AAVS_14_9_1892-1906

INTRODUCTION

The livestock sector plays a vital role in global food security by providing essential animal based protein. However, this sector continues to face significant threats from infectious diseases that can cause substantial economic losses (Kovacs et al., 2025). Foot and mouth disease (FMD) is an acute and highly contagious viral disease affecting cloven hoofed animals. It causes direct impacts, such as reduced productivity, decreased milk yield, weight loss, and reproductive disorders, as well as indirect impacts, including movement restrictions, supply chain disruptions, and trade barriers (Kamel et al., 2019; Knight- and Rushton, 2013).

In 2022, Indonesia experienced the re-emergence of FMD approximately 32 years after being declared free from the disease in 1990. The virus was suspected to have been introduced through illegal trade or the movement of live animals from endemic regions in Southeast Asia (Susila et al., 2022). In response, the government implemented mass vaccination programs, strengthened surveillance, and utilized the national animal health information system, known as iSIKHNAS. However, the effectiveness of these policies still varies across regions, particularly in Java, Sumatra, and Nusa Tenggara, especially at the farmer level as primary production actors (Chen et al., 2024; Hennessy and Rault, 2023). Despite these interventions, FMD detection rates remain relatively high in several areas, with continued impacts on livestock productivity (Nurdiansyah et al., 2026; Saptahidhayat et al., 2023), indicating that current control measures have not yet achieved sustainable disease risk reduction.

Gorontalo Province is one of Indonesia’s major beef cattle production centers and plays a strategic role in interregional livestock supply chains, particularly as a primary supplier to Kalimantan. This strategic function underscores the need for a robust animal health management system, given that the movement of livestock across regions substantially increases the risk of infectious disease transmission, including foot and mouth disease (FMD). Consequently, FMD poses significant challenges not only to animal health but also to livestock distribution, market access, and interregional trade. Based on data from the Central Statistics Agency of Gorontalo Province, (2021–2025), the cattle population in Gorontalo Province fluctuated, increasing from 261,084 head in 2021 to 266,728 head in 2022, before declining sharply to 206,802 head in 2023 and 158,436 head in 2024. This decline is used as an indicator of both dynamic changes and structural vulnerability in the beef cattle subsector.

In terms of livestock movement, FMD zoning based restrictions have been implemented since 2022. According to data from the Gorontalo Provincial Agriculture Office, these policies suspended cattle shipments from Gorontalo to Tarakan and Balikpapan from August until the end of the year. Consequently, cattle exports declined sharply from 5,845 head in 2021 to 2,896 head in 2022. This situation demonstrates that FMD-related concerns have become a strategic factor in regulating livestock distribution, even though FMD outbreaks in Gorontalo Province were only officially detected at the end of 2024. According to the annual report of the Gorontalo Provincial Agriculture Office, the number of FMD cases reached 7,454 in 2024 and 6,688 in 2025, resulting in a cumulative total of 14,142 cases during the 2024–2025 period. Gorontalo Regency recorded the highest number of cases, with 8,069 cases, followed by North Gorontalo Regency with 3,496 cases and Pohuwato Regency with 1,957 cases. In contrast, the lowest numbers were reported in Gorontalo City and Boalemo Regency, with 33 and 121 cases, respectively. The large number of cases and their wide spread show that FMD remains a serious challenge in Gorontalo Province, requiring rapid, coordinated, and sustainable control measures.

Several studies have shown that the spread of foot and mouth disease (FMD) is driven by complex epidemiological factors, including preclinical transmission and persistent infections that are not fully captured in predictive models (Chowdhury et al., 2020; Scharzenberger et al., 2025; Bertram et al., 2020), and this complexity is made worse by limited knowledge (Humphreys et al., 2025). Various technological approaches, including geographic information systems (GIS), multicriteria decision analysis, contact network models, and epidemiological modelling, have been applied to support risk mapping, livestock movement regulation, and biosecurity management (Prasetia et al., 2025; Wiratsudakul and Sekiguchi, 2018; Mfinanga et al., 2025; Ono and Shimamoto, 2026). Beyond technical dimensions, control effectiveness is strongly influenced by farmer behavior, particularly vaccine adoption shaped by risk perception, trust, and socio economic and institutional factors (Zhao et al., 2021; Donadeu et al., 2019; Railey et al., 2018). However, increased knowledge does not always translate into behavioral change (Kiayima et al., 2025; Araujo et al., 2026; Stenfeldt et al., 2025).

Additionally, surveillance is constrained by carrier animals (Ndendya and Ng’oga, 2026; Wang and Yang, 2026), while FMD imposes significant economic losses through reduced productivity and increased control costs (Govindaraj et al., 2021; Bijari et al., 2025).

Although various approaches have been applied to FMD control, they remain fragmented across disciplines and have not been fully integrated into a unified decision support framework for regional prioritization. Existing studies have primarily focused on isolated analytical components without a systematic mechanism to translate multidimensional determinants into prioritized and implementable control strategies at the subnational level. This reflects a critical gap in strategic decision making within animal health governance, where analytical outputs are not fully transformed into operational policy priorities. Therefore, an integrated strategic decision making approach is required to support evidence-based prioritization of FMD control interventions.

This study aims to empirically analyze integrated foot-and mouth disease (FMD) control strategies for beef cattle in Gorontalo Province and to formulate priority control strategies using the SWOT–QSPM approach. This study is expected to generate evidence-based strategic recommendations that are adaptive, measurable, and actionable to support the improvement of FMD control program effectiveness.

MATERIALS AND METHODS

Study location and time

This study was conducted from November 2025 to February 2026 in Gorontalo Province, Indonesia. The area was purposively selected as a beef cattle development region previously affected by foot and mouth disease (FMD).

Research approach

This study employed an exploratory sequential mixed methods approach supported by structured expert judgment and quantitative strategic assessment. This approach was used to examine internal and external strategic factors related to FMD control in beef cattle farming and to formulate priority strategies using IFE, EFE, SWOT, and QSPM analyses. The study began with a qualitative phase, in which structured interviews, observation, and documentation were used to identify and validate internal and external strategic factors. This was followed by a quantitative phase involving the assignment of weights, ratings, and attractiveness scores to evaluate and prioritize strategic alternatives. The integration of qualitative factor identification and quantitative strategic assessment enabled a more comprehensive, valid, and context-specific understanding of FMD control strategies in Gorontalo Province (Creswell and Plano, 2023). In addition, a descriptive quantitative approach was applied to systematically describe the observed conditions based on measurable data (Cleland, 2022; Sardana et al., 2023).

This study was designed as an empirical strategic assessment rather than a narrative or conceptual review. The identification of internal and external strategic factors was based on primary qualitative evidence obtained through structured interviews with expert informants and field stakeholders who were directly involved in foot and mouth Disease (FMD) prevention and control in Gorontalo Province. To ensure methodological rigor, the study adopted a Structured Expert Judgment (SEJ) approach, whereby expert knowledge was systematically elicited, validated, and aggregated to support strategic decision-making. Structured Expert Judgment is widely recognized as an evidence-based methodology for situations where empirical field observations and professional expertise must be integrated to evaluate complex policy and management problems under uncertainty (Hanea et al., 2024). The validated strategic factors were subsequently quantified through the IFE, EFE, IE Matrix, SWOT, and QSPM analytical frameworks to generate evidence-based strategic priorities derived from original field data rather than literature synthesis.

Selection of informants

This study employed a purposive sampling technique to select informants based on their roles, level of involvement, expertise, and experience in beef cattle production and foot and mouth disease (FMD) control in Gorontalo Province. The informants were classified into two categories according to their roles in the SWOT and IFE/EFE analysis: expert informants, who assigned weights to strategic factors, and field respondents, who provided ratings reflecting actual field conditions. This classification was intended to distinguish expert-based strategic weighting from field-based situational assessment. The number of expert informants (n = 9) was determined based on the structured expert elicitation principles outlined by Hanea et al., (2024), which recommend a panel size of approximately 5–12 experts, depending on the complexity of the problem and the heterogeneity of expertise involved. This range is considered adequate to ensure reliable aggregation of expert judgments in strategic assessment contexts.

Types and sources of data

This study utilized both qualitative and quantitative data. Qualitative data were obtained through structured interviews to identify internal and external factors, which served as the basis for developing variables in the SWOT analysis. Quantitative data, in the form of numerical values, were used for weighting, rating, and calculation in the QSPM method, enabling objective determination of strategic priorities.

The data in this study were classified into two types, namely primary and secondary data, which complemented each other in supporting the analysis. Primary data were collected directly through interviews with beef cattle farmers and various relevant stakeholders, including officials from the livestock services department, animal health officers, extension workers, and academics. These interviews aimed to get a clear picture of foot and mouth disease (FMD) control conditions, including the identification of internal and external factors influencing its implementation in Gorontalo Province. Meanwhile, secondary data were obtained from several official and

Table 1: Characteristics of informants.

Group	Sub-category	Inclusion Criteria	n (Number of people)
Expert Informants	Provincial Livestock Office officers (FMD division)	≥5 years of experience in livestock policy implementation and/or FMD control programs	2
	Provincial veterinarians (veterinary medical officers)	≥5 years of experience in animal health services and FMD control	1
	Provincial animal health officers	≥5 years of experience in field animal health services (vaccination, surveillance, outbreak response)	1
	Extension officers	≥5 years of experience in extension services and farmer assistance	1
	Academics	≥5 years of experience in research or teaching in livestock-related fields	1
	Farmers	≥5 years of experience and are involved in the coordination and control of FMD	3
Field Respondents	Farmers	≥5 years of experience, manage beef cattle at the farm level, and have cattle that have or have not been exposed to FMD.	20
	Extension officers	≥5 years of experience in livestock extension services	2
	District veterinarians	≥5 years of experience in field animal health services	3
	District Animal health officers	≥5 years of experience in technical field animal health services	7

credible sources, such as the national animal health information system (iSIKHNAS), reports from the Livestock and Plantation Service of Gorontalo Province, various scientific publications, and policy documents related to FMD control. These data were used to strengthen the analytical results and provide a more comprehensive empirical foundation for the study.

Data collection methods

Data collection techniques in this study included observation, interviews, and documentation, which were conducted in an integrated manner to ensure data depth and accuracy. The researcher conducted direct field observations at livestock farms to identify animal husbandry conditions, biosecurity practices, and foot and mouth disease (FMD) control measures at the field level. Structured interviews were carried out using a guided instrument with beef cattle farmers, officials from the livestock and plantation services, animal health officers, extension workers, and academics to obtain information related to internal and external factors influencing FMD control. In addition, documentary data were collected from various official sources, such as annual reports from the livestock and plantation service and data from the national animal health information system (iSIKHNAS), to complement and verify field findings.

Data analysis

Data analysis in this study was conducted using a combined qualitative and quantitative approach through SWOT and QSPM methods, following a strategic formulation framework consisting of several stages (Benzaghta et al., 2021; David, 2016)

Input stage

At this stage, informants identified internal and external factors influencing the effectiveness of foot and mouth disease (FMD) control in beef cattle. Internal factors consisted of strengths and weaknesses of the implemented control strategies, while external factors included opportunities and threats originating from the external environment. The identification process was conducted through in-depth interviews with expert informants as the primary data source. Data validation was carried out using source triangulation techniques to ensure the credibility and reliability of the information obtained.

The weighting of strategic factors in the Internal Factor Evaluation (IFE) and External Factor Evaluation (EFE) matrices was conducted using a four-point Likert scale, where 1 = not important, 2 = less important, 3 = important, and 4 = very important. Each informant assessed the level of importance of each factor. Subsequently, the scores from all informants were averaged to obtain the importance value of each factor and then normalized so that the total weights of internal and external factors each equaled 1.00. This procedure ensured that each strategic factor was assigned a relative weight according to its perceived importance based on expert judgment.

The assignment of ratings in the IFE and EFE matrices was conducted using a 1–4 scale. In this study, the rating value does not represent the importance of a factor, as factor importance is reflected in the weight, but rather indicates the relative strategic condition or response associated with each factor. For the IFE matrix, ratings followed the conventional strategic management interpretation, where 4 indicates a major strength, 3 indicates a minor strength, 2 indicates a minor weakness, and 1 indicates a major weakness. Therefore, strengths were assigned higher ratings when they were well established or effectively implemented, whereas weaknesses received lower ratings when they represented serious limitations in FMD control. For the EFE matrix, ratings reflected the effectiveness of the response to external factors, where 4 indicates a superior response, 3 an above-average response, 2 an average or limited response, and 1 a poor response. Thus, opportunities received higher ratings when they could be effectively utilized, while threats received lower ratings when they were serious and not yet adequately controlled. Each rating was then multiplied by its corresponding weight to obtain the weighted score, which was used to calculate the total IFE and EFE scores and determine the strategic position in the Internal External matrix.

Analysis stage

The total IFE and EFE scores were subsequently used in the Internal–External (IE) Matrix. The IFAS value was plotted on the horizontal axis, representing the internal condition, while the EFAS value was plotted on the vertical axis, representing the external condition. The combination of these two values determines the strategic position within the nine-cell IE Matrix, which classifies strategies into growth and build, hold and maintain, or harvest and divest strategies, depending on the cell in which the scores are located.

SWOT matrix development. At this stage, internal and external factors were mapped into the SWOT Matrix to formulate alternative strategies for FMD control in beef cattle. The mapping process generated four strategic groups, namely SO (Strength–Opportunity) strategies, which use internal strengths to capitalize on external opportunities; WO (Weakness–Opportunity) strategies, which aim to minimize weaknesses by utilizing opportunities; ST (Strength–Threat) strategies, which use strengths to address external threats; and WT (Weakness–Threat) strategies, which are defensive strategies aimed at reducing weaknesses and avoiding threats

Decision stage

At the decision stage, the Quantitative Strategic Planning Matrix (QSPM) was used to determine the priority of strategies based on the relative attractiveness of each strategic alternative. The procedure included the identification of internal and external strategic factors along with their weights derived from the IFE and EFE matrices; the assignment of Attractiveness Scores (AS) for each strategic alternative using a 1–4 scale, where 1 = not attractive, 2 = somewhat attractive, 3 = attractive, and 4 = highly attractive; and the multiplication of factor weights by AS to obtain the Total Attractiveness Score (TAS) using the following formula:

TASᵢ = ∑(Bobotⱼ × ASᵢⱼ)

Where irepresents the i-th strategic alternative and j represents the j-th strategic factor. The strategy with the highest Total Attractiveness Score (TAS) is considered the priority strategy recommended for implementation.

The research framework illustrates the analytical stages employed in this study, as presented in Figure 1, to enhance methodological transparency. The framework systematically describes the research workflow, which includes data collection, identification of internal and external factors, evaluation of strategic factors using the IFE and EFE matrices, determination of strategic positioning through the IE matrix, formulation of alternative strategies based on SWOT analysis, and prioritization of control strategies using the QSPM method.

RESULTS AND DISCUSSION

Matrix ife and efe

The Internal Factor Evaluation (IFE) matrix was developed based on primary data collected through field observations and in-depth interviews with key informants. The data were analyzed to identify the organization’s internal strategic factors, including strengths and weaknesses. Each identified internal factor was subsequently assigned a weight and rating according to its relative influence on the organization’s internal condition, resulting in a weighted score. The results of the Internal Factor Evaluation (IFE) matrix analysis are presented in Table 2.

Table 2 shows that the results of the Internal Factor Evaluation (IFE) analysis indicate a relatively strong internal condition, with a total score of 2.741. The weighted score of strengths (1.813), which exceeds the weighted score of weaknesses (0.928), indicates that the available institutional resources and existing control programmes provide a supportive foundation for strengthening FMD control management in the study area.

The main strengths identified include vaccination coverage, vaccine logistics availability, cross-sectoral coordination, the presence of trained vaccinators, and the utilization of the animal health information system (iSIKHNAS). The high weighted scores of these factors indicate a consensus among respondents regarding the strategic role of institutional and operational aspects in supporting programme success. This finding is further supported by vaccination achievements during the 2022–2024 period, which consistently met or exceeded the established targets (2022: 91.87%; 2023 and 2024 exceeded the targets). These results demonstrate that vaccine distribution systems, logistical support, vaccination implementation, and programme coordination

Table 2: Internal factor evaluation (IFE) matrix.

No	Internal Factors	Weight	Rating	Weighted Score (Weight × Rating)
Strengths
1	FMD vaccination program in beef cattle has been widely implemented across all districts/cities in Gorontalo Province	0.086	4	0.344
2	The availability of vaccine logistics is supported by surveillance and laboratory testing activities	0.084	4	0.336
3	Cross-sectoral coordination has been established, involving central government, provincial and district/city governments, BBVet, quarantine agencies, and relevant stakeholders	0.082	4	0.328
4	The national animal health information system (iSIKHNAS) is used as a basis for animal health recording and monitoring	0.084	3	0.252
5	Competent and trained vaccinators are available for FMD vaccination programs	0.079	3	0.237
6	Gorontalo Province has a strategic position as a beef cattle production area with interregional distribution networks, particularly to Kalimantan	0.079	4	0.316
Total Strength		0.494		1.813
Weaknesses
1	Low acceptance of vaccination among some farmers due to risk perception, post-vaccination trauma, and limited animal health literacy	0.086	2	0.172
2	Beef cattle management system is still dominated by extensive/traditional farming, making biosecurity implementation and vaccination difficult	0.082	2	0.164
3	Livestock identification (ear tagging) is not yet optimal and not fully integrated with the iSIKHNAS system	0.084	2	0.168
4	Limited availability of animal health personnel in the field, with overlapping workloads	0.084	2	0.168
5	Limited incentives for vaccinators, not fully supported by local government funding	0.086	2	0.172
6	iSIKHNAS system performance still faces technical constraints, including limited data entry time and access disruptions affecting real-time monitoring quality	0.084	1	0.084
Total Weakness		0.506		0.928
Total IFAS		1.000		2.741

Source: Processed data, 2026.

have functioned effectively at the implementation level.

However, these achievements primarily reflect programme implementation success and do not yet fully represent the optimization of all components within the FMD control system. The main weaknesses identified include limited field personnel, partial farmer acceptance of vaccination, suboptimal livestock identification, and technical limitations in the utilization of iSIKHNAS. Within the IFAS framework, strengths represent institutional capacity and programme implementation capability, whereas weaknesses reflect operational constraints that require further improvement. This condition indicates an implementation gap between institutional preparedness and programme execution at the field level, particularly regarding human resources and animal health data management.

These findings support the One Health approach, which emphasizes that animal disease control requires integrated coordination among animal health, human health, and environmental sectors to improve disease management effectiveness (Donnelly and Stilianakis, 2026). Therefore, strengthening the FMD control system should not rely solely on increasing vaccination coverage but also requires optimization of surveillance systems, enhancement of field personnel capacity, and strengthening collaboration among stakeholders.

At the farmer level, limited vaccine acceptance remains an aspect requiring attention, although it has not become a major constraint because vaccination coverage remained high during 2022–2024. This condition indicates that most farmers have accepted vaccination programmes; however, risk communication strategies remain necessary to maintain and improve farmer participation. This finding is consistent with Merrill et al. (2019), who reported that risk communication plays an important role in improving compliance with disease prevention practices. Furthermore, active stakeholder engagement through collaborative approaches contributes to knowledge integration and strengthens the implementation of animal health policies (Hitziger et al., 2018).

The External Factor Evaluation (EFE) Matrix is a quantitative SWOT analysis tool used to assess external factors in the form of opportunities and threats. The EFE matrix was developed based on primary data obtained from field observations and in-depth interviews with key informants. Each external factor was assigned a weight and rating to generate weighted scores that reflect the influence of the external environment and serve as a basis for determining control strategies. The results of the EFE matrix analysis are presented in Table 3.

Table 3 shows that the External Factor Evaluation (EFE) analysis resulted in a total score of 2.700, indicating that the external environment of FMD control is relatively favourable. The opportunity score (1.809) was higher than the threat score (0.891), suggesting that external factors provide greater support than constraints for the implementation of FMD control programmes. These results indicate that government policy support, institutional collaboration, and opportunities for digital system development represent important external factors influencing FMD control activities.

The main opportunities identified include national policy support, the development of Communication, Information, and Education (CIE) programmes, cross-sectoral collaboration, and the development of the animal health information system (iSIKHNAS). The availability of iSIKHNAS provides an opportunity to strengthen animal health data management through improved reporting, monitoring, and information integration, although several technical limitations remain in its current application.

The FMD CIE programme was identified as an important external opportunity because it contributes to improving farmers’ knowledge, awareness, and understanding of vaccination as a preventive measure for disease control. These activities were implemented through the delivery of information regarding FMD causes, transmission, prevention, and control by veterinary professionals, followed by discussion sessions and vaccination services for community-owned cattle. The implementation of CIE activities is relevant considering that limited understanding among farmers and vaccine refusal based on the perception that healthy animals do not require vaccination remain challenges in FMD control implementation. This finding is consistent with Merrill et al., (2019), who reported that risk communication plays an important role in improving compliance with disease prevention practices.

Furthermore, the findings support the One Health approach, which emphasizes the importance of coordination among animal health, human health, and environmental sectors in disease management (Donnelly and Stilianakis, 2026). The importance of integrated surveillance and stakeholder involvement is also reflected in previous studies. These findings reinforce the view of Kumar et al., (2021) that integrated animal disease surveillance systems can improve disease monitoring and

response through the integration of information from multiple sources. Similarly, this finding is consistent with Mariner (2009), who highlighted that participatory surveillance involving livestock owners contributes to improving the relevance and sustainability of disease control interventions

Table 3: External factor evaluation (EFE) matrix.

No	External Factors	Weight	Rating	Weighted Score (Weight × Rating)
Opportunities
1	Strong national policy support and increasing availability of animal health logistics for FMD control	0.090	4	0.360
2	Potential development of iSIKHNAS as an integrated information system to support digital transformation of surveillance and early disease detection	0.082	3	0.246
3	Strengthening cross-sector collaboration (government, academia, private sector, military/police, and livestock stakeholders) in animal disease control	0.084	4	0.336
4	Expansion of communication, information, and education (CIE) programs to improve farmer adoption of vaccination and biosecurity practices	0.090	4	0.360
5	Potential development of interregional beef cattle markets, particularly to Kalimantan, contingent upon controlled animal health status	0.087	3	0.261
6	Strengthening livestock movement control systems through checkpoints and digital-based animal health certification	0.082	3	0.246
Total Opportunities		0.515		1.809
Threats
1	Risk of FMD re-emergence due to uneven and unsustained vaccination coverage	0.084	2	0.168
2	Restrictions on interregional livestock movement that may reduce market access and disrupt beef cattle trade	0.082	2	0.164
3	Declining trust from destination regions toward beef cattle originating from Gorontalo if animal health status is not maintained	0.082	2	0.164
4	Dependence on data that is not yet fully accurate and real-time, potentially hindering evidence-based decision-making	0.079	2	0.158
5	High potential for rapid interregional spread of FMD due to livestock mobility and low biosecurity implementation	0.079	2	0.158
6	Risk of program sustainability decline due to reliance on field personnel without a stable incentive system	0.079	1	0.079
Total Threats		0.485		0.891
Total		1.000		2.700

Source: Processed data, 2026.

Despite the favourable external conditions, several threats were identified, including uneven vaccination coverage,

interregional livestock movement, declining market confidence, limited data accuracy, and low implementation of biosecurity practices among farmers. These factors indicate that FMD control remains influenced by external challenges that may affect programme implementation. Therefore, the EFE analysis demonstrates that the external environment provides substantial opportunities while simultaneously presenting several challenges that need to be considered in the overall assessment of the FMD control system.

Internal external (ie) matrix

The Internal–External (IE) Matrix was developed based on the integration of Internal Factor Evaluation (IFE) and External Factor Evaluation (EFE) scores obtained from primary data collected through field observations and in-depth interviews with key informants. The Internal–External matrix is presented in Figure 2.

Figure 2 shows that the integration of IFE and EFE scores positions the FMD control system in Cell V of the IE Matrix, indicating a hold and maintain strategic orientation. This position reflects a balance between internal and external factors, where the existing programmes should be maintained while gradually improving internal capacity, optimizing external opportunities, and addressing remaining constraints. Field findings support this position, as vaccination programmes, logistics, trained personnel, cross-sector coordination, and iSIKHNAS are already functioning, although farmer acceptance, extensive farming systems, uneven personnel distribution, limited incentives, livestock identification, and technical data constraints still require gradual improvement.

This finding is consistent with Dini and Janet (2024 who stated that the integration of SWOT, IFE, and EFE analyses provides a systematic framework

for determining strategic prsiorities under dynamic) environmental conditions. This classification is further supported by David (2016), who classified IFE and EFE scores into low (1.00–1.99), medium (2.00–2.99), and high (3.00–4.00) categories. Based on this classification, the IFAS score (2.741) and EFAS score (2.700) obtained in this study fall within the medium category, confirming that the placement of the FMD control system in Cell V of the IE Matrix is methodologically justified. Furthermore, a sensitivity analysis was conducted by simulating a ±0.5 variation in the ratings of the highest-weighted factors in the IFE and EFE matrices. The results showed that these variations did not alter the category or shift the strategic position. This indicates that the hold and maintain position remains stable under reasonable changes in the key input parameters.

Swot matrix

The SWOT analysis was conducted based on internal and external strategic factors identified through field observations and in-depth interviews with key informants. Strategic alternatives were generated using the TOWS matching approach by integrating strengths, weaknesses, opportunities, and threats based on the results of the IFE and EFE analyses. The results of the SWOT matrix are presented in Table 4.

Table 4 shows that the SWOT analysis generated twelve strategic alternatives consisting of SO, WO, ST, and WT strategies to strengthen FMD control in beef cattle production systems in Gorontalo Province. The details of each strategic alternative are described in the following section.

SO strategies

The SWOT analysis identified three SO strategies that utilize institutional strengths to capitalize on external opportunities for strengthening FMD control (Table 4). The highest-priority strategy was the optimization of FMD vaccination through national policy support and cross-sector collaboration (S1, S2, S3, S5, O1, O3), integrating vaccination coverage, vaccine logistics, trained vaccinators, and institutional coordination. These findings support the One Health approach, which emphasizes multisectoral coordination in animal disease control (Donnelly and Stilianakis, 2026), and are consistent with Pudenz et al., (2021), who highlighted the importance of collaboration among livestock producers, veterinary authorities, and other stakeholders in implementing FMD preparedness and biosecurity measures. The second SO strategy identified the integration of iSIKHNAS with vaccine logistics and field vaccinators to strengthen vaccination management, while the third identified the development of Gorontalo as a regional beef cattle production hub supported by adequate animal health management.

ST strategies

The SWOT analysis generated three ST strategies aimed at using institutional strengths to minimize external threats associated with FMD transmission. The highest-priority strategy focused on strengthening vaccination and active surveillance, particularly in areas characterized by intensive livestock movement. The second strategy emphasized controlling livestock movement through cross-sector coordination and digital animal health certification using iSIKHNAS. The third strategy focused on improving the completeness, accuracy, and validity of iSIKHNAS data to support evidence-based decision-making. These findings are consistent with Wang et al., (2021), who demonstrated that integrated FMD surveillance and risk assessment can identify areas and pathways with a higher probability of disease introduction and transmission. Their study showed that surveillance data, outbreak information, livestock distribution, and movement-related risk factors can be integrated to improve disease monitoring and inform targeted control measures. The present findings are also in line with Garner et al., (2021), who found that an appropriate combination of surveillance approaches is required to demonstrate the absence of FMD and support the recovery of disease-free status following an outbreak. Their study emphasizes that surveillance design must consider detection sensitivity, cost, time requirements, and the epidemiological characteristics of the livestock population.

Wo strategies

The SWOT analysis generated three WO strategies: improving farmers’ knowledge through Communication, Information, and Education (CIE)

programmes, strengthening the capacity of anim al health personnel, and integrating iSIKHNAS with the livestock

Table 4: SWOT matrix.

IFAS EFAS

Strength

Weaknesses

Opportunities

Strategy SO

Optimization of FMD vaccination based on national policy through cross-sector collaboration (S1, S2, S3, S5, O1, O3).

Integration of iSIKHNAS with logistical support and field vaccinators (S2, S5, O2).

Using Gorontalo as a beef cattle production hub for interregional market expansion (S6, O5).

Strategy WO

Improving farmer literacy through Communication, Information, and Education (CIE) programs (W1, W2, O4).

Strengthening the capacity of animal health human resources (W4, O3).

Digital transformation of iSIKHNAS and optimization of livestock identification (ear tagging) systems (W3, W6, O2).

Threats

Strategy ST

Strengthening vaccination and surveillance to prevent FMD re-emergence (S1, S5, T1).

Livestock movement control through cross-sector coordination and digitalization (S3, S6, T2, T5).

Improving the validity and quality of iSIKHNAS data (S4, T4).

Strategy WT

Improvement of incentive systems and distribution of animal health personnel (W5, T6).

Gradual transition from extensive to semi-intensive livestock management (W2, T5).

Strengthening the stability of the iSIKHNAS information system infrastructure (W6, T6).

Source: Processed data, 2026.

identification system. The CIE programme was identified as the highest-priority strategy because the effectiveness of vaccination and biosecurity largely depends on farmers’ knowledge, acceptance, and active participation. Meanwhile, strengthening the capacity of animal health personnel is essential to ensure the quality of vaccination services, farmer education, and disease surveillance. The integration of iSIKHNAS with the livestock identification system is also crucial for improving the traceability of vaccination status, livestock movements, and disease events. These findings are consistent with Pudenz et al., (2021), who reported that the implementation of FMD biosecurity measures by cattle producers is influenced by their knowledge, risk perceptions, confidence in the effectiveness of recommended practices, and access to relevant information.

Wt strategies

The SWOT analysis identified three WT strategies: improving incentive mechanisms for animal health personnel, promoting a gradual transition from extensive to semi-intensive livestock production systems, and strengthening the stability and reliability of the iSIKHNAS infrastructure. Improved incentives are expected to maintain the motivation, operational capacity, and service coverage of veterinarians, vaccinators, and field officers. A gradual transition to semi-intensive production can

facilitate livestock identification, vaccination scheduling,

health monitoring, biosecurity implementation, and

movement recording. Meanwhile, reliable iSIKHNAS infrastructure is required to generate accurate and timely surveillance data. These findings are consistent with Metwally et al. (2024), who emphasized that progressive FMD control requires surveillance systems capable of monitoring programme progress, evaluating interventions, and supporting risk-based decisions. Garner et al., (2021) also demonstrated that combining surveillance methods and diagnostic technologies can improve disease monitoring and post-outbreak decision-making.

Qspm matrix

Based on the IE Matrix results, FMD control in beef cattle production systems in Gorontalo Province is positioned in Cell V (Hold and Maintain), indicating that the strategic direction should focus on strengthening and maintaining the existing control system. The QSPM was then used to determine the priority ranking of the ST and WO strategies based on the internal and external factor weights derived from the IFE and EFE matrices. The resulting strategic priorities are presented in Table 5.

Based on the QSPM analysis, the strategy of livestock movement control through cross-sectoral coordination and digitalization (ST2) achieved the highest Total Attractiveness Score (TAS) of 6.224, making it the top priority for foot and mouth disease (FMD) control in Gorontalo Province. This result indicates that experts and respondents considered this strategy to be the most

appropriate among the proposed alternatives because it particularly inter-agency coordination, the support of the

national animal health information system (iSIKHNAS), and Gorontalo’s strategic role as one of Indonesia’s beef cattle-producing and supplying regions. Interview findings further revealed that most informants regarded livestock movement control as a critical component of FMD management. According to the respondents, high livestock mobility not high livestock mobility not only increases the potential for disease transmission but also affects the continuity of livestock distribution, regional market access, and the sustainability of beef cattle farming.

Table 5: QSPM Matrix.

Factor SWOT	Weight	ST1		ST2		ST3		WO1		WO2		WO3
Factor SWOT		AS	TAS	AS	TAS	AS	TAS	AS	TAS	AS	TAS	AS	TAS
S1	0.086	3	0.258	2	0.172	2	0.172	3	0.258	3	0.258	1	0.086
S2	0.084	3	0.252	3	0.252	2	0.168	3	0.252	3	0.252	1	0.084
S3	0.082	3	0.246	4	0.328	3	0.246	3	0.246	3	0.246	3	0.246
S4	0.084	3	0.252	4	0.336	4	0.336	2	0.168	3	0.252	4	0.336
S5	0.079	4	0.316	2	0.158	1	0.079	3	0.237	3	0.237	1	0.079
S6	0.079	2	0.158	4	0.316	1	0.079	2	0.158	2	0.158	2	0.158
W1	0.086	2	0.172	3	0.258	2	0.172	4	0.344	3	0.258	3	0.258
W2	0.082	2	0.164	3	0.246	2	0.164	4	0.328	3	0.246	3	0.246
W3	0.084	3	0.252	3	0.252	2	0.168	4	0.336	3	0.252	3	0.252
W4	0.084	4	0.336	4	0.336	1	0.084	3	0.252	4	0.336	2	0.168
W5	0.086	3	0.258	1	0.086	1	0.086	3	0.258	3	0.258	2	0.172
W6	0.084	2	0.168	3	0.252	4	0.336	2	0.168	3	0.252	4	0.336
O1	0.090	3	0.270	3	0.270	2	0.180	3	0.270	3	0.270	2	0.180
O2	0.082	3	0.246	4	0.328	4	0.328	3	0.246	4	0.328	4	0.328
O3	0.084	3	0.252	4	0.336	3	0.252	3	0.252	3	0.252	3	0.252
O4	0.090	3	0.270	2	0.180	3	0.270	4	0.360	3	0.270	3	0.270
O5	0.087	2	0.174	2	0.174	1	0.087	2	0.174	2	0.174	2	0.174
O6	0.082	2	0.164	4	0.328	3	0.246	2	0.164	4	0.328	2	0.164
T1	0.084	4	0.336	3	0.252	4	0.336	2	0.168	3	0.252	3	0.252
T2	0.082	3	0.246	4	0.328	3	0.246	2	0.164	2	0.164	2	0.164
T3	0.082	2	0.164	3	0.246	3	0.246	3	0.246	2	0.164	2	0.164
T4	0.079	2	0.158	3	0.237	4	0.316	3	0.237	2	0.158	3	0.237
T5	0.079	4	0.316	4	0.316	4	0.316	3	0.237	2	0.158	3	0.237
T6	0.079	2	0.158	3	0.237	2	0.158	3	0.237	2	0.158	3	0.237
Total TAS		5.586		6.224		5.071		5.760		5.681		5.080
Rank		4		1		6		2		3		5

Source: Processed data, 2026.

Therefore, strengthening coordination among the Provincial Agriculture Office, Veterinary Centers, Animal Quarantine Services, district governments, and other relevant stakeholders, while optimizing the use of digital information systems, was considered the most feasible approach to enhance the effectiveness of FMD control at the regional level. These findings are consistent with Wiratsudakul and Sekiguchi (2018), who demonstrated that regulating livestock movement and trade networks is a key component in

limiting the spread of FMD. Similarly, Wang et al., (2021)

reported that integrating disease occurrence data, livestock distribution, and animal movement information improves

surveillance accuracy and supports evidence-based decision-making for disease control. Therefore, the prioritization of the ST2 strategy is supported not only by expert judgment and stakeholders’ perceptions obtained in this study but also by scientific evidence identifying livestock movement management as a fundamental component of effective FMD control systems.

From an agribusiness perspective, livestock movement control serves not only as an animal health intervention but also as a strategy to sustain the beef cattle marketing system. This is particularly important because beef cattle farming in Gorontalo remains economically viable and continues to generate positive returns for farmers (Singgili et al., 2024). However, the profitability of these farming enterprises largely depends on uninterrupted market access and efficient livestock distribution. Consequently, movement restrictions that are implemented without appropriate management may delay livestock sales, prolong the fattening period, increase feed and labor costs, slow capital turnover, and ultimately reduce farmers’ income. Therefore, livestock movement control should focus not merely on restricting animal movement but on implementing safe animal movement practices through animal health inspection, veterinary certification, vaccination status verification, digital movement recording, and cross-jurisdictional coordination.

From a policy perspective, this strategy supports the implementation of Indonesia’s national FMD control programme through improved livestock traceability, coordinated surveillance, and digital reporting using iSIKHNAS. In terms of sustainability, effective livestock movement management contributes to economic sustainability by maintaining market access, social sustainability through stronger stakeholder collaboration, and institutional sustainability by enhancing inter-agency coordination and digital governance. Such an approach enables FMD control objectives to be achieved while minimizing disruptions to livestock trade, thereby safeguarding animal health, maintaining market access, and supporting the long-term sustainability of the beef cattle agribusiness.

The second priority strategy was improving farmers’ literacy through Communication, Information, and Education (CIE) programmes, with a Total Attractiveness Score (TAS) of 5.760. The QSPM results indicate that informants considered farmer knowledge, risk perception, and trust in animal health interventions to be important factors influencing the implementation of foot and mouth disease (FMD) control. Although vaccination programmes have been widely implemented, some farmers remain hesitant to vaccinate apparently healthy livestock because of previous negative experiences, concerns about post-vaccination reactions, limited understanding of disease prevention, and difficulties in handling cattle under extensive production systems. These findings suggest that the constraint is not merely a lack of information, but a broader behavioural and operational issue affecting farmers’ willingness and ability to adopt recommended practices.

Therefore, CIE programmes should not be limited to one-way information dissemination. They should be designed as participatory risk-communication and behaviour-change interventions involving extension officers, veterinarians, farmer groups, and trusted local livestock actors. Continuous technical assistance, farmer discussions, field demonstrations, and peer learning may help improve farmers’ understanding of vaccination, biosecurity, early disease reporting, and livestock movement regulations. This interpretation is consistent with Merrill et al., (2019), who found that compliance with livestock biosecurity practices is strongly influenced by the quality of risk communication, trust in information sources, and confidence in the effectiveness of recommended preventive measures. It is also consistent with Donadeu et al., (2019), who emphasized that vaccine adoption among smallholder farmers is shaped by access, perceived risks and benefits, trust, and the institutional context in which vaccination programmes are implemented.

The third priority strategy was strengthening animal health human resources, with a TAS value of 5.681. The findings indicate that the informants considered human resource capacity to be one of the key determinants of successful FMD control programme implementation. The limited number of field personnel has constrained the optimal implementation of vaccination, surveillance, and disease monitoring across all areas. In addition, inadequate incentives and high workloads among field officers remain important challenges to the continuity of FMD control programmes. Therefore, strengthening animal health human resources should not focus solely on increasing personnel numbers but should also include competency development, more equitable staff distribution, adequate incentive mechanisms, and enhanced capacity to utilize digital information systems for faster and more accurate decision-making. This finding is consistent with Metwally et al., (2024) who emphasized that effective animal disease control requires personnel with adequate competencies in vaccination, surveillance, reporting, and risk-based decision-making. In addition, Martins et al., (2017) identified institutional capacity, resource availability, and workforce allocation as important determinants of successful animal health programmes.

Overall, the QSPM analysis suggests that the prioritized strategies emphasize strengthening the governance of foot and mouth disease (FMD) control rather than relying solely on technical interventions such as vaccination. The selected strategies highlight that sustainable and effective FMD control depends on the integration of livestock movement management, farmer capacity development, institutional strengthening of animal health services, and the effective use of digital information systems.

Study limitations

This study has several limitations. The sample of experts and field respondents was limited, and the findings are specific to Gorontalo Province. The SWOT–IFE/EFE–QSPM approach also depends on expert judgment and stakeholder perceptions, which may introduce subjective bias. In addition, the study did not assess long-term sustainability, cost-effectiveness, implementation costs, sensitivity, or post-implementation performance. Several indicators were derived mainly from programme records and stakeholder perceptions. Future studies should use larger samples, conduct sensitivity and feasibility analyses, validate the framework in other regions, and include behavioural, economic, and implementation evaluations.

CONCLUSION

Overall, the findings indicate that FMD control in Gorontalo Province should be supported by vaccination, surveillance, institutional coordination, livestock movement control, farmer education, and digital animal health information systems. The QSPM analysis ranked livestock movement control based on cross-sector coordination and digitalization as the highest-priority strategy, followed by strengthening farmer literacy, animal health personnel, vaccination and surveillance, and the improvement of iSIKHNAS data quality. These priorities reflect the strategic conditions identified in this study and provide a basis for strengthening FMD control in Gorontalo Province.

Based on these findings, FMD control should emphasize coordinated livestock movement management while maintaining vaccination, strengthening surveillance, improving farmer literacy through Communication, Information, and Education (CIE), and enhancing digital livestock data management. Future studies should involve broader study areas and larger samples, and examine farmers’ adoption of animal health innovations as well as the economic impacts of FMD control strategies on beef cattle farming.

ACKNOWLEDGMENT

The authors express their appreciation and gratitude to the leadership of the Faculty of Agriculture, Gorontalo State University, for their moral support, attention, and encouragement provided throughout the implementation and completion of this research. We also express our sincere gratitude to all beef cattle farmers, officials of the Livestock and Plantation Service of Gorontalo Province, animal health officers, extension workers, and academics for their participation and support in the implementation of this research.

NOVELTY STATEMENT

This study provides an integrative and field-based strategic assessment of Foot-and-Mouth Disease (FMD) control in beef cattle production at the regional level by incorporating institutional capacity, livestock movement management, digital animal health information systems, farmer behavioural factors, and animal health human resources into an IFE–EFE–SWOT–QSPM framework. This study extends the application of the IFE–EFE–SWOT–QSPM framework in the field of animal health by demonstrating how these factors can be integrated to generate measurable FMD control priorities that reflect local conditions.

AUTHOR’S CONTRIBUTION

SAR and VT: Conceptualization and research design; SAR and HS: Data collection; KH and MA: Data analysis; SAR, VT, and HS: Data interpretation and manuscript writing; SAR: Manuscript revision.

Generative ai and ai assisted technology statement

The authors declare that AI-based tools were used solely for language refinement, grammar checking, and visual design assistance for Figure 1. The manuscript and Figure 1 were carefully reviewed and validated by the authors.

Conflict of interest

The authors have declared no conflict of interest.

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