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Purpose – The purpose of this chapter is to explore the question of whether there is an optimal level of time pressure in groups. Design/approach – We argue that distinguishing performance from productivity is a necessary step toward the eventual goal of being able to determine optimal deadlines and ideal durations of meetings. We review evidence of time pressure's differential effects on performance and productivity. Findings – Based on our survey of the literature, we find that time pressure generally impairs performance because it places constraints on the capacity for thought and action that limit exploration and increase reliance on well-learned or heuristic strategies. Thus, time pressure increases speed at the expense of quality. However, performance is different from productivity. Giving people more time is not always better for productivity because time spent on a task yields decreasing marginal returns to performance. Originality/value of chapter – The evidence reviewed here suggests that setting deadlines wisely can help maximize productivity.
Optimal Deadlines 1
Time Pressure, Performance, and Productivity
Don A. Moore
University of California, Berkeley
Phone: 510-642-1059
Elizabeth R. Tenney
University of California, Berkeley
Phone: 617-312-4502
citation: Moore, D. A., & Tenney, E. R. (2012). Time pressure, performance, and productivity.
Research on Managing Groups and Teams, 15, 305–326.
Optimal Deadlines 2
Purpose: The purpose of this paper is to explore the question of whether there is some optimal
level of time pressure in groups.
Design/approach: We argue that distinguishing performance from productivity is a necessary
step towards the eventual goal of being able to determine optimal deadlines and ideal durations
of meetings. We review evidence of time pressure's differential effects on performance and
Findings: Based on our survey of the literature, we find that time pressure generally impairs
performance because it places constraints on the capacity for thought and action that limit
exploration and increase reliance on well-learned or heuristic strategies. Thus, time pressure
increases speed at the expense of quality. However, giving people more time is not always better
for productivity, since time spent on a task yields decreasing marginal returns to performance.
Originality/value of paper: The evidence reviewed here suggests that setting deadlines wisely
can help maximize productivity.
Category: Conceptual paper
Keywords: Time pressure, deadlines, performance, productivity
Optimal Deadlines 3
Performance and Productivity Under Time Pressure
Time is precious. The varied and conflicting demands on our time, from professional
commitments to domestic responsibilities, push us to squeeze the most from every minute
(Hochschild, 1997; Perlow, 1998, 1999). Modern innovations like fast food drive-throughs,
cellular telephones, and microwave ovens continually increase our ability get more done in less
time. Organizations strain to make the most efficient use of their employees, laying off those
who can be spared and pushing those who remain to do more in fewer hours (Schor, 1991). By
producing more goods and services with less time, American workers have increased the nation's
productivity at an impressive rate, exceeding two percent per year for the last twenty years,
consistent productivity growth not seen since the 1960s (Bureau of Labor Statistics, 2011). Yet
time pressure imposes constraints that can limit exploration, constrain cognitive capacity, and
impair performance. Time pressure can reduce performance on everything from simple math
problems (Bryan & Locke, 1967) to piloting airplanes (Raby & Wickens, 1994). In this paper,
we will review evidence on time pressure's effects on performance and explore the question of
whether there is an optimal level of time pressure that maximizes productivity.
The majority of the research on time pressure's effect on performance focuses on the
individual level of analysis, and so we will begin by reviewing evidence on time pressure's effect
on solitary performance. There has been less research exploring what effect time pressure has in
social contexts of cooperation with others, so we will use what we know about individuals to
help explain phenomena occurring at the group level. One important distinction will cut across
the domains of solitary and cooperative tasks, and that is the distinction between performance
and productivity. Although many have suggested that time pressure is a liability and hinders
performance, the evidence reviewed here will show that it can be beneficial for productivity. In
Optimal Deadlines 4
particular, time constraints can help maximize productive output by cutting people off when
better performance is no longer worth the continued time commitment.
Performance vs. productivity
The key distinction running through this paper differentiates performance and
productivity. Performance refers to the quality of some product without regard to the time or
costs that went into producing it. For example, the number of correct answers on a test would be
a measure of individual performance. The number and quality of ideas generated by
brainstorming together is an example of group performance. It is important to note also that
there can be multiple measures of performance. A team’s work can be evaluated on the basis of
how many widgets it turned out or how many reports it produced, but also on the basis of how
cohesive the group was or how the team affected the work of other teams around it.
Productivity is performance per unit time. For example, standardized test scores are
based on the number of correct answers within a given time limit. Another example comes from
research on brainstorming: Critical assessment of the value of brainstorming for producing ideas
must include a measure of the number of ideas generated per person hour (Gallupe, Bastianutti,
& Cooper, 1991). Prior research on the effects of time pressure has too often focused on
performance without considering the question of productivity. The question of productivity
directs attention to utility: Individual and group outcomes must be evaluated on the basis of
productivity to assess whether their products are commensurate with the investments that
produced them. The value of the products of human labor must be compared with the costs of
generating them. We begin our exploration of the consequences of time pressure in groups by
Optimal Deadlines 5
considering its effects on individual performance. This will serve as the foundation on which we
then build our analysis of time pressure’s role on group and team performance.
Time pressure, in the form of both final deadlines (i.e., a fixed time limit marking an end
to some endeavor, like the end of a soccer game) and time costs (the fact that whatever task one
is doing currently is time that could be spent doing something else), often impairs solitary
performance (Ariely & Zakay, 2001; Payne, Bettman, & Johnson, 1988; Payne, Bettman, &
Luce, 1996). Time pressure motivates people to seek closure more quickly, constrains the choice
of possible decision strategies (Beach & Mitchell, 1978), and limits the search for potential
solutions (Bowden, 1985). Decision makers under time pressure tend to gather less information
and act more quickly (Christensen-Szalanski, 1980). As a result, they are less likely to revise
their initial impressions (Heaton & Kruglanski, 1991), less likely to deviate from habitual modes
of attribution (Chiu, Morris, Hong, & Menon, 2000), more likely to rely on cognitive heuristics
(Kruglanski & Freund, 1983), are less accurate (Arkes, 1991; Kelly & Karau, 1993), and are less
confident in the accuracy of their decisions (Christensen-Szalanski, 1980). When making
choices, people under time pressure focus on information relevant to negative outcomes rather
than both negative and positive outcomes, focus on ruling options out rather than in (Ben Zur &
Breznitz, 1981; Wright, 1974; Zakay & Wooler, 1984), and tend to gravitate towards the
elimination-by-aspects decision strategy which Tversky (1972) found to be flawed. Thus, there
is strong converging evidence that time pressure is detrimental to solitary performance.
Time pressure's effects on performance are generally attributable to the constraints it
imposes on cognitive capacity (Moray, Dessouky, Kijowski, & Adapathya, 1991). People have
limited cognitive and attentional resources (Fiske & Taylor, 1991), and each task requires a set
Optimal Deadlines 6
of choices regarding how to allocate those limited resources. When time is restricted, to save
cognitive resources, people are likely to use heuristic processing strategies (or “mental
shortcuts”) instead of slower, more deliberative cognitive processing. A problem with using
heuristics is that, compared to slower cognitive processing strategies, heuristic processing tends
to be more vulnerable to biases and systematic errors (Chaiken, 1980; Johnson, Payne, &
Bettman, 1993). For example, people tend to show stronger primacy effects when they are under
time pressure, focusing too much on whatever they learned first (Kruglanski & Freund, 1983).
People under time pressure are more likely to rely on stereotypes to judge others (van
Knippenberg, Dijksterhuis, & Vermeulen, 1999). People under time pressure are also more
vulnerable to anchoring biases (Kruglanski & Freund, 1983). Even choices between decision-
making strategies take cognitive resources, and time pressure reduces the tendency to revise
earlier patterns of decision making to adapt to tasks requiring new solutions (Luchins, 1942;
Ordoñez & Benson, 1997). Basically, final deadlines limit the possibility for a thorough search
for potential solutions (Bowden, 1985), and increase the probability of well-learned, simple, or
routinized behaviors.
The above evidence has shown rather convincingly that time pressure usually hurts
performance on any given task. However, taking more time on all tasks is obviously not optimal
either because people care not only about performance on a single task but also about
productivity—getting the most done in the limited time we have. The implications for time
pressure on productivity need not be negative. The research demonstrates that when people are
under time pressure, they select decision strategies that require fewer cognitive resources but that
are more prone to error. However, the selection of these flawed strategies may be perfectly
rational if the reductions in performance are outweighed by the benefits of increased speed
Optimal Deadlines 7
(Johnson, et al., 1993). For more insight into this tradeoff, we turn to research on Parkinson’s
Parkinson's Law and Productivity in Solitary Performance
Quite a bit of research on time pressure has tested the validity of Parkinson's Law in
describing the productivity of individuals under time pressure. Parkinson's Law, attributable to
British historian C. Northcote Parkinson (1957), states that work expands to fill the time
available for its completion. If allotted ten minutes to do an assignment, people will take ten
minutes to complete it. If allotted thirty minutes, people will take thirty minutes to complete it,
making the rate of work (i.e., productivity) inversely proportional to the time available. In other
words, Parkinson’s law suggests that people try to maximize performance by taking the full time
allotted to them even though doing so will hinder their productivity.
The strong form of Parkinson’s Law is obviously wrong because as time shrinks to zero
the speed of work does not go to infinity. To pick but one example, limiting a novice pianist’s
practice time to less than a second does not make the novice learn to play that much faster.
However, in its weak form Parkinson's Law predicts that more time will be spent on a task when
more time is available. This prediction is supported by a great variety of research beginning with
Aronson and Gerard (1966). Aronson and Gerard allowed their participants either 5 or 15
minutes to prepare a speech on a given topic. Not surprisingly, those given more time took
longer to prepare their speeches. In addition, those given 15 minutes on the first trial took longer
to prepare another speech when told they could take as long as they needed. Other studies have
also included measures of performance with similar experimental manipulations, and the data
consistently show that tighter final deadlines produce lower absolute performance but faster rates
of performance (Bowden, 1985; Freedman & Edwards, 1988; Kelly, 1988; Zakay & Wooler,
Optimal Deadlines 8
1984). Another good example of this pattern is from experiments in which individuals were
given anagrams to solve (Kelly, 1988). When participants were given a 5-minute time limit, they
solved an average of 23.4 anagrams, or 4.7 per minute. When they had 20 minutes to work,
however, their performance nearly doubled to 44.4 anagrams solved, while their productivity
(the ratio between performance and time) was cut in half, to 2.2 anagrams per minute. More
time was beneficial for performance—people solved more anagrams—but note that performance
did not improve linearly. Four times as much time yielded only twice as many anagrams solved.
Productivity, which is the rate of work or the ratio of performance over time, was better with
tighter time constraints.
Why does time pressure increase productivity? Researchers have assumed that increased
productivity on tasks with shorter final deadlines can be attributed to increased effort. Some
have pointed out that final deadlines increase a task's difficulty, and that achievement goals tend
to be higher for difficult tasks than for easy tasks (Bryan & Locke, 1967). Others, however,
avoid reliance on such a goal-setting mechanism, and suggest that time pressure naturally elicits
increases in the pace in activity, even if people aren’t consciously pursuing a higher productivity
goal (McGrath & Kelly, 1986). The logic underlying both these arguments rests on the untested
assumption that performance is proportional to the time spent working (constant performance
rate over the duration of the task). For example, if Kelly’s (1988) participants solved 2.2
anagrams per minute for each of the 20 minutes they had, then the increase to 4.7 anagrams per
minute under the 5-minute deadline must have represented an increase in their rate of work under
the shorter deadline. But another obvious possibility, untested in prior research, is that
productivity may be highest early on. It is possible, for instance, that even in the 20 minute
condition, participants solved 23.4 anagrams in the first 5 minutes (a rate of 4.7 anagrams per
Optimal Deadlines 9
minute), then solved only 21 anagrams in the next 15 minutes (an overall productivity of 2.2 per
There are at least four reasons why we should expect productivity to be highest at first:
1) Ceiling effects may limit later performance. If there is more than enough time to
accomplish a task and the time-performance curve approaches a performance ceiling,
more time spent working will not produce a significant increase in performance.
Variations of final deadlines within this range will have no impact on performance.
Similarly, after you have solved a crossword puzzle, it is not possible to improve your
performance by working on it more. Note that ceiling effects will only be relevant for
optimizing tasks of limited scope and not for maximizing other types of tasks (Steiner,
1972). If you are trying to solve as many crossword puzzles or knit as many sweaters as
possible, ceiling effects will not place hard limits on performance.
2) Although more time is generally better for performance, fatigue is likely to reduce the
rate at which performance improves over time.
3) If people follow the common and sensible strategy of solving the easy problems first
when all problems have equal value or of approaching a complex problem by solving the
most basic elements first, then performance will slow over time as the problems get more
4) The fourth reason that performance may not necessarily increase with time has to do with
evidence suggesting that spending an inappropriately large amount of time on a task can
actually impair performance (Payne, Samper, Bettman, & Luce, 2008). More time can
reduce performance if that time is spent thinking about factors for which further thought
is disruptive (Dijksterhuis, Bos, Nordgren, & van Baaren, 2006; Wilson, Dunn, Kraft, &
Optimal Deadlines 10
Lisle, 1989). Too much time spent analyzing and explaining one's attitudes towards
different drinks (Wilson & Dunn, 1986), varieties of jam (Wilson & Schooler, 1991), and
even romantic partners (Wilson & Kraft, 1993) can reduce the quality of subsequent
judgments. Researchers have explained these decrements in judgmental performance by
arguing that excessive introspection can lead people to include in their decision
unimportant factors that ought properly to be ignored (Wilson, Hodges, & LaFleur,
1995). In this vein, it is important to remember that greater amounts of time allow for the
achievement of multiple aims. Although work under time pressure tends to be task-
focused, unpressured work allows for relaxation, socialization, introspection, and
In sum, evidence suggests that performance and productivity follow the patterns
illustrated in Figure 1. Performance increases over time for most tasks, but at a decreasing rate.
The longer one works at something, the better the final product, but the first hour accomplishes
more than the tenth hour. Productivity is highest when work begins, and decreases with time.
This relationship is illustrated by the performance curve in Figure 1, and can help explain
differences in productivity with different final deadlines. If a final deadline forces an end to
work after just a short time, then the average productivity in that interval will be higher than if
work is allowed to continue a long time.
The contribution of this approach is that we can then assess the utility of continued work.
If the time cost associated with work is uniform, then we may simply subtract this time cost from
the utility of performance to assess the utility of work. The important feature to note is that
although the time cost of continued work is roughly linear with time (i.e., there are always other
tasks to do), if the performance curve is concave, the utility curve has a peak. This peak is the
Optimal Deadlines 11
optimal deadline. This is the point at which the marginal utility of performance is equal to the
marginal cost of continued work. The location of this peak depends on the rate of work, the
value of that work, and the cost of getting the work done. Imagine, for example, that a young
adult working at a farm gets paid $.01 for every apple he picks. His time cost is an opportunity
cost: he is forgoing the $10 per hour wage he could make at another job working at a hotel.
After he has picked the “low-hanging” fruit and his farm wage drops below $10 per hour, he
should stop picking apples and go to work at the hotel. Naturally, differences between people,
tasks, and contexts make it necessary to measure work rates, assess the value of work, and
determine the time cost of work in each context.
The question then becomes how long the deadline should be. Should the young adult set
a deadline on his apple-picking work? A rational analysis would prescribe that if additional
effort can increase performance, then work should continue as long as it's worth it (that is to say
that the value of marginal increases in performance exceeds the marginal cost of doing the work
in time, effort, and opportunity costs). Optimal final deadlines maximize utility. As Simon
(1947) pointed out, the rationality of decisions is necessarily bounded by the costs associated
with gathering information, analyzing data, predicting outcomes, and choosing among
alternatives. You should stop working on polishing that grant application when it does not
increase the expected value of applying, relative to the benefits of doing more research or extra
teaching. The most effective and productive decision-making processes maximize benefits while
minimizing costs. This means local optimization within some limited domain, since considering
all the possible alternatives is too costly because it takes too much time (Simon, 1947). Studies
that measure utility over time have consistently come to the conclusion that there is an optimal
time limit that maximizes utility (Bowden, 1985; Freedman & Edwards, 1988; Kelly & McGrath,
Optimal Deadlines 12
1985). Assuming that time costs accrue linearly with time, then the utility function will have the
shape of the middle curve in Figure 1.
If each task has an optimal deadline, one must ask the practical question of how to
determine exactly what it is. The clear answer is that the optimal deadline should coincide with
the point at which the marginal costs of continued work become equal to or greater than the
value of marginal increases in performance associated with continued work. In terms of Figure
1, work should stop at the inflection point on the utility curve where it goes from increasing to
decreasing. Every scholarly paper requires some polishing, and we all know scholars who err on
either side of the optimum. Some impatient academics routinely send papers out too quickly
before they have been sufficiently edited. Then there are those who never submit papers for
publication because they want each paper to be perfect before it goes to a journal. Determining
exactly how long the deadline should be, in terms of minutes or hours or weeks, however, will
depend on a good deal of data surrounding performance patterns over time on the specific task in
question, as well as the costs of continued work. These dimensions are also likely to vary
between people as well as between tasks. Deciding how long to polish a paper before submitting
it depends on several obvious factors: how polishing affects the probability of publication, what
other papers you could be working on, how much those efforts could contribute to their
likelihood of publication, and your impatience to get papers out—perhaps because of an
impending tenure decision. Estimating these quantities must entail some subjectivity and
guesswork, but this uncertainty is still probably better than relying on the happenstance influence
of norms or rules of thumb that ignore the particulars of your situation.
Optimal Deadlines 13
The rigidity effects (or reliance on stereotypes) shown to affect individuals under time
pressure are also evident in the behavior of groups and organizations (Staw, Sandelands, &
Dutton, 1981). Evidence indicates that the relationship between time and performance in groups
is similar to that for individuals: Groups show an overall benefit to performance given more
time, but with decreasing marginal returns (Latham & Locke, 1975). Although this makes sense
under the assumption that the best predictor of group behavior is the behavior of the individuals
that compose them, groups face issues that individuals do not, such as a need for interpersonal
coordination. We thus turn to the issue of how groups operate under time pressure, and when
possible we compare groups to individuals. Coordination issues are the first and most obvious
challenge that groups have when it comes to integrating the inputs of individuals over time, and
we consider it first. We also discuss research results on work pacing in groups. This leads
directly to a discussion of pursuing multiple goals because groups necessarily have more
complicated motives and goals than do individuals. Finally, we seek to apply some of these
lessons to meetings, as they represent the forum for group work and a ubiquitous feature of
organizational life.
Coordination Issues
Although groups can complete tasks that are more complex and demanding than any
solitary individual could ever accomplish, groups have the added burden of having to coordinate
its members. Problems that arise from coordination and lead to a reduction in group
performance can be considered process loss (Okhuysen & Bechky, 2009; Steiner, 1972; Taleb,
2011; Weick & Roberts, 1993). Many coordination problems center on temporal conflicts
(Blount & Janicik, 2002; Kwang & Swann, 2010; McGrath, 1990; Perlow, 1998). For example,
Optimal Deadlines 14
one of the reasons that brainstorming groups are less productive than individuals is that they
have to coordinate speaking turns. The person who is talking about his or her own idea is
preventing others from talking and may be interrupting others' idea-generating processes (Diehl
& Stroebe, 1987; Gallupe, et al., 1991). It is furthermore common for different people to
perceive deadlines, time pressure, and the need for speedy action differently—having group
members who do not recognize the need for speed can slow the productivity of the entire group
(Waller, Conte, Gibson, & Mason, 2001).
In addition to process loss from turn-taking and temporal conflicts, time pressure limits
groups’ opportunities to plan members’ contributions, thereby increasing the probability that
they will launch into task execution without a coordinated approach (Wittenbaum, Stasser, &
Merry, 1996). The group is especially vulnerable to a disorganized or premature task launch
when they lack experience working together. Groups may respond to these coordination
problems by adopting a more authoritarian structure (Isenberg, 1981) and becoming less tolerant
of dissenters (Kruglanski & Webster, 1991) and more prone to groupthink.
Training a group together can help reduce coordination problems and increase
productivity because it gives individuals some basis in experience for predicting others' behavior
and they can plan their own contributions accordingly (Fine, 1990; Gevers, van Eerde, & Rutte,
2001; Liang, Moreland, & Argote, 1995; Weick & Roberts, 1993). The term "entrainment"
describes the process by which people adjust their work to the pace of activity in a group, in
much the same way as individuals tend to match their pace to that of other pedestrians on a
crowded sidewalk (Kelly, 1988; Kelly & Karau, 1993; McGrath & Kelly, 1986). One result may
be that groups move through phases of task coordination together and establish a pattern
(Ancona & Chong, 1996; Gersick, 1988, 1989).
Optimal Deadlines 15
If groups rely on entrainment to coordinate their actions, one would expect that once a
group established some routine pace of work that the pace would then be resistant to change.
Research has produced some support for the rate persistence hypothesis (McGrath, Kelly, &
Machatka, 1984). Groups of three participants generated creative and unusual uses for common
objects (e.g., uses for a brick other than building a house). Groups produced as many uses for
the objects as they could in trials of 4, 8, and 12 minutes in length. Groups that had time limits
of 4-8-12 tended to produce more uses per minute across all final deadlines than groups that had
time limits of 12-8-4 (Kelly & Karau, 1993). The results show first that groups were more
productive (generating more ideas per minute) the shorter the trial, which fits with the idea that
tighter deadlines are good for productivity. Second, the results show evidence of rate
persistence: high early productivity established during the shorter (4 minute) timeframe carried
over to high later productivity when the timeframe was longer. Participants continued to work
quickly, as though they only had 4 minutes, even when they had more time. Similarly, slow
productivity established when the timeframe was initially long (12 minutes), carried over to low
later productivity when the timeframe was shorter and the pace would have needed to increase to
make up for it. This rate persistence effect has also been shown in other group work, such as
writing creative essays (Kelly & McGrath, 1985) and solving anagrams (Kelly & Karau, 1999).
These studies provide clear evidence of rate persistence in groups, but what causes it? Is rate
persistence a product of entrainment, or social coordination, as some researchers have posited, or
is it merely a byproduct of individual work patterns?
Research at the individual level shows that individuals demonstrate exactly the same
tendency of rate persistence in their performance across trials as groups (Aronson & Gerard,
1966; Aronson & Landy, 1967; Bryan & Locke, 1967). If individuals demonstrate rate
Optimal Deadlines 16
persistence, it is possible that rate persistence is not influenced by entrainment or social
coordination, but instead occurs in groups because individuals do it regardless of whether they
are cooperating or coordinating with others.
Work Pacing
How quickly groups anticipate having to work is an important influence on how they
pace their efforts. Therefore, an important question is whether groups show the same planning
fallacy as do individuals—believing that plans will be carried out more quickly than they often
are (Buehler, Griffin, & Ross, 1994). The answer is an emphatic yes. Indeed, groups tend to
show an even stronger planning fallacy (Buehler, Messervey, & Griffin, 2005). Individuals are
routinely optimistic regarding the speed with which they will get work done. Groups are even
more optimistic, perhaps because of added social pressure to give a desirable response (e.g., to
say the task will be done quickly) when others are around (Pezzo, Pezzo, & Stone, 2006). The
planning fallacy has profound implications for how people manage their time together.
One way to avoid the planning fallacy is to have an external deadline rather than ask the
people involved to make one themselves. For example, a teacher should have students turn in
assignments on specific days spaced evenly throughout the semester rather than let students
choose when to submit them. If allowed to choose, they do not leave themselves sufficient time
at the end of the semester because they incorrectly estimate the amount of time the assignments
will require (Ariely & Wertenbroch, 2002). An external deadline (set by someone or something
with a better vantage point) will force action and eliminate the problems associated with the
planning fallacy.
Given the value of deadlines and how frequently people encounter them, it is surprising
that people are poor at setting optimal deadlines for themselves. Why this is the case has partly
Optimal Deadlines 17
to do with excessive optimism regarding their discipline and work productivity in the future, but
it is also caused by the fact that people are not very good at anticipating the beneficial effects of
deadlines for productivity on themselves and their groups. In a study of participants in a
simulated negotiation situation, participants wrongly believed that a time deadline would hurt
their outcome more than it would hurt their opponent’s outcome. Participants were even worse
at anticipating the effects of deadlines on the behavior of other people and other groups (Moore,
2005). People seem to have an expectation that deadlines will constrain them and leave them at
a disadvantage. In light of evidence that deadlines can actually help planning and productivity,
people would be wise to reconsider their distaste for deadlines.
Pursuing Multiple Goals
How groups use their time depends on their goals, and groups necessarily have more
complicated motivations and goals than do individuals. Groups serve numerous functions, and
not all of a groups’ goals can be pursued simultaneously (McGrath, 1990). Time pressure may
force increased attention to some tasks at the expense of others, as proposed by the attentional
focus model of time pressure in groups (Karau & Kelly, 2004; Kelly & Karau, 1999; Kelly &
Loving, 2004). A group under time pressure may work at a furious pace to maximize output
without regard for the quality of that output. For example, researchers had groups of three
people formulate written essays on current events and varied the length of time the group had to
work on their essays, either 10, 20, or 30 minutes. The researchers measured performance in
terms of length, creativity, and adequacy. Although groups with short deadlines were able to
produce essays of adequate length, creativity took longer to achieve, suggesting that the goal of
producing something of adequate length took precedent over the goal of writing something
creative (Karau & Kelly, 1992). Time pressure might be costly to performance but beneficial to
Optimal Deadlines 18
productivity because under time pressure, production goals are given priority. Similarly,
McGrath (1990) argued that groups with more than enough time to complete their task-related
work would put more attention and effort into second-order goals of group well-being and
member support functions, which might have received short shrift in a task-focused race under
time pressure (Zaccaro, Gualtieri, & Minionis, 1995).
Other research consistent with this idea shows that group polarization (the tendency to
make extreme, one-sided decisions) depends on group time limits and the length of discussion
(Bennett, Lindskold, & Bennett, 1973). The argument is that groups whose discussions are
limited by tight final deadlines focus on shared perspectives and on building consensus quickly
compared to groups who have more time, and this tendency results in greater group polarization.
Time pressure also exacerbates the common-information bias, in which group discussion tends to
focus on information that the group members share (Gruenfeld, Mannix, Williams, & Neale,
1996; Stasser & Titus, 1985, 1987). Unique, unshared information is more likely to emerge later
in discussion (Larson, Christensen, Abbott, & Franz, 1996; Larson, Christensen, Franz, &
Abbott, 1998). These ideas are consistent with the threat-rigidity effects of Staw et al. (1981),
who argue that groups under heavy time pressure will revert to what they know best and respond
in well-learned ways to threats or pressure.
Finally, it is important to note that the question of productivity takes on increased
importance in group settings simply because there are more people involved. For example, when
time is being wasted at a meeting, the opportunity cost of that time must be multiplied by the
number of people present. Groups can accomplish more than individuals, but groups can also
waste more time. Appropriate deadlines can reduce the amount of time wasted and maximize
Optimal Deadlines 19
Meetings are such an important and ubiquitous feature of organizational life that they
deserve their own mention. The first thing many people think of at the mention of a meeting is
time costs—the opportunity cost of the time spent, and all the other things they could be doing if
they were not meeting. Indeed, when managers entering a meeting are asked what they want, the
most popular answer may be that they want the meeting to adjourn punctually (Dao, 2011).
Long, pointless meetings may be the very best way for an organization to waste the time of and
impair the productivity of its members, in part because the time costs must be multiplied by the
number of people present to compute its full cost. Given the time costs associated with
meetings, it becomes especially valuable to think about how to set final deadlines appropriately
to maximize the meeting’s utility.
Group decision rules vary along a wide continuum from dictatorship to consensus, and
some types benefit from optimal deadlines more than others. Decisions made by an individual
“dictator” can be faster and more efficient than decisions made by a group, even when that
individual is thorough in his or her consideration of information and alternatives (Eisenhardt,
1990). Dictators benefit from setting optimal deadlines. So too do autocrats, who have the
power to limit deliberation and set a deadline for the group. By contrast, decisions made by
consensus necessitate the assent of all the members of the group. They therefore take longer,
draw out more information, and allow greater opportunities for dissent. Consensus decisions are
not amenable to deadlines, since any one member can delay consensus by withholding assent.
Nevertheless, leaders of all kinds, including consensus decisions, can guide discussion and
manage group expectations regarding the pace of progress by being explicit about time limits.
So what is the right deadline to set in a meeting? The answer to this question comes from
Optimal Deadlines 20
comparing the benefits of holding the meeting with the opportunity costs of group members’
time, employing the framework proposed in this paper.
When considering the question of whether time pressure is beneficial or an obstacle for
accomplishing tasks, previous research has yielded mixed results. However, drawing a
distinction between performance and productivity as we have attempted to do in this chapter
clarifies the role that time pressure plays. When organized in this way, past research shows a
clearer pattern: time pressure generally hinders performance but helps productivity. We argue
that distinguishing performance from productivity is a necessary step towards the eventual goal
of being able to determine optimal deadlines and ideal durations of meetings. We hope that
future research will conceptualize and measure performance and productivity separately.
An interesting question to explore might be when does performance actually improve
with time pressure. As we mentioned earlier, there are some instances when taking time and
cognitive effort to deliberate could yield suboptimal decisions and outcomes (Payne, et al., 2008;
Wilson, et al., 1989). A time deadline that stops people before they have a chance to “overthink”
could be beneficial to performance. More research is needed to determine the types of tasks in
which more time impedes performance and what the cutoff or deadline should be in these
exceptional cases.
Another avenue for future research is to explore how time pressure and attention to time
changes people’s moods or attitudes toward the task they are working on. For example, being
unaware of the passage of time is associated with higher intrinsic motivation, the belief that one
is completing a task out of one’s own uncoerced desire to do so (Conti, 2001). Thus, deadlines,
which put time at the forefront of people’s minds, might undercut intrinsic motivation. Working
Optimal Deadlines 21
under a deadline might make people believe they are completing a task because they have to and
not because they want to. On the other hand, working at a fast pace to meet a deadline could
cause people to think quickly, focus rather than allow the mind to wander, and believe that time
has passed quickly rather than slowly, all of which have been associated with increased
happiness and/or enjoyment of the task at hand (Killingsworth & Gilbert, 2010; Pronin, Jacobs,
& Wegner, 2008; Sackett, Meyvis, Nelson, Converse, & Sackett, 2010). As one example of this
research, study participants listened to a song they liked while watching a song timer that was
either sped up or slowed down by 20%. When the timer counted up quickly, making it seem like
time was passing quickly, participants reported liking the song more than when the timer counted
up slowly, making it seem like time was dragging. The song itself did not change, only the
perception of time and what that meant to the participants. How deadlines change the way time
is experienced, whether the experience of time passing quickly is always enjoyable, and whether
this enjoyment would offset potential negative side effects of deadlines (e.g., stress) warrants
further discussion. There are many interesting unanswered questions regarding how deadlines
and people’s interpretation of the passage of time affect individual and group progress on
different types of tasks.
More research on deadlines and groups would also be useful to organizations and
managers. Questions to explore in this domain include: when does the vast amount of research
on individuals generalize to groups and when does it not? Does the effect of time pressure on
groups change depending on the type of task at hand (e.g., a complicated or simple task)? What
role do interim deadlines and meetings play on the tradeoff between performance and
productivity? How might group dynamics change when group members work together
Optimal Deadlines 22
repeatedly (e.g. Gevers, Rutte, & Van Eerde, 2006)? These questions essentially ask for
information on the role of time pressure in more complex, real-world situations.
Time pressure constrains cognitive capacity and the ability to get things done because
both thinking and acting take time. Although training can improve performance under time
pressure (Lin & Su, 1998), time pressure generally leads to impairments in performance in
solitary tasks. Time pressure is ubiquitous, and people have cognitive strategies for dealing with
it, but they come at a cost. These strategies tend to trade accuracy for speed by increasing
motivations to seek early closure (Kruglanski & Webster, 1996), with resulting increases in
primacy effects (Heaton & Kruglanski, 1991), increased reliance on stereotypes (van
Knippenberg, et al., 1999), and increased use of well-learned cultural response patterns (Chiu,
Hong, & Dweck, 1997; Luchins, 1942). Patterns in performance generally show decreasing
marginal returns to time (Bowden, 1985; Kelly, 1988). This means that performance rates are
highest early in a task, and decrease over time. Practically, that means that more time will
generally be associated with higher performance. However, as long as time has some cost, then
there exists some time limit that maximizes productivity.
In groups, a number of the consequences of time pressure appear to be a direct result of
time pressure's effects on the individuals in the group. Groups (Kelly & McGrath, 1985), like
individuals (Aronson & Gerard, 1966), show persistence in rates of performance across tasks.
Groups (Karau & Kelly, 1992), like individuals (Bowden, 1985), show attentional narrowing and
increased need for closure under time pressure. However, time pressure also increases problems
of interpersonal coordination in groups. In response to time pressure, groups adopt a more
Optimal Deadlines 23
stratified, hierarchical structure (Isenberg, 1981) and become less tolerant of dissenters
(Kruglanski & Webster, 1991).
This review has attempted to clarify what we do know by reviewing the effects of time
pressure in both solitary and cooperative tasks. As the evidence reviewed here demonstrates,
time pressure tends to have a deleterious effect on performance. At the same time, appropriate
use of final deadlines can maximize productivity. Deadlines can catalyze work that would have
otherwise languished and it can stimulate groups to take action where they might not otherwise
have done so. Individuals or organizations seeking to implement final deadlines that maximize
productivity would do well to understand both the shape of the performance curve and the cost of
Optimal Deadlines 24
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Author Notes
Thanks to Max Bazerman, David Messick, Keith Murnighan, Alvin Roth, and Leigh Thompson
for their support and guidance. We appreciate the Dispute Resolution Research Center at
Northwestern University for funding this research. We are further indebted to George
Loewenstein, Adam Galinsky, Robyn Dawes, Linda Argote, and Sapna Shah for reading the
paper and providing us with their comments and suggestions. Whatever errors and omissions
remain are solely our own. Correspondence regarding this paper may be addressed by e-mail to
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In many low-and middle-income countries, health systems decision-makers are facing a host of new challenges and competing priorities. They must not only plan and implement as they used to do but also deal with discontented citizens and health staff, be responsive and accountable. This contributes to create new political hazards susceptible to disrupt the whole execution of health plans. The starting point of this article is the observation by the first author of the limitations of the building-blocks framework to structure decision-making as for strengthening of the Moroccan health system. The management of a health system is affected by different temporalities, the recognition of which allows a more realistic analysis of the obstacles and successes of health system strengthening approaches. Inspired by practice and enriched thanks a consultation of the literature, our analytical framework revolves around five dynamics: the services dynamic, the programming dynamic, the political dynamic, the reform dynamic and the capacity-building dynamic. These five dynamics are differentiated by their temporalities, their profile, the role of their actors and the nature of their activities. The Moroccan experience suggests that it is possible to strengthen health systems by opening up the analysis of temporalities, which affects both decision-making processes and the dynamics of functioning of health systems.
This study explored the relationships among emotional labor (EL), job stress (JS), job characteristics (JC), social media use intensity (SM), and job performance (JP). A quantitative study was conducted with a total of 380 questionnaires collected from tour leaders. The results of the study are as follows: (1) EL has a positive impact on JS, (2) JS has a negative impact on JP, (3) JS mediates the relationship between EL and JP, and (4) JC moderates the relationship between EL and JS, and (5) SM moderates the relationship between JS and JP. Theoretical and practical implications include validating a framework and suggestions for travel agencies to improve the JP of tour leaders by working on human resource practices.
The hackathon was developed by practitioners and it could be said that they used structures and characteristics from other invention development methods that intend to spark creativity. This paper aims to define and evaluate those characteristics that serve as determinants of invention. It analyses research performed on 14 different hackathons with the following ethnographic approach: 1000 h of observation, 36 semi-structured interviews and digital ethnography (netnography). Collected data has been analysed with the use of grounded theory methods and machine learning, which has been introduced as a triangulation method. As a result 9 main characteristics within the hackathon method that serve as invention determinants were discovered and holistically described. The identified elements have been backed by different theoretical backgrounds, but as one they form a flexible and unique mixture that helps to understand the hackathon phenomenon, potential hazards and its inner mechanisms. The discovered characteristics can help in effective organization of hackathons in the future.
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Global research ethics issues are becoming increasingly important in research management. The Human Research Ethics Committee of the State University of Western Paraná (CEP Unioeste), has regulated within the scope of Unioeste and the Western region of Paraná, the ethical analysis of research proposals involving human beings, in order to enhance the researcher's autonomy in research and the protection of research participants. In this work, a procedural analysis of the decision-making reviews of CEP Unioeste was carried out, in the five-year period from 2015 to 2019, seeking to (re) discover the potential of this ethics committee. The information for the analyzes was obtained in the CEP Unioeste Performance Report, made available (restricted use) on Plataforma Brasil, a national and unified base of research records involving human beings, coordinated by the National Research Ethics Commission (Conep). The rocedures adopted by CEP Unioeste, showed a reduction in procedural pending issues in the first phase of the analyzes, speed of the processing process and expansion of the number of analyzed cases
Performance on divergent thinking (DT) tests varies by different testing conditions. Although many studies documented that DT performance increases when more time is provided, it still remains unanswered whether DT performance continues to increase linearly or follows a rather non-linear pattern as more time is allowed. The present study examined a potential curvilinear pattern in DT performance by synthesizing 237 effect size in 22 studies using a three-level approach to account for the nested structure of data. Results indicated that liberal time conditions provided significantly better DT performance than the restricted time conditions with the mean effect size (g=0.666) being considered moderate to large. The effect size was small to moderate (g = 0.493) in a group of studies that merely compared “timed” and “untimed” conditions. The effect was larger (g = 0.901) in a group of studies comparing varying amounts of time. The quadratic term of time difference between the shorter and longer time conditions turned out significantly negative indicating the inverted J-shaped relationship between time-on-task and DT performance: the DT performance increases with more time, and the growth slows down at some point. Implications for testing DT are explored.
p>Tujuan penelitian untuk mengetahui pengaruh teamwork dan time pressure terhadap affective commitment yang berdampak pada kinerja auditor BPK Perwakilan Provinsi Jawa Tengah. Variabel yang digunakan adalah teamwork dan time pressure sebagai variabel independen, kinerja sebagai variabel dependen serta affective commitment sebagai variabel intervening. Sampel yang digunakan adalah auditor BPK Perwakilan Provinsi Jawa Tengah yang berjumlah 100 responden, pengambilan sampel menggunakan purposive sampling. Metode pengumpulan data yang digunakan adalah kuesioner (angket). Pengolahan data menggunakan PLS. Analisis yang digunakan meliputi outer model, uji validitas, uji reliabilitas, inner model, dan uji hipotesis. Berdasarkan hasil analisis dapat diketahui bahwa teamwork dan time pressure berpengaruh terhadap affective commitment, time pressure berpengaruh terhadap kinerja tetapi teamwork tidak berpengaruh terhadap kinerja, dan affective commitment bukan sebagai variabel intervening hubungan antara variabel teamwork dan time pressure terhadap kinerja auditor BPK Perwakilan Provinsi Jawa Tengah. The aim of the study was to determine the effect of teamwork and time pressure on affective commitment which had an impact on the performance of the auditors in BPK Representative Office of Central Java. Variables used are teamwork and time pressure as independent variables, performance as dependent variable and affective commitment as intervening variables. The sample used was the auditor in BPK Representative Office of Central Java, amounting to 100 respondents, sampling using purposive sampling. Data collection method used is questionnaire. The analysis used includes outer model, validity test, reliability test, inner model, and hypothesis test. Based on the results of the analysis it can be seen that teamwork and time pressure have an influence on affective commitment, time pressure have an influence on performance but teamwork has no effect on their performance, and affective commitment is not an intervening variable of the relationship between teamwork and time pressure variable on the performance of the BPK Representative Office of Central Java Auditors.</p
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The role of effort and accuracy in the adaptive use of decision processes is examined. A computer simulation using the concept of elementary information processes identified heuristic choice strategies that approximate the accuracy of normative procedures while saving substantial effort. However, no single heuristic did well across all task and context conditions. Of particular interest was the finding that under time constraints, several heuristics were more accurate than a truncated normative procedure. Using a process-tracing technique that monitors information acquisition behaviors, two experiments tested how closely the efficient processing patterns for a given decision problem identified by the simulation correspond to the actual processing behavior exhibited by subjects. People appear highly adaptive in responding to changes in the structure of the available alternatives and to the presence of time pressure. In general, actual behavior corresponded to the general patterns of efficient processing identified by the simulation. Finally, learning of effort and accuracy trade-offs are discussed.
A model hypothesizes why decision makers choose different decision strategies in dealing with different decision problems. Given the motivation to choose the strategy which requires the least investment for a satisfactory solution, the choice of strategy should depend upon the type of problem, the surrounding environment, and the personal characteristics of the decision maker.
Consider the plight of an air-traffic controller choosing an altitude and course for an incoming flight, or a parent selecting a breakfast cereal during a hurried shopping trip accompanied by a cranky child. Although the consequences of these two decisions may vary, both decision makers face two potentially conflicting goals: (1) to make a good choice and (2) to reach a decision within a limited amount of time. Such choices illustrate the central topic of this chapter, the influence of time pressure upon decision making.
The study investigated participants' judgements of the defendant's guilt, severity of punishment and memory of information concerning a crime presented earlier, as a function of activated stereotype (positive versus negative) and cognitive load (i.e. self-paced versus quick processing pace). As hypothesized, it was found that judgement of guilt, punishment and memory were affected by the activated stereotype only under high-load conditions. Under these conditions, a negative stereotype of the defendant evoked higher estimates of guilt, harsher punishment and better memory of incriminating evidence than a positive stereotype, while there was no effect of stereotype valence in the low-load condition. Copyright (C) 1999 John Wiley & Sons, Ltd.
The chapter presents evidence consistent with the observations of Roethke and Vargas Llosa that introspection can be disruptive. The focus is on one type of introspection-thinking—the reasons for one's feelings. The chapter demonstrates that this type of thought can cause people to change their minds about the way they feel and lead to a disconnection between their attitudes and their behavior. It is clear that asking people to think about reasons will often produce attitude change, particularly for affectively based attitudes. The direction of this change, however, has been difficult to predict. The chapter explains people who think about reasons and end up with an attitude that is significantly more negative or positive, on the average, than the attitudes of control subjects. The direction of attitude change is difficult to predict, because it is closely related to the hypothesis about the generation of a biased sample of reasons. In the chapter, there are at least two sorts of harmful attitudes that might be changed by thinking about reasons—those that are undesirable from the individual's perspective and those that are undesirable from a societal perspective.
A theoretical framework is outlined in which the key construct is the need for(nonspecific) cognitive closure. The need for closure is a desire for definite knowledge on some issue. It represents a dimension of stable individual differences as well as a situationally evocable state. The need for closure has widely ramifying consequences for social-cognitive phenomena at the intrapersonal, interpersonal, and group levels of analysis. Those consequences derive from 2 general tendencies, those of urgency and permanence. The urgency tendency represents an individual's inclination to attain closure as soon as possible, and the permanence tendency represents an individual's inclination to maintain it for as long as possible. Empirical evidence for present theory attests to diverse need for closure effects on fundamental social psychological phenomena, including impression formation, stereotyping, attribution, persuasion, group decision making, and language use in intergroup contexts.
The present research was designed to examine the impact of temporal constraints on group interaction and performance. Thirty-six triads worked on one of two planning tasks under conditions of time scarcity, optimal time, or time abundance. Group interactions were videotaped and coded using the TEMPO system. Each group's written solution was rated on length, originality, creativity, adequacy, issue involvement, quality of presentation, optimism, and action orientation. Each proposal suggested during the interaction was rated on creativity and adequacy. Interaction process data showed that time limits were inversely related to the amount of task focus shown by groups. Performance data showed that the effects of time limits on group performance varied depending on what aspects of quality were considered. Process-performance relationships were also examined within each time condition. The findings are discussed in terms of an attentional focus model of time limits and group performance.