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The purpose of this study is to present a highly stretchable and flexible strain sensor with simple and low cost of fabrication process and excellent dynamic characteristics, which make it suitable for human motion monitoring under large strain and high frequency.

The strain sensor was fabricated using the rubber/latex polymer as elastic carrier and single-walled carbon nanotubes (SWCNTs)/carbon black (CB) as a synergistic conductive network. The rubber/latex polymer was pre-treated in naphtha and then soaked in SWCNTs/CB/silicon rubber composite solution. The strain sensing and other performance of the sensor were measured and human motion tracking applications were tried.

These strain sensors based on aforementioned materials display high stretchability (500 per cent), excellent flexibility, fast response (approximately 45 ms), low creep (3.1 per cent at 100 per cent strain), temperature and humidity independence, superior stability and reproducibility during approximately 5,000 stretch/release cycles. Furthermore, the authors used these composites as human motion sensors, effectively monitoring joint motion, indicating that the stretchable strain sensor based on the rubber/latex polymer and the synergetic effects of mixed SWCNTs and CB could have promising applications in flexible and wearable devices for human motion tracking.

This paper presents a low-cost and a new type of strain sensor with excellent performance that can open up new fields of applications in flexible, stretchable and wearable electronics, especially in human motion tracking applications where very large strain should be accommodated by the strain sensor.

This paper aims to enhance the machining accuracy of hybrid robots by treating the moving platform as the first joint of a serial robot for direct position measurement and integrating external grating sensors with motor encoders for real-time error compensation.

Initially, a spherical coordinate system is established using one linear and two circular grating sensors. This system enables direct acquisition of the moving platform’s position in the hybrid robot. Subsequently, during the coarse interpolation stage, the motor command for the next interpolation point is dynamically updated using error data from external grating sensors and motor encoders. Finally, fuzzy proportional integral derivative (PID) control is applied to maintain robot stability post-compensation.

Experiments were conducted on the TriMule-600 hybrid robot. The results indicate that the following errors of the five grating sensors are reduced by 94%, 93%, 80%, 75% and 88% respectively, after compensation. Using the fourth drive joint as an example, it was verified that fuzzy adaptive PID control performs better than traditional PID control.

The proposed online error compensation strategy significantly enhances the positional accuracy of the robot end, thereby improving the actual processing quality of the workpiece.

This method presents a technique for achieving online error compensation in hybrid robots, which promotes the advancement of the manufacturing industry.

This paper proposes a cost-effective and practical method for online error compensation in hybrid robots using grating sensors, which contributes to the advancement of hybrid robot technology.

This study explores archetypes of luxury brand Chanel through the use of visual narrative art created from studying consumer blog entries. The chapter describes visual narrative art as a qualitative research tool. Mapping contexts and stories that blog entries describe figure out the archetype of the brand. This study extends understanding of archetypes of luxury brand from different consumers’ perspectives.

Customer value co-creation in robots-mediated hospitality encounters involves active collaboration between customers and robots. In such encounters, robot capabilities, which are their functionalities or operational competences, and robot personalities, which are their interactive behaviors and communication styles, play a key role in enhancing customer value co-creation. The purpose of this study is to draw on service dominant logic to examine the role of robot capabilities and personalities in determining customer value co-creation and service satisfaction.

The authors adopted a mixed-methods research approach. A netnographic analysis was conducted on online customer reviews for robotic hotels and restaurants to identify key robot capabilities that shaped the customer experiences. Following this, a quantitative study (survey) was conducted to investigate the effects of robot capabilities and personalities on customer value co-creation and service satisfaction.

From the netnographic analysis, the authors identified cognitive, technical, interactional, emotional, personalization and autonomous capabilities as key robot capabilities influencing customer experiences. The findings of the follow-up empirical study showed that the higher-order robot capabilities construct positively influences customer value co-creation, which, in turn, affects service satisfaction. Furthermore, extroversion robot personality positively moderates this relationship, such that robots with high levels of capabilities result in greater value co-creation when robots possess extroversion personalities compared to introversion personalities.

This study advances the understanding of robot-mediated encounters by emphasizing the role of robot capabilities and personalities as crucial factors for effective customer value co-creation in the hospitality sector. Furthermore, it offers actionable insights for hospitality providers in selection of robots with key capabilities and personalities for enhancing customer satisfaction and successful value co-creation.

While previous research has predominantly focused on customer acceptance of and interaction with robots in the hospitality settings, the present study examined how and when service robots facilitate value co-creation with customers. Specifically, this study explores robot capabilities and personalities in shaping customer value co-creation perceptions. A few recent studies that examined customer-robot interactions have considered specific robot capabilities. However, given that hospitality services are experiential in nature and involve various tasks, a broad range of robot capabilities should be considered for a comprehensive understanding of the customer value co-creation process. By addressing this gap, the present study offers novel insights into what (capabilities) and how (extraversion personality) service robots facilitate customers in value co-creation and satisfaction.

Spherical robot plays an essential role in the field of mobile robot because of its unique shape and omni-directional mobility, especially in the application of planet detection. Although spherical robot has many advantages over leg robot, its obstacle climbing performance is still not satisfactory, that is exactly the motivation of this paper. The purpose of this paper is to propose a high-performance hopping mechanism for spherical robot, which can adapt to different terrain and effectively cross obstacles.

The hopping system uses torque spring as part of the energy storage mechanism, and converts the kinetic energy of rotation into elastic potential energy with a particularly designed turntable. Moreover, the track of the turntable, based on the Archimedes spiral principle, has the attributes of equidistance and equivelocity that enable better stability of energy storage process.

Experiments show that the proposed hopping mechanism can make a 250 g spherical robot jump up to 58 cm with the take-off angle of 60°. Finally, the influence of friction and take-off angle on the hopping height and distance of the robot is also analyzed, which provides a prior guidance for optimizing its jumping process.

This paper shows how to easily design a lightweight, compact and embedded spring hopping structure so that a spherical hopping robot with detection ability can be developed.

This paper aims to understand the process of guest-robot value co-creation in the restaurant context. It empirically examines the guest perception of value facilitation by service robots and its impact on guest value co-creation and advocacy intentions. It also investigates the moderating role of interaction comfort in the relationship between service robot value facilitation and guest value co-creation.

A mixed-methods approach was adopted. Ten customers who had dined at a service robot restaurant in China were interviewed in the qualitative study, followed by a quantitative study with 252 restaurant patrons to test the relationships between service robot value facilitation, guest value co-creation, interaction comfort and advocacy intentions.

Guest perceptions of six robot attributes, including role significance, competence, social presence, warmth, autonomy and adaptability, determine service robot value facilitation. Interaction comfort moderates the influence of service robot value facilitation on guest value co-creation. Additionally, guest value co-creation mediates the effect of service robot value facilitation on advocacy intentions.

This study offers an understanding of six robot attributes that can improve service robot value facilitation. Nevertheless, the authors collected data from guests who had experience at service robot restaurants. The authors encourage future research to use random sampling methods to ensure study representativeness.

This study offers strategic guidance for managers to deploy service robots in frontline roles in restaurants and provides important implications for service robot design to improve their facilitating role in the guest value co-creation process.

This study responds to a recent call for research on the role of service robots in the guest value co-creation experience. Unlike prior studies that focused on the adoption or acceptance of service robots, it examines the role of service robots in the value co-creation process (post-adoption stage). Furthermore, it is one of the early studies to identify and empirically examine the service robot attributes that enable value facilitation and foster value co-creation in guest-robot service encounters.

Many academic studies in international business empirically test the determinants of Chinese outward (O)FDI. A weakness with these studies is the limited critical evaluation given to the way in which Chinese OFDI data is collected and used. Chinese multinational enterprises (C)MNEs frequently establish special purpose entities in tax havens to transit FDI via intermediary jurisdictions. The purpose of this paper is to develop an alternative approach for measuring CMNE OFDI and subsequently explore how the results of previous studies may have been confounded use of tax havens by MNEs. The authors address the latter question by replicating widely cited quantitative studies.

Replication approach.

Through the replication of several studies, this paper finds high levels of discrepancies in general sign and significance between global ultimate ownership modeling results and those using officially recorded FDI data. More specifically, the main areas impacted by using official data rather than data which accounts for the use of tax havens are cultural proximity, geographic distance and natural resource seeking.

This paper looks at studies, which use official FDI data to understand CMNE behavior. It is important to note, however, that there are many hundreds, if not thousands, of studies that use other national-level FDI data to draw similar types of inferences about MNE activity. In this sense, the authors’ critical evaluation of CMNE work holds a much broader and, arguably, more important question: How reliable, in general, are studies, which use officially recorded FDI data? The results from this paper have already caused reflection on the impact of tax haven use on official FDI collection organizations, such as the OECD.

The social implications of companies using tax havens to route FDI is immense. The use of tax havens not only aids in tax minimization for companies, but also obscures the true providence and identity of companies. This is problematic in a society, which increasingly desires to understand where, how and by whom a product or service was created prior to consumption.

This paper argues that the tendency for Chinese MNEs to establish offshore holding companies in tax havens has given rise to significant biases in official FDI statistics. Through the use of global ultimate ownership data, the authors have put forward an alternate approach to measure genuine CMNEs’ OFDI activity, one which confronts and deals with their pervasive engagement with tax havens. Through the replication of several Chinese OFDI location choice studies, it was possible to understand how methodological issues stemming from the use of official FDI data may influence prior econometric results. In doing so, the authors hope to have sparked a debate which may lead to a re-evaluation of earlier received wisdom regarding Chinese MNE investment strategy and behaviors. This in turn should foster improved theorizing regarding the Chinese MNE and its outward investment activities.

Robotic arms’ interactions with the external environment are growing more intricate, demanding higher control precision. This study aims to enhance control precision by establishing a dynamic model through the identification of the dynamic parameters of a self-designed robotic arm.

This study proposes an improved particle swarm optimization (IPSO) method for parameter identification, which comprehensively improves particle initialization diversity, dynamic adjustment of inertia weight, dynamic adjustment of local and global learning factors and global search capabilities. To reduce the number of particles and improve identification accuracy, a step-by-step dynamic parameter identification method was also proposed. Simultaneously, to fully unleash the dynamic characteristics of a robotic arm, and satisfy boundary conditions, a combination of high-order differentiable natural exponential functions and traditional Fourier series is used to develop an excitation trajectory. Finally, an arbitrary verification trajectory was planned using the IPSO to verify the accuracy of the dynamical parameter identification.

Experiments conducted on a self-designed robotic arm validate the proposed parameter identification method. By comparing it with IPSO1, IPSO2, IPSOd and least-square algorithms using the criteria of torque error and root mean square for each joint, the superiority of the IPSO algorithm in parameter identification becomes evident. In this case, the dynamic parameter results of each link are significantly improved.

A new parameter identification model was proposed and validated. Based on the experimental results, the stability of the identification results was improved, providing more accurate parameter identification for further applications.

The principle of the medial axis calculation is complicated and difficult to implement. Moreover, the accuracy is not high. Then, as the generated path has an endpoint at the boundary of the polygon, burrs may appear on the surface of the molded piece. This paper aims to improve the warpage deformation of SLM molded parts and the surface quality of molded parts, an improved mid-axis path generation algorithm is proposed.

First, the center point is calculated by the seed point growth method based on the distance transform, and the obtained medial axis has high precision and is suitable for simple polygons and complex polygons. Then, based on the extracted medial axis, a preliminary path is generated, the path is trimmed with MATLAB to remove the redundant path. Finally, a scan along the contour of the polygon is performed to improve the surface quality of the molded part.

The algorithm reduces the internal stress generated during the molding process by continuously changing the scanning direction of the path along the boundary curve of the scanning area, thereby reducing the amount of warpage of the molded part. The result of extraction has a higher precision and wider scope of application than other methods to extract central axis, such as the Voronoi diagram-based method. The path is trimmed to remove redundant paths and the polygon boundaries are scanned to further improve the surface quality of the molded part. The results show that warpage deformation of the proposed algorithm is significantly smaller than the other two methods, thus the forming precision is higher.

An improved medial axis path generation algorithm is proposed in this paper. The proposed method is applied to improve warpage deformation occurring in the SLM process. Seed point growth of distance transformation is used to extracted central axis. The result of extraction has a higher precision and wider scope of application than other methods to extract central axis, such as the Voronoi diagram-based method.

This paper aims to discuss the effects of COVID-19 on hotel marketing and management practices and outlines a three-pronged research agenda to stimulate knowledge development in the hotel sector.

This paper is based on an overview of the relevant literature on hotel marketing and management and the hotel guest behavior. The authors also investigated hospitality service trends to propose a research agenda.

This paper presents a research agenda from three dimensions – artificial intelligence (AI) and robotics, hygiene and cleanliness and health and health care. First, different types of AI (mechanical, thinking and feeling) might open up distinct research streams at the intersection of health crises and hotel management, in light of the COVID-19 pandemic. Additionally, this paper recommends that researchers move beyond typical perspectives on the antecedents and outcomes of hotel hygiene and cleanliness to delve into guests’ perceptions of the cleanliness of specific hotel surfaces. Furthermore, a more in-depth analysis is warranted about the evolving relationship between hotels and the health-care sector.

The recommended research areas are intended to advance the knowledge base to help hotels recover from the COVID-19 pandemic. The suggested research streams are expected to provide actionable insights to promote the development and sustainability of the hotel sector.

This paper appears to be a frontier study, critically examining possible effects of the COVID-19 pandemic on hotel marketing and management practices and how hoteliers may respond to such challenges to recover after this pandemic.