Search results

Financing remains a serious concern for firms and is considered the main hurdle in the growth and development of small and medium enterprises (SMEs). Recently, a new stream of financing (SCF; supply chain finance) has emerged to meet the financing issues of SMEs. Therefore, measuring SCF is essential to support SMEs’ operations. This study aims to develop and validate the SCF scale based on extant literature.

Using a mixed-method approach, this study recruited different samples of SME entrepreneurs to confirm the internal consistency, assess construct validity and check the item structure of the SCF scale in AMOS.

The outcomes of confirmatory factor analysis demonstrated the six factors of SCF (inventory financing, working capital optimization, reverse financing, fixed assets financing, logistics financing and order cycle financing) spread over 21 items. An interitem solid structure of the SCF scale offers invaluable contributions to the supply chain management literature.

This research supports SME entrepreneurs to obtain secure financing at the best cost, mitigating the risk of default, supporting the buyers’ payment terms, providing early payment to suppliers and strengthening the firm’s value chains. SMEs can obtain financing per their requirements to support their operational business processes. Moreover, SMEs can plan, manage and control finance-related transactional activities by correctly identifying financing solutions.

The present study contributes to SCM literature by developing and validating the SCF scale. To the best of the author’s knowledge, this is the first study that redefined SCF and identified its six dimensions.

This study aims to investigate the supplier selection criteria, relationship quality and level of collaboration in Asian food businesses, while also examining the link between these practices and business performance. The research focusses on food manufacturing and exporting companies in two emerging economies, China and Vietnam.

Food manufacturing and exporting companies in two emerging economies – China and Vietnam were surveyed and analysed to extract factors that reflect supplier management and business performance along with their relationship by factor analysis and hierarchical regression. Then, a two-step cluster analysis was applied to identify clusters based on supplier management and explore how different business performance groups manage their suppliers.

Four clusters that are distinct sets of food firms with detailed references about their typical characteristics revealing their business performance and supplier management practices. Also, the study confirms that certificates, reliability and inspection results constitute the factor of quality-related criteria for food firms. It is an interesting insight into what firms prioritise in selecting and maintaining collaboration and relationships with suppliers that reflect actual demanding specifications for supplier conformity.

The study reveals the business status of the studied companies and each group's specific references, such as the criteria they prefer to select suppliers, the relationship quality and the level of collaboration.

The study is a useful reference for both researchers and practitioners to have a comprehensive view of supplier management in the food industry based on the viewpoint of Asian food manufacturers.

Research efforts aiming to improve understanding of how various organisational relationships contribute to better food quality (FQ) in a constantly changing business environment are limited. This study examines the effects of supply chain (SC) organisations on the quality of food products across multi-tiered segments with dynamic business situations.

Guided by a conceptual research framework based on contingency theory and netchain analysis, moderation-based partial least squares structural equation modelling (PLS-SEM) was used to analyse multi-tiered data from 405 shrimpers and 238 women processors in Akwa-Ibom, Lagos and Ondo states in Nigeria.

The authors' findings show that unpredictable business environments such as market turbulence (MT), power asymmetry (PA) and distrust (DT) not only directly influence SC organisations but also moderate how organisational networks contribute to improved FQ. Further results reveal that closer vertical ties such as relational contracts are prerequisites for small-scale actors to guarantee improved FQ along multiple nodes of the food system.

This is the first study to examine, from a contingency and multi-tiered perspective, how small-scale actors can maintain FQ across interdependent nodes of a food chain in a developing country context and to explore the complex interplay between SC networks and the quality of highly perishable food products in unpredictable business environments. Relevant theoretical and policy implications are discussed.

This research paper aims to examine two hybrid models of logistics service quality (LSQ) and its influence on satisfaction, loyalty and future purchase intention in a business-to-consumer (B2C) e-commerce context. This study extends the literature for LSQ by incorporating the second-order assurance quality construct, which comprises personnel contact quality, order discrepancy handling and order returns, into one of the hybrid models.

A survey-based approach is used to collect data. Participant responses to questions concerning multiple LSQ dimensions and behavioral perceptions from their most recent online shopping experience are measured using structural equation modeling.

Findings highlight the importance of including a second-order construct assurance quality as a more explanatory model. Results illustrate that online ordering procedures and assurance quality impact customer satisfaction more than other prominent LSQ dimensions. Furthermore, the findings revealed a customer loyalty is a partial mediator between customer satisfaction and future purchase intention. This underscores the significance of improved logistics services as a competitive edge for e-commerce retailers.

Implications are limited to the e-commerce B2C domain.

The findings of this study underscore critical LSQ dimensions that garner greater satisfaction and retention in the online shopping experience. The results indicate that the effective and efficient handling of the initial order and any order problem significantly influences customer satisfaction and reaps the long-term benefits of customer retention.

The authors present and empirically test a hybrid model of LSQ in a B2C e-commerce domain that captures many of the important elements of the customer experience as espoused in the literature.

This paper aims to study whether the adoption of an entry mode that fits the social trust level contributes to the improvement of foreign subsidiary performance.

The authors used the Probit model, linear regression, strategic fit approach and instrumental variable regression. The sample was made up of 11,095 observations of Chinese multinational enterprises' foreign subsidiaries in 54 countries from 2005 to 2020.

The results suggest that a host country with a high level of social trust results in fewer difficulties for enterprises in gaining legitimacy, thus foreign subsidiaries are more likely to select the wholly owned entry mode. The results also show that the effect is contingent on the formal institutions of host countries. The results of the mechanism test suggest that social trust influences subsidiaries' entry mode choice by reducing information asymmetry, costs and uncertainty risks. This study further finds that selecting a fit entry mode based on social trust level substantially increases foreign subsidiary performance and this effect is more significant when multinational enterprises (MNEs) are state-owned enterprises (SOEs).

The main limitation of this paper is its only focus on foreign subsidiaries of Chinese MNEs, which may limit the generalizability of research findings.

This paper responds to the call for conducting more research on informal institutions. Findings highlight the critical role of informal institutions in helping foreign subsidiaries in gaining legitimacy in host countries and the essentialness of selecting a fit entry mode based on the informal institutions of host countries for the development of foreign subsidiaries.

The Wiener-Hammerstein nonlinear system is made up of two dynamic linear subsystems in series with a static nonlinear subsystem, and it is widely used in electrical, mechanical, aerospace and other fields. This paper considers the parameter estimation of the Wiener-Hammerstein output error moving average (OEMA) system.

The idea of multi-population and parameter self-adaptive identification is introduced, and a multi-population self-adaptive differential evolution (MPSADE) algorithm is proposed. In order to confirm the feasibility of the above method, the differential evolution (DE), the self-adaptive differential evolution (SADE), the MPSADE and the gradient iterative (GI) algorithms are derived to identify the Wiener-Hammerstein OEMA system, respectively.

From the simulation results, the authors find that the estimation errors under the four algorithms stabilize after 120, 30, 20 and 300 iterations, respectively, and the estimation errors of the four algorithms converge to 5.0%, 3.6%, 2.7% and 7.3%, which show that all four algorithms can identify the Wiener-Hammerstein OEMA system.

Compared with DE, SADE and GI algorithm, the MPSADE algorithm not only has higher parameter estimation accuracy but also has a faster convergence speed. Finally, the input–output relationship of laser welding system is described and identified by the MPSADE algorithm. The simulation results show that the MPSADE algorithm can effectively identify parameters of the laser welding system.

This paper aims to study the agent learning from expert demonstration data while incorporating reinforcement learning (RL), which enables the agent to break through the limitations of expert demonstration data and reduces the dimensionality of the agent’s exploration space to speed up the training convergence rate.

Firstly, the decay weight function is set in the objective function of the agent’s training to combine both types of methods, and both RL and imitation learning (IL) are considered to guide the agent's behavior when updating the policy. Second, this study designs a coupling utilization method between the demonstration trajectory and the training experience, so that samples from both aspects can be combined during the agent’s learning process, and the utilization rate of the data and the agent’s learning speed can be improved.

The method is superior to other algorithms in terms of convergence speed and decision stability, avoiding training from scratch for reward values, and breaking through the restrictions brought by demonstration data.

The agent can adapt to dynamic scenes through exploration and trial-and-error mechanisms based on the experience of demonstrating trajectories. The demonstration data set used in IL and the experience samples obtained in the process of RL are coupled and used to improve the data utilization efficiency and the generalization ability of the agent.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.

Online reviews are regarded as a source of information for decision-making because of the abundance and ready availability of information. Whereas, the sheer volume of online reviews makes it hard for consumers, especially the older adults who perceive more difficulties in reading reviews and obtaining information compared to younger adults, to locate the useful ones. The main objective of this study is to propose an effective method to locate valuable reviews of mobile phones for older adults. Besides, the authors also want to explore what characteristics of the technology older adults prefer. This will benefit both e-retailers and e-commerce platforms.

After collecting online reviews related to mobile phones designed for older adults from a popular Chinese e-commerce platform (JD Mall), topic modeling, term frequency-inverse document frequency (TF-IDF), and linguistic inquiry and word count (LIWC) methods were applied to extract latent topics and uncover potential dimensions that consumers frequently referred to in their reviews. According to consumers' attitudes towards different popular topics, seven machine learning models were employed to predict the usefulness and popularity of online reviews due to their excellent performance in prediction. To improve the performance, a weighted model based on the two best-performing models was built and evaluated.

Based on the TF-IDF, topic modeling, and LIWC methods, the authors find that older adults are more interested in the exterior, sound, and communication functions of mobile phones. Besides, the weighted model (Random Forest: Decision Tree = 2:1) is the best model for predicting the online review popularity, while random forest performs best in predicting the perceived usefulness of online reviews.

This study’s findings can help e-commerce platforms and merchants identify the needs of the targeted consumers, predict reviews that will get more attention, and provide some early responses to some questions.

The results propose that older adults pay more attention to the mobile phones' exterior, sound, and communication function, guiding future research. Besides, this paper also enriches the current studies related to making predictions based on the information contained in the online reviews.

This paper aims to present a sliding mode control method based on disturbance observer (DO) for improving the reaching law of permanent magnet synchronous motor (PMSM).

Aiming at the insufficiency of the traditional exponential reaching law used in sliding mode variable structure control, an exponential reaching law related to the speed error is proposed. The improved exponential reaching law can adaptively adjust the size of the constant velocity term in the reaching law according to the size of the speed error, so as to adaptively adjust the speed of the system approaching the sliding mode surface to overcome the control deviation and improve the dynamic and steady state performance. To improve the anti-interference ability of the system, a DO is proposed to observe the external disturbance of the system, and the observed value is used to compensate the system. The stability of the system is analyzed by Lyapunov theorem. The effectiveness of this method is proved by simulation and experiment.

Simulation and experiment show that the proposed method has the advantages of fast response and strong anti-interference ability.

The proposed method cannot observe the disturbance caused by the change of internal parameters of the system.

A sliding mode control method for PMSM is proposed, which has good control performance. The proposed method can effectively suppress chattering, ensure fast response speed and have strong anti-interference ability. The effectiveness of the algorithm is verified by simulation and experiment.