An Examination of the Relationship between Perceived Body Image and Purchase Behaviour of Dietary Supplements (weight loss supplement) Among Female Adolescents. 

اختبار العلاقة بين رشاقة المراهقات والتأثيرعلى تسوّق المكملات الغذائية التي تطرحها الشركات عبر دعاياتها المعلنة

هذه الدراسة التي أجرتها الباحثة هبة جمال عن المراهقات السعوديات (على سبيل المثال لا الحصر) وقد اتضح عبر البحث الذي سينشر بالتفصيل لاحقاً من أنّ النسبة الأكبر من المراهقات وإن كنّ سمينات  لم يعرنَ اهتماماً لهذه الاعلانات أم تلك.

A case study by researcher Heba Jamal on Saudi female adolescents (as an example). Full forthcoming research will be presented in the near future. 

This study aims to explore the relationship between perceived body image and purchase behaviour of dietary supplements among adolescent Saudi girls. For the purpose of this research, body image was defined as; “a person’s perceptions, thoughts and feelings about his or her body” (Grogan, 2008). This definition incorporates two themes; body perception (an individual’s assessment of the physical aspects of their body) and body satisfaction (the extent to which an individual is content with their body size and shape). Body image perception was assessed by a silhouette matching technique, while body dissatisfaction was measured as actual/ideal discrepancy. This comes up with two main groups; positive body-image group and negative body-image group. The study questionnaire was distributed in five major cities in Saudi Arabia (representing the main five regions) over three months. these cities are, Riyadh (the capital city), Jeddah, Makkah, Medina, and Hofuf. A cross-sectional survey was conducted amongst 735 adolescents Saudi girls aged between 11 to 19 years selected from government schools using stratified random sampling technique. A pilot study was conducted and all comments were taken into consideration where errors amended. In part “1” of the questionnaire, respondents were presented with nine figures of different body images thinner to fatter (Stunkardet al 1983). Then, they were asked to select the figure that most closely matches their current body-image, as well as the figure that most represents what they would ideally like to look like, in addition to their dis/satisfaction of their actual body image. Part 2 measures respondents’ behavioural intention and actual purchase behavior of dietary supplements. Respondent rate was good as only 185 questionnaire were incomplete out of the 735 distributed questionnaire. This left us with 550 complete questionnaire for this study. The findings were classified based on the two groups; positive body-image group and negative body-image group. Most of the respondents’ age range between 14-17 years old. 65% of them are not satisfied with their current looks, while 83% chose an ideal/attractive body shape different from their won actual/current body. Moreover, the findings reveal that body dissatisfaction has a significant relationship with both; behaviour intention and actual purchase behaviour of dietary supplements. Unlike negative body-image group, the findings suggest there is no relationship between positive body-image group and behaviour intention/actual purchase behaviour of dietary supplements. Furthermore, the study offers both theoretical and managerial implications and suggests further consideration to be given to the link between body-image and purchase behavioural intention.

Introduction 

Adolescence represents a period of rapid physiological development and psychosocial maturation which associated with changes in body perception (Ramberan et al 2006). It is considered as a crucial stage of life that brings many biological, neurcognitive, social, and behavioural changes (Gottlieb et al 1998). Adolescence describes the transitional stage from childhood to adulthood. It was defined by the Committee on the Rights of the Child (CRC) as “a life stage characterised by growing opportunities, capacities, aspirations, energy and creativity, but also significant vulnerability”. More precisely, the World Health Organization (WHO) defines adolescents as those people between 10 and 19 years of age. Adolescence-related issues became of great interest for many researchers over the past view years, with more focus on issues related to dietary supplements usage. This rapid growing field of research gain its importance from the unique nature of such critical period of formative growth and development that profoundly affects health and well-being across the life course. 

Saudi Arabia, like any other developing country, went through many rapid socio-economic changes during the past decades. Such changes have greatly affected the lifestyle of the entire population. For instance, the traditional Saudi diet was replaced by the energy-dense Western diets that caused an increased prevalence of some diseases such as obesity, type 2 diabetes and hypertension (Al-Hazzaa, 2002; Musaiger, 2002). Moreover, fast food consumption and increased caloric intake, in combination with a sedentary lifestyle, is associated with rising rates of obesity in Saudi society (Musaiger, 2004). According to the Annual Statistic of Food Consumed in the Gulf Cooperation Council (GCC) in 2014, Saudi Arabia was on the top list of GCC countries in term of the amount of annual consumed food. In 2012, the amount of consumed food in the country totaled some 25.8 million metric tons, compared to 29.6 million metric tons in 2014 (961.6 kilograms per capita). This is even more relevant to the current study as adolescents became especially vulnerable to intense marketing efforts by manufacturing companies to promote unhealthy snacks, since they represent the future adult consumers (Story and French, 2004). 

The latest annual report of the Saudi General Authority for Statistics shows that 68% of the total population are below the age of 35, in which 27% of them are adolescence (SGAS, 2018). Therefore, 

Saudi adolescent girls are the main groups exposed to and affected by high fast food consumption 

Behaviours in the region (Alfaris et al, 2015). According to Zaghloul (2011), 71% of Saudi females are either overweight or obese. This, of course, explains the high prevalence of dietary supplement use among females in Saudi Arabia. Alfawaz et al (2017) found that prevalence of dietary supplement use was high among Saudi female adolescence and it was significantly associated with sociodemographic and lifestyle factors. This prevalence of dietary supplement was supported by a tremendous expansion of pharmaceutical market in Saudi Arabia. According to the Saudi Pharmaceutical Sales Forecast for the current year (2018), industry products are expected to surpass $7 billion by 2018 as compare to $4 billion 2012 from which the supplement market accounts for 4% of the total pharmaceutical market sales. 

From a social-psychological perspective, the Theory of Planned Behaviour (TPB; Ajzen, 1991) has been employed by several researches in order to explain adolescence behavior (e.g. Fila and Smith, 2006; Mok and AYK, 2013; Pawlak et al, 2008). The TPB provides a model for behavior modification in addition to prediction. It contains three main social cognitive predictors of intention and behaviour; (1) attitude, (2) subjective norm and (3) perceived behavioural control (PBC). By adopting the TPB, this research aims to enhance our understanding on the relationship between perceived trustworthiness of electronic word of mouth (eWOM) and purchase attitudes of dietary supplements amongst Saudi female adolescents. In fact, there is little empirical research on dietary supplements in the Saudi context; and therefore the current study provides a contribution for both marketing knowledge and practice for dietary supplement marketing. 

REFERENCES

Aghekyan-Simonian, M., et al. (2012). The role of product brand image and online store image on perceived risks and online purchase intentions for apparel. Journal of Retailing and Consumer Services, 19(3), 325–331.

Chiu, H.-Ch., et al. (2011). The challenge for multichannel services: Cross-channel free-riding behavior. Electronic Commerce Research & Applications, 10, 268–277.

Chiu, C. M., et al. (2012). Understanding customers’ repeat purchase intentions in B2C e- commerce: The roles of utilitarian value, hedonic value and perceived risk, Information Systems Journal, 24(1), 85–114.

Dholakia, R. R., Zhao. M. and Dholakia, N. (2005). Multichannel retailing: A case study of early experiences, Journal of Interactive Marketing, 19(2), 63-74.

Flanagin, A.J., et al. (2014). Mitigating risk in ecommerce transactions: perceptions of information credibility and the role of user-generated ratings in product quality and purchase intention. Electronic Commerce Research, 14(1), 1–23.

Flavián, C. and Guinalíu, M. (2006). Consumer trust, perceived security and privacy policy: Three basic elements of loyalty to a web site. Industrial Management & Data Systems, 106(5), 601-620.

Featherman, M.S. and Pavlou, P.A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474.

Gupta, S. and Kim, H.-W. (2007). The Moderating Effect of Transaction Experience on the Decision Calculus in On-line Repurchase. International Journal of Electronic Commerce, 12(1), 127–58.

Heitz-Spahn, S. (2013). Cross-channel free-riding consumer behavior in a multichannel environment: An investigation of shopping motives, socio demographics and product categories. Journal of Retailing and Consumer Services, 20, 570–578.

Holloway, B.B., Wang, S. and Parish, J.T. (2005). The role of cumulative online purchasing experience in service recovery management. Journal of Interactive Marketing, 19(3), 54- 66.

Hernández B., Jiménez J. and Martín M.J. (2010), Customer behavior in electronic commerce: The moderating effect of e-purchasing experience. Journal of Business Research, 63, 964–971

Hong, I.B. (2015). Understanding the consumer’s online merchant selection process: The roles of product involvement, perceived risk, and trust expectation. International Journal of Information Management, 35(3), 322–336.

Kim, S. and Park, H. (2013). Effects of various characteristics of social commerce (s- commerce) on consumers’ trust and trust performance. International Journal of Information Management, 33(2), 318– 332.

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Kim, H.-W. and Gupta, S. (2009). A Comparison of Purchase Decision Calculus Between Potential and Repeat Customers of an Online Store. Decision Support Systems, 47(4), 477–87.

Kim, D.J. (2012). An Investigation of the Effect of Online Consumer Trust on Expectation, Satisfaction, and Post-expectation. Information Systems and e-Business Management, 10(2), 219–40.

Kim, Y. and Peterson, R. A. (2017). A Meta-analysis of Online Trust Relationships in E- commerce. Journal of Interactive Marketing, 38, 44–54,

Klaus, Ph. (2013), The case of Amazon.com: Towards a conceptual framework of online customer service experience (OCSE). Using emerging consensus technique (ECT). Journal of Service Marketing, 27(6), 443-457.

Klaus, Ph. and Maklan, S. (2013). Towards a better measure of customer experience. International Journal of Market Research, 55(2), 227–246.

Kollmann, T., Kuckert, A. and Kayser, I. (2012), Cannibalization or synergy? Consumers’ channel selection in online–offline multichannel systems. Journal of Retailing and Consumer Services, 19(2), 186–194.

Kwak, H. (2012). Self-disclosure in online media an active audience perspective. International Journal of Advertising, 31(3), 485-510.

Lemke, F., Clark, M. and Wilson, H. (2011). Customer experience quality: an exploration in business and consumer contexts using repertory grid technique. Journal of the Academy of Marketing Science, 39(6), 846–869.

Lee, M. K. O. and Turban E. (2001). A Trust Model for Consumer Internet Shopping. International Journal of Electronic Commerce, 6(1), 75–92.

Lopez-Nicolas, C. and Molina-Castillo, F.J. (2008). Customer Knowledge Management and E-commerce: The role of customer perceived risk. International Journal of Information Management, 28, 102–113.

Maity, M., Hsu, M.K. and Pelton, L.E. (2012). Consumers’ Online Information Search: Gen Yers’ Finding Needles in the Internet Haystack. Journal of Marketing Channels, 19(1), 49-76.

Martins, C. and Oliveira, T. Popoviˇc A. (2014). Understanding the Internet banking adoption: A unified theory of acceptance and use of technology and perceived risk application. International Journal of Information Management, 34(1), 1– 13.

Melis, K., et al. (2015). The Impact of the Multi-channel Retail Mix on Online Store Choice: Does Online Experience Matter? Journal of Retailing, 91(2), 272–288.

Meyer, C. and Schwager, A. (2007). Understanding Customer Experience. Harvard Business Review, 85(2), 116–126.

Michell, V.W. and Prince, G.S. (1993). Retailing to Experienced and Inexperienced Consumers. Journal of Retail & Distribution Management, 21(5), 10–22.

Nepomuceno, M. V., Laroche, M., and Richard, M.-O. (2014). How to reduce perceived risk when buying online: The interactions between intangibility, product knowledge, brand familiarity, privacy and security concerns. Journal of Retailing and Consumer Services, 21, 619–629.

Neslin, S.A. and Shankar, V. (2009). Key Issues in Multichannel Management: Current Knowledge and Future Directions. Journal of Interactive Marketing, 23(1), 70–81. Olsson, L.E., et al. (2012). Measuring service experience: Applying the satisfaction with travel

scale in public transport. Journal of Retailing and Consumer Services, 19(4), 413-418. Pantano, E. and Viassone, M. (2015). Engaging consumers on new integrated multichannel retail settings: Challenges for retailers. Journal of Retailing and Consumer Services, 25,

106–114.

ISBN: 978-1-911185-59-8 (Online) ©️ 2018 The Author | ICBEMM-AICILS 2018 ©️ 2018 FLE Learning

Park, J.K., Gunn, F. and Han, S.L. (2012). Multidimensional trust building in e-retailing: Cross- cultural differences in trust formation and implications for perceived risk. Journal of Retailing and Consumer Services, 19, 304–312.

Roschk, H., Muller J. and Gelbrich, K. (2013). Age matters: How developmental stages of adulthood affect customer reaction to complaint handling efforts. Journal of Retailing and Consumer Services, 20(2), 154-164.

Stein, A. and Ramaseshan, B. (2016). Towards the Identification of Customer Experience Touch Point Elements. Journal of Retailing and Consumer Services, 30, 8-19.

Toufaily, E., Souiden, N. and Ladhari R. (2013). Consumer trust toward retail websites: Comparison between pure click and click-and-brick retailers. Journal of Retailing and Consumer Services, 20, 538–548.

Teo, T. S. H. and Liu, J. (2007). Consumer trust in e-commerce in the United States, Singapore and China. Omega, 35, 22–38.

Vanheems, R., Kelly, J. S. and Stevenson, K. (2013). The Internet, the Modern Death of a Salesman: Multichannel Retailing’s Impact on the Salesperson’s Role. International Journal of Integrated Marketing Communications, 5(2), 91-100.

Verhoef P.C., et al. (2009). Customer experience creation: determinants, dynamics and management strategies, Journal of Retailing, 85(1), 31–41.

Verhoef, P.C., et al. (2010). CRM in Data-Rich Multichannel Retailing Environments: A Review and Future Research Directions. Journal of Interactive Marketing, 24, 121–137. Walia, N., Srite, M. and Huddleston, W. (2016). Eyeing the web interface: the influence of price, product, and personal involvement. Electronic Commerce Research, 16(3), 297–333.

Yoon, H. S. and Occe ̃na, L. G. (2015). Influencing factors of trust in consumer-to-consumer

electronic commerce with gender and age. International Journal of Information Management, 35, 352–363.

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