Impacts of Endogenous Sunk-Cost Investment on the Islamic Banking Industry: A Historical Analysis
Bibliographic record
Abstract
Endogenous sunk-cost investments are optional fixed investment or capita, that a firm can choose to impact either upon its price-cost margin or its market share for capturing larger market spoils. Oft-cited examples are investments in vertical product (quality) differentiation, advertising outlays, and R&D type expenses for improving production processes. The importance of sunk-cost capital has been highlighted in the recent literature since these investments significantly influence the degree of competition in an industry mainly through forestalling entry and thereby limiting future competition in the industry. Sunk-cost investments play an important role in the debate on the competition-(in)stability perspectives for the banking industry. This paper is motivated by an important distinction, hitherto unrecognized, that some endogenous sunk-cost investments impact on the relative efficiencies of firms and thereby on its market spoils or profits, while others will only impact on its market share and thereby on profits. An example of this distinction is as follows: while quality improvement in a product or production processes will create efficiencies and, therefore, additional profits, while advertising expenses are used to snatch market shares from rivals. The unintended consequence of the first type of endogenous-sunk cost investment is to boost efficiencies and thereby shape the nature of competition in a market. The second type will have little effect on efficiencies. In this paper, by exploiting the above distinction and using a dataset created from the annual reports of nine major Islamic banks in Jordon during 1993–2010, we will apply the efficiency models and the autoregressive distributed lag (ARDL) methodology to test if information technology (IT) capital is strategically used by Islamic banks as an endogenous sunk-cost investment to boost their relative efficiencies. For the first time—to the best of our knowledge—we find that IT capital is strategically used by seven out of the nine Islamic banks. We then consider the implication of the strategic use of IT capital by Islamic banks for the nature of competition in the Islamic bank industry of Jordon. By so doing, we also argue that IT capital, through its effects on the nature of competition, will lend stability to the Islamic banking industry of Jordan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".