← Every exhibit

Figure 5From “Porter's five forces: industry explains less than the firm does”

Five forces evidence map: what the variance studies show and where they stop

Every finding behind the five forces question comes from a statistical decomposition on industry codes; none of the three studies measures a force.

Cite Embed

Figure 5Five forces evidence map: what the variance studies show and where they stop

QuestionWhat the held studies showWhere the evidence stops
How much does stable industry membership explain, pooled?About 3 to 8% of the variance in profitability (11% on market value); firm or business-unit effects about 13 to 47% (Rumelt, 1991; Hawawini et al., 2003; Fernández et al., 2019)Industry codes, not competitive arenas; US 1974 to 1996 and Spain 1995 to 2004
Is an industry's average return a reading of its stable effect?Only about 40% of the variance in four-year industry averages is stable industry effect; 15.21 points above the mean for 95% confidence (Rumelt, 1991)One data set, US manufacturing 1974 to 1977; a normal model; more years remove only the yearly part of the noise
Does industry matter more in the middle of the pack?Without each industry's two leaders and two losers, industry effects counted with yearly swings matched or exceeded firm effects on all three measures (Hawawini et al., 2003)On stable effects alone the firm still led on both profit measures; trimmed by the outcome; survivors only
Does firm size change the answer?Medium-sized Spanish firms: industry about 39% with yearly swings, firm 5.1%, on variance components analysis (Fernández et al., 2019)Level on the second method, firm marginally ahead, difference not significant; Spain only; a decade of growth
Does the firm effect measure strategy?Not shown: it holds whatever sets a firm apart (Rumelt, 1991)Descriptive models; the firm-industry interaction cannot be estimated in them (Hawawini et al., 2003)
Do the five forces explain the industry effect?Not tested by these three studiesThe industry effect also holds risk, growth and accounting practice (Rumelt, 1991)

Swipe or scroll horizontally if the table is wider than your screen.

Source: Author's evidence map. Rumelt (1991), Strategic Management Journal 12(3), pp. 168, 171, 173, 179 to 182; Hawawini et al. (2003), Strategic Management Journal 24(1), pp. 1, 6, 7, 11 to 15; Fernández et al. (2019), BRQ Business Research Quarterly 22(1), pp. 28 to 30, 32 and 33. The questions and their grouping are this essay's.

PNG4:3, 1600 × 1200, with the title, the source line and the attribution set in the image isoglu-2026-porters-five-forces-fig05.png

Source and evidence

Each line names a claim related to this exhibit, its source, and how it was checked.

  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Partition of business-unit returns, restricted model: sample A (B) 8 (4) percent stable industry, 1 (2) corporate, 46 (44) business unit, 8 (5) industry-year, 37 (45) residual; Table 4 for sample A: 8.28, 7.84, 0.80, 46.38, 36.70 (sum 100.00); Table 3 for sample B: 4.03, 5.38, 1.64, 44.17, 44.79; business-unit variance six (eleven) times the industry variance; Table 3 prints 36.87 for the sample A error, Table 4 36.70, which sums (pp. 178, 179): "8 (4) percent industry effects, 1 (2) percent corporate effects, 46 (44) percent business-unit effects, 8 (5) percent industry-year effects, and 37 (45) percent residual error"; "business-units differ from one another within industries much more than industries differ from one another"; "six times larger in sample A and eleven times larger in sample B"Rumelt (1991)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported What the components contain: the industry effect is the total of all persistent industry-specific impacts, from competitive behaviour and conditions of entry to risk and accounting practice; business-unit effects are business-specific skills, resources, reputations, learning and patents, and possibly allocation errors, which a test did not support (pp. 173, 178): "reflect differing competitive behavior, conditions of entry, rates of growth, demand-capacity conditions, differing levels of risk, differing asset utilization rates, differing accounting practices"; "they are due to the presence of business-specific skills, resources, reputations, learning, patents, and other intangible contributions to stable differences among business-unit returns"; "These results do not support the view that allocation errors are an important source of heterogeneity"Rumelt (1991)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported The model is descriptive: it offers no causal or structural explanation and deliberately sets causal mechanisms aside (pp. 169, 172): "it offers no causal or structural explanation for profitability differences across industries, years, corporations, or business-units"; "My intention here is to suppress concern with causal mechanisms and focus instead on the question of focus"Rumelt (1991)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Industry averages are noisy: about 40 percent of the variance among four-year industry average returns is stable industry effect, about another 40 percent business-unit effects that randomly combine in industry averages, the remaining fifth (sample A) industry-year and business-unit-year fluctuations, the only part more years would shrink (Table 5); conditional model with mean 0.4 times the distance above the mean and standard deviation 3.71 (p. 181, read on the page image); at 10 points the estimate is 1.08 standard deviations above zero, probability 0.14 that the effect is negative; 15.21 points needed for 95 percent confidence; on the normal approximation about one in forty, some six of 242 industries, would pass, an expectation, not a tally (pp. 168, 180 to 182): "only about 40 percent of the variance among industry returns is actually due to stable industry effects"; "industry returns are noisy estimates of the true industry effects"; "this estimate is only 1.08 standard deviations above zero"; "the observed industry average must be at least 15.21 percentage points above the mean"; "could be judged (95 percent confidence) to have positive industry effects"; "This portion would be smaller had the averages been taken over more than 4 years"; "Fewer than one in forty industry returns are high enough to pass this test"; "effects which randomly combine to affect industry averages"; "The remaining variance (one-fifth in sample A, one-eighth in sample B) is due to various industry-year and business-unit-year fluctuations"Rumelt (1991)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Limits the author states: four-digit FTC industries may be too broad; the variance of business-unit effects may differ between industries (p. 182): "industries are simply too broad to reveal the true strength of industry effects"; "some industries being much more heterogeneous than others"Rumelt (1991)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Full sample, Table 5: firm effects 27.1, 32.5 and 35.8 percent (EP/CE, TMV/CE, ROA); stable industry 6.5, 11.4 and 8.1; industry-year 4.2, 2.9 and 3.1; total industry 10.7, 14.3 and 11.2; stable firm effects more than four times stable industry effects for EP/CE and ROA (p. 11): "Total industry effects for EP/CE, TMV/CE and ROA are 10.7 percent, 14.3 percent, and 11.2 percent, respectively"; "the corresponding figures for stable firm effects are 27.1 percent, 32.5 percent, and 35.8 percent"; "stable firm effects dominate stable industry effects by a factor of more than four"Hawawini, Subramanian and Verdin (2003)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Middle of the pack, Table 8: industry effects (stable plus transient, as the authors compare them) 18.2 against firm 17.6 percent for EP/CE, 20.1 against 16.7 for ROA, 35.2 against 17.0 for TMV/CE; on stable industry effects alone 12.4 against 17.6 (EP/CE), 16.0 against 16.7 (ROA), 30.2 against 17.0 (TMV/CE); the transient component measures sensitivity to business cycles; firm-specific assets matter more only for the few leaders and losers (pp. 1, 7, 12, 13, 14): "overall industry effects (the sum of stable and transient industry effects) explain 35.2 percent in variation compared to only 17.0 percent for firm effects"; "In the case of EP/CE it is 18.2 percent for industry effects vs. 17.6 percent for firm effects and for ROA it is 20.1 percent against 16.7 percent"; "only for a few dominant value creators (leaders) and destroyers (losers) do firm-specific assets seem to matter significantly more than industry factors"; "Industry factors may have a large impact on the performance of the ‘also-ran’ firms, while for the industry leaders and losers it is firm factors that dominate"; "the transient component of industry effects measures the sensitivity of profitability to the impact of business cycles on the industry"Hawawini, Subramanian and Verdin (2003)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Limits the authors state: a statistical decomposition that does not identify sources; SIC may miss strategically relevant industries; large unexplained share; the industry-firm interaction cannot be estimated because firm is nested in industry; corporate and business effects cannot be separated, which may understate industry; 1,000 listed and possibly large firms (pp. 13 to 15): "this study performs a statistical decomposition and does not investigate the exact sources of these effects"; "the SIC system in some cases does not identify strategically relevant industries"; "a significant proportion of the performance variations observed is due to as yet completely unexplained factors"; "with the current model we cannot estimate this interaction because the firm factor is nested within the industry"; "the data do not allow us to distinguish between corporate- and business-level effects and hence may underestimate industry effects"; "a data set containing only 1000 listed firms that may potentially be large, and hence we should be cautious when seeking to generalize the results"Hawawini, Subramanian and Verdin (2003)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Pooled, Table 2: firm 12.71 percent, industry 3.35, year 0.48, industry-year 0.34, residual 83.12 (the printed total 156.82 is the small-firm total; the shares are of 211.14) (p. 29): "These show that the firm effect has the greatest explanatory power, while the industry effect is less important"; "a significant part of the variance of ROA is not explained by the model"Fernández et al. (2019)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported By size, variance components analysis, Table 3: large firm 17.99, stable industry 0.00, industry-year 15.24; medium firm 5.07, industry 18.71, industry-year 20.29; small firm 13.62, industry 0.93, industry-year 0.53 percent; industry about 39 percent against 5.07 for medium firms (pp. 29, 30, 32): "In the case of large firms, the transient industry effect explains almost as much as the firm effect, but the stable component of the industry effect has no significance whatever"; "In the case of medium-sized firms, the importance of the industry effect is eight times that of the firm effect, and is almost equally split between its two components, stable and transient"; "approximately 39% of variance explained by the industry and industry-year effects and 5.07% by the firm effect"Fernández et al. (2019)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Second method (HLM, time fixed, no industry-year term), Tables 3 and 4: medium firm 5.61 against industry 5.17 percent; the authors call the medium-size industry advantage not overwhelming and the difference not significant (pp. 29, 30): "although the greater importance of the industry effect in the case of medium-sized firms is not overwhelming"; "although the difference between effects is not significant"Fernández et al. (2019)
  • A A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Limits the authors state: no business-unit data, so a single firm effect that may understate industry; Spain only; replication in other countries proposed (pp. 28, 33): "We therefore measured a single effect at the level of the firm, which might have given rise to the industry effect being underestimated"; "it does not contain data from other countries, which prevents further generalization of the results obtained"; "very interesting to replicate the analysis in a group of countries"Fernández et al. (2019)
  • B A verified against the printed page of the primary sourceB primary source, text layer onlyC authoritative secondaryD reported Figure 5 evidence map: the questions and their grouping, and the three limits (none of these studies tests a force; the firm effect is not strategy; old and narrow evidence)Author evidence map

From the essay

Cite or embed

APA 7

Isoglu, S. (2026). Five forces evidence map: what the variance studies show and where they stop [Figure]. isoglu.com. https://isoglu.com/insights/exhibits/isoglu-2026-porters-five-forces-fig05/

BibTeX
@misc{isoglu-2026-porters-five-forces-fig05,
  author = {Isoglu, Sinan},
  title = {{Five forces evidence map: what the variance studies show and where they stop}},
  year = {2026},
  howpublished = {Figure 5, isoglu.com},
  url = {https://isoglu.com/insights/exhibits/isoglu-2026-porters-five-forces-fig05/},
  note = {From the essay {Porter's five forces: industry explains less than the firm does}}
}
Embed this exhibit

Copy this HTML to use the PNG exhibit on your site with its source line and a link back to the exhibit page.

<figure>
  <a href="https://isoglu.com/insights/exhibits/isoglu-2026-porters-five-forces-fig05/">
    <img src="https://isoglu.com/social/isoglu-2026-porters-five-forces-fig05.png" alt="Figure 5: Five forces evidence map: what the variance studies show and where they stop" width="3200" height="2400">
  </a>
  <figcaption>Figure 5: Five forces evidence map: what the variance studies show and where they stop. Source: Author&#39;s evidence map. Rumelt (1991), Strategic Management Journal 12(3), pp. 168, 171, 173, 179 to 182; Hawawini et al. (2003), Strategic Management Journal 24(1), pp. 1, 6, 7, 11 to 15; Fernández et al. (2019), BRQ Business Research Quarterly 22(1), pp. 28 to 30, 32 and 33. The questions and their grouping are this essay&#39;s. <a href="https://isoglu.com/insights/exhibits/isoglu-2026-porters-five-forces-fig05/">View exhibit</a>.</figcaption>
</figure>

Related exhibits

Figure 1Figure

Porter's five forces question in the data: industry and firm effects on profit variance in three studies

Porter's five forces: industry explains less than the firm does

Figure 3Figure

Five forces analysis and noisy industry averages: the chance that a high average hides a below-average stable industry effect

Porter's five forces: industry explains less than the firm does

Figure 6Figure

A five forces review sheet built on the variance evidence

Porter's five forces: industry explains less than the firm does

Every exhibit

Contact

Bring the question you're working on.

Research, a guest lecture, or a commercial question.