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9990 · 4.5.3

Attitudes to work — practice questions

Practice and worked examples for 9990 Attitudes to work. Short previews only — attempt the full question in MarkScheme against the official scheme.

Worked example 1

Skilled engineers at a firm score moderately on job satisfaction but many leave for competitors. Exit interviews cite 'no emotional connection' despite good pay. Remaining staff say pensions and mortgage commitments keep them in place but they do minimal extra effort. Analyse commitment types and turnover.

Show solution outline

Low affective commitment: Engineers lack emotional attachment ('no connection') — want to leave despite moderate facet satisfaction (pay OK). Herzberg: Missing motivators (meaningful projects, recognition) while hygiene (pay) holds.

Continuance commitment: Remaining staff stay for pensions/mortgage — high continuance, low affective → retention without engagement (silent withdrawal, low organisational citizenship).

Turnover model: Job alternatives abundant for skilled engineers + low affective commitment → actual turnover even when satisfaction is not terrible.

Normative commitment: Possibly low — firm may not have fostered obligation through development investment.

Interventions: Build affective commitment via participation, career paths, transformational leadership (4.2.2) — pay alone insufficient.

Evaluation: Continuance commitment reduces turnover but not absenteeism or performance. Generational stereotypes about work ethic are weak — focus on organisational practices not age labels.

Worked example 2

A tech company with 250 employees is concerned about high staff turnover. In the last year, 50 employees resigned. A survey using a 7-point scale (1=Low, 7=High) revealed the following company-wide average commitment scores:

  • Affective Commitment (AC): 3.2
  • Continuance Commitment (CC): 5.8
  • Normative Commitment (NC): 3.5

Using this data, calculate the annual turnover rate and analyse the likely causes of turnover, referencing Allen & Meyer's model.

Show solution outline

Step 1: Calculate the Annual Turnover Rate The formula for annual turnover rate is: (Number of employees who left / Average number of employees) x 100

  • Number of employees who left = 50
  • Average number of employees = 250

Calculation: (50 / 250) x 100 = 0.2 x 100 = 20%

The annual turnover rate is 20%, which is generally considered high for a tech company.

Step 2: Analyse the Commitment Scores We analyse the scores in the context of Allen & Meyer's three-component model:

  • Affective Commitment (AC) Score: 3.2/7. This score is low. It indicates that employees have a weak emotional attachment to the company. They do not 'want to' stay. Low AC is one of the strongest predictors of turnover intentions and actual turnover.

  • Continuance Commitment (CC) Score: 5.8/7. This score is high. It suggests that employees feel they 'need to' stay due to the high perceived costs of leaving. This might be due to a competitive salary, stock options, or a lack of immediate alternative jobs. This is likely the main reason the turnover rate isn't even higher.

  • Normative Commitment (NC) Score: 3.5/7. This score is low. It shows that employees feel little sense of obligation or loyalty to the company. They do not feel they 'ought to' stay. This could stem from a perception that the company has not invested significantly in their personal development.

Step 3: Synthesise and Conclude The data paints a clear picture of a workforce that is 'trapped' rather than committed. The high turnover rate of 20% is driven by very low Affective and Normative Commitment. While high Continuance Commitment is keeping some employees from leaving, it does not foster engagement or motivation. This situation, often called 'golden handcuffs', can lead to reduced performance, lower organisational citizenship behaviour, and higher absenteeism among the staff who remain. The company is at high risk of losing more employees as soon as the costs of leaving decrease (e.g., a competitor offers a better package).

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