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1 – 10 of 25Xiaochen Liu, Yukuan Xu, Qiang Ye and Yu Jin
Fierce competition in the crowdfunding market has resulted in high failure rates. Owing to their dedication and efforts, many founders have relaunched failed campaigns as a…
Abstract
Purpose
Fierce competition in the crowdfunding market has resulted in high failure rates. Owing to their dedication and efforts, many founders have relaunched failed campaigns as a second attempt. Despite the need for a better understanding, the success of campaign relaunches has not been well-researched. To fill this research gap, this study first theorizes how founders’ learning may enhance their competencies and influence investors’ attribution of entrepreneurial failure. The study then empirically documents the extent and conditions under which such learning efforts impact campaign relaunch performance.
Design/methodology/approach
This study examines 5,798 Kickstarter-relaunched campaigns. The founders’ learning efforts are empirically captured by key changes in campaign design that deviate from past business practices. Word movers’ distances and perceptual hashing algorithms (pHash) are used separately to measure differences in campaign textual descriptions and pictorial designs.
Findings
Differences in textual descriptions and pictorial designs during campaign failure–relaunch are positively associated with campaign relaunch success. The impacts are further amplified when the previous failures are more severe.
Originality/value
This study is one of the first to examine the success of a campaign relaunch after an initial failure. This study contributes to a better understanding of founders’ learning in crowdfunding contexts and provides insights into the strategies founders can adopt to reap performance benefits.
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This study assesses how relational factors and buyer-supplier relationship commitment (BSRC) influence supply chain integration (SCI) and firm performance in Bangladesh's apparel…
Abstract
Purpose
This study assesses how relational factors and buyer-supplier relationship commitment (BSRC) influence supply chain integration (SCI) and firm performance in Bangladesh's apparel manufacturing sector. Firm performance includes operational performance and innovation performance.
Design/methodology/approach
Grounded in the social exchange theory, a survey data-based structural equation modeling (SEM) approach is applied. Based on two experts and four executives' opinions and an in-depth literature review, 28 measurement items were identified in the close-ended questionnaire design. Further, 144 valid questionnaires from the manufacturer-supplier dyads in Bangladesh were collected and used for SEM analysis.
Findings
Our study reveals that relational factors positively influence BSRC. BSRC directly impacts SCI, operational, and innovation performance, whereas SCI is significantly related to operational and innovation performance. Besides, SCI mediates the two relationships: BSRC and operational performance; and BSRC and innovation performance.
Originality/value
Our results contribute to the literature and offer a new way to understand relationships that connect relational factors of BSRC, BSRC, and outcomes not only by examining the focal firm but also by examining its dyadic supplier partner separately. Separate assessment in the dyad displays some similar and dissimilar results. Moreover, we suggest practical implications for managers to enhance firm performance by focusing on the significance of linking relational factors, BSRC, and SCI.
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Hani M. Alqahtany and Wadee Ahmed Ghanem Al-Gehlani
The author’s interest in vernacular architecture, over the years, has attracted the author’s attention to three distinctive and similar forms of architecture in faraway regions of…
Abstract
Purpose
The author’s interest in vernacular architecture, over the years, has attracted the author’s attention to three distinctive and similar forms of architecture in faraway regions of the globe. These are; Asir region of Saudi Arabia, The Caucasus including the republic of Georgia, Chechenia, and North Ossetia, and Sichuan region in China. Stone towers dominate the landscape of these remote regions. The similarity of these towers in these far away regions is quite remarkable.
Design/methodology/approach
This paper will introduce these towers in their geographic, social and natural context. Although several studies have been done on these regions, it is the aim of this paper to introduce their architecture in a comparative approach to explore how these remotes corners of the globe with different historical, ethnic and cultural backgrounds developed similar architectural forms in total isolation from each other.
Findings
Architecture is a physical production of different and diverse factors. Geographically, isolated regions with similar natural and social factors, mountainous landscape, tribally-based, agrarian societies, produces similar architectural forms.
Originality/value
This paper is a clear testimony to the human nature and how people think, react and build, under similar conditions. Architecture becomes a manifestation of human oneness, unity, believes and behaviour.
Yuhan Jiao, Shuxin Guo and Qiang Liu
Testing several approaches for implied volatility modeling and forecasting.
Abstract
Purpose
Testing several approaches for implied volatility modeling and forecasting.
Design/methodology/approach
Comparative empirical study with four traded options.
Findings
Non-parametric higher-order spline is better than parametric stochastic volatility inspired (SVI) in China.
Research limitations/implications
Our results imply that even though popular on Wall Street, SVI seems not to be utilized by traders and market-makers in China.
Practical implications
Traders may consider higher-order spline as a better method for implied volatility modeling and forecasting.
Originality/value
Propose to model and forecast implied volatility via the fifth-order spline interpolation as a first; initiates studies of the empirical performance of SVI and the fifth-order spline models in implied volatility modeling and forecasting.
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Qiang Xiao, Liu Yi-Cong, Yue-Peng Zhou, Zhi-Hong Wang, Sui-Xin Fan, Jun-Hu Meng and Junde Guo
Given the current friction and wear challenges faced by automobile parts and bearings, this study aims to identify a novel texture for creating anti-friction and wear-resistant…
Abstract
Purpose
Given the current friction and wear challenges faced by automobile parts and bearings, this study aims to identify a novel texture for creating anti-friction and wear-resistant surfaces. This includes detailing the preparation process with the objective of mitigating friction and wear in working conditions.
Design/methodology/approach
Femtosecond laser technology was used to create a mango-shaped texture on the surface of GCr15 bearing steel. The optimized processing technology of the texture surface was obtained through adjusting the laser scanning speed. The tribological behavior of the laser-textured surface was investigated using a reciprocating tribometer.
Findings
The friction coefficient of the mango-shaped texture surface is 25% lower than that of the conventional surface, this can be attributed to the reduced contact area between the friction ball and the micro-textured surface, leading to stress concentration at the extrusion edge and a larger stress distribution area on the contact part of the ball and disk compared to the conventional surface and the function of the micro-texture in storing wear chips during the sliding process, thereby reducing secondary wear.
Originality/value
The mango-shaped textured surface in this study demonstrates effective solutions for some of the friction and wear issues, offering significant benefits for equipment operation under light load conditions.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0127/
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Qiang Du, Yerong Zhang, Lingyuan Zeng, Yiming Ma and Shasha Li
Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of…
Abstract
Purpose
Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.
Design/methodology/approach
This study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.
Findings
Results show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.
Originality/value
This study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.
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Ning Huang, Qiang Du, Libiao Bai and Qian Chen
In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has…
Abstract
Purpose
In recent decades, infrastructure has continued to develop as an important basis for social development and people's lives. Resource management of these large-scale projects has been immensely concerned because dozens of construction enterprises (CEs) often work together. In this situation, resource collaboration among enterprises has become a key measure to ensure project implementation. Thus, this study aims to propose a systematic multi-agent resource collaborative decision-making optimization model for large projects from a matching perspective.
Design/methodology/approach
The main contribution of this work was an advancement of the current research by: (1) generalizing the resource matching decision-making problem and quantifying the relationship between CEs. (2) Based on the matching domain, the resource input costs and benefits of each enterprise in the associated group were comprehensively analyzed to build the mathematical model, which also incorporated prospect theory to map more realistic decisions. (3) According to the influencing factors of resource decision-making, such as cost, benefit and attitude of decision-makers, determined the optimal resource input in different situations.
Findings
Numerical experiments were used to verify the effectiveness of the multi-agent resource matching decision (MARMD) method in this study. The results indicated that this model could provide guidance for optimal decision-making for each participating enterprise in the resource association group under different situations. And the results showed the psychological preference of decision-makers has an important influence on decision performance.
Research limitations/implications
While the MARMD method has been proposed in this research, MARMD still has many limitations. A more detailed matching relationship between different resource types in CEs is still not fully analyzed, and relevant studies about more accurate parameters of decision-makers’ psychological preferences should be conducted in this area in the future.
Practical implications
Compared with traditional projects, large-scale engineering construction has the characteristics of huge resource consumption and more participants. While decision-makers can determine the matching relationship between related enterprises, this is ambiguous and the wider range will vary with more participants or complex environment. The MARMD method provided in this paper is an effective methodological tool with clearer decision-making positioning and stronger actual operability, which could provide references for large-scale project resource management.
Social implications
Large-scale engineering is complex infrastructure projects that ensure national security, increase economic development, improve people's lives and promote social progress. During the implementation of large-scale projects, CEs realize value-added through resource exchange and integration. Studying the optimal collaborative decision of multi-agent resources from a matching perspective can realize the improvement of resource transformation efficiency and promote the development of large-scale engineering projects.
Originality/value
The current research on engineering resources decision-making lacks a matching relationship, which leads to unclear decision objectives, ambiguous decision processes and poor operability decision methods. To solve these issues, a novel approach was proposed to reveal the decision mechanism of multi-agent resource optimization in large-scale projects. This paper could bring inspiration to the research of large-scale project resource management.
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Zhimin Pan, Yu Yan, Yizhou Huang, Wei Jiang, Gao Cheng Ye and Hong Jun Li
The purpose of this paper is to achieve optimal climbing control of the gas-insulated switchgear (GIS) robot, as the authors know that the GIS inspection robot is a kind of…
Abstract
Purpose
The purpose of this paper is to achieve optimal climbing control of the gas-insulated switchgear (GIS) robot, as the authors know that the GIS inspection robot is a kind of artificial intelligent mobile equipment which auxiliary or even substitute human labor drive on the inner wall of the gas-insulated metal enclosed switchgear. The GIS equipment fault inspection and maintenance can be realized through the robot manipulator on the mobile platform and the camera carried on the fuselage, and it is a kind of intelligent equipment for operation. To realize the inspection and operation of the GIS equipment pipeline without blind spots, the robot is required to be able to travel on any wall inside the pipeline, especially the top of the pipeline and both right and left sides of the pipeline, which requires the flexible climbing of the GIS inspection robot. The robot device has a certain adsorption function to ensure that the robot is fully attached to the wall surface. At the same time, the robot manipulator can be used for collision-free obstacle avoidance operation planning in the narrow operation space inside the GIS equipment.
Design/methodology/approach
The above two technologies are the key that the robot completes the GIS equipment inspections. Based on this, this paper focuses on modeling and analysis of the chassis adsorption characteristics for the GIS inspection robot. At the same time, the Denavit Hartenberg (D-H) coordinate model of the robot arm system has been established, and the kinematics forward and inverse solutions of the robot manipulator system have been derived.
Findings
The reachable working space point cloud diagram of the robot manipulator in MATLAB has been obtained based on the kinematics analysis, and the operation trajectory planning of the robot manipulator using the robot toolbox has been obtained. The simulation results show that the robot manipulator system can realize the movement without collision and obstacle avoidance. The space can cover the entire GIS pipeline so as to achieve no blind area operation.
Originality/value
Finally, the GIS inspection robot physical prototype system has been developed through system integration design, and the inspection, maintenance operation experiment has been carried out in the actual GIS equipment. The entire robot system can complete the GIS equipment inspection operation soundly and improve the operation efficiency. The research in this paper has important theoretical significance and practical application value for the optimization design and practical research of the GIS inspection robot system.
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Yongsheng Zhao, Jiaqing Luo, Ying Li, Caixia Zhang and Honglie Ma
The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.
Abstract
Purpose
The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.
Design/methodology/approach
This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.
Findings
The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.
Originality/value
Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/
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Xuemei Wang, Jixiang He, Yue Ma, Hao Wang, Dehong Ma, Dongdong Zhang and Hudie Zhao
The purpose of this study is to evaluate the tannase-assisted extraction of tea stem pigment from waste tea stem, after which the stability of the purified pigment was determined…
Abstract
Purpose
The purpose of this study is to evaluate the tannase-assisted extraction of tea stem pigment from waste tea stem, after which the stability of the purified pigment was determined and analyzed.
Design/methodology/approach
The extracting process was optimized using the response surface methodology (RSM) approach. Material-liquid ratio, temperature and time were chosen as variables and the absorbance as a response. The stability of the tea stem pigment at the different conditions was tested and analyzed.
Findings
The optimized extraction technology was as follows: material-liquid ratio 1:20 g/ml, temperature 50°C and time 60 min. The stability test results showed that tea stem pigment was sensitive to oxidants, but the reducing agents did not affect it. The tea stem pigment was unstable under strong acid and strong alkali and was most stable at pH 6. The light stability was poor. Tea stem pigment would form flocculent precipitation under the action of Fe2+ or Fe3+ and be relatively stable in Cu2+ and Na2+ solutions. The tea stem pigment was relatively stable at 60°C and below.
Originality/value
No comprehensive and systematic study reports have been conducted on the extraction of pigment from discarded tea stem, and researchers have not used statistical analysis to optimize the process of tannase-assisted tea stem pigment extraction using RSM. Additionally, there is a lack of special reports on the systematic study of the stability of pigment extracted from tea stem.
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