• Digitalisation of the agrifood sector: what does Twitter tell us?


    Technology is advancing at a frenetic pace and offers the agrifood chain a large number of opportunities to make its production more efficient and sustainable. Moreover, the arrival of COVID-19 has shown that the most digitalised companies were able to continue their activities more readily than the rest. In this article we examine the degree of popularity of the different digital technologies used in the primary sector and agrifood industry based on a text analysis of over 2 million tweets on Twitter. All these technologies are essential to create a connected ecosystem that will make up the Food Chain 4.0 of the future.



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    The unexpected arrival of the pandemic has shown that the most digitalised companies were more prepared to adapt to the new situation and were able to continue to operate much more smoothly than the rest. There is no doubt that, in this new environment, the digital transformation of companies is now unavoidable in order to boost their competitiveness.

    Big data, robotics, the internet of things and blockchain are just some examples of the new digital technologies gradually being adapted by firms, particularly in the agrifood sector. Technology is advancing at a frenetic pace and is offering the agrifood chain a large number of opportunities to produce more efficiently and sustainably. However, statistical information on the degree to which such technologies have been taken up, and the most comprehensive official statistical source1, does not provide information on the primary sector. Below we present a novel analysis of the «popularity»  of new digital technologies in the agrifood sector based on data from Twitter.

    • 1. Survey on the use of information and communication technologies (ICT) and e-commerce in companies, compiled by the National Statistics Institute.
    Twitter as a source of information to detect future trends

    Data from Twitter can be extremely valuable in detecting new trends as it allows us to analyse the popularity of certain terms according to how frequently they appear in tweets. However, it is true that «talking about something» is not the same as successfully implementing the various digital technologies in a company's recurring operations. For this reason the results presented below should be interpreted simply as an indication of new trends that may be taking root in agrifood companies.

    Data from Twitter allow us to analyse how popular the different digital technologies

    are in the agrifood sector according to how often they are mentioned in tweets.

    For this study, data was processed from over 24 million tweets sent by individual users and digital media during the period 2017-2019. Among these, 2 million corresponded to the agrifood sector. Using natural language processing techniques, the tweets were categorised according to mentions of different digital technologies and to the business sector.2 The key to obtaining relevant data from social media is to first define «seed» words or phrases to identify texts corresponding to each of the business sectors, as well as «seed» words or phrases related to the different digital technologies of interest.3 Using a machine-learning algorithm, other words and phrases related to the concept in question that were not initially included were also identified, thus broadening the spectrum of texts analysed. At this stage, it is important to carefully screen for polysemous words (i.e. those that have more than one meaning, such as the word «reserva» in Spanish, which can be used to refer to a hotel booking as well as an aged wine).

    • 2. This analysis was carried out in collaboration with Citibeats, a company specialising in unstructured natural language processing.
    • 3. For example, the «seed» woods and phrases used to identify big data were: analytics, arquitectura de sistemas (system architecture), data mining, database, inteligencia empresarial (business intelligence), Python and SQL, among others (as well as the term big data per se).
    What is the degree of digitalisation of the agrifood sector according to Twitter?

    To assess the agrifood sector's degree of digitalisation according to data from Twitter, we first need to know how common tweets about digitalisation are in other business sectors. The most digitalised industry according to our analysis is the information and communication technologies (ICT) sector: 3.2% of the sector's tweets contain terms related to digitalisation, a result that is not surprising given the very nature of the industry. Next comes finance and insurance with 2.7% of the tweets.

    This percentage is obviously lower in the primary sector at 0.6% but it is similar to the 0.7% for professional, scientific and technical activities. In the case of the agrifood industry, the percentage of tweets on digitalisation is only 0.3%, very close to the basic manufacturing sector (which includes the textile, wood, paper and graphic arts industries), with the lowest percentage among the sectors analysed, 0.2%.

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    Which digital technologies are most popular in the agrifood sector according to Twitter?

    The wealth of data obtained from Twitter allow us to identify the most popular digital tools in each business sector according to how frequently they are mentioned in the tweets examined. According to our analysis, a large proportion of the primary sector's tweets about digitalisation tend to include issues related to big data (45% of all tweets about digitalisation). One clear example of the application of big data in the sector can be found in «precision agriculture» techniques which require large amounts of data to be analysed to optimise decisions and thereby increase production and, in turn, ensure sustainability. These techniques are used, for instance, to calculate the irrigation requirements of crops by taking into account climatic conditions (sunlight, wind, temperature and relative humidity) and crop characteristics (species, state of development, planting density, etc.). To carry out this calculation, real-time updated meteorological data, a large computing capacity and fast data transmission speeds are all required for an automatic irrigation system to be properly adjusted. This technology helps to use water more efficiently, a highly relevant aspect in areas with a Mediterranean climate that are extremely vulnerable to climate change and where water is in short supply.

    Big data, the internet of things and robotics are the most popular technologies in the primary sector,

    indispensable for advancing the application of precision agriculture techniques and smart automated farming.

    Other popular technologies in the primary sector are the internet of things (16% of tweets) and robotics, including drones (10% of tweets). The new digital technologies promise to revolutionise the field of agriculture and stockbreeding by the middle of this century, the same as the mechanisation of farming in the xxi century. Agricultural Machinery 4.0 (which is closer to the robots in science fiction films than to the tractors we are used to seeing on all farms in the country) helps to increase productivity whilst also improving working conditions in the field. This trend towards more automated agricultural tasks has become stronger in the wake of the coronavirus pandemic, as the difficulty in recruiting seasonal workers due to international mobility restrictions has led to increased interest in robotics and agricultural automation. In fact, companies that manufacture robots for agriculture have seen a sharp increase in orders, such as robots that pick strawberries while removing mould with ultraviolet light.14 

    The use of drones warrants particular attention as this has grown exponentially in recent years and applications are increasingly widespread: from the early detection of pests and the aerial inspection of large areas of crops to locating wild boar with heat-sensitive cameras to prevent the spread of African swine fever to domestic pigs.5

    • 4. See Financial Times Agritech «Farm robots given Covid-19 boost», 30 August 2020.
    • 5. See http://www.catedragrobank.udl.cat/es/actualidad/drones-contra-jabalies

    The popularity of various digital technologies in the agrifood sector

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    Blockchain is the technology that stands out most in the food sector (30% of the total number of tweets on the sector's digitalisation) and this comes as no surprise as it has many different applications for the food and beverage industry. Producing a chain of unalterable, reliable records, blockchain makes it possible to guarantee the complete traceability of products throughout all the links in the food chain. Simply scanning a QR code provides access to all the data regarding the origin, production method, veterinary treatments received, ingredients used, etc. A large number of agrifood companies are already experimenting with blockchain as it offers clear benefits in terms of transparency regarding origin, product quality and food safety, aspects that are increasingly valued by consumers. Blockchain technology is also being used to limit food waste, another essential challenge for the sector.

    Blockchain enables the digital verification of food products,

    making them traceable throughout the links in the food chain.

    Compared with other sectors, which tools are particularly significant for the agrifood industry?

    There are some digital technologies that are not very popular across all economic sectors, perhaps because they have a more limited or specific range of application. These are technologies that, despite having a low percentage of tweets in absolute terms according to our study, may be relatively popular for a particular sector compared with the rest.

    To detect such cases, we have calculated a new metric, namely a concentration index which takes into account the relative popularity of technologies in a sector compared with the rest of the sectors.6 By using this methodology, we have found that the primary sector continues to stand out in terms of big data. Specifically, the primary sector concentrates 9.2% of the total number of tweets mentioning big data made by all sectors, a much larger proportion than the 3.1% share of primary sector tweets out of the total number of tweets analysed (as can be seen in the following table, in this case the concentration index is 3). We have also determined that the sector is particularly interested in the internet of things, as already mentioned, but have discovered that nanotechnology is also a relatively popular technology in the primary sector. In other words, although only 3.8% of the tweets in the primary sector deal with nanotechnology, this percentage is high compared with the 1.7% share of nanotechnology tweets out of the total (in other words, this technology is not very popular in general across all sectors but is slightly more popular in the primary sector than the others). This find is not surprising since genetic engineering is one of the fields in which technology has advanced most in order to boost crop yields. For example, by optimising the yield of vines it is possible to develop plants that are much more resistant to extreme weather conditions and pests.

    • 6. The concentration index is calculated as the ratio between (1) the percentage of tweets related to a particular technology and sector out of the total tweets for this technology, and (2) the percentage of tweets by a sector out of the total tweets of all sectors. Values above 1 indicate the technology is relatively more popular in that sector.

    Concentration index for tweets related to each technology in comparison with the other sectors

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    Finally, virtual and augmented reality is also a relatively popular technology in
    the agrifood industry.
    Specifically, the agrifood industry concentrates 6.2% of the total virtual and augmented reality tweets made by all sectors, a percentage that more than doubles the 2.5% share of primary sector tweets out of the total number of tweets analysed (the concentration index is equal to 2.5 in this case). This technology uses virtual environments (virtual reality) or incorporates virtual elements into reality (augmented reality) that provide additional knowledge and data that can be used to optimise processes. At first it may be surprising that this technology is relatively popular in the agrifood industry but its uses are spreading as the industry implements digital technologies in its production processes, in the so-called Industry 4.0. One specific example of how this technology is used is in repairing breakdowns. When a fault occurs, operators can use augmented reality goggles to follow the steps contained in virtual instruction manuals that are projected onto the lens to help resolve the incident. The glasses recognise the different parts of the machine and visually indicate to operators where they should act to solve the specific problem.

    There are numerous examples of new digital technologies being applied in the agrifood sector. We are witnessing a revolution that is destined to transform the different links in the food chain: from the exploitation of data and the use of drones to make harvesting more efficient to implementing blockchain technology to improve the traceability of the final products that reach our homes. In short, the future will bring us the Food Chain 4.0, a totally connected ecosystem from the field to the table.

    Destacado Economia y Mercados
    Destacado Analisis Sectorial
    Destacado Área Geográfica

The challenges of regulation of the sharing economy

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The growth of the sharing economy offers its users the possibility to enjoy the benefits associated with this new way of doing business, from better prices, to greater flexibility, to a more efficient use of underutilised assets.1 However, all that glitters is not gold: business models related to the sharing economy also pose new and exciting regulatory challenges. This should not surprise us, considering that the current regulations have not yet been fully adapted to such business models. Besides, these business models did not even exist when many aspects of the regulatory framework were designed, such as consumer protection rules or the taxation framework.

Thus, the challenge that governments face is significant. In fact, there is already a debate regarding the possibility of creating a specific regulatory framework that reflects the new arrangements specific to the sharing economy. In this article, we classify the challenges faced by regulatory agencies into three categories: challenges related to consumers, those related to companies and those related to the competitive framework that determines the relationships between consumers and companies.

Let us start with how the regulation of the sharing economy should focus on aspects concerning consumers. There are already some figures available which can help us to assess how consumers perceive this phenomenon. The results of a survey conducted by the European Commission revealed that, in 2016, more than half of respondents were aware of the collaborative economy, but only 17% had used the digital platforms which coordinate these activities.2 In this same survey, individuals who were aware of the sharing economy were asked which aspects of these new business models they considered the most unsatisfactory. Two out of every five agreed that one of the main drawbacks as consumers was the lack of knowledge about who should be held responsible for any problems that might arise when entering into a transaction.

This response perfectly exemplifies the existence of gaps that give many consumers a certain feeling of uncertainty when using goods and services provided by the sharing economy. In transactions within the traditional economy, consumers are protected by various rights bestowed on them by the regulatory framework which clearly define how transactions with companies must be carried out. In the collaborative economy, however, the responsibilities of each party involved in transactions are not usually well defined. Therefore, situations can arise in which consumers cannot claim a refund for a product, they do not have all the information regarding the nature of the product or service that they expect to receive, or in which the product or service does not comply with minimum health and safety requirements. This latter situation could occur, for instance, in the case of platforms which allow users to share meals prepared in individuals’ homes. Yet the challenges of regulation are not easy to overcome: is it appropriate for the private kitchens of these amateur chefs to have the obligation of passing the same hygiene checks as restaurants? Not necessarily, given that such regulation could create a very high barrier to entry, which would discourage the use of these activities. One argument used to prevent over-regulation in the sharing economy is that it can «self-regulate» through the different reputation and certificate models which enable users to rate one another, thus ensuring minimum quality and safety standards in a decentralised and informal manner. However, there are limitations to these methods, since it is not always possible to verify the truthfulness of these ratings. This example highlights the need (and how difficult it is) to define a regulatory framework to protect consumers, without discouraging innovation and the development of these business models.

We will now consider the regulation of the sharing economy in relation to businesses. One point to bear in mind is that companies in the sharing economy currently operate under a regulatory framework that was not designed specifically for them. This leads to regulatory gaps, which can make it difficult for tax agencies to trace transactions, thus favouring an increase in the submerged economy. The regulation should therefore be able to distinguish correctly between transactions involving non-professionals and those involving companies that use the platforms to sell their goods or services while reducing their tax burden. In this regard, the non-binding recommendations of the European Commission consider it good practice for member states to establish minimum thresholds, above which providers cease to be considered non-professionals and are treated as companies for the purposes of the legislation and taxation rules. Nevertheless, this proposal lacks specifics, since the recommendations do not determine what these limits should be, or even what metrics should be used to measure the thresholds, which are left to each member state (or even to regional and local authorities) to choose.

At the tax level, there is a need for greater harmonisation across Europe. On the one hand, it is well known that the lack of coordination between EU member states enables some companies to benefit from the more favourable tax regimes. On the other hand, the regulatory segmentation between countries makes it difficult for many companies linked to the sharing economy to expand internationally. The scalability of these platforms is a key factor in their development and adapting to each member state’s regulatory idiosyncrasies limits this scalability. As a result, online platforms in Europe are smaller in market capitalisation and scope than those in the US.3

Finally, with regards to the competitive framework, the emergence of these new companies can improve the situation for various players involved in the sharing economy. Their entry into the market has increased competition in each sector, which directly benefits consumers, who have a wider variety of suppliers to choose from, often at lower prices. Traditional competitors can also benefit from the entry of these new players if they are able to incorporate the disruptive technology into their business model and thus improve their productivity or reach a greater number of consumers.

However, the new business models pose at least two challenges for maintaining a proper competitive framework. The first is the lack of competition that can occur between companies in the sectors in which platforms linked to the sharing economy are emerging. This possible absence of competition is due to the fact that these platforms are based on interaction between different users and they generate what is known as network effect: the utility of a good or service increases with the number of users.4 As such, these markets may end up being dominated by a relatively small number of companies. It is therefore essential for the regulatory framework to take the idiosyncrasies of these activities into account and to ensure a healthy competitive environment that is free of monopolies, in order to prevent innovation from being restricted.

The second challenge posed by the emergence of new business models related to the sharing economy is defining a competitive framework that is equally rigorous for all companies in order to ensure a level playing field. As we have discussed, some platforms associated with the sharing economy have found loopholes in the current regulatory environment that have enabled them to gain certain competitive advantages (such as a lower tax or administrative burden). The challenge for regulators is to establish a flexible and agile framework which stimulates innovation and activity in the sharing economy without undermining legal clarity, which is essential in order for all players to be on an equal footing. This is clearly a difficult task: regulators will have to tread very carefully to find the best way to combine the need for greater flexibility, on the one hand, with the safeguard of legal certainty, on the other.

In addition to the complexity of all the challenges described in this article, these platforms are innovating at an astonishing rate – much faster than the regulatory authorities can adapt. As a result, to date, the regulation has been trailing behind the changes in the business models. The new regulatory framework should therefore be able to contain the problems mentioned above, while also seeking to remain relevant in relation to the future challenges that innovations will pose.

In summary, the sharing economy has brought many opportunities for consumers and businesses, but it has also created uncertainty for consumers, businesses and the competitive environment of the economy. What is certain is that it is here to stay. Authorities should therefore adapt the regulation to fit this new paradigm, and they should do so fairly, quickly and responsibly.

Ricard Murillo Gili

CaixaBank Research

1. See the article «The sharing economy: from emerging phenomenon to a key part of the digital revolution» in this same Dossier.

2. See European Commission (2016), «European agenda for the collaborative economy - supporting analysis», Commission Staff Working Document.

3. See G. Petropoulos (2017) «An economic review of the collaborative economy», Bruegel.

4. As an extreme example of a network effect, when the telephone was invented, the consumer who purchased the first one was not able to use it. However, as other consumers bought the new device, the utility of the first consumer increased as they were able to make calls to other people.