ICT Force Towards The Indian I.T. Software Entrepreneurship

DOI : 10.17577/IJERTV2IS2026

Download Full-Text PDF Cite this Publication

Text Only Version

ICT Force Towards The Indian I.T. Software Entrepreneurship

Sheela Bhatt

Research Scholar Suresh Gyan Vihar University

Jaipur, Rajasthan, India

Abstract

This paper aims to explore the role and impact of Information on Communication Technologies towards the Indian I.T. Software Industrial sector. It surveys to examine the factors influencing the Indian I.T. Software Entrepreneurship. It searches for indicators effecting the professional environment and investigates if the Indian I.T. Software Entrepreneurs or Organizations are successful in achievement of a good Professional Development.

Throughout the study, only Primary data is used. Structured Questionnaire Module is set. Cluster sampling and Random sampling is used. Sampling frame is South India. Data collection methods are: Mails, Interviews and Schedules. Source list comprises of important Indian Software Entrepreneurs/Organization. A Pilot Testing is undertaken. To meet objectives, hypothesis test is applied. For statistical analysis, multivariate regression, Analysis of Variance and Factor Analysis is used. Test Statistics F, t is also used. For coding and computations, a suitable statistical software and Microsoft Office Excel along with embedded Q1Macros 2012 is used.

Key Words: Information on Communication Technologies, Indian, IT, Software, Factors, Industry, indicators, achievements, Entrepreneurship, Sector.

OVERVIEW

This paper comprises of 6 chapters in all. Chapter 1 is introduction to ICT and the Objectives of the paper. Chapter 2 is about the review of literature. Chapter 3 is about the methods used. Chapter 4 deals with Coding, Observations, Results and Discussion. Chapter 5 is towards meeting the objectives of research. Chapter 6 is bibliography.

  1. Introduction to ICT and objectives of this paper

    1. Familiarity with ICT

      ICT or Information on Communication Technologies has become an essential tool for the technical, economic, or social improvement of any country in the modern world today. Hence, it is embraced by all developing countries. Today, ICT related area is one of the most leading area of research . It can be viewed as an integrated term. It is also considered as an interdisciplinary area of research. India has also embraced ICT for its economic, social and technical growth.. ICT buzz includes, ICT towards education, ICT towards Women empowerment, ICT for Child Development, ICT towards Health and Pharmacy, ICT towards libraries, poverty eradication, rural development , agriculture, industrial promotion, unemployment and ICT towards Software Industries . ICT tools have shown its increasing impulse as a global force. Above all, it is equally important how a country frames the policies and strategies and how it implements ICT Tools for its own benefit.

    2. Objectives of research

      1. Objective A. To study the Impact, importance and achievement of ICT towards the Indian IT Industry, particularly the Software Entrepreneurship, by focusing towards Professional development.

      2. Objective B. To point out that knowledge is a factor of production and reveal that knowledge in the field of I.T. had developed the concept of Entrepreneurship.

  2. Review of literature

    1. Proximities and innovation evidence from Indian Information Technology industry in Bangalore

      The paper by Florian Arun Taeube [1] has a hypothesis that some Indian regions are more apt to economic development and innovation due to their higher affinity to education and learning as well as their more general openness.

      2.2 Software industry and India's economic development

      The Case of the Indian Software Industry is a research project report [2] submitted to the Sloan Foundation jointly by Arora, Ashish Athreye, Suma.

        1. Assessing Software reuse in Indian Information Technology companies: A structural equation modelling approach

          The paper by Padmanav Chary and Biswajit Mahanty [3] discusses on access to software reuse in Indian technology firms. Software reuse generates a lot of interest amongst the cross-section of people in the industry. The article [4] reviews the present status of software reuse practices in the Indian information technology firms.

        2. Role of NASSCOM

      NASSCOM under the aegis of Ministry of Commerce, Government of India had initiated a Project called NASSCOM's India-Europe Software Alliance (NIESA).

      2.5 Performance, challenges and opportunities of Indian software export India has emerged as an IT Super power, especially in the field of software and related services export. The paper [ 5] by Asheref Illiyan throws light on this.

  3. Materials and methods

    1. Types of data

      1. Primary Data. Our main study is based only on the primary data.[6]

        A Pilot Testing of the Questionnaire was conducted and there after, the required changes were made in the questionnaire.

      2. Secondary Data. This is collected through articles, research papers, journals, Indian e- Readiness Assessment reports, Reports from Indian Government Departments and Centres [7],[8],[9],[10],[11],[12], Software Technology Parks of India [13], News [14], NASSCOM publications [15].

        Table 1. Details of primary data collection

        MODULE 1

        MODULE 2

        Data collection Methods

        Mailing Interviews Schedules

        Mailing Interviews Schedules

        Sa

        mple

        60

        (Out of 75 respondents, only 60

        responded).

        32

        size

        Sampling technique

        Cluster Sampling.

        Random Sampling

        Type of universe

        Finite Population

        Finite Population

        Sampling design

        Informal experimental design (Before-and-

        after without control design) Formal experimental designs (Simple Factorial Design,Latin Square Design

        )

        Informal experimental design

        (Before-and-after without control design)

        Formal experimental designs

        (Simple Factorial Design Latin Square Design )

        Sampling unit

        Bangalore

        South India

        Source list

        Important Indian IT/ Software Companies / Entrepreneurs

        Important Indian IT/ Software Companies/Entrepreneurs

          1. Methods/tools used

            The following other statistical tools are used and multivariate analysis is also done .

            • Mean, Mode, Standard deviation,

              variance, covariance and correlation are used as tools for statistical measures.

            • ANOVA

            • Factor Analysis (Principle Component method is used to extract factors of interest)

            • Latin Square design is used to compute Covariance matrix/Correlation matrix.

            • Multivariate Regression

            • Hypothesis Testing is set to meet the objectives of the research study

            • For further hypothesis testing we use F

              statistic and /or t statistic.

          2. Other materials used

        SPSS and Excel is used. Q1 Macros 2012 incorporated/embedded with Microsoft Works (Excel) has also been used for further analysis and computations.

  4. Coding, observations, results and discussion

    1. Coding to compute important statisticl measures of variables

      The Data Base File is Processed in SPSS. Computations have been done using both SPSS and Q1 Macros 2012.

      1. SPSS syntax and Output to generate the various statistical measures.

        Output Created

        03-Dec-2012 11:03:38

        Comments

        Input Data

        C:\Users\baby\Documents

        \RANKA1_NUMRC.SAV_1.sav

        Active

        DataSet1

        Dataset

        Filter

        <none>

        Weight

        <none>

        Split File

        <none>

        Output Created

        03-Dec-2012 11:03:38

        Comments

        Input Data

        C:\Users\baby\Documents

        \RANKA1_NUMRC.SAV_1.sav

        Active

        DataSet1

        Dataset

        Filter

        <none>

        Weight

        <none>

        Split File

        <none>

        Table 2. SPSS coding notes

        No. of

        60

        User-defined missing values are treated as missing.

        Statistics are based on all cases with valid data.

        FREQUENCIES VARIABLES

        =X9 X10 X11 X12 X14 X15

        /STATISTICS=STDDEV VARIANCE MEAN MEDIAN MODE /ORDER=ANALYSIS.

        0:00:00.016

        0:00:00.017

        Rows in

        Working

        Data File

        Missing Definition

        Value of Missing

        Handling

        Cases Used

        Syntax

        Resources Processor

        Time

        Elapsed

        Time

      2. Output

        Table 3. Statistics of the various factors

        Vari able

        Va lid

        Me an

        Std

        .

        Er ror of Me an

        Med ian

        Mo de

        Std. Devia tion

        Vari ance

        X9

        60

        6.0

        .26

        9

        6.0

        4

        2.083

        4.339

        X10

        60

        8.8

        .23

        4

        10.0

        10

        1.811

        3.281

        X11

        60

        9.6

        5

        .12

        1

        10.0

        10

        .936

        .875

        X12

        60

        8.0

        7

        .22

        5

        8.00

        8a

        1.745

        3.046

        X14

        60

        9.9

        3

        .05

        8

        10.0

        10

        .446

        .199

        X15

        60

        9.6

        7

        .12

        3

        10.0

        10

        .951

        .904

        4.2. Observations

        Frequencies of Rank wise Salary Satisfaction of the variables

        Table 4. Rank wise satisfaction of variables

        RANK

        X9

        X10

        X11

        X12

        X14

        X15

        4

        24

        0

        0

        0

        0

        0

        5

        4

        4

        0

        4

        0

        4

        6

        8

        8

        0

        8

        0

        0

        7

        8

        0

        0

        12

        4

        0

        8

        12

        12

        12

        16

        4

        4

        9

        0

        0

        4

        0

        4

        4

        10

        0

        32

        37

        16

        44

        44

        Missing

        4

        4

        7

        4

        4

        4

        Total

        60

        60

        60

        60

        60

        60

        Let the variable X9 = RANK WISE SALARY SATISFACTION.

        The higher the rank the more the salary satisfaction. It has found that no respondents contribute for ranks less than 4. That is 40% of the respondents have 40% of salary satisfaction. Only 20% of respondents have 80% salary satisfaction.

        Figure1. Graph of salary satisfaction

        Let the variable X10 = RANK WISE LEISURE SATISFACTION.

        It has found that no respondents contribute for rank less than 5. 53.3% of the respondents seem to have full 100% leisure satisfaction.

        Figure 2 Graph of leisure satisfaction

        Let X11= Relationship with colleagues. 62% of the respondents seem to have 100% satisfaction with their colleagues relationship.

        Figure 3. Relationship with colleagues

        Let the variable X12 = the factor RELATIONSHIP WITH BOSS..It has found that no respondents contribute for ranks less than 4.Only 26.7% of the respondents are fully satisfied with their relationship with Boss. Again 26.7 % of them have 80% satisfaction with their Boss relationship.

        Figure 4. Graph of relationship with boss

        Let the variable X14 = the factor TEAM CO- ORDINATION . It has found that no respondents contribute for ranks less than 7. 73.3% of the respondents are fully satisfied (100%) with their Team Co-ordination.

        Figure 5. Graph of team co-ordination

        Let the variable X15 = the factor

        PROFESSIONAL ENVIRONMENT.

        It has found that 73.3% of respondents report for having 100% satisfaction with their Professional Environment.

        Figure 6. Graph of professional environment

  5. Meeting the objectives

    1. Objective A

      To study the Impact, importance and achievement of ICT towards the Indian IT Industry, particularly the Software Entrepreneurship.

      To meet this objective, we shall implement Test 1 comprising the testing of a set hypothesis.

      1. Test 1. To meet this objective, we shall study the impact of ICT towards the Professional Development of the Indian IT Software Entrepreneurs. Hence we set the testing hypothesis as follows:

        H0: Indian IT Software Entrepreneurs are unsuccessful or lack behind to show the positive impact of ICT achievements towards the Professional Development of their Organization.

        The following steps are involved.

        • To compute the rank wise correlation between the variables.

        • To determine the covariance matrix.

        • To perform ANOVA

        • To use a Test Statistic ( F or t statistic )

        • To Construct a linear multiple regression Model

        • To test the set Hypothesis .

        • Results

          We construct a regression model with factor Y = Professional Development as the Dependent variable.

          The variable names are as follows: X9 = Salary satisfaction; X10 = Leisure Satisfaction ; X11 = Relationship with Colleagues; X12 = Relationship with Boss; X4 = Team Co-ordination and X15 = Professional Development.

          The following model is regressed using SPSS statistical software. ANOVA and other results are summarized/tabulated.

          Table 5. Covariance matrix for computation of total variance

          Cov. X9 X10 X11 X12 X14 X15

          X9

          55.04

          -8.96

          -21.76

          10.24

          -23.36

          -24.96

          X10

          -8.96

          93.44

          119.04

          39.04

          114.24

          115.84

          X11

          -21.76

          119.04

          170.24

          37.44

          167.04

          167.04

          X12

          10.24

          39.04

          37.44

          45.44

          34.24

          31.04

          X14

          -23.36

          114.24

          167.04

          34.24

          167.04

          165.44

          X15 -24.96 115.84 167.04 31.04 165.44 167.04

          SYNTAX:

          DATASET ACTIVATE DataSet1.

          CORRELATIONS

          /VARIABLES=X9 X10 X11 X12 X13 X14 X15

          /PRINT=TWOTAIL NOSIG

          /MISSING=PAIRWISE.

          REGRESSION

          /MISSING LISTWISE

          /STATISTICS COEFF OUTS CI(95) R ANOVA

          /CRITERIA=PIN(.05) POUT(.10)

          /NOORIGIN

          /DEPENDENT X15

          /METHOD=ENTER X10 X11 X12 X13 X14.

          Table 6. Correlation matrix

          X9

          X10

          X11

          X12

          X13

          X14

          X15

          X9

          1

          .485**

          .191

          .597**

          .584**

          .308*

          .285*

          X10

          .485**

          1

          .118

          .304*

          .487**

          .197

          .399**

          X11

          .191

          .118

          1

          .367**

          .756**

          .629**

          .663**

          X12

          .597**

          .304*

          .367**

          1

          .528**

          .626**

          .636**

          X13

          .584**

          .487**

          .756**

          .528**

          1

          .586**

          .724**

          X14

          .308*

          .197

          .629**

          .626**

          .586**

          1

          .815**

          X15

          N

          .285*

          .399**

          .663**

          .636**

          .724**

          .815**

          1

          60

          60

          60

          60

          60

          60

          60

          Regression

          Table 7. Regression variables

          Model

          Variables Entered

          Variables Removed

          Method

          1

          Team Co-Ordination, Leisure Satisfaction, Relationship with Colleagues, Relationship with Boss, Relationship with Team

          Membersa

          .

          Enter

          a. All requested variables entered.

          Table 8. Model summary

          Model

          R

          R Square

          Adjusted R Square

          Std. Error of the Estimate

          1

          .884a

          .781

          .761

          .670

          a. Predictors: (Constant), Team Co-Ordination, Leisure Satisfaction, Relationship with Colleagues, Relationship with Boss, Relationship with Team Members

          Table 9. Variable coefficientsa

          Model

          Un standardized Coefficients

          Standa rdized Coeffi cients

          t

          Sig.

          95.0%

          Confidence Interval for B

          B

          Std. Error

          Beta

          Lower Bound

          Upper Bound

          1 (Constant)

          – 6.68

          2.548

          -2.624

          .011

          – 11.794

          -1.578

          Leisure

          .122

          .061

          .162

          1.993

          .051

          .000

          .245

          Satisfactio

          n

          Relationsh

          .220

          .172

          .150

          1.279

          .206

          -.125

          .566

          ip with

          Colleagues

          Relationsh

          .096

          .069

          .122

          1.391

          .170

          -.042

          .234

          ip with

          Boss

          Relationsh

          .510

          .398

          .166

          1.283

          .205

          -.287

          1.308

          ip with

          Team

          Members

          Team Co-

          .742

          .141

          .515

          5.265

          .000

          .460

          1.025

          Ordination

          a. Dependent Variable: Professional Environment

          Table 10. ANOVAb

          Model

          Sum of Squares

          df

          Mean Square

          F

          Sig.

          1 Regression

          86.663

          5

          17.333

          38.564

          .000a

          Residual

          24.270

          54

          .449

          Total

          110.933

          59

          a. Predictors: (Constant), Team Co-Ordination, Leisure Satisfaction, Relationship with Colleagues, Relationship with Boss, Relationship with Team Members

          Using tables, the critical values at 5% confidence level and 1% confidence level of F(5,59) is less when compared to a high computed value of F

          =38.564.That is, we reject the null hypothesis. Result1 of Test 1.. Indian IT Software Entrepreneurs are successful in showing a positive impact of ICT achievements towards the Professional Development of their Organization.

    2. Objective B

      To point out that knowledge is a factor of production and reveal that knowledge in the field of I.T. had developed the concept of Entrepreneurship.

      The following two graphs are sufficient enough to prove that knowledge is a factor of production and reveal that knowledge in the field of I.T. had developed the concept of Entrepreneurship.

      1. Purpose of Internet Use

        Figure 7. Purpose of internet use

      2. Internet Use Has Made Life Easier

        Figure 8. Internet use has made life easier

        Result 2. A Strong Agreement of the respondents towards the fact that ICT Applications are required for their present job and also that their life has become easier due to these applications further support to meet this objective. Hence we conclude that knowledge is a factor of production and reveal that knowledge in the field of I.T. had developed the concept of Entrepreneurship.

  6. Bibliography

  1. Proximities and Innovation: Evidence from Indian IT industry in Bangalore, by Florian Arun Taeube

  2. The Software Industry and India's Economic Development Wider Discussion Paper No. 2001/20 Ashish Arora and Suma Athreye

  3. Assessing software reuse in Indian information technology firms: a structural equation modelling approach Padmanav Acharya, Biswajit Mahanty page 255-275 DOI: 10.1504/IJISE.2010.035011

    International Journal of Industrial and Systems Engineering 2010 Vol. 6, No. 3 pp. 225-275, Padmanav Acharya, Biswajit Mahanty.

  4. International Journal of Industrial and Systems Engineering 2010 – Vol. 6, No.3 pp. 255 275 [5]Journal of Theoretical and Applied Information Technology © 2005 – 2008 JATIT. 1088 Performance, challenges and opportunities www.jatit.org

  1. International Journal of Computational Engineering Research, Potential of Information on Communication Technology towards the Success of the Indian IT Software Industry, by Sheela Bhatt, Dr.S.S.Sarangdevot www.ijceronline.com

  2. India: E-Readiness Assessment Report 2005

  3. Annual Report 2009-10 of the Department of Information and Technology, Ministry of Information and Communication Technology

  4. Annual Report of 2009-10 of the Department of Telecommunication, Ministry of

Information and Communication Technology [10]Reports of Annual Survey of industries for different years DRUID Working Paper No 04-10

  1. Report No. 509 of the 62nd round survey of National Sample Survey Office

  2. Official Website of the Ministry of Statistics and Program Implementation of

    Government of India, www.mospi.nic.in

  3. Software Technology Parks of India (STPI), Hyderabad

    • Department of Information Technology, Govt. of India

    • Standardisation, Testing & Quality Certification (STQC)

    • MIT Accreditation of Computer Courses (DOEACC)

    • IT & Communication Dept., Govt. of AP, AP Technology Services (APTS), Govt. of AP

    • AP Online, Govt. of Andhra Pradesh Institute of Electronic Governance HITEC City, Hyderabad

    • International Institute of Information Technology (IIIT), Hyderabad

    • Hyderabad Software Exporters Association (HYSEA)

  4. http://www.economictimes.com/today/03feat3.htm [15]http://www.nasscom.org

Leave a Reply