1932

Abstract

The use of experience sampling methods (ESM) and related techniques has exploded in organizational research. The goals of this review are to provide a focused perspective on the state of the art in using ESM and set the stage for what ESM will look like in the years to come. First, I provide a conceptually based discussion of exactly what is and what is not ESM. Next, I discuss the more advantageous elements of ESM that have surfaced from the range of disciplines that enjoy its use (e.g., reduced memory and methods biases), followed by the inevitable challenges that have sometimes limited its utility (e.g., issues with repeated assessment, missing data, and internal validity). Finally, I discuss three innovations of ESM (e.g., trait assessment, expansion to higher levels of analysis, and connection to big data) that seem likely to ensure its continued and expanded influence as a common tool for examining not only within-person psychological processes at work, but higher levels of analysis as well.

Loading

Article metrics loading...

/content/journals/10.1146/annurev-orgpsych-032414-111335
2015-04-10
2024-04-18
Loading full text...

Full text loading...

/deliver/fulltext/orgpsych/2/1/annurev-orgpsych-032414-111335.html?itemId=/content/journals/10.1146/annurev-orgpsych-032414-111335&mimeType=html&fmt=ahah

Literature Cited

  1. Archak N, Ghose A, Ipeirotis PG. 2011. Deriving the pricing power of product features by mining consumer reviews. Manag. Sci. 57:1485–509 [Google Scholar]
  2. Bakker AB, Demerouti E, Schaufeli WB. 2003. Dual processes at work in a call centre: an application of the job demands–resources model. Eur. J. Work Organ. Psychol. 12:393–417 [Google Scholar]
  3. Bakker AB, Xanthopoulou D. 2009. The crossover of daily work engagement: test of an actor–partner interdependence model. J. Appl. Psychol. 94:1562–71 [Google Scholar]
  4. Barrick MR, Mount MK. 1991. The Big Five personality dimensions and job performance: a meta-analysis. Pers. Psychol. 44:1–26 [Google Scholar]
  5. Barsky A, Kaplan SA, Beal DJ. 2011. Just feelings? The role of affect in the formation of organizational fairness judgments. J. Manag. 37:248–79 [Google Scholar]
  6. Beal DJ. 2012. Industrial/organizational psychology. See Mehl & Conner 2012, pp. 601–19
  7. Beal DJ, Ghandour L. 2011. Stability, change, and the stability of change in daily workplace affect. J. Organ. Behav. 32:526–46 [Google Scholar]
  8. Beal DJ, Trougakos JP. 2013. Episodic intrapersonal emotion regulation: or, dealing with life as it happens. Emotional Labor in the 21st Century: Diverse Perspectives on Emotion Regulation at Work Grandey A, Diefendorff J, Rupp D. 31–55 New York: Psychol. Press [Google Scholar]
  9. Beal DJ, Trougakos JP, Weiss HM. 2006a. The dynamics of emotion regulation strategies. Presented at Annu. Meet. Soc. Ind. Organ. Psychol., 21st, May 5–7, Dallas
  10. Beal DJ, Trougakos JP, Weiss HM, Dalal RS. 2013. Affect spin and the emotional labor process at work. J. Appl. Psychol. 98:593–605 [Google Scholar]
  11. Beal DJ, Trougakos JP, Weiss HM, Green SG. 2006b. Episodic processes in emotional labor: perceptions of affective delivery and regulation strategies. J. Appl. Psychol. 91:1053–65 [Google Scholar]
  12. Beal DJ, Weiss HM. 2003. Methods of ecological momentary assessment in organizational research. Organ. Res. Methods 6:440–64 [Google Scholar]
  13. Beal DJ, Weiss HM. 2013. The episodic structure of life at work. A Day in the Life of a Happy Worker Bakker AB, Daniels K. 8–24 New York: Psychol. Press [Google Scholar]
  14. Beal DJ, Weiss HM, Barros E, MacDermid SM. 2005. An episodic process model of affective influences on performance. J. Appl. Psychol. 90:1054–68 [Google Scholar]
  15. Bleidorn W, Peters AL. 2011. A multilevel multitrait-multimethod analysis of self- and peer-reported daily affective experiences. Eur. J. Personal. 25:398–408 [Google Scholar]
  16. Bliese PD, Ployhart RE. 2002. Growth modeling using random coefficient models: model building, testing, and illustrations. Organ. Res. Methods 5:362–87 [Google Scholar]
  17. Bobko P, Stone-Romero EF. 1998. Meta-analysis may be another useful research tool, but it is not a panacea. Res. Pers. Hum. Resour. Manag. 16:359–97 [Google Scholar]
  18. Bolger N, Davis A, Rafaeli E. 2003. Diary methods: capturing life as it is lived. Annu. Rev. Psychol. 54:579–616 [Google Scholar]
  19. Bono JE, Glomb TM, Shen W, Kim E, Koch AJ. 2013. Building positive resources: effects of positive events and positive reflection on work stress and health. Acad. Manag. J. 56:1601–27 [Google Scholar]
  20. Box GEP, Jenkins GM, Reinsel GC. 2008. Time Series: Forecasting and Control Hoboken, NJ:: Wiley, 4th ed..
  21. Brose A, Lovden M, Schmiedek F. 2014. Daily fluctuations in positive affect positively co-vary with working memory performance. Emotion 14:1–6 [Google Scholar]
  22. Brose A, Schmiedek F, Lovden M, Lindenberger U. 2012. Daily variability in working memory is coupled with negative affect: the role of attention and motivation. Emotion 12:605–17 [Google Scholar]
  23. Bussmann JBJ, Ebner-Priemer UW, Fahrenberg J. 2009. Ambulatory activity monitoring: progress in measurement of activity, posture, and specific motion patterns in daily life. Eur. Psychol. 14:142–52 [Google Scholar]
  24. Card NA. 2012. Multilevel mediational analysis in the study of daily lives. See Mehl & Conner 2012, pp. 479–98
  25. Carlson KD, Wu J. 2012. The illusion of statistical control: control variable practice in management research. Organ. Res. Methods 15:413–35 [Google Scholar]
  26. Chan D. 1998. The conceptualization and analysis of change over time: an integrative approach incorporating longitudinal mean and covariance structures analysis (LMACS) and multiple indicator latent growth modeling (MLGM). Organ. Res. Methods 1:421–83 [Google Scholar]
  27. Charles ST, Piazza JR, Mogle J, Sliwinski MJ, Almeida DM. 2013. The wear and tear of daily stressors on mental health. Psychol. Sci. 24:733–41 [Google Scholar]
  28. Chen H, Chiang RHL, Storey VC. 2012. Business intelligence and analytics: from big data to big impact. Manag. Inf. Syst. Q. 36:1165–88 [Google Scholar]
  29. Cohen J, Cohen P, West SG, Aiken LS. 2003. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences Mahwah, NJ: Erlbaum, 3rd ed..
  30. Conner TS. 2013. Experience sampling and ecological momentary assessment with mobile phones. Rep., Dept. Psychol., Univ. Otago, Dunedin, N.Z. http://www.otago.ac.nz/psychology/otago047475.pdf
  31. Conner TS, Reid KA. 2012. Effects of intensive mobile happiness reporting in daily life. Soc. Psychol. Personal. Sci. 3:315–23 [Google Scholar]
  32. Conway N, Briner RB. 2002. A daily diary study of affective responses to psychological contract breach and exceeded promises. J. Organ. Behav. 23:287–302 [Google Scholar]
  33. Csikszentmihalyi M, Graef R. 1980. The experience of freedom in daily life. Am. J. Community Psychol. 8:401–14 [Google Scholar]
  34. Csikszentmihalyi M, Kubey R. 1981. Television and the rest of life: a systematic comparison of subjective experience. Public Opin. Q. 45:317–28 [Google Scholar]
  35. Csikszentmihalyi M, Larson R, Prescott S. 1977. The ecology of adolescent activity and experience. J. Youth Adolesc. 6:281–94 [Google Scholar]
  36. Csikszentmihalyi M, LeFevre J. 1989. Optimal experience in work and leisure. J. Personal. Soc. Psychol. 56:815–22 [Google Scholar]
  37. Dalal RS, Bhave DP, Fiset J. 2014. Within-person variability in job performance: a theoretical review and research agenda. J. Manag. 40:1396–436 [Google Scholar]
  38. Dalal RS, Lam H, Weiss HM, Welch ER, Hulin CL. 2009. A within-person approach to work behavior and performance: concurrent and lagged citizenship-counterproductivity associations, and dynamic relationships with affect and overall job performance. Acad. Manag. J. 52:1051–66 [Google Scholar]
  39. Dale O, Hagen KB. 2007. Despite technical problems personal digital assistants outperform pen and paper when collecting patient diary data. J. Clin. Epidemiol. 60:8–17 [Google Scholar]
  40. Damasio A. 1994. Descartes’ Error Putnam, NY: Grosset
  41. Daniels K, Harris C. 2005. A daily diary study of coping in the context of the job demands–control–support model. J. Vocat. Behav. 66:219–37 [Google Scholar]
  42. Diener E, Larsen RJ. 1984. Temporal stability and cross-situational consistency of affective, behavioral, and cognitive responses. J. Personal. Soc. Psychol. 47:871–83 [Google Scholar]
  43. Diener E, Larsen RJ, Emmons RA. 1984. Person × situation interactions: choice of situations and congruence response models. J. Personal. Soc. Psychol. 47:580–92 [Google Scholar]
  44. Dormann C, Zijlstra FRH. 2003. Call centres: high on technology—high on emotions. Eur. J. Work Organ. Psychol. 12:305–10 [Google Scholar]
  45. Edwards JR. 2008. To prosper, organizational psychology should…overcome methodological barriers to progress. J. Organ. Behav. 29:469–91 [Google Scholar]
  46. Enders CK, Tofighi D. 2007. Centering predictor variables in cross-sectional multilevel models: a new look at an old issue. Psychol. Methods 12:121–38 [Google Scholar]
  47. Fisher CD, Minbashian A, Beckmann N, Wood RE. 2013. Task appraisals, emotions, and performance goal orientation. J. Appl. Psychol. 98:364–73 [Google Scholar]
  48. Fleeson WP. 2001. Toward a structure- and process-integrated view of personality: traits as density distributions of states. J. Personal. Soc. Psychol. 80:1011–27 [Google Scholar]
  49. Fleeson WP, Gallagher P. 2009. The implications of Big Five standing for the distribution of trait manifestation in behavior: fifteen experience-sampling studies and a meta-analysis. J. Personal. Soc. Psychol. 97:1097–114 [Google Scholar]
  50. Fleeson WP, Malanos AB, Achille NM. 2002. An intraindividual process approach to the relationship between extraversion and positive affect: Is acting extraverted as “good” as being extraverted?. J. Personal. Soc. Psychol. 83:1409–22 [Google Scholar]
  51. Forgas JP. 1995. Mood and judgment: the affect infusion model (AIM). Psychol. Bull. 117:39–66 [Google Scholar]
  52. Fredrickson BL. 2000. Extracting meaning from past affective experiences: the importance of peaks, ends, and specific emotions. Cogn. Emot. 14:577–606 [Google Scholar]
  53. Fredrickson BL, Kahneman D. 1993. Duration neglect in retrospective evaluations of affective episodes. J. Personal. Soc. Psychol. 65:45–55 [Google Scholar]
  54. Fullagar CJ, Kelloway EK. 2009. Flow at work: an experience sampling approach. J. Occup. Organ. Psychol. 82:595–615 [Google Scholar]
  55. Fuller JA, Stanton JM, Fisher GG, Spitzmuller C, Russell SS, Smith PC. 2003. A lengthy look at the daily grind: time series analysis of events, mood, stress, and satisfaction. J. Appl. Psychol. 88:1019–33 [Google Scholar]
  56. George G, Haas M, Pentland A. 2014. Big data and management. Acad. Manag. J. 57:321–26 [Google Scholar]
  57. George JM. 1990. Personality, affect, and behavior in groups. J. Appl. Psychol. 75:107–16 [Google Scholar]
  58. Ghose A, Yang S. 2009. An empirical analysis of search engine advertising: sponsored search in electronic markets. Manag. Sci. 55:1605–22 [Google Scholar]
  59. Glomb TM, Beal DJ, Yang T, Bhave DP. 2014. Staying power: emotional inertia as a moderator of event-affect relationships. Presented at Annu. Meet. Soc. Ind. Organ. Psychol., 29th, May 15–17, Honolulu, HI
  60. Graham JW. 2009. Missing data: making it work in the real world. Annu. Rev. Psychol. 60:549–76 [Google Scholar]
  61. Green AS, Rafaeli E, Bolger N, Shrout PE, Reis HT. 2006. Paper or plastic? Data equivalence in paper and electronic diaries. Psychol. Methods 11:87–105 [Google Scholar]
  62. Hamilton JD. 1994. Time Series Analysis Princeton, NJ: Princeton Univ. Press
  63. Harris C, Daniels K, Briner RB. 2003. A daily diary study of goals and affective well-being at work. J. Occup. Organ. Psychol. 76:401–10 [Google Scholar]
  64. Hersey RB. 1932. Rate of production and emotional state. Pers. J. 10:355–64 [Google Scholar]
  65. Hox JJ. 2010. Multilevel Analysis: Techniques and Applications New York:: Routledge, 2nd ed..
  66. Ilies R, Dimotakis N, De Pater IE. 2010a. Psychological and physiological reactions to high workloads: implications for well-being. Pers. Psychol. 63:407–36 [Google Scholar]
  67. Ilies R, Dimotakis N, Watson D. 2010b. Mood, blood pressure, and heart rate at work: an experience-sampling study. J. Occup. Health Psychol. 15:120–30 [Google Scholar]
  68. Ilies R, Scott BA, Judge TA. 2006. The interactive effects of personal traits and experienced states on intraindividual patterns of citizenship behavior. Acad. Manag. J. 49:561–75 [Google Scholar]
  69. Ilies R, Wilson KS, Wagner DT. 2009. The spillover of daily job satisfaction onto employees’ family lives: the facilitating role of work-family integration. Acad. Manag. J. 52:87–102 [Google Scholar]
  70. Jensen AR. 1998. The g Factor: The Science of Mental Ability Westport, CT: Praeger
  71. Judge TA, Locke EA, Durham CC, Kluger AN. 1998. Dispositional effects on job and life satisfaction: the role of core evaluations. J. Appl. Psychol. 83:17–34 [Google Scholar]
  72. Judge TA, Woolf EF, Hurst C. 2009. Is emotional labor more difficult for some than for others? A multilevel, experience-sampling study. Pers. Psychol. 62:57–88 [Google Scholar]
  73. Kahneman D, Krueger AB, Schkade DA, Schwarz N, Stone AA. 2004. A survey method for characterizing daily life experience: the day reconstruction method. Science 306:1776–80 [Google Scholar]
  74. Kahneman D, Riis J. 2005. Living, and thinking about it: two perspectives on life. The Science of Well-Being Huppert FA, Baylis N, Keverne B. 285–304 New York: Oxford Univ. Press [Google Scholar]
  75. Kammeyer-Mueller JD, Judge TA, Scott BA. 2009. The role of core self-evaluations in the coping process. J. Appl. Psychol. 94:177–95 [Google Scholar]
  76. Klinger E. 1978. Modes of normal conscious flow. The Stream of Consciousness: Scientific Investigations into the Flow of Human Experience Pope KS, Singer JL. 225–58 New York: Plenum [Google Scholar]
  77. Klinger E, Barta SG, Maxeiner ME. 1980. Motivational correlates of thought content frequency and commitment. J. Personal. Soc. Psychol. 39:1222–37 [Google Scholar]
  78. Kuppens P, Allen NB, Sheeber LB. 2010. Emotional inertia and psychological maladjustment. Psychol. Sci. 21:984–91 [Google Scholar]
  79. Laurila JK, Gatica-Perez D, Aad I, Blom J, Bornet O et al. 2012. The Mobile Data Challenge: big data for mobile computing research. Presented at Mob. Data Chall. Workshop, June 18–19, Newcastle, UK
  80. Le B, Choi HN, Beal DJ. 2006. Pocket-sized psychology studies: exploring daily diary software for Palm Pilots. Behav. Res. Methods 38:325–32 [Google Scholar]
  81. Lewig KA, Dollard MF. 2003. Emotional dissonance, emotional exhaustion and job satisfaction in call centre workers. Eur. J. Work Organ. Psychol. 12:366–92 [Google Scholar]
  82. Loi R, Yang J, Diefendorff JM. 2009. Four-factor justice and daily job satisfaction: a multilevel investigation. J. Appl. Psychol. 94:770–81 [Google Scholar]
  83. Mabe PA, West SG. 1982. Validity of self-evaluation of ability: a review and meta-analysis. J. Appl. Psychol. 67:280–96 [Google Scholar]
  84. Meade AW, Craig SB. 2012. Identifying careless responses in survey data. Psychol. Methods 17:437–55 [Google Scholar]
  85. Mehl MR, Conner TS. 2012. Handbook of Research Methods for Studying Daily Life New York: Guilford
  86. Mehl MR, Robbins ML. 2012. Naturalistic observation sampling: the electronically activated recorder (EAR). See Mehl & Conner 2012, pp. 176–92
  87. Miner AG, Glomb TM. 2010. State mood, task performance, and behavior at work: a within-persons approach. Organ. Behav. Hum. Decis. Process. 112:43–57 [Google Scholar]
  88. Miner AG, Glomb TM, Hulin C. 2005. Experience sampling mood and its correlates at work. J. Occup. Organ. Psychol. 78:171–93 [Google Scholar]
  89. Mitchell TR, James LR. 2001. Building better theory: time and the specification of when things happen. Acad. Manag. Rev. 26:530–47 [Google Scholar]
  90. Murdoch TB, Detsky AS. 2013. The inevitable application of big data to health care. JAMA 309:1351–52 [Google Scholar]
  91. Newman DA. 2003. Longitudinal modeling with randomly and systematically missing data: a simulation of ad hoc, maximum likelihood, and multiple imputation techniques. Organ. Res. Methods 6:328–62 [Google Scholar]
  92. Nezlek JB. 2001. Multilevel random coefficient analyses of event- and interval-contingent data in social and personality psychology research. Personal. Soc. Psychol. Bull. 27:771–85 [Google Scholar]
  93. Nezlek JB. 2012. Multilevel modeling analyses of diary-style data. See Mehl & Conner 2012, pp. 357–83
  94. Niedenthal PM. 2007. Embodying emotion. Science 316:1002–5 [Google Scholar]
  95. Ostroff C. 1993. Comparing correlations based on individual-level and aggregated data. J. Appl. Psychol. 78:569–82 [Google Scholar]
  96. Paulhus DL. 2002. Socially desirable responding: the evolution of a construct. The Role of Constructs in Psychological and Educational Measurement Brown HI, Jackson DN, Wiley DE. 49–69 Mahwah, NJ: Erlbaum [Google Scholar]
  97. Ployhart RE, Moliterno TP. 2011. Emergence of the human capital resource: a multilevel model. Acad. Manag. Rev. 36:127–50 [Google Scholar]
  98. Ployhart RE, Van Iddekinge CH, MacKenzie WI. 2011. Acquiring and developing human capital in service contexts: the interconnectedness of human capital resources. Acad. Manag. J. 54:353–68 [Google Scholar]
  99. Ployhart RE, Vandenberg RJ. 2010. Longitudinal research: the theory, design, and analysis of change. J. Manag. 36:94–120 [Google Scholar]
  100. Ployhart RE, Weekley JA, Baughman K. 2006. The structure and function of human capital emergence: a multilevel examination of the attraction-selection-attrition model. Acad. Manag. J. 49:661–77 [Google Scholar]
  101. Podsakoff PM, MacKenzie SB, Lee JY, Podsakoff NP. 2003. Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol. 88:879–903 [Google Scholar]
  102. Podsakoff PM, MacKenzie SB, Podsakoff NP. 2012. Sources of method bias in social science research and recommendations on how to control it. Annu. Rev. Psychol. 63:539–69 [Google Scholar]
  103. Ram N, Gerstorf D. 2009. Time-structured and net intraindividual variability: tools for examining the development of dynamic characteristics and processes. Psychol. Aging 24:778–91 [Google Scholar]
  104. Redelmeier DA, Kahneman D. 1996. Patient’s memories of painful medical treatments: real-time and retrospective evaluations of two minimally invasive procedures. Pain 116:3–8 [Google Scholar]
  105. Reis HT, Gable SL. 2000. Event-sampling and other methods for studying everyday experience. Handbook of Research Methods in Social and Personality Psychology Reis TH, Judd MC. 190–222 New York: Cambridge Univ. Press [Google Scholar]
  106. Robinson MD, Clore GL. 2002. Belief and feeling: evidence for an accessibility model of emotional self-report. Psychol. Bull. 128:934–60 [Google Scholar]
  107. Sbarra DA, Ferrer E. 2006. The structure and process of emotional experience following nonmarital relationship dissolution: dynamic factor analyses of love, anger, and sadness. Emotion 6:224–38 [Google Scholar]
  108. Schmidt FL, Le H, Ilies R. 2003. Beyond alpha: an empirical examination of the effects of different sources of measurement error on reliability estimates for measures of individual-differences constructs. Psychol. Methods 8:206–24 [Google Scholar]
  109. Schwartz JE, Stone AA. 1998. Strategies for analyzing ecological momentary assessment data. Health Psychol. 17:6–16 [Google Scholar]
  110. Shadish WR, Cook TD, Campbell DT. 2002. Experimental and Quasi-Experimental Designs for Generalized Causal Inference Boston: Houghton Mifflin
  111. Shiffman S, Stone AA, Hufford MR. 2008. Ecological momentary assessment. Annu. Rev. Clin. Psychol. 4:1–32 [Google Scholar]
  112. Shockley KM, Allen TD. 2013. Episodic work–family conflict, cardiovascular indicators, and social support: an experience sampling approach. J. Occup. Health Psychol. 18:262–75 [Google Scholar]
  113. Shockley KM, Ispas D, Rossi ME, Levine EL. 2012. A meta-analytic investigation of the relationship between state affect, discrete emotions, and job performance. Hum. Perform. 25:377–411 [Google Scholar]
  114. Silvia PJ, Kwapil TR, Eddington KM, Brown LH. 2013. Missed beeps and missing data: dispositional and situational predictors of nonresponse in experience sampling research. Soc. Sci. Comput. Rev. 31:471–81 [Google Scholar]
  115. Song Z, Foo MD, Uy MA. 2008. Mood spillover and crossover among dual-earner couples: a cell phone event sampling study. J. Appl. Psychol. 93:443–52 [Google Scholar]
  116. Sonnentag S. 2001. Work, recovery activities, and individual well-being: a diary study. J. Occup. Health Psychol. 6:196–210 [Google Scholar]
  117. Sonnentag S. 2003. Recovery, work engagement, and proactive behavior: a new look at the interface between nonwork and work. J. Appl. Psychol. 88:518–28 [Google Scholar]
  118. Spector PE, Brannick MT. 2011. Methodological urban legends: the misuse of statistical control variables. Organ. Res. Methods 14:287–305 [Google Scholar]
  119. Stone AA, Broderick JE, Shiffman SS, Schwartz JE. 2004. Understanding recall of weekly pain from a momentary assessment perspective: absolute agreement, between- and within-person consistency, and judged change in weekly pain. Pain 107:61–69 [Google Scholar]
  120. Stone AA, Smyth JM, Pickering T, Schwartz J. 1996. Daily mood variability: form of diurnal patterns and determinants of diurnal patterns. J. Appl. Soc. Psychol. 26:1286–305 [Google Scholar]
  121. Swallow KM, Zacks JM, Abrams RA. 2009. Event boundaries in perception affect memory encoding and updating. J. Exp. Psychol. Gen. 138:236–57 [Google Scholar]
  122. Swider BW, Zimmerman RD. 2010. Born to burnout: a meta-analytic path model of personality, job burnout, and work outcomes. J. Vocat. Behav. 76:487–506 [Google Scholar]
  123. Taylor SG, Bedeian AG, Cole MS, Zhang Z. 2015. Developing and testing a dynamic model of workplace incivility change. J. Manag In press [Google Scholar]
  124. Totterdell P, Holman D. 2003. Emotion regulation in customer service roles: testing a model of emotional labor. J. Occup. Health Psychol. 8:55–73 [Google Scholar]
  125. Trougakos JP, Beal DJ, Cheng BH, Hideg I, Zweig D. 2015. Too drained to help: a resource depletion perspective on daily interpersonal citizenship behaviors. J. Appl. Psychol. 100:22736 [Google Scholar]
  126. Trougakos JP, Hideg I, Cheng BH, Beal DJ. 2014. Lunch breaks unpacked: the role of autonomy as a moderator of recovery during lunch. Acad. Manag. J. 57:405–21 [Google Scholar]
  127. Trull TJ, Ebner-Priemer U. 2013. Ambulatory assessment. Annu. Rev. Clin. Psychol. 9:151–76 [Google Scholar]
  128. Uy MA, Foo MD, Aguinis H. 2010. Using experience sampling methodology to advance entrepreneurship theory and research. Organ. Res. Methods 13:31–54 [Google Scholar]
  129. Weiss HM, Cropanzano R. 1996. Affective events theory: a theoretical discussion of the structure, causes, and consequences of affective experiences at work. Res. Organ. Behav. 19:1–74 [Google Scholar]
  130. Weiss HM, Nicholas JP, Daus CS. 1999. An examination of the joint effects of affective experiences and job beliefs on job satisfaction and variations in affective experiences over time. Organ. Behav. Hum. Decis. Process. 78:1–24 [Google Scholar]
  131. Weiss HM, Rupp DE. 2011. Experiencing work: an essay on a person-centric work psychology. Ind. Organ. Psychol. 4:83–97 [Google Scholar]
  132. West SG, Hepworth JT. 1991. Statistical issues in the study of temporal data: daily experiences. J. Personal. 59:609–62 [Google Scholar]
  133. Wheeler L, Reis HT. 1991. Self-recording of everyday life events: origins, types, and uses. J. Personal 59:339–54 [Google Scholar]
  134. Wilhelm FH, Roth WT, Sackner MA. 2003. The LifeShirt: an advanced system for ambulatory measurement of respiratory and cardiac function. Behav. Modif. 27:671–91 [Google Scholar]
  135. Wilson RE, Gosling SD, Graham LT. 2012. A review of Facebook research in the social sciences. Perspect. Psychol. Sci. 7:203–20 [Google Scholar]
  136. Wolf G. 2010. The data-driven life. New York Times, May 2, p. MM38
  137. Zacks JM, Speer NK, Swallow KM, Braver TS, Reynolds JR. 2007. Event perception: a mind-brain perspective. Psychol. Bull. 133:273–93 [Google Scholar]
  138. Zyphur MJ, Oswald FL. 2015. Bayesian estimation and inference: a user’s guide. J. Manag 41:390420 [Google Scholar]
/content/journals/10.1146/annurev-orgpsych-032414-111335
Loading
/content/journals/10.1146/annurev-orgpsych-032414-111335
Loading

Data & Media loading...

  • Article Type: Review Article
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error