8 research outputs found
A Multi-Agent Simulation of Retail Management Practices
We apply Agent-Based Modeling and Simulation (ABMS) to investigate a set of
problems in a retail context. Specifically, we are working to understand the
relationship between human resource management practices and retail
productivity. Despite the fact we are working within a relatively novel and
complex domain, it is clear that intelligent agents do offer potential for
developing organizational capabilities in the future. Our multi-disciplinary
research team has worked with a UK department store to collect data and capture
perceptions about operations from actors within departments. Based on this case
study work, we have built a simulator that we present in this paper. We then
use the simulator to gather empirical evidence regarding two specific
management practices: empowerment and employee development
Towards the Development of a Simulator for Investigating the Impact of People Management Practices on Retail Performance
Often models for understanding the impact of management practices on retail
performance are developed under the assumption of stability, equilibrium and
linearity, whereas retail operations are considered in reality to be dynamic,
non-linear and complex. Alternatively, discrete event and agent-based modelling
are approaches that allow the development of simulation models of heterogeneous
non-equilibrium systems for testing out different scenarios. When developing
simulation models one has to abstract and simplify from the real world, which
means that one has to try and capture the 'essence' of the system required for
developing a representation of the mechanisms that drive the progression in the
real system. Simulation models can be developed at different levels of
abstraction. To know the appropriate level of abstraction for a specific
application is often more of an art than a science. We have developed a retail
branch simulation model to investigate which level of model accuracy is
required for such a model to obtain meaningful results for practitioners.Comment: 24 pages, 7 figures, 6 tables, Journal of Simulation 201
Understanding Retail Productivity by Simulating Management Practise
Intelligent agents offer a new and exciting way of understanding the world of
work. In this paper we apply agent-based modeling and simulation to investigate
a set of problems in a retail context. Specifically, we are working to
understand the relationship between human resource management practices and
retail productivity. Despite the fact we are working within a relatively novel
and complex domain, it is clear that intelligent agents could offer potential
for fostering sustainable organizational capabilities in the future. Our
research so far has led us to conduct case study work with a top ten UK
retailer, collecting data in four departments in two stores. Based on our case
study data we have built and tested a first version of a department store
simulator. In this paper we will report on the current development of our
simulator which includes new features concerning more realistic data on the
pattern of footfall during the day and the week, a more differentiated view of
customers, and the evolution of customers over time. This allows us to
investigate more complex scenarios and to analyze the impact of various
management practices
Measuring organisational performance using a mix of OR methods
Performance measurement has become an increasingly important issue in recent years. In spite of the remarkable progress that has been achieved in this area of research, many performance measurement initiatives fall short of their potential in supporting decision-making. This paper argues that adopting a multi-method approach to assessing performance has the potential to result in more comprehensive and effective performance measurement systems. To support this assertion, the paper discusses the development of a performance measurement system for a Business Tax Department, which combined the use of several operational research (OR) techniques including qualitative system dynamics, data envelopment analysis and multiple criteria decision analysis. The use of these OR techniques was influential in developing and implementing the performance measurement system and has the potential to be transferred to other contexts
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Efficiency measurement. A methodological comparison of parametric and non-parametric approaches.
The thesis examines technical efficiency using frontier efficiency estimation techniques from parametric and non-parametric approaches. Five different frontier efficiency estimation techniques are considered which are SFA, DFA, DEA-CCR, DEA-BCC and DEA-RAM. These techniques are then used on an artificially generated panel dataset using a two-input two-output production function framework based on characteristics of German life-insurers. The key contribution of the thesis is firstly, a study that uses simulated panel dataset to estimate frontier efficiency techniques and secondly, a research framework that compares multiple frontier efficiency techniques across parametric and non-parametric approaches in the context of simulated panel data. The findings suggest that, as opposed to previous studies, parametric and non-parametric approaches can both generate comparable technical efficiency scores with simulated data. Moreover, techniques from parametric approaches, i.e. SFA and DFA are consistent with each other whereas the same applies to non-parametric approaches, i.e. DEA models. The research study also discusses some important theoretical and methodological implication of the findings and suggests some ways whereby future research can enable to overcome some of the restrictions associated with current approaches