Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.



Published on

Published in: Technology, Education
  • Be the first to comment

  • Be the first to like this


  1. 1. AbstractMicrocomputer Previous playfulness research has investigatedPlayfulness: playfulness as both state and trait phenomena. For example, Webster et aL (1993) examined flow, the state of playfulness in a specific human-Stable or i computer interaction, while Martocchio and Web- ster (1992) used a trait-based approach, con- sidering playfulness a characteristic of individuals.Dynamic Trait? This research extends the investigation of play- fulness as an individual trait by using a longitudinal study to examine its temporal and situational sta-Susan E. Yager bility.University of North Texas The Computer Playfulness Scale (Webster & Martocchio, 1992) was administered four timesLeon A. Kappelman over the course of a five-week summer session toUniversity of North Texas students enrolled in a computer-literacy course, once at the beginning of the class and then following completion of three milestones in theGlenn A. Maples course work. The playfulness instrument wasUniversity of North Texas assessed for internal consistency, unidimen- sionality, and temporal and situational stability.Victor R. Prybutok The evidence indicates that the measurement isUniversity of North Texas reliable. The primary question of trait stability (stable versus dynamic) was examined in several ways, supporting the conclusion that playfulness is a stable trait. The implica~ons of these findings and suggested further research are discussed. Keywords: playfulness, longitudinal study, traits, cognitive playfulness, cognitive spontaneity, com- puter playfulness scale. ACM Categories: H.1.2, J.4, K.6.1 Introduction Increasingly, MIS designers are able to add "playful" items to systems. Flying toaster screen i savers, Porky Pigs voicing of audible cues, and desktops constructed in themes tied to Disney characters inhabit a growing number of comput- ers. Moreover, new multimedia capabilities and the advent of virtual reality offer new methods to further increase microcomputer playfulness. Con- current with these new playfulness-enhancing technologies, system designers have growing abilities to customize and individualize systems. i Increasingly sophisticated individual agents have begun to lurk in cyberspace. Application pack- ages and operating systems have almost univer- sally adopted user-adjustable graphical user inter- faces (GUIs) which are frequently customizable. These new capabilities underscore the need to understand better the role of playfulness inThe DATA BASE for Advances in Information Systems - - Spring 1997 (Vol. 28, No. 2) 43
  2. 2. system design and training. Information systems conditions of personality traits are temporal sta-professionals face a critical issue in understand- bility and cross-situational consistency (e.g.,ing when playfulness augments the learning or Veenhoven, 1994).operating of a system, when playfulness mayserve as a distraction, and how the appropriate In the MIS literature, traits are defined as staticuse of playfulness may depend on individual and aspects of human information-processing charac-system differences. teristics affecting a broad range of variables (Bostrom, Olfman, & Sein, 1990). General traits Previous playfulness research has investigated refer to comparatively stable characteristics ofplayfulness as both state and trait phenomena. individuals that are relatively invariant to situ-For example, Webster et al. (1993) examined ational stimuli (Webster & Martocchio, 1992).flow, the state of playfulness in a specific human- Cognitive traits are based on processing prefer-computer interaction, while Martocchio and ences and include cognitive styles (Bostrom,Webster (1992) used a trait-based approach, OIfman, & Sein, 1990). The effect of individualconsidering playfulness a characteristic of indivi- traits on computer usage has a rich history in theduals. This research extends the investigation of IS literature, including recent work concentratingplayfulness as an individual trait by using a on computer self-efficacy (e.g., Compeau &longitudinal study to examine its temporal and Higgins, 1995), computer anxiety (e.g., Fajou,situational stability. 1996), and conscientiousness (e.g., Stewart, Carson, & Cardy, 1996).Background MIS professionals seeking to match both theThe importance of individual differences in the systems and the training methods for thesedesign and operation of information systems can systems to individual differences should not onlybe traced to the earliest frameworks of information consider differences among individuals but alsosystems. For example, "an information system whether these differences are dynamic. In par-consists of, at least, a PERSON of a certain ticular, professionals should consider whetherPSYCHOLOGICAL T Y P E . . . "(Mason & Mitroff, users attitudes or behaviors might change as they1972, p. 475) is one of the earliest frameworks for gain exposure to a system. If the individual traitsdefining information systems. In addition to other are not stable (either temporally or situationally),effects psychological types or traits have, indi- the problem of matching these traits to systemvidual differences may affect users learning about characteristics becomes decidedly more software; and some researchers perceive acritical need to match training methods to theseindividual differences (e.g., Bostrom, Olfman, & Cognitive PlayfulnessSein, 1990). Playfulness is considered a multi-faceted con-Over the last ten years, psychologists seeking to struct, encompassing five dimensions: cognitiveexplain individual differences in personality and spontaneity, social spontaneity, physical spon-behavior increasingly subscribe to trait theories. taneity, manifest joy, and sense of humor (Barnett,Furthermore, the most popular of these psycho- 1990; Barnett, 1991; Lieberman, 1977). Theselogical trait theories is the five factor model (FFM). five dimensions are illustrated as follows: cog-This personality model (based on the dimensions nitive spontaneity is the imaginative play of youngof neuroticism, extraversion, openness, agree- children and the combinatorial play of creativeableness, and conscientiousness) is charac- adults; social spontaneity is the ability to beterized as "a basic discovery" (McCrae & John, comfortable in a group setting and to move freely1992), the basis for the field of personality and in and out of such a social structure; physicalindividual differences (Buss, 1989), and sufficient spontaneity is evident in unstructured playto characterize both normal and abnormal activities such as jumping rope; manifest joy bearsbehavior (Widiger, 1993). However, despite the different labels such as pleasure and happiness;general acceptance of trait theory as key in and sense of humor results from surprising,understanding human behavior, there is no incongruous, or novel events, whether the in-generally accepted definition of the term "per- dividual is the producer or the consumersonality trait." Personality traits are generally (Lieberman, 1977). In recent publications and forthought of as long-.term predispositions to certain this study, cognitive spontaneity in human-com-behaviors or attitudes. Two generally accepted puter interactions is considered a surrogate for 44 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)
  3. 3. "cognitive playfulness" (Martocchio & Webster, The Study1992). Cognitive playfulness has been studied asa trait that influences ease of microcomputer use Subjects and Measuresand resultant learning. "Employees higher in cog-nitive playfulness demonstrated higher test The subjects were volunteer undergraduateperformance and more positive affective out- students enrolled in a computer-literacy course atcomes than those lower in cognitive playfulness" a moderately large southwestern university and(Martocchio & Webster, 1992, p. 553). In addi- received course credit for their participation. Eachtion, those higher in playfulness are expected to of seventy-seven subjects was asked to completeexercise and develop skills through exploratory four iterations of Webster and Martocchios (1992)behaviors (Miller, 1973), resulting in improved Computer Playfulness Survey instrument (see theperformance or increased learning (Martocchio & Appendix) over a five-week summer session, onceWebster, 1992). at the beginning of the course and again following the completion of three milestones in the courseThere are, however, potential drawbacks of work. The administrations are referred to as 1)playfulness, such as requiring a longer time to initial administration, a baseline on the first day ofcomplete tasks (Sandelands, 1988), over-involve- class; 2) Windows, following introduction to andment (Csikszentmihalyi, 1975), and increased project completion using the Microsoft Windowsopportunities for non-productive play (Nash, operating environment; 3) Word, following intro-1990). Organizations must be aware that playful- duction to and project completion using Microsoftness may result in wasted time; but it may also Word; and 4) Excel, following introduction to andresult in more effective, more productive, and project completion using Microsoft Excel.higher-quality results (Starbuck & Webster, 1991 ).Computer Playfulness Scale The playfulness score was determined by adding together (i.e., a linear sum) the responses of eachThe Computer Playfulness Scale (CPS) de- individual for the seven items identified by Web-veloped by Webster and Martocchio (1992) is a ster and Martocchio (1992) as comprising theself-reported instrument. It is designed to mea- playfulness construct: spontaneous, unimagin-sure microcomputer playfulness, a situation- ative, flexible, creative, playful, unoriginal, andspecific individual characteristic which represents uninventive. This was done after adjusting for thethe degree of cognitive spontaneity in micro- three items that were reverse-scored, compen-computer interactions (Webster & Martocchio, sating for yea-saying or nay-saying individuals1992). Furthermore, microcomputer playfulness who have a more or less global tendency to agreedemonstrates higher predictive efficacy for train- or disagree (Alreck & Settle, 1995).ing effectiveness (learning or understanding),compared to previously utilized computer anxiety Two primary goals of this research were to testand computer attitudes (Webster & Martocchio, the temporal stability and situational consistency1992). Test-retest reliability has proven strong of the playfulness construct. Psychologists(correlation .85, p<.001) in previous studies using evaluating the temporal stability of other person-the CPS (Webster & Martocchio, 1992). ality traits have selected periods as short as several days or as long as several years inThe Problem evaluating trait stability. Since the focus of this research was playfulness during microcomputerBecause of the growing ability to manipulate the training, a five-week training period was used. Inplayfulness of computer systems and training, the addition to being similar in length to other traitComputer Playfulness Scale measure represents studies (e.g., Stewart, Carson, & Cardy, 1996),a potentially powerful tool allowing system design- this period meets or exceeds the length of time ofers to address the interaction of system and training in most industry training environments.individual playfulness. However, before systemdesigners can accommodate the construct of play- End-user microcomputer training is subject tofulness, its trait nature must be more fully ex- constraints that make microcomputer playfulnessplored. In particular, this research seeks to estab- less subject to environmental variation than manylish the temporal stability and situational consis- other personality constructs. One of the mosttency of the playfulness construct. important variants in computer training is task,The DATA BASE for Advances in Information Systems - - Spring 1997 (Vol. 28, No. 2) 45
  4. 4. more specifically the type of software to be playfulness scores over time or across situations.learned. Three of the most common software First this hypothesis was tested by examining thegroups are operating systems, word processing, correlations among scores obtained by the sameand spreadsheets (e.g., Jones & Berry, 1995). person on multiple administrations of the sameThis research tests across these software groups instrument (Anastasi, 1988). This is the sameas cross-situational variables. statistical procedure used to perform test-retest reliability of instruments. Reliability coefficient (r)Instrument Reliabillity: Intemal Consistency values of at least 0.70 indicate that the results areand Unidimensionality stable over time (Litwin, 1995). However, caution must be exercised when interpreting these results.Internal consistency for the seven-item play- Practice effect may falsely inflate the correlationsfulness instrument was assessed with Cronbachs (Litwin, 1995). As individuals become familiar(1951) coefficient alpha, "probably the best es- with the items on a survey, they may simply an-timate of internal consistency" (Crano & Brewer, swer based on their memory of how they1973, p. 230). The results are shown in Table 1 answered previously (Litwin, 1995). The length ofbelow. Based on the greater than 0.80 rule-of- the instrument, which included at least three otherthumb (Crano & Brewer, 1973; Nunnally, 1978; instruments in each administration, was designedBlau, 1988), these coefficients indicate that the in part to minimize this playfulness instrument appears tohave high internal consistency. Test-retest reli- To confirm further that the learning effect was notability was also examined and is discussed under a serious threat to the experiment, the authorshypothesis testing. analyzed the change in variance by individuals across administrations. In the event of a sig-Another method for assessing internal consis- nificant learning bias, one would expect de-tency is to determine whether items "share only creasing variance as answers became ~more pat"one common focus" (Crano & Brewer, 1973, p. (that is, individuals responses would increasingly231). The unidimensionality of the scale was mirror the previous set of responses). The dataevaluated by means of the factorial validity showed a slight increase in variance from the first(Kappelman, 1995) of the seven-item scale using inter-item variance measure (based on individualthe SPSS/PC+ FACTOR procedure (SPSS, Inc., differences between administrations 1 and 2) to1993). Each of the four administrations of the the last (based on differences between admin-playfulness instrument resulted in all seven items istrations 3 and 4). Although this analysis doesloading on e single factor. The first eigenvalues, not preclude a learning effect between the firstpercent of variance explained by the first eigen- and second administrations, in the opinion of thevalue, ratio of the first eigenvalue to the second, authors if such an effect was significant it wouldand range of factor Ioadings are shown in Table 2 likely increase in subsequent administrations.for each administration. Eigenvalues (3.888 to Thus, learning effect did not appear to be a sig-5.143) and percent of variance (55.5% to 73.5%) nificant threat to this investigation.are relatively large for all of the four adminis-trations, indicating a consistently high percentage These reliability coefficients between adminis-of variance explained by the first factor. The ratio trations of the same instrument represent cor-of the first to the second eigenvalues is also relations between the linear sums. Since it maysubstantial, ranging from 4.260:1 to 7.649:1. The be possible for two consecutive administrations tofactor loading should attain a minimum of 0.50 exhibit little difference while cumulative dif-(Straub, 1989) to be considered as part of a ferences over several administrations may indi-factor. Each of the administrations surpasses that cate a substantial difference, each result waslevel on all seven items. Unidimensionality is compared with all other administrations (seesupported by these results, especially by the large Table 3). The playfulness scores remainedfactor Ioadings. substantively invariant across the four adminis-Hypothesis Testing trations, supporting the stable trait charac- terization of the playfulness construct.Previous research has stated that playfulness isa trait. This study tested the hypothesis that play- The correlations appeared to weaken betweenfulness is a trait and there will be no change in non-consecutive administrations over time, 46 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)
  5. 5. Administration Cronbachs Alpha Initial (n = 60) .9029 Windows (n = 62) .8825 Word (n = 60) .8656 Excel (n = 49) .9383 Table 1. Intemal Consistency Coefficients Administration Eigenvalue Percent of Ratio of Range of Factor Variance First:Second Loadings Initial 4.454 63.6 5.643:1 .65400 - .90428 Windows 4.182 59.7 4.377:1 .61597 -. 85471 Word 3.888 55.5 4.260:1 .70640 -. 81484 Excel 5.143 73.5 7.649:1 .68962 - .88752 Table 2. Evidence of Unidimensionality (Factor Analysis) Administration Correlation Significance Initial with Windows (n = 52) .842 .000 Initial with Word (n = 50) .767 .000 Initial with Excel (n = 41 ) .669 .000 Windows with Word (n = 54) .822 .000 Windows with Excel (n = 45) .783 .000 Word with Excel (n = 44) .901 .000 Table 3. Correlations between Administrationsbringing into question either the test-retest that the results were changing. If the playfulnessreliability over short time periods or raising the trait is dynamic, one would expect to see changespossibility that playfulness is dynamic and not a occur over time. However, if it is stable, onestable trait. Comparisons were made of the means would expect to see the effect by subject. Theand standard deviations (see Table 4) using a participants themselves (SUBJECTS) accountedone-way analysis of variance (ANOVA), and no for the variance (F = 13.178, p = .000), whilesignificant difference in playfulness was found for different administrations (TIME) did not have aany of the four administrations (p = 0.867). These significant effect (F = 1.300, p = 0.276). The vari-results indicate that playfulness meets both of the ation in an individuals results can be attributed tostability requirements for personality traits - the individuals playfulness trait, not the timing ofstability across both time and situations. the administration.To test the playfulness-as-stable-trait hypothesis, Conclusionsa two-way ANOVA (see Table 5) was computed to The results of this longitudinal study indicate thatdetermine whether it was by subject or by time playfulness is a stable trait. The playfulnessThe DATA BASE for Advances in Information Systems w Spring 1997 (Vol. 28, No. 2) 47
  6. 6. Administration N Mean St. Dev. Initial 60 21.767 9.039 Windows 62 22.339 8.248 Word 60 22.250 8.171 Excel 49 21.061 9.355 Table 4. Means and Standard Deviations of all AdministrationsSourceof Sum of Squares DF Mean Square F SignificanceVadation offMain Effects 14762.725 75 196.836 12.698 .000Time 60.469 3 20.156 1.300 .276Su~ects 14707.905 72 204.276 13.178 .000Explained 14762.725 75 196.836 12.698 .000Residual 2402.781 155 15.502To~l 17165.506 230 74.633 Table 5. ANOVA Resultsscore is consistent, measures a single factor, and and knowledge of a representative spectrum ofremains somewhat static. Moreover, means and software applications.standard deviations were stable over time..Thisstudy also supports; the reliability of Webster and The resulting stable trait characterization of theMartocchios (1992) operationalization of the playfulness construct has important implicationsplayfulness construct. Their seven-item Computer to both IS academics and researchers. AlthoughPlayfulness Scale demonstrated internal con- prior research associates playfulness with in-sistency, unidimen:sionality, and temporal and creased learning and performance, our researchsituational stability as evidenced by Cronbachs suggests that the stability of the playfulness traitalpha, factor validity, and test-retest correlations. will make attempts to manipulate individual play- fulness unlikely to succeed. We would suggestPrevious researchers have suggested adapting that the playfulness construct may best betraining methods based on trainee characteristics accommodated by matching system and individual(e.g., Bostrom, Olfman, & Sein, 1988; Bostrom, playfulness.Olfman, & Sein, 1990; Wexley, 1984). Paststudies of training methods have been incon- MIS designers or trainers who wish to utilize theclusive; and external effects of those methods on playfulness trait should be able to do so bytraining effectiveness were posited to depend on performing a one-time playfulness assessmentother factors, including characteristic attributes of rather than conducting longitudinal measures onthe trainees (Tannenbaum & Yukl, 1992). More individuals. This is good news both to prac-research is needed to develop and understand titioners who are trying to build effective systemstraining method adaptations that best utilize the and to researchers trying to further investigate thestable trait nature of playfulness. playfulness construct. In particular, it greatly simplifies playfulness experimental design as itContributions and Limitations of the Work renders individual playfulness traits stable rather than dynamic.This research supports the temporal stability andsituational consistency of the playfulness con- The research limitations include those traditionallystruct. The subjects of this study demonstrated a acknowledged in conjunction with the use ofmarked stability in the playfulness trait as they student subjects. More to the point, this researchgained experience in their computing environment investigates the stability of the playfulness trait in 48 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)
  7. 7. a training environment of intermediate duration Bostrom, R. P., Olfman, L., and Sein, M. K.(five weeks) and varying software to test stability (1988). "End-User Computing: A Researchacross situations. Further investigation is war- Framework for Investigating the Train-ranted into the stability of the playfulness trait ing/Learning Process," Human Factors inacross longer periods (as might be encountered Management Information Systems, Norwood,by end-users of systems) and across alternative NJ: Ablex Publishing Corporation.situations. For instance, training type and style Bostrom, R. P., Olfman, L., and Sein, M I~could influence individual playfulness. (1990). "The Importance of Learning Style in End-User Training," MIS Quarterly, Vol. 14,Further research should build on the stability of No. 1, pp. 101-119.the playfulness trait by examining the outcomes of Buss, A. H. (1989). "Personality as Traits,"manipulating playfulness in training. For instance, American Psychologist, Vol. 44, pp. 1378-the authors are currently using treatments 1388.differing by playfulness items to investigate the Compeau, D. R., and Higgins, C.A. (1995).interaction between individuals playfulness traits "Computer Self-Efficacy: Development of aand the playfulness of the computing environment Measure and Initial Test," MIS Quarterly, determining outcomes such as training satis- 19, No. 2, pp. 189-211.faction, user satisfaction, and individual perfor- Crano, W. D., and Brewer, M. B. (1973).mance measures. Principles of Research in Social Psychology,Further research should be conducted into mech- New York: McGraw-Hill.anisms by which playfulness enhances training or Cronbach, L. J. (1951). "Coefficient Alpha andsystem performance. The proper matching of the Internal Structure of Tests, ~ Psychometrika,system and user playfulness to manipulate user Vol. 16, pp. 297-334.mood offers one interesting avenue of research. Csikszentmihalyi, M. (1975). Beyond BoredomA continuous stream of research has associated and Anxiety, San Francisco: Josey-Bass.mild mood elevation with enhanced creative Eckblad, M., and Chapman, L. J. (1986).thinking (e.g., Richards, 1993; Eckblad & Chap- "Development and Validation of a Scale forman, 1986; Schuldberg, 1990), improved problem Hypomanic Personality," Journal of Abnormalsolving (Greene & Noice, 1988), and better Psychology, Vol. 3, pp. 214-222.comprehension of new concepts (Jamison, 1989). Fajou, S. (1996). "Computer Anxiety," <http://-Proper matching of system and/or training play- with individual playfulness characteristics jou.html>may offer an opportunity to manipulate user mood Greene, T. R., and Noice, H. (1988). "Influencewith a potential outcome of better system per- of Positive Affect Upon Creative Thinking andformance. Problem Solving in Children," Psychological Reports, Vol. 63, pp. 895-898.References Jamison, K. R. (1989). "Mood Disorders and Patterns of Creativity in British Writers andAlreck, P. L., and Settle, R. B. (1995). The Artists," Psychiatry, Vol. 52, pp. 125-134. Survey Research Handbook (2nd edition), Jones, M.C., and Berry, R. L. (1995). "Infor- Chicago: Irwin Professional Publishing. mation Technology: An Assessment of StudentAnastasi, A. (1988). Psychological Testing (eth Perceptions," Journal of Computer Information edition), New York: Macmillan Publishing Com- Systems, Summer, pp. 28-32. pany. Kappelman, L . A . (1995). "Measuring UserBarnett, L. A. (1990). "Playfulness: Definition, Involvement: A Diffusion of Innovation Per- Design, and Measurement," Play and Culture, spective," DATABASE Advances, Vol. 26, No. Vol. 3, pp. 319-336. 2 and 3, pp. 65-83.Barnett, L . A . (1991). "The Playful Child: Lieberman, J. N. (1977). Playfulness, NewYork: Measurement of a Disposition to Play," Play Academic Press. and Culture, Vol. 4, pp. 51-74. Litwin, M. S. (1995). How to Measure SurveyBlau, G. J. (1988). "Further Exploring the Reliability and Validity, Vol. 7, The Survey Kit, Meaning and Measurement of Career Com- Thousand Oaks, CA: Sage Publications. mitment," Journal of Vocational Behavior, Vol. Martocchio, J. J., and Webster, J. (1992). "Effects 32, pp. 284-297. of Feedback and Cognitive Playfulness onThe DATA BASE for Advances in Information Systems - - Spring 1997 (Vol. 28, No. 2) 49
  8. 8. Performance in Microcomputer Software Measure with Workplace Implications," MIS Training," Personnel Psychology, Vol. 45, No. Quarterly, Vol. 16, No. 2, pp. 201-226. 2, pp. 553-578. Webster, J., Trevino, L. K., and Ryan, L. (1993).Mason, R. O., and Mitroff, I. I. (1973). "A "The Dimensionality and Correlates of Flow in Program for Research on Management Infor- Human-Computer Interactions," Computers in mation Systems," Management Science, Vol. Human Behavior, Vol. 9, pp. 411-426. 19, No. 5, pp. 475-487. Wexley, K. N. (1984). "Personnel Training,"McCrae, R R., and John, O. P. (1992). "An Annual Review of Psychology, Vol. 35, pp. Introduction to the Five Factor Model and Its 519-551. Applications," Journal of Personality, Vol. 60, Widiger, T. A. (1993). "The DSM-III-R Categor- 175-215. ical Personality Disorder Diagnoses: A CritiqueMiller, S. (1973). "Ends, Means, and Galum- and an Alternative," Psychological Inquiry, Vol. phing: Some Leitmotifs of Play," American 4, pp. 75-90. Anthropologist, Vol. 75, pp. 87-98.Nash, J. E. (1990). "Working at and Working: About the Authors Computer Fritters," Journal of Contemporary Ethnography, Vol. 19, No. 2, pp. 201-225. Susan Yager is a Ph.D. student in the BusinessNunnally, J. (1978). Psychometric Theory(2nd Computer Information Systems Department, Col- edition), New York: McGraw-Hill. lege of Business Administration, University ofRichards, R. (1993). "Seeing Beyond: Issues of North Texas. Her dissertation research focuses Creative Awareness and Social Respon- on the use of technology to enable virtual organi- sibility," Creativity Research Journal, Vol. 6, zations. In addition to her twenty years of industry pp. 165-183. experience, she has taught information systemsSandelands, L. E. (1988). "Effects of Work and courses, served as an academic advisor and Play Signals on Task Evaluation," Journal of mentor, and was co-editor of the proceedings for Applied Social Psychology, Vol. 18, No. 12, pp. a regional conference. She is an active par- 1032-1048. ticipant in graduate student issues at the de-Schuldberg, D. (1990). "Schizotypal and Hypo- partmental, college, university, and regional manic Traits, Creativity, and Psychological levels. E-mail: Health," Creativity Research Journal Vol. 3, pp. 218-230. Leon Kappelman, is an associate professor ofStarbuck, W. H., and Webster, J. (1991). "When business computer information systems in the is Play Productive.?" Accounting, Management, College of Business Administration at the Univer- and Information Technology, Vol. 1, No. 1, pp. sity of North Texas. His professional expertise 71-90. includes the management of information assets,Stewart, G. L., Carson, K. P., and Cardy, R. L. information systems development and main- (1996). "The Joint Effects of Conscien- tenance, change management and technology tiousness and Self-Leadership Training on transfer, project management, and information Employee Self-Directed Behavior in a Service systems assessment and benchmarking. He has Setting," Personnel Psychology, Vol. 49, No. 1, published dozens of articles and several books pp. 143-164. including Solving the Year 2000 Problem: A GuideStraub, D. W. (1989). "Validating Measurements for Dragonslayers and Their Allies, International in MIS Research," MIS Quarterly, Vol. 13, No. Thomson Computer Press (1997). 2, pp. 147-169. E-mail: kapp@unt.eduTannenbaum, S. I., and Yukl, G. (1992). "Training and Development in Work Organizations," Glenn Maples, is an associate professor at Our Annual Review of Psychology, Vol. 43, pp. Lady of the Lake University. He earned his Ph.D. 399-441. at the University of North Texas. His dissertationVeenhoven, R. (1994). "Is Happiness a Trait? examines quality measurement issues in informa- Tests of the Theory That a Better Society Does tion systems. He is an ASQC Certified Quality Not Make People Any Happier," Social Indi- Engineer. Active areas of research include MIS cators Research, Vol. 32, No. 2, pp. 101-160. quality, database security and computation ofWebster, J., and Martocchio, J. J. (1992). "Micro- control process standards. computer Playfulness: Development of a E-mail: 50 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)
  9. 9. Victor Prybutok is professor of management sci-ence and the Director of the Center for Qualityand Productivity at the University of North Texas.He is a Senior Member of the American Societyfor Quality Control (ASQC), an ASQC CertifiedQuality Engineer, and an ASQC Certified QualityAuditor. He has published over 35 journal articlesand 50 proceedings in journals that include Oper-ations Research, the American Statistician, Com-munications in Statistics, and the Journal of Pro-duction and Inventory Control.E-mail: prybutok@unt.eduThe DATA BASE for Advances in Information Systems - - Spring 1997 (Vol. 28, No. 2) 51
  10. 10. AppendixThe following questions ask you how you would characterize yourself when using microcomputers. For eachadjective below, please circle the number on the answer sheet that best matches a description of yourselfwhen you interact with a microcomputer. Strongly agree 1 2 3 4 5 6 7 Strongly Disagree Spontaneous 1 2 3 4 5 6 7 Conscientious 1 2 3 4 5 6 7 Unimaginative 1 2 3 4 5 6 7 Experimenting 1 2 3 4 5 6 7 Serious 1 2 3 4 5 6 7 Bored 1 2 3 4 5 6 7 Flexible 1 2 3 4 5 6 7 Mechanical 1 2 3 4 5 6 7 Creative 1 2 3 4 5 6 7 Erratic 1 2 3 4 5 6 7 Curious 1 2 3 4 5 6 7 Intellectually Stagnant 1 2 3 4 5 6 7 Inquiring 1 2 3 4 5 6 7 Routine 1 2 3 4 5 6 7 Playful 1 2 3 4 5 6 7 Investigative 1 2 3 4 5 6 7 Constrained 1 2 3 4 5 6 7 Unoriginal 1 2 3 4 5 6 7 Scrutinizing 1 2 3 4 5 6 7 Uninventive 1 2 3 4 5 6 7 Inquisitive 1 2 3 4 5 6 7 Questioning 1 2 3 4 5 6 7 52 The DATA BASE for Advances in Information Systems-- Spring 1997 (Vol. 28, No. 2)