Zheng-Xin Wang, Ji-Min Wu, Chao-Jun Zhou and Qin Li
Seasonal fluctuation interference often affects the relational analysis of economic time series. The main purpose of this paper is to propose a new grey relational model for…
Abstract
Purpose
Seasonal fluctuation interference often affects the relational analysis of economic time series. The main purpose of this paper is to propose a new grey relational model for relational analysis of seasonal time series and apply it to identify and eliminate the influence of seasonal fluctuation of retail sales of consumer goods in China.
Design/methodology/approach
First, the whole quarterly time series is divided into four groups by data grouping method. Each group only contains the time series data in the same quarter. Then, the new series of four-quarters are used to establish the grey correlation model and calculate its correlation coefficient. Finally, the correlation degree of factors in each group of data was calculated and sorted to determine its importance.
Findings
The data grouping method can effectively reflect the correlation between time series in different quarters and eliminate the influence of seasonal fluctuation.
Practical implications
In this paper, the main factors influencing the quarterly fluctuations of retail sales of consumer goods in China are explored by using the grouped grey correlation model. The results show that the main factors are different from quarter to quarter: in the first quarter, the main factors are money supply, tax and per capita disposable income of rural residents. In the second quarter are money supply, fiscal expenditure and tax. In the third quarter are money supply, fiscal expenditure and per capita disposable income of rural residents. In the fourth quarter are money supply, fiscal expenditure and tax.
Originality/value
This paper successfully realizes the application of grey relational model in quarterly time series and extends the applicable scope of grey relational model.
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Joonho Moon, Myungkeun Song, Won Seok Lee and Ji Min Shim
This study aims to explore the structural relationship among food quality, usefulness, ease of use, convenience, brand trust and willingness to pay. The technology acceptance…
Abstract
Purpose
This study aims to explore the structural relationship among food quality, usefulness, ease of use, convenience, brand trust and willingness to pay. The technology acceptance model was used as the theoretical foundation of this work.
Design/methodology/approach
Amazon Mechanical Turk was used to recruit survey participants, and 436 valid observations were ultimately used for the analysis. In the data analysis, the structural relationships between variables were explored through structural equation modeling.
Findings
The results of hypothesis testing show that ease of use positively affects the usefulness of the Starbucks mobile application. Usefulness also exerts positive impacts on both brand trust and convenience. Moreover, brand trust is positively associated with food quality. Finally, willingness to pay is positively influenced by both convenience and brand trust.
Originality/value
This study contributes to the literature by not only validating the technology acceptance model using the Starbucks mobile application but also proposing food quality-related attributes in the domain of the café business.
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The aim of this study is to discern the role of digital finance in driving rural industrial integration and revitalization. Specifically, it intends to shed light on how the deep…
Abstract
Purpose
The aim of this study is to discern the role of digital finance in driving rural industrial integration and revitalization. Specifically, it intends to shed light on how the deep development of digital finance can contribute to the optimization and transformation of the rural industrial structure. The research further explores the particular effects of this financial transformation in the central and western regions of China.
Design/methodology/approach
This research studies the influence of digital finance on rural industrial integration across 30 Chinese provinces from 2011 to 2020. Utilizing the entropy weight method, a comprehensive evaluation index system is established to gauge the level of rural industrial integration. A two-way fixed effects model, intermediary effect model, and threshold effect model are employed to decipher the relationship between digital finance and rural industrial integration.
Findings
Findings reveal a positive relationship between digital finance and rural industrial integration. A single threshold feature was identified: beyond a traditional finance development level, the marginal effect of digital finance on rural industrial integration increases. These effects are more noticeable in central and western regions.
Originality/value
Empirical outcomes contribute to policy discourse on rural digital finance, assisting policymakers in crafting effective strategies. Understanding the threshold of traditional finance development provides a new perspective on the potential of digital finance to drive rural industrial integration.
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Ji Min Shim, Won Seok Lee, Joonho Moon and Myungkeun Song
The purpose of this study is to identify the attributes that statistically affect reason intention. The triple bottom line, a theoretical framework of corporate social…
Abstract
Purpose
The purpose of this study is to identify the attributes that statistically affect reason intention. The triple bottom line, a theoretical framework of corporate social responsibility (CSR) consisting of economic, social and environmental subdimensions, is used as the theoretical foundation.
Design/methodology/approach
In this study, price fairness, quarantine and hygiene, and eco-friendliness represent economic, social and environmental CSR, respectively. Amazon Mechanical Turk is used for data collection. The valid number of observations is 474. Structural equation modeling is implemented to test the research hypotheses.
Findings
The results indicate that price fairness, quarantine and hygiene positively affect the reuse intention of coffee shops. However, eco-friendliness appears to be an attribute that does not significantly affect reuse intention.
Originality/value
This study theoretically contributes to the literature by demonstrating the explanatory power of triple bottom line theory for café customer intention.
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Min Ji, Shuhai Liu and Huaping Xiao
The purpose of this paper is to study the tribology behavior of steel–steel contact under the lubrication of water-based drilling mud with different oleic acid-filled…
Abstract
Purpose
The purpose of this paper is to study the tribology behavior of steel–steel contact under the lubrication of water-based drilling mud with different oleic acid-filled microcapsules as lubricant additives.
Design/methodology/approach
A ball-on-disc tribometer was used to evaluate the lubrication properties of the steel–steel contact. The wear tracks of the worn surfaces were observed by a scanning electron microscope.
Findings
Results show that the dependence of both friction and wear on the category of additives shares a consistent pattern. In contrast to oleic acid and empty microcapsules, oleic acid-filled microcapsules achieve the best tribological performance which is related to the lubricant effect of oleic acid and the isolation and rolling abilities of microcapsules.
Practical implications
This study provides a helpful method of encapsulated lubricant additives to prolong lubrication performance for steel–steel contact.
Originality/value
This study has applied microcapsules to improve the tribological properties of drilling mud.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-08-2019-0320/
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Min Ji, Detian Deng and Guangyu Li
Charitable giving in China has moved from being subjected to government attention and public skepticism to receiving government encouragement and public support. The role played…
Abstract
Purpose
Charitable giving in China has moved from being subjected to government attention and public skepticism to receiving government encouragement and public support. The role played by political connections in philanthropy is indisputable, although very few studies have explored their association from the perspective of the country’s first Charity Law of 2016. This study aims to contribute to the ongoing debate about the 2016 Charity Law and offers an understanding of the future trends in corporate charitable giving.
Design/methodology/approach
Using empirical analysis of data collected from listed companies in China, this study analyzes the impact of political connections on corporate charitable giving before and after the 2016 Charity Law. The study adopts three leading theories from previous research into corporate charitable giving and political connections: corporate social responsibility, resource dependence theory and stakeholder theory. A conceptual framework is outlined, and hypotheses are formulated accordingly.
Findings
The results show that political connections have a substantial positive impact on corporate charitable giving, both before and after the implementation of the 2016 Charity Law, which has significantly promoted and increased the amount and proportion of charitable giving. Although the 2016 Charity Law attempted to weaken the political connections of enterprises, the influence of political connections on corporate charitable giving has proved difficult to diminish or eliminate, as charity is dominated by the state.
Originality/value
This study explores the association between political connections and corporate charitable giving from the perspective of China’s Charity Law of 2016.
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Hua Pang, Kaiyang Qin and Min Ji
The primary goal of this article is to review the existing studies and offer clarity regarding the association between social media adoption and youth civic engagement.
Abstract
Purpose
The primary goal of this article is to review the existing studies and offer clarity regarding the association between social media adoption and youth civic engagement.
Design/methodology/approach
This research systematically summarizes and reviews 42 original articles published from 2010 to 2019 with an objective of offering insightful results. Additionally, a theoretical framework was carefully designed by adopting various conceptions from citizen participation and computer-mediated communication research literature.
Findings
The findings demonstrate that social media usage could generally have a positive correlation with civic participation among younger generations. Moreover, the result also highlights that certain functional features of social media uses including using social media for news consumption and expression could significantly predict civic engagement.
Originality/value
Despite the ever-growing importance of social media technologies, investigations on their differential, nonlinear and even inconsistent effects on civic engagement remain theoretically ambiguous and empirically unsubstantiated. The study represents one of the first scholarly attempts to review, summarize and analyze the extant research evidence from the past ten years.
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Abstract
Purpose
As the global emphasis on environmental consciousness intensifies, many corporations claim to be environmentally responsible. However, some merely partake in “greenwashing” – a facade of eco-responsibility. Such deceptive behavior is especially prevalent in Chinese heavy-pollution industries. To counter these deceptive practices, this study aims to use machine learning (ML) techniques to develop predictive models against corporate greenwashing, thus facilitating the sustainable development of corporations.
Design/methodology/approach
This study develops effective predictive models for greenwashing by integrating multifaceted data sets, which include corporate external, organizational and managerial characteristics, and using a range of ML algorithms, namely, linear regression, random forest, K-nearest neighbors, support vector machines and artificial neural network.
Findings
The proposed predictive models register an improvement of over 20% in prediction accuracy compared to the benchmark value, furnishing stakeholders with a robust tool to challenge corporate greenwashing behaviors. Further analysis of feature importance, industry-specific predictions and real-world validation enhances the model’s interpretability and its practical applications across different domains.
Practical implications
This research introduces an innovative ML-based model designed to predict greenwashing activities within Chinese heavy-pollution sectors. It holds potential for application in other emerging economies, serving as a practical tool for both academics and practitioners.
Social implications
The findings offer insights for crafting informed, data-driven policies to curb greenwashing and promote corporate responsibility, transparency and sustainable development.
Originality/value
While prior research mainly concentrated on the factors influencing greenwashing behavior, this study takes a proactive approach. It aims to forecast the extent of corporate greenwashing by using a range of multi-dimensional variables, thus providing enhanced value to stakeholders. To the best of the authors’ knowledge, this is the first study introducing ML-based models designed to predict a company’s level of greenwashing.