Intuition in strategic decision making:implications for strategic decision effectiveness

Intuition can produce effective strategic decisions because of its speed and ability to solve less-structured problems. Despite this, there are only a very small number of empirical studies that have examined intuition in the strategic decision-making process. We examine the relationship between the use of intuition in the strategic decision-making process, and strategic decision effectiveness. We propose that the expertise of the decision-maker, environmental dynamism and the characteristics of the strategic decision itself moderate the relationship between the use of intuition in the strategic decision making process, and strategic decision effectiveness. We make a significant theoretical contribution by integrating the management and social-psychology literatures in order to identify the variables that affect the relationship between the use of intuition in the strategic decision-making process, and strategic decision effectiveness. This article builds upon existing empirical research that has examined intuition in the strategic decision-making process, and reconciles some of the confounding results that have emerged. The paper presents a conceptual model and research propositions, which if empirically examined, would make a significant contribution to knowledge in the strategic decision-making domain of literature.

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.

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.

The role of intuition in the translation process:A case study

This paper explores the psychological construct of intuition and its influence in decision-making behavior. Intuition was defined by Jung (1971) as a primary mode of perception operating subconsciously. As opposed to sensing personality types who prefer concrete details, intuitive personality types prefer to acquire information by imagining possibilities (Myers and Myers 1995). In this paper, an analysis of verbalization data from a translation process study is discussed in order to demonstrate the influence of intuition on decision-making during the translation process and to explore the implications of this influence. Recent studies have found that intuition plays a role in learning and decision-making tasks involving affect (Laborde et al. 2010: 786). Intuition is therefore here viewed as a potentially vital component of translator behavior which could predict individuals' translating effectiveness. © John Benjamins Publishing Company.

Bayesian invariant measurements of generalisation for discrete distributions

Neural network learning rules can be viewed as statistical estimators. They should be studied in Bayesian framework even if they are not Bayesian estimators. Generalisation should be measured by the divergence between the true distribution and the estimated distribution. Information divergences are invariant measurements of the divergence between two distributions. The posterior average information divergence is used to measure the generalisation ability of a network. The optimal estimators for multinomial distributions with Dirichlet priors are studied in detail. This confirms that the definition is compatible with intuition. The results also show that many commonly used methods can be put under this unified framework, by assume special priors and special divergences.

Integrating group Delphi, fuzzy logic and expert systems for marketing strategy development:the hybridisation and its effectiveness

A hybrid approach for integrating group Delphi, fuzzy logic and expert systems for developing marketing strategies is proposed in this paper. Within this approach, the group Delphi method is employed to help groups of managers undertake SWOT analysis. Fuzzy logic is applied to fuzzify the results of SWOT analysis. Expert systems are utilised to formulate marketing strategies based upon the fuzzified strategic inputs. In addition, guidelines are also provided to help users link the hybrid approach with managerial judgement and intuition. The effectiveness of the hybrid approach has been validated with MBA and MA marketing students. It is concluded that the hybrid approach is more effective in terms of decision confidence, group consensus, helping to understand strategic factors, helping strategic thinking, and coupling analysis with judgement, etc.

An applied linguistic analysis of the simplification of narrative texts

Simplification of texts has traditionally been carried out by replacing words and structures with appropriate semantic equivalents in the learner's interlanguage, omitting whichever items prove intractable, and thereby bringing the language of the original within the scope of the learner's transitional linguistic competence. This kind of simplification focuses mainly on the formal features of language. The simplifier can, on the other hand, concentrate on making explicit the propositional content and its presentation in the original in order to bring what is communicated in the original within the scope of the learner's transitional communicative competence. In this case, simplification focuses on the communicative function of the language. Up to now, however, approaches to the problem of simplification have been mainly concerned with the first kind, using the simplifier’s intuition as to what constitutes difficulty for the learner. There appear to be few objective principles underlying this process. The main aim of this study is to investigate the effect of simplification on the communicative aspects of narrative texts, which includes the manner in which narrative units at higher levels of organisation are structured and presented and also the temporal and logical relationships between lower level structures such as sentences/clauses, with the intention of establishing an objective approach to the problem of simplification based on a set of principled procedures which could be used as a guideline in the simplification of material for foreign students at an advanced level.

Probabilistic methods for drug discovery

This thesis introduces a flexible visual data exploration framework which combines advanced projection algorithms from the machine learning domain with visual representation techniques developed in the information visualisation domain to help a user to explore and understand effectively large multi-dimensional datasets. The advantage of such a framework to other techniques currently available to the domain experts is that the user is directly involved in the data mining process and advanced machine learning algorithms are employed for better projection. A hierarchical visualisation model guided by a domain expert allows them to obtain an informed segmentation of the input space. Two other components of this thesis exploit properties of these principled probabilistic projection algorithms to develop a guided mixture of local experts algorithm which provides robust prediction and a model to estimate feature saliency simultaneously with the training of a projection algorithm.Local models are useful since a single global model cannot capture the full variability of a heterogeneous data space such as the chemical space. Probabilistic hierarchical visualisation techniques provide an effective soft segmentation of an input space by a visualisation hierarchy whose leaf nodes represent different regions of the input space. We use this soft segmentation to develop a guided mixture of local experts (GME) algorithm which is appropriate for the heterogeneous datasets found in chemoinformatics problems. Moreover, in this approach the domain experts are more involved in the model development process which is suitable for an intuition and domain knowledge driven task such as drug discovery. We also derive a generative topographic mapping (GTM) based data visualisation approach which estimates feature saliency simultaneously with the training of a visualisation model.

Kant and Darwin

The central theses of Kant's critical philosophy are sometimes said to have been overtaken by evolutionary biology. This paper considers how far this proposition can be sustained. I argue that the ‘architectonic’ or ‘system-building’ character of the mind, the categories and the forms of intuition, can indeed be seen as the outcome of a particular evolutionary lineage in a Darwinian world. I argue, further, that the principal motive energizing the critical philosophy is the 'nightmare' of physical determinism. An alternative escape route from this particular nightmare is rehearsed. If this route is taken, the intricate arguments of the Critiques are unnecessary to save moral action in a world of things. Nonetheless, insofar as 'first philosophy' necessarily starts from within the philosopher's own subjectivity, Kant's work retains its power. I suggest that the Kantian and the Darwinian interpretations are to an extent complementary. If this is so, some form of evolutionarily-informed dual-aspect psychoneural identity theory could combine the essence of the two interpretations.

Action research in a collective organisation:Developing an education programme in a pressure group

The aim of this project was to develop the education work of an environmental pressure group. The research devised and implemented a project to produce multi-media teaching packs on the urban environment. Whilst this involved understanding environmental education it was necessary to research beyond this to include the various structural and dynamic constraints on change in the field. This presented a number of methodological difficulties; from the resolution of which a model of the research process involved in this project has been developed. It is argued that research oriented towards practical change requires the insights of an experienced practitioner to be combined with the rigours of controlled systematic enquiry. Together these function as a model-building process encompassing intuition, induction and deduction. Model testing is carried out through repeated intervention in the field; thus an interplay between researcher and client ensues such that the project develops in a mutually acceptable direction. In practice, this development will be both unpredictable and erratic. Although the conclusions reached here are based on a single case study they address general methodological issues likely to be encountered in different field settings concerned with different practical problems.

Computer simulation for tube-making by the cold roll-forming process

The conventional design of forming rolls depends heavily on the individual skill of roll designers which is based on intuition and knowledge gained from previous work. Roll design is normally a trial an error procedure, however with the progress of computer technology, CAD/CAM systems for the cold roll-forming industry have been developed. Generally, however, these CAD systems can only provide a flower pattern based on the knowledge obtained from previously successful flower patterns. In the production of ERW (Electric Resistance Welded) tube and pipe, the need for a theoretical simulation of the roll-forming process, which can not only predict the occurrence of the edge buckling but also obtain the optimum forming condition, has been recognised. A new simulation system named "CADFORM" has been devised that can carry out the consistent forming simulation for this tube-making process. The CADFORM system applied an elastic-plastic stress-strain analysis and evaluate edge buckling by using a simplified model of the forming process. The results can also be visualised graphically. The calculated longitudinal strain is obtained by considering the deformation of lateral elements and takes into account the reduction in strains due to the fin-pass roll. These calculated strains correspond quite well with the experimental results. Using the calculated strains, the stresses in the strip can be estimated. The addition of the fin-pass roll reduction significantly reduces the longitudinal compressive stress and therefore effectively suppresses edge buckling. If the calculated longitudinal stress is controlled, by altering the forming flower pattern so it does not exceed the buckling stress within the material, then the occurrence of edge buckling can be avoided. CADFORM predicts the occurrence of edge buckling of the strip in tube-making and uses this information to suggest an appropriate flower pattern and forming conditions which will suppress the occurrence of the edge buckling.

The throughput order of multicast traffics with physical-layer network coding in random wireless ad hoc networks

This paper attempts to address the effectiveness of physical-layer network coding (PNC) on the throughput improvement for multi-hop multicast in random wireless ad hoc networks (WAHNs). We prove that the per session throughput order with PNC is tightly bounded as T((nvmR (n))-1) if m = O(R-2 (n)), where n is the total number of nodes, R(n) is the communication range, and m is the number of destinations for each multicast session. We also show that per-session throughput order with PNC is tight bounded as T(n-1), when m = O(R-2(n)). The results of this paper imply that PNC cannot improve the throughput order of multicast in random WAHNs, which is different from the intuition that PNC may improve the throughput order as it allows simultaneous signal access and combination.

On the capacity improvement of multicast throughput in wireless ad hoc networks with physical-layer network coding

This paper attempts to address the effectiveness of physical-layer network coding (PNC) on the capacity improvement for multi-hop multicast in random wireless ad hoc networks (WAHNs). While it can be shown that there is a capacity gain by PNC, we can prove that the per session throughput capacity with PNC is ? (nR(n))), where n is the total number of nodes, R(n) is the communication range, and each multicast session consists of a constant number of sinks. The result implies that PNC cannot improve the capacity order of multicast in random WAHNs, which is different from the intuition that PNC may improve the capacity order as it allows simultaneous signal reception and combination. Copyright © 2010 ACM.

A method for systematic artifact selection decision making

Artifact selection decisions typically involve the selection of one from a number of possible/candidate options (decision alternatives). In order to support such decisions, it is important to identify and recognize relevant key issues of problem solving and decision making (Albers, 1996; Harris, 1998a, 1998b; Jacobs & Holten, 1995; Loch & Conger, 1996; Rumble, 1991; Sauter, 1999; Simon, 1986). Sauter classifies four problem solving/decision making styles: (1) left-brain style, (2) right-brain style, (3) accommodating, and (4) integrated (Sauter, 1999). The left-brain style employs analytical and quantitative techniques and relies on rational and logical reasoning. In an effort to achieve predictability and minimize uncertainty, problems are explicitly defined, solution methods are determined, orderly information searches are conducted, and analysis is increasingly refined. Left-brain style decision making works best when it is possible to predict/control, measure, and quantify all relevant variables, and when information is complete. In direct contrast, right-brain style decision making is based on intuitive techniques—it places more emphasis on feelings than facts. Accommodating decision makers use their non-dominant style when they realize that it will work best in a given situation. Lastly, integrated style decision makers are able to combine the left- and right-brain styles—they use analytical processes to filter information and intuition to contend with uncertainty and complexity.

A stochastic frontier approach to modelling financial constraints in firms:an application to India

We propose the use of stochastic frontier approach to modelling financial constraints of firms. The main advantage of the stochastic frontier approach over the stylised approaches that use pooled OLS or fixed effects panel regression models is that we can not only decide whether or not the average firm is financially constrained, but also estimate a measure of the degree of the constraint for each firm and for each time period, and also the marginal impact of firm characteristics on this measure. We then apply the stochastic frontier approach to a panel of Indian manufacturing firms, for the 1997–2006 period. In our application, we highlight and discuss the aforementioned advantages, while also demonstrating that the stochastic frontier approach generates regression estimates that are consistent with the stylised intuition found in the literature on financial constraint and the wider literature on the Indian credit/capital market.