Organizational Behavior and Human Resource Management, Statistics, Probability and Uncertainty, Tourism, Leisure and Hospitality Management, Business, Management and Accounting
Curiosity in calamity: How personal schadenfreude shapes disaster-tourism intentions Joshin Joseph, Mahmoud M Abdelwahab, Ibrahim Elbatal, Jiju Gillariose, Mustafa M. Hasaballah Plos One, 2026 Tourism to sites of recent disaster, a form of dark tourism has raised questions about whether visitors are driven by typical travel motivations or by morbid impulses. This study examines how conventional tourist motives and the personality trait of benign schadenfreude (pleasure at others’ misfortune) jointly influence people’s intentions to visit a recent disaster site. By surveying 438 tourists to Kerala, four months after the July 2024 Wayanad landslides, we measured four common travel motives (novelty seeking, fun/entertainment, knowledge/learning, and relationship bonding) alongside a benign schadenfreude scale and visit intention. Partial least squares structural equation modelling (PLS-SEM) was employed for modeling. The model explained 58.80 percent of the variance in visit intention. Three motives viz., novelty, knowledge, and relationship had significant positive associations with intention, whereas the fun motive showed a negative effect. Schadenfreude emerged as the strongest predictor of disaster-site visit intention. Moreover, schadenfreude significantly moderated the influence of novelty seeking: respondents high in schadenfreude exhibited especially strong curiosity-driven intent to visit. These findings suggest that interest in post-disaster tourism often stems from ordinary travel drivers (curiosity, learning, social bonding), but a disposition to enjoy others’ misfortune can intensify the appeal when novel experiences are involved. The research highlights the need for ethical considerations to be followed by the destination managers and authorities in managing dark tourism destinations. Key limitations include the use of a cross-sectional data, region-specific sample and the focus on benign dimension (versus malicious) of schadenfreude. Future research should validate these results in other cultural and disaster contexts, establish causal relationships, and examine additional personal factors as well as dimensions of schadenfreude.
A Gauss Hypergeometric-Type Model for Heavy-Tailed Survival Times in Biomedical Research Jiju Gillariose, Mahmoud M. Abdelwahab, Joshin Joseph, Mustafa M. Hasaballah Symmetry, 2025 In this study, we introduced and analyzed the Slash–Log–Logistic (SlaLL) distribution, a novel statistical model developed by applying the slash methodology to log–logistic and beta distributions. The SlaLL distribution is particularly suited for modeling datasets characterized by heavy tails and extreme values, frequently encountered in survival time analyses. We derived the mathematical representation of the distribution involving Gauss hypergeometric and beta functions, explicitly established the probability density function, cumulative distribution function, hazard rate function, and reliability function, and provided clear definitions of its moments. Through comprehensive simulation studies, the accuracy and robustness of maximum likelihood and Bayesian methods for parameter estimation were validated. Comparative empirical analyses demonstrated the SlaLL distribution’s superior fitting performance over well-known slash-based models, emphasizing its practical utility in accurately capturing the complexities of real-world survival time data.
Design and Analysis of Reliability Sampling Plans Based on the Topp–Leone Generated Weibull Distribution Jiju Gillariose, Mahmoud M. Abdelwahab, Rakshana Venkatesan, Joshin Joseph, Mohamed A. Abdelkawy, Mustafa M. Hasaballah Symmetry, 2025 As part of this study, we design a reliability acceptance sampling plan under the assumption that the lifetime of a product follows the Topp–Leone generated Weibull (TLGW) distribution, a model that exhibits structural symmetry in its hazard rate behavior and distributional form. The fundamental procedures for constructing such a plan are described. We compute and tabulate the minimum sample sizes required for given risk criteria using both binomial and Poisson models for the number of failures. We also provide the operating characteristic (OC) values for the proposed sampling plans, and determine the minimum ratios of true mean life to specified mean life needed to satisfy a given producer’s risk. The role of symmetry in the TLGW distribution is highlighted in its balanced tail properties and shape characteristics, which influence the performance of the acceptance sampling plan. Finally, we illustrate the applicability of the proposed plan with real-world data.
Revisiting the Push–Pull Tourist Motivation Model: A Theoretical and Empirical Justification for a Reflective–Formative Structure Joshin Joseph, Jiju Gillariose Tourism and Hospitality, 2025 This study introduces a novel reflective–formative hierarchical model specification for the classic push–pull tourist motivation construct, aligning its measurement with the theoretical distinction between intrinsic “push” drives and external “pull” attributes. Unlike the traditional reflective-reflective structuring of tourist motivation we defied the higher order factors (novelty, knowledge and facilities as formative. Using partial least squares structural equation modeling (PLS-SEM) on a purposive sample of 319 international tourists, we empirically validate the reflective–formative (reflective first-order, formative second-order) model. The reflective–formative model showed a superior fit and predictive power: it explained substantially more variance in key outcome constructs (social motives (R2 = 53.60) and self-actualization (R2 = 23.10)) than the traditional reflective–reflective specification (social motives (R2 = 49.30) and self-actualization (R2 = 21.70)), which is consistent with best-practice guidelines for theoretically grounded models. In contrast, the incorrectly specified reflective–reflective model showed stronger effects between unrelated constructs, supporting concerns that choosing the wrong type of measurement model can lead to incorrect conclusions. By reconciling the push–pull theory with measurement design, this work’s main contributions are a theoretically justified reflective–formative model for tourist motivation, and evidence of its empirical benefits. These findings highlight a methodological innovation in motivation modeling and underscore that modeling push–pull motives formatively yields more accurate insights for theory and practice.
Mapping knowledge landscapes in influencer marketing and social media: A scientometric perspective Shibli Kuttukkan, Uzhunnan Faisal, Joshin Joseph Multidisciplinary Reviews, 2025 This study examines influencer marketing on social media from a bibliometric perspective, using the SPAR-4-SLR framework. It provides a quantitative evaluation of productivity, authorship, citation sources, and research domains by analyzing 1,067 peer-reviewed articles from the Scopus database. Additionally, the study offers a scientometric analysis of key indicators related to influencer marketing on social media, such as the domain's evolution, leading authors and sources, the impact of scholarly work, and insights into the scientific production process. Performance analysis techniques, including Total Publications, Productivity per Active Year, Total Citations, Average Citations (AC), Collaboration Index (CI), h-index, g-index, and h-10 index, were used to identify research trends. To decompose the intellectual structure of the topic, science mapping techniques such as co-word analysis, co-citation analysis, and thematic mapping were employed, following the SPAR-4-SLR framework. The study’s findings offer transparent and systematic insights into the intellectual dynamics and conceptual foundations of influencer marketing on social media, highlighting the cumulative advancements in this field. Emerging topics like virtual influencers and influencer credibility were identified as trends for future research. This comprehensive understanding of influencer marketing, its conceptual dynamics, and structural perspective will assist marketers (brands), policymakers (governments), academics, and social media service providers in shaping policies and guiding future research through the quantitative analysis of existing literature in this field.
Exploring the Relationship Between Personality and Work-Life Balance Integrating New Technologies in International Business Opportunities and Challenges, 2022
