Search results

This research aims to evaluate the factors that influence logistics outsourcing, including the impact of logistics outsourcing on measuring companies' logistics performance. This research provides interactions among the various factors (constructs) such as “financial”, “collaboration and process characteristics”, “external influencer”, and “logistics performance”.

To investigate the interaction between the constructs, structural equation modelling is proposed to understand what the relevant criteria are while outsourcing logistics. Data were acquired from surveys conducted with 129 managers from Brazilian companies in the industry sector.

The factor “collaboration and process characteristics” is what most influences the “logistics performance” of companies, highlighting the importance of managing contractors; and the “financial” factor also contributes to the logistic outsourcing decision.

Some limitations of this study need to be clarified. First, the model could test the moderate and mediate aspects by using variables inspired on RBV and TCE. Second, the sample is relatively small and restricted to the Brazilian industries' case, although the results may be useful for other countries in the world. Third, the responses represent viewpoints of the people who work in the companies. To address this issue, the authors asked respondents to fill out the questionnaire from the perspective of the organisation.

Most 3PL come from developed countries and find different requirements in Brazil. Then, this new knowledge may help 3L providers better understand the needs of the local or foreign companies that operate in the local market. The measurement model may also help to construct a new organisational process, as it sheds light on the main elements necessary for gathering logistics performance outcomes.

To the best of the authors' knowledge, the literature lacks studies on the interaction among these logistics outsourcing constructs, mainly in emerging markets where significant growth opportunities have led to logistics activities being outsourced. The literature that examines the impact of these constructs on logistics performance is also limited. Therefore, this research contributes to providing a model that measures these impacts according to the company's point of view.

This paper aims to identify and systematically summarize the relevant research on metaphors that are used to explain gender inequalities in the organizational context.

The researchers conducted a systematic literature review using bibliometric techniques and content analysis.

The systematic literature review identified a total of 1,269 papers in 688 journals written by 2,441 authors. The first paper was published in 1971 and the publication growth can be observed in the five decades analyzed. The Gender in Management: An International Journal, was the journal that published more papers about this thematic. Michelle Ryan was the most influential researcher regarding the number of papers and citations she had. The content analysis performed with the 27 most influential papers showed 4 research streams (metaphors; gender and leadership; challenges, stereotypes and toxic environment; and gender in the academy). Concerning the metaphors explored in those papers, the glass ceiling is the most prominent. Furthermore, 26 kinds of barriers were identified regarding the challenges that women face to reach positions of power.

The scrutiny of the metaphors and barriers enable access to what is being a hindrance to female progression in the organizational structure. So, this study may instrumentalize organizations and women to improve gender diversity practices in the workplace.

The value of the paper lays in the extensive literature review, using a bibliometric approach and content analysis.

When establishing a mathematical model to simulate solid mechanics, considering realistic geometries, special tools are needed to translate measured data, possibly with noise, into idealized geometrical entities. As an engineering application, wheel-rail contact interactions are fundamental in the dynamic modeling of railway vehicles. Many approaches used to solve the contact problem require a continuous parametric description of the geometries involved. However, measured wheel and rail profiles are often available as sets of discrete points. A reconstruction method is needed to transform discrete data into a continuous geometry.

The authors present an approximation method based on optimization to solve the problem of fitting a set of points with an arc spline. It consists of an initial guess based on a curvature function estimated from the data, followed by a least-squares optimization to improve the approximation. The authors also present a segmentation scheme that allows the method to increment the number of segments of the spline, trying to keep it at a minimal value, to satisfy a given error tolerance.

The paper provides a better understanding of arc splines and how they can be deformed. Examples with parametric curves and slightly noisy data from realistic wheel and rail profiles show that the approach is successful.

The developed methods have theoretical value. Furthermore, they have practical value since the approximation approach is better suited to deal with the reconstruction of wheel/rail profiles than interpolation, which most methods use to some degree.

In order to deepen the understanding of self-organization, the purpose of the paper is to raise and analyze the state of the art in the area of innovation networks, particularly the characteristics of self-organizing, relying on the theory of complex systems to overcome any shortcomings.

The databases selected for the search were Web of Science and Scopus; the keywords searched in the titles of articles were innovation networks, complex systems, self-organization and self-organizing; the timeline of the search covers the period between 2000 and 2014 due to the presence of important studies in the field of networks starting in the early 2000s; only studies published in English were used; the articles selected were examined by first reading the titles, then the abstracts, and finally the texts in full.

The way the main constructs from the analytical perspective of innovation networks intersect with complex systems explains how self-organization is presented and how it can be allowed to occur within a view of expected benefits for the purposes of these networks.

The originality of the research lies in the questioning of the classical form of organizational management in innovation networks, essentially based on the concentration of hierarchical power.

Micro and small enterprises (MSEs) play a crucial role in the development of any country by generating innovative ideas. However, they face inherent restrictions that hinder their innovation capabilities. It is essential to support innovation policies to overcome these barriers and foster innovation. This study aims to explore how innovation policies can reduce barriers to innovation in MSEs using the lens of innovation capabilities.

Through a multiple case study, the authors examined eight MSEs in São Paulo (Brazil) and five in Florence (Italy) to conduct this study. These countries share a similar level of importance when it comes to MSEs.

Current innovation policies could be more effective for MSEs if certain barriers they encounter are faced and resolved, such as limited financial resources and a scarcity of qualified workers. These barriers directly affect two key elements of their innovation capability: financial resources and human resources. Therefore, it is essential to develop innovation policies that target these elements directly to enable MSEs to overcome these obstacles and thrive.

This study aims to enhance the knowledge of how innovation policies can help alleviate obstacles to innovation and how they can influence the various components that comprise the innovation capability of MSEs. This research can be valuable for policymakers as it provides insight into which innovation policies impact each aspect of innovation capability, enabling them to choose the most suitable policy based on the specific needs and local circumstances of the MSEs.

The SARS-CoV-2 pandemic has caused a major impact on worldwide public health and economics. The lessons learned from the successful attempts to contain the pandemic escalation revealed that the wise usage of contact tracing and information systems can widely help the containment work of any contagious disease. In this context, this paper investigates other researches on this domain, as well as the main issues related to the practical implementation of such systems and specifies a technical solution.

The proposed solution is based on the automatic identification of relevant contacts between infected or suspected people with susceptible people; inference of contamination risk based on symptoms history, user navigation records and contact information; real-time georeferenced information of population density of infected or suspect people; and automatic individual social distancing recommendation calculated through the individual contamination risk and the worsening of clinical condition risk.

The solution was specified, prototyped and evaluated by potential users and health authorities. The proposed solution has the potential of becoming a reference on how to coordinate the efforts of health authorities and the population on epidemic control.

This paper proposed an original information system for epidemic control which was applied for the SARS-CoV-2 pandemic and could be easily extended to other epidemics.

This chapter presents an analysis of evidence-informed teaching practice in the context of Chilean formal education. The concept of evidence-informed practice (EIP) is tackled from the use of data from standardized assessments of learning by agents of the educational system in Chile, analyzing the relationship between the use of standardized assessments and the institutional characteristics of the educational system.

First, the Chilean educational system is characterized according to its regulation and cohesion, utilizing the Hood's matrix (2000). With the current predominance of accountability regulation with high stakes, the Chilean system presents a high degree of regulation and low cohesion. Then, the main uses of assessments in Chile are described based on the available evidence, with emphasis on the National Assessment System (SIMCE) a high-stakes assessment and an alternative assessment system (SEPA) of low stakes. Thirdly, the institutional theory is applied to analyze the factors that facilitate and obstruct EIP in schools. Finally, the chapter concludes by providing some implications for educational policy and practice.

This paper aims to investigate the effect of shear rate, concentration (4–20 kg/m³) and temperature (20°C–60 °C) on the apparent viscosity of apricot gum solutions.

Apparent viscosity has been measured using a rotational viscometer.

It has been observed that the shear stress and apparent viscosity values increase at high concentrations in the prepared apricot gum solutions. However, it is understood that the higher the temperature in the operation conditions, the lower the apparent viscosity results. Power-law is found the best-fitting model to illustrate the changes in temperature and concentration. According to the consistency coefficient and flow behavior indices, the apricot gum displayed shear-thinning behavior (pseudoplastic). The apricot gum is a polysaccharide with amino and uronic acids, according to Fouirer Transform Infrared Spektrofotometre spectra.

The results suggest that power-law model can be used to estimate the viscosity of apricot gum solutions at different temperatures and concentrations for applications for which flow behavior should be taken into account.

Exudate gums have good rheological properties and, therefore, are widely used in the food industry. Apricot gum is a biodegradable and abundant polysaccharide that enhances viscosity, stabilizes suspension or emulsion and improves the flow properties of foods. Different rheological models are used to investigate rheological properties. However, those models are time-independent to fit the experimental data.

This paper aims to propose a new ultrasonic diagnosis method for stainless steel weld defects based on multi-domain feature fusion to solve two problems in the ultrasonic diagnosis of austenitic stainless steel weld defects. These are insufficient feature extraction and subjective dependence of diagnosis model parameters.

To express the richness of the one-dimensional (1D) signal information, the 1D ultrasonic testing signal was derived to the two-dimensional (2D) time-frequency domain. Multi-scale depthwise separable convolution was also designed to optimize the MobileNetV3 network to obtain deep convolution feature information under different receptive fields. At the same time, the time/frequent-domain feature extraction of the defect signals was carried out based on statistical analysis. The defect sensitive features were screened out through visual analysis, and the defect feature set was constructed by cascading fusion with deep convolution feature information. To improve the adaptability and generalization of the diagnostic model, the authors designed and carried out research on the hyperparameter self-optimization of the diagnostic model based on the sparrow search strategy and constructed the optimal hyperparameter combination of the model. Finally, the performance of the ultrasonic diagnosis of stainless steel weld defects was improved comprehensively through the multi-domain feature characterization model of the defect data and diagnosis optimization model.

The experimental results show that the diagnostic accuracy of the lightweight diagnosis model constructed in this paper can reach 96.55% for the five types of stainless steel weld defects, including cracks, porosity, inclusion, lack of fusion and incomplete penetration. These can meet the needs of practical engineering applications.

This method provides a theoretical basis and technical reference for developing and applying intelligent, efficient and accurate ultrasonic defect diagnosis technology.