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While several studies have examined the roles of husbands and wives in making decisions about products, few have examined the impact of children. This article reports the results of a 1985 study of the influence of children on families. The study examines children's influence in each of four stages of the purchase decision, for 25 products, and by age of the children. For child‐centered (e.g., toys, children's clothing, food) and child‐used products or services (e.g., vacations, restaurant choices, outside entertainment), the study shows that children are perceived as influential by most households. Older children are perceived as more influential than younger children for nearly all the products studied. The study concludes that “family” decision making is quite different from “husband‐wife” decision making.

Examines consumers’ motivation for buying counterfeits or pirated goods. The findings indicated that, compared to those who did not buy pirated music CDs, those who bought the counterfeits viewed such purchases as less risky, and trusted stores that sell counterfeits more. They did not see counterfeits as too unfair to singers or the music industry, thought they benefit the society more, and did not see people who buy them as unethical. We also investigated the influence of social, personality, and demographic factors on consumers’ attitude towards piracy. We found that the more value‐conscious and less normatively susceptible one was, and the less integrity one had, the more favorable was one’s attitude towards piracy. Demographic characteristics were also significant in influencing attitude. Males and those from lower income groups held more favorable attitudes. Finally, attitude towards piracy was significant in influencing purchase intention.

Since 1910, when John Dewey first introduced the five‐stage decision process, it has been a widely accepted concept and still serves as the central pillar of a popular consumer behavior model. These stages are Problem Recognition, Information Search, Alternative Evaluation, Choice, and Outcomes. The importance of these stages is attested to by the considerable attention devoted to most of them in numerous textbooks and journal articles. Such attention, however, has not come to the Problem Recognition stage. While some texts provide hypothetical descriptions of this “trigger” of the decision process, theoretical discussion and empirical support are surprisingly lacking. Journal literature fares even worse, with articles on the topic almost non‐existent. Lack of information on the topic is even more ironic when one considers that a purchase cannot occur unless a problem is recognized! The purpose of this article is to provide a detailed explanation of the Problem Recognition process. The results of the few empirical studies that have been done will be examined. In addition, a proposed model of the Problem Recognition process is presented. The implications of this material will be discussed as it relates to marketing.

Adaptive slicing is a key step in three-dimensional (3D) printing as it is closely related to the building time and the surface quality. This study aims to develop a novel adaptive slicing method based on ameliorative area ratio and accurate cusp height for 3D printing using stereolithography (STL) models.

The proposed method consists of two stages. In the first stage, the STL model is sliced with constant layer thickness, where an improved algorithm for generating active triangular patches, the list is developed to preprocess the model faster. In the second stage, the model is first divided into several blocks according to the number of contours, then an axis-aligned bounding box-based contour matching algorithm and a polygons intersection algorithm are given to compare the geometric information between several successive layers, which will determine whether these layers can be merged to one.

Several benchmarks are applied to verify this new method. Developed method has also been compared with the uniform slicing method and two existing adaptive slicing methods to demonstrate its effectiveness in slicing.

Compared with other methods, the method leads to fewer layers whilst keeping the geometric error within a given threshold. It demonstrates that the proposed slicing method can reach a trade-off between the building time and the surface quality.

Compared with traditional methods relying on manual teaching or system modeling, data-driven learning methods, such as deep reinforcement learning and imitation learning, show more promising potential to cope with the challenges brought by increasingly complex tasks and environments, which have become the hot research topic in the field of robot skill learning. However, the contradiction between the difficulty of collecting robot–environment interaction data and the low data efficiency causes all these methods to face a serious data dilemma, which has become one of the key issues restricting their development. Therefore, this paper aims to comprehensively sort out and analyze the cause and solutions for the data dilemma in robot skill learning.

First, this review analyzes the causes of the data dilemma based on the classification and comparison of data-driven methods for robot skill learning; Then, the existing methods used to solve the data dilemma are introduced in detail. Finally, this review discusses the remaining open challenges and promising research topics for solving the data dilemma in the future.

This review shows that simulation–reality combination, state representation learning and knowledge sharing are crucial for overcoming the data dilemma of robot skill learning.

To the best of the authors’ knowledge, there are no surveys that systematically and comprehensively sort out and analyze the data dilemma in robot skill learning in the existing literature. It is hoped that this review can be helpful to better address the data dilemma in robot skill learning in the future.

In recent years, practitioners have identified a number of problems with traditional performance management (PM) systems, arguing that PM is broken and needs to be fixed. In this chapter, we review criticisms of traditional PM practices that have been mentioned by journalists and practitioners and we consider the solutions that they have presented for addressing these concerns. We then consider these problems and solutions within the context of extant scholarly research and identify (a) what organizations should do going forward to improve PM practices (i.e., focus on feedback processes, ensure accountability throughout the PM system, and align the PM system with organizational strategy) and (b) what scholars should focus research attention on (i.e., technology, strategic alignment, and peer-to-peer accountability) in order to reduce the science-practice gap in this domain.

The purpose of this paper is to empirically investigate the mediating effect of service quality (SQ) in the relationship between relational capital (RC) and organizational performance (OP) within the Egyptian mobile telecommunication setting.

A valid research instrument was utilized to conduct a survey of 384 top- middle- and supervisory- level managers from three Egyptian mobile telecommunications companies. The hypothesized direct relationships were tested through multiple linear regression, and the mediating effect was tested using a structural equation modeling technique.

The results revealed that the firm's “customer and supplier relations” and “marketing capability” positively affect both OP and SQ, “customer knowledge” positively affects SQ only, while “strategic alliances, licensing and agreements” do not have an association with SQ or OP. Moreover, SQ was found fully mediating the effect of RC on OP.

This is an empirical research applied in the Egyptian telecommunication setting. Its results need further investigation in other settings and countries. Also, traditional limitations of a cross-sectional study apply with respect to the attribution of causality and the time lag effects.

The optimal procedure for the Egyptian telecommunications companies is to focus their efforts on leveraging all four components of RC in order to improve SQ and consequently enhance their OP. The telecommunications companies must do all they can to connect the unconnected. As the current COVID-19 pandemic crisis has shown, connectivity is a public good.

This is the first research that merges the concepts of RC, SQ and OP in an integrated model, and tests this model empirically in the Egyptian mobile telecommunications setting.

This study aims to examine how property rights, financial liberalization and the control of corruption at the country level influence the inward and outward global engagement of domestic firms from developing countries. The author also examines whether firms with certain resource endowments such as human capital or technological capabilities are better positioned to globalize as the aforementioned institutional factors evolve.

Using a sample of 18,365 firms from 57 developing countries and multilevel modeling, the author shows that institutional factors are related to inward and outward global engagement.

The author finds that firms with human capital are more likely to move outward in the presence of lower levels of corruption. Domestic firms possessing technological capabilities are more likely to engage inward as financial liberalization eases the access to capital.

Many existing studies that have investigated the impact of institutional factors on internationalization by developing country firms have bundled different institutions together therefore sacrificing a focus on the effect of specific institutions on these firm decisions. While the author knows that institutions matter for developing country firm globalization, there is limited research on which institutions matter. There is also a debate on how institutions matter for developing country firms. The study sheds light on these aspects. The author also uses hierarchical linear modelling and uses both country- and firm-level variables.

This paper gives a review of the finite element techniques (FE) applied in the area of material processing. The latest trends in metal forming, non‐metal forming, powder metallurgy and composite material processing are briefly discussed. The range of applications of finite elements on these subjects is extremely wide and cannot be presented in a single paper; therefore the aim of the paper is to give FE researchers/users only an encyclopaedic view of the different possibilities that exist today in the various fields mentioned above. An appendix included at the end of the paper presents a bibliography on finite element applications in material processing for 1994‐1996, where 1,370 references are listed. This bibliography is an updating of the paper written by Brannberg and Mackerle which has been published in Engineering Computations, Vol. 11 No. 5, 1994, pp. 413‐55.

When integrating smart elements offered by emergent technologies, libraries are facing the challenges of technological renovation and maintaining their operation using emerging technology. Given the importance of smart library, new technologies are needed in building new libraries or renovation of existing libraries. The purpose of this paper is to propose a risk warning system for library construction or renovation in the aspect of risk management.

The proposed Internet of Things (IoT)-based system consists of sensors that automatically monitor the status of materials, equipment and construction activities in real time. AI techniques including case-based reasoning and fuzzy sets are applied.

The proposed system can easily track material flow and visualize construction processes. The experiment shows that the proposed system can effectively detect, monitor and manage risks in construction projects including library construction.

Compared with existing risk warning systems, the proposed IoT-based system requires less data for making dynamic predictions. The proposed system can be applied to new builds and renovation of libraries.