Passenger emergency evacuation from bus carriage: Results from realistic data and modeling simulations

One of critical challenges in the development of pedestrian models is the lack of relevant data under emergency conditions. In this paper, we reveal several behavior characteristics of passenger emergency evacuation from a burning bus carriage, by observing and analyzing a video recording, attempting to close the gap between practical observation and theoretical modeling. The analysis results show that there are considerable differences between real emergency evacuation and experimental normal evacuation with respect to the cumulative flows, flows, and time gap distributions. Additionally, the behavior of falling-down, which contributes to the formation of movable obstacles, interrupts the continuity of the evacuation process. Then, we incorporate these behavioral characteristics into a microscopic pedestrian model with a fine lattice space representation. The simulation results indicate that the escape is slowed down by the falling behavior, as well as by the luggage-carrying behavior.     

A Cognitive Interpretation of Data Analysis

This paper proposes a scientific model to explain the analysis process. We argue that data analysis is primarily a procedure to build understanding, and as such, it dovetails with the cognitive processes of the human mind. Data analysis tasks closely resemble the cognitive process known as sensemaking. We demonstrate how data analysis is a sensemaking task adapted to use quantitative data. This identification highlights a universal structure within data analysis activities and provides a foundation for a theory of data analysis. The competing tensions of cognitive compatibility and scientific rigour create a series of problems that characterise the data analysis process. These problems form a useful organising model for the data analysis task while allowing methods to remain flexible and situation dependent. The insights of this model are especially helpful for consultants, applied statisticians and teachers of data analysis.     

Board Efficiency and Internal Corporate Control Mechanisms

We analyze the interactions between internal and external control mechanisms in a framework in which the board selects the CEO and then decides whether to retain or dismiss him after observing a signal regarding his ability. The novel aspect of our paper is that we consider both the hiring and the firing of the CEO by the board. The type of board is defined by its ability to select a good CEO, so that the quality of the CEO depends on the type of board. Then, the dismissal-retention decision provides information not only on the quality of the CEO but also on the board's type. We show that the board's behavior depends on the pressure from the takeover market and on whether its type is publicly known. When the pressure from the takeover market is high and the type of board is private information, the board prefers not to dismiss the manager even if it has received a very low signal regarding his quality. Hence, our model endogenously derives a collusion between board and CEO in which the board does not fire a bad CEO. This behavior emerges as an attempt to hide the board's inability to accomplish the first task, CEO selection, by distorting the second task, the CEO retention-dismissal decision.     

Stochastic unpaced line design: Review and further experimental results

Previous design studies of unpaced assembly lines that exhibit stochastic task times indicate that an unbalanced allocation of task times results in optimal output rates. In this article, we present a comprehensive review of the previous literature on this topic and discuss the results of simulation experiments that test the bowl distribution for unbalancing unpaced lines. The simulation experiment was designed to test the bowl distribution in more realistic environments than previously tested and illustrates that a balanced line configuration is as good as or better than an unbalanced line configuration when task times are modeled with more typical values of variance.Stochastic unpaced assembly line research employs both simulation and analytical approaches to test the allocation of buffer capacity and task times to work stations. Analytical models are utilized to investigate simple line designs with exponential or Erlang task time distributions. Simulation is used for longer lines and for normal task time distributions. From the review of the previous research using both approaches, we note five major findings: 1) unbalancing task time allocation is optimal when task time variation is large; 2) unbalanced allocation of buffer storage capacity improves line output rate when task time variation is large; 3) output rate of an unpaced line decreases as the number of sequential workstations increases; 4) output rate increases as more buffer storage capacity is available; and 5) output rate decreases as the task time variation increases.Most of the previous research on unpaced lines investigated lines with few workstations and large task time variation. Empirical research by Dudley (6) suggests that variation of task times in practice is much less than variations employed in previous unpaced line studies. We present the results from simulation experiments that model longer unpaced lines with lower levels of task time variance of the magnitude that is likely to occur in practice.The results of our simulation experiments verify the benefits of using the bowl distribution for task time allocation when line lengths are short and task times experience large variance. However, when line lengths are extended or task time variation is reduced, the use of the bowl distribution for unbalancing the line degrades the line's efficiency. In these situations, the optimal task time allocation is a balanced line.Two important implications for managers follow from the results of our experiments: 1) that unpaced line output rate is relatively insensitive to moderate variations from optimal task time allocations when buffer storage is limited; and 2) that perfectly balanced line designs are optimal for most cases in practice.     

Learning by imitation

This paper introduces a learning algorithm that allows for imitation in recursive dynamic games. The Kiyotaki–Wright model of money is a well-known example of such decision environments. In this context, learning by experience has been studied before. Here, we introduce imitation as an additional channel for learning. In numerical simulations, we observe that the presence of imitation either speeds up social convergence to the theoretical Markov–Nash equilibrium or leads every agent of the same type to the same mode of suboptimal behavior. We observe an increase in the probability of convergence to equilibrium, as the incentives for optimal play become more pronounced.     

追赶企业技术创新演化四维驱动因素及作用机制——潍柴动力案例研究

将企业家认知作为外部环境影响企业创新行为的中介变量,完善了传统组织行为动力学的四维分析框架(人力资源、组织结构、技术和运作环境).在对潍坊柴油机动力股份有限公司案例分析的基础上,揭示追赶企业技术创新能力演化的四个驱动因素,印:具有先见的企业家认知是持续创新的根本动力和必要条件;适应性技术学习决定着技术追赶的知识基础;需...     

Showing or telling? Local interaction and organization of behavior

We present a choice model based on agent interaction. Interaction is modeled as face-to-face communication that takes place on a regular periodic lattice with decision-makers exchanging information only with immediate neighbors. We investigate the long-run (equilibrium) behavior of the resulting system and show that for a large range of initial conditions clustering in economic behavior emerges and persists indefinitely. Unlike many models in the literature, our model allows for the analysis of multi-option environments. Therefore, we add to existing results by deriving the equilibrium distribution of option popularity and thus, implicitly, of market shares. Additionally, the model sheds new light on the emergence of the novel behavior in societies.     

OCB and external–internal social networks: effects on individual performance and adaptation to change

In this study, we develop and test a model that links one's internal and external social network structures to his or her willingness and ability to adapt in a changing work context. Using a survey data from 371 employees working in 133 different branches of a large financial firm, we find that individual behaviors that explain task performance and individual adaptation to change are affected by a number of supportive social ties (size of the support network) with which one receives support inside and, mostly, outside the workplace. The results also show that individual performance and adaptation to change are affected by the level of workers' organizational citizenship behavior. We also identify a mediating effect exerted by the informational network structure (mostly an internal network) on the relationship between the support network (mostly an external network) and individual task performance.     

A synthesis of exact inferential results for exponential step-stress models and associated optimal accelerated life-tests

A reliability experimenter is often interested in studying the effects of extreme or varying stress factors such as load, pressure, temperature and voltage on the lifetimes of experimental units. Accelerated life-tests allow the experimenter to vary the levels of these stress factors in order to obtain information on the parameters of the lifetime distributions more rapidly than under normal operating conditions. Step-stress tests are a particular class of accelerated life-tests which allow the experimenter to change the stress levels at pre-fixed times during the life-testing experiment. One of the prominent models assumed in step-stress tests is the cumulative exposure model which connects the lifetime distribution of units at one stress level to the lifetime distributions at preceding stress levels. Under such a cumulative exposure model and the assumption that the lifetimes at different stress levels are exponentially distributed, we review in this article various developments on exact inferential methods for the model parameters based on different forms of censored data. We also describe the approximate confidence intervals based on the asymptotic properties of maximum likelihood estimators as well as the bootstrap confidence intervals, and provide some comparisons between these methods. Finally, we present some examples to illustrate all the inferential methods discussed here.     

Heuristic learning and the discovery of specialization and exchange

I develop and calibrate an agent-based model of boundedly rational, adaptive agents in a two-good production and exchange economy to replicate human-subject outcomes in the same eight-person experimental economy. To test agents’ ability to capture human behavior, I extend the model and use its output to make predictions about a second experimental environment in which the group of eight agents is slowly constructed by merging smaller groups. This environment improves human-subject performance in the specialization and exchange task, and commensurate improvement emerges for some parameterizations of the agent-based model. This iterative process yields incremental improvement of decision-level theories about economic discovery.     

What a Diverse Top Management Team Means: Testing an Integrated Model

Prior research has produced inconsistent results on the relationship between top management team (TMT) diversity and firm performance. Drawing on the information–social categorization framework, this study is designed to investigate both the mechanism and the contextual factors underlying the relationship between TMT cognitive diversity and firm performance by examining them in a unified model so as to better understand how a diverse TMT works. Based on a multi‐sourced survey of top managers from 118 Chinese firms, this study finds that team interdependence and team cohesion moderate in the linkage between TMT cognitive diversity and elaboration of task‐related information. In addition, TMT's elaboration of task‐related information mediates the interactive effects of TMT cognitive diversity and team interdependence on firm performance as well as the interactive effects of TMT cognitive diversity and team cohesion on firm performance.     

Cognitive reflection and economic order quantity inventory management: An experimental investigation

We use laboratory experiments to evaluate the effects of individuals' cognitive abilities on their behavior in a finite horizon economic order quantity model. Participants' abilities to balance intuitive judgment with cognitive deliberations are measured by the cognitive reflection test (CRT). Participants then complete a sequence of ordering decisions. Our results show that participants with higher CRT scores on average earn greater profit and choose more effective policies. However, these gaps are transitory as participants with lower CRT scores exhibit faster learning. We also show gender differences in performance do not hold when we control for individual CRT scores.     

Action variety of planners: Cognitive load and requisite variety

The complexity of planning tasks have increased over the past decade. There is relatively poor understanding what the implications are of increased task complexity in planning and scheduling operations. Previous work in the behavioral sciences have investigated the concept of cognitive load, addressing both task complexity and task workload or stress, and have concluded that decision makers tend to resort to routine action and reduce the variety in their actions with increasing complexity and workload. Alternatively, control theory suggests that a higher variety of actions is needed to deal with more complex problems. In this paper, we investigate the effects of task complexity in a chemical plant on the variety of actions deployed by the planners. The single work center resource structure and the availability of actual planning data from an MRP-application database allows us to both use field data and study a situation which is simple enough to measure the main effect. Our results suggest that increased task complexity without time pressure does indeed lead to increased action variety deployed by the planners.     

A goal orientation model of feedback-seeking behavior

Why do individuals differ in their feedback-seeking behavior, and how do these differences impact their task performance? The current article addresses these questions by developing a theoretical model using the individual difference of goal orientation (an orientation toward developing or demonstrating one's ability) as a central influence in the feedback-seeking process. Goal orientation is proposed to influence how individuals cognitively process the cost and value of feedback-seeking opportunities. These cognitions are then proposed to influence the choices made for six dimensions of feedback-seeking behavior—the frequency, type, source, method, timing, and sign preference. The argument is then made that assessment of multiple dimensions of feedback seeking, compared to the customary frequency assessment, should enhance our ability to explain the relationship of feedback-seeking behavior with outcomes such as task performance. Finally, the theoretical model is discussed as a platform for future research and as a source of guidance for the management of feedback-seeking behavior.     

The Importance of Communicating Workplace Privacy Policies

Employers today are faced with the task of managing workplace privacy, dealing with potential litigation, preserving the confidentiality of company information while protecting the rights of the employee. Since September 11, 2001, employers have faced new challenges including the implementation of new laws and the development of more sophisticated technology. As a result, workplace policies dealing with privacy must be clearly and effectively communicated to all affected workers. The objective of this survey research project was to measure the general public’s attitudes and perceptions of the communication of work place privacy policies. An emphasis was placed on the collection of real world data from multiple business and organizational environments, as opposed to data obtained in a controlled experimental setting.     

Lone wolves reciprocate less deviance: a moral identity model of abusive supervision*

Abstract

Although previous studies provide diverse perspectives on the influences of abusive supervision, the moral perspective receives little attention in the literature. We rely on social cognitive theory to present a moral identity model of abusive supervision that accounts for the influences of perceiving abusive supervision on organizational and interpersonal deviance. In particular, we propose that employee moral identity mediates the positive relations between abusive supervision, as perceived by followers, and their subsequent organizational and interpersonal deviance. We also test the extent to which lone wolf tendencies alleviate the main negative impact of abusive supervision on moral identity and the indirect effect of abusive supervision on organizational and interpersonal deviance through moral identity. More specifically, when the level of lone wolf tendencies is high, the relationship between abusive supervision and moral identity, and the magnitude of the moral identity mediating mechanism will be weaker. Using multi-wave, multiple-source data collected in China, our findings support most of our hypotheses and offer insightful theoretical directions for mistreatment, morality, and disposition research. Our moderated mediation model serves as a springboard for future research to understand the social cognitive processes that link abusive supervision and deviant behavior from the moral perspective.     

On the estimation of long tailed skewed distributions with actuarial applications

Very long tailed skewed distributions often arise in practice. In particular, we find that size-of-loss distributions in casualty insurance are mainly of this type. Compounding explains why many of these losses have approximate Pareto, generalized Pareto, Burr, and log-t distributions. An adaptation of the empirical mean residual life function helps the statistician select the correct model to fit in these cases. It is then discovered that minimum distance estimates, in particular that of Cramér-von Mises, and minimum chi-square estimates are extremely valuable and easy to use in the case of grouped data. Two substantial examples are given, one involving hurricane losses and the other dealing with malpractice claims.     

Strategic shirking in competitive labor markets: A general model of multi‐task promotion tournaments with employer learning

In a multitask, market‐based promotion tournament model, under different environments concerning employer learning about worker ability, it is shown that: (a) asymmetric learning in multitask jobs is a necessary condition for “strategic shirking” (i.e., underperforming on certain tasks to increase the promotion probability); (b) when learning becomes increasingly symmetric on one task, the effort allocated to that task could increase or decrease, but effort on the other task increases; (c) strategic shirking does not occur in equilibrium in single‐task models; and (d) promotions signal worker ability even when there is symmetric learning on one task, if learning is asymmetric on another.     

Priority-driven behaviors under the Boston mechanism

We study school choice markets where the non-strategy-proof Boston mechanism is used to assign students to schools. Inspired by previous field and experimental evidence, we analyze a type of behavior called priority-driven: students have a common ranking over the schools and then give a bonus in their submitted preferences to those schools for which they have high priority. We first prove that under this behavior, there is a unique stable and efficient matching, which is the outcome of the Boston mechanism. Second, we show that the three most prominent mechanisms on school choice (Boston, deferred acceptance, and top trading cycles) coincide when students’ submitted preferences are priority-driven. Finally, we run some computational simulations to show that the assumption of priority-driven preferences can be relaxed by introducing an idiosyncratic preference component, and our qualitative results carry over to a more general model of preferences.     

Environmental Change, Human Resources and Organizational Turnaround

Research on turnaround has largely focused on the impact of retrenchment and repositioning, and has paid less attention to the impact of changes in the task environment and human resources on recovery from decline. Moreover, all of the empirical research on turnaround has been conducted on private organizations. We develop a new model that is derived from theories of environmental and human resource effects on organizational performance. We apply this model to failing school districts in Texas, and find that turnaround is influenced by changes in the munificence and complexity of task environments, and the appointment of a new chief executive and front-line staff.