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This paper examines reuse patterns in transparent multi-staged contests, in which a crowd of developers can reuse others’ designs when developing a novel digital application. They compete for the best application, one that is of high quality in both code and feature. Transparency, defined as collective information access to (1) the design solution, and (2) and the quality of it, triggers variability in reuse choices. Depending on the relative performance, developers adapt their risk preference along a continuum of exploitative to explorative reuse. However, variability in reuse behavior is also shaped by an individuals’ design preference: to focus on either code or feature. To explore patterns of reuse and performance emerging from this micro-level heterogeneity, we develop an agent-based simulation model, informed by theory of reuse and variable risk preferences, as well as emerging empirical data. Our results reveal unexpected discontinuous performance patterns. Design preferences, a bias towards code or feature, lowers the collective performance of the crowd. However, transparency insulates those at the top from such negative effects. It produces high performing designs even if there is bias. Further, while transparency reduces variability and smooths the patterns among those at the top, it also creates unique opportunities for ‘newcomers’ to submit high-quality applications.

A key component of negotiation dynamics is the search for mutually beneficial agreements, and offer exchange is a key element of that process. Rooted in the tradition of information processing psychology, we develop a theoretical model that conceives of negotiation as the collaborative search of a complex offer space. Negotiators simplify and coordinate search via information contained in offer exchanges, isolating subregions of the offer space for potential solutions. We suggest that early search is more exploratory and primarily influenced by the value of offers; later search is more focused on refinement and is influenced by the content of offers. In that, search by value is substantially more difficult than search by content, and parties seek value through communicating about content. Important information about the negotiators’ perspectives is revealed in comprehensive offers, and critical insight into this search process can be gained by examining the pattern of comprehensive offers.

In this paper we replicate and extend the work of the Computers are Social Actors (CASA) researchers who repeatedly found evidence that humans treat computers with typical social norms as if they were humans. We performed a between-subjects 2x2 factorial experiment to test our hypotheses as well as an exploratory factor analysis to further refine and validate a construct which measures politeness. We retest the CASA hypothesis and found that our new hypothesis - Websites are Social Actors (WASA) reduces the CASA effect in contexts where individuals form a social attachment to websites instead of computers. We found evidence that suggests humans can exhibit politeness toward websites and literally (not virtually) treat them as social actors. Finally, we tease out the elements of politeness as a construct and identify the key items in the instrument for data reduction, and initiate efforts towards establishing reliability and construct validity. As we shall see, the results of an exploratory factor analysis are quite consistent to recent research in social cognition, and suggest that the politeness construct may be tapping similar and fundamental components of how humans engage with others in their social world.

How are norms maintained? Axelrod (in Am. Political Sci. Rev. 80(4): 1095---1111, 1986) used an evolutionary computational model to proffer a solution: the metanorm (norm to enforce norm enforcement). Although often discussed, this model has neither been sufficiently replicated nor explored. In this paper we replicate and extend that model. Results were generally supportive of the original. Speculations in the original regarding the requirement to link sanctions underlying the metanorm structure were not supported, as differentiating punishment likelihoods against defectors from punishment likelihoods against shirkers (non-enforcers of the norm against defection) lead to more efficient and effective sanctioning structures that allowed norm emergence. Replications of the Groups game (two groups differing in numbers and power) generally supported the original reports, but true norms against defection emerged only if sanctioning structures were differentiated, resulting in the Strong group developing a dominant norm against others defecting (Metavengeance). That is, when groups are involved with differential power, Metanorms fail unless a more sophisticated sanctioning structure (Metavengeance) is supported.

Our personal values are subject to forces of social influence. Deontological resolve captures how strongly one relies on absolute rules of right and wrong in the representation of one's personal values and may predict willingness to modify one's values in the presence of social influence. Using fMRI, we found that a neurobiological metric for deontological resolve based on relative activity in the ventrolateral prefrontal cortex (VLPFC) during the passive processing of sacred values predicted individual differences in conformity. Individuals with stronger deontological resolve, as measured by greater VLPFC activity, displayed lower levels of conformity. We also tested whether responsiveness to social reward, as measured by ventral striatal activity during social feedback, predicted variability in conformist behavior across individuals but found no significant relationship. From these results we conclude that unwillingness to conform to others' values is associated with a strong neurobiological representation of social rules.

The impact of tactical knowledge on integrative and distributive response-in-kind behavior sequences and the ability to shift from distributive to integrative behaviors were examined using data from a prior study. Ninety dyads engaged in a multi-issue joint venture negotiation. Forty-five dyads were provided tactical knowledge and the other 45 were not. Markov chain analysis was used to test the hypotheses. A second-order chain best fit the data. Results showed that negotiators responded-in-kind to both distributive and integrative tactical behavior regardless of tactical knowledge. In line with Weick's (1969) “double interact” proposition of interlocked behaviors, negotiators with tactical knowledge were more likely to respond-in-kind to integrative behavior than were those without such knowledge, but only after their previous integrative behavior had been reciprocated. In addition, negotiators with tactical knowledge engaged in longer chains of integrative behavior (regardless of the behavior of the other party) than did negotiators without tactical knowledge; however, this only occurred after two integrative behaviors had occurred previously.

The impact of tactical knowledge on negotiator behaviors and joint outcomes was examined. It was hypothesized that the availability of written descriptions of negotiation tactics would provide negotiators with the knowledge necessary to apply in a mixed-motive negotiation and that, as a result, these negotiators would engage in different behaviors leading to higher joint outcomes than would negotiators without this knowledge. Ninety dyads engaged in a multi-issue joint venture negotiation: 45 dyads were provided tactical descriptions, and the other 45 were not. Dyads with tactical knowledge engaged in more integrative behaviors and achieved higher joint outcomes, with integrative behaviors serving as mediators of the knowledge-outcome effect. Distributive behaviors were found to be negatively related to joint outcome but were not influenced by tactical knowledge. Although negotiations occur every day, people often fail to reach agreements that maximize joint gain, even when negotiating simple conflicts (Neale & Northcraft, 1986; Pruitt, 1981; Raiffa, 1982). When agreements are reached, there are frequently other solutions that exist which could further benefit either or both parties. In more formal terms, negotiators often do not achieve Pareto optimal solutions on tasks with integrative potential. Although people often think they have done the best they could in a negotiation, they are frequently mistaken. The problem of suboptimal negotiated solutions has been examined from both cognitive (e.g., Carroll, Bazerman, & Maury, 1988; Neale & Bazerman, 1991 ) and social interaction perspectives (Lewis & Fry, 1977; Putnam & Jones, 1982; Putnam & Wilson, 1989; Schultz & Pruitt, 1978). Although separate examination of social and cognitive processes has provided insight into specific aspects of the negotiation process, the present research is unique in that it considers these processes concurrently and in the context of a general problem-solving framework. Viewing these processes as problem solving provides a unifying framework that explains negotiation processes principally in terms of knowledge being applied to tasks. In the current study, negotiator knowledge was influenced through the use of a simple intervention: We provided negotiators with written descriptions of negotiation tactics in an attempt to influence tactical behavior and quality of the agreement.

A computational organization theory is the articulation of an organization theory in the form of a computer program. We describe an example of this approach to studying organizational phenomena through the use of simulated autonomous intelligent agents, present a detailed description of such a model, and demonstrate the application through a series of experiments conducted with the model. The model, called Plural‐Soar, represents a partial instantiation of a cognitively motivated theory that views organizational behavior as emergent behavior from the collective interaction of intelligent agents over time, and that causal interpretations of certain organizational phenomena must be based on theoretically sufficient models of individual deliberation. We examine the individual and collective behavior of the agents under varying conditions of agent capabilities defined by their communication and memory properties. Thirty separate simulations with homogeneous agent groups were run varying agent type, group size...

Sacred values, such as those associated with religious or ethnic identity, underlie many important individual and group decisions in life, and individuals typically resist attempts to trade off their sacred values in exchange for material benefits. Deontological theory suggests that sacred values are processed based on rights and wrongs irrespective of outcomes, while utilitarian theory suggests that they are processed based on costs and benefits of potential outcomes, but which mode of processing an individual naturally uses is unknown. The study of decisions over sacred values is difficult because outcomes cannot typically be realized in a laboratory, and hence little is known about the neural representation and processing of sacred values. We used an experimental paradigm that used integrity as a proxy for sacredness and which paid real money to induce individuals to sell their personal values. Using functional magnetic resonance imaging (fMRI), we found that values that people refused to sell (sacred values) were associated with increased activity in the left temporoparietal junction and ventrolateral prefrontal cortex, regions previously associated with semantic rule retrieval. This suggests that sacred values affect behaviour through the retrieval and processing of deontic rules and not through a utilitarian evaluation of costs and benefits.

Norms play essential roles in regulating aspects of social behavior in groups. Viewed as quasi-formal rules that can “instruct strangers and convey to children” how to behave in specific situations from a particular groups’ perspective – norms are models of (situationally) correct behaviors that ostensibly afford some benefit to the referent group (Brown, 1995) and are found in virtually all human societies (Eibl-Eibesfeldt, 1989). Norms, as opposed to laws, are often unwritten and generally do not emerge through an explicit democratic or other formal governing mechanisms. When interpreted as guiding standard rules of behavior within an organization, norms influence much of organizational decision making (March 1996). Furthermore, we assert that norms not only can be components of routines, but routines themselves; however, this norms as routines assertion is nonsymmetric. Norms can be viewed as routines, but not all routines can be viewed as norms, thus leaving an interesting relation on the table: some routines can be viewed as norms. It is that residual class in which we address our work – routines as norms – routines that serve the function of norms in an organizational setting.

This paper describes the implementation plans and research activities of Project Ensayo, which is developing a virtual emergency operations center (vEOC) based on one of the Nation's premier EOC 's, that of Miami-Dade County. The goal of the EOC is to coordinate for 'community continuity', in other words help communities remain resilient in the face of disaster events. Organizations of this sort suffer from the lack of normal conditions that permit organizational learning in the traditional sense. The development of the Ensayo vEOC will support a portfolio of research projects including topics related to sensor data, knowledge and social networking modeling, decision-making, software approaches to commitment-based collaboration and coordination, time-critical negotiations under emergencies, and cyber-infrastructure resources.

We extend March’s model of exploration and exploitation to consider how environmental turbulence impacts organizational knowledge in hierarchies of varying size and depth. We then evaluate additional effects of a knowledge management (KM) system that collects and shares knowledge from expert individuals in an organization. We find that in the absence of personnel turnover, a management strategy of high exploitation and low exploration for a multi-tier hierarchical organization, representative of a “top-down” knowledge management strategy, reduces the accuracy of average individual knowledge levels compared to alternative strategies. The magnitude of this reduction in accuracy increases as the number of tiers in a hierarchical organization increase. Managers operating in a flat organization will see less of a reduction compared to a multi-tier organization. Two weighted-least-squares regressions performed on two additional data sets corroborate this central observation: a “bottom-up” strategy demonstrates greater resiliency to environmental turbulence than a “top-down” knowledge management strategy for hierarchical organizations.

A problem arising out of group decision support research is to develop a method to specify and represent the important phenomena comprising the events of the participants (humans and machines). The authors propose a solution in the form of a computational model of group problem solving derived from a view of individual problem solving. They view group problem solvers from the perspective of their capacities to function as intelligent agents; that is, they may be either humans or machines. They argue that the group tasks in which such intelligent agents engage, such as 'negotiation' or 'decision making', are actually specific forms of problem solving, and that the cognitive mechanisms underlying 'group problem solving' are precisely the same as those comprising individual problem solving. One mechanism central to the model is that of learning; therefore, the authors discuss the role learning plays in group communication and coordination. In order to test one aspect of the group model, they conducted an experiment in knowledge sharing among an assemblage of artificial-intelligence scheduling agents. The results indicate that knowledge sharing can be quite beneficial, but that the effects vary according to specific task environment experiences. >