Social Identity and Social Exchange: Identification, Support, and Withdrawal from the Job

Integrating insights from the social exchange perspective and the social identity perspective on the psychological relationship between the individual and the organization, we propose that evaluations of the support received from the organization and its representatives, and organizational identification interact in predicting withdrawal from the job. Specifically, the relationship of support with withdrawal is proposed to be weaker the stronger employees identify with the organization. This prediction was confirmed in two samples focusing on different operationalizations of support and withdrawal. Sample 1 concerned the interaction of organizational support and organizational identification in predicting turnover intentions, Sample 2 concerned the prediction of absenteeism from supervisor support and organizational identification. We conclude that the present study yields promising first evidence that may lay the basis for further integration of social exchange and social identity analyses of organizational behavior.Organizational behavior;Organizational identification;Organizational support;Social identity

Semiparametric analysis to estimate the deal effect curve

The marketing literature suggests several phenomena that may contribute to the shape of the relationship between sales and price discounts. These phenomena can produce severe nonlinearities and interactions in the curves, and we argue that those are best captured with a flexible approach. Since a fully nonparametric regression model suffers from the curse of dimensionality, we propose a semiparametric regression model. Store-level sales over time is modeled as a nonparametric function of own-and cross-item price discounts, and a parametric function of other predictors (all indicator variables). We compare the predictive validity of the semiparametric model with that of two parametric benchmark models and obtain better performance on average. The results for three product categories indicate a.o. threshold- and saturation effects for both own- and cross-item temporary price cuts. We also show how the own-item curve depends on other items’ price discounts (flexible interaction effects). In a separate analysis, we show how the shape of the deal effect curve depends on own-item promotion signals. Our results indicate that prevailing methods for the estimation of deal effects on sales are inadequate.

Authenticity, employee silence, prohibitive voice, and the moderating effect of organisational identification

Authenticity is an important concept in positive psychology and has been shown to be related to well-being, health, and leadership effectiveness. The present paper introduces employee authenticity as a predictor of relevant workplace behaviors, namely employee silence and prohibitive voice. Converging evidence across two studies using cross-sectional and longitudinal designs demonstrates that when responding to hypothetical problematic workplace events (Study 1) or actual workplace experiences (Study 2), individual differences in employees’ authenticity predicted more self-reported voice behaviors and less silence that emanated from various motivations. Furthermore, authenticity scores consistently yielded predictive utility over and above the contribution of a broad set of individual and organization-based characteristics. Finally, organizational identification moderated the relation between authenticity and silence, such that for employees with high levels of identification, the relation between authenticity and silence was stronger

Does the absence of cointegration explain the typical findings in long horizon regressions?

One of the stylized facts in financial and international economics is that of increasing predictability of variables such as exchange rates and stock returns at longer horizons. This fact is based upon applications of long horizon regressions, from which the typical findings are that the point estimates of the regression parameter, the associated t-statistic, and the regression R^2 all tend to increase as the horizon increases. Such long horizon regression analyses implicitly assume the existence of cointegration between the variables involved. In this paper, we investigate the consequences of dropping this assumption. In particular, we look upon the long horizon regression as a conditional error-correction model and interpret the test for long horizon predictability as a single equation test for cointegration. We derive the asymptotic distributions of the estimator of the regression parameter and its t-statistic for arbitrary horizons, under the null hypothesis of no cointegration. It is shown that these distributions provide an alternative explanation for at least part of the typical findings. Furthermore, the distributions are used to derive a Phillips-Perron type correction to the ordinary least-squares t-statistic in order to endow it with a stable size for given, arbitrary, horizon. A local asymptotic power analysis reveals that the power of long horizon regression tests does not increase with the horizon. Exchange rate data are used to demonstrate the empirical relevance of our theoretical results

Activity topology estimation for large networks of cameras

Copyright © 2006 IEEEEstimating the paths that moving objects can take through the fields of view of possibly non-overlapping cameras, also known as their activity topology, is an important step in the effective interpretation of surveillance video. Existing approaches to this problem involve tracking moving objects within cameras, and then attempting to link tracks across views. In contrast we propose an approach which begins by assuming all camera views are potentially linked, and successively eliminates camera topologies that are contradicted by observed motion. Over time, the true patterns of motion emerge as those which are not contradicted by the evidence. These patterns may then be used to initialise a finer level search using other approaches if required. This method thus represents an efficient and effective way to learn activity topology for a large network of cameras, particularly with a limited amount of data.van den Hengel, A.; Dick, A.; Hill, R

Do leading indicators lead peaks more than troughs?

We develop a formal statistical approach to investigate the possibility that leading indicator variables have different lead times at business cycle peaks and troughs. For this purpose, we propose a novel Markov switching vector autoregressive model, where economic growth and leading indicators share a common Markov process determining the state, but such that their cycles are non-synchronous with the non-synchronicity varying across the different regimes. An empirical application to monthly US industrial production (IP) and The Conference Board's Composite Index of Leading Indicators (CLI) for the period 1959-2004 shows that on average the CLI leads IP by more than seven months at peaks, but only by three and a half months at troughs. In terms of timeliness, the CLI is therefore most useful for signalling oncoming recessions. Furthermore, we find that allowing for asymmetric lead times leads to improved real-time dating of business cycle peaks and troughs and more accurate forecasts of turning points and IP growth

A Comparison of Biased Simulation Schemes for Stochastic Volatility Models

When using an Euler discretisation to simulate a mean-reverting square root process, one runs into the problem that while the process itself is guaranteed to be nonnegative, the discretisation is not. Although an exact and efficient simulation algorithm exists for this process, at present this is not the case for the Heston stochastic volatility model, where the variance is modelled as a square root process. Consequently, when using an Euler discretisation, one must carefully think about how to fix negative variances. Our contribution is threefold. Firstly, we unify all Euler fixes into a single general framework. Secondly, we introduce the new full truncation scheme, tailored to minimise the upward bias found when pricing European options. Thirdly and finally, we numerically compare all Euler fixes to a recent quasi-second order scheme of Kahl and Jäckel and the exact scheme of Broadie and Kaya. The choice of fix is found to be extremely important. The full truncation scheme by far outperforms all biased schemes in terms of bias, root-mean-squared error, and hence should be the preferred discretisation method for simulation of the Heston model and extensions thereof

Two Lighthouses to Navigate: Effects of Ideal and Counter-Ideal Values on Follower Identification and Satisfaction with their Leaders

Ideals (or ideal values) help people to navigate in social life. They indicate at a very fundamental level what people are concerned about, what they strive for, and what they want to be affiliated with. Transferring this to a leader-follower analysis, our first Study (N = 306) confirms that followers’ identification and satisfaction with their leaders are stronger, the more leaders match followers’ ideal leader values. Study 2 (N = 244) extends the perspective by introducing the novel concept of counter-ideals (i.e., how an ideal leader should not be) as a second, non-redundant point of reference. Results confirm that a leader’s match on ideal and on counter-ideal values have independent effects in that both explain unique variance in followers’ identification and satisfaction with their leader. Study 3 (N = 136) replicates the previous results in an experimental scenario study and provides evidence for the proposed causal direction of the underlying process. We conclude that counter-ideal values might be an additional point of reference that people use to triangulate targets above and beyond ideal values and discuss the implications of our findings for value research and management