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1.what is known as attitudinal scale? discuss different types of scales and their merits and demerits.     2. A firm engaged in marketing dish TV wants to measure the satisfaction level of its consumers. design a questionnarie for this purpose.    3. explain the process of research in management field. discuss the importance of research methodology in detail.

Answer
1.what is known as attitudinal scale? discuss different types of scales and their merits and demerits


ATTITUDE SCALE
: a measure of the relative quantity of an attitude possessed by an individual as contrasted with a reference group

ATTITUDINAL
: relating to, based on, or expressive of personal attitudes or feelings <attitudinal judgment>

   Types of Attitudinal Scales

   Likert (summated rating)
   Semantic Differential
   Guttman (cumulative)
   Thurstone (equal-appearing interval)

a.   Thurston Scales
These are also known as equal appearing interval scales. They are used to measure the attitude towards a given concept or construct. For this purpose a large number of statements are collected that relate to the concept or construct being measured. The judges rate these statements along an 11 category scale in which each category expresses a different degree of favourableness towards the concept. The items are then ranked according to the mean or median ratings assigned by the judges and are used to construct questionnaire of twenty to thirty items that are chosen more or less evenly across the range of ratings. The statements are worded in such a way so that a person can agree or disagree with them. The scale is then administered to assemble of respondents whose scores are determined by computing the mean or median value of the items agreed with. A person who disagrees with all the items has a score of zero. So, the advantage of this scale is that it is an interval measurement scale. But it is the time consuming method and labour intensive. They are commonly used in psychology and education research.
b.   Guttman Scales/Scalogram Analysis
It is based on the idea that items can be arranged along a continuem in such a way that a person who agrees with an item or finds an item acceptable will also agree with or find acceptable all other items expressing a less extreme position. For example - Children should not be allowed to watch indecent programmes or government should ban these programmes or they are not allowed to air on the television. They all are related to one aspect.
In this scale each score represents a unique set of responses and therefore the total score of every individual is obtained. This scale takes a lot of time and effort in development.
They are very commonly used in political science, anthropology, publEic opinion, research and psychology.

SEMANTIC   SCALE
a.   Semantic Differential Scale
This is a seven point scale and the end points of the scale are associated with bipolar labels.
1
Unpleasant
Submissive   2   3   4   5   6   7
Pleasant
Dominant
Suppose we want to know personality of a particular person. We have options-
1.   Unpleasant/Submissive
2.   Pleasant/Dominant
Bi-polar means two opposite streams. Individual can score between 1 to 7 or -3 to 3. On the basis of these responses profiles are made. We can analyse for two or three products and by joining these profiles we get profile analysis. It could take any shape depending on the number of variables.
Profile Analysis

---------------/---------------
----------/--------------------
--------/----------------------
Mean and median are used for comparison. This scale helps to determine overall similarities and differences among objects.
When Semantic Differential Scale is used to develop an image profile, it provides a good basis for comparing images of two or more items. The big advantage of this scale is its simplicity, while producing results compared with those of the more complex scaling methods. The method is easy and fast to administer, but it is also sensitive to small differences in attitude, highly versatile, reliable and generally valid.

LIKEHART  TECHNIQUE
a.   Likert Scale
It was developed Rensis Likert. Here the respondents are asked to indicate a degree of agreement and disagreement with each of a series of statement. Each scale item has 5 response categories ranging from strongly agree and strongly disagree.
5
Strongly agree   4
Agree   3
Indifferent   2
Disagree   1
Strongly disagree
Each statement is assigned a numerical score ranging from 1 to 5. It can also be scaled as -2 to +2.
-2   -1   0   1   2
For example quality of Mother Diary ice-cream is poor then Not Good is a negative statement and Strongly Agree with this means the quality is not good.
Each degree of agreement is given a numerical score and the respondents total score is computed by summing these scores. This total score of respondent reveals the particular opinion of a person.
Likert Scale are of ordinal type, they enable one to rank attitudes, but not to measure the difference between attitudes. They take about the same amount of efforts to create as Thurston scale and are considered more discriminating and reliable because of the larger range of responses typically given in Likert scale.
A typical Likert scale has 20 - 30 statements. While designing a good Likert Scale, first a large pool of statements relevant to the measurement of attitude has to be generated and then from the pool statements, the statements which are vague and non-discriminating have to be eliminated.
Thus, likert scale is a five point scale ranging from ’strongly agreement’to ’strongly disagreement’. No judging gap is involved in this method.
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2. A firm engaged in marketing dish TV wants to measure the satisfaction level of its consumers. design a questionnarie for this purpose.

Customer Satisfaction - Your Product

Valued customer! Thank you for using our product. In order to ensure that our products meet the expectations of our valued customers we would like to invite you to share your thoughts with us about our product.

We would very much appreciate if you would please take just a few moments of your time to provide us the feedback we need to do this.

Thank you!

Suspend
Questions prefixed with an * are required
*1.    When did you buy our product?
   Less than 1 month ago
1 - 6 months ago

6 - 12 months ago

More than a year ago



*2.    How often do you use our product?
   Daily

Weekly

Monthly

Yearly

Never



*3.    How satisfied are you with the product quality?
   very satisfied
neutral

not satisfied



*4.    Compared to other similar products you have used our product is:
   don't know

the best

better

about the same
worse



*5.    Compared to other similar products on the market, the value for money of this product is:
   excellent

good

average

poor

very poor



*6.    Would you buy this product again?
   probably

probably not


*7.    Would you recommend this product to others you know?
   yes

not sure

no



8.    Is there anything else that you would like to share with us that would help us improve our product?






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3.explain the process of research in management field. discuss the importance of research methodology in detail.
Research is not about mindless fact gathering in a theoretical void, but the development and rigorous
testing of hypotheses and conjectures within theoretical frameworks. It is also about the development
of new theories, new knowledge and new understandings.

Recent development in management research
While many of us are familiar with the ‘traditional’ approach to knowledge production, often
encapsulated in the term ‘the scientific method’, there is currently considerable discussion about different modes of knowledge production and their contribution
to management research.


two modes of knowledge production.

Mode 1
being a highly traditional approach characterised by what many people would see as the scientific
method,
Mode 2 focuses on ‘research in application’. Thus Mode 2 is a paradigm particularly appropriate to the conduct of management research as much of the research is:
• Undertaken within organisations which themselves are embedded within wider institutional
frameworks
• Undertaken to inform the practice of management, and
• Undertaken in environments where the researcher is a participant in the environment where the
research is being conducted.
The two Modes are briefly contrasted in Table 1 below.

The two modes of knowledge production
A.Mode 1
Usually conducted in contexts where there is a degree of
separation between researcher and researched. Assumptions
are made about researcher objectivity and independence.

A.MODE 2
The researcher is often a participant in the research or has an
agency role in the research problem. The relationship
between the researcher and the researched is often complex.

B.MODE  1
The research is conducted from a single discipline
perspective (i.e. psychology, economics).

B.MODE  2
The research is transdisciplinary and uses theories and
concepts from several disciplines. Research is often
conducted by multi-disciplinary research teams.

C.MODE  1
The research is often conducted in a way in which the world of
theory and the world of practice are seen as distinct or where
the link between theory and practice is not made explicit.

C.MODE  2
The research is conducted in an environment where the
explicit objective of the research is to affect policy, practice
and procedures. The phrase research-based practice is often
used in these contexts. Therefore the relationship between
the worlds of theory and practice must be made explicit.

D.MODE  1
The concept ‘organisation’ is often treated simplistically with
organisations being often conceptualised as a ‘container’ with
no intrinsic properties where management takes place.

D.MODE  2
There is a need to focus on the intrinsic nature of
organisations and to develop a clear perspective on the
concept ‘organisation’ (see Hatch, 1997 or Morgan, 1997).



There are many more distinctions between these two modes of knowledge production that need to be
addressed when you are trying to ‘frame’ an initial research question.

Research Process in Business and Management

The development of a research question
To conduct research we need to develop a focus. This focus takes the form of a ‘research question’,
this is the issue that we want to explain, understand or make sense of (Weick, 1996).
Having raised the issue and emphasised the centrality of the ‘research question’, it is important to
discuss this in some detail. Developing, or articulating, a research question is the most important
element in the entire research process as, from this, many things follow.
In the assessment or evaluation of a research project, whether it is a postgraduate dissertation, a PhD,
or a piece of consultancy, being able to identify a coherent, well articulated research question is
absolutely critical. The research question encapsulates what the research is about.
However, a degree of realism needs to be applied to what can be achieved. In framing a research
question, the ‘do-ability’ of the project should always be considered. Many research questions are
soon found to be over-ambitious or not practical. Many projects fail because the researcher cannot get
access to the subject of their research. Unfortunately, this is a particular problem in management
research as many organisations will not allow the researcher access to gather data.
Why is the act of articulating a research question so important? Firstly, the research question is the
focus of the piece of work, encapsulating in a statement what it is trying to be achieved. If there is
uncertainty about the focus of the research, then a high quality piece of research cannot be
undertaken. Furthermore, the way a research question is articulated will largely determine the
methodology or approach to evidence collection and analysis that will be used.
If a research question is not articulated clearly, the wrong approach to answering the research question
may be chosen. Essentially, having defined what the research is trying to achieve will often shape
how the research will need to proceed.

Articulating a research question
Given the centrality of the research question to the research process it is essential that researchers
understand how to frame or articulate a research question. Common criticisms of research proposals
are that:
• There is no clearly articulated research question at all
• What is assumed to be the research question is articulated in a way that it does not render that
question testable
• The research question is articulated badly or it is wrongly formulated, and
• The research question was unrealistic and could not be achieved.
By focusing on trying to understand or explain something, we will inevitably be asking questions
beginning with phrases such as "How does….?"; Why does…..?"; What is the relationship between x
and y?; and, "Given a particular theory, what will be the effect of doing x on y?" Questions of this
type are research questions.
An example
An example from my own research may help to demonstrate how to formulate a research question.
In 1997 I was involved in the design of a four-year research programme to look at the changing
"Quality of Working Life" of UK managers (Worrall & Cooper, 2001). One of the elements of this
wider research programme was to explore the impact of different forms of organisational change on
managers' experiences of their working lives.

A research theme was developed out of a review of the literature on organisational change and its
impact on the survivors of change (Worrall et al, 2000). In the literature there was a clear view that
certain forms of organisational change (particularly redundancy and delayering) have had a more
profound effect on surviving employees and their organisations than have other forms of
organisational change. This was one of the questions we set out to test.
This observation posed a number of operational issues that needed to be resolved:
• Firstly, how could we categorise different forms of organisational change? and,
• Secondly, on what criteria did we want to assess the impact of change among employees?
By examining the literature we were able to identify ten forms of organisational change including
redundancy and delayering. Also from the literature, we were able to identify several aspects of
organisational life that we hypothesised that organisational change would affect. These included, for
example, employee loyalty, commitment, morale, sense of job security and motivation.
Following the review of the literature our a priori conjecture was that in organisations where there
had been organisational change involving redundancy and/or delayering the survivors of that change
would have lower levels of organisational loyalty, motivation, morale, commitment and sense of job
security than those working in organisations where there had been change without the use of
redundancy and/or delayering or those working in organisations where there had been no
organisational change at all within the last 12 months.

Operationalising the research question
In the previous section we developed a concise research question and by articulating the research
question in this way, we could more easily see how we could implement the evidence collection and
analysis phases of the research process to test our hypotheses.
While the research question was now relatively clear, we still had some work to do if we were to test
the research question operationally. First, we had a number of concepts that we were interested in
measuring (loyalty, motivation, morale, commitment and sense of job security) but before we could
measure them, we needed to be clear about precisely what it was that we were trying to measure -
essentially we needed to develop operational definitions of these terms.
Having defined concepts, the next phase of the research involves the development of operational
measures.
The easiest way to achieve conceptual clarity and develop operational definitions of concepts and
constructs is to explore the literature to see how they have been defined in earlier research. This is an
important step, as clear and concise definitions of terms need to be developed if they are to be reliably
and validly measured.
By adopting earlier operational definitions it is possible to directly compare findings with those of
other researchers in the field. In addition, it will allow the researcher to compare whether the findings
are consistent with earlier research, or not, and also isolate quite clearly what information is new (i.e.
what the contribution to knowledge has been).
It is in the development of operational measures of constructs that the terms ‘validity’ and ‘reliability’
become important. If we are to measure constructs, we need to develop items to be included in a
questionnaire that are both valid (they measure what we think they measure) and reliable (they
measure things consistently in different settings and at different times). For a discussion on the
importance of validity and reliability see Mitchell (1996).
Some discussion of the construct ‘organisational commitment’ might help here to exemplify some of
the points being made. While we might have a superficial view of what we think we mean by
‘commitment’, a review of the literature reveals that organisational psychologists have developed
more precise and refined measures of what they mean by commitment.
Psychologists differentiate between two forms of commitment: affective and continuance
commitment. Affective commitment refers to one's emotional attachment to, identification with, and
involvement with your organisation while continuance commitment refers to one's awareness of the
costs (economic and emotional) associated with leaving one's current organisation and of the
opportunities elsewhere (see Goffin & Gellatly, 2001).
Having developed these operational definitions, the evidence collection process will need to be
designed that will allow the research question to be tested given the more refined definitions. Within
our given example, the first phase was to develop a set of items that measured commitment and our
other constructs, the easiest approach being to review the literature to identify if there are any existing
and prior validated measures that can be used, some of whom are described in Cook et al (1993). The
second phase was to design an approach that allowed us to collect the actual evidence.

Designing the evidence collection and analysis process
To test the research question outlined in the example, a questionnaire was designed which was to be
administered to a random selection of UK managers. An example of part of a questionnaire to explore
the research question is shown below.
An example
What do you think about your organisation?
The following statements ask you to consider how you feel about your organisation as a whole. Read
each of the statements and tick ☑ the box that is closest to how you feel.
Strongly
Disagree
Strongly
Agree
I am proud to work for this organisation
❑1
❑2
❑3
❑4
❑5
❑6
This organisation is a good employer
❑1
❑2
❑3
❑4
❑5
❑6
I feel well informed about what is going on in the
organisation as a whole
❑1
❑2
❑3
❑4
❑5
❑6
In this organisation, people are treated fairly
❑1
❑2
❑3
❑4
❑5
❑6
I feel able to achieve my career aspirations in
this organisation
❑1
❑2
❑3
❑4
❑5
❑6
I feel a strong sense of loyalty and commitment
to this organisation
❑1
❑2
❑3
❑4
❑5
❑6
Compared to other organisations, this is a good
place to work
❑1
❑2
❑3
❑4
❑5
❑6
The evidence collection and analysis process is outlined below in Table 2.
Table 2. The evidence collection and analysis process
Stage of process
Comment
Initial questionnaire design, piloting and questionnaire
finalisation
A questionnaire was developed using a range of items
identified in prior research or constructed specifically for the
research project. Following a pilot phase, which tested for
reliability and validity, a more focused questionnaire was
developed.
A set of background questions was developed in addition to
the main items of the questionnaire to gather data about the
respondent and their organisation
Sampling frame, sample size, sampling strategy and sample
selection phase
As this was a project in conjunction with the Institute of
Management, their membership database was used as a
sampling frame. 5,000 names were selected at random.
Fieldwork management phase
Management procedures were set up to deal with the mail out
of questionnaires and their return. A second phase mail out to
non-respondents from the first phase was put in place to
boost overall response.
Data management and preparation phase
Data were checked and validated after input to SNAP (a
survey analysis package).
Data Analysis phase
Data were analysed using SNAP, SPSS and Excel. This
involved basic frequency counts and crosstabulations as well
as more advanced techniques such as Correspondence
Analysis, Factor Analysis and Analysis of Variance (Anova) to
test specific hypotheses and to elicit meaning from the data.
Writing up phase
A 27,000 word publication was produced for the Institute of
Management in addition to several journal articles. A binary
publication strategy was used with different outputs produced
for the practitioner and academic communities.
Some practical issues
While the above approach appears very straightforward, it actually requires effective project
management skills, particularly if there are tight publication or submission deadlines. If the
researcher is inexperienced, it is very easy to under-estimate how long each phase will take and the
consequences on the overall project of an individual phase over-running.
Response rates to questionnaires can often be low. In the case of face-to-face interviews it can often
be difficult to get access to organisations and it can take you a long time to negotiate access to some
organisations. The key is not to under estimate how long good research can actually take.
Data inputting requires the researcher to have thought through how the data items are to be collected
and coded - this is a far from trivial task. Badly structured or inflexibly coded data can preclude some
forms of analysis. These are all things that need to be consciously planned for.
Which parts of the process are the most difficult to deliver?
The areas where most researchers have the greatest difficulties when conducting a research
programme are the two latter phases (though this is not to give the impression that earlier phases are
easy). The main problems are often experienced in the following areas:
• Data analysis phase
• How should I analyse my data?
• How do I get my data into the software?
• How do I interpret the results of the analysis?
• How can I transcend the descriptive and use more advanced analytical techniques?
• Writing up phase
• How should I structure my research findings?
Having a clearly articulated research question will pay real dividends in the data analysis and writing
up phases of the research project. Therefore investing considerable thought into the early phases of a
research project will ensure that there is a clarity of purpose throughout.

Let us go back to the research question that we developed earlier to see what I mean. The research
question was:
“In organisations where there has been organisational change involving redundancy and/or
delayering, the survivors of that change will have lower levels of organisational loyalty, motivation,
morale, commitment and sense of job security than those working in organisations where there has
been change without the use of redundancy and/or delayering or in organisations where there has
been no organisational change.”

The data analysis phase
The analysis phase in many research projects is often weak, presenting a few frequency tables,
Cross tabulations and the occasional graph does not constitute analysis. The role of the data analysis
phase is to rigorously test the hypotheses and conjectures contained in the research question, and to
distil meaning from the collected evidence.
Again, from our research question we can show how the data analysis phase needs to be structured to
answer the specific questions raised. Essentially, we need to show that levels of commitment etc.
vary with the type of organisational restructuring that managers have experienced.
From the research question we can isolate five different organisational contexts:
1. Those where there has been no organisational change in the last year
2. Those where there has been organisational change without the use of redundancy or delayering
3. Those where there has been organisational change with redundancy but without the use of
delayering
4. Those where there has been organisational change with delayering but without the use of
redundancy
5. Those where there has been organisational change with the use of both delayering and redundancy
By having a clearly defined research question, it is relatively easy to develop a data analysis strategy.
If we look at the part of the questionnaire included above then we can formulate a hypothesis (a null
hypothesis to use the jargon) that responses on these items will not be significantly different in each of
the five organisational contexts shown above.
If there are no significant differences, then we can conclude that organisational commitment is the
same in all of the five contexts. To test hypothesis this we can use a statistical technique available in
SPSS called analysis of variance (ANOVA), with a Bonferroni post hoc procedure to identify which
organisational contexts differ significantly from each other. To find out more about SPSS see Field
(2000).
Our initial hypothesis is that the means of the "I am proud to work for this organisation" measure are
equal in the five organisational contexts. This is a hypothesis that we would like to refute, as we want
to show that there are significant differences in organisational attachment (of which being proud to
work for the organisation is one item).
By running the ANOVA procedure in SPSS we find the means of the different groups (people in
different organisational contexts). These can be seen in Table 3 below.
Table 3. Means of the groups of people in different organisational contexts
Organisational context
I am proud to work for this organisation (mean score)
1. Those where there has been no organisational change
5.2
2. Those where there has been organisational change
WITHOUT the use of redundancy or delayering
4.8
3. Those where there has been organisational change
WITH redundancy but WITHOUT the use of delayering
3.3
4. Those where there has been organisational change
WITH delayering but WITHOUT the use of redundancy
3.1
5. Those where there has been organisational change
WITH the use of both delayering AND redundancy
2.0
6. Overall mean
4.3
Table 3 reveals that the means of all groups, except 3 and 4, are significantly different from each other
and that ‘organisational identification’ (an indicator of affective commitment) is at its highest where
there has been no organisational change at all. This confirms our a priori expectations.
You will notice that the mean of Group 2 is still relatively high but significantly lower that Group 1,
indicating that organisational change, even when delayering and redundancy are not used, may cause
some reduction in affective commitment.
When redundancy or delayering is used as a means of organisational change, there is a substantial
deterioration in the mean of the affective commitment score in both Groups 3 and 4, compared to the
means of Groups 1 and 2. However, we find that the means of Groups 3 and 4 are not significantly
different from each other, so individually, the effects of redundancy and delayering are about the
same.
From this analysis we have evidence to suggest that the conjecture, that redundancy and delayering
reduce affective commitment more than other forms of organisational change, is sustained by the data.
This can be taken further by comparing the mean of group 5 with the means of groups 3 and 4.
Our analysis reveals that in those organisations where redundancy and delayering have been used, the
joint effect of redundancy and delayering seems to have a particularly pronounced effect on reducing
the affective commitment of respondents.
This finding - that the affects of redundancy and delayering are not additive but cumulative - could be
our distinctive contribution to knowledge in this particular field. In statistical terms we can posit that
there is an interaction effect between redundancy and delayering.
The writing up phase
If we are aware of the structure of the ‘research process’ and we make the process explicit to
ourselves, then the task of writing up the research becomes relatively easy as the research process
effectively defines the structure of the dissertation. Whether you are writing a dissertation, a PhD
thesis or a paper for publication, your work will comprise the same basic structure (see Perry, 1997).
A generic structure for a research paper is shown in Table 4 below.
Table 4. Generic structure for a research paper
Section
Contents and clues
Introduction
What business and management issue interests you? Why?
Why is this issue relevant to business and management research?
What are your research aims and objectives?
What is your research question and focus?
Literature review
What does the current literature have to say about the issue you want to pursue?
Where are the gaps in our knowledge?
Provide a discussion of the literature not a listing of it.
Demonstrate that you understand the concepts you are working with.
Provide clear operation definitions of concepts and constructs.
Demonstrate that you have read widely and that you have read the most up-to-date material
Methodology
How are you going to do the research?
Why have you decided to do it that way?
Discuss the methodology and provide details of sampling frames, sizes and strategies.
Critique your methodology - where is it strong, where could it have been made stronger, what
assumptions have you made.
Analysis
What is your analysis strategy in the context of your research questions?
What techniques are you going to use?
What assumptions about the data affect the use of certain techniques?
Interpret your findings in the context of the research question.
Interpret your findings in the context of the literature review.
Conclusions
What have you found out that is new?
What is the significance of what you have found out?
How does it build on the literature?
What are the implications of your research for management practitioners?
What are the implications for further research?
Summary
The purpose of this working paper has been to provide an overview of the research process, with
particular reference to the issues relevant to business and management research. The key stages in the
research process have been identified, with emphasis placed on the need for the researcher to invest
time developing a clearly articulated research question.
The key points raised in this paper are concerned with the research process at a number of levels
ranging from the conceptual to the operational:
• What are the current developments in thought about the nature of management research and how
can this be reflected in my work?
• How do I develop a concise, focused research question?
• How do I design a research project that I can realistically achieve?
• What bodies of literature do I need to examine?
• How do I structure my review of the literature?
• What are the methodological issues that arise from how I have articulated by research question?
• How am I going to collect the evidence?
• When I have collected the evidence how I am going to analyse it?
• What software should I use?
• How should I structure my work?
• How can I demonstrate that I have found out something that is rigorous but relevant and useful to
management practice?
• How do I manage the whole research process?
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