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Open Access
Article
Publication date: 22 November 2022

Kedong Yin, Yun Cao, Shiwei Zhou and Xinman Lv

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems…

Abstract

Purpose

The purposes of this research are to study the theory and method of multi-attribute index system design and establish a set of systematic, standardized, scientific index systems for the design optimization and inspection process. The research may form the basis for a rational, comprehensive evaluation and provide the most effective way of improving the quality of management decision-making. It is of practical significance to improve the rationality and reliability of the index system and provide standardized, scientific reference standards and theoretical guidance for the design and construction of the index system.

Design/methodology/approach

Using modern methods such as complex networks and machine learning, a system for the quality diagnosis of index data and the classification and stratification of index systems is designed. This guarantees the quality of the index data, realizes the scientific classification and stratification of the index system, reduces the subjectivity and randomness of the design of the index system, enhances its objectivity and rationality and lays a solid foundation for the optimal design of the index system.

Findings

Based on the ideas of statistics, system theory, machine learning and data mining, the focus in the present research is on “data quality diagnosis” and “index classification and stratification” and clarifying the classification standards and data quality characteristics of index data; a data-quality diagnosis system of “data review – data cleaning – data conversion – data inspection” is established. Using a decision tree, explanatory structural model, cluster analysis, K-means clustering and other methods, classification and hierarchical method system of indicators is designed to reduce the redundancy of indicator data and improve the quality of the data used. Finally, the scientific and standardized classification and hierarchical design of the index system can be realized.

Originality/value

The innovative contributions and research value of the paper are reflected in three aspects. First, a method system for index data quality diagnosis is designed, and multi-source data fusion technology is adopted to ensure the quality of multi-source, heterogeneous and mixed-frequency data of the index system. The second is to design a systematic quality-inspection process for missing data based on the systematic thinking of the whole and the individual. Aiming at the accuracy, reliability, and feasibility of the patched data, a quality-inspection method of patched data based on inversion thought and a unified representation method of data fusion based on a tensor model are proposed. The third is to use the modern method of unsupervised learning to classify and stratify the index system, which reduces the subjectivity and randomness of the design of the index system and enhances its objectivity and rationality.

Details

Marine Economics and Management, vol. 5 no. 2
Type: Research Article
ISSN: 2516-158X

Keywords

Article
Publication date: 15 December 2020

Yu-Hsiang Hsiao and Yu-Ting Hsiao

This study was to develop a methodology of online review analytics for hotel quality management at macro and micro levels. The macro level was for understanding the service…

Abstract

Purpose

This study was to develop a methodology of online review analytics for hotel quality management at macro and micro levels. The macro level was for understanding the service properties critical to quality and future development. The micro level was for personalized quality diagnosis for individual hotels.

Design/methodology/approach

Textual reviews of superior hotels were studied using latent semantic analysis and Kano model to understand what service properties customers concern and expect. Taguchi's quality engineering was applied to establish a quality reference base using superior hotels for evaluating other hotels in the same semantic space. A decision tree algorithm was then used to identify the properties critical to quality discrimination, and the decision rules were used to diagnose individual hotels.

Findings

The service properties concerned by customers for superior hotels were identified. The market positioning and value of each property to customers were clarified. For individual hotels, the deficiencies of service properties were diagnosed. With reference to market positioning, deficient properties of priority in improvement and the strategies for enhancing competitiveness were suggested.

Originality/value

The proposed methodology demonstrated the potential value that review analysis can achieve a new and deeper understanding of customer voices and transform it into more specific business operation requirements. The research and application gap that most previous studies only stayed at the macro-level analytics was filled. Moreover, this study effectively applied the diagnostic techniques derived from quality engineering to online review analytics.

Details

Industrial Management & Data Systems, vol. 121 no. 2
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 26 July 2011

Khairy A.H. Kobbacy and Sunil Vadera

The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing…

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Abstract

Purpose

The use of AI for operations management, with its ability to evolve solutions, handle uncertainty and perform optimisation continues to be a major field of research. The growing body of publications over the last two decades means that it can be difficult to keep track of what has been done previously, what has worked, and what really needs to be addressed. Hence, the purpose of this paper is to present a survey of the use of AI in operations management aimed at presenting the key research themes, trends and directions of research.

Design/methodology/approach

The paper builds upon our previous survey of this field which was carried out for the ten‐year period 1995‐2004. Like the previous survey, it uses Elsevier's Science Direct database as a source. The framework and methodology adopted for the survey is kept as similar as possible to enable continuity and comparison of trends. Thus, the application categories adopted are: design; scheduling; process planning and control; and quality, maintenance and fault diagnosis. Research on utilising neural networks, case‐based reasoning (CBR), fuzzy logic (FL), knowledge‐Based systems (KBS), data mining, and hybrid AI in the four application areas are identified.

Findings

The survey categorises over 1,400 papers, identifying the uses of AI in the four categories of operations management and concludes with an analysis of the trends, gaps and directions for future research. The findings include: the trends for design and scheduling show a dramatic increase in the use of genetic algorithms since 2003 that reflect recognition of their success in these areas; there is a significant decline in research on use of KBS, reflecting their transition into practice; there is an increasing trend in the use of FL in quality, maintenance and fault diagnosis; and there are surprising gaps in the use of CBR and hybrid methods in operations management that offer opportunities for future research.

Originality/value

This is the largest and most comprehensive study to classify research on the use of AI in operations management to date. The survey and trends identified provide a useful reference point and directions for future research.

Details

Journal of Manufacturing Technology Management, vol. 22 no. 6
Type: Research Article
ISSN: 1741-038X

Keywords

Article
Publication date: 7 March 2022

Huiying Gao, Shan Lu and Xiaojin Kou

The purpose of this study is to identify medical service quality factors that patients care about and establish a medical service quality evaluation index system by analyzing…

Abstract

Purpose

The purpose of this study is to identify medical service quality factors that patients care about and establish a medical service quality evaluation index system by analyzing online reviews of medical and healthcare service platforms in combination with a questionnaire survey.

Design/methodology/approach

This study adopts a combination of review mining and questionnaire surveys. The latent Dirichlet allocation (LDA) model was used to mine hospital reviews on the medical and healthcare service platform to obtain the medical service quality factors that patients pay attention to, and then the questionnaire was administered to obtain the relative importance of these factors to patients' perception of service quality. Finally, the index system was established.

Findings

The medical service quality factors patients care about include medical skills and ethics, registration service, operation effect, consulting communication, drug therapy, diagnosis process and medical equipment.

Research limitations/implications

The identification of medical service quality factors provides a reference for medical institutions to improve their medical service quality.

Originality/value

This study uses online review mining to obtain medical service quality factors from the perspective of patients, which is different from previous methods of obtaining factors from relevant literature or expert judgments; then, based on the mining results, a medical service quality evaluation index system is established by using questionnaire data.

Details

Internet Research, vol. 32 no. 5
Type: Research Article
ISSN: 1066-2243

Keywords

Article
Publication date: 8 July 2020

Samuel Tromans and Verity Chester

The purpose of this paper is to provide a commentary on “being diagnosed with autism in adulthood: a personal case study”.

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Abstract

Purpose

The purpose of this paper is to provide a commentary on “being diagnosed with autism in adulthood: a personal case study”.

Design/methodology/approach

A commentary on an individual’s personal experiences of being referred to autism assessment services and subsequently receiving a diagnosis of autism in adulthood.

Findings

Many individuals are not diagnosed with autism until their adult life, and as a result, miss the benefits of timely introduction of sources of support, such as during their schooling. Receiving an autism diagnosis can come as a relief and promote self-understanding, but availability of high-quality post-diagnostic support services and accommodating employers are both highly important.

Originality/value

A commentary on an original viewpoint is published in this special edition on gender and diversity.

Details

Advances in Autism, vol. 7 no. 3
Type: Research Article
ISSN: 2056-3868

Keywords

Article
Publication date: 7 June 2023

Khalil Idrissi Gartoumi, Mohamed Aboussaleh and Smail Zaki

This paper aims to explore a framework for implementing Lean Construction (LC) to provide corrective actions for quality defects, customer dissatisfaction and value creation…

Abstract

Purpose

This paper aims to explore a framework for implementing Lean Construction (LC) to provide corrective actions for quality defects, customer dissatisfaction and value creation during the construction of megaprojects.

Design/methodology/approach

This paper presents a case study involving the construction of the Mohamed VI Tower in Morocco. It is the tallest tower in Africa, with 55 floors and a total height of 250 m. This study of the quality of the work and the involvement of the LC was carried out using the Define–Measure–Analysis–Improve–Control approach from Lean six sigma. It describes the Critical to Quality and analyses the root causes of quality defects, customer dissatisfaction and variation in the quality process.

Findings

Firstly, the results of this study map the causal factors of lack of quality as established in the literature. Secondly, the LC tools have reduced non-value-added sources of quality waste and, consequently, improved critical quality indicators.

Research limitations/implications

This document focuses on one part of the tower’s construction and is limited to a project case in a country where LC is rarely used.

Originality/value

This study reinforces the literature reviews, surveys and the small number of case studies that have validated the potential of LC and further clarifies future directions for the practical emergence of this quality improvement approach, especially for large-scale projects.

Details

Journal of Financial Management of Property and Construction , vol. 29 no. 1
Type: Research Article
ISSN: 1366-4387

Keywords

Article
Publication date: 31 October 2023

Yangze Liang and Zhao Xu

Monitoring of the quality of precast concrete (PC) components is crucial for the success of prefabricated construction projects. Currently, quality monitoring of PC components…

Abstract

Purpose

Monitoring of the quality of precast concrete (PC) components is crucial for the success of prefabricated construction projects. Currently, quality monitoring of PC components during the construction phase is predominantly done manually, resulting in low efficiency and hindering the progress of intelligent construction. This paper presents an intelligent inspection method for assessing the appearance quality of PC components, utilizing an enhanced you look only once (YOLO) model and multi-source data. The aim of this research is to achieve automated management of the appearance quality of precast components in the prefabricated construction process through digital means.

Design/methodology/approach

The paper begins by establishing an improved YOLO model and an image dataset for evaluating appearance quality. Through object detection in the images, a preliminary and efficient assessment of the precast components' appearance quality is achieved. Moreover, the detection results are mapped onto the point cloud for high-precision quality inspection. In the case of precast components with quality defects, precise quality inspection is conducted by combining the three-dimensional model data obtained from forward design conversion with the captured point cloud data through registration. Additionally, the paper proposes a framework for an automated inspection platform dedicated to assessing appearance quality in prefabricated buildings, encompassing the platform's hardware network.

Findings

The improved YOLO model achieved a best mean average precision of 85.02% on the VOC2007 dataset, surpassing the performance of most similar models. After targeted training, the model exhibits excellent recognition capabilities for the four common appearance quality defects. When mapped onto the point cloud, the accuracy of quality inspection based on point cloud data and forward design is within 0.1 mm. The appearance quality inspection platform enables feedback and optimization of quality issues.

Originality/value

The proposed method in this study enables high-precision, visualized and automated detection of the appearance quality of PC components. It effectively meets the demand for quality inspection of precast components on construction sites of prefabricated buildings, providing technological support for the development of intelligent construction. The design of the appearance quality inspection platform's logic and framework facilitates the integration of the method, laying the foundation for efficient quality management in the future.

Details

Engineering, Construction and Architectural Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 31 January 2022

Hye Young Roh, Shujaat Ali, Hojun Song and Wan Seon Shin

This study aims to investigate the criteria to measure and manage a software project’s quality indicator elements needed to implement system integration in the Industry 4.0 era.

Abstract

Purpose

This study aims to investigate the criteria to measure and manage a software project’s quality indicator elements needed to implement system integration in the Industry 4.0 era.

Design/methodology/approach

The standard software process model SPICE: a crucial part of the system integration software development process, is analyzed to explore how the factors of the SPICE model rate qualitatively on the quality scorecard (QSC). QSC is a qualitative performance measurement model based on the cost of quality (COQ) perspective. The SPICE model’s effectiveness is examined in terms of system integration (SI) quality, and factors for improving this quality are determined.

Findings

The authors proposed future directions for improving SI management. The seven SPICE process groups were analyzed comparatively by matching them to the QSC. The SPICE model was found to achieve 63% with the required factors in QSC. Also, the uncommitted items indicated need to be considered for additional management in SI quality.

Practical implications

Since SPICE is revised every five years, it is suggested from this study that diagnosing the assessment items from the COQ perspective using QSC is one strategy to quickly enhance the quality of SI management in this rapidly changing technology revolution.

Originality/value

This research is the first study of its kind, proposing a methodology for adapting quickly to the Fourth Industrial Revolution’s changes and showing how the standards have changed the SPICE model over time.

Details

International Journal of Quality and Service Sciences, vol. 14 no. 2
Type: Research Article
ISSN: 1756-669X

Keywords

Article
Publication date: 21 March 2023

Tong Yang, Yanzhong Dang and Jiangning Wu

This paper aims to propose a method for dynamic product perceived quality analysis using social media data and to achieve a macro–micro combination analysis. The method enables…

Abstract

Purpose

This paper aims to propose a method for dynamic product perceived quality analysis using social media data and to achieve a macro–micro combination analysis. The method enables the prioritization of perceived quality attributes and provides perception causes.

Design/methodology/approach

To rationalize the macro–micro combination, ANOVA and multiple linear regression were used to identify the main factors affecting perceived quality which served as the combination basis; by using the combination basis for consumer segmentation, macro-knowledge (i.e. attribute importance and quality category of the attribute) is achieved by term frequency-inverse document frequency (TF-IDF)-based attribute importance calculation and KANO-based attribute classification, which is combined with micro-quality diagnostic information (i.e. perceived quality, perception causes and quality parameters). Further, dynamic perception Importance-Performance Analysis (IPA) is built to present the attribute priority and perception causes.

Findings

The framework was validated by the new energy vehicle (NEV) data of Autohome. The results show that price and purchase purpose are the most influential factors of perceived quality and that dynamic perception IPA can effectively prioritize attributes and mine perception causes.

Originality/value

This is one of the first studies to analyze dynamic perceived quality using social media data, which contributes to the research on perceived quality. The paper also contributes by achieving a combined macro–micro analysis of perceived quality. The method rationalizes the macro–micro combination by identifying the factors influencing perceived quality, which provides ideas for other studies using social media data.

Details

Industrial Management & Data Systems, vol. 123 no. 5
Type: Research Article
ISSN: 0263-5577

Keywords

Article
Publication date: 1 October 1988

IT IS TO BE hoped that by the time these words are being read the dispute over the Electricians' Union and the TUC will have been solved; and, we hope, with satisfaction to both…

Abstract

IT IS TO BE hoped that by the time these words are being read the dispute over the Electricians' Union and the TUC will have been solved; and, we hope, with satisfaction to both parties.

Details

Work Study, vol. 37 no. 10
Type: Research Article
ISSN: 0043-8022

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