Title: The Effect of Pay, Career Plateau & Work Environment on Employee Turnover Intentions.
National Database & Registration Authority (NADRA) is a public-sector organization providing registration services to the citizens of Pakistan. In general, objective of this study is to find out the reasons of employee turnover. The main purpose of this study was to examine the impact of lesser pay, plateaued at a stage of career and unconducive work environment on NADRA’s employees for leaving the job or service. The study was restricted to the employees of the province of Khyber Pakhtunkhwa. Official and Officer cadre employees were included in the study having of both contract and regular services. NADRA is a service providing organization providing identification documents to the bona fide citizen of Pakistan. It has spread of its branches (called Data Acquisition Units) all over Pakistan upto Tehsil level. In the province of Khyber Pakhtunkhwa there are about 160 branches. This setup is further divided in a composite zonal administration. Each zonal office manages about seven to ten Data Acquisition Units depending upon the area, vicinity and population of the region. Every Data Acquisition Unit of NADRA has staff of about 10 to 20 employees including officers, officials and support staff. There are front desk officials who deal directly with the general public and core officials to deal with beck end job. Two type of officers or line managers are deployed at a Data Acquisition Unit. One officers deals with technical issues pertaining to machines software and computers the other officer deals with the managerial and administrative aspect taking place from time to time on routine basis in the office.
All the three main points has a positive and significant indication regarding employee turnover.
Key Words: Pay, Career Plateau, Work Environment, Employee Turnover intention and NADRA Pakistan.
An Empirical Inquiry into the behavioral Dynamics of South Asian Emerging Stock Markets
This study traces behavioral patterns which influence the aggregate market in terms of under and
overreaction. These reactions are mostly observed in the form of excess volatility and
unsystematic patterns in trading volumes. Self-attribution, anchoring, herding, disposition effect,
and limited attention bias are selected for this study. The study is conducted on Karachi Stock
Exchange, Bombay Stock Exchange, Dhaka Stock Exchange, and Dow Jones Industrial Average
for Pakistani, Indian, Bangladeshi, and U.S stock markets respectively. The study is conducted
for the period 2009 to 2018 using secondary data. It was found that the overconfidence bias can
be equally observed in Pakistani, Bangladeshi, and the U.S stock markets. Using nearness to a
historical high and nearness to a 52-week high as anchors, it was found that all sampled stock
markets under-react to new incoming information. Herding bias was confirmed in Up and Down
extreme market conditions for Pakistani and Bangladeshi stock markets respectively. Similarly,
the turnover effect was confirmed in low turnover stocks for Down extreme market conditions in
Pakistani and Bangladeshi stock markets only. The disposition effect is also confirmed in Pakistani
and Bangladeshi stock markets. The limited attention bias is tested and confirmed in terms of the
significant relationship between price momentum profits and trading volume in Pakistani and
Bangladeshi stock markets. Owing to the existence of these behavioral biases in the sampled stock
markets, the market over hypothesis was tested through the Average Cumulative Excess Returns
analysis. The results confirmed overreaction for Pakistani and Bangladeshi stock markets. This
implies that losers in one testing period become winners in subsequent periods due to the investor’s
overreaction and vice versa. Moreover, excess volatility in relation to market reactions and trading
turnover is tested. It was concluded that behavioral biases in sampled stock markets lead to excess
volatility while market overreactions along with excess volatility influence the trading turnover.
Interestingly, investors’ decisions in such trends are dependent on behavioral biases, and as a result
market overreaction becomes more prolonged and denser. In other words, the over-trading on part
of investors motivated by behavioral biases results in aggregate excess volatility primarily because
of the underlying momentum in trading trends. The results of the study are useful for individual
investors in their general awareness of behavioral biases, for regulators in coming up with more
efficient models regarding stock price estimation, and for mutual funds managers to improve the
safety of their investments.