Are Distinctive Assets at your service?
When developing a brand identity, marketers design brand elements (such as logos, colours, characters, and jingles) to visually and verbally represent the brand. These are referred to as Distinctive Assets. This research explores the Distinctive Asset types used by service brands, identifies the most unique asset types and compares these results to existing benchmarks for packaged goods. It finds that most Distinctive Asset types exist in current frameworks, with two new asset types documented - Access assets (employee uniforms, vehicles, stores and app icons) and Promotion assets (price displays and special offer icons). The asset types with the highest level of brand ownership for service brands were found to be face-based assets, app icons, logos, and fonts. Service brand assets have, on average, significantly higher brand ownership than packaged goods assets. This research contributes to the debate surrounding brand identity amongst service categories, and whether branding principles can be generalised from goods to services.
The impact of data collection on service quality and satisfaction scores
This research uses mixed-mode data gathered from nine organisations, across four industries to assess whether mean and median overall service quality and satisfaction scores are affected by the mode of data collection used. Additionally, it examines whether the scale type used also impacts such scores.
Loyalty: an empirical exploration of theoretical structure in two service markets
This thesis provides direction to marketers seeking to improve loyalty levels. A more insightful view of loyalty can help marketers to develop and reinforce marketing programs to increase loyalty and hence profits, based on the types of loyalty that are actually exhibited by their consumers.
Industry benchmarking of service quality and satisfaction
This thesis establishes that there are considerable differences in service quality evaluations at an aggregate level on an industry basis.
This exercise is not seeking to explain results or variation at the individual level. This finding suggests that benchmarking by industry is a useful tool in interpreting such evaluations from customers. Clearly, there are differences between the kinds of ratings that can be expected from the customers of these different industries and these differences are managerially significant. An expert panel was established to determine managerial as well as statistical significance. The panel nominated a 16% difference (on average) as being the level at which they would consider a difference to be managerially significant and worthy of some action, There was a 30% difference between the highest and lowest rating industry (fast food and parcel delivery). Within industries however, differences were much smaller.
Identifying the dimensions of customer satisfaction – a measurement instrument
The primary aim of this thesis is to identify the external dimensions of customer satisfaction, using a non-cognitive approach. Currently, the majority of satisfaction studies have focused on examining the cognitive antecedents of the satisfaction formation process. Very few studies have adopted a multi-attribute approach using verbal responses to identify the external, environmental attributes that are factored into the satisfaction process, such as service and firm based attributes. This thesis asserts that knowledge of such external attributes is more useful to marketing practitioners than knowledge about cognitive antecedents because external attributes can be translated directly into marketing activities, and thus, is directly measurable. Hence, the focus of this research is to identify what these external attributes are, based on customers' self reported responses, and to categorise these attributes into specific dimensions. Collectively, these dimensions provide a measurement framework to guide practitioners in measuring customer satisfaction towards their organisation.
