Investigating the Effect of Technostress on the Perceived Organizational
Commitment by Mediating Role of Individual Innovation
- URL: http://arxiv.org/abs/2310.07806v1
- Date: Wed, 11 Oct 2023 18:38:43 GMT
- Title: Investigating the Effect of Technostress on the Perceived Organizational
Commitment by Mediating Role of Individual Innovation
- Authors: Hassan Hessari, Fatemeh Daneshmandi, Tahmineh Nategh
- Abstract summary: This study utilized a questionnaire survey conducted within an Engineering Consulting Company in Iran.
The research findings revealed three crucial insights.
The study underscores the importance for managers to proactively address technostress-related challenges.
- Score: 0.0
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Purpose: Technology plays a pivotal role in shaping the fate of
organizations, both positively and negatively. One of its detrimental
consequences is the emergence of "Technostress," a form of destructive stress.
This paper investigates the impact of technostress on Perceived Organizational
Commitment (POC) through the lens of individual innovation. The objective is to
provide valuable insights for organizational managers, enabling them to
effectively mitigate the adverse effects of technostress within their teams.
Design/Methodology/Approach: This study utilized a questionnaire survey
conducted within an Engineering Consulting Company in Iran, with 147
individuals participating, selected according to Morgan's table. Findings: The
research findings revealed three crucial insights: (1) Technostress
significantly and negatively influences both POC and individual innovation. (2)
Individual innovation positively and significantly impacts POC. (3) Individual
innovation acts as a mediator between technostress and POC, alleviating the
negative impact of technostress on organizational commitment. Research
Implications: The study underscores the importance for managers to proactively
address technostress-related challenges and promote individual innovation
within their organizations. These efforts are vital in enhancing organizational
commitment among employees. Originality/Value: This research makes a
significant contribution to the field by illuminating the mediating role of
individual innovation in the relationship between technostress and perceived
organizational commitment. Given the close association of employees in
engineering organizations with technology, this study sheds light on the
specific challenges faced by this sector, thereby enhancing our understanding
of technostress effects in the workplace.
Related papers
- Factory Operators' Perspectives on Cognitive Assistants for Knowledge Sharing: Challenges, Risks, and Impact on Work [51.78233291198334]
This study investigates the real-world impact of deploying Cognitive Assistants (CAs) in factories.
Our results indicate that while CAs have the potential to significantly improve efficiency through knowledge sharing, they also introduce concerns around workplace surveillance.
Our findings stress the importance of addressing privacy, knowledge contribution burdens, and tensions between factory operators and their managers.
arXiv Detail & Related papers (2024-09-30T11:08:27Z) - Do Responsible AI Artifacts Advance Stakeholder Goals? Four Key Barriers Perceived by Legal and Civil Stakeholders [59.17981603969404]
The responsible AI (RAI) community has introduced numerous processes and artifacts to facilitate transparency and support the governance of AI systems.
We conduct semi-structured interviews with 19 government, legal, and civil society stakeholders who inform policy and advocacy around responsible AI efforts.
We organize these beliefs into four barriers that help explain how RAI artifacts may (inadvertently) reconfigure power relations across civil society, government, and industry.
arXiv Detail & Related papers (2024-08-22T00:14:37Z) - Understanding the Factors Influencing Self-Managed Enterprises of Crowdworkers: A Comprehensive Review [49.623146117284115]
This paper investigates the shift in crowdsourcing towards self-managed enterprises of crowdworkers (SMECs)
It reviews the literature to understand the foundational aspects of this shift, focusing on identifying key factors that may explain the rise of SMECs.
The study aims to guide future research and inform policy and platform development, emphasizing the importance of fair labor practices in this evolving landscape.
arXiv Detail & Related papers (2024-03-19T14:33:16Z) - Responsible AI Considerations in Text Summarization Research: A Review
of Current Practices [89.85174013619883]
We focus on text summarization, a common NLP task largely overlooked by the responsible AI community.
We conduct a multi-round qualitative analysis of 333 summarization papers from the ACL Anthology published between 2020-2022.
We focus on how, which, and when responsible AI issues are covered, which relevant stakeholders are considered, and mismatches between stated and realized research goals.
arXiv Detail & Related papers (2023-11-18T15:35:36Z) - "That's important, but...": How Computer Science Researchers Anticipate
Unintended Consequences of Their Research Innovations [12.947525301829835]
We show that considering unintended consequences is generally seen as important but rarely practiced.
Principal barriers are a lack of formal process and strategy as well as the academic practice that prioritizes fast progress and publications.
We intend for our work to pave the way for routine explorations of the societal implications of technological innovations before, during, and after the research process.
arXiv Detail & Related papers (2023-03-27T18:21:29Z) - Responsible and Inclusive Technology Framework: A Formative Framework to
Promote Societal Considerations in Information Technology Contexts [1.9991645269305982]
This paper contributes a formative framework -- the Responsible and Inclusive Technology Framework -- that orients critical reflection around the social contexts of technology creation and use.
We expect that the implementation of the Responsible and Inclusive Technology framework, especially in business-to-business industry settings, will serve as a catalyst for more intentional and socially-grounded practices.
arXiv Detail & Related papers (2023-02-22T18:59:04Z) - Crowdsourcing Impacts: Exploring the Utility of Crowds for Anticipating
Societal Impacts of Algorithmic Decision Making [7.068913546756094]
We employ crowdsourcing to uncover different types of impact areas based on a set of governmental algorithmic decision making tools.
Our findings suggest that this method is effective at leveraging the cognitive diversity of the crowd to uncover a range of issues.
arXiv Detail & Related papers (2022-07-19T19:46:53Z) - TechRank: A Network-Centrality Approach for Informed
Cybersecurity-Investment [0.0]
We study the mutual influence of companies and technologies from the cybersecurity field.
This endeavor helps to measure the impact of an entity on the cybersecurity market.
arXiv Detail & Related papers (2021-12-10T14:01:49Z) - Sensemaking in Cybersecurity Incident Response: The Interplay of
Organizations, Technology and Individuals [0.5505634045241288]
This study proposes a framework that explains how the interplay among organizations, technology and individuals enables sensemaking in the process of cybersecurity incident response.
We argue that sensemaking in Incident Response is the outcome of this interaction.
arXiv Detail & Related papers (2021-07-06T23:32:18Z) - Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper [50.25428141435537]
Artificial Intelligence for IT Operations (AIOps) is an emerging interdisciplinary field arising in the intersection between machine learning, big data, streaming analytics, and the management of IT operations.
Main aim of the AIOPS workshop is to bring together researchers from both academia and industry to present their experiences, results, and work in progress in this field.
arXiv Detail & Related papers (2021-01-15T10:43:10Z) - Deep Technology Tracing for High-tech Companies [67.86308971806322]
We develop a novel data-driven solution, i.e., Deep Technology Forecasting (DTF) framework, to automatically find the most possible technology directions customized to each high-tech company.
DTF consists of three components: Potential Competitor Recognition (PCR), Collaborative Technology Recognition (CTR), and Deep Technology Tracing (DTT) neural network.
arXiv Detail & Related papers (2020-01-02T07:44:12Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.