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Innovation, Artificial Intelligence in Contingent Work-Force Management
571-590Views:669In recent years, the global use of contingent workers is rapidly increasing despite the increasing quantity of artificial intelligence applications in business. The question is "how these companies leverage the use of artificial intelligence to enhance contingent workforce's management?". The ideal goal of this paper is to develop a purely conceptual application of innovation, artificial intelligence (AI) adjacent to contingent workforce management(CWM). The researcher used qualitative information gathered from various authors and observations to reinforce the usage of AI. One of the critical tools to integrate with contingent workforce management for reduction of time spent on human resource administrative tasks is AI. There must be a transformation of thinking, accepting positive organizational change, utilization of technology and openness to new technology to foster AI. Along with that, integrating contingent workforce management with AI reduces risks and costs, increases efficiency and quality of work. Innovation and Artificial intelligence have been used in five pillars performance of contingent workforce management to mitigate the challenges associated with it.
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Challenges for Adaptation of Business Management
274-285Views:129Both the business management and the public sector try to provide employee with providing jobs, which are esteemed by the workforce and where employee has a good feeling. However the public management has a big challenge in this area, because the bussiness sector is more attractive, and competitive pay for emloyees. I tested the bussiness modell and look for their benefits and I saerch for connectivity points. This point will helps into the adaption to the non- bussiness sector.
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The Possible Job Creation and Job Destructive Effects of Technological Development
53-61Views:339Throughout history, technological change has often provided the basis for employee anxiety. Between 1811 and 1816, a group of workers in England who called themselves "Luddists" destroyed machines, because they thought it would endanger their workplace. 19th-century thinkers and economists such as Karl Marx and David Ricardo predicted that mechanizing the economy would ultimately worsen workers' conditions, depriving them of a decent wage. Over the last century, John M. Keynes (1930s) and Wassily Leontief (1950s) have expressed their fears that more and more workers will be replaced by machine solutions that will lead to unemployment. In recent years, Brynjolfsson and McAfee (2014) have argued that existing technologies reduce the demand for labor and put some of the human workforce at a permanent disadvantage. However, there are a number of compensation mechanisms that can offset the initial displacement effects of automation and process innovation in general (Vivarelli, 2015). First of all, while workers are being replaced in industries that introduce new machine technology, additional workers in new industries are needed. Second, automation (and process innovation in general) reduces average costs. Acemoglu and Restrepo (2017) found that this results, on the one hand, in the effect of price productivity (“priceproductivity”) (as production costs decrease, the industry can expand and increase labor demand); and, on the other hand, it leads to economies of scale in production (the reduction in costs due to automation leads to an increase in total output and increases the demand for labor in all industries). Similarly, Vivarelli (2015) argues that lower average costs can result in lower prices (if the industry's market structure is perfectly competitive), stimulate product demand, or result in extra profits (if the industry's structure is not perfectly competitive). If these extra profits are reinvested in the company, this investment can create new jobs. The presentation intends to present these counterbalancing cases and to provide real examples based on the literature.
