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Digitally driven virtual streamers are increasingly utilized in live-streaming commerce, possessing distinct advantages compared to human streamers. However, the applicable scenarios of virtual streamers are still unclear. Focusing on product attribute variances, this paper compares the livestreaming effects of virtual and human streamers to clarify the applicable scenarios for each and assist companies in strategically choosing suitable streamers.

We conducted four experiments utilizing both images and video as stimulus materials, and each experiment employed different products. To test the proposed model, a total of 1,068 valid participants were recruited, encompassing a diverse group of individuals, including undergraduates and employed workers.

The results indicate no significant difference between virtual and human streamers in increasing consumers’ purchase intention for utilitarian products. In contrast, human streamers are more effective in enhancing consumer purchase intention for hedonic products, with a mediating role of mental imagery quality. Consumers’ implicit personality variances also influence their willingness to accept virtual streamers.

This paper is the first to compare the effects of virtual and human streamers in promoting different products to enhance our comprehension of virtual streamers. Given the potential risks associated with human streamers, a comprehensive understanding of the role of virtual streamers is imperative for brands when deploying live-streaming commerce activities.

This paper aims to propose a general framework of shared control for human–robot interaction.

Human dynamics are considered in analysis of the coupled human–robot system. Motion intentions of both human and robot are taken into account in the control objective of the robot. Reinforcement learning is developed to achieve the control objective subject to unknown dynamics of human and robot. The closed-loop system performance is discussed through a rigorous proof.

Simulations are conducted to demonstrate the learning capability of the proposed method and its feasibility in handling various situations.

Compared to existing works, the proposed framework combines motion intentions of both human and robot in a human–robot shared control system, without the requirement of the knowledge of human’s and robot’s dynamics.

The limited strength of polylactic acid (PLA) hinders its extensive engineering applications. This paper aims to enhance its strength and realize diverse applications.

Here, the continuous fiber reinforced PLA composites are fabricated by a customized fused filament fabrication three-dimensional printer. Uniaxial tensile and three-point flexural tests have been conducted to analyze the reinforcement effect of the proposed composites. To unveil the adhering mechanism of optic fiber (OF) and PLA, post failure analysis including the micro imaging and morphology have been performed. The underlying mechanism is that the axial tensile strength of the OF and the interfacial adhesion between PLA and OF compete to enhance the mechanical properties of the composite.

It is found that 10%–20% enhancement of strength, ductility and toughness due to the incorporation of the continuous OF.

The continuous OFs are put into PLA first time to improve the strength. The fabrication method and process reported here are potentially applied in such engineering applications as aerospace, defense, auto, medicine, etc.

The purpose of this paper is to optimize a two-level perishable product supply chain by increasing its revenue with the Internet of Things (IoT). It particularly investigates how radio-frequency identification (RFID) technology impacts the revenue of the supply chain.

In this paper, two revenue models were built to calculate the revenue of perishable product supply chain before and after the application of IoT to analyze the influences of IoT on perishable product supply chain. In the case study, particular data of an aquatic product supply chain were analyzed through these models which were later solved by a computer simulation method based on Colonial Competitive Algorithm, a new heuristic algorithm inspired by imperialistic competition in human society.

Using these revenue models to compare the revenues of supply chain before and after the application of IoT, this paper concludes that the application of IoT can efficiently optimize a perishable product supply chain by balancing its wholesale profits and its total costs including logistics costs, therefore, increasing its overall revenue. However, this conclusion is only applicable for large enterprises, while small enterprises are not supposed to introduce IoT due to its high cost.

The revenue models built in this paper can be used to evaluate the profits of supply chain and help enterprises determine how to maximize their profits and whether they should introduce IoT in a perishable product supply chain. In addition, through the analysis of case study, this paper gives several valuable suggestions to help enterprises reduce their logistics costs and increase their overall revenue.

The number of farms engaged in grain production in China has been declining in recent years. Limited efforts have been devoted to examine why producers quit from grain production and how such exits affect China's grain output. Such information, however, is invaluable in understanding whether the exit from grain production should be encouraged and if so, how. The purpose of this paper is to identify the factors that influence farmers' decision to quit from grain production, with a view to drawing implications for devising policies to deal with such exits.

Both descriptive statistics and econometric techniques are used to analyse a set of unique and comprehensive farm‐level survey data to identify key factors that affect farmers' decision to quit from grain production.

Key factors that influence a farm to quit from, or stay in, grain production include: family size, the share of farming labour out of total family labour, per capita arable land, the proportion of land used for grain production, the share of family income from grains. It was also found that the level of grain prices and the sunk cost in farming, chiefly in grain production, also affect the likelihood that a household will stay or exit from grain production. Further, farmers in more economically developed regions are more likely to quit from grain production.

The paper's findings clearly indicate that farms with a larger scale of grain production and earning higher income from grain are the major contributors to China's grain production. Potential exists for China to raise its total grain output if the land from those exiting farmers is readily made available to larger producers, enabling them to further benefit from the economies of scale.

Since the launch of the Mainland and Hong Kong Closer Economic Partnership Arrangement (CEPA) in 2003, Hong Kong cinema is believed to have confronted drastic changes. Hong Kong cinema is described to be dying, lacking creative space and losing local distinctiveness. A decade later, the rise of Hong Kong – China coproduction cinema under CEPA has been normalized and changed the once pessimism in the industry. The purpose of this paper is to demonstrate how Hong Kong cinema adjusted its production and creation in the first 10 years of CEPA.

Beginning with a review of the overall development, three paradigmatic cases are examined for reflecting upon what the major industrial and commercial concerns on the Hong Kong – China coproduction model are, and how such a coproduction model is not developed as smooth as what the Hong Kong filmmakers expected.

Collectively, this paper singles out the difficulties in operation and the limit of transnationality that occur in the Chinese context for the development of Hong Kong cinema under the Hong Kong – China coproduction model.

This is the author’s research in his five-year study of Hong Kong cinema and it contributes a lot to the field of cinema studies with relevant industrial and policy concern.

Digital technologies are widely used for digitization of museum and archival heritage and creation of digital, multimedia and online exhibitions, especially in terms of costume history. Digital exhibitions require historical dress forms which were used in the past for costume presentation. The purpose of this paper is to develop a new method for parametric modeling of the nineteenth century dress forms in accordance with fashionable body shape.

Due to limited number of body measurements in historical sizing tables, it is impossible to redesign the morphology of old fashionable body with high accuracy by means of contemporary CAD. The developed method is based on two sources of information: first, historical sizing tables with body measurements; second, historical corsets. By combining both resources and applying virtual try-on technology, the full anthropometric database about the nineteenth century fashionable body shape has been organized and the parametric model of historical dress form has been generated.

The digital replica of deformable parametric dress form was created automatically in accordance with the historical sizing systems and the corsets construction. The process of reproduction of a historical dress form has been done with high accuracy due to substantial advantages of contemporary software.

This study shows new way of anthropometric data generating from the construction of close-fitting and compression undergarments. The developed method and the new database can be applied for each type of dress forms which were used in the second part of the nineteenth century to generate its digital replica in virtual reality. The new approach is joining the digital technologies and the professional knowledge as an important part of cultural heritage for studying, recreating and presenting historical costume.

This paper attempts to provide significant information on the increased growth of literature of chatbots and virtual assistants. Technological changes are dynamic and keep changing at regular intervals. Therefore, it becomes highly crucial to review the performance of chatbots and virtual assistants. This paper aims to review the literature by eminent researchers in the form of authors, keywords and major contributing organizations.

Systematic literature review and bibliometric analysis is used to analyze the growth of literature on chatbots. A sum of articles has been extracted from Scopus database with selected keywords and with certain filters. VOSviewer software is used for analysis of data. A total of 130 documents are extracted from Scopus database from 2017 to 2021 (31st August).

This study provides a significant contribution to an existing literature and provides the understanding of research in the area of chatbots and virtual assistants. The authors with maximum number of citations are Yan, Zaho, Bengio, Weizenbaum, Song, Zhou and Maedche with jointly 180 citations. Research is been contributed by different countries where the United States is the country with highest number of documents published. The United States contributes 17% of the total production in the area of chatbots and virtual assistants. The analysis shows that the area is gaining momentum as contribution in this area is been increasing in last few years.

The study shows that several branches of chatbots are also in mainstream like natural language processing, e-learning, behavioural research, conversational agents, virtual assistants, human–computer interaction, natural language and so on. It provides a wider scope to authors and researchers to gain useful insights. The bibliometric study will provide a broader spectrum in this area.

The developments in technology and also the effect of COVID-19 pandemic is boosting the adoption of technology in different sectors. Deployment of technology will uplift the economy and social infrastructure. Society can avail different services from their comfort area and also in real time. This will help in reducing wastage of resources like people visiting offices for routine jobs which can be easily availed from their workplace. Society may access better services without much human interaction.

This paper adds significant contribution to the existing literature by analysing the published papers from Scopus database. The study contains new and significant information as this study covers all industries where chatbots and virtual assistants are being applied whereas in previous literature only specific industry has been taken into consideration.

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.