Gender Differences in Union Formation in Mexico: Evidence From Marital Search Models

Although increasingly appreciated for their explanatory power in developed societies, marital search models have yet to be widely applied to developing nations. This article evaluates the applicability of marital search models to marriage timing in Mexico. The analysis compares separate models of union formation for men and women that include individual and marriage market predictors. Results show that union formation is closely linked to the uncertainties surrounding the transition to adulthood and the availability of marriageable partners. Improvements in women's economic position do not diminish the attractiveness of marriage, as female independence arguments would suggest. Instead, they are a central force behind the stability of marriage behavior in Mexico. A central transformation identified in the analysis is the reduction in sex differences in age at marriage as women expand their education and labor force participation.     

Developmental Outcomes of School Attachment Among Students of Mexican Origin

We used a longitudinal community study of 674 grade school children (Grades 5, 6, 7, and 8; 337 males, 337 females) of Mexican origin to examine outcomes of school attachment. Attachment to school is important in this population given the high level of school dropout rates of Mexican‐origin students. Results indicated that, on average, school attachment from fifth to sixth grade remains stable, but declines from sixth to eighth grade. Boys had lower levels of school attachment at fifth grade but followed similar patterns of change as girls did. Attachment to teachers, peer competence, school aspirations and expectations, and substance‐use cognitions emerged as longitudinal outcomes of level or changes in school attachment. Gender moderated associations of school attachment.     

Designing from activities. The "ability /difficulty table", a useful tool to detect the "limit users" in the Design for All Approach

In the Design for All Approach (DfA), an important phase of the design process consists in the individuation of the so-called "limit users", that are that particular group of people with the most "critical" features for the autonomous fruition of a system or a product. Generally, however, it is not easy to identify them in a complete and objective way. A clear and complete outline of design requirements with respect to the "normal" use of a service, product or environment, moreover, is of fundamental importance in inclusive design. In fact, we know how bad design, that doesn't take in account the true "strategies of use", may lead to situations of handicap, also serious, temporary or permanent, regardless if the user is a "disabled" person or not. In relation to this scenario, the paper shows the results of a research which has developed the "Ability/Difficulty Table" ("A/D Table"), a new tool useful to identify the so-called "limit users" and their needs with respect to different activities, linking the main "difficulties", expressed by people, with the "abilities" required to carry out in autonomy the investigated activity.     

Efficiency and effectiveness of knowledge management systems in SMEs

This paper proposes a 3D fuzzy logic methodology to assess the efficiency and effectiveness of knowledge management systems (KMSs) adopted by small and medium enterprises (SMEs) and identifies a classification bringing together the behaviour of SMEs when adopting KMSs. The proposed methodology was previously tested on an individual SME and then implemented on a sample of SMEs. The results highlight that there is an ample variety of behaviours related to the nature of knowledge and the KMSs used. Specifically, four typologies of behaviour are identified: the efficient and effective SME, the effective but inefficient SME, the efficient but ineffective SME, and the inefficient and ineffective SME. The results show that only 18% of surveyed SMEs are efficient and effective for both KM-Tools and KM-Practices, the remaining 82% are inefficient or ineffective for KM-Tools and/or KM-Practices. Lastly, the paper shows how this methodology may be used by an SME as a managerial tool to suggest appropriate changes to improve the efficient and effective adoption of KMSs supporting SMEs in the knowledge management processes.     

Mixture inverse Gaussian for unobserved heterogeneity in the autoregressive conditional duration model

In this paper, we assume that the duration of a process has two different intrinsic components or phases which are independent. The first is the time it takes for a trade to be initiated in the market (for example, the time during which agents obtain knowledge about the market in which they are operating and accumulate information, which is coherent with Brownian motion) and the second is the subsequent time required for the trade to develop into a complete duration. Of course, if the first time is zero then the trade is initiated immediately and no initial knowledge is required. If we assume a specific compound Bernoulli distribution for the first time and an inverse Gaussian distribution for the second, the resulting convolution model has a mixture of an inverse Gaussian distribution with its reciprocal, which allows us to specify and test the unobserved heterogeneity in the autoregressive conditional duration (ACD) model.

Our proposals make it possible not only to capture various density shapes of the durations but also easily to accommodate the behaviour of the tail of the distribution and the non monotonic hazard function. The proposed model is easy to fit and characterizes the behaviour of the conditional durations reasonably well in terms of statistical criteria based on point and density forecasts.     

The multicriteria selection of products in technological diversification strategies: an application to the Spanish automotive industry based on AHP

The economic recession, the dynamism and complexity of the markets and the generalised globalisation of the world economy have forced many companies to rethink and reorganise their industrial strategies. Through identifying and taking advantage of the key technologies of a company, this work presents a new and original methodology for dealing with a general technological diversification process. The methodology, which includes an innovative cognitive perspective and its corresponding decisional tool (decision support system) has been used to select the best product in a process of technological diversification that, along with the key technologies, identifies the sub-levels consonant to the sub-technologies and applications to sectors and products. The multicriteria selection tool employed in the proposed methodology, based on the analytic hierarchy process, allows the integration of multiple scenarios, actors and criteria, both tangible and intangible. The methodology has been applied to a case study in the Spanish automotive auxiliary sector.     

A study of Bayesian local robustness with applications in actuarial statistics

Local or infinitesimal Bayesian robustness is a powerful tool to study the sensitivity of posterior magnitudes, which cannot be expressed in a simple manner. For these expressions, the global Bayesian robustness methodology does not seem adequate since the practitioner cannot avoid using inappropriate classes of prior distributions in order to make the model mathematically tractable. This situation occurs, for example, when we compute some types of premiums in actuarial statistics in order to fix the premium to be charged to an insurance policy. In this paper, analytical and simple expressions that allow us to study the sensitivity of premiums, which are usually used in automobile insurance are provided by using the local Bayesian robustness methodology. Some examples are examined by using real automobile claim insurance data.     

Industrial applications of cross-impact analysis

The implicit or explicit ceteris paribus assumption usually made in the planning of economic systems (e.g. industries) is acceptable and accepted during periods of regular economic development; in this context, sensitivity analysis around the central projection is often used in order to measure effective elasticities to unexpected small perturbations of the system.In periods of structural change, unpredictable major events greatly reduce the value of any trend projection, and the ceteris paribus assumption has to be replaced by ‘scenarios’ of the future environment.The causal structure which generates these events is unknown; in such a situation, it seems reasonable to rely upon ‘opinions’ in order to assess the a priori probabilities of these events. Cross-impact analysis is one of the methods developed in order to improve human probability judgments of single and pairs of events and in order to deal explicitly with higher order interactions; in particular, cross-impact allows for the computation of the most probable combination of the events considered, or ‘most probable scenario’. In the industrial planning process, this ‘most probable scenario’ can be used as the set of exogeneous conditions for the central projection.