The Theory of Planned Behavior - Assignment Example

The Theory of Planned Behavior Introduction Attitudes, norms and behaviour have a basis on a set of beliefs. This means that the any intention aimed at achieving a certain behaviour should in the first place change the believes. According to Ajzen, I. (1985); Godin (1993) and Ajzen and Fishbein (2004), human behaviour while making decisions are guided by several considerations. One of the considerations is the human belief on what the likely outcomes might be and how they may influence the decisions. The stronger the belief that the likely outcomes has an impact which is more favourable, the stronger the willingness/attitude to perform a certain behaviour. Another consideration is the expectations of others and how they might influence ones decisions. This boils down to peer pressure meaning that a certain age group may be influenced by another group, or rather, an individual in a certain age bracket may be influenced by what the other is the said group do. Further, the presence of certain factors which may have an impact on making the various decisions is another consideration taken into account. A combination of the above three considerations gives rise to behavioural intentions. According to Ajzen (1987; 1991; 2002; 2005 and 2008); Kimiecik (1992) and Beck and Ajzen (1991), the more favourable a certain attitude is and it’s accompanying social pressure, the stronger the intentions to make the decision. If a person has a personal control of the over the various behaviours, then it is assumed that he/she can perform or make decisions based on the availability of opportunities. However, as Beck and Ajzen (1991) puts it, changing only one belief has no sufficient evidence that attitude will change. Through their argument, a change in one belief may affect anticipated change in another belief. In support of Beck and Ajzen assertions, Godin (1993) believes that balancing the total aggregate of the three beliefs towards a positive direction is the only assurance of attitude change towards making a decision. To Madden, Ellen and Ajzen (1992), one can change the existing beliefs and which affect the implementation of certain behaviours by giving new information leading to the formation of new beliefs which are likely to tilt the balance towards certain behaviour. However, Madden, Ellen and Ajzen (1992) point out that the information given should be as accurate as possible and should be given to all without discrimination if a valid and reliable conclusion is to be made from the findings. This is so because, it is also possible to change believes by giving powerful false information relevant to the believes. This in the short term may produce a change which may not be felt in the long run. At last, the individuals retreat back to the original beliefs prior to the powerful false information. The other important factor is the understanding that the intentions may not always result into attitude change towards behaviour. In this regard, it is always important to link the two so that perceived outcomes can be properly linked producing results (Raats, Shepherd and Sparks 1993). Research Design To gain a deeper understanding of the roles of certain factors which influence the formation of consumer purchase intentions, a study was undertaken. A sample of 150 participants took part. 74 were from the UK while the remaining 76 were from Germany. The study data was collected using a questionnaire developed using the theory of planned behaviour design methodology. The study data was analyzed using SPSS and various tests were performed as the study objectives. Results Sample Profile Frequency Percent Country United Kingdom 74 49.3 Germany 76 50.7 Total 150 100.0 Gender Female 74 49.3 Male 76 50.7 Total 150 100.0 Relationship Status Single 61 40.7 Married or in a relationship 89 59.3 Total 150 100.0 £/€ spend per week 0-39 £/€/week 50 33.3 40-79 £/€/week 70 46.7 80-119 £/€/week 28 18.7 120+ £/€/week 2 1.3 Total 150 100.0 Frequency - buying at ALDI several times a week 33 22.0 once per week 30 20.0 2-3 times a month 37 24.7 once a month 37 24.7 never 13 8.7 Total 150 100.0 Averaged yearly income in thousand £/€ 0-14´£/€ 38 27.9 15-24´£/€ 41 30.1 25-39´£/€ 37 27.2 40+´£/€ 20 14.7 74 participants were from the UK while 76 were from Germany. In addition, 74 were female, 76 were male while 61 were single compared to 89 who were married or were in a relationship. Majority of the participants (46.7%) spend £/€ 40-79 per week while 1.3% spend £/€120+ per week. Further, 49.4% bought from ALDI more than once in a month. 30.1% of the participants were earning £/€15-24 (‘000) in a given year compared to 14.7% who were earning £/€ 40+ (‘000) per year. Table 1: Descriptive Statistics N Mean Intention - It is very likely that I will buy at ALDI within the next month 150 4.20 Intention - I will purchase at ALDI the next time I need a product 150 2.99 Intention - I will try ALDI within the next month 150 4.16 Attitude ALDI - good to bad 150 11.35 Subjective Norms - People who are important to me think that I should buy at ALDI 150 3.07 Subjective Norms - People who influence my decisions think that I should buy at ALDI 150 3.00 Subjective Norms - People who are important to me buy at ALDI 150 3.50 Subjective Norms - People who are important to me do approve of me buying at ALDI 150 3.41 Perceived Behavioral Control - It does fully depend on me whether I buy at ALDI or not 150 5.35 Perceived Behavioral Control - It is fully under my control whether I buy at ALDI or not 150 5.55 Perceived Behavioral Control - I have the capability to buy at ALDI 150 5.54 Service Quality ALDI - customer could expect be treated well 150 3.61 Service Quality ALDI - employees could be expected to give customers personal attention 150 3.23 Service Quality ALDI - employees would be willing to help customers 150 3.63 Service Quality ALDI - ALDI would offer high-quality service 150 3.44 Service Quality ALDI - employees would respond to customers´ requests promptly 150 3.51 Merchandise Quality ALDI - Products purchased from ALDI would be high in quality 150 3.93 Merchandise Quality ALDI - Products purchased from ALDI have an acceptable standard of quality 150 4.31 On average, the participants indicated a strong willingness to sample products from ALDI the next time they make purchases (M = 3.7, SD = 1.43) and that the intention to buy is good (4.07). On the influence of others on the ability to make purchases, participants reported a strong influence (M = 3.2, SD = 1.41). On average, the participants reported strongly of their willingness to perceived behaviour change (M = 5.48, SD = 0.62). The service quality and merchandise quality of the products came up as key considerations for choosing ALDI products. On average, participants ranked them very highly (M = 3.48, SD = 1.14 and M = 4.12, SD = 0.99) (See appendix). Table 2: Binomial Test Category N Observed Prop. Test Prop. Asymp. Sig. (2-tailed) Gender Group 1 Female 74 .49 .50 .935 Group 2 Male 76 .51 Total 150 1.00 Country Group 1 UK 74 .49 .50 .935 Group 2 Germany 76 .51 Total 150 1.00 Based on Z Approximation A binomial test, based on approximation, was used to test for significant difference in terms of males and females and country. From the findings, there is no statistical difference in representation between males and females and by participation from both countries [Test Prop. = .5, p = .935, p > 0.05]. Table 3: Tests of Normality Country Kolmogorov-Smirnov(a) Shapiro-Wilk Statistic df Sig. Statistic df Sig. Averages Vs. Country int_avg United Kingdom .087 74 .200(*) .971 74 .092 Germany .184 76 .000 .902 76 .000 sn_avg United Kingdom .079 74 .200(*) .974 74 .124 Germany .174 76 .000 .959 76 .016 pbc_avg United Kingdom .199 74 .000 .853 74 .000 Germany .281 76 .000 .663 76 .000 service_quality_avg United Kingdom .149 74 .000 .954 74 .009 Germany .077 76 .200(*) .979 76 .230 merchandise_quality_avg United Kingdom .180 74 .000 .941 74 .002 Germany .208 76 .000 .904 76 .000 Averages Vs. Gender int_avg Female .145 74 .001 .958 74 .015 Male .123 76 .006 .935 76 .001 sn_avg Female .109 74 .031 .960 74 .020 Male .140 76 .001 .975 76 .148 pbc_avg Female .239 74 .000 .859 74 .000 Male .232 76 .000 .743 76 .000 service_quality_avg Female .117 74 .014 .968 74 .057 Male .103 76 .044 .982 76 .361 merchandise_quality_avg Female .166 74 .000 .937 74 .001 Male .172 76 .000 .939 76 .001 a Lilliefors Significance Correction A normality test was conducted in order to determine the significance of intentions, perceived behaviour change, subjective norm, service quality and merchandise quality of the participants by gender and country. The findings indicate that parametric tests cannot be used but non-parametric tests. Table 4: Non-Parametric Tests by Country int_avg sn_avg pbc_avg service_quality_avg merchandise_quality_avg Mann-Whitney U 2645.000 1663.000 1250.500 2611.000 2457.500 Wilcoxon W 5420.000 4589.000 4025.500 5537.000 5232.500 Z -.630 -4.332 -6.080 -.758 -1.357 Asymp. Sig. (2-tailed) .529 .000 .000 .449 .175 a Grouping Variable: Country Analysis per country shows that, there is significant difference between participants from the UK and those from German in perceived behaviour change and subjective norm with UK participants recording high values (U = 1250.5, p = 0.000, p0.05 and U = 2457.5, p = 0.175, p>0.05). Table 5: Non-Parametric Tests by Gender int_avg sn_avg pbc_avg service_quality_avg merchandise_quality_avg Mann-Whitney U 2670.000 2742.000 2668.500 2802.500 2765.500 Wilcoxon W 5596.000 5668.000 5443.500 5728.500 5691.500 Z -.536 -.264 -.559 -.036 -.178 Asymp. Sig. (2-tailed) .592 .792 .576 .971 .859 a Grouping Variable: Gender Non-parametric tests in terms of gender indicate that, there is no significance difference in intentions, subjective norms, perceived behaviour change and emphasis on service and merchandise quality between participants by sex (p>0.05). Reliability Test Table 6: Cronbach Alpha Values Partial Correlation Alpha (α) int_avg .8163 .6078 sn_avg .7795 .6390 pbc_avg .1794 .7827 service_quality_avg .7598 .6275 merchandise_quality_avg .7371 .6380 The Cronbach alpha values always lies between 0 and 1. In normal cases, they should not be small or large and as Netter et al. (1989) puts it, they should lie between .5 and .8. An alpha value which is .95 means that the variables are neither reliable nor valid. From the above results (table 6), all the variables impact positively on the study and are worth retaining them. Formulated Model I = SN + PBC + SQ + MQ (Where SN = Subjective Norm, PBC = Perceived Behaviour Change, SQ = Service Quality and MQ = Merchandise Quality) Model 1 I = SN + PBC Table 7: Model (SN + PBC) ANOVA Sum of Squares Df Mean Square F Sig. Regression 93.438 2 46.719 32.204 .000 Residual 213.259 147 1.451 Total 306.697 149 a Predictors: (Constant), pbc_avg, sn_avg b Dependent Variable: int_avg, R2 = .305 The model is significant at 5% level of significance [F (2,147) = 32,204, p = 0.000, p0.05). This was so since participants from both countries place high regard to quality of products. Non-parametric tests in terms of gender indicated that, there is was significance difference in intentions, subjective norms, perceived behaviour change and emphasis on service and merchandise quality between participants by sex. This was expected as both males and females if categorized give same attitudes per age bracket. Reliability and validity of data is key for trustworthy results and this formed the basis for the use of reliability analysis results to determine reliability and validity. According to Netter et al. (1989), Cronbach alpha values always lies between 0 and 1 while in normal cases, they should not be small or large (they should lie between .5 and .8). To Netter et al., alpha values which are .95 means that the variables are neither reliable nor valid. In this case, all variables were found to be reliable and valid hence the result findings can be relied on. Hierarchical regression analysis was used to test the significance of the inclusion of service and merchandise quality to a model containing subjective norms and perceived behaviour change. The first model had subjective norms and perceived behaviour change as independent variables. From the model, a unit increase in social pressure (subjective norm), ceteris paribus, leads to an increase in intentions by 0.558. Further, a unit increase in perceived behaviour change, ceteris paribus, leads to 0.262 units increase in intentions. The coefficient for subjective norm is significant (p = 0.000, p0.05). Adding Service Quality and Merchandise quality to a model with subjective norm and perceived behaviour change further explains 13.5% of the total variation in intention (R2 = 0.44). A model which includes Service Quality and Merchandise quality is significant. From the model, a unit increase in social pressure (subjective norm), ceteris paribus, leads to .370 increase in intentions to change behaviour while a unit increase in perceived behaviour change, ceteris paribus, leads to 0.225 units increase in intentions. A unit increase in product quality, ceteris paribus, leads to 0.297 units increase in intentions while a unit increase in merchandise quality, ceteris paribus, leads to 0.330 units increase in intentions. The coefficient for subjective norm is significant (β = 0.370, p = 0.000, p0.05) while those for service quality and merchandise quality are significant (β = 0.297, p = 0.003, p0.05). The results indicate that, intentions in making decisions are guided by several considerations which include believes on what the likely outcomes might be and how they may influence the decisions, the expectations of others and how they might influence ones decisions and the presence of certain factors which may have an impact on making the various decisions is another consideration taken into account. Further, it is evident that a combination of considerations gives rise to behavioural intentions as evidenced from the hierarchical regression results. References Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. In J. Kuhl & J. Beckman (Eds.), Action-control: From cognition to behavior (pp. 10-30). Heidelberg: Springer. Ajzen, I. (1987). Attitudes, traits, and actions: Dispositional prediction of behavior in personality and social psychology. In L. Berkowitz (Ed.), Advances in experimental social psychology (Vol. 20, pp. 1-53). New York: Academic Press. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 170-210. Ajzen, I. (2002). Perceived behavioral control, self-efficacy, locus of control, and the theory of planned behavior. Journal of Applied Social Psychology, 32, 661-684. Ajzen, I. (2005). Attitudes, personality, and behavior (2nd. Edition). Milton-Keynes, England: Open University Press / McGraw-Hill. Ajzen, I. (2008). Consumer attitudes and behavior. In C. P. Haugtvedt, P. M. Herr & F. R. Cardes (Eds.), Handbook of Consumer Psychology (pp. 520- 550). New York: Lawrence Erlbaum Associates. Ajzen, I., & Fishbein, M. (2004). Questions raised by a reasoned action approach: Comment on Ogden (2003). Health Psychology, 23, 430-437. Beck, L., & Ajzen, I. (1991). Predicting dishonest actions using the theory of planned behavior. Journal of Research in Personality, 25(3), 212–301. Godin, G. (1993). The theories of reasoned action and planned behavior: Overview of findings, emerging research problems and usefulness for exercise promotion. Journal of Applied Sport Psychology, 5, 130–147. Kimiecik, J. (1992). Predicting vigorous physical activity of corporate employees: Comparing the theory of reasoned action and planned behavior. Journal of Sport & Exercise Psychology, 14, 201–203. Madden, T. J., Ellen, P. S., & Ajzen, I. (1992). A comparison of the theory of planned behavior and the theory of reasoned action. Personality and Social Psychology Bulletin, 18(1), 6–9. Neter, J., Wasserman, W., & Kutner, M. H. (1989). Applied linear regression models. Irwin. Raats, M. M., Shepherd, R., & Sparks, P. (1993). Attitudes, obligations and perceived control: Predicting milk selection. Appetite, 20(3), 270–281. Appendix Read More