Xin Liu, Chenghu Zhang and Jiaqi Wu
The purpose of this study is to investigate the influencing mechanism of consumers' continuous purchase intention toward the subscriber-based knowledge payment platforms (SBKPPs).
Abstract
Purpose
The purpose of this study is to investigate the influencing mechanism of consumers' continuous purchase intention toward the subscriber-based knowledge payment platforms (SBKPPs).
Design/methodology/approach
This study obtained 226 valid samples through questionnaire surveys and used partial least square structural equation modeling (PLS-SEM) and fuzzy-set qualitative comparative analysis (fsQCA) methods to elucidate the complex causal patterns of consumers' continuous purchase intention toward the SBKPPs.
Findings
The findings revealed that perceived utilitarian value, perceived hedonic value and perceived social value directly affected consumers' continuous purchase intention, while content quality and service quality indirectly affected consumers' continuous purchase intention. In addition, this study also demonstrated that all factors must be combined to play a role, and there exist four configurations resulting in consumers' continuous purchase intention toward the SBKPPs.
Research limitations/implications
The results can help researchers and practitioners better understand the causal patterns of consumers' continuous purchase intention toward the SBKPPs.
Originality/value
This study contributes to the knowledge payment literature by investigating consumers' continuous purchase intention toward the SBKPPs. This study also provides practical enlightenment for the SBKPPs' marketing.
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Jiaqi Yin, Shaomin Wu and Virginia Spiegler
This paper models the deterioration process of a multi-component system. Each deterioration process is modelled by the Wiener process. The purposes of this paper are to address…
Abstract
Purpose
This paper models the deterioration process of a multi-component system. Each deterioration process is modelled by the Wiener process. The purposes of this paper are to address these issues and consider the cost process based on the multi-component system.
Design/methodology/approach
Condition-based Maintenance is a method for reducing the probability of system failures as well as the operating cost. Nowadays, a system is composed of multiple components. If the deteriorating process of each component can be monitored and then modelled by a stochastic process, the deteriorating process of the system is a stochastic process. The cost of repairing failures of the components in the system forms a stochastic process as well and is known as a cost process.
Findings
When a linear combination of the processes, which can be the deterioration processes and the cost processes, exceeds a pre-specified threshold, a replacement policy will be carried out to preventively maintain the system.
Originality/value
Under this setting, this paper investigates maintenance policies based on the deterioration process and the cost process. Numerical examples are given to illustrate the optimisation process.
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Yuanyuan Lan, Yuhuan Xia, Shuang Li, Wen Wu, Jiaqi Hui and Hui Deng
The purpose of this study is to explore the relationship between supervisor and coworkers’ workplace incivility and newcomer proactive behaviors. Drawing on conservation of…
Abstract
Purpose
The purpose of this study is to explore the relationship between supervisor and coworkers’ workplace incivility and newcomer proactive behaviors. Drawing on conservation of resources (COR) theory, the authors examined resource depletion as a mediator and newcomer proactive personality, as well as their current organizational tenure as moderators of the relationship between workplace incivility toward newcomers and their proactive behaviors.
Design/methodology/approach
A time-lagged research design was used to test hypotheses with data covering 322 newcomers and their immediate supervisors in two subsidiaries of a large food processing company in China. Regression analysis using the PROCESS macro in SPSS is used to test the hypotheses.
Findings
The results show that workplace incivility toward newcomers is negatively related to their proactive behaviors. This relationship is mediated by resource depletion. Furthermore, newcomers’ proactive personality moderates the relationship between workplace incivility and resource depletion. Moreover, both the direct effect of workplace incivility on resource depletion and its indirect effect on newcomer proactive behaviors are moderated by the combination of newcomer proactive personality and their current organizational tenure.
Originality/value
Drawing on COR theory, a theoretical framework is constructed that specifies the process through which workplace incivility affects proactive behaviors to expand collective understandings of workplace incivility in the newcomer context. Furthermore, the boundary conditions of the underlying process are investigated, which further enhances the contribution of this paper to the extant literature on workplace incivility.
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Jiaqi Liu, Jialong Jiang, Mingwei Lin, Hong Chen and Zeshui Xu
When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are…
Abstract
Purpose
When recommending products to consumers, it is important to be able to accurately predict how consumers will rate them. However, existing collaborative filtering models are difficult to achieve a balance between rating prediction accuracy and complexity. Therefore, the purpose of this paper is to propose an accurate and effective model to predict users’ ratings of products for the accurate recommendation of products to users.
Design/methodology/approach
First, we introduce an attention mechanism that dynamically assigns weights to user preferences, highlighting key interaction information and enhancing the model’s understanding of user behavior. Second, a fold embedding strategy is employed to segment user interaction data, increasing the information density of each subset while reducing the complexity of the attention mechanism. Finally, a masking strategy is integrated to mitigate overfitting by concealing portions of user-item interactions, thereby improving the model’s generalization ability.
Findings
The experimental results demonstrate that the proposed model significantly minimizes prediction error across five real-world datasets. On average, the evaluation metrics root mean square error (RMSE) and mean absolute error (MAE) are reduced by 9.11 and 13.3%, respectively. Additionally, the Friedman test results confirm that these improvements are statistically significant. Consequently, the proposed model more accurately captures the intrinsic correlation between users and products, leading to a substantial reduction in prediction error.
Originality/value
We propose a novel collaborative filtering model to learn the user-item interaction matrix effectively. Additionally, we introduce a fold embedding strategy to reduce the computational resource consumption of the attention mechanism. Finally, we implement a masking strategy to encourage the model to focus on key features and patterns, thereby mitigating overfitting.
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BaoJun Dong, Wei Liu, Fei Wu, JiaQi Zhu, Banthukul Wongpat, Yonggang Zhao, Yueming Fan and TianYi Zhang
The salinity of the oilfield produced water has a significant effect on steel corrosion. The purpose of this paper is to study the influence of salinity on corrosion behavior of…
Abstract
Purpose
The salinity of the oilfield produced water has a significant effect on steel corrosion. The purpose of this paper is to study the influence of salinity on corrosion behavior of X60 steel and it also provides basic for material selection of gas wells with high salinity.
Design/methodology/approach
The weight loss experiment was carried out on steel with high temperature and high pressure autoclave. The surface morphology and composition of corrosion scales were studied by means of scanning electron microscopy, energy dispersive spectroscopy and X-ray diffractometry.
Findings
The results show that as salinity increases, the corrosion rate of X60 steel will gradually experience a rapid decline stage and then a slow decline stage. X60 steel is mainly exhibiting uniform corrosion in the first rapid decline stage and pitting corrosion in the second slow decline stage. The increase in salinity reduces gas solubility, which, in turn, changes the morphology and density of the corrosion scales of X60 steel. At low salinity, loose iron oxides generated on the surface of the steel, which poorly protects the substrate. At high salinity, surface of the steel gradually forms protective films. Chloride ions in the saline solution mainly affect the structure of the corrosion scales and initiate pitting corrosion. The increased chloride ions lead to more pitting pits on the surface of steel. The recrystallization of FeCO3 in pitting pits causes the corrosion scales to bulge.
Originality/value
The investigation determined the critical concentration of pitting corrosion and uniform corrosion of X60 steel, and the new corrosion mechanism model was presented.
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Jiaqi Lu, Shijun Liu, Lizhen Cui, Li Pan and Lei Wu
A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic…
Abstract
Purpose
A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.
Design/methodology/approach
Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing.
Findings
This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.
Originality/value
The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.
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Fengwen Zhi, Zhaoqi Peng, Jiaqi Chen and MengFan Zhao
This paper aims to develop a demand scale from the perspective of scientific data providers and to analyze their demands, offering references for research and practice in…
Abstract
Purpose
This paper aims to develop a demand scale from the perspective of scientific data providers and to analyze their demands, offering references for research and practice in scientific data sharing.
Design/methodology/approach
The initial scale was designed based on a literature review. A total of 479 valid responses from data providers were collected via questionnaires. Exploratory and confirmatory factor analyses were conducted using SPSS21.0 and AMOS23.0, followed by a discussion on practical implications.
Findings
Providers exhibit significant demands in all dimensions, with data security being the most urgent, followed by data management platforms and self-value realization. Additionally, the prioritization of providers’ demands varies according to their intentions to share.
Originality/value
The study developed a scale of providers’ demands in scientific data sharing that comprises 21 items across five dimensions: data security, data management platform, self-value realization, social and benefits return and analyzed the demand degree of providers for the above items. Finally, the paper proposes strategies from stakeholders’ perspectives to meet providers’ demands and facilitate scientific data sharing.
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Rather than focussing on dyadic distributor–supplier relationships, this study aims to examine whether the difference in transaction-specific investments (TSIs) between rival…
Abstract
Purpose
Rather than focussing on dyadic distributor–supplier relationships, this study aims to examine whether the difference in transaction-specific investments (TSIs) between rival suppliers in a supplier–distributor–supplier triad influences whether distributors expropriate or maintain their supplier’s TSIs.
Design/methodology/approach
Drawing on triadic data from 276 questionnaires that address both the supplier–distributor relationship and the rival supplier–distributor relationship, a moderated regression analysis is used to test the hypotheses.
Findings
Five out of six hypotheses are supported by the empirical test. The results show that the supplier’s TSIs increase the distributor’s opportunistic behaviour and reduce cooperation when the distributor perceives that the supplier’s TSIs are lower than those of a rival supplier. In contrast, when the distributor perceives that the supplier’s TSIs are higher than those of a competitor, the supplier’s TSIs do not improve cooperation and can shift the link between the supplier’s TSIs and the distributor’s opportunism from being positive to negative.
Practical implications
The findings have implications for the top managers of supplier firms embedded in distribution networks. This study suggests that the competitor’s TSIs can be regarded as an indicator of the supplier’s relationship with the distributor. By keeping an eye on their competitors’ TSIs, the top managers of suppliers can predict the likelihood of distributors’ opportunistic and cooperative behaviour and make efforts to improve their position by adjusting their own firm’s TSIs. Furthermore, this information can help suppliers decide on their investment strategies and maintain stable and healthy relationships.
Originality/value
This study 1) examines the effect of TSIs using a triadic framework and triadic data and demonstrates that how a distributor responds to a supplier’s TSIs, with either opportunism or cooperation, depends on the relative level of those TSIs in focal and competitive relationships; and 2) reveals the expropriation effects and restraint effects of TSIs by drawing on prospect theory. This finding indicates the dynamics of TSIs in a triadic relationship.
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Wenqian Feng, Xinrong Li, Jiankun Wang, Jiaqi Wen and Hansen Li
This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for…
Abstract
Purpose
This paper reviews the pros and cons of different parametric modeling methods, which can provide a theoretical reference for parametric reconstruction of 3D human body models for virtual fitting.
Design/methodology/approach
In this study, we briefly analyze the mainstream datasets of models of the human body used in the area to provide a foundation for parametric methods of such reconstruction. We then analyze and compare parametric methods of reconstruction based on their use of the following forms of input data: point cloud data, image contours, sizes of features and points representing the joints. Finally, we summarize the advantages and problems of each method as well as the current challenges to the use of parametric modeling in virtual fitting and the opportunities provided by it.
Findings
Considering the aspects of integrity and accurate of representations of the shape and posture of the body, and the efficiency of the calculation of the requisite parameters, the reconstruction method of human body by integrating orthogonal image contour morphological features, multifeature size constraints and joint point positioning can better represent human body shape, posture and personalized feature size and has higher research value.
Originality/value
This article obtains a research thinking for reconstructing a 3D model for virtual fitting that is based on three kinds of data, which is helpful for establishing personalized and high-precision human body models.
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Jun Liu, Yunyun Yu, Fuad Mehraliyev, Sike Hu and Jiaqi Chen
Despite a significant focus on customer evaluation and sentiment analysis, limited attention has been paid to discrete emotional perspective in terms of the emotionality used in…
Abstract
Purpose
Despite a significant focus on customer evaluation and sentiment analysis, limited attention has been paid to discrete emotional perspective in terms of the emotionality used in text. This paper aims to extend the general-sentiment dictionary in Chinese to a restaurant-domain-specific dictionary, visualize spatiotemporal sentiment trends, identify the main discrete emotions that affect customers’ ratings in a restaurant setting and identify constituents of influential emotions.
Design/methodology/approach
A total of 683,610 online restaurant reviews downloaded from Dianping.com were analyzed by a sentiment dictionary optimized by the authors; the main emotions (joy, love, trust, anger, sadness and surprise) that affect online ratings were explored by using multiple linear regression methods. After tracking these sentiment review texts, Latent Dirichlet Allocation (LDA) and LDA models with term frequency-inverse document frequency as weights were used to find the factors that constitute influential emotions.
Findings
The results show that it is viable to optimize or expand sentiment dictionary by word similarity. The findings highlight that love and anger have the highest effect on online ratings. The main factors that constitute consumers’ anger (local characteristics, incorrect food portions and unobtrusive location) and love (comfortable dining atmosphere, obvious local characteristics and complete supporting services) are identified. Different from previous studies, negativity bias is not observed, which poses a question of whether it has to do with Chinese culture.
Practical implications
These findings can help managers monitor the true quality of restaurant service in an area on time. Based on the results, restaurant operators can better decide which aspects they should pay more attention to; platforms can operate better and can have more manageable webpage settings; and consumers can easily capture the quality of restaurants to make better purchase decisions.
Originality/value
This study builds upon the existing general sentiment dictionary in Chinese and, to the best of the authors’ knowledge, is the first to provide a restaurant-domain-specific sentiment dictionary and use it for analysis. It also reveals the constituents of two prominent emotions (love and anger) in the case of restaurant reviews.