ABSTRACT
The role of Digital Human Resources Management (DHRM) in the era of globalization, especially in the COVID-19 pandemic, has made a major contribution to sustainable business performance. This is interesting to study considering that the DHRM work process will take place through mobile, electronic media, social media via the internet, and also with the help of IT (information technology). This research aims to analyze the role of Digital Human Resource Management (DHRM) in contributing to the improvement of sustainable business performance in companies in DKI Jakarta. The importance of the role of DHRM is investigated because DHRM is able to do human work through software and several applications, which are supported by the internet network. Digitalization in HRM will enable companies to operate more efficiently and relevantly in the future. This type of research is qualitative which involved managers working in oil companies and transportation companies in DKI Jakarta who used DHRM in the companies where they worked. This study analyzed the data using the triangulation method through documentation, interviews and direct observation in the field with case studies. The results of the study explain that several digital HRM practices have been carried out in several companies, but other practical activities have not been carried out optimally. This is because the support from the system and the digitization of business processes that are included in HR practices are not yet optimal. However, the company realizes that DHRM is able to improve business performance in a sustainable manner. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
This work examines the regional effects of COVID-19 supply chain shocks and potential inventory strategies to sustaining overall economic productivity through lockdowns. We introduce a multi-region extension to the economic production model proposed by Pichler, et al. [15] that was used to assess the extent of Covid-related shocks to gross output through modeling the interdependency between regional and national economies at the industry level. Our extended modeling approach aims to optimize, through genetic search, the degree to which the increased inventory supply targets allow for improved economic productivity and the ideal allocation per industry which most efficiently achieves this mitigation. The approach also integrates a new data regionalization procedure which we apply to a case study of the Alabama state economy. This application is shown to identify a set of major manufacturing and service sectors, where additional inventories enable greater sustained productivity across the Alabama region. This regional analysis of the Alabama economy highlighted the importance of sectors such as chemical, petroleum, food and beverage, and vehicle manufacturing and public administration, construction, management, transportation, and healthcare towards maintaining economic productivity. The ability to quantity regional production impacts from inventory allocations is leading to starting points for determining local government policies that target their most sensitive industries. © 2022 IEEE.