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

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    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.

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The sharing economy: from emerging phenomenon to a key part of the digital revolution

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What do terms such as the sharing economy», «on-demand economy» or «gig economy» suggest to you? Probably not that much. Even Americans, who live in the country where the phenomenon is the most developed, have little knowledge of it: when asked by the Pew Research Center in 2016, two-thirds of those surveyed had never heard of the sharing economy. Of the third that had, 40% emphasised an element of selfless collaboration between people, 25% stated that despite having heard the expression they did not know what it was, while 16% gave a much more accurate answer and said that it consisted of businesses or individuals sharing goods and services under short-lived arrangements.

Why do we say that this last group were closer to the mark? Well, when we review some of the hundreds of articles, case studies and policy proposals on the topic, we find that, besides the name, there are four elements that are repeated in most definitions. The first one is that the services of the sharing economy all tend to go through online platforms and, in most cases, these platforms are accessed via a mobile or tablet computer application. A second defining aspect is that the sharing economy involves peer-to-peer relations being established between either individuals or companies. A third characteristic element is that the relations that are established between the participants in the sharing economy are temporary in nature. Finally, the fourth ingredient of the definition is the exchange of assets, resources, time or skills, in a highly flexible and dynamic manner. Thus, if these four aspects are combined (since, individually, these elements can be found in other forms of doing business and are not specific to the sharing economy), it is likely that we are in the presence of a new phenomenon which hereinafter we will refer to as the sharing economy.

The fledgling nature of this phenomenon is denoted by how difficult it is to obtain reliable estimates about it using conventional statistics. For starters, a portion of the transactions of the sharing economy cannot be captured by the usual metrics, since they are non-pecuniary activities. However, in the case of transactions that involve monetary payments, it is possible to quantify them. In general, one of the two following approaches is used to do so: either monitoring the extent of the consumption or that of the supply.

In the first instance, and despite the evidence being limited, the main conclusion is that consumers’ use of the sharing economy is still in a minority. According to the most reliable reports, between 20% and 30% of consumers in developed countries have used the digital platforms that support these services or have shared some of the tangible or intangible assets that are exchanged on them. Another aspect which is sometimes analysed is whether households receive any income from the sharing economy. According to the Pew Research Center, in the US in 2016, approximately 25% of Americans had received income from the sharing economy, although if we exclude sales of second-hand goods, the figure is reduced by more than half.

Following the second approach, and according to what is perhaps the most frequently-referenced report on the matter,1 five major sectors are often identified as using sharing economy business models: accommodation between peers or users, transportation between users, on-demand household services, on-demand professional services and collaborative finance. According to this report, in Europe in 2015, transactions in these five sectors amounted to 28 billion euros, generating revenues for the related digital platforms to the tune of 4 billion euros. Although these figures by themselves do not seem excessive, the pace of growth over the last few years is rather remarkable, since the number of transactions tripled between 2013 and 2015, while revenues quadrupled.

In view of the pace of change we are witnessing, the immediate question to consider is what the future holds for the sharing economy. Addressing this question requires us to first reflect on what the key factors that explain the phenomenon’s growth are. In general, the emergence of the sharing economy and its future dissemination is the result of the confluence of changes in two different areas: those strictly in the technological sphere and changes in consumer expectations. With regards to the former, digitisation and platforms offer suppliers the opportunity to adapt what they offer to constantly-changing conditions with a high degree of flexibility. This flexibility comes from both the manner in which the service is offered (for example, with few timetable restrictions) and the possibility to exploit users’ information (most likely using big data technologies). The services provided are often offered at a much lower cost than usual, due to factors such as the elimination of conventional intermediaries and the exploitation of underutilised assets (obvious examples of assets that are often scarcely used include homes and vehicles, but this can also be the case for intangible assets, such as certain types of knowledge).

There have also been substantial changes in consumers’ expectations and demands. Generally speaking, the benefits that consumers obtain from the sharing economy are the result of a combination of traditional economic factors (lower prices, less time devoted to searching or better matching of supply and demand, to mention just the main ones) and other factors of a social or environmental nature. These latter factors can include the satisfaction that comes with following more sustainable and environmentally-friendly consumer practices, greater transparency in the transactions, purely altruistic reasons or a sense of co-creating or, at least, guiding the service in question (for example, by offering proposals and/or rating the experience).

If these are the factors underlying the expansion of the sharing economy, it is worth considering how they interact with different business models. As with other changes associated with innovation and technological shocks, it is generally possible to distinguish three possible situations. The first situation would involve business models which have been created from scratch, using digital platforms and the collaborative approach, and which have been able to meet consumers’ new demands. We will refer to these as «pure» business models. Chronologically, these «pure» business models were the first to materialise and are more clearly associated with the phenomenon of the sharing economy. A second group is what we will refer to as «revolutionised» business models, referring to those whose traditional way of competing is being substantially altered by the emergence of the sharing economy. These business models will probably have to create hybrid business models in the future, incorporating elements of digital collaboration into other aspects of their traditional core business. Finally, there will also be companies whose business model will not be affected by the sharing economy, or only marginally so, which we will label «traditional» business models.

The forward-looking exercises available mostly focus on identifying «pure» sectors, activities and business models (in which the factors that drive the sharing economy are being exploited extensively) and projecting their future trends. This is the case, for example, of the aforementioned study, which forecasts the platforms’ revenues, as shown in the accompanying chart. This chart predicts that the platforms’ level of income will increase more than 20-fold between 2015 and 2025 in the five sectors mentioned above (accommodation between peers or users, transportation between users, on-demand household services, on-demand professional services and collaborative finance).

We know less about what could prove to be the sharing economy’s main area of expansion, namely its extension to other business models that already exist. For example, can we think of any sectors in which there are underutilised assets, increasing sensitivity regarding environmental sustainability or pressure to engage in the process of creating the experience? If the answer is yes, the sector could be susceptible to being revolutionised by digital platforms. Once way to realise the potential of the process is to determine which sectors, as conventionally defined, are being affected by the «pure» business models and to see how important they are in the economy. According to Credit Suisse, in advanced countries, the «pure» activities of the sharing economy are interacting with sectors which represent somewhere in the order of 50% of the economy. While the sharing economy is unlikely to ever reach such a high level of penetration, this figure nevertheless serves as a reminder that few sectors can be considered immune to its disruptive effects. As such, companies should devise changes in their business models to convert competitive relationships with the sharing economy into relationships of cooperation.

In conclusion, the sharing economy is a new phenomenon, as its still-blurry definition denotes, but beyond the name, what seems to be emerging is a new way of doing business. If a new Adam Smith today were to undertake the ambitious intellectual exercise of conceptualising what we have come to call the «digital economy», he would probably no longer use his famous example of the pin factory to highlight key aspects. Rather, we suspect he would find it more enlightening to explore some digital platforms, through which, by the way, he could sell his new book (sorry, ebook) to his peers, directly, which we venture might be called something like «The (digital) wealth of individuals».

Àlex Ruiz

CaixaBank Research

1. See Vaughan, R. and Daverio, R. (2016), «Assessing the size and presence of the collaborative economy in Europe», PwC. Study commissioned by the European Commission to monitor the phenomenon of the sharing economy.

 

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