Internet of Things technology applications in the workplace environment: a critical review

Nappi, Ingrid; Ribeiro, Gisèle de Campos

doi:10.1108/jcre-06-2019-0028

Cited by 27 publications

(9 citation statements)

References 59 publications

(71 reference statements)

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“…Since previous scholars have yet to investigate the mediation of employee productivity, this study makes a novel contribution. However, this mediation hypothesis has little empirical support (Nappi and de Campos Ribeiro, 2020;Guzm an and Dom ınguez, 2022). This study's fifth exciting finding is the moderating effect of resistance to change in the relationship between change management and employee productivity (Hypothesis 5).…”

Section: Results Of Hypotheses Testingmentioning

confidence: 86%

Section: Discussionmentioning

confidence: 99%

“…Though previous researchers did not emphasize this mediating effect, we attempt to explore this mediation. Some recent scholars found that workplace attachment mediates the relationship between satisfaction and productivity and is worth examining (Nappi and de Campos Ribeiro, 2020). In a similar vein, productivity can be a mediator between change management and job satisfaction.…”

Section: 24mentioning

confidence: 96%

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Knowledge management and resistance to change as moderators in the relationship between change management and job satisfaction

Shaik,

Batta,

Parayitam

2023

JOCM

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PurposeThis research aims to explore the effect of change management on job satisfaction. A conceptual model involving knowledge management and resistance to change as moderators tested the relationships in the context of a developing country, India.Design/methodology/approachData from 413 respondents from four important sectors – healthcare, education, manufacturing and information technology – were collected from southern India. First, the psychometric properties of the survey instrument were checked, and then hypotheses were tested using Hayes's PROCESS macros.FindingsThe results indicate that change management significantly predicts employee productivity and job satisfaction. Further, employee productivity mediated the relationship between change management and job satisfaction. This study also found that the resistance to change (first moderator) and knowledge management (second moderator) interacted with change management to enhance employee productivity.Research limitations/implicationsThis study has several contributions to the practitioners and academic scholars. The study has limitations, which are inherent in survey-based research, of common method bias and social desirability bias. However, the authors have taken adequate care to minimize these biases.Originality/valueThe three-way interaction (moderated moderated-mediation) tested in this research uniquely contributes to the literature on change management. To the best of the authors’ knowledge, this moderated moderated-mediation has been tested for the first time in the context of a developing country, India, and provides valuable insights into the practicing managers and change agents in bringing successful change in organizations.

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Section: Results Of Hypotheses Testingmentioning

confidence: 86%

Section: Discussionmentioning

confidence: 99%

Section: 24mentioning

confidence: 96%

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Knowledge management and resistance to change as moderators in the relationship between change management and job satisfaction

Shaik,

Batta,

Parayitam

2023

JOCM

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“…In recent decades, virtual reality (VR) related techniques [ 3 , 4 ] have been extensively exploited in a plethora of applications [ 5 ] ranging from industrial manufacturing [ 6 ], healthcare [ 7 ], entertainment [ 8 , 9 ], and education [ 10 , 11 ]. Meanwhile, different types of Internet of things (IoT) have also been deployed in practice [ 12 ], e.g., commercial and industrial scenarios [ 13 , 14 ], medical assistance [ 15 ], and smart cities [ 16 ]. Both of them have shown their capacity and potential value in multidisciplinary tasks.…”

Section: Introductionmentioning

confidence: 99%

Virtual Reality and Internet of Things-Based Music Online Learning via the Graph Neural Network

Lian

Zhou

Han³

et al. 2022

Computational Intelligence and Neuroscience

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Virtual reality and the Internet of Things have shown their capability in a variety of tasks. However, their availability in online learning remains an unresolved issue. To bridge this gap, we propose a virtual reality and Internet of Things-based pipeline for online music learning. The one graph network is used to generate an automated evaluation of learning performance which traditionally was given by the teachers. To be specific, a graph neural network-based algorithm is employed to identify the real-time status of each student within an online class. In the proposed algorithm, the characteristics of each student collected from the multisensors deployed on their bodies are taken as the input feature for each node in the presented graph neural network. With the adoption of convolutional layers and dense layers as well as the similarity between each pair of students, the proposed approach can predict the future circumstance of the entire class. To evaluate the performance of our work, comparison experiments between several state-of-the-art algorithms and the proposed algorithm were conducted. The result from the experiments demonstrated that the graph neural network-based algorithm achieved competitive performance (sensitivity 91.24%, specificity 93.58%, and accuracy 89.79%) over the state-of-the-art.

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“…Beyond the traditional privacy and security concerns that smart spaces need to face, smart workplaces propose additional threats. For example, privacy perception acquires new dimensions involving a social component, as these data can be associated with the image given to third parties or with the perception of productivity and work performance [ 24 ]. Additionally, due to the long hours that users (i.e., workers) spend in workplaces, this can be considered a strategic environment to address challenges such as user comfort and energy efficiency by means of IoT.…”

Section: Introductionmentioning

confidence: 99%

PyFF: A Fog-Based Flexible Architecture for Enabling Privacy-by-Design IoT-Based Communal Smart Environments

Benhamida

Navarro

Gómez-Carmona

et al. 2021

Sensors

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The advent of the Internet of Things (IoT) and the massive growth of devices connected to the Internet are reshaping modern societies. However, human lifestyles are not evolving at the same pace as technology, which often derives into users’ reluctance and aversion. Although it is essential to consider user involvement/privacy while deploying IoT devices in a human-centric environment, current IoT architecture standards tend to neglect the degree of trust that humans require to adopt these technologies on a daily basis. In this regard, this paper proposes an architecture to enable privacy-by-design with human-in-the-loop IoT environments. In this regard, it first distills two IoT use-cases with high human interaction to analyze the interactions between human beings and IoT devices in an environment which had not previously been subject to the Internet of People principles.. Leveraging the lessons learned in these use-cases, the Privacy-enabling Fog-based and Flexible (PyFF) human-centric and human-aware architecture is proposed which brings together distributed and intelligent systems are brought together. PyFF aims to maintain end-users’ privacy by involving them in the whole data lifecycle, allowing them to decide which information can be monitored, where it can be computed and the appropriate feedback channels in accordance with human-in-the-loop principles.

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Internet of Things technology applications in the workplace environment: a critical review

Cited by 27 publications

References 59 publications

Knowledge management and resistance to change as moderators in the relationship between change management and job satisfaction

Knowledge management and resistance to change as moderators in the relationship between change management and job satisfaction

Virtual Reality and Internet of Things-Based Music Online Learning via the Graph Neural Network

PyFF: A Fog-Based Flexible Architecture for Enabling Privacy-by-Design IoT-Based Communal Smart Environments

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