Application Of Factor Analysis Research Articles

The informativeness of impression management − financial analysts and rhetorical style of CEO letters

Purpose This paper aims to investigate the informativeness of rhetorical impression management patterns of CEO letters and examines whether these rhetorical features affect financial analysts’ forecasting behaviour. Design/methodology/approach The authors use textual analysis on a sample of 526 CEO letters of US firms and apply factor analysis on individual linguistic style measures to identify co-occurrence patterns of style features. Findings The authors identify three holistic style patterns (assertive acclaiming, cautious plausibility-based framing and logic-based rationalizing) and find that assertive rhetorical feature in CEO letters is negatively related with the dispersion of financial analysts’ earnings forecasts and positively associated with earnings forecast accuracy. CEOs’ use of a rationalizing rhetorical pattern tends to decrease the dispersion of financial analysts’ earnings, whereas a cautious plausibility-based rhetorical position is only marginally instrumental in getting more accurate earnings predictions. Practical implications Whilst impression management communication is often theorized as manipulative and void of real information content, the findings suggest that impression management serves both self-presentation and information-sharing purposes. Originality/value This paper elaborates on the co-occurrence of style characteristics in management communication and is a first attempt to validate the external ramifications of holistic style profiles of corporate narratives by focusing on an economic target audience.

Açıklık Üzerindeki Engeller: Teknoloji Geliştirme Bölgesi Firmaları Örneği

Open Innovation promises higher outcomes from innovation processes through collaboration and sharing knowledge and the intellectual assets. Inclusion of suppliers, customers or users, partners, and even competitors in innovative processes can help to overcome constraints on internal resources. For ICT companies that operate in eco-systems of technology development zones (TDZ), open innovation approach becomes more critical mostly due to the scale and experience constraints. To understand the barriers of open innovation for ICT firms in TDZs can significantly help strategy and decision makers in designing policies and actions to empower innovation processes in order to overcome these barriers and hence to utilize open innovation for higher competitiveness. Various researchers examined the challenges of open innovation in various contexts, as well as the innovativeness and business performances of TDZ companies. However, there is still a room for research on exploring the dimensions of motives and barriers of open innovation practices of these companies. This study aims to explore the barriers for open innovation in ICT TDZ companies through surveys and in-depth interviews that are carried out in 102 ICT firms in TDZs in Turkey. By applying factor analysis, the main barriers to openness are identified and relationships of these barriers with the company’s characteristics explored. Findings reveal that the most frequently perceived constraints are financial and administrative problems.

Supplier Risk Assessment Based on Best-Worst Method and K-Means Clustering: A Case Study

Supplier evaluation and selection is one of the most critical strategic decisions for developing a competitive and sustainable organization. Companies have to consider supplier related risks and threats in their purchasing decisions. In today’s competitive and risky business environment, it is very important to work with reliable suppliers. This study proposes a clustering based approach to group suppliers based on their risk profile. Suppliers of a company in the heavy-machinery sector are assessed based on 17 qualitative and quantitative risk types. The weights of the criteria are determined by using the Best-Worst method. Four factors are extracted by applying Factor Analysis to the supplier risk data. Then k-means clustering algorithm is applied to group core suppliers of the company based on the four risk factors. Three clusters are created with different risk exposure levels. The interpretation of the results provides insights for risk management actions and supplier development programs to mitigate supplier risk.

Cumulative Burden of Morbidity Among Testicular Cancer Survivors After Standard Cisplatin-Based Chemotherapy: A Multi-Institutional Study.

Purpose In this multicenter study, we evaluated the cumulative burden of morbidity (CBM) among > 1,200 testicular cancer survivors and applied factor analysis to determine the co-occurrence of adverse health outcomes (AHOs). Patients and Methods Participants were ≤ 55 years of age at diagnosis, finished first-line chemotherapy ≥ 1 year previously, completed a comprehensive questionnaire, and underwent physical examination. Treatment data were abstracted from medical records. A CBM score encompassed the number and severity of AHOs, with ordinal logistic regression used to assess associations with exposures. Nonlinear factor analysis and the nonparametric dimensionality evaluation to enumerate contributing traits procedure determined which AHOs co-occurred. Results Among 1,214 participants, approximately 20% had a high (15%) or very high/severe (4.1%) CBM score, whereas approximately 80% scored medium (30%) or low/very low (47%). Increased risks of higher scores were associated with four cycles of either ifosfamide, etoposide, and cisplatin (odds ratio [OR], 1.96; 95% CI, 1.04 to 3.71) or bleomycin, etoposide, and cisplatin (OR, 1.44; 95% CI, 1.04 to 1.98), older attained age (OR, 1.18; 95% CI, 1.10 to 1.26), current disability leave (OR, 3.53; 95% CI, 1.57 to 7.95), less than a college education (OR, 1.44; 95% CI, 1.11 to 1.87), and current or former smoking (OR, 1.28; 95% CI, 1.02 to 1.63). CBM score did not differ after either chemotherapy regimen ( P = .36). Asian race (OR, 0.41; 95% CI, 0.23 to 0.72) and vigorous exercise (OR, 0.68; 95% CI, 0.52 to 0.89) were protective. Variable clustering analyses identified six significant AHO clusters (χ2 P < .001): hearing loss/damage, tinnitus (OR, 16.3); hyperlipidemia, hypertension, diabetes (OR, 9.8); neuropathy, pain, Raynaud phenomenon (OR, 5.5); cardiovascular and related conditions (OR, 5.0); thyroid disease, erectile dysfunction (OR, 4.2); and depression/anxiety, hypogonadism (OR, 2.8). Conclusion Factors associated with higher CBM may identify testicular cancer survivors in need of closer monitoring. If confirmed, identified AHO clusters could guide the development of survivorship care strategies.

An Empirical Research on Impact of HRD Climate on Infosys Pune

In current scenario of ever changing surroundings IT sector is an emergent and mounting solitary. IT sector being a part Service industry is extreme lyreliant on the proficiencies and enthusiasm of recruits. Thus it’s momentous to investigate Human Resource Development which is comprised of two elements i.e., climate and culture of such organizations. The current research is an attempt to identify the HRD-climate practices in Infosys Pune. The investigator has used standardized planned opinion-aire together information from the 50 employees of Infosys opinionaire.The information collected was analyzed by applying Factor analysis, Friedmen-test, one-way anova, Correlations and mean score. The main aim of present research was to ex-amine the temperament of HRD-climate in Infosys and identify the factors conducive towards HRD-climate. Here researcher makes an effort to pull out notable HRD-Cli-mate components derived from the inter-relationship of variables of HRD-Climate. Based on belief of Infosys employee’s influence of HRD components is measured. The result of the study involves 50 respondents from Infosys. The correlation analysis it has been observed that all three components HRD Mechanisms, General climate and OCTAPACE Culture are highly correlated to each other the value of r is lies 0.687 to 0.834, which highlights that deviation in single component will have strong influence on other two components. HRD-mechanisms is the top influencing element with mean score of 2.14. On account of overall result research determines that employees are motivated in their organisation, there is high level of team spirit and employees are encouraged to bring creative ideas and are supported by top management of organisation.

Visual Features in the Perception of Liquids

SummaryPerceptual constancy—identifying surfaces and objects across large image changes—remains an important challenge for visual neuroscience [1, 2, 3, 4, 5, 6, 7, 8]. Liquids are particularly challenging because they respond to external forces in complex, highly variable ways, presenting an enormous range of images to the visual system. To achieve constancy, the brain must perform a causal inference [9, 10, 11] that disentangles the liquid’s viscosity from external factors—like gravity and object interactions—that also affect the liquid’s behavior. Here, we tested whether the visual system estimates viscosity using “midlevel” features [12, 13, 14] that respond more to viscosity than other factors. Observers reported the perceived viscosity of simulated liquids ranging from water to molten glass exhibiting diverse behaviors (e.g., pouring, stirring). A separate group of observers rated the same animations for 20 midlevel 3D shape and motion features. Applying factor analysis to the feature ratings reveals that a weighted combination of four underlying factors (distribution, irregularity, rectilinearity, and dynamics) predicted perceived viscosity very well across this wide range of contexts (R2 = 0.93). Interestingly, observers unknowingly ordered their midlevel judgments according to the one common factor across contexts: variation in viscosity. Principal component analysis reveals that across the features, the first component lines up almost perfectly with the viscosity (R2 = 0.96). Our findings demonstrate that the visual system achieves constancy by representing stimuli in a multidimensional feature space—based on complementary, midlevel features—which successfully cluster very different stimuli together and tease similar stimuli apart, so that viscosity can be read out easily.

Source Identification of VOCs In METU Campus Through Factor Analysis

In this study, 55 ozone precursor VOCs, which are routinely measured in PAMS (Photochemical Assessment Monitoring Station) were measured in a suburban station located at Middle East Technical University, Environmental Engineering Department in, Ankara. Daily air samples were collected in evacuated canisters between January – December, 2014. Collected samples were analyzed with GC-FID system and concentrations of 51 VOCs were determined. Mean VOC concentrations ranged between 0.048±0.061 µg m-3 (cis-2-penten) and 10±13 µg m-3 (toluene). Average benzene concentration was 1.49 ± 1.74 μg m-3. Factor Analysis (FA) was applied to determine the major sources of VOCs that contribute to the measured concentrations in the university campus. FA application revealed nine factors that can be grouped under four major components, including (1) transportation: gasoline vehicle exhaust emissions, evaporative losses from gasoline vehicles, gasoline evaporation in gas stations and diesel emissions, (2) industrial emissions: industrial evaporation and industrial application, (3) solvent emissions: surface coatings and solvent use and (4) asphalt application.

Understanding the Physiological Significance of Four Inertial Gait Features in Multiple Sclerosis.

Gait impairment in multiple sclerosis (MS) can result from muscle weakness, physical fatigue, lack of coordination, and other symptoms. Walking speed, as measured by a number of clinician-administered walking tests, is the primary measure of gait impairment used by clinical researchers, but inertial gait features from body-worn sensors have been proven to add clinical value. This paper seeks to understand and differentiate the physiological significance of four such features with proven value in MS to facilitate adoption by clinical researchers and incorporation in gait monitoring and analysis systems. In addition, this information can be used to select features that might be appropriate in other forms of disability. Two of the four features are computed using the dynamic time warping (DTW) algorithm: The "DTW Score" is based on the usual DTW distance, and the "Warp Score" is based on the warping length. The third feature, based on kernel density estimation (KDE), is the "KDE Peak" value. Finally, the "Causality Index" is based on the phase slope index between inertial signals from different body parts. Relationships between these measures and the aforementioned gait-related symptoms are determined by applying factor analysis to three common, clinical walking outcomes, then correlating the inertial measures as well as walking speed to each extracted factor. Statistically significant differences in correlation coefficients to the three extracted clinical factors support their distinct physiological meaning and suggest they may have complimentary roles in the analysis of MS-related walking disability.

ОСОБЕННОСТИ ИСПОЛЬЗОВАНИЯ ФАКТОРНОГО АНАЛИЗА В ПОЛИТОЛОГИЧЕСКИХ ИССЛЕДОВАНИЯХ

ОСОБЕННОСТИ ИСПОЛЬЗОВАНИЯ ФАКТОРНОГО АНАЛИЗА В ПОЛИТОЛОГИЧЕСКИХ ИССЛЕДОВАНИЯХ

Predicting choice of Theme-park destinations in India

Purpose: In this paper we attempt to understand the factors that provides satisfaction to the visitors of theme-park destinations and to predict visitors’ intent to re-visit the theme park destinations in India. Methodology: We have applied factor analysis to understand the attributes that attract visitors to re-visit theme parks and logistic regression techniques to predict if the visitor’s intent to re-visit theme-park destinations on a regular basis. Findings: The results suggest that major factors that visitors consider while confirming re-visit to theme parks in India include lifestyle, historical and leisure. Moreover, tourists visiting such theme parks are always interested in new, innovative and creative ideas to attract and plan their visits on a regular basis. The visitors prefer to experience and feel India mainly listening to regional music and enriching its cultural and historical importance. Originality: This will promote Indian tourism industry by motivating managers to bring up new, creative and innovative ideas to attract more visitors in theme-parks. Business managers may expand their existing business plans in Indian tourism industry.

Multivariate statistical analysis to characterize/discriminate between anthropogenic and geogenic trace elements occurrence in the Campania Plain, Southern Italy.

Shallow aquifers are the most accessible reservoirs of potable groundwater; nevertheless, they are also prone to various sources of pollution and it is usually difficult to distinguish between human and natural sources at the watershed scale. The area chosen for this study (the Campania Plain) is characterized by high spatial heterogeneities both in geochemical features and in hydraulic properties. Groundwater mineralization is driven by many processes such as, geothermal activity, weathering of volcanic products and intense human activities. In such a landscape, multivariate statistical analysis has been used to differentiate among the main hydrochemical processes occurring in the area, using three different approaches of factor analysis: (i) major elements, (ii) trace elements, (iii) both major and trace elements. The elaboration of the factor analysis approaches has revealed seven distinct hydrogeochemical processes: i) Salinization (Cl-, Na+); ii) Carbonate rocks dissolution; iii) Anthropogenic inputs (NO3-, SO42-, U, V); iv) Reducing conditions (Fe2+, Mn2+); v) Heavy metals contamination (Cr and Ni); vi) Geothermal fluids influence (Li+); and vii) Volcanic products contribution (As, Rb). Results from this study highlight the need to separately apply factor analysis when a large data set of trace elements is available. In fact, the impact of geothermal fluids in the shallow aquifer was identified from the application of the factor analysis using only trace elements. This study also reveals that the factor analysis of major and trace elements can differentiate between anthropogenic and geogenic sources of pollution in intensively exploited aquifers.

Assessing the quality and usefulness of factor-analytic applications to personality measures: A study with the statistical anxiety scale

Factor analysis (FA) is the most widely used modeling approach for developing and assessing psychometric personality measures. Furthermore, the appropriateness of an FA application of this type is generally judged on the sole basis of model-data fit, a criterion which is clearly insufficient. This article proposes a multi-faceted approach for assessing (a) the strength and replicability of the factorial solution, (b) the accuracy and effectiveness of the factor score estimates, and (c) the closeness to unidimensionality in measures that were initially designed to be single-trait. The proposal was applied to a measure of statistical anxiety, the SAS, and the main results were the following: (a) both the unidimensional and the oblique solutions were well defined and replicable, and they led to accurate factor score estimates; and (b) unidimensional-based scores were effective over the full practical range of trait values whereas the ranges of the more specific factors in the oblique solution were narrower. It is submitted that the use of the proposal and the accompanying criteria has important advantages and can help to raise standards in FA applications in personality.

서비스기업 종사원의 대인매력이 고객의 지각된 가치에 미치는 영향

This study examines the effect of interpersonal attraction among service company employees on a customer's perceived value. This was done in order to confirm the interpersonal attraction of service employees needed to enhance the performance of service companies. The categories of interpersonal attraction were defined in terms of physical attraction, social attraction, and task attraction. Perceived value was divided into quality value, emotional value, price value, and social value. The samples used were taken from those who had experienced receiving service in restaurants. This was done because restaurants are one of most common places in which most people often experience the attraction of a service provider. The survey was conducted in Seoul Station in an area of constant human movement with 317 questionnaires being used to obtain the results. By applying factor analysis, interpersonal attraction converged into three factors according to the research design. However, as the quality value and the price value converged into one factor, perceived value separated into three factors being: quality-price value, emotional value, and social value. As a result, task attraction had a positive effect on quality-price value but physical attraction had a negative effect on it. Task attraction and social attraction had a positive effect on emotional value. Physical attraction, task attraction, and social attraction all had a positive effect on social value.

Preferences on Security Issues and Ideological Competitions: A Case of the Korean National Assembly

This article examines the distinct features of the ideological thinking and their impact on ideological competitions among the members of Korean National Assembly (KNA). In particular, it analyzes the influ ence of preferences on security issues on the formation of ideological self-identification and internal competitions of the KNA. By applying factor analysis, it shows that the issue attitudes among the members of the KNA do not converge into the ideological self-identification. In addition, preferences on security issues can be distinguished from the ideological self-identification among the member of the KNA and have an independent impact on their legislative voting behavior. These results imply that a more valid understanding of the legislative behav ior among the members of the KNA could develop by specifying issue attitudes independently from the ideological self-identification.

A cognitive organization theory (COT) of organizational change

PurposeIn this paper, the authors develop a cognitive organization theory (COT) of organizational change. COT was developed in the 2000s, by taking insights from cognitive psychology and anthropology to rebuild the foundation of organizational ecology (OE), grounding macro processes of organizational legitimation, inertia and mortality in micro processes of appeal and engagement. COT also explored the micro-level process of organizational change, arguing that four features (i.e. asperity, intricacy, opacity, and viscosity) of an organization's texture impact the appeal of organizational change. However, to data, empirical studies of a COT of organizational change are absent. An important reason is that many of the new COT constructs are not linked to empirical measures. The purpose of this paper is to develop reliable and valid survey measures of COT's key constructs.Design/methodology/approachThe authors follow a three-step procedure to develop reliable and valid survey measures of COT's key constructs. First, the authors construct survey measures by using existing organizational behavior (OB) scales and develop new scales in consultation with COT experts. Second, the authors apply factor analysis to evaluate convergent and discriminant validity and use Cronbach's α to determine the reliability of the scales. Third, the authors estimate a structural equation model to determine external validity, by exploring whether the measures have the effect hypothesized in COT.FindingsThe authors find that existing OB scales can be used to proxy for COT's key constructs of appeal and engagement. The authors also find that two organizational texture variables (i.e., asperity and opacity) are significantly associated with the appeal of organizational change, further confirming the validity of applying a COT to organization change. The results are promising, proving evidence as to the criterion-related validity of the measures of COT constructs. From the total of 39 coefficients of COT-inspired independent and control variables, 22 are significant.Research limitations/implicationsThe authors’ findings illustrate that micro OB and macro OE can be effectively combined in a COT of organizational change. However, the authors' contribution is only a first step, requiring further theoretical and methodological refinement. Theoretically, OB and OE can be integrated further, by linking together more concepts and constructs from the two streams of literature. Methodologically, the link between constructs and empirical measures can be refined, by adding extra scales and items, and collecting more data to validate them.Originality/valueIn this paper, the authors develop a COT of organizational change and link its central constructs to empirical measures, by connecting them to existing OB constructs and developing new scales and items. This opens the door to empirical studies on a COT of organizational change, hereby providing a stepping-stone for further integration of micro OB and macro OE.

A Tourism Financial Conditions Index for Tourism Finance

The paper uses monthly data on tourism related factors from April 2005–June 2016 for Taiwan that applies factor analysis and Chang’s (2015) novel approach for constructing a tourism financial indicator, namely the Tourism Financial Conditions Index (TFCI). The TFCI is an adaptation and extension of the widely-used Monetary Conditions Index (MCI) and Financial Conditions Index (FCI) to tourism stock data. However, the method of calculation of the TFCI is different from existing methods of constructing the MCI and FCI in that the weights are estimated empirically. The empirical findings show that TFCI is statistically significant using the estimated conditional mean of the tourism stock index returns (RTS). Granger Causality tests show that TFCI shows strong feedback on RTS. An interesting insight is that the empirical results show a significant negative correlation between F1_visitors (Foreign Visitor Arrivals) and RTS, implying that tourism authorities might promote travel by the “rich”, and not only on inbound visitor growth. The use of market returns on the tourism stock sub-index as the sole indicator of the tourism sector, as compared with the general activity of economic variables on tourism stocks, is shown to provide an exaggerated and excessively volatile explanation of tourism financial conditions.

Improved scatter correction with factor analysis for planar and SPECT imaging.

Quantitative nuclear medicine imaging is an increasingly important frontier. In order to achieve quantitative imaging, various interactions of photons with matter have to be modeled and compensated. Although correction for photon attenuation has been addressed by including x-ray CT scans (accurate), correction for Compton scatter remains an open issue. The inclusion of scattered photons within the energy window used for planar or SPECT data acquisition decreases the contrast of the image. While a number of methods for scatter correction have been proposed in the past, in this work, we propose and assess a novel, user-independent framework applying factor analysis (FA). Extensive Monte Carlo simulations for planar and tomographic imaging were performed using the SIMIND software. Furthermore, planar acquisition of two Petri dishes filled with 99mTc solutions and a Jaszczak phantom study (Data Spectrum Corporation, Durham, NC, USA) using a dual head gamma camera were performed. In order to use FA for scatter correction, we subdivided the applied energy window into a number of sub-windows, serving as input data. FA results in two factor images (photo-peak, scatter) and two corresponding factor curves (energy spectra). Planar and tomographic Jaszczak phantom gamma camera measurements were recorded. The tomographic data (simulations and measurements) were processed for each angular position resulting in a photo-peak and a scatter data set. The reconstructed transaxial slices of the Jaszczak phantom were quantified using an ImageJ plugin. The data obtained by FA showed good agreement with the energy spectra, photo-peak, and scatter images obtained in all Monte Carlo simulated data sets. For comparison, the standard dual-energy window (DEW) approach was additionally applied for scatter correction. FA in comparison with the DEW method results in significant improvements in image accuracy for both planar and tomographic data sets. FA can be used as a user-independent approach for scatter correction in nuclear medicine.

Bandwidth Measurements within the Cloud

The search for availability, reliability, and quality of service has led cloud infrastructure customers to disseminate their services, contents, and data over multiple cloud data centers, often involving several Cloud service providers (CSPs). The consequence of this is that a large amount of data must be transmitted across the public Cloud. However, little is known about the bandwidth dynamics involved. To address this, we have conducted a measurement campaign for bandwidth between 18 data centers of four major CSPs. This extensive campaign allowed us to characterize the resulting time series of bandwidth as the addition of a stationary component and some infrequent excursions (typically downtimes). While the former provides a description of the bandwidth users can expect in the Cloud, the latter is closely related to the robustness of the Cloud (i.e., the occurrence of downtimes is correlated). Both components have been studied further by applying factor analysis, specifically analysis of variance, as a mechanism to formally compare data centers’ behaviors and extract generalities. The results show that the stationary process is closely related to the data center locations and CSPs involved in transfers that, fortunately, make the Cloud more predictable and allow the set of reported measurements to be extrapolated. On the other hand, although correlation in the Cloud is low, that is, only 10% of the measured pair of paths showed some correlation, we found evidence that such correlation depends on the particular relationships between pairs of data centers with little connection to more general factors. Positively, this implies that data centers either in the same area or within the same CSP do not show qualitatively more correlation than other data centers, which eases the deployment of robust infrastructures. On the downside, this metric is scarcely generalizable and, consequently, calls for exhaustive monitoring.

Population activity structure of excitatory and inhibitory neurons.

Many studies use population analysis approaches, such as dimensionality reduction, to characterize the activity of large groups of neurons. To date, these methods have treated each neuron equally, without taking into account whether neurons are excitatory or inhibitory. We studied population activity structure as a function of neuron type by applying factor analysis to spontaneous activity from spiking networks with balanced excitation and inhibition. Throughout the study, we characterized population activity structure by measuring its dimensionality and the percentage of overall activity variance that is shared among neurons. First, by sampling only excitatory or only inhibitory neurons, we found that the activity structures of these two populations in balanced networks are measurably different. We also found that the population activity structure is dependent on the ratio of excitatory to inhibitory neurons sampled. Finally we classified neurons from extracellular recordings in the primary visual cortex of anesthetized macaques as putative excitatory or inhibitory using waveform classification, and found similarities with the neuron type-specific population activity structure of a balanced network with excitatory clustering. These results imply that knowledge of neuron type is important, and allows for stronger statistical tests, when interpreting population activity structure.

Study of female entrepreneurship: an empirical evidence in the Municipality of León in Nicaragua

Women's entrepreneurship is one of the main challenges in economic growth. In this context, in the context of the creation of new companies, it can be considered as one of the main mechanisms that contribute in an important way to achieve the desired welfare for society, reducing unemployment, increasing innovation and improving competitiveness and favoring an important part of economic growth. This article analyzes the influence of the socioeconomic and psychosocial factors of the female entrepreneurship. For this purpose, a sample of 101 women entrepreneurs in the municipality of Leon, Nicaragua, has been used. We apply Factor Analysis and Regression Analysis, in order to detect the relationship between the considered factors. Some results indicate that all variables considered have a significant influence on the probability of entrepreneurship, the capacity of entrepreneurial women increases when they have skills, knowledge and have an early contact in the business world.