An examination of intuition in strategic decision-making:the role of context

Intuition is a vitally important concept in strategic decision making research because it enables decision-makers to rapidly detect patterns in dynamic environments in order to cope with the time-pressured, ill-structured and non-routine nature of strategic decision-making. Despite a growing body of conceptual literature emphasising the importance of intuition in strategic decision-making; there has been very little development of theory explaining the contextual factors that cause intuition to be used in the strategic decision-making process. This paper demonstrates that by integrating different contextual variables a clear understanding of the influences on the use of intuition in strategic decision-making can be developed. This article develops an integrative theoretical model together with testable research propositions, which if empirically examined, would make a substantial contribution to knowledge.

The influence of patient's age on clinical decision-making about coronary heart disease in the USA and the UK

This paper examines UK and US primary care doctors' decision-making about older (aged 75 years) and midlife (aged 55 years) patients presenting with coronary heart disease (CHD). Using an analytic approach based on conceptualising clinical decision-making as a classification process, it explores the ways in which doctors' cognitive processes contribute to ageism in health-care at three key decision points during consultations. In each country, 56 randomly selected doctors were shown videotaped vignettes of actors portraying patients with CHD. The patients' ages (55 or 75 years), gender, ethnicity and social class were varied systematically. During the interviews, doctors gave free-recall accounts of their decision-making. The results do not establish that there was substantial ageism in the doctors' decisions, but rather suggest that diagnostic processes pay insufficient attention to the significance of older patients' age and its association with the likelihood of co-morbidity and atypical disease presentations. The doctors also demonstrated more limited use of 'knowledge structures' when diagnosing older than midlife patients. With respect to interventions, differences in the national health-care systems rather than patients' age accounted for the differences in doctors' decisions. US doctors were significantly more concerned about the potential for adverse outcomes if important diagnoses were untreated, while UK general practitioners cited greater difficulty in accessing diagnostic tests.

Classifying clinical decision making:interpreting nursing intuition, heuristics and medical diagnosis

This is the second of two linked papers exploring decision making in nursing. The first paper, 'Classifying clinical decision making: a unifying approach' investigated difficulties with applying a range of decision-making theories to nursing practice. This is due to the diversity of terminology and theoretical concepts used, which militate against nurses being able to compare the outcomes of decisions analysed within different frameworks. It is therefore problematic for nurses to assess how good their decisions are, and where improvements can be made. However, despite the range of nomenclature, it was argued that there are underlying similarities between all theories of decision processes and that these should be exposed through integration within a single explanatory framework. A proposed solution was to use a general model of psychological classification to clarify and compare terms, concepts and processes identified across the different theories. The unifying framework of classification was described and this paper operationalizes it to demonstrate how different approaches to clinical decision making can be re-interpreted as classification behaviour. Particular attention is focused on classification in nursing, and on re-evaluating heuristic reasoning, which has been particularly prone to theoretical and terminological confusion. Demonstrating similarities in how different disciplines make decisions should promote improved multidisciplinary collaboration and a weakening of clinical elitism, thereby enhancing organizational effectiveness in health care and nurses' professional status. This is particularly important as nurses' roles continue to expand to embrace elements of managerial, medical and therapeutic work. Analysing nurses' decisions as classification behaviour will also enhance clinical effectiveness, and assist in making nurses' expertise more visible. In addition, the classification framework explodes the myth that intuition, traditionally associated with nurses' decision making, is less rational and scientific than other approaches.

Interactive data and retail investor decision-making:an experimental study

The results of an experimental study of retail investors' use of eXtensible Business Reporting Language tagged (interactive) data and PDF format for making investment decisions are reported. The main finding is that data format made no difference to participants' ability to locate and integrate information from statement footnotes to improve investment decisions. Interactive data were perceived by participants as quick and 'accurate', but it failed to facilitate the identification of the adjustment needed to make the ratios accurate for comparison. An important implication is that regulators and software designers should work to reduce user reliance on the comparability of ratios generated automatically using interactive data.

Unsupervised KDD to creatively support managers' decision making with fuzzy association rules:a distribution channel application

To be competitive in contemporary turbulent environments, firms must be capable of processing huge amounts of information, and effectively convert it into actionable knowledge. This is particularly the case in the marketing context, where problems are also usually highly complex, unstructured and ill-defined. In recent years, the development of marketing management support systems has paralleled this evolution in informational problems faced by managers, leading to a growth in the study (and use) of artificial intelligence and soft computing methodologies. Here, we present and implement a novel intelligent system that incorporates fuzzy logic and genetic algorithms to operate in an unsupervised manner. This approach allows the discovery of interesting association rules, which can be linguistically interpreted, in large scale databases (KDD or Knowledge Discovery in Databases.) We then demonstrate its application to a distribution channel problem. It is shown how the proposed system is able to return a number of novel and potentially-interesting associations among variables. Thus, it is argued that our method has significant potential to improve the analysis of marketing and business databases in practice, especially in non-programmed decisional scenarios, as well as to assist scholarly researchers in their exploratory analysis. © 2013 Elsevier Inc.

Understanding dynamics of strategic decision-making in venture creation:a process study of effectuation and causation

This study draws upon effectuation and causation as examples of planning-based and flexible decision-making logics, and investigates dynamics in the use of both logics. The study applies a longitudinal process research approach to investigate strategic decision-making in new venture creation over time. Combining qualitative and quantitative methods, we analyze 385 decision events across nine technology-based ventures. Our observations suggest a hybrid perspective on strategic decision-making, demonstrating how effectuation and causation logics are combined, and how entrepreneurs’ emphasis on these logics shifts and re-shifts over time. We induce a dynamic model which extends the literature on strategic decision-making in venture creation.

Mental health pharmacists views on shared decision-making for antipsychotics in serious mental illness

Background People diagnosed with serious mental illnesses (SMIs) such as schizophrenia and bipolar affective disorder are frequently treated with antipsychotics. National guidance advises the use of shared decision-making (SDM) in antipsychotic prescribing. There is currently little data on the opinions of health professionals on the role of SDM. Objective To explore the views and experiences of UK mental health pharmacists regarding the use of SDM in antipsychotic prescribing in people diagnosed with SMI. Setting The study was conducted by interviewing secondary care mental health pharmacists in the UK to obtain qualitative data. Methods Semi-structured interviews were recorded. An inductive thematic analysis was conducted using the method of constant comparison. Main outcome measure Themes evolving from mental health pharmacists on SDM in relation to antipsychotic prescribing in people with SMI. Results Thirteen mental health pharmacists were interviewed. SDM was perceived to be linked to positive clinical outcomes including adherence, service user satisfaction and improved therapeutic relations. Despite more prescribers and service users supporting SDM, it was not seen as being practised as widely as it could be; this was attributed to a number of barriers, most predominantly issues surrounding service user’s lacking capacity to engage in SDM and time pressures on clinical staff. The need for greater effort to work around the issues, engage service users and adopt a more inter-professional approach was conveyed. Conclusion The mental health pharmacists support SDM for antipsychotic prescribing, believing that it improves outcomes. However, barriers are seen to limit implementation. More research is needed into overcoming the barriers and measuring the benefits of SDM, along with exploring a more inter-professional approach to SDM.