1. ^ a b Rousseau, D. M. (1989). Psychological and implied contracts in organizations. Employee Responsibilities and Rights Journal , 2: 121-139.
2. ^ Coyle-Shapiro, Jacqueline A-M. and Parzefall, M. (2008) Psychological contracts . In: Cooper, Cary L. and Barling, Julian, (eds.) The SAGE handbook of organizational behavior. SAGE Publications, London, UK, pp. 17-34.
3. ^ Chris Aigyris, Understanding Organizational Behavior (Homewood, IU.: Dorsey Press, 1960).
A psychological contract , a concept developed in contemporary research by organizational scholar Denise Rousseau , represents the mutual beliefs, perceptions, and informal obligations between an employer and an employee . It sets the dynamics for the relationship and defines the detailed practically of the work to be done. It is distinguishable from the formal written contract of employment which, for the most part, only identifies mutual duties and responsibilities in a generalized form.the concept of psychological contract was first introduced by Argyris (1960) – “Since the foremen realize the employees in this system will tend to produce optimally under passive leadership, and since the employees agree, a relationship may be hypothesized to evolve between the employees and the foremen which might be called the ” psychological work contract .” The employee will maintain the high production, low grievances, etc., if the foremen guarantee and respect the norms of the employee informal culture (i.e., let the employees alone, make certain they make adequate wages, and have secure jobs)”.
There are number of techniques of estimating/forecasting human resources demand:
(a) Managerial Judgement
(b) Work Study Technique
(c) Ratio-trend Analysis
(d) Econometric Models
(e) Delphi Model
(f) Other Techniques
(a) Managerial Judgement:
Managerial judgement technique is very common technique of demand forecasting. This approach is applied by small as well as large scale organisations. This technique involves two types of approaches i.e. ‘bottom-up approach’ and ‘top-down approach’. Under the ‘bottom-up approach’, line mangers send their departmental requirement of human resources to top management. Top management ultimately forecasts the human resource requirement for the overall organisation on the basis of proposals of departmental heads. Under the Top-down approach’, top management forecasts the human resource requirement for the entire organisation and various departments. This information is supplied to various departmental heads for their review and approval. However, a combination of both the approaches i.e. ‘Participative Approach’ should be applied for demand forecasting. Under this approach, top management and departmental heads meet and decide about the future human resource requirement. So, demand of human resources can be forecasted with unanimity under this approach.
(b) Work-Study Technique:
This technique is also known as ‘work-load analysis’. This technique is suitable where the estimated work-load is easily measureable. Under this method, estimated total production and activities for a specific future period are predicted. This information is translated into number of man- hours required to produce per units taking into consideration the capability of the workforce. Past experience of the management can help in translating the work-loads into number of man-hours required. Thus, demand of human resources is forecasted on the basis of estimated total production and contribution of each employee in producing each unit items. The following example gives clear idea about this technique. Let us assume that the estimated production of an organisation is 3.00.000 units. The standard man-hours required to produce each unit are 2 hours. The past experiences show that the work ability of each employee in man-hours is 1500 hours per annum. The work-load and demand of human resources can be calculated as under:
Estimated total annual production = 300000 units
Standard man-hours needed to produce each unit = 2 hrs
Estimated man-hours needed to meet estimated annual production
(i x ii) = 600000 hrs
Work ability/contribution per employee in terms of man-hour = 1500 units
Estimated no. of workers needed
(iii / iv) = 600000/1500 = 400 units
The above example clearly shows that 400 workers are needed for the year. Further, absenteeism rate, rate of labour turnover, resignations, deaths, machine break-down, strikes, power-failure etc. should also be taken into consideration while estimating future demand of human resources/ manpower.
(c) Ratio-Trend Analysis:
Demand for manpower/human resources is also estimated on the basis of ratio of production level and number of workers available. This ratio will be used to estimate demand of human resources. The following example will help in clearly understanding this technique.
Estimated production for next year = 1,40,000 units
Estimated no. of workers needed (on the basis of ratio-trend of 1: 200) will be = 700
(d) Econometrics Models:
These models are based on mathematical and statistical techniques for estimating future demand. Under these models relationship is established between the dependent variable to be predicted (e.g. manpower/human resources) and the independent variables (e.g., sales, total production, work-load, etc.). Using these models, estimated demand of human resources
(e) Delphi Technique:
Delphi technique is also very important technique used for estimating demand of human resources. This technique takes into consideration human resources requirements given by a group of experts i.e. mangers. The human resource experts collect the manpower needs, summarize the various responses and prepare a report. This process is continued until all experts agree on estimated human resources requirement.
(f) Other Techniques:
The other techniques of Human Resources demand forecasting are specified as under:
(a) Following the techniques of demand forecasting of human resources used by other similar organisations
(c) Estimation based ontechniques of production
(d) Estimates based on historical records
(e) Statistical techniques e.g. co-relation and regression analysis.