Wei Wang, Yuting Xu, Yenchun Jim Wu and Mark Goh
Information distortion affects the perception of quality, which, in turn, influences investment decisions and determines the pledge results of fundraising. This study combines…
Abstract
Purpose
Information distortion affects the perception of quality, which, in turn, influences investment decisions and determines the pledge results of fundraising. This study combines signalling theory with persuasion theory to empirically study the effects of linguistic information distortion from fraudulent cues on a crowdfunding campaign's fundraising outcomes using text analytics, with implications for entrepreneurs, platforms and investors.
Design/methodology/approach
This study empirically analyzes 328,974 crowdfunding projects from the Kickstarter platform. Information distortion is detected using four indicators, based on text mining analytics. An econometric model is built to estimate the impact of information distortion, while the predictive power of the information distortion is detected through machine learning.
Findings
The results inform that distortion in the blurb, detailed description and reward statement dampen a campaign's success, but embellishing the entrepreneur's biography enhances the success of financing. Furthermore, information distortion exhibits a significant inverted U-shaped influence. The effect of the interaction terms suggests that campaigns with high pledge goals are more sensitive to information distortion, and that native-speaking entrepreneurs are adept at applying linguistic skills to promote the campaign.
Originality/value
This study provides a linguistic method to detect the influence of information distortion on crowdfunding campaigns. Further, the study offers some practical suggestions for entrepreneurs on how to generate attractive narratives, and contributes to the investor's decision-making and informs the platform's promotion strategy.
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Yong Wang, Yuting Liu and Fan Xu
Soft robots are known for their excellent safe interaction ability and promising in surgical applications for their lower risks of damaging the surrounding organs when operating…
Abstract
Purpose
Soft robots are known for their excellent safe interaction ability and promising in surgical applications for their lower risks of damaging the surrounding organs when operating than their rigid counterparts. To explore the potential of soft robots in cardiac surgery, this paper aims to propose an adaptive iterative learning controller for tracking the irregular motion of the beating heart.
Design/methodology/approach
In continuous beating heart surgery, providing a relatively stable operating environment for the operator is crucial. It is highly necessary to use position-tracking technology to keep the target and the surgical manipulator as static as possible. To address the position tracking and control challenges associated with dynamic targets, with a focus on tracking the motion of the heart, control design work has been carried out. Considering the lag error introduced by the material properties of the soft surgical robotic arm and system delays, a controller design incorporating iterative learning control with parameter estimation was used for position control. The stability of the controller was analyzed and proven through the construction of a Lyapunov function, taking into account the unique characteristics of the soft robotic system.
Findings
The tracking performance of both the proportional-derivative (PD) position controller and the adaptive iterative learning controller are conducted on the simulated heart platform. The results of these two methods are compared and analyzed. The designed adaptive iterative learning control algorithm for position control at the end effector of the soft robotic system has demonstrated improved control precision and stability compared with traditional PD controllers. It exhibits effective compensation for periodic lag caused by system delays and material characteristics.
Originality/value
Tracking the beating heart, which undergoes quasi-periodic and complex motion with varying accelerations, poses a significant challenge even for rigid mechanical arms that can be precisely controlled and makes tracking targets located at the surface of the heart with the soft robot fraught with considerable difficulties. This paper originally proposes an adaptive interactive learning control algorithm to cope with the dynamic object tracking problem. The algorithm has theoretically proved its convergence and experimentally validated its performance at the cable-driven soft robot test bed.
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Lan Xu and Yuting Zhang
This paper aims to explore the critical factors which affect the quality of preschool education service so that targeted and effective measures to improve service quality can be…
Abstract
Purpose
This paper aims to explore the critical factors which affect the quality of preschool education service so that targeted and effective measures to improve service quality can be put forward.
Design/methodology/approach
Evidential theory is applied to aggregate experts’ knowledge, and a fuzzy cognitive map (FCM) model of preschool education service quality is established to further carry out a simulation for inference, thus figuring out the critical factors to improve service quality.
Findings
The simulation results show that the main body of supervision and environment of governments and policies are two critical factors affecting the quality of preschool education service. More emphasis should be put on these two aspects, and corresponding measures can be put forward so as to ensure the quality of preschool education service.
Originality/value
This paper proposes a new model based on FCM and evidential theory to study the factors affecting preschool education service quality.
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Na Xu, Yanxiang Liang, Chaoran Guo, Bo Meng, Xueqing Zhou, Yuting Hu and Bo Zhang
Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a…
Abstract
Purpose
Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.
Design/methodology/approach
Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.
Findings
Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.
Originality/value
This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.
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Yuting Zhang, Lan Xu and Zhengnan Lu
The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of…
Abstract
Purpose
The purpose of this paper is to show that research on policy diffusion mechanism of Government Procurement of Public Services (GPPS) is beneficial to improve the efficiency of policy formulation and implementation.
Design/methodology/approach
In view of the four dimensions which are internal demand, external pressure, policy innovation environment and service characteristic, a system of factors affecting policy diffusion is established. On this basis, a Multilayer Fuzzy Cognitive Map (MFCM) model for policy diffusion of GPPS is constructed. Nonlinear Hebbian Learning algorithm and genetic algorithm are applied to optimize the two components of the MFCM model, which are relationship between nodes at the same layer and influence weights between nodes at different layers, respectively. Taking Nanjing municipal government purchasing elderly-care services in China as the empirical object, simulation of policy diffusion based on the MFCM model is carried out, aiming to obtain the key factors influencing policy diffusion and the dynamic diffusion mechanism of GPPS policy.
Findings
Research results show that, compared with monolayer Fuzzy Cognitive Map, the MFCM model converges faster. In addition, simulation results of policy diffusion indicate that economic development level of jurisdiction, superior pressure, administrative level and operability of services are key influencing factors which are under four dimensions correspondingly. And the dynamic influencing mechanism of key factors has also been learned.
Originality/value
This paper constructs the MFCM model, which is a new approach based on several monolayer FCMs, to study the policy diffusion mechanism.
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Wei Yang, Linghui Xu, Linfan Yu, Yuting Chen, Zehao Yan and Canjun Yang
Walking-aid exoskeletons can assist and protect effectively the group with lower limb muscle strength decline, workers, first responders and military personnel. However, there is…
Abstract
Purpose
Walking-aid exoskeletons can assist and protect effectively the group with lower limb muscle strength decline, workers, first responders and military personnel. However, there is almost no united control strategy that can effectively assist daily walking. This paper aims to propose a hybrid oscillators’ (HOs) model to adapt to irregular gait (IG) patterns (frequent alternation between walking and standing or rapid changing of walking speed, etc.) and generate compliant and no-delay assistive torque.
Design/methodology/approach
The proposed algorithm, HOs, combines adaptive oscillators (AOs) with phase oscillator through switching assistive mode depending on whether or not the AOs' predicting error of hip joint degree is exceeded our expectation. HOs can compensate for delay by predicting gait phase when in AOs mode. Several treadmill and free walking experiments are designed to test the adaptability and effectiveness of HOs model under IG.
Findings
The experimental results show that the assistive strategy based on the HOs is effective under IG patterns, and delay is compensated totally under quasiperiodic gait conditions where a smoother human–robot interaction (HRI) force and the reduction of HRI force peak are observed. Delay compensation is found very effective at improving the performance of the assistive exoskeleton.
Originality/value
A novel algorithm is proposed to improve the adaptability of a walking assist hip exoskeleton in daily walking as well as generate compliant, no-delay assistive torque when converging.
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This study aims to examine how intercultural competence (IC) among university students can be enhanced through two streams of higher education internationalization…
Abstract
Purpose
This study aims to examine how intercultural competence (IC) among university students can be enhanced through two streams of higher education internationalization: internationalization abroad and internationalization at home (IaH). By doing so, it aims to improve university students' IC through identifying which factors are more effective in fostering IC.
Design/methodology/approach
The study is not solely a literature review, but rather a conceptual exploration based on a selective review of the literature. Due to the exploratory nature of this study, we employed a thematic analysis approach to reviewing English language literature while incorporating relevant Chinese literature to ensure a more balanced representation.
Findings
We found that international students’ IC is influenced by their overseas learning experiences, which are closely related to the duration of stay, language proficiency, intercultural contact, university management and teachers and administrative support. On the other hand, domestic students’ IC has been influenced by various IaH experiences primarily within their home university campus, such as foreign language learning, international curriculum, extracurricular activities, communication between domestic and international students, integrated management of international students, the use of Internet and communication technology and so forth. Although a direct and definitive comparison is lacking, some comparative analyses suggest that IaH experiences may yield better results in enhancing the IC of domestic students.
Originality/value
This article advances the understanding of IC development. We call for further research that values the importance of IaH in the increasingly uncertain globalization and delves into comparative analysis of the effects of two streams of higher education internationalization.
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Juan Wang, Jie Fang and Yuting Wang
This study disentangles the impact of consumers’ adoption of mini-program channels on social media on their purchase behavior in e-marketplaces from a multichannel retailer’s…
Abstract
Purpose
This study disentangles the impact of consumers’ adoption of mini-program channels on social media on their purchase behavior in e-marketplaces from a multichannel retailer’s perspective and examines the moderating roles of two types of brand messages (informational and transformational messages).
Design/methodology/approach
Based on 2,204 transaction records from a Chinese multichannel retailer, this study used a Poisson regression model with fixed effects for empirical testing. The case of the WeChat mini-program in China was employed.
Findings
Adopting mini-program channels on social media reduces consumers’ purchase frequency but increases their purchase breadth in e-marketplaces. Moreover, informational messages worsen the negative effect of mini-program channel use on purchase frequency. In contrast, transformational messages reduce the negative effect of mini-program channel use on purchase frequency and amplify its positive effect on purchase breadth.
Practical implications
Managers can effectively leverage mini-programs to widen the range of consumers’ product purchases in e-marketplaces and the intensity of transformation messages posted within mini-programs to alleviate their negative impact on purchase frequency in e-marketplaces.
Originality/value
Previous studies only focus on the intrachannel impact of mini-program channels; however, this study highlights their cross-channel impact. Its findings underscore the dual role of mini-program channel use in e-marketplaces. Additionally, the nuanced moderating effects of informational and transformational messages enrich our understanding of mini-program channels on social media. Moreover, a substitution framework is utilized to understand the cross-channel effects generated by mini-program channels, demonstrating the applicability and generalizability of the framework in a new context.
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Xiaojun Xu, Wu He, Ping Yin, Xiaobo Xu, Yuting Wang and Haitao Zhang
The purpose of this paper is to present a new tool, business network information ecological chain (BNIEC) aiming to solve the current information problems in business network…
Abstract
Purpose
The purpose of this paper is to present a new tool, business network information ecological chain (BNIEC) aiming to solve the current information problems in business network, make more profits to business websites and to maintain the sustainable development of the business network environment in Internet of Things (IoT) era.
Design/methodology/approach
From multi-disciplinary perspectives, learning from the knowledge in information ecology, economics, the IoT and system theory, this paper first analyzes the positioning of BNIEC in different subjects. Second, it proposes the definition, components and characteristics of BNIEC and designs the BNIEC concept map helping to understand the BNIEC system. Last, this paper builds the structural model and the information flow models of BNIEC.
Findings
The study first presents the concept of BNIEC and based on the trans-disciplinary point of view, builds the structure model of BNIEC from three aspects: nodes, relations among nodes and link modes and illustrates the model using the knowledge from the system theory. Also, it builds two kinds of the information flow models by the related information knowledge in IoT.
Originality/value
This paper aims to introduce not only a new tool but an ecological idea to business network companies, to create a pleasant network environment, more than that, to make more benefits for themselves. Meanwhile, it has important significance in the sustainable development of the business network environment, business websites, business network information resources and information technology. Especially in today’s IoT era, it shows an ecological thinking to solve the information problems in business network that we may face in the future.
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Hong Ge, Wei Wang, Yuting Wang and Ran Tan
Original equipment manufacturers (OEMs) are increasingly discoursing well-known brands to support their own brands. This study explores how original equipment manufacturing (OEM…
Abstract
Purpose
Original equipment manufacturers (OEMs) are increasingly discoursing well-known brands to support their own brands. This study explores how original equipment manufacturing (OEM) brand disclosure affects willingness to buy (WTB) by examining the mediation effect of perceived brand competence (PBC) and perceived brand warmth (PBW), as well as the moderating effects of product type and consumer self-esteem (CSE).
Design/methodology/approach
This study builds on signal theory and the stereotype content model to theorize the mediating role of PBC and PBW between OEM brand disclosure and WTB. A 2×2 between-subjects experiment with 442 participants was conducted, employing ANOVA, seemingly unrelated regression and moderated mediation tests to examine the hypotheses.
Findings
OEM brand disclosure is positively related to WTB through PBC and PBW. Specifically, PBC’s mediation effect on OEM brand disclosure is stronger than that of PBW. Additionally, the mediation effect of OEM brand disclosure on WTB via PBC is moderated by product type and CSE.
Originality/value
This study contributes to the existing brand self-disclosure and brand spillover literature by opening the black box of how OEM brand disclosure affects WTB and reveals the underlying mechanisms of PBC and PBW. It offers valuable insights for OEMs to leverage previous OEM brands to support their own brands by improving PBC and PBW and is more beneficial for consumers with high self-esteem and experience products.