Search results
1 – 10 of 429Cong Zhou, Weili Xia and Taiwen Feng
This study aims to explore how relationship trust and different types of influence strategy (i.e., non-coercive and coercive influence strategy) impact green customer integration…
Abstract
Purpose
This study aims to explore how relationship trust and different types of influence strategy (i.e., non-coercive and coercive influence strategy) impact green customer integration (GCI), while investigating the moderating mechanisms of big data development and social capital.
Design/methodology/approach
Following hierarchical linear regression analysis, the authors examine hypothesized relationships by combining survey data from 206 Chinese manufacturers with secondary data.
Findings
The results show that relationship trust positively affects non-coercive influence strategy, while its impact on coercive influence strategy is insignificant. Non-coercive influence strategy has an inverted U-shaped impact on GCI. Furthermore, big data development flattens the inverted U-shaped relationship between non-coercive influence strategy and GCI. Conversely, social capital steepens the inverted U-shaped relationship between non-coercive influence strategy and GCI.
Practical implications
This study sheds light on managers on how to involve customers in GCI through friendly strategies that favor the involvement of customers and the willingness to develop environmentally friendly initiatives.
Originality/value
Although GCI has received widespread attention, how it can be enhanced remains unclear. These findings provide novel insights into the emerging GCI literature and complement social exchange theory.
Details
Keywords
Yang Liu, Wei Fang, Taiwen Feng and Mengjie Xi
Although blockchain technology holds significant promise in influencing supply chain resilience (SCR), its effectiveness depends on a variety of factors. However, given that…
Abstract
Purpose
Although blockchain technology holds significant promise in influencing supply chain resilience (SCR), its effectiveness depends on a variety of factors. However, given that blockchain adoption in SCR is still in its infancy, there is a lack of empirical research to reveal the critical success factors maximizing its efficacy. This study aims to apply an organizational information processing theory (OIPT) perspective to explore how transformational supply chain leadership (TSCL) can facilitate the deployment and connection of blockchain technology to meet the imperatives of enhancing SCR.
Design/methodology/approach
This study used a two-wave survey method to gather data from 317 Chinese manufacturers to empirically examine the hypothesized relationships.
Findings
The findings suggest that the adoption of blockchain technology enhances both the proactive and reactive dimensions of SCR, and these effects can be realized through the mediating role of TSCL. Furthermore, the positive effect of blockchain technology on TSCL is strengthened in the context of dysfunctional competition.
Practical implications
These findings suggest that companies can only enhance the benefits of disruptive technologies, such as blockchain, by fully integrating them into the operational and supply chain processes.
Originality/value
This research offers novel insights into the specific processes of how blockchain technology can be used to enhance SCR. It also deepens our comprehension of how digital technology can be optimally harnessed within the framework of OIPT, thus providing a contribution to the literature on emerging technologies and SCR.
Details
Keywords
Xuejie Yang, Dongxiao Gu, Honglei Li, Changyong Liang, Hemant K. Jain and Peipei Li
This study aims to investigate the process of developing loyalty in the Chinese mobile health community from the information seeking perspective.
Abstract
Purpose
This study aims to investigate the process of developing loyalty in the Chinese mobile health community from the information seeking perspective.
Design/methodology/approach
A covariance-based structural equation model was developed to explore the mobile health community loyalty development process from information seeking perspective and tested with LISREL 9.30 for the 191 mobile health platform user samples.
Findings
The empirical results demonstrate that the information seeking perspective offers an interesting explanation for the mobile health community loyalty development process. All hypotheses in the proposed research model are supported except the relationship between privacy and trust. The two types of mobile health community loyalty—attitudal loyalty and behavioral loyalty are explained with 58 and 37% variance.
Originality/value
This paper has brought out the information seeking perspective in the loyalty formation process in mobile health community and identified several important constructs for this perspective for the loyalty formation process including information quality, communication with doctors and communication with patients.
Details
Keywords
Baoku Li and Yafeng Nan
This paper aims to reveal the influence of the presentation of online product information (POPI) on consumer attitudes in the context of online buying digital products.
Abstract
Purpose
This paper aims to reveal the influence of the presentation of online product information (POPI) on consumer attitudes in the context of online buying digital products.
Design/methodology/approach
Two main experimental designs are used to collect data. The ANOVA, t-test and Bootstrap methods are applied to check hypotheses.
Findings
Findings of Study 1 indicate that if the POPI is combined with different types of celebrity endorsement (CE) (real vs virtual), the self-brand connection will be changed and further influence consumer attitudes toward digital products. Study 2 verifies the diverse moderating effects of the type of virtual CE. The CRP (central-route presentation) online product information with SVCE (super-realistic-digital virtual CE) can decrease consumer attitudes, while the PRP (peripheral-route presentation) online product information with AVCE (anthropomorphic virtual CE) can enhance consumer attitudes.
Practical implications
E-commerce enterprises should optimize the current layout of POPI by considering diverse matchings between POPI and CE to increase consumer attitudes. Moreover, marketers could make various schemes of POPI considering (virtual) CE and self-brand connection.
Originality/value
Findings contribute to understanding the relationship between POPI and consumer attitudes considering the mediation of self-brand connection and the mediations of virtual/real CE. Additionally, this study bridges the gap between research on virtual CE and business practices.
Details
Keywords
Yongjiang Xue, Wei Wang and Qingzeng Song
The primary objective of this study is to tackle the enduring challenge of preserving feature integrity during the manipulation of geometric data in computer graphics. Our work…
Abstract
Purpose
The primary objective of this study is to tackle the enduring challenge of preserving feature integrity during the manipulation of geometric data in computer graphics. Our work aims to introduce and validate a variational sparse diffusion model that enhances the capability to maintain the definition of sharp features within meshes throughout complex processing tasks such as segmentation and repair.
Design/methodology/approach
We developed a variational sparse diffusion model that integrates a high-order L1 regularization framework with Dirichlet boundary constraints, specifically designed to preserve edge definition. This model employs an innovative vertex updating strategy that optimizes the quality of mesh repairs. We leverage the augmented Lagrangian method to address the computational challenges inherent in this approach, enabling effective management of the trade-off between diffusion strength and feature preservation. Our methodology involves a detailed analysis of segmentation and repair processes, focusing on maintaining the acuity of features on triangulated surfaces.
Findings
Our findings indicate that the proposed variational sparse diffusion model significantly outperforms traditional smooth diffusion methods in preserving sharp features during mesh processing. The model ensures the delineation of clear boundaries in mesh segmentation and achieves high-fidelity restoration of deteriorated meshes in repair tasks. The innovative vertex updating strategy within the model contributes to enhanced mesh quality post-repair. Empirical evaluations demonstrate that our approach maintains the integrity of original, sharp features more effectively, especially in complex geometries with intricate detail.
Originality/value
The originality of this research lies in the novel application of a high-order L1 regularization framework to the field of mesh processing, a method not conventionally applied in this context. The value of our work is in providing a robust solution to the problem of feature degradation during the mesh manipulation process. Our model’s unique vertex updating strategy and the use of the augmented Lagrangian method for optimization are distinctive contributions that enhance the state-of-the-art in geometry processing. The empirical success of our model in preserving features during mesh segmentation and repair presents an advancement in computer graphics, offering practical benefits to both academic research and industry applications.
Details
Keywords
Sami Ullah, Tooba Ahmad, Mohit Kukreti, Abdul Sami and Muhammad Rehan Shaukat
Consumers and businesses are becoming increasingly conscious of sustainable business practices and are often willing to pay a premium for responsibly sourced and manufactured…
Abstract
Purpose
Consumers and businesses are becoming increasingly conscious of sustainable business practices and are often willing to pay a premium for responsibly sourced and manufactured products. Many countries and organizations have implemented regulations and standards for sustainability and companies face penalties or are barred from exporting for not meeting the requirements. Rooted in the resource-based view theory, this study aims to test a moderated mediation model to improve the sustainability performance of exporting firms.
Design/methodology/approach
Textile firms generating more than 25% of export revenues were targeted for this research. The data collected from 245 middle management-level employees were tested for reliability and validity. The structural equation modelling in AMOS 26 was used to test hypotheses.
Findings
Organizational readiness for green innovation (ORGI) has a direct positive effect on sustainability performance. The mediation analysis implies that ORGI translates into sustainability performance through improvement in green innovation performance. The moderating effect of knowledge integration highlights the importance of being prepared internally and actively seeking and incorporating external knowledge to improve green innovation performance.
Originality/value
The findings offer a solid foundation for informed decision-making, policy development and strategies to improve sustainability performance while aligning with the global nature of the textile industry and its inherent challenges. The proposed model and practical implications guide policymakers and managers of exporting firms to foster a culture of green innovation to leverage the effect of their readiness for green innovation on sustainability performance.
Details
Keywords
Salim Ahmed, Khushboo Kumari and Durgeshwer Singh
Petroleum hydrocarbons are naturally occurring flammable fossil fuels used as conventional energy sources. It has carcinogenic, mutagenic properties and is considered a hazardous…
Abstract
Purpose
Petroleum hydrocarbons are naturally occurring flammable fossil fuels used as conventional energy sources. It has carcinogenic, mutagenic properties and is considered a hazardous pollutant. Soil contaminated with petroleum hydrocarbons adversely affects the properties of soil. This paper aim to remove pollutants from the environment is an urgent need of the hour to maintain the proper functioning of soil ecosystems.
Design/methodology/approach
The ability of micro-organisms to degrade petroleum hydrocarbons makes it possible to use these microorganisms to clean the environment from petroleum pollution. For preparing this review, research papers and review articles related to petroleum hydrocarbons degradation by micro-organisms were collected from journals and various search engines.
Findings
Various physical and chemical methods are used for remediation of petroleum hydrocarbons contaminants. However, these methods have several disadvantages. This paper will discuss a novel understanding of petroleum hydrocarbons degradation and how micro-organisms help in petroleum-contaminated soil restoration. Bioremediation is recognized as the most environment-friendly technique for remediation. The research studies demonstrated that bacterial consortium have high biodegradation rate of petroleum hydrocarbons ranging from 83% to 89%.
Social implications
Proper management of petroleum hydrocarbons pollutants from the environment is necessary because of their toxicity effects on human and environmental health.
Originality/value
This paper discussed novel mechanisms adopted by bacteria for biodegradation of petroleum hydrocarbons, aerobic and anaerobic biodegradation pathways, genes and enzymes involved in petroleum hydrocarbons biodegradation.
Details
Keywords
Dongsheng Wang, Xiaohan Sun, Yingchang Jiang, Xueting Chang and Xin Yonglei
Stainless-clad bimetallic steels (SCBS) are widely investigated in some extremely environmental applications areas, such as polar sailing area and tropical oil and gas platforms…
Abstract
Purpose
Stainless-clad bimetallic steels (SCBS) are widely investigated in some extremely environmental applications areas, such as polar sailing area and tropical oil and gas platforms areas, because of their excellent anticorrosion performance and relatively lower production costs. However, the properties of SCBS, including the mechanical strength, weldability and the anticorrosion behavior, have a direct relation with the manufacturing process and can affect their practical applications. This paper aims to review the application and the properties requirements of SCBS in marine environments to promote the application of this new material in more fields.
Design/methodology/approach
In this paper, the manufacturing process, welding and corrosion-resistant properties of SCBS were introduced systematically by reviewing the related literatures, and some results of the authors’ research group were also introduced briefly.
Findings
Different preparation methods, such as rolling composite, casting rolling composite, explosive composite, laser cladding and plasma arc cladding, as well as the process parameters, including the vacuum degree, rolling temperature, rolling reduction ratio, volume ratios of liquid to solid, explosive ratio and the heat treatment, influenced a lot on the properties of the SCBS through changing the interface microstructures. Otherwise, the variations in rolling temperature, pass, reduction and the grain size of clad steel also brought the dissimilarities of the mechanical properties, microhardness, bonding strength and toughness. Another two new processes, clad teeming method and interlayer explosive welding, deserve more attention because of their excellent microstructure control ability. The superior corrosion resistance of SCBS can alleviate the corrosion problem in the marine environment and prolong the service life of the equipment, but the phenomenon of galvanic corrosion should be noted as much as possible. The high dilution rate, welding process specifications and heat treatment can weaken the intergranular corrosion resistance in the weld area.
Originality/value
This paper summarizes the application of SCBS in marine environments and provides an overview and reference for the research of stainless-clad bimetallic steel.
Details
Keywords
Yarong Zhang and Meng Hu
The susceptible-infectious-susceptible (SIS) infectious disease models without spatial heterogeneity have limited applications, and the numerical simulation without considering…
Abstract
Purpose
The susceptible-infectious-susceptible (SIS) infectious disease models without spatial heterogeneity have limited applications, and the numerical simulation without considering models’ global existence and uniqueness of classical solutions might converge to an impractical solution. This paper aims to develop a robust and reliable numerical approach to the SIS epidemic model with spatial heterogeneity, which characterizes the horizontal and vertical transmission of the disease.
Design/methodology/approach
This study used stability analysis methods from nonlinear dynamics to evaluate the stability of SIS epidemic models. Additionally, the authors applied numerical solution methods from diffusion equations and heat conduction equations in fluid mechanics to infectious disease transmission models with spatial heterogeneity, which can guarantee a robustly stable and highly reliable numerical process. The findings revealed that this interdisciplinary approach not only provides a more comprehensive understanding of the propagation patterns of infectious diseases across various spatial environments but also offers new application directions in the fields of fluid mechanics and heat flow. The results of this study are highly significant for developing effective control strategies against infectious diseases while offering new ideas and methods for related fields of research.
Findings
Through theoretical analysis and numerical simulation, the distribution of infected persons in heterogeneous environments is closely related to the location parameters. The finding is suitable for clinical use.
Originality/value
The theoretical analysis of the stability theorem and the threshold dynamics guarantee robust stability and fast convergence of the numerical solution. It opens up a new window for a robust and reliable numerical study.
Details
Keywords
Ziwen Gao, Steven F. Lehrer, Tian Xie and Xinyu Zhang
Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and…
Abstract
Motivated by empirical features that characterize cryptocurrency volatility data, the authors develop a forecasting strategy that can account for both model uncertainty and heteroskedasticity of unknown form. The theoretical investigation establishes the asymptotic optimality of the proposed heteroskedastic model averaging heterogeneous autoregressive (H-MAHAR) estimator under mild conditions. The authors additionally examine the convergence rate of the estimated weights of the proposed H-MAHAR estimator. This analysis sheds new light on the asymptotic properties of the least squares model averaging estimator under alternative complicated data generating processes (DGPs). To examine the performance of the H-MAHAR estimator, the authors conduct an out-of-sample forecasting application involving 22 different cryptocurrency assets. The results emphasize the importance of accounting for both model uncertainty and heteroskedasticity in practice.
Details