Is job performance conditioned by work-from-home demands and resources?

Prodanova, Jana; Kocarev, Ljupčo

doi:10.1016/j.techsoc.2021.101672

Cited by 49 publications

(39 citation statements)

References 74 publications

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“…Another valuable leadership skill reported in the papers includes monitoring and promoting social support, especially in sharing digital support among employees [ 58 ]. Thanks to these initiatives, employees are helped to overcome reluctance and apprehensiveness related to the use of ICT and their dependency [ 59 ]. A further issue tackled by positive and effective leadership leading to productivity is the handling of teams.…”

Section: Resultsmentioning

confidence: 99%

Consequences of COVID-19 on Employees in Remote Working: Challenges, Risks and Opportunities An Evidence-Based Literature Review

Vincenzi

Pansini

Ferrara

et al. 2022

IJERPH

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The COVID-19 pandemic forced organizations across all sectors and sizes to undertake crucial changes in order to remain productive during the emergency. Among these, the shift towards remote working arrangements is still present in our workplaces, impacting employees’ well-being and productivity. This systematic review aims to describe the pandemic’s consequences on work organization by analyzing whether and how the shift towards remote or home-working impacted employees’ productivity, performance, and well-being. Furthermore, it describes the role of individual and organizational factors in determining employees’ adjustment to remote work. Sixty-seven peer-reviewed papers published from 2020 to 2022, written in English, were selected through the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Findings describe how remote working arrangements, the workplace and organizational factors, and the employees’ individual traits and skills impacted employees’ productivity and well-being. Furthermore, they provide a description of the organizational enforcement actions reported in the literature. Managerial and practical implications, such as enforcement actions, team management strategies, and initiatives to promote employees’ physical and mental health, will be discussed in the paper.

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Section: Resultsmentioning

confidence: 99%

Consequences of COVID-19 on Employees in Remote Working: Challenges, Risks and Opportunities An Evidence-Based Literature Review

Vincenzi

Pansini

Ferrara

et al. 2022

IJERPH

View full text Add to dashboard Cite

show abstract

“…Remote work has been explored in many papers, most of which have focused on senior management support, employee satisfaction and job performance [ [48] , [49] , [50] ]. However, the link between remote work and emotional exhaustion is underexplored and remains unclear.…”

Section: Contextual and Theoretical Backgroundmentioning

confidence: 99%

Remote work as a new normal? The technology-organization-environment (TOE) context

Lit²,

Cheung³

2022

Technology in Society

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“…Limited in-person conversations and increased screen time may trigger anxiety. Moreover, interruptions from family members during working hours and lack of resources at home also create hindrances to work efficiently (Islam, 2022 ; Tønnessen et al., 2021 ; Kawakubo and Arata, 2022 ; Prodanova and Kocarev, 2021 ). These factors play a significant role in framing policies for employees.…”

Section: Introductionmentioning

confidence: 99%

Deep learning based sentiment analysis of public perception of working from home through tweets

Vohra

Garg

2022

J Intell Inf Syst

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Nowadays, we are witnessing a paradigm shift from the conventional approach of working from office spaces to the emerging culture of working virtually from home. Even during the COVID-19 pandemic, many organisations were forced to allow employees to work from their homes, which led to worldwide discussions of this trend on Twitter. The analysis of this data has immense potential to change the way we work but extracting useful information from this valuable data is a challenge. Hence in this study, the microblogging website Twitter is used to gather more than 450,000 English language tweets from 22nd January 2022 to 12th March 2022, consisting of keywords related to working from home. A state-of-the-art pre-processing technique is used to convert all emojis into text, remove duplicate tweets, retweets, username tags, URLs, hashtags etc. and then the text is converted to lowercase. Thus, the number of tweets is reduced to 358,823. In this paper, we propose a fine-tuned Convolutional Neural Network (CNN) model to analyse Twitter data. The input to our deep learning model is an annotated set of tweets that are effectively labelled into three sentiment classes, viz. positive negative and neutral using VADER (Valence Aware Dictionary for sEntiment Reasoning). We also use a variation in the input vector to the embedding layer, by using FastText embeddings with our model to train supervised word representations for our text corpus of more than 450,000 tweets. The proposed model uses multiple convolution and max pooling layers, dropout operation, and dense layers with ReLU and sigmoid activations to achieve remarkable results on our dataset. Further, the performance of our model is compared with some standard classifiers like Support Vector Machine (SVM), Naive Bayes, Decision Tree, and Random Forest. From the results, it is observed that on the given dataset, the proposed CNN with FastText word embeddings outperforms other classifiers with an accuracy of 0.925969. As a result of this classification, 54.41% of the tweets are found to show affirmation, 24.50% show a negative disposition, and 21.09% have neutral sentiments towards working from home.

show abstract

Is job performance conditioned by work-from-home demands and resources?

Cited by 49 publications

References 74 publications

Consequences of COVID-19 on Employees in Remote Working: Challenges, Risks and Opportunities An Evidence-Based Literature Review

Consequences of COVID-19 on Employees in Remote Working: Challenges, Risks and Opportunities An Evidence-Based Literature Review

Remote work as a new normal? The technology-organization-environment (TOE) context

Deep learning based sentiment analysis of public perception of working from home through tweets

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