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User value co-creation behaviors are crucial for the sustainable development of Virtual Brand Communities. This research, grounded in social exchange theory, investigates the impact of community satisfaction and identification on customer value co-creation behaviors and further explores how the reciprocity norm moderates these relationships.

Our research data were collected from users across multiple brand communities, totaling 481 survey responses. Structural equation modeling was performed to test the research hypotheses.

These results provide in-depth insights into the nexus between user-community relationships and customer value co-creation behaviors. While community satisfaction and identification positively influence co-creation, their effects vary across different value co-creation behaviors. Notably, the reciprocity norm within the community dampens the relationship between community satisfaction and value co-creation behaviors.

Unlike previous studies focusing on customer value co-creation behaviors, our research emphasizes social exchange, unveiling the mechanisms behind customer value co-creation. Our findings not only enrich the body of knowledge on customer value co-creation but also deepen our understanding of online collective behavior and knowledge sharing, offering valuable insights for the development of virtual communities.

This paper aims to present a novel particle swarm optimization (PSO) based on a non-homogeneous Markov chain and differential evolution (DE) for path planning of intelligent robot when having obstacles in the environment.

The three-dimensional path surface of the intelligent robot is decomposed into a two-dimensional plane and the height information in z axis. Then, the grid method is exploited for the environment modeling problem. After that, a recently proposed switching local evolutionary PSO (SLEPSO) based on non-homogeneous Markov chain and DE is analyzed for the path planning problem. The velocity updating equation of the presented SLEPSO algorithm jumps from one mode to another based on the non-homogeneous Markov chain, which can overcome the contradiction between local and global search. In addition, DE mutation and crossover operations can enhance the capability of finding a better global best particle in the PSO method.

Finally, the SLEPSO algorithm is successfully applied to the path planning in two different environments. Comparing with some well-known PSO algorithms, the experiment results show the feasibility and effectiveness of the presented method.

Therefore, this can provide a new method for the area of path planning of intelligent robot.

The purpose of this paper is to improve the performance of the genetic algorithm-based compliant robot path planning (GACRPP) in complex dynamic environment by proposing an improved bidirectional rapidly exploring random tree (Bi-RRT)-based population initialization method.

To achieve GACRPP in complex dynamic environment with high performance, an improved Bi-RRT-based population initialization method is proposed. First, the grid model is adopted to preprocess the working space of mobile robot. Second, an improved Bi-RRT is proposed to create multi-cluster connections between the starting point and the goal point. Third, the backtracking method is used to generate the initial population based on the multi-cluster connections generated by the improved Bi-RRT. Subsequently, some comparative experiments are implemented where the performances of the improved Bi-RRT-based population initialization method are compared with other population initialization methods, and the comparison results of the improved genetic algorithm (IGA) combining with the different population initialization methods are shown. Finally, the optimal path is further smoothed with the help of the technique of quadratic B-spline curves.

It is shown in the experiment results that the improved Bi-RRT-based population initialization method is capable of deriving a more diversified initial population with less execution time and the IGA combining with the proposed population initialization method outperforms the one with other population initialization methods in terms of the length of optimal path and the execution time.

In this paper, the Bi-RRT is introduced as a population initialization method into the GACRPP problem. An improved Bi-RRT is proposed for the purpose of increasing the diversity of initial population. To characterize the diversity of initial population, a new notion of breadth is defined in terms of Hausdorff distance between different paths.

This paper aims to design a multi-layer convolutional neural network (CNN) to solve biomimetic robot path planning problem.

At first, the convolution kernel with different scales can be obtained by using the sparse auto encoder training algorithm; the parameter of the hidden layer is a series of convolutional kernel, and the authors use these kernels to extract first-layer features. Then, the authors get the second-layer features through the max-pooling operators, which improve the invariance of the features. Finally, the authors use fully connected layers of neural networks to accomplish the path planning task.

The NAO biomimetic robot respond quickly and correctly to the dynamic environment. The simulation experiments show that the deep neural network outperforms in dynamic and static environment than the conventional method.

A new method of deep learning based biomimetic robot path planning is proposed. The authors designed a multi-layer CNN which includes max-pooling layer and convolutional kernel. Then, the first and second layers features can be extracted by these kernels. Finally, the authors use the sparse auto encoder training algorithm to train the CNN so as to accomplish the path planning task of NAO robot.

By investigating trust in the organization as a mediator and traditionality as a moderator, this study aims to examine the effect perceived organizational exploitation poses on frontline hotel employees’ service performance.

A three-wave survey that targets 219 supervisor–subordinate dyads from four Chinese hotels was conducted to test the hypotheses. The authors used SPSS 20.0 and AMOS 21.0 to analyze the data and verify the theoretical model.

This study found that perceived organizational exploitation exerts a destructive impact on frontline hotel employees’ service performance. Trust in the organization is a full mediator of the link connecting perceived organizational exploitation to service performance. Furthermore, traditionality weakens perceived organizational exploitation’s impact on trust in the organization and subsequent service performance.

The authors’ findings remind hotels to cease exploiting their employees to avoid compromising service performance. Hotels should also endeavor to instill trust among employees toward the hotel and allocate more attention to employees with lower levels of traditionality.

First, to the best of the authors’ knowledge, this study is among the first to explore the impact of perceived organizational exploitation on frontline hotel employees’ service performance. Second, this study reveals a novel mechanism underlying the connection between perceived organizational exploitation and service performance. Finally, this study identifies frontline hotel employees’ traditionality as a vital moderator that mitigates the negative relationships among perceived organizational exploitation, trust in the organization and service performance.

The purpose of this paper is to examine how Chinese immigrant businesses in Australia were able to shift from low return start-up businesses and move to more competitive business models targeting mainstream clientele. The research aims to identify the factors enabling a break-out strategy for these entrepreneurs and whether a horizontal or vertical break-out was achieved.

A qualitative research method with in-depth interviews is employed. Interviews were conducted with 55 Chinese immigrant business owners in Sydney and Canberra.

The analysis found that a break-out strategy depended on a range of business activities, including innovation, marketing, networking and personnel strategies. Importantly, the current research found that these resources have varying degrees of importance in the different stages of the transition to the new business model. Accumulating sufficient financial capital was a fundamental enabler for a break-out strategy, followed by the capacity to learn and benefit from the experience of social networks.

The current research highlights the importance of financial capital and capacity to benefit from social networks as fundamental factors in enabling a break-out strategy. The benefit of the qualitative approach in obtaining rich data needs to be offset by potential limitations on generalisability. Future research could incorporate comparison between different size businesses as well as analysing factors underpinning a failure to successfully implement a break-out.

The findings indicate that business support groups and policymakers could review access to financial capital for entrepreneurs seeking break-outs, consider improving opportunities for developing capacity to utilise heterogeneous social networks, and consider pathways for improving skills acquisition amongst immigrant entrepreneurs.

This paper contributes to the research literature on break-out strategies used by immigrant entrepreneurs by analysing, in detail, the transition steps undertaken by ethnic Chinese entrepreneurs in the shift to more competitive business models.

The purpose of this paper is to survey and express the advantages and disadvantages of the existing approaches for solving grey linear programming in decision-making problems.

After presenting the concepts of grey systems and grey numbers, this paper surveys existing approaches for solving grey linear programming problems and applications. Also, methods and approaches for solving grey linear programming are classified, and its advantages and disadvantages are expressed.

The progress of grey programming has been expressed from past to present. The main methods for solving the grey linear programming problem can be categorized as Best-Worst model, Confidence degree, Whitening parameters, Prediction model, Positioned solution, Genetic algorithm, Covered solution, Multi-objective, Simplex and dual theory methods. This survey investigates the developments of various solving grey programming methods and its applications.

Different methods for solving grey linear programming problems are presented, where each of them has disadvantages and advantages in providing results of grey linear programming problems. This study attempted to review papers published during 35 years (1985–2020) about grey linear programming solving and applications. The review also helps clarify the important advantages, disadvantages and distinctions between different approaches and algorithms such as weakness of solving linear programming with grey numbers in constraints, inappropriate results with the lower bound is greater than upper bound, out of feasible region solutions and so on.

Infrastructure projects play a significant role in community development. Infrastructure consists of many subcategories such as roads, bridges, railways, airports, communication infrastructure and harbors. The expressway is an essential part of modern transportation infrastructure. Due to its span and complexity, expressway construction results in several environmental impacts comparatively higher than typical road construction. In that event, environmental sustainability assessment in expressway construction and determining environmental measures to address those impacts is essential. Therefore, this research intends to investigate the environmental measures applicable to expressway projects in Sri Lanka.

This study involves a comparative analysis of different environmental impacts validated through expert interviews. The data required to perform the analysis were extracted through expert interviews and the Battelle method.

The findings revealed the importance of environmental indicators for expressway projects in Sri Lanka by assigning weightages. The Construction Phase received the highest weightage among three themes indicating that the construction phase causes greater environmental impact in expressway construction. Furthermore, the Site Maintenance Plan and Tree Compensating received the highest weightages under indicators.

The study makes an original contribution through the identification of indicators that lead to the improvement of environmental sustainability in expressway projects in Sri Lanka. Furthermore, the use of the Battelle method within the context of measuring environmental sustainability of expressways projects in general — and within the context of Sri Lanka — is a novel research approach.

The present work aims to prepare biocomposites blend based on linear low density polyethylene/ starch without using harmful chemicals to improve the adhesion between two phases. Also, the efficiency of essential oils as green plasticizers and natural antimicrobial agents were evaluated.

Barrier properties and biodegradation behavior of linear low density polyethylene/starch (LLDPE/starch) blends plasticized with different essential oils including moringa oleifera and castor oils wereassessed as a comparison with traditional plasticizer such as glycerol. Biodegradation behavior forLLDPE/starch blends was monitored by soil burial test. The composted samples were recovered then washed followed by drying, and weighting samples after 30, 60, and 90 days to assess the change in weight loss. Also, mechanical properties including retention values of tensile strength and elongation at break were measured before and after composting. Furthermore, scanning electron microscope (SEM) was used to evaluate the change in the morphology of the polymeric blends. In addition to, the antimicrobial activity of plasticized LLDPE/starch blends films was evaluated using a standard plate counting technique.

The results illustrate that the water vapor transition rate increases from 2.5 g m⁻² 24 h⁻¹ for LLDPE/5starch to 4.21 g m⁻² 24 h⁻¹ and 4.43 g m⁻² 24 h⁻¹ for castor and moringa oleifera respectively. Also, the retained tensile strength values of all blends decrease gradually with increasing composting period. Unplasticized LLDPE/5starch showed highest tensile strength retention of 91.6% compared to the other blends that were 89.61, 88.49 and 86.91 for the plasticized LLDPE/5starch with glycerol, castor and M. oleifera oils respectively. As well as, the presence of essential oils in LLDPE/ starch blends increase the inhibition growth of escherichia coli, candida albicans and staphylococcus aureus.

The objective of this work is to develop cost-effective and environmentally-friendly methods for preparing biodegradable polymers suitable for packaging applications.

The demand to reduce carbon emissions has become an increasingly important social factor due to the unprecedented impacts of climate change. However, most existing publications have focused on minimizing emissions during the operational phase of buildings. At the same time, there is a lack of comprehensive research conducted on carbon emissions, specifically during the construction phase. The purpose of this paper is to identify, review and classify current practices related to carbon emissions management in construction operations to gain greater insight into how to reduce and mitigate emissions and achieve more sustainable solutions.

This study reviewed the published literature on carbon emissions from construction. A total of 198 bibliographic records were extracted from the Scopus collection database and analyzed using Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). PRISMA is used as a basis for reporting possible trends, research methods and strategies used in published literatures. A total of 99 papers related to carbon emissions in the construction operations were further reviewed and analyzed. This review paper draws on existing research and identifies current carbon management patterns in construction projects.

Data indicated an upward trend in the number of publications in carbon emissions research during the last few years, particularly in 2015, 2017 and 2019. The most significant contributions to the domain were reported from China, Europe and the USA. This paper found that most studies conduct the Life Cycle Assessment (LCA) method to estimate carbon emissions. This paper found that the primary studies have focused on construction machinery and equipment emissions. The strategies such as establishing uniform standards for carbon emissions policies and regulations, equipment and logistic planning and low carbon design material will potentially impact carbon emissions reductions.

This paper provides information that will be beneficial for the construction industry to design and manage construction operations. It will also be of interest to those looking to reduce or manage construction emissions.

Although there is a diversity of current thinking related to the practical estimation and management of carbon emissions in construction projects, there is no consolidated set of keys of standardized carbon emissions management in practice. By assessing the existing paradigms of carbon assessment methods and tactics in the construction industry, this study contributed to the existing knowledge base by providing insights into current techniques in the construction sector for monitoring and mitigating emissions.