Factual Evidence on Drivers of and Obstacles to Technology Adoption

narrowly at some sectors in developing countries. There is also some heterogeneity across countries regarding the identified main obstacle. Firms in Senegal cite lack of capabilities, while firms in Vietnam mention lack of demand.

Learning about perceived obstacles is important for policy makers. Addressing those issues that entrepreneurs already identify as main obstacles may facilitate political support to implement reforms. Yet, perceived obstacles and drivers do not necessarily imply that these are the most relevant issues faced by the firms. Firms do not know what they do not know. Having more factual evidence, including impact evaluations, about the elements that determine lack of adoption is critical to designing policy well.

Factual Evidence on Drivers of and Obstacles to Technology Adoption

This section reviews the factual evidence reported in the FAT survey about key drivers and obstacles for firm technology adoption. Following the framework in figure 6.1, these factors are divided into two groups: those external to the firm and in the enabling environment; and those internal to the firm. External factors that are part of the enabling environment include infrastructure, markets and competition, financial constraints, and access to external knowledge. Internal factors to the firms that affect firms’ capabilities and knowledge include information and behavioral biases, management quality and organization, and know-how and skills.

Factors External to the Firm: An Enabling Environment

Infrastructure Infrastructure in general, from electricity to roads and telecommunications, plays an important role as an enabler of technology adoption by firms. Evidence across African countries, for instance, suggests that the spread of fast internet connection has increased firm entry, productivity, and exports in African countries (Hjort and Poulsen 2019). The rapid spread of the internet, as described in chapter 1, and recent increase in the demand for digital technologies due to the COVID-19 pandemic have heightened the role of digital infrastructure.

To assess the effect of digital infrastructure on adoption, we use a unique data set for Senegal that allows the impact of geographic proximity to internet infrastructure to be measured.8 In the spirit of Hjort and Poulsen (2019), the analysis, described in Berkes et al. (forthcoming), combines information on the GPS location of the firms that participated in the FAT survey in Senegal with the location of the node of the Senegalese internet backbone. It then explores the contribution of digital infrastructure to the adoption of technologies through the effects of the proximity to the nodes, which translate into having access to better quality internet service, which was improved through the arrival of submarine internet cables in 2011.

Map 6.1 shows the distribution of firms (blue dots) and the location of the nodes of the Senegalese internet backbone (red dots). Panel a describes the distribution of firms in the data, selected from a random sample drawn from the latest establishment census. Panel b replicates this information for firms with internet access.

The results show that the distance to a node of the Senegalese internet backbone is a strong predictor of having an internet connection. Specifically, doubling the distance from a node reduces the likelihood of having an internet connection by 5 percentage points (figure 6.4).9 Interestingly, the effect is even stronger (7 percentage points) when considering only the subset of firms established more than 10 years ago, suggesting that these firms already existed before the arrival of submarine internet cables. As expected, proximity to a node increases the likelihood of having a high-speed DSL connection.10

More important, the analysis can be extended to explore the impact of having internet on the sophistication of technology use, using instrumental variables to better identify the causal effect.11 Figure 6.5 shows that the quality of internet service can explain only adoption of more sophisticated technologies for general business functions at the extensive margin, but not for sector-specific business functions, on average, where digital may be less prevalent and internet service less of an enabler. Results are robust when restricting the sample for firms with 10 or more years of age.

Overall, the results confirm the importance of digital infrastructure as an enabler of technology for firms, but they also show that facilitating access to the internet due to improvement of infrastructure does not explain a large variation of technology sophistication across firms. In the case of sector-specific business functions (SBFs), the results can be explained by the fact that many SBFs—particularly in agriculture and manufacturing—are not fully digital or are embedded in sophisticated machines that many firms cannot afford or that pose other types of barriers in terms of firms’ access to information or know-how.

Markets, Competition, and Regulation Market structure and competition are critical external drivers for technology adoption. Competition provides incentives to adopt new technologies. For instance, competition from China has driven increases in innovation and the adoption of information and communication technologies (ICTs) in the United Kingdom (Bloom, Draca, and Van Reenen 2016). However, since work by Aghion et al. (2005) found an inverted-U relationship between innovation and competition, the literature has been more nuanced about this relationship depending on the type of market in which the firms operate. Generally, greater market competition can help enable innovation and technology adoption, especially in cases where competition is low to start with, but this pattern varies greatly by sector, and the regulatory environment can shape firms’ decisions (Hannan and McDowell 1984). Regulatory issues are also critical when it comes to adoption of certain data-intensive technologies and access to digital platforms (see box 6.1).