Developing a Framework using Interpretive Structural Modeling for the Challenges of Digital Financial Services in India

Digital financial services (DFS) can expand the delivery of basic financial services to the poor through innovative technologies like mobile-phone-enabled solutions, electronic money models and digital payment platforms. By 2020, it is estimated that the mobile will have the potential to serve about 250 million people for financial services in India. Yet there remains a long way for India to go in digital finance. Realizing this, the objectives of the current research are to recognize various key challenges of DFS, to find contextual relationships between various challenges and to develop a hierarchy of challenges to promote DFS in India. The findings revealed 45 contextual relationships among the key challenges using experts’ inputs. Implementing interpretive structural modelling (ISM) indicated “Lack of literacy/digital literacy (C4)” and “Universal unavailability of Internet (C8)” as the key driving challenges coming on the way of using DFS

A Hierarchical Framework of Challenges for Blockchain Adoption in Public Services. Implications for decision-makers

This study attempts to identify critical challenges for blockchain adoption in government, particularly public-service delivery in India, a developing country context. Through an extensive literature review and focus-group discussions with policymakers and blockchain experts, we have identified 12 adoption challenges for Blockchain in public service delivery. We then collected data and analysed using interpretive structural modeling and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) Analysis to develop a hierarchical framework of the challenges. Our findings indicate that governments must first ensure legislative support for blockchain-based transactions. This research contributes to information systems strategic planning literature and provides a framework for policymakers to craft a strategic approach to facilitate blockchain adoption

A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

E-commerce start-ups have ventured into emerging economies and are growing at a significantly faster pace. Big data has acted like a catalyst in their growth story. Big data analytics (BDA) has attracted e-commerce firms to invest in the tools and gain cutting edge over their competitors. The process of adoption of these BDA tools by e-commerce start-ups has been an area of interest as successful adoption would lead to better results. The present study aims to develop an interpretive structural model (ISM) which would act as a framework for efficient implementation of BDA. The study uses hybrid multi criteria decision making processes to develop the framework and test the same using a real-life case study. Systematic review of literature and discussion with experts resulted in exploring 11 enablers of adoption of BDA tools. Primary data collection was done from industry experts to develop an ISM framework and fuzzy MICMAC analysis is used to categorize the enablers of the adoption process. The framework is then tested by using a case study. Thematic clustering is performed to develop a simple ISM framework followed by fuzzy analytical network process (ANP) to discuss the association and ranking of enablers. The results indicate that access to relevant data forms the base of the framework and would act as the strongest enabler in the adoption process while the company rates technical skillset of employees as the most important enabler. It was also found that there is a positive correlation between the ranking of enablers emerging out of ISM and ANP. The framework helps in simplifying the strategies any e-commerce company would follow to adopt BDA in future. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature

Benchmarking the Interactions among Challenges for Blockchain Technology Adoption:A Circular Economy Perspective

The chances of food contamination and spoilage get enhanced as it passes through various stages, and prudent consumers often need transparency on the origin of food products, their production and processing facilities utilized. Blockchain, an emerging digital technology, offers food traceability solutions to consumers and supply chain partners. But presently, blockchain adoption in Indian supply chains is in the nascent stages. The present study identified the challenges of adopting blockchain technology in Indian food supply chains and modelled them using Interpretive Structural Modelling (ISM). As per the ISM, the ‘regulatory structure’ and ‘lack of realised need’ emerged as the most significant driving forces that impact other challenges, viz. ‘privacy breach issues’, ‘high costs’, ‘lack of skills’, ‘lack of technology’, ‘lack of trust’ and ‘lack of infrastructure’. These challenges have an impact on the ‘scalability problem’. The paper underlines the significance of enabling regulatory structure, improved information and communication technologies infrastructure, and convincing the supply chain stakeholders to use blockchain technology to resolve the underlying challenges and achieve its adoption and scalability in the Indian food industry.<br/

Key challenges to digital financial services in emerging economies: the Indian context

YesPurpose: Digital Financial Services (DFS) have substantial prospect to offer a number of reasonable, appropriate and secure banking services to the underprivileged in developing countries through pioneering technologies such as mobile phone based solutions, digital platforms and electronic money models. DFS allow unbanked people to obtain access to financial services through digital technologies. However, DFS face tough challenges of adoption. Realising this, the aim of this paper is to identify such challenges and develop a framework. Design/Methodology/Approach: We develop a framework of challenges by utilising Interpretive Structural Modelling (ISM) and Fuzzy MICMAC approach. We explored eighteen such unique set of challenges culled from the literature and further gathered data from two sets of expert professionals. In the first phase, we gathered data from twenty-nine professionals followed by eighteen professionals in the second phase. All were pursuing Executive MBA programme from a metropolitan city in South India. The implementation of ISM and fuzzy MICMAC provided a precise set of driving, linkage and dependent variables that were used to derive a framework. Findings: ISM model is split in eight different levels. The bottom level consists of a key driving challenge V11 (i.e. high cost and low return related problem) whereas the topmost level consists of two highly dependent challenges namely V1 (i.e. risk of using digital services) and V14 (i.e. lack of trust). The prescribed ISM model shows the involvement of ‘high cost and low return related problem (V11)’, which triggers further challenges of DFS. Originality/value: None of the existing research has explored key challenges to DFS in detail nor formulated a framework for such challenges. To the best of our knowledge, this is the first paper on DFS that attempts to collate its challenges and incorporate them in a hierarchical model using ISM and further divide them into four categories of factors using fuzzy MICMAC analysis

Determining the Factors Influencing Cloud Computing Implementation in Library Management System (LMS): A High Order PLS-ANN Approach

The principal component of this paper is to ascertain the prominent variables of technological, organizational, environmental, and financial constructs that influence library cloud computing (LCC) among the library users and professionals in the selected universities of India. This paper discusses the advantages, opportunities, challenges, and Models of Smart Library in the ICT age library management system. The study also commissioned tools viz. EFA, CFA, and structural equation assess the degree to which selected factors were associated with LCC adoption. Empirical research proposed four hypotheses by selecting the technological, organizational, environmental, and financial constructs and 16 manifests in the specified model. The model was then tested on a sample of 510 respondents of 26 major states, central and private universities of India using SEM-ANN. First, SEM was employed to find out which variables had a meaningful influence on LCC. Secondly, the output of ANN outlined the rank of influencing predictors obtained from SEM. It is evident that technological factors, greater scalability (TF_1), tech-readiness (TF_2), and easier back-up (TF_3), are the most robust antecedents of LCC. Whereas in organizational factors- recognized usefulness (OF_1), are the robust manifest, but in environmental factors-geographical reach (EF_1), administrative support (EF_2), conducive application interface (EF_4), are the significant predictors. Eventually, financial factors- cost-saving (FF_1) and better return on investment (FF_2) are the considerable predictors obtained from ANN. The findings further indicate that behavioural intention to adopt the library cloud yielded novel insights that significantly benefit users and stakeholders

Modelling of Determinants of Logistics 4.0 Adoption: Insights from Developing Countries

With the emergence of industry 4.0, several elements of the supply chain are transforming through the adoption of smart technologies such as blockchain, the internet of things and cyber physical systems. Logistics is considered one of the important elements of supply chain management and its digital transformation is crucial to the success of industry 4.0. In this circumstance, the existing logistics system needs to be upgraded with industry 4.0 technologies and emerge as logistics 4.0. However, the adoption/transformation of logistics 4.0 is dependent on several determinants that need to be explored. Therefore, this study has the prime objective of investigating the determinants of logistics 4.0 adoption in the context of a developing country, specifically, India. Initially, ten determinants of logistics 4.0 are established after a survey of the relevant literature and the input of industry experts. Further, a four-level structural model is developed among these determinants using the Interpretive Structural Modelling (ISM) approach. In addition, a fuzzy Matrix of Cross-Impact Multiplications Applied to Classification (MICMAC) analysis is also conducted for the categorization of these determinants as per their driving and dependence power. The findings show that top management supports, information technology infrastructure and financial investment are the most significant determinants towards logistics 4.0 adoption. This study facilitates the supply chain partners to focus on these high-level determinants for the effective adoption of logistics 4.0. Moreover, the findings lead to a more in-depth insight into the determinants that influence logistics 4.0 and their significance in logistics 4.0 adoption in emerging economiesinfo:eu-repo/semantics/publishedVersio

India Posts Putting Its Best Leg Forward: A Case On ICT4D

Literature has provided a robust evidence on the link between financial inclusion and development. The onus lies on governments on ensuring the diffusion of financial services to the remote corners of the nation. The rapid diffusion, penetration and global reach of Information Communication Technologies (ICT) have assisted and continues to assist this aim of governments to a large extent. Financial management is, for the poor, a fundamental and well-understood part of everyday life. To enable them with better access to needs in life leading to social inclusion, they have to supported by external financial services. In light of this scenario, this paper attempts to understand a project from the Actor Network Theory (ANT) perspective focussing on improving the disbursement of financial services in an emerging economy. Statistics indicate India has the lowest penetration of banks/ATMs per 100,000 population compared to any of the BRICS nation. The Indian Postal department utilising its large Postal Network in the world with 90% penetration in the rural areas leverage this large network for disbursement of financial services to all citizens focussing primarily on rural villages. Bringing banking services closer to citizens through these post offices ensure efficient, accessible and readily available banking network across the nation. Thereby guaranteeing financial inclusion to the rural populations. The paper highlights the dynamics and the network involved in the process of ensuring financial inclusion, followed by addressing the critical success factors and pain points in the development of this project. The study provides an example of an emerging economy utilising the available resources attempt to attain development through efficient banking system

Modeling technological change on telecenter effectiveness

Technological change (TC) is the overall process of continuous invention, innovation and diffusion of technology that aims at improving the quality of technical performance. Without TC, there would be no business growth and development particularly in a telecenter. A telecenter is public environments that people develop essential digital skills to access information and communications technologies to create, learn and achieve their specific needs. The major goal of a telecenter is to bridge the digital gap between the urban and the rural areas, and provide digital support services to the neighbouring community. Telecenter effective usage is a major issue of telecenter sustainability because it has been found that there a lack of usage. Hence, this study focused on identifying TC factors that contribute significantly to telecenter effectiveness. The first objective of the study was to identify the contributing factors of TC. The second objective was to construct a computational model based on selected factors obtained from objective 1. The third objective was to evaluate the effectiveness of the model. The research was conducted using the computational model approach through three phases: abstraction, formlization, and evaluation. The results showed that the computational model was able to show the effect of the selected TC on telecenter effectiveness in different types of scenarios. The usage of telecenter can be more effective by considering the TC factors that are appropriate