Abstract: The purpose of this research is to study of consumer
perception and understanding consumer buying behavior that related
between satisfied and factors affecting the purchasing. Methodology
can be classified between qualitative and quantitative approaches for
the qualitative research were interviews from middlemen who bought
organic vegetables, and middlemen related to production and
marketing system. A questionnaire was utilized as a tool to collect
data. Statistics utilized in this research included frequency,
percentage, mean, standard deviation, and multiple regression
analysis. The result show the reason to decision buying motives is
Fresh products of organic vegetables is the most significant factor on
individuals’ income, with a b of –.143, t = –2.470, the price of
organic vegetables is the most significant factor on individuals’
income, with a b of .176, t = 2.561, p value = .011. The results show
that most people with higher income think about the organic products
are expensive and have negative attitudes towards organic vegetable
as individuals with low and medium income level. Therefore,
household income had a significant influence on the purchasing
decision.
Abstract: Estimation of a proportion has many applications in
economics and social studies. A common application is the estimation
of the low income proportion, which gives the proportion of people
classified as poor into a population. In this paper, we present this
poverty indicator and propose to use the logistic regression estimator
for the problem of estimating the low income proportion. Various
sampling designs are presented. Assuming a real data set obtained
from the European Survey on Income and Living Conditions, Monte
Carlo simulation studies are carried out to analyze the empirical
performance of the logistic regression estimator under the various
sampling designs considered in this paper. Results derived from
Monte Carlo simulation studies indicate that the logistic regression
estimator can be more accurate than the customary estimator under
the various sampling designs considered in this paper. The stratified
sampling design can also provide more accurate results.
Abstract: Composite materials have important assets compared
to traditional materials. They bring many functional advantages:
lightness, mechanical resistance and chemical, etc. In the present
study we examine the effect of a circular central notch and a precrack
on the tensile fracture of two woven composite materials. The tensile
tests were applied to a standardized specimen, notched and a
precarcked (orientation of the crack 0°, 45° and 90°). These tensile
tests were elaborated according to an experimental planning design of
the type 23.31 requiring 24 experiments with three repetitions. By the
analysis of regression, we obtained a mathematical model describing
the maximum load according to the influential parameters (hole
diameter, precrack length, angle of a precrack orientation). The
specimens precracked at 90° have a better behavior than those having
a precrack at 45° and still better than those having of the precracks
oriented at 0°. In addition the maximum load is inversely
proportional to the notch size.
Abstract: Second line antiretroviral therapy (ART) regimen is
used when patients fail their first line regimen. There are many
factors such as non-adherence, drug resistance as well as virological
and immunological failure that lead to second line highly active
antiretroviral therapy (HAART) regimen treatment failure. This study
was aimed at determining predictor factors to treatment failure with
second line HAART and analyzing median survival time.
An observational, retrospective study was conducted in Sungai
Buloh Hospital (HSB) to assess current status of HIV patients treated
with second line HAART regimen. Convenience sampling was used
and 104 patients were included based on the study’s inclusion and
exclusion criteria. Data was collected for six months i.e. from July
until December 2013. Data was then analysed using SPSS version 18.
Kaplan-Meier and Cox regression analyses were used to measure
median survival times and predictor factors for treatment failure.
The study population consisted mainly of male subjects, aged 30-
45 years, who were heterosexual, and had HIV infection for less than
6 years. The most common second line HAART regimen given was
lopinavir/ritonavir (LPV/r)-based combination. Kaplan-Meier
analysis showed that patients on LPV/r demonstrated longer median
survival times than patients on indinavir/ritonavir (IDV/r) based
combination (p
Abstract: This paper presents a regression model with
autocorrelated errors in which the inputs are social moods obtained by
analyzing the adjectives in Twitter posts using a document topic
model, where document topics are extracted using LDA. The
regression model predicts Dow Jones Industrial Average (DJIA) more
precisely than autoregressive moving-average models.
Abstract: This paper proposes a complementary combination scheme of affine projection algorithm (APA) filters with different order of input regressors. A convex combination provides an interesting way to keep the advantage of APA having different order of input regressors. Consequently, a novel APA which has the rapid convergence and the reduced steady-state error is derived. Experimental results show the good properties of the proposed algorithm.
Abstract: This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.
Abstract: The acidity (citric acid) is the one of chemical content that can be refer to the internal quality and it’s a maturity index of tomato, The titratable acidity (%TA) can be predicted by a non-destructive method prediction by using the transmittance short wavelength (SW-NIR) spectroscopy in the wavelength range between 665-955 nm. The set of 167 tomato samples divided into groups of 117 tomatoes sample for training set and 50 tomatoes sample for test set were used to establish the calibration model to predict and measure %TA by partial least squares regression (PLSR) technique. The spectra were pretreated with MSC pretreatment and it gave the optimal result for calibration model as (R = 0.92, RMSEC = 0.03%) and this model obtained high accuracy result to use for %TA prediction in test set as (R = 0.81, RMSEP = 0.05%). From the result of prediction in test set shown that the transmittance SW-NIR spectroscopy technique can be used for a non-destructive method for %TA prediction of tomato.
Abstract: This study aim at the influence of college students’ exercise and leisure motivations on the leisure benefits while using the leisure involvement as a moderator. Whereby, the research tools used in this study included the application of leisure motivation scale, leisure involvement scale and leisure benefits scale, and a hierarchical regression analysis was performed by using a questionnaire-based survey, in which, a total of 1,500 copies of questionnaires were administered and 917 valid questionnaires were obtained, achieving a response rate of 61.13%. Research findings explore that leisure involvement has a moderating effect on the relationship between the leisure motivation and leisure benefits.
Abstract: Two new algorithms for nonparametric estimation of errors-in-variables models are proposed. The first algorithm is based on penalized regression spline. The spline is represented as a piecewise-linear function and for each linear portion orthogonal regression is estimated. This algorithm is iterative. The second algorithm involves locally weighted regression estimation. When the independent variable is measured with error such estimation is a complex nonlinear optimization problem. The simulation results have shown the advantage of the second algorithm under the assumption that true smoothing parameters values are known. Nevertheless the use of some indexes of fit to smoothing parameters selection gives the similar results and has an oversmoothing effect.
Abstract: Raphia wine is an important forest product with cultural significance besides its use as medicine and food in southern Nigeria. This work aims to evaluate the profitability of Raphia wine production and marketing in Sapele Local Government Area, Nigeria. Four communities (Sapele, Ogiede, Okuoke and Elume) were randomly selected for data collection via questionnaires among producers and marketers. A total of 50 producers and 34 marketers were randomly selected for interview. Data was analyzed using descriptive statistics, profit margin, multiple regression and rate of returns on investment (RORI). Annual average profit was highest in Okuoke (Producers – N90, 000.00, Marketers - N70, 000.00) and least in Sapele (Producers N50, 000.00, Marketers – N45, 000.00). Calculated RORI for marketers were Elume (40.0%), Okuoke (25.0%), Ogiede (33.3%) and Sapele (50.0%). Regression results showed that location has significant effects (0.000, ρ ≤ 0.05) on profit margins. Male (58.8%) and female (41.2%) invest in Raphia wine marketing, while males (100.0%) dominate production. Results showed that Raphia wine has potentials to generate household income, enhance food security and improve quality of life in rural, semi-urban and urban communities. Improved marketing channels, storage facilities and credit facilities via cooperative groups are recommended for producers and marketers by concerned agencies.
Abstract: This paper proposes a GLMM with spatial and
temporal effects for malaria data in Thailand. A Bayesian method is
used for parameter estimation via Gibbs sampling MCMC. A
conditional autoregressive (CAR) model is assumed to present the
spatial effects. The temporal correlation is presented through the
covariance matrix of the random effects. The malaria quarterly data
have been extracted from the Bureau of Epidemiology, Ministry of
Public Health of Thailand. The factors considered are rainfall and
temperature. The result shows that rainfall and temperature are
positively related to the malaria morbidity rate. The posterior means
of the estimated morbidity rates are used to construct the malaria
maps. The top 5 highest morbidity rates (per 100,000 population) are
in Trat (Q3, 111.70), Chiang Mai (Q3, 104.70), Narathiwat (Q4,
97.69), Chiang Mai (Q2, 88.51), and Chanthaburi (Q3, 86.82).
According to the DIC criterion, the proposed model has a better
performance than the GLMM with spatial effects but without
temporal terms.
Abstract: This study examines whether the Taiwan’s public debt is sustainable utilizing an unrestricted two-regime threshold autoregressive (TAR) model with an autoregressive unit root. The empirical results show that Taiwan’s public debt appears as a nonlinear series and is stationary in regime 1 but not in regime 2. This result implies that while Taiwan’s public debt was mostly sustainable over the 1996 to 2013 period examined in the study, it may no longer be sustainable in the most recent two years as the public debt ratio has increased cumulatively to 3.618%.
Abstract: This paper presents a comparative study between two
neural network models namely General Regression Neural Network
(GRNN) and Back Propagation Neural Network (BPNN) are used
to estimate radial overcut produced during Electrical Discharge
Machining (EDM). Four input parameters have been employed:
discharge current (Ip), pulse on time (Ton), Duty fraction (Tau) and
discharge voltage (V). Recently, artificial intelligence techniques, as
it is emerged as an effective tool that could be used to replace
time consuming procedures in various scientific or engineering
applications, explicitly in prediction and estimation of the complex
and nonlinear process. The both networks are trained, and the
prediction results are tested with the unseen validation set of the
experiment and analysed. It is found that the performance of both the
networks are found to be in good agreement with average percentage
error less than 11% and the correlation coefficient obtained for the
validation data set for GRNN and BPNN is more than 91%. However,
it is much faster to train GRNN network than a BPNN and GRNN is
often more accurate than BPNN. GRNN requires more memory space
to store the model, GRNN features fast learning that does not require
an iterative procedure, and highly parallel structure. GRNN networks
are slower than multilayer perceptron networks at classifying new
cases.
Abstract: This research paper aimed to find out how was the ethical climate in an organization and job performance satisfaction of employees affected employees’ engagement and commitment by using the case study of PTT Exploration and Production Public Company Limited, Thailand. The population of this research was 4,383 Thai employees of PTTEP, Thailand. From a total of 420 questionnaires sent out, 345 respondents replied. The statistics utilized was mean score and Multiple Regression Analysis. The findings revealed that the respondents had opinion towards ethical climate of their organization, job performance satisfaction and organization engagement and commitment at a high level. The test of hypothesis disclosed the determinant attributes of job performance satisfaction that affected the respondents’ overall level of organization engagement and commitment. The set of these determinant attributes consisted of employees’ responsibilities for duties, organization’s policies and practice, relationship with organization’s commanders, work security and stability, job description, career path and relationship with colleagues. These variables were able to predict the employees’ organization engagement and commitment at 50.6 percent.
Abstract: The purpose of this research was to study the influence of accountants’ potential performance on their working process, a case study of Government Savings Banks in the northeast of Thailand. The independent variables included accounting knowledge, accounting skill, accounting value, accounting ethics, and accounting attitude, while the dependent variable included the success of the working process. A total of 155 accountants working for Government Savings Banks were selected by random sampling. A questionnaire was used as a tool for collecting data. Descriptive statistics in this research included percentage, mean, and multiple regression analyses.
The findings revealed that the majority of accountants were female with an age between 35-40 years old. Most of the respondents had an undergraduate degree with ten years of experience. Moreover, the factors of accounting knowledge, accounting skill, accounting a value and accounting ethics and accounting attitude were rated at a high level. The findings from regression analysis of observation data revealed a causal relationship in that the observation data could explain at least 51 percent of the success in the accountants’ working process.
Abstract: The aims of this research are to broaden the study on the relationship between emotional intelligence and counterproductive work behavior (CWB). The study sample consisted in 441 Romanian employees from companies all over the country. Data has been collected through web surveys and processed with SPSS. The results indicated an average correlation between the two constructs and their sub variables, employees with a high level of emotional intelligence tend to be less aggressive. In addition, labeling was considered an individual difference which has the power to influence the level of employee aggression. A regression model was used to underline the importance of emotional intelligence together with labeling as predictors of CWB. Results have shown that this regression model enforces the assumption that labeling and emotional intelligence, taken together, predict CWB. Employees, who label themselves as victims and have a low degree of emotional intelligence, have a higher level of CWB.
Abstract: As widely accepted, didactic multiple-choice tests are referred as a tool providing feedback easily and quickly. Despite the final test scores are corrected by a special formula and number of high plausibility distractors is taken into consideration, the results may be influenced by the random choice. The survey was held in three academic years at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic, where the multiple-choice test scores were compared to the open-answer ones. The research sample included 567 respondents. The collected data were processed by the NCSS2007 statistic software by the method of frequency and multiple regression analysis and presented in the form of figures and tables. The results proved statistically significant differences in test scores in academic years 2 and 3, and were discussed from the point of the credit system and conditions for teaching/learning English in the Czech education system.
Abstract: The objective of this research was to study the
influence of Integrated Marketing Communication on Buying
Decision of Consumers in Bangkok. A total of 397 respondents were
collected from customers who drive in Bangkok. A questionnaire was
utilized as a tool to collect data. Statistics utilized in this research
included frequency, percentage, mean, standard deviation, and
multiple regression analysis. Data were analyzed by using Statistical
Package for the Social Sciences.
The findings revealed that the majority of respondents were male
with the age between 25-34 years old, hold undergraduate degree,
married and stay together. The average income of respondents was
between 10,001-20,000 baht. In terms of occupation, the majority
worked for private companies. The effect to the Buying Decision of
Consumers in Bangkok to including sale promotion with the low
interest and discount for an installment, selling by introducing and
gave product information through sales persons, public relation by
website, direct marketing by annual motor show and advertisement
by television media.
Abstract: This study examined the predictive effects of moral competence, prosocial norms and positive behavior recognition on school misbehavior among Chinese junior secondary school students. Results of multiple regression analysis showed that students were more likely to misbehave in school when they had lower levels of moral competence and prosocial norms, and when they perceived their positive behavior being less likely recognized. Practical implications were discussed on how to guide students to make the right choices to behave appropriately in school. Implications for future research were also discussed.