Abstract: The purpose of this paper is to investigate if there are positive and significant correlations between the dimensions of Person-Environment Fit (Person-Job, Person-Organization, Person-Group and Person-Supervisor) at the “Best Companies to Work for” in Brazil in 2017. For that, a quantitative approach was used with a descriptive method being defined as a research sample the "150 Best Companies to Work for", according to data base collected in 2017 and provided by Fundação Instituto of Administração (FIA) of the University of São Paulo (USP). About the data analysis procedures, asymmetry and kurtosis, factorial analysis, Kaiser-Meyer-Olkin (KMO) tests, Bartlett sphericity and Cronbach's alpha were used for the 69 research variables, and as a statistical technique for the purpose of analyzing the hypothesis, Pearson's correlation analysis was performed. As a main result, we highlight that there was a positive and significant correlation between the dimensions of Person-Environment Fit, corroborating the H1 hypothesis that there is a positive and significant correlation between Person-Job Fit, Person-Organization Fit, Person-Group Fit and Person-Supervisor Fit.
Abstract: Since additive manufacturing technologies constantly advance, the use of this technology in mold making seems reasonable. Many manufacturers of additive manufacturing machines, however, do not offer any suggestions on how to parameterize the machine to achieve optimal results for mold making. The purpose of this research is to determine the interdependencies of different materials and parameters within the PolyJet process by using design of experiments (DoE), to additively manufacture molds, e.g. for thermoforming and injection molding applications. Therefore, the general requirements of thermoforming molds, such as heat resistance, surface quality and hardness, have been identified. Then, different materials and parameters of the PolyJet process, such as the orientation of the printed part, the layer thickness, the printing mode (matte or glossy), the distance between printed parts and the scaling of parts, have been examined. The multifactorial analysis covers the following properties of the printed samples: Tensile strength, tensile modulus, bending strength, elongation at break, surface quality, heat deflection temperature and surface hardness. The key objective of this research is that by joining the results from the DoE with the requirements of the mold making, optimal and tailored molds can be additively manufactured with the PolyJet process. These additively manufactured molds can then be used in prototyping processes, in process testing and in small to medium batch production.
Abstract: The aim of the present study was to develop a rapid method for electronic nose for online quality control of oat milk. Analysis by electronic nose and bacteriological measurements were performed to analyze spoilage kinetics of oat milk samples stored at room temperature and refrigerated conditions for up to 15 days. Principal component analysis (PCA), Discriminant Factorial Analysis (DFA) and Soft Independent Modelling by Class Analogy (SIMCA) classification techniques were used to differentiate the samples of oat milk at different days. The total plate count (bacteriological method) was selected as the reference method to consistently train the electronic nose system. The e-nose was able to differentiate between the oat milk samples of varying microbial load. The results obtained by the bacteria total viable countsshowed that the shelf-life of oat milk stored at room temperature and refrigerated conditions were 20hrs and 13 days, respectively. The models built classified oat milk samples based on the total microbial population into “unspoiled” and “spoiled”.
Abstract: International market expansion involves a strategic process of market entry decision through which a firm expands its operation from domestic to the international domain. Hence, entry timing choices require the needs to balance the early entry risks and the problems in losing opportunities as a result of late entry into a new market. Questionnaire surveys administered to 115 Malaysian construction firms operating in 51 countries worldwide have resulted in 39.1 percent response rate. Factor analysis was used to determine the most significant factors affecting entry timing choices of the firms to penetrate the international market. A logistic regression analysis used to examine the firms’ entry timing choices, indicates that the model has correctly classified 89.5 per cent of cases as late movers. The findings reveal that the most significant factor influencing the construction firms’ choices as late movers was the firm factor related to the firm’s international experience, resources, competencies and financing capacity. The study also offers valuable information to construction firms with intention to internationalize their businesses.
Abstract: This paper presents a method of economic factorial analysis of the CO2 emissions based on the extension of the Divisia index to interconnected factors. This approach, contrary to the Kaya identity, considers three main factors of the CO2 emissions: gross domestic product, energy consumption, and population - as equally important, and allows for accounting of all of them simultaneously. The three factors are included into analysis together with their carbon intensities that allows for obtaining a comprehensive picture of the change in the CO2 emissions. A computer program in R-language that is available for free download serves automation of the calculations. A case study of the U.S. carbon dioxide emissions is used as an example.
Abstract: This paper aims to improve a fine lapping process of
hard disk drive (HDD) lapping machines by removing materials from
each slider together with controlling the strip height (SH) variation to
minimum value. The standard deviation is the key parameter to
evaluate the strip height variation, hence it is minimized. In this
paper, a design of experiment (DOE) with factorial analysis by twoway
analysis of variance (ANOVA) is adopted to obtain a
statistically information. The statistics results reveal that initial stripe
height patterns affect the final SH variation. Therefore, initial SH
classification using a radial basis function neural network is
implemented to achieve the proportional gain prediction.
Abstract: Factor analysis was applied to two stages biogas
production from banana stem waste allowing a screening of the
experimental variables second stage temperature (T), organic loading
rates (OLR) and hydraulic retention times (HRT). Biogas production
was found to be strongly influenced by all the above experimental
variables. Results from factorial analysis have shown that all
variables which were HRT, OLR and T have significant effect to
biogas production. Increased in HRT and OLR could increased the
biogas yield. The performance was tested under the conditions of
various T (35oC-60oC), OLR (0.3 g TS/l.d–1.9 gTS/l.d), and HRT (3
d–15 d). Conditions for temperature, OLR and HRT in this study
were based on the best range obtained from literature review.