A soft-computing-based method for the automatic discovery of fuzzy rules in databases:uses for academic research and management support in marketing

The study here highlights the potential that analytical methods based on Knowledge Discovery in Databases (KDD) methodologies have to aid both the resolution of unstructured marketing/business problems and the process of scholarly knowledge discovery. The authors present and discuss the application of KDD in these situations prior to the presentation of an analytical method based on fuzzy logic and evolutionary algorithms, developed to analyze marketing databases and uncover relationships among variables. A detailed implementation on a pre-existing data set illustrates the method. © 2012 Published by Elsevier Inc.

A semi-oriented radial measure for measuring the efficiency of decision making units with negative data, using DEA

Data Envelopment Analysis (DEA) is a nonparametric method for measuring the efficiency of a set of decision making units such as firms or public sector agencies, first introduced into the operational research and management science literature by Charnes, Cooper, and Rhodes (CCR) [Charnes, A., Cooper, W.W., Rhodes, E., 1978. Measuring the efficiency of decision making units. European Journal of Operational Research 2, 429–444]. The original DEA models were applicable only to technologies characterized by positive inputs/outputs. In subsequent literature there have been various approaches to enable DEA to deal with negative data. In this paper, we propose a semi-oriented radial measure, which permits the presence of variables which can take both negative and positive values. The model is applied to data on a notional effluent processing system to compare the results with those yielded by two alternative methods for dealing with negative data in DEA: The modified slacks-based model suggested by Sharp et al. [Sharp, J.A., Liu, W.B., Meng, W., 2006. A modified slacks-based measure model for data envelopment analysis with ‘natural’ negative outputs and inputs. Journal of Operational Research Society 57 (11) 1–6] and the range directional model developed by Portela et al. [Portela, M.C.A.S., Thanassoulis, E., Simpson, G., 2004. A directional distance approach to deal with negative data in DEA: An application to bank branches. Journal of Operational Research Society 55 (10) 1111–1121]. A further example explores the advantages of using the new model.

Managing service productivity using data envelopment analysis

This chapter provides the theoretical foundation and background on data envelopment analysis (DEA) method. We first introduce the basic DEA models. The balance of this chapter focuses on evidences showing DEA has been extensively applied for measuring efficiency and productivity of services including financial services (banking, insurance, securities, and fund management), professional services, health services, education services, environmental and public services, energy services, logistics, tourism, information technology, telecommunications, transport, distribution, audio-visual, media, entertainment, cultural and other business services. Finally, we provide information on the use of Performance Improvement Management Software (PIM-DEA). A free limited version of this software and downloading procedure is also included in this chapter.

The interaction between the implementation of an occupational health and safety management system and safety culture:a case study in the rubber industry

A prominent theme emerging in Occupational Health and Safety (OSH) is the development of management systems. A range of interventions, according to a prescribed route detailed by one of the management systems, can be introduced into an organisation with some expectation of improved OSH performance. This thesis attempts to identify the key influencing factors that may impact upon the process of introducing interventions, (according to B88800: 1996, Guide to Implementing Occupational Health and Safety Management Systems) into an organisation. To help identify these influencing factors a review of possible models from the sphere of Total Quality Management (TQM) was undertaken and the most suitable TQM model selected for development and use in aSH. By anchoring the aSH model's development in the reviewed literature a range ofeare, medium and low level influencing factors were identified. This model was developed in conjunction with the research data generated within the case study organisation (rubber manufacturer) and applied to the organisation. The key finding was that the implementation of an OSH intervention was dependant upon three broad vectors of influence. These are the Incentive to introduce change within an organisation which refers to the drivers or motivators for OSH. Secondly the Ability within the management team to actually implement the changes refers to aspects, amongst others, such as leadership, commitment and perceptions of OSH. Ability is in turn itself influenced by the environment within which change is being introduced. TItis aspect of Receptivity refers to the history of the plant and characteristics of the workforce. Aspects within Receptivity include workforce profile and organisational policies amongst others. It was found that the TQM model selected and developed for an OSH management system intervention did explain the core influencing factors and their impact upon OSH performance. It was found that within the organisation the results that may have been expected from implementation of BS8800:1996 were not realised. The OSH model highlighted that given the organisation's starting point, a poor appreciation of the human factors of OSH, gave little reward for implementation of an OSH management system. In addition it was found that general organisational culture can effectively suffocate any attempts to generate a proactive safety culture.

Estimating the efficiency of healthcare facilities providing HIV/AIDS treatment in Zambia:a data envelopment approach

Zambia and many other countries in Sub-Saharan Africa face a key challenge of sustaining high levels of coverage of AIDS treatment under prospects of dwindling global resources for HIV/AIDS treatment. Policy debate in HIV/AIDS is increasingly paying more focus to efficiency in the use of available resources. In this chapter, we apply Data Envelopment Analysis (DEA) to estimate short term technical efficiency of 34 HIV/AIDS treatment facilities in Zambia. The data consists of input variables such as human resources, medical equipment, building space, drugs, medical supplies, and other materials used in providing HIV/AIDS treatment. Two main outputs namely, numbers of ART-years (Anti-Retroviral Therapy-years) and pre-ART-years are included in the model. Results show the mean technical efficiency score to be 83%, with great variability in efficiency scores across the facilities. Scale inefficiency is also shown to be significant. About half of the facilities were on the efficiency frontier. We also construct bootstrap confidence intervals around the efficiency scores.

Applications of data envelopment analysis in education

Non-parametric methods for efficiency evaluation were designed to analyse industries comprising multi-input multi-output producers and lacking data on market prices. Education is a typical example. In this chapter, we review applications of DEA in secondary and tertiary education, focusing on the opportunities that this offers for benchmarking at institutional level. At secondary level, we investigate also the disaggregation of efficiency measures into pupil-level and school-level effects. For higher education, while many analyses concern overall institutional efficiency, we examine also studies that take a more disaggregated approach, centred either around the performance of specific functional areas or that of individual employees.