Xinchun Wang, Dennis B Arnett and Limin Hou
The purpose of this paper is to develop a better understanding of the process used by organizations to leverage external knowledge. A model of the knowledge leveraging process is…
Abstract
Purpose
The purpose of this paper is to develop a better understanding of the process used by organizations to leverage external knowledge. A model of the knowledge leveraging process is developed, which hypothesizes joint sensemaking is a key antecedent to both explicit and tacit knowledge exchange, a dual role for explicit knowledge exchange (i.e. as an antecedent of both tacit knowledge exchange and absorptive capacity) and absorptive capacity is a key mediator between knowledge exchange (both explicit and tacit) and organizational innovativeness.
Design/methodology/approach
The hypothesized model is tested using survey data gathered from over 230 Chinese companies. The results from the analysis of the hypothesized model are compared to ones from a theory-based rival model. The analyses are performed using partial least squares analysis.
Findings
The results suggest key roles for both joint sensemaking and absorptive capacity in the knowledge exchange process. In addition, our findings provide evidence regarding the interplay between explicit and tacit knowledge exchange and their role in the knowledge leveraging process.
Research limitations/implications
The cross-sectional nature of the study provides limited inferences regarding causality. In addition, organizational innovativeness is measured using self-reported, subjective assessments. However, the results provide valuable insights into the knowledge leveraging process.
Practical implications
The study increases our understanding of how organizations leverage external knowledge to improve organizational innovativeness. In addition, it provides specific guidance for managers interested in leveraging external knowledge.
Originality/value
Knowledge and knowledge management issues are receiving increased attention in the marketing literature. However, due to the complexity involved in transferring and using external knowledge, our understanding of the processes involved is limited. Our study provides some insights regarding how firms leverage external knowledge and therefore should be of interest to both researchers and practitioners.
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Huimin Li, Zhichao Zhao, Yongchao Cao, Limin Su, Jing Zhao and Yafei Zhang
Servitization and research and development (R&D) innovation provide new developmental opportunities for transformation in the construction industry. This study aims to explore the…
Abstract
Purpose
Servitization and research and development (R&D) innovation provide new developmental opportunities for transformation in the construction industry. This study aims to explore the transformative impact of servitization and R&D innovation on the value added of the construction industry, offering new insights into industry transformation and growth.
Design/methodology/approach
This study utilizes panel data from Chinese listed construction companies from 2014 to 2022 to empirically investigate the relationship among servitization, R&D innovation and value added in the construction industry. The data analysis is augmented by incorporating text mining techniques to rigorously investigate the interplay among servitization, R&D innovation and the value added within the construction industry.
Findings
The research findings indicate that the impact of servitization on value added follows a positive U-shaped relationship, while the influence of R&D innovation on value added exhibits an inverted U-shaped relationship. Additionally, innovation investment plays a negative moderating role in the relationship between servitization and value added.
Originality/value
This study reveals a fresh perspective on how construction companies can leverage servitization as a strategic pathway for transformation and competitive advantage. The research also lays a theoretical groundwork for future innovation investment strategies in the construction industry, emphasizing the need for a balanced approach to innovation investments to maximize value added.
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Siyuan Huang, Limin Liu, Xiongjun Fu, Jian Dong, Fuyu Huang and Ping Lang
The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In…
Abstract
Purpose
The purpose of this paper is to summarize the existing point cloud target detection algorithms based on deep learning, and provide reference for researchers in related fields. In recent years, with its outstanding performance in target detection of 2D images, deep learning technology has been applied in light detection and ranging (LiDAR) point cloud data to improve the automation and intelligence level of target detection. However, there are still some difficulties and room for improvement in target detection from the 3D point cloud. In this paper, the vehicle LiDAR target detection method is chosen as the research subject.
Design/methodology/approach
Firstly, the challenges of applying deep learning to point cloud target detection are described; secondly, solutions in relevant research are combed in response to the above challenges. The currently popular target detection methods are classified, among which some are compared with illustrate advantages and disadvantages. Moreover, approaches to improve the accuracy of network target detection are introduced.
Findings
Finally, this paper also summarizes the shortcomings of existing methods and signals the prospective development trend.
Originality/value
This paper introduces some existing point cloud target detection methods based on deep learning, which can be applied to a driverless, digital map, traffic monitoring and other fields, and provides a reference for researchers in related fields.
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Jin Sun, Xiaobo Chen, Xiaoyong Lu and Juntong Xi
The purpose of this paper is to describe a processing system for 3D dress geometry modelling and texture mapping.
Abstract
Purpose
The purpose of this paper is to describe a processing system for 3D dress geometry modelling and texture mapping.
Design/methodology/approach
Since the range image and its corresponding texture from one direction could be acquired by areal 3D scanner simultaneously, the texture can be integrated into the range image exactly. In the geometry modelling stage, the graph‐based algorithm is used for multi‐view registration. In order to enhance its robustness, a method for judging bad pairwise registration is proposed based on the computation of two views' overlapping percentage. In order to enrich its completeness, combined the graph analysis with the metaview method is used to deal with the measurement data for local details. In the texture mapping stage, based on grid search structure, the method of solving the Poisson equation for the colour field that best fits the colour gradients can produce a seamlessly textured surface quickly.
Findings
Results show that the processing system can provide a 3D textured dress geometry model with no seams and low distortion successfully.
Practical implications
The processing system can provide an accurate 3D dress geometry model, which can be used to modify the further design or virtual try.
Originality/value
A 3D dress geometry model with no seams and low distortion provides the fashion designer with not only the visual effects, but also accurate data used for design modification.
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Yijun Hou, Dongdong Wang and Guoqi Dong
The purpose of this paper is to take the early Permian no.6 coal seam in Jungar coalfield of North China as an example, this paper studied the net primary productivity (NPP) level…
Abstract
Purpose
The purpose of this paper is to take the early Permian no.6 coal seam in Jungar coalfield of North China as an example, this paper studied the net primary productivity (NPP) level of the early Permian peatland and its relationship with the atmospheric environment at that time, analyzed the influence of the atmospheric environment, and discussed its control factors.
Design/methodology/approach
First, geophysical logging signals were used for a spectrum analysis to obtain the Milankovitch cycle parameters in the no. 6 coal seam, including the eccentricity (95 ka); obliquity (35.6 ka); and precession (21.2 ka). These were then used to calculate the accumulation rate of the residual carbon in the no. 6 coal seam, which was determined to be between 49.44 and 50.57 gC/(m2 · a). The carbon loss could be calculated according to the density and residual carbon content of the no. 6 coal seam. Then, the total carbon accumulation rate of the peatland was further derived as being between 64.91 and 66.40 gC/(m2 · a). Also, the NPP of the peatland was determined to be between 129.82 and 132.8 gC/(m2 · a).
Finding
The result showed that the NPP of the early Permian peatland area was lower than that of the Holocene at the same latitude, and also lower than that of the later Permian of South China.
Originality/value
This study’s comprehensive analysis indicated that the temperature and humidity conditions, along with the oxygen and carbon dioxide levels in the atmosphere, were the main control factors of the NPP of the early Permian peatland. Also, wildfires were found to play a role.
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Na Yang, Qin Liao, Qing Li, Peng Zhang and Longqin Li
– The purpose of this paper was to find a simple and easy-operated method for filtering eco-friendly corrosion inhibitors.
Abstract
Purpose
The purpose of this paper was to find a simple and easy-operated method for filtering eco-friendly corrosion inhibitors.
Design/methodology/approach
The molecular structures and atomic electronegativities of the four kinds of natural reagents, iota-Carrageenan, sodium alginate, sodium dodecanesulphonate (SDS) and sodium dodecylbenzene sulfonate were calculated by Gaussian and Natural Bond Orbital, and the corrosion inhibition rates were forecasted by the calculated results. Then, the realistic corrosion inhibition efficiency were confirmed by electrochemical impedance spectroscopy and potentiodynamic polarization tests in 3.5 Wt.% sodium chloride corrosive solutions. At the same time, the function of pefloxacin mesylate (PM) was explored in this paper polarization tests in 3.5 Wt.% sodium chloride corrosive solutions.
Findings
Results showed that the order calculated by the chemical software was correct, and the corrosion inhibition of SDS was the best. Optimum addition of PM not only can reduce microbial corrosion but also can improve the corrosion inhibition by spatial cooperation.
Practical implications
This method can be used to filter eco-friendly corrosion inhibitors quickly. PM can be also used to improve the corrosion inhibition rate of corrosion inhibitors.
Originality/value
The present method to filter corrosion inhibitors was time-consuming, which needed lots of experiments to verify the corrosion inhibitive efficiency. The calculated method was simpler than others, which need complicated calculation process.
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Radha S., G. Josemin Bala and Nagabushanam P.
Energy is the major concern in wireless sensor networks (WSNs) for most of the applications. There exist many factors for higher energy consumption in WSNs. The purpose of this…
Abstract
Purpose
Energy is the major concern in wireless sensor networks (WSNs) for most of the applications. There exist many factors for higher energy consumption in WSNs. The purpose of this work is to increase the coverage area maintaining the minimum possible nodes or sensors.
Design/methodology/approach
This paper has proposed multilayer (ML) nodes deployment with distributed MAC (DS-MAC) in which nodes listen time is controlled based on communication of neighbors. Game theory optimization helps in addressing path loss constraints while selecting path toward base stations (BS).
Findings
The simulation is carried out using NS-2.35, and it shows better performance in ML DS-MAC compared to random topology in DS-MAC with same number of BS. The proposed method improves performance of network in terms of energy consumption, network lifetime and better throughput.
Research limitations/implications
Energy consumption is the major problem in WSNs and for which there exist many reasons, and many approaches are being proposed by researchers based on application in which WSN is used. Node mobility, topology, multitier and ML deployment and path loss constraints are some of the concerns in WSNs.
Practical implications
Game theory is used in different situations like countries whose army race, business firms that are competing, animals generally fighting for prey, political parties competing for vote, penalty kicks for the players in football and so on.
Social implications
WSNs find applications in surveillance, monitoring, inspections for wild life, sea life, underground pipes and so on.
Originality/value
Game theory optimization helps in addressing path loss constraints while selecting path toward BS.
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Ibrahim A. Amar, Aeshah Alzarouq, Wajdan Mohammed, Mengfei Zhang and Noarhan Matroed
This study aims to explore the possibility of using magnetic biochar composite (MBCC) derived from Heglig tree bark (HTB) powder (agricultural solid waste) and cobalt ferrite (CoFe…
Abstract
Purpose
This study aims to explore the possibility of using magnetic biochar composite (MBCC) derived from Heglig tree bark (HTB) powder (agricultural solid waste) and cobalt ferrite (CoFe2O4, CFO) for oil spill removal from seawater surface.
Design/methodology/approach
One-pot co-precipitation route was used to synthesize MBCC. The prepared materials were characterized by X-ray diffraction, scanning electron microscopy-energy dispersive X-ray spectroscopy, Fourier transform infrared spectroscopy. The densities of the prepared materials were also estimated. Crude, diesel engine and gasoline engine oils were used as seawater pollutant models. The gravimetric oil removal (GOR) method was used for removing oil spills from seawater using MBCC as a sorbent material.
Findings
The obtained results revealed that the prepared materials (CFO and MBCC) were able to remove the crude oil and its derivatives from the seawater surface. Besides, when the absorbent amount was 0.01 g, the highest GOR values for crude oil (31.96 ± 1.02 g/g) and diesel engine oil (14.83 ± 0.83 g/g) were obtained using MBCC as an absorbent. For gasoline engine oil, the highest GOR (27.84 ± 0.46 g/g) was attained when CFO was used as an absorbent.
Originality/value
Oil spill removal using MBCC derived from cobalt ferrite and HTB. Using tree bark as biomass (eco-friendly, readily available and low-cost) for magnetic biochar preparation also is a promising method for minimizing agricultural solid wastes (e.g. HTB) and obtaining value-added-products.
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Chih-Hsing Sam Liu and Yen-Po Fang
This paper aims to propose a new model and examine how night market entrepreneurs have achieved a competitive advantage in strongly competitive markets.
Abstract
Purpose
This paper aims to propose a new model and examine how night market entrepreneurs have achieved a competitive advantage in strongly competitive markets.
Design/methodology/approach
Two statistics methods, multiple regression analysis and structural equation models (SEM), were used to test the hypotheses for a sample of 346 vendor cases.
Findings
The results indicate that competitive aggressiveness and being proactive are positively related to risk-taking among night market vendors, which, in turn, has a positive effect on innovativeness. Further, the findings also indicate that risk-taking positively influences innovativeness and, in a mediating role, also affects competitive advantages through innovativeness.
Practical implications
Results of this study suggest that if night market entrepreneurs demonstrate innovativeness, positively develop new products and new services and attract customers to buy them, then they will have unique and attractiveness in the night markets, thus giving themselves relative competitive advantage.
Originality/value
This research is the first comprehensive examination of entrepreneurship among night market entrepreneurs to study the competitive advantages of different facets, which may provide a benchmark for future studies.
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The mandatory adoption/convergence of IFRS has increased the information quality of reported earnings in equity markets across the globe. The purpose of the study is to explore…
Abstract
Purpose
The mandatory adoption/convergence of IFRS has increased the information quality of reported earnings in equity markets across the globe. The purpose of the study is to explore whether the mandatory convergence of Indian Accounting Standards (Ind AS) with International Financial Reporting Standards (IFRS) affect the financial reporting quality of listed firms in India.
Design/methodology/approach
The sample includes 355 non-financial publicly listed firms on National Stock Exchange (NSE) of India with 1,065 firm-year observations. The authors use models similar to Jones (1991), and DeFond and Jiambalvo (1994) to investigate value relevance in the period “1st January 2017 to 31st December 2019”. The study uses the quantile regression (QR) analysis to verify our hypothesis.
Findings
The findings suggest that IFRS convergence process adds value to accounting quality of reported earnings in Indian stock market. The authors' QR estimations produce collaborating evidence on the uneven impact of IFRS across quantiles and the financial reporting quality skewed in favour of investors of high-valued firms.
Research limitations/implications
The effects of convergence with IFRS in value relevance of financial statements could be reinforced by considering alternate accrual models and incorporating more accounting measures on an expanded sample of stocks from several global markets.
Practical implications
Presently, convergence of local accounting standards to IFRS in India is only partial. The findings may produce useful insights for regulators and standard setters to further increase the value relevance of financial reports whilst they move towards full convergence.
Originality/value
The study explores the information quality of reported earnings of Indian listed firms in post-IFRS convergence period, which is not properly investigated in the literature. Moreover, the research is unique in terms of applying QR estimations to examine the value relevance of IFRS-converged financial reporting from the emerging market perspective.