This study explored the association between sensory marketing measures and client experience in an Algerian beauty clinic. This study adopted a descriptive-analytical approach, based on a questionnaire administered to a convenience sample of 30 female clients of the clinic. Both descriptive and inferential statistical analyses were conducted to test the research hypotheses. The findings revealed that the overall application of sensory marketing in the clinic was positively associated with client experience. The pre–post comparison showed a statistically significant difference in overall client experience between the two measurement phases. Following the intervention, significant associations were observed between the sensory stimuli (sight, sound, smell, taste, and touch) and client experience. Among these five dimensions, sound showed the strongest association, followed by sight and taste. This research offered practical insights into how sensory marketing could be leveraged as a tool for enhancing client experience. Understanding changes in clients’ perceptions could help inform service improvements and sensory-marketing decisions.

The adoption of intelligent transportation systems (ITS) in developing urban environments is shaped by interrelated institutional, technological, infrastructural, and socioeconomic factors. Before structural relationships among these factors can be interpreted with confidence, the psychometric properties of the measurement model must be established. This study validated an integrated ITS adoption framework for Yogyakarta, Indonesia, comprising eight latent constructs: funding/budget, government policy, infrastructure, technology, social economy, social affordability, smart readiness, and the ITS adoption framework. Data from 300 respondents were analyzed using partial least squares structural equation modeling in SmartPLS 4. The measurement model was evaluated for internal consistency reliability, convergent validity, and discriminant validity. Cronbach’s alpha and composite reliability values exceeded 0.70 across all constructs, and average variance extracted (AVE) values exceeded 0.50. The Fornell–Larcker criterion and heterotrait–monotrait ratio (HTMT) further supported discriminant validity. These findings indicate that the proposed measurement model is reliable and valid, providing a methodological foundation for subsequent structural-model evaluation and hypothesis testing. The validated instrument can support rigorous investigation of ITS adoption determinants and evidence-based transportation planning in developing urban settings.

Selecting an appropriate antihypertensive drug class for older patients with multimorbidity requires multiple clinical considerations to be evaluated simultaneously, including comorbidity-specific suitability, treatment-related risks, therapeutic priorities and professional judgement. A transparent decision-support framework is therefore needed to structure these heterogeneous considerations without implying that a mathematical ranking constitutes a clinical recommendation. An entropy-weighted group decision-support framework was developed and evaluated using a hypothetical 72-year-old patient with multiple comorbidities. Seven antihypertensive drug classes—diuretics, beta-blockers, Angiotensin-Converting Enzyme (ACE) inhibitors, Angiotensin II Receptor Blockers (ARBs), calcium-channel blockers (CCBs), alpha-1 blockers and central alpha-2 agonists—were assessed against eight criteria: physician experience, suitability for older patients, suitability for patients with diabetes, suitability for patients with kidney disease, suitability for patients with congestive heart failure, suitability for patients with a history of myocardial infarction, medication-related complication risk and rapidity of therapeutic effect. Assessments were provided independently by an internist, a cardiologist and a urologist. Criterion weights were derived using the entropy method from transformed rank-score distributions, while rank-frequency linear assignment and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) were used to aggregate expert assessments and obtain alternative rankings. ARBs were ranked first by TOPSIS and third in both optimal linear-assignment solutions. Two equally optimal linear-assignment solutions were obtained, with beta-blockers and alpha-1 blockers exchanging the first and sixth positions. Central alpha-2 agonists were ranked last by both approaches. Importantly, the complete and tie-free rankings provided by every expert resulted mathematically in identical entropy weights of 0.125 for all eight criteria, indicating that criterion differentiation was not achieved under the adopted elicitation format. The resulting rankings therefore represent methodological outputs rather than evidence of clinical superiority among antihypertensive drug classes. The framework provides a transparent means of structuring multi-criteria and multi-expert assessments in complex clinical scenarios, while its preliminary nature, limited expert panel and absence of patient-level validation preclude direct clinical application. Validation using larger and more diverse expert panels, clinically validated criteria and patient-level outcomes is warranted before the framework can be considered for clinical decision-support applications.