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AN EMPIRICAL STUDY ON THE ORGANIZATIONAL CLIMATE OF

INFORMATION TECHNOLOGY INDUSTRY IN INDIA

*Dr.Jain Mathew, **Prof.TomyK.K(corresponding author)***Dr. Uma Selvi****Dr Kennedy Andrew Thomas

The Information Technology Industry in India

India has found an unexpected opportunity in the new revolution caused by information

technology, especially in customized software development. India, with its large pool of

qualified technical professionals has been recognized as an important base for software

development (Gopalan, 2000; Paul, 2002). With a compounded annual growth rate of 32%

between 2005 and 2009 the Indian IT software and services sector has expanded almost twice as

fast as the US software sector. The sector is estimated to aggregate revenues of USD 88.1 billion

in FY2011, with the IT software and services sector (excluding hardware) accounting for USD

76.1 billion of revenues. During this period, direct employment is expected to reach nearly 2.5

million, an addition of 240,000 employees, while indirect job creation is estimated at 8.3 million.

As a proportion of national GDP, the sector revenues have grown from 1.2 per cent in FY1998 to

an estimated 6.4 per cent in FY 2011. Its share of total Indian exports increased from less than 4

per cent in FY1998 to 26 per cent in FY2011. Export revenues are estimated to gross USD 59

billion in FY2011 accounting for a 2 million workforce. The year 2010-11 was characterized by

*Professor& Head, Department of Management Studies, Christ University, Bangalore. Email:[email protected] **Professor& Head, Department of Tourism Studies, Christ University, Bangalore. Email:[email protected] ** *Professor & Head, Department of Management Studies, Cauvery College for Women,Thiruchirappally. Email:[email protected] ****Director,Centre for Education Beyond curriculum,Christ University,Bangalore [email protected]

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a consistent demand from the US, which increased its share to 61.5 per cent. Emerging markets

of Asia Pacific and Rest of the world also contributed significantly to overall growth. Within

exports, IT Services segment was the fastest growing segment, growing by 22.7 per cent over

FY2010, and aggregating export revenues of USD 33.5 billion, accounting for 57 per cent of

total exports. Indian IT service offerings have evolved from application development and

maintenance, to emerge as full service players providing testing services, infrastructure services,

consulting and system integration (NASSCOM, 2011).

The world has recognized India’s competitive advantage in software services and today India is a

magnet for software clients owing to the quality of its skilled software manpower (NASSCOM,

2010). India has gained a lot of interest as a source of software and has emerged as a leader in

the software industry (Heeks, Nicholson and Sahey, 2000). Indian firms develop software for

more than three fourth of the Fortune 500 companies and at least half of the Global 2000

corporations (NASSCOM, 2009).

The most important success factor for quality software development is having talented and smart

people (Brooks. 1987). Being manpower intensive industry, availability, cost, turnover and

productivity of manpower are critical to the functioning of the organization. The key to success

of Indian software industry is the supply of trained, low cost software professionals (Arora et aI.,

1999). Software industry is driven by technology and hence tends to be skill intensive. The level

of talent on software project is the strongest predictor of its results (Boehm, 1981). Personnel

shortfalls are one of the most severe project risks (Boehm, 1988). Software development is large-

scale integrated, intellectual work (Humphrey, 1989). The skill of developing software is the

skill of managing intellectual complexity (Curtis. 1981).

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The high rate of employee turnover has been one major issue that most software companies have

been worried about. Employee turnover causes disruptions in project implementation and loss of

skills inculcated through training and hands-on experience. Though some turnover is inevitable

and even healthy at times, a high leve1 of turnover could be detrimental to a company’s business

in a people-driven industry like software. Since the very survival and success of software

companies depend on the availability and the effective utilization of talented people, human

resource activities provide the largest source of opportunity for improving software development

productivity (Boehm, 1981).

Organizational Climate

Organizational climate has been defined as a “perception of the psychologically important

aspects of the work environment” (Ashforth, 1985) and is recognized as a potential influence on

employees’ workplace behaviour and job satisfaction (Ashforth, 1985). Climate consists of a set

of characteristics that describe an organization, distinguish it from other organizations, are

relatively enduring over time and influence the behaviour of people in it. The individual

worker’s perception of their work environment rather than a consensus view is considered, as

different individuals may perceive the same workplace in different ways (Klein, Conn, Smith, &

Sorra, 2001).

Organizational climate is defined as shared perceptions or prevailing organizational norms for

conducting workplace activities (Reichers & Schneider, 1990). It has been conceptualized as a

cognitively based set of perceptual descriptions that define the psychological climate

(Jain Mathew, 2008; James&Jones, 1974; Kozlowski&Hults, 1987), and therefore it is possible

to measure individual-level perceptions of the organizational climate for updating (Kozlowski &

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Farr, 1988; Kozlowski & Hults, 1987). So the focus is on employees’ perceptions of salient

features of the organizational context. Kozlowski and Farr (1988) recommended that research

consider the interaction between individual characteristics and perceived situational features of

the environment when determining whether technical professionals will voluntarily seek to learn

new skills. Perceptions relevant to a specific climate domain such as the innovation climate have

motivational implications on congruent behavioural outcomes (Schneider, 1983).

According to Campbell (1970) “Organizational climate can be defined as a set of attributes

specific to a particular organization that may be induced from the way that organization deals

with its members and its environment. For the individual members within the organization,

climate takes the form of a set of attitudes and experiences which describe the organization in

terms of both static characteristics (such as degree of autonomy) and behaviour outcome and

outcome-outcome contingencies.”

Organizational climate is a relatively enduring quality of the internal environment that is

experienced by its members, influences their behaviour and can be described in terms of the

value of a particular set of characteristics of the organization. It may be possible to have as many

climates as there are people in the organization when considered collectively, the actions of the

individuals become more meaningful for viewing the total impact upon the climate and

determining the stability of the work environment (Jain Mathew,2008). The climate should be

viewed from a total system perspective. While there may be differences in climates within

departments these will be integrated to a certain extent to denote overall organizational climate.

Organizational climate influences to a great extent the performance of the employees because it

has a major impact on motivation and job satisfaction of individual employees. Organizational

climate determines the work environment in which the employee feels satisfied or dissatisfied.

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Since satisfaction determines or influences the efficiency of the employees, we can say that

organizational climate is directly related to the efficiency and performance of the employees. The

organizational climate can affect the human behaviour in the organization through an impact on

their performance, satisfaction and attitudes.

Objective of the study

1. To investigate the influence of biographical variables such as gender, age, experience,

marital status, qualification and designation on the organizational climate of Information

Technology companies.

2. To study the significant difference between small scale, large scale and multi national

companies with respect to organizational climate and its dimensions.

3. To discuss the implications arising out of the study for effective management of IT

organizations.

Research design:

The present study considers organizational climate experienced currently in a number (n=389) of

38 IT companies situated in India. The study is descriptive and cross sectional type of survey. It

signifies the questions to be investigated, the process of sample selection, methods of procedure

to be followed, measurements to obtain and comparison and other analyses to be made. The

clear design of the study is as follows:

Variables of the study:

1 Organizational climate (dependent variable)

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2 Biographical variables namely type of company, Age, Gender, Marital status,

Designations, Total work experience, work experience in current organization and

Educational qualifications.

Tool Used

ORGANIZATIONAL CLIMATE SCALE

The organizational climate scale was constructed and standardized originally by Somnath

Chattopadhyay and K.G Agarwal, Later it was adapted and standardized by investigator. The

adapted and standardized organizational climate scale consists of 70 items to be responded on a

five-point scale.

Scoring of organizational climate scale is on a five point scale from 1 to 5 for the positive

response of strongly disagree scoring is 1, Disagree it is 2, Neutral is 3, Agree is 4, Strongly

Agree scoring is 5 and for negative items, the scores are given in opposite direction. The total

score of the individual was considered to statistical analysis. The total scores once taken, the

totals of 70 items are divided into eleven dimensions and are presented in the following table:

Table 1: Dimension wise distribution of items of organizational climate scale.

Dimensions Item Nos. Total Items

Performance Standards 6,9*, 10,13*, 30*, 31,57 7

Communication flow

12,17,24,34,37*, 38,49*,

52,61,65,67

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Reward system 29*, 41,54,66* 4

Responsibility 4,16*, 27*, 40 4

Conflict resolution 1*, 18*, 23,42*, 44*, 45*, 46 7

Organizational structure 14*, 19,21,35,47 5

Motivational level 28,32,51,56*, 59,68*, 69 7

Decision making process 2,15,25*, 36,43*, 62*, 70 7

Support system 3*,5*,7,8,20,48,53,55,56 9

Warmth 26,39,60,63,64* 5

Identity problems 11*, 22,33*, 50* 4

The asterisk mark indicates items scored 54321 and all other items are scored as 12345.

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Reliability and Validity

After adaptation of the original organizational climate scale by investigator, a pilot study

was carried out on a random sample of 100 employees. The reliability and validity of the scale

was assessed by the split half reliability technique and the split half reliability coefficient of the

organizational climate scale was found to be 0.8980 (89.80%). The internal consistency of the

scale was 0.9476 (94.76%). The intra-class correlations were obtained by using the item analysis

technique and intra-class correlation coefficient is ranging from 0.3541 to 0.7938. All items of

the organizational climate are found to be significant except question numbers 17 and 21 and

they were also included in the study. The corresponding validity of the organizational climate

scale was found to be 94.76%. The details are presented in the following table:

Table 2: Reliability analysis of organizational climate scale

Summary Values

Cronbach alpha, full scale 0.9476

Standardized alpha 0.9489

Corr. 1st & 2nd half 0.7254

Split-half reliability 0.8980

Guttman split-half 0.8873

Cronbach alpha-first half 0.5247

Cronbach alpha-second half 0.6104

% Of reliability 89.8000

The data for the present study was obtained from 389 employees working in different types of

Information Technology companies namely, Small and Medium Enterprises, Large scale

Enterprises and Multi National Corporations in information technology industry in India. The

employees’ details are represented in the following table.

Table-3: Distribution of IT employees according to types of company and gender.

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Type of Company Male Female Total

Small and Medium

Enterprises

70 18 88

Large scale Enterprises 122 40 162

Multi National

Corporations

90 49 139

Total 282 107 389

After the data had been collected, it was processed and tabulated using Microsoft Excel - 2000

Software.

POPULATION AND SAMPLE OF THE STUDY The population for the study was software companies in Bangalore having commenced operation

at least since 2002 because the study focused on identifying the organizational climate of the

software companies, which existed at least for three years. Using NASSCOM membership as a

measure, the number of software firms in Bangalore was 455 during the base year of data

collection. Software companies were generally classified as small and medium-scale, large-scale,

and multinational companies. Taking in to account the number of companies as per NASSCOM

data, the sample was chosen as 10% of the population. In order to get equal representation it was

decided to take 15 companies each in all the three categories, viz., small and medium-scale,

large-scale, and multinational companies. In many of the previous studies, the size of the firm

was defined in terms of number of employees (Delery and Doty, 1996; Budhwar and Sparrow,

1997; Harel and Tsafrir, 1999; Paul, 2002). This parameter appears to be quite logical in the case

of software industry because the key resource in software is human resource. It has been a

challenge to decide upon the cutoff number in order to classify firms into two categories, viz.,

large-scale and small and medium-scale. The studies that have used number of employees to

represent the size of firms have differed in the choice of cut-off points to classify firms as small

and medium-scale and large-scale firms. A study has been done based on the secondary

information available from NASSCOM website and publications like Dataquest, Computers

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Today, etc. Based on the number of employees in the software companies, it has been decided to

classify companies in to small and medium-scale and large-scale at cut-off point of 1000

employees. Hence companies that had 1000 or more employees were grouped into large-scale

and companies that had employees less than 1000 were classified as small and medium-scale and

multinational companies were taken as they are and most of them had less than 1000 employees.

The sample consisted of only those companies that were started in 2002 or before and companies

that were based in Bangalore. Bangalore was selected because it has been recognized as the

Silicon Valley of India and has the largest number of software companies in comparison with

other cities in India. Since the focus was on software companies, the companies focused on IT

enabled services were not part of the sample.

Since organizations had several software development centres, only one major centre was

selected for the study. The sample to be collected from each company was decided to be 5% of

the employees in the software company under study. Since the number of employees varies from

50 to 20000 or more across organizations, 5% of the employees of only one development centre

were selected. It was decided to administer the questionnaire to only those employees who had a

minimum of two-years of work experience in the company. This has been done in order to avoid

new employees who had no sufficient information about the organizational climate of the

company.

Although probability sampling is the ideal sampling process, convenience sampling is also used

in research owing to various reasons. Sackett and Larson (1998) argue that a convenience sample

can be relevant for research to the extent that it possesses the essential person and setting

characteristics that define membership in the intended target population. It was decided to resort

to convenience sampling because it was the feasible alternative to get adequate responses given

the stringent criteria for enlisting companies and individual respondents within them. Secondly

approval and support of the participating companies for the study was a factor not under the

control of the researcher. Moreover, cost and time constraints make probability sampling out of

reach. Further the assistance of internal coordinators in company was taken to ensure that the

questionnaires were distributed to software employees who fulfilled the criteria defined above

for respondents.

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3.12 DATA COLLECTION

A total of 1000 employees from 45 different software companies in Bangalore city were

approached for data collection. An internal coordinator was identified in each company in order

to facilitate the data collection based on the number of employees in each unit. Out of 420

responses collected from 40 companies, 389 responses from 38 companies were usable ones. The

data was collected from 14 small and medium-scale enterprises, 13 large-scale companies and 11

multinational companies.

Analysis of data

The data collected have been analyzed using the Karl Pearson’s correlation coefficient, student’s

unpaired t-test, one way analysis of variance (ANOVA) using SPSS 11.0 statistical software and

the results obtained thereby have been interpreted.

Findings

H0 1: There is no significant difference between males and females with respect to

Organizational climate in IT industry.

Table-4: Result of t-test between males and females with regard to Organizational climate

Variable

Male (n=282) Female (n=107)

t-value Signi. Mean Std.Dev. Mean Std.Dev.

Organizational climate 236.6950 33.4563 232.8972 32.4761 1.0078 NS

From table-4 we clearly observe that, Males and females do not differ significantly with respect

to Organizational climate (t=1.0078) at 0.05 level of significance. Hence, the null hypothesis is

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accepted and alternative hypothesis is rejected. In other words, the male and female IT

employees have similar organizational climate scores.

H0 2: There is no significant difference between married and unmarried IT employees with

respect to Organizational climate.

Table-5: Result of t-test between married and unmarried IT employees with regard to

Organizational climate.

Variables

Married (n=149) Unmarried (n=240)


Organizational climate 231.4027 32.13 238.2875 33.62998 -1.9964 *

* Significant at 0.05 levels

From table-5 we clearly observe that, married and unmarried IT employees differ significantly

with respect to Organizational climate (t=-1.9964) at 0.05 level of significance. Hence, the null

hypothesis is rejected and alternative hypothesis is accepted. In other words, the married and

unmarried IT employees have different organizational climate scores.

H0 3: There is no significant difference between IT employees with 1-6 years and 7 & more than

7 years of total experience with respect to Organizational climate.

Table-6: Result of t-test between IT employees with 6 years and 7 & more than 7 years of total

experience and Organizational climate.

Variables

1-6 years (n=316)

7 & more than 7 years

(n=73)



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From table-6 we clearly observe that, IT employees belonging to 1-6 years and 7 & more than 7

years of total experience do not differ significantly with respect to organizational climate

(t=0.3965) at 0.05 level of significance. Hence, the null hypothesis is accepted and alternative

hypothesis is rejected. In other words, the IT employees with 1-6 years and 7 & more than 7

years of total experience have similar organizational climate scores.

H0 4: There is no significant difference between IT employees with 1-3 years and 4 & more than

4 years of experience in current organization with respect to organizational climate.

Table-7: Result of t-test between IT employees with 1-3 years and 4 & more than 4 years of

experience in current organization and Organizational climate.

Variables

1-3 years (n=345)

4 & more than 4 years

(n=44)



From table-7, we clearly observe that IT employees belonging to 1-3 years and 4 & more than 4

years of experience in current organization do not differ significantly with respect to

organizational climate (t=1.0307) at 0.05 level of significance. Hence, the null hypothesis is

accepted and alternative hypothesis is rejected. The IT employees with 1-3 years and 4 & more

than 4 years of experience in current organization have similar organizational climate scores.

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H0 5: There is no significant difference between designations with respect to Organizational

climate.

Table-8: Result of ANOVA between designations of IT employees with respect to

Organizational climate.

Variables Summary Manager

Project

Leader/Con

sultant

Programme

r/Analyst Other F-value Signi.

Organizational

climate

Means 235.74 242.41 233.32 230.91 2.1248 NS

Std.Dev. 26.60 37.43 32.98 28.60

From table-8, we clearly observe that the IT employees belonging to different designations (do

not differ significantly with respect to Organizational climate (F=2.1248) at 0.05 level of

significance. Hence, the null hypothesis is accepted and alternative hypothesis is rejected. In

other words, the employees with different designations have similar organizational climate

scores.

H0 6: There is no significant difference between different education qualifications with respect

to organizational climate.

Table-9: Result of ANOVA between education qualifications of IT employees with respect to

organizational climate.

Variables Summary

M Tech/

M.E./M.S MCA

B Tech/

B.E MBA Other F-value Signi.

Organizational

climate

Means 229.39 233.16 235.97 239.56 235.25 0.4879 NS

Std.Dev. 23.28 35.11 32.63 27.73 38.87

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From table-9 we clearly observe that IT employees belonging to different education

qualifications do not differ significantly with respect to organizational climate (F=0.4879) at 0.05

level of significance. Hence, the null hypothesis is accepted and alternative hypothesis is

rejected. The IT employees with different education qualifications have similar organizational

climate scores.

H0 7: There is no significant difference between small scale, large scale and multi national

companies with respect to Organizational climate and its dimensions.

Table 10: The table showing one-way analysis of variance (ANOVA), the variables, SD, F-value

and its significance at 0.05 level between different seven professionals with respect to

Organizational climate and its dimensions.

Variables Summary

Small and Medium

Enterprises Large scale Enterprises

Multi Multi National

Corporations F-value Signi. Organizational climate Means 229.1477 240.4568 232.6259 3.9818 *

Std.Dev. 33.0442 36.3739 28.1912

Dimensions of Organizational climate

Performance

Standards Means 23.8750 24.7037 24.2302 1.3479 NS

Std.Dev. 3.8561 3.8800 4.0937

Communication flow Means 34.9318 36.5741 35.5683 1.7900 NS

Std.Dev. 6.5422 7.1980 6.7449

Reward system Means 13.6591 14.3765 13.8849 1.6923 NS

Std.Dev. 3.1106 3.3363 3.0647

Responsibility Means 12.2727 12.9321 13.0719 2.7419 NS

Std.Dev. 2.1103 2.6937 2.7705

Conflict resolution Means 24.4205 24.7778 23.7050 2.2057 NS

Std.Dev. 4.0193 4.9532 4.0744

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Organizational structure Means 15.0909 15.5309 15.2302 0.5089 NS

Std.Dev. 2.7486 3.5301 4.0312

Motivational level Means 23.0795 24.5988 23.8849 2.8956 *

Std.Dev. 4.9392 5.3666 3.9965

Decision making

process Means 22.0000 23.3025 21.7122 5.4118 *

Std.Dev. 3.9392 4.7432 4.3058

Support system Means 30.1364 31.6481 31.1871 1.9977 NS

Std.Dev. 4.8712 6.3427 5.4461

Warmth Means 16.2159 17.7407 16.8058 5.0418 *

Std.Dev. 3.9667 3.8683 3.6512

Identity problems Means 13.7727 14.4259 14.5108 1.6346 NS

Std.Dev. 2.6337 3.1164 3.5618

* Significant at 0.05 levels

From Table 10 it is clearly observed that:

Small scale, large scale and multi national companies differ significantly with respect to

Organizational climate (F=3.9818, <0.05) at 0.05 level of significance. Hence, the null

hypothesis is rejected and alternative hypothesis is accepted. In another words small scale, large

scale and multi national companies have different organizational climate scores.

Small scale, large scale and multi national companies do not differ significantly with respect to

dimension of organizational climate i.e. performance standards scores (F=1.3479, >0.05) at 0.05


rejected. In another words, small scale, large scale and multi national companies have similar

performance standards scores.


dimension of organizational climate i.e. communication flow scores (F=1.7900, >0.05) at 0.05



communication flow scores.

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dimension of organizational climate i.e. reward system scores (F=1.6923, >0.05) at 0.05 level of


another words, small scale, large scale and multi national companies have similar reward system

scores.


dimension of organizational climate i.e. responsibility scores (F=2.7419, >0.05) at 0.05 level of


another words, small scale, large scale and multi national companies have similar responsibility

scores.


dimension of organizational climate i.e. conflict resolution scores (F=2.2057, >0.05) at 0.05 level

of significance. Hence, the null hypothesis is accepted and alternative hypothesis is rejected. In

another words, small scale, large scale and multi national companies have similar conflict

resolution scores.


dimension of organizational climate i.e. organizational structure scores (F=0.5089, >0.05) at 0.05



organizational structure scores.


dimension of organizational climate i.e. motivational level scores (F=2.8956, <0.05) at 0.05 level

of significance. Hence, the null hypothesis is rejected and alternative hypothesis is accepted. In

another words, small scale, large scale and multi national companies have different motivational

level scores.


dimension of organizational climate i.e. decision-making process scores (F=5.4118, <0.05) at

0.05 level of significance. Hence, the null hypothesis is rejected and alternative hypothesis is

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accepted. In another words, small scale, large scale and multi national companies have different

decision-making process scores.


dimension of organizational climate i.e. support system scores (F=1.9977, >0.05) at 0.05 level of


another words, small scale, large scale and multi national companies have similar support system

scores.


dimension of organizational climate i.e. warmth scores (F=5.0418, <0.05) at 0.05 level of

significance. Hence, the null hypothesis is rejected and alternative hypothesis is accepted. In

another words, small scale, large scale and multi national companies have different warmth

scores


dimension of organizational climate i.e. identity problems scores (F=1.6346, >0.05) at 0.05 level

of significance. Hence, the null hypothesis is accepted and alternative hypothesis is rejected. In

another words, the small scale, large scale and multi national companies have similar identity

problems scores.

Implications

Since the organizational climate is very important for the IT companies, they should strive to

create a congenial organizational climate in their organizations for retention of the talent pool

and maintenance of high productivity. A climate of teamwork is key for effective creativity.

There is a significant difference between married women and unmarried women with respect to

organizational climate. It is evident from the mean scores that the unmarried women contribute

to better organizational climate. So the IT companies have to take measures to motivate the

married women employees so that they also contribute to the organizational climate. The

managements can think of flexi timings with proper accountability to support of Married

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employees. The one way ANOVA shows significant difference among small scale, large scale

and multi national IT companies with respect to organizational climate. On comparing the mean

scores it was found that the Indian Large scale IT companies have a better organizational climate

than the Small scale and multi national IT companies. The managements of Small scale and

multi national IT companies should try to improve their organizational climate. Small scale and

multinational IT companies should take quality and rewarding decisions to improve performance

standards. By a right kind of rewarding, motivating, facilitating, and creating participative

working environment the employee morale can be raised. Smaller companies can benchmark

with the large companies, especially the process and practices that can be replicated efficiently in

small and medium firms, through quality circles and continuous improvement programmes.

The study shows a significant difference on support system for female employees, married

employees and employees with more experience, compared to male employees, unmarried

employees and employees with less experience. So the managements should initiate a strong

support system for the female employees, married employees as well as the senior employees.

The female employees have low conflict resolution compared to male employees. So the

management should provide training on the conflict resolution techniques for its female

employees. They have to be empowered to withstand challenging and competitive environment.

The employees should not be discriminated on the basis of gender and there should be methods

to deal with the sexual harassment. Leaders have to ensure perceived organizational justice and

fairness at the workplace through proper remuneration and promotion. The managements can

think of flexi timings with proper accountability to support the employees.

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Conclusion

Since the organizational climate is very important for the IT companies, they should strive to

create a congenial organizational climate in their organizations for retention of the talent pool

and maintenance of high productivity. A climate of teamwork is key for effective creativity.

One of the major problems faced by the IT industry is high rate of attrition. It has been noticed

that IT companies with good organizational climate face less threat of attrition. The significant

difference between the types of companies on organizational climate shows that the large- scale

Indian IT companies have a better mean score showing better organizational climate.

Organizational climate influences to a great extent the performance of the employees because it

has a major impact on motivation and job satisfaction of individual employees. Organizational

climate determines the work environment in which the employee feels satisfied or dissatisfied.

Since satisfaction determines or influences the efficiency of the employees, we can say that

organizational climate is directly related to the effectiveness of an organization. The

organizational climate can affect the human behaviour in the organization through an impact on

their performance, satisfaction and attitudes.

A good organizational climate favors risk taking which will encourage employees to test and

exchange unusual knowledge and ideas for the prosperity of the organization. An atmosphere of

cooperation opens access among group members and creates individual motivation to exchange

knowledge with group members and teamwork. Norms for openness and teamwork in

knowledge-intensive firms facilitate disclosure of information and loyalty building. A climate of

teamwork is key to effective creativity. Creativity is hurt when an organization’s climate is

characterized by a lack of cooperation and results in lack of job satisfaction for the employees.

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