Rural Economy Research Centre Understanding farmers’ intentions to convert to organic farming An application of the theory of planned behaviour using structural equation modelling Doris Läpple Rural Economy Research Centre (RERC) Teagasc Department of Economics, National University of Ireland, Galway AESI student awards day 5 th November 2009

Rural Economy Research Centre 2 Overview of presentation Background Theory Survey design and data Methodology Preliminary results Summary and further work

Background Organic sector  Currently 1,220 organic farmers (1% of UAA)  Government target: 5% of UAA by 2012 Increased information provision Changes in organic support payments Conventional sector  Extensive mainly grass based systems many drystock farmers could easily switch to organics What effects the intention of conventional farmers to convert? Rural Economy Research Centre 3

Background PhD: Adoption of organic farming  Previous paper: Adoption and abandonment of organic farming Policy context  Conversion of existing farmers  Identify drivers and barriers Application of the TPB to understand/predict different human behaviours  Hunting behaviour (Hrubes et al, 2001), leisure choice (Ajzen and Driver, 1992), food choice (Cook et al, 2002; Lobb et al, 2007), investment behaviour (East, 1993), consumer adoption intention (Taylor & Todd, 1995) Rural Economy Research Centre 4

Theory of planned behaviour Source: Ajzen, Rural Economy Research Centre 5 Attitude toward the behaviour Subjective norm Perceived behavioural control Behavioural beliefs Normative beliefs Control beliefs Intention Behaviour

Theory of planned behaviour components Attitude (A): b: beliefs about the outcomes of the behaviour e: evaluation of this particular outcome Subjective norm (SN): nb: normative beliefs; mc: motivation to comply Perceived behavioural control (PBC): cb: control beliefs; pc: power of control Rural Economy Research Centre 6

Theory of planned behaviour belief based measures Behavioural belief: If you produce organic meat you will receive higher prices strongly agree (5) to strongly disagree (1) Outcome evaluation: Receiving higher prices is… very important (+2) to very unimportant (-2) Rural Economy Research Centre 7

Theory of planned behaviour Components consist of direct and belief based measures  Belief based measures should correlate well with direct measures of the specific component → Salient beliefs The more positive the attitude, subjective norm and perceived behavioural control the more likely the person is to perform the behaviour under study Rural Economy Research Centre 8

Methodology survey design Step 1: Open interviews to elicit salient beliefs (n = 53) Outcome beliefs Important referents Expected problems Step 2: Design structured questionnaire (n = 193)  Principle of compatibility Target - organic meat Action - producing meat organically Context - the farm Time - 5 years Data from NFS farms Rural Economy Research Centre 9

Methodology survey design Intention (2 items): How likely is it that you will produce organic meat on your farm within the next five years? measured from very likely (5) to very unlikely (1) Attitude (3 items): Producing organic meat on your farm within the next five years would be… very good (+2) to very bad (-2) ; very foolish (-2) to very wise (+2) SN (2 items): Most people who are important to you think you should produce organic meat on your farm within the next five years… definately false (-2) to definately true (+2) PBC (2 items): How confident are you of your technical ability to produce organic meat on your farm within the next five years? not at all (-2) to very confident (+2) Rural Economy Research Centre 10

Results descriptive statistics VariableRangeMeanSt. dev.Cronbach‘s α (n=193) Intention1 to Attitude-2 to SN-2 to PBC-2 to Rural Economy Research Centre 11

Results validation of belief based measures Behavioural beliefbibi oe i r s A Range1-5-2/+2(-10/+10) Fertilizer4.123 (0.767)1.082 (0.799)0.069 Higher prices3.456 (0.935)1.290 (0.776)0.213** Farm income3.197 (0.868)1.275 (0.738)0.337*** 50 ys ago3.196 (1.091) (0.869)0.412*** Rich people3.321 (0.995) (0.685)0.341*** Σ b 2 b *** Σ b 4 b *** Σ b 2 – b *** Rural Economy Research Centre 12

Results validation of belief based measures Normative belief nb i mc i r s SN Range-2 / / +10 Family (.962)2.477 (1.335)0.354*** Other farmers (.971)2.104 (1.010)0.364*** Farm advisors (1.019)2.580 (1.285)0.366*** Inf. Events (1.077)2.352 (1.267)0.363*** Farming press (1.103)2.259 (1.231)0.411*** Σ nb 1 -nb *** Rural Economy Research Centre 13

Results validation of belief based measures Control beliefcb i pc i r s PBC Range-2 / / +10 Knowledge0.244 (1.019)3.642 (.969)0.506*** Time0.155 (1.064)3.419 (1.008)0.270*** Farm conditions0.580 (1.102)3.746 (.837)0.375*** Without fertilizer0.482 (1.056)3.404 (.891)0.279*** Animal health (1.011)3.259 (.992)0.376*** Σ cb 1 – cb *** Rural Economy Research Centre 14

Methodology Measurement model Structural equations for measurement model  Observed variables are generated by a smaller number of latent variables errors of measurement for x and y  Assumptions: is uncorrelated with Rural Economy Research Centre 15

Methodology Measurement model Select a scale for the latent variable:  latent variable is assigned the scale of the i‘th observed variable Identification:  t-rule: number of equations exceeds unknowns in : identification possible Two-step rule:  Identify measurement model  Model with observed variables Rural Economy Research Centre 16

Methodology Structural Equation Model (Covariance Structure Model) SEM: Statistical methodology to test a theoretical model  Causal inferences of the theory are consistent with the data population covariance matrix of the observed variables vector of model parameters Two major subsystems:  Measurement model (confirmatory factor analysis)  Latent variable model (structural model) Rural Economy Research Centre 17 x2 x3 x1  y1y2 y3 y4 y5 y6 

Methodology categorical observed variables Linear model relating x (y) to  (  invalid c: number of categories (=5) a: category threshold y*: latent continous indicator Step 1: Estimate thresholds (assumption: y* normally distributed) N k : number of cases in the kth catgory Rural Economy Research Centre 18

Methodology categorical observed variables Step 2: Estimate latent correlations (polychorich) Step 3: Weighted least square estimator vector containing the polychorich correlations vector for implied covariance matrix consistent estimator of the asymptotic covariance matrix of Rural Economy Research Centre 19

Model Rural Economy Research Centre 20 A1 A2 A3 SN1 PBC2 A SN PBC BI I1 I2        

Model equations Rural Economy Research Centre 21

Results measurement model ParameterEstimate (st.err.)t-valueR2R2 11 I (0.034) I (---) A (0.039) A (---) A (0.052) SN (---) SN (0.079) PBC (---) PBC (0.075)  2 = 27.53, df=21, P-value=0.154,  2 /df = Rural Economy Research Centre 22

Results Structural equation model ParameterEstimate (st.err.)t-value A (  11 ) (0.090)6.517 SN (  12 ) (0.095)2.953 PBC (  13 ) (0.057)2.979 I1 ( 11 ) (0.034) I2 ( 12 ) (---) A1 ( 23 ) (0.039) A2 ( 23 ) (---) A3 ( 23 ) (0.052)  2 =6.77, df=10, P-value = 0.747,  2 /df=  Rural Economy Research Centre 23

Summary and further work Belief measures significant determinants of direct measures  Confirms model Direct components are be significant indicators of intention  Attitude strongest predictor  PBC – lower value explained by measure (self-efficacy) Further work:  Improve modelling  Include belief based measures Rural Economy Research Centre 24

Thank you for your attention! Rural Economy Research Centre