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The Current Status and Developing Trends of Industry 4.0: a Review

• Published: 09 November 2021

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• Yang Lu   ORCID: orcid.org/0000-0002-3027-3064 1  

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The core concept of Industry 4.0 is to integrate advanced information technologies, especially emerging technologies, such as the Internet of Things, 5G & 6G, data analytics and management, artificial intelligence, cloud computing, and blockchain, to achieve a consistent transformation and upgrade of manufacturing and to reshape the value chain of industry and society. More research focuses on the integration of informatization and industrialization, the digital integration and governance of the industry, and specific technical and operational objects. This paper conducts a survey trying to depict an overview of Industry 4.0, specifically a bibliographic analysis, the extant review and status, the enabling technologies, the major drivers, implementing policies in major countries, and developing trends and challenges. Furthermore, the next generation of industrial revolution Industry 5.0 is discussed. This study theoretically and practically provides a good foundation of the industrial revolution from the information systems perspective.

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Lu, Y. The Current Status and Developing Trends of Industry 4.0: a Review. Inf Syst Front (2021). https://doi.org/10.1007/s10796-021-10221-w

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DOI : https://doi.org/10.1007/s10796-021-10221-w

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KEY TAKEAWAYS

Key takeaways.

Key Takeaways 1

Introduction . 2

IT in the U.S. Economy 4

Total Jobs, Including the Mulitplier 6

Share of Traded Sectors 7

Good Jobs, Including for Non-College-Educated Workers 9

Use of IT by Other Industries 10

IT-Intensive Industries and Inflation . 10

Conclusion . 11

Appendix 1: Methodology 12

Appendix 2: Differences Between This ITIF Report and the Commerce Department’s Digital Economy Report 15

Endnotes 16

Introduction

Industries vary in the relative contributions they make to national economies: Some pay their workers more than others do. Some raise their prices more slowly than others do—or even reduce their prices over time. Some export, which expands their production and shifts the overall economy toward greater competitiveness and productivity, enabling average workers to better afford imports. And some innovate more than others, thereby driving economic growth and improving people’s quality of life. [1] America’s IT industry has all these qualities: high pay, low price inflation for consumers, strong exports, and superior innovation. This report relies on the latest data available from the federal government to examine the key role and contributions of the IT industry in the U.S. economy. Appendix 1 describes the methodology.

The U.S. IT sector (which many refer to as the “tech sector”) includes industries such as computing, data storage and processing, IT components, information services, semiconductors, and software. The sector employed 5.9 million workers in 2020, accounting for 4.4 percent of U.S. private sector jobs. [2] These workers earned more than double the average U.S. wage. [3] Taking into account the multiplier effect, the industry supports 19 percent of all U.S. jobs. [4]

The IT sector also is an important source of well-paying jobs for non-college-educated Americans. The sector pays such workers approximately 50 percent more than do non-IT industries. [5]

Importantly, the lion’s share of the sector is globally traded, meaning it exports products and services and competes with production from other countries. As a share of U.S. industries that compete in the global economy, the IT sector accounts for 28 percent of establishments, 22.4 percent of jobs, and 30.7 percent of payroll expenditures. [6] But given the ferocity of the global competition for leadership in the IT sector, the United States should take none of this for granted.

Finally, the IT sector is important not just because of its direct impact on the economy in terms of jobs and income, but also because of its indirect effect on organizations using IT to improve quality and productivity, whether they are for-profit companies, nonprofits, or governments. This is why there is a modest negative correlation between an industry’s use of IT and inflation over the last decade. In other words, industries that use more IT raise prices at half the rate than does the overall economy—and those savings are then passed onto American consumers.

More broadly, the nation’s most strategically important industries have three main characteristics—they are driven by advanced technologies, they are globally traded sectors, and they serve the dual purpose of contributing to both economic and national security—and even among the select group that meet those criteria, the IT sector is a standout for the United States, punching 35 percent above its weight in the global marketplace. That is, the U.S. IT sector represented nearly one-third of the global IT market in the most recent comparative data available from the OECD (32.1 percent), which was 35 percent higher than the U.S. share of the overall global economy. [7]

This is a telling measure of industry concentration known as location quotient (LQ), and as shown in figure 1, the trend line for the U.S. IT sector has been distinctly positive in recent decades: Its relative global market share went from 1.08x in 1995 (i.e., 8 percent higher than the size-adjusted average among 66 countries in the OECD’s dataset) to 1.35x in 2018 (or 35 percent above the relative average). In fact, if not for the IT sector’s contribution, America’s most strategically important advanced industries as a group would have receded precipitously in that period in the face of surging competition, particularly from China. The IT sector thus represents a core strength that U.S. policymakers should not take lightly.

Figure 1 : U.S. performance in advanced industry sectors [8]

Figure 2 further underscores the IT sector’s growing importance in the U.S. economy. Among strategically important advanced industries, it has stood out in recent decades as a particularly high performer—important not just for its size, but also for its growth relative to the rest of the economy. In other words, the United States—still the world’s largest economy, and among the most diversified—is becoming increasingly specialized in IT.

Figure 2 : Change in relative concentration of advanced industries in the U.S. economy, 1995–2018 (scaled to production output in 2018) [9]

IT in the U.S. Economy

In 2020, there were 275,859 IT industry establishments in the United States with a total annual payroll of $722 billion. [10]

Moreover, the sector is a source of well-paying jobs for Americans. In 2020, the average annual compensation per worker in the IT industry was $122,270, 117 percent more than the average U.S. private sector wage. [11] The Department of Commerce’s new report on the digital economy finds that from 2012 to 2020, the nominal compensation for digital economy workers grew at an average annual rate of 6.0 percent. [12] From 2019 to 2020, the average nominal compensation saw an even larger growth of 7.3 percent. [13] This report includes fewer industries than does the Commerce report. See appendix 2 for an explanation of the differences in methodology between the Department of Commerce and ITIF.

In 2020, the industry employed 5.9 million workers. [14] From 2017 to 2020, IT jobs grew more than twice as fast as total U.S. private sector jobs did (10.7 percent vs. 4.3 percent). [15] Jobs in IT hardware grew by 1.5 percent, in part because of faster productivity growth, while jobs in IT services and software grew by 12.4 percent. [16] Using a more expansive measure of the digital economy—which includes much of retail that uses e-commerce, telecommunication services, and some entertainment services—the Department of Commerce report shows the industry employed 7.8 million workers in 2020. [17]  

Figure 3 : IT industry’s share of the total U.S. economy [18]

Using the ITIF industry definition, in 2020, the IT sector accounted for 3.5 percent of all business establishments and 4.4 percent of private sector employees, meaning the average IT firm was about 27 percent larger than the average private sector firm. [19] However, because the IT industry pays so well, it accounted for 9.5 percent of all private sector wages. [20] (See figure 3 ).

As a measure of industry contribution to the economy, the most accurate measure is value added, the result of subtracting the cost of purchased inputs (e.g., raw materials, energy, etc.) from final sales. In 2020, the IT industry generated $1.2 trillion in domestic value added, approximately 5.5 percent of the U.S. economy. [21] Value added in the IT sector grew by $600 billion (109 percent) from 2010 to 2020, with data processing, Internet publishing, and other information services growing the fastest at 215.1 percent. [22] Overall, U.S. gross domestic product (GDP) grew 39 percent over the same period. [23]

The Department of Commerce found that the digital economy accounted for 10.2 percent ($2.14 trillion of value added) of U.S. GDP in 2020. [24] According to the Department, from 2012 to 2020, the digital economy’s average real (inflation-adjusted) annual growth in value added was 6.3 percent. [25] The Department’s data also highlights that the digital economy’s real value added grew 151.4 percent from 2005 to 2020. [26] (See figure 4.)

Figure 4 : Commerce Department estimates of growth in real value added in the digital economy, 2005–2020 [27]

Finally, while U.S. government data on exports is limited, export data was available for 11 of 22 IT industries. [28] These industries collectively exported $301 billion worth of IT goods in 2020. [29] Despite only making up 11 of the 112 total categories in exports, the IT industry contributed 21.2 percent to the economy’s goods exports in 2020. [30] Furthermore, the Bureau of Economic Analysis has estimated that the IT industry exported $83.9 billion worth of information and communications technology services in 2020. [31]

Total Jobs, Including the Mulitplier

The impact of the IT sector on U.S. jobs and output goes far beyond just the sector. The IT sector purchases goods and services supplied by other industries to support its core activities, which in turn creates output and jobs. In addition, IT workers spend their earnings, which creates what are called “ induced jobs .”

The sector employed 5.9 million workers in 2020. [32] When the multiplier effect—which accounts for the estimated number of supplier and induced jobs an industry contributes—is taken into consideration, the IT sector also supported an estimated 10.7 million domestic supplier jobs and 8.7 million induced jobs that year. [33] (See figure 5.) Overall, in 2020, the IT sector supported a total of 25.3 million jobs, or 19 percent of private sector employment. [34]

Figure 5 : IT-supported jobs as a share of U.S. private sector employment, 2020 [35]

Share of Traded Sectors

While comparisons with the overall economy are useful, it is important to compare the IT sector with other industries that are also globally traded. The reason is simple: The United States does not have to worry about losing its barbershop or dry-cleaning industries to foreign competition, as Americans can only patronize barbers or dry cleaners in the United States. But globally traded sectors, such as computer production, software publishing, and automobile production, can be lost to foreign competitors, in which case the number of good jobs is reduced, the trade deficit worsens, and the value of the dollar goes down.

Moreover, changes in traded sector output and jobs have multiplier effects on overall domestic output while changes in nontraded sectors do not. At the regional level, this is why mayors and governors welcome job creation from traded sectors such as IT hardware and software. These industries bring money to the local or state economy, and the companies and their workers spend that money locally, creating even more jobs. As such, traded sector growth provides multiplier effects nontraded sectors do not. Expanding output in nontraded sectors such as barber shops or hospitals generally does not lead to the net increases in indirect and induced jobs that expanding output in traded sectors lead to.

This is why the Bay Area Technology Council found, “For each job created in the local high-tech sector, approximately 4.4 jobs are created in the local non-tradable sector in the long run. These jobs could be for lawyers, dentists, schoolteachers, cooks, or retail clerks. In short, the income generated by high-tech industries spurs a high rate of economic activity that supports local jobs.” [36] The multiplier is high because the high levels of disposable income these workers have create jobs in other sectors, including nontraded jobs. Moreover, IT companies buy inputs, which also supports jobs.

As discussed in appendix 1, ITIF classified all private sector enterprises as either traded or nontraded. In 2020, the IT sector accounted for 22.4 percent of the traded sector’s employees and 28 percent of its establishments. [37] (See figure 6.) In addition, the IT industry accounted for almost one-quarter (24.4 percent) of U.S. traded sector value added in 2020. [38]

Figure 6 : IT sector as a share of all U.S. traded sectors [39]

The IT industry accounted for almost one-quarter (24.4 percent) of the U.S. traded sector value added and 30.7 percent of the traded sector’s payroll.

Relative to other traded sectors, the IT sector offers higher wages, with average pay per employee 69 percent higher than the remaining traded sector’s pay per employee. [40] While it accounted for 22.4 percent of jobs, due to its high wages per employee, the sector accounted for 30.7 percent of the traded sector payroll. [41] In other words, the IT industry generates more national income per worker. [42]

Good Jobs, Including for Non-College-Educated Workers

The IT sector provides not only jobs but also good jobs, including for non-college-educated workers. For example, the software publishers industry pays the highest wages to non-college-educated workers of any industry. [43] While the software publishers industry employs a lower percentage of workers without college degrees—18.1 percent compared with 65 percent for all industries—these workers earn an average annual salary of $94,875, which is more than 2.5 times the group’s national average in 2019 ($35,915). [44] Moreover, the software publishers industry’s wages for non-college-educated workers are even greater than the average for all workers with at least a bachelor’s degree in the economy received in 2019 ($80,638). [45] In other words, an average non-college-educated worker in the software sector can potentially earn more than a college-educated worker in the overall economy. This is likely due partly to the fact that some workers in the industry have strong programming skills but no college degree and partly that there is an overall shortage of software workers, regardless of their level of education.

Non-college-educated workers in the IT sector can earn more than college-educated workers in the overall economy.

The IT industry employs a smaller share of workers with less than a college degree (35.6 percent) compared with all industries (64.6 percent). [46] However, the average wage for workers without a college degree in the IT industry is $53,023—50.1 percent more than the non-IT industry average of $35,320. [47] Moreover, the salary gap between IT industries and the rest of the economy is increasing: In 2008, salaries for non-college-educated workers were 49.9 percent larger in IT industries than in non-IT industries, compared with 50.1 percent in 2019. [48] Table 1 lists the seven high-tech IT industries that pay non-college workers at least 50 percent more than the non-college-educated national average salary of $35,915 in 2019. [49]

Table 1 : Employment and wages of workers without college degrees in seven IT industries, 2019 [50]

Use of IT by Other Industries

Many industries across the U.S. and global economies utilize IT goods and services as key inputs in their production process. For example, thanks to IT agriculture has become more productive, using GPS-enabled farm equipment, soil sensors, and AI-powered analytics. According to the Bureau of Economic Analysis, the top 10 IT-intensive industries (industries that use the largest amount of IT intermediates as a share of their overall inputs) in the economy are:

▪ printed circuit assembly (electronic assembly) manufacturing;

▪ electronic computer manufacturing;

▪ electronic and precision equipment repair and maintenance;

▪ all other miscellaneous electrical equipment and component manufacturing;

▪ motor vehicle electrical and electronic equipment manufacturing;

▪ computer storage device manufacturing;

▪ semiconductor machinery manufacturing;

▪ audio and video equipment manufacturing;

▪ computer terminals and other computer peripheral equipment manufacturing; and

▪ federal general government (nondefense). [51]

These 10 IT-intensive industries, which make up 1.7 percent of the overall economy’s output, purchased approximately $40.4 billion in IT goods and services in 2019, with the industries making up about 10.2 percent of the economy’s use of IT intermediates in production. [52] They also spent the most on the following IT intermediates: semiconductor and related device manufacturing; other electronic computer manufacturing; audio and video equipment manufacturing; and computer systems design services. [53] As a result of the intensive use of these four IT intermediates by other industries, they collectively contributed 0.7 percent to the share of output in the economy. [54] Computer systems design services contributed the highest share of 0.4 percent to the economy’s total output in 2019. [55]

Furthermore, the IT industry contributed 0.35 percentage points to the economy’s value-added percentage growth (2.14 percent) in 2019 as either capital or physical assets used by other industries in their production process. [56] IT hardware and software contributed about 0.12 percentage points and 0.23 percentage points, respectively. [57]

IT-Intensive Industries and Inflation

Because of its impact on improving quality and boosting efficiency, IT has long been deflationary. As an indication of the scale of that effect, consider that in 33 IT industries for which data is available, the average producer price index (PPI) rose 5.4 percent from 2012 to 2022, whereas the average PPI for all commodities rose 40.9 percent in the same period. [58] (See figure 7.) In other words, IT-based goods and services have been getting significantly cheaper compared with the rest of the economy.

Figure 7 : Average 20-year increase in producer price index (PPI), 2012–2022

Not only have the prices of IT goods and services increased more slowly than inflation, but industries that use more IT as a share of their inputs tend to increase prices more slowly.

Not only have the prices of IT goods and services increased more slowly than inflation, but industries that use more IT as a share of their inputs tend to increase prices more slowly. The Bureau of Labor Statistics has data on the top 15 of 19 IT-intensive industries. [59] These 15 industries saw an average one-year percentage change in the January 2022 PPI of 5.5 percent, compared with a 1-year change in the overall final demand PPI of 10.1 percent. [60] The correlation between the total share of IT intermediates used by an industry and the 10-year change in PPI was -0.18 percent. [61] In other words, the more IT an industry used the lower its price increases were.

America’s IT sector stands out as one of the country’s most strategically important advanced industries, making outsized contributions to the broader U.S. economy in numerous ways. It is a job creator—not just in the IT sector itself, and not just for computer scientists and engineers, but also for non-college-educated workers and as a force multiplier for job creation throughout the economy. Critically, the IT sector is also globally competitive. It accounts for one-quarter of U.S. traded-sector value-added, and it commands 35 percent higher market share globally than the U.S. economy as a whole.

In the information-driven digital economy, the IT sector’s products and services are essential tools of production for companies and organizations in all other sectors of the economy, powering growth by spurring innovation and productivity. The sector also serves as a deflationary force, as the prices of IT goods and services have been getting significantly cheaper compared with the rest of the economy. Policymakers should take none of this for granted.

Appendix 1: Methodology

This study examines the IT sector, overall traded sectors (sectors that face global competition), and the overall U.S. economy. We defined the IT sector to include 48 six-digit NAICS code industries (See table 2.)

Table 2 : IT industries for analysis

ITIF selected 461 industries to represent the traded sector (those with significant exposure to global competition). This was a subjective exercise, as the federal government does not provide statistics at the six-digit NAICS level on exports or imports. These included most of agriculture, mining and manufacturing, and some services such as information services, engineering services, and market consulting services.

Annual payroll, employee count, and establishments count are the sums of the six-digit NAICS code categories in the IT sector, traded sector, or overall economy. About 4 percent—which is the share of IT employees in the economy—of “Human resources consulting services” and “Other scientific and technical consulting services” are included in the IT sector. Furthermore, “Corporate, subsidiary, and regional managing offices” is included in the IT sector using its share in the total economy to calculate its share in the sector. “Payroll per employee” is the sum of all annual payroll divided by employee count for the IT sector, traded sector, or overall economy. These estimates rely on data from the Census Bureau’s County Business Patterns survey for 2020 (the latest year of available data). The change in jobs in the IT industry from 2017 to 2020 relied on the Census Bureau’s Economic Census survey and County Business Patterns survey for 2017, and the County Business Patterns survey for 2020.

Value-added data was obtained from the Bureau of Economic Analysis’s Components of Value Added tables. “Value added” is defined as the gross output less its intermediate input. The aggregate value added of the IT sector and traded sector is the sum of the categories selected to belong to each sector. The categories selected are also subjective, as the Bureau of Economic Analysis does not have six-digit NAICS codes for value-added data. Value-added growth data was obtained from the Integrated Industry-Level Production Account’s Industry Level Production Account: Contributions to Aggregate Value Added Growth table from the Bureau of Economic Analysis.

Induced and supplier jobs created by the IT industry utilized multipliers obtained from the Economic Policy Institute’s Updated Employment Multipliers for the US economy. Induced and supplier job estimates are the result of multiplying employee counts in all IT industries (see table 2) obtained from the Census Bureau’s County Business Patterns survey for 2020 by the average of the IT industry multipliers. The category of multipliers does not use six-digit NAICS codes; however, they corresponded with the Bureau of Labor Statistics’ categories that utilize four-digit NAICS codes. As such, the multipliers selected have four-digit NAICS codes that correspond to the selected IT industries in table 2.

Export data was obtained from the Census Bureau’s USA Trade Online database. The goods export contribution of the IT sector and the traded sector is the sum of the four-digit NAICS industries selected to belong to each sector. The services exports of information and communications technology were obtained from the Bureau of Economic Analysis’s Table 3.1. U.S. Trade in ICT and Potentially ICT-Enabled Services by Type of Service.

Educational attainment and its corresponding wage data were obtained from the Census Bureau’s American Community Survey 1-Year Estimates – Public Use Microdata Sample 2019 and American Community Survey 1-Year Estimates – Public Use Microdata Sample 2008.

IT-intensive industries (industries that used the largest shares of IT intermediates as a share of their overall inputs) were obtained from the Bureau of Economic Analysis’s Use Table, Before Definition, Producers’ Value, 2012 table. The rankings of IT-intensive industries were obtained by summing the total IT intermediates each industry used and then dividing the result by the total intermediate the industry used. The inflation data utilized to calculate the 1-year and 10-year percentage change in the PPI were obtained from the Bureau of Labor Statistics’ Producer Price Index.

Appendix 2: Differences Between This ITIF Report and the Commerce Department’s Digital Economy Report

The estimates in the Department of Commerce’s Digital Economy report and data varies from this report’s estimates due to differences in methodology. The Digital Economy report uses older NAICS codes from 2007 and 2012 when selecting industries that belonged to the digital economy. In the ITIF report, only 2017 NAICS codes were used when selecting industries that belonged to the IT sector. As a result of this difference, exact comparisons between the Digital Economy report and this report’s estimates are challenging. Moreover, direct comparisons between the two reports are not possible, as the ITIF report relies only on six-digit NAICS codes when selecting IT industries while the Digital Economy report uses three-, five-, and six-digit NAICS codes in its selection of industries that belong to the digital economy. Because the Digital Economy report uses three-, five-, and six-digit NAICS codes in its selection of digital economy industries, its estimates tend to be larger than those of ITIF that use only six-digit NAICS codes. The comparison between the two reports is also hindered as the Digital Economy report uses external sources to isolate digital activities by industries that produce digital and nondigital products. ITIF does not have access to the share that was included for these industries. As such, the estimates between the two reports cannot be compared. Lastly, the differences in estimates between the two reports can also be attributed to the different data sources used. The Digital Economy report primarily used the supply-use table to obtain its estimates, whereas the ITIF report used Bureau of Economic Analysis, Census, and Bureau of Labor Statistics data to obtain its estimates.

Acknowledgment

This report was made possible in part by generous support from the Information Technology Industry Council. The Information Technology and Innovation Foundation (ITIF) maintains complete editorial independence in all its work. All opinions, findings, and recommendations are ITIF’s and do not necessarily reflect the views of its supporters. Any errors and omissions are the author’s alone.

About the Author

Robert D. Atkinson (@RobAtkinsonITIF) is the founder and president of ITIF. Atkinson’s books include Big Is Beautiful: Debunking the Myth of Small Business (MIT, 2018), Innovation Economics: The Race for Global Advantage (Yale, 2012), Supply-Side Follies: Why Conservative Economics Fails, Liberal Economics Falters, and Innovation Economics Is the Answer (Rowman Littlefield, 2007), and The Past and Future of America’s Economy: Long Waves of Innovation That Power Cycles of Growth (Edward Elgar, 2005). Atkinson holds a Ph.D. in city and regional planning from the University of North Carolina, Chapel Hill.

The Information Technology and Innovation Foundation (ITIF) is an independent, nonprofit, nonpartisan research and educational institute focusing on the intersection of technological innovation and public policy. Recognized by its peers in the think tank community as the global center of excellence for science and technology policy, ITIF’s mission is to formulate and promote policy solutions that accelerate innovation and boost productivity to spur growth, opportunity, and progress.

For more information, visit us at www.itif.org .

[1] .     Robert D. Atkinson and Daniel Castro, “Digital Quality of Life: Understanding the Benefits of the IT Revolution” (ITIF, October 2008), https://itif.org/publications/2008/10/01/digital-quality-life-understanding-benefits-it-revolution/ .

[2] .     US Census Bureau, County Business Patterns Survey 2020 (establishment, payroll, and employee estimates, six-digit NAICS industries estimates) , accessed April 28, 2022, https://data.census.gov/cedsci/table?g=0100000US&d=ECNSVY%20Business%20Patterns%20County%20Business%20Patterns&n=N0600.00&tid=CBP2020.CB2000CBP .

[3] .     Ibid.

[4] .     Ibid.; Economic Policy Institute, Updated employment multipliers for the U.S. economy (Table A2) , accessed April 5, 2022, http://go.epi.org/jobmultiplierdata .

[5] .     US Census Bureau, American Community Survey 1-year Estimates Public Use Microdata Sample 2019 (educational attainment, wage, and industries estimates) , accessed April 28, 2022, https://data.census.gov/mdat/#/ .

[6] .     US Census Bureau, County Business Patterns Survey 2020 (establishment, payroll, and employee estimates, six-digit NAICS industries estimates).

[7] .     Robert D. Atkinson, “The Hamilton Index: Assessing National Performance in the Competition for Advanced Industries” (ITIF, June 2022), https://itif.org/publications/2022/06/08/the-hamilton-index-assessing-national-performance-in-the-competition-for-advanced-industries/ .

[8] .     Atkinson, “The Hamilton Index.”

[9] .     Ibid.

[10] .   US Census Bureau, County Business Patterns Survey 2020 , op. cit .

[11] .   Ibid.

[12] .   Tina Highfill and Christopher Surfield, New and revised Statistics of the U.S. Digital Economy, 2005–2020 (Washington DC, Bureau of Economic Analysis, May 2022), 8, https://www.bea.gov/system/files/2022-05/New%20and%20Revised%20Statistics%20of%20the%20U.S.%20Digital%20Economy%202005-2020.pdf .

[13] .   Ibid.

[14] .   US Census Bureau, County Business Patterns Survey 2020 (establishment, payroll, and employee estimates, 6-digit NAICS industries estimates).

[15] .   Ibid.; US Census Bureau, Economic Census Survey 2017 (establishment, payroll, and employee estimates, six-digit NAICS industries estimates) , accessed March 18, 2022, https://data.census.gov/cedsci/table?n=N0600.00&tid=ECNBASIC2017.EC1700BASIC ; US Census Bureau, County Business Patterns 2017 (educational services six-digit NAICS establishment, payroll, and employee estimates) , accessed March 18, 2022, https://data.census.gov/cedsci/table?n=N0600.61&tid=CBP2017.CB1700CBP&nkd=EMPSZES~001,LFO~001 ; US Census Bureau, County Business Patterns 2017 (agriculture, forestry, fishing and hunting six-digit NAICS establishment, payroll, and employee estimates) , accessed March 18, 2022, https://data.census.gov/cedsci/table?n=N0600.11&tid=CBP2017.CB1700CBP&nkd=EMPSZES~001,LFO~001 . Author’s analysis: The 2017 employment data for all industries uses a combination of the 2017 Economic Census survey and the 2017 County Business Patterns survey.

[16] .   Ibid. Author’s analysis: The following six-digit NAICS industries in table 2 were considered software and services: software and other prerecorded compact disc, tape, and record reproducing; business to business electronic markets; electronic shopping and mail-order houses; software publishers; data processing, hosting, and related services; internet publishing and broadcasting and web search portals; all other information services; consumer electronics and appliances rental; custom computer programming services; computer systems design services; other computer related services; human resources consulting services; other scientific and technical consulting services; research and development in the physical, engineering, and life sciences (except nanotechnology and biotechnology); corporate subsidiary, and regional managing offices, computer facilities management services; computer training; consumer electronics repair and maintenance; computer and office machine repair and maintenance; and communication equipment repair and maintenance. All other industries not listed were considered hardware.

[17] .   Tina Highfill and Christopher Surfield, New and revised Statistics of the U.S. Digital Economy, 2005–2020, 8.

[18] .   US Census Bureau, County Business Patterns Survey 2020 (establishment, payroll, and employee estimates, six-digit NAICS industries estimates); US Census Bureau, USA Trade Online data (export estimates for four-digit NAICS industries) , accessed March 18, 2022, https://usatrade.census.gov ; Bureau of Bureau of Economic Analysis, Value Added by Industry data (U. Value Added by Industry; accessed March 18, 2022), https://apps.bea.gov/iTable/iTable.cfm?isuri=1&reqid=151&step=1 .

[19] .   US Census Bureau, County Business Patterns Survey 2020 (establishment, payroll, and employee estimates, six-digit NAICS industries estimates).

[20] .   Ibid.

[21] .   Bureau of Economic Analysis, Value Added by Industry data (U. Value Added by Industry). Author’s analysis: The value added data does not use six-digit NAICS codes, which made it challenging to objectively compare the IT industries in table 2 to the value added data. The following categories in the value added data were subjectively selected to represent the IT industries’ value added: computer and electronic products; data processing, internet publishing, and other information services; nonstore retailers; and software publishers.

[22] .   Ibid.

[23] .   Ibid.

[24] .   Tina Highfill and Christopher Surfield, New and revised Statistics of the U.S. Digital Economy, 2005-2020, 1.

[25] .   Tina Highfill and Christopher Surfield, New and revised Statistics of the U.S. Digital Economy, 2005-2020, 7.

[26] .   US Bureau of Economic Analysis, New Digital Economy Estimates, 2005–2020.

[27] .   I bid. ; Bureau of Economic Analysis, Value Added by Industry data (U. Real Value Added by Industry) , accessed May 10, 2022, https://apps.bea.gov/iTable/iTable.cfm?isuri=1&reqid=151&step=1 .

[28] .   US Census Bureau, USA Trade Online data (export estimates for four-digit NAICS industries. Author’s analysis: There are only 22 IT industries instead of the 48 industries in table 2 when four-digit NAICS codes are used instead of six-digit NAICS codes. The 11 four-digit NAICS IT industries available in the export data include the following: industrial machinery; commercial and service industry machinery; computer equipment; communications equipment; audio and video equipment; semiconductor and other electronic components; navigational/measuring/ medical/control instrument; magnetic and optical media; electrical equipment; electrical equipment and components, nesoi; and software, nesoi. The following IT industries in table 2 were not included in the export data: electronic shopping and mail-order houses; data processing, hosting, and related services; internet publishing and broadcasting and web search portals; all other information services; business to business electronic market; consumer electronics and appliances rental; custom computer programming services; computer systems design services; other computer related services; research and development in the physical, engineering, and life sciences (except nanotechnology and biotechnology); corporate subsidiary, and regional managing offices; human resources consulting services; computer facilities management services; computer training; consumer electronics repair and maintenance; computer and office machine repair and maintenance; and communication equipment repair and maintenance. 

[29] .   Ibid.

[30] .   Ibid.

[31] .   Bureau of Economic Analysis, International Transactions, International Services, and International Investment Position Tables (Table 3.1. U.S. Trade in ICT and Potentially ICT-Enabled Services by Type of Service) , accessed May 9, 2022, https://apps.bea.gov/iTable/iTable.cfm?reqid=62&step=9&isuri=1&6210=4#reqid=62&step=9&isuri=1&6210=4 .

[32] .   US Census Bureau, County Business Patterns Survey 2020 (establishment, payroll, and employee estimates, six-digit NAICS industries estimates).

[33] .   Ibid.; Economic Policy Institute, Updated employment multipliers for the U.S. economy (Table A2) , accessed April 5, 2022, http://go.epi.org/jobmultiplierdata .  

[34] .   Ibid.

[35] .   Ibid.

[36] .   Bay Area Council Economic Institute, “Local Multipliers in the High-Technology Sector” (BACEI, April 2022), http://www.bayareaeconomy.org/files/pdf/BACEI_TechMultiplier_April2022b.pdf .

[37] .   US Census Bureau, County Business Patterns Survey 2020 (establishment, payroll, and employee estimates, six-digit NAICS industries estimates).

[38] .   Bureau of Economic Analysis, Value Added by Industry data (U. Value Added by Industry).

[39] .   Ibid.

[40] .   US Census Bureau, County Business Patterns Survey 2020 (establishment, payroll, and employee estimates, six-digit NAICS industries estimates).

[41] .   Ibid.

[42] .   Ibid.

[43] .   US Census Bureau, American Community Survey 1-year Estimates Public Use Microdata Sample 2019 (educational attainment, wage, and industries estimates) , accessed April 28, 2022, https://data.census.gov/mdat/#/ .

[44] .   Ibid.

[45] .   Ibid.

[46] .   Ibid.

[47] .   Ibid.

[48] .   Ibid.; US Census Bureau, American Community Survey 1-year Estimates Public Use Microdata Sample 2008 (educational attainment, wage, and industries estimates) , accessed April 26, 2022, https://data.census.gov/mdat/#/ .

[49] .   US Census Bureau, American Community Survey 1-year Estimates Public Use Microdata Sample 2019 (educational attainment, wage, and industries estimates ), accessed April 28, 2022, https://data.census.gov/mdat/#/ .

[50] .   Ibid.

[51] .   US Bureau of Economic Analysis, The Use of Commodities by Industry, Before Redefinitions (Producers’ Prices) – Detail (Use Table, Before Redefinition, Producers’ Value, 2012 table) , accessed March 26, 2022, https://apps.bea.gov/iTable/iTable.cfm?isuri=1&reqid=151&step=1 .

[52] .   Ibid.

[53] .   Ibid.

[54] .   Ibid.

[55] .   Ibid.

[56] .   US Bureau of Economic Analysis, Integrated Industry-Level Production Account (KLEMS) (Industry-level Production Account: Contributions to Aggregate Value Added Growth) , accessed April 5, 2022, https://www.bea.gov/data/special-topics/integrated-industry-level-production-account-klems . Author’s analysis: The KLEMS data is calculated using a Tornqvist index. The growth rates are in log growth.

[57] .   Ibid.

[58] .   US Bureau of Labor Statistics, PPI Detailed Report Data for June 2012 (producer price index, Table 5 for IT Industries and Table 6 for All Commodities), accessed August 16, 2022, https://www.bls.gov/ppi/detailed-report/ppi-detailed-report-june-2012.pdf ; US Bureau of Labor Statistics, PPI Detailed Report Data for June 2012 (producer price index, Table 11 for IT Industries and Table 9 for All Commodities), accessed August 16, 2022, https://www.bls.gov/ppi/detailed-report/ppi-detailed-report-june-2022.pdf ; US Bureau of Economic Analysis, The Use of Commodities by Industry, After Redefinitions (Producers’ Prices) – Detail (Use Table, After Redefinition, Producers’ Value, 2012 table), accessed August 16, 2022, https://apps.bea.gov/iTable/iTable.cfm?isuri=1&reqid=151&step=1 .

        Author’s analysis: Data is available for the following 33 IT industries: electronic computer manufacturing; computer storage device manufacturing; computer terminal and other computer peripheral equipment manufacturing; telephone apparatus manufacturing; radio and television broadcasting and wireless communications equipment manufacturing; other communications equipment manufacturing; audio and video equipment manufacturing; bare printed circuit board manufacturing; semiconductor and related device manufacturing; capacitor, resistor, coil, transformer and other inductor manufacturing; electronic connector manufacturing; printed circuit assembly (electronic assembly) manufacturing; other electronic component manufacturing; electromedical and electrotherapeutic apparatus manufacturing; search, detection, navigation, guidance, aeronautical, and nautical system and instrument manufacturing; automatic environmental control manufacturing for residential, commercial, and appliance use; instruments and related products manufacturing for measuring, displaying, and controlling industrial process variables; totalizing fluid meter and counting device manufacturing; instrument manufacturing for measuring and testing electricity and electrical systems; analytical laboratory instrument manufacturing; other measuring and controlling device manufacturing; blank magnetic and optical recording media manufacturing; software and other prerecorded compact disc, tape, and record reproducing; electronic shopping and mail-order houses; software publishers; data processing, hosting, and related services; internet publishing and broadcasting and web search portals; semiconductor machinery manufacturing; printing machinery and equipment manufacturing; photographic and photocopying equipment manufacturing; switchgear and switchboard apparatus manufacturing; fiber optic cable manufacturing; and other communication and energy wire manufacturing.

        The PPI for the 33 IT industries is weighted using their output as a share of the 33 IT industries’ total output. Output data for each IT industry came from the BEA’s Use of Commodities by Industry, After Redefinitions (Producers’ Prices)-Detail table.

[59] .   U.S. Bureau of Labor Statistics, Producer Price Index – PPI Industry Data (producer price index estimates for industries) , accessed April 1, 2022, https://data.bls.gov/PDQWeb/pc . Author’s analysis: The Bureau of Labor Statistics only has data for the following top 19 IT-intensive industries: printed circuit assembly (electronic assembly) manufacturing; electronic computer manufacturing; all other miscellaneous electrical equipment and component manufacturing; motor vehicle electrical and electronic equipment; computer storage device manufacturing; semiconductor machinery manufacturing; irradiation apparatus manufacturing; audio and video equipment manufacturing; computer terminal and other computer peripheral equipment manufacturing; internet publishing and broadcasting and web search portals; electromedical and electrotherapeutic apparatus; other electronic component manufacturing; software publishers; telephone apparatus manufacturing; and photographic and photocopying equipment manufacturing.

[60] .   US Bureau of Labor Statistics, Producer Price Index – PPI Commodities Data (producer price index estimates for final demand of all commodities) , accessed April 27, 2022, https://data.bls.gov/cgi-bin/surveymost?wp .; US Bureau of Labor Statistics, Producer Price Index – PPI Industry Data (producer price index estimates for industries) , accessed April 1, 2022, https://data.bls.gov/PDQWeb/wp .

[61] .   Ibid.; US Bureau of Economic Analysis, The Use of Commodities by Industry, Before Redefinitions (Producers’ Prices) – Detail (Use Table, Before Redefinition, Producers’ Value, 2012 table) , accessed March 26, 2022, https://apps.bea.gov/iTable/iTable.cfm?isuri=1&reqid=151&step=1 .

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• v.7(Suppl 1); 2015 Apr

Health problems and stress in Information Technology and Business Process Outsourcing employees

Department of General Medicine, Sree Balaji Medical College, Bharath University, Chrompet, Chennai, Tamil Nadu, India

N. N. Anand

S. m. g. swaminatha gurukul, s. m. a. syed mohammed javid, arun prasad.

Stress is high in software profession because of their nature of work, target, achievements, night shift, over work load. 1. To study the demographic profile of the employees. 2. To access the level of job stress and quality of life of the respondents. 3. To study in detail the health problems of the employees. All employees working in IT and BPO industry for more than two years were included into the study. A detailed questionnaire of around 1000 IT and BPO employees including their personal details, stress score by Holmes and Rahe to assess the level of stress and master health checkup profile were taken and the results were analysed. Around 56% had musculoskeletal symptoms. 22% had newly diagnosed hypertension,10% had diabetes, 36% had dyslipidemia, 54% had depression, anxiety and insomnia, 40% had obesity. The stress score was higher in employees who developed diabetes, hypertension and depression. Early diagnosis of stress induced health problems can be made out by stress scores, intense lifestyle modification, diet advice along with psychological counselling would reduce the incidence of health problems in IT sector and improve the quality of work force.

Information Technology (IT) industry in India has got a tremendous boost due to globalization of Indian economy and favorable government policies. IT and IT related professionals are at a constant pressure to deliver services efficiently and have to be cost effective.

Employees working in IT industry are prone to develop a lot of health problems due to continuous physical and mental stress of their work. Diseases are either induced, sustained or exacerbated by stress. The common health problem due to stress are acid peptic disease, alcoholism, asthma, diabetes, fatigue, tension headache, hypertension, insomnia, irritable bowel syndrome, psychoneurosis, sexual dysfunction and skin diseases such as psoriasis, lichen planus, urticaria, pruritus, neurodermatitis etc. Globalization and privatization have brought new work relationships, job insecurity, insecurity regarding future working conditions and rapid obsolescence of skills are causes of stress. IT industry has become one of the fastest growing industries in India. Strong demand over the past few years has placed India among the fastest growing IT markets in Asia-Pacific region. The reason for choosing particularly IT and ITES employees is that the level of stress these employees face is comparatively higher than other employees. Any kind of a job has targets, and an employee becomes stressed when he or she is allotted with unachievable targets and are unable to manage a given situation. Thus, the main aim of this article is to bring to limelight the level of stress with IT and ITES employees in Chennai.

• To screen IT employees by a questionnaire that include details of health illnesses, family history of illness, diet, lifestyle, exercise and yoga activities and health checkup reports.
• To assess the severity of stress using Holmes and Rahe Stress Scale scoring which would measure stress with the number of life change units and the final score would give a rough estimate of how stress affects health of IT employees.

Material and Methods

This is a cross-sectional study involving IT employees in Chennai.

As there are no such studies available, I have done a pilot study with 30 IT employees and collected data from 1,000 IT employees. The study was started after getting Ethical Committee approval and getting consent from the employees in IT industry. The employees enrolled voluntarily to the study should be working for at least 2 years in the industry. A detailed questionnaire, including the health history, diet pattern, lifestyle and stress score was given to them-Holmes, and Rahe stress score scale. A complete master health checkup was done, and the results were analyzed.

Around 56% had musculoskeletal symptoms. 22% had newly diagnosed hypertension, 10% had diabetes, 36% had dyslipidemia, 54% had depression, anxiety and insomnia, 40% had obesity [ Figure 1 ]. Musculoskeletal symptoms included cervical and lumbar strain with or without disc disease, polyarthralgia, and muscle spasm and heel pain.

Percentage of health problems in IT and BPO employees

The stress score was higher in employees who developed diabetes, hypertension, dyslipidemia and obesity. Most of the employees who were obese had a higher stress score. Of the metabolic disorders employees with higher stress score had dyslipidemia, followed by hypertension and diabetes [ Figure 2 ].

Health problems and stress scores in IT, BPO employees

To measure stress according to the Holmes and Rahe Stress Scale, the number of “Life Change Units” that apply to events in the past year of an individual's life are added and the final score will give a rough estimate of how stress affects health.

• Score of 300 + : At risk of illness.
• Score of 150-299: Risk of illness is moderate (reduced by 30% from the above risk).
• Score <150: Only have slight risks of illness.

Among IT employees with health problems 67% were men and 33% were women [ Figure 3 ].

Health problems and sex wise distribution

Stress at work has been linked with coronary heart disease and metabolic syndrome in retrospective and prospective studies.[ 1 , 2 ] The biological mechanisms remain unclear.[ 3 ] The pathophysiological mechanisms involve direct neuroendocrine effects and indirect effects mediated by adverse health behaviors.[ 4 , 5 , 6 ] The metabolic syndrome is a cluster of risk factors that increases the risk of heart disease and type 2 diabetes.[ 7 ] Characteristics of the metabolic syndrome are abdominal obesity, atherogenic dyslipidemia (raised triglycerides, small low-density lipoprotein particles, and low concentrations of high-density lipoprotein cholesterol), high blood pressure (BP), insulin resistance (with or without glucose intolerance), and prothrombotic and proinflammatory states. Studies have found a social gradient in work stress and the metabolic syndrome,[ 8 , 9 ] suggesting a greater exposure to working stress among less advantaged social groups. Cross-sectional studies have linked work stress with components of the syndrome,[ 10 , 11 ] but this association is not consistent.[ 4 , 12 ]

Technostress is the word used to explain the phenomenon of stress arising due to the usage of computers. It is a modern disease of adaptation caused by the inability to cope with new computer technologies in a healthy manner.

Transduction is the translation of emotional distress to physiological change and then to a physical symptom. Complex autoimmune, humoral and neuromuscular mechanisms mediate this reaction, and may itself affect the environment by a social response that may yield a positive or a negative response. Effects of stress on mind and body are due to increased sympathetic nervous system activity and increased secretion of adrenaline, cortisol and other stress hormones.

Occupational (job, work or workplace) stress has become one of the most serious health issues in the modern world (Lu et al ., 2003, 479), as it occurs in any job and is even more present than decades ago. Namely, the world of work differs considerably from the working environment of 30 years ago: longer hours at work are not unusual, frequent changes in culture and structure are often cited, as well as the loss of lifetime career paths (Cooper and Locke, 2000 in Fotinatos-Ventouratos and Cooper 2005), which all leads to greater presence and levels of stress.

Hans Selye was one of the founding fathers of stress research. His view in 1956 was that “stress is not necessarily something bad – it all depends on how you take it. The stress of exhilarating, creative, successful work is beneficial, while that of failure, humiliation or infection is detrimental.” Selye believed that the biochemical effects of stress would be experienced irrespective of whether the situation was positive or negative.

Job stress occurs in response to both workplace and employee factors, but the characteristics of the workplace likely play the primary role. “Job stress can be defined as the harmful physical and emotional responses that occur when the requirements of the job do not match the capabilities, resources or needs of the worker. Job stress can lead to poor health and even injury.” (Stress at work, United States National Institute of Occupational Safety and Health, Cincinnati, 1999).

A Canadian graduate school study[ 13 ] suggested companies should invest in IT specific employee assistance programs. Survey conducted by Techweb Network Research on behalf of Op Tier quantified how stressed managers are. This survey showed the greatest cause of job stress were complexity of company IT infrastructures and poorly defined goals. 264 women employees were studied by Aziz to explore the level of stress. Resource inadequacy role overload and personal inadequacy were the main causes of stress. There was a difference between married and unmarried women. Working in IT calls for a high degree of accuracy over the long period of time, and a small lapse would be disastrous.

Studies have shown that employees with chronic work stress (three or more exposures) were nearly twice as likely to develop the metabolic syndrome[ 14 ] than those with no exposure to work stress. Women with chronic work stress were over five times more likely to have the metabolic syndrome. Greater exposure to job stress over 14 years was linked to greater risk of the metabolic syndrome, in a dose-response manner. The association was robust to adjustment for occupational status and health behaviors.[ 15 ] It is unclear whether the development of risk seen here is due in part to the direct effects of chronic stress on insulin resistance, resting BP, and lipoprotein metabolism, although this interpretation is supported by Whitehall II and other studies.[ 3 , 5 , 16 ]

Stress and its types

We cannot have a stress-free life. Stress is, of course, essential for every human being as it is considered as a boost that takes an employee to the highest ladder in the organization. The various types of stress is mentioned below:

Eustress is a type of short-term stress that provides immediate strength. It is a positive stress that arises when motivation and inspiration are needed.

Distress, on the other hand, is a negative stress brought about by constant readjustments and alternatives in a routine. Distress creates feelings of discomfort and unfamiliarity.

Hyper stress occurs when an individual is pushed beyond what he or she can handle. It results from being overloaded or overworked.

Hypo stress occurs when an individual is bored or unchallenged. People who experience hypo stress are often restless.

Stages of work stress

According to Pestonjee (1992) work stress progresses through a series of five stages.

• The honeymoon stage: Euphoric feeling if excitement, enthusiasm, challenges and pride on getting a new job. Dysfunctional processes include the depletion of energy reserves in coping and adapting to the new environment.
• The full throttle stage: Going full swing leads to a depletion of resources. Other symptoms include dissatisfaction, sleep disturbances, overeating, drinking or smoking.
• The chronic symptom stage: Development of chronic symptoms like physical illness, anger and depression.
• The crisis stage: Persistence of symptoms leads to disease, chronic backache, headache, high BP, insomnia, etc., would develop.
• Hitting the wall stage: No person can continue under strain for too long and one may reach the end of one's professional career. Burnout stress syndrome takes over.
• The opposite: Rust our stress syndrome occurs under extreme hypo stress. This is likely to occur when the gap between one’ capabilities and environmental demands becomes too wide.

Biology of stress

Prolonged exposure to work stress may affect the autonomic nervous system and neuroendocrine activity directly, contributing to the development of the metabolic syndrome.

A case–control study showed that participants in the Whitehall II study with the metabolic syndrome had raised cortisol and normetanephrine output, and also had reduced variability in heart rate.[ 5 ] Decrements in cardiac autonomic function have been linked to the metabolic syndrome in other populations and to low job control and social isolation among men in the Whitehall II study.[ 6 , 17 , 18 ] Psychobiological studies have also shown that heightened stress reactivity and impaired recovery after stress, assessed by BP and inflammatory markers, predict the 5 years progression of the metabolic syndrome.[ 18 ]

Chronic psychological stress may reduce biological resilience and thus disturb homoeostasis. Altered adrenocortical function can influence hepatic lipoprotein metabolism and insulin sensitivity at target organs.[ 15 , 19 ]

Cortisol is an insulin antagonist, and cortisol output is increased in the metabolic syndrome.[ 5 ]

Low concentrations of high density lipoprotein cholesterol and glucose intolerance have been linked with high basal secretion of cortisol.[ 20 ]

Stress at work is associated with coronary heart disease, but the biological mechanisms underlying this association are unclear

Information Technology industry causes stress among employees in many ways:

• Software packages used as the operating system for companies releases 3-4 updates in a year. The employee has to learn about these updates each time. Otherwise they would lag behind others causing pressure on the employee and increased job risk if he fails to perform well.
• Training program sanctioned by the company is not employee oriented as each employ
• Another form of stress is called technologist. People do not communicate or interact with their colleagues as before. This can cause alienated feelings among colleagues.
• Employees working in IT industry need to work with a high degree of accuracy over a long period. A small lapse can lead to disastrous effect for the company. They need to have an outlet to manage their stress.

The daily impact of IT on our lives continues unabated. As innovations and computer capacities increase this influence will continue to grow in the coming years at an increasing rate. As technology advances, there is also increased stress that is associated with it called as “technology stress.” IT is here to stay. This brings extra pressure on people to adapt to new advancements and update their knowledge in their field.

Annual stress scoring has to be done and a score above 300 needs stress management program like yoga, meditation and other destressing activities like aerobics, dance etc., would prevent or reduce risk of disease due to stress in IT people which in turn will produce a healthy community.

To manage stress these people need to play sport, have a hobby or just have a good holiday. Stress score helps us to screen who would be prone to stress related physical illness and people with a score more than 300 are at risk of illness and care should be taken at the earliest to relive their stress. Healthy employees mean better performance by employee that in turn produce a healthy community. Annual stress scoring has to be done, and employees are having a score more than 300 should be involved in active antistress management.

Source of Support: Nil

Conflict of Interest: None declared.

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• Published: 16 August 2024

The carbon emission reduction effect of China’s national high-tech industrial development zones

• Shen Zhong 1 ,
• Yaqian Wu 1 &
• Junzhi Li 2  

Scientific Reports volume  14 , Article number:  18963 ( 2024 ) Cite this article

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• Climate change
• Climate-change impacts

The double carbon goal is a wide and profound economic and social systematic change. It is also crucial to China's sustainable development. How to promote emission reduction, the National High-Tech Industrial Development Zones(NHTDZs) policy is the key to addressing this problem. Based on urban data from 2003 to 2019 from China, this paper uses the multi-time point asymptotic difference method to explore the impact of the NHTDZs establishment on carbon emissions. The establishment of NHTDZs reduces CO2 emissions, which remains valid through robustness tests. The mechanism analysis demonstrated that the construction of NHTDZs reduces CO2 emissions by increasing innovation levels, increasing research expenditures and emphasizing human capital. Further analysis shown that geographic location, initial resource endowment, population size, and level of green finance development are difference in different cities. This provides guidance promoting the development of NHTDZs and future layout.

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Introduction.

Since the Industrial Revolution, the overexploitation of natural resources by human beings in pursuit of rapid economic development has led to a rise in the content of CO2 in the atmosphere 1 , causing global warming. Global warming triggers extreme weather such as glacier melting, sea level rise, extreme heat and drought 2 , which seriously threatens the human survival. The effects of global 1warming on the ecological environment have gradually emerged, and CO2 emissions have attracted worldwide attention 3 . Approximately 200 countries and organizations around the world have signed the Paris Agreement to jointly limit rapid temperature increases and make commitments to reduce emissions. The U.S. has enacted the Clean Air Act 4 etc. The EU has formulated carbon pricing policies. China has built a “one + N” policy system of emission reduction goals and has formed a carbon pricing mechanism 5 . In addition, relevant emission reduction policies, such as pilot low carbon cities, green credit policies and environmental protection tax laws, have been introduced. Among them, NHTDZs also play a vital role in facilitating emission reduction and green low-carbon development.

To accelerate green low-carbon development, NHTDZs play a leading and radiating role in this process. It has become a model of economic transformation and an important engine of green low carbon development. NHTDZs converge many National High-tech Enterprises(HNTEs), forming a strong atmosphere of innovation and possessing fruitful innovation results. In recent years, the innovation capacity and the quantity of patents in NHTDZs have been steadily increasing, indicating that technology is constantly advancing. Technological progress can reduce energy costs and energy service prices 6 , decreasing the use of energy and reducing CO2 emissions 7 , 8 , 9 . According to the staffing structure in the NHTDZs, the education level of personnel is climbing, which indicates that human capital is accumulating. The accumulation of human capital can inspire inventions 10 , replace inputs between fossil and non-fossil energy sources 11 , and reduce energy consumption 10 and CO2 emissions. CO2 emission reduction is a continuous process that requires continuous capital investment. The capital investment within the NHTDZs has been increasing annually. Science expenditures promote the advancement of energy-saving technology, which promotes emission reduction 12 . It also promotes the development of low-carbon transportation systems, improves traffic management and logistics patterns, increases transportation efficiency and reduces carbon emissions. In addition, government financial subsidies for NHTDZs can guide enterprises toward low-carbon development and promote the production of greening products 3 . Therefore, clarifying the role played by NHTDZs in low-carbon economic transformation provides the necessary empirical support for realizing the win–win goal of ecological protection and economic development.

Studies on CO2 emission reduction have focused on the following aspects. Some scholars argue that the relationship between CO2 emissions and economic growth satisfies the EKC hypothesis. CO2 emissions decrease as economic growth 13 , 14 , 15 , 16 . Others argue that the relationship between economic growth and CO2 emissions are positive correlation 17 , 18 , 19 . From the macroeconomic perspective, some studies have considered the effects of human capital level 20 , 21 , 22 , 23 , 24 , urbanization 25 , 26 , foreign inward investment(FID) 27 , 28 , 29 , the digital economy 30 , digital finance 31 , population aging 32 , green innovation 33 , 34 , industrial structure optimization 35 and energy structure adjustment 36 on CO2 emissions. Zhang Tao's study showed that technology transfer in European countries can reduce their own carbon emissions, but increase carbon emissions in Asian countries 37 . In addition, policies are one of the influencing factors. Cheng J et al. illustrated that low-carbon city pilots reduce carbon emissions through the transformation of technological effects into green technological progress and structural effects 38 . Allocating resources to green technology innovations can improve environmental sustainability 39 . Studies by Cheng Z et al. and Xu A et al. have shown that smart cities have a carbon reduction effect 40 , 41 . Lingxuan Liu found that industrial symbiosis and renewable energy use can reduce carbon emissions in parks 42 . Yizheng Lyu studied the impact of four typical industrial parks in China on carbon emission reduction based on the land-industry-carbon integration model 43 . Xiang Yu et al. studied the effects of 20 national low-carbon pilot zones on CO2 emissions during 2012–2016 44 . Qian L et al. found that there is a suppression effect between NHTDZs and urban carbon emissions. This suppression effect has some lag and spatial spillover effects 45 . Sun Y and Woldesilassie found that NHTDZs improve innovation capacity to reduce CO2 emissions under government guidance 46 , 47 . Li X, and Wang (2023) showed that the NHTDZs policy will reduce per capita CO2 emissions 48 .

The research on carbon emission reduction is relatively rich. This study establishes a framework for further study. Considering the variations in research contents and perspectives, there is still some research space. This study empirically investigated the effects of establishing NHTDZs on CO2 emissions in China, using a multitemporal asymptotic difference approach. This demonstrates that the establishment of NHTDZs clearly reduces CO2 emissions about 2.53% after controlling influence factors. This indicates that NHTDZs achieve the goal of decreasing CO2 emissions.

The research contributions are as follows. First, the environmentally friendly and sustainable development of NHTDZs has become a key topic of study in recent years. The literature has been conducted in foreign countries, while little literature has been transferred to the Chinese context. This paper focused on the importance of the environmental aspects of establishing NHTDZs and systematically explored the CO2 emission reduction effect of NHTDZs policy, supplementing the assessment of the effect of establishing NHTDZs. Second, this paper adopts apparent carbon emission data from the China Carbon Accounting Database (CADS) to provide more evidence for the CO2 emission reduction effect of NHTDZs. Third, this research reveals the mechanism by which NHTDZs reduce CO2 emissions. Existing studies mainly focus on innovation level, environmental regulations 49 and energy 48 . This paper additionally analyzes this topic from the perspective of human capital level and R&D investment. This approach supplements the transmission mechanism. This study provides certain reference opinions for the government on the development of NHTDZs.

The rest of the paper is organized as follows: part two provides the policy background and theoretical analysis; part three presents the research data and econometric modeling setup; part four reports the empirical results and robustness tests; part five conducts the mechanism test; part six conducts the heterogeneity analysis; and part seven presents the conclusions and policy recommendations.

Policy context and theoretical mechanisms

Policy context of nhtdzs.

As an effective way to promote the integration of science technology industries, science technology parks first appeared in the United States and gradually became popular around the world. To grasp the scientific and technological revolution, China gave birth to the idea of establishing NHTDZs. In 1988, the State Council encouraged the establishment of NHTDZs in intellectually intensive areas. NHTDZs rely on domestic science and technology, economic strength, the reform of preferential policies, and the ability to fully absorb advanced foreign scientific technological resources, to achieve local optimization of hard and soft environments. In the same year, the State Council approved the establishment of the first Beijing NHTDZ and carried out the Torch Plan. Under the impetus of the Torch Program, various places have combined local characteristics and conditions to actively create NHTDZs, which opened the prelude to the construction of NHTDZs.

After that, in 1991 and 1992, the State Council approved the construction of 51 NHTDZs in two stages, which formed the preliminary scale of construction of NHTDZs. After 2007, the State Council approved the construction of new NHTDZs at different stages. Especially after 2012, the speed of construction of NHTDZs further accelerated. By the end of 2022, the number of NHTDZs will reach 173. The time of establishment are shown in Fig.  1 .

Number of NHTDZs number.

At the early stage of reform and opening to the outside world, China's industrial base was weak. The high-tech industry was basically blank, taking the development path of "industry first". At this stage, the construction of NHTDZs focused on production factors. The construction path is to create hard conditions for parks to carry out production and attract investment, with the formation of the industrial base and economic scale as the main construction goals. China's economy started to develop. CO2 emissions were low. With the expanding scale of economic construction, the state began to realize the initial purpose of constructing NHTDZs. In 2001, the slogan of second ventures was proposed. It was proposed that the construction of NHTDZs should focus on promoting the "five transformations". NHTDZs around the world choose reasonable leading industries according to their own development characteristics and resource endowments.

For example, Xiamen Torch NHTDZ focuses on the development of strategic emerging industries; Jining NHTDZ focuses on the allocation of human resources and innovation platform resources; and Suzhou NHTDZ focuses on incubating environmentally friendly innovative enterprises.

During this period, NHTDZs achieved significant results in terms of innovation, talent introduction, and the transformation of scientific and technological fruits. Figures 2 , 3 , 4 present the NHTDZs in terms of innovation, talent accumulation and R&D expenditures.

Innovation.

NHTDZs staff.

Expenditures.

As a "testing ground" for national progressive reform, the NHTDZs are driven by the national mission 23 , 48 . This process realizes the efficient recycling of resources with the specialized agglomeration of HNTEs. It adheres to circular economy and intensive development as a means of promoting coordinated environmental and ecological development. In recent years, NHTDZs have vigorously developed in term of atmospheric control, greening and energy conservation. For air pollution management, the Wuhan East Lake NHTDZ is at the leading level in air management in China. Nanning NHTDZ has greatly reduced CO2 emissions, sulfur dioxide and other gases by replacing coal with biomass as boiler fuel. On the greening side, Suzhou NHTDZ has created green projects to realize 2.5 million square meters of new urban green space. On the energy conservation front, the Zhaoqing NHTDZ vigorously promoted photovoltaic power generation; and the Guiyang NHTDZ introduced energy-saving science technology enterprises, realizing an annual emission reduction of 1.1 million tons of CO2. By strengthening ecological construction and environmental protection, NHTDZs are actively promoting low-carbon economic development.

In view of this, the authors used the establishment of NHTDZs as a natural experiment and selected samples collected between 2003 and 2019 to explore carbon emission reduction effects. After 2019, due to the new coronavirus epidemic, restrictions on economic activity and production resulted in reduced CO2 emissions 50 , 51 , 52 , which need to be excluded from this shock.

Theoretical mechanisms

NHTDZs, as entrepreneurial highlands, talent highlands and science technology bases, are important for China's strategic development. Its core competitiveness is innovation capacity. NHTDZs can improve the environment by combining human capital with innovation 53 , reducing carbon emissions 54 . Human capital has a positive moderating effect on the environmental impact of green innovation 53 .

Human capital stimulates society's willingness to use energy saving and environmental technologies. It increases individual productivity to achieve emission reductions 55 . The improvement in China's human capital is largely attributable to increased educational attainment 56 . The education level of practitioners in China's NHTDZs is international first-class and team structure is constantly optimized (see Fig. 4 ). NHTDZs drive regional transformation and upgrading through the improvement of the human capital structure and industrial structure from labor-intensive and low-value-added industries to capital-intensive and high-value-added industries, realizing green development.

NHTDZs have attracted ample HNTEs and innovative talent through preferential policies. Through financial incentives, loan interest subsidies, project grants, the transfer of rights and interests and risk compensation, NHTDZs are growing quickly. For example, the Changsha NHTDZ arranges 500 million yuan annually as a science technology innovation and industrial development fund. In addition, government subsidies are considered labels that increase companies’ recognition of capital markets, and enterprises will go further into green development planning 57 . The following hypothesis is proposed.

H1: The establishment of NHTDZs can reduce CO2 emissions.

HNTEs are the main innovation force. Technological innovation can transform traditional factor-driven approaches into innovation-driven development approaches 58 . According to Schumpeter, technological change enters the production process in the form of invention. It is possible to improve environmental quality when production processes are optimized 59 . Endogenous growth theory suggests that the function of technological change is crucial in the economic growth process. In the past, nonrenewable energy sources were used more frequently. Economic growth may increase in carbon emissions, leading to environmental degradation 60 . As an effective means to combat climate change, innovation can improve the efficiency of energy utilization 61 , promote industrial upgrading 62 and reduce carbon emissions by replacing fossil fuels with cleaner energy sources 63 .

From the perspective of technological innovation, through the implementation of green innovation strategy, enterprises carry out comprehensive greening. They reduced carbon emissions through end-of-pipe technologies, cleaner production technologies, carbon capture and other "negative emission" technologies 64 , 65 . The application of clean energy decreases public health risks 66 , 67 and the consumption of solid fuel and improves air and water quality 66 , 67 , thereby reducing air pollution 68 . The distributed photovoltaic power generation project promoted by the Zhaoqing NHTDZ optimized the energy structure. The annual power generation will reach 21.33 million kWh, which will reduce CO2 emissions by 17,512 tons of annually. The following hypothesis is proposed.

H2: The establishment of NHTDZs facilitates CO2 reduction by enhancing innovation levels.

Human capital, as a country's soft power, can also reduce CO2 emissions 69 , 70 . Human capital theory suggests that the evolution of factor endowment structure changes regional production patterns and development trends. Endogenous growth theory suggests that knowledge spillovers can generate innovations that promote economic development 71 .

The most intuitive manifestation of human capital is investment in higher education 10 . Formal education is the main way of acquiring knowledge, skills and abilities. It also affects people’s attitudes and behaviors toward environmental ecology 72 . An increased education level produces income effects and changes cognitive abilities. The Energy consumption structure changes, which reduces the use of nonrenewable energy sources 73 , 74 . The inputs of energy can decrease with increasing human resources, while the total output remains constant 75 .

Human resources improve industrial structure, shifting from primary industry senior human capital and industrial primary technology to secondary and tertiary senior human capital and new cutting-edge technology, optimizing the allocation of production factors and promoting energy conservation 77 . The knowledge spillover effect and teamwork effect of human capital enhance the knowledge stock of enterprises and promote the absorption of foreign pollution control and clean technology. According to Nelson and Phelps, a country's ability to introduce and use new technology comes from its domestic human capital stock. A high level of human resources can drive the realization of emission reduction targets 78 . The following hypothesis is proposed.

H3: The establishment of NHTDZs contributes to carbon emission reduction by increasing the level of human capital.

A green low-carbon transition is a continuous process that requires substantial financial support, active policy support, adequate subsidized funding and diversified financing channels. Government spending on R&D reduces the CO2 emissions of countries 79 and decreases the CO2 emissions of other countries 80 .

First, R&D is costly, long and risky. Most enterprises do not have enough capital to invest and have excessive concerns 81 . The government not only provides public services, but also provides policies that promote enterprises to expand strategic investment 82 . For example, Hefei city has taken the lead in taking the green low-carbon industry as the new growth momentum of the NHTDZ, skillfully handling the relationship between carbon emission reduction and economic development.

Second, the government fosters the development of new energy and low-carbon industries through industrial policies, in which enterprises establish positive linkages with energy and technology industries and promote green consumption 3 . This further provides reliable sources of funding for clean, energy-efficient and low-carbon technologies 83 which enhances environmental quality and combats climate change.

Once again, financial technology spending improves the regional digital economy, facilitating regional greening 84 . Monitoring environmental change by reducing energy usage and carbon pollution 85 . Improving the efficiency of energy use in other sectors and reducing the burden of natural resource use 86 .

Finally, there is a relationship between external investment and CO2 54 . According to opportunity cost theory, R&D investment is generally countercyclical 87 . Because of financing constraints, R&D investment increases with the prosperity of business operations 88 . External investment can transform from theory into profitable projects that generate profits and are supported by sustaining capital. The environmental quality will improve when commerce operations prosper 89 , 90 . The following hypothesis is proposed.

H4: The establishment of NHTDZs can promote carbon emission reduction by increasing investment in scientific research.

Materials and methods

Econometric methodology.

This paper adopts an asymptotic double difference model to measure the emission reduction function of NHTDZs and the model is set as follows:

In the above equation, the dependent variable \({lnco2}_{it}\) denotes the CO2 emissions of city i in year t plus 1 to take the logarithm, from the CADS.

\({park}_{it}\) indicates that city i established an NHTDZ in year t. If city i established an NHTDZ for the first time in year t, then \({park}_{it}\) =1, and conversely \({park}_{it}\) =0. The coefficient \({\alpha }_{1}\) is attention, which indicates the policy effect. \({\sigma }_{i}\) is the control city fixed effect. \({\pi }_{t}\) is the year fixed effect. \({\varepsilon }_{it}\) is the random error and is clustered at the city level. The list of NHTDZs from the Ministry of Science and Technology Torch High Technology Industry Development Center.

After 2019, due to the new coronavirus epidemic, restrictions on economic activity and production resulted in reduced CO2 emissions 50 , 51 , 52 , which need to be excluded from this shock. Furthermore, the explanatory variable data comes from the CADS database, which is updated to 2019. Therefore, the data from 2003 to 2019 are selected as the sample.

Referring to the literature, this paper incorporates a series of city-level control variables from the Statistical Yearbook of China's Cities. See Supplementary table 1.1 of part one of appendix 1 for details.

Empirical results

Baseline regression.

Table 1 shows the regression results, with each column controlling for city and year fixed effects. The negative effect gradually increases after the gradual addition of control variables and is significant at the 1% level, indicating that the establishment of NHTDZS can reduce carbon emissions at the city level. The coefficient of the core explanatory variable is − 0.0253, indicating that after the establishment of the NHTDZS, the total carbon emissions of the regions decreased by approximately 3.49%. H1 is verified.

Parallel trend testing

Is the discrepancy in total carbon emissions resulting from the establishment of NHTDZs itself? The impacts of other factors are difficult to observe. The following model is constructed for testing:

The park still indicates whether the region established an NHTDZ, so j i indicates the year in which region i obtained the first NHTDZ. Park(− 7) = 1 when t-j <  = − 7, otherwise it is 0; park(k) = 1; when t-j <  = k, k = − 6, k = -5, k = -4, k = -3, k = − 2, k = − 1, k = 0, k = 1, k = 2, k = 3, k = 4, k = 5, k = 5, k = 6; park(7) = 1, when t-j >  = − 7; otherwise it is 0. Drawing on the classic literature, the regression equation is based on the establishment of the previous year as the benchmark group, and the rest are consistent with Model 1.

The results of the parallel trend test are shown in Fig. 5 , which demonstrates the treatment trend in seven periods before and after the event, with the horizontal axis showing the years, the vertical axis showing coefficients and dashed lines indicating the confidence intervals at the 90% level. Figure  5 shows that the model satisfies the assumption of parallel trends.

Parallel trend testing.

Robustness test

Using propensity score matching methods mitigates conclusion bias due to sample selection. In this research, 1:1 and 1:4 proximity matching and kernel matching are utilized for sample matching. The regression results are shown in Supplementary table 1.2 of part one of appendix 1 . It suggests that the conclusion is robust.

Placebo test

This paper performed the following 4 aspects of the placebo test to exclude random interference. First, a time placebo test is conducted. The establishment of NHTDZs was preceded by phases 1 to 10 as a pseudo-processing group to examine the significance of the placebo effect. Second, conducting spatial placebo, a number of individuals are randomly selected from the full sample and the pseudo-processing time is set to t 1 . The remaining sample pseudo-processing time was set to t 2 , which included 1000 samples. Finally, placebo tests were conducted with and without constraints, with randomized pseudo-treatment times for each individual in the sample within a specified range, without maintaining the community structure (without constraints) and with maintaining the community structure (with constraints). The results of the tests are shown in Supplementary Fig. 1.1 – 1.4 in of part one of appendix 1.

Excluding contemporaneous policies

To exclude the interference of related policies, this paper excludes low-carbon city pilot areas, key air pollution control areas, emissions trading areas, and carbon emissions trading areas. The regression results are shown in Table 2 . After excluding relevant interference policies, the conclusion is still robust.

Incorporation of predetermined variables

When establishing NHTDZs, areas with better initial environmental conditions may be chosen. Referring to Hua yue et al. 49 , the cross-multiplication terms of municipal wastewater emissions, the comprehensive utilization rate of general industrial solid wastes, SO2 emissions, nitrogen oxide emissions and the initial time are added to model(1). The results are shown in column (1) of Table 3 . The core coefficients are negative. The conclusion is still robust.

Replacing the explanatory variables

Considering possible measure error, the explanatory variables are reconstructed and included in the regression. Specifically, the ratio of total CO2 emissions to household population, the ratio of total CO2 emissions to urban area and the ratio of GDP to CO2 emissions were regressed separately into the baseline equation. The results are shown in columns (2)-(4) of Table 3 . The park coefficients are significantly negative.

Bacon decomposition

In order to estimate the carbon emission reduction effect of the pilot policy of the NHTDZs by using the two-way fixed-effect model, it is necessary to ensure that the treatment effect of the treatment group does not change with time in addition to satisfying the parallel trend。If the treatment effect is likely to vary over time, two-way fixed-effect model should not be used to summarize the estimated effect. Bacon decomposition helps provide a way to judge whether two-way fixed-effect model can provide meaningful causal estimates. Following the approach of Goodman-Bacon (2021) 91 , the estimators obtained from the two-way effect estimation are decomposed into a weighted average of all the classical 2*2DID estimators. If the estimated effects obtained by multiplying the coefficients of all type groups with the weights and summing them are essentially the same as the treatment effects obtained in the baseline regression model (1), this indicates that the two-way fixed-effects model has meaningful causality. The decomposition results are shown in Table 4 . Samples are divided into 12 timing group (Fig.  6 ), including an always-treated group and a never-treated group. There are two types of treatment in the timing groups, the early treatment group (experimental group) vs. the late treatment group (control group), and the late treatment group (experimental group) vs. the early treatment group (control group). The sum of weighted treatment effect is − 0.0253(P = 0.062, consistent with the results estimated from two-way fixed effects). Two-way fixed model provides meaningful causal estimates.

Bacon decomposition.

Reselection of samples

First, the research retains only the treatment group that establishes a NHTDZ for the regression. Multiple NHTDZs may have a stacking effect. Column 1 of Table 5 shows the results. Second, municipalities were deleted. Municipalities are at the same administrative level as the provincial level. They differ in terms of their built-up areas, population, resources, economic vitality and so on. After, excluding the municipality samples for regression, See column 2 of Table 5 for the results. Third, the sample size was adjusted. The NHTDZS establishment time was concentrated between 1988–1997 and 2007-present. Therefore, this paper excludes the NHTDZS established in 1988–1997. The regression results are shown in column 3 of Table 5 . The above tests are significantly negative, demonstrating that the findings are credible.

Transmission mechanism analysis

Technology upgrading effect.

The innovation data come from the statistical yearbook of each city. The green innovation data come from the China Research Data Service Platform (CNRDS). patents granted, utility patents, appearance patents and green utility patents indicate a city's innovation level respectively. The results are shown in columns (1) -(4) of Table 6 . In addition, the invention score of the Peking University Enterprise Big Data Research Center(PUEBDRC) indicates a city’s innovation level. The results are shown in column (5) of Table 6 . All of the above results show that the creation of NHTDZs significantly improves the city's innovation level. H2 is valid.

In summary, measuring the level of innovation in different dimensions suggests that the establishment of NHTDZs improves a city’s innovation capacity, further reducing carbon emissions. The impact of the setting of NHTDs on carbon dioxide emissions has a technological improvement effect. It refers to that the establishment of NHTDs increase technological progress. Technological progress reduces the total amount of carbon dioxide emissions or the production of more alternative products to reduce carbon dioxide emissions. The greater the ability to innovate, the lower the CO2 emissions, which may be due to: (1) Technological innovation is NHTDs’ core competitiveness. Low-carbon technology and carbon-free technology reduce the total carbon dioxide emissions; (2) Technological innovation can replace energy-consuming products by producing new environmentally friendly products, so as to achieve the effect of energy conservation and emission reduction. Shao Shuai et al. (2022) showed that the improvement of China's technological innovation capability has a restraining effect on carbon dioxide emissions 76 . Compared to provincial development zones or other special economic zones, NHTDs have a special status and establishment goals. They can play a better role in reducing CO2 emissions through innovative channels.

• Human capital

College graduates are an important force for national scientific technological innovation. Scientific technological talent is an important part of scientific research. This approach is crucial for improving the construction of a scientific research governance system and capacity. The NHTDs is an important platform for high-quality entrepreneurship and employment, and has become a base for continuously attracting high-level innovative talents, bringing together two-thirds of the entrepreneurial talents in the national entrepreneurship plan. The number of fresh graduates from colleges and universities increased from 472,000 in 2012 to 800,000 in 2021. The improvement in Chinese's human capital is mainly due to the increase in educational attainment 56 . The most visible manifestation of investment in human capital is investment in higher education 10 . By improving the structure of human capital and industrial structure, we will drive regional transformation and upgrading, shift from labor-intensive industries to capital-intensive industries, and evolve from low-value-added industries to high-value-added industries, so as to achieve green development. To test H3, education expenditures in government finance from the China Urban Statistical Yearbook are selected as proxy variables. The results in column (1) of Table 7 show that the creation of NHTDZs improved the government's financing of education emphasis, promoting human capital accumulation. If human capital is high, technological progress is very significant 78 , and carbon reduction targets can be effectively promoted. H3 is verified.

Research expenditure mechanisms

Technological progress is conducive to CO2 reduction. R&D expenditure is the key element in promoting technological progress. When R&D investment increases, the more advanced energy-saving and emission reduction technologies and equipment will be acquired, reducing CO2 emissions. Technological transformation is an ongoing process. The innovation of enterprises in the NHTDZs has a stable source of funding, a competitive external environment and policy support, etc. Under the condition of government cultivation and subsidies, venture capital has broken through the counter-cyclical nature and accelerated the turnover speed, which eased the constraints on R&D funds and accelerated the investment process of enterprises, thereby promoting carbon emission reduction. Whether the NHTDZs can promote carbon emission reduction by increasing investment in scientific research, the following steps are taken to verify hypothesis 4. The ratio of government expenditure to science technology expenditure indicates the degree of R&D support. The FDI score and ranking from PUEBDRC measure the degree of foreign investment attraction. The results are shown in columns (2)-(4) of Table 7 , indicating that NHTDZs increase their investment in science technology R&D by obtaining government support which promotes carbon emission reduction. H4 is tested.

Heterogeneity analysis

Regional heterogeneity.

First, due to differences in administrative level, urban vitality and informatization level, cities are divided into central and peripheral cities. The results are shown in columns (1) and (2) of Table 8 . The NHTDZs in the central city have more R&D capital and personnel, which produces a rainbow effect, reducing emissions. Second, the cities were divided into large and small cities according to the median population. It has been shown that larger populations in cities have a greater demand for resource consumption, which generates more CO2. As shown in columns (3)-(4) of Table 8 . NHTDZs in large cities have certain advantages in term of their technological level, human capital, openness, and basic transportation, and they can better reduce emissions. Finally, the cities are divided into coastal and inland areas, as shown in columns (5)-(6) of Table 8 . The carbon reduction in coastal cities is better. Because coastal cities are developed and are engaged in light industry and the industrial structure is more reasonable, coastal city carbon reduction is better. All the results were subjected to 1000 bootstrap intergroup coefficient difference tests (Subsequent tests for heterogeneity were also examined) , and the results were considered significant.

Resource Heterogeneity

According to the classification criteria of the National Sustainable Development Plan for Resource-Based Cities (2013–2020), cities are divided into resource-based and non-resource-based cities. Columns (1)-(2) of Table 9 show the regression results. The effect of nonresource cities is greater 92 . It may be that resource-based cities depend on resources in the initial stages. This leads to a development model dominated by resource-based industries, which produce more CO2.

Green finance heterogeneity

Green finance can formulate green standards and principles. It provides credit support for low-carbon projects, which helps enterprises in NHTDZs obtain more funds, reducing carbon emissions. Green credit, green investment, green bonds and green support indicate green finance. The results are shown in columns (3) and (4) of Table 9 and Table 10 . The emission reduction effect is more obvious in regions with a higher level of green finance.

Discussion, conclusion and insights

NHTDZs can achieve the goal of protecting the environment and ecology on the basis of economic growth 93 . Unlike previous studies that focused on economic impacts, NHTDZs policy is included in the analytical framework for influencing CO2 emissions. Hua Y et al. (2023) combined provincial high-tech zones and NHTDZs to study their environmental effects 94 . In this paper, NHTDZs have the advantages of being high grade and enjoying strong policies, only these zones are taken as the research objects for examining emission reduction intensity. Li X (2023) showed that NHTDZs can reduce CO2 emissions through scale effects and technological innovations 48 . This paper further enriches the knowledge on the transmission mechanism of human capital stock, research investment and attractiveness of venture capital, and the Bacon decomposition of emission reductions in NHTDZs.

The research in this paper has great practical significance, but there are some limitations. In terms of data use, this study uses the CADS, which only has carbon emission data up to 2019. the data for subsequent years is missing and cannot be estimated, resulting in a sample date that can only be used to 2019. In addition, although the reliability of the results has been verified by various robustness tests, there may be factors that cannot be completely ruled out and have a potential impact on the results.

In future research, the following aspects can be strengthened: in terms of data, the data source of the explanatory variables is only a single database. for example, the reliability of the conclusions can be tested by using the measured values of other databases. In terms of the depth of research on the NHTDZs; As an important base for high-tech industries, the NHTDZs need to study its actual role in the process of China's green development from more angles, so as to provide a theoretical basis for reality.

Conclusion and inspiration

The establishment of NHTDZs is an important initiative to implement the new development concept to realize sustainable development. It has great potential compared with other traditional policies. This paper verifies the impact of the establishment of NHTDZs on carbon emissions based on city-level data in China from 2003 to 2019. This study revealed that the construction of NHTDZs is effective at reducing carbon emissions. The conclusion remains robust after a series of tests such as the exclusion of contemporaneous policies and Bacon decomposition. The mechanism results show that NHTDZs facilitate carbon emission reduction by improving innovation levels, accumulating human capital, and promoting R&D expenditures. The heterogeneity analysis revealed that the carbon emission reduction effect was greater in the central city, which has a high level of green financial development, inland areas and nonresource cities.

The construction of NHTDZs can effectively reduce regional carbon emissions, and has a positive effect on improving the level of regional innovation, research capabilities and strict conditions. Therefore, the regional government should provide certain support to the provincial development zones and economic development zones and add national inspection targets to the assessment system, to meet the conditions for application in the NHTDZs. The importance of NHTDZs for emission reduction is highlighted.

Different cities should be supported to jointly apply to the NHTDZs. Research shows that different geographic locations of NHTDZs have different emission reduction effects. The approval conditions for NHTDZs are generally more stringent. If a joint application can be made across cities, the probability of success increases. This can not only lead to sustainable development, but also competition, increasing synergistic development.

The establishment of NHTDZs has occurred for more than 30 years. Earlier-established NHTDZs may outperform later-established NHTDZs. In addition, the NHTDZs’ targets are also various. In the subsequent research, NHTDZs can be divided into specific divisions with different development goals, highlighting the national policy of "one park, one policy".

This study appreciates support for a fund: Researches on the Optimization Path of Forest and Grassland Carbon Sink Policy in Inner Mongolia Autonomous Region under the Goal of “Double Carbon” (Project Approval No. GXKY22203).

Data availability

All data used in this study are available from the corresponding author upon request.

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How to Write a Research Proposal: (with Examples & Templates)

Table of Contents

Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.  

Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.  

This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.  

What is a Research Proposal ?  

A research proposal¹ ,²  can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.   

With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.  

Purpose of Research Proposals  

A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.  

Research proposals can be written for several reasons:³  

• To describe the importance of research in the specific topic  
• Address any potential challenges you may encounter  
• Showcase knowledge in the field and your ability to conduct a study  
• Apply for a role at a research institute  
• Convince a research supervisor or university that your research can satisfy the requirements of a degree program  
• Highlight the importance of your research to organizations that may sponsor your project  
• Identify implications of your project and how it can benefit the audience  

What Goes in a Research Proposal?    

Research proposals should aim to answer the three basic questions—what, why, and how.  

The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.  

The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.  

The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.   

Research Proposal Example  

Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.  

Structure of a Research Proposal  

If you want to know how to make a research proposal impactful, include the following components:¹  

1. Introduction  

This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.  

2. Literature review  

This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.  

3. Objectives  

Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.  

4. Research design and methodology  

Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.  

5. Ethical considerations  

This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.  

6. Budget/funding  

Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.  

7. Appendices  

This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.  

8. Citations  

Important Tips for Writing a Research Proposal  

Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5  

The Planning Stage  

• Manage your time efficiently. Plan to have the draft version ready at least two weeks before your deadline and the final version at least two to three days before the deadline.
• What is the primary objective of your research?  
• Will your research address any existing gap?  
• What is the impact of your proposed research?  
• Do people outside your field find your research applicable in other areas?  
• If your research is unsuccessful, would there still be other useful research outcomes?  

  The Writing Stage  

• Create an outline with main section headings that are typically used.  
• Focus only on writing and getting your points across without worrying about the format of the research proposal , grammar, punctuation, etc. These can be fixed during the subsequent passes. Add details to each section heading you created in the beginning.   
• Ensure your sentences are concise and use plain language. A research proposal usually contains about 2,000 to 4,000 words or four to seven pages.  
• Don’t use too many technical terms and abbreviations assuming that the readers would know them. Define the abbreviations and technical terms.  
• Ensure that the entire content is readable. Avoid using long paragraphs because they affect the continuity in reading. Break them into shorter paragraphs and introduce some white space for readability.  
• Focus on only the major research issues and cite sources accordingly. Don’t include generic information or their sources in the literature review.  
• Proofread your final document to ensure there are no grammatical errors so readers can enjoy a seamless, uninterrupted read.  
• Use academic, scholarly language because it brings formality into a document.  
• Ensure that your title is created using the keywords in the document and is neither too long and specific nor too short and general.  
• Cite all sources appropriately to avoid plagiarism.  
• Make sure that you follow guidelines, if provided. This includes rules as simple as using a specific font or a hyphen or en dash between numerical ranges.  
• Ensure that you’ve answered all questions requested by the evaluating authority.  

Key Takeaways   

Here’s a summary of the main points about research proposals discussed in the previous sections:  

• A research proposal is a document that outlines the details of a proposed study and is created by researchers to submit to evaluators who could be research institutions, universities, faculty, etc.  
• Research proposals are usually about 2,000-4,000 words long, but this depends on the evaluating authority’s guidelines.  
• A good research proposal ensures that you’ve done your background research and assessed the feasibility of the research.  
• Research proposals have the following main sections—introduction, literature review, objectives, methodology, ethical considerations, and budget.  

Frequently Asked Questions  

Q1. How is a research proposal evaluated?  

A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6  

• Significance —Does the research address any important subject or issue, which may or may not be specific to the evaluator or university?  
• Content and design —Is the proposed methodology appropriate to answer the research question? Are the objectives clear and well aligned with the proposed methodology?  
• Sample size and selection —Is the target population or cohort size clearly mentioned? Is the sampling process used to select participants randomized, appropriate, and free of bias?  
• Timing —Are the proposed data collection dates mentioned clearly? Is the project feasible given the specified resources and timeline?  
• Data management and dissemination —Who will have access to the data? What is the plan for data analysis?  

Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?  

A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.  

Q3. How long should a research proposal be?  

A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.  

Q4. What are the common mistakes to avoid in a research proposal ?  

A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7  

• No clear objectives: Objectives should be clear, specific, and measurable for the easy understanding among readers.  
• Incomplete or unconvincing background research: Background research usually includes a review of the current scenario of the particular industry and also a review of the previous literature on the subject. This helps readers understand your reasons for undertaking this research because you identified gaps in the existing research.  
• Overlooking project feasibility: The project scope and estimates should be realistic considering the resources and time available.   
• Neglecting the impact and significance of the study: In a research proposal , readers and evaluators look for the implications or significance of your research and how it contributes to the existing research. This information should always be included.  
• Unstructured format of a research proposal : A well-structured document gives confidence to evaluators that you have read the guidelines carefully and are well organized in your approach, consequently affirming that you will be able to undertake the research as mentioned in your proposal.  
• Ineffective writing style: The language used should be formal and grammatically correct. If required, editors could be consulted, including AI-based tools such as Paperpal , to refine the research proposal structure and language.  

Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.  

This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.  

References  

• Sudheesh K, Duggappa DR, Nethra SS. How to write a research proposal? Indian J Anaesth. 2016;60(9):631-634. Accessed July 15, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037942/  
• Writing research proposals. Harvard College Office of Undergraduate Research and Fellowships. Harvard University. Accessed July 14, 2024. https://uraf.harvard.edu/apply-opportunities/app-components/essays/research-proposals  
• What is a research proposal? Plus how to write one. Indeed website. Accessed July 17, 2024. https://www.indeed.com/career-advice/career-development/research-proposal  
• Research proposal template. University of Rochester Medical Center. Accessed July 16, 2024. https://www.urmc.rochester.edu/MediaLibraries/URMCMedia/pediatrics/research/documents/Research-proposal-Template.pdf  
• Tips for successful proposal writing. Johns Hopkins University. Accessed July 17, 2024. https://research.jhu.edu/wp-content/uploads/2018/09/Tips-for-Successful-Proposal-Writing.pdf  
• Formal review of research proposals. Cornell University. Accessed July 18, 2024. https://irp.dpb.cornell.edu/surveys/survey-assessment-review-group/research-proposals  
• 7 Mistakes you must avoid in your research proposal. Aveksana (via LinkedIn). Accessed July 17, 2024. https://www.linkedin.com/pulse/7-mistakes-you-must-avoid-your-research-proposal-aveksana-cmtwf/  

Paperpal is a comprehensive AI writing toolkit that helps students and researchers achieve 2x the writing in half the time. It leverages 21+ years of STM experience and insights from millions of research articles to provide in-depth academic writing, language editing, and submission readiness support to help you write better, faster.  

Get accurate academic translations, rewriting support, grammar checks, vocabulary suggestions, and generative AI assistance that delivers human precision at machine speed. Try for free or upgrade to Paperpal Prime starting at US$19 a month to access premium features, including consistency, plagiarism, and 30+ submission readiness checks to help you succeed.  

Experience the future of academic writing – Sign up to Paperpal and start writing for free!  

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Sabotage as Industrial Policy

We characterize sabotage, exemplified by recent U.S. policies concerning China's semiconductor industry, as trade policy. For some (but not all) goods, completely destroying foreigners’ productivity increases domestic real income by shifting the location of production and improving the terms of trade. The gross benefit of sabotage can be summarized by a few sufficient statistics: trade and demand elasticities and import and production shares. The cost of sabotage is determined by countries' relative unit labor costs for the sabotaged goods. We find important non-monotinicities: for semi-conductors, partially sabotaging foreign production would lower US real income, while comprehensive sabotage would raise it.

We are grateful to Corina Boar, Raquel Fernandez, Sam Kortum, and Jesse Schreger for valuable comments. Please contact [email protected] with any questions or comments. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.

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Character.AI CEO Noam Shazeer returns to Google

In a big move, Character.AI co-founder and CEO Noam Shazeer is returning to Google after leaving the company in October 2021 to found the a16z-backed chatbot startup. In his previous stint, Shazeer spearheaded the team of researchers that built  LaMDA  (Language Model for Dialogue Applications), a language model that was used for conversational AI tools .

Character.AI co-founder Daniel De Freitas is also joining Google with some other employees from the startup. Dominic Perella, Character.AI’s general counsel, is becoming an interim CEO at the startup. The company noted that most of the staff is staying at Character.AI.

Google is also signing a non-exclusive agreement with Character.AI to use its tech.

“I am super excited to return to Google and work as part of the Google DeepMind team. I am so proud of everything we built at Character.AI over the last 3 years. I am confident that the funds from the non-exclusive Google licensing agreement, together with the incredible Character.AI team, positions Character.AI for continued success in the future,” Shazeer said in a statement given to TechCrunch.

Google said that Shazeer is joining the DeepMind research team but didn’t specify his or De Freitas’s exact roles.

“We’re particularly thrilled to welcome back Noam, a preeminent researcher in machine learning, who is joining Google DeepMind’s research team, along with a small number of his colleagues,” Google said in a statement. “This agreement will provide increased funding for Character.AI to continue growing and to focus on building personalized AI products for users around the world,” a Google spokesperson said.

Character.AI has raised over $150 million in funding, largely from a16z.

“When Noam and Daniel started  Character.AI , our goal of personalized superintelligence required a full stack approach. We had to pre-train models, post-train them to power the experiences that make  Character.AI  special, and build a product platform with the ability to reach users globally,” Character AI mentioned in its blog announcing the move.

“Over the past two years, however, the landscape has shifted; many more pre-trained models are now available. Given these changes, we see an advantage in making greater use of third-party LLMs alongside our own. This allows us to devote even more resources to post-training and creating new product experiences for our growing user base.”

There is a possibility that different regulatory bodies, such as the Federal Trade Commission (FTC), and the Department of Justice (DoJ) in the U.S. and the EU will scrutinize these reverse acqui-hires closely. Last month. the U.K’s Competition and Markets Authority (CMA) issued a notice saying that it is looking into Microsoft hiring key people from Inflection AI to understand if the tech giant is trying to avoid regulatory oversight. The FTC opened a similar investigation in June to look into Microsoft’s $650 million deal.

You can reach out to this reporter at [email protected] by email and on signal at ivan.42 .

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Sports Industry: A Research Guide

• Introduction
• General Resources
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Soccer is a sport with overwhelming global appeal which continues to grow with an ever-expanding audience. Referred to as football in the rest of the world, professional soccer is truly an international sport. Estimates suggest that there are over 240 million registered players worldwide with fan participation in the billions.

The Federation Internationale de Football Association (FIFA) founded in 1904, serves as the international governing body of soccer and is composed of both men's and women's clubs from around the globe and is currently made up of 205 member associations with over 300,000 clubs and 240 million players. The president of FIFA is elected by the member organizations every four years and serves as the legal representative of the body and officiates at FIFA meetings.

In 1954, FIFA began the creation of continental soccer (international football) confederations. A conference for Europe, the Union des Associations Europeennes de Football (UEFA) comprised of 25 member nations, was the first to be established, followed by the Asian Football Confederation (AFC). The Oceania Football Confederation was the last confederation to join FIFA, initially in 1966 and then becoming a fully sanctioned member in 1996. All member nations clubs within each confederation compete for the World Cup, the championship trophy awarded to the best soccer team in the international league. There is both a Men's and Women's World Cup competition. Currently, FIFA is divided into six confederations and each confederation is responsible for governing the games of its member countries, with some autonomy, according to FIFA rules and regulations.

• Asian Football Confederation (AFC) — 45 member nations
• Confederation Africaine de Football (CAF) — 52 member nations
• Confederation of North, Central America and Caribbean Association Football (CONCACAF) — 35 member nations
• Confederacion Sudamericana de Futbol (CONMEBOL)
• Oceania Football Confederation (OFC) — 11 member nations
• Union des Associations Europeennes de Football — 51 member nations

In the United States and Canada, Major League Soccer (MLS) the men's professional soccer league was founded in 1993 as part of the United States' successful bid to host the 1994 FIFA World Cup. The United States Soccer Federation sanctions MLS and there are a total of 27 teams with 24 in the United States and the 3 in Canada with plans to expand by 2023. The season is 34 games; it starts in late February or early March, and runs through mid-October ending in a 14-team playoff culminating in the MLS Cup. The league has become more profitable since its founding gaining visibility and money though TV contracts and the addition Designated Player Rule which allowed teams to sign star players such as David Beckham and Wayne Rooney.

In April 2021, twelve elite English, Spanish and Italian clubs announced a Super League leaving the existing UEFA-run Champions League but within several days the teams in England (Manchester City, Liverpool, Manchester United, Arsenal, Tottenham, Chelsea) reversed course and other teams like Inter Milan were also expected to withdraw from the proposed league.

FIFA functions as a non-profit organization and most of its revenue is derived from TV broadcast rights and advertisements for the World Cup™ though the sale of licensing rights generates millions as well. Annual budgets are submitted to the FIFA Congress for approval each year and are considered cash budgets and include FIFA expenditures consisting mostly of operational costs and competitions, contributions to players, the confederations, and FIFA development programs.

During the first 20 years of FIFA's existence, its revenue was primarily generated from subscriptions from its associations and game levies, as well as increasing revenues from the World Cup™. After 1982, FIFA expanded its commercial ventures including advertising and merchandising with the most significant increases in revenue being in TV and marketing rights, which have continued to increase over time. Additionally, the Federation receives a portion of the gross receipts from "A" matches or games played between national teams with the amount being determined by the Federation.

Media and Marketing

FIFA's largest revenue generator is broadcasting of the World Cup.™ Billions tune in making it one of the most widely viewed sporting event in the world. Europe and the U.S. are the two largest markets in generating revenue from television broadcasting rights and the cost of the TV licensing rights agreement is expected to continue rise.

The Internet is also playing a role in the growing popularity of soccer. FIFA's official World Cup™ web site reached an unprecedented number of viewers worldwide. FIFA has also begun to utilize the Internet for its marketing strategies through selling and promoting game tickets and other Word Cup™ marketing products.

Millions of people around the world play soccer in local clubs, and the salaries of these players vary dramatically. European players are the most highly paid, but salary distribution and management varies. For instance, player salaries of many UK soccer clubs account for nearly 60% of club revenues while the U.S. Major Soccer League (MLS) institutes a player salary budget for each club.

The U.S. Major Soccer League is a member of FIFA, but it operates as a single entity, which contracts players with the league rather than with individual MLS teams. Each MLS team is given an annual salary budget and is required to manage the roster salaries according to the team budget. Major League Soccer Players Union (U.S.) has published salary information on individual players since 2007 on their web site but coming up with league totals is more of an issue.

Like many other professional sports, free agency has resulted in the dramatic increase in player salaries and fees paid for player contract purchases. This has led to growing income disparities between wealthy and poorer soccer clubs, and the vast difference in salaries between the new FIFA member clubs and the older more established soccer clubs has had an impact on the player talent gap. FIFA also contributes funding for player salaries in addition to contributing a small amount towards teams and participants. The players and teams participating in the World Cup receive the majority of their additional earnings from the World Cup matches rather than the through FIFA contributions.

Books & Periodicals

These are just a few of the more business-themed resources related to soccer. Note that there may also be relevant information in the General Resources section of this guide.

The following materials link to fuller bibliographic information in the Library of Congress Online Catalog . Links to digital content are provided when available.

Internet Resources

We have included some resources that are not business specific in an effort to provide sources that can help researchers understand the sport itself and its structure.

Papers & Reports

• 2018 Partnership Trends and Opportunities in Professional Football External This white paper from Euromonitor looks at strategies like using partnerships for revenue growth.
• Deloitte Sports Business Group - Annual Review of Football Finance External This report delves into key developments across European football, including the growth of the English Premier League and its financial record breaking season, as well as our own insights on improving strategy and governance in the business of sport. The current and some earlier editions are available on their website. They also produced "Football Money League 2019" (Bullseye) in January 2019.
• Deloitte Sports Business Group - Football Money League External The publication provides an independent analysis of the clubs’ relative financial performance. 2006-current is available on their website. Copies are for some other years are also available from the International Centre for Sports Studies (CIES).
• FIFA Official Documents External See the Governance section for Financial reports. The Federation Internationale de Football Association's official annual financial report that contains facts and figures. Full reports are on their website beginning in 2002. The report provides statistics and information on FIFA's income statement and budget. The report also includes annual highlights, forecasts, budget information, and a section on special topics including the Word Cup. Also has markets information, Audience Reports, Media Rights Licensees List.
• FIFA - Development External Official surveys, reports, facts/figures, on the growth and development of soccer worldwide as well as material for those people and organizations charged with increasing the interest in and access to soccer. The predominant focus is on women’s soccer. Includes material on Governance, Financial Support, Project Funding, Expertise, Education & Technical, and Medical issues.
• Market Forces in European Soccer External This paper by Marco Haan and Rudd H. Koning at the University of Gronigen was published in December 2001, it looks at the effects regarding player-labor market changes on national and international competitions from both a theoretical and an empirical perspective. The authors attempt to show that the competitive balance in national competition has not been affected. IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis.
• Stefan Szymanski External Dr. Szymanski is the Stephen J. Galetti Collegiate Professor of Sport Management who writes regularly for Forbes and The Guardian on the business and economics of sports. His articles include: "A Theory of the Evolution of Modern Sport," Working Papers 0630, International Association of Sports Economists & North American Association of Sports Economists and "Why Have Premium Sports Rights Migrated to Pay-TV in Europe but not in the US?," IASE Conference Papers 0308, International Association of Sports Economists. He has also written the books Handbook on the Economics of Sport (2005), Playbooks and Checkbooks : An Introduction to the Economics of Modern Sports (2009), and The Comparative Economics of Sport (2010). He also wrote Soccernomics with Simon Kuper. IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis.

Official Sites

• Federation Internationale de Football Association (FIFA) External
• FIFA Associations & Confederations External
• Asian Football Confederation (AFC) External
• Confederation Africaine de Football (CAF) External
• Confederation of North, Central American and Caribbean Association Football (CONCACAF) External
• Confederacion Sudamericana de Futbol (CONMEBOL) External
• Oceania Football Confederation (OFC) External
• Union des Associations Europeennes de Football External
• FIFA World Cup External
• Major League Soccer (MLS) External
• MLS Players Association External
• Premier League External This is the European Soccer League.
• BBC Sport - Football External
• CBS Sportsline - Soccer External
• ESPN - Soccer External
• Eurosport External
• Planet Futbol - Sports Illustrated External
• Soccer America External
• Soccer Times External
• Spotrac.com - MLS External The site was begun as a tool for fantasy players but now includes team payroll, player valuation, and is more of an overall research tool.
• Yahoo Sports - Soccer External

If you are looking to search the catalog for more general titles see the Search the Library's Catalog page. Additional works on professional soccer business in the Library of Congress may be identified by searching the Online Catalog under appropriate Library of Congress subject headings. Choose the topics you wish to search from the following list of subject headings to link directly to the Catalog and automatically execute a search that will allow you to browse related subject headings. Please be aware that during periods of heavy use you may encounter delays in accessing the catalog. If you are looking for soccer (or football) in outer countries you can replace "United States" with the name of another country.  For assistance in locating the many other subject headings which relate to the soccer business, please consult a reference librarian .

• Soccer teams.
• Soccer--Economic aspects.
• Soccer--United States.
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Two decades of advancements in cold supply chain logistics for reducing food waste: a review with focus on the meat industry.

1. Introduction

Objective and scope of study.

• What is the current state of the art on beef CSCL in terms of management, sustainability, network design, and the use of information technologies for red meat waste reduction?
• To provide an overview of the current state of the art and to identify the gaps and contemporary challenges to red meat waste reduction;
• To identify key research themes and their potential role and associated elements in mitigating red meat waste reduction, especially across the beef CSCL systems;
• To pinpoint the directions in each theme that warrant further research advancement.

2. Materials and Methods

2.1. literature retrieval and selection, 2.2. extracting the research themes, 3.1. the literature review identified themes and subjects, 3.2. the literature’s evolution and descriptive results, 3.3. management, 3.3.1. logistics management and chronological evolution, 3.3.2. management and regulations, 3.3.3. management and collaboration, 3.3.4. management and costs, 3.3.5. management and inventory, 3.3.6. management and decision-making, 3.3.7. management and risks, 3.3.8. management and waste reduction, 3.3.9. management and information, 3.3.10. management and cold chain deficiencies, 3.4. sustainability, 3.4.1. sustainability and closed-loop scs (clscs), 3.4.2. sustainability and business models, 3.4.3. sustainability and wastage hotspots, 3.4.4. sustainability and packing, 3.4.5. sustainability and information flow, 3.5. network design optimisation, 3.5.1. network design and decision levels, 3.5.2. network design and the location–inventory problem, 3.5.3. network design and routing-inventory problem, 3.5.4. network design and the location routing problem, 3.5.5. network design and the integrated location–inventory routing problem, 3.5.6. network design and sustainability, 3.5.7. network design and information flow, 3.6. information technologies, 3.6.1. it and meat sc transformation, 3.6.2. emerging information technologies and meat scs, technical instruments, technological systems, 4. discussion, 4.1. management, 4.2. sustainability, 4.3. network design, 4.4. information technology, 5. conclusions.

• Management: ◦ Effective management practices are crucial for addressing FLW in beef CSCL systems. ◦ There is a notable transition from LM to FLM and SFLM, with the potential for emerging technologies to create an “Intelligent Sustainable Food Logistics Management” phase. ◦ Suboptimal management practices continue to contribute significantly to FLW, underscoring the need for enhanced strategies and adherence to regulations and standards.
• Sustainability: ◦ Sustainability in beef CSCL involves addressing social, economic, and environmental benefits. ◦ Reducing FLW can lead to increased profits, improved customer satisfaction, public health, equity, and environmental conservation by minimising resource use and emissions. ◦ Comprehensive research integrating all sustainability dimensions is needed to fully understand and mitigate FLW. Current efforts often address only parts of sustainability. A more holistic approach is required to balance environmental, economic, and social dimensions effectively.
• Network Design: ◦ Effective network design and optimisation are pivotal in reducing FLW within beef CSCL systems. ◦ There is a necessity for integrating all three levels of management decisions in the logistics network design process. Decision levels in network design must be considered to understand trade-offs among sustainability components in this process. ◦ Future research should focus on integrating management decisions and network design, CSCL uncertainties, sustainability dimensions, and advanced technologies to enhance efficiency and reduce waste in beef CSCL systems.
• Information Technologies: ◦ Information technologies such as Digital Twins (DTs) and Blockchain (BC) play a significant role in improving efficiency and reducing FLW in beef CSCL. ◦ The integration of these technologies can enhance understanding of fluid dynamics, thermal exchange, and meat quality variations, optimising the cooling process and reducing energy usage. ◦ Challenges like data security and management efficiency need to be addressed to maximise the benefits of these technologies.

Author Contributions

Data availability statement, acknowledgments, conflicts of interest.

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Davoudi, S.; Stasinopoulos, P.; Shiwakoti, N. Two Decades of Advancements in Cold Supply Chain Logistics for Reducing Food Waste: A Review with Focus on the Meat Industry. Sustainability 2024 , 16 , 6986. https://doi.org/10.3390/su16166986

Davoudi S, Stasinopoulos P, Shiwakoti N. Two Decades of Advancements in Cold Supply Chain Logistics for Reducing Food Waste: A Review with Focus on the Meat Industry. Sustainability . 2024; 16(16):6986. https://doi.org/10.3390/su16166986

Davoudi, Sina, Peter Stasinopoulos, and Nirajan Shiwakoti. 2024. "Two Decades of Advancements in Cold Supply Chain Logistics for Reducing Food Waste: A Review with Focus on the Meat Industry" Sustainability 16, no. 16: 6986. https://doi.org/10.3390/su16166986

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