Assessing subjective preferences for river quality improvements: combining Q-methodology and choice experiment data

Figures & data

Figure 1. Survey area and location of respondents’ home.

Table 1. Matrix of themes and statement typology.

Theme category	Theme content/statement type
Financial management	Apportioning liability to industrial/agricultural polluters, financial responsibility for improvements to, or remediation of, rivers.
Communication	Individual actors, collaborative agreements and communication methods.
Ethical	Environmental ethics, emotions and moral concerns.
Non-market use and non-use values	Recreational benefits, ecological preservation, intergenerational equity.
Political regulation and scientific management	Policy prescriptions, scientific methods and water quality monitoring.

Figure 2. Sorting grid configuration.

Table 2. Summary statistics of full sample and respondents’ groups.

		Respondent type
	Full sample	Non-/low use	Occasional user	Recreational user	Expert
Number of respondents	62	17	14	17	14
Male (%)	53	59	36	53	64
Mean age*	44 (18)	41 (18)	56 (18)	35 (16)	45 (12)
Graduate education (%)	48	35	64	29	71
Income (£1000s)	33.7 (23.4)	27.3 (22.3)	33.4 (14.1)	26.6 (26.4)	49.7 (20.3)
Employed^# (%)	56	53	43	41	92
Membership of environmental organisations (%)	50	12	50	71	71
Mean number of river trips in the last year*	55 (81)	1 (1)	32 (51)	96 (87)	91 (99)

Note: Standard deviation in parenthesis. Percentages rounded to nearest whole number. *rounded to nearest whole number, ^#self-employed or employed full- or part-time.

Figure 3. CE attributes and levels.

Table 3. Results of first order analyses.

Respondent type	Number of respondents	Defining sorts	Confounded sorts	Insignificant sorts	Factors extracted
Non-/low use	17	12	4	1	3
Occasional	14	9	4	1	3
Recreational	17	12	4	1	3
Expert	14	12	2	0	4
Total	62	45	14	3	13

Table 4. Meta-analysis factor array composition.

Respondent type/Factor array number	No. respondents (45 total)	Meta-analysis factor array
		1	2	3	4	5
Low/non user 1	5	0.205	0.772 ^X	0.260	0.308	0.271
Low/non user 2	5	0.242	0.124	0.607^X	0.421	0.238
Low/non user 3	2	0.076	0.220	0.090	0.669 ^X	0.003
Occasional 1	5	0.782 ^X	0.310	0.153	0.223	0.220
Occasional 2	2	0.191	0.419	0.771 ^X	0.121	0.211
Occasional 3	2	0.353	0.467 ^X	0.335	0.339	0.223
Recreational 1	6	0.323	0.821 ^X	0.266	0.319	0.018
Recreational 2	2	0.307	0.108	0.209	0.149	0.702 ^X
Recreational 3	4	0.287	0.126	0.201	0.628 ^X	0.246
Expert 1	3	0.700 ^X	0.197	0.301	0.169	0.383
Expert 2	3	0.165	0.274	0.247	0.586 ^X	0.310
Expert 3	3	0.412	0.202	0.469 ^X	0.315	0.245
Expert 4	3	0.385	0.278	0.345	0.291	0.451 ^X
Number of respondents in array		8	13	10	9	5
Eigenvalues		1.95	2.08	1.82	1.95	1.30
Variance explained by factor (%)		15	16	14	15	10
Total explained variance 70%

Note: X indicates a defining sort. Critical value for factor loading >0.430.

Table 5. Summary statistics for meta-analysis respondents.

		Factor
	Whole sample	1	2	3	4	5
Number of respondents	45	8	13	10	9	5
Male (%)	53	87	46	40	56	40
Mean age*	43 (17)	57 (12)	41 (20)	44 (14)	39 (14)	33 (11)
Graduate education (%)	49	75	23	70	44	40
Mean income (£1000s)	37.4 (23.3)	44.2 (18.4)	28.5 (19.6)	41.4 (22.2)	34.3 (25.6)	45.0 (28.3)
Employed^# (%)	62	50	54	80	56	80
Members of environmental organisations (%)	51	50	38	50	56	80
Mean number of river trips in the last year*	59 (86)	76 (82)	23 (54)	40 (60)	49 (64)	179 (119)
Perception of the likelihood of water quality improvements being made (%)
Generally positive	31	25	38	30	11	60
Neutral	13	0	15	10	22	20
Generally negative	56	75	46	60	67	20

Note: Standard deviation in parenthesis. Percentages rounded to nearest whole number. *rounded to nearest whole number, ^#self-employed, or employed full- or part-time.

Table 6. Factor Q-sort values for each statement within the meta-analysis.

		Factor array
No.	Statement	1	2	3	4	5
1	Polluters should receive financial perks (e.g. tax breaks or grants) to make their practices more environmentally friendly	−2	−3	−3	1**	−1
2##	Major polluters should be doing more to reduce river pollution	1	2	1	2	3
3	Farmers should take responsibility for reducing pollution caused by livestock farming and if they don’t they should be penalised	0	0	1	−1	−2
4#	Polluters should work with each other to tackle river pollution	0	0	1	1	−1
5	Strong effective leaders are needed to help reduce river pollution	0	1	4**	−3*	0
6	Human actions should not be allowed to pollute rivers	1	2	0	−1	−1
7	Animals, fish and plants need protection from pollution	3	5*	2	2	0
8	Farmers should have the right to manage their own land however they want without interference from the government or other regulations	−4	−3	−5	−4	−2
9#	I would like to use rivers for recreation or would use them more but they are too polluted	−1	−1	−3	−2	−3
10	Rivers should be clean for our children and our children’s children to enjoy	3	3	0	0	2
11	I would trust the authorities (e.g. the Environment Agency) if they told me river water was clean	−2	−2	−1	−3	−3
12#	I feel well informed about the subject of river water quality and water pollution	−3	−4	−2	−4	−2
13	I would be willing to pay higher food prices if farmers guaranteed they were protecting river water quality	1	−2	−1	−1	2
14	The polluter should pay for river water quality improvements	−1*	3	4	4	1
15	It is right that laws have been brought in to improve river water quality	2	−1**	3	2	5
16##	Wildlife conservation should only be considered once the polluter has met their financial goals	−3	−4	−4	−3	−4
17	Water companies should use the best available equipment to reduce river pollution whatever the financial cost	−2	1	2	−1	0
18	River water quality is important to me	4	−1	1	0	3
19	River water quality problems are a very serious issue	2	4	−1	4	0
20	Enough is currently being done to protect and improve river water quality – there is no need to do anything more	−4	−3	−2	−5	−1
21	River water should not be harmful to human health	4	2	−2*	2	1
22	Polluters should see beyond their individual interests to what is good for the environment and the rest of society	1	4	3	0	2
23	It is wrong for farmers and water company shareholders to take profits while river pollution still happens	2	0	0	−2	−3
24	We must monitor river pollution levels and make certain the data is correct so action can be taken if needed	0	0	2	1	4*
25	The Government should fine or penalise the water companies that continue to pollute	0	3	5	3	0
26##	Low cost, farm based solutions, like using fencing to keep animals and animal waste away from watercourses, would be the best way of reducing agricultural pollution of streams and rivers	−1	−1	−2	0	−2
27#	Any pollution caused by agricultural chemicals is insignificant compared to their benefits in increasing food production	−3	−2	−3	−2	−4
28	Clean rivers are an asset	5**	1	1	3	2
29	Many of the species conservationists want to protect are not worth worrying about	−5	−5	−4	−1**	−5
30	Natural things should be respected as valuable in themselves and not just for what humans can get out of them	3	2	3	−2**	4
31#	More effort should be made to inform the public about the quality of river water and what is being done to improve it	−2	0	0	0	1
32##	I would be happy to pay more on my water bill for river water quality improvements if those improvements actually happened	0	−1	−1	1	−2
33	Pollution reduction should always be carried out if there is evidence that it is needed	0	1	0	3	1
34	I think making use of rivers for recreation (boating, swimming, canoeing, fishing) is a good idea	2	−1	−1	0	3
35	Major polluters should talk to local people and seek out their knowledge to help find solutions to river pollution	−1	−2	0	1	1
36	All major polluters must take part in the process of improving river water quality	−1	1	2	5**	0

Note: This table provides exemplar Q-sorts for each factor array. Distinguishing statements (those that are significantly different from all other factors) for factors are marked * for p < 0.05 and ** for p < 0.01. Consensus statements (those that do not distinguish between any pair of factors) are marked # if non-significant at p > 0.01 and ## if also non-significant at p > 0.05.

Table 7. Q Narrative summaries.

Factor	Theme
1	A focus on ethical issues and ecological conservation, enabling species to flourish within unpolluted rivers and human recreational use.
2	Emphasis on the use of financial instruments to control the actions of major polluters. Recreational use is unimportant.
3	Hierarchical government leadership and intervention to regulate the actions of polluters thus protecting river ecology.
4	Collaboration to reduce river pollution. Pragmatism towards the environment: rivers are assets to be used.
5	Legislation, defined by sound science, bound the polluter’s autonomy. River pollution problems are overstated.

Table 8. Correlations between factors scores in the meta-analysis.

Factor	1	2	3	4	5
1	–	0.68	0.57	0.50	0.67
2		–	0.74	0.63	0.48
3			–	0.54	0.61
4				–	0.46
5					–

Table 9. CL model of Q respondents’ water quality preferences.

Variable	Coefficient	Standard Error
Baseline (Factor 3 Respondents, no survey river users) (n = 10)
Price	−0.061***	0.016
Medium ecological quality	4.203***	0.811
High ecological quality	6.177***	1.263
Medium recreational quality	2.086***	0.804
High recreational quality	1.697***	0.615
Factor 1 Respondents (n = 8)
Factor 1 × Price	0.080**	0.040
Factor 1 × Medium ecological quality	0.380	2.160
Factor 1 × High ecological quality	2.463	4.211
Factor 1 × Medium recreational quality	−0.886	1.573
Factor 1 × High recreational quality	2.564	2.713
Factor 2 Respondents (n = 13)
Factor 2 × Price	0.032*	0.018
Factor 2 × Medium ecological quality	−0.833	0.944
Factor 2 × High ecological quality	−1.015	1.423
Factor 2 × Medium recreational quality	−1.614*	0.894
Factor 2 × High recreational quality	−0.835	0.734
Factor 4 Respondents (n = 9)
Factor 4 × Price	0.055***	0.017
Factor 4 × Medium ecological quality	−2.602***	0.874
Factor 4 × High ecological quality	−3.351**	1.356
Factor 4 × Medium recreational quality	−1.063	0.878
Factor 4 × High recreational quality	−0.645	0.728
Factor 5 Respondents (n = 5)
Factor 5 × Price	0.036*	0.020
Factor 5 × Medium ecological quality	−1.645*	0.997
Factor 5 × High ecological quality	−0.948	1.667
Factor 5 × Medium recreational quality	−0.779	1.072
Factor 5 × High recreational quality	−0.900	0.945
Survey river users^# (n = 9)
Survey river users × Price	0.007	0.011
Survey river users × Medium ecological quality	−0.913	0.559
Survey river users × High ecological quality	−1.195	0.913
Survey river users × Medium recreational quality	1.036	0.643
Survey river users × High recreational quality	1.976***	0.689
Number of observations = 1080
Log likelihood = −172.793
R^2 = 0.54

Note: *, ** and *** = significance at 10%, 5% and 1% levels. CL model of price and categorical water quality levels for Factor 3 respondents, with recreational users and respondents loading on other Q factors as separate categorical interaction terms. #Respondents who use the survey river stretch of the Yare as their primary location to row or swim.