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To ensure the reliability of the situational scales, each scale item was analysed for internal consistency, that is, individual items were queried for their contribution to the overall score of the scale they were a part of. Cronbach’s alpha coefficient was first calculated to check the reliability of the different situational variables, ensuring that for each scale, only one situational variable was being measured, while enabling the removal of ambiguous items. Items were removed if they would significantly increase the Cronbach’s alpha in their absence. Table 3.7 below summarises the Cronbach’s alpha for each of the final situational variables measured.

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Table 3.7: Summary of Study 1 Pilot Situational Cronbach’s Alphas Situational Factor Alpha Value

Physical 0.6819

Social 0.7705

Temporal 0.7396

Task 0.8267

Antecedent 0.8050

The final alpha for each of the scales were acceptable given the .7 rule (Nunnally 1978; Churchill 1979; Bristow and Mowen 1998; Pallant 2005). However, Cronbach’s alpha has been described as being highly sensitive to the number of items in a scale, and that it is usual to get low

Cronbach alpha scores for scales of less than 10 items. This may account for the physical situational variable being just under 0.7. Alpha values would have degraded further, if any more items were removed from the scales.

Overall scale totals were correlated with individual items (item-to-total correlation) to assess the relative contribution of each of the items in that scale. Items with only a small correlation with the total scale have small discriminatory power and therefore do not help predict the overall trend (Burns and Bush 2003). Items correlating 0.44 or less with the total were removed from the questionnaire, which is in line with the recommended minimum correlation value of 0.35 (Churchill 1979; Bristow and Mowen 1998). From the item-to-total analysis, only one item out of those remaining scored less than 0.5 for item-to-total correlation. This offers a strong

indication that each of the remaining items are a strong predictor of their respective scale totals, thereby ensuring all of the remaining items in the scales have internal consistency.

As a result of the pilot study, the situational questionnaire was cut down from 144 items to just 35 items, across Belk’s situational scales, with each scale comprised of 7 items. By keeping the strongest questions for each of the situational factors, with item-to-total correlations exceeding 0.44 and Cronbach alpha exceeding 0.7 for all scales except physical, which scored an alpha of 0.6819, the final condensed version should be reliable for use in the final survey.

Following the pilot study of the situational questionnaire, the final consumer survey was put together with five sections. The questionnaire was designed to show the degree to which

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different factors present at the time of a shopping trip actually affect the behaviour of the customer during that shopping trip. With this in mind, the questionnaire was developed to offer insight into the effects of different components of the three term contingency on consumer choice of shopping centre. The questionnaire was organised in a way that was hoped to increase responding and minimise bias.

The first section was intended to ask questions to gain the interest and cooperation of the consumer, and to help to set the context for the rest of questionnaire. Along with the introduction to the study, this included warm up questions, including several background questions, on those shopping centres they visit with greatest frequency, reason for visit, what activities they engage in within the shopping centre, and how they got to the shopping centre.

Questions here were nominal questions, with some open ended questions. The nominal questions would be simple and quick to answer, providing an indication that the rest of the questionnaire would be similarly straight forward and interesting. This section was the start of the more taxing questions. Scales used in this study, where possible, included reverse items also, to reduce halo responses.

The third section included the dichotomous questions for those situational scales described above. Where possible questions were organised to minimise bias- for the situational section, questions measuring the five situational variables were mixed up to reduce chances of pattern response. This was also the case for the following section measuring the three dimensions of personality.

In the penultimate section, Eysenck’s personality inventory was included, dichotomous questions intended to give scale measures of extraversion, neuroticism, and psychoticism.

In the final section, respondents were asked simple, personal questions relating to their

demographic characteristics and socio-economic situation to minimise the impact of fatigue on the more important measures. These nominal questions would be simple, and require no real effort or thought on the part of the respondent to complete. It was also hoped that by including potentially sensitive questions like income, age, and postcode at the end of the questionnaire rather than at the start, this would increase response rates by minimising drop-outs from respondents who would not like to answer these questions. It should be noted that these potentially sensitive questions were altered to reduce potentially offending respondents. For

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example, respondents were given the option to opt out of giving their annual income level. The full final questionnaire (with scoring system) can be found in Appendix E.

Study 2 Measure Purification

Before reliability testing, reverse items were handled using ‘recode’ in SPSS. From the 25 valid pilot returns, Cronbach’s alpha was calculated for each of the scale measures of interest to establish whether they were reliable. Initial use of Cronbach’s alpha on data collected from the pilot for the scales can be found in the column called ‘Initial Alpha’ below, and suggested that all scales except temporal perspective, utilitarian reinforcement and dominance (highlighted in table 3.8 below) were above the accepted .7 range. Dominance, measured with only three items, had little scope for improvement by refinement. It is quite different from reliability tests in previous studies which managed to find reliable and distinct dominance measures (Newman 2007).

Temporal perspective and utilitarian reinforcement were further examined to identify items that would improve alpha if deleted. Subsequent to this, three items were removed from temporal perspective and two removed from utilitarian reinforcement. Removal of these items meant for shorter scales which achieved reliability (i.e. refined until alpha > .7). This left a questionnaire which contained, along with many miscellaneous variables, 17 scales with a total of 112 items.

To counteract the effects of an already lengthy questionnaire, further items were identified for removal, while maximising alpha scores. This meant removing items until the reliability score would no longer increase or increases are nominal. For the most part, scales which had

previously been composed of more than 5 items were reduced to 5 items in length. The column called ‘final cut’ in table 3.8 below gives the final alpha values for the study 2 pilot. Surprisingly, there were no instances at this stage where reliability was reduced by cutting down to 5 items in length. I.e. the final cut alpha value is the optimal alpha for the scale, or is not considerably less reliable than the reliability for the slightly longer optimal scale. All scales to be included in the final study are reliable at the accepted threshold of .7, except ‘dominance’; a short pre-existing scale, which was subsequently dropped, as it has been in previous studies.

According to George & Mallery’s (2003) guidelines, physical surroundings, aversive

consequences, communication approach-avoidance, and pleasure have excellent reliability; social surroundings, regulatory forces, informational reinforcement, physical approach-avoidance,

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exploratory approach-avoidance, utilitarian learning history, informational learning history and cost learning history have good reliability, and temporal perspective, utilitarian reinforcement, performance satisfaction approach-avoidance and arousal have acceptable reliability.

Another approach suggested by Foxall & Pallister (1998) was to check item-to-total correlation, so this was also considered for the pilot for study 2. Totals were first calculated for each of the scales in the table above. Item-to-total correlations were calculated for all remaining items to be contained in the final study. Full correlation tables can be found in appendix F, but a summary is provided in the final column labelled minimum item-to-total in table 3.8 above of the minimum item-to-total correlations for each final scale from the pilot. Most scales achieved

Table 3.8: Summary of Study 2 Pilot Reliability Tests

Initial Alpha First Cut Final Cut Minimum

Alpha Items Alpha Items Alpha Items

Item-to-total

Physical Surroundings 0.799 10 - - 0.912 5 .808

Social Surroundings 0.862 9 - - 0.858 5 .814

Temporal Perspective 0.643 9 0.713 6 0.751 5 .645

Regulatory Force 0.802 7 - - 0.836 5 .675

Utilitarian Reinforcement 0.678 8 0.726 6 0.797 5 .300 Informational Reinforcement 0.836 9 - - 0.864 5 .669

Aversive Consequences 0.963 5 - - 0.963 5 .875

Physical Approach-avoidance 0.868 5 - - 0.868 5 .734 Exploratory Approach-avoidance 0.898 4 - - 0.898 4 .761 Communication Approach-avoidance 0.923 6 - - 0.925 5 .755 Performance Satisfaction

Approach-avoidance 0.717 4 - - 0.717 4

.496

Utilitarian Learning History 0.722 8 - - 0.814 5 .731 Informational Learning History 0.853 10 - - 0.876 5 .752

Cost Learning History 0.843 5 - - 0.843 5 .732

Pleasure 0.914 8 - - 0.914 8 .466

Arousal 0.761 7 - - 0.761 7 .268

Dominance 0.405 3 - - 0.405 3 .560

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good item-to-total correlations. The only scales that potentially have items which do not predict well the total are utilitarian reinforcement and arousal. For utilitarian reinforcement, the

minimum item-to-total correlation was .300, the next minimum was .838, so this will be carefully examined in the final study. For arousal, the minimum item-to-total correlation was .268, with the next smallest item-to-total correlation being .556 so this shall also be examined closely in the final study. Interestingly, dominance, the only dimension to offer problems from the reliability analysis provided a good item-to-total correlation. The final questionnaire used for study 2 can be found in appendix G.

3.3.5 Collect Data (Final)