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This paper aims to propose a reasonable method to evaluate uncertainty of measurement of industrial robots’ orientation repeatability and solve the non-linear problem existing in its evaluation procedure.

Firstly, a measurement model of orientation repeatability, based on laser tracker, is established. Secondly, some factors, influencing the measurement result of orientation repeatability, are identified, and their probability distribution functions are modelled. Thirdly, based on Monte Carlo method, an uncertainty evaluation model and algorithm of measurement of industrial robot’s orientation repeatability are built. Finally, an industrial robot is taken as the research object to validate the rationality of proposed method.

Results show that the measurement model of orientation repeatability of industrial robot is non-linear, and the proposed method can reasonably and objectively estimate uncertainty of measurement of industrial robots’ orientation repeatability.

This paper, based on Monte Carlo method and experimental work, proposes an uncertainty evaluation method of measurement of industrial robots’ orientation repeatability which can solve the non-linear problem and provide a reasonable and objective evaluation. And the stochastic ellipsoid approach is firstly taken to model the repeatability of laser tracker. Additionally, this research is beneficial to decide whether the orientation repeatability of the industrial robot meets its requirements.

This paper aims to propose a four-point measurement model for directly measuring the pose (i.e. position and orientation) of industrial robot and reducing its calculating error and measurement uncertainty.

A four-point measurement model is proposed for directly measuring poses of industrial robots. First, this model consists of a position measurement model and an orientation model gotten by the position of spherically mounted reflector (SMR). Second, an influence factor analysis, simulated by Monte Carlo simulation, is performed to investigate the influence of certain factors on the accuracy and uncertainty. Third, comparisons with the common method are carried out to verify the advantage of this model. Finally, a test is carried out for evaluating the repeatability of five poses of an industrial robot.

In this paper, results show that the proposed model is better than the three-SMRs model in measurement accuracy, measurement uncertainty and computational efficiency. Moreover, both measurement accuracy and measurement uncertainty can be improved by using the proposed influence laws of its key parameters on the proposed model.

The proposed model can measure poses of industrial robots directly, accurately and effectively. Additionally, influence laws of key factors on the accuracy and uncertainty of the proposed model are given to provide some guidelines for improving the performance of the proposed model.

The purpose of this paper is to numerically investigate the effect of guide vane unsteady passing wake on the rotor blade tip aerothermal performance with different tip clearances.

The geometry and flow conditions of the first stage of GE-E3 high-pressure turbine have been used to obtain the blade tip three-dimensional heat transfer characteristics. The first stage of GE-E3 high-pressure turbine has 46 guide vanes and 76 rotor blades, and the ratio of the vane to the blade is simplified to 38:76 to compromise the computational resources and accuracy. Namely, each computational domain comprises of one guide vane passage and two rotor blade passages. The investigations are conducted at three different tip gaps of 1.0, 1.5 and 2.0 per cent of the average blade span.

The results show that the overall discrepancy of the heat transfer coefficient between steady results and unsteady time-averaged results is quite small, but the dramatic growth of the instantaneous heat transfer coefficient along the pressure side is in excess of 20 per cent. The change of the aerothermal performance is mainly driven by turbulence-level fluctuations of the unsteady flow field within gap regions. In addition, the gap size expansion has a marginal impact on the variation ratio of tip unsteady aerothermal performances, even though it has a huge influence on the leakage flow state within the tip region.

This paper emphasizes the change ratio of unsteady instantaneous heat transfer characteristics and detailed the mechanism of blade tip unsteady heat transfer coefficient fluctuations, which provide some guidance for the future blade tip design and optimization.

This study aims to the service life of TA15 alloy by solving the problem of the binding force between the matrix and AlTiSiN coating. The effect of a plasma nitriding (PN) interlayer on the magnetron-sputtered AlTiSiN coating was also investigated in detail.

The double-glow plasma alloying (DGPA) and magnetron sputtering (MS) techniques were combined as a new approach to realize a bilayer on TA15 consisting of an AlTiSiN layer with a PN interlayer. A TiN interlayer was formed via co-diffusion during the PN conducted at 1050°C for 3 h.

The PN interlayer can effectively improve the adhesion between coating and matrix; the PN/AlTiSiN coating presented excellent adhesion (80.1 N) and anti-wear property with a nano-hardness of 18.62 GPa. The resulting three-dimensional wear-track morphology exhibited a shallow depth and a narrow width.

The novel combination of the DGPA and MS technologies, using an infiltration layer rather than a coating one as the intermediate layer, can effectively enhance the adhesion between AlTiSiN coating and TA15 matrix. Meanwhile, the gradient layer can effectively improve both surface bearing and wear resistance.

This study aims to explore and clarify the mechanism by which cognitive heuristics influence strategic decision-making during the coronavirus disease 2019 (COVID-19) pandemic in an emerging economy.

Data collection was conducted through a survey completed by 213 top-level managers from firms located in the twin cities of Pakistan. A convenient, purposively sampling technique and snowball method were used for data collection. To examine the relationship between cognitive heuristics and strategic decision-making, hypotheses were tested by using correlation and regression analysis.

The article provides further insights into the relationship between cognitive heuristics and strategic decision-making during the COVID-19 pandemic. The results suggest that cognitive heuristics (under-confidence, self-attribution and disposition effect) have a markedly negative influence on the strategic decision-making during the COVID-19 pandemic in an emerging economy.

The article encourages strategic decision-makers to avoid relying on cognitive heuristics or their feelings when making strategic decisions. It provides awareness and understanding of cognitive heuristics in strategic decision-making, which could be very useful for business actors such as managers and entire organizations. The findings of this study will help academicians, researchers and policymakers of emerging countries. Academicians can formulate new behavioural models that can depict the solutions to dealing with an uncertain situation like COVID-19. Policymakers and strategic decision-making teams can develop crisis management strategies based on concepts from behavioral strategy to better deal with similar circumstances in the future, such as COVID-19.

The paper’s novelty is that the authors have explored the mechanism by which cognitive heuristics influence strategic decision-making during the COVID-19 pandemic in an emerging economy. It adds to the literature in strategic management, explicitly probing the impact of cognitive heuristics on strategic decision-making; this field is in its initial stage, even in developed countries, while little work has been done in emerging countries.

The peer review history for this article is available at https://publons.com/publon/10.1108/IJSE-10-2021-0636.

Chinese firms were operating within a closed economic environment before the “opening up” in the late 1970s, but it has only been in the late 1990s that China has recognized the importance of innovation. The Chinese government has attempted to rectify this liability by providing funding to assist Chinese firms in developing innovation capability by increasing R&D collaborations and employing external experts. The purpose of this paper is to study the innovation of Chinese firms by examining how internal and external resources interactively impact the innovation capability.

Panel data collected from Chinese manufacturers are used to test the hypothesized relationships.

The results have shown that the interplay between internal and external resources exhibits differential patterns of impact on innovation capability. The authors discover different moderating patterns of the two types of external resources: visiting experts are helpful in enhancing the effects of internal human resources, while R&D collaborations are useful in exploiting internal financial and physical resources, even when the main effect of financial resources on innovation capability is not significant.

The study contributes to the literature by providing empirical evidences on the roles of absorbed external resources and knowledge to catalyze internal resources in building up innovation capability in an emerging economy.

Despite their crucial role in sustaining national economies, small and medium enterprises (SMEs) are beset by the constraint of financing at better conditions. The purpose of this paper is to compare supply chain finance (SCF) solutions provided by commercial banks and financial service providers (FSPs) that help SMEs access financing.

This study looks at multiple case studies using in-depth interviews with focal firms (lenders) to answer the research questions. In-depth interviews were conducted with three Chinese FSPs and three commercial banks providing working capital to the same SMEs. The unit of analysis is SCF solutions that have made the companies competitive in the industry.

The case studies show that the acquisition of transaction information and business credit in SCF can reduce ex ante information asymmetry. SCF utilizing receivable transfers, closed-loop business, relational embeddedness, and a combination of outcome control and behavioral control can also reduce ex post information asymmetry. For these reasons, compared with commercial bank-dominated SCF, SCF adopted by FSPs in the supply chain can better reduce information asymmetry.

This study contributes to the emerging literature exploring the impact of SCF on SMEs accessing financing. In particular, this study provides supply chain management and operations insights on SCF and their consequent influence. Previous research has focused on the direct dyadic relationship between lenders and borrowers while neglecting supply chain effects. Uniquely, this study explores the different ways commercial banks and FSPs implement SCF solutions.

Prefabricated buildings (PBs) have proven to effectively mitigate carbon emissions in the construction industry. Existing studies have analyzed the environmental performance of PBs considering the shift in construction methods, ignoring the emissions abatement effects of the low-carbon practices adopted by participants in the prefabricated building supply chain (PBSC). Thus, it is challenging to exploit the environmental advantages of PBs. To further reveal the carbon reduction potential of PBs and assist participants in making low-carbon practice strategy decisions, this paper constructs a system dynamics (SD) model to explore the performance of PBSC in low-carbon practices.

This study adopts the SD approach to integrate the complex dynamic relationship between variables and explicitly considers the environmental and economic impacts of PBSC to explore the carbon emission reduction effects of low-carbon practices by enterprises under environmental policies from the supply chain perspective.

Results show that with the advance of prefabrication level, the carbon emissions from production and transportation processes increase, and the total carbon emissions of PBSC show an upward trend. Low-carbon practices of rational transportation route planning and carbon-reduction energy investment can effectively reduce carbon emissions with negative economic impacts on transportation enterprises. The application of sustainable materials in low-carbon practices is both economically and environmentally friendly. In addition, carbon tax does not always promote the implementation of low-carbon practices, and the improvement of enterprises' environmental awareness can further strengthen the effect of low-carbon practices.

This study dynamically assesses the carbon reduction effects of low-carbon practices in PBSC, informing the low-carbon decision-making of participants in building construction projects and guiding the government to formulate environmental policies.

This study is aimed at better understanding the evolution of inequality in carbon emission in intraincome and interincome groups in the world, and then to uncover the driving factors that affect inequality in carbon emission.

The approach is developed by combining the Theil index and the decomposition technique. Specifically, the Theil index is used to measure the inequality in carbon emissions from the perspective of global and each income group level. The extended logarithmic mean Divisia index was developed to explore the driving factors.

This study finds that the inequality in carbon emissions of intraincome group is getting better, whereas the inequality in carbon emission of interincome group is getting worse. And the difference in global carbon emissions between income groups is the main source of global carbon emission inequality, which is greater than that within each income group. In addition, the high-income group has transferred their carbon emissions to upper-middle income group by importing high-carbon-intensive products to meet the domestic demand, while lower-middle-income group do not fully participate in the international trade.

To alleviate the global carbon inequality, more attention should be paid to the inequality in carbon emission of interincome group, especially the trade between high-income group and upper-middle income group. From the perspective of driving factors, the impact of import and export trade dependence on the per capita carbon emissions of different income groups can almost offset each other, so the trade surplus effect should be the focus of each group.

In order to consider the impact of international trade, this study conducts a comprehensive analysis of global carbon emissions inequality from the perspective of income levels and introduces the import and export dependence effect and the trade surplus effect into the analysis framework of global carbon emission inequality drivers, which has not been any research carried out so far. The results of this paper not only provide policy recommendations for mitigating global carbon emissions but also provide a new research perspective for subsequent inequality research.

The purpose of this paper is to analyze the historical pattern of environmental cost due to grain production in China and to provide further implications of technologies and policies for the transformation of China’s agricultural development toward sustainable intensification.

The data sets about grain production, arable land and chemical fertilizer use in China were collected from FAO, NBSC, and IFA. Greenhouse gas emissions were estimated using life cycle assessments. The policies concerning grain production and the environment were collected from the Ministry of Agriculture, and the State Council of China.

China has produced enough food to feed its growing population, but has neglected the resource-environmental costs of grain production since 1978. Consequently, China’s grain production is always accompanied with a high cost of resource and environment sustainability. However, from 2006 to 2015, the growth rate of grain production has surpassed that of chemical fertilizer consumption, resulting in improvement in nutrient use efficiency and decreasing trends of environmental cost for grain production. This could be partially attributed to technology innovations, such as Soil-Testing and Fertilizer-Recommendations (STFR), soil quality and crop management improvement, and so on, and policy supports (policies of STFR, soil quality improvement, and high-yield construction). This indicated that China’s grain production is starting to transform from high-input and high-output model to “less for more.”

This study is the first to determine the detailed, historical role of technological innovation and agri-environmental policy on the sustainability of grain production in China. The findings should have significant implications for technology and policy for the transformation of China’s agriculture development to sustainable intensification.