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Developed countries agreed at COP15 to pay US$100bn annually for adaptation and mitigation in developing countries. This paper aims to evaluate how prepared are donors and recipients to spend this money well by analyzing institutional and organizational capabilities for climate change adaptation in least developed country (LDC) administrations using the case of Nepal, a country which can be considered to be an archetypal LDC.

The authors conducted over 100 in-depth structured qualitative interviews with government officials from across the organizational chain in the ministries concerned with climate change, ranging from the lowest-ranked employee to just under the ministerial ranks. This was supplemented with detailed surveys of three representative communities from different ecological zones in Nepal. Data were analyzed using Ostrom’s IAD framework.

Local administrations are more motivated and capable than are given credit for by donors but nevertheless face critical barriers in being able to function autonomously and confront climate change challenges. These barriers create three interrelated challenges: An organizational challenge to create intrinsic incentives which empower and grant autonomy to front line agents, an institutional challenge to go beyond accountability-focused process validation and a policy-choice challenge which avoids the temptation to write aspirational policies without clear and feasible strategies to obtain the resources necessary for their implementation.

The findings point to ways climate assistance can be restructured for more reach and effectiveness.

This paper fills a gap in the literature because community structures and institutions have been extensively analyzed in the context of adaptation, but despite being criticized, administrative structures have rarely been directly studied.

The 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.

Potential 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.

The 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.

Promoters 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.

At 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.

This study views Net-Zero as a dynamic capability for decarbonising supply chains (SCs). This study aims to investigate the relationship between three information processing-related capabilities (supply chain visibility [SCV], supply chain integration [SCI] and big data analytics [BDA]) as its antecedents and SC performance as its competitive advantage outcome.

The authors conceptualise a research model grounded in the literature based on dynamic capabilities and information processing views. The study uses a structural equation modelling technique to test the hypotheses’ relationship using the survey data from 311 industrial enterprises.

The results show that SCI and BDA positively and directly influence the Net-Zero capability (NZC). No significant direct impact is found between SCV and NZC. BDA fully mediates SCV and partially mediates SCI in their relationship with NZC. The results also confirm that NZC positively impacts SC performance (SCP).

This study contributes to operations management and SC literature by extending the knowledge about Net-Zero SCs through an empirical investigation. In particular, the study suggests BDA is essential to enhance NZC as SCV alone does not significantly contribute. The study also documents the benefit of NZC on SCP, which can encourage more volunteer actions in the industry.