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Aircraft assembly is the crucial part of aircraft manufacturing, and to meet the high-precision and high-efficiency requirements, cooperative measurement consisting of multiple measurement instruments and automatic assisted devices is being adopted. To achieve the complete data of all assembly features, measurement devices need to be placed at different positions, and the flexible and efficient transfer relies on Automated Guided Vehicles (AGVs) and robots in the large-size space and close range. This paper aims to improve the automatic station transfer in accuracy and flexibility.

A transferring system with Light Detection and Ranging (LiDAR) and markers is established. The map coupling for navigation is optimized. Markers are distributed according to the accumulated uncertainties. The path planning method applied to the collaborative measurement is proposed for better accuracy. The motion planning method is optimized for better positioning accuracy.

A transferring system is constructed and the system is verified in the laboratory. Experimental results show that the proposed system effectively improves positioning accuracy and efficiency, which improves the station transfer for the cooperative measurement.

A Transferring system for collaborative measurement is proposed. The optimized navigation method extends the application of visual markers. With this system, AGV is capable of the cooperative measurement of large aircraft structural parts.

The purpose of this paper is to study how to effectively allocate water, energy and food (WEF) resources in urban development.

An agent-based model combined with NetLogo simulation model has been used in this paper.

This paper proposes a framework for agent analysis in urban WEF consumption.

Further discussions using empirical data are of great importance.

Apply to form the development model of the city in the future.

A new method of WEF management has been used at the city level.

Social relationships play an important role in organizational entrepreneurship. They are crucial to entrepreneurs’ decisions because, despite the bleeding-edge technological advancements observed nowadays, entrepreneurs as human beings will always strive to be social. During the COVID-19 pandemic many companies moved activities into the virtual world and as a result offline Social relationships became rarer, but as it turns out, even more valuable, likewise, the inter-organizational cooperation enabling many companies to survive.

This chapter aims to develop knowledge about entrepreneurs’ SR and their links with inter-organizational cooperation. The results of an integrative systematic literature review show that the concept of Social relationships, although often investigated, lacks a clear definition, conceptualization, and operationalization. This chapter revealed a great diversity of definitions for Social relationships, including different scopes of meaning and levels of analysis. The authors identify 10 building blocks and nine sources of entrepreneurs’ Social relationships. The authors offer an original typology of Social relationships using 12 criteria. Interestingly, with regard to building blocks, besides those frequently considered such as trust, reciprocity and commitment, the authors also point to others more rarely and narrowly discussed, such as gratitude, satisfaction and affection. Similarly, the authors discuss the varied scope of sources, including workplace, family/friendship, past relationships, and ethnic or religious bonds. The findings of this study point to a variety of links between Social relationships and inter-organizational cooperation, including their positive and negative influences on one another. These links appear to be extremely dynamic, bi-directional and highly complex.

This paper aims to elucidate the relationship between entrepreneurial orientation, reverse innovation and international performance of emerging economy multinational enterprises (EMNEs).

The authors analyze archival data of Chinese limited companies between 2010 and 2016, including 11,230 firm-year observations about 1708 firms. In order to test the study’s mediation hypotheses, the authors apply an ordinary least square (OLS) regression.

The authors find evidence that the entrepreneurial orientation of EMNEs has a positive effect on reverse innovations. Furthermore, the authors find positive effects of reverse innovation on the international performance of EMNEs. This pattern of results suggests that the relationship between entrepreneurial orientation and international performance is partially mediated by reverse innovation.

The study’s findings help managers in EMNEs to promote reverse innovation by building and using their entrepreneurial orientation. It also helps them to set out and gauge the chances of success of their internationalization strategies. The findings also hold relevance for firms in developed economies as well, as they may understand which emerging economy competitors stand to threaten their positions.

The strategic role of reverse innovations – i.e. clean slate, super value and technologically advanced products originating from emerging markets – has generated considerable research attention. It is clear that reverse innovations impact the international performance of EMNEs. Yet how entrepreneurial orientation influences international performance is still underexplored. Thus, the current study clarifies the mechanism by examining and testing the mediating role of reverse innovation among the entrepreneurial orientation–international performance link.

The decarbonization of power generation is key to achieving carbon neutrality in China by the end of 2060. This paper aims to examine how green finance influences China’s low-carbon transition of power generation. Using a provincial panel data set as an empirical study example, green finance is assessed first, then empirically analyses the influences of green finance on the low-carbon transition of power generation, as well as intermediary mechanisms at play. Finally, this paper makes relevant recommendations for peak carbon and carbon neutrality in China.

To begin with, an evaluation index system with five indicators is constructed with entropy weighting method. Second, this paper uses the share of coal-fired power generation that takes in total power generation as an inverse indicator to measure the low-carbon transition in power generation. Finally, the authors perform generalized method of moments (GMM) econometric model to examine how green finance influences China’s low-carbon transition of power generation by taking advantage of 30 provincial panel data sets, spanning the period of 2007–2019. Meanwhile, the implementation of the 2016 Guidance on Green Finance is used as a turning point to address endogeneity using difference-in-difference method (DID).

The prosperity of green finance can markedly reduce the share of thermal power generation in total electricity generation, which implies a trend toward China’s low-carbon transformation in the power generation industry. Urbanization and R&D investment are driving forces influencing low-carbon transition, while economic development hinders the low-carbon transition. The conclusions remain robust after a series of tests such as the DID method, instrumental variable method and replacement indicators. Notably, the results of the mechanism analysis suggest that green finance contributes to low-carbon transformation in power generation by reducing secondary sectoral share, reducing the production of export products, promoting the advancement of green technologies and expanding the proportion of new installed capacity of renewable energy.

This paper puts forward relevant suggestions for promoting the green finance development with countermeasures such as allowing low interest rate for renewable energy power generation, facilitating market function and using carbon trade market. Additional policy implication is to promote high quality urbanization and increase R&D investment while pursuing high quality economic development. The last implication is to develop mechanism to strengthen the transformation of industrial structure, to promote high quality trade from high carbon manufactured products to low-carbon products, to stimulate more investment in green technology innovation and to accelerate the greening of installed structure in power generation industry.

This paper first attempts to examine the low-carbon transition in power generation from a new perspective of green finance. Second, this paper analyses the mechanism through several aspects: the share of secondary industry, the output of exported products, advances in green technology and the share of renewable energy in new installed capacity, which has not yet been done. Finally, this study constructs a system of indicators to evaluate green finance, including five indicators with entropy weighting method. In conclusion, this paper provides scientific references for sustainable development in China, and meanwhile for other developing countries with similar characteristics.

Air quality and its assessment in urban areas has become a necessity. This is attributed to the increasing air pollution in urban landscape from anthropogenic activities necessary for economic growth and development. This study investigates air quality and potential health risk posed from nitrogen dioxide (NO₂) to the residents of low town of Mohammedia city, Morocco.

The NO₂ concentration was measured on an hourly basis for the winter season of the year 2014, 2015 and 2016. The air quality was assessed in terms of Air Quality Index (AQI). Noncarcinogenic risk assessment was done to evaluate possible health risk to the inhabitant of low town from NO₂ exposure.

The maximum concentration reached 85–96 µg/m³ (at 6 p.m., 2014), 96–104 µg/m³ (7–9 p.m., 2015) and 102–117 (8–11 p.m., 2016). The AQI during maximum NO₂ levels (peak hours) ranged between 0–50 µg/m³ (good) to 51–100 µg/m³ (unhealthy for sensitive group). The risk quotient (RQ) was calculated for average daily intake and average hourly intake of NO₂. RQ was found to be less than 1 (no potential health risk, lifetime and hourly) for all three years. However, increase in RQ value from 0.84 (2014) to 0.98 (2016) indicates increase in potential health risk. Hence, policy and measures should be adopted to reduce the potential health risk.

This study is very first of its kind for the area and hence can serve as reference study for future works. Further studies are required to assess air pollution in other seasons (summer, spring, autumn), impact of climatic condition and parameters on air quality. Also, for direct impact assessment number of cases attributed to air pollution needs to be investigated.

Understanding China's carbon dioxide (CO2) emission status is crucial for getting Carbon Neutrality status. The purpose of the paper is to calculate two possible scenarios for CO2 emission distribution and calculated input-output flows of CO2 emissions for every 31 China provinces for 2012, 2015 and 2017 years.

In this study using the input and output (IO) table's data for the selected years, the authors found the volume of CO2 emissions per one Yuan of revenue for the industry in 2012 and the coefficient of emission reduction compared to 2012.

Results show that in the industries with a huge volume of CO2 emissions, such as “Mining and washing of coal”, the authors cannot observe the reduction processes for years. Industries where emissions are being reduced are “Processing of petroleum, coking, nuclear fuel”, “Production and distribution of electric power and heat power”, “Agriculture, Forestry, Animal Husbandry and Fishery”. For the “construction” industry the situation with emissions did not change.

“Transport, storage, and postal services” and “Smelting and processing of metals” industries in China has the second place concerning emissions, but over the past period, emissions have been sufficiently reduced. “Construction” industry produces a lot of emissions, but this industry does not carry products characterized by large emissions from other industries. Authors can observe that Jiangsu produces a lot of CO2 emissions, but they do not take products characterized by significant emissions from other provinces. Shandong produces a lot of emissions and consumes many of products characterized by large emissions from other provinces. However, Shandong showed a reduction in CO2 emissions from 2012 to 2017.

This study aims at investigating how energy strategies of China impact its energy shipping import through a strategic maritime link, the Straits of Malacca and Singapore (SOMS).

Vector error-correction modelling (VECM) is applied to examine the key energy strategies of China influencing crude oil and liquefied natural gas (LNG) shipping import via the SOMS. Strategies investigated include oil storage expansions, government-setting targets to motivate domestic gas production, pipeline projects to diversify natural gas import routes and commercial strategies to ensure oil and gas accessibility and cost-effectiveness.

For the crude oil sector, building up oil storage and diversifying oil import means, routes and sources were found effective to mitigate impacts of consumption surges and price shocks. For the LNG sector, domestic production expansion effectively reduces LNG import. However, pipeline gas import growth is inefficient to relieve LNG shipping import dependency. Furthermore, energy companies have limited flexibility to adjust LNG shipping import volumes via the SOMS even under increased import prices and transport costs.

As the natural gas demand of China continues expanding, utilisation rates of existing pipeline networks need to be enhanced. Besides, domestic production expansion and diversification of LNG import sources and means are crucial.

This study is among the first in the literature using a quantitative approach to investigate how energy strategies implemented in a nation impact its energy shipping volumes via the SOMS, which is one of the most important maritime links that support 40% of the global trades.

This study aims to investigate a locating-routing-allocating problems and the supply chain, including factories distributor candidate locations and retailers. The purpose of this paper is to minimize system costs and delivery time to retailers so that routing is done and the location of the distributors is located.

The problem gets closer to reality by adding some special conditions and constraints. Retail service start times have hard and soft time windows, and each customer has a demand for simultaneous delivery and pickups. System costs include the cost of transportation, non-compliance with the soft time window, construction of a distributor, purchase or rental of a vehicle and production costs. The conceptual model of the problem is first defined and modeled and then solved in small dimensions by general algebraic modeling system (GAMS) software and non-dominated sorting genetic algorithm II (NSGAII) and multiple objective particle swarm optimization (MOPSO) algorithms.

According to the solution of the mathematical model, the average error of the two proposed algorithms in comparison with the exact solution is less than 0.7%. Also, the algorithms’ performance in terms of deviation from the GAMS exact solution, is quite acceptable and for the largest problem (N = 100) is 0.4%. Accordingly, it is concluded that NSGAII is superior to MOSPSO.

In this study, since the model is bi-objective, the priorities of decision makers in choosing the optimal solution have not been considered and each of the objective functions has been given equal importance according to the weighting methods. Also, the model has not been compared and analyzed in deterministic and robust modes. This is because all variables, except the one that represents the uncertainty of traffic modes, are deterministic and the random nature of the demand in each graph is not considered.

The results of the proposed model are valuable for any group of decision makers who care optimizing the production pattern at any level. The use of a heterogeneous fleet of delivery vehicles and application of stochastic optimization methods in defining the time windows, show how effective the distribution networks are in reducing operating costs.

This study fills the gaps in the relationship between location and routing decisions in a practical way, considering the real constraints of a distribution network, based on a multi-objective model in a three-echelon supply chain. The model is able to optimize the uncertainty in the performance of vehicles to select the refueling strategy or different traffic situations and bring it closer to the state of certainty. Moreover, two modified algorithms of NSGA-II and multiple objective particle swarm optimization (MOPSO) are provided to solve the model while the results are compared with the exact general algebraic modeling system (GAMS) method for the small- and medium-sized problems.