Sarthak Dhingra, Rakesh Raut, Angappa Gunasekaran, B. Koteswara Rao Naik and Venkateshwarlu Masuna
This paper aims to discover and analyze the challenges hampering blockchain technology’s (BT’s) implementation in the Indian health-care sector. A total of 18 challenges have been…
Abstract
Purpose
This paper aims to discover and analyze the challenges hampering blockchain technology’s (BT’s) implementation in the Indian health-care sector. A total of 18 challenges have been prioritized and modeled based on an extensive literature search and professional views.
Design/methodology/approach
An integrated multi-criteria decision-making approach has been used in two phases. Best worst method (BWM) is used in the first phase to prioritize the challenges with sensitivity analysis to validate the findings and eliminate a few challenges. In the second phase, interpretive structural modeling is applied to the remaining 15 challenges to obtain relative relationships among them with cross-impact matrix multiplication applied to classification analysis for their categorization.
Findings
The study’s results reveal that limited knowledge and expertise, cost and risk involved, technical issues, lack of clear regulations, resistance to change and lack of top management support are the top-ranked or high-intensity challenges according to the BWM. Interpretive structural modelling findings suggest that the lack of government initiatives has been driving other challenges with the highest driving power.
Research limitations/implications
This work has been conducted in the Indian context, so careful generalization of the results is needed.
Practical implications
This work will give health-care stakeholders a better perspective regarding blockchain’s adoption. It will help health-care stakeholders, service providers, researchers and policymakers get a glimpse of the strategies for eradicating mentioned challenges. The analysis will help reduce the challenges’ impact on blockchain’s adoption in the Indian health-care sector.
Originality/value
The adoption of BT is a novel concept, especially in developing countries such as India. This is one of the few works addressing the challenges to BT adoption in the Indian health-care sector.
Details
Keywords
Apoorva Arunachal Hegde, Ajaya Kumar Panda and Venkateshwarlu Masuna
This paper aims to investigate the non-homogeneity in the speed of adjustment (SoA) of the capital structure of manufacturing companies. It also attempts to study the key…
Abstract
Purpose
This paper aims to investigate the non-homogeneity in the speed of adjustment (SoA) of the capital structure of manufacturing companies. It also attempts to study the key determinants that accelerate the speed of adjustment towards the target leverage level.
Design/methodology/approach
Using the dynamic panel fraction (DPF) estimator on the partial adjustment model, the study captures the heterogeneous SoA of 2,866 firms across eight prominent sectors of the Indian manufacturing industry from 2009 to 2020. To ensure robustness, the empirical inferences of DPF are cross-verified with the estimates of panel-corrected standard errors (PCSE).
Findings
The authors find a combination of the capital structure's slow, moderate and rapid adjustment speed along with the relevance of trade-off theory. Interestingly, the lowest and fastest SoA is recorded by the dwindling textile sector and expanding food and agro sector, respectively. Profitability, firm size, asset tangibility and non-debt tax shields are the key firm-specific parameters that impact the SoA towards the target.
Originality/value
Availing the rarely employed estimator ‘DPF’ and the objective of documenting diverse and non-uniform adjustment speeds across the Indian manufacturing sectors marks a novel addition to capital structure literature.
Details
Keywords
Apoorva Arunachal Hegde, Venkateshwarlu Masuna, Ajaya Kumar Panda and Satish Kumar
This paper aims to conduct bibliometric analysis on the studies dealing with capital structure’s speed of adjustment (SoA) and identify the prominent themes while suggesting…
Abstract
Purpose
This paper aims to conduct bibliometric analysis on the studies dealing with capital structure’s speed of adjustment (SoA) and identify the prominent themes while suggesting future research directions in the area. The existing reviews broadly focus on the capital structure, which provides the scope for conducting a review on this sub-aspect of capital structure.
Design/methodology/approach
This study uses a three-stage process to conduct this review: identification of academic journals, selection and analysis of target papers. This study uses a combination of bibliometric tools and a system thinking approach to assess the current status of publications and emerging themes within the literature.
Findings
This study has found a progressive evolution of SoA in capital structure research from 1984 to 2021. Studies largely focus on implementing the dynamic models to analyse the impact of adjustment costs, dynamic economic conditions, corporate governance practices and other variables on the firms’ adjustment speed and financial decisions. The network analysis of citations, keywords and clusters gives further knowledge on the intellectual structure of the data.
Research limitations/implications
This study is highly dependent on the papers available within the SCOPUS database. Studies not included herein are not part of this analysis, which may or may not bear an effect on the study’s findings.
Originality/value
To the best of the authors’ knowledge, the application of systems engineering concept of “system thinking approach” to identify literature gap and suggest directions for forthcoming research is the first of its kind, thus adding a novel and multidisciplinary aspect to this study.
Details
Keywords
Apoorva Arunachal Hegde, Ajaya Kumar Panda and Venkateshwarlu Masuna
This paper aims to study the leverage adjustment behavior of firms distinguished based on financial flexibility. Financial flexibility is one of the key strengths of the companies…
Abstract
Purpose
This paper aims to study the leverage adjustment behavior of firms distinguished based on financial flexibility. Financial flexibility is one of the key strengths of the companies to borrow funds for long-term capital investment. The lack of extensive studies in this domain motivates the authors to delve into the significance of financial flexibility in making corporate capital structure decisions.
Design/methodology/approach
The data comprise a combination of firm-specific and macroeconomic variables for firms in eight manufacturing sectors from 2009 to 2020. The authors employ an advance estimator, dynamic panel fraction, on the partial adjustment model to investigate the diverse impact on capital structure's speed of adjustment (SoA) between the financially flexible and financially inflexible firms. Furthermore, the authors utilize the generalized method of moments and panel-corrected standard errors to establish the robustness.
Findings
The empirical analysis reveals that the SoA of financially flexible firms lies between 19.75% and 35.38% and the SoA of financially inflexible firms lies between 11.66% and 25.81%. Due to their conserved debt capabilities, financially flexible firms can rely on leverage to stay near the target whenever they move away from it. Furthermore, financially inflexible firms exhibit a low adjustment speed due to their incompetence to borrow funds to benefit from new growth opportunities. The existence of a target ratio among the studied firms is identified from the positive coefficient of lagged dependent variable, and the relevance of trade-off theory is proved by the quick adjustment speeds in most sectors.
Originality/value
The sectoral distinction in the backdrop of the financial flexibility component adds to the research novelty and managerial implications.