Mengyang Gao, Jun Wang and Ou Liu
Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity…
Abstract
Purpose
Given the critical role of user-generated content (UGC) in e-commerce, exploring various aspects of UGC can aid in understanding user purchase intention and commodity recommendation. Therefore, this study investigates the impact of UGC on purchase decisions and proposes new recommendation models based on sentiment analysis, which are verified in Douban, one of the most popular UGC websites in China.
Design/methodology/approach
After verifying the relationship between various factors and product sales, this study proposes two models, collaborative filtering recommendation model based on sentiment (SCF) and hidden factors topics recommendation model based on sentiment (SHFT), by combining traditional collaborative filtering model (CF) and hidden factors topics model (HFT) with sentiment analysis.
Findings
The results indicate that sentiment significantly influences purchase intention. Furthermore, the proposed sentiment-based recommendation models outperform traditional CF and HFT in terms of mean absolute error (MAE) and root mean square error (RMSE). Moreover, the two models yield different outcomes for various product categories, providing actionable insights for organizers to implement more precise recommendation strategies.
Practical implications
The findings of this study advocate the incorporation of UGC sentimental factors into websites to heighten recommendation accuracy. Additionally, different recommendation strategies can be employed for different products types.
Originality/value
This study introduces a novel perspective to the recommendation algorithm field. It not only validates the impact of UGC sentiment on purchase intention but also evaluates the proposed models with real-world data. The study provides valuable insights for managerial decision-making aimed at enhancing recommendation systems.
Details
Keywords
Qiyuan Zhang, Mengyang Wang and Ziyu Zhao
In the pursuit of co-exploration, the strength and brokerage dimensions of dyadic ties create a novelty–action trade-off: tie strength facilitates coordination but constraints…
Abstract
Purpose
In the pursuit of co-exploration, the strength and brokerage dimensions of dyadic ties create a novelty–action trade-off: tie strength facilitates coordination but constraints novelty, while tie brokerage expands knowledge diversity but aggravates coordination difficulty. This study contributes towards a better understanding of this tension by comparing two dimensions of relational ties and examining their contingent values given different environmental factors and exchange characteristics.
Design/methodology/approach
The authors used survey data from 194 matched buyer–supplier dyads in China's high-tech industries and employed hierarchical moderated regression analysis to test the proposed hypotheses.
Findings
The authors find that compared with tie strength, tie brokerage has a stronger positive effect on co-exploration. Moreover, guanxi importance amplifies the effect of tie strength while decreasing the value of tie brokerage. As market uncertainty increases, the role of tie brokerage becomes more salient. Additionally, tie strength becomes less effective when buyer centralization is high, whereas tie brokerage exerts a stronger impact on co-exploration when an exchange is highly formalized.
Originality/value
This study contributes to the supply chain literature by adopting a relational perspective to integrate relational ties into the study of buyer–supplier co-exploration and by elaborating on the different implications of tie strength and tie brokerage in resolving the novelty–action trade-off. Furthermore, it provides a more nuanced understanding of when distinct dimensions of relational ties are effective, by clarifying boundary conditions in terms of environmental factors and exchange characteristics.
Details
Keywords
Jiaxuan Li, Xihong Zhang and Mengyang Wang
This paper aims to explore how two dimensions of trust, calculative trust and benevolent trust, affect supplier opportunism, and further investigates how information technology…
Abstract
Purpose
This paper aims to explore how two dimensions of trust, calculative trust and benevolent trust, affect supplier opportunism, and further investigates how information technology (IT) infrastructure capability moderates the relationship between calculative trust, benevolent trust and local supplier opportunism.
Design/methodology/approach
This study uses ordinary least square regression to test the hypotheses, using survey data from 164 buyer–supplier relationships.
Findings
The findings suggest that both rational and emotional dimensions of trust, calculative trust and benevolent trust, have negative effect on the opportunistic behavior of suppliers. Furthermore, IT infrastructure capability amplifies the inhibitory effect of calculative trust on supplier’s opportunism, while diminishing the effect of benevolent trust on suppressing supplier’s opportunism.
Originality/value
This study investigates the impacts of both rational and emotional dimensions of trust on opportunistic behavior, thereby enhancing the comprehension of the multifaceted nature of trust in interfirm relationships and contributing valuable insights into interorganizational relationship governance. Moreover, this study reveals the double-edged moderating roles of IT infrastructure capability in supply chain relationships, presenting innovative perspectives within the research on exploring the role of IT capability in business-to-business marketing relationships.
Details
Keywords
Mengyang Zhang and Sarah Gibney
The purpose of this paper is to explore the association between experiencing ageism in the workplace and working conditions on perceived job sustainability among current workers…
Abstract
Purpose
The purpose of this paper is to explore the association between experiencing ageism in the workplace and working conditions on perceived job sustainability among current workers aged 40 and over in Europe, within the context of positive and active ageing strategies and programmes.
Design/methodology/approach
Data are from the 6th round of the European Working Conditions Survey (n=22,229), and the analytical sample contains adults aged 40 and older in 28 European Member States grouped by employment regime: social-democratic regime, corporatist regime, liberal regime, Southern European regime, post-socialist corporatist regime and post-socialist liberal regime. Perceived job sustainability estimated based on whether the respondent thinks (yes/no) that they can do their current job or similar role until the age of 60 or in next five years if the respondent is aged 56 and over. Experience of ageism in the workplace (yes/no) is self-reported. Generalised structural equation modelling was used to control for both individual- and organisational-level influences and to correct for potential endogeneity in estimating the impact of experienced ageism on perceived job sustainability. In addition, employment regimes are included in the model to investigate differences in this relationship by setting.
Findings
Adults who have not experienced ageism are more likely to have positive perceptions of job sustainability, net of other factors and employment regime. Job sustainability is positively associated with age, being male, being in good health status and higher levels of work satisfaction.
Research limitations/implications
The main limitation of this study is that data are cross-sectional, and time variant factors and individual fixed characteristics are excluded from the estimation. The results are influenced by the self-reported data about experienced ageism and evaluation of workplace environment, which may lead to potential endogeneity caused by unobservable personal characteristics such as personality type.
Originality/value
Although the average reported prevalence of ageism in the workplace is 3.4 per cent across the 28 European Union Member States, this study shows that ageism imposes significant negative influence on current workers. This study has highlighted the interrelationship between ageism, workplace satisfaction and job sustainability in this comparative setting. Efforts to reduce ageism in the workplace are likely to lead to improved working conditions and job sustainability.
Details
Keywords
Fengwei Jing, Mengyang Zhang, Jie Li, Guozheng Xu and Jing Wang
Coil shape quality is the external representation of strip product quality, and it is also a direct reflection of strip production process level. This paper aims to predict the…
Abstract
Purpose
Coil shape quality is the external representation of strip product quality, and it is also a direct reflection of strip production process level. This paper aims to predict the coil shape results in advance based on the real-time data through the designed algorithm.
Design/methodology/approach
Aiming at the strip production scale and coil shape application requirements, this paper proposes a strip coil shape defects prediction algorithm based on Siamese semi-supervised denoising auto-encoder (DAE)-convolutional neural networks. The prediction algorithm first reconstructs the information eigenvectors using DAE, then combines the convolutional neural networks and skip connection to further process the eigenvectors and finally compares the eigenvectors with the full connect neural network and predicts the strip coil shape condition.
Findings
The performance of the model is further verified by using the coil shape data of a steel mill, and the results show that the overall prediction accuracy, recall rate and F-measure of the model are significantly better than other commonly used classification models, with each index exceeding 88%. In addition, the prediction results of the model for different steel grades strip coil shape are also very stable, and the model has strong generalization ability.
Originality/value
This research provides technical support for the adjustment and optimization of strip coil shape process based on the data-driven level, which helps to improve the production quality and intelligence level of hot strip continuous rolling.
Details
Keywords
Lijuan Shi, Zuoning Jia, Huize Sun, Mingshu Tian and Liquan Chen
This paper aims to study the affecting factors on bird nesting on electronic railway catenary lines and the impact of bird nesting events on railway operation.
Abstract
Purpose
This paper aims to study the affecting factors on bird nesting on electronic railway catenary lines and the impact of bird nesting events on railway operation.
Design/methodology/approach
First, with one year’s bird nest events in the form of unstructured natural language collected from Shanghai Railway Bureau, the records were structured with the help of python software tool. Second, the method of root cause analysis (RCA) was used to identify all the possible influencing factors which are inclined to affect the probability of bird nesting. Third, the possible factors then were classified into two categories to meet subsequent analysis separately, category one was outside factors (i.e. geographic conditions related factors), the other was inside factors (i.e. railway related factors).
Findings
It was observed that factors of city population, geographic position affect nesting observably. Then it was demonstrated that both location and nesting on equipment part have no correlation with delay, while railway type had a significant but low correlation with delay.
Originality/value
This paper discloses the principle of impacts of nest events on railway operation.