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    COMSATS Institute of Information & Technology

    PRODUCTIVITY GAINS FROMIMPLEMENTING EMPLOYEE

    TRAINING

    _________________________________________

    Researchers:MUHAMMAD HAMAD (FA09-BBA-057/B)

    UBAID-UR-REHMAN (FA09-BBA-095/B)

    TAIMOOR ALI DAR (FA09-BBA-093/B)

    WAJIHA ASAD (FA09-BBA-102/B)

    _____________________________________________________________________

    Submitted to:

    Ms. UZMA NAEEM

    _____________________________________________________________________

    Submission Date:

    December 19, 2011.

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    2.0 TABLE OF CONTENTS:

    SECTION DESCRIPTION PAGE #

    1.0 ABSTRACT 1

    2.0 INTRODUCTION 2

    2.1 Problem Statement 22.2 Objective 22.3 Background Information 23.0 BODY 3 11

    3.1 Literature Review 3 53.2 Theoretical Framework 5 63.3 Hypothesis Statement 63.4 Research Design 7 83.5 Data Analysis 8 - 114.0 CONCLUSION 12

    5.0 RECOMMENDATIONS 13

    6.0 ACKNOWLEDGEMENT 14

    7.0 REFERENCES 15 - 16

    8.0 APPENDIX 17 - 25

    8.1 Questionnaire 17 - 188.2 Tables 19 - 25

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    Page 1

    1.0 ABSTRACT:

    The research was undertaken in order to measure the impact of employee training on

    employee productivity. The research was started by reading relevant literature by the research

    team focusing on the two variables in discussion. A literature review was established after

    thorough reading of 25-30 articles. Literature review helped the team to identify the research

    problem and design a hypothesis statement. A theoretical framework was established to

    diagrammatically represent the relationship of employee training (independent variable),

    employee productivity (dependent variable) and age of employees (moderating variable). The

    variables were defined later on in the theoretical framework.

    On the basis of theoretical framework, a research design was established where purpose of

    the study was defined at first. Hypothesis testing was the purpose of study and type of

    investigation was initially correlational and later on the causal relationship was also tested

    during the analysis stage. Level of interference was kept minimal and employees were

    interviewed in their natural work environment. For our sampling, we used probability

    sampling and randomly chose employees from banking sector. Data collection method that

    was used during the research was Questionnaires. A questionnaire of closed ended questions

    was designed and was circulated to 100 employees in different banks (Allied Bank and State

    Bank of Pakistan) to gather the information required. Data analysis technique used was a

    computer based program named as SPSS.

    During the data analysis stage, help of a computer program named SPSS was taken to

    accurately measure the result of 100 filled questionnaires from different employees of bank.

    Using the software the correlation between the two variables i.e. employee training and

    employee productivity was checked at first. The results showed that there is a positive

    relationship between employee training and employee productivity. After the relationshipwas identified between these variables the causal relationship was tested through regression

    lines which also showed positive results. The effect of moderating variable i.e. Age of

    employees was also tested along with training and productivity and was found that employees

    belonging to the age group of 36-46 were the ones with the highest level of productivity after

    being trained. From the same results, it was derived that most experienced employees of

    banks, age group 58-60 had comparatively lower level of productivity as compared to other

    age groups.

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    2.0 INTRODUCTION

    2.1 Problem Statement:

    A problem statement is a concise description of the issues that need to be addressed by aproblem solving team and should be created by them before they try to solve the problem.

    The intention of this research is to analyze and evaluate the impact of employee training on

    employee productivity and how such impact is moderated by age of employees.

    2.2 Objective:

    The overall objective of this research paper is to provide understanding towards the impact of

    employee training programs, implemented by different organizations, on employee

    productivity. This research paper will serve as a useful piece of work in understanding the

    productivity level of employees after their organizations provide them an opportunity to get

    job related training. After this research, it will become more clear that what kind of job

    training improves the productivity of employees and how. The information will be gathered

    mainly from employees of banking sector to know the trends of employee training programs

    and its impact on productivity in this sector. This research will also help the readers to

    understand how age of employees moderates the relationship between training andproductivity of employees.

    2.3 Background Information:

    This research paper is focused towards employee training and its impact on employee

    productivity. The relationship is also studied when it is moderated by age of employees. To

    get some background information about these variables, articles focused on these variables

    were thoroughly read by the research team and wrote a literature review out of it. A

    theoretical framework was also designed to show the relationship between the dependent,

    independent and moderating variable through a diagram. A detailed research design was also

    established for this research where type of investigation and sampling design was discussed.

    During this research a sample of 100 employees were taken who were asked a set of close

    ended questions. Banking sector was chosen for this research and randomly selected

    employees from different banks were provided with the questionnaires to which they

    answered according to what they think is the impact on their productivity after they received

    some sort of training at work.

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    3.0 BODY

    3.1 Literature Review:

    Productivity Gains from Implementing Employee Training: Relationship between

    employee training and productivity exists, not only at the level of individual employee but on

    the organization level as well. The businesses which were operating below their expected

    labor productivity levels in 1983 implemented new employee training programs after 1983,

    which resulted in significantly large increase in labor productivity between 1983-1986

    (Bartel, 1991).

    Training is one of the several human resource practices that can have considerable impact on

    employee commitment. Employee training helps the organization in retention of employees

    and increases employee's commitment to the company. Companies that invest in employee

    training programs get a positive relationship between training and commitment, and an

    inverse relationship between commitment and turnover. A positive relationship between

    training and employee motivation, employee commitment and employee satisfaction has been

    found. When employees are motivated, committed and satisfied, they tend to be more skilled,

    knowledgeable, dedicated, well experienced and work as one unit to achieve organizational

    goals (Brum, 2007 and Nadeem, 2010). Training nowadays is not general and is more

    focused on specific skills. A difference exists between general and specific training. General

    training is still worthy enough for an individual if he or she quits the organization, but

    specific training of a specific technology has no value if trained workers of that technology

    leave the organization (Konings & Vanormelingen, 2010).

    Training also helps in retaining knowledge within the organization, but may not help in

    retaining employees. Sometimes organizations do not gain increased retention rates, but

    derive other direct and indirect benefits from training such as improved job performance,increased job satisfaction and reduced levels of job related stress (Acton & Golden, 2002).

    Higher wages is not only the mean of productivity; training has got a very important place in

    measuring productivity. The factor of training in the production function was around twice as

    large as the factor in the wage equation. Employee training has a positive and significant

    effect on productivity and wages, but the effect of training on wages is half the size of the

    effect on productivity. Unobserved diverse work force leads to overestimate the impact of

    training on productivity, whereas not giving importance to employee training within

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    origination leads to underestimate the impact of training on productivity (Dearden, Reed and

    Reenen: 2006, Colombo and Stanca, 2008).

    Another view about the employee training is that it is an expensive plan, so in order to get

    full value from employee training, organizations need to reinforce training and create such

    work environment that supports transfer of new knowledge/skills to the job and the

    organization (Asherman, 2010). But it is cheaper for an organization to hire trained workers

    from the competitors than to train their own skilled workers. Trained workers are paid more

    than untrained workers, but in most organizations wage premium is smaller than extra

    productivity net of the cost of training the worker (Bishop, 1994). In today's competitive

    business environment, businesses can only survive through training their employees, but

    small businesses cannot afford training both monetary as well as in terms of opportunity cost.

    It has been obvious that, on job training is still enjoying its higher status as compared to

    different training programs. Shifting of business towards services sector require the

    companies to polish the skills of employees and communicate well to remain in business

    (Fernald & Solomon, 1996). Large businesses that introduce new technology and have high

    proportion of internal promotions were more likely to have formal training programs. Formal

    training had a positive impact on labor productivity, especially in those businesses that

    evaluated their training programs based on productivity indicators. Increase in productivityattributable to training is largely due to the fact that businesses who undertake employee

    training rely on screening of job applicants which significantly enhances labor productivity

    (Bartel, 1989). Those businesses which invest in training are more productive than those who

    dont as a positive correlation between training and productivity exists (Gabriella, 2005).

    While making investment decisions, the managers have to justify each dollar of investment

    and its return. A lot many areas of organizational efficiency and effectiveness cant be

    quantified but a general agreement about the positive relation between training and

    productivity exist (Brown 2001). And by linking the positive relation of employee training

    with the overall strategy of the organization; many organization are using it as a competitive

    advantage (Khera, 2010).

    Another aspect of looking at employee training is TQM. TQM is becoming the basic

    requirement for the organizations to compete and it demands up-to-date skills of the

    employees which are only possible through training which result in better organizational

    performance (Cooney, Terziovski, and Samson, 2002). By many studies the positive relation

    of employee training and productivity has been proved but managers are still unwilling to

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    invest in training programs because they think that during the tough time of organization,

    trained employees can switch to the competitor, and therefore cost and benefits of training

    programs are matched (Glance, Hogg and Huberman, 1997). Todays rapidly changing global

    business environment forces the firms to change themselves to keep pace with the industry,

    employee training can be used as a tool to make grounds for change. Training is important for

    all managerial posts either senior executives or the front line managers because it tells the

    management how to best use the scarce resources of the firm. Organizations invest in training

    and development programs due to its sure benefit of productivity (Lee & Bruvold, 2003). The

    process of training and development starts when organization finds any gap between the

    current and desired situation, organizations try to fulfill this gap to achieve higher levels of

    productivity (Babaita, 2010).

    3.2 Theoretical Framework:

    A theoretical framework is a collection of interrelated concepts, like a theory but not

    necessarily so well worked-out. A theoretical framework guides the research, determining

    what things we will measure, and what statistical relationships we are looking for.

    (Moderating Variable)

    (Independent Variable) (Dependent Variable)

    AGE

    Employee Training Employee Productivity

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    Definition of Variables:

    Dependent variable:

    Employee Productivity: If an individual takes less time and resources to

    perfo rm a spe ci fi c task he/ she is said to be productive . Productivity is the

    dependent variable in our research and whether employee training, as an

    independent variable, increases or decreases the level of productivity is to be

    tested.

    Independent Variable:

    Employee Training:Training refers to the acquisition of knowledge, skills, and

    competencies as a result of teaching of vocational or practical skills and

    knowledge that relate to specific useful competencies. Training can be On-the-

    Job or Off-the Job Training.

    A general agreement exists between different school of thoughts that employee

    training is providing knowledge and up to date skills to the workers.

    Moderating Variable:

    The moderating variable is one that has a strong contingent effect on the

    independent variable and dependent variable relationship. That is the presence of

    a third variable modifies the original relationship between the independent and

    the dependent variables. In our research the moderating variable is the Age of

    employees.

    3.3 Hypothesis Statement:

    A hypothesis is a tentative statement about the relationship between two or morevariables.A

    hypothesis is a specific, testable prediction about what you expect to happen in your study.

    The hypothesis statement for our research on employee training and productivity is:

    If organizations implement employee training programs, then productivity level of

    employees will increase, as moderated by age of employees.

    http://psychology.about.com/od/researchmethods/f/variable.htmhttp://psychology.about.com/od/researchmethods/f/variable.htm
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    3.4 Research Design:

    Purpose of the Study:

    The purpose of this research paper is to examine the relationship between employee trainingand its impact on productivity.Hypothesis testingwill be used to test the proposed hypothesis

    statement in an attempt to answer the research problem question.

    Type of Investigation:

    At first we will find whether the relationship between employee training and productivity

    exists or not by checking the results of correlational tests. If the correlation is positive and

    strong then we will shift our focus towards establishing and analyzing cause-and-effectrelationship among employees training, productivity and their age. This causal studywill be

    conducted to understand how employee training programs causes the productivity levels of

    employees to change.

    Extent of Researcher interference:

    Due to limited authority and resources, there will be minimum interferenceby our research

    team. The study will be conducted to establish correlation & later cause-and-effectrelationships between employee training and productivity, while manipulating the

    independent (Training) and moderating (Age) variable.

    Study Setting:

    The research team will usefield study innon-contrived settingsto establish correlational and

    later causal relationship, using the same natural environment in which employees normally

    perform their duties.

    Time Horizon:

    Due to time constraints and limited resources, the research team intends to collect relevant

    data from employees in one visit to the organization. The data collected from cross-sectional

    studywill be sorted and analyzed to test the proposed hypothesis statement.

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    Unit of Analysis:

    The unit of analysis for our research study will be individual trained employeesof banking

    sector.

    Sampling Design:

    A sampling design specifies for every possible sample its possibility of being drawn. We are

    using Probability Sampling for our research where Simple Random Sampling is applied while

    selecting employees from banking sector.

    Data Collection Method:

    Data collection method that we used for our research paper is Questionnaires. We designed a

    questionnaire, mainly consisting of close ended questions using the Likert Scale and gathered

    information from almost 100 employees from different banks.

    Data Analytic Technique Used:

    For the analysis of the data gathered from questionnaires we are using a software technique.

    The software that we are using for data analysis is SPSS. SPSS is a computer program used

    for survey authoring and deployment (IBM SPSS Data Collection), data mining (IBM SPSS

    Modeler), text analytics, statistical analysis, and collaboration and deployment (batch and

    automated scoring services).

    3.5 Data Analysis:

    After obtaining data from the banking sector of Pakistan, the hypothesis that employee

    training and productivity are related to each other was being tested for correlation. The value

    of correlation coefficient is +0.557 as shown in Table 1, which means that there is a strong

    positive relationship between employee training and productivity in the banking sector of

    Pakistan. It means that if we enhance training then there will be a positive change in

    productivity of employees.

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    CORRELATIONS

    Total

    Training

    Total

    Productivity

    Total Training Pearson Correlation 1 .557**

    Sig. (2-tailed) .000

    N 100 100

    Total Productivity Pearson Correlation .557** 1

    Sig. (2-tailed) .000

    N 100 100

    **. Correlation is significant at the 0.01 level (2-tailed).

    AGE GROUPS REGRESSION LINE VALUE

    2535 Y= 1.131+0.661X 1.792

    3646 Y= 1.714+0.410X 2.124

    4757 Y=1.210+0.583X 1.793

    5860 Y=1.069+0.605X 1.674

    OVERALL Y=1.268+0.585X 1.835

    To check the effect of moderating variable age on the relationship of employee training and

    productivity first the relation was tested for age group of 25 to 35years. R square showed a

    40.8% change in employee productivity due to the training programs implemented by the

    organization. The linear regression model developed by using Table 2 (d) shows that one unit

    increase in training leads to 1.792 units increase in productivity. The ANNOVA test Table

    2(c) showed that significance level is below 0.05, which supports the significance of the

    study.

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    For the age group 36 to 46, the results obtained showed a new dimension. The results showed

    that for this age group R2is 11.5% Table 3(b). The regression line developed from the results

    showed that a unit increase in training leads to 2.124 units change in productivity of the

    employees. ANNOVA supports the findings as significance level is 0.040 because it is below

    0.05 Table 3(c).

    The results of age group 47 to 57showed 43.9% change in productivity due to independent

    variable Table 4(b). The regression line developed from Table 4(d), 1.793 units increase in

    productivity due to training being provided to the employees. Significance level is below 0.05

    which is 0.01, which is favoring our hypothesis. Table 4(c).

    For age group 58 to 60 R2 is 99.4% which is highest among all the age groups, showing

    maximum positive change in productivity of Bankers in Pakistansbanking sector table 5(b).

    In the same way regression line developed from table 5(d), 1.674 units show positive change

    in productivity if one unit of training is provided. ANNOVA shows 0.048 acceptable level of

    significance as it is below 0.05 table 5(c).

    After calculating the regression for each age group to check the effect of age on the

    relationship of employee training and productivity, regression analysis was conducted. The

    results supported our hypothesis and the regression line showed that a unit increase intraining will lead to 1.835 units change in productivity according to Table 6.

    COEFFICIENTS

    Model Unstandardized

    Coefficients

    Standardized

    Coefficients

    t Sig.

    B Std. Error Beta

    1 (Constant) 1.268 .250 5.062 .000

    Total training .585 .088 .557 6.645 .000

    a. Dependent Variable: Total Productivity

    Interpretations:

    There exist a strong positive relation between training and productivity. As showed by the

    results, productivity of employees depends upon training. If sufficient training is being

    provided to the employees there productivity will increase. The gains from training are higherfor people belonging to the age bracket of 36 to 46 years because such employees want to

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    excel in their respective job descriptions, so for this they opt for training programs to learn

    new skills. The age group of 58 to 60 showed comparatively low level of productivity

    increase due to training, this is because such employees are in later stages of their

    professional life and want a stable job instead of challenging jobs, so they hesitate in getting

    into different training programs to increase their productivity. So we can conclude that

    employees who are in their middle ages are more productive when provided opportunity to

    get into some training programs.

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    4.0 CONCLUSION:

    The result that we derived from our data analysis stage showed that there exists a strong

    positive relationship between employee training and productivity. When employees are

    provided an opportunity to get some work related training, such employees showed

    impressive improvement in their productivity level. The age being moderating variable in this

    relationship was also tested along with the dependent and independent variables. We divided

    the age of employees into 4 groups, 25-35, 36-46, 47-57 and 58-60, and results showed that

    employees of age group 36-46 had the highest level of productivity after being trained.

    Employees that belong to the last age group i.e. 58-60 showed comparatively low levels of

    productivity, this is because they want a stable job rather than a challenging one and are

    satisfied with their productivity at work, so they avoid getting into training programs.

    Hence, banking sector in Pakistan should invest more in their employee training and

    development programs to increase the overall productivity of the organization.

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    5.0 RECOMMENDATIONS:

    After working on this research paper we would like to give following recommendations to the

    Banking Sector of Pakistan.

    They should invest more on employee training programs.

    The organization should try to retain the highly trained employees by providing them

    high prospects within the organization.

    They should provide more training opportunities to newly appointed employees and

    employees of age group 36-46, as their productivity levels are the highest as per the

    data analysis.

    The organization should provide full support and guidance to employees during the

    times they are in training.

    They should encourage the most experienced employees (Age Group: 58 - 60) to take

    part in training programs and set an example for newly appointed employees.

    The organization should promote the employees to higher job titles when they show

    high levels of productivity due to training.

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    6.0 ACKNOWLEDGEMENT:

    We bow our heads in gratitude to almighty ALLAH, who blessed us with the ability and

    energy to complete this work.

    We have put all our sincere efforts in this research paper. However, it would not have been

    possible without the kind support and help of some individuals and organizations we

    collected data from. We would like to extend our sincere thanks to all of them.

    We would like to express our gratitude towards our parents, course instructors, and every

    member of the management & employees of different banks that we visited, for their kind co-

    operation & encouragement which helped us in completion of our research paper.

    Special thanks to our Research Tools & Technique course instructor, Ms. Uzma Naeem, who

    provided us an opportunity to work on this project and for her guidance and encouragement

    in carrying out this research work.

    We are also highly indebted to Mr. Zaheer A. Gureja who is Branch Manager at Humak

    Allied Bank and Mr. Arshad Mahmood who is an Audit Officer Grade 2 at State Bank of

    Pakistan for their guidance and constant supervision during our data collection stage. We

    would also like to thank all the employees of these banks, who showed patience and honesty

    while giving us information through questionnaires.

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    7.0 REFERENCES:

    Acton, T., & Golden, W. (2002). Training: the way to retain valuable it employees.

    Informing Science. Galway, Ireland.

    Asherman, I. G. (2010). Employee Training: Getting Your Money's Worth. New

    York City. Regulatory Focus, Regulatory Affairs Professional's Society.

    Babaita, I. S. (2010).Productivity as a Driving Force for Investment in Training

    and Management Development in the Banking Industry. European Journal of Social

    Sciences.

    Bartel, A. P. (1991). Productivity Gains from the Implementation of Employee

    Training Programs. Working Paper No. 3893. National Bureau of Economic

    Research. Cambridge, MA 02138. Bartel, A. P. (1989). Formal Employee Training Programs and Their Impact On

    Labor Productivity: Evidence From A Human Resources Survey. Working paper

    No. 3026.National Bureau of Economic Research. Cambridge, MA 02138.

    Bishop, J. H. (1994). The Impact of Previous Training on Productivity and Wages.

    University of Chicago Press.

    Brown, B. L. (2001). Return on Investment in Training. ERIC Clearinghouse on

    Adult, Career, and Vocational Education.

    Brum, S. (2007). Training and Employee Commitment. University of Rhode Island,

    Schmidt Labor Research Center Seminar Research Series.

    Colombo, E., & Stanca, L. (2008). The Impact of Training on Productivity:

    Evidence from a Large Panel of Firms. University of Milan Bicocca.

    Cooney, R., Terziovski, M., & Samson, D. (2002). Employee Training, Quality

    Management and the Performance of Australian and New Zealand Manufacturers.

    Working Paper 3402. Monash University.

    Dearden, L., Reed H., & Reenen J. V. (2006). The impact of training on

    productivity and wages: Evidence from British Panel Data. The Institute for Fiscal

    Studies, Houghton Street, London.

    Gabriella. (2005). Training, Productivity and Wages in Italy.Labour Economics,

    Elsevier.

    Glance, N.S., Hogg, T., & Bernardo, A. Huberman. (1997). Training and Turnover

    in the Evolution of Organizations. Organization Science 8, pg 84-96.

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    Khera, S. N. (2010). Human Resource Practices and their Impact on Employee

    Productivity: A Perceptual Analysis of Private, Public and Foreign Bank

    Employees in India. DSM Business Review, 2, 1.

    Konings. J., & Vanormelingen, S. (2010). The Impact of Training on Productivity

    and Wages: Firm Level Evidence. Discussion Paper No. 4731. The Institute for the

    Study of Labor (IZA).

    Lee, C. H. & Bruvold, N. T. (2003). Creating Value for Employees: Investment in

    Employee Development. The International Journal of Human Resource

    Management.

    Lloyd, W. Fernald Jr., George, T. Solomon. (1996). Small Business Training and

    Development: An Analysis of Manager/Employee Needs and Practices.

    International Journal of Organizational Behavior.

    Nadeem, M. (2010).Role of Training in Determining the Employee Corporate

    Behavior with Respect to Organizational Productivity. International Journal of

    Business and Management, 5, 12.

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    8.0 APPENDIX:

    8.1 QUESTIONNAIRE

    The purpose of this survey is to measure the impact of Employee Training on Employee

    Productivity. This study is purely for the research purpose and the given information will

    be kept confidential. You are requested to kindly provide us accurate information.

    Gender: Female Age: 25-35Male 36-46

    47-57

    Designation: _________________ 58-60

    TRAINING & PRODUCTIVITY

    Strongly

    Disagree

    1

    Disagree

    2

    Neither

    Agree nor

    Disagree

    3

    Agree

    4

    Strongly

    Agree

    51. Employee training programs provide

    me an opportunity to progress within

    my organization.

    2. Training helps me to define my workrelated goals and objectives more

    clearly.

    3. My organization allows employees tohave the time to learn new skills that

    prepare them for future jobs.

    4. Training programs have made memore productive at work.

    5. Training helped me in learning newwork specific skills.

    6. Training helped me achievingproductivity targets set by my

    organization.

    7. Essential skills training reduces thetime required to complete work.

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    8. My organization trains employees onskills that prepare them for future

    jobs and career development.

    9. My organization provides supportwhen employees decide to obtain

    ongoing training.10.My organization provides a

    systematic program that regularly

    assesses employees skills and

    interests.

    11.Violation of rules and regulations reduces after training.

    Yes

    No12.Does training helps in prioritizing the work?

    Yes

    No13.Do you think that number of mistakes by employees can be reduced after sufficient

    training?

    Yes

    No14.Does training help employees to bring balance between personal and professional life?

    Yes

    No15.Does Apprenticeships increase productivity?

    Yes

    No16.Is orientation given to new employees?

    Yes

    No

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    8.2 Tables:

    1) The Correlation between Employee Training and Productivity

    Correlations

    Total

    training

    Total

    productivity

    Total training Pearson Correlation 1 .557**

    Sig. (2-tailed) .000

    N 100 100

    Total productivity Pearson Correlation .557** 1

    Sig. (2-tailed) .000

    N 100 100

    **. Correlation is significant at the 0.01 level (2-tailed).

    Table 2:

    (a)

    Variables Entered/Removedb,c

    Model Variables

    Entered

    Variables

    Removed

    Method

    1 Total training . Enter

    a. All requested variables entered.

    b. Dependent Variable: Total productivity

    c. Models are based only on cases for which what

    is your age = 25-35

    (b)

    Model Summary

    Model R R

    Square

    Adjusted R

    Square

    Std. Error of

    the Estimatewhat is your

    age = 25-35

    (Selected)

    1 .638a .408 .394 .276

    a. Predictors: (Constant), Total training

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    (c)

    ANOVAb,c

    Model Sum of

    Squares

    Df Mean

    Square

    F Sig.

    1 Regression 2.305 1 2.305 30.268 .000a

    Residual 3.350 44 .076

    Total 5.655 45

    a. Predictors: (Constant), Total training

    b. Dependent Variable: Total productivity

    c. Selecting only cases for which what is your age = 25-35

    (d)

    Coefficientsa,b

    Model Unstandardized

    Coefficients

    Standardized

    Coefficients

    T Sig.

    B Std. Error Beta

    1 (Constant) 1.131 .341 3.317 .002

    Total training .661 .120 .638 5.502 .000

    a. Dependent Variable: Total productivity

    b. Selecting only cases for which what is your age = 25-35

    Table 3:

    (a)

    Variables Entered/Removedb,c

    Mod

    el

    Variables

    Entered

    Variables

    Removed

    Method

    1 Total training . Enter

    a. All requested variables entered.

    b. Dependent Variable: Total productivity

    c. Models are based only on cases for which what

    is your age = 36-46

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    Page

    21

    (b)

    Model Summary

    Model R R

    Square

    Adjusted R

    Square

    Std. Error of

    the Estimatewhat is yourage = 36-46

    (Selected)

    1 .339a .115 .089 0.288

    a. Predictors: (Constant), Total training

    (c)

    ANOVAb,c

    Model Sum of

    Squares

    Df Mean

    Square

    F Sig.

    1 Regression .376 1 .376 4.529 .040a

    Residual 2.909 35 .083

    Total 3.285 36

    a. Predictors: (Constant), Total training

    b. Dependent Variable: Total productivity

    c. Selecting only cases for which what is your age = 36-46

    (d)

    Coefficientsa,b

    Model Unstandardized

    Coefficients

    Standardized

    Coefficients

    t Sig.

    B Std. Error Beta

    1 (Constant) 1.714 .56 3.058 .004

    Total training .410 .193 .339 2.128 .040

    a. Dependent Variable: Total productivity

    b. Selecting only cases for which what is your age = 36-46

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    Page

    22

    Table 4:

    (a)

    Variables Entered/Removedb,c

    Model VariablesEntered

    VariablesRemoved

    Method

    1 Total training . Enter

    a. All requested variables entered.

    b. Dependent Variable: Total productivity

    c. Models are based only on cases for which what

    is your age = 47-57

    (b)

    Model Summary

    Model R R

    Square

    Adjusted R

    Square

    Std. Error of

    the Estimatewhat is your

    age = 47-57

    (Selected)

    1 .662a .439 .392 .271

    a. Predictors: (Constant), Total training

    (c)

    ANOVAb,c

    Model Sum of

    Squares

    df Mean

    Square

    F Sig.

    1 Regression .688 1 .688 9.375 .010a

    Residual .880 12 .073

    Total 1.568 13

    a. Predictors: (Constant), Total training

    b. Dependent Variable: Total productivity

    c. Selecting only cases for which what is your age = 47-57

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    (d)

    Coefficientsa,b

    Model UnstandardizedCoefficients

    StandardizedCoefficients

    t Sig.

    B Std. Error Beta

    1 (Constant) 1.210 .517 2.341 .037

    Total training .583 .190 .662 3.062 .010

    a. Dependent Variable: Total productivity

    b. Selecting only cases for which what is your age = 47-57

    Table 5:

    (a)

    Variables Entered/Removedb,c

    Mod

    el

    Variables

    Entered

    Variables

    Removed

    Method

    1 Total training . Enter

    a. All requested variables entered.

    b. Dependent Variable: Total productivity

    c. Models are based only on cases for which what

    is your age = 58-60

    (b)

    Model Summary

    Model R R

    Square

    Adjusted R

    Square

    Std. Error of

    the Estimatewhat is your

    age = 58-

    60(Selected)

    1 .977a .994 .989 .020

    a. Predictors: (Constant), Total training

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    Page

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    (c)

    ANOVA

    b,c

    Model Sum of

    Squares

    df Mean

    Square

    F Sig.

    1 Regression 0.073 1 0.073 176.333 .048a

    Residual 0.000 1 0.000

    Total 0.073 2

    a. Predictors: (Constant), Total training

    b. Dependent Variable: Total productivity

    c. Selecting only cases for which what is your age = 58-60

    (d)

    Coefficientsa,b

    Model Unstandardized

    Coefficients

    Standardized

    Coefficients

    t Sig.

    B Std. Error Beta

    1 (Constant) 1.069 .124 8.622 .074

    Total training 0.605 .046 .997 13.279 .048a. Dependent Variable: Total productivity

    b. Selecting only cases for which what is your age = 58-60

    Table 6:

    (a)

    Variables Entered/Removedb

    Model Variables

    Entered

    Variables

    Removed

    Method

    1 Total training . Enter

    a. All requested variables entered.

    b. Dependent Variable: Total productivity

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    (b)

    Model Summary

    Mod

    el

    R R

    Square

    Adjusted R

    Square

    Std. Error of

    the Estimate

    1 .557a .311 .304 .282

    a. Predictors: (Constant), Total training

    (C)

    ANOVAb

    Model Sum of

    Squares

    Df Mean

    Square

    F Sig.

    1 Regression 3.501 1 3.501 44.159 .000a

    Residual 7.770 98 .079

    Total 11.270 99

    a. Predictors: (Constant), Total training

    b. Dependent Variable: Total productivity

    (d)

    Coefficientsa

    Model Unstandardized

    Coefficients

    Standardized

    Coefficients

    t Sig.

    B Std. Error Beta

    1 (Constant) 1.268 .250 5.062 .000

    Total training .585 .088 .557 6.645 .000

    a. Dependent Variable: Total productivity