Towards an integrated perspective on fleet asset management: engineering and governance considerations

The traditional engineering perspective on asset management concentrates on the operational performance the assets. This perspective aims at managing assets through their life-cycle, from technical specification, to acquisition, operation including maintenance, and disposal. However, the engineering perspective often takes for granted organizational-level factors. For example, a focus on performance at the asset level may lead to ignore performance measures at the business unit level. The governance perspective on asset management usually concentrates on organizational factors, and measures performance in financial terms. In doing so, the governance perspective tends to ignore the engineering considerations required for optimal asset performance. These two perspectives often take each other for granted. However experience demonstrates that an exclusive focus on one or the other may lead to sub-optimal performance. For example, the two perspectives have different time frames: engineering considers the long term asset life-cycle whereas the organizational time frame is based on a yearly financial calendar. Asset fleets provide a relevant and important context to investigate the interaction between engineering and governance views on asset management as fleets have distributed system characteristics. In this project we investigate how engineering and governance perspectives can be reconciled and integrated to enable optimal asset and organizational performance in the context of asset fleets

Modeling churn using customer lifetime value.

The definition and modeling of customer loyalty have been central issues in customer relationship management since many years. Recent papers propose solutions to detect customers that are becoming less loyal, also called churners. The churner status is then defined as a function of the volume of commercial transactions. In the context of a Belgian retail financial service company, our first contribution is to redefine the notion of customer loyalty by considering it from a customer-centric viewpoint instead of a productcentric one. We hereby use the customer lifetime value (CLV) defined as the discounted value of future marginal earnings, based on the customer's activity. Hence, a churner is defined as someone whose CLV, thus the related marginal profit, is decreasing. As a second contribution, the loss incurred by the CLV decrease is used to appraise the cost to misclassify a customer by introducing a new loss function. In the empirical study, we compare the accuracy of various classification techniques commonly used in the domain of churn prediction, including two cost-sensitive classifiers. Our final conclusion is that since profit is what really matters in a commercial environment, standard statistical accuracy measures for prediction need to be revised and a more profit oriented focus may be desirable.Data mining; Decision support systems; Marketing; Churn prediction;

Impact of acquisition channels on customer equity, The

Customer equity (CE henceforth) is a powerful new paradigm to evaluate the firm's value and to optimally allocate marketing resources. This paper is focused on the relationship between customer acquisition and CE. The authors attempt to answer the following four questions: 1) how should customer acquisition channels be categorized to make them meaningful to managers and academics?; 2) how do we measure the effects of different acquisition channels on the firm's performance?; 3) how do we disentangle short-run effect and long-run effects?, and 4) how should the manager allocate a limited budget among the acquisition channels so as to maximize customer equity? The authors first propose a way of categorizing customer acquisition channels according to their level of contact and intrusiveness. A vector-autoregressive (VAR) model is used to examine the dynamics of acquisition channels and the firm's performance, and an empirical illustration on a surviving Internet company is provided. The results show that each cohort (i.e., customers from different acquisition channels) has different short-run and long-run effects on the firm's performance by the subsequent login and purchasing behavior. Building on previous research on optimal resource allocation, the authors develop a Marketing Decision Support System (MDSS) to help managers allocate the acquisition budget among different channels with the objective of maximizing customer equity. The consequences of naively maximizing the short-term profit and not accounting for differences in the margin contribution of different cohorts are illustrated.customer equity; customer acquisition; VAR; long-run modeling;

Reliability-based economic model predictive control for generalized flow-based networks including actuators' health-aware capabilities

This paper proposes a reliability-based economic model predictive control (MPC) strategy for the management of generalized flow-based networks, integrating some ideas on network service reliability, dynamic safety stock planning, and degradation of equipment health. The proposed strategy is based on a single-layer economic optimisation problem with dynamic constraints, which includes two enhancements with respect to existing approaches. The first enhancement considers chance-constraint programming to compute an optimal inventory replenishment policy based on a desired risk acceptability level, leading to dynamically allocate safety stocks in flow-based networks to satisfy non-stationary flow demands. The second enhancement computes a smart distribution of the control effort and maximises actuators’ availability by estimating their degradation and reliability. The proposed approach is illustrated with an application of water transport networks using the Barcelona network as the considered case study.Peer ReviewedPostprint (author's final draft

Lessons Learned and Next Steps in Energy Efficiency Measurement and Attribution: Energy Savings, Net to Gross, Non-Energy Benefits, and Persistence of Energy Efficiency Behavior

This white paper examines four topics addressing evaluation, measurement, and attribution of direct and indirect effects to energy efficiency and behavioral programs: Estimates of program savings (gross); Net savings derivation through free ridership / net to gross analyses; Indirect non-energy benefits / impacts (e.g., comfort, convenience, emissions, jobs); and, Persistence of savings

Towards Design Principles for Data-Driven Decision Making: An Action Design Research Project in the Maritime Industry

Data-driven decision making (DDD) refers to organizational decision-making practices that emphasize the use of data and statistical analysis instead of relying on human judgment only. Various empirical studies provide evidence for the value of DDD, both on individual decision maker level and the organizational level. Yet, the path from data to value is not always an easy one and various organizational and psychological factors mediate and moderate the translation of data-driven insights into better decisions and, subsequently, effective business actions. The current body of academic literature on DDD lacks prescriptive knowledge on how to successfully employ DDD in complex organizational settings. Against this background, this paper reports on an action design research study aimed at designing and implementing IT artifacts for DDD at one of the largest ship engine manufacturers in the world. Our main contribution is a set of design principles highlighting, besides decision quality, the importance of model comprehensibility, domain knowledge, and actionability of results

Access to telecommunications networks

telecommunication;telecommunication industry;networks;access to market;policy;allocation;microeconomics