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Article
Publication date: 8 July 2019

Karim A. Iskandar, Awad S. Hanna and Wafik Lotfallah

Healthcare-sector projects are some of the most complex in modern practice due to their reliance on high-tech components and the level of precision they must maintain…

Abstract

Purpose

Healthcare-sector projects are some of the most complex in modern practice due to their reliance on high-tech components and the level of precision they must maintain. Existing literature in healthcare performance specifically is scarce, but there is a recent increasing trend in both healthcare construction and a corresponding trend in related literature. No previously existing study has derived weights (relative importance) of performance metric in an objective, data-based manner. The purpose of this paper is to present a newly developed mathematical model that derives these weights, free of subjectivity that is common in other literature.

Design/methodology/approach

This paper’s model considers 17 exceptional projects and 19 average projects, and reveals the weights (or relative importance) of ten performance metrics by comparing how projects relate to one another in terms of each metric individually. It solves an eigenvalue problem that maximizes the difference between average and exceptional project performances.

Findings

The most significant weight, i.e. the performance metric which has the greatest impact on healthcare project performance, was request for information per million dollars with a weight of 16.07 percent. Other highly weighted metrics included construction speed and schedule growth at 13.08 and 12.23 percent, respectively. Rework was the least significant metric at 3.61 percent, but not all metrics of quality had low ratings. Deficiency issues per million dollars was weighted at 11.61 percent, for example. All weights derived by the model in this paper were validated statistically to ensure their applicability as comparison and assessment tools.

Originality/value

There is no widely accepted measure of project performance specific to healthcare construction. This study’s contribution to the body of knowledge is its mathematical model which is a landmark effort to develop a single, objective, unified project performance index for healthcare construction. Furthermore, this unified score presents a user-friendly avenue for contractors to standardize their productivity tracking – a missing piece in the practices of many contractors.

Details

Engineering, Construction and Architectural Management, vol. 26 no. 9
Type: Research Article
ISSN: 0969-9988

Keywords

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Abstract

Details

The Banking Sector Under Financial Stability
Type: Book
ISBN: 978-1-78769-681-5

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Article
Publication date: 14 August 2020

Rajat Kumar Behera, Pradip Kumar Bala and Rashmi Jain

Any business that opts to adopt a recommender engine (RE) for various potential benefits must choose from the candidate solutions, by matching to the task of interest and…

Abstract

Purpose

Any business that opts to adopt a recommender engine (RE) for various potential benefits must choose from the candidate solutions, by matching to the task of interest and domain. The purpose of this paper is to choose RE that fits best from a set of candidate solutions using rule-based automated machine learning (ML) approach. The objective is to draw trustworthy conclusion, which results in brand building, and establishing a reliable relation with customers and undeniably to grow the business.

Design/methodology/approach

An experimental quantitative research method was conducted in which the ML model was evaluated with diversified performance metrics and five RE algorithms by combining offline evaluation on historical and simulated movie data set, and the online evaluation on business-alike near-real-time data set to uncover the best-fitting RE.

Findings

The rule-based automated evaluation of RE has changed the testing landscape, with the removal of longer duration of manual testing and not being comprehensive. It leads to minimal manual effort with high-quality results and can possibly bring a new revolution in the testing practice to start a service line “Machine Learning Testing as a service” (MLTaaS) and the possibility of integrating with DevOps that can specifically help agile team to ship a fail-safe RE evaluation product targeting SaaS (software as a service) or cloud deployment.

Research limitations/implications

A small data set was considered for A/B phase study and was captured for ten movies from three theaters operating in a single location in India, and simulation phase study was captured for two movies from three theaters operating from the same location in India. The research was limited to Bollywood and Ollywood movies for A/B phase, and Ollywood movies for simulation phase.

Practical implications

The best-fitting RE facilitates the business to make personalized recommendations, long-term customer loyalty forecasting, predicting the company's future performance, introducing customers to new products/services and shaping customer's future preferences and behaviors.

Originality/value

The proposed rule-based ML approach named “2-stage locking evaluation” is self-learned, automated by design and largely produces time-bound conclusive result and improved decision-making process. It is the first of a kind to examine the business domain and task of interest. In each stage of the evaluation, low-performer REs are excluded which leads to time-optimized and cost-optimized solution. Additionally, the combination of offline and online evaluation methods offer benefits, such as improved quality with self-learning algorithm, faster time to decision-making by significantly reducing manual efforts with end-to-end test coverage, cognitive aiding for early feedback and unattended evaluation and traceability by identifying the missing test metrics coverage.

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Article
Publication date: 1 August 1999

William McCluskey and Sarabjot Anand

Hybrid systems as the next generation of intelligent applications within the field of mass appraisal and valuation are investigated. Motivated by the obvious limitations…

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1685

Abstract

Hybrid systems as the next generation of intelligent applications within the field of mass appraisal and valuation are investigated. Motivated by the obvious limitations of paradigms that are being used in isolation or as stand‐alone techniques such as multiple regression analysis, artificial neural networks and expert systems. Clearly, there are distinct advantages in integrating two or more information processing systems that would address some of the discrete problems of individual techniques. Examines first, the strategic development of mass appraisal approaches which have traditionally been based on “stand‐alone” techniques; second, the potential application of an intelligent hybrid system. Highlights possible solutions by investigating various hybrid systems that may be developed incorporating a nearest neighbour algorithm (k‐NN). The enhancements are aimed at two major deficiencies in traditional distance metrics; user dependence for attribute weights and biases in the distance metric towards matching categorical variables in the retrieval of neighbours. Solutions include statistical techniques: mean, coefficient of variation and significant mean. Data mining paradigms based on a loosely coupled neural network or alternatively a tight coupling with genetic algorithms are used to discover attribute weights. The hybrid architectures developed are applied to a property data set and their performance measured based on their predictive value as well as perspicuity. Concludes by considering the application and the relevance of these techniques within the field of computer assisted mass appraisal.

Details

Journal of Property Investment & Finance, vol. 17 no. 3
Type: Research Article
ISSN: 1463-578X

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Article
Publication date: 10 August 2021

Dan Wu, Hao Xu, Wang Yongyi and Huining Zhu

Currently, countries worldwide are struggling with the virus COVID-19 and the severe outbreak it brings. To better benefit from open government health data in the fight…

Abstract

Purpose

Currently, countries worldwide are struggling with the virus COVID-19 and the severe outbreak it brings. To better benefit from open government health data in the fight against this pandemic, this study developed a framework for assessing open government health data at the dataset level, providing a tool to evaluate current open government health data's quality and usability COVID-19.

Design/methodology/approach

Based on the review of the existing quality evaluation methods of open government data, the evaluation metrics and their weights were determined by 15 experts in health through the Delphi method and analytic hierarchy process. The authors tested the framework's applicability using open government health data related to COVID-19 in the US, EU and China.

Findings

The results of the test capture the quality difference of the current open government health data. At present, the open government health data in the US, EU and China lacks the necessary metadata. Besides, the number, richness of content and timeliness of open datasets need to be improved.

Originality/value

Unlike the existing open government data quality measurement, this study proposes a more targeted open government data quality evaluation framework that measures open government health data quality on a range of data quality dimensions with a fine-grained measurement approach. This provides a tool for accurate assessment of public health data for correct decision-making and assessment during a pandemic.

Details

Library Hi Tech, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0737-8831

Keywords

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Article
Publication date: 22 February 2013

Hank C. Alewine and Dan N. Stone

Environmental consequences increasingly influence management strategy and choice. The purpose of this paper is to investigate the effects on attention and investment of…

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4183

Abstract

Purpose

Environmental consequences increasingly influence management strategy and choice. The purpose of this paper is to investigate the effects on attention and investment of: incorporating environmental data into a balanced scorecard (BSC), called the sustainability balanced score card (SBSC) and the organization of environmental accounting information.

Design/methodology/approach

In a between‐participant design, participants (n ≈ 95) chose from among two investments using BSCs. Participants were randomly assigned to one of three conditions: no environmental data (control or BSC condition); environmental data embedded within the traditional BSC (four‐perspective SBSC); or environmental data added to a BSC as a standalone fifth perspective (five‐perspective SBSC).

Findings

Investment to achieve environmental stewardship objectives was greater with the four‐perspective SBSC than the traditional BSC. In addition, participants were most efficient, i.e. spent the least total time, and least time per data element examined, with the four‐perspective SBSC. Finally, the time spent examining, and decision weight given to, environmental data were unrelated.

Research limitations/implications

Professional managers and accountants may have greater knowledge of environmental metrics than do students, who are the participants in this study; hence, the results may not generalize to higher knowledgeable professionals since their processing of environmental data may differ from the lower knowledge participants of this study.

Practical implications

The form (i.e. organization) of environmental accounting data changed the allocation of participants' attention while the presence of environmental accounting data changed participants' investments; hence, both the presence and form of environmental accounting information influenced decision making.

Originality/value

This study is among the first to show differing influences from both the presence and organization of environmental accounting data on attention and investment.

Details

International Journal of Accounting & Information Management, vol. 21 no. 1
Type: Research Article
ISSN: 1834-7649

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Article
Publication date: 3 February 2012

Joel H. Helquist, Amit Deokar, Jordan J. Cox and Alyssa Walker

The purpose of this paper is to propose virtual process simulation as a technique for identifying and analyzing uncertainty in processes. Uncertainty is composed of both…

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1213

Abstract

Purpose

The purpose of this paper is to propose virtual process simulation as a technique for identifying and analyzing uncertainty in processes. Uncertainty is composed of both risks and opportunities.

Design/methodology/approach

Virtual process simulation involves the creation of graphical models representing the process of interest and associated tasks. Graphical models representing the resources (e.g. people, facilities, tools, etc.) are also created. The members of the resources graphical models are assigned to process tasks in all possible combinations. Secondary calculi, representing uncertainty, are imposed upon these models to determine scores. From the scores, changes in process structure or resource allocation can be used to manage uncertainty.

Findings

The example illustrates the benefits of utilizing virtual process simulation in process pre‐planning. Process pre‐planning can be used as part of strategic or operational uncertainty management.

Practical implications

This paper presents an approach to clarify and assess uncertainty in new processes. This modeling technique enables the quantification of measures and metrics to assist in systematic uncertainty analysis. Virtual process simulation affords process designers the ability to more thoroughly examine uncertainty while planning processes.

Originality/value

This research contributes to the study of uncertainty management by promoting a systematic approach that quantifies metrics and measures according to the objectives of a given process.

Details

Business Process Management Journal, vol. 18 no. 1
Type: Research Article
ISSN: 1463-7154

Keywords

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Article
Publication date: 9 August 2013

Yanjun Zuo and Brajendra Panda

This paper aims to develop a framework for object trust evaluation and related object trust principles to facilitate knowledge management in a virtual organization. It

Abstract

Purpose

This paper aims to develop a framework for object trust evaluation and related object trust principles to facilitate knowledge management in a virtual organization. It proposes systematic methods to quantify the trust of an object and defines the concept of object trust management. The study aims to expand the domain of subject trust to object trust evaluation in terms of whether an object is correct and accurate in expressing a topic or issue and whether the object is secure and safe to execute (in the case of an executable program). By providing theoretical and empirical insights about object trust composition and combination, this research facilitates better knowledge identification, creation, evaluation, and distribution.

Design/methodology/approach

This paper presents two object trust principles – trust composition and trust combination. These principles provide formal methodologies and guidelines to assess whether an object has the required level of quality and security features (hence it is trustworthy). The paper uses a component‐based approach to evaluate the quality and security of an object. Formal approaches and algorithms have been developed to assess the trustworthiness of an object in different cases.

Findings

The paper provides qualitative and quantitative analysis about how object trust can be composed and combined. Novel mechanisms have been developed to help users evaluate the quality and security features of available objects.

Originality/value

This effort fulfills an identified need to address the challenging issue of evaluating the trustworthiness of an object (e.g. a software program, a file, or other type of knowledge element) in a loosely‐coupled system such as a virtual organization. It is the first of its kind to formally define object trust management and study object trust evaluation.

Details

VINE, vol. 43 no. 3
Type: Research Article
ISSN: 0305-5728

Keywords

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Article
Publication date: 15 March 2011

Casey C. Bennett

The aim of this study was to evaluate the effects of a data‐driven clinical productivity system that leverages Electronic Health Record (EHR) data to provide productivity…

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1125

Abstract

Purpose

The aim of this study was to evaluate the effects of a data‐driven clinical productivity system that leverages Electronic Health Record (EHR) data to provide productivity decision support functionality in a real‐world clinical setting. The system was implemented for a large behavioral health care provider seeing over 75,000 distinct clients a year.

Design/methodology/approach

The key metric in this system is a “VPU”, which simultaneously optimizes multiple aspects of clinical care. The resulting mathematical value of clinical productivity was hypothesized to tightly link the organization's performance to its expectations and, through transparency and decision support tools at the clinician level, affect significant changes in productivity, quality, and consistency relative to traditional models of clinical productivity.

Findings

In only three months, every single variable integrated into the VPU system showed significant improvement, including a 30 percent rise in revenue, 10 percent rise in clinical percentage, a 25 percent rise in treatment plan completion, a 20 percent rise in case rate eligibility, along with similar improvements in compliance/audit issues, outcomes collection, access, etc.

Practical implications

A data‐driven clinical productivity system employing decision support functionality is effective, because of the impact on clinician behavior relative to traditional clinical productivity systems. Critically, the model is also extensible to integration with outcomes‐based productivity.

Originality/value

EHR's are only a first step – the problem is turning that data into useful information. Technology can leverage the data in order to produce actionable information that can inform clinical practice and decision‐making. Without additional technology, EHR's are essentially just copies of paper‐based records stored in electronic form.

Details

International Journal of Productivity and Performance Management, vol. 60 no. 3
Type: Research Article
ISSN: 1741-0401

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Article
Publication date: 11 March 2021

Camelia Delcea, Liviu-Adrian Cotfas, R. John Milne, Naiming Xie and Rafał Mierzwiak

The airline industry has been significantly hit by the occurrence of the new coronavirus SARS-CoV-2, facing one of its worst crises in history. In this context, the…

Abstract

Purpose

The airline industry has been significantly hit by the occurrence of the new coronavirus SARS-CoV-2, facing one of its worst crises in history. In this context, the present paper analyses one of the well-known boarding methods used in practice by the airlines before and during the coronavirus outbreak, namely back-to-front and suggests which variations of this method to use when three passenger boarding groups are considered and a jet bridge connects the airport terminal with the airplane.

Design/methodology/approach

Based on the importance accorded by the airlines to operational performance, health risks, and passengers' comfort, the variations in three passenger groups back-to-front boarding are divided into three clusters using the grey clustering approach offered by the grey systems theory.

Findings

Having the clusters based on the selected metrics and considering the social distance among the passengers, airlines can better understand how the variations in back-to-front perform in the new conditions imposed by the novel coronavirus and choose the boarding approach that better fits its policy and goals.

Originality/value

The paper combines the advantages offered by grey clustering and agent-based modelling for offering to determine which are the best configurations that offer a reduced boarding time, while accounting for reduced passengers' health risk, measured through three indicators: aisle risk, seat risk and type-3 seat interferences and for an increased comfort for the passengers manifested through a continuous walking flow while boarding.

Details

Grey Systems: Theory and Application, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2043-9377

Keywords

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