Newton Ribeiro dos Santos and Lindolpho Oliveira de Araújo
A computational implementation of the production flow analysis, a software named GROUPTEC, for a small company has been proposed. Using GROUPTEC, a case study has been devised and…
Abstract
A computational implementation of the production flow analysis, a software named GROUPTEC, for a small company has been proposed. Using GROUPTEC, a case study has been devised and applied to a company, belonging to aluminium‐manufactured products branch. Four analyses of the production flow have been performed, that is, the factory flow analysis; group analysis; line analysis, and tool analysis. After the above technique application, the final results related to the technological cells and their components; part families and machinery groups lead to an adequate cell arrangement, with a grouping efficiency of approximately 98.8 per cent. A productivity gain of 30 per cent has been estimated with the time in movement of parts and queuing at the machine.
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Bingzi Jin, Xiaojie Xu and Yun Zhang
For a wide range of market actors, including policymakers, forecasting changes in commodity prices is crucial. As one of essential edible oil, peanut oil’s price swings are…
Abstract
Purpose
For a wide range of market actors, including policymakers, forecasting changes in commodity prices is crucial. As one of essential edible oil, peanut oil’s price swings are certainly important to predict. In this paper, the weekly wholesale price index for the period of January 1, 2010 to January 10, 2020 is used to address this specific forecasting challenge for the Chinese market.
Design/methodology/approach
The nonlinear auto-regressive neural network (NAR-NN) model is the forecasting method used. Forecasting performance based on various settings, such as training techniques, delay counts, hidden neuron counts and data segmentation ratios, are assessed to build the final specification.
Findings
With training, validation and testing root mean square errors of 5.89, 4.96 and 5.57, respectively, the final model produces reliable and accurate forecasts. Here, this paper demonstrates the applicability of the NAR-NN approach for commodity price predictions.
Originality/value
On the one hand, the findings may be used as independent technical price movement predictions. Conversely, they may be included in forecast combinations with forecasts derived from other models to form viewpoints of commodity price patterns for policy research.
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Bingzi Jin and Xiaojie Xu
Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly…
Abstract
Purpose
Agriculture commodity price forecasts have long been important for a variety of market players. The study we conducted aims to address this difficulty by examining the weekly wholesale price index of green grams in the Chinese market. The index covers a ten-year period, from January 1, 2010, to January 3, 2020, and has significant economic implications.
Design/methodology/approach
In order to address the nonlinear patterns present in the price time series, we investigate the nonlinear auto-regressive neural network as the forecast model. This modeling technique is able to combine a variety of basic nonlinear functions to approximate more complex nonlinear characteristics. Specifically, we examine prediction performance that corresponds to several configurations across data splitting ratios, hidden neuron and delay counts, and model estimation approaches.
Findings
Our model turns out to be rather simple and yields forecasts with good stability and accuracy. Relative root mean square errors throughout training, validation and testing are specifically 4.34, 4.71 and 3.98%, respectively. The results of benchmark research show that the neural network produces statistically considerably better performance when compared to other machine learning models and classic time-series econometric methods.
Originality/value
Utilizing our findings as independent technical price forecasts would be one use. Alternatively, policy research and fresh insights into price patterns might be achieved by combining them with other (basic) prediction outputs.
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Xiaojie Xu and Yun Zhang
Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present…
Abstract
Purpose
Forecasts of commodity prices are vital issues to market participants and policy makers. Those of corn are of no exception, considering its strategic importance. In the present study, the authors assess the forecast problem for the weekly wholesale price index of yellow corn in China during January 1, 2010–January 10, 2020 period.
Design/methodology/approach
The authors employ the nonlinear auto-regressive neural network as the forecast tool and evaluate forecast performance of different model settings over algorithms, delays, hidden neurons and data splitting ratios in arriving at the final model.
Findings
The final model is relatively simple and leads to accurate and stable results. Particularly, it generates relative root mean square errors of 1.05%, 1.08% and 1.03% for training, validation and testing, respectively.
Originality/value
Through the analysis, the study shows usefulness of the neural network technique for commodity price forecasts. The results might serve as technical forecasts on a standalone basis or be combined with other fundamental forecasts for perspectives of price trends and corresponding policy analysis.
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Bingzi Jin, Xiaojie Xu and Yun Zhang
Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate…
Abstract
Purpose
Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.
Design/methodology/approach
The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.
Findings
A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.
Originality/value
The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.
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Cleide Gisele Ribeiro, Plinio dos Santos Ramos, Raimundo Nonato Bechara, Juliano Machado de Oliveira, Erika Bicalho de Almeida, Soraida Sozzi Miguel, Djalma Rabelo Ricardo and Rodrigo Guerra de Oliveira
The COVID-19 pandemic has created a significant disruption in the educational systems worldwide. Some institutions opted for emergency remote education due to the need to cancel…
Abstract
Purpose
The COVID-19 pandemic has created a significant disruption in the educational systems worldwide. Some institutions opted for emergency remote education due to the need to cancel in-person activities. The aims of this paper were to evaluate the use of asynchronous methodology in health sciences education, determine whether asynchronous methodology was sacrificing overall student satisfaction, and investigate whether satisfaction improved as the program develops.
Design/methodology/approach
Initially, there was phase 1 that corresponded to four weeks of activities. Each professor produced a video lesson, and after each video lesson, a weekly educational activity was made available. Next, phase 2 was implemented using the same methodology, however lasting six weeks. Three questionnaires were developed, and a Likert scale was administered to verify the students’ level of satisfaction. Data were analyzed using frequency distributions, mean values, standard deviation and confidence interval. The normality of the sum data (total of the questionnaires) was tested using the Kolmogorov–Smirnov test.
Findings
Although the students pointed out that the asynchronous methodology facilitated access to the content and considered this methodology satisfactory, they expressed a reduced level of satisfaction regarding emergency remote education in general when data from the first weeks were compared to those of the previous weeks. It is clear that students became increasingly discouraged and tired over time, which motivated the institution to shift into a combination of synchronous and asynchronous methodology to improve student learning.
Originality/value
Teaching in the field of health care encompasses difficult competencies that sometimes are impossible to be learned remotely, so there is a need to examine and evaluate properly the remote education in this area. With careful planning, educational institutions can evaluate their experiences during the pandemic, allowing those involved to highlight strengths and identify weaknesses to better prepare for future needs to improve remote education.
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Cristiano Pinto Klinger, Elvis Silveira-Martins, Gabriela Jurak de Castro and Carlos Ricardo Rossetto
The purpose of this study is to verify whether managers’ strategic orientation influences decision-making related to differentiation and whether these two factors impact on the…
Abstract
Purpose
The purpose of this study is to verify whether managers’ strategic orientation influences decision-making related to differentiation and whether these two factors impact on the performance of the firms in the Brazilian wine industry.
Design/methodology/approach
A survey was conducted with representatives from 123 wineries located in the following Brazilian states: 78.86 per cent in Rio Grande do Sul; 13.01 per cent in Santa Catarina; 2.44 per cent in Paraná; 2.44 per cent in São Paulo; 1.63 per cent in Bahia; and 1.63 per cent in Pernambuco. The data were analyzed using multivariate statistical techniques, resulting in a structural equations model of the constructs.
Findings
The research findings show that there is a positive association between prospector orientation and differentiation. Analyst positioning was negatively associated with differentiation of winery companies. It was also possible to show that differentiation has a positive relationship with performance.
Originality/value
While a previous study attempted to identify wineries’ strategic orientation using other theoretical constructs, this study makes a contribution to consolidating reflections on strategic orientation focused on differentiation and performance. The results contribute to expanding the scientific debate by filling a gap in existing theory and also provide information of use to decision-makers, demonstrating, which approaches improve differentiation, and hence, performance.
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Raysa Palheta Borges, Wladimir Colman de Azevedo Junior, Marcos Antônio Souza dos Santos and Marcos Rodrigues
Resources provided by The Northern Brazilian Constitutional Financing Fund (FNO) aim to promote regional development to economically and socially backward regions through…
Abstract
Purpose
Resources provided by The Northern Brazilian Constitutional Financing Fund (FNO) aim to promote regional development to economically and socially backward regions through subsidized financial resources for economic activities, including agriculture. This study aims to determine whether rural credit and the FNO were able to produce structural changes in the distribution of financial resources and thus contribute to economic growth in Northern Brazilian municipalities.
Design/methodology/approach
This paper used inequality indexes and the Local Indicator of Spatial Association to verify the credit concentration and the spatial presence of clusters. To analyze the role of credit in promoting agricultural growth, this paper estimated an ordinary least squares regression with panel data for 450 municipalities during 1995–2017.
Findings
The results highlighted that rural credit, including the FNO, is essential to incentivizing agricultural production and increasing rural income. However, the financial resources are mostly captured by a small share of municipalities, spatially clustered in the expanding agricultural frontier of Pará, Tocantins and Rondônia states. Low-Low clusters are mainly present in the Western Amazonian region and are subject to structural and institutional constraints that reduce their demand for credit. The FNO resources proved insufficient to reduce financial inequality between Brazil’s northern municipalities.
Originality/value
This study demonstrates that the FNO’s policies are failing to reduce the concentration of financial resources in Amazonian agriculture. The results emphasize the importance of credit for development and, consequently, reducing inequality, which leads to a higher demand for financial resources by farmers. Implications include supporting economic agents with infrastructure and technical assistance, as well as improving farmers’ access to the banking system.
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Sérgio Jesus Teixeira, João J.M. Ferreira, António Almeida and Eduardo Parra-Lopez
This study aims to analyze the contribution of tourist event and satisfaction with tourism events as a product of regional tourism competitiveness, as well as evaluate factors of…
Abstract
Purpose
This study aims to analyze the contribution of tourist event and satisfaction with tourism events as a product of regional tourism competitiveness, as well as evaluate factors of competitiveness.
Design/methodology/approach
The research followed a quantitative methodology by conducting a questionnaire on the four largest tourist events in Madeira (Carnival, Flower Festival, Atlantic Festival and Wine Festival), an insular island located in Portugal.
Findings
The sample consisted of 2,262 tourists surveyed during the year 2017 and structural equation models were used as the statistical method. Results showed that satisfaction is reflected in the client's loyalty to the choice of a tourist destination and also contributes directly and indirectly to the regional tourist competitiveness.
Originality/value
This study contributes to the valorization of local and regional events, perceived by the level of satisfaction and loyalty of tourists, as products of regional competitiveness of a tourist destination.
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Robert B. Adams and Barbara Demmig‐Adams
The purpose of this review is to compare the impact of modern food production on human health with their impact on the sustainability of food production.
Abstract
Purpose
The purpose of this review is to compare the impact of modern food production on human health with their impact on the sustainability of food production.
Design/methodology/approach
This review includes up‐to‐date information from the original literature on human nutrition as well as ecosystem ecology and presents findings in a manner accessible to both experts and non‐experts.
Findings
The evidence reviewed here indicates that modern livestock rearing and modern plant crop production both lead to adverse effects on not only human health but also on the sustainability of food production. It is concluded that different approaches are needed that increase the potential to produce healthful meat products as well as healthful plant crops – while simultaneously promoting sustainable food production and eliminating the need for pesticide use.
Practical implications
The studies reviewed suggest that the prevalence of chronic human diseases and disorders could be drastically lowered by adopting different approaches to food production, which would simultaneously protect continuing food production for human society.
Originality/value
This article provides accessible and comprehensive information to researchers, nutritionists, and consumers interested in human nutrition in its own right and in relationship to sustainable food production.