Empirical Test Of Theory Research Articles

Unraveling relationship dynamics in sports teams: A primer on the social relations model

Interpersonal behavior in sports teams are inherently intricate. The Social Relations Model (SRM) presents a compelling framework to conceptualize and dissect these complexities, enabling the empirical testing of theories concerning relationships within group settings. The SRM decomposes dyadic measurements obtained from a round-robin design into components at the individual (actor and partner) level, relationship level, and team level. Leveraging data on need satisfaction, as experienced by the coach, team captain and two other athletes in relation to each other across 96 sports teams, we showcase the application of the SRM. A step-by-step introduction to the implementation of the model in R is provided. We elucidate how the SRM facilitates the investigation of research questions that deepen our understanding of team dynamics. Our illustration reveals that while the team effect exhibits minimal explanatory power over variability, substantial variability in need satisfaction is accounted for by both individual factors (actor and partner) and relationship effects. Notably, considerable differences are observed between sports teams in the extent to which coaches elicited need satisfaction in their team members. On average, coaches elicit lower levels of need satisfaction compared to other team members. Reciprocal relationships are evident in the team captain-athlete dyad and the athlete-athlete dyad, but not in dyadic relationships with the coach. In sum, this tutorial illustrates how analyzing dyadic data from a round-robin design using the SRM can enhance our understanding of dyadic relationship data within sports teams.

Identifying the theoretical foundations of coaching as a form of ongoing professional development in early childhood education: a meta-narrative review

ABSTRACT Despite evidence of the effectiveness of coaching as a form of ongoing professional development for educators, including in early childhood education, the field lacks an understanding of what the key components of coaching are and how and why they ‘work’. An improved theoretical basis for coaching would assist in identifying these underlying mechanisms of change. However, the field has been largely undertheorised, and an awareness of which theories have been applied in the field is lacking. This study entailed a meta-narrative review of the literature to identify which theories have informed the study of ongoing professional development in education, with a focus on coaching for early childhood educators. We identified 11 foundational papers addressing ongoing professional development in education that proposed or applied theories, and 69 papers on coaching for early childhood educators with a theoretical focus published between 2002 and 2022. Among both groups of papers, there were 47 different main theories applied or proposed. The findings indicate that coaching and other forms of ongoing professional development in education remain undertheorised and theoretical consensus is lacking. The findings suggest that further empirical testing of theories is required before any path towards building a theoretical consensus will become clearer.

Mapping visual working memory models to a theoretical framework.

The body of research on visual working memory (VWM)-the system often described as a limited memory store of visual information in service of ongoing tasks-is growing rapidly. The discovery of numerous related phenomena, and the many subtly different definitions of working memory, signify a challenge to maintain a coherent theoretical framework to discuss concepts, compare models and design studies. A lack of robust theory development has been a noteworthy concern in the psychological sciences, thought to be a precursor to the reproducibility crisis (Oberauer & Lewandowsky, Psychonomic Bulletin & Review, 26, 1596-1618, 2019). I review the theoretical landscape of the VWM field by examining two prominent debates-whether VWM is object-based or feature-based, and whether discrete-slots or variable-precision best describe VWM limits. I share my concerns about the dualistic nature of these debates and the lack of clear model specification that prevents fully determined empirical tests. In hopes of promoting theory development, I provide a working theory map by using the broadly encompassing memory for latent representations model (Hedayati et al., Nature Human Behaviour, 6, 5, 2022) as a scaffold for relevant phenomena and current theories. I illustrate how opposing viewpoints can be brought into accordance, situating leading models of VWM to better identify their differences and improve their comparison. The hope is that the theory map will help VWM researchers get on the same page-clarifying hidden intuitions and aligning varying definitions-and become a useful device for meaningful discussions, development of models, and definitive empirical tests of theories.

The Usefulness of Corporate Income Tax Accounting: Evidence from Pension Returns

ABSTRACTWe explore whether income tax accounting (ITA) for pensions provides measurement benefits incremental to U.S. GAAP. We use publicly reported Form 5500 defined-benefit pension expense and funding measures, which are calculated using ITA rules, and contrast them with parallel GAAP amounts. We document that ITA measures are more strongly associated with market value, future cash contributions, the cost of equity capital, and credit ratings than comparable GAAP measures, particularly when ITA better maps to economic fundamentals and when GAAP offers greater managerial discretion. Using intraday returns and disclosure times obtained through a Freedom of Information Act request, we also find that markets quickly react to the release of ITA measures in Form 5500. Our study provides novel empirical tests of theory about the benefits of ITA using actual, not imputed, ITA measures and provides evidence that investors can and do use the unique information in a publicly disclosed tax form.JEL Classifications: H25; J32; M41; M48.

Reputation, trust, and norms as mechanisms forming academic reciprocity in data sharing: an empirical test of theory of collective action

PurposeThis research investigated how biological scientists' perceived academic reputation, community trust, and norms all influence their perceived academic reciprocity, which eventually leads to their data sharing intentions.Design/methodology/approachA research model was developed based on the theory of collective action, and the research model was empirically evaluated by using the Structural Equation Modeling method based on a total of 649 survey responses.FindingsThe results suggest that perceived academic reputation significantly increases perceived community trust, norm of data sharing, and academic reciprocity. Also, both perceived community trust and norm of data sharing significantly increases biological scientists' perceived academic reciprocity, which significantly affect their data sharing intentions. In addition, both perceived community trust and norm of data sharing significantly affect the relationship between perceived academic reciprocity and data sharing intention.Research limitations/implicationsThis research shows that the theory of collective action provides a new theoretical lens for understanding scientists' data sharing behaviors based on the mechanisms of reputation, trust, norm, and reciprocity within a research community.Practical implicationsThis research offers several practical implications for facilitating scientists' data sharing behaviors within a research community by increasing scientists' perceived academic reciprocity through the mechanisms of reputation, trust, and norm of data sharing.Originality/valueThe collective action perspective in data sharing has been newly proposed in this research; the research sheds light on how scientists' perceived academic reciprocity and data sharing intention can be encouraged by building trust, reputation, and norm in a research community.

Haploid and Sexual Selection Shape the Rate of Evolution of Genes across the Honey Bee (Apis mellifera L.) Genome.

Many species have separate haploid and diploid phases. Theory predicts that each phase should experience the effects of evolutionary forces (like selection) differently. In the haploid phase, all fitness-affecting alleles are exposed to selection, whereas in the diploid phase, those same alleles can be masked by homologous alleles. This predicts that selection acting on genes expressed in haploids should be more effective than diploid-biased genes. Unfortunately, in arrhenotokous species, this prediction can be confounded with the effects of sex-specific expression, as haploids are usually reproductive males. Theory posits that, when accounting for ploidal- and sex-specific expression, selection should be equally efficient on haploid- and diploid-biased genes relative to constitutive genes. Here, we used a multiomic approach in honey bees to quantify the evolutionary rates of haploid-biased genes and test the relative effects of sexual- and haploid-expression on molecular evolution. We found that 16% of the honey bee’s protein-coding genome is highly expressed in haploid tissue. When accounting for ploidy and sex, haploid- and diploid-biased genes evolve at a lower rate than expected, indicating that they experience strong negative selection. However, the rate of molecular evolution of haploid-biased genes was higher than diploid-based genes. Genes associated with sperm storage are a clear exception to this trend with evidence of strong positive selection. Our results provide an important empirical test of theory outlining how selection acts on genes expressed in arrhenotokous species. We propose the haploid life history stage affects genome-wide patterns of diversity and divergence because of both sexual and haploid selection.

Robust Mediation Analysis: The R Package robmed

Mediation analysis is one of the most widely used statistical techniques in the social, behavioral, and medical sciences. Mediation models allow to study how an independent variable affects a dependent variable indirectly through one or more intervening variables, which are called mediators. The analysis is often carried out via a series of linear regressions, in which case the indirect effects can be computed as products of coefficients from those regressions. Statistical significance of the indirect effects is typically assessed via a bootstrap test based on ordinary least-squares estimates. However, this test is sensitive to outliers or other deviations from normality assumptions, which poses a serious threat to empirical testing of theory about mediation mechanisms. The R package robmed implements a robust procedure for mediation analysis based on the fast-and-robust bootstrap methodology for robust regression estimators, which yields reliable results even when the data deviate from the usual normality assumptions. Various other procedures for mediation analysis are included in package robmed as well. Moreover, robmed introduces a new formula interface that allows to specify mediation models with a single formula, and provides various plots for diagnostics or visual representation of the results.

A mixed-methods study of multi-level factors influencing mammography overuse among an older ethnically diverse screening population: implications for de-implementation

BackgroundThere is growing concern that routine mammography screening is overused among older women. Successful and equitable de-implementation of mammography will require a multi-level understanding of the factors contributing to mammography overuse.MethodsThis explanatory, sequential, mixed-methods study collected survey data (n= 52, 73.1% Hispanic, 73.1% Spanish-speaking) from women ≥70 years of age at the time of screening mammography, followed by semi-structured interviews with a subset of older women completing the survey (n=19, 63.2% Hispanic, 63.2% Spanish-speaking) and providers (n=5, 4 primary care, 1 obstetrics and gynecology) to better understand multi-level factors influencing mammography overuse and inform potential de-implementation strategies. We conducted a descriptive analysis of survey data and content analysis of qualitative interview data. Survey and interview data were examined separately, compared, integrated, and organized according to Norton and Chambers Continuum of Factors Influencing De-Implementation Process.ResultsSurvey findings show that 87.2% of older women believe it is important to plan for an annual mammogram, 80.8% received a provider recommendation, and 78.9% received a reminder in the last 12 months to schedule a mammogram. Per interviews with older women, the majority were unaware of or did not perceive to have experienced overuse and intended to continue mammography screening. Findings from interviews with older women and providers suggest that there are multiple opportunities for older women to obtain a mammogram. Per provider interviews, almost all reported that reducing overuse was not viewed as a priority by the system or other providers. Providers also discussed that variation in mammography screening practices across providers, fear of malpractice, and monetary incentives may contribute to overscreening. Providers identified potential strategies to reduce overscreening including patient and provider education around harms of screening, leveraging the electronic health record to identify women who may receive less health benefit from screening, customizing system-generated reminder letters, and organizing workgroups to develop standard processes of care around mammography screening.ConclusionsMulti-level factors contributing to mammography overuse are dynamic, interconnected, and reinforced. To ensure equitable de-implementation, there is a need for more refined and empirical testing of theories, models, and frameworks for de-implementation with a strong patient-level component that considers the interplay between multilevel factors and the larger care delivery process.

A relational approach to consciousness: categories of level and contents of consciousness.

Characterizing consciousness in and of itself is notoriously difficult. Here, we propose an alternative approach to characterize, and eventually define, consciousness through exhaustive descriptions of consciousness’ relationships to all other consciousness. This approach is founded in category theory. Indeed, category theory can prove that two objects A and B in a category can be equivalent if and only if all the relationships that A holds with others in the category are the same as those of B; this proof is called the Yoneda lemma. To introduce the Yoneda lemma, we gradually introduce key concepts of category theory to consciousness researchers. Along the way, we propose several possible definitions of categories of consciousness, both in terms of level and contents, through the usage of simple examples. We propose to use the categorical structure of consciousness as a gold standard to formalize empirical research (e.g. color qualia structure at fovea and periphery) and, especially, the empirical testing of theories of consciousness.

A Robust Bootstrap Test for Mediation Analysis

Mediation analysis is central to theory building and testing in organizational sciences. Scholars often use linear regression analysis based on normal-theory maximum likelihood estimators to test mediation. However, these estimators are very sensitive to deviations from normality assumptions, such as outliers, heavy tails, or skewness of the observed distribution. This sensitivity seriously threatens the empirical testing of theory about mediation mechanisms. To overcome this threat, we develop a robust mediation method that yields reliable results even when the data deviate from normality assumptions. We demonstrate the mechanics of our proposed method in an illustrative case, while simulation studies show that our method is both superior in estimating the effect size and more reliable in assessing its significance than the existing methods. Furthermore, we provide freely available software in R and SPSS to enhance its accessibility and adoption by empirical researchers.

Brain states matter. A reply to the unfolding argument.

Recently, it has been claimed that Integrated Information Theory and other theories of its type cannot explain consciousness ("unfolding argument"). We unravel this argument mathematically and prove that the premises of the argument imply a much stronger result according to which the observed problem holds for almost all theories of consciousness. We find, however, that one of the premises is unwarranted and show that if this premise is dropped, the argument ceases to work. Thus our results show that the claim of the unfolding argument cannot be considered valid. The premise in question is that measures of brain activity cannot be used in an empirical test of theories of consciousness.

Unpacking within- and between-person effects of unstructured socializing and differential association on solo- and co-offending

Unstructured socializing and differential association are two key explanations of peer influence. Unstructured socializing serves as a situational context that promotes antisocial behavior, whereas differential association with delinquent peers leads to learned behavior. Building on these perspectives and prior research, the present study models persons as contexts and examines the impact of unstructured socializing and peer delinquency on solo- and co-offending. Specifically, we use generalized linear mixed models to separate within, between, and person-context effects on offending alone and with peers, and test for interaction effects. Key findings include significant within-individual and between-individual effects of unstructured socializing and peer delinquency on co-offending, significant person-context effects of peer delinquency on co-offending, and significant within, between, and person-context effects of peer delinquency on solo-offending. Among comparable significant relationships, peer delinquency effects were notably stronger than unstructured socializing effects. Finally, interaction models revealed that within-individual effects of unstructured socializing and peer delinquency were attenuated among those with high average peer delinquency over time. The findings hold important implications for future empirical tests of theories of peer influence and for policies and programs aimed at controlling peer influence processes on offending alone and with peers.

The Non-Normality of Firm Performance and the Consequences for Strategic Management Theory

Firm performance represents an integral outcome for most strategic management scholarship and corresponding theoretical frameworks (e.g., agency theory, RBV, competitive dynamics, and many more). Despite the inherent idea across strategy research that firm performance is heterogeneous, we have little knowledge about just how heterogeneous it is across samples of firms and how this might impact empirical tests of theories used by strategy scholars. We investigate performance heterogeneity by examining the distributions of firm performance measures (e.g., ROA, ROS, EPS, etc.). We find that extreme levels of both skewness and kurtosis vary substantively across different measures, samples, transformations, and years. We create simulations to mimic these distributions and find that such non-normality negatively impacts the efficiency of OLS, robust regression, and OLS with winsorized values. In contrast, we illustrate that quantile regression is more appropriate for modeling dependent variables following these types of extremely non-normal distributions and represents an attractive approach for researchers examining firm performance. The primary implication of our research is that the extreme non-normality of performance measures makes it difficult for researchers to find support for theoretical frameworks when using models that focus on average relationships (e.g., OLS, multilevel models, etc.). Instead, we suggest strategy theories could benefit from re-examining theorized relationships using the types of non-parametric techniques that are more appropriate for the non-normal distributions of firm performance.

Effect of Risk Management, Intellectual Capital on Performance of State Corporations in Kenya: Moderating Approach

Purpose: The main aim of the study was to determine the moderating effect of intellectual capital on the relationship between ERM risk structure practices and organizational performance of state corporations in Kenya. This study was guided by dynamic capabilities theory which attempts to explain the perspective of how intellectual capital and ERM practices affect organizational performance. Design/methodology/approach: The study used explanatory cross sectional survey design. Primary data on ERM risk structure practices, intellectual capital and organizational performance was collected from structured questionnaires. A survey was carried out on 218 state corporations in Kenya. The research hypothesis was tested using hierarchical regression analysis. Finding: The study found that intellectual capital had an enhancing and significant moderation effect on the relationship between ERM structure practice and organizational performance (β =.314, ρ< .05). Originality/value: This study contributes to theory by centering intellectual capital on the empirical testing of theory as well as the influence of intellectual assets on the relationship between enterprise risk management practices and organizational performance. In addition, the study supports the theory of Enterprise Risk Management (ERM) that emphasizes on holistic and company-wide approach of managing risks. The study further suggests that future research could build on this study by examining enterprise risk management practices in different sectors and industries using both financial and non-financial measures of performance.

A Robust Bootstrap Test for Mediation Analysis

textabstractMediation analysis is central to theory building and testing in organizations research. Management scholars often use linear regression analysis based on normal-theory maximum likelihood estimators to test mediation. However, these estimators are very sensitive to deviations from normality assumptions, such as outliers or heavy tails of the observed distribution. This sensitivity seriously threatens the empirical testing of theory about mediation mechanisms, as many empirical studies lack reporting of outlier treatments and checks on model assumptions. To overcome this threat, we develop a fast and robust mediation method that yields reliable results even when the data deviate from normality assumptions. Simulation studies show that our method is both superior in estimating the effect size and more reliable in assessing its significance than the existing methods. We illustrate the mechanics of our proposed method in three empirical cases and provide freely available software in R and SPSS to enhance its accessibility and adoption by researchers and practitioners.

A dynamic and multifunctional account of middle-range theories.

This article develops a novel account of middle-range theories for combining theoretical and empirical analysis in explanatory sociology. I first revisit Robert K. Merton's original ideas on middle-range theories and identify a tension between his developmental approach to middle-range theorizing that recognizes multiple functions of theories in sociological research and his static definition of the concept of middle-range theory that focuses only on empirical testing of theories. Drawing on Merton's ideas on theorizing and recent discussions on mechanism-based explanations, I argue that this tension can be resolved by decomposing a middle-range theory into three interrelated and evolving components that perform different functions in sociological research: (i) a conceptual framework about social phenomena that is a set of interrelated concepts that evolve in close connection with empirical analysis; (ii) a mechanism schema that is an abstract and incomplete description of a social mechanism; and (iii) a cluster of all mechanism-based explanations of social phenomena that are based on the particular mechanism schema. I show how these components develop over time and how they serve different functions in sociological theorizing and research. Finally, I illustrate these ideas by discussing Merton's theory of the Matthew effect in science and its more recent applications in sociology.

Predicting intention to use alternative dispute resolution (ADR): an empirical test of theory of planned behaviour (TPB) model

Alternative dispute resolution (ADR) has gained prevalent interests among practitioners and researchers. To better explain the factors underpinning the use of ADR, Theory of planned behaviour (TPB) model was applied to predict behavioural intention to use ADR. In general, the TPB model posits that attitude, subjective norm and perceived behavioural control explain actual behaviour. Therefore, this study investigates the role of attitude, subjective norm and perceived behavioural control towards the prediction of intention in ADR use. Data were collected from 128 ADR decision makers from Malaysian contractor firms. Both measurement and structural assessment of the model were performed by using Partial Least Squares (PLS) modelling. The results showed that TPB model provides excellent predictive accuracy and relevance for intention. The model was again examined in two distinctive scenarios. Attitude was found to be the sole predictor of intention in the occurrence of dispute; and before negotiation fails. The findings indicate a plausible future empirical investigation in the attitudinal dimension.

Relationship of employee ethnic background in Validation of Situational leadership Theory

Situational leadership theory although many use it, but empirical theory testing is related to ethnic background factorjust a few. The purpose of this research will be to test the assumption leader’s effectiveness in bureaucracy organization, by including external factor that is ethnic background of leader and subordinate, by reason of heterogeneous cultural origin to employees in bureaucracy organization in Papua. Quantitative research method with hypothesis statistical test by using statistical test of Sommer’sdyx and Lambda with experimental treatment approach to leader and subordinate as respondent at the time of filling questioner. The results of this study (1) theory is validated, but lacks the support of theoretical assumptions; (2) managed to find a significant difference between the weak ethnic origin and the level of maturity of subordinates; (3) find other influencing factors (subordinate motivation, and ego state behavior patterns). The main suggestion of this research is to deal with the methodology and avoid the psychological sensitive factors.

Reputation, trust, and norms as mechanisms leading to academic reciprocity in data sharing: An empirical test of theory of collective action

ABSTRACTThis research investigated how scientists' academic reputation, community trust, and norms regarding data sharing all influence their academic reciprocity in data sharing, which eventually leads to the scientists' data sharing intentions. This research employed Ostrom's (2003) theory of collective action to better understand scientists' data sharing behaviors from the perspective of cooperation in a community. This research empirically evaluated the research model and related hypotheses by using the Structural Equation Modeling (SEM) method on a total of 456 survey responses from biologists in the U.S. The results suggest that biologists' perceived academic reputation significantly increases their perceived community trust, norm of data sharing, and academic reciprocity. Along with perceived academic reputation, both perceived community trust and norms of data sharing also significantly increases biologists' academic reciprocity in data sharing. This research also found that biologists' academic reciprocity and norms of data sharing significantly affect their data sharing intentions. The results of this research show that the theory of collective action provides new insight to scientists' data sharing behaviors. These results suggest how we can facilitate scientists' data sharing behaviors within a research community by increasing academic reciprocity through the mechanisms of reputation, trust, and norm.

A Robust Bootstrap Test for Mediation Analysis

Mediation analysis is central to theory building and testing in organizations research. Management scholars often use linear regression analysis based on normal-theory maximum likelihood estimators to test mediation. However, these estimators are very sensitive to deviations from normality assumptions, such as outliers or heavy tails of the observed distribution. This sensitivity seriously threatens the empirical testing of theory about mediation mechanisms, as many empirical studies lack reporting of outlier treatments and checks on model assumptions. To overcome this threat, we develop a fast and robust mediation method that yields reliable results even when the data deviate from normality assumptions. Simulation studies show that our method is both superior in estimating the effect size and more reliable in assessing its significance than the existing methods. We illustrate the mechanics of our proposed method in three empirical cases and provide freely available software in R and SPSS to enhance its accessibility and adoption by researchers and practitioners.