The agricultural industry has always been considered very important economically, socially, and environmentally. In recent years, agricultural industries are beginning to use digital technologies, such as business information systems, to integrate them into their processes. Business information systems make it possible to gather information in real time, improving productivity and product safety. The adoption of information systems is still limited. The aim of the article is to explore, by combining a literature review and a survey, the enabling factors, barriers, and outcomes of business information system adoption by agricultural industries in Italy, adopting a socio-technical perspective.
The agricultural industry is a relevant sector in worldwide economies, both for the industry’s size, the relevance of the production activities that guarantee food to the world population, and the sustainability impacts of such productions [1, 2]. Organisations working in the industry are adopting digital technologies supporting a transformation process of the sector towards Agriculture 4.0. These digital technologies afford organisations to collect, manage, analyse, and generate useful information for decision-making and action [3, 4]. Digital technologies like business information systems are widely used to manage operational and administrative processes. These systems allow real-time information collection to improve productivity, and product safety [5, 6]. In transitioning towards Agriculture 4.0, agriculture organisations work in contextual conditions characterised by specific organisational, economic, demographical, and technological factors that may impact digitalisation.
Despite the relevance of the industry and considering the specific contextual conditions, research on the digitalisation of agricultural industries is still limited. In this paper we intend to explore, combining a literature review and a survey, the enabling factors, barriers, and outcomes for the adoption of digital technologies by agricultural firms in Italy, adopting a socio-technical perspective. We specifically focus on business information systems, and we aim at both identifying the factors affecting the digitization of the industry and their connections. This paper aims to answer the following research question: What is the connection between enablers, barriers, and outcomes of business information systems adoption in agriculture organisations?
The paper is structured as follows. Section 2 contextualizes the enablers, barriers, outcomes, and context of Italian agricultural industries. Section 3 introduces the data collection and analysis methodology, while section 4 presents the results. Section 5 introduces the discussions and implications, and finally, Section 6 includes conclusions and future research.
This paper builds over two streams of literature: digitalisation in the agricultural sector and socio-technical systems theory. Each of the two streams of literature is summarised in the subsections below.
The digitisation of agriculture is a process in which organisations adopt modern digital technologies to pursue organisational and business benefits such as process automation, optimisation of operations and business development [7, 8]. In the literature, the digitalisation process of agricultural industry organisations is indicated with a plethora of different names [9– 11]. For simplicity, in this paper, we will use the term Agriculture 4.0 to refer to the many different application areas – including both the operational and the administrative processes – of digital technologies in the agricultural industries to support and automate processes, collect data, and identify useful information in decision-making processes [7, 12, 13].
More and more technologies are being adopted in agricultural industries and among these are robots, which automate operational activities [13]. The Internet of Things allows various objects to be connected to provide relevant information to end users [2, 12]. Objects are defined as intelligent because they are connected to each other and interact through appropriate infrastructures based on local and global networks [14]. Big data help organisations in decisionmaking, solving internal problems and especially in planning operations [7]. Finally, business information systems are also technologies that can increase awareness of production activities, offering useful information to increase the performance of agricultural industries [4]. In Italian agricultural industries, the adoption of digital technologies is still very low. In 2021, the Agriculture 4.0 in Italy amounted to EUR 1.6 billion, but only 6% of the total area was cultivated with digital technologies [15]. According to ISTAT data, 26.1% of digitised agricultural industries are engaged in production and livestock farming, 18.4% in livestock farming, and 13.1% in agricultural activities [16].
Italian agriculture is in a renewal phase and must guarantee support for producing and distributing products to make them fast, functional, and safe [17].
Most of the research on Agricultural 4.0 limits the exploration on the functional and technical affordances of digital technologies on the operational processes with an agronomic perspective or limits to the assessment of the acceptance of digital technologies by farmers or employees [18– 20]. For a more detailed understanding of the enablers, barriers, and outcomes of business information systems adoption, in this paper, we aim to analyse the Agriculture 4.0 from a sociotechnical point of view. A socio-technical views decomposes each setting in which people interact with digital technologies in two sides: the technical side, and the social side. These two sides are mutually interactive and needs to be addressed conjointly when approaching information systems design or evaluation.
The technical side is composed by technology and tasks, while the social side is composed by people and organisations. The two components of the social and technical side have mutual interactions and need to be addressed together for a deeper understanding of the complex dynamics developing in information systems adoption. The interactions of the sociotechnical systems adopted in this paper and summarised as proposed by Bostrom and Heinen [21], are represented in Figure 1 below.
We will use this model to classify the enabling factors, the barriers, and the results of adopting information systems, integrating the environmental aspect as an element of study and classification, and we will explore the sociotechnical interaction among these factors.
Our research consists of two different phases: the literature review and the questionnaire. By extrapolating the enabling factors, barriers, and adoption outcomes from the literature, we designed a questionnaire to test the relevance of the factors with respect to the adoption of business information systems. The collected data are analysed to see if there is a connection between business information systems adoption and the barriers, enablers and outcomes identified in the literature.
The methodology used involves nonparametric tests, specifically the chi-square test (2), which allows us to obtain information regarding the significance of observed differences between the categories that could explain the differences identified in the analysis [22].
The data used for the parametric 2 are obtained through a questionnaire administered to Italian agricultural industries.
The literature analysis, carried out according to Webster and Watson [23] aims to extrapolate the enabling factors, barriers and adoption outcomes of digital technologies used in agricultural industries. The methodology, search criteria and review process results can be found in the already-published articles [24, 25]. Table 1 below shows the factors identified in the literature.
Found in [4, 14, 18, 20, 26–34] R&D BUSS COLL DYN INF DISS RESS REG INFR OWN SIZE AGE TECH ANALY
Description Found in They represent a form of economic and [1, 3, 4, 7, 35– governmental guidance that pushes 37] agricultural industries to innovate. The absence of political incentives slows down the digitisation of agricultural industries, especially small industries, which lack sufficient liquidity to implement changes and undertake investments.
Activities to improve production activities, [1, 38–40] based on a strategic approach, with the aim of implementing a series of practices and mechanisms to stimulate knowledge and technology transfer.
Introduction of innovative and strategic [1, 13, 14, business models based on the adoption of 41–43] digital technologies. companies may lack innovative elements that promote the creation of new business models. joint work between figures from different [7, 11, 14, 35, organisations, based on the development of 37, 38, 42, internal and external relations. By exchanging 44–47] data and information with other companies, agricultural industries can achieve specific objectives, also jointly. Often, there are no prerequisites to create collaborative relationships between companies, even from different sectors to promote the adoption of technologies.
Identify and understand changes and [27, 28, 45, opportunities affecting the performance of 46, 48–50] agricultural industries There must be the same level of information [34, 45] throughout the organisation, considering a decentralised structure Possibility of disseminating the information [13, 14, 20, collected and analysed in the organisation 27, 29, 31, 34, 42, 48, 51–55] It depends on dissatisfaction in the individual [4, 7, 31] operational activities of the organisation, where the improvements that technologies can bring are not recognised Absence of rules and regulations to govern the [7, 26, 29, 45, adoption of digital technologies 56, 57] Lack of tools within the organisation to [20, 58] counter cyber attacks Data collected, analysed, and managed [20, 58] through technologies lack ownership due to the lack of regulations Industry size affects technology adoption, as [31, 59] small industries have more difficulties Age affects the adoption of digital [18] technologies. In fact, adults are less likely to use technologies The use of technologies is often complex due [7, 26, 34] to their implementation caused by the lack of relationship between development Lack of digital skills to digitally analyse the [1, 26, 32– data collected through technologies 34] REC IND PROD STRA DEC
Description Inability to recognize modernity and the advantages that the adoption of technologies produces in agricultural industries
Found in [26] Absence of adequate tools capable of [40, 60] measuring human operations with respect to technologies The adoption of digital technologies allows to reduce all the production costs that companies use for production activities Adoption generates the possibility of creating new organizational and production strategies [48] The people who make up the organization have the same decision-making power NEWPRO Production processes are becoming increasingly digitized, generating changes from an organizational and cultural point of view INFCOL Exploit the information gathered through
digital technologies to make better decisions DISSINF
Take advantage of technologies to disseminate the results elaborated through the information collected
The questionnaire aims to investigate the adoption of business information systems in agricultural industries, seeking to investigate barriers, enabling factors, and adoption outcomes. Question constructs are derived from items identified in the literature review, often extrapolated from previous studies that tested similar contexts [28, 33, 63]. The questions that make up the questionnaire are mainly implemented with Likert scales of 1 to 5 points (1 - Strongly disagree, 2 - Disagree, 3 - Neutral, 4 - Agree, 5 - Strongly agree). We submitted the questionnaire using an online database, which includes information from 3,286 Italian companies in the agricultural industry and their respective email addresses.
Before sending the questionnaire to the full database, we subjected the questionnaire to two stages of revisions. In the first stage, with the help of experts in the field, we checked for functionality and correctness. In the second stage, we tested the pilot questionnaire with a sample of 193 companies belonging to the Lazio Region, which allowed us to observe and verify the correct functionality and understanding of the questions and the obtaining of feedback for improvement.
After the pilot test we improved the questionnaire due to the feedback obtained from the pilot questionnaire participants. The questionnaire administration started in April 2023, with Google Moduli, and is still ongoing, and to date, we have obtained 211 responses, with a response rate of 6,7%.
People
E B EB B B B B
Task E B E B B O
O
Through the 2, we want to test the existence of a connection between each group of the enabling factors, barriers, and outcomes and the adoption of business information systems. The 2 can measure the association between two category variables by considering the following hypotheses: • H0 = 0 (Independence between two variables) • H1 ≠ 0 (Dependence between variables)
The factors analysed in the test are derived from the literature. We summarise the enabling factors, barriers, and outcomes in the following tables 2.
E B B O O
The results show that the respondents are mainly men (81% of the sample) with an age range 41-50 years of age (36% of the sample) and with a master’s degree (42% of the sample). The industries have a turnover of ≤ € 200,000 (44% of the sample) and a size of 0-19 employees (78% of the sample). This observation is compatible with the general characteristics of the Italian context. Finally, respondents state that they have more than ten years of experience (68% of the sample), and agricultural production characterizes the largest number of industries involved in the study (78%).
To answer our research question, we conducted the 2 test. Below, in Tables 7, 8, and 9, we reported the value of each test 2.
In the following Tables, xsquared represents the value of test 2 obtained. Df indicates the degrees of freedom, p-value means the probability of the null hypothesis, and finally, supported shows, based on the results obtained, whether the factors have connections with the digital technologies analysed.
Code Cap_ff Fin_f R&D_f Buss_ff Coll_f Dyn Inf Dissf xsquared
The article we have proposed constitutes the initial step of a research project which aims to analyse the adoption of business information systems in Italian agricultural industries [49, 60, 64]. Through the questionnaire, we tried to identify whether there are links among the barriers, enabling factors, and results related to the adoption of business information systems in agricultural organisations.
Through 2 analyses, we identified relationships between the adoption of business information systems with barriers, enabling factors, and adoption outcomes. The results show that not all factors identified in the literature have links with business information systems. The model proposed below (Figure 2) includes, from a socio-technical perspective, the ranking of factors that show links because of the analysis conducted.
df
p-value
The proposed new model is very similar to the model in section 2. The factors removed are funding and incentives, present in both barriers and enablers and size of industries. The analysis of 2 shows that in both cases the adoption of business information systems is not related to the funding that the State grants for the adoption of technologies. Industries decide to adopt business information system in the presence or absence of incentives granted by the state. The companies autonomously decide to adopt business information systems, analyzing the actual usefulness but above all the intention to implement a digitization process which will lead to changes in the organization.
As regards the enabling factors, in addition to financing and incentives, new business models, collaboration relationships and dissemination of results with experts in the field are not linked to the adoption of business information systems. The new business models depend on the organization that decides to undertake a digitization process, characterized by the introduction of digital technologies such as business information systems [39]. The absence of a link between the adoption of business information systems and new business models derives from the possibility of creating new models even without the need to integrate digital technologies into processes. Having the skills and having an active environment open to change encourages companies to create and develop new businesses [42].
As far as collaboration relationships are concerned, the adopting depends on the willingness of companies to adopt digital technologies even without relationships with companies inside and outside the sector. Collaborative relationships characterize the organizational context rather than the socio-technical perspective. On the other hand, new business models and collaborative relationships, from the point of view of barriers, have links with adopting business information systems.
From a socio-technical perspective, the adoption of business information systems can be limited due to the absence of collaboration between companies lacking in the organization of relations with companies and with external stakeholders, which favor the adoption of business information systems, solving problems such as those related to lack of skills [53].
As far as new business models are concerned, organizations are incentivized to maintain traditional rather than innovative production models. Production practices are poorly digitized and less and less automated [47].
As far as barriers are concerned, company size is a factor unrelated to the adopting of business information systems. Agricultural industries may decide to adopt digital technologies regardless of their size as they may have the necessary elements, such as the skills and the willingness to innovate and develop new, increasingly digital, business models [33].
Finally, as far as adoption results are concerned, we see they all have links with adopting information systems.
The research has theoretical and practical implications.
Regarding the theoretical implications, the research, being at an early stage, does not fully consider the socio-technical perspective. Indeed, the studies conducted to identify factors and the existence of links between business information systems adoption and enabling factors, barriers and adoption outcomes are not analyzed and described from a socio-technical perspective.
For this reason, this article is a starting point in need of additions towards realizing further, even more complex analyses that consider technology adoption and a detailed description of factors, barriers, and adoption outcomes from a socio-technical perspective.
According to a practical implication, the adoption of information systems depends on several factors, which may stimulate or limit adoption or present themselves as results. In the organization, Agriculture 4.0 requires a change at the operational, management, but also administrative level. Several studies can be found in the literature analyzing the digitization process and the changes required [7, 13, 36]. However, the organization does not always have a flexible and change-oriented environment and often, the presence of stakeholder resistance to change reduces the intention towards digitization.
The research explores, considering agriculture 4.0, the link between the enablers, barriers, results, and the adoption of business information systems.
Based on the analysis of 2, we note that adopting business information systems depends on different factors that influence the organization. In some cases, they can appear both as an enabling factor and a barrier. Since data collection is still in progress, the results obtained could change, with the possibility of getting additional information, which would allow for more integration of the analysis through a socio-technical vision.
The organization must increasingly integrate business information systems with its operations and activities, having greater awareness and adequate knowledge to use them.
The article has limitations. Currently, the study only considers a test between a factor and business information systems adoption but does not explore possible combinations and cooccurrences between factors and business information systems adoption, which will be done in subsequent studies. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44. 45. 46. 47. 48. 49. 50. 51. 52. 53. 54. 55. 56. 57. 58.