An Analysis Of Variation At Transcription Factor Binding...

An Analysis Of Variation At Transcription Factor Binding...
This research paper is about "An analysis of variation at transcription factor binding sites in
Drosophila and humans". This analysis is done in order to investigate the transcription factor
binding sites variability with the comparison of ready published data of transcription factor binding
maps for Drosophila isogenic lines and human individuals.
Genome is considered as the encoder or provider of disambiguation for many diseases, viruses,
DNA and other organisms. Here it is very important to understand the concept of population
genetics. Population genetics explains the study and research of distributions and modifications of
allele frequency in a population. It further states that there are actually four evolutionary processes
such as; selection, genetic drift, mutation and gene flow.
It is important to describe an analysis of the relationship for exploration of intra species variation
and it has been seen that variation in DNA regulatory elements are common and TRFs shows a
fraction of it. Across 12 Drosophila species have been analyzed in order to see the sequence
variation at each motif position. And the results showed that motifs are conserved and depressed
level of variation has been shown across individuals.
An introduction of Transcription factor binding variability which has been taken into account
transforms itself in a sort of motif match related to mutation and enable the researchers to
investigate and makes it possible to analyze TFBS related hurdles and
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Evaluation Of Exploratory Factor Analysis Essay
4.3 Factor Analysis
Exploratory factor analyses using Varimax rotation were conducted on each of the multiple–item
scales, including the exogenous constructs ( information quality, entertainment, interactivity and
vividness) and endogenous constructs (cognitive engagement, affective engagement, behavioral
engagement and the outcomes of this engagement–loyalty and e–WOM) as a way to refine the
measures in the study. Exploratory factor analysis was conducted prior to testing the full model to
identify items with poor psychometric properties and to purify the measurement model for future
testing (Anderson & Gerbing, 1988). A priori designations for each of the proposed antecedents of
engagement (information quality, entertainment, interactivity and vividness), for loyalty, and for e–
wom were employed in the analyses, given that they have been confirmed in previous studies
(Mollen & Wilson, 2009; O'Brien & Toms, 2008; Shang et al., 2006; Shukla, 2009 ).
Eigenvalues larger than one and scree plots were analyzed to assist in determining the number of
factors for each construct. Additionally, the strength of factor loadings as well as face validity were
analyzed to further assist in determining the items to be included for each exogenous and
endogenous variables.
The coefficient reliability analysis revealed that all the scales consisting of more than two items
exceeded the recommended Cronbach‟s alpha benchmark of 0.70 (Nunnally, 1978).
4.4 Exploratory Factor Analysis of

Factors Influencing The Factor Analysis
Factor analysis According to Maria& Eva, the factor analysis is a technique in the statistics to
observe variability in the correlated variables in terms of lowers number of unobserved variables,
which is necessary for factorization (Maria& Eva, 2012). Dehak, Kenn, Dehak, Dumouchel, &
Ouellet, further stated that, the factor analysis is useful technique to investigate the relationship
between the variables in complex concepts and the main purpose of the factor analysis is to reduce
the number of variables associated with the measure and to detect the structures of the relationship
between the variables (Dehak, Kenn, Dehak, Dumouchel, & Ouellet, 2011) .
The application of factor analysis widely used in social research (Steinfeld, Navon, Creech, Yakhini,
& Tsalenko, 2014). The current study employs factor analysis to reduce the items' in the
questionnaire for data reduction as per the recommendations of In addition, the factor analysis is
used to construct the factor based on the items' in the scale (Wang & Ahmed, 2004). Hence, the
factor analysis is used for data reduction and structuring the variables. Factor analysis has two types
as discussed below, exploratory and confirmatory factor analysis (Costello & Osborne, 2005).
Exploratory Factor Analysis (EFA) Costello & Osborne, (2005) said that, factor analysis is used to
uncover the structure of relatively large set of variables in the data(Costello & Osborne, 2005). EFA
identifies the underlying relationship between the

Influencing Factors for the Selection of Mobile Phone...
African Journal of Business Management Vol.4 (13), pp. 2885–2898, 4 October, 2010 Available
online at http://www.academicjournals.org/AJBM ISSN 1993–8233 ©2010 Academic Journals Full
Length Research Paper Exploring influencing factors for the selection of mobile phone service
providers: A structural equational modeling (SEM) approach on Malaysian consumers Sabbir
Rahman1, Ahasanul Haque1* and Mohd Ismail Sayyed Ahmad2 1 Faculty of Economics and
Management Sciences, International Islamic University, Malaysia, Box No. 10, 50728 Kuala
Lumpur, Malaysia. 2 Graduate School of Management, International Islamic University, Malaysia,
Box No. 10, 50728 Kuala Lumpur, Malaysia. Accepted 26 August, 2010 The aim of this paper is to
assess ... Show more content on Helpwriting.net ...
Now Government of Malaysia plans to have a telephony penetration rate of 50% for the whole
country and 25% for the rural areas by year 2020 (State of Hawaii Government, 2002). Scrutinizing
the background of Malaysian telecommunication sector, competition can be seen as main factor by
the telecommunication service provider companies. Companies like Sapura Digital Sdn. Bhd.,
Celcom and Mobikom Berhad have gone through a market evaluation stating the fact that their
companies either should be merged with giant and more competitive companies or to be gone
through potential bankruptcies. This reflects a fact as how the market is being penetrated and
flooded by the competitors. Only Telekom Malaysia (TM) Sdn. Bhd., with its TM Touch services
has managed to maintain its credible presence in the industry. TM has been ranked as one of the
leading telecommunication service providers in the entire Asia with significant investments in
overseas. Beside TM, three other major companies have been operating in Malaysia namely
Celcom, Digi and Maxis. These three service providers usually cover the following segments of the
Malaysian telecommunication market traditional telecommunications, IP services, wireless and
mobile markets and technologies, broadband markets and technologies. They also provide most
sophisticated mobile services with an expanding number of value added services such as Short
Message Service (SMS), Wireless Application Protocol (WAP), Subscription Services (SS),

Essay On Factor Analysis
TEST OF RELIABILITY AND VALIDITY OF THE SELECTED ITEMS
In order to determine the construct validity, factor analysis was carried out with Principal
Component Method and Varimax rotation. The purpose of factor analysis was to obtain theoretically
meaningful dimensions pertaining to the study.
Before conducting factor analysis, the Kaiser‐Meyer‐Olkin measure of sampling adequacy (KMO)
and Bartlett's test of Sphericity was carried out to see the suitability of the factor model. The KMO
for both the Turnover Intention and for the Organizational Attributes were above 0.60 (0.88 for
Turnover Intentions and 0.89 for Organizational Attributes). Similarly, the Bartlett test for Sphericity
was found to be significant (1.02 for Turnover Intentions and 2.05 for Organizational Attributes; p
1.00
‐ Meeting the criteria of factor loading generally ... Show more content on Helpwriting.net ...
Hale, J. 1998. Strategic rewards: Compensation and benefits management. Management, 14 (3), 39–
50.
7. Lyon, H. L., J. M. Ivancevich, and J. H. Donnelly. 1970. A motivational profile of management
scientists. Operations Research, 19 (6), 1282–99.
8. Maslow, A. H. 1943. A theory of human motivation. Psychological Review , 50, 370–396
9. McGregor, D. 1960. The human side of enterprise. New York: McGraw–Hill.
10. Pathak, S., & Tripathi, V. 2010. Sales Force Turnover: An Exploratory Study of the Indian
Insurance Sector. Management, 5(1), 003–019.
11. Roberts, T. B. 1982. Comment on Mathes's article. Journal of Humanistic Psychology 22 (4),
97–98.
12. Rogers, P., and D. J. Peccoud. 2005. Leading from the front.
Http://www.bain.com/bainweb/publications/publications_detail.asp?
id=24349&menu_url=publications_results.asp.
13. Shoura, M. M., and A. Singh. 1998. Motivation parameters for engineering managers using
Maslow's theory. Journal of Management in Engineering 15 (5), 44–55.
14. Agent Attrition Remains High, Life insurers lose 60,000 in Q1,

Factor Analysis Magimid
Magidson et. al (2016)'s purpose was to make the Factor Analysis more straightforward and
accessible to clinicians of varying perspectives. Factor Analysis aims to understand the aspects of
certain problem behavior. In order to move forward, the problem behavior must be identified. Then
the focus moves on to the triggers and figuring out the context of what happened right before the
behavior occurred. This is known as the proximal trigger and is what is typically focused on.
However, Magidson et. al. (2016) states that in order to better understand the cause of the behavior
it is also important to look at the recent and distal triggers, which are the ongoing stressors and past
situations. Once the triggers are established the patient is ... Show more content on Helpwriting.net
...
al. (2016) provides a straightforward guide to implementing Factor Analysis. However, while
reading a few questions and criticisms did arise. First, is how Factor Analysis would help assess
potentially dangerous behavior such as severe self–injury. It can be hard to evaluate this kind of
behavior if it is not allowed to occur frequently. Magidson et. al. (2016) states that Factor Analysis is
used to pinpoint reliable relationships between the patient's natural environment and behavior. So
even though Factor Analysis examines naturally occurring behavior, such a severe problem behavior
might cause redirection which can cause interpretation to be bias. Thus, while conducting Factor
Analysis it can be challenging to have conditions in which problem behavior may increase but at the
same time have the risk minimized. Another critique is the possibility of limited assessment time. If
the contact with the client is limited whether it be because they are an outpatient or some other
factor then it can be very difficult to assess change over time and see if Factor analysis is actually
effective. It can also be difficult to make progress if time is cut short before the patient has time to
reflect upon the causes of their behavior. Lastly, Factor Analysis might not be so effective if the
patient keeps avoiding the main problem behavior. Magidson et. al. (2016) states that it is important
to acknowledge that the patient may not want to do a difficult Factor Analysis so they should warm
up with a smaller problem behavior. However, it is possible that the patient will be reluctant and
unwilling to face the behavior that is truly problematic. It is not possible to force someone who does
not want to change a certain behavior to sit there and genuinely reflect upon it. Another reason for
avoidance could possibly be fear of bringing up a traumatic event. When looking for the triggers it is
possible for a distal trigger to bring up strong emotions and traumatic memories.

A Technical Analysis of Ergonomics and Human Factors in...
A Technical Analysis of Ergonomics and Human Factors in Modern Flight Deck Design
I. Introduction Since the dawn of the aviation era, cockpit design has become increasingly
complicated owing to the advent of new technologies enabling aircraft to fly farther and faster more
efficiently than ever before. With greater workloads imposed on pilots as fleets modernize, the
reality of he or she exceeding the workload limit has become manifest. Because of the unpredictable
nature of man, this problem is impossible to eliminate completely.
However, the instances of occurrence can be drastically reduced by examining the nature of man,
how he operates in the cockpit, and what must be done by engineers to design a system in which
man and ... Show more content on Helpwriting.net ...
They will be discussed in further detail in another chapter (Hawkins, 249–54).
III. System Design A design team should support the concept that the pilot's interface with the
system, including task needs, decision needs, feedback requirements, and responsibilities, must be
primary considerations for defining the system's functions and logic, as opposed to the system
concept coming first and the user interface coming later, after the system's functionality is fully
defined.
There are numerous examples where application of human–centered design principles and processes
could be better applied to improve the design process and final product. Although manufacturers
utilize human factors specialists to varying degrees, they are typically brought into the design effort
in limited roles or late in the process, after the operational and functional requirements have been
defined (Sanders & McCormick, 727–8). When joining the design process late, the ability of the
human factors specialist to influence the final design and facilitate incorporation of human–centered
design principles is severely compromised. Human factors should be considered on par with other
disciplines involved in the design process. The design process can be seen as a six–step process;
determining the objectives and performance specifications, defining the system, basic system
design, interface design, facilitator design, and testing and evaluation of the system. This model

Factor Analysis: An Analysis Of Brand Choice Factors
much influenced by the brand name of the cars. There are too many brands of car which tend to give
more choices to the customers to choose from. Brand recognition is the area to which a brand is
accepted for stated brand choice factors. The technique used to analyze brand choice factors is factor
analysis. It focused on brand choice factors of respondents. Major variables that determine the brand
selection are presented for further factor analysis and ANOVA is used in order to analyses the
factors For that, first correlation matrix is formed to find the appropriateness of factor model by
checking whether such correlated variables exists or not. The 14 variables/factors used (In first row)
in the correlation matrix are represented by the ... Show more content on Helpwriting.net ...
Overall measure of sampling adequacy was computed and found to be 0.787 which is a good figure
Normally ,the measures can be interpreted that if the value is 0.90 or above (above marvelous), 0.8
or above (meritorious), 0.7 or above (above middling), 0.6 or above (mediocre), 0.5 or above
(miserable), 0.5 or below (unacceptable). Hence all the assumptions indicated the appropriateness of
the data to proceed for factor analysis. Thirdly, the component matrix was applied to extract
principal factors through PCA (Principal Component Analysis). Principal component analysis was
employed for extracting the factors. (ie. Eigen Value >0.5).
Table 44 Total variance Explained– Brand choice factors
Total Variance Explained
Component Initial Eigen values Extraction Sums of Squared Loadings Rotation Sums of Squared
Loadings Total % of Variance Cumulative % Total % of Variance Cumulative % Total % of Variance
Cumulative %
Marketing influence 3.769 26.925 26.925 3.769 26.925 26.925 2.289 16.352 16.352
Goodwill of brand 1.448 10.344 37.269 1.448 10.344 37.269 2.035 14.536 30.888
New technology 1.262 9.014 46.282 1.262 9.014 46.282 1.814 12.955 43.843
After sales service 1.195 8.537 54.820 1.195 8.537 54.820 1.537 10.977

Stimulus And Brand Selection
This study is an attempt to fill the gaps identified in the available literature on the association of
stimulus and brand selection. The present study measured the stimulus and its impact on brand
selection or purchase decision in the Indian online retail. To assess this relationship, different models
have been designed to investigate and measure the stimulus. For investigation purposes, a
qualitative model has been developed and presented in Chapters earlier. This model prioritized the
various factors of stimulus in context of the online retail. Next to this, the measurement aspect of
stimulus was addressed by the development of a quantitative model shown in Chapters earlier. This
model has been used to develop and validate the scale for the measurement of stimulus in the Indian
online retail. The present study comprises of the following: A broad and thorough literature review
has been conducted on the association of stimulus and brand purchase decision. The literature
review consists of the evolution and definitions of individual, technology and societal groups and
brand purchase decision, a classification of available literature, and various factors which constitute
Stimulus in S–O–R model. Based on this basis of this review, gaps, and a research agenda was
identified which provided a sound base to conduct the present study. A literature review of the
methodologies used in this field of study was also conducted. These methodologies were Analytical
Hierarchy Process

Ready to Eat Foods
2011 International Conference on E–business, Management and Economics IPEDR Vol.25 (2011) ©
(2011) IACSIT Press, Singapore Managing the Diffusion of innovation in Ready–To–Eat Food
Products in India T.Sarathy1 and Shilpa Gopal2+ 2 1 Periyar Institute of Management Studies,
Periyar University, Salem University Research Fellow, Periyar Institute of Management Studies,
PeriyarUniversity,Salem Abstract: Food occupies a major purchase amount of the normal consumer.
Food consumers have moved up Maslow's hierarchy of needs pyramid from satisfying basic
physiological needs. Rapid demographic and socioeconomic changes, such as the massive entrance
of women into the workforce and increasing multiethnicity, are fundamental drivers of food– buying
... Show more content on Helpwriting.net ...
The method suggests that eigen values greater than one be retained. . The ScreeTest is also
performed for determining the number of factors. 3. Findings and Analysis 3.1. Grand Means And
Item Means The grand mean score obtained by respondents reflecting their positive or negative
inclination towards private labels was 3.308. This indicates that on the whole, the consumers are
favourably inclined towards Ready–To–Eat Food products. Table I presents the item mean scores of
the variables. From the table it is very clear that Awareness level of Ready–To–Eat food has
recorded the highest mean rating of 3.87. Further, it can be observed that respondents are happy
welcoming new retail formats (3.62) in Salem and that they also think that the quality of Ready–To–
Eat food is reasonably good (3.62). Respondents have also confirmed that while arriving at
conclusions (3.6) on quality and other parameters they use their discretion and form independent
opinions. The following variables that reflect the inclination of respondents towards Ready–To–Eat
food have got ratings between 3.4 and 3.5.. These factors are: welcome with open mind (3.42) ,
willingness to recommend (3.52), willingness to receive suggestions (3.46), frequency of visit
(3.41), Convenience (3.45) Table 1 (Mean scores of the variables) Awareness like change brand
loyalty interest factor welcome suggest to others reliability Welcomewith open

Test Evaluation: DASS
Test Evaluation: DASS
The Depression anxiety and stress scale (DASS–21) is a 21–item quantitative measure of distress
that has 3 scales– anxiety, stress and depression, each of which has 7–items (Henry & Crawford,
2005). The DASS–21 is a shorter version of the full 42–item questionnaire (DASS) both of which
are typically used to discriminate between the three related states of depression, anxiety and stress
(Antony, Bieling, Cox, Enns, & Swinson, 1998). Distinguishing between these states has proven
difficult, particularly between anxiety and depression (Clark & Watson, 1991a) . Many of the major
scales predominantly measure the common factor of negative affectivity (Watson & Clark, 1984).
While the full version DASS is used in both clinical and research settings, the DASS–21 is typically
used for research purposes (Lovibond, 2013). As such this paper will evaluate the empirical
evidence for the validity and reliability of the DASS–21 for research purposes.
Evidence for Validity
The DASS–21 shares many similarities with the tripartite model of depression (Brown, Chorpita,
Korotitsch, & Barlow, 1997), which posits that the explanation of an affective domain requires the
evaluation of both common and distinct elements (Clark & Watson, 1991b). The tripartite model
argues that factors of anxiety and depression can be categorised as having general distress (negative
affect) as well as distinct symptoms, namely hyper–arousal, in the case of anxiety and anhedonia, in
the case of

Exploratory Factor Analysis Using Varimax Rotation Essay
Exploratory factor analyses using Varimax rotation were conducted on each of the multiple–item
scales, including the exogenous constructs ( information quality, entertainment, interactivity and
vividness) and endogenous constructs (cognitive engagement, affective engagement, behavioral
engagement and the outcomes of this engagement–loyalty and e–WOM) as a way to refine the
measures in the study. Exploratory factor analysis was conducted prior to testing the full model to
identify items with poor psychometric properties and to purify the measurement model for future
testing (Anderson & Gerbing, 1988). A priori designations for each of the proposed antecedents of
engagement (information quality, entertainment, interactivity and vividness), for loyalty, and for e–
wom were employed in the analyses, given that they have been confirmed in previous studies
(Mollen & Wilson, 2009; O'Brien & Toms, 2008; Shang et al., 2006; Shukla, 2009 ).
Eigenvalues larger than one and scree plots were analyzed to assist in determining the number of
factors for each construct. Additionally, the strength of factor loadings as well as face validity were
analyzed to further assist in determining the items to be included for each exogenous and
endogenous variables.
The coefficient reliability analysis revealed that all the scales consisting of more than two items
exceeded the recommended Cronbach‟s alpha benchmark of 0.70 (Nunnally, 1978).
4.4 Exploratory Factor Analysis of Exogenous Constructs
4.4.1

Reliability Analysis Of Refined Model With 25 Items And 5...
Reliability Analysis
The reliability analysis of refined model with 25 items and 5 factors was undertaken to verify how
strongly the attributes are associated with each other. (Hair et al., 2010). Cronbach's alpha for the
full scale came to be 0.851 .The reliability test is deemed to be acceptable when the Cronbach's
Alpha value exceeds the Nunnally's reliability criterion of 0.70 level (Hair et al., 2010). Dimension
wise the value of Cronbach's Alpha came to be 0.903 for Personal competence, High standards and
Tenacity (Factor1), 0.867 for Trust in one's instincts, Tolerance of negative affect and the
Strengthening effects of stress (Factor2), 0.932 for Positive acceptance of change and Secure
relationships with others (Factor 3), 0.752 for Control (Factor 4) and 0.812 for Spiritual influences
(Factor 5). (Refer Table 4).
[Insert Table 4 here]
Confirmatory Factor Analysis
Confirmatory factor analysis using Maximum Likelihood (ML) estimation was used to examine the
hypothesis regarding number of factors their loadings and factor inter correlations. For assessing the
model fit the independence model was compared to the hypothesized model. Results revealed that
the independence model, which tests the hypothesis that all variables are uncorrelated, was a poor fit
for the data and therefore, it should be rejected, χ²(300,N=152)=2814.908,p< 0.005. The literature
reveals that ideally, the χ² value should be small and its associated probability value should be
greater than

Factor Analysis: Based On The Common Factor Analysis Model
Factor analysis is based on the 'common factor model'. This is a theoretical model that is useful for
studying relationships among variables. It is the general way to estimate more than one factor from
the data. This model postulates that observed measures are affected by underlying common factors
and unique factors, and the correlation patterns need to be determined. In the factor analysis model,
each variable is assumed to depend on a linear combination of factors. These coefficients are called
loadings. It also includes a component called specific variance. This is due the variable's
independent random variability. It is called specific variance because it specific to each variable.
During factor extraction it is the variable's shared variance that is partitioned from its unique or
specific variance. The shared variance contributes to the determination of factors [2]. There are a
number of extraction methods available. In this paper the Maximum Likelihood Estimation method
is used. Maximum Likelihood attempts to analyze the maximum likelihood of sampling the
observed correlation matrix [9]. When applied to a data set, maximum–likelihood estimation
provides ... Show more content on Helpwriting.net ...
Sometimes the estimated loadings from a factor analysis model may give a large weight on several
factors for some of the measured variables. This makes it difficult to interpret what those factors
represent. In order to make it easy to interpret the factors, rotation of factors is done. Rotation does
not change the basic aspects of the analysis. Rotation helps to make the results more understandable
by giving a simpler structure [8]. Rotation allows the items to group into factors more distinctly. It
reduces ambiguities occur in the preliminary analysis. Ultimately, the simple structure attempts to
have each factor define a distinct cluster of interrelated variables so that interpretation is easier

Mcknsey 7S Model Framework Analysis: Walmart
The McKinsey 7S Model Framework Analysis Walmart holds a reputation of supplying services in
most global markets. The company is the world's largest revenue generator, which makes use of its
brand name to market its products. The retail brand focuses on increasing it convenience, value of
money, and offering a wide range of products in its stores. It has also realized its strengths of market
influence, low prices, high competency, large distribution networks, and wide stores. The retail store
has a team of experts that focus on aligning its internal factors to keep the store competitive and
efficient when conducting its operations. This section of makes an evaluation of the market internal
factors in Walmart using McKinsey 7S Model framework. ... Show more content on Helpwriting.net
...
Using the framework, seven internal factors will be considered. These include strategy, structure,
system, shared values, style, staff, and skills. An analysis of Walmart using these internal factors will
determine if the organization is ready for a change. The framework will also help strategizing means
of improving the company's performance, examining future likely effect of undergoing a change, the
right process during merger acquisition alignment, and formulating the best means of implementing
strategy proposed. Strategy Walmart has the strategy of maintaining a comparative advantage in the
sale of products outside its stores. Comparative advantage is the art of selling goods and services in
markets a lower opportunity cost than other participants in the same field. Walmart achieves low
cost efficiency in by buying from producers at a discount before offering to consumers at a lower
cost. The company positions its strategy at archiving optimal sales by offering the lowest prices than
competitors. The Structure of the

The Psychometric Properties Of Connor Davidson Resilience...
Resilience is of great importance for individuals working in complex and instable environments.
Individual Resilience is the ability of the individuals to bounce back and sustain in the facade of
adverse conditions. Research revealed that resilient employees are more likely to be productive,
agile and innovative during the turbulent times, thereby making it essential to have an individual
centric measure of resilience. Many such instruments are available in the literature but there is no
resilience scale widely accepted by researchers and most importantly none of the instrument has
been used to measure the resilience capacity of IT employees. The current study examined the
psychometric properties of Connor–Davidson Resilience scale in the sample of Indian IT
Executives. Data was collected using 25– Item CD–RISC scale from 160 employees of 12 IT firms
located in Chandigarh tricity region. The result of exploratory principal component factor analysis
with varimax rotation and Confirmatory Factor Analysis verified the original five factor structure as
given by Connor and Davidson (2003). In this study 74% of variance was jointly explained by the
five factors. The result supported the dimensionality, reliability (α = 0.85) and validity of the CD–
RISC scale for measuring the IT Executives resilience. The results of the study helps in representing
individual resilience as first order construct made up of 5 dimensions: Personal competence, High
standards and Tenacity, Trust in

Factor Analysis: Stages Of Factor Analysis Decision Process
3.2.1 Stages of Factor Analysis Decision process
Factor analysis is a statistical method, which is used in multivariate to describe variability between
correlated variables they are known as factors. These factors are assumed to represent the
dimensions within the data. The information which is gathered by performing factor analysis can
later reduce the set of variables in a dataset. The basic concept of factor analysis is to represent a set
of variables by a smaller set of variables.
The primary purpose of factor analysis is to define the underlying structure between the variables in
the analysis. Factor analysis condenses the information into smaller sets of variates (factors), with
minimum loss of information.
There are five stages, ... Show more content on Helpwriting.net ...
· Q factor analysis: Correlation matrix of individual variables based on their characteristics.
Condenses large number of people into distinctly different groups.
Achieving data outline vs. data reduction
Data outlining: If it is the definition of a structure, then the set of variables, which are in a
generalised format can be obtained from different ranges. The linear composite of the variables from
the generalised sets is known as variate or factor.
Data reduction: Replacing the previous original values completely with a new set of variables with
empirical value (factor score).
Variable selection: It is the process of picking a subset of variables to be used in model construction.
The analyst must consider the conceptual ideas of the variables and use judgment to the fit of the
variables to conduct factor analysis.
Utilising factor analysis with other multivariate techniques: Is the numerical value which indicates
the relative standing on a latent factor.
Stage 2: Designing a factor

10 Case Study Analysis Example
10 Case Study Analysis
Generally, there are four strategic approaches for case study analysis as identified by (Yin, 2014),
namely, theoretical proposition reliance, ground up data strategy, descriptive and plausible rival
explanation. Theoretical proposition strategy conforms to the idea of data been analysed based on
the theoretical position of the research and study objectives (Gray, 2014; Yin, 2014). On the other
hand, different analytical methods can be combine with analytical strategies in qualitative studies
analysis such as pattern matching, time series analysis and thematically analysis (Braun & Clarke,
2006; Yin, 2014). Due to the nature of this study, thematic analysis technique is employed. Thematic
analysis is a technique ... Show more content on Helpwriting.net ...
The company business operations span across all business sectors and the most expansive of it is the
cement manufacturing. With more than 10,000 employees, the company has established itself
domestically and internationally especially as a major FDI investor in Sub–Saharan Africa (SSA).
Also, company AD has wholly owned subsidiaries in 16 countries – Ghana, Senegal, Niger, Cote
d'Ivoire, Sierra Leone, Liberia, Mali, Kenya, Cameroon, Rep. Congo, Ethiopia, Tanzania, Zambia,
Zimbabwe and Nepal except in South Africa (SA) where the company has 64% stake in partnership
investment. On top of that, the company also have a procurement office in Europe and a plan for
Asia entry in 2018. AD internationalisation and foreign investment started around 2003 after the
Nigerian Government around 2001, 2002, decided to encourage local manufacturing and place
restriction on importation of cement. Afterward, it became the organisation strategic policy to
actually go and expand by first entering into nearby markets with prospect of growth. Company AD
is now the major player in Nigeria market having more than 40% market share in their products line
as well as in some SSA countries such as Senegal and

The Importance Of A Parallel Analysis Using The Program...
Another way to identify the number of factors to retain is to perform parallel analysis. Following the
steps provided by Pallant (2016), I carried out the parallel analysis using the program Monte Carlo
PCA. The results from this analysis recommend retaining only three factors (components for)
further investigation. In order to discriminate the factors (and make the interpretation of them
easier), two main and the most common, approaches to rotation will be employed. These are the
orthogonal (and specifically the varimax rotation) and the oblique rotation (and specifically the
direct oblimin method). Orthogonal factor solution assumes that the factors are not highly correlated
with each other whereas in the oblique rotation the factors allowed to correlate with each other.
Because of the nature of the constructs under investigation, I believe that the factors within the
questionnaire are correlated. Following the recommendation of Pallant (2016), I will run the
analyses using both orthogonal and oblique rotation approaches and I will finally report the one
which provides the clearest and the easiest interpretation results. I looked at the Rotated Component
Matrix in order to examine the factor loadings for each variable. Factor loading is the relationship
between a variable and a factor. In the rotated component matrix, factor loadings less than 0.4 are
not displayed because I have asked for SPSS to suppress coefficients (loadings) less than 0.4. For all
the factor

Principal Components Analysis ( Pca ) Versus Principal...
Principal Components Analysis (PCA) versus Principal Axes Factors (PAF) and Other Extraction
Methods
Broadly, conducting factor analysis (FA) allows a researcher to analyze or interpret his or her data
(e.g., measured variables) by reducing those variables into factors or components that underlie the
structure or explain the greatest amount of variance in the data (Thompson, 2004). Thompson
(2004) also tells us that FA may be used for many purposes, the most common of which is to
uncover a relationship between variables, to develop "theory regarding the nature of constructs" (p.
5), or to evaluate the validity of observed scores. To accomplish this analysis, the researcher uses
statistical software, such as the Statistical Package for ... Show more content on Helpwriting.net ...
The present paper describes the most common factor extraction methodologies and highlights
differences, similarities, and important considerations when conducting a factor analysis.
Terminology of Consequence
Before continuing, some basic terminology used in discussion of factor analysis and factor analytic
methods should be clarified. Communality coefficients (h2), according to Thompson (2004), reveal
"...how much of the variance of a given measured variable was useful in delineating the factors as a
set" (p. 20). Alternately, communality coefficients represent the proportion of that variable's
variance that is explained by the underlying factor. Additionally, the communality coefficient can be
thought of as a lower–bound estimate of a score's reliability (Thompson, 2004).
Sources of error and their effects must be understood as well. Sampling error is error unique to each
sample drawn or selected; so, the sampling error in two different samples are each different

Factors Affecting Usefulness of Social Networking in...
Factors Affecting the Usefulness of Social Networking in E–learning at German University of
Technology in Oman Revinson G. Martin "what are the factors affecting the usefulness of social
networking in e–learning at GUtech"? This will help the university administrator, students, and
educators to know the value of social networking in e–learning and will help and guide those who
develop, implement, and deliver e–learning systems. There are many social networking sites
available that the researcher perceived to be useful in the academe. However, the researcher have
used Facebook group for this study because of its popularity to the students and educators of
GUtech. II. BACKGROUND OF THE STUDY The TAM developed by Davis is one of the most ...
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However in Oman, some in the academe have not caught up with the social networking trends.
Sometimes the use of the technology in the classroom is not allowed. Few traditional educators use
the technology when they are communicating with their own colleagues. Everyday many students
are spending countless hours immersed in popular technologies–such as Facebook or Twitter–which
at first glance may seem like a waste of time, and brain cells. But the social networking technology
deserves a second, deeper look at what is actually going on [2]. GUtech is currently using a moodle–
based e–learning management system to help educators create online courses and support to
students. The university would not allow the educators and students to use social networking like
Facebook for some safety and cultural reasons. Social networking if properly used would bring
endless possibilities of online collaboration resulting good effects to the students. To effectively
implement social networking in e–learning, the students and educators of GUtech need to use it and
integrate testing and assessment tools throughout the learning process. This study extended the TAM
and answered the question PEU Fig.1. Technology Acceptance Model III. REVIEW OF RELATED
LITERATURE There were researchers that have continuously reported that the TAM was very
useful in predicting and explaining technology use in various

Online Purchase Behavior Of Consumers
Introduction
This chapter describes in detail the type of research method adopted, how the data was collected,
purpose of data collection and how this data will be analyzed to derive conclusive results. In the end
ethical issues have been discussed. The study aimed to understand the online purchase behavior of
consumers in India. The factors leading to an increase in online shopping, current trends in the
online retail market and to identify the demographic factors which influence the online purchase.
The literature review highlighted and identified important factors which influence behavior and
attitude of online consumers. These factors were considered and implemented while designing the
questionnaire.
Methodology
This research consists of both primary and secondary data. The secondary data was collected from
various sources such as academic journal, e–books, corporate annual report and library sources
related to the research topic, online purchase behavior of consumers. The primary data was collected
by using the quantitative research method. This method involves usage of numbers and statistical
techniques to measure and identify underlying patterns. Researcher's personal involvement is
required and the results obtained can be used by other studying the same field (King et al., 1994).
Quantitative methods assume that behavioral patterns can be described with the help of objective
facts and therefore holds a positivist position (Firestone, 1987). Factor analysis was used

Internal Factors: Situational Analysis Of Apple
V – Situational Analysis
A. SWOT
A.1. Internal Factor Analysis Summary (IFAS)
Internal Factors Weight Rating Weighted Score Comments
Strengths
S1: Apple has its strong market position and consumer trustworthiness.
S2: Apple chosen as the most pioneering company in the world.
S3: Apple has a strong marketing and advertising teams. .20
.15
.15 5
5
4 1
.75
.6  The major strength of Apple has its strong market position and consumer trustworthiness which
in turn to increases company's competitive advantage. Second, Apple has a full variety of software,
products and apps which are interlinked and maintain each other. Third, iTV and other new products
will be released soon.
 The Apple ... Show more content on Helpwriting.net ...
The power of Apple iOS can be dominated by Android OS.
 Samsung is the only one who provides application processors to Apple and it has asked to pay
higher price for it. It should be asked Apple to pay more because there are no feasible substitutes
who could provide Apple to application processors (Jung, 2011).
Total 0.50 1.68
Grand Total 1.00 3.4

The External Factor Analysis Summary (EFAS) is also above average, a 3.4. This just means that
Apple Company knew how to juggle its opportunities and its threats. They wisely take advantage of
any possible opportunities for further development and growth of the company. On the other hand,
they handle and deal with threats with utmost caution and they strategize on how to minimize these
threats.
A. 3. SWOT Matrix
Strengths–Opportunities Strategic Options
(Offensive and Proactive Actions) Weaknesses–Opportunities Strategic Options
(Defensive and Proactive Actions)
1. Use their current market position to help influence and promote awareness of their product.
(S1,O3)
2. Continue developing technology. (S2,O1) 1. Promote to business the safety of a having a worm
and virus free computer by using their products.

Exploratory Factor Analysis Essay
The results indicated that the Cronbach alpha for climate for sexual harassment measure was well
above 0.70 as recommended by Nunnally (1978) i.e. 0.934. The corrected item–total correlation for
all the items within the scale was positive and exceeded the value of 0.3 by a wide margin (Pallant,
2005). An examination of the scale's inter–item correlation matrix indicated that the scale showed a
moderate to strong positive correlation between all the items within the scale (Gliem & Gliem,
2003). The result determined that all items within the scales were stable enough to assess the
intended construct. Exploratory factor analysis was utilized to determine the construct validity using
principle axis factoring with varimax rotation. For climate of sexual harassment, the value of
Kaiser–Meyer–Olkin (KMO) was .919 which is superb (Hutcheson & Sofroniou, 1999, p 224–225)
and the Bartlett test of sphericity was highly significant (p < .001; df=55; Approx. Chi–
Square=2777.314) thus, supporting the factorability of the correlation matrix, proving that the factor
analysis was appropriate (Table 4). An examination of the correlation matrix disclosed many
coefficients of .3 and above and there no values that were above .9, indicating that there's no sign of
... Show more content on Helpwriting.net ...
The analysis divulged the presence of a single factor with eigenvalues exceeding 1; the first factor
accounted for a variance of 6.809 explaining 61.904 % of the total variance (Table 43). The
interpretation of the one factor was consistent with the definition of climate for sexual harassment
which was labelled as "Climate for sexual harassment". The factor loadings in the rotated factor
matrix for all the singular items were more than .6, thus proofing convergent validity (Table 4).
Furthermore, all items had loaded significantly on to one factor, hence proofing discriminant
validity. The result of the analysis supports the use of the

Analyzing The Strengths Of Qualitative And Quantitative...
Q–methodology was first introduced by psychologist William Stephenson (1902–1989). "Q–
methodology combines the strengths of both qualitative and quantitative methods" (Brown, 1996).
The method is one that studies subjectivity and can be used on various researches. Subjectivity can
be defined as "a person's communication of his or her point of view" and it is always stems from a
person's "internal frame of reference" (McKeown & Thomas, 1988). An internal frame of reference
can refer to the personal viewpoint of the respondent; in this research, it is the viewpoint of several
people for reasons why project are delayed. This frame of reference has been established through the
experience of working on or being in other ways involved in ... Show more content on
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Hence, this reference provides much more information than a 'yes, no' question ever did (McKeown
& Thomas 1988). Q–methodology uses the concept of ranking as simplified in Table 4.2. By asking
multiple people from SHTC to rank the 40 statements, the prioritization of these criteria comes
forth. All statements are based on people's opinion on why project delay, yet the comparison with
other people's opinions and ranking the statements will bring about the real subjectivity (Brown,
1993). 4.1.2 The Q–analysis process As the method revolves around the ranking of statements, the
process starts by defining these statements. This set of statements, also referred to as the Q–sample,
should comprehensively represent the concourse: the sum of all things people say or think about the
issue being investigated. The concourse is most typically collected through interviews and focus
group discussions. In addition, sources such as publications, essays, or any other sources related to
the issue may be used. The collection of the concourse and the Q–sample is described in the
previous chapter. What is in fact investigated is not just the concourse itself, but the inherent
"operant structure" that exists in the concourse or the Q–sample (Dryzek, Clark, & McKenzie,
1989). The Q–sample often exists of statements, however, it can be created from basically anything:
from words to paintings or even songs (Brown, 1996). With the Q–sample, the respondents can
participate in the

Case Study Of Activia Yogurt Honey As A Health Industry
I. Introduction
Cultural factors
In terms of cultural behaviours, the contemporary trends seem to mesmerize the customers with
several dimension of euphoria associated with it and simultaneously advocate their buying
behaviour.
Social factors
Social behaviours, on the other hand seem to tend the consumers to buy a product out of their self–
consideration since they are conditioned not to flaunt any social misery regarding a particular
product.
Individual factors
Buying decision of the customers depends on the individual choice apart from the conditioning of
the external factors that have been mentioned. Individual factor is dominated by the demographic
identity of the individual as well as the requirement of the person that needs to be ... Show more
content on Helpwriting.net ...
II. Overview of the company
Danone is a French multinational conglomerate that chiefly deals with food products and has been
enjoying more than 130 markets across the globe. In this regard, it seems imperative to note that
from 2015 onwards the fresh dairy products of Danone seem to represent a majority of their total
sales characteristics (www.dannon.com).
The yogurt in nutrition initiative that Danone Institute International took along with several other
units to promote the consumption of a balanced diet seems to consolidate with their stature as a CSR
conscious brand. The launching of Activia Yogurt Honey as a health drink seems to be a strategic
step to spread their vision regarding nutrition and balanced diets.
III. Critical analysis of social factors and individual factors
1. Social Factors
While studying consumer behaviour, Danone discovered that social conditions could be considered
a prime factor that is potent enough to make a difference. Social factors are also considered in this
regard since it takes the notion of financial intermittency into account that can be considered as a
major regulator of buying behaviour of the customers of

Tourism Research Topics
The Influence Of Shopping Motivation, Optimum Stimulation Level And Cognitive Response On
Store Patronage Satisfaction: A Case Of Indonesia Tjong Budisantoso, Notre Dame University
Katherine Mizerski, Edith Cowan University Abstract This study focuses on the relationship
between shopping motivation, optimum stimulation level and cognitive response and store
patronage satisfaction. Shopping motivation focuses on the hedonic motivations for shopping while
cognitive response is measured in terms of the perception of merchandise quality and the perception
of service quality. The results indicate that a moderate relationship exists between shopping
motivation and the perception of merchandise quality and service quality. In turn, these ... Show
more content on Helpwriting.net ...
Cognitive Response The environment offers non–verbal communication for individuals (Broadbent,
Bunt and Jencks, 1980; Rapoport, 1982 and Bitner, 1992). This view is supported by Ittelson (1973)
in his characterization of environments: "...environment always provide more information than can
possibly aroused....Environment always represent, simultaneously, instances of redundant
information, of inadequate and ambiguous information, and of conflicting and contradictory
information" (p.75). If a person is motivated to interact with the environment, this interaction would
stimulate a cognitive response. It is possible for this response to be integrated into a personally
meaningful perception which influences people's beliefs about a place, people and product (Rogers,
1979; Golledge, 1987; Kaplan and Kaplan, 1982 and Rapoport, 1982). In the retailing literature,
there is some support for the view that store environment can induce cognitive responses which in
turn may affect shopping behavior (Marzuky and Jacoby, 1986; Ward, 1992; Sirgy et al., 2000).
Bitner (1992) proposes a conceptual framework explaining how the store atmosphere influences the
approach–avoidance behavior through intervening variables. These intervening variables are
emotional response, cognitive response and

Four Factor Analysis Paper
The CFA results provided support for the four – factor model indicating the distinctiveness of the
four variables. The chi– square value for the variables. The chi – square value for the four factor
model (chi– square =4816.468, df = 246, p= 0.000) was lower than those of three factor – model
(chi– square =5247.931, df = 249, p= 0.000), the two– factor model (chi– square =6855.536, df =
251, p= 0.000) and the one factor model (chi– square =9540.195, df = 252, p= 0.000). Furthermore,
the fit indices revealed a better fit for the four factor model (TLI= .730, CFI= .759, RMSEA= .246)
relative to the three – factor model (TLI= .708, CFI= .736, RMSEA= .249), the two – factor model
(TLI= .617, CFI= .652, RMSEA= .285) and the one factor model (TLI= ... Show more content on
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Moreover, the findings declare that psychological safety fully mediate the relationship between
proactive personality and voice behavior meaning that when the employees be proactive, they need
to feel with psychological safety to voice their concerns and interests. Furthermore, the findings
proved that psychological safety partially mediate the relationship between supportive leadership
and voice behavior meaning that when the employees perceive their leaders as supportive, they may
need to feel with psychological safety to voice their concerns and interests, since the supportive
leader will provide him with support , that it avoiding him from fearing of punishment , thus
encouraging him to speak. Unlike the proactive personality construct, if the employee were
proactive, he needs necessarily to fell with psychological safe to voice, if he would not feel with
psychological safe, he would not voice because of fearing of

The Extraction Of Factors And Factors
The extraction of factors helps to determine the loading of factors. The factor loading matrix is
shown below and is estimated with two common factors. The first column of the matrix depicts the
first unrotated factor and it can be analysed that the first factor puts maximum and approximately
equal weights to the first, second and fifth variable. And, it puts the minimum weight to the third
variable, electricity. On the other hand, the second unrotated factor places the least weights to the
first and second variable, while putting the highest weight to the third variable.
Factor Loadings =
Scatter plot of Unrotated Factor Scores
The Figure. 15 shows the scatter plot of Score2 vs. Score1. It is clear that the 15th observation has
the ... Show more content on Helpwriting.net ...
Selecting an appropriate rotation is difficult task. Hence, it is preferable to perform both rotations on
the factors.
Varimax rotation technique results in high loading of each variable on a few number of factors,
ideally on one factor and hence resulting in better factor analysis. The Figure. 18 shows the biplot of
loadings of varimax rotated factors. It can be seen that in order to bring the loadings close to zero or
one, varimax has rotated the axes. The four variables are close to first factor axis. While, the third
variable lies approximately on second factor axis. Hence, the results of varimax rotation are
satisfactory because most of the variables are near to the factor axis. Figure. 17
Promax rotation can be used incase we are not able to obtain the satisfactory and simple set of
factors with an orthogonal rotation. The promax rotation allows the factor axes to have an oblique
angle between them. The Figure. 19 shown belows depicts the promax rotation. It can be seen that
the variables 1, 2 and 5 are close to the first factor axes and third variable is close to the second
factor axis. The data is better accomodated in an oblique rotation. The two latent factors can
describe variability of buildings and agriculture, which are having high impact on greenhouse gas
emissions.
Figure. 18
To understand how the rotated and unrotated solutions are related to each

Case Study: Bajaj Insurance Company
Major complaints received by customer care:
Complaints' Bajaj Component 1 2 3 4
Delays 0.498 Claim Related 0.428
Unsatisfactory Settlement 0.367 0.564
Premium and Rating 0.725
Cancellation
Impolite response from the employees 0.575
Failure to fulfill the promise 0.519
Riders Related 0.423 0.666
Difficulty in getting information
Service Quality .688
Factor Loadings 1.73 1.45 1.34 1.03
Total Variance 17.32 14.57 13.46 10.35
KMO Alpha 0.54 Sig Value 0.000**
Source: Field Survey Source: Field Survey
The above table exhibits factor analysis results for the major complaints received by Bajaj Insurance
Company. The results are categorized into four significant factors with KMO alpha 0.54 and
significant value 0.000**

Standard Deviation and Double Degree Essay
1.0 Introduction This report will cover the distribution of final exam results for BSB123 and what
factors influence the results. Factors that will be considered are the gender of the student, whether
the student is studying a double or single degree, the results from the weekly quiz's and the grade
achieved on the mid semester report. The presence of outliers will be determined to help analyse the
accuracy of the data. There are an infinite number of internal and external factors that contribute to
the outcome of a single exam result. Beaty, & Barling (1982) explains how factors such as stress and
anxiety can contribute to low test results and they give several self help solutions of how to boost
ones success. This report will ... Show more content on Helpwriting.net ...
4.3 Quiz Results Analysing the effect that the weekly quiz results have on the final exam results can
help to understand if high quiz results mean high exam results. Figure 5.0 The data in the above
scatter plot shows that there is a correlation between the quiz results and the exam results. R² =
0.536, which indicates that about 54% of the variation in the average of the quiz is accounted for the
linear relationship with the exam results. In other words, about 46% of the variation is not explained
by the least–squares regression line. 4.4 Report Results The last exam factor that will be addressed
in the bivariate section is the impact of the results from the mid semester report on the exam results.
Figure 6.0 The correlation between the report results and the final exam results in not over
whelming storage. The trend line in the graph can be seen as slopping upward from left to right
showing that. It can be seen that the majority of students that achieved well on the report also
achieved well on the exam 5.0 Trivariate analysis Trivariate analysis compares tree factors against
each other in order to help better understand the exam out comes. 5.1 Degree vs. Exam & Quiz
Figure 7.0 Figure 7.0 states that students who are doing a double degree achieve higher marks
compared to the students who are doing a single degree. On average it can be seen that over

What Is The Five Forces Analysis Of Tesco
1.4 Porter's five forces analysis of Tesco: 1.4.1 Threats of substitute products and services: In the
retail markets the threat of substitute products and services is relatively low for food items and
medium to high for the non food items. 1.4.2 Threats of new competitors: There are various
competitors in the online shopping retail business. Anyone cannot enter in the industry. The threat of
new entry into the retail business is low. Again the recession has made several restrictions for the
competitors to enter in this business. 1.4.3 Competitive rivalry: There are numerous rivals in the
online retailer in the whole Europe. These online retailers are trying to enlarge their. The position of
the competitive rivalry is relatively high 1.4.4 Bargaining power of buyers: There are huge ... Show
2) Establishment of multichannel leadership in all markets. 3) Purchase the disciplined international
growth. Through improving the following strategies Tesco could design better strategies: To build a
better Tesco continue the investment in a strong UK market. In last two years Tesco invested 1
billion euro in six area Service and staff: More 8000 new employees have been allotted and 25000
staff has been taken training. It has rescheduled 300000 hours to make sure sufficient staff at the
right time at the right place. Stores and format: To ensure better store environment and highlight the
departments that concerns most of the buyer's most significantly fresh food Tesco has refreshed over
a third of the UK stores. Range and quality: Through world class testing program to ensure product
quality Tesco has successfully upgraded 8000 of its products and 5300 has been tested. Price and
value: Logical, competitive and affordable price are quoted by Tesco itself. It is considered that
customer will trust the price and it will also be stable. By assuming the importance of pricing Tesco
has promoted prices over the last years. Brand and

Lipsle Analysis Case Study
A STEEPLE analysis is a strategic marketing tool that allows business owners to take a closer look
at the external factors that could affect the day to day running of the business. The external factors a
STEEPLE analysis includes are sociological, technological, economic, environmental, political,
legal and ethical.
After reading the (EMA, 2016) case study, it was clear that sociological factors affect Leon
substantially. One factor that has affected Leon is education; this is due to the new training
programme, Wing Tsun, Vincent has adopted in a bid to improve performance, reduce wastage and
promote staff wellbeing. Since starting, Leon's baristas have knocked 30 seconds off their time
which is now 4 minutes 30 seconds to make 6 perfect ... Show more content on Helpwriting.net ...
Additionally, another factor that I found within the (EMA, 2016) case study was that Leon plan to
open its first site outside of the UK, which will be located within Amsterdam's Schipol airport and
will be the first of a few sites within northern Europe. This will impact Leon greatly as increasing
the number of chain restaurants will be costly at first but then will provide further income which
will boost their economic growth.
After reading the (EMA, 2016) case study, I found that environmental factors affect Leon but not a
substantial amount. For example, Leon's new training programme, Wing Tsun, is not only a way to
improve performance but also to reduce wastage. This new programme was introduced after
Vincent, the co–founder of Leon, stated in an interview that 'the purpose of business should be to
make the lives of humans and the health of the planet better.' Therefore, by introducing the new
programme that helps reduce the wastage of Leon's restaurants, Vincent's company is helping the
health of the planet.
Leon may have political factors that affect their business on a day to day basis but there wasn't any
relevant information in the case study regarding politics. Therefore, I can't comment on how
political factors affect Leon.
A legal factor that was present in the (EMA, 2016) case study was taxation, particularly the 'sugar
tax'. Leon has put the 'sugar tax' into practice by adding an

M3 Team Assignment: External Factor Analysis . By Team
M3 Team Assignment: External Factor Analysis
By Team Einstein: Andrew Clapham, Benjamin Coyle, Joseph Leon, Ria Shields, & Tim Riley
Raymond A. Mason School of Business, The College of William & Mary
BUAD 5907 (A2): Strategy
January 29, 2017
Introduction The Ford Motor Company is a multinational automobile company that is headquartered
in Dearborn, Michigan. They produce a wide range of vehicles that are sold around the world, and
based on sales, they are the fifth largest automobile manufacturing company in the world (David &
David, 2017). This paper is a case study of the external factors that affect the Ford Motor Company's
strategic planning. It will use three tools to analyze Ford's strategic position. The three ... Show
Competition from auto–makers with regards to vehicle financing options. Bargaining Power of
Suppliers (Moderate)
Suppliers have limited bargaining power: Globalization increases number of available suppliers.
Supplier capital investment needed to manufacture parts limits bargaining power (i.e. cost to re–tool
or cost of losing contracts).
Market climate and quality issues may raise or lower bargaining power. Potential Development of
Substitute Products (Moderate)
Competition among competing models of vehicles; similar models/substitutes across manufacturers
exist.
Parts manufacturers produce replacement and aftermarket parts that undercut genuine automaker
parts.
Public and private transportation options (Bus, Uber, Trains, Lyft, Taxi, and etc.).
Potential Entry of New Competitors (Low)
High barriers to entry; large amount of capital required to develop, manufacture, and sell.
Economies of scale difficult to achieve as a new competitor. Bargaining Power of Consumers
(Moderate)
Cost to switch is moderate; vehicles in similar classes hold similar prices.
Market climate may allow some bargaining power.
High competition allows some bargaining power.
Sources: David & David (2017) and Ferguson (2015)
External Factor Evaluation Matrix

The External Factor Evaluation (EFE) matrix below in Exhibit 2 depicts Ford's opportunities and
threats from the outside market. After an evaluation of 20 factors, the organization performed
slightly better than

Confirmatory Factor Analysis Paper
In order to examine the first research question, which focuses on whether the two sets of
environmental behaviors are essentially the same or not they are systematically analyzed using
confirmatory factor analysis. The foundation of this analysis relies on the fact that environmental
behavior may take many forms and that those who are concerned about the environment may
engage in some behaviors more so than other forms. This possible difference in engagement may be
due to opportunity structures that help or hinder the feasibility of engaging. For example, if one does
not have access to a curbside–recycling program, it would follow that the likelihood of engaging in
this specific behavior would be lower than someone who did. This is just one ... Show more content
on Helpwriting.net ...
These included Akaike Information Criterion, the Bayseian (Schwarz) Information Criterion, the
Tucker–Lewis Index, the Comparative Fit Index, the Standardized Root Mean Squared Residual,
Root Mean Squared Error of Approximation, and the Co–efficient of Determination, which are all
obtained via the ESTAT command. Each of these measures has their own criterion that demonstrates
good model fit. I used these in order to determine which model fit the best when the modification
indices above provided several possible final steps in creating the best overall fitting model. What I
mean by this is that in some cases, the modification indices had two suggested paths to add and
regardless of which one was added the model would fit the same, or nearly the same–hundredths of
a point difference in Chi–Square value. Thus, I added each path in separate models, and utilized the
above fit statistics to assess which path offered the best fitting model. In most, if not all, cases these
measures were near identical. Thus, the final model and path selection relied on which path had the
greatest substantive meaning to the analysis, while not compromising overall model fit. The analysis
went through this process for each year and each latent construct

Examples Of Pestle Analysis In Business
A PEST analysis is a business measurement tool. PEST analysis is simple and widely used tool in
order to help you analyse and understanding market growth or decline in business environment.
PEST analyse refer to Political, Economic, Social and Technological factors. These four factors can
affect the organisation and the prevailing factors in the present scenario. The political arena has a
powerful influence upon the regulations of business and the ability of expenses of consumer and
other businesses. The economic environment factor is a direct influence on all businesses. As we
know from our lesson in the marketing environment there is microenvironment, and internal
environment is a microenvironment. The sociocultural environment shows that everything which in
related with social and cultural within a nation or society. For example like the attitudes and
opinions of consumer or the media views. Moreover, technological factor is refers to competing
technology development. Nowadays, the advance and maturity of technology has a huge effect in
business world either positively or negatively impact. PEST analysis identifying and analysing the
external factors gives an overview of the universal conditions and ... Show more content on
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Usually, there is no culture or mores which are against the oil and gas industry. The worker work in
relaxing working hours and for the professional and skilled workers can get the higher salary such as
the chief engineer, captain or master of the ship. Most of the population assume this industry like a
necessary for development and will improved living standard in future (Academic Sample Papers,
2015). Anyway, some of the people will think that the oil and petroleum industry is a main source of
pollution the environment. Thus, they think that government should take an action upon the creation
of pollution and start the law for pollution reduction. (UKessays,

Identifying Salient Factors that Affected CRM Process at...
Objectives
In the data analysis, there are two of the main objectives which will be prioritize during the research.
Here are the following objectives regarding the data analysis:
1. To identify salient factors that affected CRM process at Merck–Medco
– Once the obvious factors are being found, the company will be directed to develop the appropriate
measures which would help to process improvement. This factors can be identified through a
quantitative and qualitative method among the representatives.
2. To develop a reliable and valid instrument that will help to assure the effectiveness of the
measures and actions.
– This will then help to fulfil the dissatisfaction among the representatives. So, all of this would
subsequently lead to the successful management of customer relationships..
Analysis
The initial steps to achieve the objectives, the data will be separate into two main parts.
1. Exploratory factor analysis
The first part is related to salient factors will be determined so several measures will be produce in
order to responses to the failure of CRM failure at Merck–Medco. In this analysis, principle of axis
factoring extraction method with Varimax rotation also will be used to see the total number of
factors. The corrected–items total correlation results will be re–evaluated if the factor analysis result
in ambiguous structure. Then, the steps which to ensure all items within a factor measured will be in
similar content would be taken. At each stage,

Analytical Techniques For Marketing : Assignment
MODULE TITLE: ANALYTICAL TECHNIQUES FOR MARKETING
ASSIGNMENT TITLE: EXPLORATORY FACTOR ANALYSIS
NAME: WEI CHENG LIM
STUDENT NUMBER: 120490488
DEGREE TITLE: BA MARKETING AND MANAGEMENT
WORD COUNT: 2493 WORDS
TABLE OF CONTENTS
SECTION NUMBER AND TITLE
1. INTRODUCTION 3
2. THEORY 4 2.1 DATA REQUIREMENTS 5 2.2 THE EXPLORATORY FACTOR ANALYSIS
MODEL 7
3. APPLICATION TO MARKETING 8
4. METHOD 10
5. RESULTS 12
6. MARKETING IMPLICATIONS FOR RESULTS 14
7. CONCLUSION 15 REFERENCES 16
1. INTRODUCTION
In this modern era, the use of the online grocery shopping has increased significantly. There are
numerous online grocers in the United Kingdom including the big chain supermarkets such as
Tesco, Sainsbury and Waitrose. According to IGD (2013), one out of five households in United
Kingdom are buying their groceries online every month. IGD (2013) stated that families, especially
those with pre=school children tend to shop online for groceries. On another note, many people tend
to do their grocery shopping online because of the convenience. For example, there are some people
who prefer online grocery shopping because it saves them precious time. IGD.com (2013) quoted a
shopper saying that the individual finalised his/her idea on the train and arrange for it to be delivered
when the shopper reaches home.

The theme of this study is exploratory factor analysis. The data is made up of the measures
concerned with the

Cluster Analysis And Factor Analysis
Introduction
Cluster analysis has many different algorithms and methods to classify objects(Saunders, 1994).
One of the challenges faced by the researchers in different areas is to organize their data which is
possible by cluster analysis, it is a data analysis tool which focus on classifying the different objects
into groups such that the degree of association of the objects in a same group is highest if they
belong and least if they do not belong. Cluster analysis is a simple term, it does not identify any
statistical method or model and also there is no need to make any assumptions about distribution of
data, it is used to form groups of relevant variables without providing any explanation (Stockburger,
n.d.).
Despite their popularity, cluster analysis do provide a great opportunity for confusion and
misapplication when compared to factor analysis, discriminant analysis and multidimensional
scaling (Saunders, 1994). Both cluster analysis and factor analysis is used to organize the data into
clusters or onto factors, most of the researchers who are new to this concept may feel that these two
analyses are same, but they differ in many ways, the main objective of cluster analysis is to
categorize the data, whereas factor analysis simplify the data, it explains the correlation in a set of
data and relate variables to each other (Verial, n.d.). Cluster analysis and discriminant analysis are
the two terms where we can often get confused, the basic difference between them is

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