Followership, though less examined than leadership, plays a pivotal role in organizational success and inclusivity. Women’s followership roles are particularly important in shaping sustainable organizational cultures amid growing globalization and workforce diversity. This study explored women’s perceptions of followership with three objectives: (1) to examine how Generation Z and older generations perceive followership roles, (2) to compare generational differences in followership perceptions, and (3) to analyze the impact of cultural backgrounds. Participants from collectivist and individualist contexts (Hofstede, 1983) were recruited through snowball sampling, data collected via open-ended, in-person interviews, and an approach well-suited for exploratory research. There were a total of 16 participants. Thematic analysis was conducted using MAXQDA, identifying themes and sub-themes, which revealed how generational identity and cultural norms shape women’s experience of followership. Findings provide practical strategies to bridge generational divides, foster inclusive leader-follower cohesion, and lay the groundwork for future research on women’s followership in global organizational contexts.
Urban bus electrification is a complex multi-criteria decision under deep uncertainty. We integrate Symmetry Point of Criterion (SPC) and weighting with Compromise Ranking of Alternatives from Distance to Ideal Solution (CRADIS) within a q-rung orthopair fuzzy set (q-ROFS) environment and introduce a dual-aggregation scheme that linearly combines q-ROFWFA and q-ROFEWA via a tuneable parameter lambda to mitigate aggregation bias. We further establish theoretical properties (boundary, monotonicity, idempotency) and show that the Lance distance-based CRADIS-L yields scale-invariant ranking and formal resistance to rank reversal. On a real Istanbul case, the unit energy cost emerges as the dominant criterion (0.2975), and AB Volvo 7900 ranks first overall; extensive ablation, robustness, and statistical significance tests confirm stability and rank-order reliability. Beyond offering a reproducible decision pipeline with Bayesian fusion of user-centric and technical attributes, our framework generalizes to IFS/PyFS/FFS in the limit q -> {1,2,3} and to single-operator cases when lambda -> {0,1}.
Secure Internet of Things–cloud integration underpins information visibility, coordination, and continuity in renewable-energy supply chains, yet implementation constraints can undermine these capabilities, particularly in emerging economies. This study identifies constraints affecting secure IoT–cloud implementation in Mexico's renewable-energy supply chains, determines which warrant priority managerial attention, and develops targeted interventions intended to support supply chain viability. A systematic literature review of 104 studies, followed by two rounds of fuzzy Delphi refinement, yielded 22 constraints across five categories. Their relative importance and perceived management capability were assessed using the fuzzy linear Best–Worst Method and importance–performance map analysis. Five constraints occupied the baseline improvement-priority quadrant, combining above-mean importance with comparatively weak management: unclear data ownership and access rights, weak governance enforcement, unreliable sensor data, limited cybersecurity awareness, and inconsistent cybersecurity controls. Data ownership and access rights exhibited the highest global importance (0.137) and the lowest management score (2.67). Across 25 mean-based threshold configurations, including the baseline, data ownership, governance enforcement, and sensor-data reliability remained persistent improvement priorities, whereas the classifications of cybersecurity awareness and control consistency were more threshold-sensitive. Selected investment and technical risks were assessed as comparatively better managed, although this pattern did not extend to all financial and digital-infrastructure constraints. The results identify data governance, information reliability, and cybersecurity practice as the conditions most limiting secure IoT–cloud implementation in this setting, and provide an expert-informed basis for prioritizing interventions in renewable-energy supply chain operations.
This paper presents the design, fabrication, and measurement of a high-gain, wideband foldable reflectarray antenna optimized for 3U CubeSat deep-space communication at an 8.4 GHz downlink frequency. The antenna employs custom intertwined square loops and convoluted strips as unit elements on an FR-3703 substrate with an air gap, enabling a 360° phase shift across 240 elements. Its three-piece mechanically foldable structure deploys from a compact 10 cm × 10 cm × 30 cm stowed volume to a 30 cm × 30 cm aperture (8.4λ × 8.4λ). The design achieves a simulated gain of 26.2 dBi, sidelobe level of − 21.1 dB, and an 18
Medical insurance is designed to reimburse employees for monetary losses brought on by illness risks. However, the increasing costs of medical insurance make people tend to commit fraud. Medical insurance fraud (MIF) leads to losses for individuals, businesses, and governments, while also threatening the global sustainability of medical insurance systems. For the sake of classifying the severity of MIF, this study investigates a unique sorting method by integrating cloud model with technique for order preference by similarity to ideal solution (TOPSIS), i.e., Cloud-TOPSIS-Sort, to tackle multi-criteria sorting (MCS) problem. Firstly, given uncertainty in MCS, this study will adopt probabilistic interval-valued hesitant fuzzy set (PIVHFS) for handling uncertainty and propose a technique for objectively ascertaining the probability information in PIVHFS. Secondly, a method of transforming PIVHFS into cloud model is proposed for aggregating probabilistic interval-valued hesitant fuzzy elements (PIVHFEs). Thirdly, considering the important role of divergence in uncertainty theory, f-divergence is extended for cloud model to realize the effective processing of uncertain information. Then, a Cloud-TOPSIS-Sort method is raised, and a case study concerning MIF is used for illustrating the application of the suggested technique.
