Name
Abstract | ||
|---|---|---|
We argue that traditional cultural factors models (from Hofstede, Nisbett, etc.) are too abstract to provide good predictions
of important human performance behaviors such as directive compliance. Instead, we focus on culture-specific social interaction
behaviors (i.e., "etiquette") as a bridge between abstract cultural factors and human performance. We describe a computational
model of etiquette and politeness perception, called CECAEDA (Computational Effects of Cultural Attributes and Etiquette on
Directive Adherence). CECAEDA consists of four parts: (1) a culturally universal model of politeness perceptions, their causes
and effects, (2) a culturally universal cognitive model compliance decision making and behaviors, (3) a set of hypotheses
about how politeness perceptions alter directive compliance, and (4) a set of hypotheses about how cultural factors (specifically,
those proposed by Hofstede [1]) affect etiquette perceptions and, thus, directive compliance in culture-specific ways. Each
component is discussed in detail, followed by a brief presentation of our research test bed and paradigm for evaluating CECAEDA.
|
Year | DOI | Venue |
|---|---|---|
2009 | 10.1007/978-3-642-02707-9_64 | Human-Computer Interaction |
Keywords | Field | DocType |
abstract cultural factor,politeness,directive compliance,traditional cultural factors model,compliance decision,computational model,etiquette perception,directive compliance.,cultural factor,culturally universal cognitive model,politeness perception,etiquette,culturally universal model,culture,factor model,test bed,human performance,cognitive model,computer model,social interaction | Social psychology,Social relation,Politeness,Psychology,Directive,Cognitive model,Etiquette,Perception,Hofstede's cultural dimensions theory | Conference |
Volume | ISSN | Citations |
5614 | 0302-9743 | 4 |
PageRank | References | Authors |
0.90 | 4 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christopher A. Miller | 1 | 334 | 46.70 |
| Peggy Wu | 2 | 22 | 7.10 |
| Vanessa Vakili | 3 | 9 | 1.80 |
| Tammy Ott | 4 | 11 | 4.42 |
| Kip Smith | 5 | 4 | 0.90 |