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The purpose of this paper is to identify the design elements of environmental features that affect consumer experience in shopping malls and develop a comprehensive understanding of the relationship between architectural design and consumer experience.

Through the systematic literature review, 13 design elements were obtained and then verified through interviews of 30 professional designers. The obtained elements were made into a questionnaire to collect data across China from 1,016 consumers of different groups. Data were analyzed using cluster analysis, principal component analysis and difference analysis.

The results show that design elements that influence consumer experience in shopping malls are a four-dimensional construct: visual atmosphere, physical environment comfort, space structure and business planning, among which space structure and business planning play a larger role in the consumer experience. In addition, the perception differences of consumers for those elements are significant due to the individual differences.

This paper comprehensively investigates the architectural design elements affecting consumer experience in the Chinese mall context. Moreover, it provides unique insights about the relationship between architectural design and consumer experience by exploring the categories, weights and perception differences of those elements.

The purpose of this study is to clarify theory and identify factors that could explain the level of fintech continuance intentions with an expectation confirmation model that integrates self-efficacy theory.

With data collected from 753 fintech users, this study applies partial least square structural equation modeling to compare and select the research model with the most predictive power.

The results show that financial self-efficacy, technological self-efficacy and confirmation positively affect perceived usefulness. Among these factors, financial self-efficacy and technological self-efficacy have both direct and indirect effects through confirmation on perceived usefulness. Perceived usefulness and confirmation are positively related to satisfaction. Finally, perceived usefulness and satisfaction positively influence fintech continuance intentions.

To the best of our knowledge, this is one of the earliest studies that investigates the effect of domain-specific self-efficacy on fintech continuance intentions, which enriches the existing research on fintech and deepens our understanding of users' fintech continuance intentions. We distinguish between financial self-efficacy and technological self-efficacy and specify the relationship between self-efficacy and continuance intentions. Moreover, this study highlights the importance of assessing a model's predictive power using the PLSpredict technique and provides a reference for model selection.

Facial recognition payment is an emerging mobile payment method that uses human biometrics for personal identification. The purpose of this study is to examine how users' salient beliefs regarding the technology–organization–environment–individual (TOE–I) dimensions affect their attitudes and how attitudes subsequently influence the intention to use facial recognition payment in offline contactless services.

This study comprehensively investigates customers' decision-making psychological mechanism of using facial recognition payment by integrating the belief–attitude–intention (B–A–I) model and the extended TOE–I framework. Data from 420 valid samples were collected through an online survey and analyzed using partial least squares structural equation modeling.

Research results indicate that convenience and perceived herd exert positive effects on trust and satisfaction. Meanwhile, familiarity has a significantly positive effect only on trust but not on satisfaction. In contrast, perceived privacy risk exhibits a negative effect on both trust and satisfaction. Trust and satisfaction positively influence the intention to use facial recognition payment. Unexpectedly, self-awareness negatively moderates the effect of satisfaction on intention to use, but its effect on the relationship between trust and intention to use is non-significant.

To the best of the authors’ knowledge, this study is one of the early studies that explicate customers' psychological mechanism in facial recognition payment in offline contactless services through an understanding of the B–A–I causal linkages with the identification of users' perceptions from a comprehensive context-specific perspective. This study enriches the literature on facial recognition payment and explores the moderating role of self-awareness in the relationship between users' attitudes and intention to use, thereby revealing a complex psychological process in the usage of offline facial recognition payment systems.

Drawing on transaction cost economics (TCE) theory and organizational information processing theory (OIPT), this study investigates how the alignments between the characteristics of service (i.e. task complexity and measurement ambiguity) and governance mechanisms (i.e. contract specificity and monitoring) can affect service performance.

The paper uses a rigorously designed survey to collect data from professionals who manage service outsourcing contracts in various industries. The respondent pool consists of randomly selected members of the Institute of Supply Management (ISM). The authors’ research question is analyzed using 261 completed and useable responses. Structural equation modeling is adopted to examine the data and test the proposed hypotheses.

The authors find that both contract specificity and monitoring have a positive impact on supplier performance. Further, for high task complexity services, contract specificity is more effective than monitoring, and for high measurement ambiguity services, the opposite is true. Moreover, the effect of contract specificity is mediated by monitoring.

Service outsourcers should use both contract specificity and monitoring in governing outsourced services and know that the former depends on the latter during execution. Facing resource constraints, they can prioritize crafting detailed contract provisions over implementing monitoring for highly complex services but consider monitoring as the primary governance tool in services whose outcomes are difficult to measure.

This study is the first to couple TCE with OPIT and consider the nature of outsourced services in the choice of governance mechanisms and empirically test the simultaneous effects of contract specificity and monitoring in the context of service outsourcing.

This research aims to explore the fine-grained relationships between nurse staffing and hospital operational performance with respect to care quality and operating costs. The authors also investigate the moderation effect of competition in local hospital markets on these relationships.

A six-year panel data is assembled from five separate sources to obtain information of 2,524 USA hospitals. Fixed-effect (FE) models are used to test the proposed hypotheses.

First, nurse staffing is initially associated with improved care quality until nurse staffing reaches a turning point, beyond which nurse staffing is associated with worse care quality. Second, a similar pattern applies to the relationship between nurse staffing and operating costs, although the turning point is at a much lower nurse staffing level. Third, market competition moderates the relationship between nurse staffing and care quality so that the turning point of nurse staffing will be higher when the degree of competition is higher. This shift of turning point is also observed in the relationship between nurse staffing and operating costs.

The study identifies three ranges of nurse staffing in which hospitals will likely experience simultaneous improvements, a tradeoff or simultaneous decline of care quality and operating costs when investing in more nursing capacity. Hospitals should adjust nurse staffing levels to the right directions to achieve better care or reduce operating costs.

Nurses constitute the largest provider group in hospitals and profoundly impact care quality and operating costs among all health care professionals. Optimizing the level of nurse staffing, therefore, can significantly impact the care quality and operating costs of hospitals.

Continuous fiber reinforced thermoplastic composites (CFRTPCs) with great mechanical properties and green recyclability have been widely used in aerospace, transportation, sports and leisure products, etc. However, the conventional molding technologies of CFRTPCs, with high cost and low efficiency, limit the property design and broad application of composite materials. The purpose of this paper is to study the effect of the 3D printing process on the integrated rapid manufacturing of CFRTPCs.

Tensile and flexural simulations and tests were performed on CFRTPCs. The effect of key process parameters on mechanical properties and molding qualities was evaluated individually and mutually to optimize the printing process. The micro morphologies of tensile and flexural breakages of the printed CFRTPCs were observed and analyzed to study the failure mechanism.

The results proved that the suitable process parameters for great printing qualities and mechanical properties included the glass hot bed with the microporous and solid glue coatings at 60°C and the nozzle temperature at 295°C. The best parameters of the nozzle temperature, layer thickness, feed rate and printing speed for the best elastic modulus and tensile strength were 285°C, 0.5 mm, 6.5r/min and 500 mm/min, respectively, whereas those for the smallest sectional porosity were 305°C, 0.6 mm, 5.5r/min and 550 mm/min, respectively.

This work promises a significant contribution to the improvement of the printing quality and mechanical properties of 3D printed CFRTPCs parts by the optimization of 3D printing processes.

The purpose of this paper is to present a numerically adaptive finite element (FE) method for accurate, efficient and reliable eigensolutions of regular second- and fourth-order Sturm–Liouville (SL) problems with variable coefficients.

After the conventional FE solution for an eigenpair (i.e. eigenvalue and eigenfunction) of a particular order has been obtained on a given mesh, a novel strategy is introduced, in which the FE solution of the eigenproblem is equivalently viewed as the FE solution of an associated linear problem. This strategy allows the element energy projection (EEP) technique for linear problems to calculate the super-convergent FE solutions for eigenfunctions anywhere on any element. These EEP super-convergent solutions are used to estimate the FE solution errors and to guide mesh refinements, until the accuracy matches user-preset error tolerance on both eigenvalues and eigenfunctions.

Numerical results for a number of representative and challenging SL problems are presented to demonstrate the effectiveness, efficiency, accuracy and reliability of the proposed method.

The method is limited to regular SL problems, but it can also solve some singular SL problems in an indirect way.

Comprehensive utilization of the EEP technique yields a simple, efficient and reliable adaptive FE procedure that finds sufficiently fine meshes for preset error tolerances on eigenvalues and eigenfunctions to be achieved, even on problems which proved troublesome to competing methods. The method can readily be extended to vector SL problems.

The growth of the Chinese economy has resulted in a significant increase in construction and demolition waste (CDW), and regional differences in CDW generation are gradually increasing. The purpose of this study is to investigate the regional differences in CDW generation and the driving factors that influence CDW generation in different areas of China. To provide a systematic advisement for local governments to select the appropriate policy, reduce CDW generation.

The generation of CDW was calculated by region, based on the area estimation method, from 2005 to 2018. The relationship between CDW generation and economic development, and the driving factors of CDW generation in different regions of China, was investigated using the environmental Kuznets curve (EKC) model and the STIRPAT theoretical model.

CDW generation of China increased at the average annual growth rate of 10.86% from 2005 to 2018. The main areas of CDW generation were concentrated in the eastern and central regions, while the proportion of CDW generation in the northeast region decreased gradually, and the changes varied significantly across different regions. The EKC between CDW generation and economic development was established for the whole country, North China, Northeast China, East China, Central South China, Southwest China and Northwest China. Three main factors based on the STIRPAT theoretical model were identified and explained into a framework to reduce CDW generation. The results provided a useful theoretical basis and data support guide for devising effective policies and regulations for the Chinese context.

The findings from this study can ultimately support policymakers and waste managers in formulating effective policies for waste management strategies and CDW-specific legislation. Additionally, it can help the coordinated reduction of CDW generation across regions in China and can support construction enterprises (in their development strategies), similar developing economies and foreign firms planning to operate in China.

This study contributes to the field through the STIRPAT model on driving factors of CDW generation in the Chinese context, in different regions.

The goal of this chapter is to respond to the theoretical inquiries by scholars who are interested in how the public–private partnership (PPP) models adapt to China’s context where political power dictates economic strategies. We also want to provide suggestions to policy designers who aim to promote a sustainable investment environment for domestic and international investors. We review the literature that explains the upside and downside of PPP projects in contemporary China. (1) We classify the trajectory of PPP evolution into four phases, i.e., emergence, growth, recession and revival. (2) We note that private companies take a disadvantageous position in the partnership compared with governments and state-owned enterprises because of a lack of specialized legislation, unequal competition between private companies and state-owned enterprises and the opposition from the civic society. (3) We identify political risks as the most influential risks. Political risks also lead to the misallocation of other risks between public and private parties that contributes to the high failure rate of China’s PPP projects. Based on these findings, we recommend governments to draft specialized legislation, stabilize the political environment and provide favourable subsidies to local governments to limit the risks involved in PPP projects. We also advise private enterprises and state-owned enterprises to focus on negotiating over task and risk division with governments when they make decisions to participate in PPP projects. This full review of studies on PPP development in China provides reliable recommendations to scholars, governments and enterprises.

Parallel factor analysis (PARAFAC) coupled with support-vector machine (SVM) was carried out to identify and discriminate between the fluorescence spectroscopies of coconut water brands.

PARAFAC was applied to reduce three-dimensional data of excitation emission matrix (EEM) to two-dimensional data. SVM was applied to discriminate between six commercial coconut water brands in this study. The three largest variation data from fluorescence spectroscopy were extracted using the PARAFAC method as the input data of SVM classifiers.

The discrimination results of the six commercial coconut water brands were achieved by three SVM methods (Ga-SVM, PSO-SVM and Grid-SVM). The best classification accuracies were 100.00%, 96.43% and 94.64% for the training set, test set and CV accuracy.

The above results indicate that fluorescence spectroscopy combined with PARAFAC and SVM methods proved to be a simple and rapid detection method for coconut water and perhaps other beverages.