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

Scope Management of Non-Functional Requirements

In order to meet commitments in software projects, a realistic assessment must be made of project scope. Such an assessment relies on the availability of knowledge on the user-defined project requirements and their effort estimates and priorities, as well as their risk. This knowledge enables analysts, managers and software engineers to identify the most significant requirements from the list of requirements initially defined by the user. In practice, this scope assessment is applied to the Functional Requirements (FRs) provided by users who are unaware of, or ignore, the Non-Functional Requirements (NFRs). This paper presents ongoing research which aims at managing NFRs during the software development process. Establishing the relative priority of each NFR, and obtaining a rough estimate of the effort and risk associated with it, is integral to the software development process and to resource management. Our work extends the taxonomy of the NFR framework by integrating the concept of the "hardgoal". A functional size measure of NFRs is applied to facilitate the effort estimation process. The functional size measurement method we have chosen is COSMICFFP, which is theoretically sound and the de facto standard in the software industry

From ERP to advanced resource planning: Improving the operational performance by getting the inputs right.

In this paper, we show that the planning and decision support capabilities of the MPC (Manufacturing Planning and Control) system, which forms the core of any ERP package, may be greatly enhanced by including an Advanced Resource Planning (ARP) module as an add-on at the midterm planning level. This ARP module enables to estimate the impact of variability, complexity and dynamic system behavior on key planning parameters. As such, it yields realistic information both for short-term planning purposes and for reliable lead time quotations. We show how dynamic behavior impacts the operational performance of a manufacturing system, and discuss the framework for incorporating the ARP module into the ERP system.Planning; Operational performance; Performance; International; Science;

Determining the indirect value of a customer

The issue of accountability in marketing has led to a substantial and growing body of work on how to value customer relationships. Net present value methods (customer lifetime value / customer equity) have emerged as generally preferred ways to assess the financial value of customers. However, such calculations fail to take account of other important but indirect sources of value noted by previous researchers, such as advocacy. This paper examines the development and application of three processes to determine indirect value in business-to- business and business-to-consumer contexts. The research shows that indirect value has a measurable monetary impact not captured by conventional financial tools, and that understanding this changes the way in which customers are managed

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

Non-functional requirements: size measurement and testing with COSMIC-FFP

The non-functional requirements (NFRs) of software systems are well known to add a degree of uncertainty to process of estimating the cost of any project. This paper contributes to the achievement of more precise project size measurement through incorporating NFRs into the functional size quantification process. We report on an initial solution proposed to deal with the problem of quantitatively assessing the NFR modeling process early in the project, and of generating test cases for NFR verification purposes. The NFR framework has been chosen for the integration of NFRs into the requirements modeling process and for their quantitative assessment. Our proposal is based on the functional size measurement method, COSMIC-FFP, adopted in 2003 as the ISO/IEC 19761 standard. Also in this paper, we extend the use of COSMIC-FFP for NFR testing purposes. This is an essential step for improving NFR development and testing effort estimates, and consequently for managing the scope of NFRs. We discuss the merits of the proposed approach and the open questions related to its design

Predicting Customer Lifetime Value in Multi-Service Industries

Customer lifetime value (CLV) is a key-metric within CRM. Although, a large number of marketing scientists and practitioners argue in favor of this metric, there are only a few studies that consider the predictive modeling of CLV. In this study we focus on the prediction of CLV in multi-service industries. In these industries customer behavior is rather complex, because customers can purchase more than one service, and these purchases are often not independent from each other. We compare the predictive performance of different models, which vary in complexity and realism. Our results show that for our application simple models assuming constant profits over time have the best predictive performance at the individual customer level. At the customer base level more complicated models have the best performance. At the aggregate level, forecasting errors are rather small, which emphasizes the usability of CLV predictions for customer base valuation purposes. This might especially be interesting for accountants and financial analysts.forecasting;value;customer relationship management;customer lifetime value;customer segmentation;database marketing;interactive marketing

Decision support for build-to-order supply chain management through multiobjective optimization

This paper aims to identify the gaps in decision-making support based on multiobjective optimization for build-to-order supply chain management (BTOSCM). To this end, it reviews the literature available on modelling build-to-order supply chains (BTO-SC) with the focus on adopting multiobjective optimization (MOO) techniques as a decision support tool. The literature has been classified based on the nature of the decisions in different part of the supply chain, and the key decision areas across a typical BTO-SC are discussed in detail. Available software packages suitable for supporting decision making in BTO supply chains are also identified and their related solutions are outlined. The gap between the modelling and optimization techniques developed in the literature and the decision support needed in practice are highlighted and future research directions to better exploit the decision support capabilities of MOO are proposed

Managing customer relationships through price and service quality

This paper examines the ways in which a service provider's policies on pricing and service level affect the size of its customer base and profitability. The analysis begins with the development of a customer behavior model that uses customer satisfaction and depth of relationship as mediators of the impact of price and service level on profitability. Based on this model of customer behavior, the system is analyzed as a queuing network from which the properties of the aggregate population's behavior are derived. The analysis reveals the counterintuitive result that a policy that involves a decrease in prices or an increase in service level may lead to a smaller customer base. However, this policy may also lead to higher profits. The novelty of this result lies in the explanation of the phenomenon: that when the customer base decreases due to a change in prices or service quality, companies may experience gains in profit that result not from a decrease in costs associated with serving fewer customers but from an increase in revenues resulting from the indirect effects of the lower prices or higher level of service on customer behavior. The application of optimization techniques to the model developed in this paper yields optimality conditions through which managers can assess the long-term profitability of their pricing and service-level policies.Customer relationship management; operations/marketing interface; two-part tariffs; service operations management; service quality;