Pangasius ( Catfish) Production in Vietnam : Risk and Risk Managem ent, Technology Adoption, and Sustainability Presented by: Le Cong Tru Nong Lam University, Ho Chi Minh City, Vietnam
Contents: • Project 1: Risk Management Framework for Vietnamese Aquaculture: The Case of Vietnamese Catfish (Pangasius), 2008-2011. – in collaboration with RMIT University, Melbourne, Australia) – (investigators: Tru Cong Le, France Cheong, and Chris Cheong) • Project 2: Economic analysis of Recirculting Aquaculture System (RAS) to improve sustainability of Vietnamese pangasius production, 2012-2016 – (in collaboration with Wageningen University, Wageningen, The Netherlands. – (investigators: Pham Thi Anh Ngoc, Miranda P. M. Meuwissen, Tru Cong Le, Roel H. Bosma, Johan Verreth and Alfons Oude Lansink 2
Project 1: Risk Management Framework for Vietnamese Catfish 1. Main objective: Developing a risk management framework for Vietnamese catfish farming 2. Sub-objectives: 1. Determining perceptions of risks and risk management of Vietnamese farmers 2. Developing a risk management framework for Vietnamese catfish farming 3. Implementing and evaluating a DSS for risk management in Vietnamese catfish farming 3
Introduction: Issues with Vietnamese Catfish Industry 4
Catfish production: Fast growth 900 14000 800 12000 700 10000 Output value (VND billions) Output volume (1,000 tons) 600 8000 500 400 6000 300 4000 200 2000 100 0 0 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 Jul-08 Year Output volume (1,000 tons) Output value (VND billions) 5
Catfish exports: Decreasing and fluctuating prices 1200 4 3.76 3.5 979.036 1000 3.11 3 2.85 2.76 Export volume and value 800 736.872 2.57 Average export price 2.53 2.5 2.46 2.33 600 2 1.5 386.87 400 328.153 286.6 1 228.995 200 140.707 0.5 87.055 82.962 81.899 33.304 27.98 2.593 1.97 5.618 0.689 0 0 2000 2001 2002 2003 2004 2005 2006 2007 Year Export volume (1000 tons) Export value (USD millions Average ecport price USD/Kg) 6
Opportunities and Challenges • Opportunities – High demand from export market – Comparative advantages in catfish production – Supported by government • Challenges – Increasing production costs – Decreasing selling prices – Decreasing profitability – Frequent disease breakouts – Stricter import barriers – Higher standards for food safety and hygiene 7
Methodology
Methodology and Research Steps Methods used Literature review Research objective 1 Examining the perceptions Factor analysis of risks and risk Survey 1 Phase 1 Multiple regressions management Surveying 261 catfish Examining the farmers on perceptions perceptions of risks of risk and risk and risk management management Research objective 2 BPM Developing a risk Survey 2 Phase 2 AS/NZS 4360 RMP 8 in-depth interviews management framework Developing the risk with catfish farmers on management cost and benefit of PDF (data fitting) framework RMSs System Approach Research objective 3 Phase 3 Developing the DSS for risk management Developing a DSS for risk management Survey 3 SEM Phase 4 Surveying 55 catfish Evaluating the DSS farmers and Acceptance aquacultural staff on DSS acceptance 9
Results and Discussions
Phase 1: Perceptions of risks and risk management Data collection and data analysis Data collection: fresh survey of 261 catfish farmers in the Mekong • delta • Data analysis methods: – Exploratory Factor Analysis • Reducing 40 sources of risk into 6 categories of risk • Reducing 50 risk management strategies into 6 categories of RMS • Standardized factor scores were used as dependent variables in subsequent regressions – Multivariate Regression • RF i, t = f(Consult t , D_large t , D_medium t , Age t , Education t , Experience t , Gender t , ε t ) (1) • and • RMF j, t = f(Consult t , D_large t , D_medium t , Age t , Education t , Experience t , Gender t , RF i, t , e t ) (2) 11
Results of Multiple Regressions for Sources of Risk Sources of risk Price and credit e Pond location e Independent variables Disease and environment Production Natural conditions Legislation Intercept *0.92 -0.42 0.07 0.42 **1.32 **-0.98 Consult a *-0.28 **0.34 ***0.52 -0.06 -0.12 **0.51 D_large b **0.35 ***0.52 -0.16 0.26 ***-0.64 ***0.55 D_medium c **0.42 *0.25 0.06 0.26 -0.1 **0.31 Age (years) **-0.02 0 0 *-0.01 **-0.01 **0.02 Education (years) 0.03 0.01 -0.01 -0.01 -0.02 -0.01 Experience (years) 0 0 ***-0.04 0 ***0.04 -0.02 Gender d *-0.29 0.13 -0.25 0.22 -0.32 -0.09 R-squared ***0.12 ***0.08 ***0.08 0.04 ***0.10 ***0.10 R-squared adjusted 0.09 0.05 0.05 0.01 0.07 0.07 29.45 35.83 36.93 46.79 30.25 49.87 White heteroscedasticity statistics f -0.4937 -0.2137 -0.1791 -0.026 -0.453 0.0128) Durbin-Watson statistics 1.98 1.91 1.36 1.61 1.64 1.65 ‘*’, ‘**’ and ‘***’ denote levels of significance of 10%, 5% and 1% respectively for variables and models. 12
Results of Multiple Regressions for Risk Management Strategies Risk management strategies Independent variables Farm management Financial Input quality Extension/ Education Disease prevention Diversification Farm/farmer characteristics Intercept -0.31 -0.04 **-0.63 **1.14 *-0.89 -0.59 a Consult 0.12 -0.11 **0.42 -0.2 -0.07 ***0.52 b D_large *0.31 -0.13 -0.23 ***0.75 0.17 0.23 c D_medium **0.40 -0.04 -0.17 0.1 *0.26 -0.04 Age 0 0 0 -0.01 **0.01 0 Education 0 0 0.02 -0.01 *0.05 0 Experience *-0.02 **0.02 0.02 **-0.03 -0.02 -0.02 d Gender 0.21 0.11 -0.09 ***-0.65 -0.12 0.24 Sources of risk (1) Disease and environment 0 ***0.46 **0.14 ***0.14 ***0.27 ***0.28 (2) Production 0.05 ***-0.3 ***0.33 **0.13 ***0.20 ***-0.19 (3) Natural conditions ***0.44 ***0.4 -0.03 -0.07 *-0.10 **-0.15 (4) Price and Credit ***0.21 -0.03 ***0.16 ***0.37 **-0.14 ***-0.27 (5) Legislation **0.13 ***0.16 -0.09 ***0.23 *-0.11 *0.10 (6) Pond location ***0.28 ***-0.18 ***0.25 ***-0.28 -0.07 0.03 R-squared ***0.46 ***0.56 ***0.25 ***0.45 ***0.23 ***0.25 R-squared adjusted ***0.43 ***0.53 ***0.20 ***0.41 ***0.18 ***0.20 “*,” “**,” and “***” denote levels of significance of 10%, 5%, and 1% respectively for variables and models. a Measured as a dummy variable, where 1 denotes farms taking external technical consultancy, 0 denotes not taking technical consultancy. b Measured as a dummy variable, where 1 denotes large scale farm, which has a total area of pond greater than 2 hectares. c Measured as a dummy variable, where 1 denotes medium scale farm with a total pond area between 0.5 and 2 hectares. d Measured as a dummy variable, where 1 denotes male farm head, 0 denotes female farm head. 13
Phase 2: Catfish Risk management framework 14
7 steps for developing a risk management framework Step 7: Monitor and Review Monitoring the Risk Assessment effects of the applied risk management Step 3: Identify the risk strategies Step 1: Communicate and Step 2: Establish the Identifying Risks and Risk Management Consult Step 6: Treat the risk Context Strategies: Monitoring the risks Modelling catfish farming Business Process Consult with aquaculture Selecting the risks that are not treated The context of the risk Identify 40 sources of risk and classified in academia, local aquaculture need to be treated in the current risk management is to 6 categories of risks officers and staff management plan limited to: Identify 50 risk management strategies and Selecting risk Scope: Catfish classified into 6 categories of risk Focus group workshop management farming management strategies Updating the risk Including 20 major strategies based on Stakeholders: and risk stakeholders: catfish RMS’s efficacy Catfish farmers, management farmers, government staff, aquacultural staff, Step 4: Analyse the risk strategies extension workers, Selecting the risk researchers aquacultural experts, management Risk risk Measuring the risk consequences, university researchers, strategies based on management likelihoods, and levels of risk (risk exposure) Regularly reviewing and catfish farming net benefit evaluation criteria Measuring the efficacy of the risk the risks and risk association management strategies management strategies Step 5: Evaluate the risk Documenting the Ranking and prioritizing the risks by level of risk risks and risk management strategies 15
Phase 3: Architecture of Fish@Risk DSS 16
Phase 4: DSS Acceptance: Proposed Model for Evaluation ▽ 17
Survey Instrument Scales • Performance expectancy: item PE1-PE4 (4 items), 1-5 Likert scale • Effort expectancy : item EE1-EE4 (4 items), 1-5 Likert scale • Social influence : item SI1-SI4 (4 items), 1-5 Likert scale Computer anxiety : item AX1-AX4 (4 items), 1-5 Likert scale • • Computer self efficacy : item SE1-SE4 (4 items), 1-5 Likert scale • Behaviour intention : item BI1-BI3 (3 items), 1-5 Likert scale • Other demographic variables: – Age : 1 item, 1-5 Likert scale – Computer experience, 1 item, 1-5 Likert scale – Education : 1 item, 1-5 Likert scale – Personnel : 1 item, 1-4 Likert scale – Farming experience : 1 item, 1-4 Likert scale 28 items are developed • 18
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