Analogical reasoning is a mode of thinking in which a current situation, person, or event is compared with something encountered in the past that appears "similar" to the analogizer. The 2020 Coronavirus crisis was often compared with the 1918 flu epidemic, for instance. In addition to reasoning across time, we can also reason across space, comparing a current case with something that has been encountered within a different geographical space. Sticking with the Coronavirus example, the management of the disease in one country was often compared with that in another, with favorable or unfavorable lessons being drawn. Analogical reasoning plays a major role in crisis decision-making, in large part because decisions made under such circumstances have to be taken in rapid (and, indeed, almost immediate) fashion. When this is the case, it is often tempting to conclude that "this time will resemble last time" or "this problem will resemble a situation confronted elsewhere." But these analogies are drawn, and decisions are made, by individuals who must confront their own very human cognitive psychological limitations. Since analogies are essentially heuristic devices that cut short the process of informational search, they are usually seen as good enough but do not ensure optimal decision-making. Analogies are at a premium during crisis-like events, but their "bounded" nature means that their use will sometimes lead to errors in processing information. In particular, the drawing of an analogy often leads to an underestimation of ways in which the current crisis is "different" from the baseline event.
"Can heuristic information processing affect important product markets? We explore whether the tendency to focus on the left-most digit of a number affects how used car buyers incorporate odometer values in their purchase decisions. Analyzing over 22 million wholesale used-car transactions, we find substantial evidence of this left-digit bias; there are large and discontinuous drops in sale prices at 10,000-mile thresholds in odometer mileage, along with smaller drops at 1,000-mile thresholds. We obtain estimates for the inattention parameter in a simple model of this left-digit bias. We also investigate whether this heuristic behavior is primarily attributable to the final used-car customers or the used-car salesmen who buy cars in the wholesale market. The evidence is most consistent with partial inattention by final customers. We discuss the significance of these results for the literature on inattention and point to other market settings where this type of heuristic thinking may be important. Our results suggest that information-processing heuristics may be important even in markets with large stakes and where information is easy to observe"--National Bureau of Economic Research web site
Energy labels have been introduced in many countries to increase consumers’ attention to energy use in purchase decisions of durables. In a discrete-choice experiment among about 5,000 households, we implement randomized information treatments to explore the effects of various kinds of energy labels on purchasing decisions. Our results show that adding annual operating cost information to the EU energy label promotes the choice of energy-efficient durables. In addition, we find that a majority of participants value efficiency classes beyond the economic value of the underlying energy use differences. Our results further indicate that displaying operating cost affects choices through two distinct channels: it increases the attention to operating cost and reduces the valuation of efficiency class differences.
Caching frequently accessed data is an important technique that allows performance improvement of a system by providing reusability of data in wired and wireless data dissemination environments. Also caching is a major step in system designing to achieve high performance in areas like WWW, operating systems, databases and LDIS of wireless environments. In this paper, we propose a cache replacement policy called H-CRP, that allows clients in wired and wireless environment to perform extremely well when compared to other existing replacement policies. The novel cache replacement algorithm takes into account the parameters like frequency of access associated with data item, retrieval delay associated with accessing page and size of data for selection of eviction page that can affect cache performance whose direct impact is on cache validation cost. In case of pages with same size, randomized selection of the page for replacement is done based on heuristic value. These heuristics make the H-CRP perform better than the existing strategies of LRU, S-LRU as indicated by the simulation results. A comprehensive comparison made among LRU, S-LRU, H-CRP shows that the H-CRP significantly reduces the number of cache misses by improving the cache hit ratio compared to the other two algorithms.
In this article we discuss the affective dimension in Ladau's theory of hegemony. We offer a reconstruction of Ladau's theory and focus on the incorporation of the affective dimension as an inherent component of every process of hegemony construction. We argue that this affective component cannot be strictly reduced to linguistic operations. By considering the relation between hegemony and affective economy we can revalue the theoretical contribution of Laclau, identifying the heuristic tools he offered for socio-political analysis. Adapted from the source document.
Contribution presented at iEMSs 2002 Integrated Assessment and Decision Support Conference held in Lugano, Switzerland, on 24-27 June 2002. More details at http://www.iemss.org/iemss2002/. ; The increase in stream nutrient loads from anthropogenic sources has become a serious problem, especially in developed regions. Humans affect streams by modifying the landscape in ways that increase the transport of nutrients to surface waters, by directly dumping urban or industrial sewage into the stream, or by modifying streams in ways that reduce their ability to respond to increased nutrient loads. In Mediterranean regions these problems are compounded by the scarcity of water. The decision-making processes involved in water quality management require extensive human expertise or extensive computation with large data sets. In this sense, the STREAMES project aims to develop a knowledge-based environmental decision support system (EDSS) to support and advice water managers in the management of human-altered streams. This EDSS will integrate an Expert System (ES), concretely a rule-based reasoning system (RBS), with a Geographical Information System to address spatial information for the appropriate stream management actions, and a numerical model to estimate point and non-point nutrient sources from middle size catchments. The RBS will be developed by integrating heuristic knowledge from experts in surface water management, as well as empirical knowledge from stream scientists, based both on previous studies and on data directly acquired from experimental sampling. This paper will present the objectives of the STREAMES project with emphasis in the knowledge acquisition and development of the RBS. ; Peer reviewed
Examining the conceptual relationship between personal experience, affect, and risk perception is crucial in improving our understanding of how emotional and cognitive process mechanisms shape public perceptions of climate change. This study is the first to investigate the interrelated nature of these variables by contrasting three prominent social-psychological theories. In the first model, affect is viewed as a fast and associative information processing heuristic that guides perceptions of risk. In the second model, affect is seen as flowing from cognitive appraisals (i.e., affect is thought of as a post-cognitive process). Lastly, a third, dual-process model is advanced that integrates aspects from both theoretical perspectives. Four structural equation models were tested on a national sample (N = 808) of British respondents. Results initially provide support for the “cognitive” model, where personal experience with extreme weather is best conceptualized as a predictor of climate change risk perception and, in turn, risk perception a predictor of affect. Yet, closer examination strongly indicates that at the same time, risk perception and affect reciprocally influence each other in a stable feedback system. It is therefore concluded that both theoretical claims are valid and that a dual-process perspective provides a superior fit to the data. Implications for theory and risk communication are discussed.