Strategic-decision quality in public organizations : an information processing perspective

This study draws on information processing theory to investigate predictors of strategic-decision quality in public organizations. Information processing theory argues that (a) rational planning practices contribute to strategic-decision quality by injecting information into decision-making and (b) decision-makers contribute to strategic-decision quality by exchanging information during decision-making. These assumptions are tested upon fifty-five Flemish pupil guidance centers. Rational planning practices are operationalized as strategic planning, performance measurement and performance management. Information exchange by decision-makers during decision-making is operationalized as procedural justice of the decision-making process. Results suggest that procedural justice, strategic planning and performance management contribute to strategic-decision quality while performance measurement does not

Decision making and quality-of-information

Springer - Series Advances in Intelligent and Soft Computing, vol. 73In Group Decision Making based on argumentation, decisions are made considering the diverse points of view of the different partakers in order to decide which course of action a group should follow. However, knowledge and belief are normally incomplete, contradictory, or error sensitive, being desirable to use formal tools to deal with the problems that arise from the use of uncertain and even not precise information. On the other hand, qualitative models and qualitative reasoning have been around in Artificial Intelligence research for some time, in particular due the growing need to offer support in decision-making processes, a problem that in this work will be addressed in terms of an extension to the logic programming language and based on an evaluation of the Quality-of-Information (QoI) that stems out from those extended logic programs or theories. We present a computational model to address the problem of decision making, in terms of a multitude of scenarios, also defined as logic programs or theories, where the more appropriate ones stand for the higher QoIs values

Ambiguity in multicriteria quality decisions.

Quality is becoming an issue of increasing strategic importance in business. The aim of this paper is to analyze quality from a decision-making perspective. Quality decisions are characterized by their ambiguity while their evaluation uses a multicriteria viewpoint. Fuzzy decision theory provides a conceptual framework to model decisions with these features. It enables the decision maker to add his/her own experience and any other type of information to that obtained from hard figures. This theory is applied to a set of quality decision alternatives which are evaluated using different criteria such as their impact on fixed costs, cost of quality, leadtime and flexibility. The approach provided in this paper can be extended to other quality decisions.Quality decision-making; Quality dimensions; Fuzzy multicriteria decision making;

Factors affecting decision making effectiveness in Palestinian Banks

This study investigated the influence of information quality on decision-making effectiveness among Palestinian bank managers. Previous studies revealed the importance of information quality on decision-making effectiveness in different fields of management. Organisational structure was found to moderate information quality and decision-making effectiveness in different fields of management. However, the moderating effect of organisational structure on the relationship between information quality on decision-making effectiveness had not been addressed in the banking sector in Palestine. This cross-sectional quantitative study examined the relationship between information quality and decision-making effectiveness as being moderated by organisational structure. A total of 146 managers were surveyed in which they were required to respond to 55 items that elicited the three variables. Information quality was represented by six dimensions, organisational structure three dimensions, and decision-making effectiveness three dimensions. The data were analysed by SPSS and PLS-SEM software. The findings indicated the relevance and importance of information quality dimensions to decision-making effectiveness in the banking sector of Palestine. The result revealed four dimensions of information quality, namely, accuracy, completeness, relevancy and interpretability had a significant relationship with decision-making effectiveness. Two dimensions of organisational structure, namely, formality and centralisation, significantly moderated the relationship between information quality and decision-making effectiveness while complexity did not show a moderating effect. Overall, this study extends the understanding of the decision- making effectiveness. It contributes to building the model of the relationship between information quality and decision-making effectiveness in the banking industry. These findings will benefit bank managers in Palestine to understand the role of information quality better and utilise it towards developing sustainable banking services in Palestine

MANAGING KNOWLEDGE AND DATA FOR A BETTER DECISION IN PUBLIC ADMINISTRATION

In the current context, the society is dominated by the rapid development of computer networks and the integration of services and facilities offered by the Internet environment at the organizational level. The success of an organization depends largely on the quality and quantity of information it has available to develop quickly decisions able to meet the current needs. The need for a collaborative environment within the central administration leads to the unification of resources and instruments around the Center of Government, to increase both the quality and efficiency of decision - making, especially reducing the time spent with decision - making, and upgrading the decision – making act.administration, strategy, decision, complex systems, management, infrastructure, e-government, information society, government platform.

Strategic-Decision Quality in Public Organizations: An Information Processing Perspective.

This study draws on information processing theory to investigate predictors of strategic-decision quality in public organizations. Information processing theory argues that (a) rational planning practices contribute to strategic-decision quality by injecting information into decision making and (b) decision makers contribute to strategic-decision quality by exchanging information during decision making. These assumptions are tested upon 55 Flemish pupil guidance centers. Rational planning practices are operationalized as strategic planning, performance measurement, and performance management. Information exchange by decision makers during decision making is operationalized as procedural justice of the decision-making process. Results suggest that procedural justice, strategic planning, and performance management contribute to strategic-decision quality while performance measurement does not

The Predictive Approach to Teaching Statistics.

Statistics is commonly taught as a set of techniques to aid in decision making, by extracting information from data. It is argued here that the underlying purpose, often implicit rather than explicit, of every statistical analysis is to establish a set of probability models which can be used to predict values of one or more variables. Such a model constitutes 'information' only in the sense, and to the extent, that it provides predictions of sufficient quality to be useful for decision making. The quality of the decision making is determined by the quality of the predictions, and hence by that of the models used. Using natural criteria, the 'best predictions' for nominal and numeric variables are respectively the mode and mean. For a nominal variable, the quality of a prediction is measured by the probability of error; for a numeric variable, it is specified using a prediction interval. Presenting statistical analysis in this way provides students with a clearer understanding of what a statistical analysis is, and its role in decision making.Statistics, teaching, prediction, probability model, prediction interval.

Participation of patients in decisions about treatment for cancer

The primary aim of treatment for cancer is to improve the quality of life of patients by curing them or producing a long and worthwhile remission and ameliorating their worst symptoms. For many types of cancers, however, the most appropriate management is not always clear or based on the best evidence from well conducted randomised controlled trials. Clinicians may have more than one therapeutic option to offer patients and there are many calls for more involvement of patients in decision making about their treatment. Two fundamental issues should be determined when discussing treatment choices with patients—their own preferences about the amount and type of information that is needed and their actual rather than perceived desire for participation in decision making. A clear distinction needs to be made between a desire for information and a wish to assume responsibility for decision making. They are not one and the same thing. In one study of women with breast cancer, improvements in quality of life brought about by reduced anxiety and depression and better adjustment were primarily related to satisfaction with information they got, not merely involvement with decision making about the type of surgery.1 Many studies have shown that patients want much more information than their doctors believe they do.2 We also know that the ability of doctors to predict which patients want an active, shared, or passive role in decision making is very poor in palliative care and when active, potentially curative treatment is discussed. 3 4 Patients' preferences about choice of treatment are poorly understood and usually based on intuitive assumptions about their perceived intelligence, age, or quality of life. This problem is not confined to the United Kingdom, although the poor ratio of oncologists to patients does mean that good patient centred communication about choices available and their consequences is easily omitted in busy clinics. We await with interest more results from the study to understand prognoses and preferences for outcomes and risks of treatments from the United States.5 The choices of treatment put before patients should involve an adequate and objective appraisal of information, delivered in a patient centred manner backed by information booklets, audio and video tapes, and references to good websites such as those provided by CancerBACUP, the new National electronic Library for Health (NeLH), and the DIPEx database.6-8 Unfortunately even when evidence concerning improved survival or disease free intervals exists, data on quality of life are either missing, sketchy, or not well integrated into the analysis of overall benefit. There is some evidence that doctors do not collect accurate information about symptoms that affect quality of life; consequently patients may be agreeing to different treatments without being aware of their side effects.9 Further, doctors admit to having difficulty integrating the results from formal assessment of quality of life by questionnaires into clinical management, preferring to rely on their own clinical impressions about tolerability or impact of side effects.10 Arguably in some situations, including adjuvant therapy and palliation, these quality of life parameters might be the most important areas of information that a patient requires about likely benefit before consenting to treatment. Patients cannot participate in decision making to their desired extent unless they have the right types of information, given in ways optimal for their own level of understanding. There is a compelling need for training and other interventions to help communication between doctors and patients about the likely and preferred therapeutic goals and priorities of treatment. True patient participation, which may include an expressed preference by the patient to assume a more passive role about the type of information they require, and involvement in decision making is, for most, an unachievable goal unless we see some real improvements in the current system of healthcare delivery. Too many patients are being seen by too few doctors in over burdened clinics with inadequate support staff for meeting adequately the individual information needs of patients with cancer

Factors Influencing the Quality of Decision-Making Using Business Intelligence in a Metal Rolling Plant in KwaZulu-Natal

The current study sought to investigate the factors which influence the quality of decision-making using business intelligence (BI) in a metal rolling plant in KwaZulu-Natal. Specifically, the study was focused on information quality, system quality and BI service quality. The study used a self-administered survey sent out to participants having sufficient report runs which made up the population of the study. The collected data came from different levels of employees, namely; managers (47%) and non-managers (53%) with varying levels of BI experience, and the data was imported into SPSS for analysis. The results showed that information quality had a positive significant impact on the quality of decision-making; system quality had a positive significant impact on the quality of decision-making; and BI service quality had a positive significant impact on the quality of decision-making. Multiple linear regression analysis was conducted to determine the strength of these variances in influencing decision-making. It was found that the three variables explained 65.7% of the variance in the quality of decision-making. Overall, the study found that high quality information, coupled with a high-quality system and good BI service, leads to a higher quality of decision-making, and that the impact of BI on decision-making is positive. The study recommends that the company implement data quality management focusing on data cleansing, it should also implement more sophisticated analysis techniques to get insights and have strategies to upskill both technical and business workers