股权激励与企业绩效关系多样性的原因分析——基于系统动力学的视角

基于系统动力学理论,分析了股权激励系统动力学特征,对导致股权激励与企业绩效关系多样性的原因进行了探究。研究结果表明:以往的研究忽略了与股权激励相关的软变量;忽略了股权激励作用的延迟效应;忽略了股权激励系统中起主导作用回路的转移。并针对原因提出了一些建议和启示。     

Nonparametric Dynamic Production Analysis and the Theory of Cost

While the dynamic theory of production provides little insight towards identifying a specific functional form for the firm's technology, dynamic production analysis has been explored traditionally in a parametric framework. A nonparametric dynamic dual cost approach to production analysis is developed in this article. Recovering technological information from intertemporal cost minimizing behavior is possible without imposing a parametric functional form on the firm's technology. Nonparametric tests to analyze the structure of a dynamic technology are presented from a dynamic cost minimizing perspective. The empirical implementation of these tests is illustrated for a balanced panel data set of Pennsylvania dairy operators during the time period 1986–1992.     

An expectancy-equity model of productive system performance

Although numerous behavioral variables (e.g., personality traits, incentives, nature of supervision) have documented relationships with quantity and quality of output, i.e., performance, in production systems, existing production and operations management models are dominated by technological variables. The article addresses three questions: 1. Which technological and behavioral variables influence productive system performance? 2. How do behavioral and technological variables interact? 3. Which variables are most important under different circumstances in determining performance?An expectancy-equity model, patterned on research by Lawler [22], presents proposed relationships among variables in production systems, which are classified along a continuum from high to low process predictability. Predominant determinants of performance in various types of systems (e.g., continuous process, job shop, R&D project) are considered in light of the model. Implications for designers and analysts of productive systems and for future research are discussed.     

A new criterion for technical efficiency measures: non‐monotonicity across dimensions axioms

Based on non‐parametric deterministic production technologies radial and non‐radial measures of technical efficiency are evaluated using properties guaranteeing insensitivity to the dimensionality of technology. These new axioms are important in empirical research and may especially prevent manipulation of results when implementing these benchmark methodologies in private or public organizations. An empirical example illustrates to which extent a series of radial and non‐radial technical efficiency measures satisfies the proposed axioms. Copyright © 1999 John Wiley & Sons, Ltd.     

On the Functional Form of an Efficiency Index

An input efficiency index gives a numeric assessment of the degree to which a given input combination falls short of being efficient in producing a fixed amount of output. This paper presents a system of axioms which characterise a certain family of efficiency indices containing the well-known Farrell and Färe-Lovell indices. The family of indices satisfying the axioms can be obtained by minimizing a suitable function, called a performance evaluation, and different choices of performance evaluation will result in different indices.     

Sparse Partial Least Squares in Time Series for Macroeconomic Forecasting

Factor models have been applied extensively for forecasting when high‐dimensional datasets are available. In this case, the number of variables can be very large. For instance, usual dynamic factor models in central banks handle over 100 variables. However, there is a growing body of literature indicating that more variables do not necessarily lead to estimated factors with lower uncertainty or better forecasting results. This paper investigates the usefulness of partial least squares techniques that take into account the variable to be forecast when reducing the dimension of the problem from a large number of variables to a smaller number of factors. We propose different approaches of dynamic sparse partial least squares as a means of improving forecast efficiency by simultaneously taking into account the variable forecast while forming an informative subset of predictors, instead of using all the available ones to extract the factors. We use the well‐known Stock and Watson database to check the forecasting performance of our approach. The proposed dynamic sparse models show good performance in improving efficiency compared to widely used factor methods in macroeconomic forecasting. Copyright © 2014 John Wiley & Sons, Ltd.     

How to share when context matters: The Möbius value as a generalized solution for cooperative games

All quasivalues rest on a set of three basic axioms (efficiency, null player, and additivity), which are augmented with positivity for random order values, and with positivity and partnership for weighted values. We introduce the concept of Möbius value associated with a sharing system and show that this value is characterized by the above three axioms. We then establish that (i) a Möbius value is a random order value if and only if the sharing system is stochastically rationalizable and (ii) a Möbius value is a weighted value if and only if the sharing system satisfies the Luce choice axiom.     

Canadian Input–Output-based Multi-factor Productivity Accounts

Statistics Canada's multi-factor productivity accounts are integrated into the Canadian system of national accounts. The company's originality rests, in part, on the application of the standard productivity formula to alternative but related sets of outputs and inputs in a bottom-up approach that covers the whole business sector. The concept of vertical integration plays a central role in establishing relationships between alternative indices, including the relationships between static and dynamic indices. In the static framework, the stock of capital is exogenous. In the dynamic framework, capital goods become endogenous produced inputs. Establishments are seen as exchanging capital services across time periods. Time becomes a primary input of production, the productivity of which is associated with technical knowledge. A new measure of capital services and an extended definition of economic efficiency are finally introduced, which solve some paradoxical results that are obtained with the conentional measure.     

动态车辆调度管理系统的设计与实现

动态车辆调度管理系统充分利用计算机的大容量存储,高性能处理,高度安全可靠,高清晰的可视化数据等优势来辅助实现对车辆的管理,本系统的开发应用实现了计算机资源的合理利用,真正达到了减少本单位劳动强度与提高劳动效率的目的。     

The economic meaning of Data Envelopment Analysis: A ‘behavioral’ perspective

We reconsider the motivation of Data Envelopment Analysis (DEA), the non-parametric technique that is widely employed for analyzing productive efficiency in academia, the private sector and the public sector. We first argue that the conventional engineering motivation of DEA can be problematic since it often builds on unverifiable production axioms. We then provide a dual viewpoint and highlight the ‘behavioral’ interpretation of DEA models. We start from a specification of the production objectives while imposing minimal structure on the production possibilities, and construct tools to meaningfully quantify deviations of observed producer behavior from optimizing behavior. This brings to light the economic meaning of DEA, provides guidelines for selecting the appropriate model in practical research settings, and prepares the ground for instituting new DEA models. We also provide an empirical application that demonstrates the practical relevance of our arguments. We hope that our insights will contribute to the further dissemination of DEA, and stimulate public sector applications of DEA that build on its behavioral interpretation.     

动态联盟中防范道德风险的激励模型

本文论述了动态联盟中存在的道德风险问题,介绍了防范道德风险的Tirole模型,并通过在动态联盟中引入第三方系统,建立了一个委托—代理分析框架下的不完全信息动态博弈模型;指出盟员的收入与动态联盟利润具有动态一致性,可以通过由第三方系统(外部委托人)设计一种激励与监督并行的分配政策,来防范道德风险。最后,阐述了动态联盟运作过程中第三方系统的构成。     

中国工业生产效率的区域差异及格局演化

基于2004—2017年省级面板数据,采用SE-SBM模型对中国工业生产效率进行测度,利用Dagum基尼系数对中国工业生产效率的地区差异进行研究,运用Kernel核密度估计和速度激励模型揭示中国工业生产效率的动态格局演化特征.研究发现:中国多数省市区工业生产效率呈上升之势,区域整体差异呈现出波动且下降的趋势,西部地区工...     

Antecedents of well-being: a study to examine the extent to which personality and emotional intelligence contribute to well-being

In the debate surrounding the relationships between HRM and performance, there is an argument suggesting that a focus on understanding the role of employee attitudes and behaviours may elicit valuable insights into performance drivers. In examining individual behaviour and performance links, there is evidence that well-being plays a significant role. Other notable performance antecedents are personality and emotional intelligence (EI). This paper explores the relationships between these variables and reports the findings from a study of 156 managers. Results show relationships between well-being and EI as well as with personality, although EI explained variance beyond personality dimensions. The implications for HR of these findings are discussed.     

Residual‐based IV estimation of dynamic panel data models with fixed effects

In dynamic panel regression, when the variance ratio of individual effects to disturbance is large, the system‐GMM estimator will have large asymptotic variance and poor finite sample performance. To deal with this variance ratio problem, we propose a residual‐based instrumental variables (RIV) estimator, which uses the residual from regressing Δy_i,t?1 on as the instrument for the level equation. The RIV estimator proposed is consistent and asymptotically normal under general assumptions. More importantly, its asymptotic variance is almost unaffected by the variance ratio of individual effects to disturbance. Monte Carlo simulations show that the RIV estimator has better finite sample performance compared to alternative estimators. The RIV estimator generates less finite sample bias than difference‐GMM, system‐GMM, collapsing‐GMM and Level‐IV estimators in most cases. Under RIV estimation, the variance ratio problem is well controlled, and the empirical distribution of its t‐statistic is similar to the standard normal distribution for moderate sample sizes.     

A decision support system to improve the efficiency of resource allocation in healthcare management

Limitations in healthcare funding require hospitals to find more effective ways to utilize resources. An effective patient management system is critically dependent on the accurate analysis of individual patient outcomes and resource utilization. In the current paper, a management-oriented decision support model is thus proposed to assist health system managers in improving the efficiency of their systems. In the first stage of the model, the key variables affecting system efficiency, as well as their causal relationships, are identified through causal maps. Efficiency is measured by the total time spent in the system. In the second stage, a Bayesian Belief Network (BBN) is employed to represent both the conditional dependencies and uncertainties of the key variables. In the third stage, a sensitivity analysis is performed using a BBN to determine the most critical variable(s) in terms of impact on the system. Finally, strategies to improve system efficiency are proposed. The suggested decision support system is applied to the tomography section in the radiology department of a private hospital in Turkey.     

Econometric estimation of distance functions and associated measures of productivity and efficiency change

Multi-input multi-output production technologies can be represented using distance functions. Econometric estimation of these functions typically involves factoring out one of the outputs or inputs and estimating the resulting equation using maximum likelihood methods. A problem with this approach is that the outputs or inputs that are not factored out may be correlated with the composite error term. Fernandez et al. (J Econ 98:47–79, 2000) show how to solve this so-called ‘endogeneity problem’ using Bayesian methods. In this paper I use the approach to estimate an output distance function and an associated index of total factor productivity (TFP) change. The TFP index is a new index that satisfies most, if not all, economically-relevant axioms from index number theory. It can also be exhaustively decomposed into a measure of technical change and various measures of efficiency change. I illustrate the methodology using state-level data on U.S. agricultural input and output quantities (no prices are needed). Results are summarized in terms of the characteristics (e.g., means) of estimated probability density functions for measures of TFP change, technical change and efficiency change.     

The school as a social system: Indicators for change

In systems analysis, the school may be viewed as a functionally differentiated subsystem of the broader social system in which it is embedded. To maintain a viable relationship with that social system, the school is subject to continual changes to meet the shifting social, economic, political, and technological forces in its environment. However, the more successful the school organization is in assessing accurately changing environmental forces, and in making appropriate adjustments to those forces, the more successful will it be in resisting temporary pressures and transitory movements and in controlling its own directions.

A major research problem is to identify those organizational properties that enable the school to assess accurately new demands and to adjust appropriately to those demands. Theoretically, those properties might be expected to include: (1) operationalized statements of instrumental goals; (2) a work structure that involves interdependence in task performance; (3) participation in decision making; (4) an incentive system that utilizes performance criteria rather than expressive relationships; (5) personnel practices that encourage a cosmopolitan orientation; and (6) institutionalized provisions for change advocacy.

The specification of the relationships among these properties, or variables, and the determination of means for assessing them quantitatively, are tasks that remain to be accomplished.     

Endogenous network efficiency,macroeconomy, and competition: Evidence from the Portuguese banking industry

Although performance analysis has become a vital part of the banking industry, research on the efficiency of Portuguese banking remains scarce and focused on discussing rankings to the detriment of unveiling its productive structure relative to its competition. This issue is of utmost importance considering the relevant transformations in the Portuguese economy over the last ten years. In this study, we developed a network productive structure comprising two paradigms (the production and intermediation approaches, respectively) to assess how market competition and other macro-economic variables impact bank efficiency and their feedback effects in Portugal. Unlike previous research, an integrated multi-layer perceptron (MLP)/hidden Markov model (HMM) was used for the first time to unveil endogeneity among banking competition, macro-economic variables, and the efficiency levels of the production and intermediation approaches in banking. The findings illustrate the pattern of interaction among these variables and verify that the production efficiency is the cornerstone of endogeneity in Portuguese banks. Policy makers will find the results helpful.     

Smooth-transition error-correction in exchange rates

Recent research has increasingly suggested that exchange rates may be characterized by non-linear behavior. This paper examines whether such non-linear behavior is evident, not in rates themselves, but in the adjustment of rates back to fundamental equilibrium. Thus, we examine whether a series of four spot and forward exchange rates exhibit smooth transition non-linear error-correction dynamic behavior. Our results are supportive of this model, particularly in-sample, and suggest some salient differences in the mean-reverting behavior of spot and forward rates, which may be of use to policy authorities and model builders. However, out-of-sample forecast errors between the two models appear insignificantly different from each other.     

A graphically based machine learning approach to predict secondary schools performance in Tunisia

The main purpose of this paper is to identify the key factors that impact schools' academic performance and to explore their relationships through a two-stage analysis based on a sample of Tunisian secondary schools. In the first stage, we use the Directional Distance Function approach (DDF) to deal with undesirable outputs. The DDF is estimated using Data Envelopment Analysis method (DEA). In the second stage we apply machine-learning approaches (regression trees and random forests) to identify and visualize variables that are associated with a high school performance. The data is extracted from the Program for International Student Assessment (PISA) 2012 survey. The first stage analysis shows that almost 22% of Tunisian schools are efficient and that they could improve their students’ educational performance by 15.6% while using the same level of resources. Regression trees findings indicate that the most important factors associated with higher performance are school size, competition, class size, parental pressure and proportion of girls. Only, school location appears with no impact on school efficiency. Random forests algorithm outcomes display that proportion of girls at school and school size have the most powerful impact on the predictive accuracy of our model and hence could more influence school efficiency. The findings disclose also the high non-linearity of the relationships between these key factors and school performance and reveal the importance of modeling their interactions in influencing efficiency scores.