has been carried out in Europe, the United States, and Asia. Table 2 sums up current research investigating the emotional perspective of HE segmentation.</p> <p>Table 2. Emotional perspective in HE segmentation and choice.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Perspective</td><td>Focus</td><td>Underlying Factor</td><td>Country</td><td>Representative Studies</td></tr></thead><tbody valign="top"><tr><td>Emotional</td><td>Individual</td><td>Sociocultural influence (family, friends; barriers and supports)</td><td>US</td><td>Young (<xref ref-type="bibr" rid="bibr50">2002</xref>) Cunningham et al. (<xref ref-type="bibr" rid="bibr14">2005</xref>)</td></tr><tr><td>Israel</td><td>Avrahami & Dar (<xref ref-type="bibr" rid="bibr3">2004</xref>)</td></tr><tr><td>Intrinsic (identity construction; personal values, wishes, and expectations; psychological; relaxation and leisure)</td><td>Singapore, Hong Kong, Malaysia</td><td>Chapman & Pyvis (<xref ref-type="bibr" rid="bibr11">2006</xref>)</td></tr><tr><td>Turkey</td><td>Aycan & Fikret-Pasa (<xref ref-type="bibr" rid="bibr4">2003</xref>)</td></tr><tr><td>Cyprus</td><td>Menon (<xref ref-type="bibr" rid="bibr35">1998</xref>)</td></tr><tr><td>Spain, UK</td><td>Langa & David (2006)</td></tr><tr><td>University</td><td>Romantic or exotic quality to the sights, sounds, and smells of traditional institutions</td><td>UK</td><td>Baker & Brown (<xref ref-type="bibr" rid="bibr5">2007</xref>)</td></tr></tbody></table> </ephtml> </p> <hd id="AN0052237375-6">Integrating the rational and emotional perspectives</hd> <p>Both rational and emotional perspectives should be used to understand consumer behavior and consequently serve as a basis for segmentation (Holbrook & Hirschman, [<reflink idref="bib27" id="ref56">27</reflink>]; Sirgy, [<reflink idref="bib44" id="ref57">44</reflink>]). Zajonc ([<reflink idref="bib51" id="ref58">51</reflink>], [<reflink idref="bib52" id="ref59">52</reflink>]) and Zajonc and Markus [<reflink idref="bib53" id="ref60">53</reflink>] contend that information processing and emotions involve separate and partially independent systems and that cognitive and affective factors may interact with one another. Similarly, Ledoux [<reflink idref="bib30" id="ref61">30</reflink>] claims that 'cognition and emotion are best thought as separate but interacting mental functions mediated by separate but interacting brain systems' (p. 69). In a study of the role of rationality in the choice of a university, Menon et al. [<reflink idref="bib37" id="ref62">37</reflink>] found that the rationality postulate cannot fully explain the behavior of a large number of individual decision makers in education, since more than 40% of their survey participants could not be classified as information seekers. Therefore, the authors claim a need to take into account alternative frameworks in the attempt to explain human behavior in education as well as to study the role of individual/attitudinal characteristics such as subconscious feelings and values. Following this stream of research, the current investigation is focused on rational and emotional factors interacting with one another in segmentation for HE.</p> <hd id="AN0052237375-7">Research approach</hd> <p></p> <hd id="AN0052237375-8">Instrument development</hd> <p>We developed the field research of this article in one Latin American country, Peru, an appropriate context for the purposes of this study, because Latin American countries have been considered highly emotional compared to Western countries (Hofstede, [<reflink idref="bib25" id="ref63">25</reflink>], [<reflink idref="bib26" id="ref64">26</reflink>]).</p> <p>The first stage of the instrument development began with 21 focus groups conducted from August to October 2003, for the purpose of determining relevant rational and emotional attributes. One hundred and sixty-eight prospective students from 12 high schools (six public and six private) in the city of Trujillo (Peru) were randomly selected to participate. The main objective of the focus groups was to find emergent attributes that prospective students value when selecting a university (Strauss & Corbin, [<reflink idref="bib45" id="ref65">45</reflink>]). While both rational and emotional attributes did appear as important for prospective students, a new group that we called 'emotional goals' emerged as an additional important factor that guides students in their search process. This group covered the expectations and wishes of students for their immediate future after finishing the university. This is in line with the results of Aycan and Fikret-Pasa [<reflink idref="bib4" id="ref66">4</reflink>] who found that personal wishes and expectations are the most important factors that influenced career decisions. Fourteen rational attributes, 11 emotional attributes, and 11 emotional goals were identified during the focus groups and guided the elaboration of the questionnaire.</p> <p>Stage 2 of the instrument development process involved administering the questionnaire to a sample of 20 high school students. Few problems were identified, and after reviewing these pretest results, several minor changes were made and the final questionnaire was completed. The self-completion questionnaire comprised four sections: (a) emotional attributes: Why are you going to study at university? (b) emotional goals: How do you see yourself in six years/when you finish at university? (c) rational attributes: How important are the following attributes of a university to be chosen? and (d) sociodemographic information. In sections 1 and 2 measurements were obtained through closed multiresponse questions, where the student had the possibility to mark four alternatives as a maximum, which then were transformed and treated as binary variables. For section 3 we used a scale ranging from 1 (not important) to 7 (very important). The questionnaire has been elaborated based on the relevant literature (e.g., Aycan & Fikret-Pasa, [<reflink idref="bib4" id="ref67">4</reflink>]; Chapman & Pyvis, [<reflink idref="bib11" id="ref68">11</reflink>]; Conard & Conard, [<reflink idref="bib13" id="ref69">13</reflink>]; Cunningham et al., [<reflink idref="bib14" id="ref70">14</reflink>]; Gray et al., [<reflink idref="bib22" id="ref71">22</reflink>]; Langa & David, [<reflink idref="bib29" id="ref72">29</reflink>]; Yogev, [<reflink idref="bib49" id="ref73">49</reflink>]) and the focus groups. The rational attributes, the emotional attributes, and the emotional goals employed can be seen in Tables 3 and 4.</p> <p>Table 3. Factor analysis results.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>RATIONAL ATTRIBUTES</td><td>FACTORS (F)</td></tr><tr><td>F 1</td><td>F 2</td><td>F 3</td><td>F 4</td><td>F 5</td><td>F 6</td></tr></thead><tbody valign="top"><tr><td>STRATEGIC ALLIANCES</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Part Time Job Opportunities</td><td char=".">0.858</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>International Academic Alliances</td><td char=".">0.849</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>QUALITY AND HIGH STANDARDS</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>High Standard of Education</td><td char="." /><td char=".">0.776</td><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Excellent Teaching Staff</td><td char="." /><td char=".">0.649</td><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Excellent Resources for Research</td><td char="." /><td char=".">0.453</td><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>IMAGE</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Experience and Achievements of Institution</td><td char="." /><td char="." /><td char=".">0.717</td><td char="." /><td char="." /><td char="." /></tr><tr><td>Opinion Leader Graduates</td><td char="." /><td char="." /><td char=".">0.627</td><td char="." /><td char="." /><td char="." /></tr><tr><td>Social Cultural Activities</td><td char="." /><td char="." /><td char=".">0.465</td><td char="." /><td char="." /><td char="." /></tr><tr><td>Friends Attend</td><td char="." /><td char="." /><td char=".">0.459</td><td char="." /><td char="." /><td char="." /></tr><tr><td>INFRASTRUCTURE AND PHYSICAL FACILITIES</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Cleanness and Safety within Institution</td><td char="." /><td char="." /><td char="." /><td char=".">0.850</td><td char="." /><td char="." /></tr><tr><td>Excellent Physical and Campus Facilities</td><td char="." /><td char="." /><td char="." /><td char=".">0.520</td><td char="." /><td char="." /></tr><tr><td>ACADEMIC AND CAREER OPPORTUNITIES</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Academic Reputation</td><td char="." /><td char="." /><td char="." /><td char="." /><td char=".">0.800</td><td char="." /></tr><tr><td>Job Placement after Graduation</td><td char="." /><td char="." /><td char="." /><td char="." /><td char=".">0.520</td><td char="." /></tr><tr><td>COST AND TUITION FEES</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Cost and Tuition Fees</td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char=".">0.915</td></tr><tr><td>Eigenvalue</td><td char=".">3.386</td><td char=".">1.468</td><td char=".">1.156</td><td char=".">1.020</td><td char=".">0.944</td><td char=".">0.903</td></tr><tr><td>Cumulative % of Variance explained</td><td char=".">24.20</td><td char=".">34.70</td><td char=".">42.90</td><td char=".">50.20</td><td char=".">57.00</td><td char=".">63.40</td></tr><tr><td>Cronbach's Alpha</td><td char=".">0.89</td><td char=".">0.74</td><td char=".">0.68</td><td char=".">0.75</td><td char=".">0.77</td><td char=".">0.87</td></tr><tr><td>Kaiser-Meyer-Olkin (KMO)</td><td char=".">0.787</td></tr></tbody></table> </ephtml> </p> <p>Table 4. Cluster results.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>ATTRIBUTES</td><td>CLUSTERS (C)</td></tr><tr><td>C 1</td><td>C 2</td><td>C 3</td><td>C 4</td><td>C 5</td><td>C 6</td></tr><tr><td>n = 57</td><td>n = 97</td><td>n = 189</td><td>n = 182</td><td>n = 90</td><td>n = 62</td></tr><tr><td>(8.4%)</td><td>(14.3%)</td><td>(27.9%)</td><td>(26.9%)</td><td>(13.3%)</td><td>(9.2%)</td></tr></thead><tbody valign="top"><tr><td><bold>RATIONAL (Factors Scores)</bold></td><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /><td char="." /></tr><tr><td>Strategic alliances***</td><td char=".">0.22<sub>B</sub></td><td char=".">0.46<sub>C</sub></td><td char=".">0.04<sub>B</sub></td><td char=".">0.11<sub>B</sub></td><td char=".">–0.62<sub>A</sub></td><td char=".">–0.45<sub>A</sub></td></tr><tr><td>Quality and high standards***</td><td char=".">–0.56<sub>B</sub></td><td char=".">–0.08<sub>C</sub></td><td char=".">0.22<sub>D</sub></td><td char=".">0.38<sub>D</sub></td><td char=".">0.16<sub>D</sub></td><td char=".">–1.39<sub>A</sub></td></tr><tr><td>Image***</td><td char=".">0.15<sub>C</sub></td><td char=".">–0.04<sub>BC</sub></td><td char=".">–0.18<sub>B</sub></td><td char=".">0.47<sub>D</sub></td><td char=".">–1.00<sub>A</sub></td><td char=".">0.55<sub>D</sub></td></tr><tr><td>Infrastructure and physical facilities***</td><td char=".">–0.06<sub>B</sub></td><td char=".">–1.40<sub>A</sub></td><td char=".">0.15<sub>B</sub></td><td char=".">0.12<sub>B</sub></td><td char=".">0.54<sub>C</sub></td><td char=".">0.66<sub>C</sub></td></tr><tr><td>Academic and career opportunities***</td><td char=".">–1.90<sub>A</sub></td><td char=".">0.40<sub>C</sub></td><td char=".">0.11<sub>B</sub></td><td char=".">0.05<sub>B</sub></td><td char=".">0.17<sub>B</sub></td><td char=".">0.41<sub>C</sub></td></tr><tr><td>Cost and tuition fees***</td><td char=".">–0.09<sub>B</sub></td><td char=".">0.07<sub>B</sub></td><td char=".">–0.87<sub>A</sub></td><td char=".">0.55<sub>C</sub></td><td char=".">0.71<sub>C</sub></td><td char=".">0.00<sub>B</sub></td></tr><tr><td><bold>EMOTIONAL: Why studying in a university (%)</bold></td><td>C 1</td><td>C 2</td><td>C 3</td><td>C 4</td><td>C 5</td><td>C 6</td></tr><tr><td>Longing for improving oneself***</td><td char="%">67%<sub>AB</sub></td><td char="%">69%<sub>AB</sub></td><td char="%">79%<sub>BC</sub></td><td char="%">87%<sub>C</sub></td><td char="%">78%<sub>BC</sub></td><td char="%">63%<sub>A</sub></td></tr><tr><td>Enhance economic status***</td><td char="%">14%<sub>AB</sub></td><td char="%">18%<sub>B</sub></td><td char="%">4%<sub>A</sub></td><td char="%">9%<sub>AB</sub></td><td char="%">4%<sub>AB</sub></td><td char="%">10%<sub>AB</sub></td></tr><tr><td>Improve economic welfare***</td><td char="%">16%<sub>A</sub></td><td char="%">45%<sub>C</sub></td><td char="%">27%<sub>AB</sub></td><td char="%">29%<sub>AB</sub></td><td char="%">37%<sub>BC</sub></td><td char="%">21%<sub>A</sub></td></tr><tr><td>Independency**</td><td char="%">35%<sub>B</sub></td><td char="%">20%<sub>A</sub></td><td char="%">20%<sub>A</sub></td><td char="%">16%<sub>A</sub></td><td char="%">14%<sub>A</sub></td><td char="%">19%<sub>A</sub></td></tr><tr><td>Be able to manage on one's own**</td><td char="%">60%<sub>B</sub></td><td char="%">58%<sub>AB</sub></td><td char="%">51%<sub>AB</sub></td><td char="%">41%<sub>A</sub></td><td char="%">48%<sub>AB</sub></td><td char="%">52%<sub>AB</sub></td></tr><tr><td>Be respected by people<sup>ns</sup></td><td char="%">11%</td><td char="%">6%</td><td char="%">10%</td><td char="%">8%</td><td char="%">4%</td><td char="%">8%</td></tr><tr><td>Great professional***</td><td char="%">32%<sub>A</sub></td><td char="%">40%<sub>AB</sub></td><td char="%">59%<sub>C</sub></td><td char="%">43%<sub>ABC</sub></td><td char="%">43%<sub>ABC</sub></td><td char="%">50%<sub>BC</sub></td></tr><tr><td>Achieve personal goals***</td><td char="%">60%<sub>AB</sub></td><td char="%">53%<sub>A</sub></td><td char="%">63%<sub>ABC</sub></td><td char="%">63%<sub>ABC</sub></td><td char="%">78%<sub>C</sub></td><td char="%">74%<sub>BC</sub></td></tr><tr><td>Help parents out***</td><td char="%">37%<sub>A</sub></td><td char="%">30%<sub>A</sub></td><td char="%">32%<sub>A</sub></td><td char="%">47%<sub>AB</sub></td><td char="%">47%<sub>AB</sub></td><td char="%">58%<sub>B</sub></td></tr><tr><td>Enjoy oneself***</td><td char="%">18%<sub>B</sub></td><td char="%">12%<sub>AB</sub></td><td char="%">5%<sub>A</sub></td><td char="%">6%<sub>A</sub></td><td char="%">4%<sub>A</sub></td><td char="%">3%<sub>A</sub></td></tr><tr><td>Improve quality of life***</td><td char="%">18%<sub>A</sub></td><td char="%">27%<sub>AB</sub></td><td char="%">34%<sub>B</sub></td><td char="%">27%<sub>AB</sub></td><td char="%">17%<sub>A</sub></td><td char="%">18%<sub>A</sub></td></tr><tr><td><bold>EMOTIONAL GOALS: How do you see yourself in six years/when you finish at university? (%)</bold></td><td>C 1</td><td>C 2</td><td>C 3</td><td>C 4</td><td>C 5</td><td>C 6</td></tr><tr><td>Working<sup>ns</sup></td><td char="%">72%</td><td char="%">70%</td><td char="%">79%</td><td char="%">76%</td><td char="%">82%</td><td char="%">81%</td></tr><tr><td>Supporting personal expenses<sup>ns</sup></td><td char="%">19%</td><td char="%">30%</td><td char="%">23%</td><td char="%">32%</td><td char="%">20%</td><td char="%">26%</td></tr><tr><td>Mature<sup>ns</sup></td><td char="%">30%</td><td char="%">27%</td><td char="%">27%</td><td char="%">26%</td><td char="%">32%</td><td char="%">29%</td></tr><tr><td>Self-confident*</td><td char="%">51%<sub>B</sub></td><td char="%">42%<sub>AB</sub></td><td char="%">38%<sub>AB</sub></td><td char="%">36%<sub>AB</sub></td><td char="%">43%<sub>AB</sub></td><td char="%">26%<sub>A</sub></td></tr><tr><td>Focused on self development***</td><td char="%">5%<sub>A</sub></td><td char="%">26%<sub>B</sub></td><td char="%">14%<sub>A</sub></td><td char="%">13%<sub>A</sub></td><td char="%">9%<sub>A</sub></td><td char="%">5%<sub>A</sub></td></tr><tr><td>Professional*</td><td char="%">63%<sub>A</sub></td><td char="%">66%<sub>AB</sub></td><td char="%">76%<sub>AB</sub></td><td char="%">75%<sub>AB</sub></td><td char="%">81%<sub>B</sub></td><td char="%">73%<sub>AB</sub></td></tr><tr><td>Recognized*</td><td char="%">12%<sub>A</sub></td><td char="%">20%<sub>AB</sub></td><td char="%">20%<sub>AB</sub></td><td char="%">18%<sub>AB</sub></td><td char="%">13%<sub>A</sub></td><td char="%">27%<sub>B</sub></td></tr><tr><td>Experienced<sup>ns</sup></td><td char="%">33%</td><td char="%">34%</td><td char="%">33%</td><td char="%">27%</td><td char="%">40%</td><td char="%">45%</td></tr><tr><td>Searching for a job<sup>ns</sup></td><td char="%">4%</td><td char="%">6%</td><td char="%">8%</td><td char="%">9%</td><td char="%">4%</td><td char="%">2%</td></tr><tr><td>Living abroad<sup>ns</sup></td><td char="%">40%</td><td char="%">24%</td><td char="%">28%</td><td char="%">32%</td><td char="%">23%</td><td char="%">24%</td></tr><tr><td>Entrepreneur***</td><td char="%">19%<sub>A</sub></td><td char="%">32%<sub>B</sub></td><td char="%">19%<sub>A</sub></td><td char="%">15%<sub>A</sub></td><td char="%">11%<sub>A</sub></td><td char="%">23%<sub>A</sub></td></tr><tr><td><bold>SOCIODEMOGRAPHIC: Gender and status of high school</bold></td><td char="%" /><td char="%" /><td char="%" /><td char="%" /><td char="%" /><td char="%" /></tr><tr><td>Female*</td><td char="%">53%<sub>AB</sub></td><td char="%">44%<sub>A</sub></td><td char="%">52%<sub>AB</sub></td><td char="%">56%<sub>AB</sub></td><td char="%">64%<sub>B</sub></td><td char="%">50%<sub>AB</sub></td></tr><tr><td>Male*</td><td char="%">47%<sub>AB</sub></td><td char="%">56%<sub>B</sub></td><td char="%">48%<sub>AB</sub></td><td char="%">44%<sub>AB</sub></td><td char="%">36%<sub>A</sub></td><td char="%">50%<sub>AB</sub></td></tr><tr><td>Public high school*</td><td char="%">70%<sub>A</sub></td><td char="%">69%<sub>A</sub></td><td char="%">74%<sub>AB</sub></td><td char="%">73%<sub>AB</sub></td><td char="%">72%<sub>AB</sub></td><td char="%">89%<sub>B</sub></td></tr><tr><td>Private high school*</td><td char="%">30%<sub>B</sub></td><td char="%">31%<sub>B</sub></td><td char="%">26%<sub>AB</sub></td><td char="%">27%<sub>AB</sub></td><td char="%">28%<sub>AB</sub></td><td char="%">11%<sub>A</sub></td></tr><tr><td>Note: Row means that do not share subscripts are significantly different. The percentages of the variables reflecting emotional attributes and emotional goals should be read as the percentage of prospective students in each cluster that consider the respective variable as an emotional reason/goal.</td></tr><tr><td>***p < 0.01; **p < 0.05; *p < 0.10; <sup>ns</sup> nonsignificant difference.</td></tr></tbody></table> </ephtml> </p> <hd id="AN0052237375-9">Sample and data collection</hd> <p>The marketing director of a Peruvian university sent letters to 35 directors of high schools from Trujillo, requesting the application of the survey to junior and senior students. In Peru, a senior student is a student in his or her last year of high school education, while a junior is in his or her penultimate year (i.e., the next year seniors can enter into a university and juniors should wait two years). Twenty-eight high school directors accepted to participate in the survey. When the questionnaire was applied, interviewers introduced themselves as a body of an independent consultant agency in order to avoid biases.</p> <p>Nine hundred and twelve questionnaires were distributed to student respondents in junior and senior-level high school classes from June to July 2004. After eliminating incomplete questionnaires, 729 were processed. The sample was bistage, probabilistic, stratified based on proportional representation of students from all the high schools sampled, and independent. The sample surveyed is representative of the high school population of Peru. The characteristics of the sample under research are similar to the characteristics of the high school population in Peru according to the National Statistics Institute. Males represent 48% of the sample. The average age of the sample is 16 years old. Senior students comprise 52% of the sample. Students of public high schools represent 72% of the sample, while private high schools account for 28%.</p> <hd id="AN0052237375-10">Data analysis</hd> <p>Factor and cluster analyses were employed to determine whether the three groups of attributes (rational attributes, emotional attributes, and emotional goals) that high school students value when selecting a university could be summarized into simpler dimensions and whether the whole market could be grouped into segments. Since the scale of variables reflecting rational attributes ranged from 1 to 7, we employed factor analysis in order to reduce the number of rational attributes. The variables reflecting emotional attributes and emotional goals were treated as binary variables, which is why we introduced them directly into the cluster analysis. Thus, for the cluster analysis we used the factors resulting from the rational attributes factor analysis and the binary variables of emotional attributes and emotional goals. The Ward technique (Ward, [<reflink idref="bib46" id="ref74">46</reflink>]) and discriminant analysis were used for statistical validation of the cluster analysis. For the characterization of the clusters (segments) we employ ANOVA, Student-Newman-Keuls test, and Bonferroni test.</p> <hd id="AN0052237375-11">Results</hd> <p></p> <hd id="AN0052237375-12">Factor analysis</hd> <p>We employed principal components analysis with varimax rotation. The factor analysis final results with six-factor solution (KMO = 0.787) are presented in Table 3. The selection of the six-factor solution was based on two criteria: the eigenvalue of each factor and the cumulative percentage of explained variance. The total variance explained by the six factors is 63.4%, and the minimum eigenvalue is 0.903. Based on the scores of Cronbach's alpha, the reliability of each factor is satisfactory. The six factors include strategic alliances, quality and high standards, image, infrastructure and physical facilities, academic and career opportunities, and cost and tuition fees. The majority of these factors are in line with extant literature as reflected in Table 1. The factor of strategic alliances is a new rational attribute not previously given enough consideration in the literature. The six factors were used for post hoc segmentation analysis (Green & Krieger, [<reflink idref="bib23" id="ref75">23</reflink>]).</p> <hd id="AN0052237375-13">Cluster analysis</hd> <p>Wind [<reflink idref="bib48" id="ref76">48</reflink>] distinguishes four types of segmentation models: a priori, cluster-based designs, flexible, and componential. A priori segmentation was ruled out because management did not know in advance the number and types of segments. Flexible and componential designs, both of which rely on conjoint analysis, were inappropriate because of the large number of individuals in the market, so we used cluster-based design. Ward's [<reflink idref="bib46" id="ref77">46</reflink>] minimum variance hierarchical clustering routine with squared Euclidian distance as a distance measure was used on the factor scores and the emotional attributes to search for segments. In its most familiar form, Ward's method is a hierarchical clustering process that at each stage combines the two clusters whose fusion leads to the least increase in the error sum of squares. This clustering method was chosen because previous studies have reported that this technique is consistently more accurate than others in recovering data from different populations (Blashfield, [<reflink idref="bib8" id="ref78">8</reflink>]; Doyle & Saunders, [<reflink idref="bib17" id="ref79">17</reflink>]; Odekerken-Schröder & Wetzels, [<reflink idref="bib39" id="ref80">39</reflink>]).</p> <p>As with all clustering techniques, one of the problems is deciding how many clusters to choose. To determine the number of clusters to choose, we plotted the fusion scores (between error sums of squares of Ward method) against the number of clusters (Doyle & Saunders, [<reflink idref="bib17" id="ref81">17</reflink>]). Inspection of that plot indicated six clusters. As can be observed in Figure 1 there is a change in the error sum of squares when the number of clusters changes from 5 to 6. The error sum of squares of the 6-cluster solution is lower than the 5-cluster solution. A further increase in the number of clusters does not lead to a significantly better solution because the error sum of squares from the 6-cluster solution onward is largely stable.</p> <p>Graph: Figure 1. Error sum of squares for different clusters.</p> <p>To validate the number of clusters we used discriminant analysis. The 6-cluster solution classified correctly 77.3% of the original cases grouped. This solution had the highest rate of correct classification among all run clustered solutions. Additionally, one-way ANOVA was used to test for differences (α = 0.05) among segments. The Student-Newman-Keuls (SNK) procedure was used for multiple comparisons of the rational factors, emotional attributes, and emotional goals (see Mitchell & Olson, [<reflink idref="bib38" id="ref82">38</reflink>], for detailed explanation), as was the Bonferroni test for analyzing differences among clusters based on gender and type of high school (private or public). The results of the cluster analysis and the subsequent tests can be seen in Table 4.</p> <p>Interpretation of SNK multicomparison test is as follows. The subscripts A, B, C, and D indicate homogeneous subgroups. The mean of subgroup D is statistically greater than C, C is greater than B, and B is greater than A.[<reflink idref="bib1" id="ref83">1</reflink>] For example, the score of strategic alliances shows statistical differences among the clusters. The test of SNK suggests that strategic alliances are most valued by cluster 2 (having subscript C) and least valued by clusters 5 and 6 (both have subscript A; no statistical difference between clusters 5 and 6 on this factor). There are other cases where the difference between subgroups is not clear-cut. For instance, for the variable 'longing for improving oneself,' SNK test reveals that cluster 4 (subscript C) is clearly statistically greater than cluster 6 (subscript A); however, clusters 3, 4, and 5 are not significantly different among them (since they share subscript C). The interpretation of the Bonferroni-test follows the same rationale as SNK. If no subscript is shown, there is no statistically significant difference among the clusters on the attribute.</p> <p>Table 5 summarizes the main results of this study. The characterization of clusters is elaborated based on the results of variables that reveal statistically significant differences among clusters. We found six distinct segments (clusters) that we called 'the independent,' 'the entrepreneur,' 'the rational,' 'the dreamer,' 'the hard worker' and 'the emotional,' respectively, each one characterized by specific rational and emotional factors, and some of them have distinct emotional goals. Individuals in cluster 1 are independent and self-confident, looking for a university with a good image. Cluster 2 is composed of students with a strong entrepreneurial intention, predominantly male. Cluster 3 represents the rational individuals seeking a high quality standard and looking for a professional career. Students in cluster 3 did not differ significantly in their emotional goals. These rational students were driven by quality and high standards, and the emotional factors that matter to them are related to the material well-being and commonplace factors (i.e., they look for improved quality of life and professionalism). 'The dreamer' (cluster 4) looks for image and high quality, but at low cost. Students in cluster 4 did not differentiate significantly in their emotional goals, probably because of the lack of fit between their aspirations and the reality. 'The dreamer' tends to pursue a university career because he or she longs for personal development but at the same time is least focused on being able to manage on one's own. Cluster 5 represents the hard working (majority female) students striving for improving their welfare and achieving their professional goals. Finally, cluster 6 comprises highly emotional students, attending public, low-cost schools, looking for recognition in their community and wishing to help their parents economically and to achieve personal goals.</p> <p>Table 5. Characterization of the segments.</p> <p> <ephtml> <table><thead valign="bottom"><tr><td>Segment/Cluster</td><td>Rational Factors</td><td>Emotional Factors</td><td>Emotional Goals</td></tr></thead><tbody valign="top"><tr><td>'The independent' (cluster 1)</td><td>Strategic alliances Image</td><td>Independent Be able to manage on one's own Enjoy oneself</td><td>Self-confident</td></tr><tr><td>'The entrepreneur' (cluster 2)</td><td>Strategic alliances Academic and career opportunities</td><td>Enhance economic status and welfare</td><td>Entrepreneur Focused on self development</td></tr><tr><td>'The rational' (cluster 3)</td><td>Quality and high standard</td><td>Be great professional Improve quality of life</td><td>—</td></tr><tr><td>'The dreamer' (cluster 4)</td><td>Image quality and high standard cost</td><td>Long for improving oneself Least focused on being able to manage on one's own</td><td>—</td></tr><tr><td>'The hard worker' (cluster 5)</td><td>Infrastructure and physical facilities/cost</td><td>Improve economic welfare Achieve personal goals</td><td>Professional</td></tr><tr><td>'The emotional' (cluster 6)</td><td>Infrastructure and physical facilities Academic and career opportunities Image</td><td>Help parents out Achieve personal goals</td><td>Recognized</td></tr><tr><td /><td /><td /><td /></tr><tr><td>Note: The characterization of clusters is elaborated based on significant evidence summarized in Table 4.</td></tr></tbody></table> </ephtml> </p> <hd id="AN0052237375-14">Discussion and conclusion</hd> <p>Our work contributes to integrating rational and emotional factors in HE segmentation, following a call for a broader framework that could better account for the diversity of attributes that prospective students value in their selection of a university (e.g., Menon et al., [<reflink idref="bib37" id="ref84">37</reflink>]). In line with the extant literature, we found that quality and high standards, image of the university, infrastructure and physical facilities, academic and career opportunities, and cost and tuition fees are relevant rational factors that prospective Peruvian HE students take into account in the stage of search behavior. However, new important attributes appeared during the initial stage of instrumental development. Our focus groups revealed that international academic alliances of the universities and opportunities for part-time jobs during the undergraduate studies are key attributes that students value highly. The principal component analysis confirmed that these attributes can be grouped into one factor, which had the highest eigenvalue. Whether this is particular for Peru or can be extended to other Latin American and non-Latin countries is an opportunity for future research.</p> <p>Importantly, the high school students in our sample also placed strong emphasis on emotional factors. When jointly considered, the rational and emotional factors gave rise to a unique classification of the segments in the market under investigation. Within the six segments identified, three were comprised by factors that can be characterized as familiar and expected at both a rational and emotional level. Thus, the 'rational' students look for quality and high standards and have professional goals that would improve their quality of life. Similarly, the 'independent' and the 'hard worker' are driven by commonplace factors, such as being independent and improving economic welfare. On the contrary, the other three segments were highly singular. The 'entrepreneurs' focus on their development and look for a university as a means of network formation through international alliances and links with local entrepreneurs. This finding is interesting and calls for further research, since Peru is considered the country with the second highest level of entrepreneurial activity in the world according to the General Entrepreneurship Monitor (GEM, 2007). The 'dreamers,' on the other hand, are less practical, more inclined to the psychological aspects of personal development, and least able to fend for themselves. Perhaps the most interesting finding of the study is the 'emotional' segment. The individuals in this segment are unique in their emotional reason for going to a university: a desire to support their families economically. We could speculate that the emotional goal of being recognized in their community is linked to their wish to develop as individuals and to improve the economic conditions of their family. However, further research is needed in order to understand the hidden psychological factors. In this respect it would be useful to take advantage of theoretical advances in sociology and psychology. Furthermore, it is necessary to understand to what extent the rational and emotional attributes discussed in this paper are relevant at the time of actually choosing a university (stages 4 and 5 of Chapman's [1986] model). To determine this, an explanatory model that integrates different rational and emotional factors can be designed. An important variable that can be included in such a model is the type of university (public or private), since researchers have suggested that there might be differences in the factors that explain the choice of public or private university (Menon et al., 1998). Another potentially fruitful opportunity for future research is studying the cross-cultural differences and similarities of the influence of rational and emotional factors on the selection of a university. Following Hofstede ([<reflink idref="bib25" id="ref85">25</reflink>], [<reflink idref="bib26" id="ref86">26</reflink>]) we could expect that our results can be valid for other Latin American countries; however, further research is needed in order to understand the validity of the findings in other cultures.</p> <p>The rational and emotional attributes discussed in this research can be used as a guide for HE managers to develop segmentation and communication plans. While rational factors can be employed for the selection of the target markets, the emotional ones can be used for approaching them. We discuss in turn how an HE institution can decide which segments are more attractive and how to find and reach those segments.</p> <p>To define whether certain segments can be more attractive to a particular school versus another, it is important to take a strategic analysis point of view with respect to the matching of resources and/or strategy and the target segment(s). For example, if a university possesses superior quality and high standards (in terms of teaching staff and resources for research), then segment 3 (the rational) might be more attractive, since this is the segment more interested in quality and high standards, the resources and capabilities associated with that particular university. If, on the other hand, a university has a strong focus on international alliances, then segments 1 and 2 would be the most aligned with this focus. HE institutions that follow a strategy based on cost leadership might be more interested in segments 4 and 5 as they consider explicitly the cost as an important rational factor for selecting a university. A school interested in developing an image as a socially responsible institution could focus on segment 6 (the emotional) and support prospective students from economically marginalized areas.</p> <p>We observe two potential ways a HE institution could identify prospective students of the interested segment(s). On the one hand, HE institutions can identify prospective students based on the type of high school. Our results suggest that certain segments are more likely to be found in certain types of high schools. For instance, prospective students from segment 6 can be found largely in public high schools, while prospects from segments 1 and 2 are more likely to be found in private schools. On the other hand, if HE institutions are interested in more specific identification of prospective students, they could look for information at an individual level regarding the rational and emotional factors. In this case a school should follow the methodological process of this study and apply the field research to the population of prospective students from the high schools previously identified. For example, if an institution has identified some private high schools in which potential target students are enrolled, this institution can apply the field research to the population of students of those high schools.</p> <p>Additionally, HE managers should think about mechanisms for taking advantage of emotional factors with the aim of reaching the selected target segments. The possibility of establishing deep social networks through alumni and ex-alumni associations as well as the effects of celebrity endorsements on the beliefs of the future students and their relatives can be interesting tools to be considered at this level (e.g., McCracken, [<reflink idref="bib33" id="ref87">33</reflink>]; Penrose, [<reflink idref="bib40" id="ref88">40</reflink>]). Alumni as well as ex-alumni associations could help universities to be aware of, maintain, and reinforce the emotional bonds among the people who have been students in a higher education institution, and they constitute a signal of belonging to something special for possible future students. Following the resources/strategy and the target segment framework discussed, if an HE institution has decided to focus on, for example, segment 2, it can invite ex-alumni who are currently successful entrepreneurs and develop a strategy that associates the university with entrepreneurial success. On the other hand, an HE institution that wants to attract, for example, segment 1 could plan a strategy around a celebrity projecting an image of independence and self-confidence, as those are the emotional factors important for that segment.</p> <p>Finally, we suggest that the segmentation approach based on rational and emotional factors is potentially more effective than purely focusing on sociodemographic segmentation (Arellano, [<reflink idref="bib2" id="ref89">2</reflink>]). Besides, the insights of our research can be used to better understand the prospective students' needs and expectations and thus serve them better. For HE institutions that want to expand to the Latin American market, our research can serve as a point of departure for understanding university characteristics that students value.</p> <hd id="AN0052237375-15">Acknowledgements</hd> <p>The authors are grateful to the Commissioner for Research and Universities of the Departament d'Innovaciò, Universitat i Empresa de la Generalitat de Catalunya and the European Social Fund for the financial support that permitted the completion of this research. The authors are also grateful to the Spanish Ministry of Science and Education (<emph>Ministerio de Educación y Ciencia</emph>, project number SEJ2007-67895-C04-02) for financial support. The authors also thank the financial support of Cesar Vallejo University (Trujillo, Peru) and the professionals who collaborated in the focus groups and the survey collection. This paper has been awarded the Best Paper in Track in Marketing of Higher Education of the Academy of Marketing Annual Conference 2008 hosted by Aberdeen Business School, UK.</p> <hd id="AN0052237375-16">Notes</hd> <ref id="AN0052237375-17"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref12" type="bt">1</bibl> <bibtext> Other authors have used similar procedures. For an example see Conard & Conard, [13], pp. 7–8.</bibtext> </blist> </ref> <ref id="AN0052237375-18"> <title> References </title> <blist> <bibtext> Ajzen, I. and Fishbein, M.1980. Understanding attitudes and predicting social behavior, Englewood Cliffs, NJ: Prentice Hall.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref89" type="bt">2</bibl> <bibtext> Arellano Cueva, R. (2000). Los estilos vida en el Peru. [Lifestyles in Peru]. Lima, Peru: Consumidores y Mercados.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref52" type="bt">3</bibl> <bibtext> Avrahami, A. and Dar, Y.2004. 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  Data: A Market Segmentation Approach for Higher Education Based on Rational and Emotional Factors
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  Data: <searchLink fieldCode="AR" term="%22Angulo%2C+Fernando%22">Angulo, Fernando</searchLink><br /><searchLink fieldCode="AR" term="%22Pergelova%2C+Albena%22">Pergelova, Albena</searchLink><br /><searchLink fieldCode="AR" term="%22Rialp%2C+Josep%22">Rialp, Josep</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Marketing+for+Higher+Education%22"><i>Journal of Marketing for Higher Education</i></searchLink>. Jan 2010 20(1):1-17.
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  Data: Routledge. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site: http://www.tandf.co.uk/journals
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  Data: Journal Articles<br />Reports - Research
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  Data: <searchLink fieldCode="EL" term="%22High+Schools%22">High Schools</searchLink><br /><searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="DE" term="%22Marketing%22">Marketing</searchLink><br /><searchLink fieldCode="DE" term="%22Subcultures%22">Subcultures</searchLink><br /><searchLink fieldCode="DE" term="%22Student+Recruitment%22">Student Recruitment</searchLink><br /><searchLink fieldCode="DE" term="%22High+School+Students%22">High School Students</searchLink><br /><searchLink fieldCode="DE" term="%22College+Choice%22">College Choice</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+Making%22">Decision Making</searchLink><br /><searchLink fieldCode="DE" term="%22Focus+Groups%22">Focus Groups</searchLink><br /><searchLink fieldCode="DE" term="%22Values%22">Values</searchLink><br /><searchLink fieldCode="DE" term="%22Logical+Thinking%22">Logical Thinking</searchLink><br /><searchLink fieldCode="DE" term="%22Emotional+Response%22">Emotional Response</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Peru%22">Peru</searchLink>
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  Data: 10.1080/08841241003788029
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  Data: Market segmentation is an important topic for higher education administrators and researchers. For segmenting the higher education market, we have to understand what factors are important for high school students in selecting a university. Extant literature has probed the importance of rational factors such as teaching staff, campus facilities, and quality of education. Less attention has been devoted to the relevance of emotional factors such as personal values. The aim of this paper is to suggest a segmentation approach based on integrating rational and emotional factors that prospective students value when selecting a university. We gather information from 21 focus groups and develop a survey applied to a sample of high school students. We find six segments characterized by distinct rational and emotional underlying factors that lead to a particular composition for each segment. The factors discussed in this research can be used as a guide for higher education managers to develop segmentation and communication plans. (Contains 5 tables, 1 figure, and 1 note.)
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        Value: 10.1080/08841241003788029
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      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 1
    Subjects:
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Higher Education
        Type: general
      – SubjectFull: Marketing
        Type: general
      – SubjectFull: Subcultures
        Type: general
      – SubjectFull: Student Recruitment
        Type: general
      – SubjectFull: High School Students
        Type: general
      – SubjectFull: College Choice
        Type: general
      – SubjectFull: Decision Making
        Type: general
      – SubjectFull: Focus Groups
        Type: general
      – SubjectFull: Values
        Type: general
      – SubjectFull: Logical Thinking
        Type: general
      – SubjectFull: Emotional Response
        Type: general
      – SubjectFull: Peru
        Type: general
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      – TitleFull: A Market Segmentation Approach for Higher Education Based on Rational and Emotional Factors
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          Name:
            NameFull: Angulo, Fernando
      – PersonEntity:
          Name:
            NameFull: Pergelova, Albena
      – PersonEntity:
          Name:
            NameFull: Rialp, Josep
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2010
          Identifiers:
            – Type: issn-print
              Value: 0884-1241
          Numbering:
            – Type: volume
              Value: 20
            – Type: issue
              Value: 1
          Titles:
            – TitleFull: Journal of Marketing for Higher Education
              Type: main
ResultId 1