Qiao Li, Chunfeng Liu, Jingrui Hou and Ping Wang
As an emerging tool for data discovery, data retrieval systems fail to effectively support users' cognitive processes during data search and access. To uncover the relationship…
Abstract
Purpose
As an emerging tool for data discovery, data retrieval systems fail to effectively support users' cognitive processes during data search and access. To uncover the relationship between data search and access and the cognitive mechanisms underlying this relationship, this paper examines the associations between affective memories, perceived value, search effort and the intention to access data during users' interactions with data retrieval systems.
Design/methodology/approach
This study conducted a user experiment for which 48 doctoral students from different disciplines were recruited. The authors collected search logs, screen recordings, questionnaires and eye movement data during the interactive data search. Multiple linear regression was used to test the hypotheses.
Findings
The results indicate that positive affective memories positively affect perceived value, while the effects of negative affective memories on perceived value are nonsignificant. Utility value positively affects search effort, while attainment value negatively affects search effort. Moreover, search effort partially positively affects the intention to access data, and it serves a full mediating role in the effects of utility value and attainment value on the intention to access data.
Originality/value
Through the comparison between the findings of this study and relevant findings in information search studies, this paper reveals the specificity of behaviour and cognitive processes during data search and access and the special characteristics of data discovery tasks. It sheds light on the inhibiting effect of attainment value and the motivating effect of utility value on data search and the intention to access data. Moreover, this paper provides new insights into the role of memory bias in the relationships between affective memories and data searchers' perceived value.
Details
Keywords
Shuyi Kong, Mengling Xie, Wei Zhang, Chunfeng Xia, Xie Yi, Tamirat Solomon, Xinan Yin, Haifei Liu and Changhai Wang
This article aims to explore the key role of community participation in the protection and development of national parks under the global trend of national park development and…
Abstract
Purpose
This article aims to explore the key role of community participation in the protection and development of national parks under the global trend of national park development and provide reference for the construction of China’s national park system by analyzing international successful cases and experiences.
Design/methodology/approach
The study on “International Experience of Community Support for National Park Development” integrates multimethods, from data mining reports, journals and policy docs from WB, UNEP, to case analyses. In-depth interviews with policymakers, academics and farmers reveal needs, challenges and best practices. Comparative analysis tailors findings to China’s context, offering recommendations for enhancing community support. This hybrid approach ensures practical insights for China’s application.
Findings
The results of this study underscore the paramount significance of community participation as a cornerstone in advancing sustainable development and safeguarding national parks amidst a growing global awareness of environmental stewardship. Through a thorough examination of international National Parks such as Yellowstone, Maasai Mara, Uluru-Kata Tjuta and Sanjiangyuan, we reveal a blueprint of success that hinges on robust policy support, empowerment of local communities, strategic economic incentives and multifaceted cross-sectoral collaborations. In the context of domestic hurdles, including inadequate legal frameworks, narrow participation avenues and resource scarcities, our analysis outlines actionable recommendations aimed at fortifying policy and legal frameworks, establishing efficient engagement modalities, bolstering community capacity-building initiatives and fostering economic sustainability. This comprehensive approach presents a visionary roadmap for World’s national park system, guiding it towards achieving an optimal equilibrium where ecological integrity and community prosperity coexist harmoniously.
Originality/value
The article underscores the originality in illuminating the pivotal role of community participation in national park protection and development amidst a global shift. By delving into international exemplars like Yellowstone, Maasai Mara, Uluru-Kata Tjuta, Sanjiangyuan and Panda, it uncovers novel insights on policy frameworks, community empowerment, economic incentives and collaborative models. This work contributes to the burgeoning discourse on balancing ecological conservation with socioeconomic development, providing a blueprint for sustainable national park management of all the world.
Details
Keywords
Chunfeng Chen and Depeng Zhang
This research focuses on the role of product acquisition cues in positive word-of-mouth (PWOM) content on social media, comparing the characteristics of different sources of…
Abstract
Purpose
This research focuses on the role of product acquisition cues in positive word-of-mouth (PWOM) content on social media, comparing the characteristics of different sources of product acquisition (purchased vs. gifted) and exploring whether and how they affect consumers' reliance on word-of-mouth (WOM).
Design/methodology/approach
The research model was developed based on the mental imagery theory. Two offline experiments and two online experiments were used to test the proposed hypotheses.
Findings
The results show that, compared to the purchased source, the gifted source evokes more positive mental imagery and greater emotional attachment to the product, resulting in greater consumer reliance on PWOM. In addition, the effect of the source of product acquisition on reliance on PWOM was stronger for experiential (vs. material) products and for consumers with higher interdependent (vs. independent) self-construal.
Originality/value
This research highlights the role of product acquisition cues in PWOM in influencing consumers' evaluation of WOM, while also revealing the processes inherent in how consumers process information through mental imagery. The findings provide a more comprehensive understanding of the antecedents of reliance on WOM and offer new insights and recommendations for management practitioners.
Details
Keywords
Hongming Gao, Hongwei Liu, Weizhen Lin and Chunfeng Chen
Purchase conversion prediction aims to improve user experience and convert visitors into real buyers to drive sales of firms; however, the total conversion rate is low, especially…
Abstract
Purpose
Purchase conversion prediction aims to improve user experience and convert visitors into real buyers to drive sales of firms; however, the total conversion rate is low, especially for e-retailers. To date, little is known about how e-retailers can scientifically detect users' intents within a purchase conversion funnel during their ongoing sessions and strategically optimize real-time marketing tactics corresponding to dynamic intent states. This study mainly aims to detect a real-time state of the conversion funnel based on graph theory, which refers to a five-class classification problem in the overt real-time choice decisions (RTCDs)—click, tag-to-wishlist, add-to-cart, remove-from-cart and purchase—during an ongoing session.
Design/methodology/approach
The authors propose a novel graph-theoretic framework to detect different states of the conversion funnel by identifying a user's unobserved mindset revealed from their navigation process graph, namely clickstream graph. First, the raw clickstream data are identified into individual sessions based on a 30-min time-out heuristic approach. Then, the authors convert each session into a sequence of temporal item-level clickstream graphs and conduct a temporal graph feature engineering according to the basic, single-, dyadic- and triadic-node and global characteristics. Furthermore, the synthetic minority oversampling technique is adopted to address with the problem of classifying imbalanced data. Finally, the authors train and test the proposed approach with several popular artificial intelligence algorithms.
Findings
The graph-theoretic approach validates that users' latent intent states within the conversion funnel can be interpreted as time-varying natures of their online graph footprints. In particular, the experimental results indicate that the graph-theoretic feature-oriented models achieve a substantial improvement of over 27% in line with the macro-average and micro-average area under the precision-recall curve, as compared to the conventional ones. In addition, the top five informative graph features for RTCDs are found to be Transitivity, Edge, Node, Degree and Reciprocity. In view of interpretability, the basic, single-, dyadic- and triadic-node and global characteristics of clickstream graphs have their specific advantages.
Practical implications
The findings suggest that the temporal graph-theoretic approach can form an efficient and powerful AI-based real-time intent detecting decision-support system. Different levels of graph features have their specific interpretability on RTCDs from the perspectives of consumer behavior and psychology, which provides a theoretical basis for the design of computer information systems and the optimization of the ongoing session intervention or recommendation in e-commerce.
Originality/value
To the best of the authors' knowledge, this is the first study to apply clickstream graphs and real-time decision choices in conversion prediction and detection. Most studies have only meditated on a binary classification problem, while this study applies a graph-theoretic approach in a five-class classification problem. In addition, this study constructs temporal item-level graphs to represent the original structure of clickstream session data based on graph theory. The time-varying characteristics of the proposed approach enhance the performance of purchase conversion detection during an ongoing session.
Details
Keywords
Chunfeng Chen and Depeng Zhang
This research aims to investigate the effects of innovation types (exploratory innovation vs. exploitative innovation) on users' psychological perceptions (perceived…
Abstract
Purpose
This research aims to investigate the effects of innovation types (exploratory innovation vs. exploitative innovation) on users' psychological perceptions (perceived self-improvement and prosocial impact) and continuous knowledge sharing intention and the moderating effects of monetary incentives.
Design/methodology/approach
The research model was developed based on the self-determination theory. A two-study approach involving an online survey (n = 338) and an online experiment (n = 160) was employed to collect quantitative data. Structural equation modeling and variance analysis were adapted to analyze the data.
Findings
The results show that exploratory innovation leads to higher perceived self-improvement among users than exploitative innovation, whereas exploitative innovation leads to higher perceived prosocial impact than exploratory innovation. The perceived self-improvement and perceived prosocial impact positively affects users' continuous knowledge sharing intention. Monetary incentives moderate the relationships among perceived self-improvement, perceived prosocial impact and continuous knowledge sharing intention.
Originality/value
This research highlights the role of users' experience of initial participation in forming continuous knowledge sharing intentions and also reveals the effectiveness of monetary incentives in different types of innovation activities. The findings provide a more comprehensive understanding of the antecedents of users' continuous knowledge sharing behavior, offering new insights and recommendations for managerial practitioners.
Details
Keywords
Chunfeng Chen and Depeng Zhang
Negative word-of-mouth has a variety of negative effects on companies. Thus, how consumers process and evaluate negative word-of-mouth is an important issue for companies. This…
Abstract
Purpose
Negative word-of-mouth has a variety of negative effects on companies. Thus, how consumers process and evaluate negative word-of-mouth is an important issue for companies. This research aims to investigate the effect of emotional intensity of negative word-of-mouth on consumers' perceived helpfulness.
Design/methodology/approach
The research model was developed based on attribution theory. A four-study approach involving two field experiments and two online experiments was employed to examine the proposed hypotheses.
Findings
The results show that the emotional intensity of negative word-of-mouth negatively affects altruistic motive attributions, while altruistic motive attributions positively affect perceived helpfulness and plays a mediating role in the relationship between the emotional intensity of negative word-of-mouth and perceived helpfulness. Consumers' self-construal moderates the effects of emotional intensity of negative word-of-mouth on altruistic motive attributions and perceived helpfulness, with the negative effects of emotional intensity of negative word-of-mouth on altruistic motive attributions and perceived helpfulness being weaker for consumers with high interdependent self-construal than for those with high independent self-construal.
Originality/value
The findings not only have a significant theoretical contribution, deepening the understanding of the effects of negative word-of-mouth but also have useful implications for practitioners to improve the management of negative word-of-mouth.
Details
Keywords
Jun Wen, Carol Chunfeng Wang, Edmund Goh, Zhaohui Su and Tianyu Ying
This paper explores the role of traditional Chinese medicine (TCM) as a tourism recovery drawcard to boost China's inbound tourism after COVID-19.
Abstract
Purpose
This paper explores the role of traditional Chinese medicine (TCM) as a tourism recovery drawcard to boost China's inbound tourism after COVID-19.
Design/methodology/approach
This paper employed a mixed method involving a cross-disciplinary literature review along with reflections from experts in TCM and health communication to inform tourism management. Specifically, this paper examines TCM and its potential benefits as a medical tourism drawcard to combat COVID-19. The selected literature focusses on the image and merits of TCM to frame how this medical philosophy can be used to position China as a tourist destination. Reflections on the use of TCM as a tourism marketing tool can guide promotional strategies from the Chinese government and destination managers during and after COVID-19.
Findings
The Chinese government, the tourism industry (e.g. destination managers), the media and tourists must focus on three aspects of the role of TCM: to provide medical benefits to travellers amid COVID-19 and beyond, elevate China as a destination for global medical tourists and be leveraged as a tool for economic recovery.
Practical implications
The paper builds a tourism recovery framework for stakeholders to adopt tailored TCM communication strategies to boost its inbound tourism programme.
Originality/value
This paper is the first academic paper to review TCM comprehensively and critically in relation to China tourism and post-COVID-19 recovery measures.
Details
Keywords
Zebin Yang, Xi Chen, Xiaodong Sun, Chunfeng Bao and Jiang Lu
The purpose of this paper is to handle the problem of the radial disturbance caused by rotor mass unbalance and load change in a bearingless induction motor (BIM).
Abstract
Purpose
The purpose of this paper is to handle the problem of the radial disturbance caused by rotor mass unbalance and load change in a bearingless induction motor (BIM).
Design/methodology/approach
The active disturbance rejection controller (ADRC) is used to replace the traditional PI controller, and a cubic interpolation method is used to fit the nonlinear function of ADRC, so as to improve the control performance. Meanwhile, a disturbance observer is applied to the suspension system, and the observed disturbance acceleration is compensated to the suspension system in the form of current; thus, the suppression of the rotor radial disturbance is realized.
Findings
The proposed method can effectively suppress the radial disturbance of the rotor, meliorate the suspension performance of the motor and enhance the anti-interference ability of the system. Besides, it has excellent dynamic and static performance.
Originality/value
A radial disturbance control strategy of the BIM based on improved ADRC is proposed is to suppress the radial disturbance of the rotor. The improved ADRC is to enhance the control performance of the system, and the disturbance observer is designed to observe and compensate the disturbance.
Details
Keywords
Wenfeng Yuan, Sifeng Liu and Chaoqing Yuan
The paper attempts to establish a two‐dimension frame to analyze dynamic supplier risks of large‐scale and complex equipment and study the probability distribution of the…
Abstract
Purpose
The paper attempts to establish a two‐dimension frame to analyze dynamic supplier risks of large‐scale and complex equipment and study the probability distribution of the occurring risks.
Design/methodology/approach
Starting from the dynamic and correlated supplier risks of large‐scale and complex equipment, a two‐dimension frame to analyze these risks is established. A maximum entropy model is also built to research the probability distribution of the risks; then, K‐T conditions are proved to solve the model. A real case is also studied in the last part of the paper.
Findings
The results are convincing: in order to analyze the supplier risk dynamically of large‐scale and complex equipment development project, a two‐dimension analysis frame is established and a maximum entropy model is worked out. The case study shows that they are valuable.
Practical implications
The two‐dimension frame gives a new viewpoint for risk management, but also the maximum entropy model supplies a valuable method for risk management.
Originality/value
The paper succeeds in creating a dynamic analysis frame to study risks and building a new method to research the disciplines of the dynamic risks.
Details
Keywords
Chunfeng Chen and Depeng Zhang
The rapid development of live-streaming commerce has increased companies’ marketing effectiveness. While previous studies have explored the effects of its technical features on…
Abstract
Purpose
The rapid development of live-streaming commerce has increased companies’ marketing effectiveness. While previous studies have explored the effects of its technical features on consumers, the effects of marketing-related factors remain unknown. This study aims to investigate the effects of the marketing elements of live-streaming commerce on consumers’ purchase intentions.
Design/methodology/approach
The research model is derived from the Yale model and the benefit–risk framework. To test the study hypotheses, data were collected through a questionnaire survey of 392 live-streaming shoppers and analyzed using SmartPLS.
Findings
The empirical results indicate that broadcaster competence and online crowding increase consumers’ perception of price attractiveness while reducing their perceived uncertainty. Information diagnosticity also reduces consumers’ perceived uncertainty. Furthermore, purchase intention is positively and negatively affected by perceived price attractiveness and perceived uncertainty, respectively. Finally, product scarcity moderates the relationships between broadcaster competence, online crowding, information diagnosticity, perceived price attractiveness and perceived uncertainty.
Originality/value
The study identifies the different marketing elements in live-streaming commerce and their effects on consumers’ value evaluations and purchase intentions. The findings provide comprehensive insights into the antecedents of live-streaming shopping and offer new perceptions and recommendations for practitioners.