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EFFECTIVE RECRUITMENT AND SELECTION SYSTEM FOR
THE IT SOFTWARE INDUSTRY IN INDIA Thesis submitted for the award of the Degree of
Ph.D. (BUSINESS ADMINISTRATION)
ABSTRACT
By
Brigadier. P.K. Saxena
Under the guidance of
Dr. Mohammad Israrul Haque Dr Bhupen Srivastava
Professor Professor
Department of Business Administration Department of Organizational Behaviour &
HRM
AMU, Aligarh IMI, New Delhi
DEPARTMENT OF BUSINESS ADMINISTRATION
FACULTY OF MANAGEMENT STUDIES AND RESEARCH
ALIGARH MUSLIM UNIVERSITY
ALIGARH -202002(UP) INDIA
YEAR OF SUBMISSION 2011
1
EFFECTIVE RECRUITMENT AND SELECTION SYSTEM FOR
THE IT SOFTWARE INDUSTRY IN INDIA
Introduction
The increasing size and complexity of organizations, the intensive use of
technology, combined with changing socio-cultural norms have contributed with
immense complexity to Human Resources Management aspects of managing people in
organizations. The Information Technology (IT) Software Industry in India has attracted
worldwide attention recording phenomenal rates of growth, achieving the status of an
economy driver for a country, emerging as a superpower of the Twenty First Century. It
is equally vital that this trend continues in the midst of global challenges and competition.
While the system in vogue has been meeting the current challenges, little research has
been done to determine the effectiveness of recruitment and selection system for the IT
Software Industry in India. The purpose of this research is to determine an effective
recruitment and selection system and assist the IT Software Industry in India in meeting
the challenges of the coming decades.
Research Objectives
Keeping in view the global demand of software development and the unique
status acquired by the IT software companies in India in terms of quality, cost
competitiveness, availability of trained manpower and the infrastructure, there is a felt
need to shape the IT software industry in India, for the future. For keeping India’s
competitive advantage from declining, it is imperative that an effective system of
recruitment and selection be identified. It has been accepted that certain attributes are
required for employees employed in the IT software development and these require to be
2
tested by a system that can be evaluated for its effectiveness against measurable output
variables that reflect the output / performance of IT software companies. There is also a
requirement to evaluate the domination of certain conditions that software companies
consider such as the academic record, socio economic conditions and work experience,
for their influence on the effectiveness of the recruitment and selection system. Lastly
proper evaluation of other factors influencing effectiveness of output / performance
variables requires to be studied to arrive at a scientific model that will meet the felt need.
This would result in immense savings in time, effort and costs to all stakeholders.
Objectives
The purpose of this research is to determine the key variables in an effective
recruitment and selection system for the IT Software Companies in India. In order to
accomplish the research, the objectives formulated are:
1. To evaluate the various recruitment and selection techniques that IT software
companies in India employ. These include interviews, group tests, psychological tests,
intelligence tests, technical tests and others.
2. To determine key employee skill gauges, like academic record, socio-economic
conditions, overall work experience and experience in a specific field.
3. To determine key company performance metrics, like growth in sales, net profit
margin, revenue/profit growth and average net profit per employee.
4. To determine the relationship between key company performance metrics to
selection techniques, thereby obtaining key variables in an effective recruitment and
selection.
3
Review of Literature
A review of literature was undertaken to study the current state of
recruitment and selection in IT Software Industry in India. It has been accepted that the
quality and maturity of the Indian software industry has been realized globally. With
technology and processes undergoing rapid transition, the investment in human resource
and its development can reap rich dividends. It emerges that India is among the choices
for low cost programmers because of several factors and one of them being the
widespread knowledge of English language. Some of the other important factors that
contributed towards this success are the availability of human capital, especially the stock
of engineers available in India. Another important factor that has contributed has been the
geographical location of the country that has helped several nations explore capability to
operate round the clock. It can also be stated that the base of Indians in every part of the
world also helped bridge several gaps related to red tape and human networking. Not
withstanding these, a dispassionate reappraisal of the education facilities to meet the IT
boom amply highlights that the current system is at best only meeting the present
“demand and supply". Literature highlights that like other countries, India may also face
possibility of an upcoming talent shortage problem on account of a few factors.
The Indian Government has been aware of the complexities and has contributed
by launching a Technical Education Quality Improvement program, accepting of
proposals like setting up venture capital funding, as well as tie-up for bilateral
cooperation in IT Sector with 32 countries. India has also set up an efficient organization,
the National Association of Software and Services Companies (NASSCOM), which
provides reliable information, including individual supplier profiles, through the Internet.
4
The Indian software industry has shown flexibility in growing acceptance and adoption of
the newly emerging standards of quality management such as Capability Maturity Model
(CMM), a worldwide certification developed by the Software Engineering Institute of
Carnegie Mellon University. The quality maturity of the Indian software industry can be
judged from the fact that India has one of the largest number of companies being quality
accredited and serving the needs of the Fortune 500 companies.
The importance of effectiveness in recruitment and selection for organizational
performance has been amply highlighted as being critical to organizational success. One
of the possible ways is by initiating the screening process to include psychometrics with
other tests for selection and recruitment. It is only logical that such psychometric testing
will prove to be scientific and result oriented but whether the IT Companies are
undertaking such processes and incorporating it in their recruitment and selection system
is the purpose of this research. Studies show that Psychometrics is best used in
conjunction with other assessment and selection tools such as interviews. With quality
and cost assuming greater importance, helping the firm save money by reducing turnover
would help to cut expenses and paperwork in recruitment and contribute to the
organization. Several other advantages come to light while undertaking such tests such as
the speed, efficiency and total-in-time recruitment can really reduce the time to hours and
days rather than weeks. There is however resistance to psychological tests in several
countries including China, because such tests result in a potential loss of face for
applicants, are invasive in privacy and also statutory provisions in some countries
prohibit their use. The laws in India permit use of psychometric tests. These have been
used in organizations like the defense forces, where they have stood the test of time.
5
Not withstanding the likely changes in trends of recruitment and selection,
selection for employment in the IT Field is still based on academic performance and
possibly marginally on experience, if considered necessary, by the employer. It is seldom
on aptitude or scientific personality evaluation as done in scientifically selecting
executives or officers as leaders in other industries and organizations like the services. A
query that comes up is if recruitment and selection of a potential IT Industry employee
can be undertaken scientifically, based on aptitude for software programming so as to
make the employment of the professional effective. For this, it is important that IT
companies know what to measure and how to measure when it comes to recruitment.
Countries like China are following closely. Having achieved a great deal to
improve, they are likely to pose a major challenge to India. In comparison with India,
China has an inherent strength as an outsourcing destination. It has a huge domestic
software market that attracts domestic software firms as well as foreign software firms.
Especially, after its accession to WTO, China will promote social and economic
development through the wider use of information technology. China has absorbed
foreign direct investment (FDI) many times than that by India. The information and
telecommunication infrastructure of China is considered superior to that of India. Greater
political and social stability also give the investors more confidence and lastly
competitive advantage of lower cost of manpower in China, is another important factor.
However, there are some aspects, such as quality control processes,
communication/culture etc. where India is far ahead of China. It is vital that this edge
remains with India in the coming decades.
6
Setting of the Research Problem
To state briefly, the research purpose is to determine the key variables in
formulating a model for an effective recruitment and selection system for the IT Software
Industry in India. In order to achieve this purpose, each key research objectives, as
identified earlier pertain to determining the key variables for an effective recruitment and
selection system. Based on those techniques, key employee gauges like academic record,
work experience etc. are identified as “Input Variables”. The attributes that companies
consider essential for IT Software professionals were also identified and these also
formed part of the input variables. The companies’ performance depends on its employee
base without question and these performance indicators are identified as “Output
Variables”. Finally, using various statistical methods, an attempt is made to determine the
relationship between key company performance metrics to selection techniques, thereby
obtaining key variables in an effective recruitment and selection. The methodology used
involves testing those hypotheses using a multivariate analysis scheme. A Conceptual
Model for Research is as given below.
EFFECTIVE RECRUITMENT &
SELECTION SYSTEM
CONTROLLED FACTORS (X1, X2, ..,….Xn)
UNCONTROLLED FACTORS (Z1, Z2 ….Zn)
OUTPUT RESPONSE (Y1, Y2, ….….Yn) INCOMING
WORKFORCE
7
Identifying Key Variables
Broadly the recruitment and selection system could be analyzed in terms of their
criteria for selection, methodology of testing to include number of tests conducted, the
preference given to academic qualification / experience and other back ground
information of potential candidates and lastly the effect of other factors including size
and turnover of the Company as it affected their system of recruitment and selection. The
Pilot Questionnaire therefore elicited response to some of such queries, such as “job
specification”, the criterion taken as a screening factor for inclusion of the IT Software
Companies for the sample taken for research. The next response was “attributes”
considered by IT Software Companies, as essential for software professionals. Based on
the response from IT Companies, a list of 16 attributes (X1-X16) was compiled.
Attributes Input Variables Name
QUES 5 INTELLIGENCE X1
PROBLEM SOLVER X2
CREATIVE X3
FLEXIBLE X4
QUICK TO LEARN X5
PERSEVERING X6
PASSION FOR TECHNOLOGY X7
TEAM SPIRIT X8
PRIORITISES X9
RESULT ORIENTED X10
DESIGN MAKER X11
MOTIVATED X12
DYNAMIC X13
LONG TERM PLANNER X14
ANALYTICAL SKILLS X15
MAINTAIN FOCUS X16
8
Though several other attributes were also listed, these attributes were listed by most of
the companies and hence taken as main attributes for this study.
The next response analysed and taken as input variable has been the number tests
IT Software Companies conducted comprising Interviewing, Group Testing,
Psychological Testing, Intelligence Testing, Technical Testing etc.
QUES 3 INTERVIEW X17
GROUP TEST X18
PSYCHOLOGICAL TEST X19
INTELLIGENCE TEST X20
TECHNICAL TEST X21
OTHERS X22
The preference given to academic qualification / experience and other back
ground information of potential candidates were analyzed as the next set of input
variables.
QUES 4 ACADEMIC RECORD X23
OVERALL WORK EXPERIENCE X24
EXPERIENCE IN THE FIELD X25
SOCIO-ECONOMIC BACKGROUND X26
OTHERS X27
The effect of other factors including size and turnover of the Company as it
affected their system of recruitment and selection were taken as per variables planned
below.
Uncontrolled Factor
Size of company Z1 1-4 1 is <= 1000 employees, 2, 1001-10000, 3
10001-25000 and 4 is > 25000 employees
Turnover </>Rs1500
crores
Z2 1-2 1 less than and 2 is more than Rs1500
crores
9
The key outputs variables (Y1-Y4) for the study, to assess the effectiveness of
the model were percentage growth of sales; net profit margin, revenue/profit growth and
finally and the average net profit per employee, as given below.
Growth in Sales (%age) Y1
Net Profit Margin Y2
Revenue/Profit Growth Y3
Average Net Profit/Employee Y4
Assumptions for the Study
From the response during the interactions and interviews as also to the Pilot
questionnaire served to the IT Companies, it emerged that there is a varying nature of
recruitment and selection system that is unique to each Company. The assumptions
therefore taken at the time of the research are that the assessment and answers given by
the companies will hold for the next five years, the subjects fully understand the
questions and responded honesty; the response given by IT Companies is based on their
company position at the time the questionnaire has been served. It has been accepted that
changing environment can affect economic and output state.
Research Procedure
The research being undertaken is to identify a system of employment selection
that could lead to greater effectiveness of the IT Software Industry and provide a greater
cutting edge to meet future challenges. The research design and the procedure undertaken
for conducting the study comprised instrument development and an initial pilot survey
followed by a compilation of the feedback and statistically testing its validity and
reliability. The data was compiled and a main questionnaire was evolved. The
10
questionnaire for pilot testing comprised a questionnaire design as non- disguised and
structured with approximately 12-18 questions. Due to the variety of respondents in
terms of their turnover, number of employees and diversity in services provided, the
collection of data was unstructured. The professionals who are interviewed or to whom
questionnaires were administered comprised Project Managers, HR Managers, Industry
experts and software professionals who gave grass root inputs. From the size of the
population available, the objective is to have a sample, which represented at least a
population sample with about 95 percent confidence level. The response provided by the
IT Software Companies has been positive but their perception of corporate secrecy and
willingness to part with confidential financial data has been far from positive. Quota
sampling is used for the study of the population.
The pilot survey was sent to about 204 IT Companies identified as part of quota
sampling. The research variables identified were specific qualities and weight-ages, if
any considered for these in effectiveness of the recruitment and selection system. The
number of tests companies employ at the time of recruitment and selection, comprising
combination of interviews, psychological tests, group tests, technical tests and
intelligence tests etc. The numbers of tests conducted by companies were collated and
response was thereafter categorized into three groups. The first group A comprised
companies that undertook 4/5 prescribed tests out of Interviews, Group Tests,
Psychological Tests, Intelligence Tests, Technical Tests and others. The second group B
comprised companies that took 3/5 tests and the last group C comprised companies that
took less than two of such tests. IT Companies were also to respond to the minimum
educational qualities acceptable in terms of 10+2 level, engineering graduate and non
11
engineering graduate, preference of the IT Software Companies to the nature of entry
preferred in terms of IT engineering graduate, other engineering graduate, graduate from
non engineering stream, diploma holders and others. The other variables were the
forecast to meet challenges of the IT Industry in the next 5 years, the evolution of specific
criteria to meet the effectiveness in recruitment and selection of IT Software Companies
and the viability of undertaking psychological testing of the software professionals. A
response was also elicited to identify the possible stage at which the centralized system of
testing could be introduced.
Hypotheses Formulation
Based on the research objectives, the instrument for research (main questionnaire)
helped formulate 12 hypotheses to test relationship between the variables indentified
earlier. The level of significance for rejecting null hypothesis was kept at .05.
Descriptive statistics were computed for all variables before testing the null hypothesis
for means, standard variables, frequencies, percentages and to correlated response values
between variables. The key hypotheses relating to the questions are given below.
While it is widely perceived that greater number of tests would assist in sieving
better candidates in the selection and recruitment, the research tests for hypotheses H1- H4
posit that there is no significant difference in the growth in sales, net margin of profit,
revenue / profit growth or average net profit per employees of the IT Companies.
H1. Increased combination of interviews, psychological tests, intelligence tests,
technical tests and others taken at the time of recruitment and selection for the IT
Software Companies in India does not improve the relationship of growth in sales of IT
Software Companies.
12
H2. Increased combination of interviews, psychological tests, intelligence tests,
technical tests and others taken at the time of recruitment and selection for the IT
Software Companies in India does not improve the relationship of net profit margin of IT
Software Companies.
H3. Increased combination of interviews, psychological tests, intelligence tests,
technical tests and others taken at the time of recruitment and selection for the IT
Software Companies in India does not improve the relationship of revenue/profit growth
of IT Software Companies.
H4. Increased combination of interviews, psychological tests, intelligence tests,
technical tests and others taken at the time of recruitment and selection for the IT
Software Companies in India does not improve the relationship of average net profit per
employee, of IT Software Companies.
Considerable thought is given by IT Companies to the academic record, socio
economic conditions, overall work experience and experience in the IT field while
undertaking recruitment and selection in respective companies but only few IT Software
Companies, across the board, gave any weight-age to the socio economic back ground of
candidates, whereas in assessing the Overall Work Experience, there was much more
agreement. Hypotheses H5-H8 addresses the relative importance of these variables.
H5. The academic record has no domination while overall work experience,
experience in field and socio-economic conditions, have more effect on the recruitment
and selection for the IT Software Companies in India that affects growth in sales of IT
Software Companies.
13
H6. The academic record has no domination while overall work experience,
experience in field and socio-economic conditions, have more effect on the recruitment
and selection for the IT Software Companies in India that affects the net profit margin of
IT Software Companies.
H7. The academic record has no domination while overall work experience,
experience in field and socio-economic conditions, have more effect on the recruitment
and selection for the IT Software Companies in India that affects the revenue/profit
growth of IT Software Companies.
H8. The academic record has no domination while overall work experience,
experience in field and socio-economic conditions, have more effect on the recruitment
and selection for the IT Software Companies in India that affects the average net profit
per employee, of IT Software Companies.
Based on the feedback from companies, a generally common list attributes was
evolved that would constitute the variables. Hypotheses H9-H12 tests the relative
contributions of those parameters.
H9. The combination of various factors considered in the study at the time of
recruitment and selection for the IT Software Companies in India affects growth in sales
of IT Software Companies of all the factors considered for evaluation of the output
variables of most factors did not affect the growth in sales of IT Software Companies.
H10. The combination of various factors considered in the study at the time of
recruitment and selection for the IT Software Companies in India affects net profit
margin of IT Software Companies of all the factors considered for evaluation of output
variables, most factors did not affect the net profit margin of IT Software Companies.
14
H11. The combination of various factors considered in the study at the time of
recruitment and selection for the IT Software Companies in India affects revenue/profit
growth of IT Software Companies of all the factors considered for evaluation of the
output variables, most factors did not affect the revenue / profit growth.
H12. The combination of various factors considered in the study at the time of
recruitment and selection for the IT Software Companies in India affects average net
profit per employee of IT Software Companies of all the factors considered for evaluation
of output variables, most factors did not affect the average net profit per employee of IT
Software Companies.
Research Results and Discussion
For quantitative data sets, the inputs were normalized on a scale of 1-5 to make
them quantitative, with 1 being the least importance and 5 being the most importance. For
qualitative data sets, the inputs were marked as Y/N (Yes/No) and treated as nominal
variables.
For working out the effectiveness of the recruitment and selection system, the
output data had to be evaluated against the input variables. In order to analyze the output
variables, data pertaining to the growth in sales, net margin of profit were gathered from
the data provided by companies and in most cases obtained from the sites showing the
financial results that were public. Thereafter, the revenue/profit growth was worked out
to finally arrive at the average net profit per employee.
15
Results
The results of hypothesis testing for H-1 to H-4 are as given below:
The next vital consideration was the preference to the socio economic conditions,
academic record, overall work experience and experience in the IT field while
undertaking recruitment and selection in respective Companies. The IT Companies across
the board did not give any weightage to socio-economic background of candidates so that
was dropped from the testing. To test the null hypotheses H5 to H8, the response of the
Companies to the question of preference to the academic record, overall work experience
and experience in the IT field was classified into two categories, Group D -Companies
which value academic record but do not value overall work experience and experience in
the field and Group E Companies which value overall work experience and experience
in the field but do not value academic record as much.
Null Hypothesis Test Sig. Decision
1 The distribution of Y1 is the same
across categories of Group Q3
Independent Samples
Kruskal-Wallis Test
0.054 Accepted
2
The distribution of Y2 is the same
across categories of Group Q3
Independent Samples
Kruskal-Wallis Test
0.619
Accepted
3
The distribution of Y3 is the same
across categories of Group Q3
Independent Samples
Kruskal-Wallis Test
0.164
Accepted
4
The distribution of Y4 is the same
across categories of Group Q3
Independent Samples
Kruskal-Wallis Test
0.447
Accepted
16
Based on this classification, the results of the test are below:-
Null Hypothesis Test Sig. Decision
1
The distribution of Y1 is the
same across categories of Group
Q4
Independent
Samples Mann-
Whitney U Test
0.002
Failed to accept
2
The distribution of Y2 is the
same across categories of Group
Q4
Independent
Samples Mann-
Whitney U Test
0.741
Accepted
3
The distribution of Y3 is the
same across categories of Group
Q4
Independent
Samples Mann-
Whitney U Test
0.892
Accepted
4
The distribution of Y4 is the
same across categories of Group
Q4
Independent
Samples Mann-
Whitney U Test
0.397
Accepted
To test the hypotheses H9 to H12, the approach used here is different. A linear
effect model for all inputs was constructed and was fitted using least squares method for
the output responses. These were then fitted using least square method for the out put
variables growth in sales, net margin of profit, revenue / profit growth or average net
profit per employees of the IT Companies. The results of any such model being
17
dependent on the revenue, due consideration had to be given to the uncontrolled variables
and so out of turnover of IT Companies Z-1 and Z-2 , the latter Z-2 was blocked.
For the overall model, the highest correlation is shown for growth in sales with a
significance of 0.024 which indicates >97% confidence in the model. All other factors
show less correlation. Within the model, the attributes (X1-X16) where F is shown ~ > 3
are considered significant. Thus, for the output variables Y1-Y4, the results for
significant effects (with F-factors below) are:
Hypothesis 9 Y1: Quick to Learn (X-5), Team Spirit (X-8), Long Term Planner (X-14)
and Maintains Focus (X-16).
Hypothesis 10 Y2: Maintains Focus (X-16).
Hypothesis 11 Y3: Analytical Skills (X-15) and Passion for Technology(X-7).
Hypothesis 12 Y4: Dynamic (X-13).
Thus, we can say that only for H9 and H11 the alternate hypothesis holds
true. This is also corroborated by the result where for example the growth in sales is
correlated to hiring with real world experience rather than academic tests. For H10 and
H12, the null hypothesis holds true.
Hypothesized Relationship Results
H1. Increased combination of interviews, psychological tests
and intelligence tests taken at the time of recruitment and selection for the
IT Software Companies in India does not improve the relationship
of growth in sales of IT Software Companies.
Accepted
18
H2. Increased combination of interviews, psychological tests, intelligence
tests, technical tests and others taken at the time of recruitment and selection
for the IT Software Companies in India does not improve the relationship of
net profit margin of IT Software Companies.
Accepted
H3. Increased combination of interviews, psychological tests, intelligence
tests, technical tests and others taken at the time of recruitment and selection
for the IT Software Companies in India does not improve the relationship of
revenue/profit growth of IT Software Companies.
Accepted
H4. Increased combination of interviews, psychological tests, intelligence
tests, technical tests and others taken at the time of recruitment and selection
for the IT Software Companies in India does not improve the relationship of
average net profit per employee, of IT Software Companies.
Accepted
H5. The academic record has no domination while overall
work experience, experience in field and socio-economic conditions,
have less effect on the recruitment and selection for the IT
Software Companies in India that affects growth in sales of IT
Software Companies.
Failed
to accept
H6. The academic record, socio-economic conditions, overall
work experience and experience in field have no domination during
the recruitment and selection for the IT Software Companies in India
that affects the net profit margin of IT Software Companies.
Accepted
19
H7. The academic record, socio-economic conditions, overall
work experience and experience in field have no domination during
the recruitment and selection for the IT Software Companies in India
that affects the revenue/profit growth of IT Software Companies.
H8. The academic record, socio-economic conditions, overall work
experience and experience in field have no domination during the
recruitment and selection for the IT Software Companies in India that affects
the average net profit per employee, of IT Software Companies.
Accepted
Accepted
H9. The combination of various factors considered in the study at the time
of recruitment and selection for the IT Software Companies in
India affects growth in sales of IT Software Companies of all the factors
considered for evaluation of the output variables, most factors did
not affect the growth in sales of IT Software Companies.
Failed
to accept
H10. The combination of various factors considered in the study at the time
of recruitment and selection for the IT Software Companies in India affects
net profit margin of IT Software Companies of all the factors considered for
evaluation of output variables, most factors did not affect the net profit
margin of IT Software Companies.
Accepted
H11. The combination of various factors considered in the study at the time
of recruitment and selection for the IT Software Companies in India affects
revenue/profit growth of IT Software Companies of all the factors
considered for evaluation of the output variables, most factors did not affect
the revenue/profit growth of IT Software Companies.
Failed
to accept
20
H12. The combination of various factors considered in the study at the
time of recruitment and selection for the IT Software Companies in India
affects average net profit per employee of IT Software Companies of all the
factors considered for evaluation of output variables, most factors did not
affect the average net profit per employee of IT Software Companies.
Accepted
Conclusions
The results of the present research lead to the conclusion that there are attributes
that most IT software companies consider as essential for the potential employees
involved in software development. The research brings out that significant increase in
number of tests; during the selection process does not of yield a major advantage for a
better recruitment and selection system for the IT Software Companies. Also, while
socio-economic conditions do not have any major impact on the selection system, some
impact is experienced in the growth rate of companies while considering academic
record. Considering the attributes for aptitude identified by the IT software companies,
the research has identified these attributes along with certain other input factors, which
could be utilized for evolving a model that can give better growth in sales, margin of
profit, revenue / profit growth and finally average net profit per employee. Thus by
utilizing the model evolved by employing input, controlled and output variables used in
this research, the IT software companies have a feasible model for an effective
recruitment and selection system for the IT Software Industry in India.
21
Implications
A few of the implications of the study are that a systematic study of recruitment
models has been lacking and this study will hopefully prove to be an example of
quantitative analysis for recruitment. As is clear from testing hypotheses H1-H4,
increasing the length of the selection process does not necessary always result in
obtaining a pool of candidates that affect the company’s bottom line. For key parameters
like growth in sales, relying on antiquated academic screening criterions also does not
help. It is thus imperative that each selection team be very clear on their organizational
objective and thereby can tailor the selection criterion while recruitment for maximum
efficiency. Hypotheses H5-H8 reflects that most aptly. One can envision a multiple
parameter correlation study being conducted similar to Hypotheses H9-H12 testing where
once a model has been built that correlates the input variable in form of attributes to the
output variables. With this study, the company can do targeted selections based on their
needs. For example, growth in revenue is most linked to candidates “Passion for
Technology”. Once the company is in a growth phase, it can hire candidates from schools
which have a strong research and development wing that attracts people with a passion
for technology. The conclusion arrived to from the analysis presented above can change
significantly if either the sample size for the study or the variable set used is different. A
very good example to showcase this effect is the blocking variable. In our study, the
turnover for a company is used to segregate the data/structure differences between the
two data sets and is used as a blocking variable. If not used, the data from small turnover
companies will corrupt the analysis for the large turnover companies. A selection strategy
22
would combine elements of various hypotheses depending upon the output variable that
would need to be maximized
Suggestions for Future Studies
Based on the results and the limitations of this study, further research are
proposed for extending input variable correlation between management’s vision of how
IT Software professionals are managed and how IT Software professionals perceive
management’s vision. This study also did not investigate the differences between the
measured variables with respect to the respondents’ demographic characteristics and sex
ratios (male vs female) of employees. IT Software Companies who have different
demographic characteristics and sex ratios of employees may have different results.
Lastly, longitudinal studies are needed in order to validate the predictive dimension of the
model as has been worked out.