The effect of organizational culture on deviant behaviors in the workplace

Abstract

This study investigated the impact of organizational culture (OC) on deviant behaviors in the workplace (workplace deviant behaviors: WDB). We tested the hypothesis that different types of OC (according to the Competing Values Framework model) had an impact on WDB, in addition to the effect of Big Five personality traits. Survey research was undertaken with 954 employees of 30 enterprises in the public and private field, using a hierarchical model approach (HLM) to test the effects of four types of OC (Clan; Adhocracy; Market, Hierarchy) on WDB, over and above the effect of Five Personality traits. The HLM results partially supported our hypotheses, showing that the OC had a significant effect on WDB, with the adhocracy and clan cultures characterized by lower levels of WDB. Managerial implications about the importance of managing the OC are discussed.     

Fitting dynamic factor models to non-stationary time series

Factor modelling of a large time series panel has widely proven useful to reduce its cross-sectional dimensionality. This is done by explaining common co-movements in the panel through the existence of a small number of common components, up to some idiosyncratic behaviour of each individual series. To capture serial correlation in the common components, a dynamic structure is used as in traditional (uni- or multivariate) time series analysis of second order structure, i.e. allowing for infinite-length filtering of the factors via dynamic loadings. In this paper, motivated from economic data observed over long time periods which show smooth transitions over time in their covariance structure, we allow the dynamic structure of the factor model to be non-stationary over time by proposing a deterministic time variation of its loadings. In this respect we generalize the existing recent work on static factor models with time-varying loadings as well as the classical, i.e. stationary, dynamic approximate factor model. Motivated from the stationary case, we estimate the common components of our dynamic factor model by the eigenvectors of a consistent estimator of the now time-varying spectral density matrix of the underlying data-generating process. This can be seen as a time-varying principal components approach in the frequency domain. We derive consistency of this estimator in a “double-asymptotic” framework of both cross-section and time dimension tending to infinity. The performance of the estimators is illustrated by a simulation study and an application to a macroeconomic data set.     

Determinants of the Effective Real Exchange Rate of the Synthetic Euro: Alternative Methodological Approaches

On the basis of historical data aggregated over the period 1973 to 2000, we have experimented with four different approaches to estimate the synthetic euro's equilibrium exchange rate. Using a number of competing models with the same data set, variable definitions and sample period offers the possibility to assess the uncertainty surrounding such equilibrium levels, both from an empirical (different estimates) and a theoretical viewpoint (different specifications). In this exercise, the 'Rest of the World' is proxied by the US, the UK, Japan and Switzerland, aggregated on the basis of trade weights.
We employed reduced form co–integration models, a structural VAR, a NATREX model (estimated in structural form) and the ECB's small–sized euro area wide macro–econometric model. In this order the approaches feature an increasing degree of 'structure', in the sense of the constraints based on economic theory embedded in the econometric models that were estimated. The results confirm the high likelihood for the euro having been undervalued in Q4 2000, while stressing the significant empirical and theoretical uncertainty with respect to the equilibrium exchange rate level.     

Sharp IV Bounds on Average Treatment Effects on the Treated and Other Populations Under Endogeneity and Noncompliance

In the presence of an endogenous binary treatment and a valid binary instrument, causal effects are point identified only for the subpopulation of compliers, given that the treatment is monotone in the instrument. With the exception of the entire population, causal inference for further subpopulations has been widely ignored in econometrics. We invoke treatment monotonicity and/or dominance assumptions to derive sharp bounds on the average treatment effects on the treated, as well as on other groups. Furthermore, we use our methods to assess the educational impact of a school voucher program in Colombia and discuss testable implications of our assumptions. Copyright © 2015 John Wiley & Sons, Ltd.     

THE GINI CONCENTRATION INDEX: A REVIEW OF THE INFERENCE LITERATURE

More than a century ago, Corrado Gini proposed his well-known concentration index for measuring the degree of inequality in the distribution of income and wealth. His index is still extremely relevant and widely used in several fields of research and application. In this paper, we focus on the inferential properties of the Gini index, and discuss the main directions of analysis proposed in the literature. The aim of the paper is to provide a comprehensive review of the main developments on the inferential aspects of the Gini concentration ratio. We feel that this work can provide a valuable contribution to those scholars who are approaching the large amount of literature on the inferential properties of the Gini index.     

Foreign ownership and the credibility of national rating agencies: Evidence from Korea

By analyzing bond price reactions to rating changes in Korea, this study adds a new angle to the existing literature on Global Rating Agencies (GRAs, i.e. Moody’s, S&P’s, Fitch) with higher reputation/independence vs. National Rating Agencies (NRAs) with more in-depth local knowledge. Faced with substantial regulatory burdens, GRAs have chosen to operate indirectly in the Korean domestic market by acquiring local NRAs. In our event study, cumulative abnormal returns following downgrades by a wholly domestically owned NRA tend to dominate those from downgrades by two affiliates of GRAs. This casts doubt on the additional information value of reputation capital acquired through GRA ownership as perceived by emerging markets.     

The power of dimensional analysis in production systems design

Dimensional Analysis (DA) is a well-known methodology in physics, chemistry and other traditional engineering areas. In its simplest form, DA is used to check the meaningfulness of a set of equations (dimensional homogeneity). In the last century, the dimensional theory has been profoundly investigated: its highest achievement is the Buckingham theorem (or pi-theorem), which states that any equation modelling a physical problem can be rearranged in terms of dimensionless ratios, thus saving variables to be handled, and especially enriching the inner physical knowledge of the studied phenomenon.In this paper we investigate how DA can be applied to Operations Management (OM) topics and which benefits it can bring to researchers in this area. A literature review is performed to clarify the main operative issues regarding DA application (assumptions and limitations); then existing applications of DA to OM are explored, pointing out that few researchers have tried to apply this methodology in the OM research field.Stemming from this analysis, we applied the pi-theorem to the design of a Flexible Manufacturing System. A complex problem, requiring 13 dimensional quantities to be expressed, is first studied via simulation; then DA is applied, reducing the number of variables to 9 dimensionless ratios. The reduced problem has a suitable size to be analytically explored and a regression model is formulated which, compared with the simulation study, offers the same precision in analysing the FMS behaviour, being more compact and powerful. This application shows the potential of DA in OM research, and will hopefully draw the attention of researches to this powerful, but unfamiliar and therefore neglected, methodology.     

An agent-based model of innovation diffusion: network structure and coexistence under different information regimes

The paper analyzes how the structure of social networks affects innovation diffusion and competition under different information regimes. Diffusion is modeled as the result of idiosyncratic adoption thresholds, local network effects and information diffusion (broadcasting and demonstration effect from previous adopters). A high social cohesion decreases the probability of one innovation cornering the market. Nonetheless, with imperfect information, in small-world networks the higher speed of diffusion produced by the low average distance increases this probability. A low social cohesion also increases the probability of falling into traps of under-adoption. However, such probability is significantly lower with imperfect information, because such regime is characterized by higher levels of market concentrations and this reduces the frictions due to the coexistence of non-compatible product innovations.     

Non-market valuation of forest goods and services: Good practice guidelines

The European COST Action E45 on European Forest Externalities (EUROFOREX) participants developed a set of good practice guidelines for the non-market valuation of forests, elaborating on stated and revealed preference methodologies, as well as benefit transfer and meta-analytical procedures. This article presents a summary of the guidelines.