Task (project management)

About: Task (project management) is a research topic. Over the lifetime, 71123 publications have been published within this topic receiving 1155032 citations. The topic is also known as: problem.

Control: Organizational and Economic Approaches

Abstract: Organizational design often focuses on structural alternatives such as matrix, decentralization, and divisionalization. However, control variables e.g., reward structures, task characteristics, and information systems offer a more flexible approach. The purpose of this paper is to explore these control variables for organizational design. This is accomplished by integration and testing of two perspectives, organization theory and economics, notably agency theory. The resulting hypotheses link task characteristics, information systems, and business uncertainty to behavior vs. outcome based control strategy. These hypothesized linkages are examined empirically in a field study of the compensation practices for retail salespeople in 54 stores. The findings are that task programmability is strongly related to the choice of compensation package. The amount of behavioral measurement, the cost of measuring outcomes, and the uncertainty of the business also affect compensation. The findings have management implications for the design of compensation and reward packages, performance evaluation systems, and control systems, in general. Such systems should explicitly consider the task, the information system in place to measure performance, and the riskiness of the business. More programmed tasks require behavior based controls while less programmed tasks require more elaborate information systems or outcome based controls.

The Effects of Product Class Knowledge on Information Search Behavior

Abstract: The effects of prior knowledge about a product class on various characteristics of pre-purchase information search within that product class are examined. A new search task methodology is used that imposes only a limited amount of structure on the search task: subjects are not cued with a list of attributes, and the problem is not structured in a brand-by-attribute matrix. The results indicate that prior knowledge facilitates the acquisition of new information and increases search efficiency. The results also support the conceptual distinction between objective and subjective knowledge.

Ego depletion and the strength model of self-control: a meta-analysis.

Abstract: According to the strength model, self-control is a finite resource that determines capacity for effortful control over dominant responses and, once expended, leads to impaired self-control task performance, known as ego depletion. A meta-analysis of 83 studies tested the effect of ego depletion on task performance and related outcomes, alternative explanations and moderators of the effect, and additional strength model hypotheses. Results revealed a significant effect of ego depletion on self-control task performance. Significant effect sizes were found for ego depletion on effort, perceived difficulty, negative affect, subjective fatigue, and blood glucose levels. Small, nonsignificant effects were found for positive affect and self-efficacy. Moderator analyses indicated minimal variation in the effect across sphere of depleting and dependent task, frequently used depleting and dependent tasks, presentation of tasks as single or separate experiments, type of dependent measure and control condition task, and source laboratory. The effect size was moderated by depleting task duration, task presentation by the same or different experimenters, intertask interim period, dependent task complexity, and use of dependent tasks in the choice and volition and cognitive spheres. Motivational incentives, training on self-control tasks, and glucose supplementation promoted better self-control in ego-depleted samples. Expecting further acts of self-control exacerbated the effect. Findings provide preliminary support for the ego-depletion effect and strength model hypotheses. Support for motivation and fatigue as alternative explanations for ego depletion indicate a need to integrate the strength model with other theories. Findings provide impetus for future investigation testing additional hypotheses and mechanisms of the ego-depletion effect.

Learning without Forgetting

Abstract: When building a unified vision system or gradually adding new apabilities to a system, the usual assumption is that training data for all tasks is always available. However, as the number of tasks grows, storing and retraining on such data becomes infeasible. A new problem arises where we add new capabilities to a Convolutional Neural Network (CNN), but the training data for its existing capabilities are unavailable. We propose our Learning without Forgetting method, which uses only new task data to train the network while preserving the original capabilities. Our method performs favorably compared to commonly used feature extraction and fine-tuning adaption techniques and performs similarly to multitask learning that uses original task data we assume unavailable. A more surprising observation is that Learning without Forgetting may be able to replace fine-tuning with similar old and new task datasets for improved new task performance.