#install packages
library(ahpsurvey)
library(dplyr)executive_market <- c(1,-7,5,-2,1,4,1,4,4,7)
executive_finance <- c(NA,-8,5,-9,-6,-3,1,-5,-3,-3)
executive_engineer <- c(7,7,9,-6,-4,6,7,7,6,-3)
executive_designer <- c(7,9,9,-4,1,7,7,8,7,4)
market_finance <- c(NA,1,1,-9,-6,-5,-3,-5,-5,-7)
market_engineer <- c(1,8,5,-6,-6,5,7,3,5,-6)
market_designer <- c(NA,8,5,-4,-3,7,7,5,7,7)
finance_engineer <- c(NA,8,5,6,-4,5,9,6,5,5)
finance_designer <- c(7,7,5,9,1,7,9,9,7,7)
engineer_designer <- c(1,4,1,4,5,1,1,4,1,1)
idea_exploration <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(idea_exploration) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(idea_exploration) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
idea_exploration## Executive officers & Marketing analysts
## Expert #1 1
## Expert #2 -7
## Expert #3 5
## Expert #4 -2
## Expert #5 1
## Expert #6 4
## Expert #7 1
## Expert #8 4
## Expert #9 4
## Expert #10 7
## Executive officers & Finance analysts
## Expert #1 NA
## Expert #2 -8
## Expert #3 5
## Expert #4 -9
## Expert #5 -6
## Expert #6 -3
## Expert #7 1
## Expert #8 -5
## Expert #9 -3
## Expert #10 -3
## Executive officers & Engineers and/or technicians
## Expert #1 7
## Expert #2 7
## Expert #3 9
## Expert #4 -6
## Expert #5 -4
## Expert #6 6
## Expert #7 7
## Expert #8 7
## Expert #9 6
## Expert #10 -3
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 7 NA
## Expert #2 9 1
## Expert #3 9 1
## Expert #4 -4 -9
## Expert #5 1 -6
## Expert #6 7 -5
## Expert #7 7 -3
## Expert #8 8 -5
## Expert #9 7 -5
## Expert #10 4 -7
## Marketing analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 8
## Expert #3 5
## Expert #4 -6
## Expert #5 -6
## Expert #6 5
## Expert #7 7
## Expert #8 3
## Expert #9 5
## Expert #10 -6
## Marketing analysts & Designers
## Expert #1 NA
## Expert #2 8
## Expert #3 5
## Expert #4 -4
## Expert #5 -3
## Expert #6 7
## Expert #7 7
## Expert #8 5
## Expert #9 7
## Expert #10 7
## Finance analysts & Engineers and/or technicians
## Expert #1 NA
## Expert #2 8
## Expert #3 5
## Expert #4 6
## Expert #5 -4
## Expert #6 5
## Expert #7 9
## Expert #8 6
## Expert #9 5
## Expert #10 5
## Finance analysts & Designers
## Expert #1 7
## Expert #2 7
## Expert #3 5
## Expert #4 9
## Expert #5 1
## Expert #6 7
## Expert #7 9
## Expert #8 9
## Expert #9 7
## Expert #10 7
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 4
## Expert #3 1
## Expert #4 4
## Expert #5 5
## Expert #6 1
## Expert #7 1
## Expert #8 4
## Expert #9 1
## Expert #10 1executive_market <- c(NA,4,5,4,1,7,1,6,7,7)
executive_finance <- c(NA,-4,3,-7,-6,3,1,-2,3,3)
executive_engineer <- c(7,1,5,2,-6,6,1,2,6,6)
executive_designer <- c(NA,5,9,4,4,4,1,8,4,4)
market_finance <- c(NA,-6,1,-9,-8,-7,1,-3,-7,-7)
market_engineer <- c(7,1,-5,-7,-5,-3,1,-3,-3,4)
market_designer <- c(7,5,5,-4,1,3,1,1,3,3)
finance_engineer <- c(7,5,3,4,5,5,1,6,5,5)
finance_designer <- c(7,7,7,6,8,7,1,9,7,7)
engineer_designer <- c(1,3,5,4,4,2,1,6,2,2)
participatory_design <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(participatory_design) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(participatory_design) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
participatory_design## Executive officers & Marketing analysts
## Expert #1 NA
## Expert #2 4
## Expert #3 5
## Expert #4 4
## Expert #5 1
## Expert #6 7
## Expert #7 1
## Expert #8 6
## Expert #9 7
## Expert #10 7
## Executive officers & Finance analysts
## Expert #1 NA
## Expert #2 -4
## Expert #3 3
## Expert #4 -7
## Expert #5 -6
## Expert #6 3
## Expert #7 1
## Expert #8 -2
## Expert #9 3
## Expert #10 3
## Executive officers & Engineers and/or technicians
## Expert #1 7
## Expert #2 1
## Expert #3 5
## Expert #4 2
## Expert #5 -6
## Expert #6 6
## Expert #7 1
## Expert #8 2
## Expert #9 6
## Expert #10 6
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 NA NA
## Expert #2 5 -6
## Expert #3 9 1
## Expert #4 4 -9
## Expert #5 4 -8
## Expert #6 4 -7
## Expert #7 1 1
## Expert #8 8 -3
## Expert #9 4 -7
## Expert #10 4 -7
## Marketing analysts & Engineers and/or technicians
## Expert #1 7
## Expert #2 1
## Expert #3 -5
## Expert #4 -7
## Expert #5 -5
## Expert #6 -3
## Expert #7 1
## Expert #8 -3
## Expert #9 -3
## Expert #10 4
## Marketing analysts & Designers
## Expert #1 7
## Expert #2 5
## Expert #3 5
## Expert #4 -4
## Expert #5 1
## Expert #6 3
## Expert #7 1
## Expert #8 1
## Expert #9 3
## Expert #10 3
## Finance analysts & Engineers and/or technicians
## Expert #1 7
## Expert #2 5
## Expert #3 3
## Expert #4 4
## Expert #5 5
## Expert #6 5
## Expert #7 1
## Expert #8 6
## Expert #9 5
## Expert #10 5
## Finance analysts & Designers
## Expert #1 7
## Expert #2 7
## Expert #3 7
## Expert #4 6
## Expert #5 8
## Expert #6 7
## Expert #7 1
## Expert #8 9
## Expert #9 7
## Expert #10 7
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 3
## Expert #3 5
## Expert #4 4
## Expert #5 4
## Expert #6 2
## Expert #7 1
## Expert #8 6
## Expert #9 2
## Expert #10 2executive_market <- c(7,7,7,4,8,7,7,9,7,7)
executive_finance <- c(NA,-4,1,-9,-6,2,1,1,2,2)
executive_engineer <- c(7,-4,1,-7,7,6,3,3,6,6)
executive_designer <- c(7,3,8,-4,6,7,7,9,8,8)
market_finance <- c(1,-7,-7,-9,-7,-6,-7,-9,-6,-8)
market_engineer <- c(1,-5,-7,-8,1,3,1,-7,3,3)
market_designer <- c(NA,1,1,-5,1,5,1,1,5,5)
finance_engineer <- c(1,5,1,5,7,6,6,4,6,6)
finance_designer <- c(NA,5,9,7,7,7,6,9,7,7)
engineer_designer <- c(1,5,8,3,3,2,1,9,2,5)
cx_method <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(cx_method) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(cx_method) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
cx_method## Executive officers & Marketing analysts
## Expert #1 7
## Expert #2 7
## Expert #3 7
## Expert #4 4
## Expert #5 8
## Expert #6 7
## Expert #7 7
## Expert #8 9
## Expert #9 7
## Expert #10 7
## Executive officers & Finance analysts
## Expert #1 NA
## Expert #2 -4
## Expert #3 1
## Expert #4 -9
## Expert #5 -6
## Expert #6 2
## Expert #7 1
## Expert #8 1
## Expert #9 2
## Expert #10 2
## Executive officers & Engineers and/or technicians
## Expert #1 7
## Expert #2 -4
## Expert #3 1
## Expert #4 -7
## Expert #5 7
## Expert #6 6
## Expert #7 3
## Expert #8 3
## Expert #9 6
## Expert #10 6
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 7 1
## Expert #2 3 -7
## Expert #3 8 -7
## Expert #4 -4 -9
## Expert #5 6 -7
## Expert #6 7 -6
## Expert #7 7 -7
## Expert #8 9 -9
## Expert #9 8 -6
## Expert #10 8 -8
## Marketing analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 -5
## Expert #3 -7
## Expert #4 -8
## Expert #5 1
## Expert #6 3
## Expert #7 1
## Expert #8 -7
## Expert #9 3
## Expert #10 3
## Marketing analysts & Designers
## Expert #1 NA
## Expert #2 1
## Expert #3 1
## Expert #4 -5
## Expert #5 1
## Expert #6 5
## Expert #7 1
## Expert #8 1
## Expert #9 5
## Expert #10 5
## Finance analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 5
## Expert #3 1
## Expert #4 5
## Expert #5 7
## Expert #6 6
## Expert #7 6
## Expert #8 4
## Expert #9 6
## Expert #10 6
## Finance analysts & Designers
## Expert #1 NA
## Expert #2 5
## Expert #3 9
## Expert #4 7
## Expert #5 7
## Expert #6 7
## Expert #7 6
## Expert #8 9
## Expert #9 7
## Expert #10 7
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 5
## Expert #3 8
## Expert #4 3
## Expert #5 3
## Expert #6 2
## Expert #7 1
## Expert #8 9
## Expert #9 2
## Expert #10 5executive_market <- c(NA,5,4,6,5,5,1,-4,5,5)
executive_finance <- c(NA,-4,3,-9,-6,-5,1,-4,-5,-5)
executive_engineer <- c(7,4,3,-5,-5,-2,-3,4,-2,-2)
executive_designer <- c(7,6,7,-3,-3,-4,-3,6,-4,-4)
market_finance <- c(7,-6,-5,-9,-5,-3,NA,-3,-3,-3)
market_engineer <- c(7,-3,-5,-6,-3,-5,1,3,-5,-5)
market_designer <- c(7,1,5,-4,1,3,1,5,3,3)
finance_engineer <- c(NA,4,5,4,3,4,-3,5,4,4)
finance_designer <- c(NA,6,7,6,5,5,-3,9,5,5)
engineer_designer <- c(1,4,5,3,5,1,1,7,1,1)
idea_clustering <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(idea_clustering) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(idea_clustering) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
idea_clustering## Executive officers & Marketing analysts
## Expert #1 NA
## Expert #2 5
## Expert #3 4
## Expert #4 6
## Expert #5 5
## Expert #6 5
## Expert #7 1
## Expert #8 -4
## Expert #9 5
## Expert #10 5
## Executive officers & Finance analysts
## Expert #1 NA
## Expert #2 -4
## Expert #3 3
## Expert #4 -9
## Expert #5 -6
## Expert #6 -5
## Expert #7 1
## Expert #8 -4
## Expert #9 -5
## Expert #10 -5
## Executive officers & Engineers and/or technicians
## Expert #1 7
## Expert #2 4
## Expert #3 3
## Expert #4 -5
## Expert #5 -5
## Expert #6 -2
## Expert #7 -3
## Expert #8 4
## Expert #9 -2
## Expert #10 -2
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 7 7
## Expert #2 6 -6
## Expert #3 7 -5
## Expert #4 -3 -9
## Expert #5 -3 -5
## Expert #6 -4 -3
## Expert #7 -3 NA
## Expert #8 6 -3
## Expert #9 -4 -3
## Expert #10 -4 -3
## Marketing analysts & Engineers and/or technicians
## Expert #1 7
## Expert #2 -3
## Expert #3 -5
## Expert #4 -6
## Expert #5 -3
## Expert #6 -5
## Expert #7 1
## Expert #8 3
## Expert #9 -5
## Expert #10 -5
## Marketing analysts & Designers
## Expert #1 7
## Expert #2 1
## Expert #3 5
## Expert #4 -4
## Expert #5 1
## Expert #6 3
## Expert #7 1
## Expert #8 5
## Expert #9 3
## Expert #10 3
## Finance analysts & Engineers and/or technicians
## Expert #1 NA
## Expert #2 4
## Expert #3 5
## Expert #4 4
## Expert #5 3
## Expert #6 4
## Expert #7 -3
## Expert #8 5
## Expert #9 4
## Expert #10 4
## Finance analysts & Designers
## Expert #1 NA
## Expert #2 6
## Expert #3 7
## Expert #4 6
## Expert #5 5
## Expert #6 5
## Expert #7 -3
## Expert #8 9
## Expert #9 5
## Expert #10 5
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 4
## Expert #3 5
## Expert #4 3
## Expert #5 5
## Expert #6 1
## Expert #7 1
## Expert #8 7
## Expert #9 1
## Expert #10 1executive_market <- c(NA,-3,1,5,5,3,1,-5,3,3)
executive_finance <- c(NA,-3,2,-5,-4,2,1,-7,2,-4)
executive_engineer <- c(NA,6,9,5,8,8,3,9,8,8)
executive_designer <- c(1,8,9,7,7,9,9,9,9,9)
market_finance <- c(NA,-6,1,-9,-5,-3,1,-5,-3,-6)
market_engineer <- c(1,5,9,1,8,7,3,5,7,7)
market_designer <- c(1,7,9,3,8,8,9,8,8,8)
finance_engineer <- c(1,7,9,6,8,7,6,9,7,7)
finance_designer <- c(1,7,9,8,6,7,9,9,7,7)
engineer_designer <- c(1,4,1,3,-2,2,9,3,2,-2)
prototyping_method <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(prototyping_method) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(prototyping_method) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
prototyping_method## Executive officers & Marketing analysts
## Expert #1 NA
## Expert #2 -3
## Expert #3 1
## Expert #4 5
## Expert #5 5
## Expert #6 3
## Expert #7 1
## Expert #8 -5
## Expert #9 3
## Expert #10 3
## Executive officers & Finance analysts
## Expert #1 NA
## Expert #2 -3
## Expert #3 2
## Expert #4 -5
## Expert #5 -4
## Expert #6 2
## Expert #7 1
## Expert #8 -7
## Expert #9 2
## Expert #10 -4
## Executive officers & Engineers and/or technicians
## Expert #1 NA
## Expert #2 6
## Expert #3 9
## Expert #4 5
## Expert #5 8
## Expert #6 8
## Expert #7 3
## Expert #8 9
## Expert #9 8
## Expert #10 8
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 1 NA
## Expert #2 8 -6
## Expert #3 9 1
## Expert #4 7 -9
## Expert #5 7 -5
## Expert #6 9 -3
## Expert #7 9 1
## Expert #8 9 -5
## Expert #9 9 -3
## Expert #10 9 -6
## Marketing analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 5
## Expert #3 9
## Expert #4 1
## Expert #5 8
## Expert #6 7
## Expert #7 3
## Expert #8 5
## Expert #9 7
## Expert #10 7
## Marketing analysts & Designers
## Expert #1 1
## Expert #2 7
## Expert #3 9
## Expert #4 3
## Expert #5 8
## Expert #6 8
## Expert #7 9
## Expert #8 8
## Expert #9 8
## Expert #10 8
## Finance analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 7
## Expert #3 9
## Expert #4 6
## Expert #5 8
## Expert #6 7
## Expert #7 6
## Expert #8 9
## Expert #9 7
## Expert #10 7
## Finance analysts & Designers
## Expert #1 1
## Expert #2 7
## Expert #3 9
## Expert #4 8
## Expert #5 6
## Expert #6 7
## Expert #7 9
## Expert #8 9
## Expert #9 7
## Expert #10 7
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 4
## Expert #3 1
## Expert #4 3
## Expert #5 -2
## Expert #6 2
## Expert #7 9
## Expert #8 3
## Expert #9 2
## Expert #10 -2executive_market <- c(NA,-3,-3,-4,1,-2,-6,7,-2,3)
executive_finance <- c(NA,-6,-2,NA,-5,5,-3,1,5,-2)
executive_engineer <- c(8,-4,3,-3,1,8,1,3,8,8)
executive_designer <- c(8,5,NA,-3,4,7,-6,8,7,7)
market_finance <- c(8,-6,-3,-6,-6,3,1,-7,3,-4)
market_engineer <- c(8,-3,2,4,6,8,1,-7,8,8)
market_designer <- c(8,1,5,2,4,7,-3,5,7,7)
finance_engineer <- c(8,4,5,7,8,8,1,1,8,8)
finance_designer <- c(8,6,6,6,6,5,-3,7,5,5)
engineer_designer <- c(1,4,5,-2,-3,-5,-6,7,-5,-5)
operation_method <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(operation_method) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(operation_method) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
operation_method## Executive officers & Marketing analysts
## Expert #1 NA
## Expert #2 -3
## Expert #3 -3
## Expert #4 -4
## Expert #5 1
## Expert #6 -2
## Expert #7 -6
## Expert #8 7
## Expert #9 -2
## Expert #10 3
## Executive officers & Finance analysts
## Expert #1 NA
## Expert #2 -6
## Expert #3 -2
## Expert #4 NA
## Expert #5 -5
## Expert #6 5
## Expert #7 -3
## Expert #8 1
## Expert #9 5
## Expert #10 -2
## Executive officers & Engineers and/or technicians
## Expert #1 8
## Expert #2 -4
## Expert #3 3
## Expert #4 -3
## Expert #5 1
## Expert #6 8
## Expert #7 1
## Expert #8 3
## Expert #9 8
## Expert #10 8
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 8 8
## Expert #2 5 -6
## Expert #3 NA -3
## Expert #4 -3 -6
## Expert #5 4 -6
## Expert #6 7 3
## Expert #7 -6 1
## Expert #8 8 -7
## Expert #9 7 3
## Expert #10 7 -4
## Marketing analysts & Engineers and/or technicians
## Expert #1 8
## Expert #2 -3
## Expert #3 2
## Expert #4 4
## Expert #5 6
## Expert #6 8
## Expert #7 1
## Expert #8 -7
## Expert #9 8
## Expert #10 8
## Marketing analysts & Designers
## Expert #1 8
## Expert #2 1
## Expert #3 5
## Expert #4 2
## Expert #5 4
## Expert #6 7
## Expert #7 -3
## Expert #8 5
## Expert #9 7
## Expert #10 7
## Finance analysts & Engineers and/or technicians
## Expert #1 8
## Expert #2 4
## Expert #3 5
## Expert #4 7
## Expert #5 8
## Expert #6 8
## Expert #7 1
## Expert #8 1
## Expert #9 8
## Expert #10 8
## Finance analysts & Designers
## Expert #1 8
## Expert #2 6
## Expert #3 6
## Expert #4 6
## Expert #5 6
## Expert #6 5
## Expert #7 -3
## Expert #8 7
## Expert #9 5
## Expert #10 5
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 4
## Expert #3 5
## Expert #4 -2
## Expert #5 -3
## Expert #6 -5
## Expert #7 -6
## Expert #8 7
## Expert #9 -5
## Expert #10 -5executive_market <- c(1,-7,-8,-7,1,3,-6,8,3,3)
executive_finance <- c(1,-3,5,-7,1,7,1,9,7,7)
executive_engineer <- c(1,-6,-9,-2,-8,-6,-3,-4,-6,-6)
executive_designer <- c(NA,-6,-6,-5,-6,-5,1,2,-5,-5)
market_finance <- c(NA,4,7,1,3,4,4,4,4,4)
market_engineer <- c(1,-4,-4,7,-6,-4,-3,-6,-4,-4)
market_designer <- c(NA,1,-3,4,-4,-5,1,-5,-5,-5)
finance_engineer <- c(1,-4,-5,8,-7,-6,1,-9,-6,-6)
finance_designer <- c(NA,-4,-6,5,-5,-5,6,-8,-5,-5)
engineer_designer <- c(1,3,5,-5,4,3,6,4,3,3)
business_analytics <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(business_analytics) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(business_analytics) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
business_analytics## Executive officers & Marketing analysts
## Expert #1 1
## Expert #2 -7
## Expert #3 -8
## Expert #4 -7
## Expert #5 1
## Expert #6 3
## Expert #7 -6
## Expert #8 8
## Expert #9 3
## Expert #10 3
## Executive officers & Finance analysts
## Expert #1 1
## Expert #2 -3
## Expert #3 5
## Expert #4 -7
## Expert #5 1
## Expert #6 7
## Expert #7 1
## Expert #8 9
## Expert #9 7
## Expert #10 7
## Executive officers & Engineers and/or technicians
## Expert #1 1
## Expert #2 -6
## Expert #3 -9
## Expert #4 -2
## Expert #5 -8
## Expert #6 -6
## Expert #7 -3
## Expert #8 -4
## Expert #9 -6
## Expert #10 -6
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 NA NA
## Expert #2 -6 4
## Expert #3 -6 7
## Expert #4 -5 1
## Expert #5 -6 3
## Expert #6 -5 4
## Expert #7 1 4
## Expert #8 2 4
## Expert #9 -5 4
## Expert #10 -5 4
## Marketing analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 -4
## Expert #3 -4
## Expert #4 7
## Expert #5 -6
## Expert #6 -4
## Expert #7 -3
## Expert #8 -6
## Expert #9 -4
## Expert #10 -4
## Marketing analysts & Designers
## Expert #1 NA
## Expert #2 1
## Expert #3 -3
## Expert #4 4
## Expert #5 -4
## Expert #6 -5
## Expert #7 1
## Expert #8 -5
## Expert #9 -5
## Expert #10 -5
## Finance analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 -4
## Expert #3 -5
## Expert #4 8
## Expert #5 -7
## Expert #6 -6
## Expert #7 1
## Expert #8 -9
## Expert #9 -6
## Expert #10 -6
## Finance analysts & Designers
## Expert #1 NA
## Expert #2 -4
## Expert #3 -6
## Expert #4 5
## Expert #5 -5
## Expert #6 -5
## Expert #7 6
## Expert #8 -8
## Expert #9 -5
## Expert #10 -5
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 3
## Expert #3 5
## Expert #4 -5
## Expert #5 4
## Expert #6 3
## Expert #7 6
## Expert #8 4
## Expert #9 3
## Expert #10 3executive_market <- c(NA,-4,-3,-7,4,-2,1,-4,-2,-3)
executive_finance <- c(NA,-4,-3,-7,-5,2,1,-4,2,-4)
executive_engineer <- c(1,5,9,4,4,9,6,9,9,9)
executive_designer <- c(NA,4,7,-3,7,7,1,7,7,7)
market_finance <- c(NA,1,-3,1,-5,3,-3,1,3,3)
market_engineer <- c(1,7,9,9,1,9,6,9,9,9)
market_designer <- c(NA,5,9,6,1,7,3,6,7,7)
finance_engineer <- c(1,8,9,9,6,9,9,9,9,9)
finance_designer <- c(NA,4,9,6,4,4,3,7,4,4)
engineer_designer <- c(1,-6,-8,-5,1,-6,-6,-7,-6,-6)
engineer_method <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(engineer_method) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(engineer_method) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
engineer_method## Executive officers & Marketing analysts
## Expert #1 NA
## Expert #2 -4
## Expert #3 -3
## Expert #4 -7
## Expert #5 4
## Expert #6 -2
## Expert #7 1
## Expert #8 -4
## Expert #9 -2
## Expert #10 -3
## Executive officers & Finance analysts
## Expert #1 NA
## Expert #2 -4
## Expert #3 -3
## Expert #4 -7
## Expert #5 -5
## Expert #6 2
## Expert #7 1
## Expert #8 -4
## Expert #9 2
## Expert #10 -4
## Executive officers & Engineers and/or technicians
## Expert #1 1
## Expert #2 5
## Expert #3 9
## Expert #4 4
## Expert #5 4
## Expert #6 9
## Expert #7 6
## Expert #8 9
## Expert #9 9
## Expert #10 9
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 NA NA
## Expert #2 4 1
## Expert #3 7 -3
## Expert #4 -3 1
## Expert #5 7 -5
## Expert #6 7 3
## Expert #7 1 -3
## Expert #8 7 1
## Expert #9 7 3
## Expert #10 7 3
## Marketing analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 7
## Expert #3 9
## Expert #4 9
## Expert #5 1
## Expert #6 9
## Expert #7 6
## Expert #8 9
## Expert #9 9
## Expert #10 9
## Marketing analysts & Designers
## Expert #1 NA
## Expert #2 5
## Expert #3 9
## Expert #4 6
## Expert #5 1
## Expert #6 7
## Expert #7 3
## Expert #8 6
## Expert #9 7
## Expert #10 7
## Finance analysts & Engineers and/or technicians
## Expert #1 1
## Expert #2 8
## Expert #3 9
## Expert #4 9
## Expert #5 6
## Expert #6 9
## Expert #7 9
## Expert #8 9
## Expert #9 9
## Expert #10 9
## Finance analysts & Designers
## Expert #1 NA
## Expert #2 4
## Expert #3 9
## Expert #4 6
## Expert #5 4
## Expert #6 4
## Expert #7 3
## Expert #8 7
## Expert #9 4
## Expert #10 4
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 -6
## Expert #3 -8
## Expert #4 -5
## Expert #5 1
## Expert #6 -6
## Expert #7 -6
## Expert #8 -7
## Expert #9 -6
## Expert #10 -6executive_market <- c(NA,4,5,6,5,5,3,9,5,5)
executive_finance <- c(NA,-4,1,-4,-5,3,-3,7,3,3)
executive_engineer <- c(NA,-3,5,4,1,-4,3,8,-4,-4)
executive_designer <- c(7,3,9,7,1,6,-6,8,6,6)
market_finance <- c(NA,-6,-9,-6,-5,-3,-3,-3,-3,-3)
market_engineer <- c(7,-3,5,-4,1,-6,3,-8,-6,-6)
market_designer <- c(7,1,5,2,-3,4,1,-6,4,4)
finance_engineer <- c(7,3,7,4,4,-4,3,-8,-4,-4)
finance_designer <- c(1,6,9,8,6,-2,1,-6,-2,-2)
engineer_designer <- c(1,4,5,3,1,4,-6,6,4,4)
evaluation_method <- data.frame(executive_market, executive_finance,
executive_engineer,executive_designer, market_finance,
market_engineer, market_designer, finance_engineer,
finance_designer, engineer_designer)
colnames(evaluation_method) <- c("Executive officers & Marketing analysts" , "Executive officers & Finance analysts" ,
"Executive officers & Engineers and/or technicians" , "Executive officers & Designers",
"Marketing analysts & Finance analysts", "Marketing analysts & Engineers and/or technicians",
"Marketing analysts & Designers", "Finance analysts & Engineers and/or technicians",
"Finance analysts & Designers", "Engineers and/or technicians & Designers")
rownames(evaluation_method) <- c("Expert #1", "Expert #2" , "Expert #3" , "Expert #4" ,"Expert #5",
"Expert #6", "Expert #7" , "Expert #8" , "Expert #9" ,
"Expert #10")
evaluation_method## Executive officers & Marketing analysts
## Expert #1 NA
## Expert #2 4
## Expert #3 5
## Expert #4 6
## Expert #5 5
## Expert #6 5
## Expert #7 3
## Expert #8 9
## Expert #9 5
## Expert #10 5
## Executive officers & Finance analysts
## Expert #1 NA
## Expert #2 -4
## Expert #3 1
## Expert #4 -4
## Expert #5 -5
## Expert #6 3
## Expert #7 -3
## Expert #8 7
## Expert #9 3
## Expert #10 3
## Executive officers & Engineers and/or technicians
## Expert #1 NA
## Expert #2 -3
## Expert #3 5
## Expert #4 4
## Expert #5 1
## Expert #6 -4
## Expert #7 3
## Expert #8 8
## Expert #9 -4
## Expert #10 -4
## Executive officers & Designers Marketing analysts & Finance analysts
## Expert #1 7 NA
## Expert #2 3 -6
## Expert #3 9 -9
## Expert #4 7 -6
## Expert #5 1 -5
## Expert #6 6 -3
## Expert #7 -6 -3
## Expert #8 8 -3
## Expert #9 6 -3
## Expert #10 6 -3
## Marketing analysts & Engineers and/or technicians
## Expert #1 7
## Expert #2 -3
## Expert #3 5
## Expert #4 -4
## Expert #5 1
## Expert #6 -6
## Expert #7 3
## Expert #8 -8
## Expert #9 -6
## Expert #10 -6
## Marketing analysts & Designers
## Expert #1 7
## Expert #2 1
## Expert #3 5
## Expert #4 2
## Expert #5 -3
## Expert #6 4
## Expert #7 1
## Expert #8 -6
## Expert #9 4
## Expert #10 4
## Finance analysts & Engineers and/or technicians
## Expert #1 7
## Expert #2 3
## Expert #3 7
## Expert #4 4
## Expert #5 4
## Expert #6 -4
## Expert #7 3
## Expert #8 -8
## Expert #9 -4
## Expert #10 -4
## Finance analysts & Designers
## Expert #1 1
## Expert #2 6
## Expert #3 9
## Expert #4 8
## Expert #5 6
## Expert #6 -2
## Expert #7 1
## Expert #8 -6
## Expert #9 -2
## Expert #10 -2
## Engineers and/or technicians & Designers
## Expert #1 1
## Expert #2 4
## Expert #3 5
## Expert #4 3
## Expert #5 1
## Expert #6 4
## Expert #7 -6
## Expert #8 6
## Expert #9 4
## Expert #10 4library(kableExtra)
atts <- c("executive", "market", "finance", "engineer", "designer")
Idea_exploration <- idea_exploration %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
Participatory_design <- participatory_design %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
CX_centered_method <- cx_method %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
Idea_clustering <- idea_clustering %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
Prototyping_method <- prototyping_method %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
Operation_centered_method <- operation_method %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
Business_analytics <- business_analytics %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
Engineering_method <- engineer_method %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
Evaluation_method <- evaluation_method %>%
ahp.mat(atts = atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T) %>%
ahp.aggpref(atts, method = "arithmetic")
importance_weights <- data.frame(Idea_exploration, Participatory_design, CX_centered_method,Idea_clustering ,
Prototyping_method, Operation_centered_method, Business_analytics,Engineering_method, Evaluation_method)
colnames(importance_weights) <- c("Idea exploration","Participatory design", "CX-centered methods", "Idea clustering",
"Prototyping methods","Operations-centered methods", "Business analytics", " Engineering methods","Evaluation methods")
rownames(importance_weights) <- c("Executive officers", "Marketing analysts" , "Finance analysts" , "Engineers and/or technicians" , "Designers")
importance_weights %>% mutate_if(is.numeric, round, digits=3)## Idea exploration Participatory design
## Executive officers 0.133 0.099
## Marketing analysts 0.170 0.256
## Finance analysts 0.063 0.069
## Engineers and/or technicians 0.257 0.194
## Designers 0.377 0.382
## CX-centered methods Idea clustering
## Executive officers 0.079 0.190
## Marketing analysts 0.307 0.274
## Finance analysts 0.064 0.097
## Engineers and/or technicians 0.183 0.143
## Designers 0.366 0.296
## Prototyping methods Operations-centered methods
## Executive officers 0.100 0.169
## Marketing analysts 0.105 0.120
## Finance analysts 0.054 0.074
## Engineers and/or technicians 0.308 0.329
## Designers 0.434 0.308
## Business analytics Engineering methods
## Executive officers 0.260 0.128
## Marketing analysts 0.172 0.076
## Finance analysts 0.353 0.059
## Engineers and/or technicians 0.090 0.501
## Designers 0.125 0.237
## Evaluation methods
## Executive officers 0.102
## Marketing analysts 0.282
## Finance analysts 0.144
## Engineers and/or technicians 0.169
## Designers 0.303atts <- c("executive", "market", "finance", "engineer", "designer")
filling.idea_exploration <- idea_exploration %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_ie <- filling.idea_exploration %>% ahp.cr(atts)
filling.participatory_design <- participatory_design %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_pd <- filling.participatory_design %>% ahp.cr(atts)
filling.cx_method <- cx_method %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_cx <- filling.cx_method %>% ahp.cr(atts)
filling.idea_clustering <- idea_clustering %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_ic <- filling.idea_clustering %>% ahp.cr(atts)
filling.prototyping_method <- prototyping_method %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_pm <- filling.prototyping_method %>% ahp.cr(atts)
filling.operation_method <- operation_method %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_om <- filling.operation_method %>% ahp.cr(atts)
filling.business_analytics <- business_analytics %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_ba <- filling.business_analytics %>% ahp.cr(atts)
filling.engineer_method <- engineer_method %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_em <- filling.engineer_method %>% ahp.cr(atts)
filling.evaluation_method <- evaluation_method %>%
ahp.mat(atts, negconvert = TRUE) %>%
ahp.missing(atts, round = T, limit = T)
cr_ev <- filling.evaluation_method %>% ahp.cr(atts)
cr.value <- c(round(mean(cr_ie),2), round(mean(cr_pd),2),round(mean(cr_cx),2),
round(mean(cr_ic),2),
round(mean(cr_pm),2),round(mean(cr_om),2),
round(mean(cr_ba),2),round(mean(cr_em),2),round(mean(cr_ev),2))
design_method <- c("Idea exploration","Participatory design", "CX-centered methods", "Idea clustering",
"Prototyping methods","Operations-centered methods", "Business analytics", " Engineering methods","Evaluation methods")
cr.frame <- data.frame(design_method, cr.value)
colnames(cr.frame) <- c("Evaluated skill sets", "Consistency Ratio")
cr.frame## Evaluated skill sets Consistency Ratio
## 1 Idea exploration 0.16
## 2 Participatory design 0.10
## 3 CX-centered methods 0.08
## 4 Idea clustering 0.20
## 5 Prototyping methods 0.11
## 6 Operations-centered methods 0.12
## 7 Business analytics 0.13
## 8 Engineering methods 0.11
## 9 Evaluation methods 0.17