Analysis of barriers of mHealth adoption in the context of sustainable operational practices in health care supply chains

Abstract

PurposeThe goal of this research is to analyse the obstacles to the implementation of mobile health (mHealth) in India and to gain an understanding of the contextual inter-relationships that exist amongst those obstacles.Design/methodology/approachPotential barriers and their interrelationships in their respective contexts have been uncovered. Using MICMAC analysis, the categorization of these barriers was done based on their degree of reliance and driving power (DP). Furthermore, an interpretive structural modeling (ISM) framework for the barriers to mHealth activities in India has been proposed.FindingsThe study explores a total of 15 factors that reduce the efficiency of mHealth adoption in India. The findings of the Matrix Cross-Reference Multiplication Applied to a Classification (MICMAC) investigation show that the economic situation of the government, concerns regarding the safety of intellectual technologies and privacy issues are the primary obstacles because of the significant driving power they have in mHealth applications.Practical implicationsPromoters of mHealth practices may be able to make better plans if they understand the social barriers and how they affect each other; this leads to easier adoption of these practices. The findings of this study might be helpful for governments of developing nations to produce standards relating to the deployment of mHealth; this will increase the efficiency with which it is adopted.Originality/valueAt this time, there is no comprehensive analysis of the factors that influence the adoption of mobile health care with social cognitive theory in developing nations like India. In addition, there is a lack of research in investigating how each of these elements affects the success of mHealth activities and how the others interact with them. Because developed nations learnt the value of mHealth practices during the recent pandemic, this study, by investigating the obstacles to the adoption of mHealth and their inter-relationships, makes an important addition to both theory and practice.

Artificial intelligence as an enabler for achieving human resource resiliency: past literature, present debate and future research directions

“…He et al (2023) stated that rapidly developing technology adaptive solutions and enabling transformative management practices can enable an organization to handle crises by identifying innovative practices for organizational growth and development. Swain et al (2023) discussed that intellectual capacity is an important antecedent for adopting technological changes and enables a platform for continuous improvement. Sreenivasan and Suresh (2022) stated that AI technology application significantly improves the innovation process and creates a channel for the optimum utilization of resources.…”