• 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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How will teleworking change urban mobility and residential decisions?

What are the implications of telecommuting for urban mobility and, from a longer-term perspective, the implications for the residential real estate market?

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The coronavirus pandemic forced a high percentage of Spaniards to telework. Although this percentage has been declining as the social distancing measures have been lifted, many companies are already considering the option of offering their employees a more flexible way of working, combining days working face-to-face in the office with working remotely.

In view of this foreseeable rise in teleworking, in this article we will analyse its implications for urban mobility and, from a longer-term perspective, for the residential real estate market. After all, many families decide to buy a home near their workplace in order to minimise the time spent commuting. However, if the need to go to work in person is limited to just a few days a week, the decision on where to reside may change considerably.

Teleworking potential: greater in large cities and also among highly-skilled workers

To answer the two questions we are posing (urban mobility and place of residence), first of all it is necessary to analyse the potential for teleworking that exists according to workers’ place of residence.

In 2019, only 4.9%1 of employed people in Spain worked from home on a regular basis. However, taking into account the tasks carried out by workers in different professions, it is estimated that no less than a third of all Spanish employees could carry out their occupations remotely.2 In other words, there is a high potential to increase the number of people who telework.

But is this potential uniform across the whole of Spain or are there significant geographical differences? What we see is that the potential for teleworking is much higher in big cities, as shown in the first chart. If we classify Spanish municipalities according to their population density, we see that 39% of workers residing in large cities could telework, compared to 30% in intermediate urban areas and 23% in rural areas.

  • 1. According to date from Eurostat: https://ec.europa.eu/eurostat/web/products-eurostat-news/-/DDN-20200424-1.
  • 2. Own estimate, based on microdata from the LFS and the methodology used by Dingel and Neiman (2020). See the Focus «The COVID-19 outbreak boosts remote working» in the MR06/2020.
Teleworking potencial by autonomous community, according to the population density of the minicipality of residence

It is no surprise that large cities have greater teleworking potential, as this is where a very high percentage of «office» jobs with high teleworking potential are concentrated, in contrast to factory or farm jobs that are more common in intermediate urban or rural areas.3 However, what may come as a surprise is the considerable difference between the two percentages: nearly 20 percentage points between large cities and rural areas.

If we conduct the same exercise at the regional (autonomous community) level, we generally observe the same distribution: a higher percentage of teleworking potential in urban areas than in rural areas. This list is topped by the Community of Madrid, which far exceeds the Spanish average, with a teleworking potential percentage in large cities of 45%. The location of numerous corporate headquarters, the concentration of universities and the percentage of civil servants (above the national average) certainly explain much of this difference.

Given that we are interested in analysing the impact of teleworking on mobility and on decision-making in relation to people’s place of residence, we will focus on young workers between the ages of 25 and 39, as this is the age range in which a home is usually formed. In general, young people have a teleworking potential similar to that of the population as a whole. However, one factor that has a decisive influence on teleworking potential is the level of education achieved: young workers with higher education have a very high teleworking potential (54%), compared to 17% among young workers with secondary education or 10% among those with a lower educational level. In addition, the teleworking potential of workers with higher education is much higher in large cities than in rural areas. In particular, the teleworking potential of young university graduates in large cities is 58%, compared to 43% in rural areas, a difference of 15 points. Furthermore, the percentage of young workers with higher education is much higher in the city than in the countryside (56.9% and 37.2%, respectively). It is therefore to be expected that the increase in teleworking will have a greater impact on the decisions of young university graduates living in cities.

  • 3. The data we obtain refer to the teleworking potential of people who live in cities versus more rural areas, and not to the potential of the occupations that exist in these locations. Nevertheless, we are assuming that a significant percentage of people living in cities work in these cities, and likewise in rural areas.
Teleworking potencial of young people according to education level and the population density of the minicipality of residence
Short term: teleworking and urban mobility

If teleworking becomes more prevalent, then the frequency with which workers will travel to their workplace will be reduced. In the short term, if we assume that workers do not change their place of residence, how many fewer daily commutes would we be talking about?

Recently, as a result of the COVID-19 outbreak, the National Statistics Institute of Spain has published highly-innovative mobility data based on mobile phone geolocation information.4 Although the data in question are not restricted to workers, they offer a good approximation for employees entering large Spanish cities. According to these figures, the 10 most populated cities in Spain receive just over 40,000 people per day on average. The ranking is led, naturally, by Madrid, with more than 100,000, followed by Barcelona, with more than 70,000. Bilbao is also high in the ranking, receiving some 34,000 people daily, which represents almost 10% of the city’s residents (see third chart).

  • 4. The data can be accessed interactively at: https://www.ine.es/covid/covid_movilidad.htm. In this article we use the data for the control week (18-21 November 2019).
Mobility to the 10 most populated Spanish cities

How many of these journeys could be affected by the rise in teleworking? While it is difficult to answer this question accurately, the available data can give us an idea. Assuming that around 35% of all journeys into large cities take place for occupational reasons5 and that the teleworking potential of the workers undertaking these journeys is around 40% (a figure that corresponds to the teleworking potential in urban areas, of which approximately 5% already telework), then the daily movements into large cities could be reduced by 12.5%. However, since working from home is often combined with days spent working face-to-face, the reduction in travel may be less. For instance, if these people were to work from home 60% of the time, then urban mobility would be reduced by around 7%. This figure has significant implications for reducing congestion on roads into cities and for cutting pollution.6

  • 5. Estimate based on the mobility study by ATM (EMEF.18).
  • 6. Moreover, mobility within large cities would be affected as a result of the lower number of journeys conducted by citizens who both live and work in the city itself and also opt to telework. This would lead to a significant change in the environment given that, in the major European cities, 40% of CO2 emissions from road transportation are the result of this internal urban mobility.
Long term: teleworking and the residential property market

Beyond the short-term implications for urban mobility, if these changes in working habits are consolidated, they could lead a considerable number of people, many of whom currently live in large cities, to rethink their place of residence. For instance, home buyers of the future may be able to acquire the most expensive homes in cities for less, since a large portion of the usual buyers (highly-educated people who work in offices) could opt for housing further away from the city centre. In addition, the buyer of such a home on the outskirts of big cities will no doubt demand more square metres in order to accommodate one or home offices where they can spend part of their working day, and they will likely demand gardens and common areas given that part of their free time will be spent within the home itself, since it would be located in an area with fewer leisure and cultural activities on offer.

The rise in Google searches for the term «buy house» following the outbreak of the pandemic was indicative of a possible shift of trend in this vein, suggesting a rise in the appeal of owning a house rather than living in a flat. Thus, if teleworking ends up becoming the norm, the supply of residential housing will have to adapt to these new preferences in terms of location and type of housing. Urban planning schemes should also be reviewed to accommodate this increased demand for residential property, as well as for the related public services (schools, hospitals, etc.) and transport infrastructures.7 After all, these are transformations which could help to achieve a better territorial balance.8

This does not mean that nobody wants to live in the city! Many jobs, such as those related to tourism or personal services, can hardly be carried out remotely. On the other hand, the preferences of households are highly varied and some people choose to live in the city not because of their work but because of the wide range of shopping, cultural and leisure activities on offer. Cities have also been, and will continue to be, focal points for development thanks to the significant synergies that take place within them in terms of the generation, dissemination and accumulation of knowledge. It is therefore unlikely that the rise in teleworking will reverse the secular trend towards greater urbanisation and population density in cities, but it could help to moderate it.

  • 7. In this regard, there would be an increase in journeys into large cities on the days when people attend the workplace in person, so the long-term effect of teleworking on urban mobility would be somewhat uncertain.
  • 8. The higher prevalence of teleworking could also lead to significant changes within the commercial property sector. All of these changes in demand and supply would result in price adjustments for offices, commercial premises, etc. between the different locations.