Fiona Davies

ATM user attitudes: a neural network analysis

Shows how neural networks can bring together psychometric and econometric approaches to the measurement of attitudes and perceptions. Uses a neural network to analyse data collected from a sample of ATM users on their perceptions of ATM service. Uses the weights of connections from input nodes to hidden nodes to label the hidden nodes to represent particular respondent attitudes. Uses the network to analyse the impact of explanatory (input layer) variables on the hidden layer attributes, and through these on the endogenous (output layer) variables ‐ satisfaction with ATMs, likelihood of recommendation to others, extent and frequency of use. Defines four user types, characterized as “disaffected youth”, “technophobes”, the “pro‐technology” segment, and the “cost conscious” segment. Gives some ideas on how banks could address the needs of each segment.

The future role of bank branches and their managers: comparing managerial perceptions in Canada and Spain

Although it was predicted that bank branches would quickly become obsolete in a computerized society, the reality is that many full‐service branches are not closing but rather evolving to meet changing needs. The role of the branch manager is crucial, and is also changing. In particular, managers are expected to take a lead in marketing activities. A questionnaire study was carried out to examine managers’ changing roles, using two samples of branch managers, one from Canada and one from Spain. Managers were asked to rate 21 function variables on their importance in bank management and in facing new market trends. Differences were found between the two samples, as were similarities: both identified managerial ability, strategic autonomy of the branch and business development through increased marketing ability, as important building blocks for the future role of branches and their managers.

The Kohonen self-organizing map: an application to the study of strategic groups in the UK hotel industry

This paper examines a neural network method known as the self-organizing map (SOM). The motivation behind the SOM is to transform the data to a two-dimensional grid of nodes while preserving its ’topological’ structure. In neural network terminology this involves unsupervised learning. The nearest related statistical technique is cluster analysis. We employ the SOM in the task of identifying strategic groups of companies, using data which relate to the generic strategies suggested by Porter. Following identification of different groups of hotels with certain strategic emphases, the study investigates correlations between strategies followed and hotel performance. We compare and contrast the ’feature map’ generated by the SOM with the results of a standard cluster analysis using the k-means method. The data also cover performance indicators and the results indicate that performance varies between strategic groups.

The interactive effects of strategic marketing, planning and performance: a neural network analysis

Marketing managers practice in a consistently changing environment necessitating the need for the formalisation, implementation and evaluation of strategic marketing plans. Nevertheless, despite the advocated benefits of strategic marketing planning, a paucity of empirical evidence makes this notion speculative. This study examines the relationships between strategic marketing planning and performance. The interactive effects of strategic marketing planning and performance are stressed and examined. Findings suggest that the issue is not whether strategic marketing planning affects performance, but rather what marketing capabilities are required to enhance performance. This study extends the knowledge of strategic marketing planning and performance by focusing on the service industry, and provides controls for market-level influences by being restricted to the hotel sector.

The Comstrat Model: Development of an Expert System in Strategic Marketing

This paper introduces an expert system model which is being developed with the objective of helping marketing managers to analyse the position of their company relative to their competitors, in a particular business or product area, and then suggesting ways in which this position might be improved. The authors also discuss a predevelopment test to assess management benefits, as well as the generation and elicitation of knowledge and expertise provided by managers themselves. In particular, this research considers the potential of an expert system to aid marketing managers in making competitive analysis evaluations.

Construction and testing of a knowledge-based system in retail bank marketing

As the financial services marketplace becomes increasingly competitive, many banks and building societies are experimenting with the use of knowledge based systems (also known as expert systems). BANKSTRAT is a prototype system designed to advise on marketing strategy for retail banks/building societies. It was developed using the expert system shell LEONARDO, and demonstrated to potential users (marketing managers/ directors) in 16 banks and building societies in order to validate its rule base of advice, generate further rules, and gain feedback on how it could be extended to become a useful working model. In the majority of cases respondents agreed with advice given. Criticisms mainly centred on the model′s lack of sophistication, and many useful suggestions were made for improvement. Seventy‐five per cent of respondents believed that a fully developed version of BANKSTRAT could be of use to their company. Further developments would need to be tailored specifically to the user organization.

Olympic sponsorship: evolution, challenges and impact on the Olympic Movement

Selecting the most effective leveraging methods is crucial for national Olympic sponsors, who have limited time to achieve their sponsorship objectives. This paper presents the Optimal Leveraging Activity (OLA) model, which suggests that leveraging activities for high involvement products/services should primarily focus on enhancing brand image, knowledge and involvement, while for low involvement products/services a more sales-oriented approach is favourable. The leveraging activities of four Grand National Sponsors of the Athens Olympic Games illustrate the differences.

Comparative Computer Approaches to Multi-Outlet Retail Site Location Decisions

This article explores alternative changes that could take place in the technology, methodology, and most importantly, the practice of locational decision-making, and is part of a larger scale project aimed at investigating the practical value of artificial intelligence (AI) techniques for strategic decision-making. The research involves comparing the effectiveness of a number of AI paradigms and modelling devices, both with each other and with more conventional computer models.

The interactive effects of strategic planning on hotel performance: a neural network analysis

This paper uses a neural network to analyse the interactive effects of strategic planning on hotel performance. Based on the data collected from 100 hotel units the constructs of planning sophistication and planning thoroughness have direct positive effect on overall performance. Conversely, the degree of planning formality and rigidity )even if it is following a market‐led orientation) can hamper overall performance.

Constructing a Knowledge Base for a Marketing Expert System

Originates from a research project which aims to investigate the potential for “intelligent” computer models as decision‐support tools, with particular emphasis on strategic analysis. Describes field work carried out with the intention of validating the working models which have been developed. The fieldwork produced a number of useful suggestions whereby the particular model could be enhanced, as well as demonstrating the potential for applying intelligent models in practice.