The restrictions introduced by COVID-19 forced firms to adapt to a technology-intensive operational model. These digital transformations involved deliberations among stakeholders to adjust strategy and general functionally of companies, which included elements of the future of work. This paper leverages existing research, and input from firms in various industries to illustrate technology-based issues including elements of the future of work that are transpiring in organizations as they adapt to this disruptive environment.
This work analyzes firm-level investment in information technology and corresponding productivity through the use of a production function over the period from 1995-1997. The results are then compared to previous studies that utilized similar data and methodologies to compare productivity estimates over time. The analysis indicates that investment in IT enhances productivity over the period in question and has illustrated increasing returns over time. These findings are supported by the corresponding empirical analysis which yielded IT capital coefficients in a production function of (0.12, 0.16, 0.18) and IT flow coefficients in a similar function of (0.17, 0.24, 0.22) for the years 1995, 1996, and 1997, respectively. These results reflect the change in firm output given a one-percent change in the natural log of dollars invested in IT capital and flow, and are statistically significant.
Managing patients' length of stay is a critical task for healthcare organizations. In order to better manage the processes impacting this performance metric, providers can leverage data resources describing the network of activities that impact a patient's stay with analytic methods. Interdependencies between departmental activities exist within the patient treatment process, where inefficiency in one element of the patient care network of activities can adversely affect process outcomes.This work utilizes the method of neural networks to analyze data describing inpatient cases that incorporate radiology process variables to determine their effect on patient length of stay excesses for a major NJ based healthcare provider. The results indicate that inefficiencies at the radiology level can adversely extend a patient's length of stay beyond initial estimations. Proactive analysis of networks of activities in the patient treatment process can enhance organizational efficiencies of healthcare providers by enabling decision makers to better optimize resource allocations to increase throughput of activities.
PurposeThe evolving digital transformations of organizational processes involve vast complexities. Factors such as labor resources at the individual and team levels that integrate and utilize information resources and evolving technologies to achieve collective intelligence are essential to this process. In order to better understand evolving demands of labor resources, existing research regarding worker/technology interactions for firm performance must be implemented and adapted to the changing market. This paper provides a conceptual research model enabling organizations to better understand the integration of worker/team attributes with collaboration modes, information resources and augmented technologies that yield effective collective intelligence for decision-making.Design/methodology/approachThis manuscript includes a literature review on worker/team attributes interfacing with various technology platforms and the creation of collective intelligence. It then reviews complementary research including leadership elements for organizational outcomes and introduces more current work involving a digital transformation. The literature review provides the underpinnings for a conceptual model that incorporates essential elements for the creation of collective intelligence for decision-making and adds factors that are relevant for digital transformations. These elements include augmented technologies including cognitive technologies, collaborative platforms and worker attributes (skills, social sensitivity, leadership) all of which illustrate components of intellectual capital.FindingsThe paper summarizes key findings of existing research in worker/team interactions with technology platforms on organizational performance and provides an applied, conceptual research model incorporating these findings, along with new elements in the digital era for better identifying new worker requirements.Originality/valueThe value of this work is the introduction of an applied conceptual model based on established literature findings that includes new technologies (e.g. cognitive technologies), collaboration modes and worker/team attributes to address the requirements of the evolving knowledge worker in the digital era. It provides a framework to better understand more optimal resource allocations for the creation of collective intelligence and integrates the model components within an intellectual capital framework.
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