The Limits of ex post Implementation

The sensitivity of Bayesian implementation to agents' beliefs about others suggests the use of more robust notions of implementation such as ex post implementation, which requires that each agent's strategy be optimal for every possible realization of the types of other agents. We show that the only deterministic social choice functions that are ex post implementable in generic mechanism design frameworks with multidimensional signals, interdependent valuations, and transferable utilities are constant functions. In other words, deterministic ex post implementation requires that the same alternative must be chosen irrespective of agents' signals. The proof shows that ex post implementability of a nontrivial deterministic social choice function implies that certain rates of information substitution coincide for all agents. This condition amounts to a system of differential equations that are not satisfied by generic valuation functions.     

Methods for comparing policies using multiple criteria: an urban example

This paper looks at a variety of methods that can be used in evaluating a set of alternate policies using multiple criteria. The methods examined are the structural mapping of indifferences, utility values, lexicographic ordering, factor analysis, concordance analysis and multidimension scaling. Each method is tested using hypothetical data for a problem in which alternative policies are proposed for allocating monies to housing and health projects in a town. The aim is to try to reveal as objectively as possible, a set of preferred alternatives from which one can be chosen in the political decision-making process. After describing and testing the methods individually, they are compared both on the basis of their results and on the principles involved in their approach. Conclusions about the validity of each method are given, and it is emphasized that all methods should only be used as aids in the choice of an optimal policy.     

Self‐Selective Social Choice Functions Verify Arrow and Gibbard‐Satterthwaite Theorems

This paper introduces a new notion of consistency for social choice functions, called self‐selectivity, which requires that a social choice function employed by a society to make a choice from a given alternative set it faces should choose itself from among other rival such functions when it is employed by the society to make this latter choice as well. A unanimous neutral social choice function turns out to be universally self‐selective if and only if it is Paretian and satisfies independence of irrelevant alternatives. The neutralunanimous social choice functions whose domains consist of linear order profiles on nonempty sets of any finite cardinality induce a class of social welfare functions that inherit Paretianism and independence of irrelevant alternatives in case the social choice function with which one starts is universally self‐selective. Thus, a unanimous and neutral social choice function is universally self‐selective if and only if it is dictatorial. Moreover, universal self‐selectivity for such functions is equivalent to the conjunction of strategy‐proofness and independence of irrelevant alternatives or the conjunction of monotonicity and independence of irrelevant alternatives again.     

自建VS.并购:物流一体化竞争下的电商平台演化博弈

在竞争环境下，各大电商平台相继以自建或并购方式完成了自营物流系统的建设。文章立足于电商平台的物流一体化建设实践，以自建和并购作为电商平台构建物流体系的备选策略，首先采用逆序归纳法分别求得了两平台在均采取物流自建方案、均采取物流并购方案及一方采取物流自建方案而另一方采取物流并购方案时的均衡利润；然后，基于演化博弈理论，对不同均衡点的稳定性进行了分析；最后，得出了四种不同的演化稳定均衡结果。结果表明：（1）如果物流自建投入明显低于物流并购投入，且买家需求对竞争对手的物流服务不敏感时，两平台均将物流自建作为占优方案，从而双方的演化博弈将形成唯一的混同均衡——（物流自建，物流自建）。（2）如果物流并购投入明显低于物流自建投入，且买家需求对竞争对手的物流服务不敏感时，两平台均将物流并购作为占优方案，从而双方的演化博弈将形成唯一的混同均衡——（物流并购，物流并购）。（3）如果两种物流一体化方案的前期固定投入差异较小，且后期运营支出对物流服务水平不敏感，买家需求对对方平台的物流服务敏感时，两平台均无占优策略，而是采取与对手方案相同的物流一体化策略，使得双方的演化博弈形成两个混同均衡——（物流自建，物流自建）与（物流并购，物流并购）。（4）如果两种物流一体化方案的前期固定投入差异较小，且后期运营支出对物流服务水平不敏感，买家需求对对方平台的物流服务不敏感时，两平台均无占优策略，而是选择与对手方案相异的物流一体化策略，从而双方的演化博弈将形成两个分离均衡——（物流自建，物流并购）与（物流并购，物流自建）。     

Nonparametric Welfare Analysis for Discrete Choice

We consider empirical measurement of equivalent variation (EV) and compensating variation (CV) resulting from price change of a discrete good using individual‐level data when there is unobserved heterogeneity in preferences. We show that for binary and unordered multinomial choice, the marginal distributions of EV and CV can be expressed as simple closed‐form functionals of conditional choice probabilities under essentially unrestricted preference distributions. These results hold even when the distribution and dimension of unobserved heterogeneity are neither known nor identified, and utilities are neither quasilinear nor parametrically specified. The welfare distributions take simple forms that are easy to compute in applications. In particular, average EV for a price rise equals the change in average Marshallian consumer surplus and is smaller than average CV for a normal good. These nonparametric point‐identification results fail for ordered choice if the unit price is identical for all alternatives, thereby providing a connection to Hausman–Newey's (2014) partial identification results for the limiting case of continuous choice.     

Lead Time and Price Quotation Mode Selection: Uniform or Differentiated?

Firms in service and make‐to‐order manufacturing industries often quote lead times and prices to customers. We define uniform quotation mode (UQM) as the strategy where a firm offers a single lead time and price quotation, and differentiated quotation mode (DQM) is where a firm offers a menu of lead times and prices for customers to choose from. Both modes are followed in practice. Firms should determine which is more profitable. We classify customers into two groups: lead time sensitive (LS) and price sensitive (PS). LS customers value lead time reduction more than PS customers. We develop mathematical models of both quotation modes and analyze them to determine the most profitable mode under specified situations as well as the best lead time and price quotations within each mode. We find that DQM is dominated by UQM whenever PS customers have positive utilities from UQM or LS customers have positive utilities from DQM. Otherwise, which quotation mode is better depends on multiple factors, such as customer characteristics (including lead time reduction valuation and product valuation of a customer, and the proportion of LS customers) and production characteristics (including the desired service level and service or production cost).     

Panel Data Discrete Choice Models with Lagged Dependent Variables

In this paper, we consider identification and estimation in panel data discrete choice models when the explanatory variable set includes strictly exogenous variables, lags of the endogenous dependent variable as well as unobservable individual‐specific effects. For the binary logit model with the dependent variable lagged only once, Chamberlain (1993) gave conditions under which the model is not identified. We present a stronger set of conditions under which the parameters of the model are identified. The identification result suggests estimators of the model, and we show that these are consistent and asymptotically normal, although their rate of convergence is slower than the inverse of the square root of the sample size. We also consider identification in the semiparametric case where the logit assumption is relaxed. We propose an estimator in the spirit of the conditional maximum score estimator (Manski (1987)) and we show that it is consistent. In addition, we discuss an extension of the identification result to multinomial discrete choice models, and to the case where the dependent variable is lagged twice. Finally, we present some Monte Carlo evidence on the small sample performance of the proposed estimators for the binary response model.     

A comparison of approaches to exploit budget allocation data in cross-sectional maximum likelihood estimation of multi-attribute choice models

In this paper, four calibration approaches to exploit budget allocation data in maximum likelihood estimation of multi-attribute choice models are proposed. They differ on the implicit meaning of the dependent variable: (A) share of consumers according to the preferred alternative; (B) share of sales; (C) average share of consumer's budget; and (D) share of sales according to the preferred alternative. Differences between them can be conceived as depending on two circumstances: customer loyalty and customer selectivity. These are tested in the context of spatial consumer behavior, market response to hypermarket chains being represented as a function of their location strategies. Results show that different nuances on the definition of the dependent variable lead to slightly different relationships with the explanatory variables and to different predictive capabilities.     

LINEAR VS. NON–LINEAR MODELS OF THE FORMATION OF AFFECTIVE REACTIONS: THE CASE OF JOB ENLARGEMENT

Numerous researchers have now considered the impact of task characteristics on employee responses. However, relatively little is known about how information regarding individual task dimensions is processed to arrive at an overall judgment. Most studies simply consider the role of individual job characteristics or arbitarily apply a particular combinatory model. In the rare instances where alternative models have been simultaneously considered, there has been some apparent confusion regarding the meaning of models and/or interpretation of findings. The current study explored alternative combinatory models of human evaluative judgments. Data on task dimensions and employee affective responses were collected from subjects in two samples, one in a manufacturing firm and one in a Division of Corrections. Task dimension scores were combined by use of compensatory, conjunctive, and disjunctive models. Multiple regression was used to examine relationships between resultant scores and various affective response indices. All three models exhibited generally significant predictive ability. The linear compensatory model was found to be as powerful a predictor of evaluative judgments as were non-linear alternatives. Implications of findings are presented.     

The Effect of Firm and Host Country Characteristics on the Choice of Entry Mode: Empirical Evidence from Spanish Firms

When investing abroad firms must choose betweengoing alone or with a partner – the so-calledownership structure decision. Additionally,firms can enter a new country by acquisitionsor by greenfield investments – the foreignestablishment mode decision. These twodecisions have traditionally been analyzedseparately in the literature on entry mode.What is more, this literature has much lessanalyzed hybrid entry modes, like partialacquisitions. The aim of this paper is toanalyze how the different factors analyzed inprior research influence the choice of entrymode when jointly taking into account fouralternative entry modes: greenfield whollyowned subsidiaries, greenfield joint ventures,full acquisitions and partial acquisitions. Theempirical analysis was carried out byestimating a multinomial logit model over asample of FDIs made by Spanish firms. Ourresults also contribute to the knowledge ofspecific patterns in the choice of entry modeby firms from late investor countries, likeSpain.     

Rational Inattention Dynamics: Inertia and Delay in Decision‐Making

We solve a general class of dynamic rational inattention problems in which an agent repeatedly acquires costly information about an evolving state and selects actions. The solution resembles the choice rule in a dynamic logit model, but it is biased toward an optimal default rule that is independent of the realized state. The model provides the same fit to choice data as dynamic logit, but, because of the bias, yields different counterfactual predictions. We apply the general solution to the study of (i) the status quo bias; (ii) inertia in actions leading to lagged adjustments to shocks; and (iii) the tradeoff between accuracy and delay in decision‐making.     

基于MNL选择模型的替代产品定价和库存决策研究

受现实中生产商和大型零售商不同契约关系的启发,本文以两个生产商和一个零售商组成的系统为对象,从顾客在两种替代性产品之间的选择行为出发,分别研究了零售商定价和生产商定价模式下的最优产品定价和库存决策。研究表明,在MNL选择模型下,零售商联合定价时应当选择使得产品单位利润相等的定价策略;生产商定价博弈中存在唯一的Nash均衡。数值实验分别考察了"生产商强势"和"零售商强势"两种情形下的最优决策和利润分配情况;实验结果能给相关企业的销售模式选择带来有益的管理启示。     

Social Security Wealth and Retirement Decisions in Italy

Abstract. This paper uses administrative data to study the retirement decisions of Italian private‐sector non‐agricultural employees during the period 1977–97. Our analysis tries to assess the importance of the financial incentives built into the social security system. The basic idea is very simple: at any given age, and based on the available information, workers compare the expected present value of two alternatives: retiring today or working one more year, and then choose the best one. A key role in this kind of comparisons is played by social security wealth, whose level and changes reflect the expectations about the profile of future earnings and the institutional features of the social security system. The various incentive measures that we consider differ in the precise weight given to the social security wealth that workers accrue as they continue to work. Our model does not provide a structural representation of the retirement process. A worker's decision is modeled here following a ‘quasi reduced‐form’ approach, with the incentive measures entering as predictors of the worker's choice in addition to standard variables. The estimated models are then used to predict retirement probabilities under alternative policies that change social security wealth and derived incentive measures.     

META-DESIGN CONSIDERATIONS IN DEVELOPING MODEL MANAGEMENT SYSTEMS*

This paper examines cognitive considerations in developing model management systems (MMSs). First, two approaches to MMS design are reviewed briefly: one based on database theory and one based on knowledge-representation techniques. Then three major cognitive issues—human limitations, information storage and retrieval, and problem-solving strategies—and their implications for MMS design are discussed. Evidence indicates that automatic modeling, which generates more complicated models by integrating existing models automatically, is a critical function of model management systems. In order to discuss issues pertinent to automatic modeling, a graph-based framework for integrating models is introduced. The framework captures some aspects of the processes by which human beings develop models as route selections on a network of all possible alternatives. Based on this framework, three issues are investigated: (1) What are proper criteria for evaluating a model formulated by an MMS? (2) If more than one criterion is chosen for evaluation, how can evaluations on each of the criteria be combined to get an overall evaluation of the model? (3) When should a model be evaluated? Finally, examples are presented to illustrate various modeling strategies.     

Understanding the Role of Individual Innovativeness in the Acceptance of IT‐Based Innovations: Comparative Analyses of Models and Measures*

As new technological innovations are rapidly introduced and changed, identifying an individual characteristic that has a persistent effect on the acceptance decisions across multiple technologies is of substantial value for the successful implementation of information systems. Augmenting prior work on individual innovativeness within the context of information technology, we developed a new measure of adopter category innovativeness (ACI) and compared its effectiveness with the existing measure of personal innovativeness in IT (PIIT). Further, we examined two alternative models in which the role of individual innovativeness was theorized differently—either as a moderator of the effects the perceived innovation characteristics of usefulness, ease of use, and compatibility have on future use intention (moderator model) or as a direct determinant of the innovation characteristics (direct determinant model). To ensure the generalizability of the study findings, two field studies (N= 634) were conducted, each of which examined the two models (moderator and direct determinant) and measured individual innovativeness using the two measures (ACI and PIIT). Study 1 surveyed the online buying practices of 412 individuals, and Study 2 surveyed personal digital assistant adoption of 222 healthcare professionals. Across the markedly different adoption contexts, the study results consistently show that individual innovativeness is a direct determinant of the innovation characteristics, and the two measures share many commonalities. The new measure offers some additional utilities not found in the PIIT measure by allowing individuals to be directly classified and mapped into adopter categories. Implications are drawn for future research and practice.     

Experience-weighted Attraction Learning in Normal Form Games

In ‘experience-weighted attraction’ (EWA) learning, strategies have attractions that reflect initial predispositions, are updated based on payoff experience, and determine choice probabilities according to some rule (e.g., logit). A key feature is a parameter δ that weights the strength of hypothetical reinforcement of strategies that were not chosen according to the payoff they would have yielded, relative to reinforcement of chosen strategies according to received payoffs. The other key features are two discount rates, φ and ρ, which separately discount previous attractions, and an experience weight. EWA includes reinforcement learning and weighted fictitious play (belief learning) as special cases, and hybridizes their key elements. When δ= 0 and ρ= 0, cumulative choice reinforcement results. When δ= 1 and ρ=φ, levels of reinforcement of strategies are exactly the same as expected payoffs given weighted fictitious play beliefs. Using three sets of experimental data, parameter estimates of the model were calibrated on part of the data and used to predict a holdout sample. Estimates of δ are generally around .50, φ around .8 − 1, and ρ varies from 0 to φ. Reinforcement and belief-learning special cases are generally rejected in favor of EWA, though belief models do better in some constant-sum games. EWA is able to combine the best features of previous approaches, allowing attractions to begin and grow flexibly as choice reinforcement does, but reinforcing unchosen strategies substantially as belief-based models implicitly do.     

MODEL UNCERTAINTY

We study decision problems in which consequences of the various alternative actions depend on states determined by a generative mechanism representing some natural or social phenomenon. Model uncertainty arises because decision makers may not know this mechanism. Two types of uncertainty result, a state uncertainty within models and a model uncertainty across them. We discuss some two‐stage static decision criteria proposed in the literature that address state uncertainty in the first stage and model uncertainty in the second (by considering subjective probabilities over models). We consider two approaches to the Ellsberg‐type phenomena characteristic of such decision problems: a Bayesian approach based on the distinction between subjective attitudes toward the two kinds of uncertainty; and a non‐Bayesian approach that permits multiple subjective probabilities. Several applications are used to illustrate concepts as they are introduced.     

Wavelet‐Based Testing for Serial Correlation of Unknown Form in Panel Models

Wavelet analysis is a new mathematical method developed as a unified field of science over the last decade or so. As a spatially adaptive analytic tool, wavelets are useful for capturing serial correlation where the spectrum has peaks or kinks, as can arise from persistent dependence, seasonality, and other kinds of periodicity. This paper proposes a new class of generally applicable wavelet‐based tests for serial correlation of unknown form in the estimated residuals of a panel regression model, where error components can be one‐way or two‐way, individual and time effects can be fixed or random, and regressors may contain lagged dependent variables or deterministic/stochastic trending variables. Our tests are applicable to unbalanced heterogenous panel data. They have a convenient null limit N(0,1) distribution. No formulation of an alternative model is required, and our tests are consistent against serial correlation of unknown form even in the presence of substantial inhomogeneity in serial correlation across individuals. This is in contrast to existing serial correlation tests for panel models, which ignore inhomogeneity in serial correlation across individuals by assuming a common alternative, and thus have no power against the alternatives where the average of serial correlations among individuals is close to zero. We propose and justify a data‐driven method to choose the smoothing parameter—the finest scale in wavelet spectral estimation, making the tests completely operational in practice. The data‐driven finest scale automatically converges to zero under the null hypothesis of no serial correlation and diverges to infinity as the sample size increases under the alternative, ensuring the consistency of our tests. Simulation shows that our tests perform well in small and finite samples relative to some existing tests.     

Applying Environmental Management Strategies to the Agricultural Sector: Louisiana's Model Sustainable Agricultural Complex

The Model Sustainable Agricultural Complex (MSAC) is a 600-acre farm south of Lafayette, Louisiana, operated by the Department of Renewable Resources at University of Louisiana. The Renewable Resources Department intends to overlay a priority commitment toward the advancement of agricultural sustainability in production, education, research, and demonstration activities. As we plan the Complex's longer-term future, we are drawing upon environmental business models such as Industrial Ecology, Environmental Total Quality Management, ISO 14001, and The Natural Step for guidance.This article compares the “outputs” of those models, asking the question: If we are running an integrated agricultural complex and we genuinely want to steer the complex toward sustainability, what do the different models tell us to do? The answers to this question are regionally important, because agriculture-as-usual in the Gulf Coast is both economically distressed and environmentally problematic. Big changes are both necessary and imminent, and the environmental business literature may well serve as a valuable source of guidance.     

AN EMPIRICAL EXAMINATION OF SOCIAL POWER IN TERMS OF DECISION THEORY1

The paper presents an extension of decision theory to the analysis of social power. The power of a person, A, over another person, B, is viewed in terms of the effect A has on B's decision. The analysis is based on the idea that B's decision regarding the performance of alternative behaviors is a function of 1) B's utility for the consequences of the behaviors and 2) B's subjective probabilities that the behaviors will lead to these consequences. In these terms, A's power over B lies in A's ability to mediate various consequences for B, contingent upon B's compliance or noncompliance. Subjects were asked to consider eight situations in which hypothetical individuals had to make a choice between two courses of action. In each situation another person (A) was attempting to induce the hypothetical individual (B) to choose one of the alternatives, while various situational factors were influencing B to choose the other alternative. The subjects were asked to consider B's utilities and subjective probabilities in each situation and to indicate whether or not B should comply with A and to make ratings of A's power. The decision theory analysis did well in predicting whether or not subjects would indicate that B should comply with A. Also, subjects generally were able to correctly specify whether A or the situational factors had more influence over B's decision. Finally, the subjects' ratings of A's power in the eight situations were highly related to the decision theoretic measure of power.