FACTORS AFFECTING EMPLOYEE ABSENTEEISM: A CASE STUDY ON SALES DIVISION IN FRANCE, INDIA AND BRAZIL

FACTORS AFFECTING EMPLOYEE ABSENTEEISM: A CASE STUDY ON SALES DIVISION IN FRANCE, INDIA AND BRAZIL.

abstract. INTRODUCTION. This report is about the factors affecting employee’s absenteeism in Brazil Indian and France. This is requested by International Conglomerates (IC).

The purpose of conducting this study is to investigate the factors affecting employee absenteeism in France, India and Brazil. Absenteeism between employees has increased and the human resource manager at International Conglomerates (IC) has noticed it over the last five years..

FRANCE SOURCE INDUSTRY VARIABLES Edwards and Greasley (2010) Public sector Health, stress, financial cost Bargas and Monteiro (2014) Medical industry Age, education, function, shift, time in institution, workplace INDIA SOURCE INDUSTRY VARIABLES Rathod and Reddy (2012) Watch manufacturing industry Working condition, social and religion, welfare facilities Habeebur (2016) Retail (textile) sector Personal, family, health, psychological, social, customer related, grievance related BRAZIL SOURCE INDUSTRY VARIABLES Oenning, Carvalho and Lima (2014) Petroleum industry Gender, position, age, time at work, shift work, smoking, arterial hypertension, body mass index, etc Evans- Lacko and Knapp (2016) Medical industry Age, level of education, income.

1. Objective 1 impact of family on employee absenteeism 1.

RESEARCH QUESTIONS. 01. 04. 04. 03. 02. Impact of family on employee absenteeism.

Determine the causes of the employee’s absenteeism.

Affect Department. Factors such as family, environment, job satisfaction & health.

Concerning factors such as family, environment, job satisfaction and health and how these will affect employee absenteeism in France, India and Brazil. old place.

FAMILY Family plays a crucial role in absenteeism ( Kocakülâh et al., 2009)..

FAMILY ( Kocakülâh et al., 2009) 1. ENVIRONMENT 2.

Previous Literature. Godet- Cayré et al. (2006). Kalburgi and Thyagaraja (2013).

Summary Variables. VARIABLE Gender Ten Ure Farnity Job Satisfaction Health hallenges in Controlling Lateness. Absenteeisrn nd Labour Turnover- A Case tudY Of Christ Apostolic university wadaso. Kurnasi. Individual and Group Deterrninants Of E mployee Absenteeisrn: Test Of a Causal Factors Affecting Ernployee Absenteeisrn(A Study on A Sarnple Of Textile Workers) Individual and Group Of E mployee Absenteeism: Test Of a Causal M Odel Factors Affecting Employee Absenteeism(A Study On A Sarnple Of Textile Workers) Employee-s understanding Of Workplace Absenteeisrn and the Investigation Of Stress a s a Contributing Factor Absenteeisrn Problerns And Costs: Causes. Effects And Cures Absenteeisrn Problerns And Costs: Causes. Effects And Cures Absenteeisrn- a coenplex A absenteeisrn in Trondheim's Determinants Of Ernploy•ee Job Satisfaction:An rical Test Of a Causal Ernployee Absenteeisrn SOURCES (Kasu. 2014) (Gellatty. Akyegik. 2014) (Gellatty. Akyegik. 2014) ( Bermingham. Kocakülåh et (Kcxakülåh et 2CX)9) (Evans. 2011) (Agho)) 1995; 1995; 2013; 2CX)9) (Lager-th.off. 20-11).

( Kocakulah et al., 2016) (Karanja, 2013) (Mc Clenney , 1992) (Lambert, 2006).

Summary Models. Model Martocchio & Harrison (1993) Steers and Rhodes Model (1984 Maslow's Hierarchy Of Needs DESCRIPTION Mainly focuses on time periods. There are three of periods: Long term absence Mid-term absence Short term absence Random of empirical studied to just to find two factors: the ability to actually arrive at work, and motivation to attend. Both of these factors can be influenced by various factors. This created Process Model It focuses on three factors: STRENGHT Decide when approvals kick in and how strong they will. It also created to review time- based systems for organising theoretical propositions about absenteeism. dividing the various reasons as into the unidimensional theory that can be used for logical thinking and high accuracy (Sheng, 2007) It is able to help managers come up with ideas to help employees or subordinates to self-actualise. WEAKNESS Often violated in work absences Have a unidimensional theory rather than the theory of multiple dimensions can miss important discovery because of the lack of such factors as alleged by Burton Assumes everyone is alike, assumes every situation is alike, and assumes there is only one way to satisfy SOURCE (Timothy A. Judge,1994) (Burton (Geraldine Egan,2011) • Psychological, safety, love and belongingness, self- actualization.

Proposed Framework Hypothesis Development. Impact of ill health on employee absenteeism.

Data Analysis Technique. ANALYSIS Normality test Reliability test Descriptive analysis Correlation analysis Regression analysis REASONS Normal distribution is important as it underlies assumptions Of many statistical procedures. Example of norrnality test is Shapiro Wilk-VV test, Kolmogorov-Smirnov test. Lilliefors test and Anderson—Darling test. It refers to the consistency of scores on alternate forms of a similar test as no test would produce identical results. Descriptive analysis is the transformation of raw data into a reasonable and easily interpreted form Correlation analysis measures the extent of correspondence between twofactors, and it can may be estimated utilizing various coefficients; three most famous being Pearson's coefficient, Spearman's rho coefficient and Kendall's tau Regression is a statistical technique to determine the relationship between two or more factors. It is mainly utilizedfor forecast and causal inference. RULE OF THUMB Skewness and Kurtosis Cronbach's ALPH N/A Relationship Significant 0.01 or 0.05 >0.6 D r in W atson 1.5 —2.5 Significant 0.01 or 0.05 SOURCES (Razali and yap, 2011) (Vv'ells and Wollack, 2003) (Zikmund, (Hauke and Kossowski, 2011) (Campbell and Ca mpbel I, 2CX)8).

Data Analysis Technique Used In This Research. ANALYSIS Descriptive analysis Correlation analysis Regression analysis REASONS Descriptive analysis is the transformation of raw data into a reasonable and easily inter reted form Correlation analysis measures the extent of correspondence between twofactors, and it can may be estimated utilizing various coefficients; three most famous being Pearson's coefficient, Spearman's rho coefficient and Kendall's tau coefficient. Regression is a statistical technique to determine the relationship between two or more factors. It is mainly utilizedfor forecast and causal inference. RULE OF THUMB N/A Relationship < -1+1 Significant 0.01 or 0.05 Adjusted R Durbin 1.5 —2.5 Significant 0.01 or O SOURCES (Zikmund, 2003) (Hauke and Kossowski, 2011) (Campbell and Campbell, 2008).