infonet-economy

Two models of how people predict the next outcome in a sequence of binary events were developed and compared on the basis of gambling data from a lab experiment using hierarchical Bayesian techniques. The results from a student sample (N = 39) indicated that a model that considers run length (“drift model”)—that is, how often the same event has previously occurred in a row—provided a better description of the data than did a stationary model taking only the immediately prior event into account. Both, expectation of negative and of positive recency was observed, and these tendencies mostly grew stronger with run length. For some individuals, however, the relationship was reversed, leading to a qualitative shift from expecting positive recency for short runs to expecting negative recency for long runs. Both patterns could be accounted for by the drift model but not the stationary model. The results highlight the importance of applying hierarchical analyses that provide both group- and individual-level estimates. Further extensions and applications of the approach in the context of the prediction literature are discussed.

Decision-making is one of the core tasks in project management. Traditionally, optimization methods have been developed to support managers in finding the best solutions. Alternatively, decisions can be based on simple rules of thumb, or heuristics. Even though simple heuristics only require little in the way of time and information, they have been shown to outperform optimization methods in complex decision tasks across a wide range of situations. This chapter outlines relevant decision heuristics commonly used, demonstrates situations in which they outperform more complex decision algorithms and explains why and when simple heuristics provide powerful decision tools.

Many economic theories of decision making assume that people evaluate options independently of other available options. However, recent cognitive theories such as decision field theory suggest that people’s evaluations rely on a relative comparison of the options’ potential consequences such that the subjective value of an option critically depends on the context in which it is presented. To test this prediction, we examined pairwise choices between monetary gambles and varied the degree to which the gambles’ outcomes covered with one another. When people evaluate options by comparing their outcomes, a high covariance between these outcomes should make a decision easier, as suggested by decision field theory. In line with this prediction, the observed choice proportions in 2 experiments (N = 39 and 24, respectively) depended on the magnitude of the covariance. We call this effect the covariance effect. Our findings are in line with the theoretic predictions and show that the discriminability ratio in decision field theory can reflect the choice difficulty. These results confirm that interdependent evaluations of options play an important role in human decision making under risk and show that covariance is an important aspect of the choice context.

Many cognitive theories of judgement and decision making assume that choice options are evaluated relative to other available options. The extent to which the preference for one option is influenced by other available options will often depend on how similar the options are to each other, where similarity is assumed to be a decreasing function of the distance between options. We examine how the distance between preferential options that are described on multiple attributes can be determined. Previous distance functions do not take into account that attributes differ in their subjective importance, are limited to two attributes, or neglect the preferential relationship between the options. To measure the distance between preferential options it is necessary to take the subjective preferences of the decision maker into account. Accordingly, the multi-attribute space that defines the relationship between options can be stretched or shrunk relative to the attention or importance that a person gives to different attributes describing the options. Here, we propose a generalized distance function for preferential choices that takes subjective attribute importance into account and allows for individual differences according to such subjective preferences. Using a hands-on example, we illustrate the application of the function and compare it to previous distance measures. We conclude with a discussion of the suitability and limitations of the proposed distance function.

In management research, empirical data are often analyzed using p-value null hypothesis significance testing (pNHST). Here we outline the conceptual and practical advantages of an alternative analysis method: Bayesian hypothesis testing and model selection using the Bayes factor. In contrast to pNHST, Bayes factors allow researchers to quantify evidence in favor of the null hypothesis. Also, Bayes factors do not require adjustment for the intention with which the data were collected. The use of Bayes factors is demonstrated through an extended example for hierarchical regression based on the design of an experiment recently published in the Journal of Management. This example also highlights the fact that p values overestimate the evidence against the null hypothesis, misleading researchers into believing that their findings are more reliable than is warranted by the data.

Consumers’ purchase decisions depend on whether a product is perceived as a bargain or as overpriced. But how do consumers evaluate sales prices? The standard approach in economics, psychology, and marketing suggests that consumers’ estimates are best described by a attribute-based or piecemeal strategy that integrates information about products in a linear additive fashion. Here, we outline and test an alternative theoretical approach from the categorization literature suggesting that consumers sometimes follow an exemplar-based strategy that relies on similarity to previously encountered products. We hypothesize that people switch between these two estimation strategies depending on the context they face. To test this hypothesis, we conducted an experiment in which 64 participants repeatedly estimated the market price of different consumer products (bottles of wine). In one condition, the product prices could be well approximated with an attribute-based strategy whereas in the other condition an exemplar-based strategy worked best. Results of a subsequent testing phase indicated that participants switched between strategies depending on the structure of the presented sets. These results show that people rely on different strategies to estimate market prices, which should influence people’s consumption behavior. The results suggest that theories on categorization learning can provide a deeper insight into behavior in an economic context and allow predicting consumer behavior more accurately.

Une forme spécifique de réseau intraorganisationnel - la communauté de pratique (CDP) - prend une importance grandissante dans les organisations, pour développer et échanger du savoir et des pratiques à travers les divisions. La présente recherche explore les facteurs-clés qui permettent de piloter ces réseaux avec succès. Une investigation au sein de 39 CDP a permis de distinguer trois types de CDP. Chaque type se caractérise par une configuration différente de facteurs-clés pour réussir avec succès le pilotage du réseau.

Les ressources humaines sont l'une des composantes de la combinaison productive de la firme. Cependant, la mobilisation de ressources humaines fait courir un risque spécifique à l'entreprise. Ce risque peut être défini comme l'incertitude que fait peser l'emploi de ressources humaines sur la compétitivité et la pérennité de l'entreprise. Les risques humains sont spécifiques dans la mesure où ils sont liés à l'usage d'une ressource douée d'une volonté propre, dotée d'une intention stratégie personnelle qui peut diverger de celle de son employeur. Enfin, les RH s'inscrivent dans une perspective systémique de l'entreprise. Elles peuvent initier des risques d'ordre technologiques, informatiques, écologiques ou financiers. Pour ces raisons, il convient pour l'entreprise d'identifier, d'évaluer, de suivre et de maîtriser ce risque RH. Certains secteurs d'activité sont plus exposés que d'autres au risque humain. Plus une activité est intense en capital humain et en connaissance et plus les salariés représentent un facteur de risque. A cet égard, deux éléments font du secteur bancaire un secteur particulièrement concerné par l'analyse et la prévention du risque humain. D'une part, le capital humain constitue la principale ressource de création de valeur des banques. La masse salariale représente plus de 50% des coûts de production des établissements bancaires (en 2005, ces coûts étaient de 59,28% à la BNP Paribas, 57,38% à la Société Générale et 53,98% au Crédit Agricole). Au-delà de cette dimension quantitative, les banques sont des entreprises de connaissance, notamment pour les activités à forte valeur ajoutée de banque d'investissement et de financement, qui emploient des salariés hautement qualifiés. D'autre part, les accords de Bâle II, définis par la Banque des Règlements Internationaux, qui doivent s'appliquer dans tous les établissements financiers à compter de janvier 2007, prévoient que les banques se couvrent contre le risque opérationnel définit comme « le risque de pertes provenant de processus internes inadéquats ou défaillants, de personnes et systèmes ou d'évènements externes ». Le facteur humain peut être directement impliqué dans le risque opérationnel du fait de fraudes, de malveillances et de problèmes liés à la gestion du personnel. Il l'est également indirectement du fait d'erreurs humaines, de manque de respect des procédures ou de mauvaises saisies de données dans les systèmes d'informations. La gestion des risques humains constitue un terrain fécond d'application des enseignements et des analyses du champ théorique de l'audit social (Candau, 1985 ; Igalens, 2000 ; Combemale et Igalens, 2005). A partir de l'exemple du secteur bancaire, il convient d'approfondir la notion de risque humain et de définir des pratiques de gestion des différentes natures de risque qu'il peut recouvrir. Cinq risques humains sont exposés : risque stratégique, risque de disparition, risque d'erreur, risque de malversation et risque de conflit. Des pistes de gestion de ces risques humains sont explorées pour montrer en quoi la gestion des risques opérationnels et les pratiques de gestion des ressources humaines (rémunération, formation, gestion prévisionnelle de l'emploi et des compétences) peuvent s'articuler