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Guided by stimulus-organism-response (SOR) theory, this study analyzed the user-generated content (UGC) produced by attendees from six anime conventions in the USA.

A total of 739 online reviews and 1,932 photos were collected from the social platforms of six large anime conventions in the USA (Yelp and Facebook), and the study employed thematic analysis and image analysis to analyze the collected UGCs.

The findings revealed eight main themes (i.e. ambient and space, customers, service and products, sign and symbol, social density, emotional status, motivation, and behavior intention) and 32 subthemes across the three dimensions of SOR theory. Leveraging the power of cutting-edge image analysis, the image labels obtained from the analysis contributed to the creation of network clusters. The result of the image analysis also continued consistently with the thematic analysis result, which reflected SOR theory.

Theoretically, the study applied SOR theory and blended thematic and image analyses to gain a comprehensive understanding of anime convention attendees’ experience and categorized the attendees’ emotional status as positive or negative to reflect their overall evaluation. Practically, this study highlighted some complaints from attendees and provided suggestions for operators. However, the study focused only on large anime conventions in the USA; future studies should compare attendees’ experiences with small and large conventions or anime conventions worldwide.

The study utilized UGCs to understand the key patterns essential to attendees during anime conventions in the USA and applied SOR theory to its investigation.

This study aims to systematically review the work–family enrichment (WFE) studies in hospitality and tourism management and provide insight into the patterns and trends of WFE literature to practitioners and future researchers.

This study design followed the guidelines of preferred reporting items of systematic reviews and meta-analysis. A final sample of 23 studies related to WFE that published from 2000 to 2021 was selected and systematically analyzed.

This study resulted in a framework that the antecedents and outcomes of WFE at the organizational, job and individual levels. Moderators between antecedents and outcomes were also identified. Theories such as conservation of resources theory, boundary theory, role theory and expansion theory were frequently applied in the investigation of WFE.

This study generated a framework that illustrates the organization characteristics, the job characteristics and individual factors that have examined in hospitality literature on the topic of WFE. This study also pointed out theories that have been used in investigating WFE. However, this systematic review may subject to publication bias and number of reviewed articles remained relatively small.

This study provides suggestions on how hospitality operators could use internal marketing strategies and certain leadership styles (e.g. transformational and servant leaderships) to enhance employees’ WFE.

This study summarized the publication trends and patterns of the WFE studies in hospitality and tourism management in the past two decades, which provides suggestions for future scholars to further explore this research topic.

In this study, a novel glutathione (GSH) surface molecular imprinting polymer (SMIP) was successfully prepared by using macroporous adsorption resins (MAR) as substrate, which could separate and purify GSH efficiently.

SMIP was synthesized by chloromethylated modified MAR (LX1180-Cl) as the substrate, N, N’-methylenebisacrylamide (NMBA) as a crosslinker, GSH as a template, acrylamide (AM) and N-vinylpyrrolidone (NVP) as functional monomers. The morphology and structure of the polymer were characterized by scanning electron microscope and Fourier transforms infrared spectroscopy.

The maximum adsorption capacity toward GSH was 39.0 mg/g and the separation decree had relation to L-cysteine (L-cys) was 4.2. The optimal operation conditions were studied in detail and the got as follows: the molar ratios of NMBA, AM, GSH and NVP, were 7.0, 0.8 and 0.5. The optimal time and temperature were 14 h and 40°C, respectively. The Langmuir and pseudo-first-order model were fitting these adsorption characteristics well.

GSH has a diversity of medicinal and bioactive functions, so the purpose of this study representing a method in separate and purify technology of GSH, which provided a way for the development of medicine.

This contribution provided a novel way to separate GSH from L-cys. Under the optimal conditions, the maximum adsorption capacity toward GSH was 39.0 mg/g and the separation decree had relation to L-cys was 4.2.

Wrist-cuff oscillometric blood pressure monitors are very popular in the portable medical device market. However, its accuracy has always been controversial. In addition to the oscillatory pressure pulse wave, the finger photoplethysmography (PPG) can provide information on blood pressure changes. A blood pressure measurement system integrating the information of pressure pulse wave and the finger PPG may improve measurement accuracy. Additionally, a neural network can synthesize the information of different types of signals and approximate the complex nonlinear relationship between inputs and outputs. The purpose of this study is to verify the hypothesis that a wrist-cuff device using a neural network for blood pressure estimation from both the oscillatory pressure pulse wave and PPG signal may improve the accuracy.

A PPG sensor was integrated into a wrist blood pressure monitor, so the finger PPG and the oscillatory pressure wave could be detected at the same time during the measurement. After the peak detection, curves were fitted to the data of pressure pulse amplitude and PPG pulse amplitude versus time. A genetic algorithm-back propagation neural network was constructed. Parameters of the curves were inputted into the neural network, the outputs of which were the measurement values of blood pressure. Blood pressure measurements of 145 subjects were obtained using a mercury sphygmomanometer, the developed device with the neural network algorithm and an Omron HEM-6111 blood pressure monitor for comparison.

For the systolic blood pressure (SBP), the difference between the proposed device and the mercury sphygmomanometer is 0.0062 ± 2.55 mmHg (mean ± SD) and the difference between the Omron device and the mercury sphygmomanometer is 1.13 ± 9.48 mmHg. The difference in diastolic blood pressure between the mercury sphygmomanometer and the proposed device was 0.28 ± 2.99 mmHg. The difference in diastolic blood pressure between the mercury sphygmomanometer and Omron HEM-6111 was −3.37 ± 7.53 mmHg.

Although the difference in the SBP error between the proposed device and Omron HEM-6111 was not remarkable, there was a significant difference between the proposed device and Omron HEM-6111 in the diastolic blood pressure error. The developed device showed an improved performance. This study was an attempt to enhance the accuracy of wrist-cuff oscillometric blood pressure monitors by using the finger PPG and the neural network. The hardware framework constructed in this study can improve the conventional wrist oscillometric sphygmomanometer and may be used for continuous measurement of blood pressure.

The purpose of this paper is to examine how the Chinese wine market can be meaningfully segmented and to explore marketing implications for the Australian wine sector.

The research is descriptive in nature, using an online survey to collect quantitative data on wine consumer behaviour. A total of 407 responses were obtained. Data analysis included descriptive analysis (frequency distributions) and cluster analysis.

The research identifies three clusters of wine consumers: “the extrinsic attribute-seeking customers”, “the intrinsic attribute-seeking customers” and “the alcohol level attribute-seeking customers”. These groups of consumers were categorised using a behavioural (benefit) segmentation base.

The use of an internet survey and convenience sample limits generalisation of the findings. The adoption of a behavioural basis in conducting the segmentation is a limitation. The use of more complex segmentation bases, such as psychographics, may yield a richer understanding of the Chinese wine consumer in future studies.

The customer profiles provide Australian wine marketers with an insight into Chinese wine consumer behaviour. Brand positioning can be improved by ensuring that the brand emphasises certain product attributes which the segments value when choosing wine.

Little previous research on market segmentation has been conducted in mainland China. For Australian wine marketers, this study provides a baseline study into market segmentation and may assist with targeting and brand positioning decisions.

This study aims to investigate whether mainland Chinese audit firms’ entry into the H-share market to provide audit services affects their mainland audit pricing.

Using data on A-share listed companies in China from 2008 to 2018, a difference-in-differences model to test the research question is designed. Robustness tests are conducted to rule out alternative explanations and additional tests to shed light on the extent and inner workings of the main effect.

The entry of mainland audit firms into the H-share audit market leads to a significant decrease in mainland audit pricing. Moreover, this main effect is (i) growing with the importance of H-share audit services to mainland auditors, (ii) stronger for mainland auditors with lower industry specialisation and shorter tenures, (iii) partially mediated by audit efficiency and (iv) greater when mainland clients have higher bargaining power. Furthermore, mainland auditors’ entry into the H-share audit market does not result in significant deterioration in their mainland audit quality, and significantly increases their market share in the mainland audit market.

This study provides new empirical evidence of the relationship between audit firms’ development strategy for internationalisation and audit pricing, extends the literature on auditing issues in emerging markets and should be of potential interest to regulators and investors.

Construction projects are well known for their complexity and ambiguity. These projects carry out higher risk than traditional ones because they entail high capital outlays and intricate site conditions. Poor financial management of these projects may lead to bankruptcy; therefore, effective cash flow management is essential. Although the peculiar characteristics of construction projects, the accuracy of cash flow forecasting has been a long lasting problem. The paper aims to discuss these issues.

Many unforeseen factors affect the cash flow forecasting of construction projects. Therefore, the objective of the presented research in this paper is to examine the impact of these factors on contractor's cash flow. A model has been established by integrating analytic hierarchy process and simulation to examine the impact of various factors on cash flow. Data on the selected factors have been collected through questionnaires from various agencies in North America and China.

Results show that the most significant factors are: change of progress payment, payment duration, financial position of the contractor, project delays, and poor planning. It also shows that the effect of cash inflow factors varied approximately from 9.7 to 16.3 percent with a mean value of 12.4 percent.

The implementation of the developed models are limited to few case study projects in testing the models. However, the developed models and framework are sound for future improvement. They are considered as a major step toward a broader cash flow planning.

The developed methodology and models play essential roles in decision-making process.

The developed model is expected to help contractors realistically forecast project cash flow under uncertainty. This may lead to more dependable and professional cash flow management, which might substantially reduce failures in construction business.

Various factors may influence project finance when a multi-sourced debt financing strategy is used for financing capital investments, in general, and public infrastructure investments, in particular. Traditional indicators lack comprehensive consideration of the influences of many internal and external factors, such as investment structure, financing mode and credit guarantee structure, which exist in the financing decision making of BOT projects. An effective approach is, thus, desired. The paper aims to discuss these issues.

This paper develops a financial model that uses an interval number to represent the uncertain factors and, subsequently, conducts a standardization of the interval number. Decision makers determine the weight of each objective through the analytic hierarchy process. Through the optimization procedure, project investors and sponsors are provided with a strategy regarding the optimal amount of debt to be raised and the insight on the risk level based on the net present value, as well as the probability of bankruptcy for each different period of debt service.

By using an example infrastructure project in China and based on the comprehensive evaluation, comparison and ranking of the capital structures of urban public infrastructure projects using the interval number method, the final ranking can help investors to choose the optimal capital structure for investment. The calculation using the interval number method shows that X2 is the optimal capital structure plan for the BOT project of the first stage of Tianjin Binhai Rail Transit Z4 line. Therefore, investors should give priority to selecting a capital contribution ratio of 45 per cent for this investment.

In this paper, some parameters, such as depreciation life, construction period and concession period, are assumed to be deterministic parameters, although the interval number model has been introduced to analyze the uncertainty indicators, such as total investment and passenger flow, of BOT rail transport projects. Therefore, more of the above deterministic parameters can be taken as uncertainty parameters in future research so that calculation results fit actual projects more closely.

This model can be used to make the optimal investment decision for a project by determining the impact of uncertainty factors on the profitability of the project in its lifecycle during the project financial feasibility analysis. Project sponsors can determine the optimal capital structure of a project through an analysis of the irregular fluctuation of the unpredictable factors in project construction such as construction investment, operating cost and passenger flow. The model can also be used to examine the effects of different capital investment ratios on indicators so that appropriate measures can be taken to reduce risks and maximize profit.

The construction industry has been investigating “where Henry Ford is in the industry system.” Given that listed construction enterprises are the backbone of the promotion of the high-quality development of the industry, their research and innovation are of considerable importance. This study aims to comprehensively assess the research and development (R&D) status quo and trends within various types of construction enterprises in order to identify effective strategies to enhance R&D efficiency in the construction industry.

Based on the data won from annual reports and the CSMAR database for the period 2016–2020, this study examines 104 listed construction enterprises in China. By applying both the data envelopment analysis (DEA) method and the Malmquist productivity index, this research compares and analyzes the static and dynamic differences in R&D efficiency across different types of construction enterprises.

Results suggest that the magnitude of change in the Malmquist decomposition index of 104 listed construction enterprises gradually narrowed, but the comprehensive technological level remained relatively low. Although state-owned enterprises had an advantage in scale efficiency, meaning they could maximize output with given inputs, their technological progress efficiency, also known as the degree of technological innovation, was significantly lower than that of private enterprises. As one finding, state-owned enterprises in comparison with private enterprises experience significant R&D inefficiency. It represents the main cause of their low degree of technological innovation and efficiency.

This study assesses the R&D efficiency of listed construction enterprises in China from the perspective of different market segments, state-owned and private enterprises and suggests approaches to improve strategies for various corporate types. Thus, the study’s new findings contribute to addressing the challenge of low R&D levels in the construction industry in the fields of engineering, construction and architectural management.

The paper aims to examine the corporate social responsibility (CSR) activity of audit firms.

Using hand-collected data on all Chinese audit firms’ CSR activities from 2007 to 2020, this study constructs two measures to proxy for audit firms’ CSR engagement: a dummy variable to indicate whether an auditor engages in CSR activities in year t and the frequency with which auditors conduct CSR activities in year t. The authors use ordinary least squares regression as a baseline methodology, along with the entropy balancing method and instrumental variable approach to alleviate potential endogeneity concerns.

The baseline results show that socially responsible audit firms provide higher quality audit services than their counterparts. In particular, the authors find that clients audited by socially responsible audit firms are less likely to receive an aggressively clean opinion. Moreover, the findings suggest that CSR activities related to community and employees are more relevant in improving audit quality compared with those related to other dimensions of CSR. Further analyses show that capital markets and audit clients react positively to audit-firm CSR activity. Audit firms engaging in CSR increase their audit inputs in response to risky clients, as compared with their counterparts. Finally, cross-sectional analyses show that the positive relationship is more pronounced for non-Big 4 and non-industry experts and is attenuated by within-firm geographic dispersion. In terms of client characteristics, the positive effect of audit-firm CSR is stronger when their clients face the higher financial risk or have lower CSR awareness than others. Taken together, these findings are consistent with the ethical view of audit-firm CSR engagement.

The study advances investors’ understanding of audit-firm CSR engagement and helps them evaluate the credibility of audited financial reports. Besides, the findings may also help guide the audit firms to conduct more CSR activities and help guide the audit clients to choose CSR audit firms.

To the best of the authors’ knowledge, this study provides the first large-sample evidence by empirically examining the association between audit-firm CSR activity and audit service performance. Besides, this paper also explores audit-firm CSR activity from two competing perspectives, thereby providing a comprehensive understanding of this issue. Finally, this work responds to the call for more CSR research in emerging markets.