YT YouTube2Text

YouTube2Text → Transcripts → Comparative Scaling Techniques

Comparative Scaling Techniques — Transcript

by MCO-3 [RM&SA] · 4,186 words · 744 segments · language en · Watch on YouTube

Open in transcriber Summarize with AI Download SRT/VTT

Full transcript

0:00[Music]
0:08[Music]
0:14hello learners i
0:15am dr sabot k sharwani working with inda
0:17gandhi national open university in
0:18school of management studies
0:20the topic which i am going to talk today
0:22is comparative scaling techniques
0:24prior to going into the depth of this
0:25topic i just want to throw a light
0:27that this is part of our course called
0:29research methodology and statistical
0:30analysis
0:32which is a second year m.com course and
0:34we are here with
0:36somewhere around you know 13 to 14
0:38lectures and we have already covered you
0:40know
0:41the varieties of topic which we will
0:43recapitulate in the coming years
0:44prior to going into the depth of this
0:46topic i just want to throw a light
0:48that what exactly this competitive
0:51analysis is the if we if we talk about
0:54the data i think data is
0:56is something which consists of
0:58quantitative variables like price income
1:00sales and qualitative variables like
1:01knowledge performance and character
1:03the qualitative information must be
1:05converted into numerical form
1:07further analysis this is possible
1:09through measurement scaling techniques
1:11so when we are going to talk about this
1:13competitive scaling techniques i think
1:15this is part over the scaling techniques
1:17and and
1:19if you if you go more into the depth of
1:21the scaling techniques
1:22you know preceding session which was
1:23talking about you know the measurement
1:26there we have talk about you know how
1:28important the scaling technique is
1:29because we have
1:30we have covered you know the portion
1:32called measurement
1:33and we have covered inside it ordinal
1:36ratio
1:36and some other parts but here we are
1:39going to talk about the screen
1:40techniques which is going to be
1:42bifurcating to competitive
1:43scaling techniques and non-competitive
1:45scaling techniques so
1:47so this is the if we if we talk about
1:49the scaling techniques
1:50this is talking about the placing
1:52respondents in continuation of gradual
1:54change
1:55in the pre-assigned values symbols or
1:57numbers based on the features of
1:58particular object as per the defined
2:00rules
2:01so what we have observed that you know
2:04that in our preceding sessions if you go
2:06into the backdrop you will find out we
2:07have a dedicated sessions
2:09which was talking on the measurement so
2:11measurement is the process of observing
2:13and recording the observations
2:14that are collected as part of research
2:17the recording of the observation may be
2:18in terms of numbers
2:19or other symbols to characteristics of
2:22objects
2:23according to certain prescribed rules
2:25the respondents characteristics are
2:26feeling attitude
2:28opinions etc the most important aspect
2:30of measurement is the
2:31specification of rules for assigning
2:33numbers to characteristics
2:35the rules for assigning numbers should
2:37be standardized and applied uniformly
2:39so uniformity and this how you are going
2:43to
2:43make a standard that is very important
2:45and this must not change over time or
2:47object so
2:49this is what exactly you know the
2:50measurement is so in our preceding
2:52sessions if you see we have
2:54we have elaborately talked about you
2:55know when we were discussing about
2:56measurement and scaling techniques
2:58we have exclusively talked about the
3:00measurement but
3:01since here we are talking about the
3:03scaling technique so scaling is the
3:04assignment of objects
3:06to numbers or semantic according to a
3:08rule in scaling the objects are text
3:10statements
3:11usually statements of attitude opinion
3:13or feeling
3:14so in this measurement we have already
3:16covered you know the primary scale
3:18which was bifurcated to four important
3:19gradients nominal ordinal
3:21interval ratio nominal is lowest level
3:23of measurement we have already talked
3:25about in our preceding sessions
3:26and ratio scale is highest level of
3:28measurement if you see this particular
3:30circle i think this circle is quite
3:32explanatory in nature that if you talk
3:36about you know the ratio scale which is
3:38quite elaborative and it is considered
3:40as a big circle whereas
3:41interval ordinary nominal which are part
3:43of that circle and
3:44it's gradually you know going down and
3:46down so anyway
3:48prior to going into the depth of this
3:50scaling techniques
3:52and you know that too uh you know
3:54revolves around your competitive scaling
3:56techniques
3:56i just want to throw a light what
3:58exactly we have covered in our preceding
3:59sessions
4:00so uh this this particular course is
4:03recent methodology in statistical
4:05analysis
4:06and we are in this first block that is
4:08research and data collections
4:10and there are some uh four some more
4:12four blocks
4:13that is processing and preservation of
4:15data relational and trend analysis
4:17probability hypothesis testing
4:19interpretation reporting
4:21so as far as this particular block is
4:23concerned the first block is concerned
4:24which is talking about you know
4:26introduction to business research
4:28research plan collection of data
4:29sampling measurement and scaling
4:31techniques so
4:32we are here in this unit five that is
4:34chapter five
4:35which is more talking about you know the
4:37measurement which is talking about the
4:38scaling techniques
4:39on the other hand is talking about you
4:41know the types of screen techniques like
4:43competitive scaling techniques and
4:45non-competitive screen techniques so
4:47now again we are going to talk about you
4:48know the scaling techniques and this
4:50scaling techniques is
4:51bifurcated into competitive skills and
4:53non-competitive skills
4:54so as far as non competitive scale is
4:57concerned this we are going to cover in
4:58our
4:59next session whereas competitive scale
5:01is going to covered by us in this
5:02procedure in this present session so
5:04this comparative skills is more talking
5:06about you know the period comparison
5:09sum rank order and q sort so
5:12we are here with this competitive
5:14scaling and if we go more into the depth
5:16of this competitive scale
5:18competitive scale is is a measurement
5:20which is based on the comparison between
5:22objects whereas non-competitive scaling
5:24is
5:25is a measurement is based on individual
5:28assessment of each of the objects
5:30so what we observe that this scaling
5:32technique is purely bifurcated into
5:34comparative and non-comparative and
5:36competitive skills involves the diet
5:38comparison of stimulus objects whereas
5:40comparative scale data must be
5:42interpreted in relative manners
5:44and have only ordinal or rank order
5:46properties i think
5:47in our previous discussion we have seen
5:50that how this
5:51rank ordinal nominal and
5:54and other you know the skills are taken
5:56care and how this competitive skills
5:58revolves around the ordinal or
6:00rank order properties so ah
6:03and on this non-competitive scale is a
6:06object which is scaled independently and
6:07which we are going to take care in our
6:09next session so now we are going to
6:12talking about more talking about you
6:13know the comparative scale techniques
6:15a competitive scale is an ordinal rank
6:17order scale
6:18that can also be referred to as a non
6:21metric
6:22scale so this is purely a non-metric
6:24scale and respondents evaluate two or
6:26more objects at one time
6:28and objects are directly compared with
6:30one another as part of the
6:32measuring process so what we are going
6:34to do when we are floating our question
6:35is to the respondents
6:37and respondents are the one who who
6:38reciprocates with their answers
6:40so these respondents are are able to
6:42evaluate on two or more objects at one
6:44time and objects are directly compared
6:46with one another
6:47as part of the measuring process so this
6:49is you know
6:53analysis as far as the advantages of
6:55competitive scale is concerned
6:57it more talks about you know the small
6:58difference between stimulus objects can
7:00be detected
7:01and same known reference points for all
7:03respondents
7:04so this we have seen easily understood
7:06and can be applied
7:08involve fewer theoretical assumptions
7:10tend to
7:11reduce hello or carry over effects from
7:13one judgment to
7:14another judgment these are some of the
7:16advantages of competitive skills
7:18and if you go more into depth of this
7:19types of competitive skill techniques i
7:21think
7:22this is again bifurcated into four types
7:25which are you know quite general in
7:26nature and quite generic in nature and
7:28they are used
7:29you know with the with the change of
7:30time so paired comparison is there then
7:32rank order is there then constant sum is
7:35there then q sort is there
7:37if you are if you are more talking about
7:39you know this paired comparison
7:41it is nothing but compare between the
7:43two objects when you take two objects
7:44and you are comparing
7:45you are just pairing it we will take
7:47some good examples which are going to
7:50distinguish or you know which are going
7:52to explain elaborately about this pair
7:54comparison
7:55then you have rank order so rank order
7:57is rank more than two objects
7:58how you're going to give ratings to that
8:00how are going to give ranks to that
8:02first rank second rank third rank and so
8:03on so
8:05constant sum is nothing but how you're
8:07going to allocate a given number of
8:08points that is example given 100 to
8:10several objects so this is constant
8:12somewhere given number of point is
8:14hundred
8:15so now q sort is systematic study of
8:17participant viewpoints
8:19so what we have observed that these are
8:22the four important competitive scale
8:23techniques
8:24and if we go elaborately more into the
8:27depth of this competitive skill
8:28techniques i think the first one is the
8:29period comparison so
8:31period comparison is an activity for
8:33evaluating a small range of options
8:36by comparing them against each other so
8:39this is you know something which is
8:43considered to be a small range it is
8:45useful and easy technique for rating
8:47and ranking which i have already talked
8:48about alternatives we are the evaluation
8:50criteria
8:51and are subject by nature so what we
8:54observe that you know respondent is
8:55presented with two objects at a time
8:57so then ask to select one object in the
8:59pair according to
9:00some criteria we will take some some
9:02examples some real life scenarios which
9:04can
9:04definitely defend this particular
9:06comparison and data obtained are ordinal
9:08in nature
9:09so already we have talked about you know
9:11ordinal ratio
9:13and so these are these considered to be
9:15the ordinary nature
9:16and arranged or ranked in order of
9:18magnitude so
9:20you are going to give them the ranking
9:22in the order of you know the magnitude
9:24easy to do if
9:24only a few items are compared if numbers
9:27of comparisons too large respondents may
9:28become fatigue and no longer careful
9:31discrimination among them can be
9:33governed so
9:34what i mean to say that when you are
9:36going to talk about even the paired
9:37comparison i think
9:38this player comparison can be very well
9:40explained if you see this particular
9:41image
9:42i think we have got you know the four
9:45four persons a b c and d and you see how
9:48a is linked with b how a is linked with
9:51c
9:52how a can be linked paired with d or b
9:55can be paired with
9:56c or b can be paired with d so lot of
9:58you know permutation combination is
10:00there
10:00which can which can give you the glimpse
10:02about that how the paired
10:04comparison can be done so this is
10:07a comparative scale technique in which a
10:09respondent is presented with two objects
10:11at a time
10:12and asked to select one object according
10:14to some criteria so this is what exactly
10:17you know the period comparison scale is
10:19and the data obtained are ordinal in
10:21nature i have already talked about
10:23there are four types of cold ring this
10:24is one of the example which we are going
10:26to take here
10:26which can definitely you know give a
10:28glimpse about what exactly the paired
10:29comparison scale is
10:31and like you know the we have taken you
10:34some
10:34some some brands or the
10:38the product of that particular brand
10:39like cope pepsin sprite and lemka
10:41the respondents can prefer pepsi to coke
10:43or coke to sprite we have seen that you
10:46know how the
10:47how the brand coke pepsin sprites are
10:49there so coke
10:50if co pepsi pairing is there then coke
10:54is a brand and pepsi is one of the
10:56peering links so what we have seen that
10:58from the image that it is having you
11:00know one
11:01one point over there so like you know
11:03the there is no relation between pepsi
11:05with any of the other thing
11:07so pepsi then sprite and pepsi is there
11:10then now the number of times preferred
11:12is what that
11:13two cokes three pepsi and one sprite so
11:16this is the way by which we can paired
11:18and and if you talk about you know the
11:20competitive skill technique vis-a-vis
11:21you know the paired comparison scale
11:23a respondent is presented with two
11:25objects and asked to select one
11:26according to
11:27some criteria the data obtainer ordinal
11:29in nature
11:30paired comparison scale is the most
11:32widely used comparative scaling
11:34techniques
11:35with n brand that is n n minus 1
11:39divided by 2 this is considered to be
11:40the period comparison are required
11:42under the assumption of transitivity it
11:44is possible to convert paired
11:46comparison data to a rank order so
11:49now they are certainly stumbling blocks
11:51you know when you are you know going for
11:52the period order i think
11:54its really cumbersome when you know the
11:56data is quite large
11:58so in that case you know you are going
11:59to apply the rank order so rank order
12:01scale gives the respondent
12:02a set of items and ask them to put the
12:05items in some form of
12:07utter so so there are certain orders
12:10in which you know this form is going to
12:11be put
12:13and the measure of order can conclude as
12:15a preference importance like liking
12:17effectiveness and so on and the order is
12:20often a simple
12:21ordinal structure a is higher than b so
12:24one two and three could be the rank
12:25order which is going to be done and if
12:27you see this particular image i think
12:29we have seen that you know the rank is
12:31given on the basis of the choices
12:33like the first choice is family and
12:35friends distribution
12:36so it is coming you know on the basis of
12:38the score and
12:39score is seven so the which is highest
12:42and
12:42the lowest is uh is uh three
12:45so what we observe that you know when
12:47anybody get a choice to
12:49give priority as for the order is
12:52concerned you know the for
12:53the family and friends all are given you
12:55know the first
12:56rank because due to the seven score
12:59health is given a second rank due to
13:01sixth score purpose is given you know
13:03the third rank
13:04due to you know the third score and
13:06freedom is given you know again the
13:08third
13:09so money uh money is given nothing so
13:12that's why it is
13:13is at the fifth rank so what i mean to
13:16say
13:16that you know rank order is you know
13:19there are varieties of examples by which
13:21we can quote that this is considered to
13:22be the rank order so
13:24six flags magic mountain these are you
13:27know
13:27the amusement parks where people used to
13:29visit and they
13:30and on the weighted score you know the
13:32ranking need to be done 29 percent got a
13:35first rank
13:3620 percent hasher park got second rank
13:38walt disney world got some
13:40uh caught 17 percent so third rank and
13:42like that you know the kings island nine
13:44percent so what i mean to say
13:46based on the total respondents and you
13:48know on the basis of that the rank order
13:50need to be done
13:51so this is you know the second example
13:53as far as you know the competitive scale
13:54technique is concerned
13:55now 1.3 is the constant sum scale
14:00which is the third way of of you know
14:03types of scaling techniques type of
14:05competitive scaling techniques rather we
14:06can say a constant some skills a type of
14:09question
14:09used in market research this is
14:11exclusively used in market research
14:13survey in which respondents are required
14:15to divide a specific number of points
14:17or percents as part of a total sum
14:20so the allocation of points are divided
14:23to detail the variance and weight of
14:24each category so this is
14:26basically a constant sum scale where
14:28where you know them
14:29it is massively used in you know the
14:31market research survey and the
14:33and the very good example you know which
14:34i have which i have taken over here that
14:36that there are four marketing professors
14:39as well as three aspects
14:40that students typically find important
14:43for each aspects you know
14:45one has to assign number that reflects
14:47how well you believe each instructor
14:48performs
14:49on the aspects higher number represent
14:52higher scores
14:53the total of the instructor scores on an
14:55aspect should equal
14:56100. so what we have observed that
14:58instructor one is
14:59uh availability 30 percent fairness 35
15:02easy test is
15:0325 so this is this comes to 65
15:06plus uh 70 to 90 so instructor one has
15:10scored you know the 90
15:12marks out of 100 so this is considered
15:15to be the constant sum scale where three
15:17parameters are taken care
15:18availability fairness and easy test and
15:21structure is going to be monitored or
15:23you know
15:23evaluated on the basis of these three
15:26parameters so instructor 2
15:28again you know is based on availability
15:31fairness and easy test
15:33instructor 3 have scored in 25 25 25
15:36which comes with 75
15:38instructor 4 is getting you know
15:41somewhere around 55 so
15:43some out of this you know some total is
15:44100 so instructor 1
15:46have scored you know somewhere around
15:48which i was talking about 90
15:50and others have got less so this
15:53constant some school is somewhat
15:54moving in that direction so now divide
15:57hundred points having the following
15:58characteristics and you will find out
16:00that relative importance of
16:01characteristics is coming up so style is
16:0350
16:04right is 10 economical is 35 is five
16:07friendly dealer is hundred so
16:09this is you know the model so out of
16:11hundred you know
16:12[Music]
16:14somebody has scored this so what i mean
16:17to say the constant some scale helps
16:19researchers to discover properties
16:21the participants allocates point to more
16:23than one attribute
16:25or property indicant such that the total
16:29constant sum usually 100 or 10. so
16:32participant precision patients suffer
16:34when too many stimuli are proportioned
16:36and summed
16:37so there must be certain model where you
16:40know
16:41where we have to uh avoid you know the
16:44too many stimuli
16:45because if the parameters are three four
16:48or five
16:48i think it's better to judge otherwise
16:50you know the big issue will come up
16:52so participant ability to add may also
16:55be
16:55taxed and advantages compatibility with
16:59present and the fact that
17:00alternatives that are perceived to be
17:02equal can be scored
17:03so the scale produces interval data i
17:06think
17:07this is uh one of the best way of of
17:11judging it and now the fourth one is you
17:13know the q sort scaling so if you talk
17:15about you know the q
17:16sort scaling this is another technique
17:18as for scaling technique which
17:20revolves around the competitive scale
17:22techniques and
17:23based on you know the respondents and
17:25the q sort technique and q
17:27factor analysis so respondents are asked
17:29to sort the presented objects into piles
17:32based on similarity according to a
17:34specified criterion such as preference
17:36attitude perception etc so respondents
17:39are correlated
17:40instead of items the focus here is we
17:43need to know
17:44the human subjectivity related to the
17:46concept under consideration for
17:48study so q saw technique is mainly used
17:51for small groups or individuals
17:53q factor analysis reduces many
17:55individual viewpoints
17:57of the subjects to a few factors which
17:59claim to represent shared ways of
18:01thinking so what we have observed that
18:03you know
18:05as far as you know the comparison
18:06between the other skilling techniques
18:08so this q sword methodology works
18:14and follow certain steps like definition
18:16of the concourse
18:18development of the queue sample
18:20selection of the pset
18:21queue sorting analysis and
18:23interpretation
18:24and what we observe that you know when
18:26you talk about you know the q sort of
18:27scaling techniques
18:28it is comparative scaling technique that
18:30is very true because it is one of the
18:32fourth way of of you know the scaling
18:34techniques
18:35which revolves around the competitive
18:37screen techniques and queue sorting is a
18:38technical means whereby data are
18:40obtained
18:41for factoring and is the qualitative
18:43data collection techniques in queue
18:44methodology
18:45so queue sorting requires the
18:47participants to sort statements about a
18:49topic
18:50along a specific dimension such as how
18:52relevant
18:53how interesting or how pleasing the
18:55statements are generally in the presence
18:57of the researcher
18:58so q techniques uses rank order
19:00procedure for piles or group of the
19:02objects so now what we observe that if
19:05you go and see this
19:06the image of of you know how this q sort
19:09scaling can be governed or it's looked
19:10like i think
19:11we have left is the most disagreement
19:15and right is the most agreement
19:17so what we have seen that that
19:20if somebody had scored plus six i think
19:22in most agreed so he had
19:24given you know the weightage to this
19:25particular thing so
19:27on the other hand if you are most
19:28disagreed you can six so
19:30from from zero to minus six and from
19:34zero to plus six so most agreement is
19:36zero two plus six
19:37and most this agreement zero to minus
19:39six so
19:40this is all about you know this
19:42comparative scale technique and
19:44we have elaborately talked about you
19:45know the competitive scaling techniques
19:47and we know that
19:48how important the measurement and how
19:49important the scaling technique is
19:51when we are going to talk about you know
19:53the measurement we see that measurement
19:55is
19:55is is is the way of doing the things
19:58it's provide you know
20:00like you know you can measure in in
20:01terms in certain in kilometers or in
20:04inches or in but there are certain
20:06techniques there are certain scaling
20:08techniques which can
20:09navigate you know the researchers to to
20:12scale the things because the data
20:14we have already talked about and we have
20:16start our discussion with the data we
20:17know that
20:18data is quite gigantic right now and if
20:20data size is quite gigantic what will
20:23happen
20:23that that you are not in a position to
20:26apply
20:27the certain tools so the scaling
20:29techniques is
20:30is up to some extent narrow down the
20:32things and provide your roof provide you
20:34a platform to
20:35to get you know the best out of that so
20:37this is the way by which you know the
20:39things are going to be done
20:40and the competitive scaling technique is
20:42is you revolves around you know
20:44this particular aspects whereas
20:46non-competitive scale technique
20:48is there it is which we are going to
20:50cover in our next session
20:52and we will discuss about the this
20:54non-competitive skill technique is a
20:55more elaborative manner
20:56and if you talk about you know
20:58non-comparative scaling technique
21:00respondents evaluate only one objects at
21:02a time whereas you know we have seen
21:04that in competitive scaling techniques
21:05two objects
21:06are going to be evaluated at at one step
21:10and for this reason you know mundane
21:13scale is there a non-competitive
21:14technique consists of continuous
21:16and itemized details rating skills so
21:19anyway i think
21:19we have talked a lot about this
21:21particular session
21:23as far as the scaling technique is
21:24concerned which starts with you know the
21:27competitive screen techniques and the
21:28non-competitive screen techniques and
21:30further it is going to be bifurcated
21:32into you know some some more heads
21:34in our next sessions which purely
21:36revolves around you know the non
21:37competitive sessions
21:39we will talk more about that i hope the
21:41learner will enjoy
21:42with the with this with this terminology
21:45which is
21:46quite you know thought provoking as far
21:47as the research is concerned
21:49as far as you know the sampling is
21:50concerned as far as uh
21:52getting the extracting the information
21:54from the respondent is concerned because
21:56the intention behind the sampling is is
21:58is you know
21:59to get the best out of that and no need
22:02to you know
22:03uh go into the depth of the population
22:05or collect you know
22:06ah that the population in a holistic
22:08manner but to
22:10get you know the small portion of that
22:12and on the basis of this small portion
22:14on the basis of this
22:15small results how we are going to
22:18get best out of that this is the beauty
22:20of the sampling
22:21and when you are going more into depth
22:23of the sampling you will find out you
22:24know this measurement scaling technique
22:26is very important because
22:27the whole things you know the whole
22:29research is is become materialistic only
22:31when
22:32when researcher or the respondent used
22:34to reciprocate
22:35if respondents used to reciprocate and
22:37how you are going to
22:39tackle those those respondents view i
22:41think
22:42that that is where you know the
22:43measurement is carrying technique is
22:44very important
22:45thank you very much we will have some
22:48more thought provoking sessions which
22:49definitely talk about you know what
22:51exactly you know
22:53this tactical analysis and the
22:55researches thank you very much
23:12you

About this transcript

This page contains the full transcript of Comparative Scaling Techniques by MCO-3 [RM&SA], generated from the public captions YouTube serves with the video. The transcript has 4,186 words across 744 segments, with the original timestamps preserved so you can click any line to jump to that moment in the embedded player.

What you can do with it

Use the transcript to take notes, quote the speaker, build a study guide, generate a summary with ChatGPT or Claude via the YouTube Summary tool, or export it as a timed subtitle file with YouTube to SRT. You can also re-open it in the transcriber to translate the transcript into 100+ languages.

Free YouTube transcript tool

YouTube2Text is a free YouTube transcript generator — no signup, no daily limit. Paste any YouTube link and get the full transcript instantly, with timestamps, click-to-jump, translation to 100+ languages, AI prompts for ChatGPT, Claude, and Gemini, and exports to TXT, SRT, VTT, or Markdown.