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Managing and Motivating for Value SHORT Lectures and Articles Summary €4,99
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Managing and Motivating for Value SHORT Lectures and Articles Summary

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For this exam I summarized only the most most most important things of each lecture and article, so the outcome is this super short 6 pages summary of the whole course, and guess what? I passed! So enjoy!

Voorbeeld 2 van de 6  pagina's

  • 26 april 2021
  • 6
  • 2020/2021
  • Samenvatting
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Door: rachelvos4 • 3 jaar geleden

Ideale, simpele overview

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arti97
Lecture 1: Agency Problems
Adverse selection: According to contracting theory, the term “adverse selection” is simply
used to categorize principal-agent models in which an agent has private information already
before a contract is written. For example, a worker may know his effort costs (or a buyer may
know his willingness-to-pay) before an employer (or a seller) makes a contract offer. →
“SELECTION EFFECT”

Moral hazard (hidden information): The term “moral hazard” is used for principal-agent
models, where there is symmetric information at the time of contracting. The agent may
become privately informed after the contract is written. In this case the local business unit
has “hidden information”: The manager has local knowledge about the market that principal
does not have -> principal profits from local knowledge when local manager decides.

Moral hazard (hidden action): Again, symmetric information at the time of contracting. The
agent may become privately informed after the contract is written. But now “Hidden Action”:
The entrepreneur cannot perfectly monitor the agent efforts. The agent is simply working less,
or spends some of his time idle.

Lecture 2: Performance Measures
Performance measure: a quantifiable indicator used to assess how well an organization is
achieving the desired objectives.

Sensitivity: The extent to which the expected value of the PM changes with changes in the
agent’s effort. – degree to which the mean of the PM moves in response to an action by the
agent. (additional risk for the agent)

Precision: The extent to which the expected value of the PM is influenced by factors outside
of the control of the manager. (additional risk for the agent) – inverse of the variance of a
performance measure

Verifiability: The extent to which it is ex ante clear how the PM is calculated.

Congruence: The extent to which the PM reflects contributions to overall firm value. > A
congruent PM reflect the consequences of all actions an agent can take to increase firm value.
(additional risk for the principal)

Delegation: The extent to which employees have decision-making authority.

Aggregate PM: Measures that provide (some) information about ‘all’ actions.

Moers: If financial performance measures are good incentive measures, e.g. have relatively
high sensitivity, precision, and verifiability, then using these measures for incentive purposes
can complement the delegation choice, which results in increased delegation.

Campbell: The use of non-financial measures in promotion decisions is consistent with both
roles of promotions:

 Incentives: use of non-financials can instigate employees to improve their
performance (→ reduce moral hazard)
 Matching: non-financial measures are used to obtain incremental information about
the employee’s ability (→ reduce adverse selection)

, Lecture 3: Subjectivity
Subjective performance evaluation: allows managers to use non-contractible information to
assess actions and efforts that objective measures are not able to capture, creating a more
complete picture of performance can be positive for reducing compensation risk and
improving incentive alignment and employee motivation.

Gibbs: subjectivity in compensation contracting is used to improve congruence and noise
problems that are intrinsically linked to the use of performance measures. The evidence also
indicates that subjectivity has both purposes. Subjectivity increases pay satisfaction,
productivity, and profitability but only when it is applied in a trusting environment. Important:
subjectivity is mainly used in more complex, multi-task and noisy environments. As there is a
cost to the use of subjectivity (favoritism and influence costs), there is no real need to use
subjectivity in “easy” environments.

Cognitive information distortion: Supervisors will unintentionally bias their subjective
evaluations to be consistent with the known level of performance on the objective measure.

Bol: supervisors are influenced by the level of an unrelated objective measure in doing
subjective performance evaluation and this effect is driven by supervisors’ cognitive biases.
Supervisors use the discretion of the subjective performance evaluation to restore the fairness
of the evaluation system in case of low controllable objective measures. This effect is driven
by supervisors’ concern for fairness or self-interest. It is a bit of bad news (they anchor). The
good news, they give the benefit of the doubt (but they don’t punish for extreme good luck).

Lecture 4: Surrogation and Distortion
Campbell’s law: the more any quantitative social indicator is used for social decision-making,
the more subject it will be to corruption pressures and the more apt it will be to distort and
corrupt the social processes it is intended to monitor. Stated differently: if you start to
measure relatively inaccessible constructs, then people will overly focus on the measure.
Classical example: measuring welfare by means of economic growth.

Bloomfield’s law of measurement management: measure management arises when
performance measures capture strategic constructs with error, the people being evaluated
are aware of this fact, and people have discretion to distort either operations or reporting.
There should be three conditions present when you get this distortion. Measurement error:
the performance measure is an imperfect proxy for the underlying strategic construct.
Motivation: people are aware of the performance measures by which they are being
evaluated and care about the evaluation. Discretion: people have the ability to distort the
operations that generate the raw data used to compute the performance measure
(operational distortion), and how raw data are transformed into the performance measure
(opportunistic reporting).

Examples of BLMM: In hotel, strategic construct: happy customers, performance measure:
average score on distributed surveys. Measurement error: happy customers is not that easy
to measure. Motivation: store managers are often evaluated on customer satisfaction (next
to operational profit/revenues).

Surrogation: when people lose sight of the strategic constructs the performance measures are
intended to represent and subsequently act as the imperfect performance measures are the
constructs of interest (can happen “post incentive” phase).

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