10
Identifying Differences In Time Managers Florence S. Walker, Anne M. Parkhurst Authors’ Addresses: F. S. Walker, College of Home Economics, University of Nebraska, Lincoln, NE 68583; A. M. Parkhurst, Institute of Agriculture and Natural Resources, University of Nebraska, Lincoln, NE 68583. A measure to differentiate time managers was developed in which performance indi- cators were used to derive a self-perception measure (TM Score). It was based upon planning for the future, meeting deadlines, and accuracy in estimating duration of routine tasks. Statistical tests used to investigate time management effectiveness were analysis of variance and Pearson product -moment correlation coefficients. From the analyses it was concluded that middle-aged adults who live busy lives were more likely to be effective time managers than others. Age was one of the key characteristics related to differences in TM Scores. This finding was reinforced by information on retirement status, family description, and residential longevity. Team spirit, as indicated by family cohesion, was also another characteristic associated with differences in TM Scores, for as family cohesion increased, TM Scores also increased. Among other management prac- tices, orderly storage areas and a sense of the importance of time usage were both associated with more effective time management. A multivariate analysis (GLM proce- dure of SAS statistical computer package) produced a model that accounted for 25 percent of the total variation in TM Score. Of the six variables in the model, education, household production, and social participation in local organizations were most influential. Ability to control time gains in importance as people try to shape their lives to encompass a wider variety of activities than previously at- tempted. As an offshoot of the industrial age manifesto that &dquo;more is better than less,&dquo; a great number of activities are being packed in- to fewer days. Evidence abounds of the wide- spread urge to diversify one’s day: higher proportions of married women working for pay away from homes, higher proportions of college students combining marriage and studies, as well as higher proportions of col- lege students dividing their time between jobs and studies. Those employed in managerial situations, too, find the computer age has re- sulted in mounting pressures for quick diges- tion of information plus consideration of wider ranges of alternatives in decision situa- tions. The complexity of life today places in- creasing emphasis upon using time effectively. Some authors ascribe stress to the extreme specialization of social roles and (of the func- tions of) social organizations. Increased aware- ness of precise measurement of objective (clock) time may also contribute to stress (Moore, 1963). Time pressures are seen as a characteristic of the industrial societies stemming from the cognition that time rep- Nebraska Hatch project 92005, &dquo;Quality of Life as Influenced by Area of Residence.&dquo; Duane A. Olsen, Associate Professor, Agricultural Economics, Institute of Agriculture and Natural Resources, University of Nebraska-Lincoln, served as co-leader of Project, 1975-1978. Published as Paper Number 5724, Journal Series, Nebraska Agricultural Experiment Station.

Identifying Differences in Time Managers

Embed Size (px)

Citation preview

Identifying DifferencesIn Time Managers

Florence S. Walker, Anne M. Parkhurst

Authors’ Addresses: F. S. Walker, College of HomeEconomics, University of Nebraska, Lincoln, NE68583; A. M. Parkhurst, Institute of Agricultureand Natural Resources, University of Nebraska,Lincoln, NE 68583.

A measure to differentiate time managers was developed in which performance indi-cators were used to derive a self-perception measure (TM Score). It was based uponplanning for the future, meeting deadlines, and accuracy in estimating duration ofroutine tasks. Statistical tests used to investigate time management effectiveness wereanalysis of variance and Pearson product -moment correlation coefficients. From theanalyses it was concluded that middle-aged adults who live busy lives were more likelyto be effective time managers than others. Age was one of the key characteristics relatedto differences in TM Scores. This finding was reinforced by information on retirementstatus, family description, and residential longevity. Team spirit, as indicated by familycohesion, was also another characteristic associated with differences in TM Scores, for asfamily cohesion increased, TM Scores also increased. Among other management prac-tices, orderly storage areas and a sense of the importance of time usage were bothassociated with more effective time management. A multivariate analysis (GLM proce-dure of SAS statistical computer package) produced a model that accounted for 25percent of the total variation in TM Score. Of the six variables in the model, education,household production, and social participation in local organizations were most influential.

Ability to control time gains in importance aspeople try to shape their lives to encompass awider variety of activities than previously at-tempted. As an offshoot of the industrial agemanifesto that &dquo;more is better than less,&dquo; agreat number of activities are being packed in-to fewer days. Evidence abounds of the wide-

spread urge to diversify one’s day: higherproportions of married women working forpay away from homes, higher proportions ofcollege students combining marriage andstudies, as well as higher proportions of col-lege students dividing their time between jobsand studies. Those employed in managerialsituations, too, find the computer age has re-sulted in mounting pressures for quick diges-tion of information plus consideration ofwider ranges of alternatives in decision situa-

tions. The complexity of life today places in-creasing emphasis upon using time effectively.Some authors ascribe stress to the extreme

specialization of social roles and (of the func-tions of) social organizations. Increased aware-ness of precise measurement of objective(clock) time may also contribute to stress(Moore, 1963). Time pressures are seen as acharacteristic of the industrial societies

stemming from the cognition that time rep-

Nebraska Hatch project 92005, &dquo;Quality of Life asInfluenced by Area of Residence.&dquo; Duane A. Olsen,Associate Professor, Agricultural Economics,Institute of Agriculture and Natural Resources,University of Nebraska-Lincoln, served as co-leaderof Project, 1975-1978.

Published as Paper Number 5724, Journal Series,Nebraska Agricultural Experiment Station.

58

resents an expensive and valuable resource.As one author puts it, one of the paradoxes ofthe economy of time is the fact that, as more

disposable time is created, time becomesscarcer (Julkumen, 1977).

Investigation of household time usage canfocus upon: (1) the duration of tasks; (2) per-sonal characteristics of the worker (householdunit) who actively engages in these tasks; or(3) the surroundings in which the task occurs,including work methods (Steidl and Bratton,1968). The investigation in this article centersupon the characteristics of a sample of peoplewho exhibit work methods that result ineconomies of time regardless of the task per-formed. It contrasts with the fundamental

time-budget method of research in that thedata on which this report is based are subjec-tive : there were no enumerations of durationof tasks (Walker and Wood, 1976). Further-

more, the data reported here do not relate toopportunity costs as a basis of allocation oftime since no effort was made to identify tasksthat competed for the time span of any partic-ular task (Gronau, 1975).

In this article the thought on time manage-ment is that economies of current time usage

(management) are the result of conscious pastactions. In addition, other actions taken dur-

ing the current time will result in timeeconomies in the future. Thus time manage-ment is viewed as a continuously relatedseries of actions that the actor deliberately en-gages in with expectations of greater achieve-ment than if these actions were omitted. This

approach to time management builds some-what upon the social scientists’ conceptuali-zations of time in which the ideas of rhythm,recurrence, synchronization, sequencing, andwork pace form the basis for many of the

suggestions found in time management tech-niques (Harris, 1974; Doob, 1971; Moore,1963).This concept of time management is also as-

sociated with business-oriented time man-

agement studies (Mundell, 1970; Lakein,1974). That is, certain practices will result ingreater productivity regardless of where theyoccur.

The purpose of this article is to describe and

to test a method for distinguishing more

effective time managers from less effectivetime managers.

Specifically, these purposes are:

1. To describe the derivation of a time man-

agement scale (TM Score) to measuredifferences in time management.

2. To identify characteristics associatedwith TM Scores.

3. To determine if time management prac-tices other than those used in the deriva-tion of the TM Score are related to differ-

ences in effectiveness of time manage-ment.

4. To investigate the influence of the fol-lowing composite characteristics on ef-fectiveness of time management:a. Variety of living experiencesb. Presence of a wife who works for payc. Pace of life

Sample Characteristics

The respondents in this study were ran-domly selected from local 1976 telephone di-rectories. The communities were randomlyselected from a group of Nebraska com-munities that met predetermined criteria es-tablished for population and, in the case ofrural communities, distance from an urbancenter. Of the 800 questionnaires that weremailed, 316 were returned with 253 (31.6%)deemed usable. In brief, 49 percent werewomen, and urban residents comprised 47percent (Table 1). The majority of the respon-dents were actively involved in local commu-nity groups. Age ranged from 18 to 85 yearswith a median age of 47.7 years. The modal

group for educational attainment was highschool graduate.The description of the families in this sam-

ple indicated that median family size was 3.3members and median family type was &dquo;mar-ried with dependent children&dquo; (Table 1).While 45.5 percent of the respondents had nochildren living at home, five percent had fiveor more children at home. Seven percent had a

preschool aged child at home. There was evi-dence of family solidarity as indicated by theNC-90 Committee family cohesion measuresince 42.3 percent met requirements for highcohesiveness. This measure was based upon

59

TABLE 1

Sample Characteristics

combined responses to two questions: fre-

quency of &dquo;going places together as a family,&dquo;and frequency with which &dquo;family membersworked around the home together.&dquo; Responsealternatives were &dquo;often,&dquo; &dquo;sometimes,&dquo;&dquo;seldom,&dquo; and &dquo;never&dquo; (NC-90 Committee,1974, p. 57).Many families had high levels of household

production with median production equalling15.1 tasks.’ Household production was mea-sured by the sum of responses to 18 taskscommonly performed by family memberswhich met requirements established by Reidfor household production (1934, p. 11).Included were managerial activities such asplanning to meet the expense of future pur-chases, performance of service such as childcare or yard care, and production of material

goods such as canning or freezing food. Re-sponse alternatives were phrased to indicatewho usually performed the tasks: a familymember, someone outside the family, or thatthe task itself was not a part of that house-hold’s regime. Related to household produc-tion was a household work force measure. It

identified the number of persons within a

family able to do housework. The basis of thismeasure was responses to the question, &dquo;Howmany persons in your household, includingyourself, are able to help with the type ofhousehold activities listed above?&dquo; The listreferred to 14 of the 18 tasks identified for thehousehold production measure. In this study,respondents reported that work forces rangedfrom one to eight persons with a median of 2.5.Economic characteristics indicated median

60

income for 1975 was $14,513 while the rangewas from $1,045 to $60,000 (Table 1). Censusdata indicate that Nebraska median income in1975 was $14,209, slightly lower than medianincome for this group. Nebraska median in-come was slightly higher than U.S. median in-come in 1975.Income adequacy, an evaluation of family

income compared with family composition,has been named &dquo;index of income&dquo; by theNC-90 research project scientists (NC Com-mittee 90:1974). As computed for these 1975data, the median income index was 276.5.Barely adequate income levels equal an indexof 100. Four percent of the sample had incomeindexes below 100, while 46 percent had in-dexes of about 300. Therefore, this sample, bytwo measures of income, was in a comfortableeconomic situation with a minority indicatingeconomic hardship.Turning to job-related characteristics, 20

percent of the families were headed by a re-tired person. Taking another view of thissample, 59 percent indicated there was noout-of-home employment for the wife. Me-dian number of work hours per week for allthose who were employed was 40.3.

Composite VariablesThere were three demographic composite

variables. The first, variety of living experi-ences, was a combination of number of com-munities inhabited plus number of jobs heldsince high school graduation. Sixteen percentof the respondents were classified as havinglittle variety of living experiences. A seconddemographic composite variable concernedwife’s employment status: wife works for pay.It combined information on number of hours

per week worked at a job plus amount of payearned. In this sample, 59 percent of the wives(females) did not work outside the home, 9percent worked as volunteers (received no payfor their work hours), and the remainder, 32percent, worked for pay. Only 3 percentworked part-time, according to the number ofhours devoted to the job, so they weregrouped with full-time employees. The thirdcomposite demographic variable, pace of life,

was based upon combinations of informationon wife’s employment status and family size.Those respondents who reported not workingfor pay and were in a family of one or twomembers were considered to live at a slow

pace. Those employed and with families ofmore than three persons were considered tolive at an accelerated pace. According to thismeasure, 12 percent of the sample had a slowpace of life, while 57 percent qualified for anaccelerated pace of li f e.The second group of composite variables in-

clude four measures that were based upon in-formation on time management. The first,satisfaction with time usage, was measured bycombining evaluation of eight typical humanactivities: hobbies, including social activitiesand TV; working; at home engaged in familyactivities; shopping and housekeeping; relax-ing and personal grooming; sleeping; awayfrom home with friends; and commuting,traveling, or driving. Scores ranged from 24(highly satisfied) to zero (dissatisfied withtime usage for all eight activities). Importanceof time usage, the second time management com-posite variable, was developed by combin-ing ratings of importance for job time, non-jobtime, and time for the things you want to do.Scores ranged from a high of two (very im-portant) to a low of 15 (of little importance).The median score was 5.6. This rating indi-cated all three activities were considered im-

portant. Retrieval time, the third time man-

agement composite variable, was developedfrom information given for number of minutesneeded to locate five types of semi-importantpapers usually kept at home: unpaid bills, un-answered letters, warranties, birth or marriagecertificates, and life insurance policies. Thefastest retrieval time was four minutes to lo-cate the five types of records while the slowestwas three hours and 22 minutes. The median

was 21.3 minutes. The fourth time manage-ment composite variable, orderly storage, hadto do with combining the degree of order in avariety of storage facilities such as shelves,cupboards, closets, and drawers. Orderlystorage scores ranged from a low or zero (noorder) to a high of 12 with a median scoreof 10.5.

61

Derivation of Time Management Score

The crucial problem of this research was tofind a time management scale that would dis-tinguish between those respondents whomanage their time well and those who do not.The scale proposed here is a self-perceptionmeasure based on performance indicators. It

indicates how people perceive their time man-agement abilities. However, the foundationsof this scale rest upon what the respondentssay they actually do.Using the discriminant analysis procedure

in SPSS (Cacoullos, 1973; Nie, Hull, Jenkins,Steinbrenner, and Bent, 1975), a time man-agement score was derived as a linear combi-nation of a respondent’s self-perceived abilityto estimate time, ability to keep appoint-ments, and inclination toward advance plan-ning. The equation for standardized scoreswas:

TM Score = 0.09 estimate + 0.43 appts + 0.87 plan

Thus, the proposed score is heavily weightedby advance planning tendencies, moderatelyinfluenced by ability to keep appointments,and only slightly influenced by the ability toestimate time. It ranges from a low of 1.48 forineffective time managers to a high of 9.04 foreffective managers. The three questions usedto develop the score were:

A. When you estimate how long it takes todo a familiar task, how often do you find

your estimation is correct?B. How often do you keep appointments or

meet deadlines?C. How far in advance do you plan for the

general use of your time?

Responses to questions A and B were 5-pointLikert scales: (1) never, (2) seldom, (3) abouthalf the time, (4) almost always, (5) always. Re-sponses to the third question, C, were a 7-point Likert scale: (1) never plan for use oftime, (2) less than one day at a time, (3) oneday to six days at a time, (4) one to four weeksat a time, (5) one to two months, (6) three to sixmonths, (7) seven months up to a year at atime.The equation was developed by exploring

performance indicators such as whether or not

the respondent set aside time for housekeep-ing, shopping, job, leisure, and weekend ac-tivities. The clearest picture emerged whenthe middle group of respondents, those whoresponded &dquo;somewhat,&dquo; were omitted. The

picture did not change substantially whenonly the positive and negative responses wereincluded, but relevant combinations of vari-ables were more readily identified and com-pared. (See Table 2 for frequencies.) The strongresponses help isolate time management vari-ables that discriminate between individualson the performance indicators. Probabilities ofcorrect classification for the TM Score vari-ables in this sample were 59 percent forhousekeeping, 63 percent for shopping, 67percent for job, 69 percent for leisure, and 65percent for weekend activities. These resultsindicate that the three TM Score variables dodiscriminate between those who use man-

agement techniques and those who do not.While other variables-such as time to locate

bills, letters, instructions, certificates, and in-surance policies, as well as organization ofclosets, drawers, and cupboards-improve theprobability of correct classification (72 percentfor leisure), the improvement is not enough towarrant the additional complexity both in in-terpretation and questions asked. The pro-posed time management scale is reliable, sim-ple to use, and easily interpreted.

FindingsThe TM Score is to be interpreted as the

higher the positive number, the more effectivethe individual is with managing time. Thestatistical techniques used to compare TMScores with other variables were Pearson

product-moment correlation coefficient and

62

analysis of variance for both a one-way clas-sification and a general linear model.

Characteristics of the sample were dividedinto four categories for purposes of reporting:personal (concerning respondents’ individualcharacteristics), family (concerning the respon-dents’ family situation), economic (concerningrespondents’ income and employment situa-tion), and composite variables (concerningdemographic and management practices).Personal CharacteristicsOf the six characteristics identified as per-

sonal descriptors of respondents, three werestatistically significant when tested with theTM Scores. Personal characteristics that didmake a difference to effectiveness of time

management were age, education, and par-ticipation in local groups (Table 3). A trendwas found for community longevity (N = 251,r = -0.097, p = 0.07).When age was tested with TM Scores by

analysis of variance (SPSS: ONEWAY), thoseaged 66 or older were statistically less effectivetime managers than those in their middle

TABLE 3

®ne®vuay analysis of variance betweenTM Scores and sample characteristics

- ... -

years; namely, between the ages of 18 to 59(Table 4). Seven levels of educational attain-ment were listed on the questionnaire, start-ing with completion of grade school and end-ing with completion of graduate school or re-ceiving a professional degree. It was foundthat those enrolled in graduate or professionalschools were distinguished from all others bytheir high TM Scores. Furthermore, the LSDprocedure (0.05 level of probability) indicatedthat those who completed college or tradeschool were significantly more effective timemanagers than those who started but did not

complete high school (Table 4).Level of participation in local groups was

found to be significantly related to effective-ness of time management (Table 3). Thosewho reported no participation in local groupswere less effective time managers than those

who reported moderate or high rates of par-ticipation (Table 4). Furthermore, the LSDprocedure indicated that each group differedsignificantly from each other with respect toTM Scores. The two personal characteristicsthat made no difference with regard to TMScores were sex and residential location.

63

Family CharacteristicsOf the four family characteristics that were

studied, family cohesion and household pro-duction indicated significantly different TMScores while family description (marital sta-tus, with/out children) indicated a trend. Pres-ence of preschool children showed no sig-nificant differences (Table 3).

Family cohesion referred to work and playactivities families did as a unit. Group meansindicated that, as family cohesion increased,so did effectiveness of time management(Table 4). The analysis of variance indicatedthat those with a low degree of family cohe-sion were statistically less effective time man-agers than those with moderate or heavy de-grees of family cohesion. Household produc-tivity is a measure of the variety of householdtasks performed by either the respondent oranother family member. These tasks are thetype that could be delegated to paid employ-ees if the families are able and willing to doso. The analysis of variance of household pro-duction indicated that each level of household

production had a statistically different TMScore. Those in the high household produc-tion group scored as more effective time man-

agers (Table 4).The LSD test for family description indi-

cated that those married with dependent chil-dren were more effective time managers thanthose married without dependent children.Moreover, those widowed without dependentchildren had lower TM Scores than those

widowed with dependent children, thosemarried with dependent children, and thosewho were single.There were no significant correlations be-

tween TM Scores and size of fainily, size ofwork force, or number of children at home.

Economic CharacteristicsFive characteristics were studied to deter-

mine the effect each might have on TM Scores.No significant correlations were found foreither weekly job hours or commuting to jobfrom home. Neither were there any significantdifferences for TM Scores for 1975 family in-come. However, significant differences in TMScores were found for retirement status as well

as for index of income (Table 3).Index of income referred to adequacy of in-

come to meet family needs. Those whose in-comes were affluent were significantly bettertime managers than those whose incomeswere barely adequate (Table 4). Retirementstatus, as tested by analysis of variance, indi-cated that those who were not retired were

64

more effective time managers than those al-

ready retired.

Composite VariablesOf the three composite variables based

upon combinations of demographic informa-tion, only one, pace of life, indicated signifi-cantly different TM Scores (Table 3). Pace of lifevariable was divided into three categories:slow, moderate, and accelerated. When pace oflife was accelerated, that is, dual earners in thefamily plus large families, time managementbecame more effective. Those with a moderate

pace of life were least effective time managers,being significantly less effective time man-agers than those with an accelerated pace oflife (Table 4). Variety of living experiencesand whether or not the wife works for pay pro-duced no significant differences in TM Scores(Table 3).Of the four time management composite

variables, only one indicated significant differ-ences in TM Scores, importance of time usage(Table 3). Orderly storage indicated a trend to-ward differences in TM Scores. Importance oftime usage was a report of three general typesof activities that were rated according to theimportance they had to the respondents’well-being and happiness. As these activitiesbecame more important, the respondents alsobecame more effective time managers (Table4). Furthermore, there were statistical differ-ences between the TM Scores of those whorated the three activities as unimportant andthose who rated them as important. The studyof orderly storage showed a trend between de-grees of orderliness and effectiveness of time

management (Table 4). Differences at the 10percent level of probability in TM Scores werenoted between those with few orderly storageareas and those with many orderly ones (Table4). Evidently, the desire to have things neatlyarranged in all types of storage facilities wasrelated to the desire to manage time. Satisfac-tion with time usage and retrieval time producedno significant differences in TM Scores.

Multivariate AnalysisA multivariate analysis (Mardia, Kent, and

Bibby, 1979) was performed using the general

linear model (GLM) procedure of the SASstatistical computer package (Helwig andCouncil, 1979). The model accounted for 25percent of the total variation in the TM Score.Of the five variables included in the model,education, household production, and socialparticipation are the most influential (Table 5).All variables were significant at the five per-cent level. Other variables such as age, familydescription, index of income, pace of life, impor-tance of time usage and orderly storage wereexcluded from the model because the chi-

square test statistic indicated they were highlyrelated to the variables listed in Table 5.

Therefore, their inclusion would mask the im-

portance of those variables remaining in themodel.

Discussion, Conclusions, and ImplicationsThe TM Score was derived from time man-

agement techniques; namely, planning for thefuture, promptness, and realism of time de-mands caused by routine activities. It was as-sumed that when an individual perceived thathe (she) practiced these managerial tech-niques, he (she) was, in fact, an effective timemanager. The three techniques were stated interms that would apply to any aspect of adultlife, thus were not restricted to women nor tohome life.The original selection of the sample charac-

teristics was determined by the desire to relatea wide variety of life experiences to effectivetime management. From the nine that werefound to cause differences in time manage-

65

ment effectiveness, only one-income index-focused upon economic information. It ap-peared that time management ability relatedmore to the personal and the family sphereof life, plus data on community participation.The description that emerged of persons

more likely to be effective time managers waseither men or women who were in their mid-dle years of adult life with above average edu-cation. Not surprisingly, they consideredtime usage to be important. Turning to indi-cations of the lifestyle of the more effectivetime managers, it was evident that they werebusy people since they participated in localcommunity groups regularly and were mem-bers of families in which there was enjoymentin doing things together. This was furthersupported by evidence that increased homeproduction was associated with more effectivetime management. Those respondents with anaccelerated pace of life were more effectivetime managers than those with a moderate

pace of life.It was surprising that neither the number of

children at home nor the presence of pre-school aged children showed any significantdifference in TM Scores. Perhaps the fact thatthe sample was limited biased the results.

Only 18 families (13 percent of those with de-pendent children) had preschool aged chil-dren.That age affects time management was re-

inforced in many ways in this study. Firstthe information on retirement status, in a

sense, verified the age data that those beyondage 65 were less effective time managers. In

addition, the negative association of residen-tial longevity with TM Scores supported thefinding that those in the middle years ofadulthood were more effective time managers.Family description also supported the fact thatage affects time management. Those marriedwith dependent children were significantlyyounger (mean = 41.3 years) than those with-out children (mean = 58.9 years), and the agesof the widowed without children ranged from51 to 82 years.

Orderly types of storage areas reinforced theeffective use of time, since they enabled thetime manager to locate needed tools and

supplies quickly. Storage areas hold a widevariety of supplies and equipment and appearto be a better reference point for the effectivetime manager than specific information aboutlocation of semi-important papers consideredin the composite variable, retrieval time. Thiscould be an indication that the more effectivetime manager focuses upon grasping thewhole rather than being confused by details.Too much detail can create confusion.Team spirit, an interpretation of the family

cohesiveness measure, was another character-

istic associated with the more effective time

manager. The team spirit was reinforced byinvolvement in many local organizations.Also, there was evidence of a positive relation-ship between household production and TMScores.

A model developed by multiple analysis ofvariance explained 25 percent of the variancein TM Scores. The five characteristics con-

tributing to this explanation of differenceswere education, household production, par-ticipation in local groups, family cohesion, andretirement status. This reinforces the conceptthat time management (TM Score) is a functionof personal and family characteristics as op-posed to the economic sphere of life.Time management is a strategy used to con-

trol a busy life. A person’s accelerated pace oflife may stem from away from home activitiessuch as community involvement or employ-ment, as well as from in-home activities suchas household production. Since more effectivetime management was related to differences inpace of life, it appears that management be-havior is a learned response rather than a nat-

ural response. When there are no demands

upon the individual to use time effectively andeverything that is desirable to accomplish canbe fitted into the available time, the purpose of

management would seem to be illustrative ofParkinson’s Law, in order that empty hoursseldom occur. The TM Score, as a measure ofeffective time management, would be ineffec-tive for those with this definition of time man-

agement. However, the TM Score lends itselfto a variety of applications since it is not

bound by sex nor does it refer exclusively tohome-related tasks. Rather the reference point

66

is to somewhat unstructured activities overwhich the individual has some control. It is

hoped that this measure might be replicatedwith other audiences to prove its validity andthat it might become useful as a way of de-scribing differences in people.As pace of life accelerates for families and

individuals, time management strategies be-come more important, since they are effectivecontrol mechanisms. The payoff for time man-agement is a meshing of the diverse activitiesthat contribute to a satisfying lifestyle for anindividual or family.

References

Cacoullos, T. (Ed.) Discriminant Analysis and Appli-cations. New York: Academic Press, 1973.

Doob, L. W. Patterning of Time. New Haven, CT:Yale University Press, 1971.

Gronau, R. The effect of children on the house-wife’s value of time. Journal of Political Economy,1975, 81, 168-199.

Harris, L.C. Work and leisure: Putting it all to-

gether. Manpower, 1974, 6 (1), 23-26.Helwig, J. T., and Council, K. A. (Eds.) SAS User’sGuide (1979 Edition). Raleigh, NC: SAS Institute,Inc., 1979.

Julkumen, R. A contribution to the categories ofsocial time and the economy of time. Acta Socio-

logica, 1977, 20 (1), 5-24.

Lakein, A. How to Get Control of Your Time and YourLife. New York: The New American Library,Inc., 1974.

Mardia, K. V., Kent, J. T., and Bibby, J. M. Mul-tivariate Analysis. New York: Academic Press,1979, 300-325.

Moore, W. E. Man, Time and Society. New York:John Wiley and Sons, Inc., 1963.

Mundell, M. E. Motion and Time Study Principles andPractices. Englewood Cliffs, NJ: Prentice-HallInc., 1970.

NC-90 Committee. Patterns of living related to in-come poverty in disadvantaged families-A case-book. (North Central Regional Research Publica-tion No. 217) Ames, IA: Iowa Agricultural andHome Economics Experiment Station Special Re-port 74, 1974.

Nie, N. H., Hull, C. H., Jenkins, J. G., Steinbren-ner, K., and Bent, D. H. Statistical Package for theSocial Sciences. New York: McGraw-Hill, Inc.1975.

Reid, M. R. Economics of Household Production. NewYork: John Wiley and Sons, Inc., 1934.

Steidl, R. E., and Bratton, E. C. Work in the Home.New York: John Wiley and Sons, Inc., 1968.

Walker, K. E., and Woods, M. E. Time Use: A Mea-sure of Household Production of Family Goods andServices. Washington, D.C.: American HomeEconomics Association, 1976.

Received February 8, 1979; accepted March 26, 1982.