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Since the creation of the web, the designers are looking for friendlier ways of make web page contents, which pictures, sounds, movies and free texts attract the users’ interest. Special attention receive the text content, because is the most frequently parameter used to retrieve information from the web. A simple way in order to understand the user’s text preferences, could be collect the words used in a searching. However, this information is only well‐know for the owner of the specific searching engine. In this paper we introduce a methodology in order to extract the most interest words for a user in a particular web site, based of the user browsing behavior and the web page text content. The methodology was tested using data originated in a bank web site showing the effectiveness of our approach.

To develop a new predictive control scheme based on neural networks for linear and non‐linear dynamical systems.

The approach relies on three different multilayer neural networks using input‐output information with delays. One NN is used to identify the process under control, the other is used to predict the future values of the control error and finally the third one is used to compute the magnitude of the control input to be applied to the plant.

This scheme has been tested by controlling discrete‐time SISO and MIMO processes already known in the control literature and the results have been compared with other control approaches with no predictive effects. Transient behavior of the new algorithm, as well as the steady state one, are observed and analyzed in each case studied. Also, online and offline neural network training are compared for the proposed scheme.

The theoretical proof of stability of the proposed scheme still remains to be studied. Conditions under which non‐linear plants together with the proposed controller present a stable behavior have to be derived.

The main advantage of the proposed method is that the predictive effect allows to suitable control complex non‐linear process, eliminating oscillations during the transient response. This will be useful for control engineers to control complex industrial plants.

This general approach is based on predicting the future control errors through a predictive neural network, taking advantage of the NN characteristics to approximate any kind of relationship. The advantage of this predictive scheme is that the knowledge of the future reference values is not needed, since the information used to train the predictive NN is based on present and past values of the control error. Since the plant parameters are unknown, the identification NN is used to back‐propagate the control error from the output of the plant to the output of the controller. The weights of the controller NN are adjusted so that the present and future values of the control error are minimized.

The purpose of this paper is to investigate the relationship between firms’ entrepreneurial orientations (EOs) and the adoption of quality management (QM) practices. The role of environmental uncertainty as the moderator of the former relationship is considered.

Using theories and related empirical evidences, two research hypotheses were argued and proposed. These hypotheses were tested using data collected from a unique sample of 301 Uruguayan and Argentinean manufacturing companies with more than 20 workers assessed through personal interviews. The empirical methodology includes statistic treatment for scale validation, statistic descriptive techniques and regression analysis.

Firms’ EO is determinant for the adoption of QM practices. The environmental uncertainty strengthens the positive impact of EO on the adoption of QM practices, mainly human resource management practices.

The data come from a particular geographical context and refer to manufacturing plants. It would be interesting to extend the scope of this study to services. The collection of data from only one individual in each organization can generate a potential problem with using single-source information.

Innovative manufacturing companies that try to adopt advanced QM practices will benefit from hiring managers who are able to take risks, and to seek a long-term orientation toward being aggressive with their environment, especially in highly competitive contexts. Mustering these features may ensure perseverance in the adoption of advanced manufacturing practices, even in the presence of complex and uncertain environments.

The principal contribution of this paper is that it advances the study of the intersection between operations management and entrepreneurship, analyzing how firms’ EO affects the adoption of new methods and practices in manufacturing. Furthermore, it is important to highlight the fact that the authors use data from a unique survey of manufacturing companies from Argentina and Uruguay in the southern cone of Latin America. The authors also contribute to the open debate about the universality of QM practices.

This paper aims to understand the patterns of lean production implementation, and the relationship between three context factors (i.e. firm size, positions within the supply chain and time length of the lean initiative) and the adoption of lean production practices in firms of the automotive supply chain in Brazil.

The authors collected data from 65 companies of the automotive supply chain in Brazil. For data analysis, first a cluster analysis was performed to identify common characteristics in the companies’ context factors when considering patterns of lean implementation. Then, multivariate analysis of variance was used to investigate the differences between the context factors and the degree of use of lean practices.

High lean adopters had better performance than low lean adopters in terms of lead time, inventory and turnover. Firms at the first and second tier of the automotive supply chain were “leaner” than firms at the third tier. Large-sized firms were more likely to have a higher degree of use of lean practices than medium and smaller ones. Some, but not all, lean practices followed these patterns. Results also showed that some lean practices were most commonly adopted at the beginning of the lean journey, whereas others took more time to mature.

This paper demonstrated how lean practices were implemented at different positions within the supply chain, and the patterns of implementation often followed. It also considers lean in the context of developing countries such as Brazil.

Open innovation breadth (OIB) considers the diversity of external collaboration partners for innovation. The authors investigate the moderating effect of OIB on the relationship between industrial innovation activities (innovation inputs) and industrial innovation results (innovation outputs).

This study is based on secondary data from the Brazilian innovation survey, representing more than 30,000 innovative companies across 55 industrial sectors.

This study’s results show that OIB has different moderating effects regarding the several innovation input–output relationships. While OIB benefits some relationships, others are hampered by the diversity of collaboration partners.

Few studies have addressed OIB at the macro level. Using the perspective of transaction cost economics (TCE), the authors discuss the contributions and limitations of OIB at the industry level.

This chapter investigates how musicians at jazz jam sessions engage in what I term “aggressive emergence.” In so doing, they introduce novelty, unpredictability and creativity in their spontaneous interactions with other musicians. In order to discuss this emergence, a notion of signs in musical communications as indexes, in the Peircean sense, is developed. To produce emergence in the ongoing development of a jam session performance, musicians must produce signs that index new directions that jazz playing can take, such as different rhythmic or harmonic accompaniments, or changes to the volume at which individuals play their instruments.

The purpose of this paper is to extend research on customer loyalty status and customer demotion by investigating if the effect of demotion on customer attitudinal and behavioral responses is the same for top-tier and low-tier customers in the context of airlines.

A survey was conducted with travelers intercepted at large airport terminals in Australia. Multivariate analyses examined group differences across status change (no change vs demoted) and status level (high status vs low status). Multi-group moderation structural equation modeling (SEM) analysis tested the moderating role of status (high status vs low status) on the effects of demotion on the relationship between customers’ attitudes and loyalty intention, and between loyalty intention and share of wallet.

This study shows that the detrimental effects of demotion on the relationship between customer satisfaction/commitment/perceived betrayal on loyalty intentions, and on the relationship between loyalty intentions and share of wallet are stronger for “high status” than “low status” customers.

A cross-sectional design was employed to investigate customer demotion in the airline industry. Future studies could investigate different types of demotions in other industries by employing a longitudinal design.

The study provides new insight about the effects of status demotion and highlights that service firms could be jeopardizing the loyalty of numerous valuable customers, especially among the “high status” customer group.

This study reveals loyalty status moderates the effect of demotion on customer attitudinal responses and loyalty behaviors. It draws on social identity, social comparison, emotion and equity theories to explain the different effects of demotion on customers from different status level groups.