2.1. Agrifood Supply Chains
Supply chains are networks of organizations that engage in upstream and downstream processes and enact specific activities with the aim of producing value for both the entities involved in the chain and the final consumers, in the form of products or services [
23]. The sourcing of raw materials, the processes of manufacturing, assembly, warehousing operations, inventory and order management, the distribution procedure across the chain, the delivery to the end consumer, and also the flow of information and capital within the network, are some of the activities linked to supply chain management [
24,
25]. Although the term “chain” denotes a linear configuration resembling a pipeline structure, through which products are transformed into final goods and delivered to consumers, supply chains are in fact complex networks, connected with external and—sometimes—loosely linked actors, and exposed to the wider economic, social, and technological environment [
26,
27].
ASCs are those supply chains that aim at the movement of agrifood products from production to consumption, including pre-production practices and post-consumption activities [
28]. As in the case of industrial supply chains, ASCs are open systems, characterized by the existence of different subsystems and emergent properties, also being vulnerable to the external environment [
29,
30]. However, such supply chains have particular characteristics that affect their modus operandi.
First, the nature of agrifood products heavily impacts the operation of an ASC. The perishability of production, along with specific and long production cycles, seasonality, and uncertain quality and quantity of production due to climate conditions or plant/animal diseases [
31] make the formulation and the implementation of any strategy difficult. In addition, the perishability of products eliminates the possibility of keeping buffer stocks, thus challenging the (vertical) coordination of ASCs [
32].
Second, the structure of markets and the power hierarchies it builds greatly influence the functioning of supply chains. Although food systems and associated ASCs are not uniform around the world [
33], evidence suggests that agrifood markets are highly concentrated, with leading retail and processing companies representing dominant players in the global agrifood system [
34,
35,
36]. Concentration generates oligopsonistic conditions [
32], creating complex forms of dependence among the actors involved in ASCs.
Third, the actors involved in ASCs have to cope with changing consumer life-styles and preferences [
37,
38]. Much more than other types of products, agrifood commodities face changing demand patterns that create fluctuations in supply chain operations. Increasing concerns over food safety [
39], the processes of food production [
40] and the technologies used [
41], the substances added to food products [
42], and the environmental, social [
43], and ethical [
44] dimensions of agrifood goods lead companies involved in ASCs to constantly redefine their purpose and values, and to modify their strategies accordingly. The shift of relevant policies towards more healthy and environmentally friendly food [
45,
46] further increases the need for companies to continuously adapt their strategies as a means to sustain their market position.
2.2. Decision Support Systems in Agrifood Supply Chains
Fanti et al. (2015) [
47] presented a DSS model which pays attention to the assessment of transportation performance. A database gathers information regarding product and service prices, budget allocation, resources, and costs, and then performance indicators are calculated using simulations about transportation. Songbai et al. (2010) [
48] developed a DSS for vehicle routing. This system analyzes information regarding demand, the strength of the vehicle, the number of drivers, and mileage per vehicle. Managers can use this system to make operational decisions about transportation personnel requirements, appropriate routes, and vehicle demands based on optimization methods. Kengpol (2008) [
49] presented a DSS model for a logistics distribution network. The system analyzes data regarding locations, customers, and transportation costs to develop alternative solutions and assess them.
Existing DSS ignore important tasks of strategic planning such as the definition of objectives, the analysis of the internal and external environment, and the implementation and assessment of the supply chain’s strategy. In addition, existing systems in supply chains have paid attention to the technical characteristics of collecting, visualizing and assessing data, ignoring strategic aspects. Validi et al. (2014) [
50] proposed a DSS for coordinated distribution systems. The purpose of this model was to increase the effectiveness of logistics and reduce environmental impact. Techniques about location routing visualization were implemented to minimize costs in the supply chain. Other scholars have focused on crop production systems to support managers to handle information regarding production costs, availability of land and water, and uncertain labor supply. The creation and evaluation of feasible crop rotations on a vegetable farm was implemented using linear programming and network flows [
51,
52]. Lao et al. (2010) [
53] developed an integrative food handling system and a warehouse system. However, they concentrated on the technical characteristics of the system. Allaoui et al. (2018) [
10] and Brulard et al. (2019) [
54] concluded that the development of a comprehensive model is required which will focus on specific objectives and indicators to assess supply chain performance and support strategic and tactical decisions.
2.3. Strategic Decision Support Systems in Agrifood Supply Chain
The ISP process can be used to develop a DSS for ASCs. The ISP process includes five phases. During the strategic awareness phase, which is the first phase of the ISP process, tasks concerning the determination of important planning issues, priorities, goals, and the selection of employees who will take part in the planning team of the process, are included. The second phase, the situation and significant risk analysis, includes the following: analysis of the existing business structure, analysis of existing organizational processes and systems, and analysis of the external and internal technological environment. During the third phase of the ISP process, IS managers identify important goals, opportunities for change, and high-level IS strategies. Strategy formulation is the fourth phase of the ISP process. The most significant tasks involved in strategy formulation are the following: the determination of new business processes and IT architecture to achieve IS goals and the definition of new IS plans and priorities that will support the performance of the firm. Finally, strategy implementation involves the determination of change management processes and action plans. In addition, in this stage, IS executives evaluate the output of the ISP process and examine if the objectives have been achieved [
7,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69].
According to the phases of the ISP process, the suggested strategic DSS model includes five stages. Strategic awareness entails identifying critical future challenges, objectives, and priorities, as well as selecting employees to serve on the DSS development team. These goals refer to harvesting, warehousing, customer service, transportation, food production, inventory management, and order processing. The following are the significant risks of the second stage, known as situation analysis: analysis of the existing business structure, analysis of existing organizational processes and systems, and analysis of the external and internal technological environment. Concerning the internal environment, executives examine strengths and weaknesses regarding production costs, harvesting policies, logistical costs, logistical structure, level of demand, inventory management, warehousing, transportation, prices, systems, and materials handling [
67].
The analysis of opportunities of, and threats to, the business environment is necessary since companies operating in the agrifood industry are highly interdependent. Furthermore, this analysis supports the growth of the supply chains’ sustainability. An awareness of developments in business partner organizations, competitors, products, and markets is crucial to improving the supply chain’s performance. This analysis can be conducted using systematic scanning and through the relationship with business partners [
12]. Other factors that affect this analysis are pressure from resource scarcity, competitors, consumer demand, isomorphism, and deregulation [
14]. Therefore, managers should be aware of these factors to develop a DSS that will improve the performance of supply chains.
Moreover, managers require data regarding distribution channels, market segments where competitors are active, demands relating to product attributes, quality of suppliers, economic situation of suppliers, and buying power [
12,
70]. In addition, information regarding food production, healthy eating, the rural economy, the environment, and consumer values is also important [
31]. Nevertheless, decision makers can analyze data monitoring competitiveness in the agrifood industry [
12].
In the next stage, strategy conception, a database, application programs, and a data model are involved. This stage, which interacts with other stages, can use the results of the previous two stages as input. Thus, executives can collect, store, and retrieve the required data regarding external and internal environments as well as historical data in order to develop alternative solutions. Executives can then assess the data and choose the best alternative to develop further. These alternative scenarios regarding responsiveness, material flow, agility, costs, food quality, efficiency, and sustainability of supply chain are the outputs of this stage [
71]. Mathematical models are used to develop alternative scenarios based on the problem which has been defined. Furthermore, many models, theories, methods, algorithms, and techniques, such as intelligent data analysis, optimization techniques, multicriteria methods, and fuzzy theory are used to analyze alternative scenarios [
72].
The next stage of the DSS model is strategy formulation. The significant tasks involved in strategy formulation are the following: identification of new business processes and IT architectures to achieve the supply chain’s goals, and the definition of new IS plans and priorities that will support the performance of ASCs. Finally, strategy implementation involves the determination of change management processes and action plans. In addition, at this stage, IT managers assess the output of the ISP process and examine if the goals have been achieved.
What has been indicated by surveys examining the effect of ISP process on success is that IS managers have focused on strategic conception. Combined with opportunity analysis and evaluation, the strategy’s conception could offer more realistic alternatives. Understanding IS objectives can enable the company to define future IS and business goals. Better options and choices can be defined to produce better outcomes. The frequently encountered challenges that emerged during the execution of the ISP process were the lack of top managers’ engagement and the inability to develop effective action strategies to develop IT projects. If executives do not support the development of IS plans, team members will not be focused on the plans and will have difficulties implementing the IT strategy. Thus, it is preferable for managers to define the priorities that support their IT strategy to be better executed and achieve their objectives. Previous researchers have indicated that IT managers tend to pay attention to IT strategy implementation because they consider the execution of strategy to be a complex process [
57,
73].
Findings also indicate that some managers are overworked with respect to the ISP process whilst others are doing too little. Such approaches may prove ineffective. In the first case, the ISP process could be misunderstood, postponed, or stopped from being enforced, while in the second approach the implementation plans could be unsuccessful, meaning that their objectives could not be accomplished. The evaluation of the process is obviously of great importance if managers wish to minimize these unsatisfactory outcomes. Researchers have indicated that IT managers pay attention to strategy conception and strategy implementation, ignoring the significance of strategic awareness and situation analysis. As a consequence, the IT strategy which is being developed is not efficient and effective and it does not meet IT goals [
74,
75,
76,
77]. Furthermore, IT executives focus on reducing the required time and cost for the project. Executives pay attention to process implementation and this fact has negative results. Nevertheless, it reduces the time it takes for ISP process implementation, but the organization’s strategic goals are not aligned with IS objectives [
20,
78,
79,
80].
Regarding the existing literature five hypotheses have been identified:
Hypotheses 1 (H1). Strategic awareness for the development of DSS positively affects ISP success in the agrifood sector.
Hypotheses 2 (H2). Situation analysis for the development of DSS positively affects ISP success in the agrifood sector.
Hypotheses 3 (H3). Strategy conception for the development of DSS positively affects ISP success in the agrifood sector.
Hypotheses 4 (H4). Strategy formulation for the development of DSS positively affects ISP success in the agrifood sector.
Hypotheses 5 (H5). Strategy implementation for the development of DSS positively affects ISP success in the agrifood sector.