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An Integrative Framework of Influences on Behavior

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Design of Incentive Systems

Part of the book series: Contributions to Management Science ((MANAGEMENT SC.))

Abstract

The goals of this chapter are (1) to introduce important theories and concepts which are employed in the discussion on the hypotheses of incentive and sorting effects in Chap. 4, (2) to introduce existing economic frameworks in order to get an overview of potential contingencies concerning incentive and sorting effects, and (3) to identify literature gaps in the observation of contingency variables and develop an integrative framework of variables under investigation in the experiment. The integrative framework guides the discussion on the experimental design in Chap. 3 particularly concerning environmental variables and is specified in Chaps. 4 and 5 particularly concerning individual variables. The three goals are addressed in the subsequent three sub-sections.

Behaviour cannot be invented in the armchair. It has to be observed.

Reinhard Selten (1930 Breslau)

Selten (1998), p. 414

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Notes

  1. 1.

    More recently prescriptive decision theory has been suggested to be a third area of decision making research. In particular, business practice might be interested in this field of decision making, because its aim is to support decision makers in their decisions. As it is not meant to deal with tools for improving decision quality in this text, prescriptive decision theory is not introduced as single area of decision research (Cf. Goodwin et al. (1994)). Moreover, in some literature normative and prescriptive decision theory is used interchangeably (Cf. Bamberg and Coenenberg (2002), p. 1).

  2. 2.

    A prominent critic of the assumption of unbounded rationality is Simon (1955).

  3. 3.

    Cf. Laux (1998), p. 2; Bamberg and Coenenberg (2002), pp. 1ff.

  4. 4.

    Cf. Eisenführ and Weber (1993), p. 2; Laux (1998), p. 2.

  5. 5.

    This is only selective and very brief presentation of relevant theories. For instance, the social cognition theory is not considered (Cf. Wood and Bandura (1989)). For this and further psychological theories and discussion refer to Gerhart and Rynes (2003), pp. 119 ff., Birnberg et al. (2007) or Pinder (2008). For the transaction cost theory refer e.g. to Williamson (1981).

  6. 6.

    In literature psychological theories related to motivation are also often classified into content-based or process-based theories. Content-based theories deal with characteristics, contents and structure of motives, whereas process-based theories try to explain the emergence of motivation and its effects on behavior. Need hierarchy, two factor theory and cognitive evaluation theory can be classified as part of the content-based group; expectancy, goal-setting or equity theory generally belong to the process-based group of theories (Cf. Staehle et al. (1999), pp. 218ff.; Brandenberg (2001), p. 76).

  7. 7.

    The classification in Fig. 2.1 is not necessarily free of overlap. For instance, by means of the agency theory statements about the general importance of money can be inferred, too.

  8. 8.

    Cf. Sorger (2000), pp. 1ff.; Bonner (2008), p. 28.

  9. 9.

    Cf. von Neumann and Morgenstern (1947); Savage (1954) drawn from Sorger (2000).

  10. 10.

    Cf. Kahneman and Tversky (1979).

  11. 11.

    Cf. Eichenberger (1992); Further, refer to Allais (1953) or Ellsberg (1961) for early studies about violations to expected utility theory or to Tversky and Kahneman (1981) for an anomaly called the framing effect.

  12. 12.

    Cf. Gerhart and Rynes (2003), pp. 48ff.; Cather (2010), pp. 127ff.; Refer to Read (2007), pp. 45ff. for utility in a historical context.

  13. 13.

    Cf. Maslow (1943); Herzberg (1968); Deci and Ryan (1985) drawn from Pinder (2008), pp. 71ff., 86ff., 208ff.

  14. 14.

    Cf. Lambert (2007), p. 247.

  15. 15.

    Cf. Young and Lewis (1995), p. 56; Gerhart and Rynes (2003), pp. 8, 138; see also Sprinkle and Williamson (2007), who structure their review of experiments in management accounting according to agency principles.

  16. 16.

    Cf. Macho-Stadler et al. (2005), p. 5.

  17. 17.

    Cf. Jensen and Meckling (1976); Fama (1980); Petersen (1989), pp. 22ff.; Frese (1992), pp. 71ff.; Gibbons (1998), pp. 2f.; Laffont and Martimort (2002); Macho-Stadler et al. (2005), pp. 1, 4; Salanié (2005), pp. 5f.

  18. 18.

    Cf. Demski and Feltham (1978); Milgrom and Roberts (1992), pp. 149 ff., 166 ff.

  19. 19.

    Cf. Bamberg and Ballwieser (1987, pp. 9 ff.; Saam (2007), p. 827; Küpper (2008), pp. 83 ff.; Refer also to Saam (2007), pp. 826–829 for a more in depth overview of agency literature.

  20. 20.

    Cf. Baiman (1990), pp. 342f.

  21. 21.

    Cf. Milgrom and Roberts (1992), pp. 186f.; Brickley et al. (2009), pp. 459f.

  22. 22.

    Cf. Milgrom and Roberts (1992), pp. 166ff.

  23. 23.

    Cf. Milgrom and Roberts (1992), pp. 149ff.; Macho-Stadler et al. (2005), pp. 11f.; Early important contributions to adverse selection problems come from Akerlof (1970); Rothschild and Stiglitz (1976). For an overview to markets with asymmetric information refer to Lofgren et al. (2002).

  24. 24.

    Cf. Spence (1973); Salop and Salop (1976); Spence (1976).

  25. 25.

    Cf. e.g. Demski and Feltham (1978); Fama (1980).

  26. 26.

    Cf. Fischer (1995), p. 321.

  27. 27.

    Cf. Baiman (1990), pp. 344ff.

  28. 28.

    Cf. Baiman (1990), p. 345.

  29. 29.

    Cf. Demski and Feltham (1978), pp. 339f.; Sprinkle (2003).

  30. 30.

    Cf. Laux (1998), p. 2; Bamberg and Coenenberg (2002), pp. 1ff.; Lambert (2007).

  31. 31.

    Cf. Young and Lewis (1995), p. 57.

  32. 32.

    Cf. Allais (1953); Simon (1955); Herzberg et al. (1959), p. 114.

  33. 33.

    Cf. Ashton und Ashton (1995b), pp. 57f.

  34. 34.

    Cf. Weiner (1996), p. 219.

  35. 35.

    Cf. Wiemann (1998), p. 36; Brandenberg (2001), p. 67; Heide (2001); Pinder (2008).

  36. 36.

    Cf. Lewin (1946); Rotter (1954); Atkinson (1974); For comprehensive reviews of this literature refer to Weiner (1996), pp. 153ff. or Beckmann and Heckhausen (2006); For a review of Vroom (1964)’s theory refer to Pinder (2008), pp. 363ff.

  37. 37.

    Cf. Ryan (1958); Locke (1968); For a review of goal directed theories refer to Pinder (2008), pp. 389ff.

  38. 38.

    Cf. Adams (1963).

  39. 39.

    Refer for instance to Waller (1985); Camerer and Hogarth (1999); Bonner and Sprinkle (2002), p. 304 or Bonner (2008).

  40. 40.

    Cf. Waller and Chow (1985), p. 461.

  41. 41.

    Cf. Waller and Chow (1985), p. 461.

  42. 42.

    Cf. Camerer and Hogarth (1999).

  43. 43.

    Cf. Smith and Walker (1993).

  44. 44.

    Cf. Camerer and Hogarth (1999), p. 9.

  45. 45.

    Cf. Camerer and Hogarth (1999).

  46. 46.

    Bonner and Sprinkle (2002) use the term performance for indicating human accomplishments within laboratory experiments. In this research the term productivity is preferred, because it not only considers output but also input by definition. However, within experiments the terms can be often used interchangeably and express an output measured within and against certain standards. As will be explained below, productivity in the present experiment is defined by the amount of anagrams solved correctly (output) within 10 minutes (input) for one participant.

  47. 47.

    In their research performance has to be quantifiable, i.e. it needs to be measured according to a certain standard. This implicitly means that results of multi-person environments or markets are not considered in this study. Tasks including decisions between lotteries or certainty equivalents are not included, because of the problem of setting a normative performance standard.

  48. 48.

    Cf. Bonner and Sprinkle (2002), p. 304; In Bonner (2008), p. 198 the framework is similar. A main difference is that the incentive-scheme category is subsumed in environmental variables.

  49. 49.

    Bonner and Sprinkle (2002), p. 311.

  50. 50.

    Cf. Bonner and Sprinkle (2002).

  51. 51.

    Cf. Bonner (2008).

  52. 52.

    Cf. Bonner (2008).

  53. 53.

    Refer to Camerer (1995), pp. 652ff. for a review on framing effects.

  54. 54.

    Cf. Bonner (2008), p. 88.

  55. 55.

    Cf. Camerer and Hogarth (1999), p. 9.

  56. 56.

    Cf. Bailey and Fessler (2008).

  57. 57.

    As task difficulty is not measured objectively by taking different tasks, but subjectively by prompting individuals’ perception of task difficulty, it can be considered as an individual contingency (cf. Waller and Chow (1985), pp. 461f.). However, as the subjective perception reflects the influence of task difficulty in general, in the framework it is placed as environmental determinant. Task attractiveness is considered indirectly through elements of individuals’interest in a task (Cf. 4.2.1, 4.2.2.3).

  58. 58.

    Cf. Cadsby et al. (2007), p. 388; Hyatt and Taylor (2008), p. 42.

  59. 59.

    Cf. Bonner (2008), pp. 100ff.

  60. 60.

    Cf. Bonner (2008), p. 103.

  61. 61.

    Cf. Bonner and Sprinkle (2002), pp. 313ff.; Lazear (2004).

  62. 62.

    Cf. Bonner et al. (2000), p. 40; Gerhart and Rynes (2003), pp. 151f.; Chiappori and Salanié (2003), p. 116; Lazear (2004), p. 21; Cadsby et al. (2007), p. 387; Eriksson and Villeval (2008), pp. 412f.

  63. 63.

    Rotter (1954), p. 85.

  64. 64.

    Cf. Lewin (1946); Rotter (1954), p. 85.

  65. 65.

    Cf. Heckhausen (2006), pp. 3ff.; Pinder (2008), p. 3; Refer to von Rosenstiel (1999) for a good text on motivational foundations of incentives and an introduction to relevant motivational theories.

  66. 66.

    Cf. Staehle et al. (1999), pp. 149–164.

  67. 67.

    Cf. Waller and Chow (1985), pp. 461f.

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    Dennis D. Fehrenbacher

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Fehrenbacher, D.D. (2013). An Integrative Framework of Influences on Behavior. In: Design of Incentive Systems. Contributions to Management Science. Physica, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33599-0_2

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