Search results

The primary objective of this paper is to show a systematic and methodological approach for the digitalization of critical clinical pathways (CPs) within the healthcare domain.

The methodology entails the integration of service design (SD) and action research (AR) methodologies, characterized by iterative phases that systematically alternate between action and reflective processes, fostering cycles of change and learning. Within this framework, stakeholders are engaged through semi-structured interviews, while the existing and envisioned processes are delineated and represented using BPMN 2.0. These methodological steps emphasize the development of an autonomous, patient-centric web application alongside the implementation of an adaptable and patient-oriented scheduling system. Also, business processes simulation is employed to measure key performance indicators of processes and test for potential improvements. This method is implemented in the context of the CP addressing transient loss of consciousness (TLOC), within a publicly funded hospital setting.

The methodology integrating SD and AR enables the detection of pivotal bottlenecks within diagnostic CPs and proposes optimal corrective measures to ensure uninterrupted patient care, all the while advancing the digitalization of diagnostic CP management. This study contributes to theoretical discussions by emphasizing the criticality of process optimization, the transformative potential of digitalization in healthcare and the paramount importance of user-centric design principles, and offers valuable insights into healthcare management implications.

The study’s relevance lies in its ability to enhance healthcare practices without necessitating disruptive and resource-intensive process overhauls. This pragmatic approach aligns with the imperative for healthcare organizations to improve their operations efficiently and cost-effectively, making the study’s findings relevant.

This paper aims to identify and study the effect of identified eight barriers to sustainable consumption on consumers’ intention to purchase sustainable products.

Data were collected from a self-administered field survey in India, and 315 valid responses were obtained from the survey process. Partial least square structural equation modeling analysis was carried out to establish the validity of the measures used and to examine the impact of the identified barriers on sustainable purchase intentions.

The results of this study indicate that barriers such as low willingness to pay, low functional performance, low availability of sustainable products and difficulty of integration in the normal route have a statistically significant negative impact on consumers’ sustainable purchase intentions.

The findings of this study are useful for marketers and policymakers who want to increase the consumer adoption of sustainable products in emerging markets.

This study develops measures to capture the consumers’ perception of barriers to the adoption of sustainable products.

The paper’s purpose is to consider, using a transaction cost economics (TCE) framework, the mechanisms used by space agencies to encourage private investment in the commercial spaceflight sector.

The authors conducted a content analysis of 554 pages of news articles, relating to issues pertaining to partnerships between national government-based space agencies and private space travel providers, published over a 20-year period. Leximancer was used to initially screen the data and then the authors manually analysed the content to identify themes.

The data analysis revealed three themes, relating to: the uncertainty of space travel; National Aeronautics and Space Administration (NASA) stimulating innovation in the private sector; and risk, insurance and regulation. These themes informed by TCE reveal the “hierarchical” organisational forms used to achieve human spaceflight and then the “hybrids”, insurance and regulations used to stimulate private sector investment and innovation.

This paper contributes to the accounting literature by answering the calls of Alewine (2020) and Tucker and Alewine (2022a, b) for more research into accounting in the space context. Specifically, the paper contributes by identifying mechanisms used by NASA to stimulate private investment in the space travel sector, as well as issues that have affected the implementation of these mechanisms. The paper also contributes to the literature by, based on the analysis, identifying a series of reflections designed to stimulate further management accounting research in the space context.

The purpose of the paper is to present an integrated methodology for identifying trends in a particular subject area based on a combination of advanced text mining and expert methods. The authors aim to test it in an area of clinical psychology and psychotherapy in 2010–2019.

The authors demonstrate the way of applying text-mining and the Word2Vec model to identify hot topics (HT) and emerging trends (ET) in clinical psychology and psychotherapy. The analysis of 11.3 million scientific publications in the Microsoft Academic Graph database revealed the most rapidly growing clinical psychology and psychotherapy terms – those with the largest increase in the number of publications reflecting real or potential trends.

The proposed approach allows one to identify HT and ET for the six thematic clusters related to mental disorders, symptoms, pharmacology, psychotherapy, treatment techniques and important psychological skills.

The developed methodology allows one to see the broad picture of the most dynamic research areas in the field of clinical psychology and psychotherapy in 2010–2019. For clinicians, who are often overwhelmed by practical work, this map of the current research can help identify the areas worthy of further attention to improve the effectiveness of their clinical work. This methodology might be applied for the identification of trends in any other subject area by taking into account its specificity.

The paper demonstrates the value of the advanced text-mining approach for understanding trends in a subject area. To the best of the authors’ knowledge, for the first time, text-mining and the Word2Vec model have been applied to identifying trends in the field of clinical psychology and psychotherapy.