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1 – 10 of 985Xuhui Ye, Gongping Wu, Fei Fan, XiangYang Peng and Ke Wang
An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection…
Abstract
Purpose
An accurate detection of overhead ground wire under open surroundings with varying illumination is the premise of reliable line grasping with the off-line arm when the inspection robot cross obstacle automatically. This paper aims to propose an improved approach which is called adaptive homomorphic filter and supervised learning (AHSL) for overhead ground wire detection.
Design/methodology/approach
First, to decrease the influence of the varying illumination caused by the open work environment of the inspection robot, the adaptive homomorphic filter is introduced to compensation the changing illumination. Second, to represent ground wire more effectively and to extract more powerful and discriminative information for building a binary classifier, the global and local features fusion method followed by supervised learning method support vector machine is proposed.
Findings
Experiment results on two self-built testing data sets A and B which contain relative older ground wires and relative newer ground wire and on the field ground wires show that the use of the adaptive homomorphic filter and global and local feature fusion method can improve the detection accuracy of the ground wire effectively. The result of the proposed method lays a solid foundation for inspection robot grasping the ground wire by visual servo.
Originality/value
This method AHSL has achieved 80.8 per cent detection accuracy on data set A which contains relative older ground wires and 85.3 per cent detection accuracy on data set B which contains relative newer ground wires, and the field experiment shows that the robot can detect the ground wire accurately. The performance achieved by proposed method is the state of the art under open environment with varying illumination.
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Qiyuan Chen, Zebing Wei, Xiao Wang, Lingxi Li and Yisheng Lv
The purpose of this paper aims to model interaction relationship of traffic agents for motion prediction, which is critical for autonomous driving. It is obvious that traffic…
Abstract
Purpose
The purpose of this paper aims to model interaction relationship of traffic agents for motion prediction, which is critical for autonomous driving. It is obvious that traffic agents’ trajectories are influenced by physical lane rules and agents’ social interactions.
Design/methodology/approach
In this paper, the authors propose the social relation and physical lane aggregator for multimodal motion prediction, where the social relations of agents are mainly captured with graph convolutional networks and self-attention mechanism and then fused with the physical lane via the self-attention mechanism.
Findings
The proposed methods are evaluated on the Waymo Open Motion Dataset, and the results show the effectiveness of the proposed two feature aggregation modules for trajectory prediction.
Originality/value
This paper proposes a new design method to extract traffic interactions, and the attention mechanism is used in each part of the model to extract and fuse different relational features, which is different from other methods and improves the accuracy of the LSTM-based trajectory prediction method.
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Marta Postula, Krzysztof Kluza, Magdalena Zioło and Katarzyna Radecka-Moroz
Environmental degradation resulting from human activities may adversely affect human health in multiple ways. Until now, policies aimed at mitigating environmental problems such…
Abstract
Purpose
Environmental degradation resulting from human activities may adversely affect human health in multiple ways. Until now, policies aimed at mitigating environmental problems such as climate change, environmental pollution and damage to biodiversity have failed to clearly identify and drive the potential benefits of these policies on health. The conducted study assesses and demonstrates how specific environmental policies and instruments influence perceived human health in order to ensure input for a data-driven decision process.
Design/methodology/approach
The study was conducted for the 2004–2020 period in European Union (EU) countries with the use of dynamic panel data modeling. Verification of specific policies' impact on dependent variables allows to indicate this their effectiveness and importance. As a result of the computed dynamic panel data models, it has been confirmed that a number of significant and meaningful relationships between the self-perceived health index and environmental variables can be identified.
Findings
There is a strong positive impact of environmental taxation on the health index, and the strength of this relationship causes effects to be observed in the very short term, even the following year. In addition, the development of renewable energy sources (RES) and the elimination of fossil fuels from the energy mix exert positive, although milder, effects on health. The reduction of ammonia emissions from agriculture and reducing noise pollution are other health-supporting factors that have been shown to be statistically valid. Results allow to identify the most efficient policies in the analyzed area in order to introduce those with the best results or a mix of such measures.
Originality/value
The results of the authors' research clearly indicate the health benefits of measures primarily aimed at improving environmental factors, such as environmental taxes in general. The authors have also discovered an unexpected negative impact of an increase in the share of energy taxes in total taxes on the health index. The presented study opens several possibilities for further investigation, especially in the context of the rapidly changing geopolitical environment and global efforts to respond to environmental and health challenges. The authors believe that the outcome of the authors' study may provide new arguments to policymakers pursuing solutions that are not always easily acceptable by the public.
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Stephen Gong, Liwei Shan and Li Yu
To examine whether and how the different levels of regional economic incentives would have an effect on underwriters' market share in general.
Abstract
Purpose
To examine whether and how the different levels of regional economic incentives would have an effect on underwriters' market share in general.
Design/methodology/approach
Drawing on Chinese IPO firms during the period 2006-2016, this study examines the impact of different levels of regional economic incentives on underwriters' market share.
Findings
The authors find that regional economic incentives have a positive impact on underwriters' market share and that local economic incentives have a significantly stronger impact than central economic incentives. Furthermore, the authors find that IPO firms with underwriters driven by regional economic incentives experience worse post-IPO performance than firms with underwriters driven by central economic incentives, which do not experience a significant decline in post-IPO performance.
Originality/value
Taken together, the authors’ findings are consistent with the notion that performance assessment motivates officials at various levels of government to bring companies in their jurisdiction to the IPO market prematurely. In addition, the results indicate that central economic incentives play a significant role in driving China's macroeconomic development and market-oriented system reforms. As such, they are one of the major driving forces behind China's market-oriented system reforms.
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Juan A. Marin-Garcia, Jose A.D. Machuca and Rafaela Alfalla-Luque
To determine how to best deploy the Triple-A supply chain (SC) capabilities (AAA-agility, adaptability and alignment) to improve competitive advantage (CA) by identifying the…
Abstract
Purpose
To determine how to best deploy the Triple-A supply chain (SC) capabilities (AAA-agility, adaptability and alignment) to improve competitive advantage (CA) by identifying the Triple-A SC model with the highest CA predictive capability.
Design/methodology/approach
Assessment of in-sample and out-of-sample predictive capacity of Triple-A-CA models (considering AAA as individual constructs) to find which has the highest CA predictive capacity. BIC, BIC-Akaike weights and PLSpredict are used in a multi-country, multi-informant, multi-sector 304 plant sample.
Findings
Greater direct relationship model (DRM) in-sample and out-of-sample CA predictive capacity suggests DRM's greater likelihood of achieving a higher CA predictive capacity than mediated relationship model (MRM). So, DRM can be considered a benchmark for research/practice and the Triple-A SC capabilities as independent levers of performance/CA.
Research limitations/implications
DRM emerges as a reference for analysing how to trigger the three Triple-A SC levers for better performance/CA predictive capacity. Therefore, MRM proposals should be compared to DRM to determine whether their performance is significantly better considering the study's aim.
Practical implications
Results with our sample justify how managers can suitably deploy the Triple-A SC capabilities to improve CA by implementing AAA as independent levers. Single capability deployment does not require levels to be reached in others.
Originality/value
First research considering Triple-A SC capability deployment to better improve performance/CA focusing on model's predictive capability (essential for decision-making), further highlighting the lack of theory and contrasted models for Lee's Triple-A framework.
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Nannan Xi, Juan Chen, Filipe Gama, Henry Korkeila and Juho Hamari
In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in…
Abstract
Purpose
In recent years, there has been significant interest in adopting XR (extended reality) technologies such as VR (virtual reality) and AR (augmented reality), particularly in retail. However, extending activities through reality-mediation is still mostly believed to offer an inferior experience due to their shortcomings in usability, wearability, graphical fidelity, etc. This study aims to address the research gap by experimentally examining the acceptance of metaverse shopping.
Design/methodology/approach
This study conducts a 2 (VR: with vs. without) × 2 (AR: with vs. without) between-subjects laboratory experiment involving 157 participants in simulated daily shopping environments. This study builds a physical brick-and-mortar store at the campus and stocked it with approximately 600 products with accompanying product information and pricing. The XR devices and a 3D laser scanner were used in constructing the three XR shopping conditions.
Findings
Results indicate that XR can offer an experience comparable to, or even surpassing, traditional shopping in terms of its instrumental and hedonic aspects, regardless of a slightly reduced perception of usability. AR negatively affected perceived ease of use, while VR significantly increased perceived enjoyment. It is surprising that the lower perceived ease of use appeared to be disconnected from the attitude toward metaverse shopping.
Originality/value
This study provides important experimental evidence on the acceptance of XR shopping, and the finding that low perceived ease of use may not always be detrimental adds to the theory of technology adoption as a whole. Additionally, it provides an important reference point for future randomized controlled studies exploring the effects of technology on adoption.
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Lindani Myeza, Marianne Kok, Yvette Lange and Warren Maroun
This study aims to examine how governing bodies demonstrated stakeholder engagement during the time of the COVID-19 crisis in South Africa.
Abstract
Purpose
This study aims to examine how governing bodies demonstrated stakeholder engagement during the time of the COVID-19 crisis in South Africa.
Design/methodology/approach
This study uses a qualitative approach based on semi-structured interviews with 18 participants, comprising of preparers of financial statements, board members and management consultants/advisors. The study also relied on the analysis of articles on corporate webpages and publications produced by professional bodies on the economic, social and environmental impact of COVID-19.
Findings
The results of this study indicated that governing bodies demonstrated stakeholder engagement during times of crisis through transparent reporting, corporate social responsibility initiatives and active stakeholder inclusivity.
Originality/value
This study contributes to the body of research on stakeholder engagement during a crisis and provides evidence of the role stakeholder inclusivity can play in responding to a crisis. The findings will be useful in understanding the importance of stakeholder engagement during times of crisis. The study is one of the first, to the best of the authors’ knowledge, to evaluate how stakeholder engagement principles can be followed by governing bodies during a crisis.
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Laura V. Lerman, Guilherme Brittes Benitez, Julian M. Müller, Paulo Renato de Sousa and Alejandro Germán Frank
While it is known that digital transformation facilitates data flow in supply chains, its importance on green supply chain management (GSCM) has not been investigated concisely…
Abstract
Purpose
While it is known that digital transformation facilitates data flow in supply chains, its importance on green supply chain management (GSCM) has not been investigated concisely. This paper aims to expand the theory of digital transformation in GSCM by investigating the interconnections between these concepts and providing an integrative view of a smart green supply chain management (Smart GSCM).
Design/methodology/approach
This adopts a configurational perspective on digital transformation and supply chain management (SCM) to investigate the different dimensions of Smart GSCM and their contribution to green performance. Therefore, this paper analyzes data from 473 manufacturing companies using regression techniques.
Findings
The results show how smart supply chain contributes to green performance through managing green relationships (external GSCM activities) and establishing green operations (internal GSCM activities). Furthermore, this paper finds partial mediating effects for external and internal GSCM activities on green performance. These findings show that smart supply chain (i.e. digital transformation strategy and front-end technologies, supported by several back-end technologies) is directly associated with higher levels of GSCM. It is specifically associated with one of the internal dimensions of green operations, namely, green purchasing activities. Hence, the findings suggest that digital transformation alone is insufficient to achieve green performance, needing a GSCM configuration to mediate this effect.
Practical implications
This study calls attention to how managers should integrate these at least three different perspectives of SCM: digital transformation, external relationships and internal operations to increase green performance.
Originality/value
As the main contribution, this study provides a configurational and holistic understanding of the different dimensions and mechanisms in Smart GSCM.
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Shishu Ding, Jun Xu, Lei Dai and Hao Hu
This paper aims to solve the facility location problem of mobility industry call centers comprehensively, considering both investment efficiency and long-term development…
Abstract
Purpose
This paper aims to solve the facility location problem of mobility industry call centers comprehensively, considering both investment efficiency and long-term development efficiency.
Design/methodology/approach
In this paper, a two-phase decision-making approach within a multi-criteria decision-making (MCDM) framework has been proposed to help select optimal locations among various alternate locations. Both quantitative and qualitative information is collected and processed based on fuzzy set theory and fuzzy analytic hierarchy process. Then the fuzzy technique for order preference by similarity to an ideal solution method is incorporated in the framework to assess the overall feasibility of all alternates.
Findings
A real case of a mobility giant in China is applied to verify the effectiveness of the proposed framework. Sensitivity analysis also proves the robustness of the framework.
Originality/value
This two-phase MCDM framework allows the mobility industry call center location to be selected considering economic, human resource and sustainability elements comprehensively. The framework proposed in this paper might be applicable to other companies in the mobility industry when deciding optimal locations of call centers.
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