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Abstract

The initial sample consists of all firms that are listed at the German Stock Exchange in the CDAX-index. The CD AX is a composite index which includes the shares of all domestic companies listed in Prime Standard and General Standard (cf. Figure 8). It represents the German equity market in its entirety, i.e., all companies listed on FWB Frankfurter Wertpapierbörse (Frankfurt Stock Exchange). All in all, 678 firms were identified.

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References

  1. Figure adopted from Deutsche Börse Group.

    Google Scholar 

  2. Hite discussing Klein (1986), p. 697.

    Google Scholar 

  3. Referring to different numbers of firms and observed transactions see also Schipper & Smith (1986), p. 157. They report 63 parent firms, i.e., a much smaller amount of firms than the number of observed equity carve-outs in their sample.

    Google Scholar 

  4. Cf. Venkatraman & Tanriverdi (2004), p. 60.

    Google Scholar 

  5. “Data is considered to be objective when its meaning is the same across firms. The source of the data is considered to be secondary when the data is obtained from archives and databases outside of the firms studied” (Venkatraman & Tanriverdi 2004, p. 51).

    Google Scholar 

  6. Chang & Singh (2000), p. 740.

    Google Scholar 

  7. Cf. Villalonga (2004b), p. 501.

    Google Scholar 

  8. See, e.g., Villalonga (2004a).

    Google Scholar 

  9. See the list of sample cases and firms in Table 3 in Appendix 1.

    Google Scholar 

  10. Cf. Anslinger et al. (2003).

    Google Scholar 

  11. See Rieker (2005) for more details and examples.

    Google Scholar 

  12. Cf. Mellewigt & Kloninger (2003), p. 18 f.

    Google Scholar 

  13. Cf. Villalonga & McGahan (2005), p. 1197.

    Google Scholar 

  14. See Chapter 2.2.

    Google Scholar 

  15. See also Chapter 3.4 and the overview on exemplary empirical studies in Table 2 in Appendix 1.

    Google Scholar 

  16. Cf. Chang (1996), p. 590.

    Google Scholar 

  17. Cf. Bergh (1995), p. 229; Duhaime & Baird (1987), p. 489; Duhaime & Grant (1984), p. 310.

    Google Scholar 

  18. Cf. Duhaime & Baird (1987), p. 489; Duhaime & Grant (1984), p. 310.

    Google Scholar 

  19. Cf. Morrow et al. (2004), p. 198.

    Google Scholar 

  20. Cf. Agle et al. (2006), p. 166.

    Google Scholar 

  21. Cf. Bergh (1995), p. 229.

    Google Scholar 

  22. Product market relatedness is measured as the sales-weighted concentric diversification index and is defined as ∑ 1=1, whereby Pkl is the percentage of firm k’s sales that is in industry l defined at the four-digit SIC level, dil is a weight whose value depends on the distance between the industry i that is being exited and the other industries l in which the parent has operations. dil takes the value 2 if i and l are within the same three-digit SIC, 1 if i and l are within the same two-digit SIC, and 0 if i and l are in different two-digit SIC industries. Cf. Chang & Singh (1999), p. 1027.

    Google Scholar 

  23. Cf. Bergh (1995), p. 228; Chen & Guo (2005), p. 411.

    Google Scholar 

  24. Cf. Chi et al. (2004), p. 230; John & Ofek (1995), p. 110; Steiner (1997), p. 236.

    Google Scholar 

  25. Chi et al. (2004), p. 230; see also the study by Lubatkin et al. (1993) quoted there and Mellewigt & Kloninger (2003), p. 19.

    Google Scholar 

  26. Cf. Bühner et al. (2004), p. 734.

    Google Scholar 

  27. Cf. Gordon et al. (2000), p. 923 and 925.

    Google Scholar 

  28. Cf. Bergh (1998), p. 143; Bethel & Liebeskind (1993), p. 22; Hoskisson et al. (1994), p. 1222; Villalonga & McGahan (2005), p. 1197.

    Google Scholar 

  29. Referring to this problem, see also Bühner et al. (2004), p. 735.

    Google Scholar 

  30. Pedersen & Thomsen (2003), p. 29.

    Google Scholar 

  31. Cf. Thomsen & Pedersen (2000), p. 696; Pedersen & Thomsen (2003), p. 40.

    Google Scholar 

  32. Owner categories: 1 = banks, 2 = institutional investors (financial services), 3 = (other nonfinancial) firms, 4 = individual or family ownership, 5 = government, 6 = free float.

    Google Scholar 

  33. Cf. Agle et al. (2006), p. 166; Beckman et al. (2004), p. 265; see also Brealey & Myers (2003), p. 680.

    Google Scholar 

  34. Boyd et al. (2005), p. 249.

    Google Scholar 

  35. Cf. Beck et al. (2006), p. 13. For more information on the use of dummy variables in regression equations, see, e.g., Greene (2000), pp. 318 ff.

    Google Scholar 

  36. See Dobrev & Carroll (2003) for a review as well as new theoretical ideas and empirical findings on the impact of size effects on organizational outcomes.

    Google Scholar 

  37. Cf. Datta et al. (2003), p. 108; Dobrev et al. (2003), p. 266 f.; George (2005), p. 667; Haveman (1993), p. 608.

    Google Scholar 

  38. Cf. Dawley et al. (2002), p. 707.

    Google Scholar 

  39. Cf. Agarwal et al. (2002), p. 985, and the studies quoted there.

    Google Scholar 

  40. Cf. Servaes (1996), p. 1204 f.; see also Jandik & Makhija (2005), p. 67 ff.

    Google Scholar 

  41. For an overview on antecedents of business exit, see Chapter 2 or see Brauer (2006) for a complete review of the literature. Referring to the importance of a firm’s industrial environment, see, e.g., Barker & Duhaime (1997), p. 18.

    Google Scholar 

  42. Cf. Dobrev et al. (2001), p. 1316; Sorenson (2003), p. 453 f.

    Google Scholar 

  43. See Statistisches Bundesamt (2004, 2005a, 2005b, 2006).

    Google Scholar 

  44. Cf. Dawley et al. (2002), p. 705; Dobrev et al. (2001), p. 1321; Dobrev et al. (2003), p. 271; Ravenscraft & Scherer (1991), p. 433.

    Google Scholar 

  45. Cf. Cheng & Kesner (1997), p. 1.

    Google Scholar 

  46. Cf. Steensma & Corley (2001), p. 271 f.

    Google Scholar 

  47. Cf. Sommers et al. (1987), p. 18.

    Google Scholar 

  48. Cf. Bansal (2005), p. 201; see also Bourgeois (1981), p. 30 and 35.

    Google Scholar 

  49. Cf. George (2005), p. 662.

    Google Scholar 

  50. Cf. Barker & Duhaime (1997), p. 20 and 33. See also the studies quoted there for further details.

    Google Scholar 

  51. Cf. Love & Nohria (2005), p. 1088. Bourgeois (1981) and Singh (1986) also propose this distinction.

    Google Scholar 

  52. Cf. Bergh (1997), p. 722; Cheng & Kesner (1997), pp. 7 f.; Love & Nohria (2005), p. 1095; Morrow et al. (2004), p. 199; Singh (1986), p. 573.

    Google Scholar 

  53. Cf., e.g., Datta et al. (2003), p. 108.

    Google Scholar 

  54. Cf. Backhaus et al. (2006), p. 89 ff.; Menard (2002), pp. 75–78; Field (2003), p. 201 f.; Hutcheson & Sofroniou (1999), p. 83.

    Google Scholar 

  55. Cf. Chang & Singh (1999), p. 1028; Greene (2000), p. 813; Hoetker (2007), p. 332.

    Google Scholar 

  56. Cf. Backhaus et al. (2006), p. 426 ff.; Field (2003), p. 165; Greene (2000), p. 813 ff.; Hoetker (2007), p. 332; Menard (2002), p. 12.

    Google Scholar 

  57. Cf. Backhaus et al. (2006), p. 430 f.

    Google Scholar 

  58. Cf. Arnold (1982), p. 150.

    Google Scholar 

  59. Hoetker (2007), p. 338 (italics in the original).

    Google Scholar 

  60. See the procedure outlined by Arnold (1982), pp. 149–156. Haleblian & Finkelstein (1993) and Datta et al. (2003) provide examples for sub-group analyses according to the exemplary procedure recommended by Arnold. See also Backhaus et al. (2006), p. 74 ff.

    Google Scholar 

  61. Cf. Allison (1999), p. 188; Fahrmeir et al. (1999), p. 450.

    Google Scholar 

  62. Cf. Greene (2000), p. 155. See, e.g., the Chi-square-table in Backhaus et al. (2006), p. 818. For ?? = 0.95 and one degree of freedom in the two-group case the value for chi2 (0.95; 1) is 3.8415.

    Google Scholar 

  63. Hoetker (2007), p. 337.

    Google Scholar 

  64. For a detailed description of this procedure with an example see Allison (1999), p. 194 ff. See also Hoetker (2004), p. 9 f.

    Google Scholar 

  65. Hoetker (2007), p. 338. See also Hoetker (2006), p. 513, for an example.

    Google Scholar 

  66. Hoetker (2006), p. 512, footnote 6.

    Google Scholar 

  67. Cf. Hoetker (2007), p. 338; see also Greene (2000), p. 153 ff. For examples of how to interpret the ratios of beta coefficients see Hoetker (2006), p. 512 f.

    Google Scholar 

  68. Cf. Altman (1968), p. 591.

    Google Scholar 

  69. Cf. Bortz (2005), p. 605 and 617; Greene (2000), p. 833, footnote 19. For an application of this method in different fields, see, e.g., Altman’s (1968) seminal study in finance, Johnson’s (1971) study on market segmentation in marketing, and Peng et al. (2004) as a more recent example from management research.

    Google Scholar 

  70. Altman (1968), p. 592.

    Google Scholar 

  71. Cf. Backhaus et al. (2006), p. 154 ff.

    Google Scholar 

  72. Cf. Backhaus et al. (2006), p. 187 f.

    Google Scholar 

  73. Cf. Bortz (2005), p. 624 f.

    Google Scholar 

  74. Cf. Peng et al. (2004), p. 1122.

    Google Scholar 

  75. Cf. Chang & Singh (1999), p. 1029, especially footnote 7.

    Google Scholar 

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(2008). Methods. In: Legitimacy Needs as Drivers of Business Exit. Gabler. https://doi.org/10.1007/978-3-8349-9759-3_4

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