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The purpose of this paper is to propose an new online path planning method for porcine belly cutting. With the proliferation in demand for the automatic systems of pork production, the development of efficient and robust meat cutting algorithms are hot issues. The uncertain and dynamic nature of the online porcine belly cutting imposes a challenge for the robot to identify and cut efficiently and accurately. Based on the above challenges, an online porcine belly cutting method using 3D laser point cloud is proposed.

The robotic cutting system is composed of an industrial robotic manipulator, customized tools, a laser sensor and a PC.

Analysis of experimental results shows that by comparing with machine vision, laser sensor-based robot cutting has more advantages, and it can handle different carcass sizes.

An image pyramid method is used for dimensionality reduction of the 3D laser point cloud. From a detailed analysis of the outward and inward cutting errors, the outward cutting error is the limiting condition for reducing the segments by segmentation algorithm.

Online medical repositories provide a platform for users to share information and dynamically access abundant electronic health data. It is important to determine whether case report information can assist the general public in appropriately managing their diseases. Therefore, this paper aims to introduce a novel deep learning-based method that allows non-professionals to make inquiries using ordinary vocabulary, retrieving the most relevant case reports for accurate and effective health information.

The dataset of case reports was collected from both the patient-generated research network and the digital medical journal repository. To enhance the accuracy of obtaining relevant case reports, the authors propose a retrieval approach that combines BERT and BiLSTM methods. The authors identified representative health-related case reports and analyzed the retrieval performance, as well as user judgments.

This study aims to provide the necessary functionalities to deliver relevant health case reports based on input from ordinary terms. The proposed framework includes features for health management, user feedback acquisition and ranking by weights to obtain the most pertinent case reports.

This study contributes to health information systems by analyzing patients' experiences and treatments with the case report retrieval model. The results of this study can provide immense benefit to the general public who intend to find treatment decisions and experiences from relevant case reports.

This study aims to compares the effects of different human-like appearances (low vs. medium vs. high) of service robots (SRs) on consumer trust in service robots (CTSR), examines the mediating role of perceived warmth (WA) and perceived competence (CO) and demonstrates the moderating role of culture and service setting.

The research design includes three scenario-based experiments (Chinese hotel setting, American hotel setting, Chinese hospital setting).

Study 1 found SR’s human-like appearance can arouse perceived anthropomorphism (PA), which positively affects CTSR through parallel mediators (WA and CO). Study 2 revealed consumers from Chinese (vs. American) culture had higher CTSR. Study 3 showed consumers had higher WA and CO for SRs in the credence (vs. experience) service setting. The authors also had an exploratory analysis of the uncanny valley phenomenon.

The findings have practical implications for promoting the diffusion of SRs in the hospitality industry. Managers can increase CTSR by augmenting the anthropomorphic design of SRs; however, they must consider the differences in this effect across all service recipients (consumers from different cultures) and service settings.

The authors introduce WA and CO as mediators between PA and CTSR and set the culture and service setting as moderators.

Drawing on social identity theory (SIT), the current research highlights the sequential mediation effects of customer interaction, functional value and hedonic value in linking customer-brand identification and self-representation with online brand advocacy (OBA).

Data were gathered from 483 Egyptian and 595 non-Egyptian Aliexpress shopping platform customers, then analyzed using SmartPLS 4.

The multigroup analysis findings revealed that customer interaction and functional/hedonic values sequentially mediated the linkages of customer-brand identification and self-presentation with OBA for Egyptian and non-Egyptian user groups.

The novelty of this study is that it tested and validated customer interaction with the Aliexpress service scale, allowing for reflection on the interactive nature of this platform between Egyptian and non-Egyptian customers. SIT also lends credence to the idea that self-presentation mediates the effect of customer-brand identification on Aliexpress’s OBA, potentially shedding new light on this understudied dimension using a theoretical framework.

This study intends to investigate drivers and consequences of supply chain coordination (SCC) towards green to highlight some convincing evidence for an emerging country's exporters to promote sustainable coffee development.

Data were gathered from surveying 189 managers of coffee exporters in Vietnam and then applied PLS-SEM for analysis.

This study demonstrates that top management sensitivity, along with institutional forces of regulation, market and competition, strongly stimulate exporters' supply chain coordination towards green. Additionally, that coordination boosts the export financial and market performance.

The findings may not be generalizable because the current study only included data from Vietnamese coffee exporters.

This study contributes to the current literature by looking from the perspective of coffee exporters – leading players in supply chains for export. The research findings represent the first solid argument for Vietnam coffee exporters to encourage SCC towards green and reveal several implications for managers and policymakers to support sustainable development in an emerging country.

This study aims to measure social enterprises’ (SEs’) social objectives under the United Nation’s 17 Sustainable Development Goals (SDGs) framework, and explore the impact of SEs’ social objectives on their choices of legal forms.

This study used semi-structured questionnaires followed up by field interviews and observations of the sampled SEs. The survey sample includes 80 participants of Social Entrepreneurs Stars Competition in Zhejiang Province of China. The authors conduct content analysis to measure the objectives of SEs. The authors also perform descriptive analysis, chi-square test and regression analysis on the data.

The findings confirm the theoretical discussions that SEs’ choices of legal forms reflect SEs’ strategies toward achieving social objectives. Similar to certain countries, some SEs in China register as nonprofit entities to concentrate on nonprofitable sustainability objectives, while others register as commercial enterprises or hybrid organizations to generate profits. However, some SEs focus on profitable non-sustainability issues and fail to prioritize social objectives over economic objectives. There are positive effects of social entrepreneurs’ background similarity and negative effects of social entrepreneurs’ educational level on their SEs’ choices to register as commercial enterprises.

Due to the small size and nonrepresentative sample this study is based on, the findings need be further tested by a larger sample. SEs in different service domains rely on different types of financial resources (Mair et al., 2012; Doherty et al., 2014). In future research, the model can be expanded to test the effects of service domains and types of financial sources on SEs’ choices of legal forms.

To encourage more societal resources being allocated toward achieving the United Nations’ SDGs, policymakers and SE certification programs are recommended to explicitly incorporate sustainability objectives into the evaluation standards and supportive policies for SEs. Social entrepreneurs who aim to balance the social and economic objectives in their business are suggested to target the population with whom they share similar community background. Training or consulting programs for social entrepreneurs are suggested to provide advice tailored to their socio-economic background and personal experiences.

To the best of the authors’ this study is the first quantitative analysis to identify factors that associate with SEs’ choice of legal forms in China. The authors developed new instruments to measure SEs’ social objectives and service targets, access to financial resources and social entrepreneurs’ social-economic backgrounds.

The purpose of this study is to explore the relationship between big data and supply chain platform in China’s retail industry. With the emergence of big data resources and technologies, the business pattern of new retail advocates the combination of online and offline channels. Supply chain platform plays a key role in the implementation of retail activities, which has gradually become a research hotspot in the cross field of operations management and information system.

Through the method of literature review and case study, this study empirically explores how big data shapes supply chain platform to support new forms of online retail by grounded theory.

The model framework is validated by reliability test and coding method to process survey materials. The results identify the overall antecedents of supply chain platform and reveal positive effects between big data and new retail. The findings help firm managers build a big data-driven supply chain to support new retail.

There are insufficient studies on theoretical frameworks and interaction relationships among big data, supply chain platform and new retail.

The purpose of this study is to examine the relationship between the corporate social responsibility (CSR) performance of job-hopping executives at their former and subsequent firms.

We conduct regression analyses using a sample of firms listed on the Shanghai and Shenzhen Stock Exchanges from 2010 to 2020 to examine whether CSR performance is similar from one firm to the next as executives switch jobs.

We find a positive relationship between the CSR performance of former and subsequent firms under job-hopping executives. This relationship is the strongest in the year of the job switch; it weakens in the second year and eventually disappears in the third year. In addition, we show that this relationship benefits different CSR stakeholder groups and is contingent on executive and subsequent firm attributes and job-hopping characteristics. Furthermore, we demonstrate that firms that hire a new chief executive officer from a firm with a strong track record in CSR, the new firm experiences a significant surge in CSR performance compared with firms that do not experience such a shock.

This study has implications for executive hiring decisions.

This study extends the understanding of CSR determinants through the lens of inter-organisational ties associated with job-hopping executives.

The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners’ computational thinking.

By analyzing the mechanism of action of ITF on the development of computational thinking, an ITF strategy and corresponding ITS acting on the whole process of programming problem-solving were developed to realize the evaluation of programming problem-solving ideas based on program logic. On the one hand, a lexical and syntactic analysis of the programming problem solutions input by the learners is performed and presented with a tree-like structure. On the other hand, by comparing multiple algorithms, it is implemented to compare the programming problem solutions entered by the learners with the answers and analyze the gaps to give them back to the learners to promote the improvement of their computational thinking.

This study clarifies the mechanism of the role of ITF-based ITS in the computational thinking development process. Results indicated that the ITS designed in this study is effective in promoting students’ computational thinking, especially for low-level learners. It also helped to improve students’ learning motivation, and reducing cognitive load, while there’s no significant difference among learners of different levels.

This study developed an ITS based on ITF to address the problem of learners’ difficulty in obtaining real-time guidance in the current programming problem-solving-based computational thinking development, providing a good aid for college students’ independent programming learning.

This study aims to examine the effects of the perceived warmth and competence of humanoid robots on customer tolerance of service failure through the affective response and the boundary condition of relationship norms.

Two experimental studies were conducted to investigate the effects of perceived warmth and competence of humanoid robots’ physical appearances on tolerance of service failure and the mediating role of anger. The boundary influence of relationship norms is also explored.

The results reveal that the perception of warmth (vs. competence) robot leads to less (more) anger, which significantly results in tolerance of service failure. However, customer tolerance is insignificant under exchange norms, as the undelivered service violates the expectations of both warm and competent robots.

This study provides practical guidance for hospitality managers to implement humanoid robots in a way that minimizes the negative outcomes of service failure. Managers should also think about the appropriate match of different types of humanoid robots and relationship norms in which robots will be deployed.

This study contributes to the tolerance literature by taking a social cognition perspective to investigate the effect of humanoid robots’ physical appearances on customers’ reactions to service failure. The findings also reveal that its affective mechanism lies in the effect of expectancy violations of service failure on tolerance. Furthermore, this study extends the literature on relationship norms to the influence of company factors on effective humanoid robot implementation.