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Review of Empirical Research within RBT

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Abstract

As outlined in chapter 2, the importance of firm resources for gaining rents, i.e., the RBT, seems no longer questionable in theory, but empirical evidence on its role in strategic management is still in progress. In other words, RBT has become theoretically established in strategic management, yet, the question where we empirically stand is still to be resolved.246 Whether the central propositions of RBT withstand — overall — empirical testing is still a question unanswered, as is the query whether these empirical results might even revise RBT in general.

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References

  1. Cf. Wernerfelt (1995), p. 171f; Hoskisson et al. (1999), p. 437ff; Ambrosini/Bowman (2001), p. 825.

    Google Scholar 

  2. Cf. Eisenhardt (1989), p. 549.

    Google Scholar 

  3. Barney (2001), p. 42.

    Google Scholar 

  4. In retrieving a representative sample of empirical RBT articles, I followed David and Han’s (2004) systematics within their comprehensive review on transaction cost economics. Cf. David/ Han (2004), p. 42ff.

    Google Scholar 

  5. Cf. Light/ Pillemer (1984), p. 35.

    Google Scholar 

  6. Cf. Hunter/ Schmidt (1990), p. 507ff.

    Google Scholar 

  7. David/ Han (2004), p. 42 citing Cooper (1989), p. 58, while the emphases are added by David and Han.

    Google Scholar 

  8. Cf. Wernerfelt (1984).

    Google Scholar 

  9. Cf. Kyle et al. (2004).

    Google Scholar 

  10. Kyle et al. (2004), p. 99, capital letters added.

    Google Scholar 

  11. At this point, David and Han (2004) decided to further include keywords that would distinguish between theoretical and empirical articles, i.e., they included additional keywords such as DATA, TEST, STATISTICAL, etc. Cf. David/ Han (2004), p. 43. I followed their advice and tried to include these additional keywords, yet, after checking the results within the database for relevant RBT studies which have been frequently cited, important studies were missing, e.g., Knott (2003), Sharma and Vredenburg (1998), or Miller and Shamsie (1996). Thus, I decided not to include these keywords.

    Google Scholar 

  12. Cf. David/ Han (2004), p. 43.

    Google Scholar 

  13. Gylfason (2001), p. 558, capital letters added.

    Google Scholar 

  14. Also, the article of Yu and Krishnan (2004) within the Information Systems Journal discusses RESOURCE-BASED agents in the context of a conceptual framework for agent-based agile manufacturing cells and argues different PERFORMANCE effects of these agents, which is obviously not a RBT-related contribution. Cf. Yu/ Krishnan (2004), p. 93. And similarly, Nie (2003) within Policy Science explores the drivers of natural RESOURCE-BASED political conflicts, focusing on what factors turn “...the common political conflict into the high-level, symbolic, and SUSTAINED political conflict?” Nie (2003), p. 307, capital letters added.

    Google Scholar 

  15. Cf. Priem/ Butler (2001), p. 33.

    Google Scholar 

  16. Cf. Markman et al. (2004), p. 540.

    Google Scholar 

  17. Cf. Wernerfelt (1995), p. 172.

    Google Scholar 

  18. Cf. Barney/ Arikan (2001), p. 146.

    Google Scholar 

  19. Cf. Hansen/ Wernerfelt (1989); Rumelt (1991); Ingram/Baum (1997); Mauri/Michaels (1998). “This brings us to our major result that firm effects exist in the form of positive focus effects. That is, some differences in performance can be explained by efficiency differences firms experience in transferring competencies to widely varying markets. Interpreted in this way, this finding not only supports the revisionist view, it enriches it, since it also tells us something about the sources of efficiency differences.” Wernerfelt/Montgomery (1988), p. 250.

    Google Scholar 

  20. Cf. De Carolis/ Deeds (1999); Hoopes/Postrel (1999); Schroeder et al. (2002); Berman et al. (2002); De Carolis (2003); Carmeli/Tishler (2004a+b); Markman et al. (2004); Ray et al. (2004).

    Google Scholar 

  21. Cf. De Carolis (2003); Spanos/Lioukas (2001); Tripsas (1997).

    Google Scholar 

  22. Cf. Bates/ Flynn (1995); Christmann (2000); Schroeder et al. (2002).

    Google Scholar 

  23. Cf. De Carolis (2003); Spanos/Lioukas (2001).

    Google Scholar 

  24. Cf. Kraatz/ Zajac (2001); De Saá-Pérez/García-Falcón (2002); Spanos/Lioukas (2001).

    Google Scholar 

  25. Cf. Borch et al. (1999); Gulati (1999); McEvily/Zaheer (1999).

    Google Scholar 

  26. Cf. Carmeli/ Tishler (2004a+b); Combs/Ketchen (1999); Deephouse (2000); Rao (1994).

    Google Scholar 

  27. Cf. Carmeli/ Tishler (2004a+b); Chan et al. (2004); Zahra et al. (2004).

    Google Scholar 

  28. Cf. Bergh (2001); Combs/Ketchen (1999); Roth (1995).

    Google Scholar 

  29. Cf. Delaney/ Huselid (1996); Harel/Tzafir (1999); Khatri (2000); Koch/McGrath (1996).

    Google Scholar 

  30. Cf. Bennett et al. (1998); Combs/Ketchen (1999); McGrath et al. (1995).

    Google Scholar 

  31. Cf. Coff (1999), p. 144.

    Google Scholar 

  32. Coff (1999), p. 145.

    Google Scholar 

  33. Cf. Dutta et al. (2003), p. 619.

    Google Scholar 

  34. Cf. Miller/ Shamsie (1996), p. 523.

    Google Scholar 

  35. Cf. Hansen/ Wernerfelt (1989); Hitt et al. (1997); Jiang/Beamish (2004); Robins/Wiersema (1995).

    Google Scholar 

  36. For example, Douglas and Ryman (2003) examine the drivers of competitive advantage within the hospital industry, concentrating among others on firm-specific competencies. In order to evaluate the hospital and physician group resource endowments with regard to their relative strategic value, they utilized highly qualified industry experts. Cf. Douglas/ Ryman (2003), p. 338.

    Google Scholar 

  37. Cf. Rouse/ Daellenbach (2002), p. 964.

    Google Scholar 

  38. De Saá-Pérez/ Gárcia-Falcón (2004), p. 54.

    Google Scholar 

  39. Cf. Bharadwaj (2000), p. 176.

    Google Scholar 

  40. Cf. Powell/ Dent-Michallef (1997), p. 379f.

    Google Scholar 

  41. Cf. Deephouse (2000), p. 1092f.

    Google Scholar 

  42. Cf. Miller/ Shamsie (1996), p. 532.

    Google Scholar 

  43. Cf. Rao (1994), p. 36.

    Google Scholar 

  44. Cf. Gulati (1999), p. 405.

    Google Scholar 

  45. Cf. De Carolis (2003), p. 39.

    Google Scholar 

  46. Cf. Coff (2002), p. 125.

    Google Scholar 

  47. Cf. Carmeli/ Tishler (2004a), p. 306f and (2004b) 1264f.

    Google Scholar 

  48. Cf. Combs/ Ketchen (1999), p. 877.

    Google Scholar 

  49. Cf. Schilling/ Steensma (2002), p. 397.

    Google Scholar 

  50. Cf. Welbourne/ Andrews (1996), p. 901.

    Google Scholar 

  51. Cf. Maijoor/ Witteloostuijn (1996), p. 555.

    Google Scholar 

  52. Cf. Bennett et al. (1998), p. 9.

    Google Scholar 

  53. Cf. Steensma/ Fairbank (1999), p. 28; Schilling/Steensma (2002), p. 397.

    Google Scholar 

  54. Cf. Markman et al. (2004), p. 535f.

    Google Scholar 

  55. Cf. McEvily/ Chakravarthy (2002), p. 295.

    Google Scholar 

  56. Cf. Kogut/ Zander (1993), p. 641.

    Google Scholar 

  57. Cf. Hatch/ Dyer (2004), p. 1167.

    Google Scholar 

  58. Cf. Markman et al. (2004), p. 536f.

    Google Scholar 

  59. Cf. Maijoor/ Witteloostuijn (1996), p. 555.

    Google Scholar 

  60. Deephouse (2000), p. 1099. Deephouse (2000) includes measures of product market position and tests to see if they attenuate the effect of media reputation on performance.

    Google Scholar 

  61. Cf. Borch et al. (1999); Carmeli (2004); De Carolis (2003); Hatch/Dyer (2004); King/Zeithaml (2001); Knott (2003); Kogut/Zander (1993); Maijoor/Witteloostuijn (1996); Markides/Williamson (1996); Markman et al. (2004); McEvily/Chakravarthy (2002); Schilling/Steensma (2002); Deephouse (2000).

    Google Scholar 

  62. Cf. Carmeli (2001, 2004); Maijoor/Witteloostuijn (1996). Within their empirical RBT study, Markman et al. (2004) came to similar results: “For example, our review of top-tiered management journals could not identify an empirical study in which a single resource was operationalized, concurrently, as valuable, rare, inimitable, and non-substitutable. This was surprising because according to resource-based view (RBV) an advantage that is derived from anything less than all four attributes would quickly be neutralized. Others point out that the practical utility of valuable, rare, inimitable, and non-substitutable resources remains open to discussion until researchers and managers measure the extent to which such resources are related to superior performance.” Markman et al. (2004), p. 530.

    Google Scholar 

  63. Cf. Cronbach (1951); Nunnally (1978).

    Google Scholar 

  64. “Superior resources are more ‘efficient’ in the sense that they enable a firm to produce more economically and/or better satisfy customer wants. In other words, firms with superior resources can deliver greater benefits to their customers for a given cost (or can deliver the same benefit levels for a lower cost). Note that this is a broad view of ‘efficiency’ in that it is concerned not just with lowering costs, but also with creating greater value or net benefits (Peteraf, 2001).” Peteraf/Barney (2003), p. 311.

    Google Scholar 

  65. Marshall et al. (1975), p. 10.

    Google Scholar 

  66. Cf. Ray et al. (2004); Pisano (1994); Knott et al. (2003); Miller/Shamsie (1996); De Carolis (2003); Combs/Ketchen (1999); Christmann (2000); Sakakibara (2002).

    Google Scholar 

  67. Marshall et al. (1975), p. 11.

    Google Scholar 

  68. Cf. Marshall et al. (1975), p. 11.

    Google Scholar 

  69. Cf. McEvily/ Zaheer (1999); Tripsas (1997); Kraatz/Zajac (2001); Morris (1997); De Carolis (2003); Carmeli/Tishler (2004a+b); Powell (1995); Ray et al. (2004); Richard/Johnson (2001); McGrath et al. (1996).

    Google Scholar 

  70. Levitas/ Chi (2002), p. 960.

    Google Scholar 

  71. Cf. Schilling/ Steensma (2002); Rao (1994); Miller/Shamsie (1996).

    Google Scholar 

  72. Cf. Maijoor/ Witteloostuijn (1996); Steensma/Fairbank (1999); Schilling/Steensma (2002); Bennett et al. (1998).

    Google Scholar 

  73. Cf. Combs/ Ketchen (1999); Sharma/Vredenburg (1998).

    Google Scholar 

  74. Cf. King/ Zeithaml (2001); McEvily/Chakravarthy (2002); Markman et al. (2004); Schilling/Steensma (2002); Zander/Kogut (1995); Kogut/Zander (1993).

    Google Scholar 

  75. Cf. Deephouse (2000).

    Google Scholar 

  76. Cf. Markman et al. (2004); Maijoor/Witteloostuijn (1996).

    Google Scholar 

  77. For a comprehensive discussion on the determinants of organizational performance from a multidisciplinary perspective, see Lenz (1981).

    Google Scholar 

  78. Cf. Borch et al. (1999); Chatterjee/Singh (1999); Dussauge et al. (2000); Steensma/Corley (2001).

    Google Scholar 

  79. Cf. King/ Zeithaml (2001), p. 79.

    Google Scholar 

  80. Cf. Makhija (2003), p. 444.

    Google Scholar 

  81. Cf. Wiggins/ Ruefli (2002), p. 84.

    Google Scholar 

  82. Cf. Wiggins/ Ruefli (2002), p. 86; Anand/Singh (1997), p. 110; Farjoun (1998), p. 619; Combs/Ketchen (1999), p. 878; Daily et al. (2000), p. 519; Huselid (1995), p. 652.

    Google Scholar 

  83. Cf. Montgomery/ Wernerfelt (1988), p. 626. For more details see chapter 3.2.2.2.

    Google Scholar 

  84. Cf. Dutta et al. (2003), p. 615f.

    Google Scholar 

  85. Cf. Capron (1999), p. 996f.

    Google Scholar 

  86. Cf. McEvily/ Chakravarthy (2002), p. 294f.

    Google Scholar 

  87. Cf. Gimeno (1999), p. 114.

    Google Scholar 

  88. Cf. March/ Sutton (1997), p. 698.

    Google Scholar 

  89. Cf. Venkatraman/ Ramanujam (1986), p. 803f.

    Google Scholar 

  90. Cf. Combs et al. (2005), p. 269.

    Google Scholar 

  91. Cf. Combs et al. (2005), p. 267. Interactive outcomes of all value chain activities were, however, coded as organizational performance. For more details on Porter’s value chain concept, see chapter 2.2.2.

    Google Scholar 

  92. Cf. De Saá-Pérez/ Gárcia-Falcón (2004), p. 58.

    Google Scholar 

  93. Cf. McEvily/ Chakravarthy (2002), p. 294ff.

    Google Scholar 

  94. Cf. McGrath et al. (1995), p. 258.

    Google Scholar 

  95. Cf. Ray et al. (2004), p. 31f.

    Google Scholar 

  96. Ray et al. (2004), p. 24.

    Google Scholar 

  97. Cf. Anand/ Singh (1997); Bennett et al. (1998); Brews/Hunt (1999); Combs/Ketchen (1999); Dhanaraj/Beamish (2003); Fey et al. (2000); Lee/Miller (1999); Powell (1995); Powell/Dent-Micallef (1997); Ray et al. (2004); Wright et al. (1998).

    Google Scholar 

  98. Cf. Ray et al. (2004), p. 31f.

    Google Scholar 

  99. Cf. Bennett et al. (1998), p. 6f.

    Google Scholar 

  100. Cf. Brews/ Hunt (1999), p. 895.

    Google Scholar 

  101. Cf. Powell (1995), p. 25.

    Google Scholar 

  102. Cf. Wright et al. (1998), p. 22.

    Google Scholar 

  103. Cf. March/ Sutton (1997), p. 698; Chakravarthy (1986), p. 444.

    Google Scholar 

  104. Cf. Barnett et al. (1994), p. 12.

    Google Scholar 

  105. Cf. Daily et al. (2000), p. 519.

    Google Scholar 

  106. Cf. Anand/ Singh (1997), p. 108.

    Google Scholar 

  107. Cf. Deephouse (1999), p. 156.

    Google Scholar 

  108. Cf. March/ Sutton (1997), p. 699.

    Google Scholar 

  109. Cf. McGrath et al. (1995), p. 260.

    Google Scholar 

  110. Cf. Bennett et al. (1998), p. 10.

    Google Scholar 

  111. Cf. Venkatraman/ Ramanujam (1986), p. 804.

    Google Scholar 

  112. Cf. Venkatraman/ Ramanujam (1986), p. 808ff.

    Google Scholar 

  113. Cf. Venkatraman/ Ramanujam (1986), p. 805.

    Google Scholar 

  114. Similarly, Chakravarthy (1986) concludes in his study on measuring strategic performance differences within the computer industry that conventional profitability criteria are incapable of distinguishing differences in strategic performances and thus other criteria need to be evaluated to differentiate between “excellent” and “non-excellent” firms. Cf. Chakravarthy (1986), p. 442.

    Google Scholar 

  115. Cf. Combs et al. (2005), p. 274. “... an unidimensional composite of a multidimensional concept such as business performance tends to mask the underlying relationships among the different subdimensions.” Venkatraman/Ramanujam (1986), p. 807. “... instead of searching for that single measure which most significantly determines performance, a multi-factor model of performance should be used [...] ‘excellence’ is a complex phenomenon requiring more than a single criterion to define it.” Chakravarthy (1986), p. 446. “No single profitability measure seems capable of discriminating excellence. Moreover, accounting data that are typically used to construct these measures capture past performance or historical trends. Strategic performance needs a more futuristic measure.” Chakravarthy (1986), p. 453. Chakravarthy suggests that excellence “is not reflected in the maximization of performance along any single dimension, but rather in the ability of the firm to simultaneously maintain several performance parameters within safe limits.” Chakravarthy (1986), p. 455.

    Google Scholar 

  116. Cf. Venkatraman/ Ramanujam (1986), p. 812. See Bagozzi (1980) and Joreskog/Sorbom (1979) for an overview of structural equation models, as well as Venkatraman/Ramanujam (1986).

    Google Scholar 

  117. Cf. Montgomery/ Wernerfelt (1988), p. 626.

    Google Scholar 

  118. Chakravarthy (1986), p. 443.

    Google Scholar 

  119. Cf. Chakravarthy (1986), p. 444.

    Google Scholar 

  120. Cf. Montgomery/ Wernerfelt (1988), p. 627.

    Google Scholar 

  121. Cf. Fisher/ McGowan (1983), p. 82. For q calculating procedures see Lindenberg/Ross (1981), p. 10f.

    Google Scholar 

  122. Cf. Rouse/ Daellenbach (1999), p. 489.

    Google Scholar 

  123. Cf. Rouse/ Daellenbach (2002), p. 966.

    Google Scholar 

  124. Cf. Dess/ Beard (1984), p. 53f.

    Google Scholar 

  125. Cf. Robins/ Wiersema (1995), p. 281; Wiggins/Ruefli (2002), p. 87f.

    Google Scholar 

  126. Industry concentration as an industry structure variable according to Porter (1980), considers the number and the size distribution of competing firms within an industry. Cf. Porter (1980).

    Google Scholar 

  127. Cf. Dess/ Beard (1984), p. 55; Kotha/Nair (1995), p. 499. See also chapter 2.3.3.3.

    Google Scholar 

  128. Cf. Dess/ Beard (1984), p. 56. Kotha and Nair (1995) refer to an additional term within their conceptualization of environmental uncertainty, i.e., technological change. Yet, since their arguments basically refer to states of environmental change, their notion is included within the concept of dynamism. Cf. Kotha/Nair (1995), p. 499.

    Google Scholar 

  129. Cf. Keats/ Hitt (1988), p. 579.

    Google Scholar 

  130. Cf. Keats/ Hitt (1988), p. 579; Dess/Beard (1984), p. 56; Aldrich (1979), p. 72. For example, “organizations competing in industries that require many different inputs or that produce many different outputs should find resource acquisition or disposal of output more complex than organizations competing in industries with fewer different inputs and outputs.” Dess/Beard (1984), p. 57.

    Google Scholar 

  131. Cf. Kotha/ Nair (1995), p. 499; Dess/Beard (1984), p. 58. Note that these three indicators for environmental uncertainty can be interconnected. Keats and Hitt (1988), for instance, adopt an indicator for the complexity dimension from Grossack’s (1965) dynamic measure of industry concentration, which provides for comparability across a variety of diverse industry environments. For more details, see Keats/Hitt (1988), p. 596f.

    Google Scholar 

  132. Cf. Bennett et al. (1998), p. 9.

    Google Scholar 

  133. Cf. Majoor/ Witteloostuijn (1996), p. 561ff.

    Google Scholar 

  134. Rouse/ Daellenbach (1999), p. 491.

    Google Scholar 

  135. Cf. Priem/ Butler (2001), p. 32.

    Google Scholar 

  136. Cf. Priem/ Butler (2001), p. 31f; Godfrey/Hill (1995), p. 530; Rouse/Daellenbach (1999), p. 491.

    Google Scholar 

  137. Cf. Dess et al. (1990), p. 9. “Environments affect organizations through the process of making available or withholding resources, and organizational forms can be ranked in terms of their efficacy in obtaining resources.” Aldrich (1979), p. 61. Also Ambrosini and Bowman (2001) on the subject of resources’ value: “In face of environmental changes tacit skills may become obsolete.” Ambrosini/Bowman (2001), p. 826.

    Google Scholar 

  138. Cf. Priem/ Butler (2001), p. 31; see also Rouse/Daellenbach (1999), p. 489; King/Zeithaml (2001), p. 79; Collis/Montgomery (1995), p. 120.

    Google Scholar 

  139. Cf. Barney (2001), p. 43.

    Google Scholar 

  140. Cf. Combs/ Ketchen (1999), p. 871.

    Google Scholar 

  141. Cf. Sakakibara (2002), p. 1034.

    Google Scholar 

  142. Cf. Brush/ Artz (1999), p. 246. Farjoun (1998), for example, rely on the so-called industry skill profiles: “The first step in building the skill-based classification is the construction of industry skill profiles. To measure human skill requirements, we used the Occupational Employment Survey (OES) conducted by the U.S. Department of Labor Statistics. Indicators of both the different types of human expertise needed in an industry and the extent to which they are required.” Farjoun (1998), p. 616.

    Google Scholar 

  143. Miller et al. (1997), p. 76.

    Google Scholar 

  144. Cf. Miller/ Shamsie (1996).

    Google Scholar 

  145. Cf. Barnett et al. (1994).

    Google Scholar 

  146. Priem/ Butler (2001a), p. 32.

    Google Scholar 

  147. Cf. Barney (2001), p. 47. See Harrigan (1983) for criterion variables useful in segmenting industries.

    Google Scholar 

  148. Cf. Geringer et al. (2000), p. 59f; see also Marcus/Geffen (1998), p. 1147; Van de Ven (1992).

    Google Scholar 

  149. Cf. Keats/ Hitt (1988), p. 580.

    Google Scholar 

  150. Cf. Brews/ Hunt (1999), p. 894.

    Google Scholar 

  151. Cf. Godfrey/ Hill (1995), p. 530.

    Google Scholar 

  152. Barney/ Mackey (2005), p. 4f.

    Google Scholar 

  153. Cf. Combs/ Ketchen (1999), p. 880.

    Google Scholar 

  154. Cf. Markman et al. (2004), p. 539.

    Google Scholar 

  155. Cf. Bennett et al. (1998).

    Google Scholar 

  156. Cf. Maijoor/ Witteloostuijn (1996).

    Google Scholar 

  157. Cf. Brush/ Artz (1999), p. 243.

    Google Scholar 

  158. Brush/ Artz (1999), p. 246.

    Google Scholar 

  159. Knott (2003), p. 929.

    Google Scholar 

  160. Cf. Knott (2003).

    Google Scholar 

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(2008). Review of Empirical Research within RBT. In: Empirical Research within Resource-Based Theory. Gabler. https://doi.org/10.1007/978-3-8349-9830-9_3

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