Big Data Analytics Adoption in the Indian Insurance Industry: Challenges and Solutions

PurposeThe purpose of this paper is to provide an insight about factors affecting Big Data Analytics (BDA) utilization and adoption in Indian firms. Research studies have so far focused on BDA adoption in developed economies. This study examines the factors that influence BDA usage and adoption in the context of emerging economies.Design/methodology/approachThis study proposed a theoretical model of factors influencing BDA utilization and adoption. Two independent research streams – first, the top managers’ perceived strategic value (PSV) in BDA and second, the factors that influence the adoption of BDA theoretically – have been integrated with the technology-organization-environment (TOE) framework. In the BDA context, there was a theoretical necessity to identify the driver and barriers of BDA from the TOE framework on PSV and adoption of BDA. A qualitative exploratory study using face-to-face semi-structured interviews was carried out to collect data from 22 different enterprises and service providers in India. India was selected as the context as it is one of the fastest growing large economies of the world with huge potential of BDA to improve the business landscape.FindingsThe results showed that the major reason behind BDA non-adoption is that the organizations did not realize the strategic value (SV) of BDA, and they were not ready to make the changes because of technological, organizational and environmental difficulties. The findings corroborate previous results about significant factors affecting IT adoption and implementation and provide new and interesting insights. The main factors identified as playing a significant role in organizations’ adoption of BDA were SV of BDA, complexity, compatibility, IT assets, top management support, organization data environment, perceived costs, external pressure and industry type.Research limitations/implicationsThe main limitation related to this study is the difficulty in generalizing the findings to a larger population of enterprises. To overcome this, a statistical survey has been planned to be conducted in the future.Practical implicationsThe BDA adoption model in this study will have both managerial implications for practitioners in India, as well as those in other developing countries, and academic implications for researchers who are interested in BDA adoption in developing counties, in terms of formulating better strategies for BDA adoption. For managers, using the research model of this study could assist in increasing their understanding of why some organizations choose to adopt BDA, while similar ones facing similar conditions do not. Also, the understanding of the strategic utilization of BDA in different business processes may improve the adoption of BDA in organizations.Originality/valueThis paper contributes in exploring and enhancing the understanding of the factors affecting the utilization and adoption of BDA in organizations from an Indian perspective. This study is an attempt to develop and explore a BDA adoption model by the fusion of PSV and TOE framework. The effect of the three contexts of this framework (technological, organizational and environmental) on the strategic utilization of BDA has been studied for the first time.

Big data analytics (BDA) adoption has gained attention in both practical and theoretical circles owing to the opportunities and advantages that can be reaped from it. In theory, the majority of researchers have evidenced the benefits of BDA, although barriers to its adoption have also been mentioned. This study draws upon the technology-organisation-environment framework and resource-based view theory to propose an integrated model that examines the drivers and impact of BDA adoption in the retail industry in Jordan. The proposed single model encapsulates the aspects of BDA adoption and performance. The study makes use of an online questionnaire survey to collect the required data, and the research model is eventually validated based on 132 responses gathered from the retail industry in Jordan. The findings highlight two major observations. The first is that relative advantage, organisational readiness, top management support, government support, data variety and data velocity all have a significant influence over BDA adoption. The second observation is that a significant association exists between BDA adoption and firm performance, providing information on the way firms can enhance their BDA adoption for enhanced performance. This study contributes to literature dedicated to examining BDA in terms of its drivers and impact on performance and can be used as a reference in developing nations.

Implementing Big Data Analytics (BDA) could enhance the efficiency and effectiveness of Community Health Centres (CHCs). This study focuses on improving healthcare service delivery in CHCs located in the Nkangala District through the adoption of BDA. It identifies a specific research gap and seeks to consolidate existing knowledge while revealing challenges and opportunities in BDA implementation. This literature review was conducted using a systematic method that adheres to PRISMA principles. The review process involved the identification and selection of peer-reviewed publications in English up to 2024. The search was carried out among several major academic databases, including PubMed, Taylor & Francis Online, Google Scholar, IEEE Xplore, SpringerLink, ScienceDirect, and JSTOR. Specific search terms related to data-driven approaches and healthcare service delivery were used. The inclusion criteria focused on studies addressing the adoption and implementation of BDA in CHCs, while exclusion criteria eliminated studies not relevant to this context. The selected studies were analysed to assess the research state, identify key themes, and highlight gaps and challenges in BDA adoption within CHCs. A total of 31 studies met the inclusion criteria, demonstrating variability in study design, geographic location, and focus areas related to BDA adoption and implementation. The synthesis of results unveiled common challenges, best practices, and outcomes associated with BDA implementation, including technological, organizational, and human factors influencing successful integration. The development and implementation of data-driven methodologies in healthcare service delivery present several challenges, including evidence limitations such as heterogeneity in study designs, restricted generalizability, and variability in study quality. Additionally, the short duration of many studies complicates the evaluation of their long-term impacts. Despite these challenges, the transformative potential of data-driven approaches highlights the necessity for further research to enhance adoption strategies and address existing research gaps.

This paper investigates the challenges in implementing enterprise risk management (ERM) in the Indian insurance sector. This is the first such study within the Indian insurance market, which is essential for risk management professionals, policy makers and regulators to understand these gaps and work towards addressing them. The Government of India has recently opened the Indian insurance sector for 100 per cent foreign direct investment, and this paper will be helpful for new investors in the Indian market. The research adopts a semi-structured interview-based approach to address the research problem under investigation. The respondents are primarily senior risk professionals in the Indian insurance industry. The paper identifies an inadequate understanding of the roles and responsibilities of the first and second line of defence. There are challenges in the quantification of non-financial risk as well as the availability of data for this purpose. There is inadequate risk training and a lack of standard risk language among the insurance companies. The authors recommend (based on the results of this paper) that the regulator and the Board of Insurance Companies should work together to address these gaps and make the Indian insurance sector more robust and resilient to manage future emerging risks. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.

One of the key responsibilities of a government is to provide efficient health care services that are better and affordable. In Burundi, patients’ health records are collected using handwritten forms and stored in filing cabinets. Evidence’ based research and practice shows that adoption of a Big Data Analytics (BDA) system can significantly improve health care services. Unfortunately, BDA adoption models and automated assessment tools are lacking not to mention the dearth caused by researchers’ predominant focus on the technical aspects. Therefore, the aim of this study was to propose a BDA system adoption model for improving health care services in Burundi’s public hospitals. This was achieved through a mixed research method a large part being qualitative. The factors that influence the adoption of BDA in public healthcare services using the Technology Organization Environment (TOE) adoption theory through a desk research. Semi-structured interviews, observations and document reviews were used to investigate the methods used to collect, store and analyze data in Public hospitals of Burundi. Afterwards, a web based automated Adoption Readiness Assessment Tool (ARAT) was developed then used to assess the readiness of Burundi in adopting a BDA system in its public hospitals. The assessment results showed that the country has adequate telecommunication infrastructures and has started using information systems like OpenClinic and District Health Information Software 2 (DHIS2) in some public hospitals, the government has set up policies for e-Health and the level of awareness is high as well among health workers. But there are improvements to be made in order to assure that the adoption is successful. Lastly, a tailored adoption model was proposed describing what should be done and how in order to assure a successful adoption of a BDA in public hospitals.

Background: The idea of insurance was discovered several millennia before Christ (BC). In the second and third millennia BC, traders from China and Babylonia practiced shifting or dispersing risks. Today, insurance is the foundation of the economy, but expanding its penetration is difficult in emerging nations. The fourth insurance industry revolution in the developed world was sparked by the recent advent of IoT, Big Data, and InsurTech. Objective: To boost insurance coverage in Morocco, this study examines the problems with and potential solutions to InsurTech, IoT and bigdata analytics. Research Methodology: To identify the themes and factors pertaining to problems and solutions in implementing InsurTech, IoT and bigdata analytics in Morocco's insurance business, this study used a systematic literature review. To find pertinent material from Google Scholar, several keywords were employed. The filtered studies were examined based on inclusion and exclusion standards. Findings: This report outlined many obstacles to InsurTech, IoT and bigdata analytics adoption in the Morocco insurance sector as well as potential remedies. The proposals could help policymakers improve the insurance industry service delivery. InsurTech, Insurance Industry, Digital Technologies, Morrocco, IoT and bigdata analytics..

The concept of insurance was found several centuries before Christ. Correspondingly, Chinese and Babylonian traders practiced moving or dispensing risks in the second and third millennia BC. Nowadays, insurance is the backbone of the economy. The recent introduction of big data, IoT, and other forms of InsurTech led to the fourth industrial revolution in insurance in the developed world. The industry is looking to improve the ergonomics of remote sensing technology to improve the acceptability of the clients. The adaptation of IoT in developing economies may provide a solution in increasing insurance penetration. This study explores the challenges and solutions in adopting IoT to increase insurance penetration in India. This study applied a systematic literature review (SLR) to extract the themes/variables related to challenges and solutions in adopting IoT in India’s insurance sector. Several keywords were used to search the relevant literature from Google Scholar. Based on inclusion and exclusion criteria, the filtered studies were explored. This study listed several challenges and their solutions in the adaption of IoT in the Indian insurance industry. Policymakers could adapt the suggestions provided to improve the service delivery insurance sector. The authors listed several challenges and solutions in the adaption of IoT in the Indian insurance industry through a systematic literature review to facilitate the policymakers to make the right decisions.

This study explores the relationship between financial reporting quality and insurer governance, with the hypothesis that robust governance procedures exert better control over managers’ opportunistic behavior. The analysis is based on a dataset of insurer firms from 2014 to 2021. The econometric results obtained using the two‐step system GMM technique reveal that the overarching influence of corporate governance on enhancing financial reporting quality is evident, with board and risk governance matters the most. Among individual governance attributes, the optimal board size, a higher proportion of independent directors, audit and risk committees’ size, and risk committee independence play a significant role in governing discretionary accruals. The efficacy of governance mechanisms considerably differs across life and non‐life insurers, shedding light on the nuanced dynamics within the Indian insurance market. The results lend empirical support to resource dependency and agency theories within the Indian insurance sector. The implications suggest potential avenues for amending or redesigning governance norms with specificities of insurers and the ultimate goal of fostering an environment conducive to enhancing the reporting quality of Indian insurance firms.

The adoption of big data analytics (BDA) is increasing pace both in practice and in theory, owing to the prospects and its potential advantages. Numerous researchers believe that BDA could provide significant advantages, despite constant battles with the constraints that limit its implementation. Here, we suggest an incorporated model to investigate the drivers and impacts of BDA adoption in the Jordanian hotel industry based on the technology–organisation–environment framework and the resource-based view theory. The suggested model incorporates both the adoption and performance components of BDA into a single model. For data collection, in this study, we used an online questionnaire survey. The research model was verified based on responses from 119 Jordanian hotels. This study yielded two significant findings. First, we discovered that relative advantage, organizational readiness, top management support, and government regulations have a major impact on BDA adoption. The study results also reveal a strong and favourable association between BDA adoption and firm performance. Finally, information sharing was found to have a moderating effect on the association between BDA adoption and firm performance. The data revealed how businesses might increase their BDA adoption for improved firm performance. The present study adds to the limited but growing body of literature investigating the drivers and consequences of technology acceptance. The findings of this study can serve as a resource for scholars and practitioners interested in big data adoption in emerging nations.

Talent management is a critical area of focus in the Indian insurance sector, which is experiencing exponential rise, competition, and transformation. This bibliometric analysis aims to provide a detailed understanding of the intellectual structure, thematic trends, and performance patterns in the academic literature on this topic. Using analytical tools and science mapping methodologies, the study synthesizes insights from 25 high-quality, peer-reviewed research articles published between 2014 and 2024. These articles/papers highlight key contributions from prominent authors, institutions, and journals, while uncovering thematic clusters such as employee retention strategies, technological integration in HR practices, and public versus private sector dynamics. The analysis points to a regular growth in research outcomes, driven by the sector's challenges such as high attrition rates, talent shortages, and the integration of digital tools in workforce management. It also identifies emerging trends like AI-driven HR analytics and workplace engagement practices as essential in addressing talent-related issues. However, gaps persist in areas like regional disparities, cross-sectoral comparisons, and the impact of cultural factors on HR practices. By resolving these disparities, this bibliometric analysis offers practical recommendations for practitioners and establishes a groundwork for future research on effective talent management strategies in the Indian insurance industry.

This study explores the growth potential and role of digital repositories in the Indian insurance industry, focusing on how e-Insurance Accounts (eIAs) simplify policy management and enhance customer engagement. By providing centralized access to policy information, these repositories facilitate faster claims processing, reduce paperwork, and improve overall convenience for policyholders. The study examines four leading insurance repositories: NSDL Database Management Limited (NDML), CAMS Repository Services Limited (CAMSRep), Karvy Insurance Repository Limited (KIRL), and Central Insurance Repository Limited (CIRL), which collectively manage millions of e-Insurance accounts and policies. These repositories, operating under the Insurance Regulatory and Development Authority of India (IRDAI), play a crucial role in facilitating the digital management of insurance policies. By offering secure, centralized platforms, they streamline policy administration, enhance customer convenience, and support the broader digitalization efforts within the Indian insurance sector. A qualitative research methodology was employed, utilizing data from official annual reports and service documents from insurance repositories. The study also reviewed trends in policy digitalization and repository growth, focusing on user experiences and system efficiencies. Despite the benefits, challenges such as limited awareness, low digital literacy, and concerns over data security hinder wider adoption of e-Insurance Accounts. The findings highlight the transformative impact of digital repositories in the Indian insurance sector and the need for strategies to promote smoother transitions to digital platforms, ensuring enhanced customer satisfaction and operational efficiency.

Technology has revolutionized business operations around the world. There is an ever-increasing trend to digitize business operations around the world. It is not uncommon to see the application of Big Data Analytics (BDA) throughout a vast range of industries and organizations in today's extremely competitive world. However, BDA adoption in supply chain (SC) is less accepted and research in this area remains at its infancy. BDA is extremely useful throughout supply chain functions like manufacturing, distribution, procurement, and marketing. However, a sizable portion of sectors continues to hold divergent opinions regarding big data's alleged benefits. Moreover, there is not a lot of empirical studies that have been published that addresses the adoption of such a tool or better yet, that investigates what factors affect the decision to adopt BDA in supply chain management (SCM). This study aims to develop and extend technology acceptance model (TAM) that considers the critical factors that may affect BDA adoption in SCM by critically analyzing the existing literature. Upon reviewing the literature, it became evident that the main categories of factors that have been thoroughly examined and recognized to be crucial in comprehending BDA adoption and acceptability in SCM are the organizational- and individual-related factors, such as top management and computer self-efficacy.

The insurance industry has marked its importance in augmenting the process of economic growth through its prominent contribution in terms of financial intermediation, capital accumulation, resource allocation and risk protection. The Indian insurance industry has shown a sharp rise since the formation of Insurance Regulatory and Development Authority in 1999. Assuming the important and potential role of insurance, this study aims to investigate the macro-economic factors that may influence the life insurance sector in India with time-series data covering a period of 39 years (1980-2018). Employing Engle-Granger co-integration, ordinary least square regression and causality analysis it is found that foreign direct investment (FDI), broad money (M2) and gross capital formation (GCF) positively and significantly influence insurance sector growth in India. Engle-Granger causality test reveals one way causal relationship from GCF to life insurance penetration, whereas FDI and M2 are in reverse causality that runs from insurance penetration. The practical implication of this study lies in utilising the findings of this study by the policymakers in framing favourable policies to ensure sustained growth of the life insurance sector in India. The study is limited to the consideration of macro-economic factors only.

Background and Aim: The author provides a foundational understanding of Big Data, describing its characteristics and the inadequacy of traditional management methods. This serves as a general introduction to the topic. However, this section could more explicitly articulate the specific research problem or gap concerning Big Data Analytics (BDA) adoption within Small and Medium-Sized Enterprises (SMEs) in the Eastern Economic Corridor (EEC). While the importance of BDA for strategic decision-making and competitive advantage is mentioned, a more direct linkage to the challenges or unique circumstances of SMEs in this particular region would strengthen the problem statement. The research aims to investigate BDA adoption among SMEs in the EEC, as clearly stated. This section effectively introduces the theoretical underpinnings by referencing the Technology-Organization-Environment (TOE) framework and the Technology Acceptance Model (TAM). The author correctly identifies key components of these frameworks—technological attributes, organizational conditions, external environmental factors from TOE, and perceived usefulness and perceived ease of use from TAM. To further enhance this, a concise justification for selecting these specific frameworks, perhaps highlighting their relevance to understanding technology adoption in an SME context or their complementary nature, would add depth. The objectives are well-defined, aiming to identify critical influencing components and analyze relationships among variables, which guide the study. Material and Methods: The author clearly outlines the methodological approach. The sample group of 340 SME entrepreneurs in the EEC, selected via purposive sampling, is appropriately described. This section precisely details the primary data collection instrument as a questionnaire, structured into six sections, differentiating between open-ended and closed-ended Likert scale questions. The inclusion of specific validation metrics - a content validity index (IOC) of 0.874 and an overall reliability (Cronbach’s alpha) of 0.936 - is commendable. These values indicate a robust instrument, which is essential for the credibility of quantitative research findings. This level of detail in the abstract is suitable, providing confidence in the data collection process. Results: The author presents key findings from the statistical analyses with precision. The result from Confirmatory Factor Analysis (CFA) highlights organizational leadership capability as the most influential observed variable, with a beta coefficient of 0.915. This emphasizes its importance in fostering technology acceptance and implementation, especially for SMEs facing competitive pressures and rapid technological changes in the EEC. Furthermore, the Structural Equation Modeling (SEM) analysis is reported to show a strong and statistically significant relationship between technological factors and perceived usefulness (β = 0.653, p < 0.01). The inclusion of specific fit indices (Chi-square = 686, df = 350, p-value = 0.001, and RMSEA = 0.032) confirms a good model fit. These findings provide concrete evidence of the variables influencing BDA adoption, aligning well with the study's objectives. Conclusions: The analysis concludes that a supportive organizational system significantly influences employees’ confidence and perceived ease of use with information technology. This directly connects to the findings regarding organizational leadership and perceived ease of use. The author emphasizes that when organizational structures align with technological goals, employees are more likely to integrate technology into their work. Based on these insights, the author provides actionable recommendations for SMEs in the EEC. These include prioritizing leadership development through continuous training and knowledge enhancement, enabling leaders to drive technology adoption. Additionally, the author suggests improving internal systems for flexibility and responsiveness to technological changes, fostering an innovation-friendly culture, and providing staff training in BDA. This section effectively summarizes the study's implications, highlighting how these efforts can lead to sustainable growth, market competitiveness, and effective adaptation in the digital era. However, the terms "Organization" and "Technology" are very broad. To enhance specificity and improve the discoverability of this research, it is recommended to use more precise terms. For instance, "Organizational Factors," "Organizational Readiness," or "Organizational Culture" would better capture the nuanced aspects of the organization's role in BDA adoption as discussed in the abstract, particularly the emphasis on leadership and internal systems. Similarly, "Technological Factors," "Technological Readiness," or "Technology Adoption" would be more specific than simply "Technology," aligning more closely with the study's focus on adoption. Including "Small and Medium-Sized Enterprises" (SMEs) and "Eastern Economic Corridor (EEC)" as keywords would also be beneficial, as these are critical contextual elements of the research, ensuring the study is easily found by those interested in this specific sector and geographic region.

PurposeThe study challenges the assumption of independence among Technological, Organizational and Environmental (TOE) factors and investigates the influence of TOE factors on Big Data Analytics (BDA) adoption among Small and Medium Enterprises (SMEs). Top management support was proposed as a mediator between technological and organizational factors and BDA adoption. Furthermore, the moderating effect of environmental factors on the association between relative advantage, compatibility, competitiveness, organizational readiness and BDA adoption was evaluated.Design/methodology/approachData were collected from 171 SME manufacturing firms and analyzed using the partial least squares technique.FindingsThe findings confirmed the interrelationships among the TOE factors. The effects of compatibility, competitiveness and organizational readiness on BDA adoption were mediated by top management support. Furthermore, environmental factors moderate the influences of compatibility and organizational readiness on top management support.Originality/valueThe findings contribute to the TOE model by challenging the assumption of independence among TOE factors, and future studies should use this model with more caution and consider the potential relationships between TOE factors.