Los agentes estatales

As Chapter 2 observes, a case study methodology approach is constrained by time, financial budget, resources and other significant research constraints. From 17 Pacific Island nations for Chapters 5-7, it specifically applied the proposed methodology to one Cook Islands, case study. Specific climate change projections are highlighted in Chapter 4. This is selected as a location for field research for reasons of transport accessibility; cost, previous climate change research, data, time and stakeholder contact information availability. It offers greater physical vulnerability to risks along with divergences in disruption risks, impact costs and adaptation solutions. This country is also politically stable, minimising field investigator risk. It has decades of project experience in climate change adaptation and disaster risk reduction including surveys, with significant risk awareness campaigns by researchers and NGOs. Kaiteie and Hogan (2008) consider climate and risk exposure divergences across several Pacific Islands, further

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improves a conceptual framework’s validity and structural robustness. Section 2.7 identified various advantages to using Pacific MSCs, with a smaller sample pool. These avoid outsourcing and offer limited customs, trade and beneficiation stages, simplifying data collection and empirical, impact cost analysis. The Cook Islands has just completed climateproofing of Aviatu/Mangaia Harbour to provide a case study of actual climate change adaptation for ports. It had the research benefit of responding to initial contacts. Australia and New Zealand were excluded as developed countries with considerable resources to adapt. Tuvalu, Nauru, Niue, Palau, the Marshall Islands and other Pacific nations were primarily excluded as being remote, economically peripheral, even lacking a functioning port authority website. Several lacked sufficient stakeholder contacts or possessed myriad similarities in projected risks and adaptation strategies. Therefore, this research represents a conceptual point of departure, in evaluating these impacts for Pacific MSCs. It offers case studies that are comparable, relevant, concise, specific, consistent, have information and cooperative stakeholders. This research retains certain economic significance for global stakeholders, which depend upon these supply chains.

3.4.4: Sampling Strategy/Identifying Potential Respondent Stakeholders

A MSC stakeholder is defined in Figure 2.1. Participants are assessed through initial questions and stratified sampling selection (Bouma and Ling 2006; Frankfort-Nachmias and Nachmias 2007; Bryman 2012) to indicate whether they are a stakeholder. More detail is provided in Appendix I-V. Consulting these experienced stakeholders aware of climate change, in stratified sampling, selects stakeholders from specific supply chain stages over random population sampling. This aims to improve the interview response rate, quality, accuracy of data and validity to subsequent stakeholders (Aggarwal et al. 2011; McNamara, Hemstock and Holland 2013). To establish an effective respondent, snowballing, sampling strategy; recruitment utilised a combination of networking at specialist conferences/contacts in Appendix VIII (research output). It uses direct, publicly available websites (principally the major seaport as the major MSC stage affected), secondary data contact information and a polite request to various Pacific agencies//associations. This request enquired if the invitation, survey and consent form is circulated to relevant supply chain contacts. Contacts can voluntarily choose to participate/disclose contact details, to protect confidentiality.

The sample strategy is primarily based around supply chain producers, seaport authorities, government, intermodal transport and other commercial participants. They are capable of offering an informed perspective and will be directly affected by climate change on a MSC. This is based on limited information availability and sample poll with few Pacific MSC stakeholders, as regular users of Cook Islands and

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Pacific main ports with accessible contact details. Demographics are not expected to influence thesis results. The research justification for the stratified, participant sample included only a few existing, pertinent MSC stakeholders who are prepared to respond. It also considers if questions are relevant to specific, research objectives and compatible with the case study, data availability and existing sources, suggested by Jira and Toffel (2012).

3.4.5: Data Collection Methods

Primary data collection is acquired through field research with direct stakeholder consultation, semi- structured interviews, to establish method and data analysis in Stages II-IV. The researcher submitted a stakeholder interview, introduction letter, distributed via email and in person, where necessary. This invited the respondent to participate (Appendix I/III) by signing the informed consent form (Appendix II/IV) and completing the survey/interview (Appendix IV). Approximately 1 and 2 weeks later, polite reminder emails will be sent to any respondent who have not submitted forms/responses (Appendix VI). This encouraged responses by emphasising the research value and their participation. Secondary data was obtained from physical and electronic sources. Where necessary, follow-up visits to collect data results/conduct interviews are undertaken to improve participant, response rates. Participants also indicated a preference for open-ended questions, which they personally contribute. This improved the response rate.

3.4.6: Data Management and Storage

All research data is securely stored in a safe University location at the Australia Maritime College, Launceston Campus for a minimum five years until being destroyed. This adheres to the 2007 Australian Code for the Responsible Conduct of Research, section 2.1 and the University of Tasmania, Data Management Guidelines, section 4.3. Only aggregated, non-identifiable data from which personal details/perspectives are removed; will be publicly published and disseminated except with participant stakeholders’ signed permission and informed consent. All physical data is locked in a filing cabinet, all- electronic data in a University secure, password protected computer, in a safe location. Only researchers involved in the study will have access. Data is backed up through a secure online UTAS Cloud service and working copies on password-protected flash drives. To maintain file integrity, these are not used on public computers with unrestricted access.

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No direct physical, personal, legal, environmental, social, cultural, political, technical, operation or financial risks were envisioned to participants. However, undertaking any research involving human participants at the University of Tasmania or any other Australian university requires reassurances ethical issues have been considered to protect respondent rights. This research complies with section 1 of the 2007, National Statement on Ethical Conduct for Human Research to protect research integrity, ensure merit and respect for participants by identifying risks. This thesis undertook full peer-reviewed interview pre-testing and confirmation of candidature presentations. It received ethical clearance approval from the Tasmania, Social Sciences, Human Research, Ethics and the Cook Islands, Ethics Review Committees (Appendixes VI/VII). It specifically outlined how any projected ethical consideration will be addressed in Appendixes I-V. These include the confidentiality and anonymity of participants from foreign countries and other rights and risks including commercially sensitive data. The statement’s section 2.2 requires sufficient information granted to participants to enable an adequate understanding. A free choice to participate or withdraw was made clear on the form. Participants were given a month’s notice, and 4-5 weeks to decide to participate in the interview. Reminders were submitted over several weeks, to indicate availability for an interview over the next 2-3 months. Access to confidential or commercially sensitive to information is anticipated in calculating supply chain, economic impact costs but only with participants’ prior consent. Risks are reduced in referring to past risk events and confidential, secure results. Participants are further protected, being notified verbally and via specific invitation, reminder and informed consent forms (Appendixes I-IV) of their rights. Contact information is provided if they have any research concerns to the investigator and committee. They can withdraw at any time and their data can only be utilised with formal signed consent.

To consider participants’ rights in other countries under the 2007 Statement (section 4.8); this research undertook a separate Cook Islands ethics review application, as the researcher could not locate equivalents for other locations. All data collected is treated in the strictest confidence, aggregated and made non-identifiable with personal contact details removed. It is securely stored and managed (section 5.3.5) to further protect specific rights prior to publication/dissemination. Participants will be also offered the chance to review the aggregated results once personal identification has been erased. There are no ethical considerations or risks expected for other research stages. These involve data analysis, with no human interaction or need to be based outside the Launceston university campus or Australia. The investigator not the participants/University bore the fiscal costs and risks that may develop through field research. From a risk management perspective, a slight, personal risk element occurs from conducting

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field research in foreign/Pacific countries. These might be susceptible to natural disasters, social, climate and economic/political instability as developing nations. However, this researcher notes the historic stability of Cook Islands, along with Pacific stakeholder experience for generalised, climate change research projects. It articulates how various issues/risks was resolved in the attached approved Cook Islands and Tasmania, Ethics Committee applications. This researcher has extensive travel experience on 5 continents over many years; has conducted similar survey field research on 3 continents and lived/educated in Africa, Europe and Oceania. Any adverse event or unexpected development affecting this research was formally reported to Ethics Committees, with an explanation wherever possible to minimise risk.

3.4.8: Monitoring, Bias and Error Control

To reduce potential sources of bias, ensure error control, ethical considerations and research quality, this thesis undertook several monitoring procedures for quality assurance. These monitoring procedures include regular scheduled meetings with PhD supervisors, an academic peer-reviewed Confirmation of Candidature and subsequent annual Reviews of Progress. It includes the ethics application process (Appendix I-V) and annual and final reports noting any specific issues that may occur throughout all research stages. The interview schedule/survey was also subject to peer review, pre-testing, providing a further source of bias and error control. The process revealed the need to reduce ambiguous or double- barrelled questions, provide sufficient answer space, simplify questions and provide more explicit, concise, relevant information as suggestions. These were adopted to improve the stakeholder participation rate.

Respondents will be offered the explicit choice of ensuring errors are controlled and minimised able to review aggregated, non-identifiable data results, prior to thesis submission and identification. This reduces issues of selective recall/subjective awareness of events. Personal interviews can aid clear response articulation. Any participant who withdraws at any stage and indicates that withdrawal, will have their results removed from the study and accumulated data destroyed. However, stakeholders may communicate with each other, given normal, interactive proximity to conduct business. These might inadvertently refer to the interview, research process as a source of bias, (though not from the research investigator). Often issues of omitted variable, spurious, regression correlation, random and systematic sampling error and survey bias exist. This occurs where the way it is framed/presented can alter the response (Schuldt, Roh and Schwarz, 2015).

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To reduce response bias, the interviewer/all appendix sheets adopts neutral, unemotive language and tones, not revealing personal preferences but clearly establishing a range of study-related, fixed choices. It also allows open-ended responses to endorse stakeholder participation. Certain participants preferred open-ended questions, which they can contribute more personally relevant perspectives. Given potential sensitivity over climate change, the study and research methodology concentrate on specific risks, impact costs, constraints and solutions to marine resources. This presents as a key MSC commodity, rather than communities covered in previous studies (Kaiteie and Hogan 2008; Dumaru et al 2011; SPC 2013b). It avoids subjective judgements or perspectives, emphasising anonymity to facilitate research candour. It provided a thesis established source of related risks, impact cost types and adaptation solutions. This prevents over-demanding recall, with sufficient time warning/opportunity in advanced notice to establish solutions. It offered stakeholders the choice to identify others the researcher had not considered to improve results. However, past training/experience of climate risks might alter perspectives and responses significantly. A positive response bias aims to be minimised through third party verification; calculated impact cost analysis and field research. This ascertains direct vulnerabilities, risks, costs, constraints and degree of proposed adaptation strategy effectiveness. It can be confirmed through other stakeholders, indirectly checking response data for further validity with stakeholders prior to submission. For this thesis, several factors may influence the nature of and limit stakeholder participation rates including asking for potentially commercially sensitive cost information. Adaptation strategies may lack attention or resource priorities. Power may be located at headquarters with little or no local autonomy to influence policy responses. Insufficient data may exist. Interviews may be unpopular in taking scarce time, (although to incentivise participation; a free research copy was offered.) Projected climate change uncertainty and inconsistency in existing research prompts moral hazard and risk averse stakeholders. For small Pacific nations exceeding 30 years of climate change adaptation a risk of over-information and exposure exists, combined with aid dependency reducing autonomous initiative. Stakeholders can tire of the same questions repeated. This risk occurs when existing aid agencies/researchers do not consult previous research in consultation and in proposing adaptation project solutions.

3.5: ANALYTICAL FRAMEWORK:

3.5.1: Analytical Framework: Probability of a Historic/Future Climate Change Risk/Conditional Probability of a MSC Asset/System Failure and Factors Affecting Risks

Section 3.2’s evaluation of existing, quantitative method studies established the Poisson distribution over alternatives. This establishes the foundations of the following, analytical risk framework for general and

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MSCs. It validates the above conceptual method, through identifying and defining risks. This framework considers climate change and non-climate factors that influence the probability of a risk occurrence, the scenario and time horizon through Figure 3.2. Specific scenarios and time horizons are verified scientifically through the IPCC reports. Climate data is independently and consistently established by the SPC, SPREP and Australia’s CSIRO. The proposed research method will incorporate the probabilities of a projected risk occurrence, combined with its impact cost consequences across Pacific MSCs. An absence of suitable alternative methods, equations, studies with specific probabilities and theory for effective risk management was established in Chapters 2/3.2. Without established equations to estimate climate change risks using specific probability distributions, section 3.2 previously justified the Poisson distribution for Equation 3.1. This applies the average probability of a past risk event occurring to a historic, Pacific risk event. This method proposes its contribution to risk management theory to calculate the average, independent probability of a specific and short term, risk event in Appendices. It advances an equation and framework integrating the risk type, its probability of occurrence, past data, potential accumulative risk, an event’s frequency and duration.

Probability of a Historic Pacific, Climate Change Risk Event Occurring.

Although current studies have not specifically applied risk probability theory to projecting future climate change risk; this thesis’s theoretical contribution proposes adapting basic distribution/equations to form equation 3.1 (Section 3.2). This method and Chapter 4 Pacific Futures tool, climate change projection techniques and screening criteria enable future event probability calculations. It considers the probability of a future risk event, not only needs to evaluate past risk events but changes in time, rather than remaining static. It must incorporate accumulating risk and the joint probability of 2 or more risk interactions (when such events occur); given climate change is fundamentally dynamic. To resolve problems of selective recall and limited information, the method proposes emphasising recent, past events for which stakeholder data potentially exists. This estimates expected average number of risk events per year given historical, actual events and future projected increases in frequency/probability of occurrence. These are adjusted for increased, accumulating risks per year to calculate future probabilities.

Unlike previous probabilities assuming the status quo remains over an event or asset’s lifetime, this framework considers risk events as fundamentally dynamic rather than static (merely reliant on historic time series data, given uncertainty and climate change). These include increases in yearly, accumulative, Pacific risk. An interaction or joint probability is necessary for calculating certain related events. For

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precipitation, SST, wind velocity and cyclones; earthquakes and volcanoes simultaneously. This method provides flexibility across time horizons, supply chain stakeholders and climate change scenarios. Event probabilities, the degree of confidence and significance of results are adjustable based on available and simulated data.

This framework will assist policy stakeholders to understand personal impact costs and across supply chains, as they possess very few research examples of specific costs. As a pioneering method for climate change, risk management for MSCs; method provide research advantages as per the Appendices. It is adaptable to divergent risks, asset types, scenarios, stakeholders and stages. It can incorporate resilience, vulnerability, accumulated risk and factors affecting the probability of risk occurrence and adaptation costs. This method details how risks diverge across individual specific MSCs for Pacific, small island, developing states. It aims to be sufficiently robust to overcome challenges of risk double counting, underestimation/overestimation, subjective stakeholders’ risk perceptions and factoring past, present and future risks. These risks may influence each other as risk interdependencies. This thesis’s contribution to above, existing literature methods is to consider how risks and impact costs can also vary across countries, economic sectors and stakeholders. These differ from experience, education, climates, environments, asset properties and stakeholder willingness/capacity to pay and adapt.

Previous risk management methods are mostly restricted to average events and the normal Gaussian distribution, including Formal Safety Assessment. These methods also use stakeholder perceptions to qualitatively measure risk. They do not standardise risk definitions or quantifying probability criteria. Events are seldom independent, conditional upon recent/past factors. This thesis follows statistical outliers in its distribution (Mandelbrot sets), based on projected, climate change simulations. It also incorporates original, empirical and field data. Its criteria are independently evaluated and established where possible. It utilises time series data to convert the probability of a low probability, high impact, Black Swan event into more frequent events. The principle concern of Pacific MSC stakeholders is asymmetrical information. They might not know of, or agree with available information sources, the probability of an asset failure or the criteria used to measure failure (i.e. cost/ performance/ sustainability). They may be unaware of how to calculate general and conditional probability. They may not possess criteria to determine resilience, vulnerability and adaptive capacity to quantify probability. This thesis’s conceptual contribution provides criteria in Figure 3.4. These criteria convert these factors into information for stakeholder requirements and functions. This risk estimation approach needs to indicate the probability of an asset/system failure. It identifies which risks to prioritise and why. It identifies when and

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where to prioritise this risk. These criteria then assist in calculating historic, current and future impact costs as potential consequences.

Figure 3.4: Key Variables for Climateproofing Against Risks

Stakeholder Criteria in Evaluating Which Risks to Prioritise and Why?

• Probability of Climate Change Risk Occurrence/Conditional Probability of Asset Failure.

• Size of Impact Costs/Consequences.