Impact of demographic factors on motivation article OF EMPLOYEES IN HEALTHCARE SECTOR OF BANGALORE, INDIA

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IMPACT OF DEMOGRAPHIC FACTORS ON MOTIVATION OF
EMPLOYEES IN HEALTHCARE SECTOR OF BANGALORE, INDIA
ABSTRACT
There are several factors that affect the performance of employees in an organization. In
this connection, motivations of employees have become topics of interest in modern business
organizations and more specifically in human resource management, because with the creation
of high-quality motivational system, organization can increase its productivity and competitive
ability. Healthcare service providers in metropolitan cities like Bangalore are facing stiff
competition because of the mushrooming number of hospitals. In such an environment keeping
the healthcare professionals motivated is the key to remain competitive. This paper will show the
results of a conducted survey carried out among employees in healthcare sector on the territory
of Bangalore which is one of the hubs of health care industry in India. The aim of the research is
to find out which interactions between the demographic factors - gender, marital status, and
annual income to the motivation of employees in healthcare sector, as well as the implications of
these relations.
Key words: Motivation, Employees, Healthcare, Demography
INTRODUCTION
“Train people well enough so they can leave, treat them well enough so they don’t want to.”
Richard Branson
The Indian healthcare industry, which comprises hospitals, medical infrastructure,
medical devices, clinical trials, outsourcing, telemedicine, health insurance and medical
equipment, was estimated at US$ 160 billion by 2017. On the back of continuously rising
demand, the hospital services industry is expected to be worth US$ 81.2 billion by 2015. The
Indian hospital services sector generated revenue of over US$ 45 billion in 2012. This revenue
increased at a compound annual growth rate (CAGR) of 20 per cent during 2012-2017,
according to a RNCOS report titled, ‘Indian Medical Device Market Outlook to 2017’. The
industry in India is pegged at US$ 1 billion per annum, growing at around 18 per cent touched
US$ 2 billion by 2015. India has witnessed an influx of patients from Africa, CIS countries, Gulf
and SAARC nations, Pakistan, Bangladesh and Myanmar, who mainly come for organ
transplant, orthopedic, cardiac and oncology problems. Apollo Hospitals has six tele-medicine
(through video-conferencing system) centers in the East and North East India. Plans are afoot to
add another 24 over the next couple of years.
A healthcare industry stands eighth among the fastest growing industries in India
providing 13.5 million jobs. Compared to other industries, the health-care industry plays a vital
role, as a whole it is expected to realize a relative increase in the number of career opportunities
across the spectrum of its many specialties. The demand for health-care workers is grown faster
than the average rate for all occupations between 2000 and 2010. In particular, the demand for
home care aides, registered nurses, physician assistants, nurse practitioners, physical therapists,
non-traditional health aides, and physicians will continue to increase at a healthy pace. This trend
also applies to technical and administrative jobs, as hospitals continue to focus their energies on
more efficient management and profitability.
Immensely society is attracted to the health-care industry for its human touch and
service-oriented aspects. However, transition from service oriented to business oriented in the
economy exhibit that the health industry is pioneering and earning interesting fruitful results.
Hospitals, nursing homes, home health care, specialized clinics-and even to some extent

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organizations that provide alternative medical treatments-are being run increasingly like any
other major for-profit organization. Health care today is all about big business-with its focus
sharpening on higher profits.
Domestic Healthcare Market Size
The Indian health care sector is poised to touch US$ 100 billion by 2015 and US$ 275.6
billion by 2020, according to industry estimates. In 2013, healthcare and life sciences emerged as
the second favourite destination for venture capital after technology, attracting 27 investments
worth US$ 181 million, according to research firm Venture Intelligence.
Growth in Market
Healthcare as an industry in India has grown to become one of the most promising and
progressive sectors poised for rapid growth. It is expected to reach US$ 100 billion by 2015 from
the current US$ 65 billion, and is projected to reach USD 250 billion by 2020.India’s one billion
plus population and the sustained rapid economic growth the country has been experiencing
continues to create tremendous demand for better healthcare. A major thrust on medical tourism,
government initiatives and focus on public private partnership has added stimulus to this growth.
Apart from the presence of corporate hospitals, the availability of highly qualified doctors and
scientists, their expertise and state-of-the-art technology have enabled India become an attractive
destination globally for medical tourism, clinical studies and research and development. India's
healthcare system is developing rapidly and continues to expand its coverage, services and
expenditure in the public as well as private sectors.
Bengaluru, the capital city of Karnataka state of India is not only the hub of Information
Technology Bengaluru is the capital city of Karnataka but also one of the top locations for
various healthcare segments providing remedies to the ailments of patients with highly
sophisticated treatment using high-end technology. Bengaluru is considered as the place of
interest for medical tourist. Most experienced and highly qualified doctors are the highlights of
Bengaluru Multi-specialty Hospitals.
Foreigners from countries like Bangladesh, Iraq, Yemen, Maldives, Oman, Mauritius,
Tanzania, Kenya, Nigeria and Indonesia prefer Bengaluru hospitals for some of the chronic
ailments like cancer care, organ transplants, cardiac care, nephrology, urology, neurosurgery and
orthopedics.
Specialty Healthcare Providers
Health is the most significant part of a person’s life. Bad health drains a person
financially, emotionally and mentally. A quality treatment from a good hospital is all you need to
remain fit. Numerous hospitals providing world class treatment have attempted to cut costs; they
have turned to firms that can provide specialized services at rock-bottom prices. People across
the globe prefer Bengaluru for treatments. The treatment ranges from the ordinary treatment to
the saviour once. These include everything from nursing homes to home combination therapy
providers to diabetes treatment providers. Clinics that focus on special treatments such as
chemotherapy, MRI and other scanning techniques, and physical therapy are proliferating. Most
of the specialty hospitals are small and locally run and these hospitals undoubtedly emerge as
their popularity increases.
However, choosing the best hospital for the required treatment is a herculean task. Some
of the points to remember while choosing the hospital are hospital background, Success Rate of
the required treatment, the surgeons and doctors available, Technology used for the treatment,
Hospitality, and Cost effectiveness.

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DEMOGRAPHIC FACTORS AND MOTIVATION
Studies reveal that employees’ demographic aspects have a role in their job attitudes and
motivation. Factors such as age, education, gender and job tenure might be playing an effective
role in employee motivation and job attitude (Churchill et al, 1979; Dubinsky and Skinner 1984;
Ingram and Bellinger 1983; Lefkowitz 1994).
Employees who are valuable resources contribute to the activities of the organizations,
based on the appropriate opportunities given by the organizations. It’s also critical for employees
to stick to the organization and work towards organizational goals for organizations to be
successful (Molander, 1996). Such commitment can be elicited through motivation.
There are a few motivational studies done in India in certain industry types and also
among certain employee categories (Mundhra and Jacob, 2011).
One such study has been conducted in a manufacturing industry to check the intrinsic
motivation and its influence on performance (In that study, ‘competence’, ‘autonomy’ and
‘relatedness’ were tested among different gender, age and education group), and it was found
that for the age group below 28 years and above 35 years the ‘competence’ as a factor had
negligible impact. However, ‘autonomy’ and ‘relatedness’ had a high influence across age
groups (Mundhra and Jacob, 2011).
The same test on ‘education levels’ revealed that the factor ‘competence’ had a negligible
influence on all education group. ‘Autonomy’ and ‘relatedness’ had a moderate to strong
influence on people of all education groups (Mundhra and Jacob, 2011).
In another similar study conducted in ‘services’ industries based on the ‘intrinsic’
motivation and its performance influence, the results observed were not the same. The intrinsic
factors considered were ‘competence’, ‘autonomy’ and ‘relatedness’. This study revealed that
‘competence’ as an intrinsic factor had a negligible influence on performance, across age groups.
‘Autonomy’ as a factor had a negligible influence on the performances of people of 28-35 years
age group as well as people who were above 35 years. ‘Autonomy’, however, had a moderate
influence on the age group upto 28 years.
When the data studied on the basis of the education of the participants, it was found that
‘competence’ as a motivational factor had only a negligible influence on Graduates and
Engineers. However, it had a moderate influence among Post Graduates. It was also observed
that ‘autonomy’ had a moderate influence on people who were Graduates and Engineers.
‘Relatedness’ as a factor had a moderate to strong influence on all age groups except those
whose education was ‘miscellaneous’ (Mundhra, 2010).
Banerjee and Duflo (2006) made an attempt to study the ‘extrinsic’ motivation of health
workers and teachers with regard to absenteeism, as absenteeism poses a big issue in the public
health centres and schools in developed countries. The finding was that teachers were responding
positively to extrinsic motivation with respect to absenteeism irrespective of the fact that the
incentive offered was not extravagant (Banerjee and Duflo, 2006).
When two factor theory of motivation was studied in one of the researches in India, it
revealed that the real motivating factors for the new generation were yet to be identified. Several
studies in the past also have concluded that there is no similarity in the two factors identified by
Fredric Herzberg; but not many have explored the factors that actually exist and are appropriate
for the present workforce (Guha, 2010).
In yet another study conducted among Insurance Companies Officers (Balachander,
Panchanatham and Subramanian, 2010) of both private and government sectors, it was seen that
both the category officers expressed the same opinion about the satisfaction on pattern of

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working and chances to learn. However, the opportunity to learn more was with the employees in
the private sector. The major observation here was that the job situation was influencing the
motivation of both the government and private insurance sectors. A place, culture, climate and
environment in which an employee performs his duty in the company could be termed as a ‘job
situation’. The characteristics of Job situations are factors in the work environment which affect
motivation in the organization (Singh, 2005).
There is a dearth of motivational studies in India with specific stress on industries. There
are a few researches available which were conducted in non- IT industries such as manufacturing
and service industries. Similar is the case of with the studies done on demographic factors and
their influence on work motivation. Studies done on ‘extrinsic’ and ‘intrinsic’ motivation
inclination of various demographic groups are also very few. This clearly demands studies in this
area.
OBJECTIVES
1. To study the factors that motivates the healthcare sector employees in Bangalore, India.
2. To determine the factors (both the intrinsic and the extrinsic rewards) that contributes
towards employee’s motivation in multi-specialty hospitals in Bangalore, India.
3. To find out the relationship between the demographic variables and employees motivation
in healthcare sector in Bangalore, India.
HYPOTHESES
H01: There is no association between Gender and Employees motivation.
H02: There is no association between Marital status and Employees motivation.
H03: There is no association between Annual Income and Employees motivation.
RESEARCH METHODOLOGY
The present study is a descriptive research based on self-administered questionnaires on
the healthcare professionals of Bangalore from ten hospitals Fortis Hospital, Manipal Hospital,
Columbia Asia Referral Hospital, Sparsh Hospital, Aster CMI Hospital, Apollo Hospital,
Hosmat Hospital, People Tree Hospital, BGS Global Hospital, and Narayana Hrudayalaya. A
multi-stage convenience sampling was adopted to collect information from 488 respondents from
the hospitals. Preliminary discussions were held with healthcare professionals to gather
information to get clarity on different factors that motivates them. Based on the discussions, the
most relevant motivational factors in the study area were selected. The data collected was
analyzed mainly thorough descriptive statistics, using Kruskal-Wallis tests. The SPSS (Version
20.0) software was used to execute the analysis process. Methods such as tabular formats were
used to derive and summarize the data. The desired level of significant chosen was 0.05 with the
given test.
The Kruskal-Wallis test is a nonparametric (distribution free) test, and is used when the
assumptions of one-way ANOVA are not met. Both the Kruskal-Wallis test and one-way
ANOVA assess for significant differences on a continuous dependent variable by a categorical
independent variable (with two or more groups). In the ANOVA, we assume that the dependent
variable is normally distributed and there is approximately equal variance on the scores across
groups. However, when using the Kruskal-Wallis Test, we do not have to make any of these
assumptions. Therefore, the Kruskal-Wallis test can be used for both continuous and ordinal-
level dependent variables. However, like most non-parametric tests, the Kruskal-Wallis Test is
not as powerful as the ANOVA.

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Table 1
Research Methodology Summary
Particulars Description
Type of Research Descriptive and Explanatory research
Sampling Non – Probability Sampling
Population Employees at Select Multi-Specialty Hospitals in Bangalore
Unit Employees who are working for at least 3 years full time
Size and Frame
work
488 samples (Confidence Level of 95%)
Technique Multi-Stage Convenience sampling technique (Non-
probability Sampling)
Data sources Primary Data – Structured Questionnaire
Secondary Data – Books, Articles, Journals and websites
Statistical Tools
used
Kruskal-Wallis Test
Validity and Reliability of the Instrument
The instrument used for this study was a thorough construct that was based upon two
types of legality: Validity and Reliability of the Instrument. The survey instrument was
canvassed to 500 respondents and the researcher got 488 responses back. This team of
participants was instructed to react to questionnaire and show their issues relating to the topic of
research. In addition, information was analyzed to determine the reliability of the tool.
Cronbach’s alpha coefficient of 0.968 indicates a high level of internal consistency for our scale
with these specific sample respondents.
Table 2
Reliability Statistics
SCOPE AND LIMITATIONS
The study was conducted in the hospitals of Bangalore. It is believed that the findings in
this City are fair representative of the other parts of the country with similar demography and
development. Other limitations have been identified in this study are, the sample size do not
ensure representative and conclusive finding, the factors motivating the employees of the
healthcare sector professionals of the consumers is changing fast and hence cannot be truly
predicted and finally, a more robust analysis is needed to reach a strong conclusion.
DATA ANALYSIS AND INTERPRETATION:
Demographic variables
This section of the survey questionnaire extracts information regarding the Gender,
Marital Status and Annual Income of the respondents in order to understand the responses and
the resulting conclusions drawn as shown in the Tables and graphs below. Furthermore the
researcher is trying to find if the demographic variables has any relationship with the motivation
of the employees in healthcare sector.
Reliability Statistics
Cronbach’s Alpha
Cronbach’s Alpha Based on
Standardized Items
N of Items
0.968 0.968 25

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Table 3
Gender wise distribution of Sample Respondents
Gender
Frequency Percent Valid Percent Cumulative Percent
Valid
Male 264 54.1 54.1 54.1
Female 224 45.9 45.9 100.0
Total 488 100.0 100.0
The above Table explains the distribution of sample by their gender. From the above
table it is clear that the majority of the respondents were male constituting 54.1 percent of the
total respondent. The share of female respondents was 45.9 percent. It implies that the sample is
unequally distributed gender wise with dominance of male.
Chart 1
Gender wise distribution of Sample Respondents
Table 4
Marital status wise distribution of Sample Respondents
Marital status
Frequency Percent Valid Percent Cumulative Percent
Valid
Married 264 54.1 54.1 54.1
Unmarried 224 45.9 45.9 100.0
Total 488 100.0 100.0
The above Table explains the distribution of sample by their Marital status. From the
above table it is clear that the majority of the respondents were married constituting 54.1 percent
of the total respondent. The share of unmarried respondents was 45.9 percent. It implies that the
sample is unequally distributed marital status wise with more of married healthcare
professionals.
54%
46%
Gender wise distributionof Sample
Respondents
Male
Female

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Chart 2
Marital status wise distribution of Sample Respondents
Table 5
Annual Income wise distribution of Sample Respondents
Annual Income
Frequency Percent Valid Percent Cumulative Percent
Valid
3- 5 Lacs 201 41.2 41.2 41.2
2-3 Lacs 287 58.8 58.8 100.0
Total 488 100.0 100.0
The above Table explains the distribution of sample by their Annual Income. From the
above table it is clear that the majority of the respondents fell in the income category of 2-3 Lacs
constituting 58.8 percent of the total respondent. The share of respondents with annual income of
3-5 Lacs was 41.2 percent. It implies that the sample is unequally distributed Annual income
wise with more of healthcare professionals falling into lower income group.
Chart 3
Marital status wise distribution of Sample Respondents
54%
46%
Marital status wisedistributionof Sample
Respondents
Married Unmarried
41%
59%
Annual Income wise distribution of Sample
Respondents
3- 5 Lacs 2-3 Lacs

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Kruskal-Wallis-Tests:
Kruskal-Wallis-Test of whether Gender has any significant relationship with the
Motivation
Table 6
Descriptive Statistics: Gender and Motivation
Descriptive Statistics
N Mean Std. Deviation Minimum Maximum
Motivation 487 3.61 .612 2 4
Gender 488 1.46 .499 1 2
Table 7
Ranks: Gender and Motivation
Ranks
Gender N Mean Rank
Motivation
Male 263 246.09
Female 224 241.55
Total 487
Table 8
Test Statistics: Gender and Motivation
Test Statisticsa,b
Motivation
Chi-Square .187
df 1
Asymp. Sig. .666
a. Kruskal Wallis Test
b. Grouping Variable: Gender
H01 : There is no association between Gender and Employees motivation.
H0A: There is association between Gender and Employees motivation.
A Kruskal Wallis Test H test was run on SPSS 16.0 to determine if there were any
differences in Gender with the motivational factors like Management/Supervisor Loyalty to
Employees, Good Working Conditions, Job Security, Good Wages, Gratitude for a Job Well
Done, A Feeling of Being Involved, Promotion or Career Development, Interesting Work,
Tactful Discipline, Monetary Incentives for a Job Well Done, Supervisor’s Help with Personal,
Problems, Public Celebration for a Job Well Done. The above Test Statistics shows that the
scores were not statistically significant between the Gender & Motivation which is represented
by: (1) =0.187, p=0.666.
Kruskal-Wallis-Test of whether Marital Status has any significant relationship with the
Motivation

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Table 9
Descriptive Statistics: Marital Status and Motivation
Descriptive Statistics
N Mean Std. Deviation Minimum Maximum
Motivation 487 3.61 .612 2 4
Marital Status 488 1.46 .499 1 2
Table 10
Ranks: Marital Status and Motivation
Ranks
Marital Status N Mean Rank
Motivation
Married 263 246.09
Unmarried 224 241.55
Total 487
Table 11
Test Statistics: Marital Status and Motivation
Test Statisticsa,b
Motivation
Chi-Square .187
df 1
Asymp. Sig. .666
a. Kruskal Wallis Test
b. Grouping Variable: Marital Status
A Kruskal Wallis Test H test was run on SPSS 16.0 to determine if there were any
differences in Marital Status with the motivational factors like Management/Supervisor Loyalty
to Employees, Good Working Conditions, Job Security, Good Wages, Gratitude for a Job Well
Done, A Feeling of Being Involved, Promotion or Career Development, Interesting Work,
Tactful Discipline, Monetary Incentives for a Job Well Done, Supervisor’s Help with Personal,
Problems, Public Celebration for a Job Well Done. The above Test Statistics shows that the
scores were not statistically significant between the Marital Status & Motivation which is
represented by: (1) =0.187, p=0.666
Kruskal-Wallis-Test of whether Annual Income has any significant relationship with the
Motivation
Table 12
Descriptive Statistics: Annual Income and Motivation
Descriptive Statistics
N Mean Std. Deviation Minimum Maximum
Motivation 487 3.61 .612 2 4
Annual Income 488 2.59 .493 2 3

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Table 13
Ranks: Annual Income and Motivation
Ranks
Annual Income N Mean Rank
Motivation
3- 5 Lacs 201 247.40
2-3 Lacs 286 241.61
Total 487
Table 14
Test Statistics: Annual Income and Motivation
Test Statisticsa,b
Motivation
Chi-Square .298
df 1
Asymp. Sig. .585
a. Kruskal Wallis Test
b. Grouping Variable: Annual Income
A Kruskal Wallis Test H test was run on SPSS 16.0 to determine if there were any
differences in Annual Income with the motivational factors like Management/Supervisor Loyalty
to Employees, Good Working Conditions, Job Security, Good Wages, Gratitude for a Job Well
Done, A Feeling of Being Involved, Promotion or Career Development, Interesting Work,
Tactful Discipline, Monetary Incentives for a Job Well Done, Supervisor’s Help with Personal,
Problems, Public Celebration for a Job Well Done. The above Test Statistics shows that the
scores were not statistically significant between the Annual Income & Motivation which is
represented by: (1) =0.298, p=0.585.
As observed from the above discussions, the researcher concludes that, “There is no
positive impact of Demographic Characteristics on Employee Motivation at Select Multi-
Specialty Hospitals in Bangalore” is not rejected and the researcher retains the Null
Hypothesis.
CONCLUSION
Human Resources are considered as the most important assets of every organization and
it plays an important role in realizing organization’s objectives. There is a positive relationship
between employee motivation and organizational productivity. More motivated employees are
more productive, more loyal and more committed to their work. An increase in the competitive
front and to retain the top performance employees in healthcare industry have becomes crucial.
Hence the motivation of employees has become more important for healthcare industry. But, in
the given research reason the demographic variables were not found significant in employees
motivation. And hence, other factors which motivate the employees are necessary to be studied
in greater details.

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