Strong Impact Research Articles

Impact of rural transformation on rural income and poverty for sustainable development in Bangladesh: A moments‐quantile regression with fixed‐effects models Approach

AbstractThis study examines the impact of rural transformation on income and poverty in Bangladesh using district‐level panel data from five rounds of the Household Income and Expenditure Survey conducted in 1995, 2000, 2005, 2010, and 2016. Two key indicators are assessed: the share of high‐value agriculture and non‐farm employment. Fixed effects and moments‐quantile regression models are employed to analyze the relationships between rural transformation, income, and poverty, accounting for education, healthcare, electricity access, and land ownership. The results show that both high‐value agriculture and non‐farm employment significantly boost rural income and reduce poverty. Geographic disparities are evident, with high‐value agriculture being most effective in agriculturally favorable regions, while non‐farm employment has a stronger impact in areas with fewer agricultural opportunities. These findings are critical in shaping policies aligned with Sustainable Development Goal 1, which seeks to eradicate poverty. The findings indicate the need for policies to prioritize high‐value agriculture and non‐farm employment to promote income growth and reduce poverty. Expanding agricultural extension services and vocational training is vital for this transformation, alongside targeted investments in infrastructure, education, healthcare, and energy access to enhance rural development and poverty alleviation across Bangladesh.

The role of motivation and knowledge in promoting green consumer behavior in Saudi Arabia and Pakistan

This research explores the factors influencing consumers’ intentions and behaviors toward purchasing green products in two culturally and economically distinct countries, Saudi Arabia and Pakistan. Drawing on Ajzen’s Theory of Planned Behavior (TPB), the study examines the roles of altruistic and egoistic motivations, alongside environmental knowledge, in shaping green consumer behavior. Altruistic motivation, driven by concern for societal well-being and environmental sustainability, is found to have a stronger impact on green purchase intention and behavior in both countries, particularly in Pakistan. Egoistic motivation, which focuses on personal benefits like health and cost savings, also contributes but with a lesser influence. The research employs a cross-sectional survey design, collecting data from 1000 respondents (500 from each country) using a stratified random sampling technique. The collected data were analyzed using structural equation modeling (SEM) to examine the relationships between variables and test the moderating effects of environmental knowledge. The results reveal that environmental knowledge significantly moderates the effect of both altruistic and egoistic motivations on green purchase intention, enhancing the likelihood of eco-friendly consumption. These findings underscore the importance of environmental education in promoting sustainable consumer behavior. The originality of this study lies in its comparative analysis of green consumerism in two distinct contexts and its exploration of motivational factors through the TPB framework. Practical implications suggest that policymakers and marketers can develop strategies that appeal to both altruistic and egoistic drivers while enhancing consumer knowledge of environmental issues. The study contributes to the literature by expanding TPB to include the moderating role of environmental knowledge in understanding green consumption behavior across diverse cultures.

How hotel VR photography previews enhance customers’ immediate booking intention through mental imagery and perceived value

Purpose The purpose of this study is to examine how a hotel virtual reality photography (VRP) preview enhances customers’ immediate booking intention compared to a picture preview. Design/methodology/approach Data were collected using a one-factor between-subject experimental design and time-based systematic sampling. Respondents were asked to read a scenario on an iPad and assess a hotel preview (VRPs vs pictures) before answering the questionnaire. Findings The results show that a hotel VRP preview generates more mental imagery than a picture preview in terms of quantity, vividness, modality and valence. These four dimensions of mental imagery indirectly influence customers’ immediate booking intentions through perceived utilitarian value and hedonic value, among which modality has the greatest influence on utilitarian value and valence has the greatest influence on hedonic value. Moreover, utilitarian value has a stronger impact on customers’ immediate booking intentions than does hedonic value. Originality/value The results obtained in this study contribute to hospitality research by using cognitive consistency theory as the overarching framework, combining mental imagery theory, media richness theory and perceived value theory to explain the mechanism of tourists’ hotel booking decision-making from hotel previews. Comparing this study’s results with previous studies shows the difference in the effects of 360° (head-mounted) videos, VRPs and pictures on evoking mental imagery across tourism and hotel products, updating our knowledge of VR technology in tourism marketing.

Understanding the importance of café portable cup design and environmental concerns on green on-the-go consumption: a comparative study of gender

ABSTRACT With massive coffee sales comes a detrimental environmental impact due to high disposable cup usage. This study examined how Starbucks portable cup design and environmental concerns shape green purchase intention by extending the TPB model. Structural analysis revealed that aesthetics, symbolism, functionality, and environmental concerns influenced consumer attitudes, contributing to purchase intention alongside perceived behavioral control and subjective norms within the TPB framework. Multigroup analysis found that symbolism has a stronger impact on females’ attitudes, while functionality has a stronger impact on males’ attitudes. Additionally, attitude mediated the effects of design and environmental concerns on green purchase intention.

Comparing the distinctive influences of physical and social servicescapes on brand love for internet‐famous restaurants

Purpose This study aims to investigate the different effects of physical and social servicescapes on brand love for internet-famous restaurants, focusing on their pathways and strengths of influence. Design/methodology/approach Structural equation modeling was applied to analyze data from 387 online questionnaires in China. Findings Results indicate that social servicescape directly influences brand love for internet-famous restaurants, while physical servicescape does not. The effect of physical servicescape on brand love for internet-famous restaurants is mediated by perceived coolness and perceived enjoyment, whereas social servicescape’s influence is mediated solely by perceived enjoyment. Overall, physical servicescape has a stronger impact on brand love for internet-famous restaurants compared to social servicescape. Practical implications The findings help internet-famous restaurants create effective physical and social servicescapes to enhance brand love, underscoring that physical servicescape is more crucial than social servicescape for cultivating this love. Originality/value This study contributes to the literature by analyzing the heterogeneous pathways and strengths of physical and social servicescapes influencing brand love for internet-famous restaurants, while highlighting the mediating role of perceived coolness and expanding the application scope of cognitive appraisal theory.

Reconstructed influenza A/H3N2 infection histories reveal variation in incidence and antibody dynamics over the life course.

Humans experience many influenza infections over their lives, resulting in complex and varied immunological histories. Although experimental and quantitative analyses have improved our understanding of the immunological processes defining an individual's antibody repertoire, how these within-host processes are linked to population-level influenza epidemiology in humans remains unclear. Here, we used a multilevel mathematical model to jointly infer antibody dynamics and individual-level lifetime influenza A/H3N2 infection histories for 1,130 individuals in Guangzhou, China, using 67,683 haemagglutination inhibition (HI) assay measurements against 20 A/H3N2 strains from repeat serum samples collected between 2009 and 2015. These estimated infection histories allowed us to reconstruct historical seasonal influenza patterns in humans and to investigate how influenza incidence varies over time, space, and age in this population. We estimated median annual influenza infection rates to be approximately 19% from 1968 to 2015, but with substantial variation between years; 88% of individuals were estimated to have been infected at least once during the study period (2009 to 2015), and 20% were estimated to have 3 or more infections in that time. We inferred decreasing infection rates with increasing age, and found that annual attack rates were highly correlated across all locations, regardless of their distance, suggesting that age has a stronger impact than fine-scale spatial effects in determining an individual's antibody profile. Finally, we reconstructed each individual's expected antibody profile over their lifetime and inferred an age-stratified relationship between probability of infection and HI titre. Our analyses show how multi-strain serological panels provide rich information on long-term epidemiological trends, within-host processes, and immunity when analysed using appropriate inference methods, and adds to our understanding of the life course epidemiology of influenza A/H3N2.

Predictive models of tranquility in urban public open spaces based on audiovisual indicators analysis

Tranquil areas significantly enhance residential environmental quality and social well-being. However, a structured predictive assessment mechanism has yet to be established. This study develops prediction models for diverse places by conducting tranquility analyses based on 91 sample sites, integrating 10 objective and 31 subjective audiovisual indicators. The results indicate: (1) For auditory aspects, objective indicators such as sound level and psychoacoustic parameters demonstrate higher explanatory power compared to subjective indicators. By contrast, for visual aspects, subjective indicators such as perceived intensity and evaluation demonstrate higher explanatory power than objective indicators. (2) Sensitivity to sound is higher than to visual stimuli when perceiving tranquility. Negative elements (e.g., artificial sounds (AS): R = -0.69, p ≤ 0.05, other artificial elements (OAE): R = -0.41, p ≤ 0.05) have a stronger impact than positive elements (e.g., natural sounds (NS): R = 0.62, p ≤ 0.05, natural elements (NE): R = 0.29, p ≤ 0.05). (3) Key predictive variables for potential tranquil areas include the number of noises (NN), natural sounds/artificial sounds (NS/AS), civilization level (CL), Loudness, and natural contextual elements/other artificial elements (NCE/OAE). For natural places, AS and the number of people (NP) are key predictive variables. Similarly, for historical and cultural places, LA90, NN, and OAE are key predictive variables. These findings can be applied to the prediction, identification, and evaluation of different types of urban tranquil areas, thereby guiding their creation and optimization.

Supervised machine learning-based categorization and prediction of uranium adsorption capacity on various process parameters

Existing uranium poses significant dangers to the environment and the general population's health. Within the scope of this study, machine learning techniques were utilized to assess the characteristics that influence uranium adsorption. The adsorbent material, pH, temperature, solid-liquid ratio (SLR), and initial concentration (Ci) values were imported as the feature to evaluate using ML models in this study. The finding concluded that the Convolutional Neural Network (CNN) model performed excellently by attaining an accuracy of 98%, which is very high in classifying low and high levels of adsorption predictions. The Random Forest model was also the best performer for Qe prediction, with the lowest MSE value of 334.45 and the highest Squared-R score of 0.92 for the uranium adsorption process. Permutation Importance analysis indicated that initial concentration had the strongest impact on Qe. Knowing that a good interaction between uranyl ions and adsorbent surface would result in more active sites for trapping radioactive metal, optimizing this parameter can be quite helpful for designing new materials capable of capturing uranium species strongly from solutions. ML model excels at predicting Qe in uranium adsorption and can directly accommodate large datasets and non-linear input parameter-Qe interactions. As noted, the innovation poised to drive ML research has been made possible by recent technological developments in machine learning and can improve while offering new ways of addressing difficult environmental problems.

Justification for knowing in a digitalised landscape

Epistemic beliefs are described as the way individuals regard the nature of knowledge and knowing. The nature of knowledge can be explored as dimensions describing the certainty and the structure of knowledge, whereas the nature of knowing can be explored as dimensions describing the source of knowledge and the justification for knowing. Recent research suggests justification for knowing as consisting of three strategies for justifying knowing: 1) justification by authority, 2) justification by multiple sources, and 3) personal justification. Knowledge is considered to originate from various sources, where testimony is regarded as the most important. Many online interactions are about conveying information to others and thus, testimonial in nature. The information we receive in various testimonies requires justification using the appropriate justification method. Therefore, source of testimony is central when justifying knowing. In a pilot study among first-year students we explored how the source of testimony and the type of information affect the choice of justification method. The use of justification methods was measured using the Internet-Specific Epistemic Justification Inventory (ISEJ). The results indicate that the source of testimony has a stronger impact than type of information on the choice of justification method.

Global dynamics of a periodically forced SI disease model of Lotka–Volterra type

In this paper, we investigate the dynamics of an SI disease model of Lotka–Volterra type in the presence of a periodically fluctuating environment. We give a global analysis of the dynamical behavior of the model. Interestingly, our results show that the permanence guarantees the existence of a unique positive harmonic time-periodic solution which is globally attracting when the horizontal disease transmission has a weaker impact than the intraspecific competition. While for the case when the horizontal disease transmission has a stronger impact than the intraspecific competition, we numerically show that complex dynamics such as chaos can occur in a permanent system. Nonetheless, we provide sufficient conditions for the existence and uniqueness of the positive harmonic time-periodic solution for the latter case. The impact of the environment on the spread of disease is studied by using a bifurcation analysis. We show that in each of the qualitatively different cases of the associated autonomous SI model in a constant environment, an alternative possibility can appear in the periodic model.

Các yếu tố ảnh hưởng đến ý định mua trước trả sau đối với hình thức thanh toán trực tuyến của thế hệ Z

In recent years, Buy Now - Pay Later forms of payment are becoming popular, however, the core basic principle of “Buy Now Pay Later” in providing credit Interest-free benefits for consumers are being challenged by inflation and rising interest rates. This study was conducted to build a model to study factors affecting the intention to buy now - Pay later for online payment methods of generation Z, including: (1) Perceived benefits, (2) Perceived ease of use, (3) Perceived risks,(4) Digital financial knowledge, (5) Social influence. Using a survey of 306 sample members, the authors concluded that the Social Influence factor has the strongest impact on the intention to use Buy now - Pay later for customers. with the online payment method of generation Z. From there, the authors propose appropriate solutions to help the government, consumers and businesses doing business on e-commerce platforms.

The Moderating Roles of Environmental Awareness and Product Knowledge on the Impact of Marketing Mix Elements on Purchase Intention

The purpose of this study is to examine the moderating effects of environmental awareness (EA) and product knowledge (PK) on the relationship between marketing mix elements and the purchase intention of electric vehicles (EVs) in Thailand. Based on a quantitative research design, 253 samples of Thai respondents aged 20 and above were collected via an online questionnaire as a research tool. Structural Equation Modeling (SEM) analysis was used to analyze the proposed hypotheses. The results indicate that all four marketing mix elements, which are product attributes, pricing strategy, distribution channels (place), and promotional activities, significantly influence the purchase intention of electric vehicles. Product attributes (b = 0.523) have the strongest impact on purchase intention, followed by pricing strategy (b = 0.501), distribution channels (place) (b = 0.477), and promotional activities (b = 0.334) respectively. The results of moderation analysis reveal that environmental awareness significantly moderates the effect of product attributes (b = 0.412) and pricing strategy (b = 0.305) on purchase intention but is not found in the relationships of distribution channels (place) and promotional activities toward purchase intention. Additionally, consumer product knowledge of EVs was found to significantly and negatively moderate only the influence of promotional activities (b = -0.343) on purchase intention. In other words, potential consumers who possess higher EV knowledge seem to be less influenced by promotional activities in their decision to buy EVs. These findings highlight the importance of integrating environmental concerns and EV product knowledge into the firm’s marketing strategies to boost EV adoption in emerging countries. The implications and recommendations will be discussed in the paper.

The Impact of FDI On Economic Growth: Evidence from Different Sectors and Economic Conditions

The objective of this study is to examine how the foreign direct investment (FDI) influence China's economic expansion and evaluate its diverse role in various sectors and economic circumstances. This study uses multiple regression panel data Fixed Effects models with the robust standard errors to investigate further the potential significant impacts of both FDI inflows and outflows on economic development in China. The study employs panel data from 29 provinces in China, spanning the period from 2003 to 2021 for its analysis. This study found that FDI inflow contribute significantly and positively on growth in three different sectors, while outflow of FDI shows insignificant but positively correlated with growth. The results of coefficients reveal that FDI inflow in secondary sector has the strongest impact on growth, followed by primary and tertiary sector. Additionally, by including crisis in the models, the positive and significant impact of FDI inflow remain unchanged with the domestic investment became significantly and positively affect the economic growth. Hence, this study recommends the policy makers to promote and encourage more foreign investors to invest in China by giving some incentives such as reduction in capital gains taxes and more subsidies to the domestic firms especially in secondary sector.

Processing, Nutrients, Market Access, and Pumpkin Rice Acceptance

This study investigates the effects of processing techniques, nutrient content, and market accessibility on consumer acceptance of pumpkin analogue rice in Indonesia. As consumer demand for healthier and more sustainable food alternatives grows, understanding the key factors driving acceptance of innovative products like pumpkin analogue rice is critical. Using a quantitative approach, data were collected from 90 respondents through structured questionnaires and analyzed with SPSS version 25. The results reveal that processing techniques, nutrient content, and market accessibility significantly influence consumer acceptance, with nutrient content having the strongest impact. The findings suggest that optimizing processing methods, emphasizing health benefits, and improving market accessibility are essential for increasing the adoption of pumpkin analogue rice. This study provides practical insights for food producers and marketers seeking to promote healthier food alternatives in emerging markets.

Analysis of the Influence of Intrinsic and Extrinsic Factors on Teachers' Work Motivation in Improving Educational Performance in Elementary Schools

This research investigates the influence of intrinsic and extrinsic factors on teachers' work motivation and its impact on educational performance at primary schools. The study addresses the crucial role of teacher motivation in enhancing school education quality. Using a quantitative, descriptive-correlational methodology, the study examined the statistical relationships between intrinsic factors, such as job satisfaction and commitment, and extrinsic factors, such as financial rewards and work environment, on teachers' motivation. Data was gathered from 60 respondents, selected through purposive sampling, and analyzed using multiple linear regression and Pearson correlation. The results revealed that intrinsic factors had a stronger impact on work motivation than extrinsic factors, though both were significant. Teachers who experienced greater job satisfaction and commitment exhibited higher motivation, ultimately leading to better performance in teaching. The study concludes that strategies for improving teacher motivation should prioritize intrinsic factors, while still recognizing the importance of supportive extrinsic elements. This research provides valuable insights into balancing motivational strategies and suggests further exploration in diverse educational contexts to validate the findings.

Quantifying the weights of sensory influences on postural control across development

BACKGROUND: This study examined the weighting of multisensory and anthropometric factors in driving children’s and adult’s postural control. METHOD: A data set was created by aggregating individual participants’ postural stability measures from four target studies, employing participants ranging in age from 3 to 11 years, along with young adults. Using a meta-regression approach, this aggregate data set was then predicted from dummy codings of the including visual, haptic, and proprioceptive sensory inputs manipulated in these studies, as well as the anthropometric factor of participant height. Two forms of coding regimens were examined – one capturing simple presence versus absence of sensory sources, and one quantifying the degree of stability provided by sensory sources. RESULTS: The results of this study revealed that proprioceptive input had the strongest impact on stability, followed by roughly equivalent visual and haptic inputs, and finally anthropometric factors. Developmentally, this pattern of findings was stable by 5- to 7-years of age. Although both coding schemes predicted posture, the degree of stability coding scheme provided consistently superior predictions. INTERPRETATION: These findings are discussed with respect to a multicomponential approach to postural control, a framework that emphasizes the importance of multiple component factors in characterizing complex behavior.

The Effect of Job Recognition and Development Opportunities on Loyalty and Job Satisfaction of Generation Z in Jakarta's Creative Industries

This study investigates the influence of job recognition and development opportunities on job satisfaction and loyalty among Generation Z employees in Jakarta’s creative industries. Using a quantitative approach, data was collected from 230 respondents through a Likert-scale questionnaire and analyzed using Structural Equation Modeling (SEM-PLS). The results show that both job recognition and development opportunities have significant positive effects on job satisfaction and loyalty. Development opportunities were found to have a stronger impact on job satisfaction, while job recognition also significantly influenced both outcomes. These findings highlight the importance of tailored human resource strategies that focus on recognizing employee contributions and providing career development pathways. Organizations in Jakarta’s creative industries can enhance retention and satisfaction by investing in these key areas.

Individual-level metabolic connectivity from dynamic [18F]FDG PET reveals glioma-induced impairments in brain architecture and offers novel insights beyond the SUVR clinical standard.

This study evaluates the potential of within-individual Metabolic Connectivity (wi-MC), from dynamic [18F]FDG PET data, based on the Euclidean Similarity method. This approach leverages the biological information of the tracer's full temporal dynamics, enabling the direct extraction of individual metabolic connectomes. Specifically, the proposed framework, applied to glioma pathology, seeks to assess sensitivity to metabolic dysfunctions in the whole brain, while simultaneously providing further insights into the pathophysiological mechanisms regulating glioma progression. We designed an index (Distance from Healthy Group, DfHG) based on the alteration of wi-MC in each patient (n = 44) compared to a healthy reference (from 57 healthy controls), to individually quantify metabolic connectivity abnormalities, resulting in an Impairment Map highlighting significantly compromised areas. We then assessed whether our measure of metabolic network alteration is associated with well-established markers of disease severity (tumor grade and volume, with and without edema). Subsequently, we investigated disruptions in wi-MC homotopic connectivity, assessing both affected and seemingly healthy tissue to deepen the pathology's impact on neural communication. Finally, we compared network impairments with local metabolic alterations determined from SUVR, a validated diagnostic tool in clinical practice. Our framework revealed how gliomas cause extensive alterations in the topography of brain networks, even in structurally unaffected regions outside the lesion area, with a significant reduction in connectivity between contralateral homologous regions. High-grade gliomas have a stronger impact on brain networks, and edema plays a mediating role in global metabolic alterations. As compared to the conventional SUVR-based analysis, our approach offers a more holistic view of the disease burden in individual patients, providing interesting additional insights into glioma-related alterations. Considering our results, individual PET connectivity estimates could hold significant clinical value, potentially allowing the identification of new prognostic factors and personalized treatment in gliomas or other focal pathologies.

Downward Intergenerational Support and Well-Being in Older Chinese Adults

Life satisfaction, as an important indicator of subjective well-being, is crucial for older adults. This study aims to examine the effects of downward intergenerational financial and practical support on life satisfaction among older adults in China, while exploring the mediating role of self-esteem and the potential differences across gender. Data were collected from 507 older adults aged 60 and above in China. The findings indicate that both financial and practical support provided by older adults positively predict their life satisfaction. Mediation analysis reveals that self-esteem partially mediates the relationship between downward intergenerational support and life satisfaction. This suggests that helping their children enhances older adults’ sense of self-worth, which in turn improves their overall well-being. Gender differences were also observed: financial support had a stronger impact on life satisfaction for men, while practical support was more significant for women. These results highlight the influence of traditional gender roles and cultural expectations on the dynamics of intergenerational support in contemporary Chinese families.

Emotional aftermath of the 2020 U.S. presidential election: a study of hindsight bias in younger and older adults

ABSTRACT Hindsight bias – also known as the knew-it-all-along effect – is a ubiquitous judgment error affecting decision makers. Hindsight bias has been shown to vary across age groups and as a function of contextual factors, such as the decision maker’s emotional state. Despite theoretical reasons why emotions might have a stronger impact on hindsight bias in older than in younger adults, age differences in hindsight bias for emotional events remain relatively underexplored. We examined emotion and hindsight bias in younger and older adults (N = 272) against the backdrop of the 2020 U.S. presidential election. Participants predicted electoral college votes for the two presidential candidates before the election and were asked to remember their predictions approximately three weeks later, after the election results had been finalised. Republicans, for whom the electoral outcome was negatively tinged, exhibited greater hindsight bias for President Biden’s result compared with Democrats, for whom the electoral outcome was positive. The asymmetry in hindsight bias between Republicans and Democrats was similar for younger and older participants. This study suggests that negative emotions may exacerbate hindsight bias, and that adult age differences in hindsight bias observed in laboratory settings may not translate to real-world contexts.