With the booming development of computer, optical and sensing technologies and cybernetics, the technical research in unmanned vehicle has been advanced to a new era. This trend…
Abstract
Purpose
With the booming development of computer, optical and sensing technologies and cybernetics, the technical research in unmanned vehicle has been advanced to a new era. This trend arouses great interest in simultaneous localization and mapping (SLAM). Especially, light detection and ranging (Lidar)-based SLAM system has the characteristics of high measuring accuracy and insensitivity to illumination conditions, which has been widely used in industry. However, SLAM has some intractable problems, including degradation under less structured or uncontrived environment. To solve this problem, this paper aims to propose an adaptive scheme with dynamic threshold to mitigate degradation.
Design/methodology/approach
We propose an adaptive strategy with a dynamic module is proposed to overcome degradation of point cloud. Besides, a distortion correction process is presented in the local map to reduce the impact of noise in the iterative optimization process. Our solution ensures adaptability to environmental changes.
Findings
Experimental results on both public data set and field tests demonstrated that the algorithm is robust and self-adaptive, which achieved higher localization accuracy and lower mapping error compared with existing methods.
Originality/value
Unlike other popular algorithms, we do not rely on multi-sensor fusion to improve the localization accuracy. Instead, the pure Lidar-based method with dynamic threshold and distortion correction module indeed improved the accuracy and robustness in localization results.
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Rui Yi, Haojun Wang, Bei Lyu and Qinghua Xia
The study aims to empirically study the effect of venture capital on open innovation of China's enterprises.
Abstract
Purpose
The study aims to empirically study the effect of venture capital on open innovation of China's enterprises.
Design/methodology/approach
This paper selects China's A-share listed companies on the small and medium-sized enterprises (SMEs) board and the Growth Enterprise Market from 2014 to 2018 as research samples to empirically study the effect of venture capital on open innovation of China's enterprises.
Findings
The authors find that venture capital can significantly promote open innovation of enterprises. This promoting effect is more significant when the venture capital institutions have profounder industry experience, higher shareholding ratio and are syndicated. Further research finds that venture capital mainly promotes open innovation through three mechanisms: increasing monetary funds, improving absorptive capacity and strengthening executive incentives, and the effect of venture capital on open innovation is significantly different under the conditions of different regions, industries and property rights.
Originality/value
This paper not only reveals the effect of venture capital on enterprises' open innovation and the specific mechanism, but also provides empirical evidence for emerging economies to build a national innovation ecosystem and make use of capital markets to accelerate innovation strategies.
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The purpose of this paper is to provide a critical historical analysis of the business (mis)behaviors and influencing factors that discourage enduring cooperation between…
Abstract
Purpose
The purpose of this paper is to provide a critical historical analysis of the business (mis)behaviors and influencing factors that discourage enduring cooperation between principals and agents, to introduce strategies that embrace the social values, economic motivation and institutional designs historically adopted to curtail dishonest acts in international business and to inform an improved principal–agent theory that reflects principal–agent reciprocity as shaped by social, political, cultural, economic, strategic and ideological forces
Design/methodology/approach
The critical historical research method is used to analyze Chinese compradors and the foreign companies they served in pre-1949 China.
Findings
Business practitioners can extend orthodox principal–agent theory by scrutinizing the complex interactions between local agents and foreign companies. Instead of agents pursuing their economic interests exclusively, as posited by principal–agent theory, they also may pursue principal-shared interests (as suggested by stewardship theory) because of social norms and cultural values that can affect business-related choices and the social bonds built between principals and agents.
Research limitations/implications
The behaviors of compradors and foreign companies in pre-1949 China suggest international business practices for shaping social bonds between principals and agents and foreign principals’ creative efforts to enhance shared interests with local agents.
Practical implications
Understanding principal–agent theory’s limitations can help international management scholars and practitioners mitigate transaction partners’ dishonest acts.
Originality/value
A critical historical analysis of intermediary businesspeople’s (mis)behavior in pre-1949 (1840–1949) China can inform the generalizability of principal–agent theory and contemporary business strategies for minimizing agents’ dishonest acts.
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Lila Rajabion, Amin Sataei Mokhtari, Mohammad Worya Khordehbinan, Mansoureh Zare and Alireza Hassani
The aim of this paper is to provide a comprehensive and detailed review of the state-of-the-art mechanisms of knowledge sharing (KS) in the supply chain (SC) field, as well as…
Abstract
Purpose
The aim of this paper is to provide a comprehensive and detailed review of the state-of-the-art mechanisms of knowledge sharing (KS) in the supply chain (SC) field, as well as directions for future research. Briefly, this paper tries to offer a systematic and methodical review of the KS mechanisms in the SC to provide a comparative summary of the selected articles, to collect and describe the factors that have the influence on KS and SC, to explore some main challenges in this field and to present the guidelines to face the existing challenges and outlining the key areas where the KS mechanisms in SC can be improved.
Design/methodology/approach
In the current study, a systematic literature review up to 2018 is presented on the supply chain’s mechanisms of KS. The authors identified 21,907 papers, which are reduced to 25 primary studies through the paper-selection process.
Findings
The results showed that the KS in SC helps to increase the success of the organizations, improve employee performance, increase competitive advantage, enhance innovation and improve relationships between supplier and consumer. However, there were some weaknesses, such as staff resistance to share knowledge in the SC because of fear of job loss.
Research limitations/implications
There are several limitations to this study. This study limited the search to Google Scholar. There might be other academic journals where Google does not find their paper and they can offer a more complete picture of the related articles. Finally, non-English publications were omitted from this study. It is possible that the research about the application of KS in SC can also be published in other languages. In addition, more studies need to be carried out using other methodologies such as interviews.
Originality/value
The paper presents a comprehensive structured literature review of the articles’ mechanisms of KS in SC. The paper’s findings can offer insights into future research needs. By providing comparative information and analyzing the current developments in this area, this paper will directly support academics and practicing professionals for better knowing the progress in KS mechanisms.
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Y.L.R. Moorthi and Bijuna C. Mohan
The purpose of this paper is to relate the customer value proposition offered by a bank with its structure of ownership.
Abstract
Purpose
The purpose of this paper is to relate the customer value proposition offered by a bank with its structure of ownership.
Design/methodology/approach
The study adopted a combination of exploratory and descriptive approaches. The attitudes and opinions of bank customers were gauged through a survey. Based on literature, a pool of items was identified to measure the construct of value proposition. It was hypothesized that different types of banks in India are chosen for different benefits offered by them. The relationship between value proposition and its constituent variables functional, emotional and self-expressive benefits was analyzed using multiple regression.
Findings
Results prove that while self-expressive benefits drive the choice of foreign banks (FBs), functional benefits are important for all types of banks.
Research limitations/implications
The research intends to study only the perceptions of customers having an account in Indian public sector banks, private sector banks or FBs.
Practical implications
The study helps to relate the type of bank (public, private or foreign) a customer chooses, with the value proposition it offers. Using this study, banks can configure the value proposition that is appropriate for their target segment.
Originality/value
The paper examines the value proposition offered by the three different types of banks (public, private and foreign) empirically. It links bank choice of the customer to the benefit assortment offered by different types of banks.
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Rui Yuan and Shuwen Liu
The study explores how pre-service teachers engage in Tong Ke Yi Gou (“Same lesson and different design”) as a Chinese version of lesson study in a language teacher education…
Abstract
Purpose
The study explores how pre-service teachers engage in Tong Ke Yi Gou (“Same lesson and different design”) as a Chinese version of lesson study in a language teacher education course.
Design/methodology/approach
Data were collected from multiple sources, including semi-structured interviews, field observations, as well as individual reflections constructed by the participants. The different data sources served to triangulate and enrich each other, shedding light on the student teachers’ learning experiences through lesson study.
Findings
The findings of the study reveal the participants’ enhanced motivation and participation through a process-oriented, collaborative design (i.e. joint lesson planning, micro-teaching, collaborative debrief and individual reflections). In addition, the participants engaged in constant comparisons at multiple levels, which collectively refined and expanded their pedagogical knowledge about language teaching. Such rich and collaborative experiences further contributed to their reflections on and for practice as future language teachers. On the other hand, the study also reveals the emotional challenges faced by some participants due to the competitive atmosphere brought by the comparative element embedded in the process of Tong Ke Yi Gou.
Originality/value
This study incorporates the mode of Tong Ke Yi Gou into a pre-service teacher education course in order to examine how it can benefit student teachers’ learning to teach. The findings highlight the power of “comparison” in promoting student teachers’ reflective and analytical thinking at multiple levels with practical implications for current pre-service teacher education programs.
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The rich primary and secondary data sources for studying historical Chinese marketing theory and practice are discussed. This paper aims to briefly address possible challenges…
Abstract
Purpose
The rich primary and secondary data sources for studying historical Chinese marketing theory and practice are discussed. This paper aims to briefly address possible challenges (and their solutions) to using these sources.
Design/methodology/approach
A bibliographic review is used to analyze historical sources pertaining to Chinese marketing theory and practice.
Findings
Marketing scholars can draw from multiple but neglected and underused Chinese sources to glean important historical data reflecting pre-1949 Chinese marketing.
Research limitations/implications
Underused Chinese multilateral historical marketing materials are inalienable to extending historical marketing study. Many studies about marketing theory and practice are amenable to such materials.
Practical implications
By scrutinizing these materials, contemporary marketers can formulate parallel strategies from the repertoire of historical marketing strategies.
Originality/value
This is the first comprehensive survey of an invaluable non-Western source for historical research in marketing.
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Guang-Zhi Zeng, Zheng-Wei Chen, Yi-Qing Ni and En-Ze Rui
Physics-informed neural networks (PINNs) have become a new tendency in flow simulation, because of their self-advantage of integrating both physical and monitored information of…
Abstract
Purpose
Physics-informed neural networks (PINNs) have become a new tendency in flow simulation, because of their self-advantage of integrating both physical and monitored information of fields in solving the Navier–Stokes equation and its variants. In view of the strengths of PINN, this study aims to investigate the impact of spatially embedded data distribution on the flow field results around the train in the crosswind environment reconstructed by PINN.
Design/methodology/approach
PINN can integrate data residuals with physical residuals into the loss function to train its parameters, allowing it to approximate the solution of the governing equations. In addition, with the aid of labelled training data, PINN can also incorporate the real site information of the flow field in model training. In light of this, the PINN model is adopted to reconstruct a two-dimensional time-averaged flow field around a train under crosswinds in the spatial domain with the aid of sparse flow field data, and the prediction results are compared with the reference results obtained from numerical modelling.
Findings
The prediction results from PINN results demonstrated a low discrepancy with those obtained from numerical simulations. The results of this study indicate that a threshold of the spatial embedded data density exists, in both the near wall and far wall areas on the train’s leeward side, as well as the near train surface area. In other words, a negative effect on the PINN reconstruction accuracy will emerge if the spatial embedded data density exceeds or slips below the threshold. Also, the optimum arrangement of the spatial embedded data in reconstructing the flow field of the train in crosswinds is obtained in this work.
Originality/value
In this work, a strategy of reconstructing the time-averaged flow field of the train under crosswind conditions is proposed based on the physics-informed data-driven method, which enhances the scope of neural network applications. In addition, for the flow field reconstruction, the effect of spatial embedded data arrangement in PINN is compared to improve its accuracy.
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Lihua Chen, Yi Lu and Rui Zhao
The purpose of this paper is make a significant contribution to the supply chain knowledge system through research on modern supply chain system in China, providing guidance for…
Abstract
Purpose
The purpose of this paper is make a significant contribution to the supply chain knowledge system through research on modern supply chain system in China, providing guidance for theoretical research such as methodology of dynamic resource allocation and application of innovative small- and middle-sized service system in the supply chain.
Design/methodology/approach
The paper uses structural analysis of Chinese competitive advantage, and it applies comparative analysis of supply chain models in China, the USA and Japan through the factor disintegration of trading environment.
Findings
China’s supply chain model has virtual scale and virtual capabilities. The relationship with suppliers is more dynamic. The requirements for resolving uncertainty are higher. Business transfer is more frequent.
Research limitations/implications
Researchers are encouraged to propose the specific supply chain models in China further with the game theory, auction theory, etc.
Practical implications
It provides advice for government policy making and gives Chinese enterprises guidance to improve operation management.
Originality/value
This paper specifically analyzes characteristics of China supply chain and gives enlightenment for supply chain innovation.
Details
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En-Ze Rui, Guang-Zhi Zeng, Yi-Qing Ni, Zheng-Wei Chen and Shuo Hao
Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural…
Abstract
Purpose
Current methods for flow field reconstruction mainly rely on data-driven algorithms which require an immense amount of experimental or field-measured data. Physics-informed neural network (PINN), which was proposed to encode physical laws into neural networks, is a less data-demanding approach for flow field reconstruction. However, when the fluid physics is complex, it is tricky to obtain accurate solutions under the PINN framework. This study aims to propose a physics-based data-driven approach for time-averaged flow field reconstruction which can overcome the hurdles of the above methods.
Design/methodology/approach
A multifidelity strategy leveraging PINN and a nonlinear information fusion (NIF) algorithm is proposed. Plentiful low-fidelity data are generated from the predictions of a PINN which is constructed purely using Reynold-averaged Navier–Stokes equations, while sparse high-fidelity data are obtained by field or experimental measurements. The NIF algorithm is performed to elicit a multifidelity model, which blends the nonlinear cross-correlation information between low- and high-fidelity data.
Findings
Two experimental cases are used to verify the capability and efficacy of the proposed strategy through comparison with other widely used strategies. It is revealed that the missing flow information within the whole computational domain can be favorably recovered by the proposed multifidelity strategy with use of sparse measurement/experimental data. The elicited multifidelity model inherits the underlying physics inherent in low-fidelity PINN predictions and rectifies the low-fidelity predictions over the whole computational domain. The proposed strategy is much superior to other contrastive strategies in terms of the accuracy of reconstruction.
Originality/value
In this study, a physics-informed data-driven strategy for time-averaged flow field reconstruction is proposed which extends the applicability of the PINN framework. In addition, embedding physical laws when training the multifidelity model leads to less data demand for model development compared to purely data-driven methods for flow field reconstruction.