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Article
Publication date: 25 February 2025

Jing Wang, Ting-Ting Dong and Ding-Hong Peng

Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial…

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Abstract

Purpose

Green innovation in human-centric smart manufacturing (HSM-GI) has emerged as a new paradigm in innovation management for Industry 5.0. The evaluation analysis method is crucial for measuring the development progress and guiding continual improvements of HSM-GI. Since this process of HSM-GI can be regarded as complex and interactive, a holistic picture is often required to describe the interrelations of its antecedents and consequences. In this respect, this study aims to construct a causality network indicator system and proposes a synergy evaluation method for HSM-GI.

Design/methodology/approach

Firstly, based on the Driver force-State-Response (DSR) causal-effect framework, this study constructs a holistic indicator system to analyze the interactions between environmental and human concerns of HSM-GI. Secondly, owing to the imprecision of human cognition and synergy interaction in the evaluation process, a flexible hesitant fuzzy (HF) superiority-inferiority synergetic evaluation method is presented. This method quantifies the strengths of causal relationships and expresses the incentives and constraints attitudes of humans. Finally, the proposed framework is applied to six HSMs in the electronic technology industry.

Findings

The driving force and state of the HSM-GI system exhibit an upward trend, while the response continues to decline due to changing market demands. The order and synergy degree have shown an increasing trend during 2021–2023, particularly significant for BOE and Haier Smart Home. HSM-GI systems with higher scores mostly have functional coordination and a coherent synergy structure.

Originality/value

This study demonstrates the proposed approach’s applicability and assists policymakers in formulating targeted strategies for green innovation systems.

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 19 February 2025

Nguyen Cong Chinh and Nguyen Nhat Tung

This study aims to introduce an effective optimization algorithm for finding the suitable penetration of renewable distributed generators (RDGs) in the power system. The target of…

3

Abstract

Purpose

This study aims to introduce an effective optimization algorithm for finding the suitable penetration of renewable distributed generators (RDGs) in the power system. The target of this research is to minimize the total costs, including the cost of emissions, the cost of purchasing electricity from the primary grid and the cost of branch power losses.

Design/methodology/approach

Energy valley optimizer (EVO) is applied to solve the optimization problem for determining the integration of photovoltaic units and wind turbine units in the system. This study considers the time variation of load demand and output power of units to improve the quality of the found solution. Simulation results are collected for evaluating the performance of the used methods in the same conditions.

Findings

The results indicated the huge economic and technical benefits from adopting the optimal solution of placement and sizing of RDGs in the power system. Besides, the outstanding efficiency of EVO is also proven through comparison with sunflower optimizer, drawer algorithm, osprey optimization algorithm, genetic algorithm, particle swarm optimization and artificial bee colony algorithm.

Originality/value

The mathematical models for the objective function and the constraints are appropriately described for the optimization problem. A simulation program for applying the optimization algorithms to the above problem is developed in the MATLAB software. The simulation results demonstrated the excellent benefits not only economically but also technically for the hybrid distribution system.

Details

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0332-1649

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Article
Publication date: 9 September 2024

Zeqian Wang, Chengjun Wang, Xiaoming Sun and Tao Feng

The role of inventors' creativity is crucial for technological innovation within enterprises. The mobility of inventors among different enterprises is a primary source for…

100

Abstract

Purpose

The role of inventors' creativity is crucial for technological innovation within enterprises. The mobility of inventors among different enterprises is a primary source for companies to acquire external knowledge. The mechanism of “learning-by-hiring” is widely recognized by companies. Therefore, it is important to determine how to allocate network resources to enhance the creativity of inventors when companies hire mobile inventors.

Design/methodology/approach

The study suggests an analytical framework that analyzes alterations in tie strength and structural holes resulting from the network embeddedness of mobile inventors as well as the effect of the interaction between these two variables on changes in inventor’s creativity after the mobility. In addition, this paper examines the moderating impact of cognitive richness of mobile inventors and cognitive distance between mobile inventors and new employers on the correlation between network embeddedness and creativity.

Findings

This study found that: (1) The increase of tie strength has a significant boost in creativity. (2) Increasing structural holes can significantly improve the creativity of mobile inventors. (3) When both the tie strength and the structural holes increase, the creativity of the mobile inventors significantly increases. (4) It is important to note that when there is a greater cognitive distance, stronger tie strength promotes the creativity of mobile inventors. Additionally, cognitive richness plays a significant role in moderating the relationship between changes in structural holes and the creativity of mobile inventors.

Originality/value

These findings provide theoretical guidance for firms to effectively manage mobile inventors and optimize collaborative networks within organizations.

Details

Management Decision, vol. 63 no. 3
Type: Research Article
ISSN: 0025-1747

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Article
Publication date: 12 January 2024

Pengyun Zhao, Shoufeng Ji and Yuanyuan Ji

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

102

Abstract

Purpose

This paper aims to introduce a novel structure for the physical internet (PI)–enabled sustainable supplier selection and inventory management problem under uncertain environments.

Design/methodology/approach

To address hybrid uncertainty both in the objective function and constraints, a novel interactive hybrid multi-objective optimization solution approach combining Me-based fuzzy possibilistic programming and interval programming approaches is tailored.

Findings

Various numerical experiments are introduced to validate the feasibility of the established model and the proposed solution method.

Originality/value

Due to its interconnectedness, the PI has the opportunity to support firms in addressing sustainability challenges and reducing initial impact. The sustainable supplier selection and inventory management have become critical operational challenges in PI-enabled supply chain problems. This is the first attempt on this issue, which uses the presented novel interactive possibilistic programming method.

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Article
Publication date: 2 January 2025

Fabrizio Erbetta and Graziano Abrate

This paper aims to examine whether the pro-environmental engagement (PEE) of firms in response to the environmental expectations of stakeholders increases firm market power and…

12

Abstract

Purpose

This paper aims to examine whether the pro-environmental engagement (PEE) of firms in response to the environmental expectations of stakeholders increases firm market power and whether the level of stakeholder PEE can counterbalance this effect.

Design/methodology/approach

This study draws on stakeholder theory and the co-production paradigm. The stakeholder perspective provides a theoretical basis for the increase in market power of organizations that improve their PEE, while co-production paradigm provides a theoretical foundation for the negative impact of stakeholder PEE on market power. The empirical evidence is derived from waste management services in Italy. The authors use a stochastic frontier approach to determine firm market power indices in relation to firm and stakeholder PEE.

Findings

The results confirm that market power increases when stakeholder expectations are met, while stakeholder commitment (mainly service recipients) challenges this effect. Furthermore, the findings suggest the existence of a self-reinforcing mechanism, as organizational efforts tend to keep pace with the empowerment of service recipients.

Originality/value

The originality of the study lies in the use of market power as a performance parameter, which has the advantage of being directly related to the acquisition of monopoly rents. In this context, the sustainability efforts of firms have strategic valence, as they allow them to approach a monopolistic condition, while the co-production efforts of service recipients can mitigate this socially undesirable outcome.

Details

Social Responsibility Journal, vol. 21 no. 3
Type: Research Article
ISSN: 1747-1117

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Article
Publication date: 21 February 2025

Yuanzhen Chu, Weipeng Sun, Pengcheng Mou, Qiuyu Lin, Yong Jiang and Shuangxi Wang

Steel structures are easily corroded under coastal atmospheric environment due to high humidity and high saltwater spray. To extend service life of steel structure infrastructure…

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Abstract

Purpose

Steel structures are easily corroded under coastal atmospheric environment due to high humidity and high saltwater spray. To extend service life of steel structure infrastructure, it is necessary to remove rust and apply paint on the steel structure once a year. However, existing wall-climbing sandblasting robots are difficult to work on narrow steel beams and cause serious environmental pollution. The purpose of this study is to design a robot that can effectively remove rust from narrow steel beams and reduce environmental impact to extend the service life of steel structure infrastructure.

Design/methodology/approach

The heavy-duty wall-climbing robot designed in this study can effectively solve the above problems. The robot achieves adjustable magnetic adsorption force of the permanent magnet adsorption through a novel switch design and can work flexibly and stably on narrow steel beams through a worm-like internal and external alternating motion structure. In addition, it is equipped with a sandblasting recovery device to reduce environmental pollution.

Findings

The on-site test results on steel beams show that trust removal level can reach Sa2.0. The recovery rate of sandblasting and rust removal is close to 95%. The robot can carry a 40 kg sandblasting equipment and move at a speed greater than 40 cm/min, indicating that it can efficiently complete the rust removal work of narrow steel structures.

Originality/value

The originality lies in the design of the robot with features such as adjustable magnetic adsorption, special motion structure for narrow beams and a sandblasting recovery device. The value is that it can solve the problems of existing robots in working on narrow steel beams and environmental pollution and effectively extend the service life of steel structure infrastructure by efficiently removing rust.

Details

Industrial Robot: the international journal of robotics research and application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0143-991X

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Article
Publication date: 21 February 2025

Xiaohong Wang, Meilin Zhao and Lei Cheng

Environmental, social and governance (ESG) greenwashing is a form of social responsibility response that appears compliant but is substantively oppositional. As an abnormal social…

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Abstract

Purpose

Environmental, social and governance (ESG) greenwashing is a form of social responsibility response that appears compliant but is substantively oppositional. As an abnormal social behavior, existing research has rarely focused on the deep-seated strategic logic behind ESG greenwashing. Business strategy emerges as the linchpin for companies undertaking a series of decision-making actions. Consequently, this research seeks to provide new insights into the strategic drivers behind corporate greenwashing and the role of institutional investors in mitigating these practices.

Design/methodology/approach

The research utilizes empirical analysis based on data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges from 2010 to 2022. ESG performance data is sourced from the Bloomberg ESG Disclosure Ratings and Thomson Reuters’ Asset4 database. Business strategy is assessed using six key indicators. The study employs institutional theory as the analytical framework, examining the impact of business strategy on ESG greenwashing and investigating the internal mechanisms driving these behaviors.

Findings

The study finds that compared with defender strategies, prospector strategies are more likely to lead to ESG greenwashing behavior. Specifically, aggressive business strategies tend to facilitate corporate ESG greenwashing. Mechanism analysis indicates that, compared to defenders, prospectors induce ESG greenwashing by increasing information asymmetry (reputation effect) and being constrained by financing limitations (profit-seeking effect). From an external governance perspective, this study finds that institutional investor ownership can mitigate the impact of business strategy on ESG greenwashing. Furthermore, additional research confirms that in heavily polluting industries, the positive effect of business strategy on ESG greenwashing is more pronounced, whereas implementing the Environmental Protection Tax Law curtails the impact of business strategy on ESG greenwashing.

Originality/value

This study analyzes the role of business strategy in ESG greenwashing, particularly in the context of emerging economies such as China, contributing uniquely to the literature on corporate decision-making and green management. The research extends the application of institutional theory to the field of corporate environmental strategy and introduces the concepts of reputation and profit-seeking effects, offering fresh perspectives on understanding ESG greenwashing behavior. It also provides empirical evidence of the governance role of institutional investors in addressing managerial opportunism related to ESG greenwashing, enriching the existing theoretical framework. Finally, the study highlights the need to establish stronger institutional and managerial mechanisms to effectively tackle corporate greenwashing, offering valuable insights for future research and practice.

Details

Business Process Management Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-7154

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Article
Publication date: 20 February 2025

Nikolaos Galanos, Evangelos Papoutsis-Kiachagias and Kyriakos Giannakoglou

This paper aims to present a topology optimization (TopO) method for designing heat exchangers (HEx) with two working fluids to be kept apart. The introduction of cut–cells gives…

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Abstract

Purpose

This paper aims to present a topology optimization (TopO) method for designing heat exchangers (HEx) with two working fluids to be kept apart. The introduction of cut–cells gives rise to the cut-cell TopO method, which computes the optimal distribution of an artificial impermeability field and successfully overcomes the weaknesses of the standard density-based TopO (denTopO) by computing the fluid–solid interface (FSI) at each cycle. This allows to accurately solve the flow and conjugate heat transfer (CHT) problem by imposing exact boundary conditions on the computed FSI and results to correct performances computed without the need to re-evaluate the optimized solutions on a body-fitted grid.

Design/methodology/approach

The elements of an artificial impermeability distribution field defined on a background grid act as the design variables and allow topological changes to take place. Post-processing them yields two fields indicating the location of the two flow streams inside the HEx. At each TopO cycle, the FSIs computed based on these two fields are used as the cutting surfaces of the cut-cell grid. On the so-computed grid, the incompressible Navier–Stokes equations, coupled with the Spalart–Allmaras turbulence model, and the temperature equation are solved. The derivatives of the objective and constraint functions with respect to the design variables of TopO are computed by the continuous adjoint method, using consistent discretization schemes devised thanks to the “Think Discrete – Do Continuous” (TDDC) adjoint methodology.

Findings

The effectiveness of the cut-cell–based TopO method for designing HEx is demonstrated in 2D parallel/counter flow and 3D counter flow HEx operating under both laminar and turbulent flow conditions. Compared to the standard denTopO, its ability to compute FSIs along which accurate boundary conditions are imposed, increases the accuracy of the flow solver, which usually leads to optimal, rather than sub-optimal, solutions that truly satisfy the imposed constraints.

Originality/value

This work proposes a new/complete methodology for the TopO of two-fluid systems including CHT that relies on the cut-cell method. This successfully combines aspects from both TopO and Shape Optimization (ShpO) in a single framework thus overcoming the well-known downsides of standard denTopO regarding its accuracy or the need for a follow-up ShpO after TopO. Instead of adding the well-known Brinkman penalization terms into the flow equations, it computes the FSIs at each optimization cycle allowing the solution of the CHT problem on a cut-cell grid.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0961-5539

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Article
Publication date: 18 February 2025

Prashant Premkumar, S.D. Sumod, A. Rajeev and P.N. Ram Kumar

The present study examines the impact of sustainable transitions on the energy and environmental efficiency (EEE) of nations across the developed and developing world. It studies…

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Abstract

Purpose

The present study examines the impact of sustainable transitions on the energy and environmental efficiency (EEE) of nations across the developed and developing world. It studies the temporal shift in the share of renewable sources in energy generation. It also analyses the shift in the efficiency frontier of nations using data envelopment analysis (DEA). Further, it studies the macro-level drivers of EEE in the countries.

Design/methodology/approach

As the first step, we benchmark the EEE of the developed and developing nations using DEA. Subsequently, we look at the influence of institutional quality, human capital, R&D and knowledge systems on EEE, to develop a comprehensive understanding of the macro-level drivers of EEE.

Findings

Our analyses reveal that a country’s institutional quality, human capital and R&D are critical determinants of EEE. The results show that while human capital has a significant positive impact on EEE, R&D expenditure alone has no substantial impact. The findings also suggest that knowledge diffusion disperses best practices across nations and bridges EEE gaps.

Practical implications

Attempts to promote sustainable energy transitions and improve EEE have met with varying levels of success. The results of this study will provide a useful guideline for the governments to achieve the goal of EEE through sustainable energy transitions (SET).

Originality/value

Unlike previous studies, we adopt a multi-factor EEE assessment. We also examine additional influences like the human capital of a nation and its knowledge management system to develop a comprehensive understanding of the macro-level drivers of EEE.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

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Article
Publication date: 20 February 2025

Dijoy Johny, Sidhartha S. Padhi and T.C.E. Cheng

The purpose of this research is to address the challenges of selecting optimal drones for disaster response operations under uncertainties. Traditional static (deterministic…

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Abstract

Purpose

The purpose of this research is to address the challenges of selecting optimal drones for disaster response operations under uncertainties. Traditional static (deterministic) models often fail to capture the complexities and uncertainties of disaster scenarios. This study aims to develop a more resilient and adaptable decision-making framework by integrating the best-worst method (BWM) with stratified multi-criteria decision-making (SMCDM), focusing on various uncertainty scenarios such as weather conditions, communication challenges and navigation and control issues.

Design/methodology/approach

The methodology involves identifying seven essential criteria for drone evaluation, guided by contingency theory. The BWM derives optimal weights for each criterion by comparing the best and worst alternatives. The SMCDM incorporates different uncertainty scenarios into the decision-making process. Sensitivity analysis assesses the robustness of decisions under various criterion weightings and operational scenarios. This integrated approach is demonstrated through a practical application to the Kerala flood scenario.

Findings

The integrated stratified BWM method proves to be highly effective in adapting to different uncertainty scenarios, enabling decision-makers to consistently identify the optimal drone for disaster response. The method’s ability to account for uncertain conditions such as weather, communication challenges and navigation issues ensures that the optimal drone is selected based on the situation at hand.

Research limitations/implications

The methodology fills critical gaps in the literature by offering a comprehensive model that incorporates various scenarios and criteria for optimal drone selection. However, there are certain limitations. The reliance on expert opinions for criterion weightings introduces subjectivity, potentially affecting the generalizability of the results. In addition, the study’s focus on a single case, the Kerala floods, limits its applicability to other geographic contexts. Integrating real-time data analytics into the decision-making process could also enhance the model’s adaptability to evolving conditions and improve its practical relevance.

Practical implications

This research offers a practical, adaptable framework for selecting optimal drones in disaster scenarios. By integrating BWM with SMCDM, the methodology ensures decision-makers can account for real-time uncertainties, such as weather or communication disruptions, to make more informed choices. This leads to better resource allocation and more efficient disaster response operations, ultimately enhancing the speed and effectiveness of relief efforts in various contexts. The method’s ability to adjust based on scenario-specific factors ensures that drones are optimally deployed according to the unique demands of each disaster.

Social implications

By incorporating SMCDM, the proposed methodology assists decision-makers in appropriately choosing drones based on their characteristics crucial for specific scenarios, thereby enhancing the efficiency and effectiveness of relief operations.

Originality/value

This study presents a unique integration of the BWM with SMCDM, creating a dynamic framework for drone selection that addresses the challenges posed by uncertain disaster environments. Unlike traditional methods, this approach allows decision-makers to adjust criteria based on evolving disaster conditions, resulting in more reliable and responsive drone deployment. The method bridges the gap in existing literature by offering a comprehensive tool for disaster response, providing new insights and practical applications for optimizing drone operations in complex, real-world scenarios.

Details

Management Decision, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0025-1747

Keywords

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