Search Results (21)

The increasing integration of renewable energy sources into electricity grids has created a critical need for residential energy flexibility, i.e., the ability of consumers to adjust their electricity consumption patterns in response to grid conditions. Understanding the psychological and behavioral factors that influence consumers’ willingness to provide such flexibility is essential for designing effective demand response programs. Drawing on the motivation–opportunity–ability (MOA) framework, value–belief–norm (VBN) theory, and insights from behavioral economics, this study examined the individual-level factors related to residential consumers’ intentions to offer energy flexibility. Survey data were collected from 1278 respondents across Greece, Slovenia, and Finland as part of the iFLEX project. Using path analysis, we found that environmental personal norms significantly predicted flexibility behavioral intentions, while environmental worldviews predicted personal norms. Moreover, personal norms mediated the relationship between environmental worldviews and behavioral intentions. The results also supported an updated, hierarchical MOA framework, demonstrating that energy flexibility capacity acts as an upstream enabler for digital tech expertise, while automated flexibility/flexibility advice and flexibility visualization operate as highly co-dependent opportunity factors. Ultimately, the integrated model demonstrated strong explanatory power, accounting for 37% of the variance in flexibility behavioral intentions ($R^2=0.37$), and remained highly robust across diverse socio-demographic profiles. Normative social influence ($\beta =0.26$), external flexibility control ($\beta =0.23$), and external locus of control ($\beta =0.18$) emerged as the primary direct predictors of flexibility intentions, supported by environmental personal norms, environmental worldviews, flexibility visualization, and digital tech expertise. Drawing on Kahneman’s dual-process theory, we interpret these findings in terms of the cognitive effort required for flexibility decisions. These findings extend VBN and MOA theories in the context of residential energy flexibility and offer practical insights for designing effective demand response programs. Full article

Carbon inclusivity (CI) mechanisms face weak low-carbon adoption despite strong consumer intention in China. Prior studies explain low-carbon behavior mainly from individual psychological perspectives yet rarely investigate the intention–behavior gap in the digital–physical scenarios of CI mechanisms. Furthermore, single theoretical lenses such as the Motivation–Opportunity–Ability (MOA) framework or Social Practice Theory (SPT) have clear limitations in interpreting this gap. This study integrates the MOA framework with SPT to construct a novel “Motivation–Intention–Context–Practice–Behavior” (MICPB) model, framing behavioral change as a dynamic interplay of internal motivation, external opportunities, and evolving social practices. Different from studies adopting MOA or SPT in isolation, the MICPB model bridges individual psychological processes and routine social practices to unpack the intention–behavior gap. Adopting grounded theory to analyze 42 interviews from China’s CI pilot regions, we identify three core dimensions of the gap: limited internal competencies and emotional conflicts, fragmented external incentives and platform defects, and misalignment between low-carbon values and daily routines. The MICPB model reveals that the gap stems from misalignment across motivation, context and practice, and enriches MOA theory by incorporating practice-based dynamics. This integrated framework deepens understandings of barriers to consumer low-carbon participation under CI schemes. This study suggests coordinated policy and corporate efforts to restructure social practices, bridge the intention–behavior gap, and align digital governance with low-carbon transitions. Full article

MoA (mathematics of arrays) is a theory of parallel operations on arrays that can describe all known algorithms in linear algebra, signal processing, and HPC because they are based on primitive recursion and array shapes. Mapping parallel algorithms to computer architectures remains more of an art than a science, and specific mathematical techniques are needed to provide a basis for performance evaluation at a level abstract enough to constitute an experimental science. In this paper we present a methodology for parallel code generation from MoA expressions. Then, we relate the MoA operators to the linear space of memory elements in computer architecture. Finally, we define a theory of execution costs that is based on classical operations research and is formally related to MoA-based parallel code generation. This constitutes a formalized and mechanizable approach to performance prediction, portability and optimization. Full article

In 2021, Quanzhou, China, was added to the UNESCO World Heritage List. Using the Motivation–Opportunity–Ability (MOA) theoretical framework, this study examines how motivation, opportunity, and ability factors influence community participation (CP) in conserving and developing tourist attractions. Quanzhou’s World Heritage Site (WHS) was chosen as the case study, while Social Media Involvement (SMI) was selected as a moderator for this analysis. Through PLS-SEM, a total of 405 valid responses were examined and evaluated. The findings show that based on the MOA framework, Motivation Positive Perceptions (MPP), Opportunity (OPP), Awareness (AAW), and Knowledge (AKN) have significant positive effects on CP, whereas Motivation Negative Perceptions (MNP) exert a significant negative effect on CP and Motivation Interest (MINT) does not achieve statistical significance. Additionally, all motivation, opportunity, and ability factors have significant positive moderating relationships with CP through SMI. Hence, this study confirms that the MOA framework is applicable to the context of Chinese World Heritage Sites; it extends the current understanding of how social media can play a role in the governance of cultural heritage (CH). Thus, this study provides both a theoretical basis and practical considerations for CP in the sustainable conservation and tourism development of WHSs. Full article

In the context of China’s dual-carbon agenda and the Digital China initiative, elucidating the role of digital literacy in shaping consumption-based household carbon emissions (HCE) is essential for advancing low-carbon urban living and supporting a broader green transition. Existing research has rarely examined, at the individual level, how digital capability shapes household consumption decisions and the structure of carbon emissions. Accordingly, this study draws on matched household-individual microdata from the China Family Panel Studies (CFPS). We employ a two-way fixed effects model, kernel density analysis, and qualitative comparative analysis. We test the nonlinear effect of digital literacy on household consumption-related carbon emissions and examine its heterogeneity. We also examined the mediating role of perceived environmental pressure, social trust and income level. The research results show that: (1) The net impact of digital literacy on carbon emissions related to household consumption shows an inverted U-shaped curve, rising first and then falling. When digital literacy is low, it mainly increases emissions by expanding consumption channels, reducing transaction costs and improving convenience. Once digital literacy exceeds a certain threshold, the mechanism will gradually turn to optimize the consumption structure, so as to support the low-carbon transformation of individuals. (2) The impact of digital literacy on HCE is structurally different in different types of consumption. In terms of transportation and communication expenditure, the emission reduction effect is the most significant, and with the improvement in digital literacy, this effect will become more and more obvious. For housing-related consumption, the turning point appeared the earliest. With the improvement in digital literacy, its effect will enter the emission reduction stage faster. (3) Digital literacy can reduce carbon emissions related to household consumption by enhancing residents’ perception of environmental pressure and strengthening social trust. However, it may also increase emissions by increasing residents’ incomes, because it will expand the scale of consumption, which will lead to an increase in carbon emissions related to household consumption. (4) The heterogeneity analysis shows that as digital literacy improves, carbon emissions increase more strongly among rural residents, people with low human capital, low-income households, and women. However, the turning-point threshold for emission reduction is relatively lower for women and rural residents. (5) Low-carbon transitions in household consumption are shaped by dynamic interactions among multiple factors, and multiple pathways can coexist. Digital literacy can work with environmental responsibility to endogenously promote low-carbon consumption behavior. It can also, under well-developed infrastructure, empower households and amplify the emission-reduction effects of technology. Full article

In the context of multi-autonomous underwater vehicle (multi-AUV) operations, the target assignment is addressed as a multi-objective allocation (MOA) problem. The selection of strategy for multi-AUV target allocation is dependent on the current non-cooperative environment. This paper establishes a multi-AUV allocation situation advantage evaluation system to assess and quantify the non-cooperative environment. Based on this framework, a multi-AUV target allocation model using a bi-matrix game theory is developed, where multi-AUV target allocation strategies are considered as part of the strategic framework within the game. The payoff matrix is constructed based on factors including the situational context of multi-AUV operations, effectiveness, and AUV operational integrity. The Nash equilibrium derived from the game analysis serves as the optimal solution for resource distribution in multi-AUV non-cooperative scenarios. To address the challenge of finding the Nash equilibrium in bi-matrix games, this paper introduces a repulsion process quantum particle swarm optimization (RPQPSO) algorithm. This method not only resolves the complexities of Nash equilibrium computation but also overcomes the limitations of traditional optimization methods that often converge to local optima. A simulation experiment of multi-AUV operations is designed to validate the multi-AUV target allocation model, demonstrating that the RPQPSO algorithm performs effectively and is applicable to multi-AUV task scenarios. Full article

Mathematics of Arrays (MoA) concerns the formal description of algorithms working on arrays of data and their efficient and effective implementation in software and hardware. Since (multidimensional) arrays are one of the most important data structures in Fortran, as witnessed by their native support in its language and the numerous operations and functions that take arrays as inputs and outputs, it is natural to examine how Fortran can be used as an implementation language for MoA. This article presents the first results, both in terms of code and of performance, regarding this union. It may serve as a basis for further research, both with respect to the formal theory of MoA and to improving the practical implementation of array-based algorithms. Full article

Although digital hoarding behavior does not directly affect physical space, with the popularization of cloud storage services, its impact on energy consumption has become increasingly significant, posing a challenge to environmental sustainability. This study focuses on the factors influencing consumer digital hoarding behavior on e-commerce platforms, aiming to provide management decision-making references for e-commerce enterprises to deal with consumer digital hoarding phenomena and improve transaction effectiveness. Based on the Motivation–Opportunity–Ability (MOA) Theory and through the Adversarial Interpretive Structure Modeling Method (AISM), this study systematically identifies and analyzes the influencing factors. The findings reveal that emotional attachment, burnout, and fear of missing out are the main motivational factors directly affecting consumer digital hoarding behavior, with strong interconnections between these factors. Perceived usefulness and platform interaction design are significant opportunity factors, indirectly affecting digital hoarding behavior by improving user experience and satisfaction. E-commerce platform convenience, anticipated ownership, perceived economic value, emotional regulation ability, auxiliary shopping decision-making, perceived behavioral control, and information organization ability are the foundational and intermediate factors. The research results emphasize the importance of understanding consumer digital hoarding behavior in the context of sustainable development. This is not only conducive to optimizing the shopping cart function and data management strategy of e-commerce platforms and improving transaction conversion rates but also provides a reference for policymakers to formulate data management and privacy protection policies. Full article

The rapid development of rural tourism has placed significant pressure on the rural environment, and relying solely on the government and market forces is insufficient for effective governance. It is urgent to integrate endogenous rural forces into environmental governance. The development of social behavior theory offers new insights into exploring sustainable approaches for resident participation in environmental governance in rural tourism areas. This paper, based on the Stimulus-Organism-Response (SOR) theoretical framework from social behavior theory, outlines the entire process of rural tourism residents transitioning from individual stimuli to psychological responses and ultimately to participation in environmental governance. This study combines the Motivation-Opportunity-Ability (MOA) model to analyze the stimulus factors affecting local residents and jointly constructs a path mechanism model for resident participation in environmental governance in rural tourism areas. A total of 462 valid questionnaires were collected through a survey, and the Partial Least Squares Structural Equation Modeling (PLS-SEM) method was used for empirical testing to determine the path coefficients between variables. On this basis, a system dynamics model was constructed to simulate the dynamic evolution of the relationships between variables. This study found the following: (1) In the process of rural tourism, residents’ participation in environmental governance relies on motivational factors at the stimulus level to play a core leading role; opportunity factors act as catalysts, and ability factors serve as auxiliaries; participation willingness at the organism level plays a crucial role. (2) Material pursuit and formal institutions are the strongest single sustainable factors for residents’ participation in environmental governance in rural tourism areas; combinations of variables such as local attachment, governance knowledge, and governance identity have significant effects. It is recommended that future rural tourism leverage government guidance, coordinate interests, and adhere to a collaborative development approach to ensure the sustainable development of the rural tourism environment. Full article

Type 2 diabetes mellitus (T2DM) is characterized by insulin resistance and/or defective insulin production in the human body. Although the antidiabetic action of corn silk (CS) is well-established, the understanding of the mechanism of action (MoA) behind this potential is lacking. Hence, this study aimed to elucidate the MoA in different samples (raw and three extracts: aqueous, hydro-ethanolic, and ethanolic) as a therapeutic agent for the management of T2DM using metabolomic profiling and computational techniques. Ultra-performance liquid chromatography-mass spectrometry (UP-LCMS), in silico techniques, and density functional theory were used for compound identification and to predict the MoA. A total of 110 out of the 128 identified secondary metabolites passed the Lipinski’s rule of five. The Kyoto Encyclopaedia of Genes and Genomes pathway enrichment analysis revealed the cAMP pathway as the hub signaling pathway, in which ADORA1, HCAR2, and GABBR1 were identified as the key target genes implicated in the pathway. Since gallicynoic acid (−48.74 kcal/mol), dodecanedioc acid (−34.53 kcal/mol), and tetradecanedioc acid (−36.80 kcal/mol) interacted well with ADORA1, HCAR2, and GABBR1, respectively, and are thermodynamically stable in their formed compatible complexes, according to the post-molecular dynamics simulation results, they are suggested as potential drug candidates for T2DM therapy via the maintenance of normal glucose homeostasis and pancreatic β-cell function. Full article

Traditional agricultural business entities present environmental problems such as high energy consumption and high pollution. To achieve goals such as carbon capping and carbon neutrality, governments should encourage urban agricultural operators to sell low-carbon agricultural products online. This could play an important role in smoothing the connection between production and marketing, achieving industrial prosperity and promoting low-carbon agricultural development. This paper explores the formation and behavioral transformation of online sales intention by combining the theory of planned behavior, the Motivation–Opportunity–Ability (MOA) model, and the binary Probit regression model using data from 106 questionnaires. The study found that economic expectations and social norms can significantly improve online sales intention during the formation stage of online sales intention. Behavior control is not conducive to improving online sales intention. In addition, we found a gap between the willingness of urban agricultural operators to sell online and their behavior. This gap requires activation and adjustment of the opportunity and capability factors in the behavior transformation phase. Finally, we found that the strengthening of policy conditions and management capacity facilitated the transformation of urban agricultural operators’ willingness to sell online into behavior. This paper provides recommendations for the online sales of low-carbon agricultural products. While we continue to deepen urban agricultural operators’ knowledge of online sales, we should also pay attention to the creation of external opportunities that are suitable for the development of online sales, and identify differences in capacity among operators. This will provide precise services. Full article

Background: Ice sports are an effective means to promote the physical health of adolescents, and the willingness to participate in ice sports is the basis of adolescents’ awareness of their participation in ice sports and an important prerequisite for their participation. The aim of this study is to investigate the mechanisms influencing adolescents’ willingness to participate in ice sports. Methods: Using the stimulus-organism-response theoretical framework, the motivation-opportunity-ability model, and the technology acceptance model, a theoretical model of the influencing mechanisms of adolescents’ participation in ice sports was constructed. A total of 3419 secondary school students were surveyed, and the data were analyzed using structural equation modeling, the mechanisms influencing adolescents’ willingness to participate in ice sports and the moderating role of perceived riskiness and perceived ease of use are proposed and tested. Results: The study found that participation motivation, participation ability, perceived usefulness, and perceived risk all have significant effects on adolescents’ willingness to participate in ice sports. The degree of influence in descending order is as follows: ability to participate, perceived usefulness, motivation to participate, and perceived risk. Perceived risk plays a mediating role in the process of motivation to participate and ability to participate influencing willingness to participate. Perceived ease of use plays a mediating role in the process of motivation to participate influencing perceived usefulness. Conclusions: This study provides a systematic understanding of the mechanisms that influence adolescents’ willingness to participate in ice sports. The findings provide valuable insights into the subject of adolescents’ ice sport participation and can inform the development of strategies to increase participation in these activities. Future research should deepen the investigation of the patterns of willingness to participate in ice sports behavior among adolescents, which is important for promoting the sustainable development of ice sports, improving the health of adolescents, and advancing the construction of a healthy China, a healthy world, and global health. Full article

The COVID-19 pandemic has been an historic challenge to public health, and to behavior change programs. There have been challenges in promoting vaccination in LMICs, including Nigeria. One important hypothesis deserving consideration is the ability to obtain vaccination as a potential barrier to vaccination uptake. The MOA (motivation, opportunity, and ability) framework, as illustrated by multiple theories such as COM-B, EAST, and the Fogg model, is a primary theoretical basis for the evaluation of this ability as a factor in vaccination uptake. There is little research on measuring the ability to get vaccinated in LMICs, including on the role of all of the MOA framework. The aim of this study was to develop and evaluate an ability factors index measured through social media-based data collected in Nigeria in late 2021 and early 2022. We present findings from an online survey of 8574 Nigerians and highlight new social media-based data collection techniques in this research. This study found that a new ability factors index comprising 12 items was associated with vaccine uptake independent of measures capturing other components of the MOA framework. This index may serve as a valuable research instrument for future studies. We conclude that a person’s perceived ability to get vaccinated, measured by a newly validated index, is related to vaccination uptake and hesitancy, and that more research should be conducted in this area. Full article

Food choices are determined by intrinsic and extrinsic product characteristics, biological and physiological features, psychological factors, and situational and socio-cultural factors. Self-determination theory offers the explanation of health behavior change identifying motivations located along a continuum of autonomy. Another approach to the motivations guiding health behaviors, including food choices, relies on distinguishing thematic categories. Health motivations seem to be an obvious determinant of health behaviors, but final decisions regarding health are also the effect of other types of motivations such as economic, cultural, or emotional. The role of marketing pressure in modern society is perceived to be an important source of motivation for purchasing food and other products. The Motivation–Opportunity–Ability (MOA) framework was initially proposed in order to explain the processing of brand information from advertisements and was later expanded to other areas, including health and nutritional behaviors. The aim of this study was the analysis of determinants of food choices. We have developed a common regression model including six categories of motivations addressed by the Eating Motivations Scale and three health literacy types corresponding with element of ability from the MOA framework, adjusted for socio-demographic factors, health status, and the use of the Internet and TV. The analysis was performed on data from a computer-assisted web-based interviewing (CAWI) survey among 2008 adult Internet users completed in May 2022. The uni- and multivariate linear regression models were developed with the Index of Unhealthy Food Choices (IUFC), calculated based on the responses to items asking about the frequency of the consumption of twelve food categories. Univariate modeling revealed that IUFC is significantly associated with health, food, and e-health literacies and with five out of six eating motivations. However, the multivariate regression model yielded significant associations only for eating motivations but not for the three literacy scores. Health motivation was negatively associated with IUFC (B, standard error (SE): 0.83, 0.07; 95% confidence interval (95% CI): 0.98–0.69), but positively with emotional (B, SE: 0.22, 0.04; 95% CI: 0.14–0.3), economic (B, SE: 0.41, 0.08; 95% CI: 0.25–0.56), and marketing (B, SE: 0.62, 0.08; 95% CI: 0.47–0.78) motivations. Our findings suggest that motivations guiding food choices may prevail over the element of ‘ability’ distinguished in the frameworks and models that explain people’s behaviors, including behaviors relating to health. Thus, it is essential to emphasize development of appropriate motivations and not only to provide knowledge and skills. Furthermore, one should also remember motivations other than health motivations when searching for the determinants of health behaviors. Full article

Advancements in IoT technology contribute to the digital progress of health science. This paper proposes a cloud-centric IoT-based health management framework and develops a system prototype that integrates sensors and digital technology. The IoT-based health management tool can collect real-time health data and transmit it to the cloud, thus transforming the signals of various sensors into shared content that users can understand. This study explores whether individuals in need tend to use the proposed IoT-based technology for health management, which may lead to the new development of digital healthcare in the direction of sensors. The novelty of this research lies in extending the research perspective of sensors from the technical level to the user level and explores how individuals understand and adopt sensors based on innovatively applying the IoT to health management systems. By organically combining TAM with MOA theory, we propose a comprehensive model to explain why individuals develop perceptions of usefulness, ease of use, and risk regarding systems based on factors related to motivation, opportunity, and ability. Structural equation modeling was used to analyze the online survey data collected from respondents. The results showed that perceived usefulness and ease of use positively impacted adoption intention, Perceived ease of use positively affected perceived usefulness. Perceived risk had a negative impact on adoption intention. Readiness was only positively related to perceived usefulness, while external benefits were positively related to perceived ease of use and negatively related to perceived risk. Facilitative conditions were positively correlated with perceived ease of use and negatively correlated with perceived risk. Technical efficacy was positively related to perceived ease of use and perceived usefulness. Overall, the research model revealed the cognitive mechanism that affects the intention of individuals to use the system combining sensors and the IoT and guides the digital transformation of health science. Full article