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PDSI and Consumer Behavior Essay Assignment
According to the model of motivation process (Schiffman & Kanuk, 2004), unfulfilled needs, wants, and desires in their continuum arouse psychological tension, which is an unpleasant psychosocial state or feeling. This psychological tension drives consumers to seek outside stimuli, and consumption behavior is likely to follow if they perceive that a product stimulus is likely to satisfy their unfulfilled desires through reinforced provision.
Based on this motivation process, Funk (2008) further proposed the sport and event consumer motivation process, modified to accommodate sport settings (e.g. separating the needs domain from the wants domain). Two overarching prerequisites of positive consumer behavior were acknowledged in both models: (a) consumers have unfulfilled needs, wants, and desires, and (b) stimuli can satisfy these needs, wants, and desires. That is, positive consumer behavior is likely to occur when individuals perceive that sport participation might fulfill their symbolic desires.
Due to the rich symbolism of participatory sport products, including leisure and phys- ical activities (Dimanche & Samdahl, 1994; Kang, 2002; Kirkcaldy et al., 2002), sport events (Funk, Toohey, & Bruun, 2007; Kaplanidou & Gibson, 2012), and derivative sport equipment and apparel (Kwak & Kang, 2009), a sufficient supply of symbolic meanings in sport participation, at least at an aggregate level, is likely to exist. In this way, one of the two prerequisites of consumption has been confirmed. Therefore, a high level of PDSI would lead to positive consumer behavior.
Among the key constructs for assessing consumer behavior, personal involvement and actual consumption are two commonly used measures. Personal involvement is an individual’s perceived relevance of a marketing stimulus, a perception driven by inherent needs, values, and interests (Mittal, 1995; Zaichkowsky, 1985), including both enduring
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(long-term and stable) and situational (temporary and changeable) involvement (Havitz & Mannell, 2005; Houston & Rothschild, 1978). As this study was focused on people’s long- term sport participation, personal involvement here would fall toward the end of enduring tendency.
Personal involvement has been widely adopted to examine symbolic consump- tion in various industries, such as music (e.g. Larsen, Lawson, & Todd, 2010), fashion (Auty & Elliott, 1998; Banister & Hogg, 2004), leisure (Kyle, Graefe, Manning, & Bacon, 2003; Schouten & McAlexander, 1995), and tourism (e.g. Ekinci, Sirakaya-Turk, & Preciado, 2013; Gross & Brown, 2006). Personal involvement in sport represents the perceived interest and importance of sport to an individual (Shank & Beasley, 1998).
Building upon the personal involvement inventory (PII) of Zaichkowsky (1985), Shank and Beasley (1998) developed a widely-adopted sport involvement inventory that includes eight semantic differential items to accommodate the sport consumption setting (e.g. Ko, Kim, Claussen, & Kim, 2008; Koernig & Boyd, 2009; McGehee, Yoon, & Cárdenas, 2003). The majority of marketing practices aim to promote purchase behavior.
Among the various measures of sport consumption (e.g. money, time, word-of-mouth, and TV view- ership), money and time expenditure are directly measurable, are tied to sport partici- pation, and have been widely used in previous studies (e.g. Lera-López & Rapún- Gárate, 2007; Taks, Renson, & Vanreusel, 1994). Based on the above discussion, the fol- lowing three hypotheses were proposed and tested in this study:
H1: PDSI would positively impact personal involvement in sport participation.
H2: PDSI would positively impact money expenditure in sport participation.
H3: PDSI would positively impact time expenditure in sport participation.
In addition, the hierarchy of effects model by Lavidge and Steiner (1961) suggests that con- sumer responses evoked by marketing stimulation move hierarchically through four stages: cognitive, affective, conative, and behavioral. As implied by its definition, personal involvement is a subjective and attitudinal construct in the domain of affection and therefore, is supposed to take place prior to actual consumption behavior. This relationship has been supported by a number of empirical studies in sport marketing (e.g. Ko et al., 2008; Koernig & Boyd, 2009; McGehee et al., 2003). Accordingly, the following hypotheses were proposed and tested:
H4: Personal involvement would positively impact money expenditure in sport participation.
H5: Personal involvement would positively impact time expenditure in sport participation.
Together, all five hypotheses constitute a relationship model (Figure 1) for examining the nomological validity of the proposed PDSI measurement tool and discovering how and to what extent PDSI influences sport consumer behavior.
Method and results
Phase 1: generating the initial pool of desired self-images
Method Toexploresalientdesiredself-imagesinsportparticipation, adata-drivenapproachwasused based on two considerations. First, although the topic of self-image has been covered in the general literature, no systematic study was found to identify salient desired self-images of
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sport participants and the factor structure of these self-images. It might be unfeasible to con- ceptualize a priori schema about PDSI dimensionalities through the literature review. Second, a data-driven approach has been widely adopted when exploring the salient brand characteristics of sport products, such as sport team personality (e.g. Braunstein & Ross, 2010; Heere, 2010), sport event personality (e.g. Lee & Cho, 2012), athlete images (e.g. Braunstein & Zhang, 2005), and destination images (e.g. Hosany, Ekinci, & Uysal, 2006; Kaplan, Yurt, Guneri, & Kurtulus, 2010).
As the pursuance of desired self-images through sport participation could be considered a way of self-branding (i.e. individuals develop and promote the characteristics they most desire for themselves), starting the ana- lyses with data-driven approach fits the current research context and reasoning process. Third, the data-driven approach (an inductive reasoning process) provides an open- minded perspective as a starting point to comprehensively explore the statistical dimension- ality of PDSI in the context of sport participation. The findings could serve as an empirical foundation to support future investigations by using a deductive approach.
Phase 1 generated candidate items of PDSI via a qualitative approach. Two screening criteria were set to choose appropriate self-images in sport participation: (a) each charac- teristic should be derived from the context of sport, and (b) the description of each charac- teristic should express an individual’s self-image. Overall, Phase 1 consisted of four steps. First, a comprehensive review of literature was conducted in the areas of human person- ality, brand image/personality, athlete brand image, event personality, and motives in sport consumption. Second, two focus groups of four people were organized to assess whether PDSI existed in sport participation. Research respondents included students at undergraduate and graduate levels and faculty members who were affiliated with a large public university in the United States and also professionals who were sport consumers. Specifically, each focus group was conducted according to the following procedure:
Figure 1. Proposed relationship model. Notes: PDSI = Participant desired self-image, INV = Personal involvement, Money = Monetary expenditure, Time = Time expenditure.
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the primary investigator introduced the purpose and topic of the focus group study; (2) the primary investigator explained the concept of PDSI and used two specific examples (i.e. participation in golf and purchase of newly released running shoes) to help respon- dents understand its meaning; (3) respondents were asked whether they had pursued desired self-images in reality; and (4) if they had, they were asked to share these experiences and provide their perceptions of relevant images.
Third, to supplement the pool of desired self-images generated from the literature review, an open-ended PDSI survey was conducted. Respondents were asked to list in written form at least 10 desired self- images meeting the two criteria mentioned above. Fourth, all generated self-images were sent to a panel of four experts (i.e. two professors, one practitioner, and one doctoral student in sport marketing) for a content validity test, in which all self-image items were evaluated based on the above-mentioned screening criteria to reduce inaccuracy and redundancy of expressions.
Results The qualitative research process produced 82 self-images. Respondents in the two focus groups helped confirm the presence of desired self-images in sport participation, either by succinctly expressing their desires or by recalling actual experiences. Additionally, a total of 113 respondents in the United States filled out the open-ended survey over a span of one week through Amazon Mechanical Turk, which yielded another list of 107 self-images. Altogether, 189 candidate self-images were shown to the panel of experts for a test of content validity.
Based on their feedback, 83 self-images were dropped due to overlap with other images, unclear expressions, or irrelevance. The final pool contained 106 self-images without redundancy. The wording of the items was also improved based on the feedback provided by the panel members.
Phase 2: initial exploratory factor analysis
Method An online questionnaire designed using Qualtrics included three sections preliminary PDSI items, sport participation, and socio-demographics. For the PDSI section, the follow- ing question was presented: ‘to what extent do you desire to obtain the following images from participating in the sport you indicated?’ Respondents were asked to rate the 106 candidate self-images on a 5-point Likert scale (1 = ‘absolutely no desire for this image’ to 5 = ‘extremely high desire for this image’). To avoid the order effect in filling out ques- tionnaires, the 106 self-images were set to be listed in a random order. In the current study, self-images with a mean value in the top 40% range of the 5-point scale (i.e. larger than 3.4) were considered highly desired and were further analyzed in subsequent data analysis. To measure sport participation, respondents were asked to identify one sport activity in which they had most frequently participated (at least once per month). For sample description purpose, respondents were asked to provide demographic information about gender, age, ethnicity, household income, and education level.
A total of 413 online questionnaires were collected in three weeks through Amazon Mechanical Turk, which has been widely adopted as an effective data collection method in behavioral and psychological research (Buhrmester, Kwang, & Gosling, 2011; Chandler, Mueller, & Paolacci, 2014; Paolacci & Chandler, 2014). Excluding 43 questionnaires due to
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a severe rate of missing items (i.e. over 30%) or failure in the attention check questions, valid data from 370 respondents in the United States were included in subsequent ana- lyses. Table 2 presents the socio-demographic information of the respondents and Table 3 lists major sport activities that survey respondents had most frequently participated. Descriptive statistics for socio-demographics and desired self-images were calculated using Statistical Package for the Social Sciences (SPSS) 19.0. An exploratory factor analysis (EFA) was conducted using Mplus 7.0. To determine the number of extracted factors, both parallel analysis and traditional approach (i.e. using eigenvalue, explained variance, and scree plot) were considered (Hair, Black, Babin, & Anderson, 2010; Hayton, Allen, & Scarpello, 2004). The following criteria were used to determine the final list of items: (a) each item had a factor loading equal to or greater than .50 without severe cross-loading (i.e. the difference between two loading values is less than .40), (b) each factor was interpretable, (c) each loaded item on a factor was interpretable, and (d) each factor had at least three items.
Results As shown in Table 4, 49 out of 106 candidate self-images met the criterion of being highly desired (i.e. a mean value larger than 3.4) and were, therefore, analyzed in the EFA. The significant Bartlett Test of Sphericity (p < .01) and the Kaiser–Meyer–Olkin statistic of .978 indicated the appropriateness of conducting EFA with the current data.
In the parallel analysis, three factors’ eigenvalues from sample correlation matrix were larger than their eigenvalues obtained from the parallel analysis (see Table 4), suggesting that these three factors should be retained. However, given that the retained items should have a factor loading equal to or greater than .50 and without severe cross-loading, the
Table 2. Socio-demographic information of respondents in Phase 2 (N = 370). Variable Category N %
Gender Male 226 61.1 Female 144 38.9
Age 18–25 73 19.7 26–35 150 40.5 36–45 71 19.2 46–55 55 14.9 56 and above 21 5.7
Ethnicity African American 24 6.5 American Indian 3 0.8 Asian 29 7.8 Caucasian 282 76.2 Hispanic 25 6.8 Other 7 1.9
Household income Below $20,000 45 12.2 $20,000–39,999 86 23.2 $40,000–59,999 65 17.6 $60,000–79,999 64 17.3 $80,000–99,999 55 14.9 $100,000–149,999 41 11.1 $150,000–199,999 9 2.4 Above $200,000 5 1.4
Education In high school now 2 0.5 High school graduate 62 16.8 In college now 47 12.7 College graduate 186 50.3 Advanced degree 66 17.8 Other 7 1.9
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PDSI and Consumer Behavior Essay Assignment
RUBRIC |
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Excellent Quality 95-100%
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Introduction
45-41 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Literature Support 91-84 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Methodology 58-53 points Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met. |
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Average Score 50-85% |
40-38 points More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided. |
83-76 points Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration. |
52-49 points Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met. |
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Poor Quality 0-45% |
37-1 points The background and/or significance are missing. No search history information is provided. |
75-1 points Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration. |
48-1 points There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met |
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PDSI and Consumer Behavior Essay Assignment |
PDSI and Consumer Behavior Essay Assignment