A fuzzy-based decision model application on strategic management

In this article, the objective is to demonstrate the effects of different decision styles on strategic decisions and likewise, on an organization. The technique that was presented in the study is based on the transformation of linguistic variables to numerical value intervals. In this model, the study benefits from fuzzy logic methodology and fuzzy numbers. This fuzzy methodology approach allows us to examine the relations between decision making styles and strategic management processes when there is uncertainty. The purpose is to provide results to companies that may help them to exercise the most appropriate decision making style for its different strategic management processes. The study is leaving more research topics for further studies that may be applied to other decision making areas within the strategic management process.

A new aggregation method for strategic decision making and its application in assignment theory

A new aggregation method for decision making is presented by using induced aggregation operators and the index of maximum and minimum level. Its main advantage is that it can assess complex reordering processes in the aggregation that represent complex attitudinal characters of the decision maker such as psychological or personal factors. A wide range of properties and particular cases of this new approach are studied. A further generalization by using hybrid averages and immediate weights is also presented. The key issue in this approach against the previous model is that we can use the weighted average and the ordered weighted average in the same formulation. Thus, we are able to consider the subjective attitude and the degree of optimism of the decision maker in the decision process. The paper ends with an application in a decision making problem based on the use of the assignment theory.

Ag Decision Maker, May 2014, Vol. 18, no. 7

A Business Newsletter for Agriculture

Ag Decision Maker, June 2014, Vol. 18, no. 8

A Business Newsletter for Agriculture

Ag Decision Maker, July 2014, Vol. 18, no. 9

A Business Newsletter for Agriculture

Identification of Conifer Trees in Iowa, September 22, 1998

This publication is designed to help identify the most common trees found in Iowa. It is based on vegetative characteristics including leaves, fruit, and bark. It is neither complete nor without possible oversights. Separate species are grouped by similar characteristics, mainly based on type and arrangement of leaves. These groups are; awl- or scale like needles; single needles, flattened with rounded tips; single needles, square in cross section, with pointed tips; and needles in bundles or fascicles of two or more. Remember, vegetative characteristics are quite variable; use more than one specimen for comparison.

Identification of Hardwood Trees in Iowa, September 1998

This publication is designed to help identify the most common hardwood or deciduous trees found in Iowa. It is based on vegetative characteristics including leaves, fruit, and bark. It is neither complete nor without possible oversights. Separate species are grouped by similar characteristics, mainly based on type and arrangement of leaves. Remember, vegetative characteristics are quite variable; use more than one specimen for comparison.

20 Native Trees to Plant, January 25, 2010

If you have ever flown in an airplane over Iowa, you would see that our woodlands are scattered along the rivers and streams and areas too steep to farm. You would also see a green carpet of trees within out cities and towns. Did you know the 90% of the over 2.7 million acres of forest in Iowa is owned by over 138,000 different private owners? Or that 30% of the land cover in a typical Iowa community if covered by trees? Trees are vital for the protection of our drinking water supply, critical for wildlife habitat, and help sustain employment of over 7,000 Iowans in the wood products industry. This booklet "20 Native trees to Plant" will help you gain a greater knowledge about Iowa's trees and forests. Learn about and enjoy Iowa's trees. Consider ways that you can improve our environment by planting and caring for Iowa's trees and forests.

Plant Trees with help from CRP, February 4, 2010

It's a fact. Landowners like the five couples featured in the publication have helped replant Iowa. In fact, Iowa's forests and dwindled from an original 7 million acres to only 1.4 million acres in 1974. The state now has 2.8 million acres, surpassing the acreage of woodlands more than a century ago.

Ag Decision Maker, August 2014, Vol. 18, no. 10

A Business Newsletter for Agriculture

Predictive analysis and mapping of indoor radon concentrations in Switzerland

It is estimated that around 230 people die each year due to radon (222Rn) exposure in Switzerland. 222Rn occurs mainly in closed environments like buildings and originates primarily from the subjacent ground. Therefore it depends strongly on geology and shows substantial regional variations. Correct identification of these regional variations would lead to substantial reduction of 222Rn exposure of the population based on appropriate construction of new and mitigation of already existing buildings. Prediction of indoor 222Rn concentrations (IRC) and identification of 222Rn prone areas is however difficult since IRC depend on a variety of different variables like building characteristics, meteorology, geology and anthropogenic factors. The present work aims at the development of predictive models and the understanding of IRC in Switzerland, taking into account a maximum of information in order to minimize the prediction uncertainty. The predictive maps will be used as a decision-support tool for 222Rn risk management. The construction of these models is based on different data-driven statistical methods, in combination with geographical information systems (GIS). In a first phase we performed univariate analysis of IRC for different variables, namely the detector type, building category, foundation, year of construction, the average outdoor temperature during measurement, altitude and lithology. All variables showed significant associations to IRC. Buildings constructed after 1900 showed significantly lower IRC compared to earlier constructions. We observed a further drop of IRC after 1970. In addition to that, we found an association of IRC with altitude. With regard to lithology, we observed the lowest IRC in sedimentary rocks (excluding carbonates) and sediments and the highest IRC in the Jura carbonates and igneous rock. The IRC data was systematically analyzed for potential bias due to spatially unbalanced sampling of measurements. In order to facilitate the modeling and the interpretation of the influence of geology on IRC, we developed an algorithm based on k-medoids clustering which permits to define coherent geological classes in terms of IRC. We performed a soil gas 222Rn concentration (SRC) measurement campaign in order to determine the predictive power of SRC with respect to IRC. We found that the use of SRC is limited for IRC prediction. The second part of the project was dedicated to predictive mapping of IRC using models which take into account the multidimensionality of the process of 222Rn entry into buildings. We used kernel regression and ensemble regression tree for this purpose. We could explain up to 33% of the variance of the log transformed IRC all over Switzerland. This is a good performance compared to former attempts of IRC modeling in Switzerland. As predictor variables we considered geographical coordinates, altitude, outdoor temperature, building type, foundation, year of construction and detector type. Ensemble regression trees like random forests allow to determine the role of each IRC predictor in a multidimensional setting. We found spatial information like geology, altitude and coordinates to have stronger influences on IRC than building related variables like foundation type, building type and year of construction. Based on kernel estimation we developed an approach to determine the local probability of IRC to exceed 300 Bq/m3. In addition to that we developed a confidence index in order to provide an estimate of uncertainty of the map. All methods allow an easy creation of tailor-made maps for different building characteristics. Our work is an essential step towards a 222Rn risk assessment which accounts at the same time for different architectural situations as well as geological and geographical conditions. For the communication of 222Rn hazard to the population we recommend to make use of the probability map based on kernel estimation. The communication of 222Rn hazard could for example be implemented via a web interface where the users specify the characteristics and coordinates of their home in order to obtain the probability to be above a given IRC with a corresponding index of confidence. Taking into account the health effects of 222Rn, our results have the potential to substantially improve the estimation of the effective dose from 222Rn delivered to the Swiss population.

Ag Decision Maker, September 2014, Vol. 18, no. 11

A Business Newsletter for Agriculture

You are not alone...making an informed decision about your pregnancy, January 1997

When you are faced with a difficult decision, it’s not unusual to feel confused, frustrated, and perhaps a little frightened because you are not sure what to expect or where to turn for answers. The purpose of this handbook is to assist you in making an informed choice about your pregnancy.

Ag Decision Maker, Novmeber 2014, Vol. 19, no. 1

A Business Newsletter for Agriculture

Ag Decision Maker, October 2014, Vol. 18, no. 12

A Business Newsletter for Agriculture