The Role of IT Identity and Paradoxes in Explaining Avoidance Strategies

The increasing use of technology in personal and professional environments has led to the development of an information technology (IT) identity, which describes the extent to which individuals view IT as integral to their sense of self. Further, technology paradoxes describe the contradictory nature of IT, which can lead to behavioral disengagement, causing significant disruptions in enterprise digitization. Thus, this study develops a theory-based model to explore the interplay between IT identity and technology paradoxes and their effects on behavioral disengagement. The findings reveal that IT identity mitigates the perception of technology paradoxes and impacts behavioral disengagement. We contribute to literature by quantifying and validating their effects and suggesting opportunities for future research. That way, practitioners can develop more effective strategies for promoting engagement and addressing disengagement among employees or users

Supporting the Billing Process in Outpatient Medical Care: Automated Medical Coding Through Machine Learning

Reimbursement in medical care implies significant administrative effort for medical staff. To bill the treatments or services provided, diagnosis and treatment codes must be assigned to patient records using standardized healthcare classification systems, which is a time-consuming and error-prone task. In contrast to ICD diagnosis codes used in most countries for inpatient care reimbursement, outpatient medical care often involves different reimbursement schemes. Following the Action Design Research methodology, we developed an NLP-based machine learning artifact in close collaboration with a general practitioner’s office in Germany, leveraging a dataset of over 5,600 patients with more than 63,000 billing codes. For the code prediction of most problematic treatments as well as a complete code prediction task, we achieved F1-scores of 93.60 % and 78.22 %, respectively. Throughout three iterations, we derived five meta requirements leading to three design principles for an automated coding system to support the reimbursement of outpatient medical care

IT Governance Mechanisms, Employees\u27 Digital Mindset, and Behavioral Outcomes

The disruptive nature of digitalization and the complexity and ambiguity of their technical properties require many new skills from employees today. Recent research emphasizes that the employees’ digital mindset plays an essential role in digital transformation by leveraging employee engagement. This paper aims to advance the understanding of how the behavioral outcomes of digital mindset, which encompass interpersonal interaction, focus of attention, enthusiasm for development, perspective on setbacks, and construal of effort, can be positively influenced during digital initiatives. We develop a novel research model integrating two literature streams: information technology and mindset. We conceptually link back to the behavioral outcomes of digital mindset by looking at the influence of IT governance mechanisms as potential antecedents. Our model explains how IT governance mechanisms influence the behavioral outcomes of digital mindset and helps future researchers by providing propositions on the impact of IT governance mechanisms towards more employee engagement

“Who Am I When Everything has Changed?” The Impact of Scaled-agile Organizations on Professional Role Identity

As digital technology continues to advance, organizations require more flexibility to meet the needs of their customers and remain competitive. To do so, many incumbent organizations fundamentally change their established structures and processes to implement scaled-agile organizations (SAO), emulating digital organizations and leveraging development speed and customer focus. However, when everything changes, there are significant effects on the employees’ identities. Thus, we explore how implementing an SAO affects employees’ professional role identities (PRI). The paper follows a case study approach analyzing two cases with 21 interviews, observational, and secondary data collected over a period of 18 months. We contribute to the literature by identifying three effects of an SAO implementation on PRI (threat, empowerment, and extension) and describing how individuals react based on the effect on their PRI. We inform practitioners on the overall SAO implementation process and consequences for professionals, offering a new perspective on organizational transformation challenges

The Interplay of IT Identity and Digital Mindset in the Workplace

IT identity plays a significant role in individuals\u27 IT adoption and use behaviors and can impact job satisfaction. However, other individual traits, like the digital mindset, previously showed to also affect the effects of the intertwining of IT and workplaces on job satisfaction. Therefore, we examine the role of a digital mindset in shaping IT and job identity and survey 167 employees. By analyzing the relationship between these concepts, the paper contributes to a better understanding of how identities are formed and how they affect job satisfaction in the digitally-enabled workplace. Our results demonstrate that IT identity’s effect on job satisfaction is fully mediated by job identity. We also reveal that a digital mindset moderates the relationship between IT and job identities. Further, we discuss the key challenges and opportunities associated with the adoption and use of IS in organizations and provide insights into the future directions of IS research. Overall, we contribute to the ongoing discourse on the role of IT identity and digital mindset in the workplace and provide valuable insights for researchers and practitioners

Supporting the billing process in outpatient medical care: Automated medical coding through machine learning

Reimbursement in medical care implies significant administrative effort for medical staff. To bill the treatments or services provided, diagnosis and treatment codes must be assigned to patient records using standardized healthcare classification systems, which is a time-consuming and error-prone task. In contrast to ICD diagnosis codes used in most countries for inpatient care reimbursement, outpatient medical care often involves different reimbursement schemes. Following the Action Design Research methodology, we developed an NLP-based machine learning artifact in close collaboration with a general practitioner’s office in Germany, leveraging a dataset of over 5,600 patients with more than 63,000 billing codes. For the code prediction of most problematic treatments as well as a complete code prediction task, we achieved F1-scores of 93.60 % and 78.22 %, respectively. Throughout three iterations, we derived five meta requirements leading to three design principles for an automated coding system to support the reimbursement of outpatient medical care