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Software comes from India, hardware comes from China. Why is that? Why did China and India take such different paths to global dominance in new high-tech industries? Will their paths continue to diverge or converge? How can other countries learn from their successes – and failures – in reaching global scale in new industries? To answer these questions, this book presents the first rigorous comparison of the growth of the IT industries in China and India, based on interviews with over 300 companies. It explains the different growth paths of the software and hardware sectors in each country, providing insights into the factors behind the emergence of China and India as global economic powers. It provides a compelling case study of how differences in economic policies and the investment climate affect industrial growth. This book sheds new light on common debates on 'China versus India', on why India is the software capital of the world while China is a manufacturing powerhouse. It refutes common myths about the growth of these industries – for example, the role of Non-Resident Indians or the Y2K problem in the growth of the Indian software industry, the role of government intervention in industrial growth, and the relative size of China and India's software industries.

Software comes from India, hardware comes from China. Why is that? Why did China and India take such different paths to global dominance in new high-tech industries? Will their paths continue to diverge or converge? How can other countries learn from their successes and failures in reaching global scale in new industries? To answer these questions, this book presents the first rigorous comparison of the growth of the IT industries in China and India, based on interviews with over 300 companies. It explains the different growth paths of the software and hardware sectors in each country, providing insights into the factors behind the emergence of China and India as global economic powers. It provides a compelling case study of how differences in economic policies and the investment climate affect industrial growth. This book sheds new light on common debates on \"China versus India\", on why India is the software capital of the world while China is a manufacturing powerhouse. It refutes common myths about the growth of these industries for example, the role of Non-Resident Indians or the Y2K problem in the growth of the Indian software industry, the role of government intervention in industrial growth, and the relative size of China and India's software industries.

Purpose This paper aims to investigate how knowledge sharing influences technological innovation capability (TIC) of the software small- and medium-sized enterprises (SSMEs). Design/methodology/approach Based on the theories regarding knowledge management, TIC, software engineering and open innovation, this paper constructed a research model comprising factors affecting knowledge sharing, knowledge sharing and TIC, and then tested the model quantitatively. The study focuses on SSMEs in China collecting 457 online questionnaires and uses a structural equation model to test the hypotheses. Findings The knowledge sharing culture, organizational structure, middle-level leadership and management system have significantly positive effects on tacit knowledge sharing; management system and IT support have significantly positive effects on explicit knowledge sharing; both explicit and tacit knowledge sharing have significantly positive effects on TIC. Research limitations/implications The study enriches the research on knowledge sharing and TIC. However, it does not consider factors affecting knowledge sharing at the non-organizational level or the interaction between explicit and tacit knowledge sharing. Practical implications The study offers several recommendations/suggestions for helping SSMEs to promote and implement explicit or tacit knowledge sharing and TIC. Originality/value This paper examines the impact of knowledge sharing on TIC from the perspective of knowledge management deconstructing knowledge sharing from the epistemological dimension and the TIC of software companies on the basis of software engineering theory. It provided a new theoretical perspective for the research of knowledge management and technological innovation management in SSMEs.

As the world's largest coal producer, China was accounted for about 46% of global coal production. Among present coal mining risks, methane gas (called gas in this paper) explosion or ignition in an underground mine remains ever-present. Although many techniques have been used, gas accidents associated with the complex elements of underground gassy mines need more robust monitoring or warning systems to identify risks. This paper aimed to determine which single method between the PCA and Entropy methods better establishes a responsive weighted indexing measurement to improve coal mining safety. Qualitative and quantitative mixed research methodologies were adopted for this research, including analysis of two case studies, correlation analysis, and comparative analysis. The literature reviewed the most-used multi-criteria decision making (MCDM) methods, including subjective methods and objective methods. The advantages and disadvantages of each MCDM method were briefly discussed. One more round literature review was conducted to search publications between 2017 and 2019 in CNKI. Followed two case studies, correlation analysis and comparative analysis were then conducted. Research ethics was approved by the Shanxi Coking Coal Group Research Committee. The literature searched a total of 25,831publications and found that the PCA method was the predominant method adopted, and the Entropy method was the second most widely adopted method. Two weighting methods were compared using two case studies. For the comparative analysis of Case Study 1, the PCA method appeared to be more responsive than the Entropy. For Case Study 2, the Entropy method is more responsive than the PCA. As a result, both methods were adopted for different cases in the case study mine and finally deployed for user acceptance testing on 5 November 2020. The findings and suggestions were provided as further scopes for further research. This research indicated that no single method could be adopted as the better option for establishing indexing measurement in all cases. The practical implication suggests that comparative analysis should always be conducted on each case and determine the appropriate weighting method to the relevant case. This research recommended that the PCA method was a dimension reduction technique that could be handy for identifying the critical variables or factors and effectively used in hazard, risk, and emergency assessment. The PCA method might also be well-applied for developing predicting and forecasting systems as it was sensitive to outliers. The Entropy method might be suitable for all the cases requiring the MCDM. There is also a need to conduct further research to probe the causal reasons why the PCA and Entropy methods were applied to each case and not the other way round. This research found that the Entropy method provides higher accuracy than the PCA method. This research also found that the Entropy method demonstrated to assess the weights of the higher dimension dataset was higher sensitivity than the lower dimensions. Finally, the comprehensive analysis indicates a need to explore a more responsive method for establishing a weighted indexing measurement for warning applications in hazard, risk, and emergency assessments.

Along with the rapid development of the global digital economy, China is experiencing profound transformations in industrial digitization. These transformations may significantly affect the urban-rural income gap. Using panel data from 30 Chinese provinces from 2012 to 2022, this paper empirically examined the impact of industrial digitalization on the urban-rural income gap based on a fixed-effects model. The findings reveal that the development of industrial digitalization in China widens the urban-rural income gap. Mechanism analysis indicates that industrial digitalization increases software business revenue and employment in the information services sector, thereby expanding the urban-rural income gap; additionally, industrial digitalization widens the income gap between urban migrants and rural migrant populations, further increasing the overall urban-rural income disparity. Heterogeneity analysis demonstrates that in the eastern region, industrial digitalization significantly enlarges the urban-rural income gap, whereas its effects are not significant in the central and western regions. The conclusions of this study provide empirical support and policy insights for China in advancing industrial digitalization and promoting common prosperity.

At present, China is in the rapid development stage of urbanization, and construction activities are becoming more frequent. This is accompanied by a large amount of construction and demolition waste (C&DW), which raises many problems with its governance, such as occupying valuable land resources, causing air pollution, and consuming raw materials. In this study, taking Guangzhou as an example, the system dynamics principle was used to establish an environmental assessment model of C&DW, and Vensim software was used to simulate and analyze the environmental, economic, and social impacts of various disposal methods of C&DW. The results showed that (1) among all waste disposal methods, landfill disposal had the highest greenhouse gas emissions. It was estimated that the greenhouse gas emissions from landfill disposal will account for 75% of the total emissions in 2030, while the greenhouse gas emissions from recycling disposal will only account for 0.5%. (2) The simulation results showed that, according to the current data, the land area occupied by waste landfills and illegal dumping in 2030 will be about 4.88 million m 2 , and the economic loss caused by land loss and global warming will account for 9.1% of Guangzhou’s GDP in 2030, which is equivalent to the national economy of a regional city with a less developed economy. (3) Enhanced supervision could significantly reduce the amount of illegal dumping, but its effect on landfill disposal and recycling would be very limited. According to the results of the simulation analysis, some suggestions were put forward to improve the environmental, economic, and social impact of C&DW disposal in Guangzhou.

Since digital piracy has posed a significant threat to the development of the software industry and the growth of the digital media industry, it has, for the last decade, held considerable interest for researchers and practitioners. This article will propose an integrated model that combines the theory of planned behavior (TPB) and ethics theory, the two theories that are most often used in digital piracy studies. Data were obtained from university students in China, and the model was examined using the structural equation model (SEM). The results show that moral obligation and justice, derived from ethics theories and TPB variables, such as attitude, subjective norms, and perceived behavioral control, influence the behavioral intentions of individuals to commit digital piracy. The attitude of individuals toward digital piracy is also found to be influenced by perceived benefits, perceived risk, and habit.

Data centers are becoming considerably more significant and energy-intensive due to the exponential growth of cloud computing. Cloud computing allows people to access computer resources on demand. It provides amenities on the pay-as-you-go basis across the data center locations spread over the world. Consequently, cloud data centers consume a lot of electricity and leave a proportional carbon impact on the environment. There is a need to investigate efficient energy-saving approaches to reduce the massive energy usage in cloud servers. This review paper focuses on identifying the research done in the field of energy consumption (EC) using different techniques of machine learning, heuristics, metaheuristics, and statistical methods. Host CPU utilization prediction, underload/overload detection, virtual machine selection, migration, and placement have been performed to manage the resources and achieve efficient energy utilization. In this review, energy savings achieved by different techniques are compared. Many researchers have tried various methods to reduce energy usage and service level agreement violations (SLAV) in cloud data centers. By using the heuristic approach, researchers have saved 5.4% to 90% of energy with their proposed methods compared with the existing methods. Similarly, the metaheuristic approaches reduce energy consumption from 7.68% to 97%, the machine learning methods from 1.6% to 88.5%, and the statistical methods from 5.4% to 84% when compared to the benchmark approaches for a variety of settings and parameters. So, making energy use more efficient could cut down the air pollution, greenhouse gas (GHG) emissions, and even the amount of water needed to make power. The overall outcome of this review work is to understand different methods used by researchers to save energy in cloud data centers.

Media censorship is a hallmark of authoritarian regimes. We conduct a field experiment in China to measure the effects of providing citizens with access to an uncensored internet. We track subjects’ media consumption, beliefs regarding the media, economic beliefs, political attitudes, and behaviors over 18 months. We find four main results: (i) free access alone does not induce subjects to acquire politically sensitive information; (ii) temporary encouragement leads to a persistent increase in acquisition, indicating that demand is not permanently low; (iii) acquisition brings broad, substantial, and persistent changes to knowledge, beliefs, attitudes, and intended behaviors; and (iv) social transmission of information is statistically significant but small in magnitude. We calibrate a simple model to show that the combination of low demand for uncensored information and the moderate social transmission means China’s censorship apparatus may remain robust to a large number of citizens receiving access to an uncensored internet.