Expert responses (raw data) on the Factor groups
nonmon_engagement <- c(7,7,-4,-7,7,-8,-5,-5,5,7,7,2,-7)
nonmon_enterprises <- c(5,5,4,1,7,-6,-3,-6,1,6,-6,1,3)
nonmon_cultural <- c(-5,6,5,-7,5,-5,-7,-7,5,7,8,-5,-6)
nonmon_support <- c(-7,4,1,-3,7,-8,-5,1,-5,6,7,6,6)
nonmon_energy <- c(-7,8,3,4,7,-9,-3,-3,-5,6,1,7,-7)
nonmon_govern <- c(8,5,7,1,9,-8,-3,5,5,8,9,8,7)
nonmon_networks <- c(-5,5,7,-5,8,-8,-7,1,-5,3,-3,4,-5)
nonmon_relations <- c(3,7,7,3,8,1,-4,1,-5,3,8,6,-6)
nonmon_citizen <- c(4,3,-5,-6,8,-7,-4,-3,-5,4,8,6,-6)
nonmon_viablebm <- c(-5,8,-5,-2,7,-6,-7,-4,8,6,8,5,6)
nonmon_financial <- c(7,8,7,8,9,-9,-3,3,8,8,9,8,3)
engagement_enterprises <- c(-5,5,4,4,8,1,-7,-4,-6,2,-6,2,6)
engagement_cultural <- c(-3,6,1,-4,8,-4,-7,-7,-6,3,1,-3,-8)
engagement_support <- c(-3,8,-6,-2,7,5,-4,2,-6,3,1,3,5)
engagement_energy <- c(-7,8,-7,3,8,9,-2,2,-6,5,6,7,-8)
engagement_govern <- c(1,3,-5,6,9,9,-3,5,1,5,6,8,4)
engagement_networks <- c(-5,3,1,1,8,5,-7,2,1,-3,1,3,-8)
engagement_relations <- c(1,6,1,1,8,3,-6,4,-6,-3,5,5,6)
engagement_citizen <- c(1,8,-6,1,8,8,-6,1,1,1,1,5,1)
engagement_viablebm <- c(-5,7,-6,4,7,1,-6,1,4,4,5,7,-6)
engagement_financial <- c(1,3,6,8,9,9,-3,3,6,4,7,9,5)
entreprises_cultural<- c(1,7,5,-5,6,8,5,1,1,-4,1,2,-7)
entreprises_support <- c(-3,7,4,1,6,9,5,7,-5,-4,1,4,5)
entreprises_energy <- c(1,7,4,3,7,9,4,4,-5,3,5,7,-9)
entreprises_govern <- c(NA,9,6,3,9,9,3,7,1,-5,8,8,6)
entreprises_networks <- c(1,4,-4,1,7,3,3,5,5,-5,1,4,-4)
entreprises_relations <- c(3,5,-4,-3,7,7,2,7,-5,-2,7,5,5)
entreprises_citizen <- c(3,8,1,-3,7,1,5,6,-3,1,1,5,6)
entreprises_viablebm <- c(1,8,1,1,7,1,3,4,5,-4,5,8,3)
entreprises_financial <- c(5,8,6,8,9,9,3,4,7,5,7,9,6)
cultural_support <- c(1,4,1,4,8,8,-3,7,-5,-4,1,5,7)
cultural_energy <- c(1,4,1,7,8,9,-2,4,3,1,6,8,-5)
cultural_govern <- c(3,7,1,9,9,9,6,7,1,-2,9,8,8)
cultural_networks <- c(-3,7,1,5,8,3,3,5,-4,-5,1,5,7)
cultural_relations <- c(1,5,1,1,8,5,-3,7,1,-4,5,7,8)
cultural_citizen <- c(3,6,1,2,8,4,-3,6,1,2,1,6,8)
cultural_viablebm <- c(1,8,1,9,8,1,-3,4,1,-4,6,7,7)
cultural_financial <- c(3,7,1,9,9,9,3,4,8,4,7,9,8)
support_energy <- c(1,8,-5,4,7,9,2,-3,-2,3,8,7,-9)
support_govern <- c(5,7,1,9,9,9,-2,5,4,4,8,8,1)
support_networks <- c(1,8,-4,1,8,4,3,1,-5,1,1,3,-8)
support_relations <- c(3,7,1,4,8,6,3,1,-3,1,6,4,-7)
support_citizen <- c(1,4,-7,1,8,3,2,-2,4,5,1,4,-8)
support_viablebm <- c(1,5,-4,5,8,2,2,-2,4,6,7,7,4)
support_financial <- c(3,8,-4,9,8,9,3,3,7,7,7,8,6)
energy_govern <- c(5,9,5,1,9,9,-2,7,3,3,5,6,9)
energy_networks <- c(1,3,5,-4,7,7,4,2,1,-3,-7,-5,7)
energy_relations <- c(1,7,5,-6,7,6,2,3,1,3,-7,-4,8)
energy_citizen <- c(1,7,-3,-6,7,4,5,1,4,3,1,-4,8)
energy_viablebm <- c(-3,7,1,1,7,5,3,1,4,4,1,6,8)
energy_financial <- c(3,8,5,6,9,9,-2,1,7,5,7,7,9)
govern_networks <- c(-5,8,-2,-8,-9,-9,3,-4,-4,-5,-8,-7,-8)
govern_relations <- c(-2,2,-2,-8,-9,-7,-6,1,-4,-3,-2,-5,1)
govern_citizen <- c(3,3,-6,-8,-9,-5,-2,-2,1,4,-8,-6,1)
govern_viablebm <- c(-2,8,-5,-6,-9,-3,1,-2,-3,2,1,-3,-8)
govern_financial <- c(1,8,1,1,-9,9,-2,-2,5,6,-5,5,1)
networks_relations <- c(6,4,1,1,8,-6,-2,2,1,4,1,4,6)
networks_citizen <- c(5,5,-4,1,8,-5,-5,1,1,7,5,1,6)
networks_viablebm <- c(1,7,-3,7,-8,-4,-5,1,2,6,8,6,7)
networks_financial <- c(5,7,1,9,9,9,-3,2,5,7,8,7,8)
relations_citizen <- c(1,5,-5,1,1,-6,-2,-2,1,3,1,-4,5)
relations_viablebm <- c(-5,7,-5,7,-6,1,-2,-3,3,3,5,7,4)
relations_financial <- c(-2,7,-5,8,9,9,-2,1,5,7,8,9,6)
citizen_viablebm <- c(-7,8,4,8,6,1,1,-2,3,-6,7,7,-4)
citizen_financial <- c(1,8,6,9,9,9,1,1,5,6,2,9,6)
viablebm_financial <- c(7,6,5,2,9,9,3,3,6,8,1,7,6)
factor_group <- data.frame(nonmon_engagement, nonmon_enterprises, nonmon_cultural, nonmon_support, nonmon_energy, nonmon_govern, nonmon_networks, nonmon_relations, nonmon_citizen, nonmon_viablebm, nonmon_financial, engagement_enterprises, engagement_cultural, engagement_support, engagement_energy, engagement_govern, engagement_networks, engagement_relations, engagement_citizen, engagement_viablebm, engagement_financial, entreprises_cultural, entreprises_support, entreprises_energy, entreprises_govern, entreprises_networks, entreprises_relations, entreprises_citizen, entreprises_viablebm, entreprises_financial, cultural_support, cultural_energy, cultural_govern, cultural_networks, cultural_relations, cultural_citizen, cultural_viablebm, cultural_financial, support_energy, support_govern, support_networks, support_relations, support_citizen, support_viablebm, support_financial, energy_govern, energy_networks, energy_relations, energy_citizen, energy_viablebm, energy_financial, govern_networks, govern_relations, govern_citizen, govern_viablebm, govern_financial, networks_relations, networks_citizen, networks_viablebm, networks_financial, relations_citizen, relations_viablebm, relations_financial, citizen_viablebm, citizen_financial, viablebm_financial)
colnames(factor_group) <- c("1","2","3","4","5","6","7","8","9","10","11","12","13","14","15","16","17","18","19","20","21","22","23","24","25","26","27","28","29","30","31","32","33","34","35","36","37","38","39","40","41","42","43","44","45","46","47","48","49","50","51","52","53","54","55","56","57","58","59" ,"60","61","62","63","64","65")
rownames(factor_group) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" , "Expert#10" , "Expert #11" , "Expert#12" , "Expert#13")
factor_group
## 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
## Expert #1 7 5 -5 -7 -7 8 -5 3 4 -5 7 -5 -3 -3 -7 1 -5 1 1 -5 1 1 -3
## Expert #2 7 5 6 4 8 5 5 7 3 8 8 5 6 8 8 3 3 6 8 7 3 7 7
## Expert #3 -4 4 5 1 3 7 7 7 -5 -5 7 4 1 -6 -7 -5 1 1 -6 -6 6 5 4
## Expert #4 -7 1 -7 -3 4 1 -5 3 -6 -2 8 4 -4 -2 3 6 1 1 1 4 8 -5 1
## Expert #5 7 7 5 7 7 9 8 8 8 7 9 8 8 7 8 9 8 8 8 7 9 6 6
## Expert #6 -8 -6 -5 -8 -9 -8 -8 1 -7 -6 -9 1 -4 5 9 9 5 3 8 1 9 8 9
## Expert #7 -5 -3 -7 -5 -3 -3 -7 -4 -4 -7 -3 -7 -7 -4 -2 -3 -7 -6 -6 -6 -3 5 5
## Expert #8 -5 -6 -7 1 -3 5 1 1 -3 -4 3 -4 -7 2 2 5 2 4 1 1 3 1 7
## Expert #9 5 1 5 -5 -5 5 -5 -5 -5 8 8 -6 -6 -6 -6 1 1 -6 1 4 6 1 -5
## Expert#10 7 6 7 6 6 8 3 3 4 6 8 2 3 3 5 5 -3 -3 1 4 4 -4 -4
## Expert #11 7 -6 8 7 1 9 -3 8 8 8 9 -6 1 1 6 6 1 5 1 5 7 1 1
## Expert#12 2 1 -5 6 7 8 4 6 6 5 8 2 -3 3 7 8 3 5 5 7 9 2 4
## Expert#13 -7 3 -6 6 -7 7 -5 -6 -6 6 3 6 -8 5 -8 4 -8 6 1 -6 5 -7 5
## 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46
## Expert #1 1 NA 1 3 3 1 5 1 1 3 -3 1 3 1 3 1 5 1 3 1 1 3 5
## Expert #2 7 9 4 5 8 8 8 4 4 7 7 5 6 8 7 8 7 8 7 4 5 8 9
## Expert #3 4 6 -4 -4 1 1 6 1 1 1 1 1 1 1 1 -5 1 -4 1 -7 -4 -4 5
## Expert #4 3 3 1 -3 -3 1 8 4 7 9 5 1 2 9 9 4 9 1 4 1 5 9 1
## Expert #5 7 9 7 7 7 7 9 8 8 9 8 8 8 8 9 7 9 8 8 8 8 8 9
## Expert #6 9 9 3 7 1 1 9 8 9 9 3 5 4 1 9 9 9 4 6 3 2 9 9
## Expert #7 4 3 3 2 5 3 3 -3 -2 6 3 -3 -3 -3 3 2 -2 3 3 2 2 3 -2
## Expert #8 4 7 5 7 6 4 4 7 4 7 5 7 6 4 4 -3 5 1 1 -2 -2 3 7
## Expert #9 -5 1 5 -5 -3 5 7 -5 3 1 -4 1 1 1 8 -2 4 -5 -3 4 4 7 3
## Expert#10 3 -5 -5 -2 1 -4 5 -4 1 -2 -5 -4 2 -4 4 3 4 1 1 5 6 7 3
## Expert #11 5 8 1 7 1 5 7 1 6 9 1 5 1 6 7 8 8 1 6 1 7 7 5
## Expert#12 7 8 4 5 5 8 9 5 8 8 5 7 6 7 9 7 8 3 4 4 7 8 6
## Expert#13 -9 6 -4 5 6 3 6 7 -5 8 7 8 8 7 8 -9 1 -8 -7 -8 4 6 9
## 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 NA
## Expert #1 1 1 1 -3 3 -5 -2 3 -2 1 6 5 1 5 1 -5 -2 -7 1 7
## Expert #2 3 7 7 7 8 8 2 3 8 8 4 5 7 7 5 7 7 8 8 6
## Expert #3 5 5 -3 1 5 -2 -2 -6 -5 1 1 -4 -3 1 -5 -5 -5 4 6 5
## Expert #4 -4 -6 -6 1 6 -8 -8 -8 -6 1 1 1 7 9 1 7 8 8 9 2
## Expert #5 7 7 7 7 9 -9 -9 -9 -9 -9 8 8 -8 9 1 -6 9 6 9 9
## Expert #6 7 6 4 5 9 -9 -7 -5 -3 9 -6 -5 -4 9 -6 1 9 1 9 9
## Expert #7 4 2 5 3 -2 3 -6 -2 1 -2 -2 -5 -5 -3 -2 -2 -2 1 1 3
## Expert #8 2 3 1 1 1 -4 1 -2 -2 -2 2 1 1 2 -2 -3 1 -2 1 3
## Expert #9 1 1 4 4 7 -4 -4 1 -3 5 1 1 2 5 1 3 5 3 5 6
## Expert#10 -3 3 3 4 5 -5 -3 4 2 6 4 7 6 7 3 3 7 -6 6 8
## Expert #11 -7 -7 1 1 7 -8 -2 -8 1 -5 1 5 8 8 1 5 8 7 2 1
## Expert#12 -5 -4 -4 6 7 -7 -5 -6 -3 5 4 1 6 7 -4 7 9 7 9 7
## Expert#13 7 8 8 8 9 -8 1 1 -8 1 6 6 7 8 5 4 6 -4 6 6