Influence of CEOs’ religious affiliations on firms’ advertising spending and shareholder value
Bibliographic record
Abstract
Purpose This study aims to answer two unique related questions on the overarching relationship between a CEO’s personal religious affiliation, the firm’s advertising spending decision and its shareholder value. First, does the CEO’s religious affiliation, a proxy for risk taking, influence the firm’s advertising spending decision? Second, does the advertising spending decision mediate the relationship between the CEO’s religious affiliation and the firm’s shareholder value? Design/methodology/approach This study uses data on the religious affiliations of CEOs of publicly listed US firms, 1992–2014, from Marquis Who’s Who; advertising spending and shareholder value from Compustat, and panel data-based regression models including CEO characteristics from ExecuComp, and firm-, industry- and time-based controls. Findings We find higher advertising spending levels for Protestant over Catholic-led firms, and advertising spending mediates the relationship between a CEO’s religious affiliation and the firm’s shareholder value. Research limitations/implications Marketing theory needs to incorporate the missing but fundamental effect of the CEO’s religious affiliation-based values on decisions and outcomes. Practical implications Boards of Directors may need to align the CEO’s and their firm’s spending goals. Originality/value While previous studies focused on the influence of religious affiliation on consumers’ attitudes and behavior, and executives’ financial and R&D spending decisions, this study, to the best of the authors’ knowledge, is the first to investigate the effect of a CEO’s religious affiliation on the firm’s advertising spending decision and its shareholder value.
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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".