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The purpose of this study is to examine how existing supply chain finance challenges confronting SMEs are affected by the emergence of smart fintech providers. In so doing the paper aims at uncovering critical role of fintech service provision in SCF and associated mechanisms that affect the SCF partners.

An in-depth case study approach has been applied in this study. The overall design is informed by a 5-stage-based case study approach developed in operation management, including the literature review and research question, followed by case selection and instrument development, the data gathering, the analysis and findings and dissemination.

The study shows that fintech service provider is capable of offering different digital technologies adapted to specific needs while concomitantly orchestrating the information flow across the partners. Key mechanisms that influence the establishment of trust-based relationships among the SCF partners, and related service processes and value creation based on the platform system architecture are explained.

Several practical implications for digital platform management and other key digital SCF partners are identified.

This paper contributes a novel perspective on the importance of digital trust in SCF and also contributes to the existing literature by filling up a gap with a new and fine-grained understanding of the role of fintech companies in SCF.

Security education, training and awareness (SETA) programs are the key to addressing “people problems” in information systems (IS) security. Contrary to studies using conventional methods, the present study leveraged an “event” lens and dimensionalized employees' perceptions into three sub-dimensions: perceived novelty, perceived disruption and perceived criticality. Moreover, this research went a step further by examining how pedagogical and communication approaches to a SETA program affect employees' perceptions of the program. This study then investigated whether – and if so, how – these approaches impact employees' perceptions of the SETA program and their subsequent commitment to it.

Utilizing a factorial-based scenario survey, this study empirically tested a model of the above relationships via covariance-based structural equation modeling.

The results of this research showed that pedagogical approaches were more effective than communication approaches and that employees' perceptions of the SETA program accounted for a large variance in their commitment to SETA.

First, this research deepens understanding of the protection of information assets by elaborating on the different approaches that organizations can take to encourage employees' commitment to SETA. Second, the study enriches the SETA literature by theorizing a SETA program as an organizational “event”, which represents a major shift from the conventional approach. Third, the study adds to the theoretical knowledge of the event lens by extending it to the SETA context and investigating the relationship among three event strength components.

Maximum k vertex cover problem is a significant combinatorial optimization problem with various applications, such as transportation planning, social networks and sensor placement. Up to now, no practical algorithm has ever been proposed to solve this problem. Therefore, this paper aims to present an efficient local search algorithm LSKVC combining three methods for it.

First, the quick incremental evaluation method is proposed to update the related vertex scores following each addition or removal incrementally rather than recalculating them, which can speed up the algorithm. Second, the configuration checking method forbids vertices whose configuration has not changed since the last removal from being added into the candidate solution again, which can avoid the cycling problem effectively. Third, the two-stage exchange method swaps the pairs of inside and outside vertices separately rather than simultaneously, which can guarantee the tradeoff between the accuracy and complexity of the algorithm.

The proposed algorithm LSKVC is compared with the traditional GRASP algorithm and the well-known commercial solver CPLEX on DIMACS and BHOSLIB benchmarks. For the best solutions, the LSKVC algorithm is significantly superior to GRASP and CPLEX on DIMACS instances and the CPLEX solver fails, and the LSKVC algorithm slightly outperforms GRASP on the BHOSLIB instances. In addition, we undertake comparative studies of the offered methodologies and demonstrate their efficacy.

In previous research, the focus on the maximum k-vertex cover problem primarily centered around exact algorithms and approximation algorithms, with limited application of heuristic algorithms. While heuristic algorithms have been well-explored for the closely related Minimum Vertex Cover problem, they have seen limited application in the context of the maximum k-vertex cover problem. Consequently, existing algorithms designed for the Minimum Vertex Cover problem do not exhibit satisfactory performance when applied to the maximum k-vertex cover problem. In response to this challenge, we have undertaken algorithmic improvements specifically tailored to address this issue.

The Soybean Producer Subsidy Policy (SPSP), an agricultural support policy enacted in China within the past few years, is designed to optimise crop planting structure. This study analyses the impact of SPSP on the crop planting structure in terms of absolute and comparative incomes and elucidates the mechanisms involved.

Utilising balanced county-level panel data from 966 counties in China’s major soybean-producing regions, spanning from 2008 to 2021, we investigate the impacts of SPSP on crop planting structure by applying a difference-in-difference (DID) model.

The findings reveal several crucial insights. First, SPSP optimises the crop planting structure in Northeast China, primarily through an expansion in the area sown to soybeans and a simultaneous reduction in the area sown to maize. Second, the impacts of SPSP gradually strengthen over time but begin to weaken by 2021. Third, heterogeneity analysis indicates that the effects of SPSP are most pronounced in Eastern Inner Mongolia, followed by Heilongjiang, Jilin, and Liaoning. Finally, SPSP incentivises farmers to expand soybean sown areas by improving absolute rather than comparative incomes from soybean cultivation.

Addressing structural contradictions within China’s food supply chain necessitates the adjustment of support policies for different crops to mitigate market distortions. Establishing a holistic agricultural support system encompassing various crops could promote sustainable agricultural practices in the future.

Our findings are valuable for policy makers in China and globally who aim to establish support systems for regional linkages that include a variety of crops.

Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.

The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.

The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.

First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.

The purpose of this paper is to examine the influence of intelligent manufacturing on audit quality and its underlying mechanism as well as the variation in this influence across different types of organizations.

This research utilizes a difference-in-differences (DID) method to examine how enterprises that apply intelligent manufacturing choose auditors and impact their audit work. The study is based on 15,228 observations of Chinese-listed A-shares from 2011 to 2020.

(1) There is a strong correlation between intelligent manufacturing and audit quality. (2) This positive correlation is statistically significant only in state-owned enterprises (SOEs), those that have steady institutional investors and where the roles of the CEO and chairman are distinct. (3) Enterprises that have implemented intelligent manufacturing are more inclined to employ auditors who possess extensive industry expertise. The auditor's industry expertise plays a crucial role in ensuring audit quality. (4) The adoption of intelligent manufacturing also leads to higher audit fees and longer audit delay periods.

This paper validates the beneficial impact of intelligent manufacturing on improving corporate governance. In addition, it is recommended that managers prioritize the involvement of skilled auditors with specialized knowledge in the industry to ensure the high audit quality and the transparency of information in intelligent manufacturing enterprises.

This study builds upon previous research that has shown the importance of artificial intelligence in enhancing audit procedures. It contributes to the existing body of knowledge by examining how enterprise intelligent manufacturing systems (IMS) enhance audit quality. Additionally, this study provides valuable information on how to improve audit quality in the field of intelligent manufacturing by strategically selecting auditors based on resource dependency theory.

The profound impact of the COVID-19 pandemic on the film industry has underscored the growing significance of online movies. However, there is limited research available on the factors that influence the viewership of online films. Therefore, this study aims to use the signaling theory to investigate how signals of varying qualities affect online movie viewership, considering both signal transmission costs and prices.

This study uses a sample of 1,071 online movies released on the iQiyi from July 2020 to July 2022. It uses OLS regression and instrumental variable method to examine the impact of various quality indicators on the viewership of online movies, as well as the moderating effect of price.

After conducting a thorough analysis of this study, it can be deduced that the varying impacts on online movie viewership are attributed to disparities in signal transmission costs. Specifically, star influence and rating exhibit a positive effect on the viewership of online movies, whereas the number of raters has a detrimental impact. Furthermore, there exists an “inverted U-shaped” relationship between the number of reviews and online movie viewership. Additionally, within the consumer decision-making process, both price-cost and price-quality relationships coexist. This is evident as prices negatively affect online movie viewership but positively moderate the relationship between rating, number of reviews and online movie viewership.

The research findings of this study offer valuable insights for online film producers to effectively leverage quality signals and pricing, thereby capturing market attention and enhancing film profitability.

This study aims to examine the impact of firm-generated content (FGC) on lesbian, gay, bisexual, transgender, queer/questioning (LGBTQ+) influencers, focussing on inclusive marketing strategies and enquires the ability of LGBTQ+ influencers to enhance brand engagement and loyalty within diverse communities.

A quantitative approach was utilized, and data was collected via social media platforms. Structural equation modelling (SEM) was employed to explore the relationships between FGC, influencer content, dimensions of place attachment and brand loyalty.

According to the findings FGC positively influences LGBTQ+ influencers, which in turn affect in a significant way place identity and place social bonding. Both dimensions of place attachment were found to have a positive impact on brand loyalty, which indicate that LGBTQ+ influencers have an important role in enhancing brand engagement through inclusive marketing.

Firms in order to increase their brand loyalty and customer engagement, need to adopt inclusive marketing strategies that resonate with LGBTQ+ communities. In order to do so they need to work with LGBTQ+ influencers that can effectively communicate the brand’s commitment to diversity and inclusion, thus fostering a stronger emotional connection with the brand.

This study introduces a conceptual framework that highlights the mediator role of place attachment in the relationship between influencer marketing and brand loyalty. This research contributes to the existing literature by providing empirical evidence on the effectiveness of leveraging LGBTQ+ influencers in inclusive marketing campaigns.