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This study aims to explore the effect of digitalization on the promotion of enterprise R&D cooperation, and it analyzes the microimpact mechanism and boundary conditions of enterprise digitalization on enterprise R&D cooperation.

Based on survey data sourced from the World Bank Enterprise Surveys of the business environment of Chinese enterprises in 2012, this study applies multiple regression methods to test theoretical hypotheses.

Enterprise digitalization positively affects the breadth and intensity of enterprise R&D cooperation. Employees’ digital literacy plays an intermediary role between enterprise digitalization and enterprise R&D cooperation. The subordinate attributes of enterprises weaken the positive relationship between enterprise digitalization and the breadth and intensity of enterprise R&D cooperation. The shareholding of state-owned enterprises reinforces the positive relationship between digitalization and the intensity of enterprise R&D cooperation. However, such shareholding shows no significant regulatory effect on digitalization and the breadth of enterprise R&D cooperation.

Focusing on the digital transformation of the enterprise, this study discusses its impact mechanism on enterprise R&D cooperation, including the impact on the intensity and breadth of R&D cooperation. The study further examines the regulatory effect of organizational inertia on enterprise digital and R&D cooperation from two aspects: resource rigidity and routine rigidity. It emphasizes the significance of the digital literacy of employees in enterprise digitalization and discusses the micromechanism of enterprise digitalization and enterprise R&D cooperation.

The construction industry accounts for a large proportion of the economy of developing countries, but the connotation and influencing factors of high-quality development (HQD) are still unclear. This study aims to gain a more comprehensive insight into the current development status of the regional construction industry under China's HQD orientation and the obstructive factors affecting its development and to provide informative suggestions for its HQD prospects.

In this study, the construction industry of 16 cities in the Chengdu-Chongqing economic circle (CCEC), a new region in southwest China, was used as the research object to collect data from the 2006–2019 yearbooks, construct an evaluation index system for HQD of the construction industry, derive the development level of the construction industry using the entropy value method and spatial autocorrelation method and then apply the barrier Diagnostic model was used to compare and analyze the impact level of each index.

In terms of the time dimension, the development of the construction industry in CCEC is characterized by “high in the twin core and low in the surrounding area”, with unbalanced and insufficient development; in terms of spatial correlation, some factors have positive aggregation in spatial distribution, but the peripheral linkage decreases; through barrier analysis, the impact of different barrier factors is different.

This paper will help governments and enterprises in developing countries to make urban planning and management policies to fundamentally improve the development of the construction industry in underdeveloped regions.

Exploring the influencing factors on urban rail transit (URT) ridership is vital for travel demand estimation and urban resources planning. Among various existing ridership modeling methods, direct demand model with ordinary least square (OLS) multiple regression as a representative has considerable advantages over the traditional four-step model. Nevertheless, OLS multiple regression neglects spatial instability and spatial heterogeneity from the magnitude of the coefficients across the urban area. This paper aims to focus on modeling and analyzing the factors influencing metro ridership at the station level.

This paper constructs two novel direct demand models based on geographically weighted regression (GWR) for modeling influencing factors on metro ridership from a local perspective. One is GWR with globally implemented LASSO for feature selection, and the other one is geographically weighted LASSO (GWL) model, which is GWR with locally implemented LASSO for feature selection.

The results of real-world case study of Shenzhen Metro show that the two local models presented perform better than the traditional global model (OLS) in terms of estimation error of ridership and goodness-of-fit. Additionally, the GWL model results in a better fit than GWR with global LASSO model, indicating that the locally implemented LASSO is more effective for the accurate estimation of Shenzhen metro ridership than global LASSO does. Moreover, the information provided by both two local models regarding the spatial varied elasticities demonstrates the strong spatial interpretability of models and potentials in transport planning.

The main contributions are threefold: the approach is based on spatial models considering spatial autocorrelation of variables, which outperform the traditional global regression model – OLS – in terms of model fitting and spatial explanatory power. GWR with global feature selection using LASSO and GWL is compared through a real-world case study on Shenzhen Metro, that is, the difference between global feature selection and local feature selection is discussed. Network structures as a type of factors are quantified with the measurements in the field of complex network.

Fragment impact is one of the main threats for the safety of storage tank in aircraft. This study aims to investigate the influence of inserted baffle on hydrodynamic ram (HRAM) and damage of storage tank to optimize the protective performance of storage tank under fragment impact.

The characteristics of initial shock wave, cavity evolution, velocity attenuation of fragment and anti-penetration performance of baffle-inserted tanks were evaluated by experimental and numerical methods.

Results indicated that the inserted baffle in tank could significantly increase the velocity attenuation rate of fragment in water. The volume of the second cavity caused by the inserted baffle rapidly decreased with the baffle position moving backward. For the baffle-inserted tank, the deformation of the front and rear walls was substantially weakened, and the alleviating effect for front wall was more significant. Comparing with the ordinary storage tank, the inserted baffle at normalized position 0.25, 0.5 and 0.75 in tank made the ballistic limit velocity of storage tank increasing by 118.3%, 20.0% and 54.0%, respectively.

The findings of this work illustrating the HRAM history and damage map of storage tanks after inserted baffle could provide a convenient approach to improve the anti-penetration performance of storage tanks effectively.

In some three-dimensional (3D) printing application scenarios, e.g., model manufacture, it is necessary to print large-sized objects. However, it is impossible to implement large-size 3D printing using a single projector in digital light processing (DLP)-based mask projection 3D printing because of the limitations of the digital micromirror device chips.

A multi-projector DLP with energy homogenization (EHMP-DLP) scheme is proposed for large-size 3D printing. First, a large-area printing plane is established by tiling multiple projectors. Second, the projector set’s tiling pattern is obtained automatically, and the maximum printable plane is determined. Third, the energy is homogenized across the entire printable plane by adjusting gray levels of the images input into the projectors. Finally, slices are automatically segmented based on the tiling pattern of the projector set, and the gray levels of these slices are reassigned based on the images of the corresponding projectors.

Large-area high-intensity projection for mask projection 3D printing can be performed by tiling multiple DLP projectors. The tiled projector output energies can be homogenized by adjusting the images of the projectors. Uniform ultraviolet energy is important for high-quality printing.

A prototype device is constructed using two projectors. The printable area becomes 140 × 210 mm from the original 140 × 110 mm.

The proposed EHMP-DLP scheme enables 3D printing of large-size objects with linearly increasing printing times and high printing precision. A device was established using two projectors to practice the scheme and can easily be extended to larger sizes by using more projectors.

There has been a growing interest amongst academics, researchers employers and governments/policymakers on ageing workplaces and workforces. As populations age and pension ages rise, older workers are finding themselves having to delay or postpone their retirement and organisations are looking for ways to enable them to do so in sustainable work. Workplace ageing is impacting both European and Asian societies and governments and employers are taking nationally specific approaches to age-related human resource management, social and public policies. In Europe, national governments are being led by the European Union in developing social and public policies to support older workers in maintaining employment through lifelong learning, flexible working, health management and job rotation. Tiger economies have focused on the ‘working pensioner’ pension rules which enable older workers to phase into retirement. China is facing rapid ageing but still maintains early retirement as a way to help older workers move out of physically and mentally demanding work. In addition to providing an outline for the remainder of the book, we also present a survey of older employees undertaken in the United Kingdom and Hong Kong which explores experiences in work, workplace relationships, skills and retirement plans. The survey is used as a common resource for the remaining chapters.

The hosts' third-party certifications in the sharing accommodation platforms have largely overlooked how the provision of such certification information could facilitate the trust-building process and subsequently influence consumers' purchase intention. Adopting an institution-based trust perspective, the authors differentiate various types of hosts' certification information (i.e. financial certification and social certification) and examine their role in the trust-building process between the hosts and the customers on sharing accommodation platforms.

This study uses the property-month level data of Airbnb Beijing from January 2019 to June 2020. Econometric analyses are adopted to evaluate the impact of institution-based trust on consumers' purchase intention. Specifically, the ordinary least square is used to testify the relationship between institution-based trust and purchase intention.

The empirical results show that the information on institution-based trust increases the likelihood that customers would reach purchase decisions. More importantly, results show that both financial certification and social certification affect consumers' purchase intention. The results further show that listings' attributes moderate the relationship between institution-based trust and customer purchase intention. Moreover, the authors find that “Superhost” and “Experience” positively moderate such relationships.

This paper confirms that the host certification fosters institution-based trust and reveals the impact of hosts' certification on consumers' purchase intentions. This study is among one of the first studies to incorporate institution-based trust into the trust formation on the sharing economy platform, which can improve the understanding of trust in the sharing economy context. The authors emphasize the importance of trust types on sharing economy platforms.

The purpose of this paper is to compare GM(1,1) model, rolling GM(1,1) model and metabolism GM(1,1) model included in the GM(1,1) model cluster and use these models to forecast global oil consumption.

Simulated sequences will be generated randomly, and used to test the models included in the GM(1,1) model cluster; and these grey forecasting models are applied to forecast global oil consumption.

Effectiveness of these grey forecasting models is proved by random experiments, which explains the model adaptability. Global oil consumption is predicted, and it shows that global oil consumption will increase at a rather big growth rate in the next years.

The effectiveness of medium-term prediction of these grey forecasting models is analyzed by random experiments. These models are compared, and some basis for model selection is obtained.

The purpose of this paper is to investigate three issues: how does an innovative search (local search and boundary-spanning search) impact firm innovation performance of latecomers; how does capability reconfiguration (capability evolution and capability substitution) mediates the relationship between innovative search and firm innovation performance; and how does the technological leapfrogging process (initial stage, following stage, synchronization stage and leading stage) moderate the relationship between capability reconfiguration and firm innovation performance.

A “resource-capability-performance” theoretical framework was developed to explore the relationships between local/boundary-spanning search, capability reconfiguration and firm innovation performance. The data were collected by sending out surveys to managers and employees in various industries in mainland China. These hypotheses were tested using structural equation models and hierarchical regressions.

The results showed that: innovative search has a direct causal relationship to capability reconfiguration; local search and boundary-spanning search are conducive to improve the innovation performance of latecomers; the impact of local search and boundary-spanning search on innovation performance is realized through the completion of mediating role of capability reconfiguration; there are differences in the path of local search and boundary-spanning search affecting the capability reconfiguration of enterprise innovation performance; and the relationship between innovative search, capability reconfiguration and enterprise innovation performance evolves with the enterprise in different stages of technological leapfrogging.

This study explores the relationship and the path of innovative search to firm innovation performance and analyzes the path difference between local search and boundary-spinning search, which enriches the research of organizational search and enterprise innovation. This paper reveals the whole path of innovative search affecting innovation performance, discusses the important role of capability reconfiguration and makes incremental contributions to dynamic capability theory. It studies the evolution of innovative search on innovation performance under the background of technological leapfrogging, which provides a new perspective for the study of organizational search and capability-based theory.

Metaheuristic algorithms based on biology, evolutionary theory and physical principles, have been widely developed for complex global optimization. This paper aims to present a new hybrid optimization algorithm that combines the characteristics of biogeography-based optimization (BBO), invasive weed optimization (IWO) and genetic algorithms (GAs).

The significant difference between the new algorithm and original optimizers is a periodic selection scheme for offspring. The selection criterion is a function of cyclic discharge and the fitness of populations. It differs from traditional optimization methods where the elite always gains advantages. With this method, fitter populations may still be rejected, while poorer ones might be likely retained. The selection scheme is applied to help escape from local optima and maintain solution diversity.

The efficiency of the proposed method is tested on 13 high-dimensional, nonlinear benchmark functions and a homogenous slope stability problem. The results of the benchmark function show that the new method performs well in terms of accuracy and solution diversity. The algorithm converges with a magnitude of 10-4, compared to 102 in BBO and 10-2 in IWO. In the slope stability problem, the safety factor acquired by the analogy of slope erosion (ASE) is closer to the recommended value.

This paper introduces a periodic selection strategy and constructs a hybrid optimizer, which enhances the global exploration capacity of metaheuristic algorithms.