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Chapter-2

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2. Review of Literature

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Many researchers have done studies on performance appraisal system and

performance management system in India and abroad. It is very interesting to do

research on performance management system wherein this concept is being

introduced step by step. This chapter review of literature, reviews the literature of

performance management system herein published literature in the area was taken in

account. The literature review starts where Beer -et al (1979), McAfee and

Champagne (1993), Allan (1994), Armstrong and Baron (1998) have strongly

suggested that PMS if well designed and implemented leads to positive individual and

organizational outcomes. However, researchers have seen very specific elements or

outcomes of PMS rather than the whole system that may have been implemented and

for example performance discussions between subordinate and supervisors, during the

performance management process have been found to influence the performance and

behaviour of employees (Beer, 1981).

Leventhal(1980),Cascio and Bernardin(1981), Greenberg (1986), Alexander and

Ruderman(1987), Murphy and Cleveland (1991).The ability to appeal a rating, which

is considered unfair, inaccurate, or biased, is an important component to ensure

perceptions of procedural fairness.

There is a sufficient amount of empirical evidence exists in private sectors that

indicates that merit pay plans generally have a positive impact on employee

performance and organizational productivity (Heneman, 2002; Huselid, 1995;

Jenkins, Mitra, Gupta, & Shaw, 1998, Locke, Feren, McCaleb, Shaw, & Denny,

1980).

Dipboye, Robert L. and de Pontbriand, Rene (1981). In this study, 474 exempt

employees in a research and development organization were surveyed regarding their

opinions and perceptions of the appraisal process. Opinions of the appraisal and

appraisal system were positive to the extent they believed that (a) there was an

opportunity to state their own side of the issues, (b) the factors on which they were

evaluated were job relevant, and (c) objectives and plans were discussed.

Rao (1982). Conducted a survey of appraisal practices in 45 different organizations (

34 private and 11 public sector) and he found that about 50percent of the

organizations seem to profess the purpose of their appraisal as regulating employee

52

behaviour as well as developing employee capabilities. About 30 percent of them still

use appraisals only for controlling and regulating employee behaviour whereas only

about 10 percent seem to use appraisals mainly for developmental purposes.

Gangotra (1983). In a survey conducted in Jyoti Limited, Baroda wherein 70

managers responded to a questionnaire on performance appraisal system. Out of these

37 responded as appraisers and 33 responded as appraisees. Jyoti’s have an evaluation

system requiring each appraiser to assess his subordinates on performance related

qualities. After completing his assessment, each appraiser is expected to discuss with

his appriasee before sending form to personnel department.

Longenecker, Gioria and Sims (1987), Fried and Tiegs (1995). There is some

evidence that raters deliberately distort subordinates performance ratings for political

reasons, like manager provides inflated ratings to their subordinates in order to project

his/her good image or to avoid any confrontation.

Another study sought to identify factors related to employee perceptions of the

accuracy of performance ratings they received using a subjective rating system. It

also sought to determine if the relationship between these correlates and perceived

fairness and accuracy was moderated by employee sex and/or race. The results were

based on the analysis of items from questionnaires completed by 234 government

employees whose job performance was rated on a graphic rating scale.

Longenecker, Gioia, and Sims (1987). This indicates that managers have frequently

used the decision autonomy available to them under more traditional performance

management systems to bias and alter employee evaluations where both deflating and

inflating them, in order to further their own interests and given that procedurally just

performance management systems make such distortions more difficult, it seems

doubtful that managers will react favourably to restrictions on their ability to act

unilaterally. In support of this study, Brett, Ury and Goldberg (1989) have found that

managers who were "winning" under existing organizational conflict resolution

systems presented significant barriers to the implementation of procedures that

safeguarded the interests of both employees and their organization. Thus, there is

evidence that managers will react unfavourably to procedurally just performance

management systems, both because managers place a higher priority on efficiency in

53

HR procedures than on fairness and because they prefer to avoid constraints on their

decision autonomy.

Bies and Shapiro (1987).It is now a widely accepted fact that perceptions of fairness

influence the way people think, feel, and act on the job.

Amba Rao (2000) In Indian organisations, if employee has his own experiences of

success as well as found involvement in the PMS then it reduces the anxiety of

employees.

Wehrenberg, Stephen B. (1988). For measurement and evaluation of employee

performance, supervisors need to be trained otherwise correct evaluation cannot be

done which can cause damage to the employee evaluation.

Stephan and Dorfman (1989). Found that the outcomes of effective performance

appraisal are improvement in the accuracy of employee performance and

establishing relationship between performance on tasks and a clear potential for

reward and according to Grote, D (2000). Public organizations defined that

Performance appraisal today use an essential part of organizational life, for it

help to justify compensation differentiation, promotion, demotion, selection

validation, and termination.

Perry, James L –et al (1989). Four hundred and ninety six PMRS employees were

selected, employed by the U.S. General Services Administration (GSA). The results

indicate that PMRS merit increases have become automatic and the tendency to rate

large numbers of employees “fully doing well" which assures that many employees

receive performance awards as well. The opportunities to achieve large increases in

pay under PMRS still appear to be quite small.

Tyler (1989), Folger & Cropanzano (1998). This work usually has found that the

more just or fair employees consider such systems to be, the more satisfied and

accepting they are of the resultant outcomes, even when those outcomes are less than

desirable therefore the strength of these things has led to propose that the provision of

fair procedures is a more powerful foundation for the management of employees than

is the provision of valued rewards.

54

Eisenberger, Robert and Valerie Davis-LaMastro (1990).The study combining across

361 respondents in nine organizations such as manufacturing, insurance etc. There

was a highly consistent positive relationship of perceived support with employee

attendance and job performance. In addition, the positive relationship found in the

study between perceived support and employees' diligence in carrying out

conventional role responsibilities, perceived support might be associated with

constructive innovation on behalf of the organization without the anticipation of direct

reward or personal recognition.

Earley and Shalley (1991). Feedback and goal setting are widely believed to affect

performance positively through enhancing the motivation necessary for work

performance and Roberts and Reed (1996) proposed that goals, participation and

feedback impact on appraisal acceptance, which affects appraisal satisfaction and

finally employee productivity and motivation.

Guinn, Kathleen A and Corona, Roberta (1991). The lack of clarity about

performance goals reflected a lack of focus on results. It was perceived by the

employees that pay was increased based on their length of service than their

performance.

Mossholder, Kevin W –et al (1991). The study examined employee reactions and

perceptions with regard to role failure act and failure to maintain adequate privacy of

performance appraisal system wherein result indicates that organizations should

construct and administer appraisal system in such a way as to minimize employee’s

apprehensions about information privacy.

Kalpan and Norton (1992, 1993, 1996). They have developed the notion of a balanced

scorecard and suggest performance management including focusing on internal

business processes, customers, finances and learning and growth. Balanced scorecard

is key to translate the organization’s strategy into the right and integrated set of

measures, only then the performance management system can provide control by

providing guidance and monitoring financial results because these are the drivers of

future performance wherein employee know that how is to be performed? Where,

Peter Drucker (1992) uses of five gauges in business to control performance and

Reichheld (1996) suggests that performance management system is a key to success

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and defines what a company will become by tracking the flow of value to and from a

company’s employee.

O’ Neal, Sandra and Palladino, Madonna (1992). A system which supports the

primary goals of the business by significantly improving the outcomes and

management of employee performance wherein performance management can

succeed and the challenges can be met by involving employees in the process and

providing tangible and fair rewards for observable high performance.

McCabe, Douglas and Lewin, David (1992). Two dimensions of employee voice have

been considered wherein first was the formal grievance procedure and second was

participative management. To keep employees and non-management personnel, away

from these things make effective impact on employee and organizational

performance.

Mc Afee and Champagne (1993). This study identified the certain key aspects for

successful PMS implementation wherein supervisors must chart out the critical

competence areas, discuss and work them out with employees to establish a feasible

action plan. Moreover, organizations must establish a norm for self development

“employees need to know that they are expected continually to enhance their job

skills". The goals must be mutually developed and should be measurable, specific,

relevant, attainable, time-framed and challenging. Managers must be provided with

training to explain them the purpose and specific methodology of performance

management.

Johnson, Bradford A and Ray, Harry H (1993). In McDonnell helicopter co. required

a new compensation system then human resource department asked to employees to

develop skill based pay system for their units where new system and involvement of

employees in its development has significantly increased productivity of organization.

Arthur,Jeffrey B. (1994). Identifying two types of HR systems control, commitment

and specific combinations of policies and practices are useful in predicting differences

in performance and turnover across 54 U.S steel minimills.HR systems moderated the

relationship between turnover and manufacturing performance.

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Mavis, Mary (1994). Manager’s learning is required for taking employee feedback in

effective way therefore managers must validate feedback they offer to their employee.

Managers are required to understand and differentiate feedback and consequences

vary from person to person, even if the feedback different employees receive is

similar. Eventually, managers need to train for taking feedbacks. (Appendix-5)

Waldman, David A (1994). Suggested that performance management efforts focused

on group level rewards and appraisal will have a greater positive effect on Total

Quality Management implementation efforts than on efforts focusing on individuals,

particularly at lower hierarchical levels. Moreover, these effects will be further

maximized when coupled with a continuous improvement approach to work systems.

Wyatt (1994). Carried out a study which focusing on identifying best practices in

performance management by examining the systems of a selected group of 37

companies recognized for financial success and innovative human resource programs.

This emerged from the study, are a set of best practices that could facilitate the

process of designing, implementing, and monitoring performance management. These

are: internal and external alignment; flexibility, simplicity, decentralized control, a

measurement process, greater links between performance and pay, feedback from

multiple sources, senior management involvement and employee development.

Huselid, Mark A.(1995).Evaluated the links between systems of high performance

work practices and firm performance. Sample of nearly one thousand firms indicate

that these practices have an outcome of turnover and productivity of corporate

financial performance.

Murphy and Cleveland (1995). Performance management systems will work most

excellent when the formal goals and organizational uses of performance appraisal are

consistent with the goals of other appraisal elements along with the rater and the ratee.

Murphy and Cleveland (1995).There are typically many penalties and few rewards for

doing true appraisals. Employees are likely to regard a less than glowing performance

appraisal as a punishment, even if it is richly deserved and honest appraisals are likely

to lead to ill will between subordinates and supervisors. (Appendix-3)

57

Taylor, M.S -et al (1995). Performance management is the area in which manager’s

reactions have been found in this area which indicates that the time and effort required

of managers are much greater for more procedurally just performance management

systems than for more traditional and less procedurally fair systems, which have

fewer safeguards against bias and fewer opportunities for employee voice.

Dolan, L.Shimon and Moren, Denis (1995). Data were collected from 487 non-

management subordinates in a large fast food restaurant enterprise in province of

Quebec. The results indicate that the quality of rater ratee relationship is significantly

related to overall ratee perceptions of the appraisal process, perceived fairness of

appraisal process and acceptability of the PA system.

Sabharwal (1995), Gopalan and Rivera (1997). Studies indicate that the Indian society

is characterized by a culture of high power distance between superiors and

subordinates.

Tang and Sarsfield-Baldwin (1996), Thurston (2001). This research indicates that

procedural and distributive justice factors have been consistently correlated with

employee’s positive affective reactions toward their performance appraisal system.

Bradt, Jeffery A (1996). Employee would be more motivated by a performance

management system that focuses on their contributions to the organization. The key

determinates of employee motivation is right evaluation of their contribution.

Flapper, Simme DP –et al (1996). Have a consistent PMS more is required than a

consistent performance measurement system where the functions in the organization

and the tasks for which they are held responsible have been understood to be given.

This does not apply for new organizations or new tasks however, but in that case it

has to be decided which responsibilities should be assigned to which functions.

Sparrow and Budhwar (1997). It was found that trust with the leader plays major role

in the acceptance of PMS.

Gosselin, Alain –et al (1997). Diverse 265 employees were surveyed and result

indicated that performance feedback should be an ongoing process from their

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supervisors. Ratees preferred to have their assessments more than once in a year, at

least twice in a year.

Odden and Clune (1998). Whether it comes through district decentralization or

school choice options, site-based budget autonomy has been theorized to have

the potential for improving resource allocation and school performance and Odden

and Kelley (2002) argues that school-based budgeting allows for more flexible and

efficient compensation plans aligned with performance and skills.

Cawley, Brain D. (1998). Participation in performance appraisal process was most

strongly positively related to the employee satisfaction and the PAS perceived utility

of the appraisal, motivation of employees to improve performance as well as

perceived fairness of the system.

Wright, Allan (1998). This study reveals that to build a strong working relationship

with a subordinate, particular emphasis is placed on the skills necessary because

without these skills lasting changes in performance are unlikely to occur.

Mount, Michael K –et al (1998). 2350 managers rated their own performance and

were also rated by two subordinates, two peers and two bosses and result indicated

that trait effects in the performance ratings.

Taylor, Susan M –et al (1998). They examined manager’s reactions to the

implementation of a procedurally just performance management system in two

samples where findings indicated that managers who perceived unfairness in their

own most recent performance evaluations reacted more favourably to the

implementation of a procedurally just performance management system than those

who did not perceive unfairness.

Otley (1999), Ferraira and Otley (2005). A curiosity in performance management has

been an issue of latest academic attention which has a distress with the use of targets

in this perspective and this attention is significant in relation to the public services

where there has been a distinguished practical focus on the use of targets (Broadbent

and Laughlin, 2006) which are argued to be performance procedures that can be used

in the context of performance management system.

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Talyor, P J and Pierce, J L (1999). A longitudinal evaluation was conducted on the

effects of introducing a performance management system which attributed employee

attitude, merit based pay etc. in government organizations. The results indicated that

performance planning and goal setting component of the system had favourable

consequences for at least some employee’s attitudes and for lower performing

employees the organizational commitment and increased cooperation and satisfaction

with one’s supervisor.

Stivers, Bonnie P and Joyce, Teresa (2000). Performance management systems

should include a balanced set of procedures that are linked to the organization’s

strategic objectives wherein managers require timely “gauges” to control operations

and get feedback on strategy achievement wherein these gauges must be provided in a

balanced performance management system which includes both non financial and

financial measures.

Herman, Steensma and Lisette, Otto (2000). In this study 78 employees and 33

supervisors completed a questionnaire to evaluate Performance Appraisal (PA)

sessions. The results demonstrate supervisors perceived that they used more

participative leadership and had better conversational techniques than the

subordinates perceived. Supervisors also had a more positive perception of the

number of topics that were discussed in PA sessions.

Mabey, Christopher (2001). Conducted study of participants in a 360-degree

programme for middle and senior managers at a UK university where finding

indicates that 360 degree does have the effect of catalyzing more focused self

developmental activities and this is more favourable appraisal of development is due

to enhanced motivation and more accurate diagnosis arising.

Thurston (2001), Cook and Crossman (2004). Perception of fairness of the

performance appraisal system would influence positive affective reactions like

performance appraisal satisfaction.

Byrne and Cropanzano(2001).Distributive fairness, procedural fairness, and

interpersonal fairness are integral components of’ organizational justice, which

may be defined as the study of fairness at work.

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Crouch, & Mabogoane (2001). This provides great insights for performance

management in institutions because performance management fills the gap in the

needs to manage faculty performance and it is also used to get a basis posture for

professional development and feedback in terms of vocation performance.

Crouch, & Mabogoane (2001). Provides great insights for performance management

in institutions since, performance management fills the gap in the needs to handle

faculty performance and it is also used to get a basis posture for feedback and

professional development in terms of vocation performance.

Erdogan, Berrin (2002). Procedural, interactional, and distributive justice perceptions

are examined in terms of their theoretical and measurement properties. The proposed

model identifies several directions for future research in performance appraisal area.

Justice perceptions will be related to organization-related, leader-related, and

performance-related outcomes, through improved exchanges with the organization

and the leader, and through increased accountability pressures. Therefore,

performance appraisal is argued to be a critical incident, which shapes future

interactions between the leader and member as well as the leader and organization,

and influences future attitudes and behaviours. Differential relationships are expected

between different types of justice and outcomes, but all types of justice perceptions

are argued to be important for organizational effectiveness.

Neary, D. Bradford (2002). This study was done at TRW Inc. where approx 100000

employees were employed. The company implemented a common, online and

companywide system that supports company’s performance management system.

This system got overwhelming positive response and it was a uniform and effective

way to evaluate and develop employees.

Chen, Zhen Xiong –et al (2002). The sample was taken from six Chinese companies

to investigate the relationship between loyalty to supervisor and employee’s in role

and extra role performance in comparison with that of organizational commitment.

The result indicated that loyalty to supervisor was more strongly associated with both

in role and extra role performance than organizational commitment.

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Jude, T. Rich (2002). To avoid mismanagement of performance, there are two critical

changes required to move in performance management. The first is to avoid making

performance management once or twice a year and feedback must be on regular basis.

The second is to shift from a one size fit processes for all the employees with different

types to tailor made processes according to the nature of work.

Thach, Elizabeth C (2002). 281 executives participated in a six months coaching and

360 degree feedback process and result suggested that combination of individual

coaching and multi-rater feedback do increase leadership effectiveness, eventually

coaching and 360 degree feedback makes positive impact in terms of developing

leaders.

David P. Baker and R.Key Dismukes (2002).Explore facets of crew- performance

assessment and discuss specific strategies for training pilot instructors to accurately

assess aircrew performance.

Risher, Howard (2003). A bell-shaped curve may not be right for every employer but

it is important to recognize the star and poor performers and star performers to be

rewarded in a way that confirms their value whereas the poor performers need to

leave or improve. The performance system alone is not able to create a high-

performance organization and it needs to be seen as well as managed, as an element of

organization strategy. It is an important tool for communicating priorities and for

providing essential feedback and new expectations. Performance management must

not be handled as an HR problem.

Lawler and McDermott (2003) in their study on performance management practices

of medium and large US corporations found that PMS design related practices or

factors such as goals, business strategy driven performance, joint establishment of

performance goals, performance results, development planning and salary linkage

were highly correlated with system effectiveness.

Wingrove, Clinton (2003). New technology and processes recommend solutions for

ineffective performance management systems and for maximum impact, technology

should be designed to support the process and the process must be designed to reflect

what current technology can now support.

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Lawler, E and McDermott, M (2003). 55 HR managers from medium and large

companies participated at the University of Southern California where results strongly

argue that practices like goal setting, competency models, communication, reward

system practices, behaviour of managers and training all potentially have a positive

impact on the effectiveness of performance management system.

Groeschl, Stefan (2003). Evidence has been provided that supports the assumption

“culture is an important factor influencing the understanding and interpretation of the

performance appraisal process and its development, implementation and other

performance appraisal related characteristics”.

O’Neill, Colleen and Holsinger, Lori (2003). Mercer survey of 300 large North

American companies, it has been found that A) Organizations are better at evaluating

performance than providing ongoing feedback. B) Despite skill gaps, there are little

training given which effects the performance of employee. C) Performance

management systems are more aligned with compensation than with development. D)

Performance planning if important factor for any change or improvement in employee

as well as organization performance.

Roberts (2003). Studies have found that the supervisor’s goal setting behaviour, and

his/her relations with subordinates accounted for 53% of the variance in

appraisal satisfaction, and employees’ perception of their meaningful role in the

appraisal process enhances their satisfaction and acceptance of the system.

Lawler and McDermott (2003). In their study on performance management practices

of large and medium US companies found that PMS design related factors or

practices such as business strategy driven performance goals, performance results and

salary linkage, joint establishment of performance goals and development planning

were highly correlated with system effectiveness. In this study, they also found certain

“high impact” practices which brought about “differentiation” in performance

management process and these are: termination of lowest rated individuals, training

for appraisee, calibration meetings (that compare ratings by different managers) and

e-HR systems.

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Problems with the design or implementation of merit plans may interfere with

employees’ perceptions of either distributive equity or procedural equity (Folger &

Konovsky, 1989, Terpstra & Honoree, 2003). Perceived pay inequity may lead to

decreased motivation and performance, lower overall job satisfaction, higher

absenteeism and turnover, and more pay-related grievances and lawsuits (Milkovich

& Newman, 2005).

Paul and Anantharaman (2003).Used interviews with employees in 35 different

software companies located in India to show the positive effect of ‘people

management practices’ on organizational performance and people management

practices were defined by nine indicators, training, performance appraisal, induction,

selection, job design, work environment, compensation, career development and

incentives.

Luthans, Fred and Peterson, Suzanne J. (2003). The study suggested that when 360

degree feedback is combined with coaching, it is enhancing self awareness and

behavioural management which leads to improve self and employee attitudes and

eventually even improved performance of employee. Herein, feedback coaching

resulted in employee and manager satisfaction, intention to turnover, commitment and

lead to organization’s performance. Feedback-coaching is a winning combination to

help in competitive world economy.

Furnham, Adrian (2004). Feedback is supposed to be correcting or rewarding and its

aim is to give useful insight into work processes and outcomes. Moreover, at

workplace managers required to know not only how to score or ranking and judge, but

also how to give that information back to employees or individuals. Annual appraisal

system was not taken seriously and often not conducted at all, because since they had

little connection with rewards, pay or promotion.

London, Manuel –et al (2004). They suggested that educating employees and

managers in the context of the expected performance dimensions, can help them to

recognize desired behaviours, evaluate performance correctly and provide meaningful

feedback, as well as guide their own goal setting and performance tracking. Feedback

workshops, appraisal discussions and coaching can make easy these processes.

Performance evaluation and goal setting can be used to establish a wide range of

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developmental assignments and an ongoing program evaluation is required to identify

areas for continuous enhancement of the system.

Summers, Lynn (2005). Effective pay for performance requires that two processes,

performance management and compensation management, not only function well

separately but also operate together in an integrated way. Compensation management

cannot fully realize its potential without accurate assessments of individual

employee’s performance, assessments that properly come from a performance

management system.

Varman, Rahul (2005). Evaluation of performance appraisal system of Kashipur

textile showed that implementation of performance appraisal system in family run

business, found difficult as well as professionalize their management system. which

inculcate, lack of information for goal setting, discrepancy between self rating and

supervisor’s rating, communication barriers and the PA system was based on

personality traits.

Appelbaum, Steven H. and Jacques, Adam –et al. (2005). Conducted a survey to

measure employee satisfaction and found a correlation between job satisfactions, low

motivation and the resulting low productivity. A direct correlation was also found

between low productivity and poor communication between management, supervisors

and employees.

Waal, Andre A.De (2006). This study was conducted in an organization to know the

effect of behavioural and cultural factors on their performance management system

where it has been found that behavioural and cultural factors were having less

importance in performance management system. (Appendix-10)

Pedzani,Monyatsi and Trudie, Steyn –et al (2006). In this study,413 respondents

captured teacher perceptions of the appraisal system in secondary schools in

Botswana. In results, it appears that many teachers did indeed believe that teacher

appraisal could be beneficial in motivating them to improve their performance.

However, most teachers appeared to be either doubtful or negative about this. This is

indeed a disconcerting finding.

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Nankervis and Compton (2006). In their study, they covered 961 organizations of

Australian industry and came out with few ultimate principles of PMS. These are 1.

Strategic alignment of organizational goals and employee goals and outcomes 2. User

friendliness, consistency, equity and transparency 3. Clear links between appraisal

and salary review 4. Human resource development, coaching and succession plans.

De Nisi and Pritchard (2006) in their expectancy based motivation model for

individual performance improvement presented a number of implications for the

design of an “ideal' PMS”. This study shows that the system should be simple and

transparent so that performance ratings can be easily understood by employees and

performance standards and expectations should be clearly stated so that everyone

involved (appraisee, appraiser and HR) understands what is rewarded and what is

expected. Separate appraisals for feedback and decision making purposes would make

the process easier to understand and explain. Beyond formal appraisals (which happen

half yearly or once a year), informal appraisals and feedback must be a part of the

system.

Nankervis and Compton (2006). In this study, 961 Australian organizations were

covered and came out with few ideal principles of PMS design and implementation.

These principles are: user friendliness, strategic alignment of organizational goals and

employee goals and outcomes, clear links between appraisal and salary review,

consistency, equity and transparency, human resource development, coaching and

succession plans.

Morgan, Robert (2006). The performance management systems do hold the potential

for greatly improving the efficiency, capabilities and strategic value of compensation

and benefits professionals and their associates in human resources. To improve the

usefulness of performance management systems, the key is integrating them into a

holistic and strategic talent management system. Then human resource professionals

can influence technology to create, update, and continuously improve full-scale,

comprehensive talent management programs. (Appendix-6,7,8)

Kuvaas, Bard (2007). The study examined two different models of the relationship

between employee perceptions of developmental performance appraisal and self-

reported work performance: a mediation model and a moderation model. Results from

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a cross-sectional survey of 434 employees showed that the relationship between

perceptions of developmental performance appraisal and self-reported work

performance was mediated by employee’s intrinsic motivation, and strongly

moderated by their autonomy orientation. For employees with a weak autonomy

orientation, the relationship was positive, but for those with a strong autonomy

orientation, the relationship was negative.

Helm, Corey –et al (2007). This study conducted University of Texas, M.D.Anderson

cancer centre, Texas where results indicated that there is positive link between pay

and performance of employees as well as goal alignment plays a vital role in

performance management system.

Bhatnagar, Jyotsna (2007). The result of 272 BPO and ITES employees survey,

showed low engagement at the beginning of the career and after completion of 16

months with the organization, they showed high engagement levels and also indicated

high loyalty but only for a limited time. Organizational culture, career planning,

incentives with organizational support are three distinct factors in which the first two

were pinpointing of high attrition.

Rao, A Srinivasa (2007). Study conducted in Grasim cement industry, where it is

found that employees were aware about goal setting process and the system in general

but there was a gap in communicating with superiors. Generally, superior treat

performance appraisal process as an authority.

Memon (2007) concluded that quality of faculty is an input to institutional success

and for ensuring the quality of faculties there must be well defined performance

criteria. This study quoted educational qualification, teaching practices, nonexistence

of proper monitoring system or effective supervision as reasons of low quality of

teaching.

James R. Van Scotter and Jennifer R. Burnett. (2007). After expert ratings were

obtained, US Air Force Officers with an average of six years experience rated the

performance of four officers who delivered 6-7 minute briefings on their research

projects; 26 raters reported being acquainted with one or more of the briefers. Raters

were randomly assigned to use a rating format designed to encourage between-ratee

comparisons on each dimension or a format in which each ratee was separately rated

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on all dimensions. The results show that prior acquaintance with the ratee results in

more accurate ratings. Ratings were also more positive when raters had prior contact

with the person they rated.

Oakes, Kevin (2007). The study result shows that most of the organizations only aim

to use the performance management process for employee learning and development,

goal setting, compensation and identification of key performers.

Terpstra & Honoree (2008). Very little empirical research has been conducted

concerning the pressure of merit pay plans on faculty performance in four-year

colleges and universities. However, one recent study found that faculty perceived

their merit pay plans to have a somewhat positive effect on service levels, teaching

effectiveness, research quantity and quality. Problems with the design or

implementation of merit plans may interfere with employees’ perceptions of either

distributive equity or procedural equity (Folger & Konovsky, 1989, Terpstra &

Honoree, 2003) and perceived pay inequality can lead to decreased motivation and

performance, lower overall job satisfaction, higher absenteeism and turnover, and

more pay-related grievances and lawsuits (Milkovich & Newman, 2005).

Sanwong, K (2008). 75 employees studied at a Thai university and covered

supervisors, clients, juniors and employees wherein it has been found that the 360-

degree appraisal system is successful to evaluate employees.

Luthans, Fred –et al (2008). This study conducted to examine whether the use of

social recognition, money and feedback have a similar impact on employee

performance in the context of a modern Korean broadband internet service firm and

found that money and social recognition had a major impact on performance

outcomes but feedback did not result in as strong. When compared to the control

group then all three reward incentives showed significantly more improvement of

overall performance. Though, social recognition would have a relatively stronger

impact than money and feedback in this context was not statistically supported.

Rao, T.V (2008). Despite the fact that PMS is treated as a system it should be

recognized that it is more than a system and it is in fact the reason for the very

existence of employees and the organization. Reducing the entire year’s work of an

employee to a number is ignoring the potential of employee in building organizations.

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Performance appraisal ratings are bound to be subjective wherein they should be

treated with respect and kept at a remote. By using IT support and other technological

advancements participation, trust, and transparency can be enhanced. The time has

come when PMS can be taken out of the hands of the HR Managers and given to the

line managers, the ownership and seriousness can be shifted to line managers, and

PMS can be integrated better with work and business. However, it should not be a

full-time job, but only a part-time job so that no new power centres get developed and

HR Managers can at best be used to facilitate the developmental needs by gathering

and disseminating learning resources, learning interventions, and packages.

In 2008 a paper reports on a study that used focus group interviews with employees in

an upscale hotel in Hong Kong, a special administrative region in China, on their

views of the appraisal system that has been used. Research findings reveal that the

system could be further improved.

Bowes, Barbara (2009). “Objectives need to be cascaded throughout the organization

and clearly communicated to employees”. A performance management system is not

about trying to control employees, but rather to focus on improving overall

performance and this does not only ensure that the employee is doing the correct tasks

but also ensures that there are effective organizational supports in place to help make

it happen and management needs to ensure rewards are in tune with organizational

goals.

“A key reason that people leave their jobs is a perceived lack of company direction”.

Moideenkutty, Unnikammu (2009). The study was done to understand the

organizational citizenship behaviour and individual outcomes wherein result indicate

positive relationship between citizenship behaviours and social exchange outcomes

provided by supervisors exist. Supervisors providing social exchange outcome for

individuals.

Sharkie, Robert (2009). In this study, it has been found that vulnerability of

employees in the employment relationship has increased the importance of trust in

encouraging employee for extra role behaviour outside their contractual or legal

compulsion. Trust can make strong relationship bond which can help in increasing

employee performance.

69

Mamman, Aminu –et al (2009). In this study, secondary and primary data were

collected from two multinational organizations working in Nigeria, i.e ESN Nigeria

and KG Nigeria. The results of investigation and the review of literature shows that

the Performance Management (PM) policies are partially ethnocentric but the

practice, as perceived by some organizations, is polycentric. For instance, some

organizations perceived some degree of patronage and nepotism in the system as well

as many felt that their line managers were biased against them. Likewise, a significant

number of employees felt that their views were not taken into account during PM

review as well as they do not get any feedback from their supervisors. This shows that

local supervisors and managers adopted HRM policies anyway. Herein, also noted

that differences between policy and practice wherein lag in the implementation of the

policy. The findings that line managers do not implement PM policies as prescribed

but also that there are variations across organizations regarding the degree of

adaptation of PM practices.

Ohemeng, Frank L.K (2009). Information obtained from interviews of senior

bureaucrats and chief executive officers of state-owned enterprises (SOEs) of Ghana

and result shows, many developing countries have introduced performance

management as a means to measure individual and organizational efficiency in order

to ensure that public sector organizations meet the needs of the public. The

implementation of performance management systems in many of these countries has

been affected by a number of constraints like institutional disintegration, culture,

public apathy and leadership support, thus making it difficult for many of them to

realize the ‘benefits’ of such a system. With these constraints, performance

management no matter how attractive it may be will not achieve the desired results in

developing countries and the influence of socio-cultural norms on the bureaucratic

environment should be carefully analyzed and incorporated into the system being

developed.

Kumari, Geeta –et al (2010). This study was done on performance management

system applied in Endurance private limited, Maharashtra in India wherein most of

the employees were in the opinion that performance management system is strongly

needed and it carries a very high impact on performance of the employees. Moreover,

this system should also be continuously reviewed and if there is a need, it should be

70

changed as per the need. All the employees must have a clear vision about “what they

have to achieve” therefore proper guiding the subordinates to decide their

performance targets for the employees to work accordingly as well as supervisors

must help their subordinates to decide their performance targets.

Jie Chen, Derek Eldridge (2010). The study conducted on an MNC subsidiary located

in Southern China where it has been found that the implementation of appraisal

system was distant from attaining an optimistic effect in a Chinese business setting

like employees were nowhere near being able to be involved in setting objectives and

developmental plans. The appraisal system was not perceived be fair enough due to

the influence of seniority based rewards system and supervisors hesitated to take

ownership of performance reviews.

Liu, Xiangmin and Batt, Rosemary (2010). This multilevel study examined the role of

supervisors in improving employee performance through the use of coaching and

group management practices and result indicates that the amount of coaching that an

employee received each and every month predicted objective performance

improvements over time. Workers showed higher performance where their supervisor

emphasized group incentives and group assignments as well as wherein technology

was more automated. Eventually, the positive relationship between coaching and

performance was stronger where supervisors made greater use of group incentives and

technological changes were less frequent.

Goyal, Rita (2011). For the purpose of the study, data were collected through personal

contact of 250 employees in four branches of LIC in northern India. The result of

study revealed that difference is significant between the perception of male and

female employees regarding performance appraisal. Female employees have

favorable attitude towards performance appraisal as compared to male employees.

There is no significant difference among employees at different level regarding their

perception of performance appraisal selected branches of LIC.

Schraeder, Mike and Jordan, Mark (2011). This sets in motion the eternal need for

scholars and managers to remain cautious in understanding shifting employee needs

and dynamic organizational contingencies which have implications on the process of

managing employee performance. Practices related to managing employee

71

performance are likely to change over the time (Diana, Deadrick and Donald,

Gardner, 1997).

Omboi, Bernard Messah and Shadrack, M. Kamencu (2011). In this study population

of interest in the selected tea estates of Kenya wherein 70 respondents were selected.

The study revealed that competence, assessment and development, management by

objectives, performance based pay and employee training all affected employee

performance in Kenya tea development agency.

Reddy, Anuradha (2011). This study conducted to analyze the impact of culture and

cultural dimensions on performance management in UAE organizations. The

conclusion found that policies and procedures need to be shaped in such a way that it

comply with culture of both the countries. The most important explanatory variable is

subsidiary role and national culture of the country of origin. This carry significance as

organizational capabilities of the subsidiary companies increase, the role of subsidiary

employee in achievement of corporate objectives also increases.

Mone, Edward –et al (2011). Study conducted in a large corporation and results

indicated that performance management can play an important role for managers, as

fostering high level of employee engagement and avoiding burnout. Eventually, it is

found that performance management is a driver of employee engagement.

Chen, Tingting –et al (2011). For the study, the data were collected from 185 full time

employees in China and results revealed that developmental and evaluative

performance appraisals were linked to appraisee reactions to the workgroup in both

positive and negative sense wherein these two relationships were mediated by

perceived cooperative goals and competitive goals, respectively. Finding shows that

individual performance appraisal has both direct and indirect mediating effects on

attitudinal reactions to workgroups.

Prasetya, Arik and Kato, Masanori (2011).This survey was conducted at PT. Telkom

Kandatel Malang which is a company engaged in telecommunication services in

Indonesia. The 57 respondents in this survey are permanent employees of PT.

Telkom Kandatel Malang with working experience more than 3 years. This

study revealed that the perceptions by the employees of PT. Telkom Kandatel

Malang concluded that the majority (> 50%) already know and understand well

72

about the purpose, type, timing, methods, and related interviews conducted,

although there are some employees who have different views. Regarding the

salary system at PT. Telkom Kandatel Malang in terms of the level of justice,

competitiveness, and clarity, more than 50% of employees said fair enough, quite

competitive, and it was clear.

Shrivastava, A and Purung, P (2011). The study was done on two Indian bank where

one was government and another was private. From 340 employees data were

collected including both the banks situated in India. Result indicates that performance

appraisal system (PAS) of both the banks was significantly different where private

sector bank employees perceive performance appraisal factors, such as rater’s

confidence, goal setting, providing feedback, clarifying expectations and explaining

rating decisions to be fairer and feeling satisfaction with their PAS, as compared to

the government bank employees.

Azzone, Giovanni and Palermo, Tommaso (2011). This study was done on six Italian

central government institutions and study shows that performance appraisal and

rewards as a mechanism to provoke a shift in organizational culture and the behaviour

clearly tends to neglect the learning dimension of the change Process.

Risher, Howard (2011). This study suggested that performance management may be a

valuable tool when systems are properly designed and implemented and the key is

providing adequate preparation and support for managers.

Barani, G. and Rajesh. R (2012). This study focus on the factors influencing on the

performance of faculty members in technical education institutions in Tamilnadu and

100 respondents are selected wherein primary data is collected by using structured

questionnaire. This research work has been carried out to investigate the factors

influencing faculty performance of technical education institutions wherein personal

profile contains 81% of respondents are male, 52% of respondents are between the

age group of 23-30 years. 47% respondent’s monthly salary less than 10,000, 49% are

lecturers , 34% are UG holders, 48% belongs to engineering disciple and 48% are

having experience less than 2 years. Factor analysis extracted six factors which

influences highly on the performance of faculty members and these factors are,

personal benefits of the faculty members, job security aspects, additional

73

responsibilities, training and development, teaching aid and facilities in the college,

and work freedom in the routine work schedule. Results show that all the factors

identified by factor analysis have direct and positive impact with the factors

influencing faculty performance.

Mensah, Francis O.B –et al (2012). Data was collected from 140 both academic and

administrative employees of the institution in Ghana, who had worked in the

institution for at least two consecutive years. The result revealed a negative perception

that the employees held of the Performance Appraisal System (PAS) and also indicate

that employees of the institution perceive that the performance appraisal system of the

institution is affected by subjectivity and is influenced by some major errors where

the most common of which were the similarity and the halo effect biases. Many of the

employees viewed the system as important to both their individual career goals as

well as the objectives of the institution but there was irregular and inadequate

feedback on appraisal outcomes to all employees, except in the case of very poor

performers. Performance Appraisal (PA) was conducted only annual basis, and this

created fertile grounds for the occurrence of the recency error.

Chang, Chu-Hsiang –et al (2012). The result of analysis shows relation of Core Self

Evaluation (CSE) with a variety of outcomes which is including in-role and extra-role

job performance, job and life satisfaction and perceptions of the work environment.

The effort on CSE’s incremental discriminate and predictive validity recommends that

CSE has the potential to be an influential conceptualization of how we see ourselves.

Risher, Howard (2012). His survey revealed no evidence companies are considering

the elimination of the practice of performance management. Those who are involved

in planning or managing performance systems need to develop strategies for

addressing problems and building support as well as the audit must be part of any

action plan.

Gupta, Vishal and Kumar, Sushil (2012). The study investigated the relationship

between justice perceptions and a one dimensional conceptualization of engagement

and the relationship between justice perceptions and a three dimensional

conceptualization of engagement. Findings revealed a significant positive relationship

between distributive and informational justice dimensions and employee engagement.

74

Distributive justice and informational justice dimensions were found to have a

stronger impact on employee engagement conceptualized as antipode of burnout.

Significant relationships were found to exist between distributive and informational

performance appraisal justice dimensions and engagement, even when the measures

were used of engagement that conceptualizes it differently. Therefore, the results

provide some support for the justice engagement relationship. Employees who

perceive distributive and informational justice during performance appraisal process

are more likely to be engaged in their work and exhibit greater well-being. More

specifically, employees who perceive procedural justice during performance appraisal

session show greater interest employees who perceive distributive performance

appraisal justice exhibit greater dedication and vitality. Employees who perceive

informational justice are more physically, cognitively and behaviourally engaged in

their work. Employees who feel that they have been given fair ratings also tend to

believe that the procedures followed are fair and just.

Chompukum, Pachsiry (2012). In this study data were collected from 476 employees

in the four largest banks in Thailand. Suggested proposed model, it would be expected

that attitude towards performance evaluation would correlate with linkage between

consequences and targeted performance, coaching and perceived performance

management effectiveness.

Francis O. Boachie (2012). The study conducted on polytechnic in Takoradi, Ghana

where data was collected 140 employees of the institution, which included both

academic and administrative staff both. The study indicates that employees of the

institution perceive that the performance appraisal system of the institution is affected

by some major errors.

Akuoko, Kofi Osei (2012).For the study data were collected from 147 employees of

six financial institutions were chosen in the Kumasi Metropolis, Ghana. The study

demonstrated that the performance appraisal system can be an effective tool in

employee motivation if both the process and outcome are fair. The study also revealed

that employee participation in the appraisal process was high and this led to employee

motivation and perception of the process and outcome as fair.

75

Sahoo, Chandan K and Jena, Sambedna (2012). Performance management system

utilized by the manufacturing sectors shows that no single system is successful in

enhancing the performance of an organization and the PMS’s function has a

significant positive impact on performance of the employees when it is implemented

successfully.

Baird, Kevin –et al (2012). The survey conducted 450 Australian local governments’

employees where performance management systems of Australian local councils were

less effective in relation to the achievement of staff related outcomes and moderately

effective in relation to performance related outcomes. The results indicated a

significant relationship between the uses of multi dimensional performance measures

like training, link of performance to rewards, team work and respect for people,

outcome orientation with the effectiveness of PMS. Many other factors were found to

influence the effectiveness of performance management system for small and large

sized committees.

Singh, Anupriya (2013). This research was conducted in four Indian software services

organizations with the purpose of understanding the perceptions of HR managers

regarding design, implementation and outcomes of their organizational performance

management systems. It is gathered that the most important purpose for which PMS is

designed is “compensation and rewards” (more than 90% HR managers stated this)

and “Providing performance feedback” and “Promotion” are two other important

purposes to a great extent as identified by more than 80% HR managers. The least

popular objectives for which the PMS is perceived to be designed are: “retention or

termination”, “identification of training and development needs” and “assigning role

in a project”.

Fragouli, Evangelia E (2014). Through questionnaire, sample data collected from 30

employees of the private sector where study found that an effective management

policy of human resources and performance management could be a way to come out

from organizational crisis or at least can reduce the loss of organization’s profit. It

also revealed that human resources management policies and performance

management practices as one of the most important and evolutional managerial skills,

could be a way out of the economic crisis period.

76

Sawitri, Dyah and Muis, Mahlia (2014). Training and development function, it is a

logical application of a employee development process which is very familiar to the

performance management system and if the top management personnel in the field of

training and development has undergone significant experiences within the strategic

planning, the operational lines is often seen as a essential and important process for

employee as well as organizational development.

By reviewing of many published papers and articles of foreign and Indian authors, the

gap was found for study. There are studies conducted in the field of manufacturing,

finance, education, airline, IT etc. but it was found that no study was conducted

specifically for cement companies in India.

77

Chapter-3

78

3. Research Methodology

79

3.1 The Study

By the extensive literature review, it has been found that work on PMS is done in

many India and other countries and there is no significance work done for cement

companies in Indian context. PMS is very important factor in Human Resource

Management (HRM), which plays a key role in cement industries because often

cement industries are situated in remote areas wherein basic amenities, work

environment, work life balance, benefits etc are major concerned. The present study

will focus on factors of PMS of cement companies in Rajasthan. Wherein important

factors of PMS in cement companies will be identified by factor analysis. Then,

further these factors have any significant differences with demographic variables are

to be analysed.

3.1.1 Hypotheses

Hypotheses of study are:

1H0 : There is no significant difference of factors of PMS for gender.

1H1 : There is significant difference of factors of PMS for gender.

2H0 : There is no significant difference of factors of PMS for age.

2H1 : There is significant difference of factors of PMS for age.

3H0 : There is no significant difference of factors of PMS for education.

3H1 : There is significant difference of factors of PMS for education.

4H0 : There is no significant difference of factors of PMS for designation.

4H1 : There is significant difference of factors of PMS for designation.

5H0 : There is no significant difference of factors of PMS for year of service.

5H1 : There is significant difference of factors of PMS for year of service.

Hypotheses could have been made with all the identified factors with demographic

variables but, since factors of PMS were not identified at the time of study therefore

80

hypotheses for the study were taken in broader sense. This study can be taken further

for all the identified factors with demographic variables, as future research.

3.2 The Design

The quantitative study is done where primary data collected by administering

questionnaire from cement company’s employees of Rajasthan.

A factorial study is an experiment whose design consists of two or more factors and

each with discrete possible levels whose possible combination is made of these levels

across all such factors. These designs are called “factorial design” (William,

M.K.Trochin, 2007).

A factorial design is the most common way to study the effect of two or more

independent variables and in a factorial design, all levels of each independent variable

are combined with all levels of the other independent variables to produce all possible

conditions(William, M.K.Trochin, 2007).

A factorial design is normally used by scientists wishing to understand the effect of

two or more independent variables upon a single dependent variable.

Factorial design is a tool that is particularly useful to the marketing manager. Since

most of the elements that influence the profitability of a product cannot be physically

isolated and controlled, the influence of the many variables must be studied at one

time. This can best be accomplished by the use of factorial design (Kenneth P. Uhl,

1962).

Mainly, factorial design is a technique which permits a statistical indication of the

significance and the interaction of the various factors used in the sample experiment.

Basically, factorial design is a technique which permits a statistical indication of the

significance and the relationship (or interaction i of the various factors used in the

sample experimentation (Kenneth P. Uhl, 1962).

It is multiplicity of variables which makes it so complex to differentiate pertinent

variations. Furthermore, the amount of variance attributed to any one factor may be

quite tiny, so that in any single case it becomes merely a matter of chance. Hence,

81

factorial design can be of considerable aid therefore it enables the researcher to base

his observations on a great number of conditions and cases, with accompanying

statistical certainty, and at the same time to disentangle the complicated causal net

(Kenneth P. Uhl, 1962).

If there are two independent variables and each of which has two levels then this

would be called a (two-by-two) 2x2 factorial design. If the two factors where each

factor has three levels then it would be a 3x2 (three by two) factorial design. It is

important that the number of distinct conditions formed by combining the levels of

the independent variables is always just the product of the numbers of levels. We can

see that in a 3x2 design distinct conditions are 6 and in a 2x2 design, four distinct

conditions therefore we can easily determine the number of different combination

groups that we have in any factorial design by multiplying through the number

notation.

Herein, we have factor of PMS and demographic variables for research design. A

level is a subdivision of a factor wherein whatever factors come from the study and

the demographic variables make factorial design for the study. Here, we consider that

factors have 9 levels and demographic variables have 2 levels (i.e male and female)

then we have 2x9 factorial designs.

82

Table-5

Demographic Variables

Gender

Male Female

Factors

F1 A1 B1

F2 A2 B2

F3 A3 B3

F4 A4 B4

F5 A5 B5

F6 A6 B6

F7 A7 B7

F8 A8 B8

F9 A9 B9

83

A level is a subdivision of a factor and demographic variables make factorial design

herein factor has 9 levels and the demographic variables have 5 levels to make

factorial design for the study. Here, we can say that we have 5x9 factorial designs.

Demographic Variables

Age

19-30 31-40 41-50 51-60

61 &

above

Factors

F1 A1 B1 C1 D1 E1

F2 A2 B2 C2 D2 E2

F3 A3 B3 C3 D3 E3

F4 A4 B4 C4 D4 E4

F5 A5 B5 C5 D5 E5

F6 A6 B6 C6 D6 E6

F7 A7 B7 C7 D7 E7

F8 A8 B8 C8 D8 E8

F9 A9 B9 C9 D9 E9

Table-6

84

A level is a subdivision of a factor and demographic variables make factorial design

herein factor has 9 levels and the demographic variables have 5 levels to make

factorial design for the study. Here, we can say that we have 5x9 factorial designs.

Demographic Variables

Education

12th &

below

Diploma &

undergraduate Graduate Postgraduate Others

Factors

F1 A1 B1 C1 D1 E1

F2 A2 B2 C2 D2 E2

F3 A3 B3 C3 D3 E3

F4 A4 B4 C4 D4 E4

F5 A5 B5 C5 D5 E5

F6 A6 B6 C6 D6 E6

F7 A7 B7 C7 D7 E7

F8 A8 B8 C8 D8 E8

F9 A9 B9 C9 D9 E9

Table-7

85

A level is a subdivision of a factor and demographic variables make factorial design

herein factor has 9 levels and the demographic variables have 4 levels to make

factorial design for the study. Here, we can say that we have 4x9 factorial designs.

Demographic Variables

Designation

Sr.Officer &

below

Asst.Manager

to Sr.Manager

Asst.GM

to Sr.GM

AVP &

above

Factors

F1 A1 B1 C1 D1

F2 A2 B2 C2 D2

F3 A3 B3 C3 D3

F4 A4 B4 C4 D4

F5 A5 B5 C5 D5

F6 A6 B6 C6 D6

F7 A7 B7 C7 D7

F8 A8 B8 C8 D8

F9 A9 B9 C9 D9

Table-8

86

A level is a subdivision of a factor and demographic variables make factorial design

herein factor has 9 levels and the demographic variables have 5 levels to make

factorial design for the study. Here, we can say that we have 5x9 factorial designs.

Demographic Variables

Years of service

Upto 5

years

6 to 10

years

11 to 15

years

16 to 20

years

21 years

& above

Factors

F1 A1 B1 C1 D1 E1

F2 A2 B2 C2 D2 E2

F3 A3 B3 C3 D3 E3

F4 A4 B4 C4 D4 E4

F5 A5 B5 C5 D5 E5

F6 A6 B6 C6 D6 E6

F7 A7 B7 C7 D7 E7

F8 A8 B8 C8 D8 E8

F9 A9 B9 C9 D9 E9

Table-9

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3.3 The Sample

Final questionnaire of total 52 items was administered to cement company’s

employees of Rajasthan and got 471 responses wherein 63 responses were partially

filled therefore only 408 respondents considered. These 408 samples are taken from

the different level of management and non-management employees from major

cement companies such as ACC, Binani Cement, Shree Cement, Ambuja Cement,

JKCement, UltraTech Cement, Mangalam Cement etc. The random sampling is done

to collect the data.

88

3.4 The Tools

89

3.4.1 Data Collection

The data collection is used for study are mainly primary. The primary data are those,

which are collected afresh and for the first time, and thus happen to be original in

character.

In this study, primary data collected by administering questionnaire of 52 items to the

employees of the different cement companies in Rajasthan. To collect the data,

questionnaire was administered to all level of employees.

3.4.2 Data Analysis

The data, after collection, has processed and analyzed. The process implies editing,

coding, classification, and tabulation of collected data.

The statistical tools are applied for the study Factor analysis, ANOVA in this study.

3.4.2.1 Reliability and validity

Before administering the 52 items questionnaire, we checked reliability and validity

of questionnaire. To check the reliability, we found the Cronbach's Alpha value that

came .819 which shows that this instrument is reliable to use for the study.

90

Scale: ALL VARIABLES

Case Processing Summary

N %

Cases Valid 52 100.0

Excluded 0 .0

Total 52 100.0

a. List wise deletion based on all variables in

the procedure.

Reliability Statistics

Cronbach's Alpha N of Items

.819 52

Table-10

To check validity, pilot study is done. Initially questionnaire was made with 80 items

then it was given to all levels of 139 employees of cement industries wherein 18 items

were removed of less importance which were indicated by the respondents.

Thereafter, 62 items questionnaire was administered to the 37 judges who were expert

in this field wherein 10 items were indicated of less importance which were removed

from the questionnaire. Then in final questionnaire of total 52 items with 5 points

likert’s scale was administered and got 471 responses wherein 63 responses were

91

partially filled therefore only 408 respondents considered and tabulated their feedback

and SPSS is used for analysis of tabulated data. Factor analysis is done.

Questionnaire was administered to the 679 employees of all levels in different cement

companies in Rajasthan wherein 471 employees responded. Out of 471 responses,

only 408 responses were considered for analysis and rest omitted because these

omitted responses were not properly or partially filled.

3.4.3 Factor Analysis

Data collected from the 52 items questionnaire and tabulated for the analysis. For

analysis of data SPSS is used. We apply factor analysis to all 52 items for 408

respondents and principal component analysis method is used for extraction wherein

factors having 1 or more eigen value to be extracted. Varimax rotation method is used

to display the rotated solution. After applying, different table are found.

The KMO (Kaiser-Meyer-Olkin) is measure of sampling adequacy which varies from

0 to 1. The value closer to 1.00 is better and the value of .6 suggested the minimum.

Here we got 0.71 which suggests that our sample is adequate for factor analysis.

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The first table is communalities.

Communalities

Initial Extraction

Q1 1.000 .970

Q2 1.000 .683

Q3 1.000 .552

Q4 1.000 .656

Q5 1.000 .675

Q6 1.000 .827

Q7 1.000 .630

Q8 1.000 .818

Q9 1.000 .697

Q10 1.000 .699

Q11 1.000 .987

Q12 1.000 .922

Q13 1.000 .863

Q14 1.000 .666

Q15 1.000 .741

Q16 1.000 .719

Q17 1.000 .742

Q18 1.000 .660

Q19 1.000 .701

93

Q20 1.000 .725

Q21 1.000 .720

Q22 1.000 .987

Q23 1.000 .847

Q24 1.000 .975

Q25 1.000 .616

Q26 1.000 .971

Q27 1.000 .783

Q28 1.000 .763

Q29 1.000 .685

Q30 1.000 .974

Q31 1.000 .506

Q32 1.000 .715

Q33 1.000 .970

Q34 1.000 .910

Q35 1.000 .768

Q36 1.000 .678

Q37 1.000 .790

Q38 1.000 .771

Q39 1.000 .966

Q40 1.000 .903

Q41 1.000 .949

Q42 1.000 .790

Q43 1.000 .856

94

Q44 1.000 .954

Q45 1.000 .954

Q46 1.000 .942

Q47 1.000 .925

Q48 1.000 .921

Q49 1.000 .969

Q50 1.000 .877

Q51 1.000 .911

Q52 1.000 .969

Extraction Method: Principal Component

Analysis.

Table-11

Communalities:

Communalities table shows that how much of the variance in the variables has been

accounted for by the extracted factors. The communalities explains that what

proportion of each variable’s variance is shared with the factors which have been

created. The first column of communalities shows components or items or variables

that have been used which are 52. The second column initial, when principal

component analysis method is used then communalities initial value always comes

1.00. The third column extracted shows, how much variance each variable has in

common with the variables that we kept. In our table, for instance we find .970

extracted values in Q1 which means 97% of the variance in Q1 is accounted for and if

we see Q8 then its extracted value is .818 means 81.8% of the variance in Q8 is

accounted for. The principal component communalities (extraction, as the initial are

always 1.00) ranging from .506 to .987, thus most of the variance of these variables is

accounted for by these factor solution.

95

If a variable does not share much variance with the other variables or with the

retained factors or variables (i.e very less extracted value) then it is unlikely to be

useful in defining a factor.

In our communalities table, we have high variance of each variable therefore we take

all the listed items.

Total Variance Explained

Component

Initial Eigen values Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings

Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

% Total

% of

Variance

Cumulative

%

1 13.887 26.705 26.705 13.887 26.705 26.705 12.664 24.355 24.355

2 11.019 21.191 47.896 11.019 21.191 47.896 6.823 13.121 37.475

3 5.744 11.047 58.943 5.744 11.047 58.943 5.928 11.399 48.875

4 3.910 7.518 66.462 3.910 7.518 66.462 5.066 9.742 58.616

5 2.675 5.145 71.607 2.675 5.145 71.607 3.702 7.120 65.736

6 1.471 2.829 74.435 1.471 2.829 74.435 3.680 7.076 72.812

7 1.328 2.554 76.989 1.328 2.554 76.989 1.586 3.049 75.862

8 1.135 2.182 79.171 1.135 2.182 79.171 1.429 2.749 78.611

9 1.079 2.074 81.246 1.079 2.074 81.246 1.370 2.635 81.246

10 .946 1.819 83.064

11 .858 1.650 84.715

12 .763 1.467 86.182

13 .673 1.295 87.476

14 .638 1.227 88.704

15 .596 1.146 89.849

16 .584 1.124 90.973

17 .534 1.028 92.001

18 .469 .903 92.904

19 .413 .794 93.698

20 .392 .753 94.451

21 .362 .696 95.147

22 .341 .655 95.802

23 .323 .621 96.423

24 .270 .519 96.942

25 .262 .503 97.445

96

26 .252 .485 97.930

27 .216 .416 98.346

28 .183 .351 98.697

29 .122 .235 98.932

30 .102 .196 99.128

31 .097 .187 99.315

32 .073 .140 99.456

33 .068 .131 99.586

34 .056 .108 99.694

35 .042 .080 99.774

36 .035 .067 99.841

37 .030 .057 99.898

38 .024 .047 99.945

39 .018 .035 99.981

40 .006 .012 99.993

41 .004 .007 100.000

42 1.016E-14 1.954E-14 100.000

43 5.794E-15 1.114E-14 100.000

44 1.844E-15 3.546E-15 100.000

45 4.332E-16 8.330E-16 100.000

46 2.730E-16 5.250E-16 100.000

47 1.426E-17 2.742E-17 100.000

48 -3.233E-18 -6.217E-18 100.000

49 -2.449E-16 -4.709E-16 100.000

50 -1.241E-15 -2.386E-15 100.000

51 -2.265E-15 -4.356E-15 100.000

52 -6.832E-15 -1.314E-14 100.000

Extraction Method: Principal Component analysis.

Table-12

97

Total Variance Explained:

Total variance explained is the total amount of variability of the original variables

explained by each factor solution. In the table of total variance explained, the first

column is component or items or variables which are used for study.

“Eigen values are the variances of the factor”

The Eigen value allows us to know how much variation each factor or component can

explain. When factor analysis is performed then how many factors to settle on is

decided according to the Eigen value

Next column is initial Eigen values, eigenvalues are the variance of the factor or

variables and the total variance is equal to the number of variables used in the analysis

which is 52 i.e the total of all eigenvalues will be the total number of factors or

variables herein the total number of variables are 52.

In the first column, the first factor will always account for the most variance (highest

Eigenvalue 13.887) and next factor will account for as much of the left over variance

as it can and so on. Hence, each successive factor or variable is accounting for less

and less variance.

In an analysis of 52 items, the initial eigenvalues show that for each of those 52

factors, how much of the variance in the 52 variables was captured by that factor.

Here would be 52 units and each factor’s Eigenvalue corresponds with some portion

of those items. If we see, the first Eigen value is 13.887 which accounts for 26.70%

(i.e 13.887/ 52) of the total items and next Eigen value is 11.019 which accounts for

21.19% (i.e 11.019/ 52) and so on.

The Eigen value rule (Kaiser,1960) asserts that factors with Eigen values less than

1.00 should not be retained therefore in this analysis, we consider the factors which

has Eigen values 1.00 or higher. The factors only be extracted when they have 1 or

more than 1 Eigen value herein 9 factors are having more than 1.00 Eigen value

therefore only 9 factors extracted and rest were omitted. This is because a factor with

Eigen value of 1 account for as much variance as a single variable or factor and that is

why only factors that explain at least the same amount of variance as a single variable

98

is worth keeping and the factors that explain the least amount of variance are

generally discarded.

The eigenvalues from 13.887 to 1.079 are considered wherein rest all values are less

than therefore these values are being omitted.

% of variance: This contains the % of total variance accounted for by each factor

here in the first value is 26.705 which means 26.205% variance is explained by this

factor. The first factor accounts for 26.205% of the variance and the second 21.191%

and so on till 2.074%, rest all remaining factors are not significant.

Cumulative %:

This column contains the cumulative % of variance accounted for by the current and

all preceding factors. Herein if we see third row which shows a value of 58.943%, it

means that the first three factors together account for 58.943% of the total variance.

Likewise, ninth row shows value 81.246% , means the all nine factors together

account for 81.246% of the total variance.

99

Rotated Component Matrixa

Component

1 2 3 4 5 6 7 8 9

Q1 .341 -.274 .008 .051 -.102 .881 .000 .048 -.076

Q2 .079 .308 .334 .127 .011 .877 .128 .162 .125

Q3 .301 .230 .061 .024 .018 .360 .875 .014 -.023

Q4 .023 .266 -.428 -.311 .175 -.117 .899 .019 .031

Q5 .402 -.036 -.064 -.064 -.019 -.116 .209 -.066 .834

Q6 .128 .098 -.233 .042 -.010 .100 -.069 .837 .031

Q7 -.248 .221 -.108 .087 -.095 -.330 .370 .801 -.333

Q8 .291 .107 .406 .256 -.088 .351 .059 .781 .075

Q9 .180 .410 -.026 .130 -.029 .079 -.079 -.029 .875

Q10 -.318 .323 .060 -.007 -.034 .821 .087 .003 -.052

Q11 .165 .073 -.164 .022 .017 .796 -.117 .009 .029

Q12 -.244 .406 .323 .381 -.133 .782 -.017 .011 .032

Q13 .219 .150 -.022 .153 .050 .395 .017 -.368 .922

100

Q14 .087 .339 -.286 -.191 .103 -.144 -.089 -.088 .934

Q15 .166 .209 -.339 .033 .045 .332 -.064 .717 .083

Q16 .416 .120 .034 .261 -.042 .401 .129 .918 .065

Q17 .147 .049 .316 -.060 .033 -.093 -.055 .886 .022

Q18 -.231 -.176 .284 -.150 -.012 .116 .053 .871 -.174

Q19 -.032 -.234 .375 .128 -.081 .086 .989 -.107 -.013

Q20 -.051 -.082 .017 .008 -.069 .776 .132 .021 .267

Q21 .111 .034 .047 .054 -.014 .771 .210 -.050 .085

Q22 -.265 -.103 .164 .242 .811 -.058 .117 -.009 -.029

Q23 .183 -.187 .323 .430 .808 .423 .036 .020 -.040

Q24 -.190 .192 -.274 -.233 .787 -.053 .030 -.031 .017

Q25 -.260 -.107 .321 -.045 .741 -.072 -.038 -.203 -.123

Q26 .274 .235 .272 .852 .317 .024 -.030 -.030 .080

Q27 .450 -.005 .417 .822 .208 .123 .020 -.030 .037

Q28 .197 -.453 .272 .277 .915 .149 .092 -.023 -.031

Q29 .367 .103 .103 .216 .908 .090 .011 .137 -.154

101

Q30 .928 .151 -.133 -.374 .136 .400 -.141 .013 -.012

Q31 .814 .110 -.293 -.226 .099 .079 .097 .237 .065

Q32 -.217 -.054 .398 .209 .044 .224 .178 .976 .101

Q33 .028 .888 .008 .051 -.102 .128 .000 .048 -.076

Q34 -.050 .873 -.209 -.143 .002 .096 -.070 -.092 .186

Q35 -.337 .856 .166 .058 -.045 .280 .062 .096 -.031

Q36 .368 .088 -.251 .982 .043 .305 -.249 .075 .074

Q37 .169 -.076 -.127 .789 .013 .404 -.404 .076 .049

Q38 -.149 .020 .940 .166 .017 .006 .075 -.071 -.333

Q39 .856 .117 -.119 -.331 .138 -.426 .209 .027 -.003

Q40 .799 -.350 .433 .211 -.127 .015 .100 .055 -.038

Q41 .407 -.238 .115 .100 -.271 .824 -.068 .440 .048

Q42 -.320 .294 .974 -.162 -.381 .356 -.131 .218 -.054

Q43 -.196 -.012 .879 -.280 .274 -.421 .165 .382 .074

Q44 -.364 -.021 .833 .237 -.258 .012 .108 .401 -.112

Q45 -.364 .998 .400 .147 -.258 .012 .108 .337 -.112

102

Q46 .078 .927 -.155 .010 .134 -.019 -.080 .322 .024

Q47 -.204 .918 .091 .289 .348 .001 .194 .181 -.116

Q48 .103 .850 -.195 -.104 .180 -.020 -.107 .227 .041

Q49 -.259 .898 -.313 -.254 -.137 -.003 .049 .164 .437

Q50 .150 .831 .112 .345 .200 -.435 .114 .085 .075

Q51 -.291 .729 .091 .220 .430 .003 .212 .349 .320

Q52 .722 .160 -.313 -.154 -.137 -.003 .049 .164 .034

Extraction Method: Principal Component

Analysis.

Rotation Method: Varimax with Kaiser

Normalization.

Table-13

103

Rotated component matrix:

In the principal component analysis output, the rotated component matrix gives the

rotated factor loadings, which represent both how the variables are weighted for each

factor and correlation of each variable with each factor. The extraction method will

produce factor loadings for every item on every extracted factor. Rotation is a way of

maximizing high loadings and minimizing low loadings so that the simplest possible

structure is achieved therefore this is considered to take factor loadings instead of

component matrix. Herein we have rotated component matrix which explains that 9

components extracted have factor loadings in each components. The relationship of

each variable to the underlying factor is expressed by the so called factor loading. As

high factor loading, shows factor association is strongest with the variable. If we see

sixth component, the factor loading of Q1 is .881 which means variable has a

correlation of 0.88 with factor and this would be considered as a strong association.

We considered factor loading which is more than 0.5 and rest omitted.

In first component, we find Q30, Q31, Q39, Q40, Q52 are having .928, .814,

.856,.799,.722 high factor loadings and rest values are having low factor loading

which can be suppressed. These 5 variables Q30, Q31, Q39, Q40, Q52 represent one

factor which can be expressed by one name.

Likewise, in second component we find Q33, Q34, Q35, Q45, Q46, Q47, Q48, Q49,

Q50, Q51 are having .888, .873, .856, .998, .927, .918, .850 .898, .831, .729 high

factor loadings these 9 variables will be represented by one factor.

Likewise, in third component we find from Q38, Q42, Q43, Q44 are having 940, .974,

.879, .833 high factor loadings these 4 variables will be represented by one factor.

Likewise, in forth component we find from Q26, Q27, Q36, Q37 are having .852,

.822, .982, .789 high factor loadings these 4 variables will be represented by one

factor.

104

Likewise, in fifth component we find from Q22, Q23, Q24, Q25, Q28, Q29 are having

.811, .808, .787, .741, .915, .908 high factor loadings these 6 variables will be

represented by one factor.

Likewise, in sixth component we find from Q1, Q2, Q10, Q11, Q12, Q20, Q21, Q41

are having .881, .877, .821, .796, .782, .776, .771, .824 high factor loadings these 8

variables will be represented by one factor.

Likewise, in seventh component we find from Q3, Q4, Q19 are having .875, .899,

.989 high factor loadings these 3 variables will be represented by one factor.

Likewise, in eighth component we find from Q6, Q7, Q8, Q15, Q16, Q17, Q18, Q32

are having .837, .801, .781, .717, .918, .886, .871, .976, high factor loadings these 8

variables will be represented by one factor.

Likewise, in ninth component we find from Q5, Q9, Q13, Q14 are having .834, .875,

.922, .934 high factor loadings these 4 variables will be represented by one factor.

Herein 52 items are reduced and came as 9 factors.

ANOVA

We have taken level of significance α = 0.05 and p is the significance value. If p ≤ α

then null hypothesis to be rejected and if p > α the null hypothesis to be accepted.

To analyze the data, first we compute the means of group and then run the ANOVA

because there are 3 or more groups. To run ANOVA, we assume that each group is

approximately normal and the population is normally distributed. ANOVA is used by

comparing means to determine if the means are statistically different.

We run one way ANOVA in SPSS with factors and demographic variables. In

analysis table, the significance value help to determine if condition means were

105

relatively the same of if they were significantly different from one another. If sig.

value is greater than 0.05 then there is no statistically significant difference and if sig.

value is less than 0.05 then there is a statistically significant in the means.

In ANOVA result table, F values in the column shows ratio of two mean square

values. Whenever null hypothesis is true, F value is expected to have a value close to

1.00 most of the time and if a large F ratio means that the variation among group

means is more i.e a large value of F indicates relatively more difference between

groups than within groups.

106

Mean

Gender

Male Female

Mean Mean

Goal 3.45 3.50

Career planning 2.55 2.62

Compensation 2.92 3.03

Role 3.35 3.47

Review 3.13 3.19

Feedback

Reward

Benefits

Work freedom

2.54

2.31

2.61

2.90

2.47

2.37

2.54

2.81

Table-14

107

One way ANOVA

Sum of Squares df Mean Square F Sig.

Goal Between Groups .038 1 .038 1.044 .307

Within Groups 14.892 406 .037

Total 14.930 407

Career planning Between Groups .078 1 .078 1.995 .159

Within Groups 15.920 406 .039

Total 15.998 407

Compensation Between Groups .186 1 .186 1.938 .165

Within Groups

Total

39.029

39.216

406

407

.096

Role Between Groups .273 1 .273 3.716 .055

Within Groups 29.880 406 .074

Total 30.154 407

Review Between Groups .062 1 .062 1.186 .277

108

Within Groups 21.185 406 .052

Total 21.247 407

Feedback Between Groups .095 1 .095 2.187 .140

Within Groups 17.560 406 .043

Total 17.654 407

Reward Between Groups .054 1 .054 1.123 .290

Within Groups 19.393 406 .048

Total 19.447 407

Benefits Between Groups

Within Groups

Total

.075

7.821

7.896

1

406

407

.075

.019

3.894

.049

Work freedom Between Groups .143 1 .143 1.819 .178

Within Groups 31.978 406 .079

Total 32.121 407

Table-15

109

A one way ANOVA is conducted to compare the effect of factors on gender wherein

result shows

1. In benefits row the p value is 0.049 which is less than 0.05 and the F value is

3.894. It means that there is statistically significant difference in means. In this

case null hypothesis is rejected and alternative hypothesis is accepted.

2. If we see other factors such as goal, career planning, compensation, role of

supervisor, performance review, feedback, reward and recognition and work

freedom, these p values are greater than 0.05 and their most of them F values

are approximately near to the 1.00. It means that there is no statistically

significant difference in means therefore in this case null hypothesis is

accepted and alternative hypothesis is rejected.

110

Mean

Age

19-30 31-40 41-50 51-60 61+

Mean Mean Mean Mean Mean

Goal 3.47 3.42 3.49 3.43 3.50

Career planning 2.54 2.52 2.60 2.58 2.75

Compensation 2.95 2.86 2.96 2.94 3.00

Role 3.36 3.34 3.33 3.37 3.38

Review 3.12 3.10 3.17 3.16 3.25

Feedback 2.53 2.53 2.56 2.51 2.78

Reward 2.31 2.32 2.28 2.36 2.17

Benefits 2.61 2.60 2.57 2.62 2.62

Work freedom 2.90 2.92 2.86 2.86 2.75

Table-16

111

One Way ANOVA

Sum of Squares df Mean Square F Sig.

Goal Between Groups .267 4 .067 1.835 .121

Within Groups 14.663 403 .036

Total 14.930 407

Career planning Between Groups .438 4 .110 2.837 .024

Within Groups 15.560 403 .039

Total 15.998 407

Compensation Between Groups .654 4 .163 1.708 .147

Within Groups 38.562 403 .096

Total 39.216 407

Role Between Groups .049 4 .012 .165 .956

Within Groups 30.104 403 .075

Total 30.154 407

Review Between Groups .295 4 .074 1.416 .228

112

Within Groups 20.952 403 .052

Total 21.247 407

Feedback Between Groups .322 4 .080 1.871 .115

Within Groups 17.332 403 .043

Total 17.654 407

Reward Between Groups .235 4 .059 1.234 .296

Within Groups 19.211 403 .048

Total 19.447 407

Benefits Between Groups .089 4 .022 1.144 .336

Within Groups 7.807 403 .019

Total 7.896 407

Work freedom Between Groups .290 4 .072 .917 .454

Within Groups 31.832 403 .079

Total 32.121 407

Table-17

113

A one way ANOVA is conducted to compare the effect of factors on age wherein

result shows

1 In career planning row the p value is 0.024 which is less than 0.05 and the F

value is 2.837. It means that there is statistically significant difference in

means. In this case null hypothesis is rejected and alternative hypothesis is

accepted.

2 If we see other factors such as goal, compensation, role of supervisor,

performance review, feedback, reward and recognition, benefits and work

freedom, these p values are greater than 0.05 and their most of them F values

are approximately near to the 1.00. It means that there is no statistically

significant difference in means therefore in this case null hypothesis is

accepted and alternative hypothesis is rejected.

114

Mean

Education

12th and below

Diploma &

undergraduate Graduate Postgraduate Others

Mean Mean Mean Mean Mean

Goal 3.42 3.44 3.46 3.48 3.44

Career planning

Compensation

Role

Review

Feedback

Reward

Benefits

Work freedom

2.52

2.94

3.38

3.09

2.56

2.33

2.56

2.94

2.57

2.93

3.40

3.13

2.54

2.30

2.61

2.88

2.55

2.93

3.33

3.13

2.52

2.33

2.61

2.88

2.55

2.90

3.37

3.13

2.55

2.28

2.62

2.91

2.60

3.05

3.05

3.07

2.58

2.40

2.40

2.90

Table-18

115

One way ANOVA

Sum of Squares df Mean Square F Sig.

Goal Between Groups .113 4 .028 .772 .544

Within Groups 14.817 403 .037

Total 14.930 407

Career planning Between Groups .108 4 .027 .684 .603

Within Groups

Total

15.890

15.998

403

407

.039

Compensation Between Groups .142 4 .035 .366 .833

Within Groups 39.074 403 .097

Total 39.216 407

Role Between Groups .820 4 .205 2.817 .025

Within Groups 29.334 403 .073

Total 30.154 407

Review Between Groups .081 4 .020 .384 .820

116

Within Groups

Total

21.166

21.247

403

407

.053

Feedback Between Groups .111 4 .028 .637 .636

Within Groups 17.543 403 .044

Total 17.654 407

Reward Between Groups

Within Groups

Total

.209

19.238

19.447

4

403

407

.052

.048

1.094

.359

Benefits Between Groups .335 4 .084 4.459 .002

Within Groups 7.561 403 .019

Total 7.896 407

Work freedom Between Groups .127 4 .032 .399 .809

Within Groups 31.994 403 .079

Total 32.121 407

Table-19

117

A one way ANOVA is conducted to compare the effect of factors on education

wherein result shows

1 In role of supervisor row the p value is 0.025 and F value is 2.817, in benefits

row the p value is 0.002 and F value is 4.459 herein all p values are less than

0.05. It means that there is statistically significant difference in means. In this

case null hypothesis is rejected and alternative hypothesis is accepted.

2 If we see other factors such as goal, compensation, career planning,

performance review, feedback, reward and recognition and work freedom,

these p values are greater than 0.05 and their most of them F values are

approximately near to the 1.00. It means that there is no statistically significant

difference in means therefore in this case null hypothesis is accepted and

alternative hypothesis is rejected.

118

Mean

Designation

Sr.officer & below

Asst.Manager to

Sr.Manager Asst.GM to Sr.GM AVP & above

Mean Mean Mean Mean

Goal 3.46 3.44 3.46 3.42

Career planning 2.57 2.53 2.53 2.66

Compensation 2.96 2.88 2.93 3.14

Role 3.36 3.35 3.30 3.43

Review 3.13 3.13 3.08 3.23

Feedback 2.55 2.52 2.56 2.40

Reward 2.30 2.33 2.32 2.39

Benefits 2.59 2.61 2.62 2.62

Work freedom 2.88 2.89 2.94 2.80

Table-20

119

One way ANOVA

Sum of Squares df Mean Square F Sig.

Goal Between Groups .054 3 .018 .491 .689

Within Groups 14.876 404 .037

Total 14.930 407

Career planning Between Groups .357 3 .119 3.072 .028

Within Groups 15.641 404 .039

Total 15.998 407

Compensation Between Groups 1.077 3 .359 3.803 .010

Within Groups 38.139 404 .094

Total 39.216 407

Role Between Groups .212 3 .071 .953 .415

Within Groups 29.942 404 .074

Total 30.154 407

Review Between Groups .225 3 .075 1.444 .230

120

Within Groups 21.021 404 .052

Total 21.247 407

Feedback Between Groups .369 3 .123 2.879 .036

Within Groups 17.285 404 .043

Total 17.654 407

Reward Between Groups .188 3 .063 1.318 .268

Within Groups 19.258 404 .048

Total 19.447 407

Benefits Between Groups .047 3 .016 .802 .493

Within Groups 7.849 404 .019

Total 7.896 407

Work freedom Between Groups .237 3 .079 1.002 .392

Within Groups 31.884 404 .079

Total 32.121 407

Table-21

121

A one way ANOVA is conducted to compare the effect of factors on designation

wherein result shows

1 In career planning row the p value is 0.028 and F value is 3.072, in

compensation row the p value is 0.010 and F value is 3.803, in feedback row

the p value is 0.036 and F value is 2.879 herein all p values are less than 0.05.

It means that there is statistically significant difference in means. In this case

null hypothesis is rejected and alternative hypothesis is accepted.

2 If we see other factors such as goal, performance review, role of supervisor,

reward and recognition, benefits and work freedom, these p values are greater

than 0.05 and their most of them F values are approximately near to the 1.00.

It means that there is no statistically significant difference in means therefore

in this case null hypothesis is accepted and alternative hypothesis is rejected.

122

Mean

Years of service

Upto 5 6 to 10 11 to 15 16 to 20 21 and above

Mean Mean Mean Mean Mean

Goal 3.45 3.46 3.46 3.41 3.46

Career planning 2.52 2.58 2.57 2.56 2.43

Compensation 2.92 2.92 2.97 2.97 2.71

Role 3.37 3.34 3.34 3.38 3.18

Review 3.11 3.14 3.13 3.17 3.07

Feedback 2.54 2.54 2.53 2.54 2.55

Reward 2.33 2.31 2.32 2.33 2.24

Benefits 2.61 2.59 2.60 2.62 2.61

Work freedom 2.93 2.86 2.90 2.87 2.93

Table-22

123

One way ANOVA

Sum of Squares df

Mean

Square F Sig.

Goal Between Groups .064 4 .016 .437 .782

Within Groups 14.866 403 .037

Total 14.930 407

Career planning Between Groups .344 4 .086 2.214 .067

Within Groups 15.654 403 .039

Total 15.998 407

Compensation Between Groups .532 4 .133 1.385 .238

Within Groups 38.684 403 .096

Total 39.216 407

Role Between Groups .342 4 .085 1.155 .330

Within Groups 29.812 403 .074

Total 30.154 407

Review Between Groups .100 4 .025 .476 .753

124

Within Groups 21.147 403 .052

Total 21.247 407

Feedback Between Groups .003 4 .001 .016 .999

Within Groups 17.651 403 .044

Total 17.654 407

Reward Between Groups .069 4 .017 .358 .838

Within Groups 19.378 403 .048

Total 19.447 407

Benefits Between Groups .050 4 .012 .639 .635

Within Groups 7.846 403 .019

Total 7.896 407

Work freedom Between Groups .340 4 .085 1.077 .367

Within Groups 31.781 403 .079

Total 32.121 407

Table-23

125

A one way ANOVA is conducted to compare the effect of factors on years of service

wherein result shows

1 If we see all factors such as goal, career planning, performance review,

compensation, role of supervisor, reward and recognition, feedback, benefits

and work freedom, these p values are greater than 0.05 and their most of them

F values are approximately near to the 1.00 or less. It means that there is no

statistically significant difference in means therefore in this case null

hypothesis is accepted and alternative hypothesis is rejected.

126

Chapter-4

127

4. Results and Discussions

128

To collect data from the employees of cement companies, one measurement

instrument is prepared. Reliability of measurement tool signifies the consistency. To

check the reliability of this instrument, SPSS is used to find out the cronbach’s alpha

which confirms the reliability of scale. Cronbach’s alpha value is measured which

was 0.819 therefore instrument was reliable for collecting data and study.

Quantitative study pertaining to performance management system of cement

companies is done wherein important factors have been identified. Data analysis is the

process of analyze data wherein data collected from 408 respondents from various

level of cement companies in Rajasthan is analyzed with the help of SPSS.

Initially, the data analysis inculcates factor analysis then ANOVA is used. Factor

analysis is used to reduce the total items and identify main factors i.e it reduces large

number of variables in less number of main factors. This factor analysis is performed

on the basis of principal component analysis and varimax rotation. While performing

factor analysis, it was decided to have extracted factors those who are having Eigen

value 1 or more than 1.

Factor analysis gives different tables of result.

The first table is communalities.

Communalities: Communalities table shows that how much of the variance in the

variables has been accounted for by the extracted factors.

The principal component communalities (extraction, as the initial are always 1.00)

ranging from .506 to .987, thus most of the variance of these variables is accounted

for by these factor solution.

If a variable does not share much variance with the other variables or with the

retained factors or variables (i.e very less extracted value) then it is unlikely to be

useful in defining a factor.

In our communalities table, high variance of each variable therefore we took all the

listed items for study.

129

Total Variance Explained:

Total variance explained is the total amount of variability of the original variables

explained by each factor solution. In the table of total variance explained, the first

column is component or items or variables which are used for study.

In an analysis of 52 items, the initial Eigenvalues show that for each of those 52

factors, how much of the variance in the 52 variables was captured by that factor.

Here would be 52 units and each factor’s Eigenvalue corresponds with some portion

of those items. If we see, the first Eigen value is 13.887 which accounts for 26.70%

(i.e 13.887/ 52) of the total items and next Eigen value is 11.019 which accounts for

21.19% (i.e 11.019/ 52) and so on.

we consider the factors which has Eigen values 1.00 or higher. The factors only be

extracted when they have 1 or more than 1 Eigen value herein 9 factors are having

more than 1.00 Eigen value therefore only 9 factors extracted and rest were omitted.

This is because a factor with Eigen value of 1 account for as much variance as a

single variable or factor and that is why only factors that explain at least the same

amount of variance as a single variable is worth keeping and the factors that explain

the least amount of variance are generally discarded.

The eigenvalues from 13.887 to 1.079 are considered wherein rest all values are less

than therefore these values are being omitted.

Rotated component matrix:

In the principal component analysis output, the rotated component matrix gives the

rotated factor loadings, which represent both how the variables are weighted for each

factor and correlation of each variable with each factor. The extraction method

produced factor loadings for every item on every extracted factor.

Herein we have rotated component matrix which explains that 9 components

extracted have factor loadings in each components. As high factor loading, shows

factor association is strongest with the variable. The factor has low factor loading i.e

less than 0.5 was not taken.

In first component, we find Q30, Q31, Q39, Q40, Q52 are having .928, .814,

.856,.799,.722 high factor loadings and rest values are having low factor loading

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which can be suppressed. These 5 variables Q30, Q31, Q39, Q40, and Q52 represent

one factor which can be expressed by one named factor. This is named “Goal

Setting”.

Likewise, in second component we find Q33, Q34, Q35, Q45, Q46, Q47, Q48, Q49,

Q50, Q51 are having .888, .873, .856, .998, .927, .918, .850 .898, .831, .729 high

factor loadings these 9 variables represent one factor which is expressed by one

named factor called “Career planning and appraisal system”.

Likewise, in third component we find from Q38, Q42, Q43, Q44 are having 940, .974,

.879, .833 high factor loadings these 4 variables represent one factor which is

expressed by one named factor called “Compensation”.

Likewise, in forth component we find from Q26, Q27, Q36, Q37 are having .852,

.822, .982, .789 high factor loadings these 4 variables represent one factor which is

expressed by one named factor called “Role of supervisor”.

Likewise, in fifth component we find from Q22, Q23, Q24, Q25, Q28, Q29 are having

.811, .808, .787, .741, .915, .908 high factor loadings these 6 variables represent one

factor which is expressed by one named factor called “Performance review”.

Likewise, in sixth component we find from Q1, Q2, Q10, Q11, Q12, Q20, Q21, Q41

are having .881, .877, .821, .796, .782, .776, .771, .824 high factor loadings these 8

variables represent one factor which is expressed by one named factor called

“Learning and feedback”.

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Likewise, in seventh component we find from Q3, Q4, Q19 are having .875, .899,

.989 high factor loadings these 3 variables represent one factor which is expressed by

one named factor called “Reward and recognition”.

Likewise, in eighth component we find from Q6, Q7, Q8, Q15, Q16, Q17, Q18, Q32

are having .837, .801, .781, .717, .918, .886, .871, .976, high factor loadings these 8

variables represent one factor which is expressed by one named factor called

“Personal benefits”.

Likewise, in ninth component we find from Q5, Q9, Q13, Q14 are having .834, .875,

.922, .934 high factor loadings these 4 variables represent one factor which is

expressed by one named factor called “Work freedom”.

Herein 52 items are reduced and came as 9 factors.

Final Result : These core 9 factors Goal setting, career planning and appraisal

system, compensation, role of supervisor, performance review, learning and feedback,

reward and recognition, personal benefits and work freedom are identified by doing

this study that they are highly important for the cement companies.

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ANOVA

To check our hypotheses, we run ANOVA that which of the hypotheses are true. We

have taken level of significance α = 0.05 and p is the significance value. If p ≤ α then

null hypothesis to be rejected and if p > α the null hypothesis to be accepted.

We run one way ANOVA in SPSS with factors and demographic variables. In

analysis table, the significance value help to determine if condition means were

relatively the same of if they were significantly different from one another. If sig.

value is greater than 0.05 then there is no statistically significant difference and if sig.

value is less than 0.05 then there is a statistically significant in the means.

In ANOVA result table, F values in the column shows ratio of two mean square

values. Whenever null hypothesis is true, F value is expected to have a value close to

1.00 most of the time and if a large F ratio means that the variation among group

means is more i.e a large value of F indicates relatively more difference between

groups than within groups.

A one way ANOVA is conducted to compare the effect of factors on gender wherein

result shows

1 In personal benefits row the p value is 0.049 which is less than 0.05 and the F

value is 3.894. It means that there is statistically significant difference in

means. In this case null hypothesis is rejected and alternative hypothesis is

accepted.

2 If we see other factors such as goal, career planning, compensation, role of

supervisor, performance review, feedback, reward and recognition and work

freedom, these p values are greater than 0.05 and their most of them F values

are approximately near to the 1.00. It means that there is no statistically

significant difference in means therefore in this case null hypothesis is

accepted and alternative hypothesis is rejected.

For personal benefit factor p value is less than 0.05 therefore null hypothesis is

rejected and alternative hypothesis is accepted but rest of these factors we

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have p value is more than .05 herein the null hypothesis is accepted and

alternate hypothesis is rejected. Eventually, for personal benefit factor gender

has significant difference whereas rest factors do not have any significant

difference for gender. Except personal benefit factor, factors of PMS have

same significance for any of the gender i.e either male or female, they have

same significance.

A one way ANOVA is conducted to compare the effect of factors on age wherein

result shows

1. In career planning row the p value is 0.024 which is less than 0.05 and the F

value is 2.837. It means that there is statistically significant difference in

means. In this case null hypothesis is rejected and alternative hypothesis is

accepted.

2. If we see other factors such as goal, compensation, role of supervisor,

performance review, feedback, reward and recognition, personal benefits and

work freedom, these p values are greater than 0.05 and their most of them F

values are approximately near to the 1.00. It means that there is no statistically

significant difference in means therefore in this case null hypothesis is

accepted and alternative hypothesis is rejected.

For career planning factor p value is less than 0.05 therefore null hypothesis is

rejected and alternative hypothesis is accepted but rest of these factors we

have p value is more than .05 herein the null hypothesis is accepted and

alternate hypothesis is rejected. Eventually, for career planning factor age has

significant difference whereas rest factors do not have any significant

difference for age. Except career planning factor, factors of PMS have same

significance for any of the age i.e for any age, they have same significance.

A one way ANOVA is conducted to compare the effect of factors on education

wherein result shows

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1 In role of supervisor row the p value is 0.025 and F value is 2.817, in personal

benefits row the p value is 0.002 and F value is 4.459 herein all p values are

less than 0.05. It means that there is statistically significant difference in

means. In this case null hypothesis is rejected and alternative hypothesis is

accepted.

2 If we see other factors such as goal, compensation, career planning,

performance review, feedback, reward and recognition and work freedom,

these p values are greater than 0.05 and their most of them F values are

approximately near to the 1.00. It means that there is no statistically significant

difference in means therefore in this case null hypothesis is accepted and

alternative hypothesis is rejected.

For role of supervisor and personal benefits factors p value is less than 0.05

therefore null hypothesis is rejected and alternative hypothesis is accepted but

rest of these factors we have p value is more than .05 herein the null

hypothesis is accepted and alternate hypothesis is rejected. Eventually, for role

of supervisor and personal benefits factors, education has significant

difference whereas rest factors do not have any significant difference for

education. Except role of supervisor and personal benefits factors, factors of

PMS have same significance for any of the education i.e for any education,

they have same significance.

A one way ANOVA is conducted to compare the effect of factors on designation

wherein result shows

1 In career planning row the p value is 0.028 and F value is 3.072, in

compensation row the p value is 0.010 and F value is 3.803, in feedback row

the p value is 0.036 and F value is 2.879 herein all p values are less than 0.05.

It means that there is statistically significant difference in means. In this case

null hypothesis is rejected and alternative hypothesis is accepted.

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2 If we see other factors such as goal, performance review, role of supervisor,

reward and recognition, benefits and work freedom, these p values are greater

than 0.05 and their most of them F values are approximately near to the 1.00.

It means that there is no statistically significant difference in means therefore

in this case null hypothesis is accepted and alternative hypothesis is rejected.

For career planning, compensation and feedback factors p value is less than

0.05 therefore null hypothesis is rejected and alternative hypothesis is

accepted but rest of these factors we have p value is more than .05 herein the

null hypothesis is accepted and alternate hypothesis is rejected. Eventually, for

career planning, compensation and feedback factors, designation has

significant difference whereas rest factors do not have any significant

difference for designation. Except career planning, compensation and

feedback factors, factors of PMS have same significance for any of the

designation i.e for any designation, they have same significance.

A one way ANOVA is conducted to compare the effect of factors on years of service

wherein result shows

1 If we see all factors such as goal, career planning, performance review,

compensation, role of supervisor, reward and recognition, feedback, benefits

and work freedom, these factor’s p values are greater than 0.05 and their most

of them F values are approximately near to the 1.00 or less. It means that there

is no statistically significant difference in means therefore in this case null

hypothesis is accepted and alternative hypothesis is rejected.

Eventually, for every factor of PMS does not have any significant difference

for designation i.e for any year of service, they have same significance.

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Final Result:

If we see that only personal benefits, career planning, role of supervisor,

compensation and feedback factor have significant difference with demographic

variables but rest factors goal setting, performance review, reward and recognition

and work freedom do not have significant difference with demographic variable.

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Chapter-5

138

5. Summary and Conclusion

139

Performance management is very important aspect of human resource management

for any organization. In India, development is taking place very fast in recent years

therefore cement companies are being evaluated most important companies. Cement

companies must have effective performance management system, if cement

companies are having performance management system then it must be reviewed to

see the effectiveness of the system. In years back, performance appraisal system was

in use wherein ratings were given to the employees, once in a year or twice in a year.

Now it has been transformed in performance management system wherein continuous

monitoring and improvement of employees are to be recorded. Therefore this study is

done for performance management system of cement companies instead of

performance appraisal system.

The researcher found in the literature review that many studies are done on

performance management system of different companies in India and abroad. In these

studies, different factors were found (i.e goal setting, fairness of appraisal system,

feedback, merit pay etc) for different organizations that were having importance for

them. These factors were generally not more than 3 to 4 for any organization whereas

in this study, nine factors of PMS i.e goal, career planning, performance review,

compensation, role of supervisor, reward and recognition, feedback, benefits and

work freedom are having importance for the cement companies. It clearly indicates

that either cement companies performance management system is not effective or

system is missing. These factors required proper implementation to the cement

companies those who are not having PMS and if cement companies have already

PMS system then these factors must be considered.

The important nine factors are:

Goal setting: It is the initial stage of performance planning wherein organization and

department goals and objectives must be clearly defined and easy to understand by the

employee. It decides inputs and corresponding output by the employee as well as fixes

accountability of employee for the tasks, assigned to them.

Career planning and appraisal system: Career planning system must be clearly

defined to the employees and appraisal system must be clearly defined and

documented as well as easy to understand by the employees.

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Compensation: Pay and promotion decisions must be linked with the performance

achievements.

Role of supervisor: Supervisors must be able to handle performance the performance

of subordinate and must be concentrating on managing performance rather than

controlling.

Performance review: Performance review is for employee to develop and grow

therefore performance review must be done periodically and continuous interaction of

supervisor with employee. The review must be based on factors previously agreed

upon. There must be system defined to observe and fill the competency gap.

Learning and Feedback: Learning is the continuous process which must be at work

place as well as outside from the organization because technology is developing very

fast and competitiveness is being increased every day. Continuous learning make

employee up to date with current scenario and this gives employee to develop new

competencies and grow. Therefore, there must be a system for indentify training

needs. Feedback is mirror to show employee performance therefore continuous

feedback must be given as soon as activity is performed.

Reward and recognition: There must be clearly defined system for reward and

recognition of employees for their motivation.

Personal benefits: Job security is the major concern for every employee therefore it

must be clearly defined. Work life balance, basic amenities etc are the major

concerned which are to be taken care.

Work freedom: Work autonomy, participative decision making and value of ideas

can be entertained to some extent wherever required.

After determining the important PMS factors, we analyzed their relation with

demographic data wherein it has been found that most of the factors are not having

much significant difference with gender, age, education, designation and year of

service therefore PMS factors do not have much significance for gender, age etc. It

does not affect that what gender you are or what age you are but the factors are

important for cement company’s PMS.

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Chapter-6

142

6. Implications and suggestions

143

This extensive study is done to know the important factors of performance

management system for cement companies in Rajasthan and these important factors

have any significance on demographic variables, used for the study. Based on overall

study, researcher has strong opinion that these implication and suggestions will help

to the cement companies at the time of introduction and implementation of

performance management system. If PMS is already implemented then this can make

improvement in their performance management system.

After factor analysis, we have identified the core important factors which are goal

setting, career planning and appraisal system, compensation, role of supervisor,

performance review, learning and feedback, reward and recognition, personal benefits

and work freedom. These factors are important for the cement companies and

acceptance of these results will make the cement company’s performance

management system more effective when they enable these PMS factors in their

organization and they can achieve better than the present.

By literature review, it has been found that in Indian and international organizations

there are some (i.e 2, 3 factors) factors which were important to be implemented or to

be introduced. Herein, 9 important factors found i.e goal setting, career planning and

appraisal system, compensation, role of supervisor, performance review, learning and

feedback, reward and recognition, personal benefits and work freedom which shows

that cement companies are required to see their performance management system.

Because any of the company who is lacking with these important aspects of PMS then

they must review their performance management system.

This study suggests to cement companies of Rajasthan to review their performance

management system and if they are lacking with these factors then introduction is

required for effective PMS. In case, cement companies are having these factors in

their PMS then they must review their PMS and do effective implementation.

If any cement company is having performance appraisal system then it can be

transformed from performance appraisal to performance management system with

these important PMS factors for effective PMS system.

These PMS factors are useful for cement companies as well as academicians wherein

academicians can go for further research and can suggest other important aspects.

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When these important PMS factors were analyzed with demographic variables then

result shows that most of the factors are not having much significant difference with

gender, age, education, designation and year of service therefore researcher suggests

that PMS factors do not have much significance for gender, age etc. It does not affect

that, what gender you are or what age you are but the factor is important for cement

company’s PMS.

This study helps to cement industries, academicians, researchers etc. In cement

industry, with increasing competition and paradigm shift, strategic decisions are very

important therefore top management are required to consider factors of PMS in their

strategic decisions. Middle and lower management employees will be benefitted with

low attrition rate, high motivation and job satisfaction that will lead to increase

employee productivity. In academic courses like MBA, MHRM etc, these findings

can be imparted for practical approach with the text. Researchers can take forward

this research to Indian or international context.

The future research can be done in Indian or global context of performance

management system for cement companies.

Future research can be done in Rajasthan with the context of factors of human

resource management systems in cement companies, to have broader view.