• 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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Teleworking and productivity: a complex binomial

COVID-19 and the social distancing measures imposed to curb its spread have forced a large number of people to telework. This is a practice which has been somewhat uncommon in our society to date, but which will no doubt persist long beyond the current pandemic. The shift from going to the office – where a large number of tasks are carried out that could easily be performed remotely – to teleworking has ramifications in many areas, ranging from the purely economic to the social. In this article, we focus on the economic sphere, and particularly on the impact of teleworking on productivity.

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The pros and cons of teleworking: concentration versus collaboration

Nicholas Bloom, professor of economics at Stanford University, published an empirical analysis in 2015 on the benefits of teleworking in terms of labour productivity.1 The study, based on the results of an experiment conducted over a nine-month period in one of the world’s largest tourism service companies, concluded that remote working boosted workers’ performance by 13%. This improvement is attributed to them having both fewer distractions and fewer breaks per shift worked.2

A significant insight from the study is that adapting to employees’ preferences is a key factor. Thus, the increase in workers’ performance goes from 13% to 22% when teleworking is voluntary rather than imposed. After all, while it offers a potentially excellent way to boost concentration levels, teleworking also leads to social and professional isolation, which can have a negative impact on worker productivity.

In addition to boosting performance, two additional elements favoured further increases in the company’s productivity. Firstly, there was a lower staff turnover rate among the employees who worked remotely, which substantially reduces the costs associated with selecting and training new employees. Secondly, the lower maintenance costs of office buildings more than offsets the digital investment made in the homes of employees working remotely. These three elements (performance, staff turnover and maintenance cost savings), when taken together, represented an improvement in the productivity of the company analysed by Bloom of 20%-30%. But is creative work also more productive in a teleworking situation? Are there types of creativity that may particularly benefit from a shared working environment?

Open, flexible and versatile office environments facilitate creativity and innovation. In particular, an important element for innovation is knowledge sharing, a process that occurs more frequently and easily when face-to-face interactions occur between colleagues.3 The reason for this is none other than the climate of trust that this kind of face-to-face interaction generates. In fact, Silicon Valley’s big technology companies had not opted for teleworking prior to the pandemic precisely because worker interaction and collaboration is essential to their constant innovation in products and services.

At this juncture, however, it is important to make two clarifications. Firstly, the use of advanced technologies that enable frequent and relatively personal contact with workers remotely can also foster a climate of trust and, therefore, knowledge sharing. Secondly, new generations of workers (digital natives) may require less face-to-face contact in order to establish the links of trust needed to collaborate among colleagues.

Finally, remote working is not exempt from other problems. For instance, it has been documented that working remotely still carries a certain «stigma», as the amount of time a worker spends in the office is often associated with their commitment to the company.4 Bloom’s study, for example, identifies a negative relationship between teleworking and professional progress: if we consider two equally productive employees, the one working from the office was more likely to be promoted than the one working remotely.

  • 1. See N. Bloom, J. Liang, J. Roberts and Z.J. Ying (2015). «Does working from home work? Evidence from a Chinese experiment». The Quarterly Journal of Economics, 130(1), 165-218.
  • 2. Working overtime was not allowed during the experiment. The people working remotely used the time that they previously spent commuting to deal with personal matters, such that by the time they started their shift they did not need to take breaks to do so.
  • 3. See T.D. Golden and S. Raghuram (2010). «Teleworker knowledge sharing and the role of altered relational and technological interactions». Journal of Organizational Behavior, 31(8), 1061-1085.
  • 4. For example, J.C. Williams, M. Blair-Loy and J.L. Berdahl (2013). «Cultural Schemas, social class, and the flexibility stigma». Journal of Social Issues, 69(2), 209-234.
The case of Spain: how much are we talking about?

The work of Bloom and co-authors offers us a starting point for making a first approximation of the impact of teleworking on productivity in Spain. To perform this calculation, we will take as a starting point this study’s estimates on the impact of teleworking on workers’ productivity. We will then use the percentage of employees in Spain who could potentially work remotely (our estimates place this figure at around 33%).5 Finally, we will apply the so-called «translation rate»: as Bloom and co-authors warn, in order to make the most of teleworking, it is not enough merely for it to be possible to perform the work in question remotely; it is also necessary that the person wishes to do so and that they have the right conditions at home to perform their work (e.g. a separate room for working or a broadband internet connection).

  • 5. See the Focus «The COVID-19 outbreak boosts remote working» in the MR06/2020.
Macroeconomic impact of teleworking: scenarios

In the table we show the results in two possible scenarios. In a first, more favourable scenario, we consider the upper bracket of the productivity increase range reported by Bloom and co-authors (30%). We also consider a high translation rate of 75%, which means that most workers whose jobs can be performed remotely actually wish to work from home and have the conditions in which to do so. In a second, much less favourable scenario, we consider the lower bracket of the productivity increase range (20%) and a low translation rate of 25%. As can be seen in the table, the widespread adoption of teleworking could boost Spain’s productivity by between 1.4% and 6.2%.

At first glance, this may seem like a significant amount, especially given that the average growth in Spanish productivity between 2000 and 2018 was a modest 0.3% per year.6,7 However, when visualising a paradigm shift like the one we are proposing, we must picture a progressive change that could take several years. The arrival of computers in the 1970s and 1980s can serve as an example: their introduction led to substantial productivity gains, but these were gradual given that their introduction brought with them new ways of working and new products and services that are still having an impact on productivity growth to this day.

  • 6. Source: Bank of Spain.
  • 7. At a growth rate of 0.3% per year, it takes 19 years to achieve 6% growth.
Conclusions

Teleworking increases productivity. This increase is due to the fact that remote working creates an environment that favours concentration, reduces the number of breaks taken per shift worked, and offers savings for the company in terms of the cost of space and a lower staff turnover.

Nevertheless, in order to realise its full potential, a change in business culture is also required in order to adapt each occupation’s tasks to the working methods that are best suited to performing them. If the office remains the best space for innovation, then it may be interesting to explore ways of working that alternate remote working – a form that allows for higher concentration levels – with working face-to-face, so as to continue to drive innovation.

Similarly, the benefits of teleworking can only be realised if the worker can choose whether to work remotely or not, and if the space they have set aside for doing so and the other circumstances in which it is done are guaranteed to be suitable. Otherwise, the experience can prove counterproductive. As Nicholas Bloom, co-author of the article in favour of teleworking we mentioned earlier, said in a recent interview on the rise in teleworking during the COVID-19 crisis: «We are home working alongside our kids, in unsuitable spaces, with no choice and no in-office days... This will create a productivity disaster for firms.»8

  • 8. Adam Gorlick. «Productivity pitfalls of working from home in the age of COVID-19». SIEPR, 30 March 2020.