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Open Access
Article
Publication date: 28 February 2022

Duncan Maxwell and Rachel Couper

Construction suffers from “peculiarities” that concern the temporary natures of the construction site, project teams and unique product design. Considering the digital…

1822

Abstract

Purpose

Construction suffers from “peculiarities” that concern the temporary natures of the construction site, project teams and unique product design. Considering the digital transformation of construction, new solutions are being investigated that can provide consistent data between changing projects. One such source of data manifests in the tracking of logistics activities across the supply chain. Construction logistics is traditionally considered a site management activity focused solely on the “back end” of projects, but an expanded logistics focus can unlock new avenues of improvement. This study aims to understand the requirements and benefits of such a consistent thread of data.

Design/methodology/approach

From a research project with one of Australia’s largest contracting companies, this paper details a series of construction tracking tests as an empirical case study in using Bluetooth low energy aware tracking technology to capture data across the manufacture, delivery and assembly of a cross-laminated timber structural prototyping project.

Findings

The findings affirm the tracking of expanded logistics data can improve back-end performance in subsequent projects while also demonstrating the opportunity to inform a project’s unique front-end design phase. The case study demonstrates that as the reliability, range and battery life of tracking technologies improve, their incorporation into a broader range of construction activities provides invaluable data for improvement across projects.

Originality/value

As a live case study, this research offers unique insights into the potential of construction tracking to close the data loop from final site assembly back to the early project design phase, thus driving continual improvement from a holistic perspective.

Details

Construction Innovation , vol. 23 no. 2
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 14 February 2023

Jeongbeom Hahm, Heedong Choi, Hirotaka Matsuoka, Jiyoung Kim and Kevin K. Byon

The purpose of this study was to identify existing users' acceptance of the multidimensional health and fitness features of wrist-worn wearable devices (WWDs) required for each…

Abstract

Purpose

The purpose of this study was to identify existing users' acceptance of the multidimensional health and fitness features of wrist-worn wearable devices (WWDs) required for each stage of physical activity (i.e. before, during and after) and examine the relationship between its acceptance (i.e. knowledge acquisition, perceived usefulness and perceived ease of use) and the actual use of its health and fitness attributes.

Design/methodology/approach

Both qualitative and quantitative approaches were taken to analyze the relationships. A focus group interview was conducted (N = 9) to design the research model, including the operationalized definition of the study constructs. A questionnaire survey was conducted with respondents in South Korea (N = 480). Partial least squares structural equation modeling via Smart PLS 3.0 was employed to test the hypotheses.

Findings

When users learned to use fitness functions and perceived them as useful for physical activity without causing any difficulty, they tended to use those functions more, which provided enhanced health benefits in the digitalized interactive environment of WWDs.

Originality/value

This research is one of the first to examine the relationship between the perceived user value of WWDs and their actual usage within a digitalized and interactive environment. The results are expected to offer theoretical insights into how well users accept the health and fitness components of WWDs. Practically, it will build awareness of what makes users adopt and use WWDs, helping practitioners design better health promotions and campaigns associated with WWDs.

Details

International Journal of Sports Marketing and Sponsorship, vol. 24 no. 2
Type: Research Article
ISSN: 1464-6668

Keywords

Open Access
Article
Publication date: 17 November 2023

Matthew Ikuabe, Clinton Aigbavboa and Ernest Kissi

In most developing countries, the delivery of construction project is still characterised by inefficiencies resulting from the use of outdated methods and techniques, which…

Abstract

Purpose

In most developing countries, the delivery of construction project is still characterised by inefficiencies resulting from the use of outdated methods and techniques, which retards project performance. Hence, the call for the implementation of innovative technologies such as humanoids in the execution of construction projects as it has been proven to be very effective in other sectors while improving productivity and quality of work. Consequently, this study looks at how humanoids can be used in the construction industry and what benefits they can bring.

Design/methodology/approach

The study employed a quantitative approach underpinned in post-positivist philosophical view using questionnaire as the instrument for data collection. The target respondents were construction professionals, and purposive sampling was used, while a response rate of 62.5% was gotten. The methods of data analysis were mean item score, standard deviation and one-sample t-test.

Findings

The findings revealed that humanoids can be used in progress tracking, auto-documentation and inspection and surveillance of tasks in construction activities. Also, the most important benefits of using humanoids in construction work were found to be shorter delivery times, fewer injuries and more accurate work.

Practical implications

The outcome of the study gives professionals and relevant stakeholders in construction and other interested parties' information about the areas where humanoids can be used and their benefits in construction.

Originality/value

The novelty of this study is that it is a pioneering study in South Africa on humanoids' usage in the construction industry. Also, it expands the existing borderline of the conservation of construction digitalisation for enhanced project execution.

Details

International Journal of Building Pathology and Adaptation, vol. 41 no. 6
Type: Research Article
ISSN: 2398-4708

Keywords

Article
Publication date: 16 August 2021

Shilpa Gite, Ketan Kotecha and Gheorghita Ghinea

This study aims to analyze driver risks in the driving environment. A complete analysis of context aware assistive driving techniques. Context awareness in assistive driving by…

279

Abstract

Purpose

This study aims to analyze driver risks in the driving environment. A complete analysis of context aware assistive driving techniques. Context awareness in assistive driving by probabilistic modeling techniques. Advanced techniques using Spatio-temporal techniques, computer vision and deep learning techniques.

Design/methodology/approach

Autonomous vehicles have been aimed to increase driver safety by introducing vehicle control from the driver to Advanced Driver Assistance Systems (ADAS). The core objective of these systems is to cut down on road accidents by helping the user in various ways. Early anticipation of a particular action would give a prior benefit to the driver to successfully handle the dangers on the road. In this paper, the advancements that have taken place in the use of multi-modal machine learning for assistive driving systems are surveyed. The aim is to help elucidate the recent progress and techniques in the field while also identifying the scope for further research and improvement. The authors take an overview of context-aware driver assistance systems that alert drivers in case of maneuvers by taking advantage of multi-modal human processing to better safety and drivability.

Findings

There has been a huge improvement and investment in ADAS being a key concept for road safety. In such applications, data is processed and information is extracted from multiple data sources, thus requiring training of machine learning algorithms in a multi-modal style. The domain is fast gaining traction owing to its applications across multiple disciplines with crucial gains.

Research limitations/implications

The research is focused on deep learning and computer vision-based techniques to generate a context for assistive driving and it would definitely adopt by the ADAS manufacturers.

Social implications

As context-aware assistive driving would work in real-time and it would save the lives of many drivers, pedestrians.

Originality/value

This paper provides an understanding of context-aware deep learning frameworks for assistive driving. The research is mainly focused on deep learning and computer vision-based techniques to generate a context for assistive driving. It incorporates the latest state-of-the-art techniques using suitable driving context and the driver is alerted. Many automobile manufacturing companies and researchers would refer to this study for their enhancements.

Details

International Journal of Pervasive Computing and Communications, vol. 19 no. 3
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 19 February 2024

Eiman Almheiri, Mostafa Al-Emran, Mohammed A. Al-Sharafi and Ibrahim Arpaci

The proliferation of smartwatches in the digital age has radically transformed health and fitness management, offering users a multitude of functionalities that extend beyond mere…

Abstract

Purpose

The proliferation of smartwatches in the digital age has radically transformed health and fitness management, offering users a multitude of functionalities that extend beyond mere physical activity tracking. While these modern wearables have empowered users with real-time data and personalized health insights, their environmental implications remain relatively unexplored despite a growing emphasis on sustainability. To bridge this gap, this study extends the UTAUT2 model with smartwatch features (mobility and availability) and perceived security to understand the drivers of smartwatch usage and its consequent impact on environmental sustainability.

Design/methodology/approach

The proposed theoretical model is evaluated based on data collected from 303 smartwatch users using a hybrid structural equation modeling–artificial neural network (SEM-ANN) approach.

Findings

The PLS-SEM results supported smartwatch features’ effect on performance and effort expectancy. The results also supported the role of performance expectancy, social influence, price value, habit and perceived security in smartwatch usage. The use of smartwatches was found to influence environmental sustainability significantly. However, the results did not support the association between effort expectancy, facilitating conditions and hedonic motivation with smartwatch use. The ANN results further complement these outcomes by showing that habit with a normalized importance of 100% is the most significant factor influencing smartwatch use.

Originality/value

Theoretically, this research broadens the UTAUT2 by introducing smartwatch features as external variables and environmental sustainability as a new outcome of technology use. On a practical level, the study offers insights for various stakeholders interested in smartwatch use and their environmental implications.

Details

Asia-Pacific Journal of Business Administration, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1757-4323

Keywords

Article
Publication date: 5 October 2022

H.P.M.N.L.B. Moragane, B.A.K.S. Perera, Asha Dulanjalie Palihakkara and Biyanka Ekanayake

Construction progress monitoring (CPM) is considered a difficult and tedious task in construction projects, which focuses on identifying discrepancies between the as-built product…

Abstract

Purpose

Construction progress monitoring (CPM) is considered a difficult and tedious task in construction projects, which focuses on identifying discrepancies between the as-built product and the as-planned design. Computer vision (CV) technology is applied to automate the CPM process. However, the synergy between the CV and CPM in literature and industry practice is lacking. This study aims to fulfil this research gap.

Design/methodology/approach

A Delphi qualitative approach was used in this study by conducting two interview rounds. The collected data was analysed using manual content analysis.

Findings

This study identified seven stages of CPM; data acquisition, information retrieval, verification, progress estimation and comparison, visualisation of the results and schedule updating. Factors such as higher accuracy in data, less labourious process, efficiency and near real-time access are some of the significant enablers in instigating CV for CPM. Major challenges identified were occlusions and lighting issues in the site images and lack of support from the management. The challenges can be easily overcome by implementing suitable strategies such as familiarisation of the workforce with CV technology and application of CV research for the construction industry to grow with the technology in line with other industries.

Originality/value

This study addresses the gap pertaining to the synergy between the CV in CPM literature and the industry practice. This research contributes by enabling the construction personnel to identify the shortcomings and the opportunities to apply automated technologies concerning each stage in the progress monitoring process.

Details

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

Keywords

Open Access
Article
Publication date: 1 August 2023

Sheila Siar

Measuring research’s policy influence is challenging, given the complexity of the policy process, the gradual nature of policy influence, and the time lag between research…

1691

Abstract

Purpose

Measuring research’s policy influence is challenging, given the complexity of the policy process, the gradual nature of policy influence, and the time lag between research investment and impact. This paper assesses measurement approaches and discusses their merits and applications to overcome various hurdles.

Design/methodology/approach

Relevant articles and studies were selected and analyzed. First, the research-policy interface was revisited to understand their link and how research influences policy making. Second, the most common approaches for measuring policy influence were reviewed based on their features, strengths, and limitations.

Findings

The three approaches reviewed — pyramid, influencing, and results chain — have their respective strengths. Thus, research organizations planning to design a program for monitoring and evaluation (M&E) of policy influence have to adopt the best possible features of each approach and develop a customized method depending on their objectives and overall M&E framework.

Originality/value

This paper fosters a deeper understanding of leveraging the three approaches.

Details

Public Administration and Policy, vol. 26 no. 2
Type: Research Article
ISSN: 1727-2645

Keywords

Book part
Publication date: 20 November 2023

Halah Nasseif

The use of technology in Saudi Arabian higher education is constantly evolving. With the support of the 2030 Saudi vision, many research studies have started covering learning…

Abstract

The use of technology in Saudi Arabian higher education is constantly evolving. With the support of the 2030 Saudi vision, many research studies have started covering learning analytics and Big Data in the Saudi Arabian higher education. Examining learning analytics in higher education institutions promise transforming the learning experience to maximize students' learning potential. With the thousands of students' transactions recorded in various learning management systems (LMS) in Saudi educational institutions, the need to explore and research learning analytics in Saudi Arabia has caught the interest of scholars and researchers regionally and internationally. This chapter explores a Saudi private university in Jeddah, Saudi Arabia, and examines its rich learning analytics and discovers the knowledge behind it. More than 300,000 records of LMS analytical data were collected from a consecutive 4-year historic data. Romero, Ventura, and Garcia (2008) educational data mining process was applied to collect and analyze the analytical reports. Statistical and trend analysis were applied to examine and interpret the collected data. The study has also collected lecturers' testimonies to support the collected analytical data. The study revealed a transformative pedagogy that impact course instructional design and students' engagement.

Article
Publication date: 22 July 2022

Bushan Mathavan, Ali Vafaei-Zadeh, Haniruzila Hanifah, T. Ramayah and Sherah Kurnia

This paper aims to investigate the key enablers and inhibitors that influence the intention to use fitness wearables using the value-based adoption model (VAM).

1144

Abstract

Purpose

This paper aims to investigate the key enablers and inhibitors that influence the intention to use fitness wearables using the value-based adoption model (VAM).

Design/methodology/approach

Data were collected using a structured online questionnaire from 323 respondents who had never used fitness wearables. A purposive sampling technique was used in this study. Smart PLS was employed to test the research framework and hypotheses using a two-step approach.

Findings

The findings support some of the hypotheses developed with R2 values of 0.622 for perceived value (PV) and 0.567 for intention to use fitness wearable. Perceived enjoyment, perceived social image and perceived usefulness had a positive effect on PV. In addition, health information sensitivity (HIS) was positively related to perceived privacy risk and health information accuracy was positively related to perceived usefulness. Surprisingly, this study did not find any significant relationship between perceived fee, perceived privacy risk, perceived health increase and perceived design aesthetics with PV.

Practical implications

This study's findings can help designers and manufacturers design fitness wearables by considering factors that users find valuable, thus satisfying consumers' needs.

Originality/value

This study tries to model behavioural intention of fitness wearable usage of individual users by using the VAM with the addition of two new antecedences, HSI and health information accuracy, to better explain the behaviour.

Details

Asia-Pacific Journal of Business Administration, vol. 16 no. 1
Type: Research Article
ISSN: 1757-4323

Keywords

Article
Publication date: 28 January 2022

Jiaqi Li, Guangyi Zhou, Dongfang Li, Mingyuan Zhang and Xuefeng Zhao

Recognizing every worker's working status instead of only describing the existing construction activities in static images or videos as most computer vision-based approaches do;…

Abstract

Purpose

Recognizing every worker's working status instead of only describing the existing construction activities in static images or videos as most computer vision-based approaches do; identifying workers and their activities simultaneously; establishing a connection between workers and their behaviors.

Design/methodology/approach

Taking a reinforcement processing area as a research case, a new method for recognizing each different worker's activity through the position relationship of objects detected by Faster R-CNN is proposed. Firstly, based on four workers and four kinds of high-frequency activities, a Faster R-CNN model is trained. Then, by inputting the video into the model, with the coordinate of the boxes at each moment, the status of each worker can be judged.

Findings

The Faster R-CNN detector shows a satisfying performance with an mAP of 0.9654; with the detected boxes, a connection between the workers and activities is established; Through this connection, the average accuracy of activity recognition reached 0.92; with the proposed method, the labor consumption of each worker can be viewed more intuitively on the visualization graphics.

Originality/value

With this proposed method, the visualization graphics generated will help managers to evaluate the labor consumption of each worker more intuitively. Furthermore, human resources can be allocated more efficiently according to the information obtained. It is especially suitable for some small construction scenarios, in which the recognition model can work for a long time after it is established. This is potentially beneficial for the healthy operation of the entire project, and can also have a positive indirect impact on structural health and safety.

Details

Engineering, Construction and Architectural Management, vol. 30 no. 4
Type: Research Article
ISSN: 0969-9988

Keywords

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