Report on Faculty Salary Factors & Innovation in UK Companies

This report investigates the causal factors influencing faculty salary and innovation within UK companies. The faculty salary analysis examines the impact of publication, position, and university affiliation, employing statistical methods like regression to determine significant relationships. The innovation section focuses on the impact of company size and cooperation agreements on innovation likelihood, utilizing ANOVA and cluster analysis to classify innovation patterns. Key findings reveal the statistical significance of several factors on both faculty salary and innovation, providing valuable insights into these complex relationships. Desklib offers this student-contributed report and many other resources to aid students in their academic pursuits.

Individual Report

TABLE OF CONTENTS
Task 1...........................................................................................................................................3
Task 2...........................................................................................................................................6
DISCUSSION................................................................................................................................10
REFERENCES..............................................................................................................................13

Task 1
DISCUSSION
Topic 1:
Could you determine the causal factors (publication, position, university) that have effect on
the likelihood of faculty salary? Please explain the results.
Wage payment is a significant determinant of labor-management relations. Laborers are very
worried about pay levels because their livelihood is linked to the sum of funds they earn.
Managements, on the whole, are hesitant to raise wages because the level of manufacture will
rise, and revenues will fall.
Wage prices are determined by the macroeconomic factors, or market structures forces, which
perform at the national level. When there is a huge requirement for a special type of highly
skilled workers and a smaller deliver, wages will rise. On the other hand, if imports exceed
exports, people will be able to offer low pay rates.
The willingness of a company to earn will have an impact on the wage rate that is earned; if
somehow the company is losing money, it is not really able to earn higher wages. A large
corporation may be willing to pay more now to attract good employees. Staff get paid increased
wages during periods of affluence because organisation likes to share earning with them.
No business can afford to ignore current wage rates. The wage rates paid in the business or by
other businesses in the same location will be used to set wage rates. If a company or unit pays
low wages, employees will leave as soon as they can find another job. It will be impossible to
keep good employees for long periods of time.
In several businesses, salary are linked to the cost of living of the company, ensuring that
workers are paid fairly. The cost of living in a given location has a direct impact on wage rates.
Laborers will accept a wage that will allow them to maintain a minimum living wage.

Earnings will be modified as well terms of price index number. Workers' money supply will be
eroded as the price index rises, and they will earn a living wage. If prices remain stable, frequent
pay rises may not be necessary.
The participation of labourers to increase supply is referred to as efficiency. It also accounts for
the contribution of other production factors such as equipment, metals, and governance.
Increased wages are sometimes linked to increased productivity. If productivity exceeds a certain
threshold, workers may be offered additional bonuses or other incentives. In production plants, it
is normal place to award productivity bonuses. To keep improving labourers' work environment,
the government may pass a bill establishing minimum wage laws. This may provide them with a
minimum standard of living. Labor leverage is weak in developing economies, and bosses
continue to manipulate labourers by charging person poverty pay.
H0: There is no significant relationship between casual factors like publication, position and
university over the likelihood of faculty salary.
H1: There is a significant relationship between casual factors such as publication, position and
university over likelihood of faculty salary.
Model Summaryb
Model R R Square Adjusted R
Square
Std. Error of
the Estimate
Durbin-Watson
1 .659a .434 .428 20677.910 1.396
a. Predictors: (Constant), prof, osu, female, pubindx, assist, assoc
b. Dependent Variable: salary
ANOVAa
Model Sum of Squares df Mean Square F Sig.
1 Regression 185458035781.
828 6 30909672630.3
05 72.290 .000b
Residual 241580416113.
242
565 427575957.723

Total 427038451895.
071 571
a. Dependent Variable: salary
b. Predictors: (Constant), prof, osu, female, pubindx, assist, assoc
Coefficientsa
Model Unstandardized
Coefficients
Standardized
Coefficients
t Sig. Collinearity
Statistics
B Std. Error Beta Tolerance VIF
1
(Constant) 64884.788 6643.615 9.766 .000
assist -
14300.375 7165.398 -.152 -1.996 .046 .173 5.775
assoc -9498.573 6878.987 -.135 -1.381 .168 .105 9.557
prof 15387.342 6668.421 .257 2.307 .021 .081 12.383
female 2648.341 3283.388 .027 .807 .420 .919 1.088
osu 3606.315 3038.545 .038 1.187 .236 .980 1.021
pubindx 255.486 22.857 .379 11.178 .000 .869 1.151
a. Dependent Variable: salary
Collinearity Diagnosticsa
Model Dimensio
n
Eigenvalu
e
Conditio
n Index
Variance Proportions
(Constant
)
assist asso
c
pro
f
femal
e
os
u
pubind
x
1
1 2.838 1.000 .00 .00 .00 .00 .01 .02 .04
2 1.286 1.485 .00 .02 .01 .00 .23 .01 .03
3 1.014 1.673 .00 .08 .03 .00 .01 .05 .00
4 .845 1.832 .00 .02 .00 .00 .02 .90 .00
5 .702 2.011 .00 .03 .03 .00 .66 .00 .00
6 .306 3.045 .01 .00 .00 .01 .07 .00 .93
7 .009 18.121 .99 .85 .92 .98 .00 .01 .00
a. Dependent Variable: salary
Residuals Statisticsa
Minimum Maximum Mean Std. Deviation N
Predicted Value 50584.41 143862.52 83674.70 18022.074 572
Residual -60905.223 110653.781 .000 20568.982 572

Std. Predicted Value -1.836 3.340 .000 1.000 572
Std. Residual -2.945 5.351 .000 .995 572
a. Dependent Variable: salary
Charts

Task 2
Topic 2:
Questions:
• Could you determine the causal factors (size and cooperation) that have effect on the
likelihood of innovation in UK companies? Please explain the results.
Organizations of all sizes must develop and implement innovative measures to enhance
productivity in their current operations. Machine learning (AI) is being used in factory guidance
and control systems, for example. Slightly earlier activity should be concentrated in a few
centres, according to knowledge. More needs to be done to turn the fruits of early-stage ventures
into thriving businesses. Power supply manufacturing, robotics, and negligible air transport are
all instances. To adapt the quantification between the government and business, a more definite

self evident set of bonuses is required. Within both applying systems to current materials and in
scaling up new ones, the government should be willing to engage in risk - taking up front. This
must be done inside one set of "edge protection" that assures investment with reasonable care
and judgment. Spine profit contribution must reimburse for the choice made. Framework for
evolving tech startups must be offered. Infrastructure for the future must be developed in
collaboration with the industry. The United Kingdom wants to understand where its
competitiveness is now and in the future. It must just sent clear indications to the industry and
advertise innovative thinking in these favoured industries.
• Could you classify the innovation in UK companies in function of the Size and
cooperation agreements? Please explain the results.
The United Kingdom has a long history of using innovation to transform the society. The
influence on daily lives is undisputable, from the Industrial Age to the recent vaccine
development. Researchers want to reignite this passion in all UK citizens, enabling those to
capitalise that the invention economic system will provide. The next ten years will be marked by
significant change. The 2020s are a critical juncture for the UK's long term prosperity, with the
climate change issue and a net zero aim as well as the speed of new innovation. As a result, the
government has released "Build Back Better: A Plan for Growth," that either centred on
connectivity, skills, and entrepreneurship as the foundation for economic revival. From climatic
changes and an eventual decline to global pandemics, pioneered the concept of the world's most
pressing issues. The United Kingdom must be at the forefront of the response to these threats.
Now that we've left the EU, we'll be highly responsive to these challenges, as well as other
possibilities, in order to maintain the UK's global leadership in scientific research, investigation,
and advancement. Besides which, enterprisecan level the growth and promote greater new jobs
and swing trades by bringing improvement in areas, areas, and companies out across UK as
enterpriserebuild better. This UK-wide Strategic Planning lays out thelong-term plan for
supplying innovation-led economic expansion in terms of building on this foundation and seize
this momentous event. Its main goal is to increase private sector investment across the UK by
fostering the right conditions for all enterprises to promote innovation and providing them with
the conviction to do so. Enterprisewill also demonstrate direct leader and action – for example,
by releasing new missions and supporting future technologies – clearly indicating where the

congress will put more emphasis in the future. Innovation is key to the United Empire's recovery.
It's at the heart of 'Build Back Better: ThePlan for Growth,' as well as everything else
enterpriselike to accomplish, from combating the coronavirus (COVID-19) to having achieved
net zero and establishing a Global Britain. Increasing private-sector innovation is critical to the
UK's economic success and to achieving the UK's goals of being a good thing on world - wide
issues such as climate change, wildlife habitat, affluence, and protection. The various elements
that make up innovation – invention, invention, innovation, and surrogacy – are difficult to
separate. Businesses, gov, Technology nonprofits, financial intermediaries, wealthy donors,
foreign organizations, and others must all work together. The primacy of all this broad structure
and if enterprisewill foster it were outlined in the 2020 R&D Roadmap. This Approach
concentrates on how the UK's investigations, growth, and development system can be used to
sustain initiatives.
Factor analysis
KMO and Bartlett's Test
Kaiser-Meyer-Olkin Measure of Sampling
Adequacy. .741
Bartlett's Test of
Sphericity
Approx. Chi-Square 3589.475
df 10
Sig. .000
One way anova
H0: There is no difference being present between the innovation and size or cooperation
H1: There is a statistical difference being present among innovation and size or cooperation
ANOVA
Sum of
Squares
df Mean Square F Sig.
size of company
(staff)
Between Groups 562134.999 31 18133.387 2.080 .000
Within Groups 42627302.564 4890 8717.240
Total 43189437.563 4921

Cooperation
Between Groups 208.855 31 6.737 43.042 .000
Within Groups 765.422 4890 .157
Total 974.277 4921
Cluster analysis
Initial Cluster Centers
Cluster
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
size of
compa
ny
(staff)
3 1 1 4 3 4 1 2 1 3 4 2 4 3 2
Cooper
ation 1 0 0 1 0 1 1 0 0 0 1 1 0 0 1
REGR
factor
score
1 for
analysi
s 1
.40
523
-.83
769
1.61
216
1.61
216
3.03
895
-.83
769
.58
910
.40
523
3.03
895
1.48
589
3.03
895
-.83
769
.40
523
-.83
769
2.24
122
Iteration Historya
Iteration Change in Cluster Centers
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1 .181 .643 .618 .181 .455 .588 .608 .237 .000 .245 .028 .473 .119 .250 .439
2 .120 .014 .279 .119 .170 .000 .265 .135 .839 .058 .196 .085 .092 .000 .297
3 .208 .006 .068 .047 .293 .000 .164 .027 .449 .427 .018 .068 .088 .000 .191
4 .132 .000 .018 .005 .084 .003 .032 .000 .102 .063 .018 .000 .000 .007 .199
5 .015 .000 .000 .000 .014 .023 .016 .000 .213 .000 .000 .008 .000 .000 .064
6 .004 .000 .000 .000 .000 .000 .006 .000 .190 .000 .000 .000 .000 .000 .090
7 .000 .000 .000 .000 .000 .000 .028 .000 .000 .000 .000 .000 .000 .000 .027
8 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000 .000
a. Convergence achieved due to no or small change in cluster centers. The maximum absolute
coordinate change for any center is .000. The current iteration is 8. The minimum distance
between initial centers is 1.414.

Final Cluster Centers
Cluster
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
size of
compa
ny
(staff)
3 2 2 4 3 4 2 2 2 3 4 2 4 3 3
Cooper
ation 1 0 0 1 0 0 1 0 1 0 1 1 0 0 1
REGR
factor
score
1 for
analysi
s 1
.21
653
-.81
170
1.41
498
1.65
127
2.64
904
-.73
102
.75
253
.01
681
2.54
909
.70
937
3.00
655
-.38
827
.10
593
-.59
431
1.59
275
Number of Cases in each
Cluster
Cluster
1 404.000
2 1389.000
3 155.000
4 204.000
5 96.000
6 265.000
7 160.000
8 605.000
9 58.000
10 274.000
11 56.000
12 210.000
13 137.000
14 731.000
15 178.000
Valid 4922.000
Missing 4505.000

REFERENCES
Books and Journal
Bell A., Chetty R., Jaravel X., Petkova N. and Van Reenen J. (2017) ‘Who Becomes an Inventor
in America? The Importance of Exposure to Innovation’. NBER Working Paper No. 24062,
December 2017. The Equality of Opportunity Project. ↩
Gabriel M., Ollard J. and Wilkinson N. (2019) ‘Opportunity Lost: How inventive potential is
squandered and what to do about it’.
IPO (2016) ‘Gender Profiles in UK Patenting. An Analysis of Female Inventorship.’ ↩
Ozgen et al. (2013); Garnero et al. 2014 ↩
Schneider J. and Eckl V. (2016) ‘The Difference Makes a Difference: Team Diversity and
Innovation’
Van Reenen J. (2020) ‘Innovation Policies to Boost Productivity. A policy proposal’. The
Hamilton Project.