Supply chains are both capital assets for shrimp farmers, and a structure that they utilise when putting together livelihood strategies. The capital that influences the supply chain management are: human resources (work force), environmental assets (raw material supply), financial assets influencing the production and sources aspect;
social assets influencing the market in strengthening the branding image; and physical assets (infrastructure and technology including the packing) influencing the delivery and returns.
In regards to transforming structures and processes in the SLF, changes in access to those assets also change the supply chain. Transforming a supply chain also opens up new livelihood strategies and the chance of larger returns (livelihood outcomes).
Holding particular assets makes a shrimp farmer part of this supply chain. Different farmers have different levels of access and control (which can be considered capital assets), but all of them benefit from the structure. Therefore incorporating a focus on elements that cause changes in the supply chain can be usefully combined with
analysing the performance risks
analysing the risks consequences
Responding to risk Evaluating final outcome
77 analysing changes in producers’ access to other assets identified in the SLF framework.
Incorporating supply chain risk management and the SLF stages is useful for identifying the transformation process of the shrimp industry in Sidoarjo before and after the mud volcano. Through this research design, I am able to assess broader issues affecting markets and supplies that are linked to shrimp farmers’ livelihood outcomes. Chart 4.3 provides the utilisation of the SLF as a research tool representing key components of the SLF linking to the variables associated with the mud volcano in Porong.
This thesis employs four out of five components of the SLF in order to address the three objectives of the research. The thesis focuses on livelihood choices and outcomes. First, it explores the contextual factors contributing to vulnerabilities among shrimp farmers in response to the mud volcano in Porong. Second, it identifies the patterns of community access to the Livelihood Assets Pentagon. Third, it examines the specific roles, responsibilities, and relationships of the different groups of stakeholders involved. By identifying the roles, responsibilities and relationships, it is able to reconstruct the transforming structures and processes in the shrimp farmers’ community. Fourth, it identifies shrimp farmers' livelihood strategies in response to the shock and stress caused by environmental degradation.
This thesis does not directly address the full range of livelihood outcomes of shrimp farmers, which would require further research and a longitudinal dataset. However, here the SLF is utilised to examine adaptation to a disaster amongst shrimp farmers through assessing their circumstances, the types of capital they possess, the transforming structures and processes they can utilise, and the livelihood strategies they develop.
Outcomes generally link to the assets; however the outcome has two adverse effects as it links not only to assets but it may also create other vulnerabilities and assets. For example as depicted in Chart 4.3 the outcome of the SLF adaptation scheme is having a positive response from the buyers. It could be considered as another market asset, however due to the acceptance of the buyers, the buyers also create their own standard in expecting a high quality standard of the shrimp. At the same time they
78 also may seek a potential shrimp supplier which has strict standards in conducting aquaculture and has lower prices, which could make the Sidoarjo shrimp farmer vulnerable.
It was assumed that these features of the SLF, would be useful to analyse both multi-dimensional and multi-faceted issues that are associated with the research objectives and the questions of this thesis. An adapted SLF that is appropriate to capture the issues which affected the local community in Sidoarjo was developed using the five components of the SLF to answer the research question and the objectives of this research project.
79 Chart 4.3 The SLF adaptation of Sidoarjo shrimp farmer
Physical
80 4.3. Technical approaches used for data analysis
4.3.1. Coding qualitative data
Data collected from interviews was primarily qualitative in nature. The interview data was recorded, transcribed and then manually coded into themes and then organised into separate word files for each theme. The themes were aligned with the questions in the questionnaire. An open coding system was applied to each of the independent (control) and dependent (target) groups to allow the widest range of trends to emerge.
Table 4.2 Component of coding and tasks utilised
Component of Coding Task
1. Open Coding · Categories and code data
broadly
· Make notes while reading
· Assist in concept mapping
2. Axial Coding · Use and review initial codes and concepts
· Analyse causes and
consequences, conditions and interactions, strategies and processes
· Categories themes and explore linkages
3. Selective Coding · Use to select interesting cases of contrasting themes and
behaviour patterns
Sources: Neuman (2006); Saunders (2016)
81 The second step involved reviewing coded data to identify key issues relevant to the research objectives and infer connections among various data elements. The third step highlighted several cases with contrasting themes during the observations as a case study for showing good practices toward disaster resilience in aquaculture. Successive reading and interpretations of the data, including key analytic and explanatory themes, are indicated in Table 4.2
4.3.2. Descriptive statistics and constructing comparable groups
Descriptive statistical analysis was used to represent an overview of the survey data. This analysis describes respondents’ answers through the distribution of items of each variable. Adams et al. (2007) assert that the validity of statistical analysis is based on numerical representations of information. The literature highlights numerous statistical methods as useful analytical tools to describe and compare variables that focus on central tendencies and discrepancies of a given phenomenon.
The thesis classifies farmers by geographical location of the shrimp farm, and the extent to which it was impacted by the mud flow, as described in 4.1.2. The thesis also compares the situation for different groups of employees within the shrimp industries of i)the shrimp farm owners, ii) the shrimp pond supervisor, and iii) the shrimp pond worker, as discussed in section 4.1.2.
The questionnaire also captured a range of other types of data that were useful for comparative purposes, and understanding the sector. For example, the information categorised in this study included the respondents’ residential address (establishing the distance of their home from the polluted rivers). This classification enabled comparison with the control group that provided an overview of a description of the effects of the disaster based on residential location. Other information includes business ownership, the size of the business (small, medium or large scale operation), who are the affected people; were they employed as a worker or as a supervisor/manager or an owner of a shrimp pond.
This information was grouped into six key categories: demographic data, business
82 profiles, worker profiles, scope of marketing chains, data about changes in the shrimp production over time, and data that demonstrated the changes of the shrimp farming industry and livelihoods due to the mud volcano.
4.3.3. Types of capital in the SLF
The five social capitals adopted from the Sustainable Livelihood Framework are also important for the thesis, and are the basis for chapter 6 on differences between the owners, managers and workers in the shrimp farm industry.
Social capital provides information on: (i) composition of the family; (ii) family income; (iii) the nature of employees and their recruitment process, and (iv) political connectivity. The second capital is financial assets, including all information about the respondents’ income, productivity, the degree of accessing credit and other financial support from banks, along with the receipt of money (assistance). The third capital is human assets where the data and information represent the skill levels of shrimp farmers, knowledge, the ability of the respondent, and the leadership structure. The fourth capital addresses physical assets. This cluster includes an irrigation infrastructure, tools and equipment, availability of affordable transportation, security, and access to energy sources.
The fifth type, environmental capital, captures data and information about the water and environmental quality, the degree of difficulties in accessing shrimp fry or infant fish, and pond embankment quality.
4.3.4. Analysis of the patterns of community access to the Livelihood Pentagon of Assets
According to DFID (1999); Scoones (1998, 2015a) the Asset Pentagon is a central element of the SLF. The Pentagon analysis is used to identify the trade-offs that possibly occurs between different assets. It represents the different distributions of and access to environmental, social, financial, physical, and human resource assets. Further, the Pentagon analysis is able to create a quantifiable indicator of assets in order to seek the sequencing or substitution between assets (Scoones, 1998, 2015a).
83 For the Asset Pentagon analysis in chapter 6, survey data was analysed using SPSS, and frequencies and descriptive statistics were used to obtain measurements. The results obtained from SPSS were grouped into a scoring table.
The information extracted from the questionnaires was grouped into the five types of capital representing the five Pentagon Assets in the SLF, namely human, social, financial, environmental, and physical assets.
The scoring table representing a 0-100 point scale was categorised into three groups. Responses with a score between 0-35 were categorised as low access. The responses with a score between 35-65 were categorised as medium access. Those responses with a score of over 66 were categorised as assets where respondents have good access. After completing the scoring table, the information was uploaded into a Microsoft Excel spreadsheet and converted into charts using a radar model.
Chart 4.4 The Pentagon Asset Model
Legend:
A: Environmental Assets D: Physical Assets
B: Social Assets E: Human Resources Assets C: Financial Assets
Sources: The Pentagon Model adopted from the DFID (1999); Scoones (2009) E
D
A
B
C
84 Chart 4.4 represents the different distributions of and access to environmental, social, financial, physical, and human resource assets in the target group compared to the control group. The two shaded pentagons in Chart 4.4 demonstrate the condition of the two different research groups. The blue shaded pentagon, represents the targeted research groups whose water sources were affected by mud. The grey shaded pentagon shows the condition of shrimp farmers in the controlled research groups whose ponds/ water resources had not been mud affected. The different shape of each pentagon displays the different levels of access to livelihood assets.
4.4. Methodological challenges and limitations
The focus of this thesis is limited to investigating the events in Sidoarjo from May 2006 when the mud volcano erupted and up to April 2013, the conclusion of field data collection. The research conducted is a case study of shrimp farmers in Sidoarjo impacted by the mud volcano in Porong that makes use of the SLF to assess shrimp farmers’ responses to the mud volcano. A case study approach is useful to investigate a chosen research question addressing a single issue. This type of approach can be characterised as a single case study with multiple units of analysis.
During the fieldwork I encountered difficulties in several instances in obtaining important data from the relevant authorities. First, I was unable to access the water quality audit data of Porong and Aloo Rivers, the data is owned by Balai Pengelolaan Sungai Brantas (Brantas River Management Centre). Second, although, I managed to interview a key member of PT ATINA personnel, I did not obtain longitudinal shrimp productivity data concerning their shrimp farmers.
Third, despite persistent efforts, I was unable to interview officials of the BPLS (Badan Penanggulangan Lumpur Sidoarjo-The Mitigation Agency in Porong) due to the sensitive nature of the research topic, but I did locate useful secondary data on their website. The importance of using multi-faceted research methods was demonstrated when I finally obtained data about the government (BPLS) response
85 to the disaster, unavailable to me from official sources, directly from the affected shrimp farmers.
4.5. Ethics approval for the research
The above research for this thesis conformed to the requirements of Curtin University ethics approval (reference no 124/2012) and as such was conducted following the Australian Code for the Responsible Conduct of Research.
Fieldwork, and data collection in Sidoarjo was also conducted using the established research protocols of Indonesia. It also received the appropriate support and clearance from The Islamic University of Sunan Ampel in Surabaya (reference no: is 02/1/TL.00/188/lemlit/P/2012). Before the field work commenced, permission was also obtained from Badan Keselamatan Bangsa Dan Perlindungan Masyarakat (Baskebanglinmas) (The National Safety and Public Protection Agency) of Kabupaten Sidoarjo (Sidoarjo District), and subsequently from the head of civil administration in each of the sampled subdistricts chosen as research locations.
The process of recruiting research participants observed appropriate protocols, ensuring that all interviewees signed informed consent forms prior to being interviewed. In order to maintain the confidentiality of the sampled interview and survey, no personally identifiable data were recorded. Participants were informed that they might withdraw at any stage during the interviews without giving any reasons.
4.6. Conclusion
An adapted Sustainable Livelihood Framework (SLF) has served as the organizational framework for data collection and analysis for this thesis. Complex issues have been examined using a mixed methods approach which has included a literature review, field survey, key informant interviews and participant observation. The qualitative and quantitative data obtained by the described methods was analysed using several tools, in particular the Livelihood Pentagon Assets Analysis that depicts the patterns of community access to five livelihood
86 assets. The supply chain risk management analysis was also utilized within the SLF due to the importance of changes in the supply chain to the assets and livelihoods of shrimp farmers.
The next chapter explores the resilience of Sidoarjo shrimp farmers six years after the Porong Mud Volcano began erupting.
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