1. Introduction
The advance in the competitiveness of industries passing through the new industrial revolution, the digitalization of manufacturing, called Industry 4.0, is driven by groups of emerging and disruptive technologies [
1]. Through technological advances, there have been significant increases in industrial productivity since the first industrial revolution until where we are now, in the midst of a new industrial transformation driven by some key technologies such as big data, the cloud, and IoT [
2], bringing important contributions in terms of scalability and interoperability of solutions [
3]. The development of advanced electronic, information, and manufacturing technologies is changing the production process of companies [
4], which transforms traditional manufacturing into intelligent manufacturing, increasing the competitiveness and flexibility of organizations [
5,
6]. It is proven that the process of Industry 4.0 and digital transformation in emerging countries has its peculiarities and differs from developed countries [
7]. Consequently, emerging countries have their perceptions and particularities of Industry 4.0 technologies [
8]. Digital transformation and innovation processes are also making their way into the food industry, giving rise to Agriculture 4.0 [
2,
9].
The food industry encompasses different players, from farmers to food manufacturing and processing companies. As the world population grows [
10,
11], one of the challenges for agriculture and the food industry is to increase or optimize production and processing [
12,
13] sustainably. Agriculture plays a very important role in many countries’ gross domestic product (GDP) [
14]. In the world, agriculture accounts for 6.4% of GDP, and in some countries, it is the dominant sector [
15]. In emerging countries such as Brazil, agriculture is critical to improving economic performance in the coming years [
16,
17]. In countries with more developed economies, agriculture can also be used to leverage their international market share of agricultural products [
18]. In this context, digital transformation is emerging as an enabler for agricultural development and the food industry, transforming traditional food systems into advanced, technology-based systems [
19,
20].
Through Industry 4.0 technologies and digital transformation, conventional agriculture and the food industry will give rise to Agriculture 4.0 [
20,
21]. Digital transformation is defined as a process of change in the use of digital technologies that generates better performance in the processes of a business [
22]. Digital transformation is important because it stimulates the industry to seek changes [
23,
24,
25,
26]. On the other hand, digital transformation can increase uncertainty, as managers need to know what to commit to and what needs to be adapted faster [
27,
28,
29], generating results faster. Although digital transformation is becoming a strategic imperative in traditional industry sectors [
30,
31], how these industries will digitally transform remains unclear. There is a need to understand digital transformation and identify which digital technologies are most suitable for each industry sector [
32].
Moreover, the impacts of digital transformation can be measured to help verify improvements in competitiveness. The measurement of competitiveness can be used as a tool for strategic management, making it possible to monitor and optimize a company’s performance [
33,
34]. From this measurement, companies in the food industry can make comparisons. To improve their competitiveness, they must correctly invest their resources, adapt to the market, manage knowledge, and integrate new technologies [
35]. Still, the uncertainties of which Industry 4.0 digital technologies should be adopted in each industrial sector concern managers, making it difficult to invest in such technologies, especially in the food industry. The uncertainties worldwide affect all industrial sectors and are the main barrier to going forward with Industry 4.0/Agriculture 4.0, especially in emerging countries. Emerging countries do not have the economic empowerment and technical knowledge to bet in an environment with many uncertainties [
36,
37]. Measuring digital technologies’ impact on competitiveness might be an approach to guide industries to advance in their journey towards development.
1.1. Digital Technologies Adoption in Industrial Sectors
To advance in Agriculture 4.0, digital technologies from previous stages are required [
20]. As stated by the CNI report [
38] and Refs. [
39,
40], technologies such as sensors, CAD-CAM systems, and MES-SCADA systems from the third industrial revolution are still fundamental to Industry 4.0. It is important to highlight this due to the need for a minimum technological architecture to implement the integration and digitization concepts from Industry 4.0 [
2]. Based on this,
Table 1 presents a list of eleven technologies frequently associated with the Industry 4.0 concept [
38,
41,
42].
The digital technologies presented in
Table 1 are directly related to digital transformation and were used in the CNI survey; they comprise concepts such as vertical integration, horizontal integration, and end-to-end engineering [
24,
40]. Vertical integration refers to integrating all elements at the factory level until management-level decision-making [
43]. Horizontal integration refers to collaborating with different actors (e.g., suppliers and manufacturing enterprises) in the value chain, exchanging information and resources in real-time [
44]. End-to-end engineering integrates the entire value chain of the product, from its raw material until after-sales, to optimize the product and industrial processes [
45].
These three integrations are fundamental to achieving better results in industrial performance in the fourth industrial revolution [
46,
47]. However, which digital technologies should be integrated to achieve these results is a concern to managers. The adoption of Industry 4.0 digital technologies depends on the context of each industrial sector [
39]. Moreover, this adoption also depends on the country’s context [
48]. Despite the industrial sectors having similar manufacturing and process characteristics apart from the country, the context of each country should be considered, especially when related to their R&D investment level and technology acquisition. Therefore, the competitiveness and technology adoption levels will differ from sector to sector [
49].
The use of digital technologies arising mainly from Industry 4.0 has been the subject of research for over a decade, but there are still questions about how to apply them in practice. In this sense, this article seeks to explore the current status of implementation and knowledge of the leading technologies in different industry sectors in an emerging country, focused on the food industry, which is one of the links that make up the Agriculture 4.0 concept. To achieve the goal, two questions arise: (i) What is the current status of digital technology implementation in different industry sectors? (ii) Which digital technologies can be leveraged to increase the food industry’s performance towards Agriculture 4.0? The research questions take into account that different industry sectors have particularities. Still, it is important to analyze all sectors, seeking to understand how one sector can contribute to others [
39], and especially how other sectors can contribute to the digital transformation of the food industry, an integral part of Agriculture 4.0.
These questions were answered by ranking the competitiveness of different industrial sectors when implementing digital technologies to understand into which level the food industry fits. In answering the research questions, we present a framework of digital transformation to boost food industry competitiveness towards Agriculture 4.0. To do this framework, we analyze secondary data from a large-scale survey applied in Brazil by the National Confederation of Industries (CNI), comprising a sample of 2225 companies from different industrial segments in this emerging country. We used the multiobjective optimization by ratio analysis (MOORA) method, considering two weighting emphases for the criteria. The first emphasizes the alternatives and criteria with different weights, while the second considers the Fuzzy Delphi method’s integration for the weights’ unification. These procedures allowed us to provide an overview of the most prominent digital technologies for each industrial sector, always focusing on the food industry and giving an initial perspective to managers in an emerging country like Brazil. Finally, this study provides insights into how the 28 industrial sectors can contribute to the advancement of digital transformation in the food industry, contributing to developing the concept of Agriculture 4.0.
The results show that the most developed industries regarding digital technologies are the electrical, electronics, plastics, and vehicle industries, while the food industry is one of the industries that uses digital technologies the least. Emerging countries can contribute to developing digital technologies by doing groundwork and preparation, which can be replicated in other countries. Finally, the presented framework shows which technologies are the greatest drivers of competitiveness in the food industry towards Agriculture 4.0. This information should be the target of future research, showing how it should and can be used in practice to become accessible to any type or size of company. The advancement of research focused on certain technologies and applications contributes to the advancement of digital transformation in the food industry and the development of the concept of Agriculture 4.0.
The remainder of the paper is organized as follows.
Section 3 details the methodological procedures used,
Section 4 presents the results obtained,
Section 5 brings a broad discussion about the findings, and
Section 6 presents the paper’s conclusions.
2. Correlated Works
The current literature has provided us with the most important digital technologies responsible for transitioning from classical (current) digitization to Agriculture 4.0. The present work sought to investigate research on how the food industry can contribute to advancing the concept of Agriculture 4.0. Agriculture and the food industry are becoming increasingly innovative with new infrastructures, computing platforms, and biotechnologies such as gene editing or synthetic food production [
50]. Digital technologies are changing how companies do business and establish deeper relationships with customers, suppliers, and other stakeholders [
51,
52,
53]. For example, the food industry comprises many companies and represents the largest contributing industry in the European Union regarding economic output and employment [
54,
55]. In this context, Brazil is a major food supplier for the world market, which is constantly increasing. The rapid growth and development of digital technologies in the agriculture and food industry will lead to profound modernization in key sectors of the world economy [
56]. Despite its importance, studies on the agri-food sector are scarce [
57], as is information regarding digital transformation, which is a challenge for companies that were not originally digital and are on the verge of migrating to Agriculture 4.0 [
58,
59]. Agriculture 4.0 consists of the adoption of digital technologies to manage agricultural or industrial processes [
60,
61] to monitor different parameters [
62] based on a data set [
63,
64,
65]. The data can power food from crop cultivation to processing [
66,
67], lowering production costs and eliminating non-essential inputs [
68,
69]. The authors of [
70] report that adopting new digital technologies promotes a sustainable agricultural production chain. Agriculture 4.0 is also defined as the implementation of information and communication technologies (IoT, GPS, big data) on farms by farmers seeking to improve the quality and increase the productivity of their farms [
71,
72]. For [
9], Agriculture 4.0 should follow the examples of the evolution of European industries. The authors of [
73] add that Agriculture 4.0 represents an excellent opportunity to consider the variability and uncertainties in the agricultural and food chain. For the authors [
74,
75], economic development and digital technologies concern the sustainable environment. This evidence of the importance of studies focused on economic development will also bring sustainable development in the whole productive chain in which the food industry is inserted.
4. Results
We used the w-MOORA method to define the weights for the competitiveness of each Industry 4.0 digital technology using Question (i). We evaluated the scores of 11 digital technologies related to Industry 4.0 in 28 industrial sectors from the CNI survey [
38].
Table 3 shows our categorizations of the considered variables in our analysis.
We used the following criteria to determine the relevance of each technology: low ≤ 10 (not highlighted); medium = 11–18 (light gray highlighted); and high ≥ 19 (dark gray highlighted). As can be seen, most industrial sectors have at least one digital technology on a large scale (i.e., with the greatest potential to boost the competitiveness of the Brazilian industry over the next five years). Besides, most industrial sectors have two or more digital technologies on a medium scale. These findings show that the respondents expect good results in competitiveness from adopting Industry 4.0 digital technologies within five years. However, some digital technologies such as DAwS and Simulation are not expected to provide good results, with low scale as the main answer. The Fuzzy Delphi method helped us to obtain the weights for use in the FD-MOORA method. In other words, the opinion of all the industrial sectors was considered to assign a single weight to the importance of each digital technology. We used this procedure to understand the general importance level of digital technologies.
Table 4 presents the overall ranking of the most relevant digital technologies.
The digital technologies considered with the greatest potential for increasing competitiveness were: IES (integrated engineering systems), DAS (digital automation with sensors), Flex (flexible lines), Big Data, and MES-SCADA. Technologies such as flexible lines and big data are considered some of the most disruptive in Industry 4.0 [
39,
46]. At the same time, MES-SCADA, IES, and DAS are called integrative digital technologies and support the integration and connection of all elements of the factory [
40]. As evidenced, DAwS and Simulation have a low weight (lowest potential) when we incorporated FD-MOORA with w-MOORA, corroborating the previous results. Based on these data, we elaborated on the ranking of the Brazilian industry sectors with the most potential for competitiveness utilizing Question (i). The results of the two rankings are presented in
Table 5.
In the w-MOORA ranking, the five most competitive industrial sectors in Brazil regarding the use of digital technologies of Industry 4.0 are (1) electrical equipment, (2) computers, electronics, and optical products, (3) motor vehicles, trailers, and semi-trailers, (4) machinery and equipment, and (5) plastics products. These five industrial sectors had higher indexes, Yi > 35. From the sixth position in this ranking, the final indexes have smaller differences, all under Yi < 31. The five least competitive industrial sectors are (25) rubber products, (26) other transport equipment, (27) mining of non-metal ores, and (28) repair and installation, all under Yi < 12. In the FD-MOORA ranking, the top five positions are (1) computers, electronics, and optical products, (2) electrical equipment, (3) plastics products, (4) motor vehicles, trailers, and semi-trailers, and (5) basic metals with Yi > 26.5.
The rankings obtained by the two methods have differences and similarities. These differences and similarities are because, while the w-MOORA method considers only the specialists’ view of the industrial sector to calculate their respective competitiveness, the FD-MOORA method covers the opinion of all specialists, converging on a single weight to each technology. When different opinions are considered, it is possible to identify that the range of the final ranking is higher, with a standard deviation of 12.17. On the other hand, utilizing a single weight, the competitiveness index between the sectors is more leveled with a smaller amplitude, resulting in a standard deviation of 7.77. The ranking difference obtained between the two methods is detailed in
Figure 2.
It is observed that in both rankings, the first positions do not suffer excessive differences, showing that the opinion of the specialists of these companies converges with the general opinion of the Brazilian industry. The sharpest differences (above three positions) are in the sectors of pulp and paper (four positions), machinery and equipment (four positions), chemicals (four positions), and wood products (four positions), with the largest differences in the HPPC (nine positions) and printing and reproduction of recorded media (nine positions).
The companies that obtained a better position in the FD-MOORA ranking compared to w-MOORA are the companies in the pulp and paper, chemicals, and wood products industrial sectors. On the other hand, the industrial sectors that obtained a better position in the w-MOORA ranking and greater differences in comparison to the other ranking are machinery and equipment, HPPC, and printing and reproduction of recorded media. To summarize and complement the findings,
Figure 3 represents the level of competitiveness of all analyzed sectors and the utilization rate of digital technologies.
We used Question (i) from the CNI survey to illustrate which sectors of the Brazilian industry could achieve better competitiveness results using Industry 4.0 digital technologies. We also used Question (ii) to show what digital technologies are most utilized in each sector. The combination of Questions (i) and (ii) allowed us to understand the relationship between digital technologies already in use and the most prominent from the w-MOORA and FD-MOORA methods. The industrial sectors on the left are the most competitive, while those on the right are the least competitive. The circles represent the utilization rate of each digital technology for each industrial sector. On the left side, the important weight of each digital technology to boost competitiveness is represented. The range size illustrates the difference among weights. It is noted that the CAD-CAM, DAS, and IES technologies are the most utilized in Brazilian companies. The others do not have a high utilization percentage, with their thresholds below 21. All these analyses helped us to build
Table 6, which illustrates the adoption patterns and digital technologies with high implementation in each industrial sector.
We used the same criteria for ‘boost competitiveness’ in the w-MOORA method. In the case of ‘already in use’, we used the criteria in
Figure 3 for utilization percentage. Some digital technologies such as Big Data and DAwS have a considerable percentage in some industrial sectors, but we did not include them in
Table 6 due to our criteria utilization. Next, we discuss these findings with our final framework.
6. Conclusions
In this article, we analyze the level of competitiveness of 28 industrial sectors based on their perspectives on Industry 4.0 digital technologies. We evidenced that no sector of the Brazilian industry is engaged with disruptive technologies in their manufacturing processes. In addition, we defined three profiles (misaligned, partially aligned, and aligned) in the Brazilian industry, explaining their relationship with digital technologies in Industry 4.0. We discuss the reasons for these patterns, providing examples of behaviors in different industrial sectors in an emerging country, in this case Brazil. After defining these profiles, we further analyze the food industry, a key player in the global agro-industrial system. After the analysis and comparisons with other sectors, it was possible to identify that the food industry is partially aligned with digital technologies arising from advances in Industry 4.0 and Agriculture 4.0. This led us to conclude that the food industry needs attention to keep up with the technological development of other sectors to increase productivity and efficiency and enhance competitiveness.
The analysis of different industry sectors allowed us to visualize and indicate which technologies be leveraged for the competitiveness of the food industry, thus also taking a large step towards the development of the concept of Agriculture 4.0, which has the premise of applying technologies from primary food production to its processing. Agriculture 4.0, through technologies and digital transformation, can contribute to the sustainable increase of food production, especially in current times when the world population is growing rapidly and the adaptation of different crops and production systems to different demands must be faster. The industry is not engaged with disruptive technologies in its manufacturing processes.
The current literature has provided us with the most important digital technologies that are enablers of the concept of Agriculture 4.0. The present paper sought to investigate how the food industry can contribute to advancing the concept of Agriculture 4.0. To do so, we started with studies about the implementation of digital technologies in different industry sectors to understand the positioning of the food industry in this context. The results showed that the food industry has a low application of digital technologies and that to improve its performance, some technologies are more suitable for developing the industry. The food industry is one of the links in the Agriculture 4.0 concept. It was found that research in this area is more recent than the research on Industry 4.0, so this paper sought to explore this gap. As a result, we present a framework composed of three phases; classical automation represents the first phase, that is, with the technologies currently used by the food industry. The second phase is the transition to Agriculture 4.0, indicating which digital technologies are fundamental to starting a digitalization process in the food industry. The third phase is Agriculture 4.0 because the basic and essential technologies that permeate this concept are already in place, ensuring better communication throughout the food production chain. The novelty of this article is highlighted in the framework of
Figure 5. This figure can guide future research to enhance the transition of the food industry towards digitalization and implementation of technologies that make up Agriculture 4.0.
The investigation of several industry sectors was necessary to have an overview of the industry, finding patterns of technology adoption that could be shared across different sectors. In
Figure 4, we present this overview based on CNI’s database. Through
Figure 4, it was possible to find adoption patterns for the food industry, which gave rise to
Figure 5.
Figure 5 can be very useful for the companies and producers that make up the food industry and can also serve as a basis for consultation by policymakers and universities. For the managers in the food industry, it serves as a basis for the diagnosis and preparation of companies to make investments in new technologies, bringing gains to production and processing and making the transition to Agriculture 4.0. For policymakers and universities,
Figure 5 indicates which technologies would be more interesting to focus investments on, either through funding or research, because these are the technologies that most contribute to a rapid transition to Agriculture 4.0 according to the patterns studied in different sectors. In this sense,
Figure 5 can serve as a guide for the digital transformation of the food industry in the transition to Agriculture 4.0.
Limitations and Future Trends
The technologies presented in the framework of
Figure 5 are interconnected and allow the simulation of processes through virtual environments and their analysis. In emerging countries such as Brazil, the actors of the agroindustrial system still make little use of simulation and virtual systems as analysis tools to improve processes, improve productivity, or reduce production and processing costs. The identification of barriers and potential drivers for the application of these digital transformation technologies and making the transition to Agriculture 4.0 in Brazil’s agroindustrial system can be the target of future research, since Brazil is one of the largest food producers in the world and can serve as a model for the application and development of these technologies in other countries. Another important area of research is to analyze the social and environmental impacts that the use of digital technologies in the industry brings to other links in the food production chain.