Why Do Software Firms Fail? Capabilities, Competitive Actions, and Firm Survival in the Software Industry from 1995 to 2007
Why this work is in the frame
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Bibliographic record
Abstract
This study examines why firms fail or survive in the volatile software industry. We provide a novel perspective by considering how software firms' capabilities and their competitive actions affect their ultimate survival. Drawing on the resource-based view (RBV), we conceptualize capabilities as a firm's ability to efficiently transform input resources into outputs, relative to its peers. We define three critical capabilities of software-producing firms—research and development (RD), marketing (MK), and operations (OP)—and hypothesize that in the dynamic, high-technology software industry, RD and MK capabilities are most important for firm survival. We then draw on the competitive dynamics literature to theorize that competitive actions distinguished by a greater emphasis on innovation-related moves will increase firm survival more than actions emphasizing resource-related moves. Finally, we postulate that firms' capabilities will complement their competitive actions in affecting firm survival. Our empirical evaluation examines a cross-sectional, time series panel of 5,827 observations on 870 software companies from 1995 to 2007. We use a stochastic frontier production function to measure the capability for each software firm in each time period. We then use the Cox proportional hazard regression technique to relate capabilities and competitive actions to software firms' failure rates. Unexpectedly, our results reveal that higher OP capability increases software firm survival more than higher MK and RD capabilities. Further, firms with a greater emphasis on innovation-related than resource-related competitive actions have a greater likelihood of survival, and this likelihood increases even further when these firms have higher MK and OP capabilities. Additional analyses of subsectors within the software industry reveal that firms producing visual applications (e.g., graphical and video game software) have the highest MK capability but the lowest OP and RD capabilities and make twice as many innovation-related as resource-related moves. These firms have the highest market values but the worst Altman Z scores, suggesting that they are valued highly but also are at high risk for failure, and indeed the firms in this sector fail at a greater rate than expected. In contrast, firms producing traditional decision-support applications and infrastructure software have different capabilities and make different competitive moves. Our findings suggest that the firms that persist and survive over the long term in the dynamic software industry are able to capitalize on their competitive actions because of their greater capabilities, and particularly OP capabilities.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it