Digital technologies shaping the nature and routine intensity of shopfloor work

IF 3 2区 社会学 Q2 BUSINESS Competition & Change Pub Date : 2022-06-09 DOI:10.1177/10245294221107489
A. Szalavetz
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引用次数: 1

Abstract

Drawing on data from Hungarian manufacturing companies, this paper aims to explore the ways in which digital technologies affect the nature and routineness of work. It concludes that digital technologies impinge on some defining features of occupations, such as workload and intensity of work; the degree to which the tasks can be explicitly defined, measured and codified; composition and amount of skills required for task execution; and the importance of experience or tacit knowledge for task execution. Non-technological factors, such as managerial approach to technology and work design moderate outcomes. Evidence indicates that a reduction in the routine content of job tasks applies only to relatively skilled employees. For low-skilled employees, certain digital assistance solutions increase routine and engender deskilling. We conclude that a qualitative enrichment of shopfloor work becomes apparent only if (1) employees are skilled enough to become upskilled – and thus engaged not only in digitally enabled but also in digitally augmented, high-value activities; (2) employees’ work tasks are reorganised, work design and work practices modified, and employees upskilled. Without appropriate managerial interventions envisaging the augmentation of work, digital technology implementation entails deskilling and/or technological unemployment, rather than providing richer dimensions to shopfloor work.
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数字技术塑造了车间工作的性质和常规强度
利用匈牙利制造公司的数据,本文旨在探讨数字技术影响工作性质和例行性的方式。报告的结论是,数字技术影响了职业的一些决定性特征,比如工作量和工作强度;任务可以明确定义、衡量和编纂的程度;执行任务所需技能的组成和数量;以及经验或隐性知识对任务执行的重要性。非技术因素,如管理方法对技术和工作设计的影响。有证据表明,减少工作任务的常规内容只适用于相对熟练的员工。对于低技能员工来说,某些数字辅助解决方案增加了日常工作,并导致了技能的丧失。我们得出的结论是,只有在以下情况下,车间工作的定性丰富才会变得明显:(1)员工的技能足以提高技能,从而不仅参与数字化启用的活动,而且还参与数字化增强的高价值活动;(2)重组员工的工作任务,修改工作设计和工作实践,提高员工的技能。如果没有适当的管理干预措施来设想工作的增加,数字技术的实施将导致技能丧失和/或技术性失业,而不是为车间工作提供更丰富的维度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
7.20
自引率
7.70%
发文量
37
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