Small‐scale Inference: Empirical Bayes and Confidence Methods for as Few as a Single Comparison

Empirical Bayes methods of estimating the local false discovery rate (LFDR) by maximum likelihood estimation (MLE), originally developed for large numbers of comparisons, are applied to a single comparison. Specifically, when assuming a lower bound on the mixing proportion of true null hypotheses, the LFDR MLE can yield reliable hypothesis tests and confidence intervals given as few as one comparison. Simulations indicate that constrained LFDR MLEs perform markedly better than conventional methods, both in testing and in confidence intervals, for high values of the mixing proportion, but not for low values. (A decision‐theoretic interpretation of the confidence distribution made those comparisons possible.) In conclusion, the constrained LFDR estimators and the resulting effect‐size interval estimates are not only effective multiple comparison procedures but also they might replace p‐values and confidence intervals more generally. The new methodology is illustrated with the analysis of proteomics data.     

Group decision-making: Head-count versus intensity of preference

This paper puts forth a framework for reshaping the group decision-making process. The proposed framework extends from the usual one-issue-at-a-time decision-making to one that involves several related issues simultaneously. Weaknesses of the traditional majority voting mechanism are first identified, and then a different voting method that takes each individual voter's sentiment into account is discussed. Specifically, a decision-maker is asked to express his/her intensity of preference for the issues encountered. Three hierarchical structures—benefits, costs, and risks—are developed to evaluate the alternatives. Due to the nature of pairwise comparisons and synthesis, the proposed method is amenable to consensus building and has higher reliability and consistency. It can be used for candidate selection, e.g. governmental election, when a large population is involved. It is also effective for resource allocation and prioritization when a small group or business is concerned. We believe the proposed approach has potential for resolving deficiencies of the conventional voting mechanism, and can be applied to many real-world problems. Its implementation on the Internet is also discussed.     

Entry‐Timing Advantages in Renewable Natural Resources Industries

In this paper, we explore the conditions of entry‐timing advantages in renewable natural resource industries. Drawing from behavioural theory of the firm, we classify firms in two groups depending on the different heuristics used to make entry decisions when facing the cyclical endogenous nature of these industries: crowd firms are procyclical, making decisions based on the current phase of the industry cycle, whereas anti‐crowd firms follow a countercyclical strategy, making uncertain, and risky decisions by estimation of the next phase of the cycle. Therefore, anti‐crowd firms anticipate the deployment of resources each cycle, potentially gaining entry‐timing advantages beyond those provided by traditional competitive isolating mechanisms. Through a mathematical simulation of a performance feedback model, we reveal that the entry‐timing advantage of the anti‐crowd group becomes possible when the rivalry in the industry and the price sensitivity of competitors are high, and when the time required to deploy the resources is short.     

Options‐based HRM,intellectual capital,and exploratory and exploitative learning in law firms' practice groups

The current study intends to uncover the strategic contribution of human resource management by introducing a unique construct of options‐based (vis‐à‐vis project‐based) HRM and examining its links to intellectual capital and exploratory and exploitative learning in the context of law firms' practice groups. Empirical results show that options‐based HRM is positively related to the practice group's explorative and exploitative learning. The intellectual capital mediates the relationships between options‐based HRM and the practice group's learning for exploration and exploitation. This study makes a valuable contribution to the HRM literature by establishing the mechanisms by which HRM enables organizational learning and extending the scope of HRM research to professional service firms. Our findings also provide valuable implications for the literature of organizational learning. © 2012 Wiley Periodicals, Inc.     

Measurement error in discrete health facility choice models: An example from urban Senegal

We use individual‐level health facility choice data from urban Senegal to estimate consumer preferences for facility characteristics related to maternal health services. We find that consumers consider a large number of quality‐related facility characteristics, as well as travel costs, when making their health facility choice. In contrast to the typical assumption in the literature, our findings indicate that individuals frequently bypass the facility nearest their home. In light of this, we show that the mismeasured data used commonly in the literature produces biased preference estimates; most notably, the literature likely overestimates consumer distaste for travel.     

Hospital competition under pay‐for‐performance: Quality,mortality, and readmissions

Health outcomes, such as mortality and readmission rates, are commonly used as indicators of hospital quality and as a basis to design pay‐for‐performance (P4P) incentive schemes. We propose a model of hospital behavior under P4P where patients differ in severity and can choose hospital based on quality. We assume that risk‐adjustment is not fully accounted for and that unobserved dimensions of severity remain. We show that the introduction of P4P which rewards lower mortality and/or readmission rates can weaken or strengthen hospitals' incentive to provide quality. Since patients with higher severity have a different probability of exercising patient choice when quality varies, this introduces a selection bias (patient composition effect) which in turn alters quality incentives. We also show that this composition effect increases with the degree of competition. Critically, readmission rates suffer from one additional source of selection bias through mortality rates since quality affects the distribution of survived patients. This implies that the scope for counterproductive effects of P4P is larger when financial rewards are linked to readmission rates rather than mortality rates.     

A generalized correlated binomial distribution with application in multiple testing problems

A typical microarray experiment often involves comparisons of hundreds or thousands of genes. Since a large number of genes are compared, simple use of a significance test without adjustment for multiple comparison artifacts could lead to a large chance of false positive findings. In this context, Tsai et al. (Biometrics 59:1071–1081, 2003) have presented a model that studies the overall error rate when testing multiple hypotheses. This model involves the distribution of the sum of non-independent Bernoulli trials and this distribution is approximated by using a beta-binomial structure. Instead of using a beta-binomial model, in this paper, we derive the exact distribution of the sum of non-independent and non-identically distributed Bernoulli random variables. The distribution obtained is used to compute the conditional false discovery rates and the results are compared to those obtained, in Table 3, by Tsai et al. (Biometrics 59:1071–1081, 2003).     

On aggregation and welfare analysis

In this article, the beginnings of a new approach to the theory of aggregation are developed. The basic idea is that aggregation should involve two things: (a) data over which social preferences are defined should be mapped into a smaller-dimensional space, and (b) there should exist an ordering on that lower-dimensional space such that an improvement in this criterion implies an improvement for any of a class of social preference functions and of a class of individual preference relations defined over the original space. Results are developed which show that this conception of aggregation can yield meaningful results; particularly with respect to comparisons of ‘real national income’ in two situations, for a given economy.     

The Financing of Investment in Utility Assets

This article concerns appropriate ways to finance investment in quasi‐public assets, such as those of utilities. Pursuing the principle of charging the user, analogies are drawn with not‐for‐profit investment, dedicated to the service of users. Focusing on intergenerational equity, an arguably typical pattern of intergenerational investment transactions is identified and proposed as a financing norm. It is shown that, while an investing generation will always experience a real resource cost, the burden can be alleviated in welfare terms if all new investment is financed by borrowing. Charges or taxes levied for maintenance and replacement of assets offer scope for improving the intergenerational welfare balance.     

Which Resources Matter How and Where? A Meta‐Analysis on Firms’ Foreign Establishment Mode Choice

Firm resources play an important role in explaining the foreign establishment mode choice. However, a theoretical framework that simultaneously a) differentiates between heterogeneous types of resources, b) provides a rationale that consistently explains how firms adapt their establishment mode choice to their resource base, and c) reflects on contextual factors that intervene in the consistency of the direct relationships is largely missing. The present paper draws on the resource‐based view (RBV) to develop such a framework. More specifically, we study the effect of knowledge‐based and experience‐based resources on a firm's establishment mode choice and the moderating impact of cultural distance on these relationships. We validate our theoretical framework by a meta‐analysis (integrating 31 studies with 13,559 establishment mode choices) and find that knowledge‐based resources enhance a firm's propensity for greenfield investments, while experience‐based resources more likely lead to acquisitions. Further, cultural distance increases knowledge‐intensive firms’ preference for greenfield investments.     

Differentiated‐product distribution in a dual‐channel supply chain

This study presents a theoretical framework to explore the mechanism of firms' preference for different distribution strategies. The results indicate that the manufacturer, retailer, and e‐tailer would prefer the distribution strategy of selling low‐end and high‐end products through offline and online channels, respectively, when consumers are minimally sensitive to the product‐quality differentiation. By contrast, supply‐chain firms would prefer the distribution strategy of selling high‐end and low‐end products through offline and online channels when consumers are significantly sensitive to the product‐quality differentiation. Firms demonstrate different preferences for distribution strategy when consumers are moderately sensitive to product‐quality differentiation.     

Evaluation and Selection of Sustainable Strategy for Green Supply Chain Management Implementation

The aim of this study is to explore the implementation of green supply chain management (GSCM) strategies and to select the best GSCM strategy using fuzzy analytical network process (ANP) methodology. The ANP helps in analyzing the interdependence and interrelations among the various determinants and dimensions of GSCM strategy selection. Fuzzy set theory is applied to avoid the vagueness and uncertainty in human preference judgement. This study uses an empirical case study of an Indian automobile organization to validate the applicability of the proposed model. The results show that the resource based strategy is in first position, having the maximum impact on each determinant. The case organization should improve the green management system with the assistance of a suitable GSCM strategy, i.e. the resource based strategy. This study may help managers to make decisions, and to analyze and standardize their environmental advantages dynamically. The robustness of the projected model is checked by conducting a sensitivity analysis. Copyright © 2018 John Wiley & Sons, Ltd and ERP Environment     

Analysis of the front‐end loading of Alberta mega oil sands projects

Recent large capital oil sands construction projects have all experienced significant cost overruns. There are a number of reasons for these overruns, some of which are listed in this article. This article provides a review of recent experiences and challenges in delivering mega oil sands projects in Alberta. In addition, this article focuses on the front‐end loading (planning) phases 1, 2, and 3 and describes the effort needed to deliver mega projects, provides schedule comparisons of key engineering milestones, and analyzes scope changes and contingencies.     

Time Use,Exploitation, and the Dual‐Career Household: Competing Perspectives

This article evaluates Laibman's reformulation of Marxian exploitation theory, and compares it to two preference‐based analyses of household time use (advanced by Becker and Hakim). Using a quantitative Marxist approach, and the British Household Panel Survey (BHPS), we show profound dissatisfaction with working hours for members of dual‐career households, and inequality, by gender, vis‐à‐vis pure consumption time. The results support exploitation‐based theories of the household, and cast doubt on such preference‐based theories of time use.     

IT Contract Flexibility and Negotiator Incentives

Information Technology outsourcing contracts are plagued by inflexibility. We develop an economic model to explain how the contract negotiator's incentives influence contract flexibility. We show that neither wage nor one‐time commission type pay gives any preference for flexibility. However, a promotion incentive, where the bonus is an ongoing bonus, does give the negotiator a preference for less flexible contracts. The preference for less flexible contracts increases as the discount rate increases. The preference for less flexible contracts increases as the number of competitors for the promotion increases. Copyright © 2015 John Wiley & Sons, Ltd.     

Privacy Regulation and Market Structure

This paper models how regulatory attempts to protect the privacy of consumers' data affect the competitive structure of data‐intensive industries. Our results suggest that the commonly used consent‐based approach may disproportionately benefit firms that offer a larger scope of services. Therefore, though privacy regulation imposes costs on all firms, it is small firms and new firms that are most adversely affected. We then show that this negative effect will be particularly severe for goods where the price mechanism does not mediate the effect, such as the advertising‐supported Internet.     

TACKLING FALSE POSITIVES IN BUSINESS RESEARCH: A STATISTICAL TOOLBOX WITH APPLICATIONS

Serious concerns have been raised that false positive findings are widespread in empirical research in business disciplines. This is largely because researchers almost exclusively adopt the ‘p‐value less than 0.05’ criterion for statistical significance; and they are often not fully aware of large‐sample biases which can potentially mislead their research outcomes. This paper proposes that a statistical toolbox (rather than a single hammer) be used in empirical research, which offers researchers a range of statistical instruments, including a range of alternatives to the p‐value criterion such as the Bayesian methods, optimal significance level, sample size selection, equivalence testing and exploratory data analyses. It is found that the positive results obtained under the p‐value criterion cannot stand, when the toolbox is applied to three notable studies in finance.     

Forecast Encompassing and Parameter Estimation*

A desirable property of a forecast is that it encompasses competing predictions, in the sense that the accuracy of the preferred forecast cannot be improved through linear combination with a rival prediction. In this paper, we investigate the impact of the uncertainty associated with estimating model parameters in‐sample on the encompassing properties of out‐of‐sample forecasts. Specifically, using examples of non‐nested econometric models, we show that forecasts from the true (but estimated) data generating process (DGP) do not encompass forecasts from competing mis‐specified models in general, particularly when the number of in‐sample observations is small. Following this result, we also examine the scope for achieving gains in accuracy by combining the forecasts from the DGP and mis‐specified models.