Value Of Information In Decision Research Articles

Value of Information for Decision Making under Uncertainty

Value of Information for Decision Making under Uncertainty

Individual empowerment of agile and non-agile software developers in small teams

ContextEmpowerment of employees at work has been known to have a positive impact on job motivation and satisfaction. Software development is a field of knowledge work wherein one should also expect to see these effects, and the idea of empowerment has become particularly visible in agile methodologies, in which proponents emphasise team empowerment and individual control of the work activities as a central concern. ObjectiveThis research aims to get a better understanding of how empowerment is enabled in software development teams, both agile and non-agile, to identify differences in empowering practices and levels of individual empowerment. MethodTwenty-five interviews with agile and non-agile developers from Norway and Canada on decision making and empowerment are analysed. The analysis is conducted using a conceptual model with categories for involvement, structural empowerment and psychological empowerment. ResultsBoth kinds of development organisations are highly empowered and they are similar in most aspects relating to empowerment. However, there is a distinction in the sense that agile developers have more possibilities to select work tasks and influence the priorities in a development project due to team empowerment. Agile developers seem to put a higher emphasis on the value of information in decision making, and have more prescribed activities to enable low-cost information flow. More power is obtained through the achievement of managing roles for the non-agile developers who show interest and are rich in initiatives. ConclusionAgile developers have a higher sense of being able to impact the organisation than non-agile developers and have information channels that is significantly differently from non-agile developers. For non-agile teams, higher empowerment can be obtained by systematically applying low-cost participative decision making practices in the manager–developer relation and among peer developers. For agile teams, it is essential to more rigorously follow the empowering practices already established.

The role of automatic identification (Auto ID) in the computer integrated manufacturing (CIM) architecture

Time availability of manufacturing information in the right place and in a usable format has a direct bearing on how organization resources are used to effect the required value-added activities on a product to impart economic value to the end product. The CIM architecture provides a definition and structure to tail or the knowledge base for easy access and utilization to accomplish organizational goals. Most organizations have pockets of localized information domains stemming from individual or group innovativeness in their efforts to overcome obstacles in any given project. Unfortunately, most of this information is not tapped and further disseminated for use at a later time to solve similar problems. There is thus a need, within the CIM architecture construct, for complete and flexible information flow, capturing the procedures for each task. Once capture, timely distribution is required to enable decisions to be made based on up-to-date information. A number of Automatic identification (Auto ID) technologies exist to aid in dealing with informtion capture and dissemination in an automated manufacturing environment, and thus facilitate implementation of the CIM architecture, to address the time value of information in decision making. This paper will examine how Auto ID technologies such as bar code technology, radio frequency technologies and others fit into the structure of CIM architecture, to provide the informational relationships in an organization to link at the facets of the CIM architecture, and provide the knowledge required for the organization to be competitively productive.

Taxonomy for surveying the use and value of geographical information!

Abstract Understanding the use and value of geographical information in decision making has been identified as crucial to the further development of geographical information systems and related spatial analysis techniques. Research into the use of geographical information will be through surveys and case studies. A taxonomy for investigating the use of geographical information and its associated value is needed to structure the surveys and case studies. This paper presents an initial attempt at such a taxonomy, intended to support continuing research into the use and value of geographical information. The survey methodology to be supported will be mostly telephone and/or mail questionnaires, and this has influenced the structure of the taxonomy. The goal of this work is to create a taxonomy suitable for use in surveys that will enhance the understanding of the use and value of geographical information in decision making.

The value of information in decision making

This paper reports upon an experiment conducted to test a normative model of information evaluation as a descriptive representation of human behavior in judging the value of information. The test was conducted under a more general set of assumptions than those used in previous research. Subjects judged the maximum amount that they would be willing to pay for a single marble drawn from one of two urns containing many black and white marbles. Five levels of priors and accuracy of the information source, and three types of decision maker models were experimentally manipulated. The results confirm previous research which has suggested that normative models are not appropriate descriptive representations of information evaluation behavior. Among alternative models tested, observed behavior was best represented by one containing a multiplicative rule to combine the subjective levels of accuracy, priors, and type of decision maker, and an averaging rule to combine the manipulated factors.

Value of information for decisions

Information that will reduce the risk of a decision may be costly in time, effort, or money. The maximum amount that should be invested in the information—its fair cost—depends upon payoffs, the diagnosticity of the data source, and prior probabilities of the hypotheses. These are the independent variables of this experiment. Subjects estimated the fair costs by means of the Marschak bidding procedure. The subjects' bids changed in the direction appropriate to each of the three independent variables, but not enough to be optimal.