906 resultados para Competing Predictions
Resumo:
The inconsistent findings of past board diversity research demand a test of competing linear and curvilinear diversity–performance predictions. This research focuses on board age and gender diversity, and presents a positive linear prediction based on resource dependence theory, a negative linear prediction based on social identity theory, and an inverted U-shaped curvilinear prediction based on the integration of resource dependence theory with social identity theory. The predictions were tested using archival data on 288 large organizations listed on the Australian Securities Exchange, with a 1-year time lag between diversity (age and gender) and performance (employee productivity and return on assets). The results indicate a positive linear relationship between gender diversity and employee productivity, a negative linear relationship between age diversity and return on assets, and an inverted U-shaped curvilinear relationship between age diversity and return on assets. The findings provide additional evidence on the business case for board gender diversity and refine the business case for board age diversity.
Resumo:
We present three competing predictions of the organizational gender diversity-performance relationship: a positive linear prediction, a negative linear prediction, and an inverted U-shaped curvilinear prediction. The paper also proposes a moderating effect of industry type (services vs. manufacturing). The predictions were tested using archival quantitative data with a longitudinal design. The results show partial support for the positive linear and inverted U-shaped curvilinear predictions as well as for the proposed moderating effect of industry type. The results help reconcile the inconsistent findings of past research. The findings also show that industry context can strengthen or weaken gender diversity effects.
Resumo:
Research on workforce diversity at the organisational level gained momentum in the 1990s, because of the growing trend in HR research to link HR practices with organisational performance. The new parallel wave of research focused on the business case for diversity, in which diversity was linked to organisational performance. However, the results of these studies, mainly focusing on linear diversity-performance relationships, have been inconsistent. Based on contrasting theories, this paper proposes three competing predictions of the gender diversity-performance relationship at the organisational level: a positive linear relationship derived from the resource-based view of the firm, a negative linear relationship derived from self-categorisation and social identity theories, and a U-shaped curvilinear relationship derived from the integration of the resource-based view of the firm with self-categorisation and social identity theories. The U-shaped relationship accounts for the inconsistent findings in past research, because different proportions of men and women produce different social dynamics that have different effects on organisational performance. Further, the proposed U-shaped relationship can have different slopes in the manufacturing and services industries. The paper contributes to the field of diversity by strengthening its weak theoretical foundations and by highlighting the industry differences.
Resumo:
Research on workforce diversity gained momentum in the 1990s. However, empirical findings to date on the link between gender diversity and performance have been inconsistent. Based on contrasting theories, this paper proposes a positive linear and a negative linear prediction of the gender diversity-performance relationship. The paper also proposes that industry type (services vs. manufacturing) moderates the gender diversity-performance relationship such that the relationship will be positive in service organisations and negative in manufacturing organisations. The results show partial support for the positive linear gender diversity-performance relationship and for the moderating effect of industry type. The study contributes to the field of diversity by showing that workforce gender diversity can have a different impact on organisational performance in different industries.
Resumo:
Empirical findings on the link between gender diversity and performance have been inconsistent. This paper presents three competing predictions of the organizational gender diversity-performance relationship: a positive linear prediction derived from the resource-based view of the firm, a negative linear prediction derived from self-categorization and social identity theories, and an inverted U-shaped curvilinear prediction derived from the integration of the resource-based view of the firm with self-categorization and social identity theories. This paper also proposes a moderating effect of industry type (services vs. manufacturing) on the gender diversity-performance relationship. The predictions were tested in publicly listed Australian organizations using archival quantitative data with a longitudinal research design. The results show partial support for the positive linear and inverted U-shaped curvilinear predictions as well as for the proposed moderating effect of industry type. The curvilinear relationship indicates that different proportions of organizational gender diversity have different effects on organizational performance, which may be attributed to different dynamics as suggested by the resource-based view and self-categorization and social identity theories. The results help reconcile the inconsistent findings of past research that focused on the linear gender diversity-performance relationship. The findings also show that industry context can strengthen or weaken the effects of organizational gender diversity on performance.
Resumo:
Adaptive Resonance Theory (ART) models are real-time neural networks for category learning, pattern recognition, and prediction. Unsupervised fuzzy ART and supervised fuzzy ARTMAP synthesize fuzzy logic and ART networks by exploiting the formal similarity between the computations of fuzzy subsethood and the dynamics of ART category choice, search, and learning. Fuzzy ART self-organizes stable recognition categories in response to arbitrary sequences of analog or binary input patterns. It generalizes the binary ART 1 model, replacing the set-theoretic: intersection (∩) with the fuzzy intersection (∧), or component-wise minimum. A normalization procedure called complement coding leads to a symmetric: theory in which the fuzzy inter:>ec:tion and the fuzzy union (∨), or component-wise maximum, play complementary roles. Complement coding preserves individual feature amplitudes while normalizing the input vector, and prevents a potential category proliferation problem. Adaptive weights :otart equal to one and can only decrease in time. A geometric interpretation of fuzzy AHT represents each category as a box that increases in size as weights decrease. A matching criterion controls search, determining how close an input and a learned representation must be for a category to accept the input as a new exemplar. A vigilance parameter (p) sets the matching criterion and determines how finely or coarsely an ART system will partition inputs. High vigilance creates fine categories, represented by small boxes. Learning stops when boxes cover the input space. With fast learning, fixed vigilance, and an arbitrary input set, learning stabilizes after just one presentation of each input. A fast-commit slow-recode option allows rapid learning of rare events yet buffers memories against recoding by noisy inputs. Fuzzy ARTMAP unites two fuzzy ART networks to solve supervised learning and prediction problems. A Minimax Learning Rule controls ARTMAP category structure, conjointly minimizing predictive error and maximizing code compression. Low vigilance maximizes compression but may therefore cause very different inputs to make the same prediction. When this coarse grouping strategy causes a predictive error, an internal match tracking control process increases vigilance just enough to correct the error. ARTMAP automatically constructs a minimal number of recognition categories, or "hidden units," to meet accuracy criteria. An ARTMAP voting strategy improves prediction by training the system several times using different orderings of the input set. Voting assigns confidence estimates to competing predictions given small, noisy, or incomplete training sets. ARPA benchmark simulations illustrate fuzzy ARTMAP dynamics. The chapter also compares fuzzy ARTMAP to Salzberg's Nested Generalized Exemplar (NGE) and to Simpson's Fuzzy Min-Max Classifier (FMMC); and concludes with a summary of ART and ARTMAP applications.
Resumo:
A new neural network architecture is introduced for incremental supervised learning of recognition categories and multidimensional maps in response to arbitrary sequences of analog or binary input vectors. The architecture, called Fuzzy ARTMAP, achieves a synthesis of fuzzy logic and Adaptive Resonance Theory (ART) neural networks by exploiting a close formal similarity between the computations of fuzzy subsethood and ART category choice, resonance, and learning. Fuzzy ARTMAP also realizes a new Minimax Learning Rule that conjointly minimizes predictive error and maximizes code compression, or generalization. This is achieved by a match tracking process that increases the ART vigilance parameter by the minimum amount needed to correct a predictive error. As a result, the system automatically learns a minimal number of recognition categories, or "hidden units", to met accuracy criteria. Category proliferation is prevented by normalizing input vectors at a preprocessing stage. A normalization procedure called complement coding leads to a symmetric theory in which the MIN operator (Λ) and the MAX operator (v) of fuzzy logic play complementary roles. Complement coding uses on-cells and off-cells to represent the input pattern, and preserves individual feature amplitudes while normalizing the total on-cell/off-cell vector. Learning is stable because all adaptive weights can only decrease in time. Decreasing weights correspond to increasing sizes of category "boxes". Smaller vigilance values lead to larger category boxes. Improved prediction is achieved by training the system several times using different orderings of the input set. This voting strategy can also be used to assign probability estimates to competing predictions given small, noisy, or incomplete training sets. Four classes of simulations illustrate Fuzzy ARTMAP performance as compared to benchmark back propagation and genetic algorithm systems. These simulations include (i) finding points inside vs. outside a circle; (ii) learning to tell two spirals apart; (iii) incremental approximation of a piecewise continuous function; and (iv) a letter recognition database. The Fuzzy ARTMAP system is also compared to Salzberg's NGE system and to Simpson's FMMC system.
Resumo:
The study centers on the power of Right-Wing Authoritarianism (RWA) and Social Dominance Orientation (SDO) as predictors of prejudice against stereotypical and nonstereotypical homosexuals under the threat of death and the threat of uncertainty. Right-wing authoritarianism (RWA) is an individual difference variable that measures the tendency for individuals to unquestionably follow those perceived to be authorities. Social Dominance Orientation (SDO) is an individual difference variable that measures the degree to which an individual prefers inequality among social groups. The RWA and SDO Scales are considered to be two of the strongest predictors of prejudice, such as prejudice against homosexuals. The study focuses on the unique predictive power of these two variables in predicting prejudice against homosexuals. The study also examines the role of situational threat in prejudice, specifically the threat of death (mortality salience) and the threat of uncertainty (uncertainty salience). Competing predictions from theories involving the threat of death (Terror Management Theory) and the threat of uncertainty (Uncertainty Management Theory) are also tested. The preference for expected information in the form of stereotypes concerning male homosexuals (that is, a stereotypical or non-stereotypical homosexual) were tested. The difference between the predictive power ofRWA and SDO was examined by measuring how these variables predict liking of a stereotypical or non-stereotypical homosexual under the threat of death, the threat of uncertainty, or a control condition. Along with completing a measure for RWA and a measure for SDO, participants were asked to think of their own death, of their being uncertain or about watching television then were asked to read about a week in the life of either a stereotypical or non-stereotypical male homosexual. Participants were then asked to evaluate the individual and his essay. Based on the participants' evaluations, results from 180 heterosexual university students show that RWA and SDO are strong predictors for disliking of a stereotypical homosexual under the threat of uncertainty and disliking of a non-stereotypical homosexual under the threat of death. Furthermore, however, results show that RWA is a particularly strong predictor of disliking of a stereotypical homosexual under the threat of uncertainty, whereas SDO is an exceptionally strong predictor of disliking of the non-stereotypical homosexual under the threat of death. This further adds to the notion that RWA and SDO are indeed unique predictors of prejudice. Implications are also explored, including the fact that the study simuhaneously examined the role of individual difference variables and situational threat variables, as well as exploratory analysis on Dominating Authoritarians.
Resumo:
Theoretical models on moral hazard provide competing predictions on the incentive-risk relationship. These predictions are derived under the assumptions of homogeneous agents and exogenous risk. However, the existing empirical evidence does not account for risk-aversion heterogeneity and risk endogeneity. This paper uses a well-built database on tenancy contracts to address these issues. Detailed information on cropping activities is used to measure the exogenous risk. Risk-aversion heterogeneity and other self-selection problems are addressed through a portfolio schedule and a subsample of farmers who simultaneously own and sharecrop different farms. This controlled exercise finds a direct relation between incentives and exogenous risk.
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This study examined the role of team identification in the dissimilarity and conflict relationship. We tested competing predictions that team identification would either mediate or moderate the positive associations between visible (age, gender and ethnic background), professional (background) and value dissimilarity and task and relationship conflict. Data was collected from 27 MBA student teams twice during a semester. Multilevel modelling and a longitudinal design were used. Results showed that value dissimilarity was positively associated with task and relationship conflict at Time 2. Its effects on relationship conflict at Time 1 were moderated by team identification. Team identification also moderated the effects of gender, age and ethnic dissimilarity on task conflict at Time 2, and the effects of gender and professional dissimilarity on relationship conflict at Time 2. No support was obtained for the mediating role of team identification on the associations between dissimilarity and conflict, or for changes in the effects of dissimilarity over time.
Resumo:
We test competing linear and curvilinear predictions between board diversity and performance. The predictions were tested using archival data on 288 organizations listed on the Australian Securities Exchange. The findings provide additional evidence on the business case for board gender diversity and refine the business case for board age diversity.
Resumo:
Global increase in sea temperatures has been suggested to facilitate the incoming and spread of tropical invaders. The increasing success of these species may be related to their higher physiological performance compared with indigenous ones. Here, we determined the effect of temperature on the aerobic metabolic scope (MS) of two herbivorous fish species that occupy a similar ecological niche in the Mediterranean Sea: the native salema (Sarpa salpa) and the invasive marbled spinefoot (Siganus rivulatus). Our results demonstrate a large difference in the optimal temperature for aerobic scope between the salema (21.8°C) and the marbled spinefoot (29.1°C), highlighting the importance of temperature in determining the energy availability and, potentially, the distribution patterns of the two species. A modelling approach based on a present-day projection and a future scenario for oceanographic conditions was used to make predictions about the thermal habitat suitability (THS, an index based on the relationship between MS and temperature) of the two species, both at the basin level (the whole Mediterranean Sea) and at the regional level (the Sicilian Channel, a key area for the inflow of invasive species from the Eastern to the Western Mediterranean Sea). For the present-day projection, our basin-scale model shows higher THS of the marbled spinefoot than the salema in the Eastern compared with the Western Mediterranean Sea. However, by 2050, the THS of the marbled spinefoot is predicted to increase throughout the whole Mediterranean Sea, causing its westward expansion. Nevertheless, the regional-scale model suggests that the future thermal conditions of Western Sicily will remain relatively unsuitable for the invasive species and could act as a barrier for its spread westward. We suggest that metabolic scope can be used as a tool to evaluate the potential invasiveness of alien species and the resilience to global warming of native species.
Resumo:
Native-like use of preterit and imperfect morphology in all contexts by English learners of L2 Spanish is the exception rather than the rule, even for successful learners. Nevertheless, recent research has demonstrated that advanced English learners of L2 Spanish attain a native-like morphosyntactic competence for the preterit/imperfect contrast, as evidenced by their native-like knowledge of associated semantic entailments (Goodin-Mayeda and Rothman 2007, Montrul and Slabakova 2003, Slabakova and Montrul 2003, Rothman and Iverson 2007). In addition to an L2 disassociation of morphology and syntax (e.g., Bruhn de Garavito 2003, Lardiere 1998, 2000, 2005, Prévost and White 1999, 2000, Schwartz 2003), I hypothesize that a system of learned pedagogical rules contributes to target-deviant L2 performance in this domain through the most advanced stages of L2 acquisition via its competition with the generative system. I call this hypothesis the Competing Systems Hypothesis. To test its predictions, I compare and contrast the use of the preterit and imperfect in two production tasks by native, tutored (classroom), and naturalistic learners of L2 Spanish.
Resumo:
In various attempts to relate the behaviour of highly-elastic liquids in complex flows to their rheometrical behaviour, obvious candidates for study have been the variation of shear viscosity with shear rate, the two normal stress differences N(1) and N(2) especially N(1), and the extensional viscosity eta(E). In this paper, we shall be mainly interested in `constant-viscosity` Boger fluids, and, accordingly, we shall limit attention to N(1) and eta(E). We shall concentrate on two important flows - axisymmetric contraction flow and ""splashing"" (particularly that which arises when a liquid drop falls onto the free Surface of the same liquid). Modem numerical techniques are employed to provide the theoretical predictions. It is shown that the two obvious manifestations of viscoelastic rheometrical behaviour can sometimes be opposing influences in determining flow characteristics. Specifically, in an axisymmetric contraction flow, high eta(E) , can retard the flow, whereas high N(1) can have the opposite effect. In the splashing experiment, high eta(E) can certainly reduce the height of the so-called Worthington jet, thus confirming some early suggestions, but, again, other rheometrical influences can also have a role to play and the overall picture may not be as clear as it was once envisaged.
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A standard finding in the political economy of trade policy literature is that we should expect export-oriented industries to attract more assistance than import-competing industries. In reality, however, trade policy is heavily biased toward supporting import industries. This paper shows within a standard protection for sale framework, how the costliness of raising revenue via taxation makes trade subsidies less desirable and trade taxes more desirable. The model is then estimated and its predictions tested using U.S. tariff data. An empirical estimate of the costliness of revenue-raising is also obtained.