Sustainable Innovation Management Model (MGI) for Agro-Industrial Citrus Chain

Abstract

This paper proposes a sustainable innovation management model (hereinafter MGI) aimed at enhancing sustainability and leveraging open innovation opportunities within the Citrus agro-industrial chain in the Quindío Department, Colombia. The methodology combines surveys, consensus percentages, relevance and congruence indices, and a review of the literature from the last ten years, particularly in the Google Scholar and Scopus databases. A total of 97 documents directly related to innovation management in the citrus sector were reviewed, along with 58 indirect references. Through three questionnaires, 120 variables were identified, categorized into input (53), transformation (36), and output (31) stages. The findings, supported by sector analysis and foresight studies conducted for six regional agro-industrial chains, led to the development of three potential MGI models, one of which was selected for further application. The study highlights several challenges within the citrus value chain, including weak leadership, limited market competitiveness, outdated organizational structures, slow adoption of advanced technologies, and inadequate investment. The proposed MGI, with a focus on sustainable innovation, offers a generic interactive model that presents a dynamic and adaptable solution to drive competitiveness and value creation in the citrus sector. The chain studied requires not only the participation of different interest groups, but also the application of artificial intelligence to close the gaps and allow for sustainable innovation to be generated of sustainable innovation.

1. Introduction

In recent years, interest in research on innovation management has increased. There has been a notable and exponential increase in the application of management concepts, methodologies, techniques, and tools, particularly in the realm of innovation, across various organizational contexts. Innovation management models (MGIs) have garnered significant attention, both for their conceptual development and practical implementation within companies. This interest arises, among other reasons and as stated by [1], citing Mintzberg, from the need to align innovation strategies with organizational structures. While citrus production is geographically widespread across Colombia, it is predominantly concentrated in six key productive regions, distributed across several departments: (1) Atlantic Coast (Atlántico, Magdalena, Cesar, and Bolívar); (2) Northeast (Santander, Norte de Santander, and Boyacá); (3) Center (Cundinamarca, Tolima, and Huila); (4) Eastern Plains (Meta and Casanare); (5) West (Antioquia, Valle del Cauca, Caldas, Risaralda, and Quindío); and (6) South (Cauca and Nariño). Nationally, the average farm size is 5.6 hectares (ha.), though significant disparities exist between producing regions, largely due to the varying levels of organizational management within the sector. For instance, producers in the West core manage up to 600 hectares, while smaller producers typically operate around 20 hectares. In contrast, producers in the South and Northeast cores are generally small-scale operators, with farms averaging approximately 1 hectare, and the largest producers in these regions manage more than 10 hectares.

The same source [2] points out that the export of citrus fruits from Colombia have experienced consistent growth in recent years. For instance, between 2011 and 2021, the export value of Tahiti lime surged by 34% annually, climbing from USD 2.5 million in 2011 to USD 49.3 million in 2021. Export volumes also saw a significant rise, growing by 38% each year during the same period, from 1591 tons to over 39,000 tons. The main destinations for Colombian Tahiti lime are North America, western Europe, and the Caribbean, showcasing its expanding global presence. Additionally, other Colombian citrus fruits, such as oranges and various types of lemons, have made a notable impact in markets like the United States, Canada, and the European Union, owing to their high quality and exceptional flavor. By December 2024, Colombian citrus exports showed further growth, particularly in lemons, with an increase of 62.7%, while Tahiti lime exports grew by 58% in 2021, a trend projected to continue through 2024.

Globally, lemon production during the 2020–2021 period reached 8.4 million tons, maintaining a stable level compared to the 2019–2020 period. The largest producers are Mexico, accounting for 34.2%; the European Union with 19.7%; and Argentina at 13.7%. Other significant producers include Türkiye, the United States, South Africa, and Israel. For mandarins, 2021 saw a production of 33.3 million tons, marking a growth of 4.2%, driven largely by China, which holds 69.5% of the global market share, followed by the European Union at 10.3% and Türkiye at 4.8%. In terms of oranges, Brazil leads with 12.8%, China with 15.4%, and the European Union with 13.5%. Global orange production totaled 48.6 million tons, reflecting a 5.5% increase from 2019–2020.

Citrus consumption is predominantly focused on fresh fruit, in line with population eating habits. For example, the consumption of orange juice has slightly decreased by 15.2%, as fewer people are incorporating it into their breakfast routines. Despite having multiple agro-industrial uses such as essential oils, citrus flour, pulp, and juices, the orange is primarily consumed as fresh fruit or juice. Mandarins are mainly consumed fresh or as juice, while lemons are primarily used in gastronomy, for lemon juice, and in various industries.

The international pricing of citrus fruits is primarily influenced by major producing countries, including the United States, Brazil, and Spain. The U.S. has faced significant production challenges due to the spread of Huanglongbing (HLB), a disease that has impacted citrus yields. In Brazil, where citrus is predominantly used for juice, concentrate, and pulp production, the industry has suffered a major setback. Conversely, Spain remains unaffected by HLB and continues to contribute significantly to the global market. For mandarins, global prices are primarily determined by the supply from China and Spain. In South America, Peru stands out as the largest producer of mandarins. Meanwhile, Mexico and Argentina dominate the international lemon market.

According to the 2024 report by [3], citrus fruit production has increased in Asia, Africa, and several American countries due to favorable climatic conditions. However, Europe has witnessed a downward trend in sweet citrus production, although lemon production has seen an upward shift. Concurrently, demand in Europe has decreased. Specifically, world orange production for the 2023/24 season is expected to rise by 1%, reaching approximately 47.4 million tonnes. While Brazil and the European Union have experienced declines in production, these losses have been offset by larger crops in Egypt, the United States, and Türkiye. Consumption of oranges for industrial processing has risen in line with production, while exports have remained stable. In contrast, global orange juice production is projected to decrease by 3%, totaling 1.5 million tonnes, due to a reduction in fruit availability for processing in Brazil, which accounts for over 70% of global orange juice production. Both consumption and exports are expected to decline in response to the reduced supply [3].

Looking ahead, Reference [3] forecasts a decrease in the consumption of citrus for processing due to declining supplies. European Union citrus production is expected to fall by 2%, reaching 5.5 million tonnes, driven by lower yields attributed to volatile weather patterns. Excessive rainfall during fruit cultivation, followed by drought conditions, heat stress, and irrigation restrictions, has had a negative impact on yields and fruit size.

In the mandarin sector, global production for 2023/24 is forecast to increase by 1.2 million tonnes, reaching 38.2 million tonnes. This growth is largely attributed to favorable climatic conditions and higher yields in China and Türkiye, as well as an expansion in the harvested area. As a result, both consumption and exports are expected to rise. Similarly, grapefruit production for 2023/24 is projected to reach 6.9 million tonnes, benefiting from favorable weather and increased production in China and Türkiye. While consumption for processing remains stable, exports are expected to increase due to the larger supply [3].

In light of the significance of the citrus industry in both the global market and the Colombian context in the department of Quindío, this study aims to address a central question: What are the key variables that should be considered for the development of an innovation management model (MGI) for the citrus agro-industrial chain?

To facilitate the understanding of this research, the article is organized as follows: Section 2 outlines the theoretical framework, with a focus on the context and concepts of the agro-industrial chain under study, as well as the structure of the citrus chain in Colombia. This section also introduces the concepts of sustainable innovation models. Section 3 details the materials and methods used in the study, including a comprehensive literature review from specialized databases such as Google Scholar and Scopus, expert consultations, and validation through surveys and relevance and congruence indexes. Section 4 presents the results and key findings, including the proposed MGI. Section 5 offers a discussion structured around three key axes of analysis. Section 6 concludes this study, while Section 7 provides recommendations. Finally, the references used in this research are detailed.

2. Theoretical Framework

2.1. Context and Concepts of the Citrus Agro-Industrial Chain

The citrus genus consists of a diverse array of species and varieties, with southeast Asia being the primary region of origin and the richest in biodiversity. Among these, fruits such as oranges, mandarins, limes, lemons, and grapefruits are especially valued for their health-promoting properties. These fruits are rich in essential nutrients, including vitamin C, carotenoids (provitamin A), folic acid, flavonoids, essential oils/monoterpenes, and limonoids, all of which contribute to their beneficial effects on human health [4].

To better understand the concept of agro-industrial chains, which this paper aligns with the concept of production chains, it is important to recognize the range of perspectives presented in the literature [5,6,7,8,9]. In Latin America, the notion of the production chain first emerged in the 1990s to highlight collaborative efforts across various stages of production and the development of sectoral policies and business support from government bodies [9]. As per Law 811 of June 2023, which amends Law 101 of 1993 and establishes chain organizations in the agricultural, fishing, forestry, and aquaculture sectors (Agricultural Transformation Societies, or SATs), a production chain refers to a series of interconnected activities that span from the creation of an agricultural product to its final commercialization [10].

One of the pressing challenges for Colombian citrus farming is the threat posed by the incurable citrus disease Huanglongbing (HLB). This disease has led to the declaration of emergencies in seven departments, prompting efforts within the citrus chain to mobilize resources for developing strategies to address the crisis, such as the establishment of Regional Control Areas (ARCOs).

Although Colombia has seen an increase in citrus exports, particularly to the United States following the approval of the sweet citrus export protocol, the citrus chain continues to face significant intermediation, which causes distortions in market pricing and information. This, in turn, has led to negative effects and inequalities in the distribution of profits along the chain, with producers receiving the smallest share.

This agro-industrial chain operates within a broader framework of public policies, shaped by various regulatory instruments. For example, Law 29 of 1990 set forth the competitiveness policy and created the National Competitiveness Council as an advisory body to the government. At the agro-industrial level, Law 607 of 2000 restructured the creation and operation of the Municipal Units for Agricultural Technical Assistance (Umata), regulating direct rural technical assistance in accordance with the National System of Science and Technology. Additionally, documents such as the Strategic Plan for Science, Technology, and Innovation for the Colombian Agricultural Sector (PECTIA) 2017–2027 [11] have been issued to address diverse aspects of the agro-industrial landscape.

2.2. Citrus Agro-Industrial Chain in Colombia

The citrus agro-food chain in Colombia encompasses a wide range of actors, including producers, marketers, processing industries (with a focus on juice production), seed producers, suppliers of agricultural inputs, exporters, universities, research centers, and both regional and national institutions that support the sector. Key institutions involved in the process include the Colombian Institute of Agriculture (ICA), the National Learning Service (SENA), the International Center for Tropical Agriculture (CIAT), Asohofrucol, agricultural secretariats, and regional autonomous corporations, among others [12,13,14].

In terms of its organizational structure, the citrus chain in Colombia is governed by a National Council, six regional committees, three national and regional technical secretariats, and four national thematic committees or working groups.

Table 1. Structure of the citrus agro-industrial chain in Colombia.

	Organization of the Chain
Thematic tables	National Council	National Technical Secretariat
Regional secretariat	Regional committees	Regional secretariat
Regional committee	Regional secretariat	Thematic table and regional committee

Source: Own elaboration (2025).

shows the structure and organization of the current agro-industrial chain in Colombia.

The citrus sector is further supported by organizations such as Asohofrucol and Asocítricos, along with the National Fund for Horticultural Development, a parafiscal fund administered by Asohofrucol. The Fund’s objectives include promoting research, providing technical assistance, facilitating technology transfer, training, collecting and disseminating industry information, fostering the creation of marketing companies, developing collection and distribution channels, supporting exports, and stabilizing fruit and vegetable prices to ensure the growth of the subsector. These efforts aim to benefit both producers and national consumers.

The citrus chain encompasses a wide array of products in its primary phase, including oranges, lemons, limes, tangerines, and grapefruits, as well as a variety of products from the industrial phase, such as juices, concentrates, nectars, purees, pastes, pulps, jellies, jams, oils, essences, and pellets for animal feed.

2.3. Innovation and Sustainability Models

Sustainable innovation has multiple definitions, especially in studies on the development of new products, processes, services, and technologies. According to [15], sustainable innovation is a process that integrates environmental, social, and financial considerations into business systems, from idea generation to research and development (R&D) and commercialization. Sustainable innovation seeks to go beyond mere attention to current consumer needs and proposes radically different solutions that foster a balanced relationship between society, the environment, and the economy [16]. Other studies affirm that sustainable innovation is characterized by continuous improvement or renewal, seeking better economic performance, lower environmental impact, and positive social outcomes [17,18].

The literature on the intersection of sustainability and innovation models is extensive. The investigation of [19] explored social innovation and sustainability in Latin America; other studies have focused on specific business innovation and sustainability frameworks. The works of [20,21,22,23,24,25,26,27] are relevant to understanding the relationship between innovation and sustainability. Their work addresses key challenges such as the urgent need for a transformation in development models, sustainable production and consumption patterns, the identification of innovative business models that support sustainable performance, and the complex decision-making required to achieve sustainability goals.

In the context of the agro-industrial food sector, particularly citrus fruits, various approaches and applications have been proposed. For instance, research has highlighted numerous innovation initiatives that involve a broad range of stakeholders, including clients, suppliers, universities, and governmental and non-governmental organizations, despite this sector’s relatively low technological development [28,29,30,31,32,33]. Collaborative innovation processes are imperative for organizations within agro-industrial chains, particularly the food sector [34,35].

Innovation processes and sustainable innovation management models have evolved significantly, enabling the development of Management and Governance Indicators (MGIs) across various sectors. These models typically propose the application of distinct stages in different areas, contributing to organizational management and enhancing sector competitiveness [36,37].

Innovation management has been analyzed from diverse perspectives, enriching the field of knowledge [38]. Scholars generally agree that, within the application sectors, it is essential to organize and direct human talent and available resources—both economic and technological—toward generating new knowledge. This, in turn, improves production conditions, market supply, and competitiveness, particularly for products within agro-industrial chains, such as citrus fruits [39,40].

Hence, it is pertinent to investigate agro-industrial chains and, specifically, the citrus chain, in order to contrast empirical information with analysis based on the application of methodologies that involve the different actors in the chain.

3. Materials and Methods

To propose an MGI for the citrus agro-industrial chain in Quindío, Colombia, a mixed-methods approach was employed to gather a comprehensive range of data and facilitate the comparison of various sources (primary, secondary, and tertiary). It is important to note that while the PRISMA 2020 methodology (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) was used for the literature review, the research does not solely rely on database article reviews. Instead, a combination of various sources and methods was utilized. The methodological design was structured into four phases, as shown in Figure 1, providing a clear roadmap for its implementation.

3.1. Phase 1

The methodology for the literature review was based on the PRISMA 2020 standards to ensure transparency and reliability in the literature review. The phases include (1) the identification of critical surveillance factors with research questions, keywords, and study conditions; (2) a detailed review of the specialized literature through the use of advanced search equations in Scopus and Google Scholar, in order to select the articles associated with the topic; and (3) the application of inclusion and exclusion criteria, to analyze the articles obtained for the subsequent identification of variables.

In Phase 1, in addition, critical surveillance factors (CSFs) were established, and this included the proposed research questions, descriptors or keywords, and the study conditions.

Table 2. Critical surveillance factors (CSF).

Topic Key	Subtopics	Descriptors	Determinant Factors
The growing interest in the formulation of MGIs highlights the need for R&D&I strategies aligned with organizational models.	What conceptual aspects are considered key in the formulation of MGIs for the generation of new strategies?	MGIs, innovation management, R&D&I.	I Analysis of MGIs correlated with the citrus chain.
	Does an MGI contribute to the strategy and structure of organizations in the citrus sector?	Alignment of strategies and innovation management models with citrus.

Source: Own elaboration (2025).

lists the topics, subtopics, descriptors, and determining factors related to CSF (see Table 2).

Meanwhile,

Table 3. Search equation applied in Scopus for citrus.

Search Equations	Number of Articles	Related Articles
Equation 1: TITLE-ABS-KEY (innovation AND model AND citrus AND orange AND tangerine)	2	2
Equation 2: TITLE-ABS-KEY (“Management model” OR “Citrus management”) AND (“Citrus” OR “Oranges” OR “Lemons” OR “Mandarins” OR “Grapefruits”)	221	7
Equation 3: TITLE-ABS-KEY (“Innovation management” OR “Innovation model”) AND (“Citrus” OR “Oranges” OR “Lemons” OR “Mandarins” OR “Grapefruits”)	97	0
Equation 4: (TITLE-ABS-KEY (“innovation strategies”) AND TITLE-ABS-KEY “citrus”)	2	2
Equation 5: (TÍTULO-LLAVE-ABS (“innovación”) Y TÍTULO-LLAVE-ABS (“limón”))	35	1
Equation 6: (TITLE-ABS-KEY (innovation AND management) AND TITLE-ABS-KEY (citrus))	58	3

Source: Own elaboration (2025).

corresponds to the different search equations, applied in Scopus, on strategies and MGIs.

Table 4. Google Scholar article search equation.

Keywords	Related Articles
Innovation management models and innovation models.	10

, on the other hand, shows the same equations, but applied to Google Scholar.

An advanced search was then conducted, using various combinations of terms and Boolean operators, yielding significant results on innovation and management models in the citrus sector. We identified 221 articles on management models, 97 on management and innovation, 35 on lemons, and 2 related to innovation strategies in citrus fruits such as oranges and tangerines. In addition, 58 articles were selected for detailed analysis, based on inclusion and exclusion criteria, and Google Scholar provided 10 additional articles on MGI.

Table 5. Inclusion and exclusion criteria.

Inclusion Criteria	Exclusion Criteria
Articles on MGIs in the citrus sector that address topics such as the formulation of R&D+i strategies for the citrus industry.	Articles that are not directly related to the citrus sector.
Articles that present cases of the implementation of innovation and management models in the citrus fruit sector, with a focus on new methodologies to optimize production and management.	Articles that do not present a practical view of the implementation of innovation management models in the citrus sector.
Articles that investigate the relationship between R&D+i policies and the improvement of competitiveness in the citrus market, using innovative management models.	Articles that do not present an analysis of innovative management models in the context of citrus, such as those that focus solely on the general theory of innovation without examining its specific application to the citrus industry.

Source: Own elaboration (2025).

records the inclusion and exclusion criteria for the respective analysis.

After applying the criteria in Table 5, 425 articles were analyzed, resulting in a final sample of n = 25 texts. The systematic review involved the identification of input, transformation, and output variables, which were included in an analysis matrix in Excel. Figure 2 presents the flow of the PRISMA 2020 process for selecting the final documents.

3.2. Phase 2

A Likert scale was used with input, transformation, and output variables, which yielded other key findings, especially to determine critical areas associated with innovation management in the citrus chain. Specifically, the relevant variables for the formulation of the MGIs were identified and classified under the components of input, transformation, and output.

3.3. Phase 3

In this phase, a selection of articles was made using a similarity index to determine the relevant elements of the MGI to be proposed. In total, eleven (11) articles were found, which were subsequently evaluated. For the analysis, evaluation concepts such as excellent, good, fair, and poor were applied.

3.4. Phase 4

In this last phase, the variables identified in the previous phases were analyzed and prioritized to arrive at the proposed MGI. Furthermore, several actions were carried out with different focus groups to align the variables identified and selected in the previous phases in order to validate the chosen MGI.

This was carried out to ensure that it could be implemented coherently and effectively to address the issues in the citrus chain related to management and innovation.

4. Results

4.1. Phase 1

Once the relevant articles were selected, a review and selection of the pertinent variables that could impact the MGI to be developed were conducted. The equations applied for the citrus sector provided a variety of significant results: The equation “innovation AND model AND citrus AND orange AND tangerine” yielded two (2) related articles, highlighting the specific interest in innovation models for citrus fruits such as oranges and tangerines. The equation that included terms like “Management model” and “Citrus management” along with different types of citrus resulted in a total of 221 articles, emphasizing the relevance of management models for the citrus sector. The equation focusing on “Innovation management” and “Innovation model” combined with specific citrus terms yielded 97 articles, indicating a focus on innovation management within the citrus industry. The equation combining “innovation strategies” with “citrus” generated two (2) articles, emphasizing the connection between innovation strategies and the citrus sector. The equation focusing on “innovation” and “lemon” identified 35 articles, showing a specific interest in innovation related to lemons. The equation addressing “innovation AND management” in the context of “citrus” resulted in 58 articles, signaling the importance of innovation management in the citrus industry with a specific focus on administration.

The review yielded a total of 17 articles in Scopus and 10 articles in Google Scholar, with the analysis of authors, titles, variables, or characteristics of the MGIs found. The identification of variables for the citrus sector revealed a broad range of crucial aspects. These variables span from critical competitiveness factors, public policies, and value chains to supply chain practices, corporate sustainability, and performance metrics. The importance of organizational resilience, innovation in regulations and standards, as well as adaptation to international competition and multichannel insertion in value chains is highlighted. The MGI named Agrópolis MACTOR emerges as a key element, supported by inter-institutional collaboration, prioritization of efficient and sustainable technologies, and patent analysis to gain competitive advantages. The integration of technologies associated with Industry 4.0, technological surveillance, and good agricultural practices underscores the importance of innovation strategies, system adaptability, and the creation of added value and distribution. Regarding public investment in research and development, its cost–benefit ratio is emphasized, along with the relevance of agricultural technologies and their economic impact. Efficient management of variables such as adoption coefficients, profitability, and return on investment in innovation, as well as the relevance of innovations, are crucial factors. Variables related to innovation management encompass a changing business environment; innovative strategies; influencing factors; various management models, such as Bujangseta Technology; innovation characteristics; and technology adoption models. The creation of new edible products, the development of sustainable technologies, and the management of innovation networks emerge as key aspects of innovative management. The identification of these variables provides a comprehensive view of the essential elements for innovation and management in the citrus sector. The diversity of factors considered reflects the complexity and the need for integrated approaches to promote 352 sustainable and competitive development in this sector.

4.2. Phase 2

In this phase, the analysis of the results from the first survey for the citrus sector is presented, detailing the analysis of the results obtained from the first survey, in which experts from the sector under study participated. These results were tabulated and, subsequently, the following values were calculated and applied: 1. Winning priority variable: mode 4 or 5 and consensus above the average of the thematic grouping; 2. Non-winning variable: mode 0, 1, or 2 and consensus above the thematic grouping; and 3. Variables under discussion: all other variables.

Table 6. Calculations for input variables in the citrus sector.

Variables	Mode	Modal Frequency	Percentage of Consensus (%)
(1) Creativity	5	5	83%
(2) Leadership	5	4	67%
(3) Investment in equipment and infrastructure	4	5	83%
(4) R&D+i activities	5	5	83%
(5) Innovation management system (IMS)	4	4	67%
(6) Technological development and key technologies	5	4	67%
(7) Innovation scenario	5	3	60%
(8) Innovation capabilities	5	5	83%
(9) Knowledge generation	5	5	83%
(10) Product quality	5	4	67%
(11) Innovation objectives	5	5	83%
(12) Alternative innovation routes	4	4	80%
(13) Innovation culture	5	5	83%
(14) Strategic intelligence	5	4	67%
(15) Agriculture 4.0 and 5.0	5	5	83%
(16) Sustainable agriculture	5	4	67%
(17) Technological innovation projects	5	4	67%
(18) Agricultural innovation platforms	5	4	67%
(19) Information and communication technologies	5	4	67%
(20) New production technologies	5	4	67%
(21) Circular economy	5	4	67%
(22) University–industry–government linkages	5	4	67%

Source: Own elaboration (2025).

shows the mode, modal frequency, and percentage of consensus for the expert surveys. Twenty-two variables were evaluated.

In the previous table, the evaluated variables show consistency in the mode and modal frequency, indicating a degree of agreement among the experts. A modification of 67% to 83% in the consensus percentage is highlighted. Key variables such as creativity, investment in equipment and infrastructure, R&D&I activities, innovation capabilities, knowledge generation, innovation objectives, innovation culture, and Agriculture 4.0 and 5.0 obtained a high consensus of 83%, reflecting strong convergence of opinions on these aspects. For the transformation component,

Table 7. Calculations of transformation variables in the citrus sector.

Variables	Mode	Modal Frequency	Percentage of Consensus (%)
(1) Strategy for innovation management	5	5	83%
(2) Production process	5	4	67%
(3) Transformation with added value	5	5	83%
(4) Development of new products through testing and prototyping	5	4	67%
(5) Training and knowledge transfer	5	6	100%
(6) Development of innovative products or processes	5	4	67%
(7) Knowledge management	5	5	83%
(8) Technology management	5	5	83%
(9) Scaling innovations	5	4	67%
(10) Analysis of national, local, and territorial innovation systems	5	4	67%
(11) Foresight	5	5	83%
(12) Process and technological innovation	5	4	67%
(13) Growth strategy	5	4	67%
(14) Product innovation program	5	4	67%
(15) Sustainable development	5	5	83%
(16) Circular economy	5	5	83%
(17) Knowledge management	5	5	83%
(18) Strategic innovation projects	5	4	67%
(19) Knowledge networks	5	5	83%

Source: Own elaboration (2025).

reflects the results obtained during the transformation phase, highlighting the influence of these variables according to the responses collected in the surveys directed at experts. These results are reflected in the table of transformation variable calculations for the analyzed sector, where the influence of these variables is also highlighted according to the responses gathered in the expert surveys. In total, 19 variables were evaluated through the technical expertise of subject matter specialists.

Table 7 shows these variables, as well as the mode, modal frequency, and percentage of consensus.

The variables reveal consistency in the mode and modal frequency, indicating a consistent degree of agreement among the experts. Notably, there is an increase in the consensus percentage from 67% to 100%. These results highlight the importance of strategy for innovation management, training and knowledge transfer, as well as knowledge and technology management, with a high level of consensus among the experts. Attention to sustainability and the circular economy also emerge as key aspects in innovation management.

Table 8. Calculations for the output variables in the citrus sector.

Variables	Mode	Modal Frequency	Percentage of Consensus (%)
(1) Value creation	5	6	100%
(2) Product portfolio	5	5	83%
(3) Profitability of innovation	5	5	83%
(4) Brand image	5	5	83%
(5) Organizational resilience	5	5	83%
(6) Access to new markets	5	6	100%
(7) Participation in innovation networks	5	5	83%

Source: Own elaboration (2025).

, on the other hand, presents the data related to the output variables collected in this study, highlighting the mode, modal frequency, and the percentage of consensus reached, obtained from the responses of the experts in the surveys. In total, seven variables were evaluated through the technical expertise of subject matter specialists.

In the analysis of Table 8, the results reflect a high level of consensus among the experts regarding the importance of value creation, access to new markets, and participation in innovation networks. Organizational resilience, profitability of innovation, and product portfolio management also stand out as key elements in innovation management. The next step was to ask specific questions for each priority variable, to build three (3) conceptual models, which were presented to the experts during a participatory workshop that facilitated the selection of the most appropriate model for innovation in the citrus sector.

4.3. Phase 3

In this phase, the final variables for the MGI were determined, based on different authors [41,42,43]. The relevance and consistency of the questions related to the key variables were also evaluated. In Phase 3, and citing [44], congruence and relevance indexes were applied, which were evaluated as follows:

• Congruence: Each expert evaluated whether the content of each item included in the questionnaire reflected the specified objectives and scored “1” if the content was specified, “−1” if they believed it did not measure it, and “0” if there were doubts about whether it measured it.
• Relevance: Each expert evaluated whether the content of each item included in the questionnaire reflected the relevance of each item on a Likert scale from 1 to 5 to measure the proposed objective, from “not relevant at all” (1) to “completely relevant” (5).

The three surveys used relevance and congruence index techniques, mode, modal frequency, and consensus percentages to determine whether a question, variable, or model was a priority or whether it remained under discussion or was a priority. Seven people participated in the first survey, including chain actors and R&D&I management experts, to validate theoretical aspects, variables, relevance, and consistency indices. Meanwhile, nine and three experts participated in the second and third surveys, respectively.

4.4. Phase 4

Three (3) prototypes of MGIs were developed, adapted to the citrus agro-industrial chain, and, in a workshop called “Co-development of the management model design proposal”, the MGI for this chain was determined.

Table 9. Unassociated vs. associated variables for the MGI graphing.

Unassociated Variables	Associated Variables
Input Variables
Idea management/creativity, leadership, investment in equipment and infrastructure, engagement, R&D&I activities, innovation management system, Agriculture 4.0 and/or 5.0, sustainable agriculture, agricultural innovation platforms, technological innovation projects, technological development and key technologies, knowledge generation, product quality, innovation objectives, alternative innovation pathways, innovation culture and climate, technological and competitive intelligence and surveillance, information and communication technologies, new production technologies, future production systems, circular economy, university–business–state linkage.	Innovation management and systems. Technological development and agriculture. Research and development and surveillance. Quality and product. Innovation and technologies. Commitment and university–business–state linkage. Circular economy.
Transformation Variables
Strategy for innovation management, production process, transformation with added value, development of new products through testing and prototyping, training and knowledge transfer, development of innovative products or processes, knowledge management, technology management, scaling program, sustainable development, circular economy, knowledge management, strategic innovation projects, knowledge networks.	Innovation management, programs, and projects. Process and transformation with added value. Development, training, and knowledge management and networks. Technology and scaling. Foresight, growth, and sustainability.
Output Variables
Value creation, product portfolio, profitability of innovation, brand image, organizational resilience, access to new markets, participation in innovation networks.	Value chain and product portfolio. Profitability and access to markets. Image. Participation in networks. Organizational resilience.

Source: Own elaboration (2025).

shows the associated and non-associated variables for the graphical representation of the MGI.

4.4.1. MGI 1: Lineal

The first MGI corresponded to a linear, sequential, and organized structure, providing a clear understanding of the process from input to the expected results. MGI 1 schematizes the process in a sequential and organized manner, carrying out a progressive transformation of input variables into ideas and process improvements. This approach allows for understanding how each variable contributes to the expected outcome, facilitating the generation of innovative products by the organization. The model delves into the concept of significant variables by addressing them successively. Each of the variables can be analyzed individually or in groups, depending on the specific point in the innovation management process. This sequential approach provides a detailed and structured view of idea development and improvements, which can be beneficial for analysis and decision-making within the organization. Among the contributions of MGI 1, with regard to the input variables, the inclusion of key elements such as idea/creativity management, leadership, investment in equipment and infrastructure, engagement, and R&D&I activities, among others, stands out. The connection of these variables with the subsequent phases of the process emphasizes their importance in innovation generation. The transformation variables include strategies for innovation management, new product development, training, and knowledge transfer, among others. These elements reflect the importance of internal actions and processes for driving innovation effectively. As for the output variables, value creation, product portfolio, profitability of innovation, brand image, organizational resilience, access to new markets, and participation in innovation networks are highlighted. These results show the positive and diversified impact that can be achieved through effective innovation management. MGI 1 offers a structured and sequential approach to innovation management, comprehensively addressing key variables at each phase of the process. This model provides a solid foundation for analyzing and developing innovative strategies, emphasizing the relevance of the identified variables in generating meaningful results for the organization.

Table 10. Summary of the linear MGI.

MGI	Linearity Between Input, Transformation, and Output Variables
Authors	Luis Fernando Gutiérrez Cano, Jhon Wilder Zartha Sossa, John Fredy Moreno Sarta, Gina Lía Orozco Mendoza, Tatiana Álvarez Ríos y Juan Carlos Palacio Piedrahita.
Description	Information flows and linear relationships between input, transformation, and output variables.
Contribution of the model	The contributions of the MGI are presented in the “Results Analysis” Section of the third survey. Outsourcing allows for the knowledge to be transferred to be displayed in different formats, not only from person to person but also from persons to different formats, meaning that the knowledge must be understood in order to be represented in some format. Furthermore, it is the step prior to combination, which allows for increasing, contrasting, detailing, and discerning knowledge through interaction and contributions with other people, with different experiences and interpretations around the same topic.

Source: Own elaboration (2025).

corresponds to the summary of the linear MGI.

4.4.2. MGI 2: Generic Interactive

The second MGI, generic interactive, represents a combination of forces that allow for flexible and adaptive development of the chain. It facilitates continuous feedback between input, transformation, and output variables, and each part of MGI2 optimizes and adjusts variables according to the specific policies and needs of the organizations within the chain. Within the contributions of MGI 2, the input variables address crucial aspects such as idea/creativity management, leadership, investment in equipment and infrastructure, and engagement, among others, covering a broad spectrum of elements that influence innovation management. The inclusion of variables such as Agriculture 4.0 and/or 5.0, agricultural innovation platforms, and technological innovation projects reflects the model’s adaptability to specific environments, such as in the agro-industrial chain. The transformation variables, such as strategy for innovation management, new product development, training, and knowledge transfer, show the diversity of actions that can take place simultaneously to drive innovation. Knowledge management and participation in innovation networks reinforce the importance of continuous collaboration and communication. As for the output variables, the model seeks to create value, develop a product portfolio, achieve profitability in innovation, build a strong brand image, strengthen organizational resilience, and ensure access to new markets. Participation in innovation networks is highlighted as a key element for effective insertion into the innovative ecosystem. The generic interactive model provides a flexible and dynamic perspective on innovation management, emphasizing the importance of the interconnection of variables and adaptability to the specific needs of the organization. This approach aims to enhance innovative capacity through the simultaneity of actions and continuous feedback between the phases of the process.

Table 11. Synthesis of the generic interactive MGI.

MGI	Feedback/Iterations Between Variables
Authors	Luis Fernando Gutierrez Cano, Jhon Wilder Zartha Sossa, John Fredy Moreno Sarta, Gina Lía Orozco Mendoza, Tatiana Álvarez Ríos y Juan Carlos Palacio Piedrahita.
Description	Information flows and feedback and iteration between input, transformation, and output variables. Related to policies and the needs of the context.
Contribution of the model	The contributions of the MGI are presented in the “Results Analysis” Section of the third survey.

Source: Own elaboration (2025).

presents the synthesis of MGI 2.

4.4.3. MGI 3: Strategic Alignment and Innovation

The proposed or winning MGI-3 seeks a more robust and cohesive integration of the different phases of the innovation process. It is based on the concept of variable leverage, which allows for constant feedback between the input, transformation, and output stages.

Table 12. Synthesis of the MGI for strategic alignment and innovation.

MGI	Strategic Alignment and Innovation
Authors	Luis Fernando Gutiérrez Cano, Jhon Wilder Zartha Sossa, John Fredy Moreno Sarta, Gina Lía Orozco Mendoza, Tatiana Álvarez Ríos y Juan Carlos Palacio Piedrahita.
Description	Iterations between input, transformation, and output variables. Feedback between variables and bidirectional information and knowledge flows. Related to policies and the needs of the context.
Contribution of the model	The contributions of the MGI are presented in the “Results Analysis” Section of the third survey.

Source: Own elaboration (2025).

presents the summary of MGI-3, aligned with the strategic aspect:

Figure 3 shows the MGI-3 model, which enables effective integration of the different phases of the innovation process. This model facilitates dynamic feedback between input, transformation, and output variables and considers context-specific policies and needs, aligning with monitoring and foresight studies. Furthermore, it is a flexible and adaptive model that offers a competitive and strategic advantage.

Within the contributions of MGI-3, the set of input variables addresses key aspects such as idea management and creativity, leadership, investment in equipment and infrastructure, engagement, and R&D&I activities, among others. The inclusion of elements such as Agriculture 4.0 and/or 5.0, agricultural innovation platforms, and technological innovation projects reflects the model’s adaptability to specific environments, such as the agro-industrial chain. Regarding the output variables, the model seeks to achieve value creation, develop a robust product portfolio, attain profitability from innovation, build a strong brand image, strengthen organizational resilience, and ensure access to new markets. Active participation in innovation networks is positioned as a strategic factor to consolidate the value chain and product portfolio. The proposed mixed model seeks to synergistically integrate the various phases of the innovation process, establishing a coherent link between the input, transformation, and output variables. Its flexibility and capacity to adapt to organizational policies make it a powerful tool for managing innovation in dynamic and evolving environments.

Innovation management can be realized through functions such as inventorying, evaluating, monitoring, assimilating, enriching, managing projects, and protecting (technological rights and intellectual property). Furthermore, the approach to analyzing innovation management maturity is related to activities such as technological surveillance, technological foresight, creativity techniques, internal and external analysis, and innovation process models (for R&D&I activities) and innovation management models (for R&D&I management activities) [45]. This generated the opportunity and decision to include, within the project registered with the Ministry of Science, the co-development of an MGI for each of the six (6) agro-industrial chains selected, including the citrus sector. Additionally, the Ministry of Sciences established the requirement that it be for highly innovative companies. Before obtaining this certification, companies must demonstrate that they have an organizational structure for innovation. This structure refers to an R&D&I model.

This model, proposed and co-developed with the chain’s actors, will be able to fulfill various functions, including understanding the key variables for new R&D&I projects and initiatives; identifying information and knowledge flows between input and output transformation variables; serving as input for each company for future R&D&I management certifications, with a view to complying with the Colombian Technical Standard NTC-5801, UNE, or ISO; and providing decision-makers in the agro-industrial sector and regional innovation systems with elements to define and align public policies conducive to the development of the chain, specifically in the case of citrus fruits [46,47].

5. Discussion

This section is divided into three discussion axes. Axis 1 focuses on the analysis of the propose MGI-3 and compares it with other MGI studies. Axis 2 examines the alignment of primary topics and technologies identified in the prospective study for 2035 in the citrus agro-industrial chain, emphasizing the importance of sustainability variables and their relationship with the MGI chosen by chain actors. Axis 3 presents an analysis of the proposed MGI-3 in relation to opportunities for open innovation.

5.1. Axis 1

Given the social and economic significance of industrial agro-chains, several studies on MGI (management of innovation and technology) for the agro-industry have been proposed, aiming to enhance competitiveness in a market characterized by VICA (Volatile, Uncertain, Complex, and Ambiguous) or FANI (Fragile, Ambiguous, Non-linear, and Uncertain) environments. The research conducted indicates that the MGI for the citrus agro-industrial chain is a topic with limited references in the specialized literature from indexed journals. A preliminary search in the Scopus database, using the terms “open innovation management models” and “citrus agro-industrial chain”, yielded no results. However, when using the search terms “innovation models” and “citrus”, five results were found, of which two were conference papers, two were articles from indexed journals, and one was a book chapter. A further search in Scopus, using the criteria “citrus models” and “open innovation management models”, returned a single result, a conference paper [48]. This paper discusses the growing importance of networking beyond disciplinary and organizational boundaries toward an open R&D system aimed at commercialization.

Regarding the management of innovation and knowledge (MGI) in the citrus sector and open innovation models, existing research addresses key issues related to best practices concerning the actors involved and their necessary interactions. However, the literature on MGI specifically within the citrus industry is sparse [49]. A targeted review of databases revealed that research on MGI and its relationship with open innovation models is limited, focusing on specific topics, but not addressing the agro-industrial chain selected for this study. Notably, the studies by [50,51,52] explored open innovation in its various forms, as well as internal or closed innovation, recognizing these as distinct governance models with differing benefits and costs. In the absence of the MGI-1 selection, linear models, such as those developed by [53], which emphasize that innovation follows a unidirectional path from basic research to commercial application, have been influential. While this approach has proven essential for the development of technological innovations in various industries, its applicability to agro-industrial sectors is more limited. For example, in the citrus industry, where climatic and social factors play a crucial role, a more flexible model is required—one that fosters continuous feedback and interaction among the various actors involved.

Additionally, given the pivotal role of agro-industrial chains in socio-economic contexts, numerous prospective studies have emerged to monitor and forecast trends and scenarios within various production chains. In particular, prospective analyses conducted by [54] on the blackberry agro-industrial chain and [55] on multiple sectors have been instrumental in guiding decision-making, mitigating sector-specific uncertainties, and aligning strategies with available resources and capacities.

A second search criterion, focused on prospective studies and agro-industrial chains, yielded four relevant studies. The first, authored by [56], is a prospective study on coconuts (Cocos nucifera) aimed at identifying relevant technologies. This research utilized the Delphi method (hereafter MD) in two rounds to prioritize innovations, supplemented by technological monitoring through literature reviews and market surveillance. Another study, by [57], examined fertilizers as critical inputs in agro-industrial chains, suggesting that strategic alliances could mitigate risks associated with price volatility and supply chain stability. A third study presented a prospective analysis of the impact of the COVID-19 pandemic on the food industry in Italy, proposing that this unprecedented crisis could serve as a catalyst for advancing sustainability within food systems, as outlined in the European Green Deal [58].

It is clear to point out that although the topics addressed in these previously mentioned investigations are important for understanding the MGI, they do not coincide with the findings of this study and, in particular, because they were not applied to a specific agro-industrial chain, as is the case of the citrus sector with the proposal of an MGI, based on a methodology with the participation of actors linked to the chain.

5.2. Axis 2

Within the framework of the General Royalties System project (which is a system that supports the financing of research projects in Colombia) and the Ministry of Science, Technology, and Innovation Minciencias, the MD to 2035 was applied in various agro-industrial chains, including the future study for the citrus agro-industrial chain; this method had the purpose of prioritizing topics, technologies, and innovations through consultation with stakeholders in the chain.

The Delphi study had already been previously used in other agro-industrial chains, such as the works of [59,60]. However, these previous studies did not make specific mentions of innovations and technologies within the framework of the concept of convergent technologies Nano, Bio, Info, and Cogno. For the MD, two rounds were applied, with the participation of several experts. In total, 31 topics and technologies were prioritized and classified into groups as follows: 1. General; 2. Cultivation; 3. Product and Byproduct Innovation; 4. Technology; and 5. Genetics. Figure 4 shows these prioritized topics and technologies for the proposed MGI-3.

At the beginning of the questionnaire regarding the alignment of future study results with MGI, stakeholders were asked whether the topics/technologies/innovations influence or are of greater importance to drive the MGI.

The following presents the priority topics and technologies for the MGI of the agro-industrial chain, the subject of study (see Figure 5):

The results obtained from the alignment of future studies with the innovation management model, particularly the 16 priority topics and technologies aligned with the model, as seen in Figure 5, become an input for new R&D&I projects and initiatives for actors in the citrus agro-industrial chain.

After reviewing similar research, it is relevant to highlight some of them that, however, do not address the findings obtained in the present research. For example, [61] examined existing technologies and stated that they are insufficient to achieve environmental goals. It analyzed the Dutch program for the development of sustainable technology, which aimed to increase eco-efficiency. Another study [62] investigated clean technologies as a source of competitive advantages at the business level, focusing on developing countries. This work found that the most frequent barriers were associated with high capital costs and low priority in financing. Other barriers included the lack of a conducive environment based on capacity and research and development (R&D) activities.

Sustainable innovation studies have analyzed aspects of technological clusters or industrial sites. For example, research [63] analyzed incremental and radical innovations, based on case studies in ethanol, hybrid, and hydrogen fuel cell vehicles. The work of [64] compared governance structures for biofuel technologies and hybrid electric vehicles in Sweden. Meanwhile, the work of [65] analyzed the impact of cleaner production processes in a mechanical and metal parts cluster for cars in Serra Gaúcha, Brazil, and [66] assessed the progress of the Eco-Industrial Parks (EIP) initiative in China, based on interviews in 33 locations.

Then, after this analysis, adding to what was indicated in Axis 1, and by comparing research on MGI for other agro-industrial chains, the importance and contribution of this research to a better understanding of the studied chain is demonstrated. In the two axes proposed in the Section 5, it was confirmed that although there are similar studies, none correspond to the one specifically found in this article. Hence the importance of this research, especially when the proposed MGI-3 is closely related to sustainability, a topic that is also a priority for the competitiveness of organizations, especially those belonging to the studied agro-industrial sector.

5.3. Axis 3

Research into the application of open innovation typically focuses on identifying best practices and emphasizing solutions to the challenges encountered within the specific thematic areas they address. However, the body of scientific literature on sustainable innovation models and the potential opportunities provided by open innovation within the citrus agro-industrial sector remains limited. A thorough review of existing studies reveals that, while research on open innovation is diverse and focused on specific topics, no studies specifically address the citrus industry. For instance, [48] examine local open innovation initiatives as a means of enhancing public policies that foster collaboration for innovation in small and medium enterprises (SMEs). Their study explores how public policies can effectively facilitate innovation partnerships between companies, entrepreneurs, research institutions, and the public sector, ensuring these collaborations are accessible and beneficial to SMEs. The authors conclude that applying a variety of open innovation models is essential to strengthening regional development across various contexts. Similarly, the research conducted by [49] investigates internal or closed innovation models, which are characterized by distinct governance structures, each offering unique benefits and costs. The authors develop a comparative framework for innovation management and categorize four distinct governance forms for open innovation; however, their analysis does not extend to the agro-industrial sector, which is the focus of the current study.

Overall, existing studies on open innovation predominantly address a range of organizational contexts. For example, [67] assert that organizations pursue open innovation processes to access external knowledge. Their research highlights that SMEs can enhance their productivity by integrating open innovation practices into their operations.

From these studies, it is evident that the proposed MGI-3 model for the citrus agro-industrial chain, leveraging the opportunities presented by open innovation, constitutes a crucial approach to bridging existing gaps in the sector. Once MGI 3 was defined, alongside its associated priority variables and technologies, a further investigation was conducted to explore previous research on Open Innovation in the food sector. Although recent studies, such as those by [68,69], have contributed to the literature, it remains relatively sparse. This presents an opportunity to propose innovation challenges that address the priority technologies identified in the MGI for the citrus agro-industrial chain.

After corroborating the findings of various open innovation platforms, where solvers and seekers can collaborate to address challenges, a selection of platforms hosting challenges and/or innovation projects related to the agro-industrial sector is presented [61].

In total, six (6) platforms were analyzed, presenting challenges, cases, and projects related to food or agroindustry. For example, Wazoku (https://www.wazokucrowd.com/ accessed on 18 March 2025) addresses challenges in vegetable oils, legumes for diversity, agricultural intensification, and sustainability, as well as Optimal Crops Identification for Agrophotovoltaic Applications and Satellite-Based Remote Sensing for Smallholder Farms. The Ninesigma platform (https://www.ninesigma.com/ accessed on 18 March 2025) is contributing to biodegradable fertilizers, maize, and salt in food products. Ruta N focuses on livestock, tanning, and vegetable oils. The yet2 platform (https://www.yet2.com/services/open-innovation-portals/ accessed on 18 March 2025) has conducted projects on new protein suppliers, as well as topics related to cellular aquaculture for isolating live fish cells, cultivating them, and subsequently assembling them into fresh and frozen seafood products. The Itonics platform (https://www.itonics-innovation.com/open-innovation accessed on 18 March 2025) features initiatives on intelligent trend exploration in the food industry. Finally, the Ennomotive platform (https://www.ennomotive.com/ accessed on 18 March 2025) has challenges related to sustainable energy in cacao drying. However, no projects, challenges, or cases specifically related to citrus were found on these platforms.

Regarding the I’mnovation platform (https://www.imnovation-hub.com/es/ accessed on 18 March 2025), it presents challenges in sectors such as energy, construction, water, digital transformation, science and technology, and society. In the food sector, it featured a challenge on an inflatable aeroponic garden for lettuce in the desert. Among the 44 challenges reported on the platform, none are specifically related to the citrus agro-industrial chain.

There are numerous MGIs, which represent elements and variables that characterize them. For example, the work of [70], which corresponds to a fifth (5th)-generation model and represents an open innovation model, or the model of [71], who developed feedback loops. The reference models also include the work of [72,73,74], who proposed not only ideas and methodologies, but also the alignment of the market with technology, as well as proposing solutions through invention and/or adaptation of technologies. In the same sense as the previous ones, it is pertinent to mention the work of [75] on challenge-driven innovation policies.

The proposed MGI-3 or MGi features innovative aspects such as alignment with monitoring and prospective studies; specific elements or aspects of sustainability and sustainable development in agriculture; as well as variables in technological capabilities; and, in particular, specific mention of the importance of aligning with open innovation challenges.

6. Conclusions

The proposed MGI-3 represents a sustainable agribusiness model within the citrus production chain. This model holds significant potential to foster the development of emerging enterprises in Quindío Department, facilitating their progression from inception through to full-scale development, thereby ensuring the sustainability of both citrus products and their derivatives. As evidenced by the findings of this research, two critical factors for success in the citrus production chain—competitiveness and added value—require ongoing diversification of the product offering through innovation, which in turn enables access to new markets.

In the specific context of Quindío, MGI-3 emerges as the most appropriate framework to address challenges within the citrus sector. It encompasses the entire lifecycle of enterprise development, from idea generation to full realization, while considering multiple essential factors that ensure the long-term sustainability of citrus production in the region. Achieving sustainability within the citrus production chain necessitates the active participation and support of both institutional and governmental bodies within the citrus cluster. Thus, the involvement of these stakeholders is paramount to the successful implementation of this model.

Furthermore, it is both possible and desirable for MGI-3 to align with the key themes of technologies and innovations identified in the two Delphi rounds, as well as with the evolving trends, invariants, and other transformative factors anticipated between 2024 and 2035.

The identification of priority variables also highlights several challenges that may impede the sector’s development and competitiveness. These challenges include the potential absence of organizational structures capable of effectively managing innovation, low adoption rates of advanced agricultural technologies, and insufficient investment in research and development. Additionally, there is a pressing need to improve product quality standards, diversify offerings, and enhance collaboration among universities, industry, and government entities. The integration of circular economy principles, implementation of targeted innovation management programs, and reinforcement of organizational resilience are also critical areas requiring attention.

To address these shortcomings, MGI-3 offers the potential to bridge gaps in the citrus sector by focusing on essential elements such as idea management, leadership, investment in infrastructure, and research, development, and innovation (R&D&I) activities. The model’s adaptability to specific regional contexts is evident in its incorporation of advanced elements such as Agriculture 4.0 and 5.0, agricultural innovation platforms, and technological innovation projects. In the transformation phase, the model emphasizes the development of strategies for innovation management, value-added transformation, and new product development, with a particular focus on knowledge and technology management, underpinned by foresight and growth strategies. MGI-3 aims to generate value, build a robust portfolio, achieve profitability through innovation, and enhance organizational resilience, with strategic emphasis on participation in innovation networks.

Regarding open innovation, the citrus agro-industrial chain stands to benefit significantly from open innovation platforms, which facilitate the resolution of challenges within the food and agro-industry sectors. These platforms can foster the development of strategies to address innovation challenges identified by industry stakeholders, in alignment with the priority variables of MGI-3 and previous technological surveillance and foresight studies.

In conclusion, MGI-3, as a generic interactive model, offers a dynamic and adaptable solution to enhance competitiveness and value creation within the citrus sector. By emphasizing collaboration, sustainability, and innovation, the model serves as a strategic tool to address the challenges identified within the sector and facilitate its long-term growth and development.

Our MGI, compared to other MGIs, has innovative aspects such as alignment with monitoring and prospective studies; specific elements or aspects of sustainability and sustainable development in agriculture; as well as variables in technological capabilities; and, in particular, the specific mention of the importance of aligning with open innovation stakeholders.

Finally, given the dynamic nature of organizational structure models, the proposed MGI, while containing prioritized and related variables in inputs, transformation, and outputs, is appropriate and aligned with the current situation of the citrus chain in the region of origin of this research. For new uses, scaling, and processes, new variables, prioritizations, and structures appropriate for the regions must be taken into account.

7. Recommendations

In the context of the recommendations for the implementation of MGI-3, as proposed by companies within the sector, several critical considerations must be taken into account. Among the most significant are the following:

• Active Engagement of Senior Management: It is essential that senior leadership demonstrate a clear and unwavering commitment to the MGI’s implementation by dedicating necessary resources and providing strategic direction for its execution.
• Comprehensive Organizational Involvement: The process of MGI implementation should involve all organizational levels, fostering active participation and ensuring the commitment of employees to the management of ideas, innovation, and organizational change.
• Training and Capacity-Building: Adequate training programs focused on MGI concepts, tools, and methodologies should be provided to all members of the organization, ensuring that they possess the necessary skills to contribute effectively to the innovation process.
• Fostering an Innovative Organizational Culture: A culture that encourages creativity, innovative thinking, and experimentation should be cultivated. This will promote the generation and exchange of ideas within the organization.
• Phased Implementation: It is advisable to begin the MGI implementation in specific areas of the organization, with the intention of gradually expanding to other departments or processes. This phased approach allows for continuous adjustments and improvements during the rollout.
• Establishing Monitoring and Evaluation Mechanisms: Mechanisms for monitoring and evaluating the progress and outcomes of MGI implementation should be established. These data can be used to make ongoing adjustments and refine the process as necessary.
• Collaboration and Knowledge Sharing: Companies should actively seek collaboration with other firms, research institutions, and government agencies. Participation in innovation networks can facilitate the exchange of knowledge, experiences, and best practices, thus fostering the development of the citrus sector