Development and implementation issues for managing sales performance

The research project concentrates on the issues which a host organisation faces, in developing and implementing an efficient and cost-effective conceptual framework for measuring and managing sales performance in the automotive retail sector. Sales performance is a critical and main issue for an organisation in order to achieve its strategic objectives, by translating the results into action and monitoring the process. Due to the global financial crisis, organisations experience an economic downturn. This makes the use of a standard framework which can support their derived action plans of vital importance. This framework would aim to offer a holistic view of the sales performance with accurate results. A review of the literature provided extensive information and analysis of the different models and frameworks that could be identified and used in performance measurement literature. In addition, it provided an evaluation of the existing documentary and practices of the host organisation regarding performance measurement. As, a result, the needs for the development of an improved framework were identified. The proposed methodology was based on the integration of three frameworks, namely the SWOT Analysis, Balanced Score Card and Internal procedures as part of a performance management system. The research indicated that it is essential to synthesise and extend the existing models and frameworks with the aim to produce the most suitable conceptual framework based on the size, kind, and available resources of the organisation. Through qualitative and quantitative analysis, this project provides evidence, which indicates the successful application of measuring and managing sales performance techniques through the use of reports, training communication capabilities and presentation skills. It creates a new political and organisational challenge for the staff of the organisation, which in its turn had to learn to interact fast and effectively in order to achieve their targets. It considers the external and internal influences impacting on a sales organisation and how the management team and staff can offer an actively sought process to monitor business performance on an on-going basis and to generate recommendations for changes. The research indicates that the proposed framework connects the measurement results with the derived action plans following a continuing improvement approach. The project has not only a theoretical approach but it also focuses on the implementation process. The proposed framework was developed in the host organisation with a step by step methodology establishing a reporting analysis tool. It concludes by the realisation that specific processes are required to implement the sales performance reporting analysis tool

ROBOUT: a conditional outlier detection methodology for high-dimensional data

This paper presents a methodology, called ROBOUT, to identify outliers conditional on a high-dimensional noisy information set. In particular, ROBOUT is able to identify observations with outlying conditional mean or variance when the dataset contains multivariate outliers in or besides the predictors, multi-collinearity, and a large variable dimension compared to the sample size. ROBOUT entails a pre-processing step, a preliminary robust imputation procedure that prevents anomalous instances from corrupting predictor recovery, a selection stage of the statistically relevant predictors (through cross-validated LASSO-penalized Huber loss regression), the estimation of a robust regression model based on the selected predictors (via MM regression), and a criterion to identify conditional outliers. We conduct a comprehensive simulation study in which the proposed algorithm is tested under a wide range of perturbation scenarios. The combination formed by LASSO-penalized Huber loss and MM regression turns out to be the best in terms of conditional outlier detection under the above described perturbed conditions, also compared to existing integrated methodologies like Sparse Least Trimmed Squares and Robust Least Angle Regression. Furthermore, the proposed methodology is applied to a granular supervisory banking dataset collected by the European Central Bank, in order to model the total assets of euro area banks

Banks’ business models in the euro area: a cluster analysis in high dimensions

We propose a clustering method for large dimensional data to classify the 365 largest euro area financial institutions according to their business model. The proposed clustering approach is applied to granular supervisory data on banks’ activities and combines also dimensionality reduction and outlier detection. We identify four business models, namely wholesale funded, securities holding, traditional commercial and complex commercial banks while identifying as outliers the banks that follow idiosyncratic business models. Evidence is provided that the sets of banks following the distinct business models differ with respect to performance and risk indicators

Banks’ risk-taking within a banking union

We study the relationship between banks’ size and risk-taking in the context of supranational banking supervision. Consistently with theoretical work on banking unions and in contrast to analyses emphasising incentives underpinned by the too-big-to-fail effect, we find an inverse relationship between banks’ size and non-performing loan growth for a sample of European banks. Evidence is provided that the mechanism operates through the enhanced organisational efficiency of the supranational set-up rather than incentives alignment among the supervisors and the banks

Emil Lederer and the Schumpeter- Hilferding-Tugan-Baranowsky Nexus

This paper focuses on the thinking of Emil Lederer, one of the leading academic socialists of Germany in the 1920s. Lederer's views on economic development, technical change, credit and business cycles are compared to those of Schumpeter. The paper traces the roots of some of their ideas back to the work of two prominent Marxists, Rudolf Hilferding and Mikhail Ivanovich Tugan-Baranowsky. The paper concludes that although Lederer and Schumpeter are traditionally classified in different schools of thought, their theoretical views on many issues converge. © 2011 Taylor & Francis

Heterodox influences on Schumpeter

Purpose - Joseph Alois Schumpeter's ideas are in the discussion agenda of various economists working in different theoretical traditions. However, several aspects of his work remain unexplored. In particular, the origin of his ideas in the context of the then prevalent economic theories of the German-speaking camp, have not been widely discussed. The purpose of this paper is claim that the elaborations of certain German-speaking heterodox economists and/or schools of economic thought may be traced in Schumpeter's oeuvre. Design/methodology/approach - The influence of the German Historical School and specifically of Gustav von Schmoller, Max Weber and Werner Sombart on typical Schumpeterian themes is examined. In a similar vein, it is argued that Schumpeter's analysis presents striking similarities with the works of the Austro-Marxist Economist Rudolf-Hilferding and the Austrian Social Democrat Emil Lederer. Findings - In this context, certain Schumpeterian insights appear less original. Originality/value - Conclusively, it may be inferred that a deeper understanding of Schumpeterian economic analysis presupposes an acquaintance with certain heterodox theoretical traditions of the German-speaking world. © Emerald Group Publishing Limited

Macroprudential stress-testing practices of central banks in Central and Southeastern Europe: comparison and challenges ahead

This paper reviews and compares stress-testing practices of central banks in Central and Southeastern Europe (CSEECBs) and outlines challenges in the area of stress testing going forward. The authors, focusing their comparison on CSEECBs, construct the baseline and stress scenarios, map macroeconomic scenarios and microeconomic factors to risk factors, calculate risk exposures to different risk indicators, and estimate outcome indicators to inform macroprudential policy. The main challenges going forward concern data reliability, consideration of quantitative microprudential indicators, incorporation of feedback effects in stress tests, institutionalization of macroprudential policy responses to alarming stress-test results, and information exchange for better cross-border supervision.Web of Science48414311