Set Of Hypotheses Research Articles

Accurate and Efficient Stereo Matching via Attention Concatenation Volume.

Stereo matching is a fundamental building block for many vision and robotics applications. An informative and concise cost volume representation is vital for stereo matching of high accuracy and efficiency. In this article, we present a novel cost volume construction method, named attention concatenation volume (ACV), which generates attention weights from correlation clues to suppress redundant information and enhance matching-related information in the concatenation volume. The ACV can be seamlessly embedded into most stereo matching networks, the resulting networks can use a more lightweight aggregation network and meanwhile achieve higher accuracy. We further design a fast version of ACV to enable real-time performance, named Fast-ACV, which generates high likelihood disparity hypotheses and the corresponding attention weights from low-resolution correlation clues to significantly reduce computational and memory cost and meanwhile maintain a satisfactory accuracy. Furthermore, we design a highly accurate network ACVNet and a real-time network Fast-ACVNet based on our ACV and Fast-ACV respectively, which achieve state-of-the-art performance on several benchmarks.

How do you know that you don’t know?

Whenever someone in a team tries to help others, it is crucial that they have some understanding of other team members’ goals. In modern teams, this applies equally to human and artificial (“bot”) assistants. Understanding when one does not know something is crucial for stopping the execution of inappropriate behavior and, ideally, attempting to learn more appropriate actions. From a statistical point of view, this can be translated to assessing whether none of the hypotheses in a considered set is correct. Here we investigate a novel approach for making this assessment based on monitoring the maximum a posteriori probability (MAP) of a set of candidate hypotheses as new observations arrive. Simulation studies suggest that this is a promising approach, however, we also caution that there may be cases where this is more challenging. The problem we study and the solution we propose are general, with applications well beyond human–bot teaming, including for example the scientific process of theory development.

Who Deserves To Be Supported? Analysing Attitudes Towards Horizontal Redistribution in Nigeria

Despite the widespread recognition of the risk that group‐based inequalities, or so‐called horizontal inequalities (HIs), pose for the political stability and social cohesion of multi‐ethnic societies, extremely little research has been conducted on how people perceive these inequalities and how these perceptions, in turn, are associated with people’s attitudes towards group‐based or horizontal redistribution. In this article, we systematically analyse how people’s perceptions of prevailing socio‐economic HIs shape their attitudes towards horizontal redistribution in Nigeria, a country confronted with sharp and persistent inequalities between different ethnic groups. We develop a set of hypotheses for explaining differences in support for horizontal redistribution policies and test these hypotheses empirically with the help of a unique survey panel of about 2300 Nigerians.

The role of financial and non-financial incentives in influencing the improvement of the academic performance level of employees: An applied study in Baghdad’s private colleges

This research deals with the effect of job incentives in its two dimensions (financial and non-financial) as an independent variable on the dimensions of job performance (efficiency, effectiveness, productivity). Management is interested in improving the job performance of employees, in addition to knowing the extent to which management supports the motivation strategies followed. Sustainable development describes the dimensions of job performance mentioned above and the extent of their contribution to promoting and achieving the goals of the organization and testing the impact of the incentives variable on job performance. The research identified a set of hypotheses that were tested using the SPSS program, and a random sample of 50 professors and administrators working in the field of academic work in several private colleges was selected. The research reached a set of conclusions, the most important of which was that the total incentives had a weak role in the performance of the organization in question, except for the efficiency dimension, where it had a good role in influencing according to the variables included in the study model. The research also presented a set of recommendations and future proposals aimed at reducing the size of the studied problem.

Quantitative Research Design and Sample Trends: A Systematic Examination of Emerging Paradigms and Best Practices

Research design and sampling are pivotal in scientific research, shaping methodology and ensuring the credibility and validity of findings, necessitating clear and focused attention from researchers. Based on the above statement the study was focused on underlining the research design's basic terms and sample in order for researchers to be reliable in their research. The study used PRISMA to select the sample of documents. 30 major studies were used to explain the research objectives. The study covers only four types of research design i.e. Descriptive, Developmental, Experimental, and Casual Comparative. Results highlight the four research designs that aim to answer, words to be concerned with during objective setting, statistical tools, data visualization, words to be selected during hypothesis setting based on tools, and the minimum number of samples required depending on various tools. The research concludes that the choice of effective research design terms is pivotal. In statistical analysis, hypothesis wording directs research, with terminology so depending on the tools appropriate words need to be selected. Researchers need to make sure that the minimum sample size is right. However, larger samples improve the stability and accuracy of results. This study contributes by explaining essential research design terminology on sample selection, and their influence on statistical analysis, providing researchers with a clear guide to improve credibility and validity in their work.

Emotional Intelligence and Internal Marketing as Determinants of Job Satisfaction and Satisfaction with Life among Portuguese Professionals

The main purpose of this study is to analyze emotional intelligence and internal marketing as predictors of job satisfaction and satisfaction with life among working professionals in Portugal. At the same time, the relationships between internal marketing, job satisfaction, job determinants, organizational commitment, job performance and employee loyalty are explored. To this end, a conceptual model and a set of hypotheses were defined to respond to the postulated research objectives using structural equation modeling, applied to a random sample (n = 1310). The research results show that internal marketing has a statistically significant influence on job satisfaction. In turn, job satisfaction has a direct and positive influence on employee commitment and employee loyalty. Commitment and emotional intelligence have a direct, positive and significant influence on performance. Job satisfaction and emotional intelligence have a positive influence on satisfaction with life. This study presents itself as a novelty for science while making important contributions to organizations since it conceives a new conceptual model that enables organizations to perceive the relationships between the different determinants of job satisfaction and performance in order to promote their productivity, profitability and organizational competitiveness.

Thriving in private family firms as a non-family employee: an empirical study

PurposeWorkplace thriving (WT), self-job crafting (SJC), and workplace belongingness (WB) have been shown to lead to positive outcomes for organizations and their employees. However, there seems to be a dearth of insights into the relationship between the three constructs, and non-existent in the context of non-family employees (NFEs) working in private family firms. Therefore, this study examines whether enabling NFEs to craft their own jobs leads them to reappraise their position in the organization, thus influencing both WB and WT.Design/methodology/approachLeaning on the conservation of resources (COR) theory and with the support of the self-determination theory (SDT), a set of hypotheses is posited relating the dimensions of SJC (seeking resources, seeking challenges and job-demand reduction) to WT, through WB as a mediator. The hypotheses are tested through partial least squares structural equation modeling (PLS-SEM) by collecting survey data from 256 NFEs working in private family firms in Oman.FindingsThe results indicate that all three dimensions of job crafting have a positive influence on WB. In the case of direct effect on WT, only the relationship between seeking challenges and WT was significant. However, the relationships between all 3 dimensions of SJC and WT became significant through WB as mediator.Research limitations/implicationsThe implication of this study is that merely empowering non-family employees to craft their own jobs may not lead them to thrive in private family firms. However, if they appraise such empowerment as significant resource-gain that leads them to feel that they belong to the organization, then it is likely to enhance WT.Practical implicationsThis study presents evidence for private family firms that by emphasizing on creating a sense of belongingness among their non-family employees, they can create a workplace where such employees can thrive.Originality/valueThree novel contributions are presented through this research: (1) this appears to be the first study that integrates the COR theory with SDT to enrich the fragmented literature on NFEs in family firms by presenting an integrated framework that links SJC, WB and WT, (2) the study presents nuanced insights into the relationships between the dimensions of SJC and WT and (3) finally, this study provides evidence on the mediating role of WB between dimensions of SJC and WT, which seems to be overlooked in the past.

Maximum-Subsampling Test of Equal Predictive Ability

In comparing the accuracy of any two competing forecasts, under the assumption that the loss differentials are covariance stationary, Diebold and Mariano (DM) proposed a test statistic that is asymptotically normal. This test is further studied by Giacomini and White (GW). However, under the DM-GW framework, the estimator of the variance of the DM test can be inaccurate in small samples, which yields size distortions; see, for example, Coroneo and Iacone (CI). To alleviate this challenge, we propose a maximum-subsampling (MS) test that does not require estimating the long-run variance induced by a number of autocovariances. Accordingly, the MS test is applicable for comparing the predictive ability between two competing forecasts even when the loss differentials are serially correlated with arbitrary autocovariance structures. We demonstrate that the MS test converges to the type I extreme value distribution under the DM-GW null hypothesis with proper conditions. In addition, under a set of alternative hypotheses, we show the MS test is consistent. We further compare the MS test with the DM test and two CI tests via five simulation settings, which are either modified or adapted from McCracken and Coroneo and Iacone. Simulation results show that the MS test performs satisfactorily.

Tourism development: A capacity dynamic

<p>The internationally adopted definition of tourism prompts to develop a systemic dynamic approach of tourism development. The paper proposes to conceptualize tourism development as a system interlinking three agents: transport, domestic tourism activities and the visitor; generating three types of development tourism development dynamics. In a second step, it uses this framework to develop, with a minimalist set of hypotheses, a capacity-based model enabling to consider destination tourism development as a microfounded supply-driven systemic dynamic process. Through the lens of the model, exhaustion or asymmetric distribution of market power may halt destination tourism development. Using the model’s framework, the structuring forces of the Tourism Area Life Cycle (TALC) are explained by the dual impact of capacity dynamics: accelerating by increasing arrivals, and at the same time decelerating by declining price elasticities.<strong></strong></p>

The Political Economy of Life Satisfaction: Democracy, National Wealth, and Personal Income

Abstract Numerous studies examine the micro-dynamics of subjective well-being (SWB) generally, or life satisfaction (LS) more specifically. Others also document the macro determinants of SWB and LS. We propose a model linking the two, in which an individual’s life satisfaction is contingent on (1) personal circumstances, (2) national factors such as democratic governance and the national wealth, and (3) the explicit interaction of these two levels of analysis. We test three sets of hypotheses that arise from this model with compiled data from six waves of the World Values Survey (WVS) data. The empirical evidence we present supports most of the hypotheses, including our novel proposition that both national wealth and democracy reduce the effect of individual personal income on LS.

An approach to unified formulae for likelihood ratio calculation in pairwise kinship analysis.

Introduction: The likelihood ratio (LR) can be an efficient means of distinguishing various relationships in forensic fields. However, traditional list-based methods for derivation and presentation of LRs in distant or complex relationships hinder code editing and software programming. This paper proposes an approach for a unified formula for LRs, in which differences in participants' genotype combinations can be ignored for specific identification. This formula could reduce the difficulty of by-hand coding, as well as running time of large-sample-size simulation. Methods: The approach is first applied to a problem of kinship identification in which at least one of the participants is alleged to be inbred. This can be divided into two parts: i) the probability of different identical by descent (IBD) states according to the alleged kinship; and ii) the ratio of the probability that specific genotype combination can be detected assuming the alleged kinship exists between the two participants to the similar probability assuming that they are unrelated, for each state. For the probability, there are usually recognized results for common identification purposes. For the ratio, subscript letters representing IBD alleles of individual A's alleles are used to eliminate differences in genotype combinations between the two individuals and to obtain a unified formula for the ratio in each state. The unification is further simplified for identification cases in which it is alleged that both of the participants are outbred. Verification is performed to show that the results obtained with the unified and list-form formulae are equivalent. Results: A series of unified formulae are derived for different identification purposes, based on which an R package named KINSIMU has been developed and evaluated for use in large-size simulations for kinship analysis. Comparison between the package with two existing tools indicated that the unified approach presented here is more convenient and time-saving with respect to the coding process for computer applications compared with the list-based approach, despite appearing more complicated. Moreover, the method of derivation could be extended to other identification problems, such as those with different hypothesis sets or those involving multiple individuals. Conclusion: The unified approach of LR calculation can be beneficial in kinship identification field.

Compliance with national standards of decentralized public services: The case of preschool services in Albania

AbstractIn the last few decades, many Central and Eastern European Countries (CEEC) engaged in processes of decentralization in which responsibilities of the national government are transferred to local government units (LGUs). Yet, it is still unclear under what circumstances LGUs in recently decentralized CEEC can deliver high‐quality public services. We put forward the argument that political, administrative, and financial factors related to characteristics of the LGU, and their implementation structure can explain the quality of public services, understood here as the compliance with standards set at central government level. We deduce a set of hypotheses which we test with the example of the public service of preschool education in Albania using generalized linear mixed‐effects models. We find that albeit fiscal factors are important, the relation between money and high‐quality public services is more complex than previously assumed. We find that private donations can undermine central government standards, and that requirements not involving financial costs are more likely implemented. Further, political, and administrative factors, although previously often neglected, play an important role. We find that outsourcing certain functions leads to higher service quality, and that urban areas provide higher quality services indicating that political actors need to focus on rural areas.

Mitigating the unwillingness to exchange knowledge: a focus on exporters’ networks

Purpose This paper aims to explain the unwillingness to exchange export knowledge by members of exporters’ networks and provides potential solutions to this problem. Design/methodology/approach This study uses data from a survey of 301 members of a French exporter’s network to test a set of hypotheses with partial least squares structural equation modeling. Findings Network participants’ export experience and age have a negative influence on their willingness to exchange knowledge. However, positive attitudes toward the network (perception of network quality, commitment) can mitigate those negative links. Practical implications Network members’ unwillingness to exchange knowledge represents a major challenge that threatens the existence of knowledge networks. The findings suggest solutions to this issue for network managers. Originality/value This study views knowledge exchange in a network as a risky behavior. It explains why members do not participate in networks. The model shows how contrary forces work and interact to deter or foster knowledge exchange.

The Use of Digital Payment Methods and its Implications on Financial Inclusion: A Survey Study

In the digital era, the advent of electronic payment systems has revolutionized financial transactions, with significant implications for financial inclusion. This research paper delves into the dynamics of digital payment methods and their impact on financial inclusion in India, focusing on user demographics, adoption rates, perceptions, and barriers to usage.
 The study was underpinned by several research objectives aimed at understanding the nuances of digital payment adoption across different demographic segments, assessing the perception of security and privacy, evaluating the role of digital payments in reducing cash dependency, identifying the adoption barriers, and recommending inclusive strategies for broader access. A set of research questions and hypotheses were formulated in line with these objectives.
 A quantitative research approach was employed, involving a survey disseminated across multiple Indian states. The survey, comprising structured questionnaires, targeted a diverse population segment, accumulating a total of 500 responses. The data collected was rigorously analyzed using descriptive statistics, inferential tests (t-tests and ANOVA), and thematic analysis for open-ended responses.
 Key findings of the study indicated a higher propensity for digital payment adoption among younger individuals, with notable hesitancy among older demographics. Security and privacy concerns were prevalent, significantly influencing user behavior, particularly among females. The research also highlighted a substantial reduction in cash dependency among digital payment users, indicating an increase in financial autonomy. However, significant barriers, including digital literacy, infrastructure inadequacies, and language barriers, especially in rural areas, impede widespread adoption.
 These findings have profound implications for financial inclusion, emphasizing the need for a multifaceted approach to address the digital divide. The study underscores the necessity for stakeholder collaboration in enhancing digital infrastructure, literacy, and trust, thereby fostering an inclusive financial environment. The insights derived are of paramount importance for policymakers, financial institutions, and fintech companies aiming to innovate and expand the reach of digital financial services.

EEGManyPipelines: A Large-scale, Grassroots Multi-analyst Study of Electroencephalography Analysis Practices in the Wild.

The ongoing reproducibility crisis in psychology and cognitive neuroscience has sparked increasing calls to re-evaluate and reshape scientific culture and practices. Heeding those calls, we have recently launched the EEGManyPipelines project as a means to assess the robustness of EEG research in naturalistic conditions and experiment with an alternative model of conducting scientific research. One hundred sixty-eight analyst teams, encompassing 396 individual researchers from 37 countries, independently analyzed the same unpublished, representative EEG data set to test the same set of predefined hypotheses and then provided their analysis pipelines and reported outcomes. Here, we lay out how large-scale scientific projects can be set up in a grassroots, community-driven manner without a central organizing laboratory. We explain our recruitment strategy, our guidance for analysts, the eventual outputs of this project, and how it might have a lasting impact on the field.

The Impact of Education on Fertility During the Chinese Reform Era (1980–2018): Changes Across Birth Cohorts and Interaction with Fertility Policies

We examined the influence of education on fertility decisions in contemporary China, drawing upon theoretical insights that emphasise the role of social institutions, gender relations, and life course dynamics in shaping family behaviour. This led us to propose a set of hypotheses that explain the differential effect of education on each parity. We used information on female cohorts born between 1960 and 1989, coming from the China Family Panel Studies for 2010–2018. We applied event history models with both independent and simultaneous equations models to account for selection and endogeneity effects. The results point to a substantial contribution of the increased educational attainment in the population in the fertility decline and current low levels of fertility, beyond the role of fertility policies. Consistent with our hypotheses, the results show that woman’s educational attainment has a strong negative effect on the hazard of bearing a second or third child. Male partner’s educational attainment also has a negative effect on the hazard of transition to a second or third birth, yet with a weaker intensity. We also found that the negative effect of education on second birth rates significantly declines across birth cohorts. The results show little educational differentials in the probability of bearing a first child, while the better educated postpone first births. Moreover, the effect of fertility policies, measured at the individual level, gradually increases with the level of education.

Social media “stars” vs “the ordinary” me: influencer marketing and the role of self-discrepancies, perceived homophily, authenticity, self-acceptance and mindfulness

PurposeSocial media influencers have become constant companions of a large audience of young consumers, but a crucial yet underexplored area of examination relates to the implications of exposure to influencers for an individual’s self-concept. This study aims to examine if and how individuals experience self-discrepancies when exposed to influencers and the impact of such discrepancies on their affect, cognition and behaviors toward the influencers and the brands they endorse.Design/methodology/approachThe authors thematically analyze 17 semistructured interviews, develop a conceptual model and present a set of hypotheses. The hypotheses are tested by analyzing survey data from 503 respondents using structural equation modeling.FindingsIndividuals actively engage in comparisons with influencers’ virtual self-presentation and treat them as emblematic of an ideal self. The associated self-discrepancy can lead to both negative and positive affect, but while the latter has a positive impact on e-word of mouth (WOM) and purchase intent, the former has a negative impact. Perceived homophily dampens the impact of exposure to influencer content on discrepancy and strengthens the link between discrepancy and positive affect. Self-acceptance and mindfulness positively moderate the impact of discrepancy on positive affect and negatively on negative affect. Perceived authenticity strengthens the impact of positive affect on e-WOM and dampens the impact of negative affect on purchase intention.Research limitations/implicationsThe authors contribute to the literature on self-discrepancies by identifying a consumer context where, in addition to the theoretically predicted negative affect, an individual may experience more positive emotions like feeling motivated or inspired because of the perceived attainability of an influencer as an ideal self. The authors contribute to the influencer marketing literature by examining the influencer–follower relationship and its implications for an individual’s self-concept, including the role played by perceived homophily and authenticity. The authors also contribute to the literature on consumer well-being and identify the role of self-acceptance and mindfulness in shaping consumer experiences.Practical implicationsThe authors provide a nuanced analysis of the impact of influencer marketing on consumer behavior with a focus on its impact on an individual’s self-concept. The authors argue for the role of perceived homophily and authenticity in shaping favorable consumer behavior outcomes and offer evidence for more inclusive approaches to marketing.Originality/valueThe authors identify the influencer–follower relationship as a unique social exchange where the source of self-discrepancy is also a homophilic solution provider for achieving one’s ideal self and report both positive and negative effects as outcomes of experiencing a self-discrepancy induced by a target perceived as more attainable. The authors situate understandings of perceived homophily and authenticity along these relationships and identify self-acceptance and mindfulness as mechanisms used by individuals to deal with discrepancies.

Enhancing Collaborative Learning and E-Mentoring in a Smart Education System in Higher Education

The requirement to develop a smart education system is critical in the era of ubiquitous technology. In the smart education environment, intelligent pedagogies are constructed to take advantage of technological devices and foster learners’ competencies which undoubtedly assist learners in dealing with knowledge and handling issues in a dynamic society more effectively and productively. This research suggests two effective learning strategies: (1) collaborative learning, which helps learners improve their knowledge and skills by exchanging resources and experiences, and (2) e-mentoring, which connects learners to a wide range of professional communities. This research first proposes a model to show how these two learning methods help learners achieve their goals, along with a set of hypotheses that are explained in detail. Then, a smart education system is proposed which comprises the two learning strategies with the necessary features. Lastly, two questionnaires, one for facilitators and the other for learners, are used to evaluate the usefulness and the feasibility of the proposed model in a real-world educational environment. The great majority of respondents agreed with all the statements, demonstrating the efficiency of the research for educators and learners.

Sustainability drivers and national culture in buyer-supplier environmental practices: an institutional perspective

Purpose This study aims to explore how sustainability drivers interact with national culture to explain the adoption of buyer–supplier environmental sustainability practices. Design/methodology/approach Drawing on Institutional Theory, this study proposes three sets of hypotheses focused on the role of key cultural dimensions: uncertainty avoidance, power distance and institutional collectivism. It uses a sample of 284 manufacturing plants across three industries and 14 countries to test these hypotheses, using regression analysis. Findings Findings suggest that national culture matters in the adoption of buyer–supplier environmental practices; however, its effect is contingent upon the particular combination of cultural dimensions and drivers analyzed. Originality/value This study enhances the understanding of the drivers behind buyer–supplier environmental practices by offering a novel examination of their interaction with national culture. This helps explain the heterogeneity in environmental sustainability adoption across countries.

A model-based hypothesis framework to define and estimate the diel niche via the 'Diel.Niche' R package.

How animals use the diel period (24-h light-dark cycle) is of fundamental importance to understand their niche. While ecological and evolutionary literature abound with discussion of diel phenotypes (e.g. diurnal, nocturnal, crepuscular, cathemeral), they lack clear and explicit quantitative definitions. As such, inference can be confounded when evaluating hypotheses of animal diel niche switching or plasticity across studies because researchers may be operating under different definitions of diel phenotypes. We propose quantitative definitions of diel phenotypes using four alternative hypothesis sets (maximizing, traditional, general and selection) aimed at achieving different objectives. Each hypothesis set is composed of mutually exclusive hypotheses defined based on the activity probabilities in the three fundamental periods of light availability (twilight, daytime and night-time). We develop a Bayesian modelling framework that compares diel phenotype hypotheses using Bayes factors and estimates model parameters using a multinomial model with linear inequality constraints. Model comparison, parameter estimation and visualizing results can be done in the Diel.Niche R package. A simplified R Shiny web application is also available. We provide extensive simulation results to guide researchers on the power to discriminate among hypotheses for a range of sample sizes (10-1280). We also work through several examples of using data to make inferences on diel activity, and include online vignettes on how to use the Diel.Niche package. We demonstrate how our modelling framework complements other analyses, such as circular kernel density estimators and animal movement modelling. Our aim is to encourage standardization of the language of diel activity and bridge conceptual frameworks and hypotheses in diel research with data and models. Lastly, we hope more research focuses on the ecological and conservation importance of understanding how animals use diel time.