What Do You Want to Be When You Grow Up? Cognitive Flexibility Influences Career Decision Making and Related Anxiety

Career indecision is a stage most individuals pass through during their lifetime, but it is often accompanied by anxiety. While anxiety can have a positive influence on decision making by focusing attention and cognitive resources, excess anxiety can disrupt the career decision-making process. Existing literature links anxiety to cognitive flexibility, an individual’s ability to efficiently switch between thoughts and ideas and adapt to evolving situations, with young adults higher in cognitive flexibility typically experiencing less anxiety than their less flexible peers. However, no studies to date have examined cognitive flexibility as it relates to career indecision or career-indecision-related anxiety. This study examines the relationships between cognitive flexibility, career indecision, and anxiety in undergraduate students. 156 undergraduate students (72% female, 91% Caucasian, 63% juniors and seniors) completed an online Qualtrics survey assessing career indecision, career anxiety, cognitive flexibility, and general demographic information including academic trajectory, career confidence, and personal characteristics. The previously documented relationship between career indecision and anxiety was supported, but the discovery that both career indecision and anxiety share significant relationships with cognitive flexibility augments prior research by examining cognitive flexibility in the context of career decision-making. While cognitive flexibility did relate to both career-indecision-related anxiety and career indecision, it did not directly mediate the relationship between these two variables, and once its relationship with career indecision was partialled, it no longer significantly correlated with career-indecision-related anxiety. This suggests cognitive flexibility could serve as a mechanism to promote career decision-making, thereby reducing career-indecision-related anxiety

The effects of decision flexibility in the hierarchical investment decision process

Large institutional investors allocate their funds over a number of classes (e.g. equity, fixed income and real estate), various geographical regions and different industries. In practice, these allocation decisions are usually made in a hierarchical (top-down), consecutive way. At the higher decision level, the allocation is made on basis of benchmark portfolios (indexes). Such indexes are then set as targets for the lower levels. For example, at the top level the allocation decision is made on the basis of asset class benchmark indexes, on the second level the decisions are made on the basis of sector benchmark indexes, etc. Obviously, the lower levels have considerable flexibility to deviate from these targets. That is the reason why targets often come with limits on the maximally allowed deviation (or "tracking error") from these targets. The potential consequences of deviations from the benchmark portfolios have received very little attention in the literature. In this paper, we discuss and illustrate this influence. The lower level tracking errors with respect to the benchmark indexes propagate to the top level. As a result the risk-return characteristics of the actual aggregate portfolio will be different from those of the initial benchmark-based portfolio. We illustrate this effect for a two level process to allocate funds over individual US stocks and sectors. We show that the benchmark allocation approaches used in practice yield inferior solutions when compared to a non-hierarchical approach where full information about individual lower level investment opportunities is available. Our results reveal that even small deviations from the benchmark portfolios can cause large shifts in the top-level risk-return space. This implies that the incorporation of lower level information in the initial top-level decision process will lead to a different (possibly better) allocation.decision flexibility;multi-level decision process;porfolio management;tracking error analysis

Dubious decision evidence and criterion flexibility in recognition memory.

When old-new recognition judgments must be based on ambiguous memory evidence, a proper criterion for responding "old" can substantially improve accuracy, but participants are typically suboptimal in their placement of decision criteria. Various accounts of suboptimal criterion placement have been proposed. The most parsimonious, however, is that subjects simply over-rely on memory evidence - however faulty - as a basis for decisions. We tested this account with a novel recognition paradigm in which old-new discrimination was minimal and critical errors were avoided by adopting highly liberal or conservative biases. In Experiment 1, criterion shifts were necessary to adapt to changing target probabilities or, in a "security patrol" scenario, to avoid either letting dangerous people go free (misses) or harming innocent people (false alarms). Experiment 2 added a condition in which financial incentives drove criterion shifts. Critical errors were frequent, similar across sources of motivation, and only moderately reduced by feedback. In Experiment 3, critical errors were only modestly reduced in a version of the security patrol with no study phase. These findings indicate that participants use even transparently non-probative information as an alternative to heavy reliance on a decision rule, a strategy that precludes optimal criterion placement

Conceptualisation of family farms’ flexibility

Agricultural enterprises in transition countries face dynamic changes in the prevailing economic, legal and political conditions. The success of an enterprise depends on its ability to adjust its farming system in response to these changing conditions. To meet this challenge, flexible and adaptable production technology is required. Thus, the farm’s choice of technology is an important decision which determines its future performance. Although the concept of a firm’s flexibility is widely analysed in microeconomics literature, there is no comprehensive framework to facilitate the analysis of family farms’ flexibility, especially considering market imperfections and other obstacles associated with the transition process. In this paper we formulate the theoretical framework for flexibility analysis in order to investigate the impact of farm-specific characteristics on optimal flexibility design and to explain the differences between farms using different production technologies. In a simplified formal model, a competitive risk-averse firm producing one product is assumed to face fluctuating demand under uncertainty. By choosing the level of flexibility, the decision-maker determines the technology of the firm, expressed by the cost function. The optimal level of flexibility will be found by backward induction in the two-stage decision-making process, including ex ante technology decision and ex post output level decision. Using comparative statics and existing theoretical literature, some hypothesis about the relationship between flexibility and other firm characteristics will be formalised. Some possible model extensions that account for specific characteristics of the family farm business in transition countries, as well as future empirical analysis are discussed.flexibility, output price risk, family farms, Farm Management,

Developments in linear and integer programming

In this review we describe recent developments in linear and integer (linear) programming. For over 50 years Operational Research practitioners have made use of linear optimisation models to aid decision making and over this period the size of problems that can be solved has increased dramatically, the time required to solve problems has decreased substantially and the flexibility of modelling and solving systems has increased steadily. Large models are no longer confined to large computers, and the flexibility of optimisation systems embedded in other decision support tools has made on-line decision making using linear programming a reality (and using integer programming a possibility). The review focuses on recent developments in algorithms, software and applications and investigates some connections between linear optimisation and other technologies

Evaluation Periods and Asset Prices in a Market Experiment

We test whether the frequency of feedback information about the performance of an investment portfolio and the flexibility with which the investor can change it influence her risk attitude in markets.In line with the prediction of Myopic Loss Aversion (Benartzi and Thaler, 1995), we find that more information and more flexibility result in less risk taking.Market prices of risky assets are significantly higher if feedback frequency and decision flexibility are reduced.This result supports the findings from individual decision making, and shows that markets do not eliminate such behavior.information;portfolio investment;performance;financial risk;asset valuation

The Manufacturing Flexibility to Switch Products: Valuation and Optimal Strategy

This paper applies a dynamic programming methodology to the valuation problem for the flexibility to switch. In our model, flexibility provides an investor with the right, or option, to perform a switch between a less profitable and a more profitable project at no cost. In contrast to previous analyses, the option to switch can be exercised in the future at any time during the decision horizon. We present the solution methodology that allows to determine the value of the flexibility and to identify the optimal timing of the switching decision. Comparative statics demonstrate how changes in the input parameters affect the values of the problem"s solution. The results partially explain why investing in flexible manufacturing systems is reported to have both low profitability and rate of diffusion.manufacturing flexibility, real option, capital budgeting