Search results

This paper examines pre- and post-production water treatment practices among food processors and investigates factors, especially managerial perceptions of environmental pressure that encourage or preclude either process.

To consider potential spillover effects across two water-treatment practices, the bivariate probit model based on random utility theory is used to investigate how practices are influenced by managerial perceptions of environmental pressure and measured by manager perceptions on water costs, water availability, water safety and quality.

Results indicate that firms with a managerial perception that water costs are low are less likely to conduct both pre- and post-production water treatment practices, while the perception of high water quality has a negative effect on water treatment prior to use. This study also confirms the positive correlation of the pre- and post-water treatment practices among food processors. Practices also change with firm features including production scope, scale, target market and expected future sales growth.

This study provides unique insights about water treatment practices and generates knowledge to enhance food safety and environmental sanitation in the food industry. Results are helpful to design and provide additional training and educational programs that target the enhancement of environmental and water quality awareness among food company managers and modify food safety policy instruments and environmental regulations pertaining to surface water resources.

Research exploring water-treatment practices in the food industry has been limited. Using a representative sample of food processors in the city of Shanghai, this study contributes to the literature on the examination of internal drivers of voluntary environmental management (VEM) with a focus on managerial perceptions of environmental pressure, establishes the correlation between pre- and post-production water treatment practices and identifies and quantifies the effects of relevant factors.

The present research aims to identify determinants for citizen’ behavioural adoption of e-government, explore relationships among these variables and investigate whether the proposed model can provide a more comprehensive manner to understand the adoption of e-government.

First, a survey is administered to collect data, then the Cronbach’s alpha is assessed for internal consistency of measurement scales; second, confirmatory factor analysis is conducted to evaluate the measurement model; finally, a structural equation model is used to test the proposed hypotheses and explore the determinants of e-government adoption.

Results indicate that the proposed model is a stable model with powerful explanatory of variation. In addition, some new relationships in the e-government context are found, whose disposition to trust has positive effect on social norms, whereas perceived risk negatively influences perceived behaviour control. Moreover, other key dominants have been investigated.

The findings have enabled us to better understand factors affecting intention and also provided a solid theoretical research model for future study.

At present, the research on energy consumption of human clothing mainly focuses on behavior observation method, questionnaire survey method, heart rate monitoring method and electronic motion sensor, etc. In order to solve the problem of energy consumption caused by clothing with different characteristics, an identification method of energy consumption for different types of clothing was proposed.

The model robot was designed to reproduce the motion state by simulating the human body in the working mode, and the protective energy consumption test platform was built. In order to explore the influence of different characteristics of clothing on the energy consumption of equipment system, orthogonal experiments were carried out on the model robot experimental platform, and a mathematical model for predicting the energy consumption of clothing based on Tabu search algorithm to optimize support vector machine regression (TS-SVR) optimized by tabu algorithm was proposed.

Compared with three regression prediction algorithms, the accuracy of the model was quantified by the determination coefficient and root mean square error according to the predicted value of the model and the actual value of the experiment. The results showed that the model based on TS-SVM can predict the energy consumption of human body more accurately.

Based on TS-SVR model, it can well predict the relationship between clothing with different characteristics and physical energy consumption, and can accurately evaluate the clothing grade of different characteristics.

This study aims to identify the factors to food safety certification adoption among farmers in Malaysia.

This study was conducted qualitatively using a method of interviewing with unstructured questions. To identify the factors that influence and prevent the adoption of food safety certification among Malaysian farmers, nine (n = 9) agricultural industrial experts were randomly chosen.

Based on data analysis using thematic analysis, the respondent highlighted 14 factors to food safety certification. Specifically, the most frequent determinant highlighted by the respondent is enforcement (12). Additionally, it has been proven that the identified factors aligned with existing theories: technology, organization and environment (TOE) framework and eco-innovation theory. These theories help researchers to create effective strategies and produce significant findings from their research.

To the best of the authors’ knowledge, this study is the first to investigate food safety certification adoption among farmers in the Malaysian agriculture industry using the integration of the TOE framework and eco-innovation theory. The stakeholder is expected to receive the benefits of creating efficient campaigns to encourage more farmers to obtain food safety certification. This study provides further knowledge by improving the understanding of the processes involved in certification adoption, providing context-specific insights, best practices, policy guiding development and emphasizing the effects of certification on sustainability and competitiveness.

This study aims to solve the problem that the traditional hierarchically performed hazard origin and propagation studies (HiP-HOPS) cannot make dynamic model for the complex system such as integrated modular avionics (IMA) system.

A new combination method that combines HiP-HOPS with architecture analysis and design language (AADL) is proposed.

The combination method potentially reduces the amount of rework required for safety analysis and modelling of a modified design.

Modelling the IMA system with the combination method can just make qualitative analysis but cannot make quantitative analysis.

The static model depicts the fault propagation among the components while the dynamic model describes the composite fault with AADL for IMA system.

The results of the case study show that the proposed method not only keeps model consistency but also makes safety analysis and modelling for IMA system efficiently.

The purpose of this study is to increase maximum lift/drag ratio (E_max) of tactical unmanned aerial vehicles (TUAVs) via applying novel small aerodynamic modifications.

A TUAV is manufactured in Erciyes University, Faculty of Aeronautics and Astronautics, Model Aircraft Laboratory. It has both passive and active morphing capabilities. Its nosecone and tailcone shapes are redesigned to improve E_max. Moreover, active flow control is also built on its wing for improving E_max.

Using these novel small aerodynamic modifications, considerable improvement on E_max is obtained.

Permission of Directorate General of Civil Aviation in Turkey is required for testing TUAVs in real-time applications.

Small aerodynamic modifications such as nosecone-tailcone shape modifications and building active flow control on wing are very beneficial for improving E_max of TUAVs.

Small aerodynamic modifications satisfy confidence, high performance and easy utility demands of TUAV users.

The study will enable the creation of novel approaches to improve E_max value and therefore aerodynamic performance of TUAVs.