Search results

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.

Following hierarchical linear regression analysis, the authors examine hypothesized relationships by combining survey data from 206 Chinese manufacturers with secondary data.

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.

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.

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.

Green practices are essential for sustainability. However, it is challenging due to the socioeconomic and environmental concerns. Similarly, after the induced SDG-12 and SDG-13 by United Nations, the pressure groups forced manufacturers to consider sustainability. Therefore, this research aims to examine the sustainability through multifaceted green functions in manufacturing is examined.

Data were collected from 293 supply chain professionals of manufacturers from a developing economy. Hypotheses were tested through a quantitative method using partial least squares-structural equation modeling with the help of SmartPLS version 4 to validate the measurement model.

The findings revealed that all six direct hypotheses were supported. However, out of four hypotheses of mediation, one was not supported. Besides, a sequential mediation of green supply chain environmental cooperation and green human resource management was supported. The findings illustrated that green supply chain practices positively influence all used variables.

This research provides practical insight to practitioners to implement green practices in their supply chain networks for social, economic and environmental sustainability and compliance with SDG-12 and SDG-13. The sustainability was validated in a higher-order construct (HOC) (formative), including sequential mediation in the model with the support of resource dependency theory. Therefore, this study adds substantial literature to the existing body of knowledge.

This research provides an interdisciplinary framework by adding knowledge to the Resource Dependency Theory to address Sustainable Development Goals-12 (SDGs) and SDG-13. Likewise, this research provides an extension towards the body of knowledge on the issue, which can be used in future research and critical examinations for cleaner and sustainable production. So far, in Pakistan, no research has looked at the function of these integrated variables in the manufacturing industry with a diligent focus on sustainability as it was validated in a higher-order construct (formative) with one sequential mediation, which makes this research unique.

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.

This study used a two-wave survey method to gather data from 317 Chinese manufacturers to empirically examine the hypothesized relationships.

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.

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.

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.

This paper aims to introduce corporate social responsibility into the green supply chain and analyse the impact of different decision makers’ decision-making schemes on carbon emission reduction in the supply chain.

This study uses a two-stage low-carbon supply chain composed of a manufacturer and retailer as the research object. It uses the Stackelberg game model to analyse optimal carbon emission reduction and its influence under different decision-making modes.

Increased consumer green preferences and trust can improve the manufacturing enterprises’ carbon emission reduction rate. The carbon emission reduction rate decreases with increased green innovation costs. When green technology innovation costs remain constant, the greater the market capacity, the higher the carbon emission reduction rate. Market capacity has the most significant impact on the optimal carbon emission reduction rate without considering social responsibility decisions and has the least impact on the optimal carbon emission reduction rate while fully considering the social responsibility decision. To achieve decarbonisation production, the market capacity must be small, and when green innovation costs are high, it is the optimal choice without considering social responsibility. To achieve a higher level of carbon emission reduction, when the market capacity is low and the research and development cost is high or when the market capacity is large, it is the optimal choice.

The results provide scientific policy decisions and management significance for governments and enterprises in low-carbon subsidies and supply chain management. The findings also provide a basis for future theoretical research and enterprise practice.

Based on the attention-based view (ABV), this study examines the mechanism of external pressure and internal managerial interpretation affecting the promotion of green entrepreneurial orientation (GEO) of agricultural enterprises.

Based on data collected from 208 agricultural enterprises in China, the conceptual model was tested by using hierarchical regression.

The results show that managerial interpretation can affect the promotion of GEO. Command and control regulation, market-based regulation and green market pressure are important external pressures that affect the promotion of GEO. In addition, managerial interpretation mediates the relationship between command and control regulation and GEO, market-based regulation and GEO, as well as green market pressure and GEO.

This study proposes a key path for promoting the adoption and implementation of GEO by agricultural enterprises. The research results provide experience for emerging and developing countries to promote the GEO of agricultural enterprises, which is helpful to alleviate the environmental problems caused by the development of agricultural enterprises.

For the first time, this study introduced the ABV into the research of GEO. The research results enrich the theoretical perspective of GEO and expand the research field of the ABV. In addition, this study fills the research gap that existing research has not paid enough attention to the internal driving factors of GEO and opens the black box between the external pressure and GEO.

Improving productivity and efficiency has always been crucial for industrial companies to remain competitive. In recent years, the topic of environmental impact has become increasingly important. Published research indicates that environmental and economic goals can enforce or rival each other. However, few papers have been published that address the interaction and integration of these two goals.

In this paper, we identify both, synergies and trade-offs based on a systematic review incorporating 66 publications issued between 1992 and 2021. We analyze, quantify and cluster examples of conjunctions of ecological and economic measures and thereby develop a framework for the combined improvement of performance and environmental compatibility.

Our findings indicate an increased significance of a combined consideration of these two dimensions of sustainability. We found that cases where enforcing synergies between economic and ecological effects were identified are by far more frequent than reports on trade-offs. For the individual categories, cost savings are uniformly considered as the most important economic aspect while, energy savings appear to be marginally more relevant than waste reduction in terms of environmental aspects.

No previous literature review provides a comparable graphical treatment of synergies and trade-offs between cost savings and ecological effects. For the first time, identified measures were classified in a 3 × 3 table considering type and principle.

Effective green supply chain management (GSCM) has become a potentially valuable tool of securing competitive advantage and improving operational performance (OP) as competition is no longer exists between the firms but within green supply chains. The aim of this empirical study is to determine the link between GSCM practices (GSCMPs) and OP within the manufacturing sector of Bangladesh mediated by perceived competitive advantage (PCA). GSCMPs were divided into three further dimensions: green eco-design (GED), green supply chain partnering (GSCP) and internal green orientation (IGO).

The study selected 376 individuals as respondents who work as the top-level managers and the members of the Board of Directors at different Bangladeshi manufacturing firms through purposive sampling. A partial least square-based structural equation modeling (PLS-SEM) was utilized to identify the relationships between the three dimensions of, GSCMPs, and the single dependent variable, OP.

The study identified that two factors, GED and GSCP, have significant positive relationships with OP. On the other hand, another factor, IGO has a statistically insignificant relationship with OP. Regarding the mediating effects, the study identified that PCA can fully mediate the insignificant relationship between IGO and OP, and partially mediate the significant relationship between GSCP and OP. On the contrary, PCA has no mediating effect on the relationship between GED and OP.

This empirical study is an effort that examined the role of GSCMPs on the OP in the Bangladeshi manufacturing context. It is believed that this empirical investigation will prompt future theoretical studies and empirical experiments to enrich academia. Further, the findings of this study can serve as foundational guidance for policymakers and/or managers studying the formulation and implementation of GSCMP-related policies and strategies.

The present study aims to examine the relationship between green economic incentives (GEIs) and environmental commitment (EC) as drivers of the circular economy (CE) practices in small and medium enterprises (SMEs).

A cross-sectional study of 594 assistant managers and SME managers was used while data were analyzed through Smart PLS.

The results showed that GEIs positively affect the SMEs' EC and the CE practice model. Furthermore, EC is the mediator between GEIs and the three CE practices: internal environmental management, eco-design and corporate asset management and recovery (CAM&R).

The present study provided a basis for understanding the relevance of SMEs' CE practices and designing a strategic plan for its implementation. Also, it provides insight into that collaboration between triple helix (the government, SMEs and the community) is needed in increasing environmental awareness toward sustainability.

This study enhanced the natural resource-based view (NRBV), describing the mechanisms that view GEIs and EC as pollution prevention in CE practice.

This paper aims to examine the impact of carbon emissions (carbon dioxide [CO₂]) reduction on tax evasion behaviour.

This study uses data from 200 countries from 2000 to 2017. The empirical analysis is based on various methodological tools, including ordinary least-squares model, fixed- and random-effects models. In addition, GMM and linear mixed model has been used for robustness purposes.

The results show that carbon emissions reduction significantly affects tax evasion behaviour; when carbon emissions decrease, tax evasion behaviour increases. This indicates that the reduction of CO₂ emissions is linked to significant costs, placing a financial burden on companies and leading them to evade taxes to counterbalance these costs.

This study has important implications, as it highlights that the efforts made by countries to minimize CO₂ emissions are associated with high costs and may lead to increased tax evasion, potentially contributing to countries’ budget deficits. The results provide valuable insights for policymakers and stakeholders to implement effective environmental and fiscal regulations that contribute to a sustainable and eco-friendly future. These regulations can help maintain a balance between improving economic growth and ensuring the protection of the environment.

To the best of the authors’ knowledge, this is the first paper to test the impact of carbon emissions on tax evasion using macro-level data.

The purpose of this study is to investigate the application of non-destructive testing methods in measuring bearing oil film thickness to ensure that bearings are in a normal lubrication state. The oil film thickness is a crucial parameter reflecting the lubrication status of bearings, directly influencing the operational state of bearing transmission systems. However, it is challenging to accurately measure the oil film thickness under traditional disassembly conditions due to factors such as bearing structure and working conditions. Therefore, there is an urgent need for a nondestructive testing method to measure the oil film thickness and its status.

This paper introduces methods for optically, electrically and acoustically measuring the oil film thickness and status of bearings. It discusses the adaptability and measurement accuracy of different bearing oil film measurement methods and the impact of varying measurement conditions on accuracy. In addition, it compares the application scenarios of other techniques and the influence of the environment on detection results.

Ultrasonic measurement stands out due to its widespread adaptability, making it suitable for oil film thickness detection in various states and monitoring continuous changes in oil film thickness. Different methods can be selected depending on the measurement environment to compensate for measurement accuracy and enhance detection effectiveness.

This paper reviews the basic principles and latest applications of optical, electrical and acoustic measurement of oil film thickness and status. It analyzes applicable measurement methods for oil film under different conditions. It discusses the future trends of detection methods, providing possible solutions for bearing oil film thickness detection in complex engineering environments.