Proving the performance of a new revenue management system

Revenue management (RM) is a complicated business process that can best be described ascontrol of sales (using prices, restrictions, or capacity), usually using software as a tool to aiddecisions. RM software can play a mere informative role, supplying analysts with formatted andsummarized data who use it to make control decisions (setting a price or allocating capacity fora price point), or, play a deeper role, automating the decisions process completely, at the otherextreme. The RM models and algorithms in the academic literature by and large concentrateon the latter, completely automated, level of functionality.A firm considering using a new RM model or RM system needs to evaluate its performance.Academic papers justify the performance of their models using simulations, where customerbooking requests are simulated according to some process and model, and the revenue perfor-mance of the algorithm compared to an alternate set of algorithms. Such simulations, whilean accepted part of the academic literature, and indeed providing research insight, often lackcredibility with management. Even methodologically, they are usually awed, as the simula-tions only test \within-model" performance, and say nothing as to the appropriateness of themodel in the first place. Even simulations that test against alternate models or competition arelimited by their inherent necessity on fixing some model as the universe for their testing. Theseproblems are exacerbated with RM models that attempt to model customer purchase behav-ior or competition, as the right models for competitive actions or customer purchases remainsomewhat of a mystery, or at least with no consensus on their validity.How then to validate a model? Putting it another way, we want to show that a particularmodel or algorithm is the cause of a certain improvement to the RM process compared to theexisting process. We take care to emphasize that we want to prove the said model as the causeof performance, and to compare against a (incumbent) process rather than against an alternatemodel.In this paper we describe a \live" testing experiment that we conducted at Iberia Airlineson a set of flights. A set of competing algorithms control a set of flights during adjacentweeks, and their behavior and results are observed over a relatively long period of time (9months). In parallel, a group of control flights were managed using the traditional mix of manualand algorithmic control (incumbent system). Such \sandbox" testing, while common at manylarge internet search and e-commerce companies is relatively rare in the revenue managementarea. Sandbox testing has an undisputable model of customer behavior but the experimentaldesign and analysis of results is less clear. In this paper we describe the philosophy behind theexperiment, the organizational challenges, the design and setup of the experiment, and outlinethe analysis of the results. This paper is a complement to a (more technical) related paper thatdescribes the econometrics and statistical analysis of the results.

A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters

Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.

Ownership structure, customer satisfaction and brand equity

This paper studies the interaction between ownership structure, taken as a proxy for shareholders commitment, and customer satisfaction - the main driver of consumer loyalty - and their impact on a firm s brand equity. The results show that customer satisfaction has a positive direct effect on brand equity but an indirect negative one because of reductions in ownership concentration. This latter effect emerges when managers are mainly customer-oriented. Such result gives out a warning signal that highlights the perverse effect of implementing policies, focused excessively on satisfying customers at the expense of shareholders, on a firm s brand equity. The empirical analysis uses an incomplete panel data comprising 69 firms from 11 nations, for the period 2002-2005.

Pro-adrenomedullin usefulness in the management of children with community-acquired pneumonia, a preliminary prospective observational study

BackgroundIn adult population with community acquired pneumonia high levels of pro-adrenomedullin (pro-ADM) have been shown to be predictors of worse prognosis. The role of this biomarker in pediatric patients had not been analyzed to date. The objective of this study is to know the levels of pro-ADM in children with community acquired pneumonia (CAP) and analyze the relation between these levels and the patients¿ prognosis.FindingsProspective observational study including patients attended in the emergency service (January to October 2009) admitted to hospital with CAP and no complications at admission. The values for pro-ADM were analyzed in relation to: need for oxygen therapy, duration of oxygen therapy, fever and antibiotic therapy, complications, admission to the intensive care unit, and length of hospital stay. Fifty patients were included. Ten presented complications (7 pleural effusion). The median level of pro-ADM was 1.0065¿nmol/L (range 0.3715 to 7.2840¿nmol/L). The patients presenting complications had higher levels of pro-ADM (2.3190 vs. 1.1758¿nmol/L, p¿=¿0.013). Specifically, the presence of pleural effusion was associated with higher levels of pro-ADM (2.9440 vs. 1.1373¿nmol/L, p¿<¿0.001).ConclusionsIn our sample of patients admitted to hospital with CAP, pro-ADM levels are related to the development of complications during hospitalization.

On the tractability of the piecewise-linear approximation for general discrete-choice network revenue management

The choice network revenue management (RM) model incorporates customer purchase behavioras customers purchasing products with certain probabilities that are a function of the offeredassortment of products, and is the appropriate model for airline and hotel network revenuemanagement, dynamic sales of bundles, and dynamic assortment optimization. The underlyingstochastic dynamic program is intractable and even its certainty-equivalence approximation, inthe form of a linear program called Choice Deterministic Linear Program (CDLP) is difficultto solve in most cases. The separation problem for CDLP is NP-complete for MNL with justtwo segments when their consideration sets overlap; the affine approximation of the dynamicprogram is NP-complete for even a single-segment MNL. This is in contrast to the independentclass(perfect-segmentation) case where even the piecewise-linear approximation has been shownto be tractable. In this paper we investigate the piecewise-linear approximation for network RMunder a general discrete-choice model of demand. We show that the gap between the CDLP andthe piecewise-linear bounds is within a factor of at most 2. We then show that the piecewiselinearapproximation is polynomially-time solvable for a fixed consideration set size, bringing itinto the realm of tractability for small consideration sets; small consideration sets are a reasonablemodeling tradeoff in many practical applications. Our solution relies on showing that forany discrete-choice model the separation problem for the linear program of the piecewise-linearapproximation can be solved exactly by a Lagrangian relaxation. We give modeling extensionsand show by numerical experiments the improvements from using piecewise-linear approximationfunctions.

Clinical management and burden of bipolar disorder: a multinational longitudinal study (WAVE-bd Study)

BACKGROUND: Studies in bipolar disorder (BD) to date are limited in their ability to provide a whole-disease perspective--their scope has generally been confined to a single disease phase and/or a specific treatment. Moreover, most clinical trials have focused on the manic phase of disease, and not on depression, which is associated with the greatest disease burden. There are few longitudinal studies covering both types of patients with BD (I and II) and the whole course of the disease, regardless of patients' symptomatology. Therefore, the Wide AmbispectiVE study of the clinical management and burden of Bipolar Disorder (WAVE-bd) (NCT01062607) aims to provide reliable information on the management of patients with BD in daily clinical practice. It also seeks to determine factors influencing clinical outcomes and resource use in relation to the management of BD. METHODS: WAVE-bd is a multinational, multicentre, non-interventional, longitudinal study. Approximately 3000 patients diagnosed with BD type I or II with at least one mood event in the preceding 12 months were recruited at centres in Austria, Belgium, Brazil, France, Germany, Portugal, Romania, Turkey, Ukraine and Venezuela. Site selection methodology aimed to provide a balanced cross-section of patients cared for by different types of providers of medical aid (e.g. academic hospitals, private practices) in each country. Target recruitment percentages were derived either from scientific publications or from expert panels in each participating country. The minimum follow-up period will be 12 months, with a maximum of 27 months, taking into account the retrospective and the prospective parts of the study. Data on demographics, diagnosis, medical history, clinical management, clinical and functional outcomes (CGI-BP and FAST scales), adherence to treatment (DAI-10 scale and Medication Possession Ratio), quality of life (EQ-5D scale), healthcare resources, and caregiver burden (BAS scale) will be collected. Descriptive analysis with common statistics will be performed. DISCUSSION: This study will provide detailed descriptions of the management of BD in different countries, particularly in terms of clinical outcomes and resources used. Thus, it should provide psychiatrists with reliable and up-to-date information about those factors associated with different management patterns of BD. TRIAL REGISTRATION NO: ClinicalTrials.gov: NCT01062607.

Measuring service quality in sport management: an application of the SERVQUAL scale

The aim of this study is to provide an instrument for measuring service quality in sports enterprises from the point of view of the customers. For this purpose we intend to elaborate an enquiry starting out from a more general scale called SERVIQUAL. We have limited our research project to sports enterprises where the customer participates actively, i.e., we have excluded sports clubs and other organizations which offer sport as entertainment. Our choice is mainly due to the fact that few studies have been carried out in this area and that sports has been earning an increasing amount of adepts during the last decades in Spain. The DELPHI method has been applied with the collaboration of a panel of experts in order to evaluate the viability and adequacy of the modified SERVQUAL scale.

Clinical management and burden of bipolar disorder: a multinational longitudinal study (WAVE-bd Study)

BACKGROUND: Studies in bipolar disorder (BD) to date are limited in their ability to provide a whole-disease perspective--their scope has generally been confined to a single disease phase and/or a specific treatment. Moreover, most clinical trials have focused on the manic phase of disease, and not on depression, which is associated with the greatest disease burden. There are few longitudinal studies covering both types of patients with BD (I and II) and the whole course of the disease, regardless of patients' symptomatology. Therefore, the Wide AmbispectiVE study of the clinical management and burden of Bipolar Disorder (WAVE-bd) (NCT01062607) aims to provide reliable information on the management of patients with BD in daily clinical practice. It also seeks to determine factors influencing clinical outcomes and resource use in relation to the management of BD. METHODS: WAVE-bd is a multinational, multicentre, non-interventional, longitudinal study. Approximately 3000 patients diagnosed with BD type I or II with at least one mood event in the preceding 12 months were recruited at centres in Austria, Belgium, Brazil, France, Germany, Portugal, Romania, Turkey, Ukraine and Venezuela. Site selection methodology aimed to provide a balanced cross-section of patients cared for by different types of providers of medical aid (e.g. academic hospitals, private practices) in each country. Target recruitment percentages were derived either from scientific publications or from expert panels in each participating country. The minimum follow-up period will be 12 months, with a maximum of 27 months, taking into account the retrospective and the prospective parts of the study. Data on demographics, diagnosis, medical history, clinical management, clinical and functional outcomes (CGI-BP and FAST scales), adherence to treatment (DAI-10 scale and Medication Possession Ratio), quality of life (EQ-5D scale), healthcare resources, and caregiver burden (BAS scale) will be collected. Descriptive analysis with common statistics will be performed. DISCUSSION: This study will provide detailed descriptions of the management of BD in different countries, particularly in terms of clinical outcomes and resources used. Thus, it should provide psychiatrists with reliable and up-to-date information about those factors associated with different management patterns of BD. TRIAL REGISTRATION NO: ClinicalTrials.gov: NCT01062607.