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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 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.

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.

Numerically analyzed the flow characteristic and explored the hydrodynamic mechanism of the S-shaped region formation of a Francis pump-turbine.

Three-dimensional steady and unsteady simulations were performed for a number of operating conditions at the optimal guide vanes opening. The steady Reynolds averaged Navier-Stokes equations with the SST turbulence model were solved to model the internal flow within the entire flow passage. The predicted discharge-speed curve agrees well with the model test at generating mode. This paper compared the hydrodynamic characteristics of for off-design cases in S-shaped region with the optimal operating case, and more analysis focuses particularly on very low positive and negative discharge cases with the same unit speed.

At runaway case towards smaller discharge, the relative circumferential velocity becomes stronger in the vaneless, which generates the “water ring” and blocks the flow between guide vane and runner. The runner inlet attack angle becomes larger, and the runner blade passages nearly filled with flow separation and vortexes. The deterioration of runner blade flow leads to the dramatic decrease of runner torque, which tends to reduce the runner rotation speed. In this situation, the internal flow can’t maintain the larger rotating speed at very low positive discharge cases, so the unit discharge-speed curves bend to S-shaped near runaway case.

The analysis method of four off-design cases on S-shaped region with the comparison of optimal operation case and the calculated attack angles are adopted to explore the mechanism of S characteristic. The flow characteristic and quantitative analysis all explain the bending of the unit discharge-speed curves.

With the rapid development of cloud computing, most software firms face the significant choice of whether they should change the versioning strategy of enterprise software from releasing the on-premise version to the software-as-a-service (SaaS) version. Data being generated and hosted on SaaS vendors' servers brings multiple effects. It enables customers to enjoy the flexibility of accessing data and using the software remotely, named the “portability” effect. However, on the other hand, the cumulative data resources on the cloud also provide a clear target for external attacks, leading to the concern of information security. Considering these, the authors hope to offer insights for software firms by exploring the strategy selection problem.

Taking the portability effect and security risks of the SaaS licensing model into account, the authors develop a two-period model to figure out the market segmentation and identify the feasible conditions for employing three alternative strategies. Comparative statics analyses are conducted to explore the influencing mechanism of exogenous factors on strategy selection. The authors also discuss the strategy selection in the presence of the network effect and the security loss faced by users of on-premise software.

One significant finding is that the on-premise strategy can be excluded when the potential loss from security risks is small. Under this circumstance, the dual version strategy is optimal provided that the increase of customer valuation caused by portability effect is below a threshold. Otherwise, the SaaS strategy generates the highest profit. When the potential loss from security risks turns large, the on-premise strategy, the dual version strategy and the SaaS strategy are the optimal options in order as the portability effect on customer valuation gets stronger.

Previous literature has insufficiently addressed the versioning issue of enterprise software. In this paper, the distinctive features of the SaaS model are considered, and differentiated results compared with previous work are obtained. The research results provide guidelines for software firms in deciding their product releases in the future.