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The purpose of this paper is to highlight the problems of using metadata to file electronic documents as well as the problems of using a purely functional filing scheme. It aims to explore how a functional file plan can be created from a business classification scheme by inserting “metadata signpost folders” at strategic points in the filing hierarchy to create a “hybrid functional file plan”.

The paper draws on experience and published literature to discuss methods for creating a hybrid functional file plan.

The paper concludes that functional filing is the only method of filing e‐documents that can effectively support good information management practice, enabling all e‐documents to be managed in line with corporate information management policies, and that it may also be the only viable method of providing true “shared” filing in support of knowledge management and business efficiency.

The article shows that a functional filing scheme, retrieving, cross‐referencing and grouping documents by subject (or other metadata attributes) requires special measures and suggests that current IT, EDRM and related technologies may not fully meet the requirements by searching/sorting on metadata terms. It may be necessary to compromise a purely functional file plan by the inclusion of metadata “signpost” folders into the functional folder structure in order to create a hybrid functional file plan.

The paper aims to provide a practical example of the implementation of a business classification scheme (BCS) within the Sector Skills Development Agency (SSDA)

The case study encompasses the implementation of the BCS without an electronic document and records management system (EDRMS), the introduction of associated policies and procedures, training and upgrades to software and hardware during the first 18 months of the project

The paper finds that it is now always appropriate for an organisation to implement an EDRMS in order to achieve compliance. The key is ensuring that a relevant and tested BCS is in place accompanied by related policies and procedures on its use.

Prior to embarking on implementing a BCS or EDRMS consideration should be given to the organisation's culture and structure. Achieving buy‐in from users is essential, which can be achieved through taking the time to understand users' ways of working and potential issues they may identify.

The paper provides a practical example of BCS implementation without the use of an EDRMS.

By the end of this chapter, you should be able to demonstrate an understanding of:

The impact of increasing competition occurring within the UK retail environment.

Consumers efforts to reduce the disparity between beliefs and behaviours, as conceptualised within cognitive dissonance theory.

The alignment with marketing, the wider economy and the retail sector as a means to identify ways to shape value creation.

This paper explored the new features of emerging stock markets, in order to point out the most associated indicators of increasing stock return volatility, which may lead to instability of emerging markets. The study covers a sample of five geographical areas of emerging economies, including Mexico, Korea, South Africa, Turkey, and Malaysia. It used the backward multiple‐regression technique to examine the relationship between monthly changes of stock price indices as dependent variable and the associated predicting local as well as international variables, which represent possible causes of increasing price volatility and initiating crises in emerging stock markets. The study covered monthly data for a period of forty‐eight months from January 1997 to December 2000. The study revealed that stock trading volume and currency exchange rate respectively represent the highest positive correlation to the emerging stock price changes; thus represent the most predicting variables of increasing price volatility. International stock price index, deposit interest rate, and bond trading volume were moderate predicting variables for emerging stock price volatility. While changes in inflation rate showed the least positive correlation to stock price volatility, thus represents the least predicting variable.