A closer examination of causal inference: The roles of consensus, distinctiveness, and consistency information.

Orvis, Bruce R.; Cunningham, John D.; Kelley, Harold H.

doi:10.1037/0022-3514.32.4.605

Cited by 211 publications

(219 citation statements)

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“…While, as a general conceptual framework, cybernetic information processing can be overlain onto numerous theoretical perspectives to highlight the importance of environmental feedback (Edwards 1992), the significance of environmental feedback to attributional processes largely has been overlooked in sales research. This is despite suggestions from attribution theorists that how individuals use related information to make causal inferences is the foundation for understanding attribution making (Orvis, Cunningham, and Kelley 1975).…”

Section: Overviewmentioning

confidence: 48%

Control Systems' Effect on Attributional Processes and Sales Outcomes: A Cybernetic Information-Processing Perspective

Fang

Evans

Landry

2005

Journal of the Academy of Marketing Science

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Built upon a cybernetic information-processing framework, this article advances and empirically tests a conceptual model proposing the relationships between sales controls (outcome, activity, capability), salespeople's attributional ascriptions (effort, strategy, ability), attributional dimensions (internal/external, stable/unstable), and psychological consequences (job satisfaction, performance expectation Sales performance is a function of how salespeople adapt and adjust to successes and failures within their selling environments (Weitz, Sujan, and Sujan 1986). Understanding this adjustment process should be important to sales and marketing managers. Perhaps the most obvious means of management affecting a selling environment is through directing salespeople with sales control systems (Oliver and Anderson 1994). With regard to sales successes and failures, salespeople are likely to use these control systems as perceptual screens to filter their own evaluations of their sales performance (Lord and Maher 1990). For example, if the sales expectations of the firm focus on sales volume, low performance on volume may be attributed to too little effort (e.g., laggards), or by contrast, high performance may be attributed to high levels of effort (e.g., rate busters). Despite the importance of such performance attributions on sales behaviors (e.g., DeCarlo, Teas, and McElroy 1997), it is surprising that how control systems influence salespeople's attribution processes remains underresearched. While marketing research specifically addresses attribution retraining, or the coaching of salespeople to make helpful attributions (e.g., Sujan 1999), no research has been conducted to aid sales managers in understanding how salespeople's attributions are made within particular selling environments.

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Section: Overviewmentioning

confidence: 48%

Control Systems' Effect on Attributional Processes and Sales Outcomes: A Cybernetic Information-Processing Perspective

Fang

Evans

Landry

2005

Journal of the Academy of Marketing Science

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“…All previous models Kelley, 1967Kelley, , 1973Orvis et al, 1975), with the exception of those of Forsterling (1989) and Hilton and Slugoski (1986), made predictions that were based on configurations. One interpretation of all configuration-based models is that they predict the same attributions for all of our problems that shared a configuration.…”

Section: Interpretation Of Biases Based On Experiments Specifying Conmentioning

confidence: 99%

“…The causal attribution literature in social psychology has largely measured performance against an apparently different normative standard: namely, variations of Kelley's (1967Kelley's ( ,1973 influential proposal that people are "intuitive scientists" who use a mechanism of causal induction analogous to the analysis of variance (ANOVA) (Cheng & Novick, 1990a;Forsterling, 1989;Hewstone & Jaspars, 1987;Hilton, 1988Hilton, ,1990Jaspars, 1983;Orvis, Cunningham, & Kelley, 1975;Pruitt & Insko, 1980). This literature has, until recently, presented a chaotic picture of causal induction not unlike that in cognitive psychology: Causal induction sometimes conforms to the normative standard but often deviates from it.…”

Section: Kelley's Analysis Of Variance Modelmentioning

confidence: 99%

Covariation in natural causal induction.

Cheng

Novick²

1992

Psychological Review

367

321

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The covariation component of everyday causal inference has been depicted, in both cognitive and social psychology as well as in philosophy, as heterogeneous and prone to biases. The models and biases discussed in these domains are analyzed with respect to focal sets: contextually determined sets of events over which covariation is computed. Moreover, these models are compared to our probabilistic contrast model, which specifies causes as first and higher order contrasts computed over events in a focal set. Contrary to the previous depiction of covariation computation, the present assessment indicates that a single normative mechanism-the computation of probabilistic contrasts-underlies this essential component of natural causal induction both in everyday and in scientific situations.We do not perceive the visual world as a two-dimensional mosaic of bits of light patches. Instead, these data from the retina are processed by our central visual system to yield a coherent perception of the world, reflecting its visual and spatial structures. Similarly, we do not perceive our lives or the world beyond as a stream of unconnected elemental events. Here, too, central processes act on the data to yield an organized view, structured in terms of commonsensical and scientific theories. Causal induction is an example of such organizing processes. When a government resorts to violent suppression of its people or yields to peaceful reform, when a couple decides to date or a marriage breaks up, or when an epidemic strikes or a new vaccine controls it, we seek out causes.How do ordinary people induce the causes of events? Moreover, given that the primary goals of causal induction are the recovery of the causal structure of the world and the prediction of future events, is the mechanism underlying natural causal induction adequate for satisfying these goals? Covariation-the change in the probability of an effect given the presence versus the absence of a potential cause-has generally been regarded as a necessary (although insufficient) criterion of normative causal induction. 1 The computation of covariation has generated a considerable body of research in the cognitive and social literatures, both of which have presented rather messy pictures of the psychological mechanism. These literatures suggest that the covariation component in natural causal induction is non-

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“…events in the real world, and from these instances they compute co-occurrence between the events to make causal attributions (Cheng & Novick, 1990;Försterling, Buhner, & Gall, 1998;Hewstone & Jaspers, 1987;Hilton & Slugoski, 1986;Orvis, Cunningham, & Kelley, 1975;Pruitt & Insko, 1980;Sutton & McClure, 2001).…”

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confidence: 99%

Covariation and quantifier polarity: What determines causal attribution in vignettes?

2006

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Tests of causal attribution often use verbal vignettes, with covariation information provided through statements quantified with natural language expressions. The effect of covariation information has typically been taken to show that set size information affects attribution. However, recent research shows that quantifiers provide information about discourse focus as well as covariation information. In the attribution literature, quantifiers are used to depict covariation, but they confound quantity and focus. In four experiments, we show that focus explains all (Experiment 1) or some (Experiments 2-4) of the impact of covariation information on the attributions made, confirming the importance of the confound. Attribution experiments using vignettes that present covariation information with natural language quantifiers may overestimate the impact of set size information, and ignore the impact of quantifier-induced focus. q 2005 Elsevier B.V. All rights reserved.Keywords: Attribution theory; Causal reasoning; Covariation; Quantifiers Den divorced Angie, Maureen loves Billy, Ian hates Phil-but why? Making causal attributions about social situations is a core part of every day human cognition. A prominent idea about how people make causal attributions is that they use covariation information, the observed co-occurrence of two events (Kelley, 1967). More recently, covariation theory in its many guises assumes that people are exposed to instances of

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A closer examination of causal inference: The roles of consensus, distinctiveness, and consistency information.

Abstract: The research reported here was conducted under National Science Foundation Grants GS-1121X and GS-33069X. The authors are grateful to John H. Harvey for his advice and help on the research.

Cited by 211 publications

References 4 publications

Control Systems' Effect on Attributional Processes and Sales Outcomes: A Cybernetic Information-Processing Perspective

Control Systems' Effect on Attributional Processes and Sales Outcomes: A Cybernetic Information-Processing Perspective

Covariation in natural causal induction.

Covariation and quantifier polarity: What determines causal attribution in vignettes?

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