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This study aims to examine the role of face consciousness, materialism and risk of embarrassment in determining consumer purchase intention toward counterfeit luxury brand. In addition, the authors explore boundary conditions of these relationships.

Study 1, a survey research (N = 321), examines the mediating role of risk of embarrassment between face consciousness on the purchase intention toward luxury counterfeits. Study 2 (N = 345), an experimental study, examines the moderating role of brand prominence of counterfeit (i.e. whether it contains prominent brand signals). Study 3 (N = 315) explores how the above-mentioned relationships are moderated by consumers’ moral rationalization (i.e. whether consumers seek rationalization when behaving unethically).

First, this research shows that risk of embarrassment mediates the negative relationship between face consciousness and Chinese consumers’ purchase intention toward luxury counterfeits, whereas this relationship was not found between materialism and counterfeit purchase intentions. Second, this negative mediating effect holds only when the counterfeit brand is highly prominent. Third, the mediating effect depends on consumers’ moral rationalization, with a positive impact on the purchase intention toward luxury counterfeits, regardless of brand prominence.

This study represents a preliminary inquiry into the dynamics between face consciousness and materialism in influencing Chinese consumers’ purchase intention toward counterfeit luxury products. Unlike their Western counterparts, whose materialistic views of possessions predict their counterfeit luxury consumption (Davidson et al., 2019), Chinese consumers are more likely to be driven by the social implications of counterfeit luxury to communicate a prestigious social image to others on account of genuine luxuries’ high social recognition.

While Chinese consumers are one of the most potent global luxury buyers, they are immersed in the world’s biggest counterfeit luxury market. By digging into the core value of Chinese consumers (i.e. face consciousness), this research provides a number of managerial implications for luxury goods companies to engage in international efforts to educate consumers against counterfeit luxury.

This study makes at least three contributions to the counterfeit consumption literature. First, this study represents a preliminary inquiry into the dynamics between face consciousness and materialism in influencing Chinese consumers’ purchase intention toward counterfeit luxury products. Second, this research identified the complex mechanism of face consciousness as an independent variable on consumers’ purchase intention toward luxury counterfeits. Finally, the authors examined the boundary conditions of brand prominence and consumers’ moral rationalization. The findings may help luxury brand managers identify strategies to discourage counterfeit consumption.

The authors empirically examined social capital factors affecting patients' social support acquisition with the aim of providing guidance to patients seeking social support online.

The authors used social network analysis to extract data about social capital factors from online health communities and text mining to identify forms of informational support and emotional support grounded in online, text-based communication. Moreover, the authors employed a random coefficient model to understand the dynamic influence of social capital factors on both informational and emotional support.

The results from the empirical analyses show that structural connections have a lasting impact on the acquisition of both types of support; that is, social connections developed in the past will have an effect on the future. For relational capital, strong ties were less important; the quantity of connections mattered more than the quality when acquiring informational support. The use of health-related language increased the amount of informational support acquired. Over time, patients gained increasing social support, which primarily came from the patients' historical threads, likely via searches from peers facilitated by accumulated social capital.

The authors' research adds to the literature on social capital and social support in online health communities by exploring how the three dimensions of social capital affect social support acquisition. The authors' research also contributes to the online health care literature by examining social support from a dynamic perspective. Practically, the authors' findings provide guidance for patients on what decisions to make to acquire more social support.

This study investigates drivers and dynamics of preferences for brand prominence among the Chinese little emperors (LEs) residing in the US, a unique but powerful consumer group with dual-cultural characteristics.

Using an online survey, the proposed model was tested with a convenience sample of the Chinese LE generation residing in the US

Susceptibility to normative influence was a significant cultural driver of conspicuous, social, and unique value perceptions of luxury consumption among the Chinese LE generation residing in the US Perceived conspicuous and social values of luxury consumption were the primary drivers of this group's brand prominence preference for luxury fashion bags. However, perceived unique value of luxury consumption did not necessarily lead these consumers to prefer prominent logos or marks on a luxury bag. Furthermore, sociodemographic factors (gender, age, and time lived in the US) significantly affected perceptions and preferences related to luxury consumption among this consumer group.

This study advances the luxury literature by examining the drivers and dynamics of brand prominence preference among the Chinese LE generation residing in the US By testing the role of different sociodemographic factors, we demonstrate heterogeneity within this group and the evolving nature of their perceptions and preferences related to luxury consumption as they are acculturated to Western culture. We used a convenient sample and focused on luxury fashion bags for measuring preference for brand prominence, limiting the generalizability of the findings.

Luxury brands should effectively convey conspicuous and social values in product designs, advertising and promotions as these values play integral roles in determining the Chinese LE generation's preference for brand prominence. Our findings also highlight the importance of fine-tuned approaches to different segments within the LE generation cohort.

This study fills several gaps in the luxury literature by empirically investigating various factors affecting preference for brand prominence among the Chinese LE generation residing in the US, an important but under-researched luxury segment.

The model of pay-for-knowledge incentivizes individuals with financial rewards for sharing their expertise, facilitating a transactional exchange between knowledge providers (sellers) and seekers (buyers). While this model is effective in promoting paid contributions, its influence on free knowledge exchanges remains ambiguous, creating uncertainty about its overall impact on platform knowledge ecosystems. This study aims to explore the mechanim of how knowledge payment influences free knowledge contribution. Based on relational signaling theory, this study posits that a buyer’s payment for knowledge acts as a positive relational signal in the buyer–seller relationship and examines how the signaling effect varies across different social contexts through attribution theory.

This paper empirically tests the hypotheses by analyzing a data set comprising 630 instances from 359 unique knowledge sellers on Zhihu, a prominent knowledge-sharing platform in China. This paper use zero-inflated negative binomial models to conduct this analysis.

The findings reveal that when buyers pay for knowledge, this action positively influences sellers to contribute knowledge for free. However, the strength of this influence is moderated by the platform’s social functions: appreciation feedback tends to weaken this effect, while social network ties enhance it.

Prior research has predominantly focused on the financial incentives of pay-for-knowledge and its spillover effects on unpaid users’ activities. This study shifts the focus to the social dimensions of pay-for-knowledge, arguing that buyer-initiated knowledge payments signal buyers’ commitment to foster reciprocal relationships with sellers. It expands the literature on the relationship between knowledge payment and contribution, moving beyond financial incentives to include social factors, thus enriching our understanding of the interplay between paid and free knowledge activities. Additionally, the empirical evidence supports the efficacy of pay-for-knowledge in promoting both free and paid contributions within knowledge-sharing platforms.

In the hybrid knowledge-sharing platform where paid and nonpaid (“free”) knowledge activities coexist, users’ free knowledge contribution may be influenced by financial factors. From the perspective of opportunity cost, this study investigates the direct effect of how the amount of monetary income from users’ contribution to paid knowledge activities influences their free knowledge contribution behavior in the future. Further, this study aims to verify the interaction effect of financial and nonfinancial factors (i.e. the experience of free knowledge contribution and social recognition) on free knowledge contribution.

Objective data was collected from a hybrid knowledge-sharing platform in China and then analyzed by using zero-inflated negative binomial regression model.

Results show that the amount of monetary income that knowledge suppliers gain from paid knowledge contribution negatively influences their free knowledge contribution. Experience of free knowledge contribution strengthens the negatively main effect, while social recognition has the weakening moderating role.

Although some studies have explored and verified the positive spillover effect of financial incentives on free knowledge contribution, the quantity dimension is ignored. This study examines the hindering influence of the quantity of monetary income from the perspective of opportunity cost. By taking the characteristic of knowledge suppliers and platforms as moderators, this study deepens the understanding of the influence of monetary income on free knowledge contribution in the hybrid knowledge-sharing platform.

The adoption of emerging information and communication technologies in construction project teams has engendered numerous virtual spaces, characterized by communication visibility and content persistence. As a result, the knowledge exchanged in these virtual spaces serves as a team’s digital resources. However, the extant literature mostly takes a process-based approach to examine the impact of knowledge sharing, thus failing to fully comprehend the process of converting digital resources into performance, resulting in a gap in the literature.

This study employs team resource-based theory to construct a theoretical model and develop hypotheses. Specifically, knowledge integration capability and team efficacy are hypothesized as two types of critical capabilities that mediate the links between knowledge sharing (quantity and quality) in virtual spaces and management performance. Data from 128 middle and senior construction project managers were collected to test the proposed theoretical model.

The results suggest that relationships between knowledge sharing (quantity and quality) and project management performance are both mediated by knowledge integration capability. Moreover, team efficacy could only partially translate knowledge sharing quantity into performance and couldn’t transform knowledge sharing quality into performance. Besides, knowledge integration is found to strengthen the link between knowledge sharing quantity and performance but weaken the relationship between knowledge sharing quality and performance.

This study explores how knowledge shared in virtual spaces could be leveraged for improving management performance in construction project teams. The findings in this study enhance the understanding of knowledge sharing in digital environments and afford important insights into transforming digital resources into performance within construction project teams.

Social loafing in knowledge contribution (namely, knowledge contribution loafing [KCL]) usually happens in group context, especially in the mobile collaboration tasks. KCL shows dynamic features over time. However, most previous studies are based on static assumption, that is, KCL will not change over time. This paper aims to reveal the dynamics of KCL in mobile collaboration and analyze how network centrality influences KCL states considering the current loafing state.

This study is based on empirical study design. Real mobile collaboration behavioral data related to knowledge contribution were collected to investigate the dynamic relationship between network centrality and KCL. In total, 4,127 chat contents were collected through Slack (a mobile collaboration APP). The text data were first analyzed using the text analysis method and then analyzed by a machine learning method called hidden Markov model.

First, the results reveal the inner structure of KCL, showing that it has three states (low, medium and high). Second, it is found that network centrality positively influences individuals involved in medium and high loafing state, while it has a negative influence on individuals with low loafing state.

The limitations are related to the single machine learning method and no subdivision of social network. First, this paper only uses one kind of text classification model (TF-IDF) to divide chat contents, which may not be superior to other classification models. This paper considers the eigenvector centrality, and not further divides the social network into advice network and expressive network.

This study helps companies infer tendency of different KCL and dynamically re-organize a mobile collaborative team for better knowledge contribution.

First, previous studies based on static assumptions regarding KCL as static and the relationship between loafing reducing mechanisms and team members KCL does not change over time. This study relaxes static assumptions and allows KCL to change during the process of collaboration. Second, this study allows the impact of network centrality to be different when members are in different KCL states.

In today’s turbulent and complex era, initiative behavior is becoming more drawn to construction projects but challenging to arouse as it is free of the established regulations in project practice. Given the prevalence of social media (SM) in modern workplaces, this study is thereby motivated to investigate whether and how SM use can act to drive initiative behavior of construction project members (PMs) in this context.

This study sharply examines two distinct types of SM use – work-related and social-related – to explore their roles in driving the initiative behavior of construction PMs. Additionally, self-determination theory is employed to explore their underlying translation mechanisms and associated boundary conditions. A survey dataset collected from 229 construction PMs is used to empirically test the proposed theoretical model.

Empirical results show that role-breadth self-efficacy, psychological safety and project identification, by satisfying basic psychological needs respectively, act as crucial bridging roles in translating SM use into initiative behavior of PMs. Such mediation effects are applied to both work-related and social-related SM use with varied mechanisms. Besides, prevention focus is found to be a contingent moderator on these relationships, with a strengthening role toward role-breadth self-efficacy and a weakening role toward project identification.

This study digs into the nuanced mechanisms of how SM use benefits construction projects, especially in terms of PMs’ initiative. The findings of this research afford new insights into effectively invigorating the initiative behavior of construction PMs under the current digital momentum.

In an intelligent transportation system (for short, ITS) environment, a vehicle’s motion is affected by the information in a large scale. The purpose of this paper is to study the integration effect of multiple vehicles’ delayed velocities on traffic flow.

This paper constructed a new car-following model to study the integration effect of multiple vehicles’ delayed velocities on traffic flow. The new model is analyzed by linear and nonlinear perturbation method theoretically and also verified by simulation.

It is found out that the integration of preceding vehicles’ delayed velocities affect the stability of traffic flow importantly, and three preceding vehicles’ delayed velocities information should be considered in real traffic.

The new car-following model by considering the integration effect of multiple vehicles’ delayed velocities is firstly proposed in this paper. The research result shows that three preceding vehicles’ delayed velocities information is the best choice to stabilizing traffic flow.

The purpose of this paper is to develop a theoretical model of a jump diffusion-mean reversion constant proportion portfolio insurance strategy under the presence of transaction cost and stochastic floor as opposed to the deterministic floor used in the previous literatures.

The paper adopts Merton’s jump diffusion (JD) model to simulate the price path followed by risky assets and the CIR mean reversion model to simulate the path followed by the short-term interest rate. The floor of the CPPI strategy is linked to the stochastic process driving the value of a fixed income instrument whose yield follows the CIR mean reversion model. The developed model is benchmarked against CNX-NIFTY 50 and is back tested during the extreme regimes in the Indian market using the scenario-based Monte Carlo simulation technique.

Back testing the algorithm using Monte Carlo simulation across the crisis and recovery phases of the 2008 recession regime revealed that the portfolio performs better than the risky markets during the crisis by hedging the downside risk effectively and performs better than the fixed income instruments during the growth phase by leveraging on the upside potential. This makes it a value-enhancing proposition for the risk-averse investors.

The study modifies the CPPI algorithm by re-defining the floor of the algorithm to be a stochastic mean reverting process which is guided by the movement of the short-term interest rate in the economy. This development is more relevant for two reasons: first, the short-term interest rate changes with time, and hence the constant yield during each rebalancing steps is not practically feasible; second, the historical literatures have revealed that the short-term interest rate tends to move opposite to that of the equity market. Thereby, during the bear run the floor will increase at a higher rate, whereas the growth of the floor will stagnate during the bull phase which aids the model to capitalize on the upward potential during the growth phase and to cut down on the exposure during the crisis phase.