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1 – 10 of over 1000
Article
Publication date: 11 September 2023

Enayon Sunday Taiwo, Farzad Zaerpour, Mozart B.C. Menezes and Zhankun Sun

Overcrowding continues to afflict emergency departments (EDs), and its attendant consequences are becoming increasingly severe. The burden of the COVID-19 pandemic is further…

Abstract

Purpose

Overcrowding continues to afflict emergency departments (EDs), and its attendant consequences are becoming increasingly severe. The burden of the COVID-19 pandemic is further escalating the situation worldwide. One of the most critical questions is how to adequately quantify what constitutes overcrowding and determine implications for operations management in improving service efficiency. This paper aims to discuss the aforementioned.

Design/methodology/approach

The authors propose the time and class complexity measures for ED service systems, taking into account important patient-level and system characteristics. Using an extensive data set from a Canadian ED, the authors investigate the performance of complexity-based measures in predicting service delays.

Findings

The authors find that the complexity measure is potentially more important than some well-known crowding metrics. In particular, EDs can improve service efficiency by managing the level of complexity within a desirable interval. Furthermore, complexity exposes how the interplay between demand-side behavioral changes and supply-side responses affects operational performance. Moreover, the results suggest that arrival patterns—the number of patients of each class arriving per time and times between events (arrivals and service completions)—increase the risk of service delays more than the demand volume.

Originality/value

This paper is the first to provide an extensive investigation into the application of the complexity-based measure for ED crowding. The study demonstrates potential values to be gained in ED service systems if complexity measure is incorporated into their operations management decisions.

Details

International Journal of Operations & Production Management, vol. 44 no. 4
Type: Research Article
ISSN: 0144-3577

Keywords

Open Access
Article
Publication date: 23 February 2024

Emmadonata Carbone, Donata Mussolino and Riccardo Viganò

This study investigates the relationship between board gender diversity (BGD) and the time to Initial Public Offering (IPO), which stands as an entrepreneurially risky choice…

Abstract

Purpose

This study investigates the relationship between board gender diversity (BGD) and the time to Initial Public Offering (IPO), which stands as an entrepreneurially risky choice, particularly challenging in family firms. We also investigate the moderating role of family ownership dispersion (FOD).

Design/methodology/approach

We draw on an integrated theoretical framework bringing together the upper echelons theory and the socio-emotional wealth (SEW) perspective and on hand-collected data on a sample of Italian family IPOs that occurred in the period 2000–2020. We employ ordinary least squares (OLS) regression and alternative model estimations to test our hypotheses.

Findings

BGD positively affects the time to IPO, thus, it increases the time required to go public. FOD negatively moderates this relationship. Our findings remain robust with different measures for BGD, FOD, and family business definition as well as with different econometric models.

Originality/value

The article develops literature on family firms and IPO and it enriches the academic debate about gender and IPOs in family firms. It adds to studies addressing the determinants of the time to IPO by incorporating gender diversity and the FOD into the discussion. Finally, it contributes to research on women and outcomes in family firms.

Details

Management Decision, vol. 62 no. 13
Type: Research Article
ISSN: 0025-1747

Keywords

Article
Publication date: 7 February 2022

Bankole Osita Awuzie, Zwelinzima P. Mcwari, Progress Shingai Chigangacha, Clinton Ohis Aigbavboa, Theo C. Haupt and Lovelin Obi

An increase in outsourcing of consultancy services has been observed during procurement and delivery of public-sector infrastructure projects. However, the incidence of project…

Abstract

Purpose

An increase in outsourcing of consultancy services has been observed during procurement and delivery of public-sector infrastructure projects. However, the incidence of project failure has continued unabated despite this shift by public-sector entities. Also, there appears to be limited literature focussed on seeking to provide the rationale governing the decision to outsource or insource consultancy services by public-sector organisations. The purpose of this study was to appraise the performance of public-sector projects in which consultancy services have been outsourced or insourced. These are the gaps which this study was undertaken to fill.

Design/methodology/approach

A grounded theory methodology (GTM) research design was adopted based on the nature of evidence sought and gathered from a Provincial Department of Public Works and Infrastructure (PDPWI) in South Africa. Data was obtained from a mixture of semi-structured interviews and project-specific documents spanning a five-year period and was analysed according to the procedures associated with GTM. Accordingly, open coding, axial coding and pattern matching were carried out at several intervals to develop categories and themes.

Findings

The findings of the study showed the absence of a structured approach within the PDPWI for facilitating decisions pertaining to outsourcing or insourcing consultancy services within construction projects. Furthermore, the study established that both approaches yielded similar results across all performance facets of cost, time and quality. In addition, a detailed insight into the steps required for the successful application of GTM in built environment research has been provided in the study.

Originality/value

Limited studies have been undertaken to compare the impact of either outsourced or insourced services on the organisational and project performance. This was the gap to which the study reported in this paper was undertaken to contribute.

Details

Journal of Engineering, Design and Technology , vol. 22 no. 2
Type: Research Article
ISSN: 1726-0531

Keywords

Open Access
Article
Publication date: 18 May 2023

Anna Trubetskaya, Alan Ryan and Frank Murphy

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment…

4769

Abstract

Purpose

This paper aims to introduce a model using a digital twin concept in a cold heading manufacturing and develop a digital visual management (VM) system using Lean overall equipment effectiveness (OEE) tool to enhance the process performance and establish Fourth Industrial Revolution (I4.0) platform in small and medium enterprises (SMEs).

Design/methodology/approach

This work utilised plan, do, check, act Lean methodology to create a digital twin of each machine in a smart manufacturing facility by taking the Lean tool OEE and digitally transforming it in the context of I4.0. To demonstrate the effectiveness of process digitisation, a case study was carried out at a manufacturing department to provide the data to the model and later validate synergy between Lean and I4.0 platform.

Findings

The OEE parameter can be increased by 10% using a proposed digital twin model with the introduction of a Level 0 into VM platform to clearly define the purpose of each data point gathered further replicate in projects across the value stream.

Research limitations/implications

The findings suggest that researchers should look beyond conversion of stored data into visualisations and predictive analytics to improve the model connectivity. The development of strong big data analytics capabilities in SMEs can be achieved by shortening the time between data gathering and impact on the model performance.

Originality/value

The novelty of this study is the application of OEE Lean tool in the smart manufacturing sector to allow SME organisations to introduce digitalisation on the back of structured and streamlined principles with well-defined end goals to reach the optimal OEE.

Details

International Journal of Lean Six Sigma, vol. 15 no. 8
Type: Research Article
ISSN: 2040-4166

Keywords

Book part
Publication date: 4 April 2024

Ren-Raw Chen and Chu-Hua Kuei

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this…

Abstract

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

Details

Advances in Pacific Basin Business, Economics and Finance
Type: Book
ISBN: 978-1-83753-865-2

Keywords

Article
Publication date: 8 September 2022

Johnny Kwok Wai Wong, Mojtaba Maghrebi, Alireza Ahmadian Fard Fini, Mohammad Amin Alizadeh Golestani, Mahdi Ahmadnia and Michael Er

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes…

Abstract

Purpose

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

Design/methodology/approach

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

Findings

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

Originality/value

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

Details

Construction Innovation , vol. 24 no. 2
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 27 March 2024

Erfan Anjomshoa

Key performance indicators (KPIs) play a pivotal role in evaluating the level of success of an organization in achieving its business objectives. The objective of the current…

Abstract

Purpose

Key performance indicators (KPIs) play a pivotal role in evaluating the level of success of an organization in achieving its business objectives. The objective of the current research is to identify and prioritize effective KPIs in branding products and construction projects, which contribute to the success of construction companies in a competitive environment.

Design/methodology/approach

The present research is of an inferential, descriptive and survey nature. In this study, we identified the influential key performance indicators of construction companies in branding products and construction projects for success in a competitive environment through a literature review and expert opinions. The data were collected using a questionnaire, and a combination of the one-sample t-test method with a 95% confidence level and the fuzzy multiple attribute decision-making (FMADM) method was employed for analysis.

Findings

The results indicate that the most influential key performance indicators for construction companies in branding products and construction projects for success in a competitive environment are, in order of significance, the following indices: “Marketing and Advertising,” “Financial,” “Creativity,” “Technical and Operational” and “Social and Political.”

Originality/value

The present research examines the importance of branding construction products and projects for the success of construction companies by improving their business objectives and utilizing key performance indicators throughout the product lifecycle (production and construction). This study provides solutions on how construction companies can increase their competitive advantage through branding and achieve long-term success in the global construction industry.

Details

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

Keywords

Article
Publication date: 4 December 2023

Jin Lu, Mohammad Falahat and Phaik Kin Cheah

This study aimed to develop an in-depth understanding of the outcomes of servant leadership at the team and organizational levels. It reviews the relationship between servant…

Abstract

Purpose

This study aimed to develop an in-depth understanding of the outcomes of servant leadership at the team and organizational levels. It reviews the relationship between servant leadership and its team- and organizational-level outcomes, and examines the mediation and moderation effect of the relationship. It further identifies the mechanism by which servant leadership is beneficial to the organization.

Design/methodology/approach

A systematic literature review is conducted, focused on 52 articles published between 2012 and 2022. Content analysis and descriptive analysis were used to respond to the research questions.

Findings

A new conceptual model was developed to better understand the outcomes, mediators and moderators of servant leadership at team and organization level.

Research limitations/implications

Future research should further explore outcomes of servant leadership at team and organizational levels and test how mediators affect the relationship between servant leadership and associated outcomes.

Practical implications

This study provides a framework for leaders on how servant leadership contributes to teams and organizations, and how a leader applies servant leadership.

Originality/value

This systematic review presents a new model that builds on existing research into servant leadership and its impact on team and organizational levels completed in the past decade. To date, there have been no reviews of servant leadership that focus only on outcomes at the team and organizational levels using a widely recognized database.

Details

Journal of Organizational Change Management, vol. 37 no. 2
Type: Research Article
ISSN: 0953-4814

Keywords

Article
Publication date: 6 March 2024

Ruoxing Wang, Shoukun Wang, Junfeng Xue, Zhihua Chen and Jinge Si

This paper aims to investigate an autonomous obstacle-surmounting method based on a hybrid gait for the problem of crossing low-height obstacles autonomously by a six wheel-legged…

Abstract

Purpose

This paper aims to investigate an autonomous obstacle-surmounting method based on a hybrid gait for the problem of crossing low-height obstacles autonomously by a six wheel-legged robot. The autonomy of obstacle-surmounting is reflected in obstacle recognition based on multi-frame point cloud fusion.

Design/methodology/approach

In this paper, first, for the problem that the lidar on the robot cannot scan the point cloud of low-height obstacles, the lidar is driven to rotate by a 2D turntable to obtain the point cloud of low-height obstacles under the robot. Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping algorithm, fast ground segmentation algorithm and Euclidean clustering algorithm are used to recognize the point cloud of low-height obstacles and obtain low-height obstacle in-formation. Then, combined with the structural characteristics of the robot, the obstacle-surmounting action planning is carried out for two types of obstacle scenes. A segmented approach is used for action planning. Gait units are designed to describe each segment of the action. A gait matrix is used to describe the overall action. The paper also analyzes the stability and surmounting capability of the robot’s key pose and determines the robot’s surmounting capability and the value scheme of the surmounting control variables.

Findings

The experimental verification is carried out on the robot laboratory platform (BIT-6NAZA). The obstacle recognition method can accurately detect low-height obstacles. The robot can maintain a smooth posture to cross low-height obstacles, which verifies the feasibility of the adaptive obstacle-surmounting method.

Originality/value

The study can provide the theory and engineering foundation for the environmental perception of the unmanned platform. It provides environmental information to support follow-up work, for example, on the planning of obstacles and obstacles.

Details

Robotic Intelligence and Automation, vol. 44 no. 1
Type: Research Article
ISSN: 2754-6969

Keywords

Article
Publication date: 19 March 2024

Cemalettin Akdoğan, Tolga Özer and Yüksel Oğuz

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of…

Abstract

Purpose

Nowadays, food problems are likely to arise because of the increasing global population and decreasing arable land. Therefore, it is necessary to increase the yield of agricultural products. Pesticides can be used to improve agricultural land products. This study aims to make the spraying of cherry trees more effective and efficient with the designed artificial intelligence (AI)-based agricultural unmanned aerial vehicle (UAV).

Design/methodology/approach

Two approaches have been adopted for the AI-based detection of cherry trees: In approach 1, YOLOv5, YOLOv7 and YOLOv8 models are trained with 70, 100 and 150 epochs. In Approach 2, a new method is proposed to improve the performance metrics obtained in Approach 1. Gaussian, wavelet transform (WT) and Histogram Equalization (HE) preprocessing techniques were applied to the generated data set in Approach 2. The best-performing models in Approach 1 and Approach 2 were used in the real-time test application with the developed agricultural UAV.

Findings

In Approach 1, the best F1 score was 98% in 100 epochs with the YOLOv5s model. In Approach 2, the best F1 score and mAP values were obtained as 98.6% and 98.9% in 150 epochs, with the YOLOv5m model with an improvement of 0.6% in the F1 score. In real-time tests, the AI-based spraying drone system detected and sprayed cherry trees with an accuracy of 66% in Approach 1 and 77% in Approach 2. It was revealed that the use of pesticides could be reduced by 53% and the energy consumption of the spraying system by 47%.

Originality/value

An original data set was created by designing an agricultural drone to detect and spray cherry trees using AI. YOLOv5, YOLOv7 and YOLOv8 models were used to detect and classify cherry trees. The results of the performance metrics of the models are compared. In Approach 2, a method including HE, Gaussian and WT is proposed, and the performance metrics are improved. The effect of the proposed method in a real-time experimental application is thoroughly analyzed.

Details

Robotic Intelligence and Automation, vol. 44 no. 1
Type: Research Article
ISSN: 2754-6969

Keywords

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