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1 – 10 of 11Lisa Bosman, Taofeek Oladepo and Ida Ngambeki
Upon graduating from university, many engineers will work in new product development and/or technology adoption for continuous improvement and production optimization. These jobs…
Abstract
Purpose
Upon graduating from university, many engineers will work in new product development and/or technology adoption for continuous improvement and production optimization. These jobs require employees to be cognizant of ethical practices and implications for design. However, little engineering coursework, outside the traditional ABET (Accreditation Board for Engineering and Technology) required Engineering Ethics course, accounts for the role of ethics within this process. Because of this, engineering students have few learning opportunities to practice and reflect on ethical decision-making.
Design/methodology/approach
This paper highlights one approach to integrating ethics into an engineering course (outside of engineering ethics). Specifically, the study is implemented within a five-week module with a focus on big data ethics, as part of a Supply Chain Management Technology course (required for Industrial Engineering Technology majors), using metacognition as the core assessment.
Findings
Four main themes were identified through the qualitative data analysis of the metacognitive reflections: (1) overreliance on content knowledge, (2) time management skills, (3) career connections and (4) knowledge extensions.
Originality/value
Three notable points emerged which contribute to the literature. First, this study showcased one example of how an ethics module can be integrated into an engineering course (other than Engineering Ethics). Second, this study demonstrated how metacognitive reflections can be used to reinforce student self-awareness of the learning process and connections to big data ethics in the workplace. Finally, this study exhibited how metacognitive reflection assignments can be deployed as a teaching and learning assessment tool, providing an opportunity for the instructor to make immediate changes as needed.
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Dominik Oehlschläger, Andreas H. Glas and Michael Eßig
Inaccurate capturing and processing of customer requirements result in negative economic and ecological effects. Digital twins of customer demands promise to remedy these issues…
Abstract
Purpose
Inaccurate capturing and processing of customer requirements result in negative economic and ecological effects. Digital twins of customer demands promise to remedy these issues. However, successful implementation necessitates users' technology acceptance. This study contrasts three hierarchical digital twin levels with different degrees of user integration and examines determinants for their respective acceptance.
Design/methodology/approach
A structural equation model is applied in a comparative manner, considering different levels of digital twin radicalness. A multidimensional approach is used to measure attitudes towards usage. Data are collected in the context of organisational supply management.
Findings
Results show harmonious effects across digital twin levels. This indicates that technological radicality plays only a subordinate role when assessing acceptance determinants such as user perception on ease of use, usefulness, trust and risk.
Practical implications
Rather than focussing solely on technological factors, findings suggest that users prioritise the actual outcome and efficiency of the system. This perspective offers practical implications for organisations seeking to implement advanced systems and emphasises the significance of user perceptions beyond technological features.
Social implications
The societal impact of this research are an appreciation of customer roles in the supply chain where an enhanced detection of customer needs and preferences aligns businesses with the dynamic and evolving demands of a diverse and a continuously environmentally-conscious consumer base.
Originality/value
This study applies a measurement model for technology acceptance in a unique and multidimensional manner. Thereby, a comparative analysis of user perceptions across different digital twin levels sheds more light on a nascent, promising and underexplored technological method. This interdisciplinary research combined knowledge from the supply chain management and management information systems fields by highlighting key factors for the adoption of complex technological methods.
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This study aims to examine digital consumer culture and behavior in the community, namely, 180° Movement Digital Training Center (DTC), in Jakarta, Indonesia. It aims to describe…
Abstract
Purpose
This study aims to examine digital consumer culture and behavior in the community, namely, 180° Movement Digital Training Center (DTC), in Jakarta, Indonesia. It aims to describe the dynamics of digital consumer culture in contemporary society, particularly as experienced by the youth community in Jakarta in the context of socio-technology relations and incorporates it into the diagram of digital consumer culture network.
Design/methodology/approach
This research uses a constructivist qualitative approach and socio-technical relation analysis through actor-network theory and digital consumer culture.
Findings
The study finds that the individual model of digital consumption is constructed through the process of problematization, interessement, enrollment and mobilization of individuals. It generates a culture in which consumers are constantly up to date with high-intensity information, but within increasingly shorter timeframes, while also considering principles of affordability, needs, desires and satisfaction. The network of digital consumer culture construction among informants is peculiar and unstable.
Research limitations/implications
The study of digital consumer culture within the 180° Movement DTC community highlights how consumer behaviors of its members are facilitated and interconnected within a digital cultural network. However, this research is constrained by the dialectical interplay between Christian principles and the emerging values of consumer culture, a result of the scarcity of theoretical resources and information. This study also provides a specific contribution as a foundation for mapping the volatile digital consumer culture for researchers.
Practical implications
Understanding the socio-technological relationships and consumption behavior of the youth community could help digital platforms tailor their services more effectively. It could also guide the 180° Movement DTC in developing programs that resonate with the youth, bridging the gap between the physical and virtual realms. Ultimately, this could lead to a more engaged and digitally literate society.
Social implications
This study contributes to a broader societal understanding of how digital technology is shaping consumer behavior and identity within youth communities, which can influence social dynamics and interactions. It provides insights into the potential social impacts of digital technology, such as changes in relationships, communication patterns and self-perception, informing societal discourse on digital culture.
Originality/value
In addition to presenting socio-technological analysis on Indonesian consumer culture using actor-network theory, some also show that studies on digital connectivity ambivalence that concern the relationship between humans as actors and non-humans as actors have become one of the popular sociology studies at present.
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Karthikeyan Paramanandam, Venkatachalapathy S, Balamurugan Srinivasan and Nanda Kishore P V R
This study aims to minimize the pressure drop across wavy microchannels using secondary branches without compromising its capacity to transfer the heat. The impact of secondary…
Abstract
Purpose
This study aims to minimize the pressure drop across wavy microchannels using secondary branches without compromising its capacity to transfer the heat. The impact of secondary flows on the pressure drop and heat transfer capabilities at different Reynolds numbers are investigated numerically for different wavy microchannels. Finally, different channels are evaluated using performance evaluation criteria to determine their effectiveness.
Design/methodology/approach
To investigate the flow and heat transfer capabilities in wavy microchannels having secondary branches, a 3D conjugate heat transfer model based on finite volume method is used. In conventional wavy microchannel, secondary branches are introduced at crest and trough locations. For the numerical simulation, a single symmetrical channel is used to minimize computational time and resources and the flow within the channels remains single-phase and laminar.
Findings
The findings indicate that the suggested secondary channels notably improve heat transfer and decrease pressure drop within the channels. At lower flow rates, the secondary channels demonstrate superior performance in terms of heat transfer. However, the performance declines as the flow rate increased. With the same amplitude and wavelength, the introduction of secondary channels reduces the pressure drop compared with conventional wavy channels. Due to the presence of secondary channels, the flow splits from the main channel, and part of the core flow gets diverted into the secondary channel as the flow takes the path of minimum resistance. Due to this flow split, the core velocity is reduced. An increase in flow area helps in reducing pressure drop.
Practical implications
Many complex and intricate microchannels are proposed by the researchers to augment heat dissipation. There are challenges in the fabrication of microchannels, such as surface finish and achieving the required dimensions. However, due to the recent developments in metal additive manufacturing and microfabrication techniques, the complex shapes proposed in this paper are feasible to fabricate.
Originality/value
Wavy channels are widely used in heat transfer and micro-fluidics applications. The proposed wavy microchannels with secondary channels are different when compared to conventional wavy channels and can be used practically to solve thermal challenges. They help achieve a lower pressure drop in wavy microchannels without compromising heat transfer performance.
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Elena Stefana, Paola Cocca, Federico Fantori, Filippo Marciano and Alessandro Marini
This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.
Abstract
Purpose
This paper aims to overcome the inability of both comparing loss costs and accounting for production resource losses of Overall Equipment Effectiveness (OEE)-related approaches.
Design/methodology/approach
The authors conducted a literature review about the studies focusing on approaches combining OEE with monetary units and/or resource issues. The authors developed an approach based on Overall Equipment Cost Loss (OECL), introducing a component for the production resource consumption of a machine. A real case study about a smart multicenter three-spindle machine is used to test the applicability of the approach.
Findings
The paper proposes Resource Overall Equipment Cost Loss (ROECL), i.e. a new KPI expressed in monetary units that represents the total cost of losses (including production resource ones) caused by inefficiencies and deviations of the machine or equipment from its optimal operating status occurring over a specific time period. ROECL enables to quantify the variation of the product cost occurring when a machine or equipment changes its health status and to determine the actual product cost for a given production order. In the analysed case study, the most critical production orders showed an actual production cost about 60% higher than the minimal cost possible under the most efficient operating conditions.
Originality/value
The proposed approach may support both production and cost accounting managers during the identification of areas requiring attention and representing opportunities for improvement in terms of availability, performance, quality, and resource losses.
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Pietro Pavone, Paolo Ricci and Massimiliano Calogero
This paper aims to investigate the literacy corpus regarding the potential of big data to improve public decision-making processes and direct these processes toward the creation…
Abstract
Purpose
This paper aims to investigate the literacy corpus regarding the potential of big data to improve public decision-making processes and direct these processes toward the creation of public value. This paper presents a map of current knowledge in a sample of selected articles and explores the intersecting points between data from the private sector and the public dimension in relation to benefits for society.
Design/methodology/approach
A bibliometric analysis was performed to provide a retrospective review of published content in the past decade in the field of big data for the public interest. This paper describes citation patterns, key topics and publication trends.
Findings
The findings indicate a propensity in the current literature to deal with the issue of data value creation in the private dimension (data as input to improve business performance or customer relations). Research on data for the public good has so far been underestimated. Evidence shows that big data value creation is closely associated with a collective process in which multiple levels of interaction and data sharing develop between both private and public actors in data ecosystems that pose new challenges for accountability and legitimation processes.
Research limitations/implications
The bibliometric method focuses on academic papers. This paper does not include conference proceedings, books or book chapters. Consequently, a part of the existing literature was excluded from the investigation and further empirical research is required to validate some of the proposed theoretical assumptions.
Originality/value
Although this paper presents the main contents of previous studies, it highlights the need to systematize data-driven private practices for public purposes. This paper offers insights to better understand these processes from a public management perspective.
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This culminating chapter reviews the impacts of the pandemic on global systems of education. Drawing on the insights of the preceding chapters, this chapter offers three ideas for…
Abstract
This culminating chapter reviews the impacts of the pandemic on global systems of education. Drawing on the insights of the preceding chapters, this chapter offers three ideas for the future. First, schools of education should engage in innovative learning experiences including in person, online and hybrid learning opportunities. Second, staff support and development are key areas for future growth. Similarly, the third area for future growth is deeper consideration of student well-being and development. The pandemic placed these ideas at the forefront of conversation, and schools of education are positioned to continue that conversation, taking action to create transformative educational experiences.
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Ernesto Cardamone, Gaetano Miceli and Maria Antonietta Raimondo
This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation…
Abstract
Purpose
This paper investigates how two characteristics of language, abstractness vs concreteness and narrativity, influence user engagement in communication exercises on innovation targeted to the general audience. The proposed conceptual model suggests that innovation fits well with more abstract language because of the association of innovation with imagination and distal construal. Moreover, communication of innovation may benefit from greater adherence to the narrativity arc, that is, early staging, increasing plot progression and climax optimal point. These effects are moderated by content variety and emotional tone, respectively.
Design/methodology/approach
Based on a Latent Dirichlet allocation (LDA) application on a sample of 3225 TED Talks transcripts, the authors identify 287 TED Talks on innovation, and then applied econometric analyses to test the hypotheses on the effects of abstractness vs concreteness and narrativity on engagement, and on the moderation effects of content variety and emotional tone.
Findings
The authors found that abstractness (vs concreteness) and narrativity have positive effects on engagement. These two effects are stronger with higher content variety and more positive emotional tone, respectively.
Research limitations/implications
This paper extends the literature on communication of innovation, linguistics and text analysis by evaluating the roles of abstractness vs concreteness and narrativity in shaping appreciation of innovation.
Originality/value
This paper reports conceptual and empirical analyses on innovation dissemination through a popular medium – TED Talks – and applies modern text analysis algorithms to test hypotheses on the effects of two pivotal dimensions of language on user engagement.
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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.
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Mansik Yun, Nga Do and Terry Beehr
The purpose of the current research is to examine the crucial role of employees' perception of an incivility norm in predicting supervisors' incivility behaviors, which in turn…
Abstract
Purpose
The purpose of the current research is to examine the crucial role of employees' perception of an incivility norm in predicting supervisors' incivility behaviors, which in turn, results in employees enacting incivility toward their coworkers and employees' emotional exhaustion.
Design/methodology/approach
In Study 1, an experience sampling method (a daily-diary approach) in which 143 male participants from several construction sites completed a total of 1,144 questionnaires was used . In Study 2, cross-sectional data from 156 male employees working in a manufacturing organization was collected. In Study 3, a quasi-experiment was conducted in which 33 and 36 employees were assigned to the intervention and control groups, respectively.
Findings
In Studies 1 and 2, it was revealed that employees are likely to experience their supervisor’s incivility behaviors when perceiving such incivility behaviors are more acceptable within the organization (incivility norm). Further, once employees experience incivility from their supervisor, they are more likely to enact incivility toward their coworkers and experience emotional exhaustion. In Study 3, changing organizational policies via implementing grievance procedures was effective in improving the study’s outcome variables.
Originality/value
Incivility norms predict some negative work outcomes such as incivility behaviors as both a victim and instigator, and emotional exhaustion. Further, reducing an adverse organizational norm (i.e. incivility norm) via instituting grievance procedures was effective in reducing incivility behaviors and emotional exhaustion.
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