Chapter 3. Increasing effective use

The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law.

Increasing effective use: What matters most for policy?

Foster more sophisticated Internet usage for all

Promote the uptake of more sophisticated online activities; today, 74% of individuals use the Internet for email, but only 9% take online courses.
Close the significant usage gap between individuals with high versus low education levels for many key online activities, such as Internet banking.

Realise the potential of digital government

Shift from an e-government to a holistic and user-driven digital government approach, while further improving online public services; less than 60% of people across the OECD visit or interact with public authorities’ websites.
Ensure coherent use of digital technologies and data across all parts and levels of government and stimulate public sector innovation and civic engagement.

Boost adoption, diffusion and effective use of digital tools in firms, especially small and medium-sized enterprises

Boost the adoption, diffusion and effective use of advanced digital tools which drive productivity in firms; today, big data analysis is performed by 33% of large firms, but only by 19% of medium-sized and by 11% of small firms.
Promote investment in information and communication technologies (ICTs) and intangible assets, foster business dynamism and structural change, and support small and medium-sized enterprises (SMEs) to overcome challenges in adopting advanced digital tools.

Leverage skills for people, firms and governments to thrive in the digital age

Ensure everyone has the skills needed for a digital world; currently, only 31% of adults have sufficient problem-solving skills for technology-rich environments.
Review education and training systems to empower people to prosper and workers to succeed, and better exploit the possibilities of digital learning.

Address mistrust to increase online engagement

Raise awareness and empower people and businesses to manage digital risks to (re)gain trust in online environments.

The power and potential of digital technologies and data for individuals, governments and firms depend on their effective use. To foster more sophisticated usage, public policy should focus on narrowing the education gap. Governments should realise the potential of digital government, adopt a user-driven approach and make digital government services digital by design. To boost productivity, it is essential to promote the adoption, diffusion and effective use of advanced digital tools, especially in SMEs, including by promoting investment in ICTs and intangible assets, notably skills, and by fostering business dynamism. At the same time, policies need to strengthen trust in digital environments, for example by raising awareness and empowering people and organisations to better manage digital risk.

Foster more sophisticated Internet usage for all

Simple Internet use among individuals is widespread across the OECD. However, less than 80% of individuals are daily Internet users so far and more sophisticated online activities are less common in most countries. Typically, usage rates decline with the degree of sophistication of an online activity. For example, 74% of individuals use the Internet for email, but only 9% take online courses (Figure 3.1). In addition, most users tend to perform only a limited number of simple activities rather than a diversified range of activities, including sophisticated ones (OECD, forthcoming_[1]). Strikingly, activities related to personal and professional development, such as online courses or professional social networking, are among the least performed. Large differences in use also remain across countries, with a gap of over 80 percentage points, for example, in Internet banking between the countries with the highest and the lowest usage rates.

One key factor affecting individuals’ usage is educational attainment (and skills, further discussed below). The usage gap between high and low-educated individuals is over 40 percentage points for some activities, such as Internet banking. Users that perform many different activities, including more sophisticated ones such as online courses and content creation, are more likely to have a tertiary degree, whereas low-educated individuals more commonly carry out simple activities and use the Internet for communication and leisure (OECD, forthcoming_[1]). Other important factors influencing usage (that might be related to education levels) include age, employment status, income, gender as well as (non-)acceptance of using digital technologies. Policies that empower people, notably with the skills needed for more complex usage, are thus crucial to foster sophisticated Internet use for all (see Chapter 6).

Realise the potential of digital government

It is now imperative for governments to go digital themselves. For many countries, this implies a shift from e-government towards the more holistic and user-centred approach of digital government. Beyond digital public service provision, digital government includes the promotion of innovation in the public sector and expanded civic engagement (see Chapters 4 and 6).

A core principle of digital government is to leverage digital technologies more fully for a user-driven approach, i.e. to design, develop, deliver and monitor public policies and services centred around people and user needs (citizens and businesses), rather than based on top-down assumptions (OECD, 2018_[3]). Digital technologies should not only be used to digitise analogue processes and services, but as an opportunity to fundamentally rethink and reorganise government processes, procedures and services as being digital by design, and facilitate the involvement of people’s preferences and user needs as drivers of change. In line with this approach, countries are increasingly adopting a “mobile first” approach to digital government.

Digital technologies offer opportunities to increase access to, reach and quality of public services, and to improve policy making and service design. One key enabler of wider uptake of digital services across the economy and society are eIDs and electronic and/or digital signatures (OECD, 2018_[4]). For example, the Estonian government introduced a mandatory eID card that can be used for giving one’s digital signature. This has not only facilitated the use of digital government services, but has also required many Estonian businesses to upgrade their digital technologies to comply with the sophisticated digital security requirements of the eID card.

Many countries have digitalised at least some aspects of their public administration or services. For example, in 29 OECD countries, tenders are announced and contract awards notified via a national central e-procurement system, and in an increasing number of countries all tax filings for personal and corporate income tax returns are submitted online (OECD, 2017_[5]; OECD, 2017_[6]). Many OECD countries have advanced in using digital tools not only within and by the government, but in partnership with the private sector (Box 3.1).

3.1. Public-private co-operation on the collection of value-added tax on online sales

Digital technologies create new opportunities for co-operation between the public and private sectors. For example, such co-operation has taken place in the context of more efficient and effective tax collection. Several countries have introduced liability regimes for digital platforms related to value-added tax or goods and services tax (VAT/GST), with the objective to reduce the costs and risks for tax authorities of administering, policing and collecting VAT/GST on the ever-increasing volumes of online sales.

Some countries have introduced a regime that makes digital platforms liable for assessing, collecting and remitting the VAT/GST due on online sales facilitated by the platforms. While being implemented by a growing number of jurisdictions, this regime is still relatively new, in particular with regards to online sales that involve the importation of low-value goods. Some of these countries have complemented this approach with voluntary or obligatory information-sharing arrangements between platforms and tax authorities, as well as educational measures targeted to sellers on platforms. Other countries have chosen to limit requirements for digital platforms to information-sharing and specific measures to tackle possible fraud by online sellers.

Source: Ongoing project by the OECD’s Working Party 9 on Consumption Taxes.

However, at a much more basic level, significant potential still remains in many countries for general use and wider uptake of digital government services. Less than 60% of people across the OECD visit or interact with public authorities’ websites and many fewer use the Internet to download or send filled forms via public authorities’ websites (Figure 3.2). The available data on the use of digital technologies by governments are still largely limited to the uptake of digital government services by individuals.

Going beyond digital government services, digital government strategies are useful in promoting the effective use of digital tools within the public sector (OECD, 2014_[7]). For example, digital government strategies can help to more fully integrate digital technologies in decision-making processes, for shaping strategic agendas and for public sector, legal and regulatory reforms. A digital government strategy should also address major cross-cutting challenges governments face when going digital and help put in place key enablers of digital transformation. For example, coherent use of digital technologies across different parts and levels of government and public sector organisations as well as interoperable digital solutions and data standards, is essential.

Boost adoption, diffusion and effective use of digital tools in firms, especially small and medium-sized enterprises

A key condition for using digital technologies in firms is investment in ICTs. For example, investment in high-speed broadband (see Chapter 2) has strong positive effects on the adoption of digital tools (Andrews, Nicoletti and Timiliotis, 2018_[8]). While in 2017 average ICT investment as a share of gross domestic product (GDP) in OECD countries was 2.4%, many observers have pointed to a decrease since its peak in 2000, some of which may be attributable to the growing use of cloud computing by firms (OECD, 2019_[9]).

Indeed, the nominal value of ICT investment as a share of GDP for computer hardware and telecommunication equipment decreased between 1999 and 2015. However, investment in computer software and databases increased by 44% relative to GDP over the same period. Furthermore, the ratio of ICT investment to GDP increased in volume, i.e. when controlling for the increase in ICT prices relative to GDP prices. The increase in investment in ICT equipment relative to GDP was equal to 65% in volume over 1999-2015, i.e. the same as the increase in computer software and databases in volume (OECD, forthcoming_[10]).

Countries promote ICT investment through a variety of policy measures. For example, financial schemes tend to provide monetary support or incentives for the purchase of ICT equipment or towards ICT development. Non-financial support is often provided through targeted training, mostly focused on the digitalisation of business services, e-commerce, or on the effective use of digital media (see more on skills and training below) (OECD, forthcoming_[10]). Other approaches used across OECD countries include, in the order of frequency: measures to facilitate data (re)use across organisations and sectors, promotion of e-health applications and e-commerce, digital content creation and diffusion and measures to foster the uptake of the Internet of Things (IoT) and machine-to-machine communication (OECD, 2017_[11]).

Investment in ICTs is a necessary but not a sufficient condition for the diffusion of digital tools; a second essential condition is investment in complementary assets, knowledge-based capital (KBC) in particular, including research and development (R&D), data, design, new organisational processes, and firm-specific skills (see Chapter 4). For example, incentives to invest in R&D appear to be associated with greater adoption of customer relationship management (CRM) software and cloud computing (Andrews, Nicoletti and Timiliotis, 2018_[8]). For a number of years already, investment in KBC has increased faster than investment in physical capital (machinery, equipment, buildings) in many countries and significantly exceeds investment in physical capital in some (OECD, 2013_[12]). Today, investment in computer software and databases account for between two-thirds and a half of total ICT investment (OECD, forthcoming_[10]).

ICTs are only productive when firms effectively use the digital tools they invest in. Most firms across the OECD use at least a “basic”1 broadband connection and simple digital tools such as websites. However, significant scope remains for more widespread usage of more advanced digital tools, for example, for deeper digital market integration (i.e. e-purchases, e-sales, social media, customer relationship management software), digitalisation of business processes and firm re-organisation (i.e. enterprise resource planning [ERP] software, cloud computing, supply-chain management [SCM] software), or to leverage the IoT (i.e. radio-frequency identification [RFID]).

While, on average, almost 80% of firms have a website, only 30% purchase cloud computing. Wider diffusion is crucial given that many advanced digital tools are found to be productivity-enhancing, especially when combined with complementary investments in managerial and technical skills (Gal et al., 2019_[13]; Sorbe et al., 2019_[14]; OECD, 2015_[15]). Large potential could be unleashed in particular in SMEs. Currently, important differences exist for all digital tools by firm size; for example, big data analysis is performed by 33% of large firms, but only by 19% of medium-sized and by 11% of small firms (Figure 3.3).

Many of these digital tools are most widely diffused in ICT-intensive and services sectors; however, large potential also lies in their usage in manufacturing and industrial production. Two major trends have made digital technologies an increasingly transformational force for industrial production: 1) cost reduction, enabling wider technology diffusion; and 2) the combination of different technologies, enabling innovation and new types of applications.

While key digital technologies like big data analytics, cloud computing, and the IoT each by themselves have started to transform business and production models in many industries, including less digital-intensive sectors, their potential is even larger when used in combination. Building on these technologies, additive manufacturing (i.e. 3D printing), autonomous machines and systems, artificial intelligence (AI), robotics, and human-machine integration create additional potential for applications, productivity effects, and possibly disruption in a range of industries. Together, advanced application of these and possibly other technologies are likely to enable more and more fully automated production processes, from design to delivery (OECD, 2017_[17]).

Unleashing the potential of digital tools for firms to increase productivity requires successful diffusion (Box 3.2). Recognising the limitations of a linear technology diffusion model of the past for a dynamic and networked digital environment, approaches to boost diffusion should take into account not only the individual firm, but also their networks of suppliers, users and customers. Key actors and institutions for technology diffusion include government technology transfer offices, universities, other non-governmental stakeholders and test beds which can help to de-risk prospective investments. Examples of diffusion mechanisms used in different countries include industrial extension programmes, technology transfer, technology-oriented business services, applied technology centres, R&D centres, knowledge exchange and demand-based instruments. In addition, networks, partnerships, and open-source collaborations are increasingly important in orchestrating diffusion (OECD, 2017_[17]).

3.2. Uneven adoption and diffusion of digital technologies help explain the digital “productivity paradox”

One of the great promises of digital transformation is to drive productivity growth by enabling innovation and reducing the costs of business processes (Goldfarb and Tucker, 2017_[18]). But despite the diffusion of digital technologies since the mid-1990s, aggregate productivity growth has slowed over the past decade or so, sparking a lively debate about the potential for digital technologies to raise productivity. While some have suggested that this digital “productivity paradox” may partly be explained by inadequate measurement, OECD work suggests that this does not explain the slowdown (Ahmad, Ribarsky and Reinsdorf, 2017_[19]). Moreover, the adoption and diffusion of digital tools is not uniform across firms, industries, sectors and countries (Calvino and Criscuolo, forthcoming_[20]; OECD, 2017_[21]).

Importantly, the aggregate productivity slowdown masks a widening gap in multi-factor productivity growth among firms, with firms in ICT-intensive services sectors leading at the frontier (Figure 3.4). Throughout the economy, this divergence is driven not only by some leading firms pushing out the productivity frontier, but also by the stagnating productivity of a long tail of laggard firms with limited capabilities of, or lack of incentives for, adopting new technology and best practices (Andrews, Criscuolo and Gal, 2016_[22]).

These signs suggest that the main source of the productivity slowdown may not be so much a slowing of innovation by the most globally advanced firms, but an uneven uptake and diffusion of these innovations throughout the economy (OECD, 2015_[23]). This could also reflect being at the cusp of a new technological wave where only a few front-runners have mastered the new opportunities created by digital technologies, and the know-how needed to exploit these opportunities has not yet been codified for easy dissemination. Adoption and diffusion of digital technologies remain well below potential, but can be facilitated by public policies.

Sources: Goldfarb and Tucker (2017_[18]), “Digital economics”, https://www.nber.org/papers/w23684; Ahmad, Ribarsky and Reinsdorf (2017_[19]), “Can potential mismeasurement of the digital economy explain the post-crisis slowdown in GDP and productivity growth?”, https://dx.doi.org/10.1787/a8e751b7-en; Calvino and Criscuolo (forthcoming_[20]), “Business dynamics and digitalisation: A progress report”; OECD (2017_[21]), OECD Science, Technology and Industry Scoreboard 2017: The Digital Transformation, https://dx.doi.org/10.1787/9789264268821-en; Andrews, Criscuolo and Gal (2016_[22]), “The Best versus the Rest: The global productivity slowdown, divergence across firms and the role of public policy”, https://dx.doi.org/10.1787/63629cc9-en; OECD (2015_[23]), The Future of Productivity, https://dx.doi.org/10.1787/9789264248533-en.

Digital tools can help SMEs develop more efficient business processes and diverse product lines, as well as scale up and internationalise. However, their current underuse by SMEs highlights important barriers to adoption, which can include a lack of collateral to take risk and to access finance to invest in technologies and complementary assets, or a lack of key capabilities, e.g. human resources and management expertise. For instance, lack of investment in in-house innovation and organisational capabilities limits the capacity of SMEs to take full advantage of data analytics, engage in e-commerce and participate in knowledge networks. To help SMEs overcome barriers to effective use of advanced digital tools, governments need to support and better target policies to SMEs (Box 3.3).

3.3. Support and better target policies to small and medium-sized enterprises

To help SMEs overcome barriers to the use of advanced digital tools, policy makers can create favourable conditions for ICT adoption, such as policies that foster ICT investment, skills development and business dynamism. They must also address specific challenges faced by SMEs through more targeted policies. Examples of policy approaches include:

Support schemes to facilitate the adoption of tools that are particularly beneficial and may be new to SMEs, such as cloud computing, which requires limited up-front investment and offers flexible upscaling or downscaling of activities.
Measures to help SMEs overcome obstacles to better exploit and protect intellectual property and leverage other intangibles. This may include, for example, targeted skills development or measures to overcome hurdles to accessing intellectual property, such as administrative burdens and complex and costly litigation and enforcement mechanisms.
Policies targeting firms by size should avoid creating disincentives for SMEs to scale up. For instance, in the case of regulatory simplification for SMEs, efficient firms may choose to remain small to avoid the additional regulatory burden that may come with a certain size threshold.
Exemptions of certain rules for SMEs to facilitate regulatory compliance. For example, the EU General Data Protection Regulation includes a derogation for organisations with fewer than 250 employees with regards to data record-keeping.
Programmes that raise awareness of and create opportunities for linkages and partnerships between SMEs and larger firms, domestically and internationally, can help SMEs to exploit their potential in producing intermediate goods and digital services.

These and other policy measures to support SMEs may be taken into account in the context of a digital transformation strategy (see Chapter 9) to ensure coherence and co-ordination across different SME related measures implemented across different policy areas.

Sources: OECD (2017_[5]), Government at a Glance 2017, https://dx.doi.org/10.1787/gov_glance-2017-en; OECD (2018_[24]), “Enabling SMEs to scale up”, https://www.oecd.org/cfe/smes/ministerial/documents/2018-SME-Ministerial-Conference-Plenary-Session-1.pdf.

A business environment that encourages the most efficient allocation of resources and facilitates structural change also encourages the adoption and diffusion of digital technologies, with higher diffusion of selected digital technologies in sectors with higher firm turnover (i.e. entry and exit) (Calvino and Criscuolo, forthcoming_[20]). This is in part because the digitalisation of firms involves experimenting with digital technologies, with some firms successfully adopting digital tools and rapidly scaling-up, and others scaling-down and potentially exiting the market (Andrews and Criscuolo, 2013_[25]). However, data for the past decade shows that business dynamism has been declining in many OECD countries (Criscuolo, Gal and Menon, 2014_[26]) and resource misallocation is on the rise (Adalet McGowan, Andrews and Millot, 2017_[27]; Berlingieri, Blanchenay and Criscuolo, 2017_[28]).

Structural reforms can help boost business dynamism. In some countries, existing frameworks may implicitly or explicitly favour incumbents and hinder experimentation with new ideas, technologies and business models that underpin successful small and large firms. Policies that can affect competitive pressure and business dynamism, and in turn technology diffusion and better resource allocation, include: labour market regulations, employment protection legislation, and the design of insolvency regimes, e.g. less penalising sanctions for bankruptcy and lower barriers to corporate restructuring of insolvent firms (Andrews, Nicoletti and Timiliotis, 2018_[8]; Adalet McGowan and Andrews, 2018_[29]; Sorbe et al., 2019_[14]).

Leverage skills for people, firms and governments to thrive in the digital age

People need the right mix of skills to use digital technologies effectively in life and at work. The available evidence shows that the diffusion of online activities is more widespread among individuals with higher education levels than among less educated individuals (see Figure 3.1). Individuals with sound cognitive skills, notably numeracy, literacy, and problem-solving skills in technology-rich environments, are found to be most likely to perform a more diversified range of activities, including more complex/sophisticated online activities (OECD, forthcoming_[1]).

While a mix of skills is crucial (see Chapters 5 and 6), many adults, the elderly in particular, lack sufficient problem-solving skills in technology-rich environments. Only 31% of 16-64 year-olds perform at a medium or high level in problem-solving in technology-rich environments (Figure 3.5). If one considers a mix of skills that includes literacy and numeracy, the number of adults lacking basic cognitive skills to be productive in digital environments is close to one in five adults in several countries (OECD, forthcoming_[1]).

Additional skills are required for effective use of digital tools in firms or other organisations, including governments and the public sector. While the range of all skills or the precise combination of several specific skills needed differs depending on the usage, e.g. the online activity to be undertaken or the task that needs to be performed at work, and may further evolve over time, important skills include generic ICT,2 ICT specialist3 and data specialist4 skills, as well as complementary skills and competences that enable high-performance work practices5 (OECD, 2017_[11]; OECD, 2015_[15]), such as team work, autonomy, problem solving, creative thinking, communication, collaboration, and emotional intelligence and a strong ability to continue learning (see Chapter 5).

Several of these skills are directly associated with higher adoption of digital tools in firms. For example, the quality of management,6 ICT skills and the participation in life-long learning and on-the-job training are associated with higher adoption of CRM and cloud computing by firms (Andrews, Nicoletti and Timiliotis, 2018_[8]). While the right skills are equally important for digital government and the public sector (OECD, 2017_[31]), public employers, as well as smaller and laggard firms, tend to face challenges in recruiting talent, which is often lured by competitive offers from leading and large private firms (OECD, 2017_[32]).

Ensuring the long-term provision of skills that are needed in the digital age requires a fresh look at education systems. In addition to the central role of fundamental literacy and numeracy skills, every student needs access to education that delivers ICT and complementary skills, including problem-solving skills in technology-rich environments, to effectively navigate a digital world (of work). Curricula, in tertiary education in particular, need to ensure a sufficient number of courses for ICT and data specialists as well as options to acquire important complementary competences, such as social, communication or management skills. The acquisition of some important skills starts with early childhood education, which in turn should be considered to ensure equal access to key skills for all.

In view of faster returns to investment in skills, training is crucial, in particular the training of low-skilled workers. Whether publicly or privately provided, taken out of or on-the-job, firms and individuals alike may need incentives to provide and undergo training. While training high-skilled workers can foster technology diffusion, the greatest diffusion effects come from providing training to low-skilled workers. These workers also tend to face a higher likelihood of automation and are most in need of training (see Chapter 5), and the marginal benefit of training for technology adoption is twice as large for low-skilled than for high-skilled workers. This also implies that measures to train low-skilled workers are likely to entail a double dividend for productivity and inclusiveness (Andrews, Nicoletti and Timiliotis, 2018_[8]).

Important potential for making education and training more effective lies in better using of digital technologies for teaching and learning. Over the past decade, different approaches to digital learning have evolved and often improved access to and flexibility of learning, including by allowing access to education and training over the Internet (see Chapter 5), and/or by unbundling and personalising it. Examples include:

digital learning materials and open educational (online) resources, which create new possibilities such as digital annotations, machine-scorable online quizzes, links to tutorials, etc. and can greatly reduce cost per learner
blended or hybrid learning, which may take the form of digital face-to-face learning or flipped classrooms courses
personalised instructions and adaptive learning, including through games and enhanced through data collection, predictive analytics and AI
digital immersive learning that can facilitate faculty-student and student-student interactions and substitute for “hands-on” educational experiences.

While these approaches have much potential, when teachers are involved, the skills, motivations and attitudes of teachers are keys for the success of digital learning. For example, teachers’ problem-solving skills in technology-rich environments have a significant positive relationship with students’ performance in computer problem solving and computer mathematics (OECD, forthcoming_[1]).

Besides having enough of the right skills, allocating skilled workers to the jobs they are best equipped for is important to foster usage. Reducing skills mismatch is found to relate positively to economic performance and technology diffusion. For example, a lower skills mismatch is associated with disproportionately higher adoption rates of CRM software and cloud computing in knowledge-intensive sectors compared to other sectors (Andrews, Nicoletti and Timiliotis, 2018_[8]). While the best-performing firms, especially multinational ones, tend to have access to multiple labour markets and talent pools, and can attract talent with better paid and more attractive jobs, SMEs, laggard firms, and the public sector tend to face greater challenges in finding and competing for the human capital they need.

Address mistrust to increase online engagement

Trust underpins most digital relationships and transactions and a lack of trust is an important barrier to diffusion and effective use (see Chapter 7). Concerns about digital security and/or the protection of personal information can severely hamper individuals’ propensity to carry out online activities. In several OECD countries, over 30% of individuals report that they do not provide personal information on online social networks and, on average (EU28), 14% do not order goods or services online and refrain from Internet banking because of security concerns (Figure 3.6).

Such concerns can be grounded in negative experiences, such as being the victim of financial loss from a fraudulent online payment or from phishing/pharming; trust can also be compromised by re-occurring personal data breaches that have been increasing in terms of scale and profile over recent years (OECD, 2017_[11]). For businesses as well, trust is a key factor affecting the use of digital tools. For example, the risk of a security breach and uncertainty about the location of stored data are key reasons for businesses not to use cloud computing, and these concerns are reflected in cloud computing usage rates that are below potential, notably among SMEs (see Figure 3.3).

Mistrust is exacerbated by digital security incidents, including in the public sector, that have increased in terms of both sophistication and magnitude of impact over the past decade, as well as by privacy risks that increase with the collection and use of big data and the challenge to fully comply with relevant privacy regulation (OECD, 2017_[11]). These hurdles are particularly important for SMEs, which often lack the awareness and/or the resources to adequately manage digital security and privacy risks. Finally, governments may also face challenges to manage risk with regards to securing digital assets and services and privacy, for example when linking initially separate data sets or when opening up government data to the public. To address mistrust as a barrier for use requires all actors to better manage digital risk, i.e. build capacities to assess digital risk and reduce it to an acceptable level, including through risk mitigation and/or transfer (see Chapter 7).

References

Adalet McGowan, M. and D. Andrews (2018), “Design of insolvency regimes across countries”, OECD Economics Department Working Papers, No. 1504, OECD Publishing, Paris, https://dx.doi.org/10.1787/d44dc56f-en. [29]

Adalet McGowan, M., D. Andrews and V. Millot (2017), “The walking dead?: Zombie firms and productivity performance in OECD countries”, OECD Economics Department Working Papers, No. 1372, OECD Publishing, Paris, https://dx.doi.org/10.1787/180d80ad-en. [27]

Ahmad, N., J. Ribarsky and M. Reinsdorf (2017), “Can potential mismeasurement of the digital economy explain the post-crisis slowdown in GDP and productivity growth?”, OECD Statistics Working Papers, No. 2017/09, OECD Publishing, Paris, https://dx.doi.org/10.1787/a8e751b7-en. [19]

Andrews, D. and C. Criscuolo (2013), “Knowledge-based capital, innovation and resource allocation”, OECD Economics Department Working Papers, No. 1046, OECD Publishing, Paris, https://doi.org/10.1787/5k46bj546kzs-en. [25]

Andrews, D., C. Criscuolo and P. Gal (2016), “The Best versus the Rest: The global productivity slowdown, divergence across firms and the role of public policy”, OECD Productivity Working Papers, No. 5, OECD Publishing, Paris, https://dx.doi.org/10.1787/63629cc9-en. [22]

Andrews, D., G. Nicoletti and C. Timiliotis (2018), “Digital technology diffusion: A matter of capabilities, incentives or both?”, OECD Economics Department Working Papers, No. 1476, OECD Publishing, Paris, https://dx.doi.org/10.1787/7c542c16-en. [8]

Berlingieri, G., P. Blanchenay and C. Criscuolo (2017), “The great divergence(s)”, OECD Science, Technology and Industry Policy Papers, No. 39, OECD Publishing, Paris, https://dx.doi.org/10.1787/953f3853-en. [28]

Calvino, F. and C. Criscuolo (forthcoming), “Business dynamics and digitalisation: A progress report”, OECD Science, Technology and Industry Working Papers, OECD Publishing, Paris. [20]

Criscuolo, C., P. Gal and C. Menon (2014), “The dynamics of employment growth: New evidence from 18 countries”, OECD Science, Technology and Industry Policy Papers, No. 14, OECD Publishing, Paris, https://dx.doi.org/10.1787/5jz417hj6hg6-en. [26]

Eurostat (2018), Digital Economy and Society Statistics, https://ec.europa.eu/eurostat/web/digital-economy-and-society/data/comprehensive-database (accessed December 2018). [33]

Gal, P. et al. (2019), “Digitalisation and productivity: In search of the holy grail – Firm-level empirical evidence from EU countries”, OECD Economics Department Working Papers, No. 1533, OECD Publishing, Paris, https://doi.org/10.1787/5080f4b6-en. [13]

Goldfarb, A. and C. Tucker (2017), “Digital economics”, NBER Working Paper No. w23684, https://www.nber.org/papers/w23684. [18]

OECD (2019), “ICT Access and Usage by Households and Individuals”, OECD Telecommunications and Internet Statistics (database), OECD, Paris, https://dx.doi.org/10.1787/b9823565-en (accessed 28 January 2019). [2]

OECD (2019), “ICT Access and Use by Businesses”, OECD Telecommunications and Internet Statistics (database), OECD, Paris, https://dx.doi.org/10.1787/9d2cb97b-en (accessed 31 January 2019). [16]

OECD (2019), Measuring the Digital Transformation: A Roadmap for the Future, OECD Publishing, Paris, https://doi.org/10.1787/9789264311992-en. [9]

OECD (2018), “Enabling SMEs to scale up”, discussion paper, SME Ministerial Conference, OECD, Paris, https://www.oecd.org/cfe/smes/ministerial/documents/2018-SME-Ministerial-Conference-Plenary-Session-1.pdf. [24]

OECD (2018), Going Digital in a Multilateral World, OECD, Paris, www.oecd.org/mcm/documents/C-MIN-2018-6-EN.pdf. [3]

OECD (2018), OECD Regulatory Policy Outlook 2018, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264303072-en. [4]

OECD (2018), Survey of Adult Skills (PIAAC), OECD, Paris, http://www.oecd.org/skills/piaac (accessed in September 2018). [30]

OECD (2017), Core Skills for Public Sector Innovation, OECD, Paris, https://www.oecd.org/media/oecdorg/satellitesites/opsi/contents/files/OECD_OPSI-core_skills_for_public_sector_innovation-201704.pdf. [31]

OECD (2017), Government at a Glance 2017, OECD Publishing, Paris, https://dx.doi.org/10.1787/gov_glance-2017-en. [5]

OECD (2017), OECD Digital Economy Outlook 2017, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264276284-en. [11]

OECD (2017), OECD Science, Technology and Industry Scoreboard 2017: The Digital Transformation, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264268821-en. [21]

OECD (2017), Report on the Implementation of the Recommendation of the Council on Digital Government Strategies, internal document, OECD, Paris. [32]

OECD (2017), Tax Administration 2017: Comparative Information on OECD and Other Advanced and Emerging Economies, OECD Publishing, Paris, https://dx.doi.org/10.1787/tax_admin-2017-en. [6]

OECD (2017), The Next Production Revolution: Implications for Governments and Business, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264271036-en. [17]

OECD (2015), Data-driven Innovation: Big Data for Growth and Well-being, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264229358-en. [15]

OECD (2015), The Future of Productivity, OECD Publishing, Paris, https://dx.doi.org/10.1787/9789264248533-en. [23]

OECD (2014), Recommendation of the Council on Digital Government Strategies, OECD, Paris, https://www.oecd.org/gov/digital-government/Recommendation-digital-government-strategies.pdf. [7]

OECD (2013), New Sources of Growth: Knowledge-based Capital. Key Analyses and Policy Conclusions – Synthesis Report, OECD, Paris, http://www.oecd.org/sti/inno/knowledge-based-capital-synthesis.pdf. [12]

OECD (forthcoming), “ICT investments in OECD and partner countries: Trends, policies and evaluation”, OECD Digital Economy Papers, OECD Publishing, Paris. [10]

OECD (forthcoming), OECD Skills Outlook 2019, OECD Publishing, Paris. [1]

Sorbe, S. et al. (2019), “Digital dividend: Policies to harness the productivity potential of digital technologies”, OECD Economic Policy Papers, No. 26, OECD Publishing, Paris, https://doi.org/10.1787/273176bc-en. [14]

Wooldridge, J.M. (2009), “On estimating firm-level production functions using proxy variables to control for unobservables”, Economics Letters, Vol. 104, Issue 3, p. 112-114 https://doi.org/10.1016/j.econlet.2009.04.026. [34]

Notes

← 1. A “basic” broadband connection has an advertised download rate of at least 256 kilobits per second (kbps). In contrast, “fast” broadband features download speeds of at least 100 Megabits per second (Mbps).

← 2. ICT skills used at work include, for example, basic computer skills, communication and information search skills, and proficiency in using office productivity software

← 3. ICT specialists include ICT service managers, ICT professionals, ICT technicians, Electro-technology engineers, and Electronics and telecom installers and repairers.

← 4. Data specialists include mathematicians, actuaries, statisticians, and database and network professionals.

← 5. High performance work practices include skills and competences such as team work, autonomy, task discretion, mentoring, job rotation, and applying new learning, as well as management practices including bonus payments, training, and flexible working hours.

← 6. Proxied by the share of workers involved in management practices that stimulate employee and organisational performance and the training received by future managers in management schools.

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