scholarly journals The Effect of Planned Breaks on Worker Productivity and the Moderate Role of Workload in a Manufacturing Environment

2020 ◽  
Vol 10 (12) ◽  
pp. 1366-1383
Author(s):  
Siyuan Yi ◽  
Qiguo Gong ◽  
Feng Dong ◽  
Hui Wang

The productivity of land has been often discussed and deliberated by the academia and policymakers to understand agriculture, however, very few studies have focused on the agriculture worker productivity to analyze this sector. This study concentrates on the productivity of agricultural workers from across the states taking two-time points into consideration. The agriculture worker productivity needs to be dealt with seriously and on a time series basis so that the marginal productivity of worker can be ascertained but also the dependency of worker on agriculture gets revealed. There is still disguised unemployment in all the states and high level of labour migration, yet most of the states showed the dependency has gone down. Although a state like Madhya Pradesh is doing very well in terms of income earned but that is at the cost of increased worker power in agriculture as a result of which, the productivity of worker has gone down. States like Mizoram, Meghalaya, Nagaland and Tripura, though small in size showed remarkable growth in productivity and all these states showed a positive trend in terms of worker shifting away from agriculture. The traditional states which gained the most from Green Revolution of the sixties are performing decently well, but they need to have the next major policy push so that they move to the next orbit of growth.


2020 ◽  
Author(s):  
Aruna Ranganathan ◽  
Ranjitha Shivaram

Using ethnographic, personnel, and experimental data from an Indian garment factory, this paper investigates whether and how manager gender affects female worker productivity. We find that female managers motivate greater female worker productivity than male managers by engaging in subordinate scut work, the practice of voluntarily getting one’s hands dirty to perform subordinates’ routine tasks, which increases subordinates’ engagement with their work. Our qualitative data help to generate hypotheses that we explore using personnel data on individual productivity and test causally using a laboratory-in-the-field experiment in which we randomly assign workers to supervisors and experimentally manipulate supervisors’ ability to perform subordinate scut work. This paper contributes to the literature on motivating worker productivity by drawing attention to the important role of manager gender and by studying a less-researched organization context—that of a female-dominated workplace. The paper also contributes to the literature on women in management by investigating their impact on worker performance, measured objectively, and uncovering subordinate scut work as a specific managerial practice that female managers can use to foster engagement with work and improve female worker productivity. This paper was accepted by Greta Hsu, organizations.


1999 ◽  
Vol 41 (10) ◽  
pp. 863-877 ◽  
Author(s):  
Wayne N. Burton ◽  
Daniel J. Conti ◽  
Chin-Yu Chen ◽  
Alyssa B. Schultz ◽  
Dee W. Edington

ILR Review ◽  
1984 ◽  
Vol 37 (2) ◽  
pp. 252-262 ◽  
Author(s):  
Frank A. Sloan ◽  
Killard W. Adamache

This study examines the impact of unions on worker compensation and total costs in hospitals, both in specific departments and in the hospital as a whole. An analysis of data for 367 hospitals for the years 1974 and 1977 shows that unions raised the mean compensation of hospital workers by 8.8 percent without producing offsetting increases in worker productivity. Thus, unions do increase hospital costs, although far less than health insurance and other factors do.


2021 ◽  
pp. 267-284
Author(s):  
Lina Dencik

The dual occurrences of constant data collection and use of artificial and autonomous systems in the workplace are having a profound impact on workers’ lives. Workers are subjected to constant surveillance that not only monitor worker productivity but factors unrelated to work. At the same time, machine learning systems are using these data to transform how work is being allocated, assessed and completed and as a result, worker lives and value in the workplace and beyond. Yet governance frameworks for AI have thus far been advanced with a noticeable absence of worker voice, unions, and labour perspectives. In this chapter I will discuss how concerns about data and data infrastructures need to be situated as part of a workers’ rights agenda, the role of the labour movement in advancing alternative governance frameworks, and the potential for data justice unionism.


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