|
Items in cart [0] |
Questions? Call 888-624-8373 |
| Copyright © 2009. National Academy of Sciences. All rights reserved. Terms of Use and Privacy Statement |
Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 31
OI)UCI'IVI]Y IN THE SPACE STATION
Raymond S. Nickerson
~)I3tJCIION
Cat is productivity? How do we measure it, predict it and control it
on earth? To what extent can that knowledge be extrapolated to a space
con ~ c? What do we not know about productivity on earth that might be
found out--and is worth finding out--through research? How might the
expected findings be applied to space? How should the research be
directed to ensure its applicability to space? Are there important
questions about productivity In space that earth-based research is not
likely to held answer?
d
I wish I could promise to answer these questions here. Unhappily, I
cannot. These are the kinds of questions that I have had In mind,
however, in preparing this paper. In what follows ~ will focus first
on the notion of productivity and on how it has been measured and
manipulated in earth environments, and then turn to the question of
productivity in space, or more specifically, the Space Station. The
paper ends with a set of recommendations for research.
WED IS ~OOtJCr~?
Productivity is an elusive concept. It seems straightforward enough
when one begins to consider it. It is Gary to think about the
productivity of chickens or dairy cons in terms of eggs laid or milk
produced per unit time; here we are dealing with output in a very
literal sense. And it does not tax one's imagination to think about
comparing the output of the one producer with that of the other. To do
this we need a way to describe eggs and milk quantitatively in the same
terms. whichis not difficult. Since eggs and milk are valued as
foodstuffs, we could describe them both with respect to their
nutritional ingredients. But quantifying productivity only In terms of
output is not very useful from an economic point of view, and as it
relet== to chickens and cows as producers it would be grossly unfair to
the chickens; we must also take into account how much chickens and cows
consume IN order to produce a given amount of nutritive capital by
means of eggs and milk respectively. And to round out the picture we
must factor into the equation not only what the producers -at, but
31
OCR for page 32
32
other resources upon which the Or continuing production depends. To do
all this we may find it convenient, since not all the factors that must
be considered are nutritional, to quantify everything in monetary
terms. But this gives us no serious problem. The situation is still
fairly simple concepts ally: chickens and coos produce foodstuffs that
can be given a monetary value, and to do so they consume resources that
have a monetary cost; productivity can be thought of in terms of the
value of what is produced and the cost of producing it. This all makes
intuitive sense.
When one tries to apply the same type of thinking to human
productivity, one has no trouble as long as the human activity involved
is analogous to laying eggs and giving milk, in the sense of producing
tangible goods that can be Bled to satisfy basic human needs, and
consuming resources in the process of doing so. The picture gets Aces
clear quickly, however, when what is produced is not so
tangible--perhaps not even readily identifiable--and not easily
quantified in monetary terms. How does one measure the productivity,
for example, of the teacher, the scientist, the poet, the philosopher,
the salesperson, the physician, the corporate executive, the athlete,
the entertain~r—or the astronaut?
Lack of definitional precision has seldom been a great deterrent to
the use of words, and "productivity" is no exception On this regard.
It is a popular word in economics, and like "truth" and "keautv.~'
~ ~ ~ ~ __ _ . _= . _ = ~ = _ _ ~= . ~ _. ~ ~
, ,
,~l~l~ =~1~1 of mu=1 w == "~ -em, was amp- 1~ menu=. Within the
literature pertaining to space exploration, one finds references to
Increases in the productivity Of spacecraft crews resulting fans
charges ~ displays, control pry or other variables, but seldom
is it clear ~c~y ~t this means. the word is also seen ~ughout
ache human factors li~ture more generally; although Muckier (1982)
has changed that ache unconstrained way in which it is use here mans
; - c mar A; PP;~10 - ~ A;c~ ;~ ~ A;= ~~' =~
^. — &~ - ~' ~ =~ - - ~ ~11 ~1 ~''~ ~11~e ~ petit,
pr~uctivi~ is often use more or less as a synonym for performance;
if performance improves, by nearly any criterion, productivity is did
to go up; if performance degrades, productivity is said to go da an.
Sometimes the word is given a precise quantitative mean mg by virtue
of the variables that are involved in its measurement. Indices of
productivity are typically expressed as a ratio where the numerator is
some measure of output (what is produced or the value of same) , and the
denom m ator is some measure of input (what is amp up in the production
process or the cost of same). What constitutes input and output, and
how they are quantified, differs considerably frwu case to case,
however; and changes in productivity indices over time can sometimes be
difficult to Interpret (Badly, 1986). Moreover, often the word is used
as though it were intended to connote a quantitative entity, but there
is no clue as to what the input and output variables are or how they
could be measured.
go concepts that are closely plated to productivity are Chose of
Production and efficien - . ~uctivi~r implies production, or more
specifically, product arid pricer. Activity is an attribute of a
producer; and a producer, by definition, is one who prices
sc~thir~. At is product may be tangible (paper clips, a household
OCR for page 33
33
appliance, an airplane) or intangible (an educational service,
entertainment). A producer may be a person, a person-machine system, a
team, a factory, an industry, an economic sector (agriculture), a
nation, the world.
But although productivity and production are closely related
concepts they are not the same. AS we have noted, productivity is
usually expressed as a ratio of some measure of output or product value
to same measure of input or production cost, and the goal, in most
cases, is to make this ratio as high ~= possible. Production usually
refers only to output quantity. Given these connotations, it is Busy
to imagine production Increasing or decreasing independently of changer
in productivity. If, for example, a manufacturer produced 10 percent
more items in a given year than in the preceding year, but doing so
required a 15 percent increase in the number of employees, we might my
that production increased while the productivity of the employees
declined.
The concept of efficiency, like that of productivity, relates Output
to the resource consumed in obtaining it. Efficiency has to do with
getting the mast out of given resources; the challenge is to organize a
production process so as to munlmize wasted effort. A process is said
to be made more efficient when the unit costs of output are decreased
or when the consumption of a fixed amount of resources yields a greater
output than before.
Techniques for measuring the efficiency of assembly line workers
were among the earliest contributions of engineering psychology to the
manufacturing process and have been used expensively in the work
place. These have typically involved analyzing production tusks into
observable components. The development of tack-analysis techniques Hal
received considerable attention from human factors engineers (Van Cott
and Kincaid, 1972; Woodson, 1981~. Such techniques have been more
readily applied to psychomotor tasks than to basks that are primarily
cognitive in nature or even those that have major cognitive
components. Attention has been focused increasingly, however, on the
problem of analyzing cognitively-demandin; tasks, as an increasing
percentage of the tasks performed by people in the work force are
defined more by cognitive than by psychomotor demands.
We cannot hope to settle terminologies issues here. More Over,
definitions are of limited utility when dealing with terms that are
widely used, with a variety of connotations, within a field. For
present purposes, prcOuctivity will be taken to be very close, but not
quite identical, in meaning to efficiency. An entity (person, group,
system) will be considered highly prc*uctive when it uses its resources
to = advantage in accomplishing its goals. One can be efficient
in the sense of not wasting resources simply by using those resources
very sparingly, but that type of efficiency could be counterproductive
if resources are husbanded to the point of precluding getting the task
done. To be productive one has to use one's resources and use them
well.
As a working definition of productivity I will use: effective and
efficient use of resources in accomplishing a goal. The emphasis is on
both effectiveness and efficiency. A prc~uctive system is one that
OCR for page 34
34
gets the Intended job done and does so with a munlmum of wasted effort
and resources. I do not mean to split hairs here in making a
distinction between efficiency and productivity; if one's idea of
efficiency incorporates effectiveness, then ~ see no objection to
thinking of efficiency and productivity as more or less synonymous.
Effort and rescuracs can be wasted as a consequence of many factors,
such as poor training, lack of motivation, mismanagement, faulty
organization, mlsscheduling, and a host of others. Productivity will
be said to increase when either more is accomplished with no increase
in consumed resources or the same objectives are attained with a
smaller expenditure of resources.
These are still somewhat imprecise notions, but not so imprecise as
to be useless. In the Space Station context, as elsewhere, when
modifications in design or operating prcce~ures have big effects on
productivity, there probably will be no difficulty in getting a
consensus that productivity has really been improved. When Masks are
performed more easily, more reliably, and with fewer costly errors,
most interested observers will probably be willing to describe what has
happened as an increase in productivity, and even if not, they a ~
likely to agree that changes for the better have occurred. It seems to
be generally assumed, if only tacitly, that anything that improves
human performance (increases speed, accuracy, reliability) probably
Increases numan pro~uct~v~y. This appears to me to be a reasonable
assumption, and a very useful one. Frequently in this paper, the
discussion focuses on variables that influence performance, the
justification being the assumption that what affects performance for
better or worse will affect productivity in a comparable way.
ASSESSING PRO WCTIVITY
It is helpful in the present context to distinguish between the problem
of determining what the level of productivity is at any given time and
that of determinirg Nether pr~uctivi~ is Wing, or has Carded.
One might assume that the second prowlers is more clifficult than the
first, inasmuch as a = of ~e, or difference, is derived frmn
the more fi~nt=1 measure of absolute value: to determine whether
pr ~ uctivi~r is rare or less this weak than it was last, one simply
takes the difference between this week's measure an] last week's. But
this is so only if one wishes to know the magnitude of the difference.
If one is content to know only the direction of the difference, it may
not be necessary to know the individual magnibudes, at least if the
magnitude of the difference is relatively large. One does not have to
know the precise weight of each of two objects to know which one weighs
more, especially if the difference is siz-=hie.
Productivity as a Percentage of Capacity
~uctivi~ is sometimes quantified In terms of performance relative
taxing. Centesis done, maxi~outputorperformanceis~
OCR for page 35
35
as the starers against which to evaluate the actual output or
performance, whether the performer is an individual, a system (say a
factory), or an economy. Thus one might encounter the claim ~t the
pr 0uctivit~r of a given industry In a particular region is currently at
about 70 percent, which would mean that that industry is operating at
70 percent of what, under certa m assumptions, is the maximum
possible. Economists often refer to how close to capacity factories
and other manufacturing facilities are operating. The ability to
specify hew close to capacity some entity is operating presupposes a
metric in terms of which to quantify the operation. Determining what
constitutes maximum capacity can sometimes be a complicated and
controversial pr Mess. Further, maximum must be understood as maximum
within a particular context. The maximum output of a given factory,
for example, could mean maximum obtainable with the present tooling,
layout, manpower and stock; alternatively it could refer to what would
be obtainable if one or more of these constraints on output were
relieved.
As applied to individual human beings, capacity con not== the best
(which often, but not always, equates to most) one can do ~ a given
situation, the limit of human performance--or, more accurately, the
limit of the individual performer. Conceptually, there are two ways to
determine capacity in any given instance: one is to derive it free
theoretical considerations; the other is to measure performance under
ideal conditions. Neither works very well. While information theory
once provided a basis for the hope of defining capacity theoretically,
it prayed to be a false Elope, and psychologists have not yet found or
developed an alternative that can do the job. Ideal conditions for
performing a given ta~k--which Mold have to include an optimally
motivated performer--have proved also to be easy to conceptualize but
difficult if not impossible to actualize.
Differential Productivity
Differential productivity in a business context is sometimes measured
in terms of changes In the number of employees or amount of employee
time required to get a fixed amount of work done, or conversely by
changes in the amount of work accomplished by a fixed staff. Thus a
retail company is said to have doubled the productivity of its bill
collection departments when it managed, by computerizing its operation,
to place the same number of reals with a 50% reduction in staff. And
the productivity of an insurance company is described as increasing
fivefold when the number of policies issued per employee per year
increased by a factor of five (Bower, 1986~.
Studies of individual human productivity In specific job situations
have often focused on the performance of individuals relative to the
performance of other individuals on the same task. It is possible to
say that A is more productive than B without saying anything very
precise about how productive eight individual is relative to a larger
frame of reference. Measures of white-collar productivity typically do
not yield absolute quantities, but do permit comparisons among similar
OCR for page 36
36
organizations (Drucker, 1986).
In the Space Station program, attention will probably be focused
primarily on differential productivity (the cost of attaining some
production objective in space relative to that of obtaining it on
Perth; or the cost at one time relative to that at another). While it
would be interesting to be able to relate productivity to some
theoretical maximum in this context (e.g. by relating production to
some measure of capacity), it is not clear how to do that.
Fortunately, it is not necessary to be able to quantify maximum
productivity in order to determine whether one is moving toward or away
from it.
That is not to suggest that assessing differential productivity is
likely to be an easy task. Several investigators have commented on the
variability of measurements of productivity, especially those that
relate to individual'' human productivity, and on the resulting need to
make many measurements over a considerable period of time if reliable
numbers are to be obtained (Muckier, 1982~. It is especially difficult
to measure productivity in intellectual tasks, inasmuch as methods for
assessing cognitive performance are not well developed. When a person
is staring cut of his office window, it may be impossible to tell
whether he is idly daydreaming or is engrossed in "productive"
thought. And even if he were known to be daydreaming, it would not
follow necessarily that that time was lost from a productivity point of
view. One widely held view of p,~blem-solving distinguishes an
"incubation" period in the problel`-solving process during which
progress is made on a problem in spite of--perhaps because of--the fact
that the individual is not consciously focusing on the problem to be
solved and there are numerous examples of scientists and other
thinkers reporting insights that have occurred when they were not
actively engaged in working on the problem.
Whatever methods are developed for measuring productivity must take
guality--as well sac quantity--of output or work into account in some
way. In manufacturing operations, product quality affects measures of
productivity to the degree that items that fail to meet a preset
standard become rejects. The importance of quality control in this
sense is obvious and the difficulties that some industries (e.g. the
manufacturing of computer microchips) have had are well known. this
type of linkage between quality and quantity is a fairly gross one
however. Differences ~ quality tend to be ignored so long as the
quality is not sufficiently low to necessitate rejection. In
nonmanufacturing activities the relationship between quality an]
quantity is even more tenuous, in spite of the fact that here one might
expect qualitative dif^=erenm~s In output to be both large and
important. Quality will certainly be an important consideration in the
Space Station context. m e quality of the experiments that are done,
for example, will be at least as important as the number.
OCR for page 37
37
Workload and Its Assessment
In a complex system the operation of which deperxis on functions
performed bar both people end machines and, especially, by people and
machines in interaction, high productivity will rehire that workloads
be at or near c ~ imal level. Significant overload will r educe
productivity through increases in the frequency of human error;
significant underload will mean wasted rcsawrocs at best and possibly
direct negative impact on productivity resulting from boredom,
inattentiveness or other diffim~1 ties arising from feelings of being
underutilized or unimportant to the operation. Workload and its
assessment will be important considerations, therefore, in efforts to
understand, measure, or control productivity In space.
As in the case of efficiency, the workload carried by an individual
is much easier to measure when the task is primarily physical than when
it has major cognitive components. As Wierwille et al. (1985) point
out, a major consequence of the increasing automation of modern systems
is a shift in the role of the human cgerator away face. manned control
and toward monitoring and performance evaluation, and this Hal
complicated considerably the problem of quantifying the operator's
workload. How can we hope to determine how har5--how close to
capacity an individual is working when most of what he is doing is
ment=1 activity that is not directly observable?
The measurement of mental workload has been recognized by human
factors researchers as a major challenge to the field and this
recognition has stimulated considerable activity (Chiles and Alluissi,
1979; Eggemeier, 1980; X~lsbeek, 1968; R bray, 1979; Parks, 1979;
Sheridan and Simpson, 1979; Singleton et al., 1971; Williges and
Wierwille, 1979~. Work in the area is still in the exploratory and
formative stages, however, and there has not yet emerged a theory or
even a widely agreed upon set of concepts and measurement procedures
that are needed to provide a sense of stability and coherence.
An indication of the magnitude of the problem and of the current
status of work on it is provided In the Proceedings of a NATO
Conference on Month Workload published In 1979. Johannsen (1979:3)
cpened the conference with the observation that "there exist too many
conflicting ideas about the definition and measurement of workload",
and expressed the hope that the conference would produce a consensus
among participants on a definition and on a procedure for workload
assessment. In his preface to the conference prcocedings, Moray
(1979:VIII), the organizer, acknowledged that these hopes were not
realized, but noted that participants from various disciplines did come
to "very similar Inclusions about the validity, usefulness, ark
promise (or lack of each) for a wide variety of methods for approaching
the assessment of workload in the human operator". It is unfortunate
that the proceedings does not contain a summary of these conclusions.
It does contain, however, a report from each of five participant
groups, classified an experimental psychology, control engineering,
mathematical modelling, physiological psychology and applications.
m e experimental psychologists summarized the fir conclusions this
way: " m e concept [mental workload] reflects a genuine dimension or
OCR for page 38
38
dimensions of human experience in daily work...it is a concept
absolutely required for the adequate analysis and description of such
hanks Flasks that are not necessarily physically demanding but that are
experienced as exhausting and stressful nonetheless] and for
predicting, at the design stage, the future performance of such
[automatic and semi-automatic man-machine] systems... On the other
hand the concept is at present very ill-def~ned with several probably
a; c0; ~~ maim; ~=
~1~- `~ an... There is no satisfactory theory of 'mental
workloads' (Johannsen et al., 1979:101). Johannsen et al stress the
multidimensional nature of workload, and deny the appropriateness of
trying to quantify it as a scalar variable. They specifically rule cut
the possibility of meaningfully comparing different tasks with respect
to workload, except when the tasks are very similar in structure.
The conclusions drawn by the experimental psychologists in the NATO
workshop clearly caution against any expectation that the problem of
workload measurement will be resolved soon. They are equally clear,
however, ~ supporting the view that workload is an essential concept
if we are to understand the role of human beings in mcdern systems and
design tasks that impose reasonable demands on their capabilities. It
could prove to be an especially important concept in the context of the
Space Station because of the unusual cognitive demands that that
environment will represent. A detailed under standing of those
demands insofar as possible in anticipation of the depicyment of the
station ~ surely must be a primary objective of the human factors effort
In this program.
One of the approaches that has been used to identify performance
measures that are sensitive to workload has been to take a variety of
cancli~te measures in situations in which workload is intentionally
varied and SCQ which of then vary with workload manipulation (I i
arm Wierwille, 1983; Hicks arx] Wienville, 1979; Wierwi1le arm Connor,
1983; Wier~rille et al., 1985~. =dh of this work has beer done in
flight simulators. Candidate n ~ sates that have been studied include
opinion scales (subjects' ratings of the task in terms of specified
descriptors), physiological measures (heart rate, respiration rate,
pupil diameter, eye-blink frequency, eye-fixation fraction), measures
of performance on secon ~ tasks (time estimation, tapping
regularity), and measures of performance on the primary task. A
limitation of this approach is that viable measures, at best, reflect
difference= in workload; they do not provide an indication of how herd
or how clod to capacity one is working in any particular case.
Many of the sues of pilot workload have made use of post flight
questionnaires. ~ Ruse this approach is heavily dependent on memory,
Rehmann et al. (1983) explored the possibility of having subjects
report how hard they are working periodically while performing a tank.
Workload judgements did change in this case with controlled changes in
task difficulty, but this measurement technique has the disadvantage
that it could interfere with the performance of the primary back,
especially when the latter is very demanding.
The intrusiveness of the measurement
process has been a major
drawback of many approaches to workload assessment, and especially
those that make use of a secondary back (Rolfe, 1971; for a summary of
OCR for page 39
39
nearly 150 sties using sorry tasks see Ogden et al., 3979~. One
way ~ avoid the use of an intrusive task arx] also dependence on ache
subject's merry is to monitor physiological indicants of workload that
can be darned automati~A.]ly. Israel et al. (1980) have argued that
some of the ~ysiologim=1 measures that have been tried; ~ vanic skin
response, heart rate variability, and pupil diameter reflect changes in
autonomic nervoll,= system activity and so are sensitive to changes in
emotional state independently of their origin. As a physiological
measure that is more likely to be indicative unambiguously of Wharves
in tile cognitive Innards of a bask, they propose the everlt-related
brain potential and, in particular, its Iate positive or p300
eminent. Widens (1979, also has argued for the use of evoked
~ , _
__ ~_~ _~ _ TO ~ ~l _~ fit ^~\ ~ ~ =~_ O~ ~~ ~~_~
pO`ell~lals . Reseal en ad . t 11:1UUJ presently coma [LIEU one e~er~nc
supporting the idea that this measure does vary with task demands and
that obtaining it need not interfere with the primary task. While it
would be imprudent to conclude from these data that
electro-physiological monitoring of workload will be effective in the
Space Station, the possibility deserves further exploration.
Varying workload for experiments purposes is probably not feasible
within the Space Station context, or at least the amount of this type
Of experimentation that can be done will probably be very limited. It
will be essential to attempt to have workloads be as close to ideal as
they can be made freon the very beginn mg. Of course when evidence
indicates that an initially established workload is not ideal, the
workload should be changed ~ the indicated direction, and keeping
track of such changes can provide some of the data that would have been
obtained from controlled experimentation. The goal must be to minimize
the need for such changes, however, which requires being able to
predict the effects of different workloads from data obtained In earth
environments.
DEIERMINPNTS OF PRO WCTIVITY
Ah ~ e seems to be a consensus among investigators that productivity is
a function of many variables, and that attempts to affect it that focus
on one or a small subset of those variables and ignore the others run
the risk of doing more harm than good (MucX1er, 1982; Sutermeister,
1976). Among the determinants of productivity that would ~ ve to be
included In any extensive list are the following.
Human Capabilities and Limitations
A great bead of information has been compiled about human Capabilities
and limitations and is available in various engineering psychology
handbooks. What is known in this regard clearly sets bounds on what
~ . . ~ ~ . ~ . . . ~ ~
numan ne logs Ln general can he expected to co In SpeCl~lC rack
situations. Individual differences are also germane to the question of
human productivity. People differ widely with respect to both physical
and mental capabilities, and the productivity of individuals is bound
OCR for page 40
40
to vary with the degree to which then' individual capabilities match
the demands of specific Basks. Aptitude testing and job screening and
selection procedures are based on these assumptions.
Task Demands
Evidence supports the intuitively appealing idea that people work best
when the demands upon them are neither too great nor too small. This
is one form of the "in verted-U hypothesis" regarding the relationship
between workload and performance, which holds that performance of a
given task is optimal for a workload level that is ~~ermediate between
one that is excessively Hugh and one that is so low as to promote
ha,... fM~ I h 1~:~ . W^1 If:_ 1 C)7~2 1 C)7A ~
_~. `~-~_~, An_' I_ ~~, '=~. The detrimental effects
of overloading are somewhat better documented than are those of
underioading (Weiner, 1975; Weiner et al. 1984~.
The possibility that
underioading can affect performance negatively takes on special
significance, however, in the context of systems in which humans
function primarily as supervisors of automated processes.
Motivation
One can hardly doubt that motivation affects performance. It Is cI-a
In particular that performance suffers when motivation is very low.
What is less clear is how performance is affected when motivation
bed untruly high. Merest in = ~ motivation that is
relatively law at We outed will at certainly lead ~ i~pr~ed
performance, but what has - ns when motivation that is arcade very high
is mcreas ~ still further? Is there such a thing as trying too hard?
Wanting too badly to succeed? Some investigators believe there is, and
that when motivation is extremely high it has a debilitating effect.
This is another form of the inverted-U hypothesis mentioned above;
except that in this case the performance determinant of interest is
motivation rather than task demands. It may be that the detrimental
effects associated with Motivation becoming too high are better
attributed to anxiety over the possibility of failing; fear, especially
den it beds panic, unsubtly can cause performance to
deteriorate. Ac cording to thin vicar, if privation becalms arbitrarily
high but is not accompanied by such fur, we Ward not nosily
expect perforate to fall off. The distir~tion between very high
motivation and fear of failure may be an important one in the Space
Static context; it scud be helpful ~ have a better understarxlir~ of
the rules of these variables as determinants of pr~Ctivi~r and
performance.
Physiologic State
Fatigue has lord been recognized as a factor in ricing proclivity
in many settings (Simpson and Weiser, 1976). indeed it he been
OCR for page 41
41
defined Operationally as a decrease In performance as a corpulence of
pronged activity (~lsb~k, 1971~. Math of the resort on this
topic has focus on the problem of schooling rest breaks in such a
way as to minimize fatigue (Bechtold et al., 1984; <;anaro and Bechtold,
1985~. The tasks involved in these studio have often been physically
strenuous and the results are of limited applicability to tasks that
are primarily cognitive in nature. Exceptions include sties of the
performance of aircr~rs over extended periods (Carmen, 1971, 1973~. A
major question of relevance to productivity in the Space Station is how
productivity might be affects by the various physiological effects
that can be expected from prolonged living ~ the Space Station
environment. Little is yet known about the physiological consequence-=
of living in such environments for longer than a few weeks at a time.
Training
Performance, especially of complex Basks, obviously improves with
training and practice. An aspect of the relationship between training
and performance that is especially important relative to the Space
Station context has to do with the obscuring of differences by ceiling
effects. The fact that one has, through practice, gotten to the point
of being able to perform a Desk without error is not compelling
evidence that one has really mastered the task. The true test may come
when that task must be performed under stress or in concert with
competing demands on ones resources. To make the point another way,
the fact that boo people perform a given bask equally well under
acoommo~atlng conditions is not good evidence that they will perform it
equally well under stress.
Capabilities and T.;m~tations of Machines
Just as the capabilities and limitations of the humans in a complex
system help determine the productivity of the system as a whole, so do
the capabilities and limitations of the machines involved. Unlike the
capabilities of human beings, those of the machines that are available
for use In the Space Station can be expected to evolve even over the
next few derides. Initial plans for the use of technology in the
Station take this fact into account. Plans to use artificial
Lnt~lligence, for example, explicitly note the unlikelihood that this
technology will be used extensively for operational purposes during the
initial years of the program. However, provision is being made for its
incorporation as the technology matures to the point of being reliably
applicable. We would expect that as machine capabilities are extended
and improved, a major consequence would be increased productivity of
the Space Station as a whole. Nether this proves to be the case and,
if so, exactly how rein to be seen.
OCR for page 71
71
modifying that model contritely as further relevant data are
obtained, esE^:ially from e~rien~ ~ apace. Conditions in
space exploration will charge and the durations of says In
Apace will Ink ~ se, so the mcdel will have to evolve to
acocmrodate those changes. On the assumption that the changes
that Drier will be evolutionary and relatively continue us, one
can hope for a model that is highly predictive of the situation
that is current at any given time and reasonably predictive of
the situation as it is anticipated to be in the n-~r-term
future.
m;~;rIc:F~
AXerstedt, T., and Gillberg, M.
1981 Sleep disturbance and shift work. In A. Reinberg, N. Vieux,
and P. Andlauer, eds., Night and Shift Work: Biological and
Social Aspects. Oxford: Pergamon Press.
Baily, M. N.
1986 What has happened to productivity growth. Science
234:443-451.
Bechtold, S. E., Ganaro, R. E., and Sumners, D. L.
1984 Maximization of labor productivity through Optimal
rest-break schedules. Management Science 30:1442-1458.
Berry, C. A.
1969 Preli ~ clinical report of the medical aspects of
Apollos VII and VIIT. Aerospace Medic me 40:245-254.
1970 Summary of medical experience in the Apollo 7 through 11
mart spaceflights. Aerospace Meclicme 41:500-519.
Bawen, W.
1986 The pure payoff freon office Muters;. Fortune 5:20-24.
advent, D. E.
1971 Decision art Stress. Near York: Academic Press.
Backfield, C. A.
1965 Isolation, Clinical and E~riment~1 Approaches. New York:
Barton House.
Cameron, C.
1971 Fatigue problems in modern ir~ustry. Ergona~nics 14:713-720.
1973 A theory of fatigue. Ergonc~mics 16:633-648.
Hi, J. G., and Wierwille, W. W.
1983 A Orison of rating scale, se~rx~ary task, physiological,
and primary-task workload estimation ~hniqu~s in a
simulated flight task Sizing ~nications load.
Oman Factors 25 (6~: 623-641.
OCR for page 72
72
Somali, J. G., and Wierwille, W. W.
1983 A cc mparison of rating scale, secon~ary-task, physiological,
and primary-~ck workload estimation techniques in a
simN1ated flight task emphasizing communications load.
Human Factors 25~6~:623-641.
Chaudhari, P.
1986 Electronic and magnetic materials. Scientific American
255~4~:136-144.
Chiles, W. D., and Allu~si, E. A.
1979 On the specification of Operator or occupational workload
with performance-mYasurement methods. Human Factors
21:515-528.
Clearwater, Y.A.
1985 A human place in outer soace. Psychology Today 7:34-43.
Clearwater, Y. A. and Kaspar, P.
1986, Humanizing space. Professional Careers. 10/11:5-8.
Cobb, S., and Rose, R. M.
1973 Hypertension, peptic ulcers and diabetes ~ air traffic
controllers. Jcurnal of the American Medical Association
224:489-492.
Crump, J. H.
1979 A review of stress in err traffic control: Its measurement
and effects. Aviation Space and Environmental Medicine
50:243-248.
Danaher, J. W.
1980 Human error in AIC system operations. Human Factors
22(5):535-S45.
Dray, S. M., Ogden, W. G., and Vestewig, R. E.
1981 Measuring performance with a menu-selection human computer
interface. Pp. 746-748 in Proceedings of the Human Factors
Society 25th Annu21 Meeting
.
Drucker, P. F.
1986 ~ e Frontiers of Management. New York: Truman Talley Books
Eason, R. G. and Harber, M. R.
1972 Sensory, perceptual, and motor factors. Human Factors in
rorx~-Duration Spaceflight. Washington, DC: National
Academy of Sciences.
OCR for page 73
73
Eggemei~r, F. T.
1980 Some current issues in workload measures nt. Pp. 669-673 in
Proceedings of the Human Factors Society 24th Annual
Meeting.
Ehrenreich, S. L.
1981 Query languages: Design recommendations derived from the
human factors literature. Human Factors 23(6):709-725.
Fidell, S. A.
1977 -~~ ~
Effects of stress on performance. The C- System User Vol
I: A Review of Research on Human Performance as it Relates
to the Design and Operation of Command, Control, and
Fornication Systems. ~ Report 3459.
Flakelman, J. M., and Kirschner, C.
1981 ~
An information-pr~cessing ~nterpr=tation of air traffic
control stress . Iran Factors 22 ( 5 ) : 561-567 .
Fitts, P. M. (Ed. )
1951 Iran Engineering for an Effective Air-Navigation and
~raffic~ontrol System. Columbus, OH: Ohio State
Un~versi~ F~r~ F~ation.
ser. T. M., ~ try, D. E., Adey, W. R., ark Gala ~ as, R.
1972 Physiological and Medical Factors. Human Factors ~
Long-Duration Spaceflig ht. Washington, DC.: National
Academy of Sciences.
Ganaro, R. E., and Bechtold, S. E.
1985 A study of the reduction of fatigue impact on productivity
- through optimal rest break scheduling. Human Factors
27:459-466.
Garriott, O. K.
1974 Skylab report:
186:219-225.
M~n's role in space research. Science
Garriott, O. K., Parker, R. A. R. Lichtenberg, B. K., an] Merbold, U.
1984 Payload crew members' view of Spacelab operations. Science
225:165-167.
Ginliano, V. E.
1982 The Mechanization of Office Work.
247:(3)148-164.
Gunderson' E; K. E. (Ed.)
1974 Human Adaptability to Antarctic Conditions.
American Geophysical Union.
Scientific American
Washington, DC:
OCR for page 74
74
Gunderson, E. K. E.
1963 Emotional symptoms in extremely isolated groups. Archives
of General Psychiatry 9:74-80.
GunJerson, E. D. E. and Nelson, P. D.
1963 Adaptation of small groups to extreme environments.
Aerospace Medicine 34:1111-1115.
Gunn, T. G.
1982 The mechanization of design and manufacturing.
American 247:~3~114-130.
Halley, A. H.
1968 Airport.
Scientific
New York: Doubleday and Company.
Haythorn, W. W., and Wrath, J. J., and Hollander, E. P., and Latane,
B
· .
1972 GrcNp processes and interpersonal interaction. Human
Factors in Long-Duration Space flight. ~~ ~~
National Academy of Sciences.
Washington, DC.:
Hicks, T., and Wierwille, W.
1979 Cc mparison of five mental workload assessment procedures in
a ~ inq-base simulator. Human Factors 21:129-144.
Holmes, D. S., and Roth, D.
1985 Association of aerobic fitness with pulse rate an]
subjective responses to psychological stress.
Psycho physiology 22(5):525-529.
Howard, R. D., Miller, R. H., Minsky, M. L., and et al.
1982 Space Analications of Automation. Robotics and Machine
Ihtelliqance Systems (ARAMIS).
Phase I, Structural Assembly
Expansion. Volumes 1-5, Space Systems laboratory and
Artificial Intelligence Laboratory, SSL Reports #2S-82 -
#29-82, Massachusetts Institute of Technology, Cambridge,
-
Isreal, J. B., Wickens, C. D., and Chesney, G. L.
1980 The event-related brain potential as an index of
display-mon~tor m g workload. Human Factors 22(2):211-224.
Jchannsen, G.
1979 Workload and workload measurement. Pp. 3-11 in N. ~bray,
ea., Mental Workload: Its Theory and Measurement. New
York: Plenum.
OCR for page 75
75
, Pear, R., Rasmussen, J., Sand~s , A., and
J~arms~, G., Mbray, N.
wicks, C.
1979 Final report of e~rimen - 1 psychology group. Pp. 101-114
in N. ~ray, ea., Mental Workload: Its lheor~r and
asu~t.
New York: Plenum.
Jason, L. C., Williams, H. L., and Stern, J. A.
1972 Privation, Ignition, and slec~p~rk factor; cen~-arxt
autonamic-ners s-system indices. E ~ an Factors in
Long-Duration Spaceflig ht. Washington, DC.: National
Academy of Sciences.
Jones, E. R., Chiles, W. D., and Voas, R. B.
1972 Human factors and operational requirements. Human Factors
in Iong-Duration Spaceflight. Washington, DC.: National
Academy of sciences.
JSC
1979 Space Operations Centers A Concept Analysis. JSC-16277.
NASA/Johnson Space Center.
X~lsbeek, J. W. H.
1968 Measurement of Tenth work an] of acceptable work: Possible
applications in industry. International Journal of
Production Research 7:33-45.
1971
Sinus arrhythmia and the dhal task method ~ measuring
mental load. In W. T. Singleton, J. G. Fox, and D.
Whitfield, eds., Measurement of Man at Work. London:
Taylor and Francis.
Kennedy, R. S.
1972 A Bibliography of the Role of the Vestibule Apparatus Under
Water and Pressure: Content-Oriented and Annotated.
M4306.03.5000~, Naval Medical Research Instib~te Report
No. 1.
Bessel, C. J., and Wi~ns, C. D.
1983 The transfer of failure~etection skills between monitoring
and controlling Comic systems. Ran Factors 24~1~:49-60.
Kirk, K. R., and preen, M. N.
1982 E~crav~hicular Mobility Unit.
Ser~rir=s Workshop 1:44-72.
NASA-JSC-18201. Satellite
Lazarus, R. A., ark Monat, A.
1977 Stress ark coping—Some current issues ark controversies.
In A. Monat and R. S. Iazarus, eds., Stress ark coping. New
York: Columbia University Press.
OCR for page 76
76
To=, E., and McGregor, J.
1985 Mimic ~ Sew ti~ ~ MU retied ~s~.
Human Factors 27 (2~: ~ 57-162 .
Le~renthal, H., arxi Lir~sley, D. B.
1972 Subjective static. Human Factors in Long-~tion
Spaceflight. Washir~on, DC.: National Academy of Sciences.
sley, D. B., ark Jones, E. R.
1972 Physical factors. Mean Factors in Lor~-Du~tion
Spaceflight. Washington, DC.: Nations Academy of Sc:ier~ces.
Fetus, J. P., Jr., Bored, R., ark Patton, R. M.
1982 Astronaut activity. Workshop Exceedings: Space Mean
Factors, 1, T - Erg, VA, II—28—II—64 .
Wrath, J. J.
1965 Performance sharing in an allH;o~visual vigilance task.
Mean Factors 7:141-153.
Miser, D.
1966 Human factors In reliability. In W. G. Ireson, ea.,
Reliability Handbook. New York: M=raw-Hill.
Miller, D. P.
1981 Depthybreadth tradeoff ~ hierarchical pu'cer ~ll-C
P~i~s of ache mean Factors Society Inch Anne
Meeting. Santa Monica, CA: Man Factors Society.
Montemarlo, M. D., and Cron, A. C., eds.
1982 Space ran Factors Workshop, voles 1 are 2. Office
of Aeronautics and Space Technology ~ST, Code ~H-6,
Walton, DC.
~ray, N.
1979 Preface. Pp. V-VIII In N. Mbray, ea., Mental Workloac]: Its
Theory and Mbasur~r~t. Near York: Plan.
Suckler, F. A.
1982 Evaluating pnxtuctivity. In M. D. Emmett and E. A.
Flei~n, 0~., Mean Performance arm ~ctivit:,r, Sol. 1,
Mean Capability Assessment. Hillside N.J.: L. Erratum
Associates.
NASA-ASK E:
1985 Autonomy and human element ~ pace. Proceedings of the
1983 ~SA/ASE:E: SO Faculty Workshop at Stanford
University.
National Commission on Space
1986 Pion~rir~ the Space Frontier. N - r York: Bantam Books.
OCR for page 77
77
Nickerson, R. S.
1986 Using Computers:
Human Factors
Information Systems. MIT
PŁ~5S (Bradford Books).
Nickerson, R. S. and others
1984 Research Neat= on the Interaction Between Information
Systems and their Users: Report of a Workshop. Washington,
DC: National Academy Press.
Norman, G. R., MbFariane, A. G., and Strainer, D. L.
1985 Patterns of illness among individuals reporting high and low
stress. Canadian Journal of Psychiatry 30(6):400-405.
Ogden, G. D., Is vine, J. M., and Eisner, E. J.
1979 Measurement of workload of secondary tasks. Human Factors
21:529-548.
Parks, D.
1979 Current workload methods and emerging challenges. In N.
Mbray, ea., Mental Workload: Theory and Measurement. New
York: Plenum.
Price, H.E.
1985
The allocation of functions in systems.
27:33-45.
Human Factors
Price, H. E., Chicano, R. E., and Van Cott, H. P.
1982 The Allocation of functions ~ M~n-~ch~ne Systems: A
Perspective and Literature Review. NUREG-CR-2623, Oak
Ridge, TN: Oak Ridge National Laboratories.
Price, H. B., and Pulliam, R.
1983 Control room function allocation - A need for men-co muter
symbiosis.
Dover Co:
Engineers.
Proceedings of the 1982 1~:~ Computer Forum.
Institute of Electrical and Electronic
Rehmann, J. T., Stein, E. S., and Rosenberg, B. L.
1983 Subjective pilot workload assessment. Human Factors
25(3):297-307.
Rolfe, J. M.
1971 The secondary task as a measure of mental load. In
W. T. Singleton, J. G. Fox, and D. Whitfield, eds.,
Measurement of Man at Work. London: Taylor and Francis.
Schultz, D. P.
1965 Sensory Restriction: Effects on Behavior. New York:
Academic = - s.
OCR for page 78
78
Sc~hwab, E. C., N~amn, H. C., and Pisoni, D. B.
1985 Sew effects of training on Mae perception of synthetic
Oh. Human Factors 27(4):395-408.
Sells, S. B., arm G~l~;on, E. K.
1972 A social system approach to lore - oration missions. Oman
Factors in Long-~ration Spaceflight. Wa~ir~ton, DC.:
National Academy of Skiers;.
Sheila, P., and Salably, G.
1985 ~ act of dep1:h of menu hierarchy on performance
effectiveness In a supervisory Cask: Ccmputerized flexible
manufacturing system. Human Factory 27~6~:713-722.
Sharit, J., and Salvendy, G.
1982 Occupational stress: Review and reappraisal. Human Factors
24~2~:129-162.
Sheridan, T .B., and Simpson, R. W.
1979 Tc ward the Definition and Measurement of the Mental Workload
of Transport Pilots. Flight Transportation Man-~achine
Laboratory, Technical Report No. DOr-06-70055. Cambridge,
MA: MIT.
Simon on, E., and Weiner, P. C., eds.
1976 Psychological Aspects and Physiological Correlate= of Work
and Fatigue. Springfield, IL: Charles C. mamas.
Singleton, W. T., Fox, J. G., and Whitfield, D., eds.
1971 Measurement of Man at Work. Lan don: Taylor and Francis.
- Small, D. W., and Weldon, L. J.
1983 An experimental comparison of natural and structured query
languages. Human Factors 25~3~:253-263.
Smith, S.
1969 Studies of small gram In conf~nemnt. In J. P. Z0bek,
ea., Sensory Deprivation: Fifteen Years; of Research. New
York: Appleton Century~fts.
Smith, R. P.
1981 Boredom: A rapier. Oman Factors 23(3):329-340.
Sutermeister, A.
1976 People and Pr~cti~rity. 3rd. - ;tion, N - r York:
M~;raw-Hill.
Swain, A. D.
3970 Devel~nt of a Oman Ever Rate Data Bank. Sandia
Corporation Report SC-R-70-4286, A~uq~e, Ha: Sarx~ia
Corporation.
OCR for page 79
79
1978 Estimat mg Human Error Rates and their Effects on System_
Reliability. Sandia Corporation Report SAND77-1240,
Albuquerque, NM: Sandia Corporation.
Taylor, F. W.
1947 Scientific Management. New York: Harper Brothers.
m iel, E. D., and Xurtzman, C. R.
1983 Space Applications of Autcmation, Robotics and Machine
Intelligence Systems (ARAMIS). Fhase II, Telepresence.
[1-3], SSL Reports #30-83 - #32-83, Space Systems Laboratory
and Artificial Ihtelligence Laboratory. Cambridge, MA: MIT
Tilley, A. J., Wilkinson, R. T., and Drud, M.
1981 Night and day shifts compared ~ terms of the quality and
quantity of sleep recorded in the home and performance
measured at work: A pilot study. In A. Reinberg, N. Vieux,
and P. Andiauer, epic., Night and Shift Work: Biological and
Social Aspects. Oxford: Pergamon Press.
Tilley, A. J., Wilkinson, R. T., Warren, P. S. G., Watson, B., and
Drud, M.
1982 The sleep and performance of shift workers. Human Factors
24(6):629-641.
VanAllen, J. A.
1986a Myths and realities of space flight. Science
4754:1075-1076.
1986b Space science, space technology and space station.
- Scientific American 254~1~:32-34.
VanCott, H. P., and Kincaid, R. G., are.
1972 Human Engineering Guide to Equipment Design. Revised
Motion. Spo ~ ored by the Joint Army-Navy-Air Force Steering
Committee, U.S. Department of Defense. Washington, DC.:
U.S. Government Pr toting Office.
Weiner, E. L.
1975 C>n si~tanec~us monitoring and trucking. Jourr~1 of Applied
Psychology 60: ~ 00-105.
Weiner, E. L., Curry, R. E., arm Faustian, M. L.
1984 Vigilance and task load: ~ search of the invert U.
Ivan Factors 26:215-222.
Welford, A. T., ed.
1974 In lJTYi~r Stress. New York: John Wiley and Sons.
Welfo~, A. T.
1973 Stress and performance. Ergonamim~ 16:567-580.
OCR for page 80
80
Weybrew, B. B.
1961 Mean factors arxlworkenvirorment. II. Ibe i~actof
isolation Won personnel. Journal of Occupational Medicine
3: 290-294.
1963
Psyc~hological problems of prolorx~ec] marine su~ence.
Pp. 87-125 in N. Moms, R. ~a~rs, ark E. Healer, Us.,
Unusual ~virorcner~ts and Human Behavior. New York:
Dillon.
Wickens, C. D.
1979 Measures of workload, stress, ark secondary tasks. In N.
Moray, ea., Mental Workload: Its Theory and Measurement.
London: Plenum.
Wickens, C. D., and Kessel, C.
1979 The effects of participatory mode and task workload on the
detection of dynamic system failures. :: Transactions on
Systems blur our c t~=~ s. SMC-13:24-31.
1980
Processing resource demands of failure detection in dynamic
systems. Journal of Experimental Psychology: Human
Perception ark Performance 6 (3) : 564-577 .
Wierwille, W. W., and Connor, S. A.
1983 Evaluation of 20 workload ensures using a psychomotor Wok
In a moving-base aircraft simulator. Wren Factors
25~1) :1-16.
Wierwille, W. W., Rahi~ni, M., and Mali, J. G.
1985 Evaluation of sixteen measures of my workload using a
si~rn~ated flight task ~asizing mediations activity.
Ryan Factors 27: 489-502 .
Williges, R. C., arm Wierwille, W. W.
1979 B~vior~ measures of aircrew In workload. Tan
Factors 21:549-574.
Wise, J. A.
1985 me Quantitative Modeling of mean Spatial H8bitahilit:y.
NOVA Grant ~ 2-346. Moffett Field, CA: N~;A-Ames
P~a~ Center.
1986
The space station: mean factors and habitability. In
Factors Society Bulletin 29 (5) :1-3 .
Watson, W. E.
1981 Iran Factors Design Handbook. New York:
M~Graw-Hil 1.
OCR for page 81
81
Yours, L. R.
1969 Cn adaptive manual control. 1~:~: Transactions of
M~n-MAchine Systems. M~-10: 292-331.
Zubek, J. P.
1973 Behavioral and physiological effects of prolonged sensory
and perceptual deprivation--a review. up. 8-83 in In in
Isolation and Confinement. Chicago: Oldie Publishing Co
Zubek, J. P., and Bayer/ S. M., and Milstein, S., and Shephard, J. M.
1969 Behavioral and physiological changes during prolonged
immobilization plus perceptual deprivation. Journal of
Abnormal Psychology 74:230-236.
i.
Representative terms from entire chapter:
human productivity
