Mandatory accounting disclosure by small private companies

This article analyzes how mandatory accounting disclosure is grounded on differentrationales for private and public companies. It also explores technological changes, such ascomputerised databases and the Internet, which have recently made disclosure of companyaccounts by small companies potentially less costly and more valuable, thanks to electronicfiling and universal online access to credit information systems. These recent developmentsfavour policies that would expand the scope of mandatory publication for small companies incountries where it is voluntary. They also encourage policies to reduce the costs and enhancethe value of disclosure through administrative reforms of filing, archive and retrieval systems.Survey and registry evidence on how the information in the accounts is valued and used bycompanies is consistent with these claims about the evolution of the tradeoff of costs andbenefits that should guide policy in this area.

Are Americans' musical preferences more omnivores today?

Although we found a general trend favouring the omnivorousness thesis, as soon as we adjusted it to a set of structural factors and consumers tastes it was clear that this was caused by elitist inclusive omnivores who had increased the scope of their tastes. In general, younger cohorts were becoming less omnivorous, nevertheless, they were also becoming more educated and had greater to higher levels of inc ome, making the youth moreomnivorous. As expected, upscale consumers set limits on their popular taste: musicalgenres, whose audiences had educational levels below the mean profile were less preferredby upscale respondents. In spite of this, as time passed, some popular brows gained socialstatus.

Hybrid consumption paths in the attribute space: A model and application with scanner data

This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products.We run some simulations to analyze the consumption paths out of the steady state. Underthe hybrid utility assumption, the consumer behaves inertially among the unfamiliar brandsfor several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.

Cumulative dominance and heuristic performance in binary multi-attribute choice

Several studies have reported high performance of simple decision heuristics multi-attribute decision making. In this paper, we focus on situations where attributes are binary and analyze the performance of Deterministic-Elimination-By-Aspects (DEBA) and similar decision heuristics. We consider non-increasing weights and two probabilistic models for the attribute values: one where attribute values are independent Bernoulli randomvariables; the other one where they are binary random variables with inter-attribute positive correlations. Using these models, we show that good performance of DEBA is explained by the presence of cumulative as opposed to simple dominance. We therefore introduce the concepts of cumulative dominance compliance and fully cumulative dominance compliance and show that DEBA satisfies those properties. We derive a lower bound with which cumulative dominance compliant heuristics will choose a best alternative and show that, even with many attributes, this is not small. We also derive an upper bound for the expected loss of fully cumulative compliance heuristics and show that this is moderateeven when the number of attributes is large. Both bounds are independent of the values ofthe weights.

Specificity revisited: The role of cross-investments

Previous analysis has shown that traders may opt for specific technologies with nojoint productivity advantage as a way to commit themselves to trading jointly, butonly when long-term contracting is infeasible. This paper proves that speciÞcity canalso be optimal (by relaxing the budget-balance constraint) in settings with long-termcontracting. Traders will opt for specificity when one trader makes a cross-investmentand either (1) this cross-investment has a direct externality on the other trader, (2) bothparties invest, or (3) private information is present. The specificity (e.g. from non-salvageable investments, specific assets and technologies, narrow business strategies,and exclusivity restrictions) is equally effective regardless of which trader's alternativetrade payoff is reduced. Specificity supports long-term contracts in a broad rangeof settings - both with and without renegotiation. The theory also offers a novelperspective on franchising and vertical integration.

Biased quantitative measurement of interval ordered homothetic preferences

We represent interval ordered homothetic preferences with a quantitative homothetic utility function and a multiplicative bias. When preferences are weakly ordered (i.e. when indifference is transitive), such a bias equals 1. When indifference is intransitive, the biasing factor is a positive function smaller than 1 and measures a threshold of indifference. We show that the bias is constant if and only if preferences are semiordered, and we identify conditions ensuring a linear utility function. We illustrate our approach with indifference sets on a two dimensional commodity space.

Implementing TURF analysis through binary linear programming

This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.

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.

An enhanced concave program relaxation for choice network revenue management

The network choice revenue management problem models customers as choosing from an offer-set, andthe firm decides the best subset to offer at any given moment to maximize expected revenue. The resultingdynamic program for the firm is intractable and approximated by a deterministic linear programcalled the CDLP which has an exponential number of columns. However, under the choice-set paradigmwhen the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has beenproposed but finding an entering column has been shown to be NP-hard. In this paper, starting with aconcave program formulation based on segment-level consideration sets called SDCP, we add a class ofconstraints called product constraints, that project onto subsets of intersections. In addition we proposea natural direct tightening of the SDCP called ?SDCP, and compare the performance of both methodson the benchmark data sets in the literature. Both the product constraints and the ?SDCP method arevery simple and easy to implement and are applicable to the case of overlapping segment considerationsets. In our computational testing on the benchmark data sets in the literature, SDCP with productconstraints achieves the CDLP value at a fraction of the CPU time taken by column generation and webelieve is a very promising approach for quickly approximating CDLP when segment consideration setsoverlap and the consideration sets themselves are relatively small.

What do the papers sell?

We model the market for news as a two-sided market where newspapers sell news to readers who value accuracy and sell space to advertisers who value advert-receptive readers. We show that monopolistic newspapers under-report or bias news that sufficiently reduces advertiser profits. Newspaper competition generally reduces the impact of advertising. In fact, as the size of advertising grows, newspapers may paradoxically reduce advertiser bias, due to increasing competition for readers. However, advertisers can counter this effect of competition by committing to news-sensitive cut-off strategies, potentially inducing as much under-reporting as in the monopoly case.

Behavioral assumptions and management ability

The paper explores the consequences that relying on different behavioral assumptions intraining managers may have on their future performance. We argue that training with anemphasis on the standard assumptions used in economics (rationality and self-interest) is goodfor technical posts but may also lead future managers to rely excessively on rational and explicitsafeguarding, crowding out instinctive relational heuristics and signaling a bad human type topotential partners. In contrast, human assumptions used in management theories, because oftheir diverse, implicit and even contradictory nature, do not conflict with the innate set ofcooperative tools and may provide a good training ground for such tools. We present tentativeconfirmatory evidence by examining how the weight given to behavioral assumptions in the corecourses of the top 100 business schools influences the average salaries of their MBA graduates.Controlling for the self-selected average quality of their students and some other schools characteristics, average salaries are seen to be significantly greater for schools whose core MBAcourses contain a higher proportion of management courses as opposed to courses based oneconomics or technical disciplines.

Pitfalls to avoid when measuring institutions: Is "Doing Business" damaging business?

Over recent years, both governments and international aid organizations have been devoting large amounts of resources to simplifying the procedures for setting up and formalizing firms. Many of these actions have focused on reducing the initial costs of setting up the firm, disregarding the more important role of business registers as a source of reliable information for judges, government departments and, above all, other firms. This reliable information is essential for reducing transaction costs in future dealings with all sorts of economic agents, both public and private. The priorities of reform policies should therefore be thoroughly reviewed, stressing the value of the legal institutions rather than trivializing them as is often the case.

How to recognize opportunities: Heterarchical search in a Wall Street trading room

Our task in this paper is to analyze the organization of trading in the era of quantitativefinance. To do so, we conduct an ethnography of arbitrage, the trading strategy that bestexemplifies finance in the wake of the quantitative revolution. In contrast to value andmomentum investing, we argue, arbitrage involves an art of association - the constructionof equivalence (comparability) of properties across different assets. In place of essentialor relationa l characteristics, the peculiar valuation that takes place in arbitrage is based on an operation that makes something the measure of something else - associating securities to each other. The process of recognizing opportunities and the practices of making novel associations are shaped by the specific socio-spatial and socio-technical configurations of the trading room. Calculation is distributed across persons and instruments as the trading room organizes interaction among diverse principles of valuation.

Perceptual mapping of practical ethics along the value chain: A multiple correspondence analysis with industry and cultural indices as supplementary variables

This paper presents findings from a study investigating a firm s ethical practices along the value chain. In so doing we attempt to better understand potential relationships between a firm s ethical stance with its customers and those of its suppliers within a supply chain and identify particular sectoral and cultural influences that might impinge on this. Drawing upon a database comprising of 667 industrial firms from 27 different countries, we found that ethical practices begin with the firm s relationship with its customers, the characteristics of which then influence the ethical stance with the firm s suppliers within the supply chain. Importantly, market structure along with some key cultural characteristics were also found to exert significant influence on the implementation of ethical policies in these firms.

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.