My interest in this topic initiated from my experiences in dealing with the Darden Faculty during my 19 years in the Dean's Office.  Often, very intelligent, highly motivated, and economically trained faculty did not make the choices and think about issues as one might expect a rational person might.  The second motivating factors was my son Ross giving me Dan Ariely's Predictably Irrational: The Hidden Forces that Shape Our Decisions book for Christmas. 

Here are some examples in a operations environment:

Waiting:  When designing and managing a queueing system, it is important to recognize that people typically perceive that actual time they must wait is longer than it is really it.  This misperception is most evident when waiting involves phenomena as waiting alone, waiting with no explanation given, when they are anxious, when their time is unoccupied, or having the length of the wait be uncertain.  Most people do not like what they perceive as unfair waits when someone who arrives later gets served faster.  Recognizing and address these behavioral phenomena can be just as important as optimizing the system.

Forecasting:  Many operations decisions use forecasts as in important input.  Something as simple as how you ask for a forecast can affect the accuracy.  It is well known that people are overconfident in making forecasts.  For example, if you ask someone for a 90% confidence value range for the maximum temperature next month, their range will miss the mark nearly half the time.  However, if you were to ask the chances the high temperature will be in the same ranges as you get in the previous question, the chance they will say this range will include the maximum is lower than 90%.  This is called format dependence.  See "A Better Way to Forecast" by Uriel Haran and Don A. Moore, California Management Review, Vol. 57, No. 1, (Fall, 2014).

Newsvendor Problem:  Real world examples of the problem are any time one must make a decision before uncertainty is revealed.  The mathematics have been worked out for computing the optimal decision, but in over 18 laboratory experiments involving a wide variety of subjects including students with no exposure to the problem, MBA students who have studied the problem and executives the results are overwhelming that subjects make poor decisions.  They tend to anchor on the average demand and give too much weight to the most recent value of demand (see “Review of Behavioral Operations Experimental Studies of Newsvendor Problems for Operating Room Management” by Ruth E. Wachtel and Franklin Dexter, International Anesthesia Research Society, Vol. 110, No. 6, (June 2010).

Supply Chain (Multilevel Ordering):  Experiments involving the beer game where participants are making decisions in a multilevel situation have shown that even when subjects understand the causes of the “bullwhip effect” and share information show that participants order too much at times and not enough at others.

Supply Chain Negotiations:  Buyers and sellers often do not follow optimal choices because their decisions are affected by their emotions.