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Article
Publication date: 25 November 2019

Ying Sun and Shanyong Wang

The purpose of this paper is to observe consumers’ attitudes toward and intentions to purchase green products on social media and to explore the relationships among social…

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4787

Abstract

Purpose

The purpose of this paper is to observe consumers’ attitudes toward and intentions to purchase green products on social media and to explore the relationships among social media marketing, perceived consumer effectiveness (PCE), product knowledge, subjective norms, perceived behavioral control, price consciousness and attitudes toward and intentions to purchase green products. In addition, this research attempts to further understand these relationships in different consumer groups.

Design/methodology/approach

A questionnaire survey method was used to collect data from consumers in China. The Amos 22.0 software package was used to conduct the data analysis.

Findings

The empirical results suggest that attitude, subjective norms and perceived behavioral control positively affect purchase intentions, while price consciousness negatively affects purchase intentions. Product knowledge positively affects consumers’ attitudes and purchase intentions, and PCE positively affects consumers’ attitudes. As expected, social media marketing positively affects subjective norms, product knowledge and PCE and negatively affects price consciousness. However, there is no significant relationship between PCE and purchase intentions. According to the results of multigroup structural equation modeling analysis, the effects differ significantly among different consumer groups.

Originality/value

This study enriches the research about the factors that influence consumers’ purchases of green products in emerging countries in the social media marketing context.

Details

Asia Pacific Journal of Marketing and Logistics, vol. 32 no. 4
Type: Research Article
ISSN: 1355-5855

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Article
Publication date: 1 November 2021

Ying Sun, Tieshan Li and Shanyong Wang

This research aims to conduct a comprehensive conceptual model and empirical validation of the integration of negative (ego-centric) and positive (altruistic and…

Abstract

Purpose

This research aims to conduct a comprehensive conceptual model and empirical validation of the integration of negative (ego-centric) and positive (altruistic and ego-centric) drivers of green buying based on social dilemma theory and psychological egoism theory.

Design/methodology/approach

Data were collected using a self-administered questionnaire survey and analyzed with hierarchical regression analysis.

Findings

The results indicate that moral obligations, green self-identity, environmental concern and social pressure are positively related to green purchase intention, while perceived cost of green purchasing and price sensitivity are negatively. Meanwhile, social pressure positively moderates the relationship between price sensitivity and consumers' green purchasing intention, but negatively moderates the relationship between perceived cost of green purchasing and consumers' green purchasing intention.

Originality/value

First, this study is a comprehensive model of the concept and empirical validation of the integration of negative (ego-centric) and positive (altruistic and ego-centric) drivers of green buying. Specially, this study emphasizes the neglected importance of positive ego-centric factors of green consumer behavior. Second, this study explicitly incorporated the moderating effect of social pressure in the context of China. Since green buying is a social dilemma, the changes in this social dilemma after being affected by social pressure under the Chinese collectivist culture are also worth noting. Third, little is known about what motivates green consumption in emerging economies, and this has been hampered by a lack of cultural knowledge, conceptual richness and behavioral research that critically analyses consumer behavior.

Details

Asia Pacific Journal of Marketing and Logistics, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1355-5855

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Article
Publication date: 6 April 2020

Annan Jiang, Shuai Zheng and Shanyong Wang

This paper aims at the problem of surrounding rock excavation damage zone of tunneling in the rich water region, this paper aims to propose a new seepage-stress-damage…

Abstract

Purpose

This paper aims at the problem of surrounding rock excavation damage zone of tunneling in the rich water region, this paper aims to propose a new seepage-stress-damage coupling model and studied the numerical algorithm. This reflects the characteristics of rock damage evolution, accompanied by plastic flow deformation and multi-field interaction.

Design/methodology/approach

First of all, rock elastoplastic damage constitutive model based on the Drucker–Prager criterion is established, the fully implicit return mapping algorithm is adopted to realize the numerical solution. Second, based on the relation between damage variation and permeability coefficient, the rock stress-seepage-damage model and multi-field coupling solving iterative method are presented. Finally, using the C++ language compiled the corresponding programs and simulated tunnel engineering in the rich water region.

Findings

Results show that difference evolution-based back analysis inversed damage parameters well, at the same time the established coupling model and calculating program have more advantages than general conventional methods. Multiple field coupling effects should be more considered for the design of tunnel support.

Originality/value

The proposed method provides an effective numerical simulation method for the construction of the tunnel and other geotechnical engineering involved underground water problems.

Details

Engineering Computations, vol. 37 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

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Article
Publication date: 14 August 2018

Jing Wang, Shanyong Wang, Yu Wang, Jun Li and Dingtao Zhao

This paper aims to explore the intention of consumers to visit green hotels in China through the theory of planned behavior (TPB) extended by adding perceived consumer…

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2052

Abstract

Purpose

This paper aims to explore the intention of consumers to visit green hotels in China through the theory of planned behavior (TPB) extended by adding perceived consumer effectiveness and environmental concern.

Design/methodology/approach

The TPB model is used as the basic theoretical framework but is extended by adding two critical variables. Data is collected from 324 respondents by using a self-administered questionnaire survey and analyzed with the assistance of structural equation modeling.

Findings

The empirical results show that perceived consumer effectiveness and environmental concern have positive effects on the attitude and the intention of consumers to visit green hotels, and that perceived consumer effectiveness has the largest effect. However, in China, the impact of environmental concern on the intention of consumers to visit green hotels is relatively limited, and the subjective norm has a strong effect. In addition, this research verifies the usefulness of the extended TPB model in understanding the intention of consumers in green hotels industry in China. This is evidenced by a comparison of the initial TPB model with the extended TPB model where the explanatory power has improved from 65 to 68 per cent.

Originality/value

This research contributes to TPB theory by addressing certain gaps in the literature regarding the intention of consumers to visit green hotels in China. Furthermore, considering the limitations of the TPB model, two pro-social variables, namely, perceived consumer effectiveness and environmental concern, are incorporated into the TPB model to better understand the intention of consumers to visit green hotels. Also, this research addresses the gap that studies on the role of perceived consumer effectiveness are limited in the tourism and hospitality management literature. The results indicate that perceived consumer effectiveness has the largest influence on the intention of consumers to visit green hotels.

Details

International Journal of Contemporary Hospitality Management, vol. 30 no. 8
Type: Research Article
ISSN: 0959-6119

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Article
Publication date: 20 November 2017

Shanyong Wang, Jun Li and Dingtao Zhao

The purpose of this paper is to apply an extended technology acceptance model to examine the medical data analyst’s intention to use medical big data processing technique.

Abstract

Purpose

The purpose of this paper is to apply an extended technology acceptance model to examine the medical data analyst’s intention to use medical big data processing technique.

Design/methodology/approach

Questionnaire survey method was used to collect data from 293 medical data analysts and analyzed with the assistance of structural equation modeling.

Findings

The results indicate that the perceived usefulness, social influence and attitude are important to the intention to use medical big data processing technique, and the direct effect of perceived usefulness on intention to use is greater than social influence and attitude. The perceived usefulness is influenced by perceived ease of use. Attitude is influenced by perceived usefulness, and attitude acts as a mediator between perceived usefulness and usage intention. Unexpectedly, attitude is not influenced by perceived ease of use and social influence.

Originality/value

This research examines the medical data analyst’s intention to use medical big data processing technique and provides several implications for using medical big data processing technique.

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Article
Publication date: 20 November 2017

Jun Li, Ming Lu, Guowei Dou and Shanyong Wang

The purpose of this study is to introduce the concept of big data and provide a comprehensive overview to readers to understand big data application framework in libraries.

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2336

Abstract

Purpose

The purpose of this study is to introduce the concept of big data and provide a comprehensive overview to readers to understand big data application framework in libraries.

Design/methodology/approach

The authors first used the text analysis and inductive analysis method to understand the concept of big data, summarize the challenges and opportunities of applying big data in libraries and further propose the big data application framework in libraries. Then they used questionnaire survey method to collect data from librarians to assess the feasibility of applying big data application framework in libraries.

Findings

The challenges of applying big data in libraries mainly include data accuracy, data reduction and compression, data confidentiality and security and big data processing system and technology. The opportunities of applying big data in libraries mainly include enrich the library database, enhance the skills of librarians, promote interlibrary loan service and provide personalized knowledge service. Big data application framework in libraries can be considered from five dimensions: human resource, literature resource, technology support, service innovation and infrastructure construction. Most libraries think that the big data application framework is feasible and tend to apply big data application framework. The main obstacles to prevent them from applying big data application framework is the human resource and information technology level.

Originality/value

This research offers several implications and practical solutions for libraries to apply big data application framework.

Details

Information Discovery and Delivery, vol. 45 no. 4
Type: Research Article
ISSN: 2398-6247

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Article
Publication date: 4 October 2018

Shoufu Lin, Shuochun Cai, Ji Sun, Shanyong Wang and Dingtao Zhao

The purpose of this paper is to identify the drivers of manufacturing transformation and upgrading and examine their influencing paths and effects. The study also…

Abstract

Purpose

The purpose of this paper is to identify the drivers of manufacturing transformation and upgrading and examine their influencing paths and effects. The study also dynamically evaluates and compares the achievements of the manufacturing transformation and upgrading of various economies.

Design/methodology/approach

This paper establishes the mechanism model of manufacturing transformation and upgrading based on the partial least squares approach to structural equation modeling. With the help of a mechanism model, the study carries out empirical analysis using panel data from the G20 for 2005–2015.

Findings

Innovation, measured by innovation input and innovation output, has the largest positive effect on manufacturing transformation and upgrading. Economic development has a negative direct effect, as well as positive indirect effects. Its total effect is positive but small. Economic openness has no significantly direct effect, but has significantly positive indirect effects. Its total effect is significantly positive, but is the smallest among drivers. Developed economies have relatively higher but decreasing achievements, whereas emerging economies have lower but increasing achievements and maintain the catch-up trend toward developed economies.

Originality/value

Few macro empirical studies examine the drivers and achievements of manufacturing transformation and upgrading. A need has arisen for evidence-based research and policies to guide governments in their efforts to promote manufacturing transformation and upgrading. This may be the first macro-level study to empirically analyze the drivers of manufacturing transformation and upgrading, and their influencing paths as well as achievements.

Details

Journal of Manufacturing Technology Management, vol. 30 no. 1
Type: Research Article
ISSN: 1741-038X

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Article
Publication date: 3 August 2015

Liang Wan, Biao Luo, Tieshan Li, Shanyong Wang and Liang Liang

– This paper aims to investigate the relation between technological innovation modes and their impact on eco-efficiency of industrial enterprises in China.

Abstract

Purpose

This paper aims to investigate the relation between technological innovation modes and their impact on eco-efficiency of industrial enterprises in China.

Design/methodology/approach

This paper first constructs a model to evaluate and measure the eco-efficiency of industrial enterprises in China from 2006 to 2010. Second, this paper compares the role of technological innovation modes – specifically, domestic independent innovation, foreign technology import and domestic technology transfer – in improving eco-efficiency of industrial enterprises in the Eastern, Central and Western regions of China by logarithmic regression.

Findings

The study finds that domestic independent innovation has a positive significant influence in improving eco-efficiency of industrial enterprises in the Eastern region; domestic technology transfer has a positive significant role in the Central region; and foreign technology import and domestic technology transfer positively affect the Western region.

Originality/value

This paper is the first to identify the role of technological innovation modes in improving eco-efficiency. The findings can help enterprises in the three regions adopt the most effective technological innovation mode. In addition, the results provide valuable insights into policy development to improve China’s overall eco-efficiency and to balance economic and industrial development among the three regions.

Details

Nankai Business Review International, vol. 6 no. 3
Type: Research Article
ISSN: 2040-8749

Keywords

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