Purpose This study aims to revisit the expropriation and bonding effects of specific asset investment (SAI) in B2B marketing channels by considering the dual pathways of channel role behaviors (suppliers’ in-role contract enforcement and distributors’ extra-role altruistic behavior) between SAI and cooperative performance and examines how suppliers’ fairness perceptions (distributive and procedural fairness) moderate these relationships. Design/methodology/approach Drawing on agency theory and equity theory, this study develops a comprehensive model connecting SAI, channel role behaviors and fairness perceptions. The hypotheses were tested using survey data collected from 580 home appliance distributors in mainland China. Findings The results reveal that SAI positively influences both suppliers’ in-role contract enforcement and distributors’ extra-role altruistic behavior, with both channel role behaviors positively contributing to cooperative performance in B2B relationships. Fairness perceptions moderate these relationships differently: distributive fairness enhances the relationship between SAI and distributors’ extra-role altruistic behavior, while procedural fairness strengthens the relationship between SAI and suppliers’ in-role contract enforcement. Channel role behaviors partially mediate the relationship between SAI and cooperative performance. Originality/value This study contributes to B2B marketing channel literature by revisiting SAI from the perspective of channel role behaviors, providing a novel lens to understand the expropriation and bonding effects in industrial exchange relationships. By identifying how suppliers’ SAI simultaneously influence different types of channel role behaviors, this study reveals important mechanisms through which these investments transmit to cooperative performance. This study also demonstrates how different dimensions of fairness shape these behavioral pathways in B2B contexts, offering new insights for channel relationship management beyond traditional perspectives.

ABSTRACT Fast-moving consumer goods (FMCG) brands are increasingly pursuing a purpose. Despite this development, it is unclear how brand purpose affects brand outcomes, such as loyalty. This article addresses this research gap by examining how brand purpose affects brand loyalty in the FMCG sector, with special consideration given to brand distinctiveness and brand-value congruence. Online survey data from 400 UK consumers, representative in terms of age, gender, and political party affiliation, were analysed using partial least squares structural equation modelling. The results reveal that brand purpose only indirectly enhances brand loyalty through brand distinctiveness, while the direct effect of brand purpose on brand loyalty is not significant, irrespective of brand-value congruence. Hence, brand distinctiveness represents an important but underexplored mechanism through which brand purpose exerts its positive impact on brand loyalty. This improved understanding of the relationship between brand purpose and brand loyalty can help brand managers incorporate brand purpose into strategies to profile brands in the highly competitive FMCG sector.

Initial public offerings represent one of the most information‑dense and uncertainty‑laden stages in corporate finance. Although regulatory frameworks require firms to disclose extensive risk information, long‑standing questions remain about whether investors genuinely understand these disclosures or simply navigate around them. This study examines the relationship between investor awareness of IPO risk factors and the risks that issuing firms formally disclose. Grounded in behavioural finance and disclosure theory, the research explores whether a meaningful gap exists between what companies communicate and what investors actually comprehend. The study draws on survey data from a multi‑country sample of IPO investors and uses structured Likert‑scale analysis to assess awareness across seventeen categories of macroeconomic, regulatory, financial, and firm‑specific risk. These categories reflect the breadth of risks typically highlighted in prospectuses and provide a detailed basis for evaluating how investors interpret disclosed information. The findings reveal a high degree of alignment between investor awareness and the risk categories disclosed by firms. This challenges the common assumption that retail investors routinely misunderstand IPO risks or are overwhelmed by disclosure complexity. Instead, the results suggest that investors engage selectively but meaningfully with the information they consider most relevant. The study contributes empirical evidence to ongoing debates about disclosure effectiveness, investor cognition, and market transparency. It also offers practical implications for regulators seeking to refine disclosure requirements, for issuing firms aiming to communicate risk more effectively, and for investor education initiatives focused on strengthening informed participation in IPO markets.

This study explores the relationships between ICT uses for various purposes and mental health and the moderating effect of technology learning among Chinese and Korean older Americans. The survey data were collected from 513 Chinese and Korean older Americans in New York City. Negative binomial regression was used to examine the relationships between ICT uses for social, instrumental, and health purposes, and depressive symptoms. Interaction terms between ICT use variables and technology learning styles were created for the moderation test. We found that ICT uses for social contact and health purposes were significantly associated with lower depressive symptoms among the Chinese and Korean older Americans, and the benefits were more pronounced for those who learned ICT independently. This study highlighted the importance of supporting ICT uses for social contact and health purposes and technology learning process to improve mental health of older Asian Americans.

ABSTRACT A key methodological concern in using large language models (LLMs) for survey research is whether their outputs are merely ‘prompt-valid’ rather than ‘theory-valid.’ This study empirically evaluates that distinction. Using a validated structural model linking perceived aging risk, attitudes toward private medical insurance, and insurance purchase intentions, it compares one human dataset with four GPT-4o datasets generated under progressively structured prompts. GPT-4o produces plausible Likert-scale responses and, when given path-informed instructions, recovers the expected mediation structure. However, without such cues, the model fails to reproduce the theory-consistent relationships that reliably emerge in human data. These findings indicate that structural coherence in LLM-generated responses primarily reflects the relational logic imposed by the prompt rather than autonomous inference. LLMs may support pretesting and instrument development, but their role in theory testing should remain supplementary, transparent, and methodologically constrained.

Species distribution models (SDM) are key tools in ecology, conservation, and natural resources management. They are traditionally trained with data on direct species observations. However, if collecting species data is difficult or expensive, complementary information sources on species distributions are needed. Expert knowledge has been demonstrated to improve SDM predictions in a number of such applications but there is still no consensus on methods to integrate information from several experts into a single coherent species distribution prediction. Moreover, since expert assessments are inherently subjective and prone to biases, expert‐driven SDMs should calibrate their assessments. We propose a method to tackle these challenges by extending the hierarchical Bayesian integrated species distribution modeling framework to expert informed species distribution modeling. We treated map‐like expert assessments as data and integrated them with calibration data on species recordings. Our integrated SDM has model components to estimate experts' reliability and to adjust for potential biases in their assessments. After integrated inference, we used the model to make predictions over a study area. We tested our approach with an extensive simulation study and a real world case study comprising ten expert assessments and survey data on pikeperch larvae from a coastal area of the Gulf of Finland. Expert assessments significantly improved species distribution predictions compared to predictions conditioned on survey data only. They also improved parameter inference, thus strengthening the ecological interpretation of the results. The skill of the experts, and biases in their assessments, varied considerably in the case study though, emphasizing the importance of formal expert calibration provided by our model. Our results show that expert elicitation can be an efficient tool for improving species distribution model predictions. Our approach is especially useful for applications where any type of species data are expensive to collect but local species experts can easily be reached.

Small business entrepreneurs face challenges in attracting investors and stabilizing their ventures, yet many adopt socially responsible HRM practices beyond shareholder demands, legal compliance, and union contracts. What drives these choices remains underexplored. Drawing on upper echelon theory, this study examines how CEO founders’ social-emotional skills and race predict the adoption of fair pay practices. We further suggest that access to market salary data and pay equity information (fair pay knowledge) serve as cognitive mechanisms linking founder characteristics to compensation decisions. Survey data from 125 women entrepreneurs in the U.S. indicate that higher responsible decision-making competency is associated with greater fair pay knowledge, which in turn predicts implementation of fair pay practices. Notably, after accounting for human capital, social-emotional skills, and firm revenue status, Black, Indigenous, and people of color reported lower adoption of fair pay practices, largely due to reduced fair pay information access relative to their White counterparts.

Purpose This study aims to examine the impact of innovative work behaviour (IWB) on sustainable innovation in micro-enterprises. While IWB is recognised as a driver of innovation in larger firms, its role in small-scale businesses remains unclear. This research investigates whether IWB fosters social and ecological innovations in micro-enterprises. Design/methodology/approach The study is based on survey data from 1,848 Polish micro-enterprises. A multivariate probit model (MVP) is used to assess the relationship between different dimensions of IWB (idea generation, exploration, championing and implementation) and sustainable innovations, measured according to the OSLO Manual and European Commission frameworks. Findings The results show that only idea exploration (seeking improvements beyond routine tasks) and idea implementation (efforts to develop new solutions) have a significant influence on sustainable innovation. Other IWB dimensions, such as idea generation and championing, have no significant effect. This suggests that proactive problem-solving and applied innovation are key to advancing sustainability in micro-enterprises. Practical implications Micro-enterprises should prioritise fostering employee behaviours related to exploring and implementing innovative solutions. Policymakers and business leaders should focus on training programs that enhance these capabilities to support ecological and social innovation. Originality/value This study provides empirical evidence on how IWB influences sustainability in micro-enterprises, an under-researched sector. By identifying the most impactful dimensions of IWB, it offers valuable insights for both academia and practice.

Purpose Brands increasingly rely on both celebrities and social media influencers to build brand equity in digitally mediated environments. Despite their widespread managerial use, it remains unclear why these two types of opinion leaders shape consumer-based brand equity (CBBE) through different psychological mechanisms. This study addresses this issue by examining whether credibility and parasocial relationships (PSRs) operate as distinct pathways through which celebrities and influencers contribute to brand equity on social media. Clarifying these mechanisms is essential for advancing endorsement theory and for guiding more effective endorsement strategy decisions. Design/methodology/approach The study employs a quantitative, cross-sectional design based on survey data from 310 active social media users in Lithuania. To capture both contributory and indispensable mechanisms, the analysis integrates partial least squares-structural equation modeling with Necessary Condition Analysis (NCA), allowing for a comparison of sufficiency-based effects and non-compensatory conditions across celebrity and influencer endorsement contexts. Findings The results reveal structurally different endorsement mechanisms. For influencers, credibility strengthens PSRs, which in turn positively drive CBBE. In contrast, for celebrities, PSRs do not significantly translate into brand equity. Instead, credibility emerges as a critical prerequisite for celebrities to generate brand equity, even though it does not exert a direct net effect. NCA further shows that PSRs are required, albeit weakly, for influencer-driven brand equity, whereas credibility constitutes a necessary condition in celebrity endorsements. Practical implications The findings demonstrate that celebrities and influencers should not be treated as interchangeable endorsement sources. Influencer strategies should prioritize long-term collaborations that foster relational closeness and emotional attachment, whereas celebrity endorsements require careful credibility screening and strategic fit with brand values. These insights enable managers to align endorsement choices with specific brand equity objectives and to evaluate endorsement effectiveness using mechanism-consistent performance metrics. Originality/value This study advances endorsement research by incrementally extending and refining existing theory to explain why celebrities and influencers influence brand equity through fundamentally different causal pathways. By combining structural equation modeling with NCA, it introduces an asymmetric perspective that moves beyond traditional net-effect explanations and clarifies theoretical boundary conditions in social media endorsement research.

Family stability is increasingly understood as a dynamic outcome shaped by cumulative life experiences rather than static structural conditions. This study examines the contribution of women’s learning trajectories to family stability, conceptualizing learning as a continuous and adaptive process unfolding across the life course. Using a quantitative explanatory design, survey data were collected from 312 adult women actively involved in family functioning. Women’s learning trajectories and family stability were measured as composite variables, and data were analyzed using linear regression and one-way analysis of variance. The results indicate that women’s learning trajectories significantly predict family stability (β = 0.61, p < 0.001), explaining 37% of the variance in the outcome. ANOVA results further reveal significant differences in family stability across low, moderate, and high learning trajectory groups, with the highest stability observed among women with sustained learning engagement over time. These findings provide empirical support for life-course perspectives on learning, demonstrating that cumulative learning experiences among women play a central role in sustaining family stability. The study contributes to research on gender, education, and family by offering a trajectory-oriented quantitative approach with implications for lifelong learning and family-centered policy interventions.

Denominator inflation (DI) can burden long-standing immunization information systems (IIS), evident through a system having more client records than population estimates. DI underestimates IIS vaccination coverages compared to National Immunization Surveys (NIS) data. To mitigate DI, the Wisconsin Immunization Registry (WIR) implemented a dormant indicator in June 2020. Clients are presumed to have left the jurisdiction and are placed in the dormant state if they meet the following criteria: client age is at least 11 years old, no updates to the client record in at least 10 years, and the record has not been queried in the last five years. The querying component is a novel approach when compared to American Immunization Registry Association recommendations for the Patient Active/Inactive Status. The study purpose was to quantify how incorporating the dormant state in an adolescent population assessment impacts Wisconsin's vaccination coverage rates compared to the NIS-Teen estimates. This study also addressed the population characteristics of adolescent dormant state and non-dormant state client records. The study population included all Wisconsin adolescents, aged 13-18 years, and assessed vaccine uptake for Meningococcal ACWY , Tdap, HPV initiation, and HPV Complete. Vaccination coverage was assessed, with and without the dormant clients, and then compared to the NIS-Teen estimates. Descriptive statistics were assessed among dormant and non-dormant clients, including a regional variation assessment. Initial results showed an increase in adolescent vaccination rates for all vaccines and series when excluding dormant clients and suggest a more accurate assessment in line with NIS-Teen estimates. Dormant clients had a higher proportion of unknown and missing data fields for race, sex, and ethnicity. At this time, removing dormant client records is an effective strategy for reducing DI in WIR, with opportunities for further refinement.

Access to safe drinking water in rural areas remains a global challenge, particularly where decentralized supply systems are common and water quality is highly variable. In this study, we analyze the relationship between the chemical composition of drinking water and community perceptions of its quality in rural settlements of the Akmola Region of Kazakhstan across different landscape types. Using a mixed-methods approach, hydrochemical analyses of household water samples were conducted, ANOVA and Spearman correlation tests were applied, and village-level survey data were collected to assess the complaints, satisfaction, and water purification practices of residents. Results indicate that most water sources are of Ca–Mg–Cl–HCO 3 type, with steppe villages showing higher levels of dissatisfaction. These findings highlight the importance of aligning technical water assessments with local perceptions to improve rural water governance and foster community trust in water safety initiatives.

Early neonatal mortality is a serious public health issue in Ethiopia. Therefore, this study aimed to map the regional disparities and identify factors contributing to early neonatal mortality in Ethiopia over time. Ethiopian demographic and health survey (2000-2019) dataset were utilized. A total of 80,286 early neonates was included in this study. Logit based decomposition analysis was employed to understand the contributing factors for the change in early neonatal mortality over time. Getis Ord GI* statistic was performed to identify the cold and hot spots of the early neonatal mortality in Ethiopia. In addition, kriging interpolation was used to predict the burden of early neonatal mortality in the unsampled areas of the country based on the observed data. Early neonatal mortality trends in Ethiopia has been decline from 43 in 2000 to 33 in 2019 per 1000 live births. It was spatially clustered, with significant hotspots in the Benishangul Gumuz and some areas of Oromia, Tigray, Amhara and Somali regions. In the logit multivariable decomposition analysis babies born in rural (B - 0.0002, 95% CI - 0.002 to - 0.001), Women had partner (B - 0.0005, 95% CI - 0.0007 to - 0.0003), preceding birth interval ≥ 2years (B - 0.008, 95% CI - 0.005 to - 0.001), Health facility delivery (B - 0.001, 95% CI - 0.003 to - 0.001), had ANC visits (B - 0.02, 95% CI - 0.03 to - 0.01), early initiations of breastfeeding (B - 0.002, 95% CI - 0.003 to - 0.001), multiple pregnancies (B - 0.002, 95% CI - 0.003 to - 0.001), and mothers education higher (B - 0.004, 95% CI - 0.006 to - 0.002) were a substantial factors that contribute to the change in the decline in early neonatal mortality in Ethiopia over time. Strengthen maternal and newborn care, expand skilled birth attendance, enhance antenatal and postnatal services, and utilize spatial evidence to inform targeted policy and resource allocation.

Agri-environmental subsidies had been implemented to promote sustainable agriculture in regions such as the EU and the U.S. prior to the year 2000. Contract-Based Agri-Environmental Schemes (AESs) are designed to promote green, sustainable agriculture by employing environmentally friendly farming practices (EFFPs) to reduce pollution and meet other environmental goals. A central challenge, however, is the limited inclusion of small farmers, who are key to agricultural sustainability and form the backbone of production, particularly in developing countries. This study aims to investigate the preferences and participation of small farmers in AESs to enable effective policy design. Using discrete choice experiments (DCEs) and a latent class model (LCM) on survey data collected in 2017 from three key rice-producing counties in China—Fangzheng (Heilongjiang), Qingtongxia (Ningxia), and Yixing (Jiangsu)—allowed us to identify two distinct preference classes: “experienced adopters” and “potential adopters”. The results confirmed (1) a high participation rate of small farmers in AESs. Compensation can further motivate them to sign a contract. (2) There is significant heterogeneity among small farmers’ preferences on various EFFPs, so flexible and modulated schemes are needed; (3) those with experience in EFFPs are more likely to participate in AESs; and (4) the modular AES contract with progressive subsidy ties makes payments directly based on EFFP adoption, addressing the shortcomings of China’s current area-based subsidy system. The results of this paper can help policymakers fine-tune farming policies that effectively engage smallholders, thereby alleviating tensions over production–pollution cycles and fostering a more targeted and sustainable agricultural policy system.

ABSTRACT This study analyzes 2021 Chinese Social Survey data to examine how social capital relates to trust in police. Multiple mediation analysis shows social capital directly enhances police trust. Public security perception is a significant mediator, whereas political participation alone is not. However, a sequential pathway exists: social capital → public security perception → political participation → police trust. The most influential indirect mechanism is “social capital → public security perception → police trust.” These findings clarify the interplay between social capital, institutional perceptions, and civic engagement in building public trust, offering insights for improving police-community relations.

This research paper analyses the effects of the Punjab Kissan Card Subsidy Program (KCSP) on food security, utilizing primary survey data from 440 farming households PAN India based in four food insecure vulnerable districts of Southern Punjab- Lodhran, Rahim Yar Khan, Layyah and Muzaffargarh. A multi-stage stratified random sampling approach designed to select the respondents and to collect data on socio-demographic variables, livelihood activities and validated measures of food security was used, including Food Consumption Score (FCS) and the Household Food Insecurity Access Scale (HFIAS). A double robust econometric approach based upon Propensity Score Matching (PSM) and Inverse Probability Weighted Regression Adjustment (IPWRA) was used to correct for potential selection bias. Results indicate that there is heightened dietary diversity in participating households which have food secure status as measured by FCS toward higher levels and a reduced food insecure status as measured by HFIAS which declined on respective scores through the models. The positive impact of the program is generated the more the farmer has access to ICT tools and digital assistance to improve thereby the income accruing from the utilization of those tools hence highlighting what the digital inclusion can bring in maximizing that benefit from food insecurity generated by the KCSP. While the KCSP is shown to have considerable potential to improve food security in the participants, structural barriers exist, including tenant farmers excluded from the program, poor awareness and complexity of access and registration. Policy implications include simplifying access and registration, increasing digital literacy and providing complementary nutrition intervention focused initiatives that will ensure that the level of food security is potentially healthy, nutritional, beneficial and beneficial for all involved onward sustainably.

Incomplete survey data often undermines the reliability of Building Information Models (BIM), particularly for structures with restricted access and complex geometries. This study demonstrates a hybrid Scan-to-BIM workflow that integrates terrestrial laser scanning (TLS) and unmanned aerial vehicle (UAV) photogrammetry, supported by a predictive feasibility concept, to improve documentation accuracy and completeness. A two-phase strategy was validated on a chapel case study. Phase 1, combining TLS and ground-based photogrammetry, achieved only 54% coverage due to severe occlusions and limited scanner placement. These results led to the formulation of a Predictive Scan Feasibility Estimation Model (PSFEM), designed to generalize site-specific parameters such as scanner range, clearance angle, and building height into a decision-support tool for future surveys. Guided by the recognition of Phase 1 limitations, Phase 2 incorporated UAV photogrammetry and supplemental TLS, increasing coverage to 96%. Comparative analyses confirmed consistency in accuracy and improved geometric completeness. While the PSFEM was developed retrospectively based on the limitations identified in Phase 1, its analytical validation demonstrates the potential value of predictive planning for reducing redundant site visits and enhancing BIM reliability. The proposed framework provides a transferable basis for applying predictive hybrid workflows in both heritage and complex building documentation. This workflow offers a practical and scalable method for Scan-to-BIM documentation, applicable to heritage as well as other complex buildings, enabling high accuracy and completeness while effectively managing time and resources.

Some mentoring programs for youth have incorporated principles or strategies from cognitive behavioral therapy (CBT), but research addressing the effectiveness of such programs is limited. This research is an evaluation of the impact of participation in Reach & Rise®, a program in which all mentors are supported in using CBT principles in their relationships with youth. Researchers randomly assigned youth either to be matched with a mentor through Reach & Rise® (i.e., treatment group; n = 316) or a waitlist control group (n = 284). We examined intent-to-treat effects using youth and caregiver survey data 15 months after study enrollment. Relative to the waitlist control group, we found treatment group youth to be significantly less likely at follow-up to report delinquent behavior (Treatment: 8%, Control: 15%, respectively) and substance use (28% and 43%, respectively). Treatment group youth also had significantly greater self-reported connectedness to school (Cohen's d = 0.267) and caregiver-reported academic performance (d = 0.214) and, at borderline significance (p = .05), greater reported connectedness to their families (d = 0.177). The groups did not differ on the remaining measures, which included youth reports of depressive symptoms, happiness, hope for the future, life satisfaction, and quality of peer relationships. Reach & Rise® shows promise for reducing problem behavior among youth while also positioning them for success and positive adaptation in contexts that are important for adolescent development. In the future, researchers should investigate avenues for broadening the scope of benefits to include aspects of emotional well-being. In view of the support established through this research for the effectiveness of the overall program, another logical next step would be to examine the unique contribution of the CBT principles embedded in the program to youth outcomes.

The object of research in the article is the information technology of autonomous group control of a multi-satellite system for remote sensing of the Earth. An orbital grouping of small satellite clusters is considered as case study. Clusters refer to satellites that are located close to each other. The information technology is based on an agent-oriented approach and information interaction of satellite software agents based on the use of inter-satellite communications. The information interaction of agents is considered taking into account the dynamics of the establishment of inter-satellite communication lines over time. It is assumed that communication within clusters is possible in real time, and communication between clusters is only possible within time intervals during which the necessary conditions are met. The purpose of information interaction protocols is the autonomous group solution (without the participation of the ground control complex) of the following tasks: 1) distribution and redistribution of requests within each cluster and 2) between clusters, 3) determination and coordination of the procedure for transmitting observation data to Earth during the establishment of communication sessions with ground points, and 4) search for an appropriate distribution of survey data between clusters using inter-satellite communication, ensuring a reduction in the time of delivery of survey data to Earth. In the process of participating in information interaction protocols, agents perform autonomous planning of the targeted use of their satellite. This planning includes finding an acceptable shooting plan and forming a flight plan taking into account the technical capabilities and limitations of the satellite, as well as taking into account the control of the electrical balance. Demonstration of capabilities and evaluation of the effectiveness of information technology is carried out using software implementation of its simulation model. The article provides a description of examples of output data that are generated during simulation modeling.

ABSTRACT Institutional investors are increasingly responding to biodiversity loss through nature‐related investment strategies. Using survey data from 557 institutional investors, this study examines the drivers of strategy selection and how biodiversity risk is integrated across investor types, sizes, and regions. Financial motivations, especially risk reduction and return opportunities, are most strongly associated with divestment and portfolio biodiversity risk analysis, while shareholder engagement remains comparatively limited. Pressure from clients and activists steers institutional investors toward visible, low‐burden measures (risk analysis, divestment, and target‐setting) rather than resource‐intensive stewardship. US‐based investors report stronger commitments to nature‐related investments, whereas larger institutions do not exhibit higher engagement. The findings suggest targeted policy support for nature‐related investment practices: clearer recognition of biodiversity loss as a financially material risk within fiduciary frameworks, integration of nature objectives into stewardship codes and proxy‐voting norms, and harmonized biodiversity disclosure standards to reduce data uncertainty and enable more effective investor responses.