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This paper aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

In this paper, an improved artificial potential field method is proposed, where the object can leave the local minima point, where the algorithm falls into, while it avoids the obstacle, following a shorter feasible path along the repulsive equipotential surface, which is locally optimized. The whole obstacle avoidance process is based on the improved artificial potential field method, applied during the mechanical arm path planning action, along the motion from the starting point to the target point.

Simulation results show that the algorithm in this paper can effectively perceive the obstacle shape in all the selected cases and can effectively shorten the distance of the planned path by 13%–41% with significantly higher planning efficiency compared with the improved artificial potential field method based on rapidly-exploring random tree. The experimental results show that the improved artificial potential field method can effectively plan a smooth collision-free path for the object, based on an algorithm with good environmental adaptability.

An improved artificial potential field method is proposed for optimized obstacle avoidance path planning of a mechanical arm in three-dimensional space. This new approach aims to resolve issues of the traditional artificial potential field method, such as falling into local minima, low success rate and lack of ability to sense the obstacle shapes in the planning process.

Security is one of the major challenges in the design and implementation of protocols for mobile ad hoc networks (MANETs). In such systems, the cooperation between nodes is one of the important principles being followed in the current research works to formulate various security protocols. Many existing works assume that mobile nodes will follow prescribed protocols without deviation. However, this is not always the case, because these networks are subjected to a variety of malicious attacks. Since there are various models of attack, trust routing scheme can guarantee security and trust of the network. The purpose of this paper is to propose a novel trusted routing model for mitigating attacks in MANETs.

The proposed model incorporates the concept of trust into the MANETs and applies grey relational analysis theory combined with fuzzy sets to calculate a node’s trust level based on observations from neighbour nodes’ trust level, these trust levels are then used in the routing decision-making process.

In order to prove the applicability of the proposed solution, extensive experiments were conducted to evaluate the efficiency of the proposed model, aiming at improving the network interaction quality, malicious node mitigation and enhancements of the system’s security.

The proposed solution in this paper is a new approach combining the fundamental basics of fuzzy sets with the grey theory, where establishment of trust relationships among participating nodes is critical in order to enable collaborative optimisation of system metrics. Experimental results indicate that the proposed method is useful for reducing the effects of malicious nodes and for the enhancements of system’s security.

The alienation of megaproject environmental responsibility (MER) behavior is destructive, but its mechanism has not been clearly depicted. Based on fraud triangle theory and the fuzzy set qualitative comparative analysis (fsQCA) method, this study explored the combined effect of antecedent factors on alienation of MER behavior.

Based on the fraud triangle theory and literature review, eight influencing factors associated with the alienation of MER behavior were first identified. Subsequently, the fuzzy-set qualitative comparative analysis was used in this study to reveal configurations influencing alienation of MER behavior.

The study found nine configurations of MER behavioral alienation antecedent factors, integrated into three types of driving modes, i.e. “economic pressure + learning effect,” “institutional defect + moral rejection,” and “information asymmetry + economic pressure + expectation pressure.”

By analyzing the configuration effects of various induced conditions, this study puts forward a comprehensive analysis framework to solve the alienation of MER behavior in the megaprojects and a practical strategy to control alienation of MER behavior.

As megaprojects bear extensive and profound social responsibilities throughout the project life cycle, formulating effective measures for improving construction enterprise social responsibility is key to project success. Given the current research is relatively lack of these measures, this study aims to formulate a meta-network framework to improve the megaproject social responsibility behaviour (MSRB) for construction enterprises.

First, this study implements literature review, expert interview and field investigation to identify the construction enterprise MSRB and its influencing factors. Second, this study evaluates the MSRB implementation level of the selected construction enterprises and proposes the above mentioned meta-network framework. Next, this meta-network is configured to reflect the impact of MSRB strategic adjustment. Last but not least, a real-world case study is carried out to validate this framework.

The best MSRB performance is always witnessed from the contractor group, followed by the project client group and the site supervisor group. The outcomes of implementing certain managerial strategies indicate that (1) social responsibility cognition is a critical factor for all the groups; (2) communication mechanism and normative pressure are the critical factors for clients; (3) coercive pressure is a critical factor for supervisors and (4) cultural cognitive pressure is a critical factor for clients and contractors.

The use of the framework in proactive assessment and management of MSRB can lead to effective strategies for construction enterprises to increase the efficiency and quality of projects.

Considering the small sample size and non-linear characteristics of historical energy consumption data from certain provinces in Southwest China, the authors propose a hybrid accumulation operator and a hybrid accumulation grey univariate model as a more accurate and reliable methodology for forecasting energy consumption. This method can provide valuable decision-making support for policy makers involved in energy management and planning.

The hybrid accumulation operator is proposed by linearly combining the fractional-order accumulation operator and the new information priority accumulation. The new operator is then used to build a new grey system model, named the hybrid accumulation grey model (HAGM). An optimization algorithm based on the JAYA optimizer is then designed to solve the non-linear parameters θ, r, and γ of the proposed model. Four different types of curves are used to verify the prediction performance of the model for data series with completely different trends. Finally, the prediction performance of the model is applied to forecast the total energy consumption of Southwest Provinces in China using the real world data sets from 2010 to 2020.

The proposed HAGM is a general formulation of existing grey system models, including the fractional-order accumulation and new information priority accumulation. Results from the validation cases and real-world cases on forecasting the total energy consumption of Southwest Provinces in China illustrate that the proposed model outperforms the other seven models based on different modelling methods.

The HAGM is used to forecast the total energy consumption of the Southwest Provinces of China from 2010 to 2020. The results indicate that the HAGM with HA has higher prediction accuracy and broader applicability than the seven comparative models, demonstrating its potential for use in the energy field.

The HAGM(1,1) is used to predict energy consumption of Southwest Provinces in China with the raw data from 2010 to 2020. The HAGM(1,1) with HA has higher prediction accuracy and wider applicability compared with some existing models, implying its high potential to be used in energy field.

Theoretically, this paper presents, for the first time, a hybrid accumulation grey univariate model based on a new hybrid accumulation operator. In terms of application, this work provides a new method for accurate forecasting of the total energy consumption for southwest provinces in China.

Although domestic research on Chinese management is emerging, a suitable domestic theory is still needed to support and explain Chinese management practice. Given that, this paper aims to extract ideas of cultivation from Confucianism and propose a theoretical framework of self-cultivation with a purpose to provide new explanations for domestic (nondomestic as well) management practice.

Drawing from pre-Qin cultivation discourse and management practice, this paper develops a theoretical framework of self-cultivation and discusses its implications.

This paper argues that self-cultivation emphasizes self-consciousness, initiative and selflessness. It also includes self-reflection, self-discipline, self-study and self-improvement, as well as self-dedication, all of which reflect the ideal realm of “self-cultivation.” This “realm” refers to the process of pursuing an ideal personality and high moral standards.

This paper contributes to the literature by identifying various potential applications of self-cultivation theory to domestic research on organizational behavior in China.

Megaprojects have a long-lasting impact on all three dimensions of sustainability-social, environmental and economic. The advent of the COVID-19 pandemic has further heightened the importance of sustainability due to its disastrous consequences on the global economy and business activities. This study aims to explore the interactions and interventions of various actors in the megaproject field to institutionalise sustainability.

The current study adopted the organisational field approach as the theoretical lens to understand the decision-making process amongst multiple actors with conflicting interests that come together to play an active role in addressing a common interest of sustainability in megaprojects. A single case study has been undertaken using an Indian metro rail megaproject with multiple sources of data (interviews, documents, media reports).

This study showed that the institutionalisation of sustainability is dependent on interactions of various organisations and influences from institutions. Various institutional measures organised within the field to enhance sustainability practices before and during the COVID-19 pandemic are captured. Four institutional logics (instrumental, intrinsic, equivocal and political) that emerged from the case study are discussed. Finally, while not exhaustive, this study proposed recommendations that can help refine sustainability actions considering COVID-19 implications on megaprojects.

This study's findings emerged from a single case study. The developed conceptual framework can help further research with multiple cases of megaprojects in various fields or countries.

This study would be novel in advancing the organisational field approach in megaproject sustainability.

The role of corporate social responsibility (CSR) fulfillment is critical when building resilience of project-based organizations (PBOs). However, fulfilling CSR to build a highly resilient PBO remains a black box problem. This study explores the different CSR combinations that enhance PBO resilience.

This study defines CSR in terms of shareholder, employee, and social CSR, and analyzes corporate characteristics in terms of corporate scale and nature. Data are collected from Hexun.com and the China Stock Market and Accounting Research Database (CSMAR). The qualitative comparative analysis (QCA) method is used to analyze 48 listed construction and engineering companies from China to explore the CSR configurations for PBOs in enhancing organizational resilience.

A large firm size is a necessary condition for high organizational resilience. We find six paths to build high and non-high resilience in PBOs, and the driving mechanisms of high and non-high resilience exhibit an asymmetric relationship.

This study cracks the black box of CSR fulfillment and PBO resilience. It reveals the CSR configurations that enhance or inhibit the resilience of PBOs. It also provides scientific basis for PBOs in their fulfillment of CSR in response to crises, and the enhancement of organizational resilience. Future research can be expanded to other industries, as the study sample is only limited to civil engineering construction companies. Since this study uses cross-sectional data, time series can be introduced in the future to further explore the relationship between CSR and organizational resilience.

This study provides targeted suggestions that can help decision-makers of construction companies to determine how they can fulfill CSR to enhance organizational resilience. At the same time, it can provide intellectual support for PBOs to cope with systemic crises and promote the fulfillment of CSR.

In terms of theoretical value, on the one hand, this study verifies the relationship between CSR fulfillment and PBO resilience, revealing its mechanism of action and multiple paths; on the other hand, it provides a new way of thinking for management research methods and enriches the theoretical study of organizational resilience.

The harsh environment of space, especially radiation of direct solar rays, can potentially raise the temperature of the spacecraft to harmful levels. Thermal control coatings (TCCs) fix the thermal condition of the spacecraft acceptable for its components. This is possible by diffusely reflecting all effective ultraviolet (UV), visible (VIS) and near infrared (IR) (NIR) wavelengths of solar radiation and emmition of IR energy. The most commonly used TCCs have used ZnO as a pigment, but absorption of the UV light by ZnO pigment can change the ideal condition of these TCCs. The aim of his study is the using the porous ZnO particles as pigment to prevent the UV absorption.

To enhance the efficiency of these coatings, in the present study, nano-porous zinc oxide particles were synthesized and used as pigments for white TCCs.

The results revealed that the proposed TCC (TPZ), Thermal control coating with porous ZnO had better reflection (scattering) and emittance properties in comparison with the coating using ZnO as a pigment (TZ coating); so this coating had a solar absorptance value equal to 0.141, whereas this value for TZ was 0.150. Furthermore, TPZ showed higher thermal emittance (0.937) in comparison with TZ (0.9). These changes were because of the improvement in the refractive index, shape and surface area of the pigments. The general trend of the scattering coefficients for the prepared coating, as calculated from the Kubelka–Munk equation, showed that scattering was more efficient in the UV region, as compared with the TCC containing ZnO pigments.

This type of pigment for the first time is evaluated in TCCs.

The purpose of this study is to systematically analyze the wear of cylindrical needle bearings in rotary vector reducers under temperature rise and identify the influencing factors.

Based on the dynamic characteristics of the RV-20E reducer, the time-varying contact force of the cylindrical needle bearing and the entrainment speed of the inner and outer raceways were calculated. A mixed elastohydrodynamic lubrication model of the needle bearing, considering friction and temperature rise, was established using a dynamic rough tooth surface model. The model solved for the oil film thickness, contact stress and wear conditions of the bearing raceway contact area. The effects of the number of rolling needles, the diameter of rolling needles and surface strength on the wear characteristics were analyzed.

The results of this study show that the oil film thickness, oil film pressure and surface scratches of cylindrical needle bearings exhibit an uneven, patchy distribution under the combined effects of friction and temperature rise. When the radius of the rolling needle is less than 1.44 mm, inner ring wear is less than outer ring wear. Conversely, when the radius exceeds 1.44 mm, inner ring wear is greater. The optimal rolling needle radius is 1.6 mm. Increasing the number of rolling needles and enhancing the yield strength of the contact surface significantly extend bearing life.

This study provides valuable recommendations for optimizing bearing structural parameters and material characteristics in the design of rotary vector reducers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0242/