Total Quality Management, Market Orientation, and Performance: Empirical Insights from the Moroccan Hospitality Industry
Bibliographic record
Abstract
The intensity of competition in the hospitality industry has long since highlighted the importance of addressing the intellectual aspect through management practices that focus on the environment, which have become essential in responding to changing market demands. Market Orientation (MO) is widely recognized as a critical growth strategy. It enables organizations to use real-time market intelligence to capitalize on business opportunities and make strategic and operational decisions that align with changing market dynamics. This study takes MO as the research object and investigates the factors influencing its implementation focusing on Total Quality Management (TQM) practices. The research also examines the impact of MO on hotel performance (HP) and assesses how interfunctional coordination (IC) moderates the MO/HP relationship. The study formulates a comprehensive theoretical model, presenting 3 hypotheses. Subsequently, the questionnaire was distributed to hotels based in Morocco, and a total of 93 usable responses were collected. PLS-SEM via Smart PLS 4.0 is used to test the model. Results showed that TQM practices are internal drivers of MO and that MO fosters HP. Moreover, IC moderates the MO/HP relationship, reducing the direct effect. This research offers an empirical contribution by examining how hotels embrace two managerial approaches to enhance performance. Furthermore, it provides a deeper explanation of the current challenges within the Moroccan hospitality industry that justify the focus of the study.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".