Search results

The purpose of this study is to address the welding demands within large steel structures by presenting a global spatial motion planning algorithm for a mobile manipulator. This algorithm is based on an independently developed wall-climbing robot, which comprises a four-wheeled climbing mobile platform and a six-degree-of-freedom robotic manipulator, ensuring high mobility and operational flexibility.

A convex hull feasible domain constraint is developed for motion planning in the mobile manipulator. For extensive spatial movements, connected sequences of convex polyhedra are established between the composite robot’s initial and target states. The composite robot’s path and obstacle avoidance optimization problem are solved by constraining the control points on B-spline curves. A dynamic spatial constraint rapidlye-xploring random trees-connect (RRTC) motion planning algorithm is proposed for the manipulator, which quickly generates reference paths using spherical spatial constraints at the manipulator’s end, eliminating the need for complex nonconvex constraint modeling.

Experimental results show that the proposed motion planning algorithm achieves optimal paths that meet task constraints, significantly reducing computation times in task conditions and shortening operation times in non-task conditions.

The algorithm proposed in this paper holds certain application value for the realization of automated welding operations within large steel structures using mobile manipulator.

The purpose of this paper is to explore a novel measurement approach for wheel-terrain contact angle using laser scanning sensors based on near-terrain perception. Laser scanning sensors have rarely been applied to the measurement of wheel-terrain contact angle for wheeled mobile robots (WMRs) in previous studies; however, it is an effective way to measure wheel-terrain contact angle directly with the advantages of simple, fast and high accuracy.

First, kinematics model for a WMR moving on rough terrain was developed, taking into consideration wheel slip and wheel-terrain contact angle. Second, the measurement principles of wheel-terrain contact angle using laser scanning sensors was presented, including “rigid wheel - rigid terrain” model and “rigid wheel - deformable terrain” model.

In the proposed approach, the measurement of wheel-terrain contact angle using laser scanning sensors was successfully demonstrated. The rationality of the approach was verified by experiments on rigid and sandy terrains with satisfactory results.

This paper proposes a novel, fast and effective wheel-terrain contact angle measurement approach for WMRs moving on both rigid and deformable terrains, using laser scanning sensors.

Improving the prediction accuracy of design time for complex products is significant for improving the accuracy of product development and control plans. The purpose of this study is to propose an intelligent pre-estimation method of design time for complex products based on v-SVM.

First, an evaluation model for designer knowledge abilities based on v-SVM is built, which considers the fuzziness and dynamics of designer knowledge abilities. Next, a pre-estimation method for the design time of complex products based on v-SVM is built. This method takes into account the impacts of designer knowledge abilities and design task characteristics on the design time. Then, an adaptive genetic algorithm is programmed to optimize the parameters in the evaluation model and the pre-estimation method. Finally, a practical application and comparative analysis of the proposed pre-estimation method is suggested to verify the validity and applicability of this research.

First, the evaluation of designer knowledge abilities is a prediction problem that is both fuzzy and multivariate time series. Second, the pre-estimation of design time is a problem that is fuzzy and multivariate. Third, the pre-estimation accuracy of the proposed method is higher when compared with traditional methods.

This paper presents an intelligent pre-estimation method of design time for complex products. Unlike previous research, the pre-estimation method takes into account the impacts of both the designer knowledge abilities and the design task characteristics on the design time.

This study aims to investigate how Lean Six Sigma (LSS), a widely used paradigm that promotes competitive advantage of different organisations in a more sustainable and environmentally friendly way, affects operational performance in different organisational contexts. Although LSS is widely used to improve operational performance, the impact of LSS on operational performance appears to be different in different organisational contexts, prompting the attention of researchers and managers to shift from lean philosophy to the impact of contextual variables on the effectiveness of LSS implementation.

This study uses a quantitative research design and conducts an empirical study in Pakistan. The sample consists of 339 management employees with an effective response rate of 67.8% in various sectors. In this study, partial least square structural equation modelling is used to examine the relationships among the variables using the resource-based view (RBV) and dynamic capability theory (DCT) to support the model of this study.

This study reveals that the relationship between LSS and operational performance is partially mediated by green human resource management (GHRM) and internal environmental management (IEM). The moderating effect of the organisational developmental culture between LSS and operational performance is not identified, implying that the effect of developmental culture could vary under different cultures.

There is a lack of empirical studies investigating the role of GHRM, IEM and developmental culture in developing countries. This study extends the literature on the RBV and DCT in operational performance. The study’s outcome provides theoretical and practical implications for enhancing the effect of LSS implementation on operational performance in focal small and medium-sized enterprises (SMEs) through human and environmental management factors.

The purpose of this paper is to investigate the relationship between tax avoidance and earnings persistence in the light of a developing economy, with the main focus on China.

In the analysis, the author conducts a survey on the tax avoidance situation of Chinese listed companies from 2012 to 2020. Then, a multivariate regression analysis is performed in order to analyse the relationship between corporate tax avoidance and earnings persistence.

The findings of the present study show that tax avoidance has a significant positive effect on earnings persistence. However, when the degree of tax avoidance is high, the “risk effect” of tax avoidance exceeds the “value effect”, and tax avoidance will reduce the persistence of earnings. This conclusion is even more prominent when the company is non-state-owned. Further research shows the increase of institutional investors’ shareholding ratio can improve “value effect” of tax avoidance, lessen “risk effect” of tax avoidance, and positively affect the relationship between tax avoidance and earnings persistence.

This study provides evidence for investors to understand the dual effect of tax avoidance on earnings persistence. The results may have implications for regulatory bodies. They can provide a better understanding of the corporate governance role of institutional investors in curbing opportunistic tax avoidance.

This study enriches the research on tax avoidance effects by analysing the impact of tax avoidance on earnings persistence. This study also compensates for the shortcomings of analysing earnings persistence mainly from the perspective of tax differences in the past, and promotes the study of the corporate governance effects of institutional investors under different levels of tax avoidance.

Organizational networking has been acclaimed as a useful tool for knowledge transfer. However, the demerit associated with knowledge transfer is the leakage of commercially valuable information/knowledge. The purpose of this paper is to empirically establish a useful framework for helping collaborative projects reduce potential knowledge leakages.

The study applies a hybrid methodology to collect data. Postulates are tested through SPSS 23 and Process Macro 3.0 model 7.

The study finds that knowledge leakage is negatively influenced by contract completeness. Contract completeness has a positive effect on trust and a negative effect on distrust. Partner’s learning intent moderates the relationship of contract completeness with trust and distrust. Trust and distrust negatively mediate the relationship between contract completeness and knowledge leakage.

The study contributes to the theories of information processing and knowledge management by empirically stating how contract completeness, an organizational structure, supports knowledge management under the influence of partner’s opportunism. The study sees positivism in distrust and explains how practitioners maintain an observatory eye on partner’s opportunism by virtue of distrust ultimately adding value to the distrust literature.

The conceptual framework is novel because this is the first attempt to investigate the moderation effect of partner’s opportunism on the relationship of contract completeness and relational factors; and the mediation effects of trust and distrust between contract completeness and knowledge leakage.

Constructed upon the knowledge-based view, the purpose of this study is to investigate the interrelationship between internal marketing, knowledge management processes and knowledge worker satisfaction. The study also postulates that specific combinations of internal marketing dimensions and knowledge management processes can lead to improved knowledge worker satisfaction.

The study sample is gathered from 248 personnel of Pakistan higher education institutions (HEI’s). The interrelationships are checked through Smart PLS 3.2.8. The fuzzy set qualitative comparative analysis (fsQCA) is used to examine configurational paths for improving knowledge worker satisfaction.

The results of the study show that in HEI’s, internal marketing has a substantial influence on knowledge management processes, and knowledge management processes strongly enhance knowledge worker satisfaction. The result from fsQCA reveals multiple configurational paths to improve knowledge worker satisfaction.

There is a scarcity of research that has explored the association of internal marketing, knowledge management processes and knowledge worker satisfaction. This study attempts to examine their inter-relationships in HEI’s. Methodologically, the study contributes by combining direct and configurational methods to foster the knowledge of organizational (higher education) matters. The use of fsQCA reveals multiple pathways to improve knowledge worker satisfaction and exposes asymmetric relationships between internal marketing and knowledge management processes that lead to knowledge worker satisfaction. The study identifies the interactions among variables that might not be directly obvious via conventional symmetric methods.

Social media facilitates consumer exchanges on product opinions and provides comprehensive knowledge of online products. The interaction between consumers and e-retailers evolves into a collective set of dynamics within a complex system. Agent-based modeling is well suited to stimulate such complex systems. The purpose of this paper is to integrate agent-based model and technique for order performance by similarity to ideal solution (TOPSIS) to simulate decision behaviors of e-retailers in competitive online markets.

An agent-based network model using the TOPSIS driven by actual price data is developed. The authors ran an experimental model to simulate interactions between online consumers and e-retailers and to record simulation data. A nonparametric test is used to conduct data analysis and evaluate the sensibility of parameters.

Simulation results showed that different profits could be obtained for various brands under different social network structures. E-retailers could achieve more profits through cross-selling than single-selling; however, the highest profits can be achieved when some adopt cross-selling, whereas others use single-selling. From a game perspective, the equilibrium for price-adjustment frequency can be determined from the simulation data. Thus, price adjustment differences significantly affect e-retailer profit.

This study provides new insights into the evolutionary dynamics of online markets. This work also indicates how to build an integrated simulation model with an agent-based model and TOPSIS and how to use an integrated simulation model and interpret its results.

Telecommunications regulation in Hong Kong (China) is interesting as a case study of pro‐competitive regulation in a geographically small city of some 6.8 million people. It is also of particular interest because The Office of the Telecommunications Authority, the sector regulator, has for four years running (1999‐2002) been voted the best Asian regulator by readers of Telecom Asia. What policies were applied to warrant this sustained approval rating? This paper examines these policies and suggests further improvements.

The purpose of this paper is to establish the index system of leading industries in Kashgar urban agglomeration, and use the multi-attribute weighted intelligent grey target decision-making evaluation model to measure the comprehensive effect, so as to select the leading industries of Kashgar urban agglomeration.

First, 18 industries in Kashgar urban agglomerations are taken as objectives, and four indexes, namely, demand income elasticity index, growth rate index, labor productivity growth rate index and contribution rate of output value, are selected to construct an evaluation system for leading industry selection in Kashgar urban agglomerations. Then, grey incidence degree method is used to determine the decision-making power of each decision-making objective. Finally, multi-attribute weighted intelligent grey target decision-making evaluation model is used to measure the comprehensive effect of the objective system of leading industries in Kashgar urban agglomerations.

It can be seen that the multi-attribute weighted intelligent grey target decision-making evaluation model is more convenient to be used in selecting regional leading industries, and the results are accurate and feasible. Based on the calculation results and the actual economic development requirements of Kashgar urban agglomeration, the leading industries of Kashgar urban agglomeration can be determined as: wood processing, furniture, paper making and printing; wholesale and retail; construction; equipment manufacturing; transportation, storage and postal services.

First, it is a new method in selecting regional leading industry by using the multi-attribute weighted intelligent grey target decision-making evaluation model. Second, since there is relatively little research on Kashgar urban agglomeration, especially on leading industries in Kashgar urban agglomeration. The research in this paper can not only enrich the research on selecting leading industries in urban agglomeration but also provide scientific reference for relevant government agencies to formulate economic development plans.