Overview: Individual and organizational perspectives on emotion management and display

As reported in Volume 1 of Research on Emotions in Organizations (Ashkanasy, Zerbe, & Härtel, 2005), the chapters in this volume are drawn from the best contributions to the 2004 International Conference on Emotion and Organizational Life held at Birkbeck College, London, complemented by additional, invited chapters. (This biannual conference has come to be known as the “Emonet” conference, after the listserv of members.) Previous edited volumes (Ashkanasy, Härtel, & Zerbe, 2000; Ashkanasy, Zerbe, & Härtel, 2002; Härtel, Zerbe, & Ashkanasy, 2004) were published every two years following the Emonet conference. With the birth of this annual Elsevier series came the opportunity for greater focus in the theme of each volume, and for greater scope for invited contributions. This volume contains eight chapters selected from conference contributions for their quality, interest, and appropriateness to the theme of this volume, as well as four invited chapters. We again acknowledge in particular the assistance of the conference paper reviewers (see the appendix). In the year of publication of this volume the 2006 Emonet conference will be held in Atlanta, USA and will be followed by Volumes 3 and 4 of Research on Emotions in Organizations. Readers interested in learning more about the conferences or the Emonet list should check the Emonet website http://www.uq.edu.au/emonet/.

Improved methods for predicting individual leaf area and leaf senescence in maize (Zea mays)

The ability to predict leaf area and leaf area index is crucial in crop simulation models that predict crop growth and yield. Previous studies have shown existing methods of predicting leaf area to be inadequate when applied to a broad range of cultivars with different numbers of leaves. The objectives of the study were to (i) develop generalised methods of modelling individual and total plant leaf area, and leaf senescence, that do not require constants that are specific to environments and/or genotypes, (ii) re-examine the base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence, and (iii) assess the method of calculation of individual leaf area from leaf length and leaf width in experimental work. Five cultivars of maize differing widely in maturity and adaptation were planted in October 1994 in south-eastern Queensland, and grown under non-limiting conditions of water and plant nutrient supplies. Additional data for maize plants with low total leaf number (12-17) grown at Katumani Research Centre, Kenya, were included to extend the range in the total leaf number per plant. The equation for the modified (slightly skewed) bell curve could be generalised for modelling individual leaf area, as all coefficients in it were related to total leaf number. Use of coefficients for individual genotypes can be avoided, and individual and total plant leaf area can be calculated from total leaf number. A single, logistic equation, relying on maximum plant leaf area and thermal time from emergence, was developed to predict leaf senescence. The base, optimum, and maximum temperatures for calculation of thermal time for leaf senescence were 8, 34, and 40 degrees C, and apply for the whole crop-cycle when used in modelling of leaf senescence. Thus, the modelling of leaf production and senescence is simplified, improved, and generalised. Consequently, the modelling of leaf area index (LAI) and variables that rely on LAI will be improved. For experimental purposes, we found that the calculation of leaf area from leaf length and leaf width remains appropriate, though the relationship differed slightly from previously published equations.

The proportion of individual lucerne plants resistant to Phytophthora medicaginis and Colletotrichum trifolii in Australian cultivars

Phytophthora root rot (Phytophthora medicaginis) and colletotrichum crown rot (Colletotrichum trifoli) are the 2 most serious pathogens of lucerne in eastern Australia. Work reported in this paper shows that in glasshouse tests of the 11 most commonly grown Australian lucerne cultivars, the proportion of individual plants with resistance to both pathogens ranges from 0 (Hunter River and Aurora) through to a maximum of 19.8% (Sequel HR). Within 9 of the cultivars, the proportion of individual plants resistant to the 2 pathogens was <7%. Since these 2 diseases are known to cause serious losses in eastern Australia, the results indicate further improvement in lucerne production can be obtained by increasing the proportion of individual plants in a cultivar resistant to both pathogens. This would be best achieved by identifying dominant sources of resistance and incorporating this into on-going lucerne breeding programs.

Individual and household willingness to pay for public goods

The issue of whether willingness to pay (WTP) for the benefits generated by a public good should be elicited on an individual or on a household basis is addressed. Differences between individual and household WTP may arise when members of the household are mutually altruistic. It is shown that, for general specifications of altruism, household WTP is less than the sum of household members' individual WTP. Implications for the choice between household and individual measures of WTP are considered, and issues in the elicitation of household WTP are addressed.

Stochastic structure and individual-tree growth models

The majority of past and current individual-tree growth modelling methodologies have failed to characterise and incorporate structured stochastic components. Rather, they have relied on deterministic predictions or have added an unstructured random component to predictions. In particular, spatial stochastic structure has been neglected, despite being present in most applications of individual-tree growth models. Spatial stochastic structure (also called spatial dependence or spatial autocorrelation) eventuates when spatial influences such as competition and micro-site effects are not fully captured in models. Temporal stochastic structure (also called temporal dependence or temporal autocorrelation) eventuates when a sequence of measurements is taken on an individual-tree over time, and variables explaining temporal variation in these measurements are not included in the model. Nested stochastic structure eventuates when measurements are combined across sampling units and differences among the sampling units are not fully captured in the model. This review examines spatial, temporal, and nested stochastic structure and instances where each has been characterised in the forest biometry and statistical literature. Methodologies for incorporating stochastic structure in growth model estimation and prediction are described. Benefits from incorporation of stochastic structure include valid statistical inference, improved estimation efficiency, and more realistic and theoretically sound predictions. It is proposed in this review that individual-tree modelling methodologies need to characterise and include structured stochasticity. Possibilities for future research are discussed. (C) 2001 Elsevier Science B.V. All rights reserved.

Individual differences in motivated social cognition: The case of self-serving information processing

Three experiments examined the hypothesis that people show consistency in motivated social cognitive processing across self-serving domains. Consistent with this hypothesis, Experiment 1 revealed that people who rated a task at which they succeeded as more important than a task at which they failed also cheated on a series of math problems, but only when they could rationalize their cheating as unintentional. Experiment 2 replicated this finding and demonstrated that a self-report measure of self-deception did not predict this rationalized cheating. Experiment 3 replicated Experiments 1 and 2 and ruled out several alternative explanations. These experiments suggest that people who show motivated processing in ego-protective domains also show motivated processing in extrinsic domains. These experiments also introduce a new measurement procedure for differentiating between intentional versus rationalized cheating.