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There is a wide range of opinion as to the purpose for which chemical abstracts are prepared, varying from the view that they should be little more than a record of the title, author and reference, to that which vaguely hopes that they will contain ‘everything of importance’ from the original communication, and in some way, thereby, save the reader the trouble of consulting that original. There is an element of justification for both views, and it is of value to define the purpose of the chemical abstract in some detail.

We outline the standards for “good” performance measures and propose the Data Envelopment Analysis (DEA) as a method for performance measurement on individual level.

Using the example of a German cooperative bank with a cohort of 40 employees, we apply a multi-stage DEA approach to measure employee performance and report on the results. Based on those results a DEA-based approach for a strategic performance appraisal process is introduced.

We illustrate that DEA provides clear feedback information on an individual level, which enables management to accurately identify fields of specific improvement.

The proposed approach for a strategic performance appraisal process is yet of theoretical nature. Consequently, the practical implementation of this approach is a purpose of further research.

Capital investment decisions need to take account of the relevant cash flows which are incremental to each project. The tax effects of a project are clearly an example of relevant cash flows. However, the tax effects of one project may impact upon the tax effects of another. For example, one project may result in significant capital expenditure, which could change the firm's basic profits such that a different marginal tax rate may be applied. The marginal tax rate of a second project depends upon whether the first project is accepted. Thus capital investment decisions need to be made considering projects jointly. The importance of this has been highlighted by a number of authors, including Fawthrop (1971), Grundy and Burns (1979) and Rickwood and Groves (1979). Simulation models have been built by Hodgkinson (1989), whereas optimisation models have been developed by Berry and Dyson (1979), Pointon (1982) and Ashford, Berry and Dyson (1986).

We identify a novel concept of discretionary idiosyncratic volatility proxied by the idiosyncratic volatility component not related to the non-systematic industry volatility as a source of agency problems that have implications for firms’ cash holdings and their investment decisions. We find that firms with low discretionary idiosyncratic volatility, which likely captures discretionary effort and risk-taking by managers, have smaller cash reserves. Moreover, while high discretionary idiosyncratic volatility firms spend cash internally (internal capital building), low discretionary idiosyncratic volatility firms use it for external acquisitions, consistent with the “quiet life” hypothesis. Our findings thus indicate a need for reinforcement of existing regulations and corporate laws to control for agency costs, which could in turn reduce firm risk and the probability of financial meltdown at the aggregate level.

To investigate the impact of performance measurement in strategic planning process.

A large scale survey was conducted online with Warwick Business School alumni. The questionnaire was based on the Strategic Development Process model by Dyson. The questionnaire was designed to map the current practice of strategic planning and to determine its most influential factors on the effectiveness of the process. All questions were close ended and a seven‐point Likert scale used. The independent variables were grouped into four meaningful factors by factor analysis (Varimax, coefficient of rotation 0.4). The factors produced were used to build regression models (stepwise) for the five assessments of strategic planning process. Regression models were developed for the totality of the responses, comparing SMEs and large organizations and comparing organizations operating in slowly and rapidly changing environments.

The results indicate that performance measurement stands as one of the four main factors characterising the current practice of strategic planning. This research has determined that complexity coming from organizational size and rate of change in the sector creates variation in the impact of performance measurement in strategic planning. Large organizations and organizations operating in rapidly changing environments make greater use of performance measurement.

This research is based on subjective data, therefore the conclusions do not concern the impact of strategic planning process' elements on the organizational performance achievements, but on the success/effectiveness of the strategic planning process itself.

This research raises a series of questions about the use and potential impact of performance measurement, especially in the categories of organizations that are not significantly influenced by its utilisation. It contributes to the field of performance measurement impact.

This research fills in the gap literature concerning the lack of large scale surveys on strategic development processes and performance measurement. It also contributes in the literature of this field by providing empirical evidences on the impact of performance measurement upon the strategic planning process.

Data envelopment analysis (DEA) and window analysis are used to follow the changes in Australian trading banks' pure technical efficiency, scale efficiency, and the nature of returns to scale. The main findings indicate declining average efficiency scores until 1991, followed by a steady rise thereafter. Pure technical inefficiency emerges as a greater source of inefficiency than scale inefficiency. Overall, regional banks exhibit increasing returns to scale and major trading banks exhibit decreasing returns to scale. Also worthy of note is the mixed size of banks operating at optimal returns to scale.

The current chapter is a tentative step toward investigating the allocation of advertising budget between the internet platform and the entity platform according to the long-term and short-term achievement of advertising investment. We provide a decision-making framework on how to allocate the advertising budget to the two platforms for the best results. The integrated effect of advertising investment consists of two parts. Goodwill and customer scale reflect the long-term achievement, and sale profit represents the short-term achievement. We selected some representative feasible investment plans as decision-making units (DMUs), and calculated the values of sale profit, goodwill, and customer scale as three outputs. To determine the best advertising investment plan, we use data envelopment analysis (DEA) model to seek efficient plans, and then determine the best one from those efficient plans through preference investigation and super-efficiency technique.

The purpose of this chapter is to cover banking efficiency using the concept of the Meta frontier function and to study group and subgroup differences in the production technology. This study estimates the technical efficiency (TE) and technology gap ratios (TGRs) for banks in Islamic countries. Using the assumption of the convex hull of the Meta frontier production set using the virtual Meta frontier within the nonparametric approach as presented by Battese and Rao (2002), Battese et al. (2004), and O'Donnell et al. (2007, 2008) and after relaxing this assumption, the study investigates if there is a significant difference between these two methods. To overcome the deterministic criterion addressed to nonparametric approach, the bootstrapping technique has been applied. The first part of this chapter covers the analytical framework necessary for the definition of a Meta frontier function and its estimation using nonparametric data envelopment analysis (DEA) in the case where we impose the assumption of the convex production set and follows in the case of relaxation of this assumption. Then we estimated the TE and the TGR in concave and nonconcave Meta frontier cases by applying the Bootstrap-DEA approach. The empirical part will be reserved for highlighting these methods on data bank to study the technical and technological performance level and prove if there is a difference between the two methods. Three groups of banks namely commercial, investment, and Islamic banks in 17 Islamic countries over a period of 16 years between 1996 and 2011 are used.