Does internationalization encourage state-owned enterprises to utilize subsidies to innovate? Evidence from high-tech and automobile manufacturing industries of Chinese listed companies

Purpose Drawing on the resource-based view, institutional logic and isomorphic pressure theories, this study constructed a theoretical model to explore the correlations between government subsidies and innovation performance. Particularly, this study aims to investigate the moderating effects of ownership types and degree of internationalization on these relationships. Design/methodology/approach To empirically test the relationships, the authors use panel data from high-tech manufacturing and automobile manufacturing industries in Chinese A stock listed companies for the period 2011–2015 and performed regression analysis. Findings Results indicate that government subsidies positively enhance enterprises’ innovation performance; there is a big gap between government subsidies’ incentive effect on innovation performance between state-owned enterprises (SOEs) and private-owned enterprises (POEs); with the improvement of internationalization, the promotion effect of government subsidies on enterprise innovation performance is strengthened; there is a three-way interaction between government subsidies, degree of internationalization and ownership types, such that in the presence of a low degree of internationalization, there is a big gap in the incentive effect of government subsidies on the innovation performance of SOEs and POEs; in the presence of a high degree of internationalization, the gap is significantly reduced. Originality/value This is an empirical study on the impact mechanism of ownership types and internationalization on the relationship between government subsidies and innovation performance in China. It provides valuable insights to show how internationalization can dramatically improve SOEs’ efficiency disadvantages in the allocation of government subsidies to innovation activities.

Strategic sourcing model for green supply chain management: an insight into automobile manufacturing units in India

PurposeSupplier selection (SS) is one of the prime competencies in a sourcing decision. Taking into account the key role played by suppliers in facilitating the implementation of green supply chain management (GSCM), it is somewhat surprising that very little research attention has been imparted to the development of a strategic sourcing model for GSCM. This research aims to develop a strategic sourcing framework in which supplier organizations are prioritized and ranked based on their GSCM performance. Accordingly, the benchmark organization is identified and its strategy is explored for GSCM performance improvement.Design/methodology/approachThe research develops an innovative GSCM performance evaluation framework using six parameters, namely, investment in corporate social responsibility, investment in research and development, utilization of renewable energy, total energy consumption, total carbon-di-oxide emissions and total waste generation. An integrated multicriteria decision-making (MCDM) approach is proposed in which the entropy method calculates criteria weights. The Complex Proportional Assessment (COPRAS) and the Grey relational analysis (GRA) methods are used to rank supplier organizations based on their performance scores. A real-world case of green supplier selection (GSS) is considered in which five leading India-based automobile manufacturing organizations (Supplier 1, Supplier 2, Supplier 3, Supplier 4 and Supplier 5) are selected. Surveys with industry experts at the strategic, tactical, and operational levels are carried out to collect relevant data.FindingsThe results reveal that total carbon dioxide emission is the most influential parameter, as it gains the highest weight. On the contrary, investment in research and development, and total waste generation have no significant impact on GSCM performance. Results show that Supplier 5 secures the top rank. Hence, it is the benchmark organization.Research limitations/implicationsThe proposed methodology offers an easy and comprehensive approach to sourcing decisions in the field of GSCM. The entropy weight-based COPRAS and GRA methods offer an error-free channel of decision-making and can be proficiently used to outrank various industrial sectors based on their GSCM performances. This research is specific to the automobile manufacturing supply chain. Therefore, research outcomes may vary across supply chains with distinct characteristics.Practical implicationsThe basic propositions of this research are based on a real-world case. Hence, the research findings are practically feasible. The less significant parameters identified in this study would enable managers to impart more attention to vulnerable areas for improvement. This research may help policymakers identify the influential parameters for effective GSCM implementation. As this research considers all aspects of sustainability, the strategies of the benchmark supplier have a direct impact on organizations' overall sustainability. The study would enable practitioners to make various strategies for GSCM performance improvement and to develop a cleaner production system.Originality/valueThe originality of this research lies in the consideration of both economic, social, environmental and operational aspects of sustainability for assessing the GSCM performance of supplier organizations. Quantitative criteria are considered so that vagueness can be removed from the decision. The use of an integrated grey-based approach for developing a strategic sourcing model is another unique feature of this study.

Effect of Compressive Strain Rate on Microstructure and Mechanical Properties of 7050 Aluminium Alloy

7050 aluminium alloy is a superior material used in the areas of aerospace and automobile manufacturing. In this work, homogeneous cast cylinder samples of 7050 aluminium alloy with size of Φ80 mm × 100 mm were compressed isothermally at 350°C with compressive strain rate of 0.1 s−1,1 s−1, and 10 s−1, respectively. The samples were then processed into standard tensile specimens, and then tensile testing was done by using the GL8305 universal testing machine. The grain sizes and fracture morphology were analyzed by the SEM observation and cellular automaton (CA) method. The effect of compressive strain rate on microstructure and mechanical properties of 7050 aluminium alloy was investigated. The results show the following. (1) Grain refinement occurred after compression. The grain sizes of the samples decrease with the decrease of compressive strain rate. The grain sizes in the radial edge and the axial center of the cylinder samples are the smallest. (2) The tensile strength and breaking elongation rate were improved when compared to the original alloy. The mechanical properties of samples compressed with compressive strain rate of 0.1 s−1 are the best. (3) The fracture morphology of the samples shows that the fracture of the samples is ductile fracture. The sizes and depths of dimples increased with the decrease of grain sizes.

Research on Carbon Emissions of Electric Vehicles by Constructing Mathematical Model Based on Big Data

After the “3060” carbon peak and neutrality strategic goal was put forward, various industries actively responded to find new ways for energy conservation and emission reduction. In the field of automobile manufacturing, the transition from traditional fuel vehicles to electric vehicles is an inevitable trend. This paper builds a mathematical model that uses the three major indicators of carbon emissions per 100 kilometers, energy-saving emission reduction coefficients, and annual carbon emissions as parameters to measure carbon emissions benefits, and combines survey data to conduct empirical analysis to explore the advantages of electric vehicles in energy saving and emission reduction compared with traditional fuel vehicles under different power supply structures. At the same time, based on the existing data and conclusions, the research is extended to the analysis of carbon emissions prospects in decades, and the possible contribution of future electric vehicles in energy utilization and environmental protection is predicted, to explore its role in promoting the achievement of the double-carbon goal, and put forward corresponding recommendations based on the research results.

Safety and Ergonomics Risk Assessment (SERA): A Customized Ergonomics Assessment Tool for Automobile Manufacturing

Musculoskeletal disorders continue to be a leading source of lost workdays across all industries. Common ergonomics assessment tools may include criteria extraneous to the stresses at specific companies or industries. Therefore, the creation of assessment tools, based on scientifically validated methods, with industry- or company-specific stresses may be of benefit. The BMW Group has developed the Safety and Ergonomics Risk Assessment (SERA) tool. This ergonomics assessment method incorporates the most up-to-date scientific methods and international standards, and is used worldwide in all production facilities of the BMW Group. As noted above, a major advantage of SERA over conventional ergonomics tools is the focus on ergonomics stresses common to automobile manufacturing and the consequent exclusion of irrelevant parameters, thereby reducing the time, effort, and training required for workplace assessments. Other advantages include the international uniformity of assessments and a web- and database-implementation allowing for easily comparable international reporting. The implementation of this method at the BMW Group has enabled a greater transparency for ergonomics across all international plants, and more effective and targeted ergonomics interventions. This publication will outline the basic motivation for SERA, highlight the relevant scientific sources and international standards, and general steps of an evaluation.

Calibration of Parallel Kinematic Machine Based on Stewart Platform – A Literature Review

Stewart platform-based Parallel Kinematic Machines (PKM) have been extensively studied by researchers due to their inherent finer control characteristics. This has opened its potential deployment opportunities in versatile critical applications like the medical field, engineering machines, space research, electronic chip manufacturing, automobile manufacturing, etc. All these precise, complicated, and repeatable motion applications require micro and nano-scale movement control in 3D space; a 6-DOF PKM can take this challenge smartly. For this, the PKM must be more accurate than the desired application accuracy level and thus proper calibration for a PKM robot is essential. Forward kinematics-based calibration for such hexapod machines becomes unnecessarily complex and inverse kinematics complete this task with much ease. To analyze different techniques, an external instrument-based, constraint-based, and auto or self-calibration-based approaches have been used for calibration. This survey has been done by reviewing these key methodologies, their outcome, and important points related to inverse kinematic-based PKM calibrations in general. It is observed in this study that the researchers focused on improving the accuracy of the platform position and orientation considering the errors contributed by a single source or multiple sources. The error sources considered are mainly structural, in some cases, environmental factors are also considered, however, these calibrations are done under no-load conditions. This study aims to understand the current state of the art in this field and to expand the scope for other researchers in further exploration in a specific area.

INNOVATIVE SUPPLY CHAIN SOLUTION FOR INDIAN AUTOMOBILE MANUFACTURING SECTOR: A CASE STUDY

In Indian Automobile Industry for heavy & commercial vehicle segment, manufacturers always face the major problem of supply chain management. As manufacturer follows any kind of solution scheme, they do not find very improved results, so for Indian condition an innovative solution of supply chain is required. The study is based on using In Bound & Out Bound Strategy together providing an edge to come over the Supply chain management problem.