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Many cities of various types are distributed in the large area of mountainous regions in China. In these cities, there are acute contradictions between man and earth. Considering that the space growth mode of mountainous cities is widely different from that of flatland cities, the fractal method was adopted in the research aimed at demarcating the urban growth boundary of mountainous cities. The fractal features of the investigated mountainous cities in space were figured out via inference from their function, dimension, region, grade, and environment, and the fractal mode and conceptual framework of urban growth boundary of Qin-Ba mountainous region were constructed according to some concepts and methods such as fractal dimension, fractal network, and fractal order. In the research, the traditional urban growth boundary form-was decomposed into scattered points (point form), paths (linear form), and patches (plane form) to form the fractal theory units for the research of urban growth boundary, and the leading idea, procedure, and control method for “fractal demarcation of urban growth boundary” were established to provide strategies for demarcation of urban space growth boundary of Qin-Ba mountainous region.

Building upon uncertainty reduction theory, this work aims to explore how four uncertainty reduction factors (i.e. online property review, online textual description, online visual description and online instant messenger) mitigate property quality uncertainty and property fit uncertainty, which further influence Airbnb use intention.

This work tests the proposed research model using a structural equation modeling approach with 335 Airbnb users.

The findings reveal that the online property review, online textual description, online visual description and online instant messenger can efficiently mitigate property quality uncertainty and property fit uncertainty, which ultimately influence Airbnb use intention.

This study provides useful insights on mitigating property uncertainty in the peer-to-peer (P2P) accommodation platforms. Researchers are encouraged to investigate the boundary conditions that influence the effectiveness of uncertainty reduction strategies in alleviating property uncertainty.

P2P accommodation service providers are suggested to take actionable uncertainty reduction strategies to mitigate property uncertainty in online P2P accommodation platforms.

First, this study advances research on P2P accommodation by identifying two key types of property uncertainty, namely, property quality uncertainty and property fit uncertainty. Second, this study extends research on P2P accommodation by proposing contextualized passive, active and interactive uncertainty reduction strategies in mitigating property uncertainty. Third, this study extends uncertainty reduction theory to the P2P accommodation context. Fourth, this study enriches uncertainty reduction theory by verifying the mediating effects of property quality uncertainty and property fit uncertainty.

Disruption considerably prolongs session times for surgery, affects the quality of patient care, and prolongs waiting lists. In addition, there is a strong relationship between disruption and surgical error. This research aims to provide a platform for healthcare services to identify the sources of preventable disruption affecting operative time within the perioperative process and to effectively reduce it.

Events inside and outside operating rooms that disturb the operative time were recorded for 31 elective surgeries over the period of five months. Disruption events were classified according to the hospital's requirements and the findings were reviewed by the surgical teams. Lean thinking approaches were used to achieve the purpose of this study.

Preventable disruption caused an increase in surgical time of approximately 25 per cent. Preventable disruption consisted of poor information flow, failure to follow concepts of methods study, lack of communication and lack of coordination. Coordination failures were the main reason for disruption followed by the lack of following the principles of motion economy.

Surgical disruption has substantial financial implications for hospitals. This research indicates that it is possible to reduce operative time considerably by eliminating preventable disruption. Such additional time could be utilised to deal with the pressure of emergency cases, reduce the waiting lists for elective surgery, increase operating room utilisation, and reduce medical errors.

For successful servitization, manufacturing firms must understand how their customers adopt new services. The purpose of this paper is to explore customers’ readiness for a manufacturer’s new services to complement its goods. The goal is to increase knowledge of the aspects that manufacturers should consider when bringing new kinds of services to market.

A qualitative case study design is used to analyze readiness for services and interest in service adoption in three customer firms of a manufacturer. The interview data were collected from 14 persons at customer sites and were content analyzed.

The results show that readiness – a concept that is often used in the field of technology – is relevant also for the service adoption process. In a business-to-business context, readiness for service adoption concerns the individual and organizational levels, and hence a new dimension of organizational culture and habits had to be added to the concept that originally focuses on individuals. People consider different factors when making consecutive decisions during the service adoption process and these factors can vary even within a company. The cornerstone for new service adoption is the customer firm’s actual need for the service.

The results offer new knowledge about service adoption in a business-to-business context by taking a customer firm’s perspective. They, thus, complement previous studies on the supplier perspective of servitization and service adoption in consumer business. The contributions help manufacturers focus their efforts when bringing new services to market.

This paper aims to examine the evidence of risk spillovers between Shanghai and London non-ferrous futures markets using a dynamic Copula-CoVaR approach.

With daily data, the marginal distributions and optimal Copula functions are determined using the kernel estimation method and squared Euclidean distance test. The conditional value-at-risk and the conditional value-at-risk spillover rate are computed from the Copula estimated parameters based on the Copula-CoVaR model. Also, the dynamic correlation coefficient between the two futures markets is investigated.

The empirical results are as follows: overall, the risk spillover effect exerted by the London Metal Exchange on the Shanghai Futures Exchange is more significant than vice versa. Moreover, the degree of risk spillovers exerted by the London Metal Exchange on the Shanghai Futures Exchange for zinc and copper are more significant when they are depressed in the London Metal Exchange. Moreover, the dynamic of the correlation between the Shanghai and London futures markets is attributed to be largely due to changes in the global economy.

The Copula-CoVaR model used in this paper is suitable for measuring the risk spillovers between two different markets, while the risk spillovers across multiple markets or the consideration of multiple risk factors cannot be accurately captured using this framework. Multiple state variables to capture time variation in the conditional moments of return series will be a topic in future research.

The results provide theoretical support for risk management and monitoring of the non-ferrous futures markets.

The ability of the Copula function to accurately describe a nonlinear relationship and tail correlation is harnessed to measure the risk spillovers, explore the degree and direction of risk spillovers and identify the source of risk spillovers. The global economy is incorporated as a macro factor to explore its inner connection with the dynamic of risk spillovers in the non-ferrous metal futures market.

The purpose of this paper is to provide a flexible tool to predict the particle temperature distribution for traditional laser applications and for the most recent diode laser processes. In the past few years, surface processing and rapid prototyping applications have frequently implemented the use of powder delivery nozzles and high power fibre‐coupled diode lasers with highly convergent laser beams. Owing to the complexity and variety of the process parameters involved in this technology, mathematical models are necessary to understand and predict the deposition behaviour. Modeling the dynamics of the melting pool and the particle temperature distribution is critical for achieving a good deposition quality.

This study focuses on the development of mathematical models to predict the particle temperature distribution over the melting pool. An analytical and a numerical solution are proposed for two cases of laser intensity distribution: top hat and Gaussian.

The results show that a more vertical position of powder delivery nozzle will lead to a higher and more uniform particle temperature distribution, in particular for the top‐hat intensity distribution case.

Previous work has dealt only with Gaussian laser spatial distributions and collimated laser beams. Therefore, they were limited to a specific class of laser processes. This work provides a flexible tool to predict the particle temperature distribution for traditional laser applications (powder delivery nozzle and Gaussian laser profile) and for the most recent diode laser processes (powder delivery nozzle and top‐hat laser distribution with highly convergent laser beam). In addition, the results demonstrate that the particle temperature does not monotonically increase while increasing the nozzle inclination as in the case of a collimated laser beam, but some particles show a minimum temperature for intermediate values of the nozzle inclination angle.

The purpose of this paper is to establish an orbital launch window for manned Moon‐to‐Earth trajectories to support China's manned lunar landing mission requirements of high‐latitude landing and anytime return, i.e. the capability of safely returning the crew exploration vehicle at any time from any lunar parking orbit. The launch window is a certain time interval during which the transearth injection may occur and result in a safe lunar return to the specified landing site on the surface of the Earth.

Using the patched conic technique, an analytical design method for determining the transearth trajectories is developed with a finite sphere of influence model. An orbital launch window has been established to study the mission sensitivities to transearth trip time and energy requirements. The results presented here are limited to a single impulsive maneuver.

The difference between the results of the analytical model and high‐fidelity model is compared. This difference is relatively small and can be easily eliminated by a simple differential correction procedure. The launch window duration varies with launch date, from less than one hour to greater than 20 h, and the launch window occurs every day in the sidereal month.

The solution can be used to serve as an initial estimate for future optimization procedures.

The orbital launch window can be used to provide the basis for the preparation of an orbital launch timetable compatible with lunar missions and re‐entry conditions requirements.

Previous studies were mainly concentrated on the launch windows for the departure from the Earth. This paper investigates and establishes the orbital launch window for Moon‐to‐Earth trajectories.

The aim of the present article is to decide the ideal number of warehouses for a food manufacturer in the north of Spain (Asturias) for the year 2000, and their ideal location in the Spanish Peninsula by cluster analysis. The stages followed are to comment first on the underlying assumptions of the study, then on the methodology and the structure of the program developed to solve the problem, as well as on their input and output files. How the cluster and cost are calculated is discussed and finally the solution to this real case is provided.

The “patient journey” technique is one that has been used by health care providers to investigate the strengths and weaknesses of their service delivery. The purpose of this paper is to discuss the experience of adapting this approach for use in an atypical context – the comparison of two systems for managing health care complaints and notifications. It highlights a number of relevant considerations and provides suggestions for similar studies.

The design and methods of the study are described, with commentary on the success of key aspects and challenges encountered. To enable comparison between the two systems, this study had a “paired” design, in which examples were selected from each system so that they matched on basic, prescribed, criteria. Data about each matter’s journey were then collected from administrative records.

While, overall, the technique provided rich data on the processes of the systems under investigation, the type of data collected (related to administrative/communicative events) and the study’s comparative purpose required consideration and management of a number of issues. These included the implications of using administrative records and the impact of differences between the systems on the paired design.

This paper describes an attempt to apply the “journey” approach in a context that is uncommon in two ways: first, in its focus on regulatory processes (complaint/notification handling), rather than care provision to an individual patient; and second, in its objective of comparing two different systems. It is hoped this account will assist in further development of this technique.