Xiaoping Liu, Shiyu Wang and Yingqian Liang
Based on the construal level theory, this research study examines the interactive effect between social crowding and corporate social responsibility (CSR) statement type on…
Abstract
Purpose
Based on the construal level theory, this research study examines the interactive effect between social crowding and corporate social responsibility (CSR) statement type on consumers' purchase intention.
Design/methodology/approach
The authors conducted two empirical experiments on a total of 508 subjects.
Findings
There is an interactive effect between social crowding and CSR statement type on consumers' purchase intention. Specifically, in high social crowding situations, concrete CSR statements lead to consumers' higher purchase intention, while in low social crowding situations, abstract CSR statements lead to consumers' higher purchase intention. Self-construal and processing fluency play a moderating and mediating role in the mechanism.
Originality/value
This research study contributes to the theoretical understanding of the interaction between social crowding and CSR statements, enriching the field of consumer behavior research on social crowding. Additionally, it offers practical insights for enterprises on how to present CSR information in crowded situations.
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Xiaoping Liu and Hong He
Drawing on the stakeholder theory and stimulus-organism-response (S-O-R) model, this study examines the relationship between corporate social responsibility (CSR) disclosures and…
Abstract
Purpose
Drawing on the stakeholder theory and stimulus-organism-response (S-O-R) model, this study examines the relationship between corporate social responsibility (CSR) disclosures and users' knowledge-sharing behaviors on social media (SM). Two underlying mechanisms are used to explain the relationship between CSR disclosures and knowledge sharing, namely, CSR identification and content richness.
Design/methodology/approach
An empirical analysis based on a negative binomial regression model is conducted using CSR data disclosed on corporate official Microblog in the past year on 30 companies with a high CSR development index in China.
Findings
CSR disclosures are positively related to users' knowledge-sharing behaviors, and this relationship is mediated by CSR identification. Content richness strengthens the positive relationship between CSR disclosures and users' CSR identification. User's retweeting behavior is positively related to commenting behavior.
Originality/value
This is one of the few studies to investigate the relationship between CSR disclosures and knowledge sharing on SM. The findings of this study can help companies formulate and implement effective CSR disclosure strategies to achieve sustainable development of companies.
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Meier Zhuang, Wenzhong Zhu, Lihui Huang and Wen-Tsao Pan
The main purpose of this paper is to explore the influence mechanism of corporate social responsibility (CSR) for smart cities on consumers' purchase intention. The authors aim to…
Abstract
Purpose
The main purpose of this paper is to explore the influence mechanism of corporate social responsibility (CSR) for smart cities on consumers' purchase intention. The authors aim to identify the key components of CSR for smart cities based on the perspective of consumers, namely responsibility toward consumers, environment and community and validate their relationship.
Design/methodology/approach
The authors exploit data collected by questionnaire surveys to estimate the effects of CSR for smart cities on consumers' purchase intentions and to investigate the statistical causality between them. The multilinear regression model is used to figure out the different impact levels of the three dimensions of CSR for smart cities on consumers' purchase intention.
Findings
The results illustrate that CSR for smart cities and its three dimensions all have significant positive impacts on consumers' purchase intentions. Besides, consumer–corporate identity (CCI) exerts a partial mediation effect on this influence mechanism.
Research limitations/implications
This research is based on a rather small sample size. Besides, due to the time limitation and other factors, some other control variables are neglected in the regression model. Therefore, the impact level could be distorted.
Practical implications
The authors put forward management implications according to research conclusions. Corporates should actively fulfill the CSR in the field of consumer responsibility to boost consumers' purchase intention. Corporate should strengthen the interaction with consumers to improve their corporate identity.
Originality/value
The main contribution of this paper is to provide convincing evidence of the impacts of CSR for smart cities on consumer purchase intention (CPI), thus proposing effective measures for corporates to win more consumers by taking on social responsibility for smart cities. This paper takes CCI as mediating variable to deepen the understanding of the impacts of CSR for smart cities on CPI, which is innovative and beneficial to enriching literature in related fields.
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Weihua Liu, Yanjie Liang, Xiaoran Shi, Peiyuan Gao and Li Zhou
The review aims to facilitate a broader understanding of platform opening and cooperation and points out potential research directions for scholars.
Abstract
Purpose
The review aims to facilitate a broader understanding of platform opening and cooperation and points out potential research directions for scholars.
Design/methodology/approach
This study searches Web of Science (WOS) database for relevant literature published between 2010 and 2021 and selects 86 papers for this review. The selected literature is categorized according to three dimensions: the strategic choice of platform opening and cooperation (before opening), the construction of an open platform (during opening) and the impact of platform opening and cooperation (after opening). Through comparative analysis, the authors identify research gaps and propose four future research agendas.
Findings
The study finds that the current studies are fragmented, and a research system with a theoretical foundation has not yet formed. In addition, with the development of platform operations, new topics such as platform ecosystems and open platform governance have emerged. In short, there is an urgent need for scholars to conduct exploratory research. To this end, the study proposes four future research agendas: strengthen basic research on platform opening and cooperation, deeply explore the dynamic evolution and cutting-edge models of platform opening and cooperation, analyze potential crises and impacts of platform openness and strengthen research on open platform governance.
Originality/value
This is the first systematic review on platform opening and cooperation. Through categorizing literature into three dimensions, this article clearly shows the research status and provides future research avenues.
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Xiaoyu Yan, Weihua Liu, Victor Shi and Tingting Liu
The literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.
Abstract
Purpose
The literature review aims to facilitate a broader understanding of on-demand service platform operations management and proposes potential research directions for scholars.
Design/methodology/approach
This study searches four databases for relevant literature on on-demand service platform operations management and selects 72 papers for this review. According to the research context, the literature can be divided into research on “a single platform” and research on “multiple platforms”. According to the research methods, the literature can be classified into “Mathematical Models”, “Empirical Studies”, “Multiple Methods” and “Literature Review”. Through comparative analysis, we identify research gaps and propose five future research agendas.
Findings
This paper proposes five research agendas for future research on on-demand service platform operations management. First, research can be done to combine classic research problems in the field of operations management with platform characteristics. Second, both the dynamic and steady-state issues of on-demand service platforms can be further explored. Third, research employing mathematical models and empirical analysis simultaneously can be more fruitful. Fourth, more research efforts on the various interactions among two or more platforms can be pursued. Last but not least, it is worthwhile to examine new models and paths that have emerged during the latest development of the platform economy.
Originality/value
Through categorizing the literature into two research contexts as well as classifying it according to four research methods, this article clearly shows the research progresses made so far in on-demand service platform operations management and provides future research directions.
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Huajing Ying, Huanhuan Ji, Xiaoran Shi and Xinyue Wang
In the presence of coronavirus disease 2019 (COVID-19), due to the social distance restriction, consumers' regular consumption behaviors and patterns have been changing…
Abstract
Purpose
In the presence of coronavirus disease 2019 (COVID-19), due to the social distance restriction, consumers' regular consumption behaviors and patterns have been changing fundamentally. Thereafter, an innovative group buying model has emerged and developed explosively with a specific focus on consumer's location, known as community-based group buying (CGB). The purpose of this paper is to investigate the transfer mechanism of user's trust in dyadic contexts of social and commercial role-playing in the CGB program.
Design/methodology/approach
This study adopts an empirical research method, with an online and offline questionnaire survey, a total of 382 responses have been obtained. Then, both descriptive analysis and hierarchical regression analysis are conducted to explore the dual roles of group leader and its corresponding effects on consumers' trust (i.e. emotional trust and behavioral trust) and engagement actions (i.e. purchase and share) in the CGB program.
Findings
Results indicate that resident's trust and their perception of group leader's friend role can positively enhance their engagement actions in the CGB programs. Meanwhile, for the purpose of profit maximization, the group leader is more willing to play a friend role in transactions no matter whether the role conflict exists.
Originality/value
Research findings provide some managerial insights for CGB platform on the selection and training of group leaders and the incentive mechanism design.
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Jingyu Pei, Xiaoping Wang, Leen Zhang, Yu Zhou and Jinyuan Qian
This paper aims to provide a series of new methods for projecting a three-dimensional (3D) object onto a free-form surface. The projection algorithms presented can be divided into…
Abstract
Purpose
This paper aims to provide a series of new methods for projecting a three-dimensional (3D) object onto a free-form surface. The projection algorithms presented can be divided into three types, namely, orthogonal, perspective and parallel projection.
Design/methodology/approach
For parametric surfaces, the computing strategy of the algorithm is to obtain an approximate solution by using a geometric algorithm, then improve the accuracy of the approximate solution using the Newton–Raphson iteration. For perspective projection and parallel projection on an implicit surface, the strategy replaces Newton–Raphson iteration by multi-segment tracing. The implementation takes two mesh objects as an example of calculating an image projected onto parametric and implicit surfaces. Moreover, a comparison is made for orthogonal projections with Hu’s and Liu’s methods.
Findings
The results show that the new method can solve the 3D objects projection problem in an effective manner. For orthogonal projection, the time taken by the new method is substantially less than that required for Hu’s method. The new method is also more accurate and faster than Liu’s approach, particularly when the 3D object has a large number of points.
Originality/value
The algorithms presented in this paper can be applied in many industrial applications such as computer aided design, computer graphics and computer vision.
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Zhiwei Zhang, Saasha Nair, Zhe Liu, Yanzi Miao and Xiaoping Ma
This paper aims to facilitate the research and development of resilient navigation approaches, explore the robustness of adversarial training to different interferences and…
Abstract
Purpose
This paper aims to facilitate the research and development of resilient navigation approaches, explore the robustness of adversarial training to different interferences and promote their practical applications in real complex environments.
Design/methodology/approach
In this paper, the authors first summarize the real accidents of self-driving cars and develop a set of methods to simulate challenging scenarios by introducing simulated disturbances and attacks into the input sensor data. Then a robust and transferable adversarial training approach is proposed to improve the performance and resilience of current navigation models, followed by a multi-modality fusion-based end-to-end navigation network to demonstrate real-world performance of the methods. In addition, an augmented self-driving simulator with designed evaluation metrics is built to evaluate navigation models.
Findings
Synthetical experiments in simulator demonstrate the robustness and transferability of the proposed adversarial training strategy. The simulation function flow can also be used for promoting any robust perception or navigation researches. Then a multi-modality fusion-based navigation framework is proposed as a light-weight model to evaluate the adversarial training method in real-world.
Originality/value
The adversarial training approach provides a transferable and robust enhancement for navigation models both in simulation and real-world.
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Zhiwei Zhang, Zhe Liu, Yanzi Miao and Xiaoping Ma
This paper aims to develop a robust navigation enhancement framework to handle one of the most urgent needs for real applications of autonomous vehicles nowadays, as these corner…
Abstract
Purpose
This paper aims to develop a robust navigation enhancement framework to handle one of the most urgent needs for real applications of autonomous vehicles nowadays, as these corner cases act as the most commonly occurred risks in potential self-driving accidents.
Design/methodology/approach
In this paper, the main idea is to fully exploit the consistent features among spatio-temporal data and thus detect the anomalies and build residual channels to reconstruct the abnormal information. The authors first develop an anomaly detection algorithm, then followed by a corresponding disturbed information reconstruction network which has strong robustness to address both the nature disturbances and external attacks. Finally, the authors introduce a fully end-to-end resilient navigation performance enhancement framework to improve the driving performance of existing self-driving models under attacks and disturbances.
Findings
Comparison results on CARLA platform and real experiments demonstrate strong resilience of the authors’ approach which enhances the navigation performance under disturbances and attacks.
Originality/value
Reliable and resilient navigation performance under various nature disturbances and even external attacks is one of the most urgent needs for real applications of autonomous vehicles nowadays, as these corner cases act as the most commonly occurred risks in potential self-driving accidents. The information reconstruction approach provides a resilient navigation performance enhancement method for existing self-driving models.
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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…
Abstract
Purpose
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.
Design/methodology/approach
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.
Findings
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.
Originality/value
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.