Barriers to accurately measuring patients’ dietary intake in hospitals using the visual estimation method

2016 ◽  
Vol 29 (8) ◽  
pp. 835-845 ◽  
Author(s):  
Yui Kawasaki ◽  
Yui Kojima ◽  
Rie Akamatsu
Keyword(s):  
Dietary Intake ◽  
Estimation Method ◽  
Reliability And Validity ◽  
Estimation Methods ◽  
Clinical Settings ◽  
Visual Estimation ◽  
Content Type ◽  
Clinical Nurses ◽  
Individual Interviews ◽  
Routine Work

Purpose Visual estimation, an easy-to-perform technique, is commonly used in hospitals to assess dietary intake in patients. The authors performed a qualitative study where the authors interviewed nurses and dietitians about their perceptions of barriers to accurately measuring patients’ dietary intake in hospitals using the visual estimation method. The paper aims to discuss these issues. Design/methodology/approach Ten dietitians and ten clinical nurses responded to 30-minute individual interviews in Tokyo, Japan, in September 2014. Each interview was conducted using a common protocol of open-ended questions focusing on the challenges of the visual estimation method and barriers to accurately measuring patients’ dietary intake as part of their routine work. The tape-recorded interviews were transcribed and analyzed based on grounded theory. Findings Five main categories emerged: hospitals, meals, colleagues, raters, and patients. Various individual barriers such as skill, attitude, knowledge, and others that had not been considered in previous studies also emerged. External barriers that were out of the raters’ control, such as shortage of time, human resources, financial ability, and others, emerged from the “hospitals” category. Research limitations/implications Research participants were all females and many of them had less than ten years of experience. Practical implications In addition to standardizing the visual estimation process, medical staff need to overcome various other internal and external barriers to accurate measurements. Originality/value This is the first study to articulate some important barriers that influence reliability and validity when measuring patients’ dietary intake by visual estimation methods in typical clinical settings.

Dynamic endogeneity and corporate governance-performance relationship

2017 ◽  
Vol 44 (5) ◽  
pp. 727-744
Author(s):  
Sujani Thrikawala ◽  
Stuart Locke ◽  
Krishna Reddy
Keyword(s):  
Corporate Governance ◽  
National Level ◽  
Estimation Method ◽  
Estimation Methods ◽  
Governance System ◽  
Past Performance ◽  
Gmm Estimation ◽  
Content Type ◽  
Dynamic Framework

Purpose The purpose of this paper is to examine the relationship between corporate governance (CG) and microfinance institution (MFI) performance, using a dynamic panel generalised method of moments (GMM) estimator to mitigate the serious issues with endogeneity. Design/methodology/approach Inconsistent findings and a general lack of empirical results for the microfinance industry leave an unclear message regarding the impacts of CG on MFI performance, especially in emerging economies. The authors use GMM estimation techniques to examine whether CG has an influence on MFI performance. Findings This study confirms that the MFIs’ contemporaneous performance and CG characteristics are statistically significantly positively linked with their past performance. This study finds statistically significant governance effects on MFI performance, including the presence of international directors and/or donor representatives on the board, client representatives on the board, percentage of non-executive directors and the quality of the national governance system. Practical implications These findings provide some insights for policy-makers and practitioners to develop suitable policies and guidelines to streamline MFIs’ operations in emerging countries. Moreover, national and international investors and donors may use these finding as a benchmark for their investment and funding decisions. Originality/value This paper is the first to estimate the CG and performance relationship of MFIs in a dynamic framework by applying the GMM estimation method. This approach improves upon traditional estimation methods by controlling the likely sources of endogeneity. Further, this paper examines whether quality of national-level governance characteristics is related to performance measures of profitability and outreach of MFIs.

A grey rough set model for evaluation and selection of software cost estimation methods

2014 ◽  
Vol 4 (1) ◽  
pp. 3-12 ◽  
Author(s):  
Jun Liu ◽  
Jian-Zhong Qiao
Keyword(s):  
System Theory ◽  
Rough Set ◽  
Cost Estimation ◽  
Estimation Method ◽  
Grey System Theory ◽  
Estimation Methods ◽  
Software Cost Estimation ◽  
Grey System ◽  
Software Cost ◽  
Content Type

Purpose – Due to the limitation of acknowledgment, the complexity of software system and the interference of noises, this paper aims to solve the traditional problem: traditional software cost estimation methods face the challenge of poor and uncertain inputs. Design/methodology/approach – Under such circumstances, different cost estimation methods vary greatly on estimation accuracy and effectiveness. Therefore, it is crucial to perform evaluation and selection on estimation methods against a poor information database. This paper presents a grey rough set model by introducing grey system theory into rough set based analysis, aiming for a better choice of software cost estimation method on accuracy and effectiveness. Findings – The results are very encouraging in the sense of comparison among four machine learning techniques and thus indicate it an effective approach to evaluate software cost estimation method where insufficient information is provided. Practical implications – Based on the grey rough set model, the decision targets can be classified approximately. Furthermore, the grey of information and the limitation of cognition can be overcome during the use of the grey rough interval correlation cluster method. Originality/value – This paper proposed the grey rough set model combining grey system theory with rough set for software cost estimation method evaluation and selection.

Comparing alternative approaches to estimate customer equity

2017 ◽  
Vol 35 (5) ◽  
pp. 611-625 ◽  
Author(s):  
Cleo Schmitt Silveira ◽  
Marta Olivia Rovedder de Oliveira ◽  
Fernando Bins Luce
Keyword(s):  
Data Model ◽  
Convergent Validity ◽  
Estimation Method ◽  
Customer Equity ◽  
Estimation Methods ◽  
Private Companies ◽  
Content Type ◽  
Estimation Formula ◽  
Multi Method Approach ◽  
Marketing Resource Allocation

Purpose The purpose of this paper is to explore the differences and similarities between two methods/models for estimating customer equity (CE): one using behavior-based data and one using market-based data. Design/methodology/approach Two separate analyses of the same market scenario (telecom industry) were conducted, by applying the CE estimation method from Rust et al. (2004) and the CE model from Gupta et al. (2004). Findings Different methods/models can produce similar estimates, which corroborates the defense of an integrated multi-method approach to evaluating CE. In addition, they each provide different benefits. The behavioral data model provides identification of CE drivers and assists in the task of marketing resource allocation, the market-based data model is simple and easy to implement and is recommended in cases when CE is used as a financial indicator. Originality/value This paper contributes to the CE literature in the following ways. First, it demonstrates the possibility of obtaining similar estimates of CE using distinct types of data and data collection procedures, and with two different estimation methods/models. Second, it confirms that either model allows firms to compute the expected market capitalization at any given time using customer and financial information. Third, it demonstrates the convergent validity of these two methods/models for estimating CE for either public or private companies, thus legitimizing the comparison of their respective CE values, regardless of the type of source data or estimation formula used.

scholarly journals Golf destinations’ brand personality: the case of the Algarve

2015 ◽  
Vol 9 (2) ◽  
pp. 133-153 ◽  
Author(s):  
Rosaria Luisa Gomes Pereira ◽  
Antónia Correia ◽  
Ronaldo L.A. Schutz
Keyword(s):  
Structural Equation ◽  
Brand Personality ◽  
Reliability And Validity ◽  
Great Difficulty ◽  
Content Type ◽  
Personality Scale ◽  
Individual Interviews ◽  
Personality Models ◽  
Destination Brand ◽  
Brand Personality Scale

Purpose – The purpose of this paper is to develop and validate a measurement brand personality scale for golf destinations and simultaneously to assess the destination personality of the Algarve as a golf destination. Design/methodology/approach – A set of 36 unrepeated items, generated from individual interviews with experts in tourism and golf in the Algarve and from promotional texts in golf-related websites, was the base for a survey instrument. The survey was applied to a convenient sample of 600 golf players in the Algarve, and 545 (valid) questionnaires were analysed to refine the scale. Golf players assessed the Algarve as a golf destination and the components of the relational brand personality (functional, symbolic and experiential). Two multi-dimensional brand personality models were estimated by using structural equation modelling. Findings – Findings indicate that golf players ascribe personality characteristics to destinations. The brand personality of the Algarve is translated into three main dimensions enjoyableness, distinctiveness and friendliness when tourists/golf players reveal their overall perception of the destination. The brand personality of golf destination Algarve is reflected in the dimensions reliability, hospitality, uniqueness and attractiveness when tourists/golf players assess the components of the relational brand personality. Refined scales consisting of 10 and 11 items were finally derived meeting both reliability and validity requirements. Research limitations/implications – The analysis is based on personality perceptions of only one golf destination. Another limitation is the fact that both interviewees and respondents had great difficulty in expressing themselves tending to use repeated words. Also, the fact that the research was conducted in two languages since translation and retroversion of the items may lead to some loss in meaning or sense. Moreover, the experiential component of the relational brand personality might have been further explored to relate golf destination brand personality to the tourist experience. Practical implications – Important contributions are that both qualitative and quantitative approaches should be used in the measurement of brand personality. A reliable and valid tool to assess golf destination brand personality is a valuable marketing management resource. Social implications – Destination managers will be able to plan marketing actions that will help to change general destination attitudes and product-destination attitudes, establishing the destination brand and creating differentiation, resulting in increased preference and usage, higher emotional ties, trust and loyalty towards the brand. Also, marketers should place great emphasis on building a connection between destination personality and tourists/golf players’ self-concept. Originality/value – This is one of the first pieces of research to validate a specific brand personality scale to golf destinations. Results of this study make important theoretical contributions to the understanding of brand personality in the context of tourism destinations in general, and golf destinations in particular.

Parameter estimation of UAV from flight data using neural network

2018 ◽  
Vol 90 (2) ◽  
pp. 302-311 ◽  
Author(s):  
Dhayalan R. ◽  
Subrahmanyam Saderla ◽  
Ajoy Kanti Ghosh
Keyword(s):  
Parameter Estimation ◽  
Design Methodology ◽  
Maximum Likelihood Method ◽  
Estimation Method ◽  
Likelihood Method ◽  
Estimation Methods ◽  
Process Noise ◽  
Content Type ◽  
Flight Data ◽  
Aerial Vehicle

Purpose The purpose of this paper is to present the application of the neural-based estimation method, Neural-Gauss-Newton (NGN), using the real flight data of a small unmanned aerial vehicle (UAV). Design/methodology/approach The UAVs in general are lighter in weight and their flight is usually influenced by the atmospheric winds because of their relatively lower cruise speeds. During the presence of the atmospheric winds, the aerodynamic forces and moments get modified significantly and the accurate mathematical modelling of the same is highly challenging. This modelling inaccuracy during parameter estimation is routinely treated as the process noise. Furthermore, because of the limited dimensions of the small UAVs, the measurements are usually influenced by the disturbances caused by other subsystems. To handle these measurement and process noises, the estimation methods based on neural networks have been found reliable in the manned aircrafts. Findings Six sets of compatible longitudinal flight data of the designed UAV have been chosen to estimate the parameters using the NGN method. The consistency in the estimates is verified from the obtained mean and the standard deviation and the same has been validated by the proof-of-match exercise. It is evident from the results that the NGN method was able to perform on a par with the conventional maximum likelihood method. Originality/value This is a partial outcome of the research carried out in estimating parameters from the UAVs.

How triple-role conflicts of Chinese enterprise trade unions impact employees' satisfaction: rights expectation as moderator

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Han Ren ◽  
Charles Weizheng Chen ◽  
Jiuhua Cherrie Zhu ◽  
Yuling Chen
Keyword(s):  
Trade Unions ◽  
High Reliability ◽  
Reliability And Validity ◽  
Three Dimensions ◽  
Role Conflicts ◽  
Content Type ◽  
Individual Interviews ◽  
Chinese Enterprise ◽  
Employees Satisfaction ◽  
Exploratory Factor Analyses

PurposeThis paper aims to explore the extent to which unionized employees are dissatisfied in Chinese Enterprise Trade Unions (CETUs) when they perceive high levels of the triple-role conflicts, as well as whether rights expectations will moderate these relationships. The authors define CETUs' triple-role conflicts as the extent to which CETUs and their cadres prioritize fulfilling the roles of preserving social stability (“peace”) and/or maintaining the production order (“production”) over protecting worker's rights and interests (“workers” rights).Design/methodology/approachPilot study developed the scales via both qualitative and quantitative studies, which include item generation using the transcript of individual interviews with 36 informants, and exploratory factor analyses with 106 respondents. The study used a sample of 327 employees from more than 20 firms in North and Southwest China.FindingsResults indicate high reliability and validity of the scales and provide largely consistent supports for our hypotheses: three dimensions of triple-role conflicts are negatively related to employees' satisfaction in CETUs, and rights expectations moderate these relationships.Originality/valueThis study developed three scales to respectively measure CETUs' triple-role conflicts, rights expectation and satisfaction in CETUs. More importantly, the findings shed light on the moderating mechanism of rights expectation in the relationships between triple-role conflicts and satisfaction in CETUs.

Using The Fully Modified M Method In Estimating The Effect Of Cultivated Area On Barley Production In Iraq For The Period 1970-2018

2020 ◽  
Vol 2020 (66) ◽  
pp. 101-110
Author(s):  
. Azhar Kadhim Jbarah ◽  
Prof Dr. Ahmed Shaker Mohammed
Keyword(s):  
Regression Model ◽  
Moving Average ◽  
Estimation Method ◽  
Estimation Methods ◽  
Autoregressive Moving Average ◽  
Moving Average Models ◽  
Error Terms ◽  
Relationship Of ◽  
The Relationship ◽  
Barley Crop

The research is concerned with estimating the effect of the cultivated area of barley crop on the production of that crop by estimating the regression model representing the relationship of these two variables. The results of the tests indicated that the time series of the response variable values is stationary and the series of values of the explanatory variable were nonstationary and that they were integrated of order one ( I(1) ), these tests also indicate that the random error terms are auto correlated and can be modeled according to the mixed autoregressive-moving average models ARMA(p,q), for these results we cannot use the classical estimation method to estimate our regression model, therefore, a fully modified M method was adopted, which is a robust estimation methods, The estimated results indicate a positive significant relation between the production of barley crop and cultivated area.

scholarly journals Comparative Analysis of Kinect-Based and Oculus-Based Gaze Region Estimation Methods in a Driving Simulator

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 26
Author(s):  
David González-Ortega ◽  
Francisco Javier Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez
Keyword(s):  
Virtual Reality ◽  
Comparative Analysis ◽  
Driving Simulator ◽  
Estimation Method ◽  
Estimation Methods ◽  
Gaze Estimation ◽  
Driving Simulators ◽  
Oculus Rift ◽  
Gaze Patterns ◽  
And Performance

Driver’s gaze information can be crucial in driving research because of its relation to driver attention. Particularly, the inclusion of gaze data in driving simulators broadens the scope of research studies as they can relate drivers’ gaze patterns to their features and performance. In this paper, we present two gaze region estimation modules integrated in a driving simulator. One uses the 3D Kinect device and another uses the virtual reality Oculus Rift device. The modules are able to detect the region, out of seven in which the driving scene was divided, where a driver is gazing at in every route processed frame. Four methods were implemented and compared for gaze estimation, which learn the relation between gaze displacement and head movement. Two are simpler and based on points that try to capture this relation and two are based on classifiers such as MLP and SVM. Experiments were carried out with 12 users that drove on the same scenario twice, each one with a different visualization display, first with a big screen and later with Oculus Rift. On the whole, Oculus Rift outperformed Kinect as the best hardware for gaze estimation. The Oculus-based gaze region estimation method with the highest performance achieved an accuracy of 97.94%. The information provided by the Oculus Rift module enriches the driving simulator data and makes it possible a multimodal driving performance analysis apart from the immersion and realism obtained with the virtual reality experience provided by Oculus.

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