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Dissertation Abstract Writing Examples

Abstract 1

The ability of traditional statistical methods employed in classification and segmentation tasks to provide highly accurate results is limited in today’s business environment. That is why non-parametric techniques such as artificial neural networks are becoming increasingly popular with both researchers and business practitioners. The main aim of this dissertation was to explore how consumers’ behaviour could be predicted with the help of artificial neural networks. To achieve this aim, the researcher used the market segmentation theory, according to which companies identify homogenous groups of consumers who share the same or similar characteristics. The researcher collected primary qualitative data from 15 managers and owners of small and medium enterprises (SMEs) currently operating in the UK electronics sector. Semi-structured, open-ended interviews carried out using Skype were the main data collection instrument. According to the thematic analysis findings, there is a clear advantage of using artificial neural networks over more traditional discriminant analysis tools for market segmentation purposes. The interviewees indicated that artificial intelligence (AI)-powered analysis methods are more flexible and generate more accurate market-related information. The use of only two measures, namely flexibility and accuracy, to assess the effectiveness of artificial neural networks in predicting consumer behaviour is the key limitation of this study.

 

Abstract 2

This project attempted to assess the effect of supply chain management on the quality of customer service at the example of 3 hotels in the UK. Using the resource-based view and agency theory, the researcher explored how different supply chain management variables (e.g. relationships with suppliers and procurement quality) affected the value of the hotels’ services from the perspective of their customers. The researcher adopted a mixed-method approach. On the one hand, primary qualitative data was collected from a total of 5 hotel managers by means of semi-structured interviews. On the other hand, self-administered questionnaires were distributed among 132 customers of the target hotels to obtain primary quantitative data. Using both quantitative (e.g. linear regression and factor analysis) and qualitative (e.g. content analysis) techniques, the researcher found that the supply chain management variables directly influence the quality of the accommodation services provided by the hotels. In turn, high-quality hotel services maximise their perceived value, which adds to the level of customer service quality. Although two data sources were used in this project for triangulation purposes, it is still limited in terms of reliability because of the small interview sample size. The inclusion of additional supply chain management variables (e.g. communication effectiveness) could also contribute to the validity and reliability of the produced empirical findings.

 

Abstract 3

The main purpose of this dissertation was to analyse the impact of racial discrimination on employee morale and motivation in the automotive industry. The achievement of this aim required collecting primary quantitative data from 94 employees of four automotive companies (i.e. Audi, BMW, Volkswagen, and Ford) that run business operations in the UK. Data was collected using self-administered questionnaires distributed online. The analysis methods employed by the researcher included linear regression, descriptive statistics, and graphical analysis. Based on the analysis outcomes, as well as the most notable employee motivation theories (e.g. Maslow’s hierarchy of needs and Herzberg’s two-factor theory), it was established that racial discrimination in the workplace produced a strong negative impact on the respondents’ morale, commitment, and creativity. Being more precise, racial jokes, overt bias, and stereotyping were identified to have the strongest effect on the mentioned dependent variables. By contrast, the role of indirect discrimination was considered minor. Hence, while automotive companies’ organisational policies do not put their employees who belong to a racial minority at a disadvantage, they are still treated differently due to race by their colleagues. The main limitation of this project is that its findings are based on individual perceptions, which may be biased and subjective.