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1 – 10 of 369
Article
Publication date: 26 March 2024

Hilary Omatule Onubi

The impact of mankind on the environment and the usage of natural resources might be influenced by spirituality, through the consciousness of creating an improved moral sense…

Abstract

Purpose

The impact of mankind on the environment and the usage of natural resources might be influenced by spirituality, through the consciousness of creating an improved moral sense regarding the consequences of human activities and the necessity to alter these to achieve sustainable development. However, the spiritual element in the form of ecospirituality (ES) has not been sufficiently considered in pro-environmental studies as it relates to the influence of green training (GT) on voluntary workplace green behaviour (VWGB) in the construction sector. This study aims to determine the effect of GT on VWGB and the mediating effect of ES on the relationship between GT and VWGB on construction projects.

Design/methodology/approach

This study’s data were gathered through a questionnaire survey of construction site managers and project managers by adopting the probability sampling method. 249 appropriately completed questionnaires were returned. The data obtained were analysed by means of the partial least squares structural equation modelling technique (PLS-SEM).

Findings

The outcomes of the study show that GT has a significant positive impact on VWGB, while ES has a significant mediating effect on the relationship between GT and VWGB, both supporting the study’s hypotheses.

Practical implications

These findings point to the fact that the hitherto conflicting results reported in earlier studies on the GT–VWGB relationship can be attributed to the lack of consideration given to ES. Hence, special attention should be given to ES.

Originality/value

This research presents actions to enhance the transformation of GT into VWGB by giving due consideration to ES, which was not taken into account in previous studies.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 31 August 2023

Albi Thomas and M. Suresh

This paper aims to “identify,” “analyse” and “categorise” the readiness factors of lean sustainability in health-care organisation using total interpretive structural modelling…

Abstract

Purpose

This paper aims to “identify,” “analyse” and “categorise” the readiness factors of lean sustainability in health-care organisation using total interpretive structural modelling (TISM).

Design/methodology/approach

To obtain the data, a closed-ended questionnaire was used in addition to a scheduled interview. To identify how the factors interact, the TISM approach was used, and the matriced’ impacts croise’s multiplication applique’e a UN classement (MICMAC) analysis was used to rank and categorise the lean sustainability readiness factors.

Findings

This study identified ten lean sustainability readiness factors for health-care organisation. The identified factors are resources utilization practice (F1), management commitment and leadership (F2), operational flexibility (F3), workforce engagement and time commitment (F4), sustainability motivational factors (F5), awareness of lean and sustainable practice (F6), hospital design (F7), energy efficiency practices in hospitals (F8), responsible autonomy (F9) and new system adoptability training (F10). The key/driving factors are identified in this study are operational flexibility, sustainability motivational factors, management commitment and leadership, new system adoptability training.

Research limitations/implications

The study focussed primarily on lean sustainability factors for the health-care sector.

Practical implications

This research will aid key stakeholders and academics in the better understanding the readiness factors that influence lean sustainability in health-care organisation. This study emphasises the factors that must be considered when applying lean sustainable practices in health care as a real-world application in a health-care organisation. These readiness factors for lean sustainability can be used by an organization to comprehend more about the concept and the components that contribute to health-care lean sustainability.

Originality/value

This study proposes the TISM technique for health care, which is a novel attempt in the subject of lean sustainability in this sector.

Details

International Journal of Pharmaceutical and Healthcare Marketing, vol. 18 no. 1
Type: Research Article
ISSN: 1750-6123

Keywords

Open Access
Article
Publication date: 2 February 2023

Azemeraw Tadesse Mengistu and Roberto Panizzolo

This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises…

2551

Abstract

Purpose

This paper aims to identify and empirically analyze useful and applicable metrics for measuring and managing the sustainability performance of small and medium-sized enterprises (SMEs).

Design/methodology/approach

To achieve the objective of the paper, potential metrics were adopted from previous research related to industrial sustainability and an empirical analysis was carried to assess the applicability of the metrics by collecting empirical data from Italian footwear SMEs using a structured questionnaire. The SMEs were selected using a convenience sampling method.

Findings

The results of the within-case analysis and the cross-case analysis indicate that the majority of the metrics were found to be useful and applicable to each of the SMEs and across the SMEs, respectively. These metrics emphasized measuring industrial sustainability performance related to financial benefits, costs and market competitiveness for the economic sustainability dimension; resources for the environmental sustainability dimension; and customers, employees and the community for the social sustainability dimension.

Research limitations/implications

Apart from the within-case analysis and cross-case analysis, it was not possible to conduct statistical analysis since a small number of SMEs were accessible to collect empirical data.

Originality/value

The findings of the paper have considerable academic, managerial and policy implications and will provide a theoretical basis for future research on measuring and managing industrial sustainability performance. By providing a set of empirically supported metrics based on the triple bottom line approach (i.e. economic, environmental and social metrics), this paper contributes to the existing knowledge in the field of industrial sustainability performance measurement.

Details

International Journal of Productivity and Performance Management, vol. 73 no. 11
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 1 April 2024

Armin Saadatian and Svetlana Olbina

The retail sector has the largest energy consumption among commercial buildings in the U.S. Although previous studies explored benefits, barriers and solutions for implementing…

Abstract

Purpose

The retail sector has the largest energy consumption among commercial buildings in the U.S. Although previous studies explored benefits, barriers and solutions for implementing sustainability in various building sectors, research focused on retail facilities has been very scarce. This study aims to explore U.S. facilities managers’ perceptions of barriers that prevented the implementation of energy-efficiency practices in the retail sector. Their perceptions were compared by facility size and facilities management company’s business revenue.

Design/methodology/approach

An online survey was distributed to the members of the International Facility Management Association and the author's LinkedIn network. The survey responses were analyzed using descriptive statistical analysis and ANOVA.

Findings

Managers from large facilities, as opposed to those from small ones, significantly more agreed that the unavailability of building automation systems, a lack of professional writing skills and a lack of awareness of life cycle cost (LCC) were the barriers. Business revenue did not cause significantly different perceptions of the barriers except for a lack of awareness of LCC and a lack of support from upper management.

Originality/value

This study fills the research gap on energy efficiency in the retail sector by revealing U.S. facilities managers’ perceptions of the barriers to the implementation of energy-efficiency practices in retail stores. This novel study compares perceptions of the facilities managers by facility size and business revenue; this comparison has not been performed before. The study also identified several new barriers to the implementation of energy efficiency in the retail sector.

Details

Facilities , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0263-2772

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

Article
Publication date: 28 July 2023

Somtochukwu Victor Okeke, Nabaz Nawzad Abdullah, Shaibu Mohammed Onakpa, Peter Nwokolo, Joel C. Ugwuoke, Ngozi Agujiobi-Odoh and Verlumun Celestine Gever

This study aims to assess the impact of visual multimedia in improving entrepreneurial competence and economic self-efficacy among widowed women farmers.

Abstract

Purpose

This study aims to assess the impact of visual multimedia in improving entrepreneurial competence and economic self-efficacy among widowed women farmers.

Design/methodology/approach

The participants received entrepreneurial training through visual multimedia package. The sample size was made up of 540 widowed women farmers. The entrepreneurship competence and economic self-efficacy scales were used as the instruments for data collection. The purpose of the entrepreneurial competence scale was to measure the mental competence of the participants to engage in entrepreneurial ventures. On the other hand, the economic self-efficacy scale measured the ability of the women to solve their financial problems, thus, meeting their financial needs. Both scales were administered face-to-face to the participants before, and after the training and during follow-up assessment after three years.

Findings

The result of the study showed that the women farmers reported low entrepreneurship competence and economic self-efficacy before the training. After the training, the women farmers who received the multimedia training reported an improvement, but those who did not receive the training did not show an improvement. A follow-up assessment after three years revealed stability in the improvement among women farmers who received the training. It was also indicated that interactive visual multimedia was found to be more effective than noninteractive visual multimedia.

Originality/value

This study has provided empirical evidence on how best to empower widowed women farmers by improving their entrepreneurial competence and economic self-efficacy. This information could be useful for policy formulation and advocacy in relation to women’s empowerment.

Details

Gender in Management: An International Journal , vol. 39 no. 2
Type: Research Article
ISSN: 1754-2413

Keywords

Open Access
Article
Publication date: 17 March 2023

Charlotta Winkler

This paper aims to explore the process of implementing solar photovoltaic (PV) systems in construction to contribute to the understanding of systemic innovation in construction.

Abstract

Purpose

This paper aims to explore the process of implementing solar photovoltaic (PV) systems in construction to contribute to the understanding of systemic innovation in construction.

Design/methodology/approach

The exploratory research presented is based on qualitative data collected in workshops and interviews with 76 construction- and solar-industry actors experienced in solar PV projects. Actor-specific barriers were identified and analysed using an abductive approach.

Findings

In light of established definitions of systemic innovation, the process of implementing solar PV systems in construction involves challenges regarding technical and material issues, competencies, and informal and formal institutions. The specificities of this case highlight the necessity of paying attention to details in the process and to develop knowledge of systemic innovation in construction since the industry’s involvement in addressing societal challenges related to the energy transition will require implementing such innovations much more in the future.

Practical implications

New knowledge of solar PV systems as an innovation in professional construction is collected, enabling the adaptation of management strategies for its implementation. This knowledge can also be applied generally to other challenges encountered in highly systemic innovation implementation. Solar industry actors can gain an understanding of solar-specific challenges for the construction industry, challenges for which they must adapt their activities.

Originality/value

The exploration of actor-specific experiences of solar PV projects has resulted in a novel understanding of this specific innovation and its implementation. The findings illustrate a case of a high level of systemic innovation and the need to use a finer-grained scale for classification when studying innovation in construction.

Details

Construction Innovation , vol. 24 no. 7
Type: Research Article
ISSN: 1471-4175

Keywords

Article
Publication date: 26 March 2024

Xichen Chen, Alice Yan Chang-Richards, Florence Yean Yng Ling, Tak Wing Yiu, Antony Pelosi and Nan Yang

Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This…

Abstract

Purpose

Despite extensive academic research related to digital technologies (DT), their integration into architecture, engineering and construction (AEC) projects lags in practice. This paper aims to discover DT deployment patterns and emerging trends in real-life AEC projects.

Design/methodology/approach

A case study methodology was adopted, including individual case analyses and comparative multiple-case analyses.

Findings

The results revealed the temporal distribution of DT in practical AEC projects, specific DT products/software, major project types integrated with digital solutions, DT application areas and project stages and associated project performance. Three distinct patterns in DT adoption have been observed, reflecting the evolution of DT applications, the progression from single to multiple DT integration and alignment with emerging industry requirements. The DT adoption behavior in the studied cases has been examined using the technology-organization-environment-human (TOE + H) framework. Further, eight emerging trend streams for future DT adoption were identified, with “leveraging the diverse features of certain mature DT” being a shared recognition of all studied companies.

Practical implications

This research offers actionable insights for AEC companies, facilitating the development of customized DT implementation roadmaps aligned with organizational needs. Policymakers, industry associations and DT suppliers may leverage these findings for informed decision-making, collaborative educational initiatives and product/service customization.

Originality/value

This research provides empirical evidence of applicable products/software, application areas and project performance. The examination of the TOE + H framework offers a holistic understanding of the collective influences on DT adoption. The identification of emerging trends addresses the evolving demands of the AEC industry in the digital era.

Details

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

Keywords

Article
Publication date: 9 October 2023

Felipe Alexandre de Lima, Stefan Seuring and Andrea Genovese

Operationalizing R-imperatives in firms is seen as vital to bolstering circularity through reduce, reuse and recycle and building circular supply chains (CSCs). However, this…

Abstract

Purpose

Operationalizing R-imperatives in firms is seen as vital to bolstering circularity through reduce, reuse and recycle and building circular supply chains (CSCs). However, this process introduces various uncertainties to firms within CSCs. This is a gap that still requires an in-depth analysis, particularly to answer the question of how firms align the operationalization of R-imperatives with uncertainty management to improve sustainability performance and accelerate the transition toward CSCs.

Design/methodology/approach

This paper fills this gap through a multiple-case study, whereby nine firms from varying structures, regions and manufacturing industries were examined. Qualitative content analysis was employed to examine the collected primary (27 semi-structured interviews) and secondary data (internal management reports, publicly available corporate reports and website content).

Findings

The findings support the evidence that the operationalization of R-imperatives is not a straightforward process. Within-firm and SC uncertainties largely emerged and made the building of CSCs complex. Consequently, strategies aimed at reducing uncertainty were paramount to managing uncertainties and enhancing sustainability performance. For instance, implementing durable or modular designs helped firms easily reuse, repair and recycle products. In turn, firms achieved material efficiency and contributed to extending the life cycle of products.

Practical implications

This paper explains how firms can align R-imperatives operationalization with uncertainty management to improve sustainability performance and enhance CSCs. Accordingly, firms should complement R-imperatives operationalization with proactive uncertainty management and an assessment of all environmental, economic and social sustainability dimensions.

Originality/value

This paper fills a critical gap in circular supply chain management literature by unveiling its linkage with uncertainty management and sustainability performance. Empirical insights from nine firms within CSCs are provided to guide scholars and managers interested in implementing R-imperatives.

Details

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

Keywords

Article
Publication date: 29 March 2024

Pratheek Suresh and Balaji Chakravarthy

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a…

Abstract

Purpose

As data centres grow in size and complexity, traditional air-cooling methods are becoming less effective and more expensive. Immersion cooling, where servers are submerged in a dielectric fluid, has emerged as a promising alternative. Ensuring reliable operations in data centre applications requires the development of an effective control framework for immersion cooling systems, which necessitates the prediction of server temperature. While deep learning-based temperature prediction models have shown effectiveness, further enhancement is needed to improve their prediction accuracy. This study aims to develop a temperature prediction model using Long Short-Term Memory (LSTM) Networks based on recursive encoder-decoder architecture.

Design/methodology/approach

This paper explores the use of deep learning algorithms to predict the temperature of a heater in a two-phase immersion-cooled system using NOVEC 7100. The performance of recursive-long short-term memory-encoder-decoder (R-LSTM-ED), recursive-convolutional neural network-LSTM (R-CNN-LSTM) and R-LSTM approaches are compared using mean absolute error, root mean square error, mean absolute percentage error and coefficient of determination (R2) as performance metrics. The impact of window size, sampling period and noise within training data on the performance of the model is investigated.

Findings

The R-LSTM-ED consistently outperforms the R-LSTM model by 6%, 15.8% and 12.5%, and R-CNN-LSTM model by 4%, 11% and 12.3% in all forecast ranges of 10, 30 and 60 s, respectively, averaged across all the workloads considered in the study. The optimum sampling period based on the study is found to be 2 s and the window size to be 60 s. The performance of the model deteriorates significantly as the noise level reaches 10%.

Research limitations/implications

The proposed models are currently trained on data collected from an experimental setup simulating data centre loads. Future research should seek to extend the applicability of the models by incorporating time series data from immersion-cooled servers.

Originality/value

The proposed multivariate-recursive-prediction models are trained and tested by using real Data Centre workload traces applied to the immersion-cooled system developed in the laboratory.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0961-5539

Keywords

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