Search Results (16)

Generative artificial intelligence (GenAI) is increasingly used in entrepreneurial practice, yet limited empirical evidence explains how sustainability-oriented entrepreneurs appropriate it in relation to Triple Bottom Line (TBL) performance. This study examines the strategic alignment paradox faced by entrepreneurs who pursue accountable sustainability outcomes while using fast-moving, probabilistic, and partly opaque technologies. It investigates whether Sustainability Orientation (SO) is associated with Sustainable Entrepreneurial Performance (SEP) through five theoretically distinct GenAI appropriation dimensions: Adoptive, Customized, Ethical, Integrative, and Interface Appropriation. In this study, Ethical Appropriation is interpreted as ethical-boundary permissiveness because the retained GAIA items capture acceptance of self-serving, improper, or beyond-intended GenAI use rather than broad responsible-AI governance. A cross-sectional survey of 360 GenAI-using entrepreneurs and SME owner-managers in Saudi Arabia was analyzed using PLS-SEM in SmartPLS 4, with a 10,000-resample bootstrapping procedure, MICOM, permutation-based multi-group analysis, and higher-order robustness tests. The empirical results show that SO is positively and significantly associated with Customized, Ethical, and Integrative Appropriation, but has no significant relationship with Adoptive or Interface Adoptive Appropriation or Interface Appropriation. The aggregate model explains 60.8% of the variance in SEP. Mediation analysis indicates that the observed indirect association between SO and aggregate SEP is statistically significant only through the Customized, Ethical, and Integrative pathways. The pillar-specific analysis further shows that the aggregate SEP construct masks important differences across TBL outcomes: Integrative Appropriation is consistently associated with all three pillars; Ethical Appropriation is selectively associated with economic sustainability and should be interpreted as a governance warning rather than as evidence of responsible-AI governance; and Customized Appropriation is associated only with environmental and social sustainability. Finally, multi-group analysis provides no statistically robust evidence of gender-based heterogeneity after Bonferroni correction, suggesting that the SO–GenAI appropriation–SEP relationships are broadly comparable across male and female respondents in this sample. Overall, the findings suggest that GenAI should not be treated as a monolithic adoption construct; its sustainability implications depend on how generative tools are customized for specific tasks, interpreted with attention to ethical-boundary permissiveness, and structurally integrated into business routines. Full article

Social media studies often rely on one platform while drawing conclusions about online publics more generally. This study tests that inferential move through an event-centered comparison of El Niño discourse across X/Twitter, YouTube, Facebook, Reddit, TikTok, and LinkedIn. The observation window ran from 9 May through 17 May 2026, several days before and after the May 14 El Niño Watch issued by the National Oceanic and Atmospheric Administration (NOAA), which reported an 82 percent probability of El Niño emerging during May to July 2026 and a 96 percent probability of continuation through the 2026 to 2027 Northern Hemisphere winter. The corpus contains 8145 items classified as highly or moderately related to El Niño after platform-specific collection and common annotation. X/Twitter supplies 7075 items, YouTube 864, Facebook 66, Reddit 59, TikTok 50, and LinkedIn 31. Texts were annotated with a shared structured schema covering relevance, sentiment, emotion, topic, stance, likely misinformation, personal experience, humor, calls to action, language, engagement, and length. The results show that platform choice changes the empirical object. X/Twitter appears multilingual, fast-moving, and weather-heavy. YouTube is more negative, humorous, and personally experiential. Facebook is long-form and media/news oriented, with the highest model-flagged likely misinformation rate. Reddit is concentrated around weather concern. TikTok is short, playful, and personal. LinkedIn is small, professional, and mostly informational. These differences caution against generalizing from one platform to social media as a whole unless a study explicitly defines its scope, accounts for platform and genre differences, and recognizes that visible discourse may include organizational, algorithmically amplified, automated, or otherwise inauthentic activity alongside genuine human expression. Full article

The adoption of disruptive technologies has become increasingly critical for organizations, particularly following the global shifts prompted by the COVID-19 pandemic. Despite the potential benefits, many organizations, including those in the Fast-Moving Consumer Goods (FMCG) industry, face significant hurdles in this transition. Consequently, this study aims to understand the primary challenges and enabling factors influencing the adoption of disruptive technologies for sustainable digital transformation within the South African FMCG sector. A quantitative methodology was employed, utilizing a questionnaire for data collection. Data from 102 respondents were analyzed using SPSS version 28, involving descriptive statistics (mean item score) to rank factors and exploratory factor analysis (EFA) to identify underlying constructs, and a reliability test was carried out with a score of 0.7. Key challenges identified include high initial costs and poor collaboration. Prominent enabling factors include top management commitment and operational cost reduction. The EFA revealed significant underlying challenge dimensions such as “Infrastructural and Resources Constraints” and “Human Factors Constraints,” and enabling dimensions including “Organizational Commitment and Strategy” and “Leadership.” The study concludes with key implications for promoting successful adoption. The adoption of disruptive technologies has become a strategic imperative for sustainable digital transformation (SDT), particularly in emerging markets such as South Africa’s FMCG sector. This study investigates the key challenges and enabling factors shaping technology adoption within this context. A quantitative methodology was employed, using a structured questionnaire distributed to 102 professionals across FMCG organizations in Gauteng. Exploratory factor analysis (EFA) revealed latent dimensions within both challenges and enablers, which were then interpreted through the lens of Rogers’ Diffusion of Innovation (DOI) theory. To enhance analytical clarity, a matrix model was developed linking factor dimensions to DOI attributes such as relative advantage, complexity, compatibility, trialability, and observability. The study found that high initial costs, poor collaboration, and human capability gaps significantly impede adoption, while strong leadership, strategic alignment, and operational cost savings facilitate it. The findings underscore the need for systemic interventions that address not only technical readiness but also leadership, organizational culture, and structural alignment. Practical implications are outlined for both policy and management, particularly in leveraging DOI attributes to accelerate digital transformation, as well optimize innovation diffusion within resource-constrained environments. For the future, the study proposed a hybrid methodology incorporating qualitative interviews to enhance depth and suggests longitudinal tracking to capture temporal shifts in transformation maturity. Full article

Background: Globally, in the Fast-Moving Consumer Goods (FMCG) industry, excess inventory results from the bullwhip effect. Earlier, barcode-based two-bin systems were limited by manual scanning; hence, a more responsive system is needed to align the inventory with real-time demand. Prior studies have predominantly concentrated on mitigating demand fluctuations and employed comparatively low-efficiency systems, hindering excess inventory (EI) reduction. Methods: This study proposes identifying research gaps, considering the distributor-manufacturer relationship, and developing an RFID-based modified two-bin system and mathematical model to reduce EI and control over manufacturers’ excessive cost. Results: This study tested through Python-based simulation using historical data from an FMCG manufacturer, and the proposed model achieved a reduction in 67% EI and 73% month-wise holding costs. Moreover, the integration of the Artificial Bee Colony algorithm optimizes rework rates within budget, including reworking shop-floor and holding costs, contributing to a monthly excessive cost reduction of 34–48%, alongside a corresponding 41–44% cumulative excessive cost reduction. Conclusions: Bringing significant implications on digitalized SCM, this study offers a practical and scalable solution for perishable FMCG items facing demand variability and budget constraints. Collectively, this novel perspective bridges research gaps and motivates future research for embedding trend-aligned parameters, enhancing the model’s performance through diverse SCM contexts like safety stock and backorder cost optimization. Full article

The retail sector is the most demand-sensitive echelon in the supply chain, where non-moving items accumulate and become dead stock. Existing inventory management studies focus on fast-moving products and income generation. This paper focuses on dead stock management and proposes a mixed strategy solution using a pure integer non-linear programming model that minimizes the dead stock management cost of a retail chain operator. The number of products and volume of product-related data in a retail chain system require big data analysis to ensure sustainable inventory practices that reduce waste generated from dead stock inventory. Through hypothetical data sets, the 3-store, 10-product run showed that discount percentage, expected sales success probability of a product in a store location, and disposition of unsold products were the main drivers of the decisions made by the model. The most significant cost contributors arising from these decisions were the unrecovered product cost (UPC), disposed product cost (PC), and salvage value from the successful sale of dead stock. Inventory managers must balance the effect on these cost components when they choose the strategies to use in managing dead stock. Full article

This study investigates the decision-making process behind moving into a senior living community. Prospective residents were asked to identify the most important qualities of a happy, healthy, and engaged life, so called successful aging. Our effort resulted in a scale with 27 items reflecting seniors’ needs for successful aging. Building upon the Andersen’s model to predict the medical service utilization, this study developed the Needs of Successful Aging-Enabling-Psychosocial (N-SEP) model. The results showed the needs for successful aging have a positive effect on prospective residents’ attitudes and subjective norms, which in turn affect seniors’ decision to move. In addition, enabling factors were found to increase the perceived control, leading to a decision to move. This study benefits both senior living practitioners and academics who are interested in studying this fast-growing field in the future. Full article

Urban renewal has driven historic conservation districts to experience a series of changes characterized by gentrification. In the 21st century, internet traffic can be fully monetized. The intervention of the internet has made the gentrification process more diversified. Using color and item detection, points of interests (POIs), and word cloud analysis, this study takes a typical historic conservation district as an example to explore how it changed spatially, economically, and socially during the gentrification process. The results show that the internet celebrity economy possesses both promoting and dissolving effects. The promoting effects include the following: (1) the internet celebrity economy breaks the elites’ monopoly on spatial aesthetic discourse; (2) emotional value has promoted the integration of different groups’ consumption; and (3) gentrification occurs locally so spatial exclusion is not significant. The dissolving effects include the following: (1) the low-cost and rapid renovation of space reduces spatial quality; and (2) the fast-moving consumer model may possibly lead to unsustainable development. This study proposes that the intervention of the internet celebrity economy can alleviate the isolation drawbacks of traditional gentrification and promote social equity, and the promoting effects outweigh the negative effects. Full article

Background: Foundational research on the gamma distribution and inventory control highlighted its flexibility and practicality for managing fast-moving finished goods. Nonetheless, concerns remain about conventional statistical approximations of lead-time demand (LTD) distributions. Real-world lead times often result in nonstandard LTD forms, and traditional methods may introduce parameter mismatches under nonclassical conditions. Despite these challenges, this research demonstrates that a gamma LTD approximation is an effective method for managing these goods. Methods: This study employs numerical experiments to assess accuracy at high service levels, focusing on errors in system cost and product availability. Three propositions are validated: (1) a standard distribution generally characterizes the demands of fast-moving items; (2) demand variability systematically modifies the form of nonstandard LTD distributions, enhancing accuracy; (3) nonclassical conditions generally improve the accuracy of properly parameterized gamma approximations. A purposive sample of disruptive lead-time distributions found in global maritime supply chains drives numerical experiments. Results: Externally validated evidence provides the following findings within our study context: (1) a nonstandard lead-time distribution does not necessarily result in a similar LTD distribution, as it also depends on demand variability; (2) demand variability positively affects the form of a nonstandard LTD distribution under conventional conditions, with nonclassical conditions enhancing this effect; (3) the shape transformations almost always improve the accuracy of a gamma approximation. Conclusions: A gamma LTD approximation can manage inventory for fast-moving finished goods effectively, even with disruptive lead times under both conventional and nonclassical conditions. Full article

Moving fast by high-speed planing craft (HSPC) is advantageous for some special missions, though it causes severe hull vibrations and shocks that can transfer to the human body and increase health and comfort risks. This study reviews the current safety standards to avoid human safety risks affected by whole-body vibrations (WBVs), as well as the safety status of HSPC occupants. In addition, the efficiency of motion-reduction devices (trim tab and interceptor) and shock/vibration-mitigation devices (shock-mitigation seat) in improving the safety of HSPC occupants is examined according to existing documents. The research methodology was based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRIS-MA) method, and published papers in the Scholar, Scopus, and Web of Science databases were analyzed. Because most of these publications are academic research, issues of bias in the eligible publications were not of particular interest. During this systematic review, many gaps and challenges in current information on safety improvement devices were found that need to be addressed in future studies, such as a lack of information on motion-reduction devices and shock-mitigation seat performance in reducing lateral and fore-and-aft motions. Referring to these gaps and challenges can be valuable as a suggestion to improve current knowledge in research and reduce safety risks. Full article

The fashion industry is one of the world’s largest and third most polluting industries. It produces a carbon footprint of around 10% annually, which is much higher than the footprint produced by flights and shipping. Nowadays, there is an increase in demand for different and new products for people of all ages due to which fast-changing fashion is becoming a trend. But there is a hidden cost in the manufacturing of each material, which is ignored by people and which costs the environment and eventually the health of people. It not only pollutes the air due to the emission of greenhouse gases but also consumes plenty of water along with an increase in plastic and some other waste that pollutes our environment. The solution to the problem is to avoid and move away from this fast fashion trend and subsequently buy a few items of clothing that are good in quality and do not pose a threat to the environment. But this will lower the sales as well as the revenue of the fashion industry, which will eventually affect our economy. The purpose of this study is to construct a novel fractional mathematical programming model that caters to both objectives, i.e., minimizing environmental pollution and maximizing the revenue of the fashion industry with respect to the constraints based on the industry and environment. Full article

Alpine skiing is characterized by specific and dynamic conditions and demands constant processing of visual information and fast decision-making. A fast response time is necessary for protective movements which reduce the number and severity of additional head impacts. The apparent detriments to visual performance caused by protective headgear are concerning and should be considered moving forward in recreational alpine skiing. The aim of this study was to examine the effects of wearing the three most common combinations of protective headgear in skiing on the timing of visual stimuli perception and adequate response when simulating on-the-slope situations. The sample consisted of 45 recreational-level skiers (27 M, 18 F; age 30.6 ± 8.19 years) who had finished basic alpine skiing school, had been skiing 6–10 years continuously, and were students of Faculty of Kinesiology, University of Zagreb. They did not report any serious medical conditions regarding vision. The overall testing was conducted in the winter season during January and February of 2022. Reaction time on perceived visual stimuli was observed in a way that a skier was approaching behind a participant’s back from both the left and right side. A 2 × 3 (helmet*condition) mixed-model repeated-measures ANOVA was used to determine differences between helmet users and non-users in each tested condition. When observing the results, it was confirmed that the response time of the participants was the slowest when wearing a ski helmet and goggles combined. Furthermore, one of the most important findings was the determined differences in reaction time between helmet users and non-users, i.e., prior helmet users tended to react faster to the upcoming visual stimuli when wearing combined ski helmet and goggles. In the design and construction of the goggles, it is also necessary to pay attention to reducing the thickness of the frame in order to reduce the distance between the eye and the lens, which consequently reduces interference in the peripheral parts of the field of vision. In future studies, the same testing protocol with all the possible combinations of wearing a ski cap, a helmet, sunglasses, and goggles is necessary to gain a clearer insight into the effect of each item of headgear separately and in various combinations. Full article

The non-terrestrial network (NTN) is a network that uses radio frequency (RF) resources mounted on satellites and includes satellite-based communications networks, high altitude platform systems (HAPS), and air-to-ground networks. The fifth generation (5G) and NTN may be crucial in utilizing communication infrastructure to provide 5G services in the future, anytime and anywhere. Based on the outcome of the Rel-16 study, the 3rd generation partnership project (3GPP) decided to start a work item on an NTN in 5G new radio (NR) Rel-17, and the focus of the study was on mobility management procedures, due to the movements of NTN platforms; especially, low earth orbit (LEO) satellites. Handover enhancements were discussed to tackle the frequent handover due to the fast satellite movement. Therefore, the major problem of handover in LEO satellite systems was the signaling storm created by handing over all user equipment (UE) in a cell to a new cell because when the UE crosses the boundary between the neighboring cell of a satellite, an intra-satellite or cell handover occurs; thus, all users in a cell are expected to experience a change of cell due to handover every few seconds. In addition, UE location is not easy to define due to moving cell/beam situations. In this study, we propose machine learning-based solutions for handover decisions in non-terrestrial networks for cell handovers or intra-satellite handovers to reduce signaling storms during handovers where the handover requests will be executed by clustered users. First, the dataset was generated by the simulator that simulates communication between users and satellites. Second, we preprocessed the data, and also used the feature creation technique to create the distance feature using the Haversine formula, and then applied clustering and classification algorithms. The experimental results show that the distance between a user and its cell center is an important parameter for handover decisions in NTN, and the random forest outperforms all models with a higher accuracy of 99% along with a better F1-score of 0.9961. Full article

The discounted {0-1} knapsack problem (D{0-1}KP) is a multi-constrained optimization and an extended form of the 0-1 knapsack problem. The DKP is composed of a set of item batches where each batch has three items and the objective is to maximize profit by selecting at most one item from each batch. Therefore, the D{0-1}KP is complex and has found many applications in real economic problems and other areas where the concept of promotional discounts exists. As DKP belongs to a binary class problem, so the novel binary particle swarm optimization variant with modifications is proposed in this paper. The acceleration coefficients are important parameters of the particle swarm optimization algorithm that keep the balance between exploration and exploitation. In conventional binary particle swarm optimization (BPSO), the acceleration coefficients of each particle remain the same in iteration, whereas in the proposed variant, fitness-based acceleration coefficient binary particle swarm optimization (FACBPSO), values of acceleration coefficients are based on the fitness of each particle. This modification enforces the least fit particles to move fast and best fit accordingly, which accelerates the convergence speed and reduces the computing time. Experiments were conducted on four instances of DKP having 10 datasets of each instance and the results of FACBPSO were compared with conventional BPSO and the new exact algorithm using a greedy repair strategy. The results demonstrate that the proposed algorithm outperforms PSO-GRDKP and the new exact algorithm in solving four instances of D{0-1}KP, with improved convergence speed and feasible solution time. Full article

Background: The Mediterranean diet (MD) is associated with significant health benefits, including prevention of noncommunicable diseases (NCDs). Given the important migratory flow from Romania to Italy in recent decades, this study seeks to evaluate the differences between the nutritional habits of Romanian children and adolescents in Romania compared with those of Romanian children who moved to Italy or were born in Italy from both Romanian parents. Method: To assess adherence to MD, parents of Romanian children in Romania (RCR) and Romanian children in Italy (RCI) answered questions from an adapted version of the KIDMED test. Results: The results show that the high KIDMED index among RCI is significantly higher than the same index among RCR (68.09 versus 17.76, p < 0.05). RCR obtained a higher KIDMED score on different items: they had a lower consumption of fast food and sweets but an increased consumption of nuts, yogurts, and cheese. Conclusions: RCI have a better adherence to MD, but, at the same time, they are more exposed to westernized diet and practice less physical activity. Nutrition education is an important tool for improving health outcome. Full article

This paper considers the coherent integration problem for moving target detection using frequency agile (FA) radar, involving range cell migration (RCM) and the nonuniform phase fluctuations among different pulses caused by range-agile frequency (R-AF) coupling and velocity-time-agile frequency (V-T-AF) coupling. After the analysis of the term corresponding to the phase fluctuation caused by V-T-AF coupling, the term can be regarded as related to an equivalent non-uniform slow time, and nonuniform fast Fourier transform (NUFFT) could be the solution. So a fast coherent integration method combining Radon Fourier transform (RFT) and NUFFT based on low-rank approximation, i.e., Radon-NUFFT, is proposed. In this method, the RCM is solved by Radon algorithm via target trajectory searching, the non-uniform phase fluctuation caused by R-AF coupling is compensated by constructing a compensation item corresponding to the range and agile frequency. In addition, the compensation of the non-uniform phase fluctuation caused by V-T-AF coupling is converted into a problem of spectral analysis of non-uniform sampling complex-valued signal, which is solved by the NUFFT based on low rank approximation. Compared with the existing methods, the proposed method can realize the coherent integration for FA radar accurately and quickly. The effectiveness of the proposed method is verified by simulation experiments. Full article