Search results

The purpose of this paper is to evaluate the technical efficiency and production risk in China's rice production and examine the effect of factor market reform on these two agricultural performance metrics.

Using an unbalanced farm-level panel data with 2,193 observations on 329 rice farms from 2004 to 2016, the authors estimate a translog stochastic production frontier model that accounts for both technical inefficiency and production risk. A one-step procedure through the maximum likelihood method that combines the stochastic production frontier, technical inefficiency and production risk functions is used to circumvent the bias problem often found in the conventional two-step model.

Estimation results show that both land and labor market reforms significantly improved the level of technical efficiency over the years, although the effect of land market deregulation is of a much higher magnitude compared to the latter. The land market reform, however, has also increased the risk of production. The authors further find that a higher proportion of hired labor in total labor cost helps lower production risk, while also acting to decrease technical efficiency. Additionally, agricultural subsidies not only increased the output variability but also lowered technical efficiency

First, the authors evaluate the effect of market deregulation on technical efficiency and production risk under a stochastic frontier framework that simultaneously accounts for both production performance metrics, which is important from a statistical point of view. Further, the authors exploit both cross-sectional and time-series variations in a panel setting to more accurately estimate the technical inefficiency scores and production risk for individual farmers, and investigate how the exogenous land and labor market reforms influence these two production performance measures in China's rice farming. This is the first study in the literature to analyze these questions under a panel framework.

This paper mainly aims to deal with the problems of uncertainties including modelling errors, unknown dynamics and disturbances caused by load mutation in control of permanent magnet synchronous motor (PMSM).

This paper proposes an enhanced speed sensorless vector control method based on an active disturbance rejection controller (ADRC) for a PMSM. First, a state space model of the PMSM is obtained for the field orientation control strategy. Second, a sliding mode observer (SMO) based on back electromotive force (EMF) is introduced to replace the encode to estimate the rotor flux position angle and speed. Third, an infinite impulse response (IIR) filter is introduced to eliminate high frequency noise mixed in the output of the sliding mode observer. In addition, a speed control method based on an extended state observer (ESO) is proposed to estimate and compensate for the total disturbances. Finally, an experimental set-up is built to verify the effectiveness and superiority of the proposed ADRC-based control method.

The comparative experimental results show that the proposed speed sensorless control method with the IIR filter can achieve excellent robustness and speed tracking performance for PMSM system.

An enhanced sensorless control method based on active disturbance rejection controller is designed to realize high precision control of the PMSM; the IIR filter is used to attenuate the chattering problem of traditional SMO; this method simplifies the system and saves the total cost due to the speed sensorless technology.

The use of sensorless can reduce costs and be more beneficial to actual industrial application.

The proposed enhanced speed sensorless vector control method based on an ADRC with the IIR filter enriches the control method of PMSM. It can ameliorate system robustness and achieve excellent speed tracking performance.

This research proposes and examines a theoretical model grounded in anthropomorphism theory considering the curvilinear and linear relationships between service robot anthropomorphism and consumer usage intention and explores the mediating effect of perceived risk.

To examine the developed model, two complementary studies are designed. In Study 1, multi-time data of 511 participants show that service robot anthropomorphism inverts U-shaped (curvilinear) relationship on consumer usage intention and perceived risk mediates this curvilinear relationship. In Study 2, multi-source data of 460 volunteers are used to confirm the findings of Study 1 and examine that consumer empathy moderates the complex nonlinear effect of service robot anthropomorphism on perceived risk, and the indirect curvilinear effect of service robot anthropomorphism on consumer usage intention through perceived risk.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

This research provides preliminary and yet important findings on how service robot anthropomorphism most likely is positively associated with consumer usage intention, i.e. the positively influence mechanism of service robot anthropomorphism on consumer usage intention.

In recent years, Malaysia has seen a dramatic change in the landscape of financial transactions due to the fast growth of mobile payment systems. This study aims to examine the technological, organisational and environmental (TOE) factors of merchants’ adoption intention to use mobile payment platforms essential for the continuing development and profitability of these cutting-edge payment options.

The research model was developed from the TOE framework and tested with the data collected from 120 merchants in Malaysia. The partial least squares structural equation modelling technique was used in analysing the collected data.

Technology readiness and competitor pressure were directly related to merchants' mobile payment adoption intention and indirectly through perceived strategic value. Also, perceived ease of use and perceived strategic value were significant predictors of the adoption intention of mobile payment.

This model demonstrates the relevance of TOE in explaining merchants' mobile payment adoption intention, with implications for policy and strategy to support the broader adoption of mobile payment platforms in Malaysia.

This study aims to identify the significant factors that influence the continuation intention (CI) to use a digital wallet in the regions with low technology infrastructure and among the consumers possessing low levels of digital and financial literacy.

Data for the study were collected from the rural parts of South India with 295 digital wallet users. Co-variance-based structural equation modelling (SEM) (CB-SEM) using maximum likelihood estimation method and Bayesian SEM (BSEM) approaches were executed to test the influence of independent variables on the dependent variable and to ensure the validation of the proposed hypothetical model.

The results showed that trust, incentives, technology satisfaction (TS), facilitating condition, performance expectancy, effort expectancy, habit and hedonic motivation significantly influenced the CI to use a digital wallet. In addition, incentives positively impact habit for the CI to use a digital wallet.

The present study is based on the samples from the regions with low technology infrastructure and among the consumers possessing low levels of digital and financial literacy in the rural parts of South India, which limits the generalisation of results.

The results provide impetus to the government, digital wallet marketers and users regarding how the CI to use a digital wallet can be encouraged among the low-adoption regions.

This study remains unique as the assessment of CI to use a digital wallet was conducted in low-adoption regions (rural parts of India) in extending Unified theory of acceptance and use of technology 2 with TS. A comparison of results arrived from CB-SEM with those of the BSEM ensures that the validation of the hypothetical model is found to be another major methodological contribution towards the consumer behaviour literature.

This study aims to investigate the influence of environmental factors on individual personality traits associated with mobile paymens (MP) adoption using the technological personal environment (TPE) theory as a framework for the proposed theoretical model.

A total of 736 feedback from respondents was used to validate the proposed model using structural equation modeling. The model comprises Trust and Self-efficacy to explain MP adoption from a personal trait perspective. Meanwhile, environmental aspects are represented by social influence, vendor regulations and network externalities.

The result indicates that self-efficacy has the most significant direct effect on user intention to use MP, followed in decreasing order of significance by social influence, trust, vendor regulations and network externalities. Furthermore, social influence is the most contributing aspect from the environmental area that influences user intention directly and indirectly through trust and self-efficacy as mediators. Meanwhile, the moderating effect analysis also found that gender moderates the effect of user self-efficacy on MP adoption.

This study fills the gap by comparing trust and self-efficacy and exploring how those factors are developed and affected by the environmental aspect of MP usage. It was discovered that self-efficacy was the most influential construct influencing the adoption of MP. Social influence was identified as the primary environmental factor that directly impacts user intention regarding MP usage. Furthermore, gender was shown as a moderator, as males place a higher value on self-efficacy as a factor affecting their intention to embrace MP in comparison to females.