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Secret consumption refers to consumption of a product in a private situation, with the intent or behavior of hiding the consumption from others. This study contributes to the secret consumption literature by identifying the antecedents of secret consumption along with the explaining mechanism and boundary condition.

An online study with experiment design was conducted to examine the impact of extroversion/introversion, self-presentation and product scarcity on secrete consumption.

The results show that consumer extraverted disposition and the self-presentation motive negatively influence secret consumption intention and suggest this relationship is explained by the self-presentation need. The findings also revealed that perceived product scarcity attenuated the negative impact of extraversion and self-presentation on secret consumption intention.

The findings provide interesting insights into advertising and retailing. In recognizing that secret consumption is a prevalent phenomenon in consumer behavior that may improve actual consumer product evaluation and preference, retailers or brand managers may encourage consumers to consume secretly.

This empirical study is a first attempt to explore the antecedents, mediating mechanism and boundary condition of consumer intention to engage in secrete consumption. The findings of the study provide important implication to theoretical development and managerial applications in advertising and retailing.

This paper aims to explore the impact of green finance on the heterogeneity of enterprise green technology innovation and the underlying mechanism between them.

Using the data of China's A-share listed enterprises from 2008 to 2020 and the fixed effect model, the authors empirically explore the relationship and mechanism between green finance and green technology innovation by constructing the green finance index while considering both the quality and quantity of innovation.

The study suggests that green finance is positively related to the quality and quantity of enterprise green technology innovation, while green finance is more effective in stimulating the quality of green technology innovation than quantity. In addition, alleviating financial mismatch and improving the quality of environmental information disclosure are core mechanisms during the process of green finance facilitating green technology innovation. Furthermore, green finance exerts a more positive effect on the quality and quantity of green technology innovation with large-size enterprises, heavily polluting industries and enterprises in the eastern region.

This paper enriches the literature on green finance and green technology innovation and provides practical significance for green finance implementation.

This study aims to develop a Stackelberg Game Model for seeking the optimal subsidy plans with varying levels of government financial capability (GFC). Furthermore, the scenario-based analysis is conducted and will enable governments to identify a comprehensive subsidy plan as follows: improve project performance and optimise social welfare.

A Stackelberg Game Model is developed to optimise the effectiveness of subsidies on the performance of public-private partnerships (PPPs).

According to the scenarios that are generated from the model, governments that are confronting with limited public budgets could reduce the intensity of performance incentives and increase the participation-oriented subsidy. Whilst a participation-oriented subsidy can stimulate private organisations’ willingness to participate in infrastructure PPPs, a performance-oriented subsidy is capable of facilitating the projects’ performances. Intuitively, the performance-oriented subsidy enables the private entities of PPPs to improve their efforts on the projects to realise higher profits. However, the participation-oriented subsidy is unable to affect the level of their effort spent on the projects. To satisfy both parties’ expectations in a PPP, the performance-oriented subsidy needs to be prioritised for a purpose of enabling higher quality outputs.

The game model developed in this study contributes to the literature by offering new insight into the underlying mechanism of governments and private entities, in terms of their decision-making for subsidy planning and contributions (i.e. resource allocation and spending) during the life-cycle of PPPs. This research enriches the government subsidy model by revealing the effects of the GFC and clarifies the impacts of two different schemes of subsidy on the performance of PPPs.

The government has been conventionally viewed as being omnipotent to provide PPPs with a wide range of subsidies. However, the subsidies are not unlimited, due to GFC. In addressing this void, this study has modelled the impacts of government subsidy plans with a consideration of GFC-related constraints. The combined effects of the participation- and performance-oriented subsidies on the project performance of PPPs have been examined.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

Placement prominence is a multidimensional concept. Previous studies have defined and operationalized prominence in different ways, and no studies have tried to systematically examine what should and should not be counted as prominence. This study aims to fill this gap.

Using a content analysis of six short films and a survey study on 129 Chinese young adults, this study systematically examined 13 dimensions of placement prominence on the memory of placed brands.

Factor analysis has reduced the 13 dimensions into five factors: contextual, narrative, sensory, exposure and spatial prominence. Fuzzy-set qualitative comparative analysis (QCA) software was used to conduct a contrarian case analysis and test for predictive validity. This was followed by a QCA to identify the optimal configurations of the five factors that may lead to a high recognition of the placed brands. The optimal configurations were also contrasted across two gender and brand familiarity groups. While the optimal configurations of prominence on brand memory for male and female participants were largely the same, the combinations differed between participants with low and high brand familiarity.

Previous studies in product placement usually operationalize prominence with a few dominant dimensions intuitively though several other dimensions, and their interactions could also affect the prominence level. To the best of authors’ knowledge, this is the first study that used multiple dimensions of prominence configurations to identify paths that may lead to low and high brand memory. The empirical results contribute to the theory and understanding of the effect of prominence on brand memory and provide guidance to brand managers in determining which prominence configuration is the most suitable for achieving their promotional objective.

This study aims to provide a series of drivers that prompt the blockchain technology (BT) adoption decisions in circular supply chain finance (SCF) and also assesses their degrees of influence and interrelationships, which leads to the construction of a theoretical model depicting the influence mechanism of BT adoption decisions in circular SCF.

This study mainly uses the technology-organization-environment (TOE) framework, which focuses on the aspects based on the nature of innovation, intra-organizational characteristics and extra environmental consideration, to identify the drivers of blockchain adoption in circular SCF context, while the significance and causality of the drivers are explained using interpreting structural models (ISMs) and the decision-making trial and evaluation laboratory (DEMATEL) method.

The findings of this study indicate that government policy and technological comparative advantage are the underlying reasons for BT adoption decisions, management commitment and financial expectations are the critical drivers of BT adoption decisions while other factors are the receivers of the mechanism.

This study provides theoretical references and empirical insights that influence the technology adoption decisions of both BT and circular SCF by practitioners.

The theoretical research contributes significantly to current research and knowledge in both BT and circular SCF fields, especially by extending the existing TOE model by combining relevant enablers from technological, organizational and external environmental aspects with the financial performance objectives of circular SCF services, which refer to the optimization of the financial resources flows and financing efficiency.

This study aims to investigate the factors driving viewers' purchase intention in live-streaming by incorporating stimuli–organism–response (S–O–R) framework and extroversion–introversion personality perspectives.

Data collected from 228 users on live-streaming platforms in Taiwan were used to test the proposed model. The partial least squares method was used to test the measurement and the structural models.

Product attractiveness and trust in streamer significantly impacts purchase intention. The results also reveal that interactivity, breadth of information and uniqueness of information significantly impact product attractiveness, whereas social presence, breadth of information and uniqueness of information positively affect trust in streamer. Furthermore, streamer attractiveness has a greater effect on the purchase intention of extroverts.

This study investigates how the features of media, message and streamer impact purchase intention through their reactions to live-streaming. This research is also one of the earliest studies to examine the moderating role of extroversion–introversion personality on purchase intention and its antecedents in live-streaming commerce.

With the rapid growth of the domestic lending industry, assessing whether the borrower of each loan is at risk of default is a pressing issue for financial institutions. Although there are some models that can handle such problems well, there are still some shortcomings in some aspects. The purpose of this paper is to improve the accuracy of credit assessment models.

In this paper, three different stages are used to improve the classification performance of LSTM, so that financial institutions can more accurately identify borrowers at risk of default. The first approach is to use the K-Means-SMOTE algorithm to eliminate the imbalance within the class. In the second step, ResNet is used for feature extraction, and then two-layer LSTM is used for learning to strengthen the ability of neural networks to mine and utilize deep information. Finally, the model performance is improved by using the IDWPSO algorithm for optimization when debugging the neural network.

On two unbalanced datasets (category ratios of 700:1 and 3:1 respectively), the multi-stage improved model was compared with ten other models using accuracy, precision, specificity, recall, G-measure, F-measure and the nonparametric Wilcoxon test. It was demonstrated that the multi-stage improved model showed a more significant advantage in evaluating the imbalanced credit dataset.

In this paper, the parameters of the ResNet-LSTM hybrid neural network, which can fully mine and utilize the deep information, are tuned by an innovative intelligent optimization algorithm to strengthen the classification performance of the model.

The purpose of this research paper is to explore the determinants of patients' service choices between telephone consultation and text consultation in online health communities (OHCs).

This study utilized an empirical model based on the elaboration likelihood model and examined the effect of information, regarding service quality (the central route) and service price (the peripheral route), using online health consultation data from one of the largest OHCs in China.

The logistic regression results indicated that both physician- and patient-generated information can influence the patients' service choices; service price signals will lead patients to cheaper options. However, individual motivations, disease risk and consulting experience change a patients' information processing regarding central and peripheral cues.

Previous researchers have investigated the mechanism of patient behavior in OHCs; however, the researchers have not focused on the patients' choices regarding the multiple health services provided in OHCs. The findings of this study have theoretical and practical implications for future researchers, OHC designers and physicians.