Types Of Misfit Research Articles

A pedagogy of anachronism: learning through a misfit between theory and practice

This paper presents a pedagogy of anachronism where learning occurs through a misfit between theory and practice. It was developed and tested in a class taught from 2016 to 2019, where students repeated Kevin Lynch’s original 1960 experiment on cognitive mapping in a location much smaller in scale and with a very different social composition from the cities that Lynch analyzed. The deliberate misfit transformed a method designed to understand user perception into the very problem itself, provoking students to ask important epistemological questions and recognize the situatedness of theory. A pedagogy of anachronism resists the uncritical instrumentalization of canonical ideas and trains students to think deeply about the normative and epistemological basis of design/planning practice. The paper ends by suggesting different types of misfits that can extend this pedagogy for other learning objectives.

Enterprise Resource Planning Modification: A Literature Review

The current low success level of Enterprise Resource Planning (ERP) implementation stimulates the rise of research to find the critical success factor of it. One of the challenges of ERP implementation is to find a ‘fit’ between business and system requirements. It is claimed that standardizing business processes to follow the ERP system will positively impact organizations to follow the best practice process. However, there is another challenge that organization should not reengineer their business process to fit the ERP system, but rather modify or customize the ERP system to match their business process. This belief argues that standardizing business processes is not the right solution that applies to every organization since it can degrade an organization’s competitive advantages. Based on the background, the research aimed to construct a comprehensive review to succeed in implementing an ERP system, particularly on ERP modification, using a systematic literature review method. It was done by collecting and analyzing scientific publications related to ERP critical success factors with special attention to system modification. The literature review results in a comprehensive explanation of ERP modification. It includes elaborating on different types of misfit and customization to cultivate the understanding of ERP modification, a flowchart to analyze misfit to help the organization to evaluate modification requests, and critical success factors of modified ERP implementation.

The impact of supply chain fit on business and innovation performance in Brazilian companies

PurposeThis paper investigates the effect of the fit between supply and demand uncertainty (SDU) and supply chain responsiveness (SCR) (SC fit) on business and innovation performance in Brazilian companies.Design/methodology/approachThe study presented an analysis carried out on an empirical study based on a sample of 150 manufacturing companies. Business and innovation performance of companies with different types of SC fit ( high–high and low–low fits) and misfit (positive and negative) are compared and discussed.FindingsThe results indicated that SC fit had a positive effect on both business and innovation performance. Further analyses suggested that companies with SC fit present similar business performance, independent of the level of SDU that characterizes the environment where they compete, while companies in environments with higher levels of uncertainty tend to present superior innovation performance. Companies with positive and negative misfit present similar performance.Originality/valueAn analysis of the literature showed that there is no consensus when it comes to the definitions and measurements of SC fit. The paper investigates the effects of SC fit on business and innovation performance, while previous empirical studies have mainly addressed its impact on financial performance. Moreover, this study compares the effects of two types of fit and two types of misfit and assesses SC fit in Brazilian manufacturing companies, analyzing the context of an under-researched reality.

Advancing and Evaluating IRT Model Data Fit Indices in Organizational Research

Item response theory (IRT) models have a number of advantages for developing and evaluating scales in organizational research. However, these advantages can be obtained only when the IRT model used to estimate the parameters fits the data well. Therefore, examining IRT model fit is important before drawing conclusions from the data. To test model fit, a wide range of indices are available in the IRT literature and have demonstrated utility in past research. Nevertheless, the performance of many of these indices for detecting misfit has not been directly compared in simulations. The current study evaluates a number of these indices to determine their utility for detecting various types of misfit in both dominance and ideal point IRT models. Results indicate that some indices are more effective than others but that none of the indices accurately detected misfit due to multidimensionality in the data. The implications of these results for future organizational research are discussed.

Prior Sensitivity of the Posterior Predictive Checks Method for Item Response Theory Models

ABSTRACTBayesian item response theory (IRT) modeling stages include (a) specifying the IRT likelihood model, (b) specifying the parameter prior distributions, (c) obtaining the posterior distribution, and (d) making appropriate inferences. The latter stage, and the focus of this research, includes model criticism. Choice of priors with the posterior predictive checks (PPC) model-checking method requires more attention. The objective of this research is to investigate the extent of the effect of prior specification on the conclusions drawn from the PPC method. Findings indicated that the choice of discrepancy measure is an important factor in the overall success of the method, and that different discrepancy measures are affected more than others by prior specification. The use of percent correct as a discrepancy statistic was ineffective regardless of prior specification or type of misfit. Recommendations and suggestions for future research are provided.

Perceived underqualification and job attitudes: the role of transformational leadership

PurposeThe purpose of this paper is to delve into perceived underqualification, which refers to employees’ awareness that they have deficient abilities relative to their job demands (abilities<demands). In examining person–job (P–J) misfit, previous research has primarily focused on one type of misfit, overqualification (abilities>demands), leaving the other type, underqualification, unexplored. To address the neglect, this study investigates how perceived underqualification relates to job attitudes (job satisfaction, organizational commitment, and turnover intention) and how transformational leadership moderates the relationships.Design/methodology/approachSurvey data were collected from employees working at diverse organizations in South Korea over two waves; at Time 1, perceived underqualification and transformational leadership were measured and at Time 2, job attitude variables were measured. Responses from 188 employees were used for hypothesis testing.FindingsPerceived underqualification is negatively related to job satisfaction and organizational commitment and positively related to turnover intention when transformational leadership is low. However, under high transformational leadership, such negative attitudinal implications of perceived underqualification are weakened.Originality/valueBy examining underqualification for the first time, this study corrects the current incomplete and biased understanding of P–J misfit, which is exclusively overqualification-focused. In addition, this study provides new insight into individual responses to P–J misfit by revealing that the responses are not always negative. This study specifies transformational leadership as the contingency factor that enables such responses, thus further advancing the P–J misfit literature that has hardly examined the leadership effect.

Posterior calibration of posterior predictive p values.

In order to accurately control the Type I error rate (typically .05), a p value should be uniformly distributed under the null model. The posterior predictive p value (ppp), which is commonly used in Bayesian data analysis, generally does not satisfy this property. For example there have been reports where the sampling distribution of the ppp under the null model was highly concentrated around .50. In this case, a ppp of .20 would indicate model misfit, but when comparing it with a significance level of .05, which is standard statistical practice, the null model would not be rejected. Therefore, the ppp has very little power to detect model misfit. A solution has been proposed in the literature, which involves calibrating the ppp using the prior distribution of the parameters under the null model. A disadvantage of this "prior-cppp" is that it is very sensitive to the prior of the model parameters. In this article, an alternative solution is proposed where the ppp is calibrated using the posterior under the null model. This "posterior-cppp" (a) can be used when prior information is absent, (b) allows one to test any type of misfit by choosing an appropriate discrepancy measure, and (c) has a uniform distribution under the null model. The methodology is applied in various testing problems: testing independence of dichotomous variables, checking misfit of linear regression models in the presence of outliers, and assessing misfit in latent class analysis. (PsycINFO Database Record

Fits and misfits of supply chain flexibility to environmental uncertainty

PurposeThe purpose of this paper is to compare the effects on performance of two types of misfits (overfit vs underfit) as well as two types of fits (high-high fit vs low-low fit) between environmental uncertainty and supply chain flexibility.Design/methodology/approachThe two asymmetry hypotheses have been tested with survey data from 212 Chinese manufacturing firms.FindingsThe results in general provided empirical evidences for the asymmetric effects in the fits and misfits between environmental uncertainty and supply chain flexibility. For the same degree of misfit, underfit deteriorates performance more than overfit. In addition, high supply chain flexibility fitting high environmental uncertainty (i.e. high-high fit) results in a higher performance than low supply chain flexibility fitting low environmental uncertainty (i.e. low-low fit).Practical implicationsIt suggests that managers should strive to avoid the underfit of supply chain flexibility rather than the overfit, if the perfect fit is impossible to achieve. In addition, as it is beneficial to realize the fit of supply chain flexibility to high levels of environmental uncertainty, managers should probably embrace the highly uncertain environment and enhance the supply chain flexibility of their organizations to meet the increasing uncertainty of environment.Originality/valueFit and misfit are the core concepts to understand the relationships among environmental uncertainty, supply chain flexibility strategy, and performance. While the existing literature highlights the differential performance consequences of fit vs misfit between environmental uncertainty and supply chain flexibility strategy, the effects on performance are assumed to be the same for the two types of misfits, and two types of fits. The authors challenge these symmetry assumptions by arguing that overfit has a less negative effect on performance than underfit, and high-high fit has a stronger positive effect than low-low fit. The authors found empirical evidence in a large sample of Chinese manufacturing firms.

Nanotubes from Chalcogenide Misfit Compounds: Sn–S and Nb–Pb–S

Carbon fullerenes and nanotubes revolutionized understandingof the reactivity of nanoscale compounds. Subsequently, our group and others discovered analogous inorganic compounds with hollow, closed nanostructures. Such inorganic nanostructures offer many applications, particularly in the energy and electronics industries. One way to create inorganic nanostructures is via misfit layer-ed compounds (MLC), which are stacks of alternating two-dimensional molecular slabs, typically held together via weak van der Waals forces. They contain "misfits" in their a-b plane structures that can make them unstable, leading to collapse of the slabs into tubular nanostructures. For example, metal chalcogenide MLCs of the general formula (MX)1+y/TX2 (M = Sn, Pb, Bi, Sb, and other rare earths; T = Sn, Ti, V, Cr, Nb, Ta, etc.; X = S or Se) consist of a superstructure of alternating layers where the MX unit belongs to a (distorted NaCl) orthorhombic symmetry group (O), the TX2 layer possesses trigonal (T) or octahedral symmetry, and the two layers are held together via both van der Waals and polar forces. A misfit in the a axis or both a and b axes of the two sublattices may lead to the formation of nanostructures as the lattices relax via scrolling. Previous research has also shown that the abundance of atoms with dangling bonds in the rims makes nanoparticles of compounds with layered structure unstable in the planar form, and they tend to fold into hollow closed structures such as nanotubes. This Account shows that combining these two triggers, misfits and dangling bond annihilation in the slab rims, leads to new kinds of nanotubes from MLCs. In particular, we report the structure of two new types of nanotubes from misfits, namely, the SnS/SnS2 and PbS/NbS2 series. To decipher the complex structures of these nanotubes, we use a range of methods: high-resolution transmission electron microscopy (HRTEM), energy-dispersive X-ray spectroscopy (EDS), selected area electron diffraction (SAED) analyses, scanning electron microscopy (SEM), and Cs-corrected scanning transmission electron microscopy (STEM) in the high-angle annular dark-field mode (HAADF). In both new types, the lattice mismatch between the two alternating sublayers dictates the relative layer-stacking order and leads to a variety of chiral tubular structures. In particular, the incommensuration (a type of misfit) of the SnS2/SnS system in both the (in plane) a and b directions leads to a variety of relative in-plane orientation and stacking orders along the common c-axis. Thus the SnS/SnS2 nanotubes form superstructures with the sequence O-T and O-T-T, and mixtures thereof. We also report nanotubes of the misfit layered compound (PbS)1.14NbS2, and of NbS2 intercalated with Pb atoms, with the chemical formula PbNbS2. Thus, the possibility to use two kinds of folding mechanisms jointly offers a new apparatus for the synthesis of unique 1-D nanostructures of great complexity and a potentially large diversity of physicochemical properties.

Asymmetrical Effects in Both Fits and Misfits between Environment and Strategy

Fit and misfit are the core concepts to understand the relationships among environment, strategy, and performance. While the existing literature highlights the differential performance consequences of fit versus misfit between environment and strategy, they usually assume symmetrical effects on the performance of both overfit and underfit (two types of misfits), and low-low fit and high-high fit (two types of fits). We challenge these symmetry assumptions by arguing that, overfit has a less negative effect than underfit, and high-high fit has a stronger positive effect than low-low fit. The hypotheses were tested using data from 212 Chinese manufacturing firms. The results revealed that for the fits and misfits between environmental uncertainty and service-dominant logistics flexibility strategy, the less harmfulness of overfit than underfit and the more benefit of high-high fit than low-low fit hypotheses are both supported. In addition, for the fits and misfits between environmental uncertainty and prod...

Misfit of rigid tools and interferometer subapertures on off-axis aspheric mirror segments

Rigid tools can confer advantages at certain stages of manufacturing off-axis mirror segments, but the misfit due to surface asphericity and asymmetry poses constraints on their application. Types of misfit are classified and, using least squares, the best-fit tool forms with different distances from the pole of the parent asphere are calculated. The outer mirror segment for the European extremely large telescope is taken as a case-study, assuming a rigid tool size of 150 mm. A simple independent approximation validates the calculation. A close parallel is wavefront misfit in subaperture interferometry, which is also considered.

A short exploration of structural noise

“Structural noise” is a term often used to describe model‐to‐measurement misfit that cannot be ascribed to measurement noise and therefore must be ascribed to the imperfect nature of a numerical model as a simulator of reality. As such, it is often the dominant contributor to model‐to‐measurement misfit. As the name “structural noise” implies, this type of misfit is often treated as an additive term to measurement noise when assessing model parameter and predictive uncertainty. This paper inquires into the nature of defect‐induced model‐to‐measurement misfit and provides a conceptual basis for accommodating it. It is shown that inasmuch as defect‐induced model‐to‐measurement misfit can be characterized as “noise,” this noise is likely to show a high degree of spatial and temporal correlation; furthermore, its covariance matrix may approach singularity. However, the deleterious impact of structural noise on the model calibration process may be mitigated in a variety of ways. These include adoption of a highly parameterized approach to model construction and calibration (including the strategic use of compensatory parameters where appropriate), processing of observations and their model‐generated counterparts in ways that are able to filter out structural noise prior to fitting one to the other, and/or through implementation of a weighting strategy that gives prominence to observations that most resemble predictions required of a model.

Understanding Organization—Enterprise System Fit: A Path to Theorizing the Information Technology Artifact

Packaged software applications such as enterprise systems are designed to support generic rather than specific requirements, and hence are likely to be an imperfect fit in any particular instance. Using critical realism as our philosophical perspective, we conducted a three-year qualitative study of misfits that arose from an enterprise system (ES) implementation. A detailed analysis of the observed misfits resulted in a richer understanding of the concept of fit and of the ES artifact itself. Specifically, we found six misfit domains (functionality, data, usability, role, control and organizational culture) and within each, two types of misfit (deficiencies and impositions). These misfit types correspond to two newly defined types of fit: fit as coverage and fit as enablement. Our analysis of fit also revealed a new conceptualization of the ES artifact, with implications for IT artifacts in general.

Investigation of a Nonparametric Procedure for Assessing Goodness-of-Fit in Item Response Theory

Tests of model misfit are often performed to validate the use of a particular model in item response theory. Douglas and Cohen (2001) introduced a general nonparametric approach for detecting misfit under the two-parameter logistic model. However, the statistical properties of their approach, and empirical comparisons to other methods, have not been examined. In the present study, a Monte Carlo simulation study was used to examine the empirical Type I error rates and power of two nonparametric statistics based on the Douglas and Cohen (2001) approach. The procedures are compared to two commonly used goodness-of-fit statistics, S-X 2 (Orlando & Thissen, 2000) and BILOG's G 2 (Mislevy & Bock, 1990), across conditions varied by test length, sample size, and the percentage of misfitting items. Overall, the nonparametrically based statistics controlled the Type I error rate and exhibited the most power across all conditions. Due to its close association with a graphical representation of the item response function, it is argued that the Douglas and Cohen (2001) approach may also allow for a more informative inspection of the type of misfit that is present in test items, although at a slightly greater computational cost.

Testing Hypotheses About the Person-Response Function in Person-Fit Analysis

The person-response function (PRF) relates the probability of an individual's correct answer to the difficulty of items measuring the same latent trait. Local deviations of the observed PRF from the expected PRF indicate person misfit. We discuss two new approaches to investigate person fit. The first approach uses kernel smoothing to estimate continuous PRF estimates. Graphical displays of PRFs were used to localize and diagnose misfit. The second approach approximates the PRF by a logistic regression model. Hypothesis tests on the regression parameters were used to detect certain types of misfit. A simulation study was conducted to investigate the Type I error rates and the detection rates of the regression approach.

Diagnosing item score patterns on a test using item response theory-based person-fit statistics.

Person-fit statistics have been proposed to investigate the fit of an item score pattern to an item response theory (IRT) model. The author investigated how these statistics can be used to detect different types of misfit. Intelligence test data were analyzed using person-fit statistics in the context of the G. Rasch (1960) model and R. J. Mokken's (1971, 1997) IRT models. The effect of the choice of an IRT model to detect misfitting item score patterns and the usefulness of person-fit statisticsfor diagnosis of misfit are discussed. Results showed that different types of person-fit statistics can be used to detect different kinds of person misfit. Parametric person-fit statistics had more power than nonparametric person-fit statistics.

Experimental and computational approach for the evaluation of the biomechanical effects of dental bridge misfit

Dental bridges supported by osseointegrated implants are commonly used to treat the partially or completely edentulous jaw. The bridges are manufactured in metal alloy using a sequence of technological steps which well match the requirement to get custom overstructures but does not guarantee geometrical and dimensional tolerances. Dentists often experience that a perfect fit of the bridge with the abutments is almost impossible to achieve.When a misfitting bridge is forced on the abutments, deformations may occur inducing a permanent preload at the fixture–bone interface and the greater the misfit the greater is the preload and the risk of implant failure. This work gives an evaluation of the biomechanical effects induced by a misfitting bridge when forced on two supporting dental implants. The strains induced in the bridge have been measured using two purposely designed and fabricated experimental devices allowing different types of misfit. FEM 3D models of the bridge and of the bridge anchored to the bone by implants have been developed. The former has been validated by simulating the same loading conditions as in the experimental tests and comparing the bridge strains. Both models have been used for the evaluation of the stress induced in the bridge and at the fixture–bone interface by bridge length errors. The results show that the method may help to estimate the stress distribution in the bridge and bone as a consequence of different dental bridge misfits.

Grain-boundary structures in polycrystalline metals at the nanoscale

We present a detailed analysis of grain-boundary structures in computer-generated Cu and Ni three-dimensional nanocrystalline samples. The study includes both totally random and textured microstructures with grain sizes in the range of 5\char21{}12 nm. A detailed direct visualization technique is used at the atomic scale for studying the grain-boundary structural features. The study focuses on determining the presence of regions in the boundary exhibiting order and structural units normally expected for high-angle boundaries. For low-angle boundaries we investigate the presence of dislocation networks accommodating the misfit between the grains. A significant degree of crystalline order is found for all the boundaries studied. The highest degree of structural order was identified for boundaries with misfits within about 10\ifmmode^\circ\else\textdegree\fi{} deviation from the perfect twin. These grain boundaries contain a repeated building structure consisting of structural units typical of a $\ensuremath{\Sigma}=3$ symmetrical tilt twin boundary and highly disordered steps between those structural units. For all other types of misfit, we also observe some degree of structural coherence, and misfit accommodation occurs in a regular pattern. The cases studied include grain boundaries with a high-index common axis and show structural coherency that is independent of the grain size. Similar results are obtained for textured samples containing only low-angle grain boundaries, where regular dislocation arrays that are typical of larger grain materials are observed. These results provide evidence against the view of grain boundaries in nanocrystals as highly disordered, amorphous, or liquidlike interfaces. The results suggest that the grain-boundary structure in nanocrystalline materials is actually similar to that found in larger grain polycrystals.

Trait Level Estimation for Nonfitting Response Vectors

Item responses that do not fit an item response theory model may cause the latent trait value, 0, to be inaccurately estimated. Although in many studies the proportion of nonmodel-fitting response vectors (NRvs) identified (i.e., the detection rate) has been investigated, less is known about the severity of the inaccuracy of the estimated 0 (0) in relation to the rate at which response patterns are classified as not fitting a model using person-fit statistics. In the present study, three scoring methods-maximum likelihood estimation (MLE), expected a posterior (EAP) estimation, and biweight estimation (BIw)-were used to estimate 0 when NRVS were present. The detection rate of the lz person-fit statistic (Drasgow, Levine, &amp; Williams, 1985) was also investigated. It was found that NRVS influenced the value of 8, and this depended heavily on the type of misfit and the 8 level. It was also found that the BIW scoring method reduced the bias in 0 and improved the detection rate compared to MLE and EAP for examinees located at the extreme ends of the 8 continuum. Results of this study extended the results obtained by Reise (1995) and showed that the low detection rates found in his study were due to the particular kind of procedure used to generate NRVS.

The Power of Rasch Person-Fit Statistics in Detecting Unusual Response Patterns

Five Rasch person-fit indexes were compared on their ability to detect spuriously high and low nonsystematic response patterns. The moderating effects of test dimensionality, type of misfit, and test length were also investigated. Results indicated that (1) all fit indexes were not significantly correlated with Rasch trait estimates; (2) their sampling distributions deviated significantly from the standard normal distribution; (3) using adjusted cutoff criteria to identify misfit, ECI2z, ECI4z, Iz, and WSR-C performed equally well in the detection of misfit regardless of test dimensionality, type of misfit, and test length (however, only lz is recommended for the spuriously high response patterns for a two-dimensional test); (4) the false positive rate for each index was less than the nominal .05 level; (5) Rasch person-fit indexes are more sensitive to spuriously high response patterns than to spuriously low response patterns on a two-dimensional test, but when the test is unidimensional they demonstrate equal sensitivity to both types of misfit; and (6) the detectability of misfit increases with test length.