Search results

Understanding people’s intentions to be an internet entrepreneur is an important issue for educators, academics and practitioners. The purpose of this paper is to develop and validate a scale to measure internet entrepreneurial self-efficacy.

Based on an analysis of 356 responses, a scale of internet entrepreneurial self-efficacy is validated in accordance with established scale development procedures.

The internet entrepreneurial self-efficacy scale has 16 items under three factors (i.e. leadership, technology utilization and internet marketing and e-commerce). The scale demonstrated adequate convergent validity, discriminant validity and criterion-related validity. Nomological validity was established by the positive correlation between the scale and, respectively, internet entrepreneurship knowledge and entrepreneurial intention.

This study is a pioneering effort to develop and validate a scale to measure internet entrepreneurial self-efficacy. The results of this study are helpful to researchers in building internet entrepreneurship theories and to educators in assessing and promoting individuals’ internet entrepreneurial self-efficacy and behavior.

The study aims to examine the relationships among personality traits (i.e. the Big Five personality traits and locus of control), self-perceived facial attractiveness, motivations (i.e. intrinsic and extrinsic motivation) and intention toward live stream broadcasting. It also investigates the moderating role of perceived behavioral control in the relationship between motivations and intention.

Data collected from a sample of 637 participants are used to examine the research model and test the hypotheses with the employment of partial least squares structural equation modeling.

The study shows that motivations and perceived behavioral control are significant predictors of intention. Perceived behavioral control has a significant moderating effect between motivations and intention. Intrinsic motivation is positively influenced by self-perceived facial attractiveness, agreeableness, extraversion and internal locus of control, while extrinsic motivation is positively predicted by self-perceived facial attractiveness, conscientiousness and extraversion.

This study enhances our understanding of the determinants of intention toward live stream broadcasting by exploring its relationships with motivations, self-perceived facial attractiveness and personality, as well as the moderating effects of perceived behavioral control.

Analysis of characteristic driving operations can help develop supports for drivers with different driving skills. However, the existing knowledge on analysis of driving skills only focuses on single driving operation and cannot reflect the differences on proficiency of coordination of driving operations. Thus, the purpose of this paper is to analyze driving skills from driving coordinating operations. There are two main contributions: the first involves a method for feature extraction based on AdaBoost, which selects features critical for coordinating operations of experienced drivers and inexperienced drivers, and the second involves a generating method for candidate features, called the combined features method, through which two or more different driving operations at the same location are combined into a candidate combined feature. A series of experiments based on driving simulator and specific course with several different curves were carried out, and the result indicated the feasibility of analyzing driving behavior through AdaBoost and the combined features method.

AdaBoost was used to extract features and the combined features method was used to combine two or more different driving operations at the same location.

A series of experiments based on driving simulator and specific course with several different curves were carried out, and the result indicated the feasibility of analyzing driving behavior through AdaBoost and the combined features method.

There are two main contributions: the first involves a method for feature extraction based on AdaBoost, which selects features critical for coordinating operations of experienced drivers and inexperienced drivers, and the second involves a generating method for candidate features, called the combined features method, through which two or more different driving operations at the same location are combined into a candidate combined feature.

Cooperative driving refers to a notion that intelligent system sharing controlling with human driver and completing driving task together. One of the key technologies is that the intelligent system can identify the driver’s driving intention in real time to implement consistent driving decisions. The purpose of this study is to establish a driver intention prediction model.

The authors used the NIRx device to measure the cerebral cortex activities for identifying the driver’s braking intention. The experiment was carried out in a virtual reality environment. During the experiment, the driving simulator recorded the driving data and the functional near-infrared spectroscopy (fNIRS) device recorded the changes in hemoglobin concentration in the cerebral cortex. After the experiment, the driver’s braking intention identification model was established through the principal component analysis and back propagation neural network.

The research results showed that the accuracy of the model established in this paper was 80.39 per cent. And, the model could identify the driver’s braking intent prior to his braking operation.

The limitation of this study was that the experimental environment was ideal and did not consider the surrounding traffic. At the same time, other actions of the driver were not taken into account when establishing the braking intention recognition model. Besides, the verification results obtained in this paper could only reflect the results of a few drivers’ identification of braking intention.

This study can be used as a reference for future research on driving intention through fNIRS, and it also has a positive effect on the research of brain-controlled driving. At the same time, it has developed new frontiers for intention recognition of cooperative driving.

This study explores new directions for future brain-controlled driving and wheelchairs.

The driver’s driving intention was predicted through the fNIRS device for the first time.

This paper aims to provide a new method to study and improve the dynamic characteristics of the four-column resistance strain force sensor through the elastomer structure design and optimization.

Based on the mechanism analysis method, the authors first present a dynamic characteristic model of the four-column resistance strain force sensors’ elastomer. Then, the authors verified and modified the model according to the Solidworks finite element simulation results. Finally, the authors designed and optimized two types of four-column elastomers based on the dynamic characteristic model and verified the improvement of sensor dynamic performance through a hammer knock dynamic experiment.

The Solidworks finite element simulation and hammer knock dynamic experiment results show that the relative error of the model is less than 10%, which confirms the accuracy of the model. The dynamic performance of the sensors based on the model can be improved by more than 30%, which is a great improvement in sensor dynamic performance.

The authors first present a dynamic characteristic model of the four-column elastomer and optimize the four-column sensors successfully based on the mechanism analysis method. And a new method to study and improve the dynamic characteristics of the resistance is provided.

The spatiotemporal compression effect of China–Europe Railway Express (CR-Express) can reduce the flow costs of resources between China’s node cities. Additionally, it can break through the limitations of low-added-value marine products, significantly impacting the logistics industry efficiency. However, there are few literature verifying and analyzing its heterogeneity. This study explores the impact of CR-Express on the efficiency of logistics industry in node cities and analyzes the heterogeneity.

First, this study uses panel data to measure the efficiency of node city logistics industry. Secondly, this study discusses the impact of the opening of CR-Express on the efficiency of logistics industry in node cities based on the multi-period differential model. Finally, according to the node city difference, the sample city experimental group is grouped for heterogeneity analysis.

The results show that CR-Express can promote the urban logistics industry efficiency, with an average effect of 4.55%. According to the urban characteristics classification, the heterogeneity analysis shows that the efficiency improvement effect of logistics industry in inland cities is more obvious. The improvement effect of node cities and central cities in central and western China is stronger, especially in the sample of megacities and type I big cities. Compared with non-value chain industrial products, the CR-Express has significant promotion effects on the logistics efficiency of the cities where main goods are value chain products.

Under the background of double cycle development, this paper can provide a scientific basis for the investment benefit evaluation of CR-Express construction and the follow-up route planning.

This study aims to highlight the impact of altruistic-self and hunger awareness on socially responsible food consumption through the lens of self-awareness and self-congruity theories due to the great challenge of Sustainable Development Goal 2: Zero Hunger.

A survey was conducted with a sample of 812 respondents. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) confirm each variable's structure through the measurement model and test the hypothesis to support a structural model.

The results highlight that the combination of altruistic-self and hunger awareness (AS-HA congruence) drives consumers to execute socially responsible food consumption. Meanwhile, consumers' food-saving attitude mediation translates to the attitude towards responsible and ethical use increasing socially responsible food consumption, a contextual development in the theory of congruence. Conversely, hunger awareness is not confirmed as significantly influencing socially responsible food consumption.

This research provides valuable insights for academicians and practitioners in developing food waste management strategies that can be implemented to reduce food wastage.

Food waste is a global concern and is challenging for many manufacturing, distribution and individual wastage levels. However, food wastage by consumers is one of the most critical problems which can be minimised with awareness and attitudinal changes in behaviour as a form of socially responsible consumption.

This study aims to elucidate the process and internal mechanism of place identity construction in traditional villages under the impact of tourism by taking Cuandixia village as a case. The research methods comprise participatory observation and in-depth interviews with the residents. The main results are as follows: the impact of tourism on traditional villages is mainly reflected in space reconstruction, livelihood change, social relations restructuring and culture change; under the impact of tourism, the representation of residents’ identity construction shows complexity, with positive and negative effects; and the place identity construction of residents affects their perception of and attitudes toward tourism. Moreover, self-esteem and self-efficacy principles play a key role in their perception of tourism. This study provides some reference for further investigation of the tourism development model and the mental mechanism of residents in traditional villages.

This study aims to test the compensatory consumption theory with the explicit hypothesis that China's new-rich tend to waste relatively more food.

In this study, the authors use Heckman two-step probit model to empirically investigate the new-rich consumption behavior related to food waste.

The results show that new-rich is associated with restaurant leftovers and less likely to take them home, which supports the compensatory consumption hypothesis.

Understanding the empirical evidence supporting compensatory consumption theory may improve forecasts, which feed into early warning systems for food insecurity. And it also avoids unreasonable food policies.

This research is a first attempt to place food waste in a compensatory-consumption perspective, which sheds light on a new theory for explaining increasing food waste in developing countries.

Minimizing the energy consumption in a wireless sensor node is important for lengthening the lifetime of a battery. Radio transmission is the most energy-consuming task in a wireless sensor node, and by compressing the sensor data in the online mode, it is possible to reduce the number of transmission periods. This study aims to demonstrate that temporal compression methods present an effective method for lengthening the lifetime of a battery-powered wireless sensor node.

In this study, the energy consumption of LoRa-based sensor node was evaluated and measured. The experiments were conducted with different LoRaWAN data rate parameters, with and without compression algorithms implemented to compress sensor data in the online mode. The effect of temporal compression algorithms on the overall energy consumption was measured.

Energy consumption was measured with different LoRaWAN spreading factors. The LoRaWAN transmission energy consumption significantly depends on the spreading factor used. The other significant factors affecting the LoRa-based sensor node energy consumption are the measurement interval and sleep mode current consumption. The results show that temporal compression algorithms are an effective method for reducing the energy consumption of a LoRa sensor node by reducing the number of LoRa transmission periods.

This paper presents with a practical case that it is possible to reduce the overall energy consumption of a wireless sensor node by compressing sensor data in online mode with simple temporal compression algorithms.