Sampling and study area.

Sampling was purposive to maximize diversity and prioritize information-rich individuals from the Indonesian poultry sector. Initial participants were identified through consultation with local collaborators and policymakers based on their knowledge or strategic role in the poultry sector, and subsequent participants were recruited through snowball sampling until we felt we had reached a sufficient diversity of views (i.e., actors operating at different levels of the value chains and geographic places) and that data was sufficiently rich to answer the research question. The final sample included policymakers from the Directorate of Livestock and Animal Health Services (DGLAHS), representatives from non-governmental organizations, industry associations, university professors, technical service officers (TSO) from input companies, poultry company managers, and farmers. Although the layer sector was primarily targeted upon the government’s request, several interviewees also had experience in the broiler sector. The study area covered five provinces within which most layer poultry production is concentrated: DKI Jakarta, Yogyakarta, Central Java, East Java and West Java.

Data collection.

Semi-structured interviews were used to collect rich, descriptive and contextually situated data for exploring the range of attitudes, experiences, perceptions, and behaviours of a diversity of poultry stakeholders. This flexible format allowed adjustment of the emphasis and order of the topics according to the interviewee’s responses and for interviewers to follow-up more extensively on any unexpected themes that emerged during the discussion [27–30].

To build a priori semi-structured interview guides, an initial literature review was conducted. Based on this review, the following topics were included: (1) Role and challenges of the interviewee in their field of work; (2) Practices and challenges related to the prevention and control of poultry diseases; (3) Antimicrobial use and stewardship, and (4) Practices and challenges related to the management of poultry-related information. The interview guide is provided in S1 Appendix. The questionnaire was reviewed and practiced amongst researchers and piloted with an independent small-scale farmer to ensure understandability. Interviews were conducted by two separate teams composed of one English-speaking researcher, two Indonesian-speaking researchers, and one professional translator with experience in animal health. Interviews were conducted at the interviewee’s workplace, in public spaces such as cafes or restaurants, or online depending on logistical constraints. Representatives from associations, institutions, and government bodies were interviewed in groups of two to five people.

Data analysis.

Thematic analysis of interview transcripts was conducted following the framework from Braun and Clarke [22] and taking into account recommendations from Castleberry and Nolen for increasing consistency in coding and ensuring transparency and thoroughness of the analytical process [31]. Although this framework is described linearly, several cycles of coding and interpretation were performed iteratively throughout the analytical process. A codebook was developed to map the coding process [32] and ensure consistency across transcripts. It also aimed to demonstrate rigour in the methodology by providing a clear audit trail [33]. The software NVivo [34] was used to facilitate data management.

1. Data familiarization. Interviews were audio recorded and transcribed verbatim in the original language (either Indonesian or English). English recordings were transcribed by English-speaking members of the research team and Indonesian recordings were transcribed and translated by Indonesian native speakers. All verbatim transcripts were reviewed carefully by the Indonesian-speaking members of the research team before and after translation to assess quality and become familiar with the data. Where necessary, unclear data excerpts were checked against audio recordings or field notes and annotated with contextual explanations to inform the interpretation.
2. Initial coding. The entire dataset was coded systematically using a primarily inductive or “data-driven” approach [35, 36] (i.e., without committing to a pre-existing theory or framework) to best represent meaning as communicated by participants. Deductive coding was used to some degree to ensure meanings were relevant to the research question and provide more details on some aspects of interest. This combined approach is appropriate for studies that aim to explore specific issues but also leave scope for unexpected aspects of participants’ experiences or interpretations to be brought up [37, 38]. Semantic (explicit) and latent (implicit) codes were developed to allow the data to be both described and interpreted [22]. An initial codebook was developed, including the following components: label, definition, and ideas to include or exclude. When coding the excerpts from interview transcripts, the researcher retained as much contextual information as needed to ensure quotes would be understandable.
3. Generating themes. Once all data had been coded, the data was reviewed to determine how codes may be grouped to form themes or sub-themes [35]. “Keyness” or meaningfulness was the central criterion for determining themes (i.e., whether it captures something important in relation to the research question) [22, 31].
4. Reviewing themes. Themes were reviewed against the entire dataset to determine whether they formed a coherent pattern and were relevant to the research question [22, 38, 39]. Codes or themes that shared the same underlying meaning were merged, while those that did not fit within the overall analysis were discarded and their data re-coded as appropriate to facilitate the most meaningful interpretation of the data. The first author recorded all decisions to rename, merge, discard, and sort codes into themes in NVivo to keep track of the changes and allow for going back and re-code previously coded material to ensure consistency in coding.
5. Refining and defining themes. Themes were reviewed individually and in relation to one another. An accompanying narrative was written for each theme and sub-theme.
6. Producing the report. Themes were organized together with their analytic narratives to illustrate the overall story in response to the research question. Direct quotations were collated in a table (S2 Appendix). All quotations were referred to in the main text using identifiers and the most relevant were reproduced in full to demonstrate how themes are rooted in empirical data and allow the reader to assess the validity of the interpretation. Minor grammatical and linguistic corrections were made by the researcher to ensure comprehension. Where necessary, contextual explanations were added in brackets.

Economic vulnerability of poultry producers.

Poultry producers generally were concerned about high production costs in Indonesia which they told us greatly limited their profit margins. Most small- and medium-scale independent farmers experienced economic hardship and appeared to be the most vulnerable to changing market circumstances due to insufficient cash flow or poor financial management. Farmers felt this was most apparent during the COVID-19 pandemic, which led to a sharp decrease in the number of independent smallholders, while contract farmers’ losses were absorbed by their companies. Farmers generally expressed a pessimistic view regarding the future and stressed the psychological burden of maintaining their businesses in the face of competition and uncertainty (a1, a2, a3, a4).

“Only big integrators, big companies can survive because they have a lot of money. But small farmers, many of them they close, they sell their cages […]. It’s quite challenging to be a farmer in Indonesia.”

(a4)

An unstable and unpredictable market.

A lack of coordination between supply and demand appeared to be a recurring issue, causing frequent and significant egg and DOC price fluctuations that could not be predicted based on foreseeable geographical and seasonal variations. Farmers felt they had no control over prices and no choice but to follow market trends, without any external support (a5, a8).

“That’s why the breeders now are like a tossed ship. Like the ship in the middle of the sea doesn’t know where it’s going, its purpose is not clear. We must survive alone, we must fight alone.”

(a5)

Interviewees told us that the lack of price regulation and official certification schemes opened the door to uncontrolled production and fraudulent practices, allowing, for instance, farmers or traders to artificially increase prices by retaining eggs or by using false labels (e.g., for omega eggs) (a6, a7).

Difficulties in sourcing farm input.

Price and availability of day-old chicks (DOCs) and poultry feed, which together account for more than 80% of farmers’ production costs, were the main concerns of most poultry producers. Indonesia’s heavy reliance on imports for the supply of DOCs and feed raw materials (e.g., meat-bone-meal, soy-bean-meal, corn, etc.) made local production highly sensitive to international commodity prices, exchange rate variations, and global shocks such as the COVID-19 pandemic or the Ukraine-Russia war (a8). We were also told that government import policies and subsidy schemes also had a strong impact on availability and price stability. The Directorate General of Livestock Farming and Animal Health has established import quotas on grandparent DOC in an attempt to achieve a balance between supply and demand. However, interviewees told us that the quotas appeared to be determined with limited stakeholder consultation and based on inaccurate data, leading to an imbalance between supply and needs (a9).

“The government imports this GPS [grandparent stock] as if they are doing whatever they want. This means that the need is not calculated, how much is needed for DOC [day-old chicks], how many eggs are needed, oh if I have to import that much, there won’t be any.”

(a9)

Farmers believed that the government’s strategy of favouring local corn production by limiting imports has created many difficulties for sourcing poultry feed. In their opinion, local corn production remains insufficient and sub-optimally managed (a10), with temporal and geographical imbalances between corn and poultry production coupled with logistical issues in conveying feed raw materials. Farmers also reported difficulties in accessing subsidized corn and complained of its poor quality and prices being higher than unsubsidized corn. This led feed dealers and farmers to develop variable coping strategies, which negatively impacted the quality of feed (e.g., replacement with wheat, use of fake meat-bone-meal, mixing with sand).

Unequal power dynamics.

As Indonesian poultry production has intensified and as integrated companies have developed, farmers felt that integrators’ monopoly in the domestic market was being reinforced (a11). Independent farmers were becoming increasingly dependent on large integrated companies for the supply of production input and had to comply with their terms and conditions, such as the bundling of feed and DOCs. Many independent farmers expressed a fatalistic view, believing that they did not have the capacity to compete and were doomed to be overtaken by large players (a12, a13, a14).

“It is impossible for us small farmers to face them. They have DOC [day old chicks], they have feed, they have medicine, they have vaccines, even the last one, they have all the final results. […] My question is, will integrators replace us after we run out?”

(a12)

Government perceived to have weak interest and involvement in the poultry sector.

From the perspective of private stakeholders, the government had little interest in poultry and focused more on cattle. In particular, small-medium independent farmers felt abandoned by the government and complained of a lack of financial support (b1, b2).

“Our association [of small poultry farmers] still needs to improve our relationship with the government because government policies often do not suit our needs. Of course, the government must consider the interests of prominent business people, but this policy is ultimately not in the interests of our farmers.”

(b2)

Being more advanced in terms of knowledge and technology, large-scale farms or companies failed to see the benefits of interacting with the government and often displayed a distrustful attitude towards them (b3, b4, b5). Interactions were generally limited to the NKV (Nomor Kontrol Veteriner, veterinary control number) certification or compartmentalization program for Avian Influenza (AI) (b6).

Information gaps lead to inadequate management of poultry diseases.

Private actors were generally reticent about sharing their internal data and rarely reported diseases to authorities for fear of penalties (b7). The official animal information system iSIKHNAS, which has been successful in cattle, was perceived by interviewees as ineffective in poultry (b8). Therefore, data held by the government was considered incomplete or inaccurate, leading to inadequate policy-making and response to industry needs, and in particular late or no response to disease outbreaks (b9, b10, b11).

“After all, the government is often not ready, especially when facing poultry disease outbreaks. […] If we weren’t prepared, we would have collapsed a long time ago for various reasons.”

(b10)

Many mentioned the first AI crisis in 2003, telling us that the government failed to recognize the threat, forcing farmers to manage the issue themselves by sourcing vaccines from China outside any legal framework (b11, b12).

“the government at that time [during the first AI outbreak in 2003], they were unwilling to declare that we had been infected by avian influenza. […] The ability of our government to address this issue was very weak.”

(b11)

Industry actors perceive academic education and research as disconnected from real-life.

Actors from the private sector felt that the academic world was disconnected from the reality in the field. A farming businessman suggested that poultry sciences should be taught by private industry experts to ensure knowledge is rooted in real life and to better prepare future practitioners (b13). However, he deplored academia’s closed attitude towards external lecturers (b14).

“Academics are usually born in a community where a system has been formed. […] They feel confident and do not need advice from others. […] That’s their weakness. They have a good brain but can’t accommodate outside advice”

(b14)

Additionally, he considered academics’ way of communicating to be inadequate for farmers and focused too much on the theory compared to the practicalities (b15).

Multiple and increasingly complex health challenges.

Avian Influenza, Newcastle disease (ND) and colibacillosis were the most frequent diseases mentioned by farmers. Other significant health hazards mentioned included chronic respiratory disease (CRD), coryza, infectious bronchitis (IB), infectious bursal disease (IBD or Gumboro), and general metabolic diseases due to environmental factors. According to farmers, although health authorities recognized AI and ND as priorities, they tended to neglect non-zoonotic diseases that are still responsible for important economic losses such as IB or CRD (c1). While many farmers had experienced devastating AI outbreaks in the past, they reported a reduction in their occurrence and severity following the wide use of vaccination and improvement of biosecurity (c2). However, they also described a shift in disease symptoms, from high mortality to more unclear signs, making it increasingly difficult to diagnose (c3, c4).

“It is different from 10 years ago […] In terms of disease, nowadays cases of disease are increasingly complex, they do not stand alone, so the symptoms are not clear and this does require a lab approach”

(c3)

Interviewees also pointed out the role of environmental risk factors in disease introduction and spread, including high poultry population and farm densities, low feed and water quality, and exposure to extreme weather events.

Lacking or inadequate management of poultry health.

According to stakeholders responsible for providing support to farmers (including research institutions, NGOs, university professors, and technical service officers), many small-scale independent farmers lack the necessary knowledge and resources to implement adequate biosecurity and health management, and absence of biosecurity practices remain frequent (e.g., mixing of age groups, no all in-all out) (c5). Diseases are generally managed by farmers themselves based on their own experience, without seeking laboratory diagnosis. In addition, farmers thought that prescription and use of medicines were driven by the commercial interests of private veterinarians and technical officers from pharmaceutical companies (c6). With the rapid growth of the sector, independent farmers and company managers mentioned struggling to hire qualified poultry workers with sufficient awareness and knowledge about biosecurity and farm management (c7, c8). Interviewees from research and non-governmental institutions also highlighted the responsibility of the government in these issues:

“The problem is that for animal health, if you look at the budget here in the Ministry, the budget has been going down year after year, livestock production is much more important than animal health, so it’s partly the problem of the government itself”

(c9)

Control and support from health authorities to farmers appeared to be lacking due to insufficient financial and human resources, but also due to the unstable political and administrative environment which farmers told us frequently disrupted the funding and implementation of national health programs (c9, c10). This was even more critical at the time of the study, as the government had reallocated most of its resources to the management of a nationwide FMD outbreak.

Resistance to behavioural changes.

Several farmers and technical service officers described a generational gap regarding farming practices. They mentioned it was difficult to educate the old generation of farmers and update their knowledge about poultry farming because of their unwillingness to change practices that have been passed down through generations (c11, c12).

Because they feel right, it is difficult to change the mindset of farmers. […] And sometimes that’s wrong, because they have the principle of "I’ve been there for decades, what are you new kids doing?", it’s sometimes difficult for us to go there for education”

(c11)

In contrast, the younger generation was thought to be more aware of the importance of biosecurity and more willing to use IT tools for farm management.

Capacity to collect and analyze farm data varies significantly among stakeholders.

Most of the small- and medium-scale independent farmers we interviewed collected farm data on a routine basis using a combination of paper-based and spreadsheet systems. Nonetheless, some of them felt they lacked the necessary technical skills and resources to collect data comprehensively and analyze it to its full extent (d1, d2). Although integrated companies and associations can manage large amounts of data, their internal system appeared to operate in silos on an individual farm or customer basis, thereby limiting their analytical capacity (d3, d4). Management of data by the government itself was also thought to be suboptimal by some participants, as highlighted by an industry association that criticized what they described as burdensome submission procedures and underutilization of data (d5).

“Even with the government, we feel that they might not be able to provide valid data. […] The government needs to be encouraged the importance of actually compiling this data so it can actually be used for something. It’s not just asking for data and then stop there, because they don’t have any system to compile them.”

(d5)

Additionally, issues of quality, representativeness, and timeliness of data collection were considered by both public and private stakeholders to impair their ability to forecast trends and prepare for future shocks. Many interviewees expressed doubts regarding the validity of public data, stressing their belief in its lack of representativeness and potential falsification, especially for population data for which there is an incentive for farmers to underreport to avoid taxation (d5, d6, d7).

Dissemination of information relies mostly on informal channels.

Information-sharing by interviewees relied largely on informal channels such as WhatsApp (WA), SMS, or personal interaction during stakeholder forums or industry events (e.g., seminars, professional fairs). Most interviewed farmers described being part of regional WA groups through which they share information about prices, disease events, and seek advice from fellow farmers or experts. Likewise, companies used WA to facilitate communication amongst their technical staff, collect farm data, and provide technical support to workers or customers (e.g., support for diagnosis). Because of their close relationship with farmers, technical service officers from input companies had a central role in the transmission of information, acting as bridges between separate business networks (d8).

“Information spreads through suppliers. […] If there’s a big problem, the supplier usually has a stake. For example, if there is a virus, later, the vaccine supplier will announce to Blitar farmers through a seminar, "So we got information that this virus has started to enter Blitar." […] However, between farmers, no one wants to tell each other.”

(d9)

Although the farmers we interviewed remained reluctant to directly disclose information to other farmers or government agents, they told us they were more open to discussing with visiting officers who subsequently spread the information within their customer network or reported to their company to inform business decisions (e.g., production of specific vaccines) (d8, d9, d10).

Barriers to data sharing.

The farmers and other industry stakeholders interviewed were generally reluctant to share their internal information, especially disease events and performance data. Interviewees stressed the importance of personal prestige but also the fear that disclosure of internal information would bring negative consequences, such as the loss of competitive advantage, close-down of business, trade disruptions, and increased taxation (d11, d12, d13). Private stakeholders often did not see any benefits of reporting health issues, especially large companies that felt they had sufficient resources to manage them internally without external intervention (d14, d15).

“it is not easy to get the data [from sector 3 farmers], they don’t want to share any information, especially if there is no benefit for them. […] the key is I think, how to show and to prove they get the benefit, and how to prove this really secure and confidential.”

(d15)

Poultry health and production data was therefore managed through multiple systems with different standards and procedures, which resulted in high variability and discrepancies between private and official data, further impairing its usability.

Strengthening intersectoral collaboration.

Despite most actors working in silos, many recognized the need for increased collaboration. Farmers were increasingly developing into cooperatives or partnerships to strengthen their competitiveness against larger players and facilitate access to feed and subsidies (e1, e2). The small- and medium-scale independent farmers in particular appeared to be those most in need of peer support, as they did not benefit from government subsidies (e3). Alternatively, an increasing number of farmers told us they are converting to the nucleus-plasma system (i.e., contracting with a company) which is believed to offer better technical support and financial security (e4).

Public and private stakeholders generally appeared to adopt a distrustful attitude towards each other and were reluctant to cooperate, as stressed by both a government agent (e5) and a pharmaceutical company (e6).

“If farms really think the government is corrupt, then they also feel the government is not independent […] if you want to use the Public Private Partnership approach, the main problem is information confidentiality and good governance.”

(e5)

“It would be better if the government could support us. […] If they collaborated with us, they could work faster because we have the laboratories so we could help them. But I think they don’t trust us yet.”

(e6)

Representatives from associations such as ADHPI (Asosiasi Dokter Hewan Perunggasan Indonesia, association of poultry veterinarians), PINTAR (local association of poultry farmers in Lampung), or ASOHI (Asosiasi Obat Hewan Indonesia, Indonesian Veterinary Medicine Association) stressed their role as intermediaries in facilitating communication and building trust between private and public actors. For instance, ADHPI organizes a multi-stakeholder forum called OBRASS (Obrolan Santai Seputar Unggas), to provide opportunities for informal discussion between private and public stakeholders. They also told us they contributed to policymaking by conveying stakeholders’ issues to the government and supporting the dissemination and implementation of official guidelines and regulations.

Several associations and private companies highlighted the advantages of collaborating with universities and institutions for research and development (e7), for instance by partnering with local farmers to develop and evaluate new feed additives. However, they felt there was a lack of communication from institutions regarding current research (e8).

Addressing education and research gaps.

Associations, input companies, and integrators told us they were investing significant efforts to educate farmers on farm and poultry health management to help them increase their productivity and profitability (e9). Education was provided through seminars led by experts from companies or universities, onsite training, or newsletters. However, those providing the education felt that important knowledge gaps remained, especially in smallholders. Farmers generally relied on their practical experience and a diversity of informal information sources including technical service officers, university professors, the internet, fellow farmers, and veterinarians who may sometimes lack scientific updates (e10). A local entrepreneur thought training should be tailored to the specific needs of small-scale farmers (e11):

“These past few years, I have tried to educate middle to lower-level farmers whose animal health awareness still needs to improve. […] However, my efforts are still very far away. […] The seminars they need are about disease management and production management in a language they can easily digest”

(e11)

There is also a strong need for research and innovation in poultry nutrition and health, especially for alternatives to antimicrobials and raw feed materials that can be locally produced (e12). However, according to academics, research in poultry is not yet sufficiently developed to support the rapid growth of the industry (e13).

“Even though we are number four in Asia […] it is not easy to find funding for research in poultry. […] And indeed, that is our weakness, even though the poultry industry in Indonesia is quite large, the research is not yet developed.”

(e13)

Improving data integration and real-time surveillance.

Stakeholders were increasingly convinced of the importance of good monitoring of production and health data as key to successful business development (e14, e15). Companies and a significant proportion of independent farmers used production data to evaluate performance, provide early warnings, and guide disease investigation. However, the level of analysis was variable and several interviewees felt they lacked the capacity to analyze it to its full potential. This trend is also driven by evolutions in market demand and regulations. For instance, access to international and high-value markets is dependent on providing internal surveillance data to demonstrate AI-free status (e16).

Nonetheless, important data gaps remain to be addressed. Independent farmers are particularly in need of commodity price data to manage their sales and purchases, while feed and pharmaceutical companies are most interested in health information to provide better services to their customers (e.g., tailored vaccination programs) and plan their production accordingly. Additionally, the lack of data integration and timeliness impede their capacity to anticipate and respond to potential future threats (e17, e18), as emphasized by a pharmaceutical company:

“Now we only know when the disease is here. But the disease is not just there all of a sudden, there is this process, and we need to know this process […] We don’t want to fight fires, once we have fires and we fight it, we don’t want to do this. We want to know the pattern so that we can be better prepared.”

(e17)