797 resultados para Conversion decision-making
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Despite concerted academic interest in the strategic decision-making process (SDMP) since the 1980s, a coherent body of theory capable of guiding practice has not materialised. This is because many prior studies focus only on a single process characteristic, often rationality or comprehensiveness, and have paid insufficient attention to context. To further develop theory, research is required which examines: (i) the influence of context from multiple theoretical perspectives (e.g. upper echelons, environmental determinism); (ii) different process characteristics from both synoptic formal (e.g. rationality) and political incremental (e.g. politics) perspectives, and; (iii) the effects of context and process characteristics on a range of SDMP outcomes. Using data from 30 interviews and 357 questionnaires, this thesis addresses several opportunities for theory development by testing an integrative model which incorporates: (i) five SDMP characteristics representing both synoptic formal (procedural rationality, comprehensiveness, and behavioural integration) and political incremental (intuition, and political behaviour) perspectives; (ii) four SDMP outcome variables—strategic decision (SD) quality, implementation success, commitment, and SD speed, and; (iii) contextual variables from the four theoretical perspectives—upper echelons, SD-specific characteristics, environmental determinism, and firm characteristics. The present study makes several substantial and original contributions to knowledge. First, it provides empirical evidence of the contextual boundary conditions under which intuition and political behaviour positively influence SDMP outcomes. Second, it establishes the predominance of the upper echelons perspective; with TMT variables explaining significantly more variance in SDMP characteristics than SD specific characteristics, the external environment, and firm characteristics. A newly developed measure of top management team expertise also demonstrates highly significant direct and indirect effects on the SDMP. Finally, it is evident that SDMP characteristics and contextual variables influence a number of SDMP outcomes, not just overall SD quality, but also implementation success, commitment, and SD speed.
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The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.
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Strategic decision making (SDM) in a small business is an informal, highly personalised cognitive process which is emergent in nature. SDM determines the extent to which decision makers generate innovative decision-making options, and is therefore critical in order for small businesses to achieve strategic flexibility to enable strategic adaptation to turbulent environments. By examining SDM in small businesses, this research has the potential to address a major criticism of the extant literature in that it has been pre-occupied with measuring the formality of strategic planning and has neglected the informal, highly personalised and cognitive nature of strategic decision making in a small businesses.
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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.
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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.
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This is the first of two linked papers exploring decision making in nursing which integrate research evidence from different clinical and academic disciplines. Currently there are many decision-making theories, each with their own distinctive concepts and terminology, and there is a tendency for separate disciplines to view their own decision-making processes as unique. Identifying good nursing decisions and where improvements can be made is therefore problematic, and this can undermine clinical and organizational effectiveness, as well as nurses' professional status. Within the unifying framework of psychological classification, the overall aim of the two papers is to clarify and compare terms, concepts and processes identified in a diversity of decision-making theories, and to demonstrate their underlying similarities. It is argued that the range of explanations used across disciplines can usefully be re-conceptualized as classification behaviour. This paper explores problems arising from multiple theories of decision making being applied to separate clinical disciplines. Attention is given to detrimental effects on nursing practice within the context of multidisciplinary health-care organizations and the changing role of nurses. The different theories are outlined and difficulties in applying them to nursing decisions highlighted. An alternative approach based on a general model of classification is then presented in detail to introduce its terminology and the unifying framework for interpreting all types of decisions. The classification model is used to provide the context for relating alternative philosophical approaches and to define decision-making activities common to all clinical domains. This may benefit nurses by improving multidisciplinary collaboration and weakening clinical elitism.
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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.
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This paper explores differences in how primary care doctors process the clinical presentation of depression by African American and African-Caribbean patients compared with white patients in the US and the UK. The aim is to gain a better understanding of possible pathways by which racial disparities arise in depression care. One hundred and eight doctors described their thought processes after viewing video recorded simulated patients presenting with identical symptoms strongly suggestive of depression. These descriptions were analysed using the CliniClass system, which captures information about micro-components of clinical decision making and permits a systematic, structured and detailed analysis of how doctors arrive at diagnostic, intervention and management decisions. Video recordings of actors portraying black (both African American and African-Caribbean) and white (both White American and White British) male and female patients (aged 55 years and 75 years) were presented to doctors randomly selected from the Massachusetts Medical Society list and from Surrey/South West London and West Midlands National Health Service lists, stratified by country (US v.UK), gender, and years of clinical experience (less v. very experienced). Findings demonstrated little evidence of bias affecting doctors' decision making processes, with the exception of less attention being paid to the potential outcomes associated with different treatment options for African American compared with White American patients in the US. Instead, findings suggest greater clinical uncertainty in diagnosing depression amongst black compared with white patients, particularly in the UK. This was evident in more potential diagnoses. There was also a tendency for doctors in both countries to focus more on black patients' physical rather than psychological symptoms and to identify endocrine problems, most often diabetes, as a presenting complaint for them. This suggests that doctors in both countries have a less well developed mental model of depression for black compared with white patients. © 2014 The Authors.
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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.
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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.
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the article views examine the problems concerning with the sources of origin of unconscious the inner personal conflicts and the way the presence of this factor is reflected on the decision-making process by a person.