Time dependent patient no-show predictive modelling development

2016 ◽  
Vol 29 (4) ◽  
pp. 475-488 ◽  
Author(s):  
Yu-Li Huang ◽  
David A. Hanauer
Keyword(s):  
Predictive Model ◽  
Predictive Models ◽  
Negative Impact ◽  
Area Under The Curve ◽  
Wait Time ◽  
Predictive Modelling ◽  
Time Dependent ◽  
Misclassification Rate ◽  
Data Set ◽  
Content Type

Purpose – The purpose of this paper is to develop evident-based predictive no-show models considering patients’ each past appointment status, a time-dependent component, as an independent predictor to improve predictability. Design/methodology/approach – A ten-year retrospective data set was extracted from a pediatric clinic. It consisted of 7,291 distinct patients who had at least two visits along with their appointment characteristics, patient demographics, and insurance information. Logistic regression was adopted to develop no-show models using two-thirds of the data for training and the remaining data for validation. The no-show threshold was then determined based on minimizing the misclassification of show/no-show assignments. There were a total of 26 predictive model developed based on the number of available past appointments. Simulation was employed to test the effective of each model on costs of patient wait time, physician idle time, and overtime. Findings – The results demonstrated the misclassification rate and the area under the curve of the receiver operating characteristic gradually improved as more appointment history was included until around the 20th predictive model. The overbooking method with no-show predictive models suggested incorporating up to the 16th model and outperformed other overbooking methods by as much as 9.4 per cent in the cost per patient while allowing two additional patients in a clinic day. Research limitations/implications – The challenge now is to actually implement the no-show predictive model systematically to further demonstrate its robustness and simplicity in various scheduling systems. Originality/value – This paper provides examples of how to build the no-show predictive models with time-dependent components to improve the overbooking policy. Accurately identifying scheduled patients’ show/no-show status allows clinics to proactively schedule patients to reduce the negative impact of patient no-shows.

Developing a predictive model of construction industry-university research collaboration

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Monty Sutrisna ◽  
Dewi Tjia ◽  
Peng Wu
Keyword(s):  
Data Collection ◽  
Predictive Model ◽  
Construction Industry ◽  
Research Collaboration ◽  
Ann Model ◽  
Data Set ◽  
Content Type ◽  
Construction Companies ◽  
Likelihood Model ◽  
Artificial Neural Network Ann

Purpose This paper aims to identify and examine the factors that influence construction industry-university (IU) collaboration and develop the likelihood model of a potential industry partner within the construction industry to collaborate with universities. Design/methodology/approach Mix method data collection including questionnaire survey and focus groups were used for data collection. The collected data were analysed using descriptive and inferential statistical methods to identify and examine factors. These findings were then used to develop the likelihood predictive model of IU collaboration. A well-known artificial neural network (ANN) model, was trained and cross-validated to develop the predictive model. Findings The study identified company size (number of employees and approximate annual turnover), the length of experience in the construction industry, previous IU collaboration, the importance of innovation and motivation of innovation for short term showed statistically significant influence on the likelihood of collaboration. The study also revealed there was an increase in interest amongst companies to engage the university in collaborative research. The ANN model successfully predicted the likelihood of a potential construction partner to collaborate with universities at the accuracy of 85.5%, which was considered as a reasonably good model. Originality/value The study investigated the nature of collaboration and the factors that can have an impact on the potential IU collaborations and based on that, introduced the implementation of machine learning approach to examine the likelihood of IU collaboration. While the developed model was derived from analysing data set from Western Australian construction industry, the methodology proposed here can be used as the basis of predictive developing models for construction industry elsewhere to help universities in assessing the likelihood for collaborating and partnering with the targeted construction companies.

Reduction of tension effects on partner evaluation

2018 ◽  
Vol 36 (4) ◽  
pp. 425-439
Author(s):  
Ossi Pesämaa ◽  
Peter Dahlin ◽  
Christina Öberg
Keyword(s):  
Structural Equation ◽  
Negative Impact ◽  
Equation Modeling ◽  
Negative Effects ◽  
Data Set ◽  
Content Type ◽  
Business Partners ◽  
Positive Side ◽  
Tension Management ◽  
Business To Business

Purpose The purpose of this paper is to examine how tension management as a means of achieving compromise and overcoming minor conflicts reduces the effects of the opportunism and bargaining costs of relationships on the evaluation of business partners. The paper proposes and tests a theoretical model with a full-information approach using structural equation modeling. Design/methodology/approach The data set was based on 312 observations from a unique survey based on a business-to-business relationship sample in Sweden. The measurements reflect the effects of partner opportunism, bargaining costs, and tension management on partner evaluations. Findings The findings corroborate that partner opportunism and bargaining costs have a negative impact on partner evaluation. In addition, the model shows that tension management weakens the negative effects of opportunism and bargaining costs on the evaluation. Originality/value This study offers evidence on how negative effects are reduced through intervening constructs. With most studies focusing on the positive side of relationships, this paper makes an important contribution to the literature through not only describing negative effects, but also how these can be decreased.

“When I get older, I wanna be an entrepreneur”: the impact of disability and dyslexia on entrepreneurial self-efficacy perception

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Benjamin Powers ◽  
Séverine Le Loarne-Lemaire ◽  
Adnane Maalaoui ◽  
Sascha Kraus
Keyword(s):  
Self Efficacy ◽  
Negative Impact ◽  
Research Question ◽  
Entrepreneurial Intention ◽  
Economic Life ◽  
Entrepreneurial Intentions ◽  
Data Set ◽  
Content Type ◽  
The Usa ◽  
The Impact

PurposeThis article contributes to the literature on entrepreneurship for people with disabilities through a better understanding of the impact of entrepreneurial self-efficacy perceptions on entrepreneurial intentions in populations with lower levels of self-esteem. It investigates the entrepreneurial intention and self-efficacy of a population of students suffering from dyslexia, which is a learning disability.Design/methodology/approachThe paper is based on the study of a data set of 796 male and female adolescents in the USA, aged 13–19 years, both with and without dyslexia. The sample is a convenient one. The whole sample replied to the questionnaire on their self-efficacy perception and their intention to create, one day, their own venture. They also self-declare their dyslexia. Regressions have been conducted to answer the research question.FindingsResults show that having dyslexia has a negative impact on entrepreneurial self-efficacy perceptions. They also reveal that self-efficacy perceptions mediate the relationship between dyslexia and entrepreneurial intentions and their three antecedents (social norms, control behavior and perceived ability).Research limitations/implicationsThe sample is composed of students from private schools and might socially be biased.Practical implicationsOur findings relaunch the debate on the necessity to develop education programs that consider the personal-level variables of students, specifically the development of entrepreneurial self-efficacy among adolescents with disabilitiesSocial implicationsSuch findings should help to better understand students who are suffering from dyslexia and help them find a place in society and economic life.Originality/valueThis is so far the first study that has been conducted on dyslexic adolescents.

Crossing the threshold from founder management to professional management in Russian firms

2015 ◽  
Vol 21 (1) ◽  
pp. 76-106 ◽  
Author(s):  
Galina Shirokova ◽  
Gina Vega ◽  
Dmitri Knatko
Keyword(s):  
Emerging Markets ◽  
Institutional Environment ◽  
Negative Impact ◽  
Institutional Factors ◽  
Ceo Succession ◽  
Institutional Perspective ◽  
Data Set ◽  
Content Type ◽  
Professional Management ◽  
Organisational Factors

Purpose – The purpose of this paper is to bring together a strategic choice perspective and an institutional perspective in order to address the key research questions: how do Russian founder-CEOs perceive the institutional environment when succession issues are taken into consideration?; how do the perceived characteristics of different formal and informal institutions affect the founder-CEO’s decision to delegate authority to a professional CEO?; and what are the main barriers to founder-CEO succession in threshold firms in emerging markets such as Russia? Design/methodology/approach – Using a data set of 500 entrepreneurial companies from fast growing industries in Russia, the paper defines and studies threshold firms and analyses how various perceived characteristics of the institutional environment in emerging markets influence the likelihood of transition from founder management to professional management. Findings – Institutional factors such as poor security of property rights and dependence of the business on relationships with government officials have a negative impact on the likelihood of founder-CEO succession in threshold firms in emerging markets. At the same time, the perception of contract law as insecure increases the likelihood of transition from founder management to professional management. Originality/value – Most research on initial succession deals with internal organisational factors and does not consider external environments and their influence on founder-CEO departure and willingness to exit from company management. This study is unique in its focus on the external environment and institutional factors and their impact on management transitions in threshold firms in emerging economies.

scholarly journals Validation of Predictive Models for Autoimmune Encephalitis-Related Antibodies to Cell-Surface Proteins Expressed in Neurons: A Retrospective Study Based in a Hospital

2021 ◽  
Vol 12 ◽  
Author(s):  
Siqi Ding ◽  
Jiaoni Gong ◽  
Jiahe Lin ◽  
Yi Wang ◽  
Yingjie Hua ◽  
...  
Keyword(s):  
Cell Surface ◽  
Predictive Model ◽  
Predictive Models ◽  
Area Under The Curve ◽  
Autoimmune Encephalitis ◽  
Autoimmune Disorder ◽  
Surface Proteins ◽  
Cutoff Score ◽  
Cell Surface Proteins ◽  
The Mean

Objective: Autoimmune encephalitis (AE) is a severe but treatable autoimmune disorder that is diagnosed by antibody (Ab) testing. However, it is unrealistic to obtain an early diagnosis in some areas since the Ab status cannot be immediately determined due to time and technology restrictions. In our study, we aimed to validate the Antibody Prevalence in Epilepsy and Encephalopathy (APE2) score among patients diagnosed with possible AE as a predictive model to screen AE patients with antibodies to cell-surface proteins expressed in neurons.Methods: A total of 180 inpatients were recruited, and antibodies were detected through serological and/or cerebrospinal fluid (CSF) evaluations. The APE2 score was used to validate the predictive models of AE with autoantibodies.Results: The mean APE2 score in the Ab-positive cases was 7.25, whereas the mean APE2 score in the Ab-negative cases was 3.18 (P < 0.001). The APE2 score had a receiver operating characteristic (ROC) area under the curve of 0.924 [P < 0.0001, 95% confidence interval (CI) = 0.875–0.973]. With a cutoff score of 5, the APE2 score had the best psychometric properties, with a sensitivity of 0.875 and a specificity of 0.791.Conclusion: The APE2 score is a predictive model for AE with autoantibodies to cell-surface proteins expressed in neurons and was validated and shown to have high sensitivity and specificity in our study. We suggest that such a model should be used in patients with a suspected diagnosis of AE, which could increase the detection rate of Abs, reduce testing costs, and help patients to benefit from treatment quickly.

Dispersion beyond miles: configuration and performance in virtual teams

2017 ◽  
Vol 23 (3) ◽  
pp. 186-204 ◽  
Author(s):  
Ambika Prasad ◽  
Darleen DeRosa ◽  
Michael Beyerlein
Keyword(s):  
Virtual Teams ◽  
Team Performance ◽  
Electronic Communication ◽  
Negative Impact ◽  
Spatial Distance ◽  
Future Research ◽  
Data Set ◽  
Content Type ◽  
And Performance ◽  
The Impact

Purpose The purpose of this paper is to understand different aspects of structural dispersion in virtual teams (VTs). The study measures five types of dispersion, their impact on VT performance and the moderating effect of electronic communication. Design/methodology/approach The authors collected data from 44 globally distributed VTs representing 403 members. The authors used details of the members’ locations to measure five elements of dispersion for each team: spatial, time-zone, number of locations, extent of numerical balance across locations and extent of isolated members for a team. The authors used two items to assess effective electronic communication and measured team performance on four items from three sources – members, leaders and third-party stakeholders. Findings Using regression, the authors found that the number of sites, degree of team balance and isolation had a negative impact on team performance. Spatial and temporal dispersion did not impact performance. Effective electronic communication moderated the relationship of team performance with team balance and the number of sites. Research limitations/implications Study presents novel findings on the role of team configuration in VTs. Limitations: the study provides pointers to the likelihood of a non-linear relationship between spatial distance and performance; however, the scope of the paper does not permit an examination of this model. Future research can study this relationship. Second, the study does not examine how team configuration impacts the team processes that discount performance. Finally, the study treats each index of dispersion as independent of the others. The analysis does not study the interplay between and among the indices. Practical implications The findings provide clear indicators for managers and researchers of VTs on the issues associated with the location and configuration of the teams. Managers, while designing and managing dispersed members are now informed of the impact of the number of sites and the sub-group dynamics. The study underscores the importance of effective electronic communication in managing dispersion. Social implications The study presents how faultiness based on location of VT sub-groups (as represented in the configuration of a team) can hamper performance. Literature suggests that this faultiness can also extend to social identities (based on gender, culture, etc.). The indicators provided by this study in this respect provide a topical focus for research because diverse dispersed teams are becoming more prevalent. Originality/value The study is the first empirical exploration of dispersion in VTs beyond the traditionally acknowledged dimensions of spatial distance and time-zones. It is a timely response to the recent trends in literature. Additionally, the study derives data from a unique data set of global VTs, thus making findings easily generalizable.

Temporary contracts, participation in decision making and job satisfaction in European workers

2017 ◽  
Vol 38 (6) ◽  
pp. 875-892 ◽  
Author(s):  
Salomé Goñi-Legaz ◽  
Andrea Ollo-López
Keyword(s):  
Job Satisfaction ◽  
Decision Making ◽  
Negative Impact ◽  
Secondary Data ◽  
Temporary Workers ◽  
Data Set ◽  
Content Type ◽  
Temporary Contracts ◽  
Temporary Contract ◽  
Participation In Decision Making

Purpose The purpose of this paper is to establish to what extent temporary contract and participation in decision making impact on employees job satisfaction and to propose a model whereby participation in decision making mitigates against the negative impact that temporary work has on job satisfaction. Design/methodology/approach The authors use data for a representative sample of 14,778 employees in 23 European countries. In order to test the hypotheses, the authors use regression models and the Chow test. Findings The results show that while temporary contracts decreases job satisfaction, participation in decision making increases it. However, autonomous teams, job autonomy, and job involvement buffer against the negative effect that temporary contract has on job satisfaction. Research limitations/implications The use of secondary data and the non-longitudinal nature of the data set. Practical implications The effect of participation in decision making in job satisfaction is greater for temporary workers than for permanents. Participation in decision making should not be restricted to permanent workers. Originality/value Participation in decision making and temporary contracts has been considered incompatible practices. The paper contributes to enrich the understanding of the relationship between these practices and job satisfaction. Sample representatives support the results obtained.

Key variables to predict tie strength on social network sites

2015 ◽  
Vol 25 (2) ◽  
pp. 218-238 ◽  
Author(s):  
Pin Luarn ◽  
Yu-Ping Chiu
Keyword(s):  
Social Network ◽  
Predictive Model ◽  
Social Network Sites ◽  
Theory And Practice ◽  
Tie Strength ◽  
Online Questionnaire ◽  
Design Of Algorithms ◽  
Data Set ◽  
Subjective Data ◽  
Content Type

Purpose – The purpose of this paper is to predict tie strength using profile similarities and interaction data between users, and thus distinguish between strong and weak relationships on social network sites (SNSs). Design/methodology/approach – This study developed a program and an online questionnaire to collect the data set from Facebook, and then integrated that data set with a subjective data set consisting of participants’ opinions of the strength of their friendships on Facebook. The model developed here for predicting tie strength performed well when was applied on a data set of 6,477 SNSs’ ties, distinguishing between strong and weak ties with over 50 percent accuracy. Findings – The results developed an algorithm (predictive model) that quantifies and measures tie strength continuously to bridge the gap between theory and practice. The results found that the variables in the dimension of emotional intensity had stronger effects than other interaction variables. Originality/value – This study developed a predictive model that helps explain the meaning of interaction on SNSs, providing an efficient method to examine tie strength on SNSs. The tie strength estimates can also be used to improve the range and performance of various aspects of SNSs, including link predictions, product recommendations, newsfeeds, people searches, and visualization. Such understanding of the structure of SNSs might lead ultimately to the design of algorithms that can detect trusted or influential users of SNSs.

scholarly journals The factors that determine shopping centre rent in Wuhan, China

2016 ◽  
Vol 34 (2) ◽  
pp. 172-185 ◽  
Author(s):  
Qiulin Ke ◽  
Wencan Wang
Keyword(s):  
Negative Impact ◽  
Emerging Market ◽  
Central Area ◽  
Central China ◽  
Market Condition ◽  
Adjustment Process ◽  
Data Set ◽  
Content Type ◽  
Shopping Centres ◽  
The Impact

Purpose – The purpose of this paper is to investigate the factors that affect the retail rent of shopping centres in Wuhan, an important city in central China. Design/methodology/approach – The study uses a data set of 68 shopping centres in urban Wuhan. A regression model is constructed to estimate the impact on retail rent of a composite range of variables that would capture the physical characteristics, spatial characteristics, potential attractiveness of shopping centres and market condition. Findings – The empirical findings suggest the ceiling height, closeness to metro line station, being situated in commercial central area, vacancy rate and income have significant impact on rental level. Unexpected, the retail mix has a significant negative impact on rent. The impact of the more determining factors found in Western research – size, age, parking space and anchor tenant – is not supported in the Wuhan study. Practical implications – While 68 shopping centres are included in the test, the sample size is relatively small. The comparatively short history of retail market in Wuhan would not allow to test the rent adjustment process. Originality/value – This is the first paper to investigate retail rent determinants in a second-tier city in China. The results of the study give designers, developers and investors critical insights into the determinants of retail rent in an emerging market.

Development of predictive models for effective process parameter selection for single and overlapping laser clad bead geometry

2018 ◽  
Vol 24 (1) ◽  
pp. 214-228 ◽  
Author(s):  
Kush Aggarwal ◽  
R.J. Urbanic ◽  
Syed Mohammad Saqib
Keyword(s):  
Data Collection ◽  
Predictive Model ◽  
Laser Cladding ◽  
Process Planning ◽  
Process Parameters ◽  
Predictive Models ◽  
Goodness Of Fit ◽  
Bead Geometry ◽  
Content Type ◽  
Non Linear

Purpose The purpose of this work is to explore predictive model approaches for selecting laser cladding process settings for a desired bead geometry/overlap strategy. Complementing the modelling challenges is the development of a framework and methodologies to minimize data collection while maximizing the goodness of fit for the predictive models. This is essential for developing a foundation for metallic additive manufacturing process planning solutions. Design/methodology/approach Using the coaxial powder flow laser cladding method, 420 steel cladding powder is deposited on low carbon structural steel plates. A design of experiments (DOE) approach is taken using the response surface methodology (RSM) to establish the experimental configuration. The five process parameters such as laser power, travel speed, etc. are varied to explore their impact on the bead geometry. A total of three replicate experiments are performed and the collected data are assessed using a variety of methods to determine the process trends and the best modelling approaches. Findings There exist unpredictable, non-linear relationships between the process parameters and the bead geometry. The best fit for a predictive model is achieved with the artificial neural network (ANN) approach. Using the RSM, the experimental set is reduced by an order of magnitude; however, a model with R2 = 0.96 is generated with ANN. The predictive model goodness of fit for a single bead is similar to that for the overlapping bead geometry using ANN. Originality/value Developing a bead shape to process parameters model is challenging due to the non-linear coupling between the process parameters and the bead geometry and the number of parameters to be considered. The experimental design and modelling approaches presented in this work illustrate how designed experiments can minimize the data collection and produce a robust predictive model. The output of this work will provide a solid foundation for process planning operations.

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