Integration of Analytic Hierarchy Process with Regression Analysis to Identify Attractive Locations for Market Expansion

Selection of new geographies in which to expand is a key decision for businesses aspiring to go beyond the opportunities in the existing markets. The conventional approaches of market selection can only provide a set of systematic steps for problem solving without considering the relationships between the decision factors. Decision models based on statistical techniques are able to examine the relationship between decision factors but are unable to effectively assist decision makers in identifying the most promising market, particularly in terms of prioritizing across decision factors. Analytic Hierarchy Process (AHP) is a commonly used approach for choosing alternatives by prioritizing across multiple decision factors. The typical AHP modelling requires knowledge of criteria and/or alternatives along with their relative weights, generally elicited from field experts. Quite often, firms encounter situations where decision makers are aware of only the overall objective and a set of earmarked geographies for setting up market locations while being relatively unaware of decision criteria and relative weights. This precludes using AHP to identify promising market locations. This paper conceptualizes a market selection decision model that integrates AHP with statistical modelling techniques to identify the attractive market locations for the purpose of expansion. The model first uses principal component analysis and multiple regression to determine significant decision criteria and their weights. Thereafter, it applies AHP to prioritize the market locations across the decision criteria. This integrative approach is illustrated for identifying the attractive locations in rural markets for a steel firm in India. The major advantage of this approach is that unlike the existing models, it works in situations when firms have not enough knowledge about factors for evaluating alternative market locations. Another key advantage of the proposed model is that of economizing resources for data collection on variables representing decision factors. Copyright © 2012 John Wiley & Sons, Ltd.     

A History Which Began to Be Told: A Clinical Case

This article aims to reflect on the possible contributions of psychoanalysis in relation to severely disturbed patients by means of the presentation of a clinical case. Beginning with the family history, the evolutionary process of the symptoms and identification movements of the patient are analysed. The observation of the transference dynamics is emphasised, showing how the desire of the analyst and his privileged listening will allow the patient some level of possible subjective structure.     

John Polkinghorne on Three Scientist-Theologians

In 1996, John Polkinghorne published Scientists as Theologians: A Comparison of the Writings of Ian Barbour, Arthur Peacocke and John Polkinghorne. Responding to this book and his subsequent writing, I first summarize four topics on which we all agree: (1) critical realism; (2) holism, emergence, and levels of organization; (3) human nature; and (4) limitations in God's power. I then discuss our differences concerning: (1) classification schemes; (2) concepts of God; (3) laws of nature; (4) divine action; and (5) Christology. I then explore the contexts in which we were writing: our differing scientific disciplines, theological traditions, and academic institutions. Some concluding reflections concern our place in the interdisciplinary field of “science and religion.”     

基于个体的退休心理模型

退休是个体在特定年龄领取养老金的行为及动态过程。退休模型包括退休的影响因素模型、退休过程模型和退休结果模型三类。其中,退休的影响因素模型包括前因变量模型和退休多水平模型,分别从个人-环境和宏观角度提出了影响退休的各类因素;退休过程模型包括退休决策三阶段模型、退休时间过程模型和退休适应动态模型,分别从阶段性、个体差异性和动态性的角度揭示了退休过程的心理特点;退休结果模型分析了退休对个人和组织的影响。退休四阶段模型是在西方模型的基础上结合中国国情提出的一个整合模型。未来研究应丰富研究对象的类型、揭示影响退休的心理学变量的作用机制、加强应用性并进行本土化研究。     

The mediating and moderating role of planning on mothers’ decisions for early childhood dietary behaviours

Objective: Examine the roles of action and coping planning on the intention–behaviour relationship for mothers’ decisions for their young children’s dietary behaviours.

Design: Prospective design with two waves of data collection, one week apart.

Main outcome measures: Mothers (N = 197, M_age = 34.39, SD = 5.65) of children aged 2–3 years completed a main questionnaire assessing planning constructs and intentions, and a one-week follow-up of the target behaviours – ‘healthy eating’ and ‘discretionary choices’.

Results: Intention was the strongest predictor of behaviour for both dietary behaviours. For healthy eating, intention moderated the indirect relationship between intention–behaviour via planning; coping planning was less important when intention was strong. Further, intention was not a direct predictor of behaviour when intention was relatively low. Action planning was not a direct predictor of either behaviour after accounting for intention and coping planning; action planning on behaviour was mediated by coping planning (only for healthy eating). Intention was not a direct predictor of coping planning; intention on coping planning was mediated by action planning. Neither type of planning predicted discretionary choices.

Conclusion: Current findings contribute novel information on the mechanisms underpinning the effect of action and coping planning on the intention–behaviour relationship.     

Intuition, reason, and metacognition

Dual Process Theories (DPT) of reasoning posit that judgments are mediated by both fast, automatic processes and more deliberate, analytic ones. A critical, but unanswered question concerns the issue of monitoring and control: When do reasoners rely on the first, intuitive output and when do they engage more effortful thinking? We hypothesised that initial, intuitive answers are accompanied by a metacognitive experience, called the Feeling of Rightness (FOR), which can signal when additional analysis is needed. In separate experiments, reasoners completed one of four tasks: conditional reasoning (N = 60), a three-term variant of conditional reasoning (N = 48), problems used to measure base rate neglect (N = 128), or a syllogistic reasoning task (N = 64). For each task, participants were instructed to provide an initial, intuitive response to the problem along with an assessment of the rightness of that answer (FOR). They were then allowed as much time as needed to reconsider their initial answer and provide a final answer. In each experiment, we observed a robust relationship between the FOR and two measures of analytic thinking: low FOR was associated with longer rethinking times and an increased probability of answer change. In turn, FOR judgments were consistently predicted by the fluency with which the initial answer was produced, providing a link to the wider literature on metamemory. These data support a model in which a metacognitive judgment about a first, initial model determines the extent of analytic engagement.     

Multi-attribute,multi-alternative models of choice: Choice,reaction time,and process tracing

The first aim of this research is to compare computational models of multi-alternative, multi-attribute choice when attribute values are explicit. The choice predictions of utility (standard random utility & weighted valuation), heuristic (elimination-by-aspects, lexicographic, & maximum attribute value), and dynamic (multi-alternative decision field theory, MDFT, & a version of the multi-attribute linear ballistic accumulator, MLBA) models are contrasted on both preferential and risky choice data. Using both maximum likelihood and cross-validation fit measures on choice data, the utility and dynamic models are preferred over the heuristic models for risky choice, with a slight overall advantage for the MLBA for preferential choice. The response time predictions of these models (except the MDFT) are then tested. Although the MLBA accurately predicts response time distributions, it only weakly accounts for stimulus-level differences. The other models completely fail to account for stimulus-level differences. Process tracing measures, i.e., eye and mouse tracking, were also collected. None of the qualitative predictions of the models are completely supported by that data. These results suggest that the models may not appropriately represent the interaction of attention and preference formation. To overcome this potential shortcoming, the second aim of this research is to test preference-formation assumptions, independently of attention, by developing the models of attentional sampling (MAS) model family which incorporates the empirical gaze patterns into a sequential sampling framework. An MAS variant that includes attribute values, but only updates the currently viewed alternative and does not contrast values across alternatives, performs well in both experiments. Overall, the results support the dynamic models, but point to the need to incorporate a framework that more accurately reflects the relationship between attention and the preference-formation process.     

Can confidence come too soon? Collective efficacy,conflict and group performance over time

Groups with a strong sense of collective efficacy set more challenging goals, persist in the face of difficulty, and are ultimately more likely to succeed than groups who do not share this belief. Given the many advantages that may accrue to groups who are confident, it would be logical to advise groups to build a high level of collective efficacy as early as possible. However, we draw on Whyte’s (1998) theory of collective efficacy and groupthink, to predict that when confidence emerges at a high level toward the beginning of a group’s existence, group members may be less likely to engage in process conflict; a form of conflict that may be beneficial in the early phase of a group project. We found support for this prediction in two longitudinal studies of classroom project teams.