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The design of retail backroom storage areas has great impact on in-store operations, customer service level and on store life-cycle costs. Moreover, backroom storage in modern retail grocery stores is critical to several functions, such as acting as a buffer against strong demand lifts yielded by an ever-increasing promotional activity, stocking seasonal peak demand and accommodating e-commerce activities. The purpose of this paper is to propose a framework to design retail backroom storage area. Furthermore, the authors aim to draw attention to the lack of literature on this topic, while clarifying the relationship between this promising research stream and the considerable body of research regarding the design and operations of conventional warehouses, as well as retail in-store operations.

The key literature on backrooms, grocery retail, in-store operations, warehouse design and operations was reviewed. This allowed an understanding of the gap in the literature regarding the design of backrooms. Moreover, a case study methodological approach was conducted in a Portuguese retailer to extend the literature review.

Despite having functions similar to conventional warehouses, backroom storage facilities have particularities that deserve a distinct analysis. Thus, the authors stress these differences and demonstrate how they influence the development of a novel backroom design framework.

This paper fills a gap by proposing a framework to design backroom areas. Furthermore, this research may help practitioners to better design backroom areas, since this process currently lacks a formal and standardized procedure.

Disruptions are appearing more frequently and having an ever greater impact on supply chains (SC), affecting the vulnerability and sustainability of organisations. Our study proposes an innovative approach to address contemporary challenges by introducing coopetition as a strategic capability. The aim of this study is to enable companies to adapt and thrive by applying a tool that measures and monitors different logistical scenarios to improve performance and antifragility.

With the aim of jointly planning transport activities of two competing companies, we present a linear programming model that promotes synergies which enhance resource utilisation. To demonstrate the validity of the model, a case study is conducted to measure, monitor and evaluate the results obtained after collaborating on SC activities.

Current tools to support logistics planning are not effective because they hamper information exchange, cost allocation and performance measurements. Our innovative model optimises collaborative networks (CNs) and monitors economic, environmental and social improvements. The case study shows the reduction of logistics costs (13%), carbon footprint (37%) and the improvement of social antifragility when agility and flexibility emerge.

CNs have become an effective means of enhancing resilience, but there are no empirical contributions to demonstrate how to achieve this. We provide a real case with computational experiments that provide empirical evidence of the effectiveness of the model, which measures, optimises and evaluates SC performance in coopetitive environments. This approach is a guide to researchers and practitioners when creating simulations to reduce risks and facilitate decision-making.

This paper aims to propose a learning evaluation model for Green Belts and Black Belts at the training level. A question bank has been developed on the basis of Bloom’s learning classification and applied to a group of employees who were being trained in Six Sigma (SS). Their results were then used to decide on the students’ approval and to guide the instructor’s plan of teaching for the next classes.

An action research has been conducted to develop a question bank of 310 questions based on the revised Bloom’s Taxonomy, to implement the evaluation model, and to apply it during the SS training.

The evaluation model has been designed so that the students do not proceed unless they have acquired the conceptual knowledge at each step of the DMAIC (Define, Measure, Analyze, Improve and Control) roadmap. At the end of the evaluation process, the students’ results have been analyzed. The number of mistakes in all stages of DMAIC was equal, implying that the training was uniform the entire roadmap. However, the opposite happened in each of the Bloom’s Taxonomy levels, showing that some skills need to be better stimulated by the instructor than others.

The learning evaluation model proposed in this paper has been applied to a group of 70 employees who were being trained in SS at a Brazilian aircraft manufacturer. The data have been analyzed using Microsoft Excel^® and Minitab^® 17 Statistical Software.

Despite the abundance of courses offering the SS Green Belt and Black Belt certifications, there is no standard evaluation to ensure the training quality. Thus, this paper proposes an innovative learning evaluation model.

The purpose of this paper is to present a programming by demonstration (PbD) system based on 3D stereoscopic vision and inertial sensing that provides a cost-effective pose tracking system, even during error-prone situations, such as camera occlusions.

The proposed PbD system is based on the 6D Mimic innovative solution, whose six degrees of freedom marker hardware had to be revised and restructured to accommodate an IMU sensor. Additionally, a new software pipeline was designed to include this new sensing device, seeking the improvement of the overall system’s robustness in stereoscopic vision occlusion situations.

The IMU component and the new software pipeline allow the 6D Mimic system to successfully maintain the pose tracking when the main tracking tool, i.e. the stereoscopic vision, fails. Therefore, the system improves in terms of reliability, robustness, and accuracy which were verified by real experiments.

Based on this proposal, the 6D Mimic system reaches a reliable and low-cost PbD methodology. Therefore, the robot can accurately replicate, on an industrial scale, the artisan level performance of highly skilled shop-floor operators.

To the best of the authors’ knowledge, the sensor fusion between stereoscopic images and IMU applied to robot PbD is a novel approach. The system is entirely designed aiming to reduce costs and taking advantage of an offline processing step for data analysis, filtering and fusion, enhancing the reliability of the PbD system.

This paper aims to report the first iteration on the Light Detection and Ranging (LIDAR) Engineering Model altimeter named HELENA. HELENA is a Time of Flight (TOF) altimeter that provides time-tagged distances and velocity measurements. The LIDAR can be used for support near asteroid navigation and provides scientific information. The HELENA design comprises two types of technologies: a microchip laser and low noise sensor. The synergies between these two technologies enable developing a compact instrument for range measurements of up to 14 km. Thermal-mechanical and radiometric simulations of the HELENA telescope are reported in this paper. The design is subjected to vibrational, static and thermal conditions, and it was possible to conclude by the results that the telescope is compliant with the random vibration levels, the static load and the operating temperatures.

The Asteroid Impact & Deflection Assessment (AIDA) is a collaboration between the NASA DART mission and ESA Hera mission. The aim scope is to study the asteroid deflection through a kinetic collision. DART spacecraft will collide with Didymos-B, while ground stations monitor the orbit change. HERA spacecraft will study the post-impact scenario. The HERA spacecraft is composed by a main spacecraft and two small CubeSats. HERA will monitor the asteroid through cameras, radar, satellite-to-satellite doppler tracking, LIDAR, seismometry and gravimetry.

The HELENA design comprises two types of technologies: a microchip laser and low noise sensor. The synergies between these two technologies enable developing a compact instrument for range measurements of up to 14 km.

In this paper is reported the first iteration on the LIDAR Engineering Model altimeter named HELENA. HELENA is a TOF altimeter that provides time-tagged distances and velocity measurements. The LIDAR can be used for support near asteroid navigation and provides scientific information. The HELENA design comprises two types of technologies: a microchip laser and low noise sensor. The synergies between these two technologies enable developing a compact instrument for range measurements of up to 14 km.

This study aims to identify stakeholders’ perceptions of the effects associated with different components of intellectual capital (IC) on the sustainable development (SD) practices of higher education institutions (HEIs).

The empirical approach uses a structural equation model to provide new empirical findings in relation to 738 students and 587 lecturers/researchers at seven Portuguese state HEIs through quantitative research.

The results obtained are, firstly, important contributions to the literature on the IC and SD practices of HEIs, as a relationship between these two constructs is confirmed, especially through relational capital (RC) and structural capital (SC). Secondly, the stakeholders considered show different perceptions of the influence of the components of HEIs’ IC on these institutions’ SD practices, and thirdly, perception of the economic dimension is most influenced.

The empirical findings indicate the need to provide better information about HEIs’ policies and practices of SD and how the latter contribute to the SD of the institution and its region of influence.

No previous studies investigate students and teachers/researchers’ perceptions of the social, environmental, economic and organizational dimensions of SD in HEIs and at the same time how those perceptions can be influenced by the components of IC (e.g. human capital, SC, RC) in that institution.

The objective of this chapter is to describe and analyze Brazil's main steps in its long and incomplete process of organizing a professional and responsive public service. During the twentieth century, Brazil had two authoritarian regimes and organized a state-oriented process of industrialization. After 1988, democracy has changed how public administration should be constituted, imposing demands for universal recruitment and accountability. The level of professionalization of the federal public service was improved, with a higher level of education, better wages and the recruitment of public servants to management positions. The challenges ahead are improving governance and executive coordination and raising the responsiveness and quality of public management (such as human resources, planning, budgeting, procurement, information and communication technologies, and organizational modeling) in a context of political instability, slow economic recovery, and substantial public debts at the federal government.

The purpose of this study is to investigate the influence of firm-specific investor sentiment on Brazilian companies’ accrual-based earnings management between 2010 and 2018. The paper aims to bring deeper insight into the relationship between the investor expectations and managers’ decision-making in an emerging market.

The authors use the quantitative approach and apply a multiple linear regression model to test the relationship among the abnormal accruals, the firm-specific investor sentiment index and the control variables. The final sample includes data from 175 companies, between 2010 and 2018.

These results reveal a negative association between firm-specific investor sentiment and accrual-based earnings management, which could mean that the risk propensity of managers to manipulate earnings increases when they face known losses in the capital market.

The research findings provide a valuable understanding of how emerging capital market expectations can influence managerial decisions, such as accrual-based earnings management. The geographical area of study was limited to only Brazil.

Previous studies on developed markets show that market-wide investor sentiment positively influences accrual-based earnings management. However, the present study shows that the firm-specific investor sentiment index has a significant and negative relationship with Brazilian companies’ earnings manipulation, whereas market sentiment indicates contradictory relationship in previous studies in the country.

El propósito de este estudio es investigar la influencia del sentimiento de los inversionistas a nivel de empresa en la manipulación contable de las empresas brasileñas entre 2010 y 2018. El documento pretende aportar una visión más profunda sobre la relación entre las expectativas de los inversores y la toma de decisiones de los gestores en un mercado emergente.

usamos el enfoque cuantitativo y aplicamos un modelo de regresión lineal múltiple para probar la relación entre las acumulaciones anormales, el índice de sentimiento de los inversores a nivel de empresa y las variables de control. La muestra final incluye datos de 175 empresas, entre 2010 y 2018.

Los resultados revelan una asociación negativa entre el sentimiento de los inversores a nivel de empresa y la manipulación contable basada em acumulaciones, lo que podría significar que la propensión al riesgo de los administradores a manipular las ganancias aumenta cuando enfrentan pérdidas conocidas en el mercado de capitales.

los resultados de la investigación proporcionan una valiosa comprensión de cómo las expectativas de los mercados de capitales emergentes pueden influir en las decisiones de gestión, como la manipulación contable basada en acumulaciones. El área geográfica de estudio se limitó únicamente a Brasil y, en consecuencia, los hallazgos y conclusiones del estudio tuvieron sus límites.

estudios anteriores sobre mercados desarrollados muestran que el sentimiento de los inversores a nivel de mercado influye positivamente en la manipulación contable. Sin embargo, el presente estudio muestra que el índice de sentimiento de los inversores a nivel de empresa tiene una relación significativa y negativa con la manipulación de las ganancias de las empresas brasileñas, mientras que el sentimiento del mercado indica una relación contradictoria en estudios anteriores en el país.