The perception of the autonomy supportive behaviour as a predictor of perceived effort and physical self-esteem among school students from four nations

Grounded in self-determination theory (SDT), this study tested a model of motivational sequence in which perceived autonomy support from teachers in a physical education (PE) context predicted the perceived effort and physical self-esteem via self-determined motivation in school students. School students aged 12 to 16 years from Estonia (N = 816), Lithuania (N = 706), Hungary (N = 664), and Spain (N = 922) completed measures of perceived autonomy support from PE teachers, need satisfaction for autonomy, competence, relatedness, self-determined motivation, perceived effort and physical self-esteem. The results of the structural equation model (SEM) of each sample indicated that the students’ perceived autonomy support from the teacher was directly related to effort and indirectly via autonomous motivation, whereas physical self-esteem was related indirectly. Confirmatory factor analyses and multi-sample structural equation revealed well-fitting models within each sample with the invariances of the measurement parameters across four nations. The findings support the generalizability of the measures in the motivational sequence model to predict perceived effort and physical self-estee

A Cross-National Comparison of Consumers\u27 Attitudes Toward Direct Marketing and Purchase Intention

Existing research indicates that attitudes toward the three elements of direct marketing (the source, mode, and response channel) influence consumers\u27 intentions to purchase directly marketed products. While research investigating attitudes and consumers\u27 response has been conducted in the U.S., there has been no research to date which examines attitude structures and purchase intentions towards direct marketing in a multi-country setting, in spite of the standardized global efforts of direct marketeers. This study presents findings on attitude structures regarding direct marketing for three affluent open markets, the U.S., Singapore, and the Netherlands and empirically investigates the relationships between these consumers\u27 attitudes toward the three elements of direct marketing and purchase intentions

Statistical modelling of software reliability

During the six-month period from 1 April 1991 to 30 September 1991 the following research papers in statistical modeling of software reliability appeared: (1) A Nonparametric Software Reliability Growth Model; (2) On the Use and the Performance of Software Reliability Growth Models; (3) Research and Development Issues in Software Reliability Engineering; (4) Special Issues on Software; and (5) Software Reliability and Safety

A Comprehensive Analysis of Proportional Intensity-based Software Reliability Models with Covariates (New Developments on Mathematical Decision Making Under Uncertainty)

The black-box approach based on stochastic software reliability models is a simple methodology with only software fault data in order to describe the temporal behavior of fault-detection processes, but fails to incorporate some significant development metrics data observed in the development process. In this paper we develop proportional intensity-based software reliability models with time-dependent metrics, and propose a statistical framework to assess the software reliability with the timedependent covariate as well as the software fault data. The resulting models are similar to the usual proportional hazard model, but possess somewhat different covariate structure from the existing one. We compare these metricsbased software reliability models with eleven well-known non-homogeneous Poisson process models, which are the special cases of our models, and evaluate quantitatively the goodness-of-fit and prediction. As an important result, the accuracy on reliability assessment strongly depends on the kind of software metrics used for analysis and can be improved by incorporating the time-dependent metrics data in modeling

Modelling Open-Source Software Reliability Incorporating Swarm Intelligence-Based Techniques

In the software industry, two software engineering development best practices coexist: open-source and closed-source software. The former has a shared code that anyone can contribute, whereas the latter has a proprietary code that only the owner can access. Software reliability is crucial in the industry when a new product or update is released. Applying meta-heuristic optimization algorithms for closed-source software reliability prediction has produced significant and accurate results. Now, open-source software dominates the landscape of cloud-based systems. Therefore, providing results on open-source software reliability - as a quality indicator - would greatly help solve the open-source software reliability growth-modelling problem. The reliability is predicted by estimating the parameters of the software reliability models. As software reliability models are inherently nonlinear, traditional approaches make estimating the appropriate parameters difficult and ineffective. Consequently, software reliability models necessitate a high-quality parameter estimation technique. These objectives dictate the exploration of potential applications of meta-heuristic swarm intelligence optimization algorithms for optimizing the parameter estimation of nonhomogeneous Poisson process-based open-source software reliability modelling. The optimization algorithms are firefly, social spider, artificial bee colony, grey wolf, particle swarm, moth flame, and whale. The applicability and performance evaluation of the optimization modelling approach is demonstrated through two real open-source software reliability datasets. The results are promising.Comment: 14 pages, 11 figures, 7 table

Models for Paired Comparison Data: A Review with Emphasis on Dependent Data

Thurstonian and Bradley-Terry models are the most commonly applied models in the analysis of paired comparison data. Since their introduction, numerous developments have been proposed in different areas. This paper provides an updated overview of these extensions, including how to account for object- and subject-specific covariates and how to deal with ordinal paired comparison data. Special emphasis is given to models for dependent comparisons. Although these models are more realistic, their use is complicated by numerical difficulties. We therefore concentrate on implementation issues. In particular, a pairwise likelihood approach is explored for models for dependent paired comparison data, and a simulation study is carried out to compare the performance of maximum pairwise likelihood with other limited information estimation methods. The methodology is illustrated throughout using a real data set about university paired comparisons performed by students.Comment: Published in at http://dx.doi.org/10.1214/12-STS396 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Adapting tam and ECT: continuance intention of e-shopping in Saudi Arabia

The objective of this study is to clarify the theoretical problem and identify factors that could explain the level of continuance intention of e-shopping in context of Saudi Arabia. The study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure age differences with regard to continuance online shopping intentions. Structural equation model confirms model fit. The research findings confirm that Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance. The structural weights are mostly equivalent between the young and old groups, but the regression path from subjective norms to perceived usefulness is not invariant, with that relationship being stronger for the younger respondents. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The model explains 65% of the intention to continue shopping online. The research findings suggest that online strategies cannot ignore either the direct and indirect effects on continuance intentions

Understanding the factors that derive continuance intention of e-shopping in Saudi Arabia: Age group differences in behaviour

The objective of this study is to clarify the theoretical problem and identify factors that could explain the level of continuance intention of e-shopping in context of Saudi Arabia. The study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure age differences with regard to continuance online shopping intentions in Saudi Arabia. The sample (n=465) consists of 68.8% women and 31.4% men, 348 younger than 35 years old and 117 older than 35. A structural equation model confirms model fit. The research findings confirm that Perceived usefulness, enjoyment, and subjective norms are determinants of online shopping continuance in Saudi Arabia. The structural weights are mostly equivalent between the young and old groups, but the regression path from subjective norms to perceived usefulness is not invariant, with that relationship being stronger for the younger respondents. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The model explains 65% of the intention to continue shopping online. The research findings suggest that online strategies cannot ignore either the direct and indirect effects on continuance intentions in Saudi Arabia. The model can be generalized across the three main commercial regions of Saudi Arabia

Driving online shopping: Spending and behavioral differences among women in Saudi Arabia

This study proposes a revised technology acceptance model that integrates expectation confirmation theory to measure gender differences with regard to continuance online shopping intentions in Saudi Arabia. The sample consists of 650 female respondents. A structural equation model confirms model fit. Perceived enjoyment, usefulness, and subjective norms are determinants of online shopping continuance in Saudi Arabia. High and low online spenders among women in Saudi Arabia are equivalent. The structural weights are also largely equivalent, but the regression paths from perceived site quality to perceived usefulness is not invariant between high and low e-shoppers in Saudi Arabia. This research moves beyond online shopping intentions and includes factors affecting online shopping continuance. The research model explains 60% of the female respondents’ intention to continue shopping online. Online strategies cannot ignore either the direct and indirect spending differences on continuance intentions, and the model can be generalized across Saudi Arabia