AI strategy of India: policy framework, adoption challenges and actions for government

Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023

BACKGROUND

Recently, the application of deep learning (DL) has made great progress in various fields, especially in cancer research. However, to date, the bibliometric analysis of the application of DL in cancer is scarce. Therefore, this study aimed to explore the research status and hotspots of the application of DL in cancer.

METHODS

We retrieved all articles on the application of DL in cancer from the Web of Science database Core Collection database. Biblioshiny, VOSviewer and CiteSpace were used to perform the bibliometric analysis through analyzing the numbers, citations, countries, institutions, authors, journals, references, and keywords.

RESULTS

We found 6,016 original articles on the application of DL in cancer. The number of annual publications and total citations were uptrend in general. China published the greatest number of articles, USA had the highest total citations, and Saudi Arabia had the highest centrality. Chinese Academy of Sciences was the most productive institution. Tian, Jie published the greatest number of articles, while He Kaiming was the most co-cited author. IEEE Access was the most popular journal. The analysis of references and keywords showed that DL was mainly used for the prediction, detection, classification and diagnosis of breast cancer, lung cancer, and skin cancer.

CONCLUSIONS

Overall, the number of articles on the application of DL in cancer is gradually increasing. In the future, further expanding and improving the application scope and accuracy of DL applications, and integrating DL with protein prediction, genomics and cancer research may be the research trends.

The Brazilian (Non)perspective on national strategy for artificial intelligence

This article examines the design dynamics and process of the Brazilian National Strategy for Artificial Intelligence (EBIA). We argue that Brazil has a long history of policies for digital development, covering a range of policies that encourage research and development and deploy AI-based digital technologies in industry and governments. Specifically for the AI policy, we analyze how these policies are fragmented into different initiatives without an approach to integrating the instruments and their mixes. We analyze how and why the Brazilian National Strategy for Artificial Intelligence design fails to implement and create an integrated perspective of these policies. This perspective for AI policy in Brazil results in fragmentation and failures to involve actors in the formulation and implementation process. The article concludes that the Brazilian perspective for artificial intelligence, emerging with EBIA, reproduces a situation of path dependence without promoting significant policy changes for the development and application of this technology in society.

Artificial Intelligence Adoption and Digital Innovation: How Does Digital Resilience Act as a Mediator and Training Protocols as a Moderator?

This study aims to discover how technology firms accomplish digital innovation through AI adoption. The current research also investigated digital resilience’s role as a mediator and training protocol’s role as a moderator between AI adoption and digital innovation links. The data collection and analysis were conducted using a quantitative method. To examine the research hypotheses, we chose technology firms that face problems regarding the enhancement of digital innovation. The findings confirmed that the digital innovation of technology firms is forecasted through AI adoption. The results proved that digital resilience plays a mediating role between AI adoption and digital innovation links. Technology firms play a key role in the advancement of digital technology. This research study adds to the existing knowledge by offering a digital innovation model with the combined influence of AI adoption, digital resilience, and training protocol. This study will be helpful for top management by showing when, why, and how AI adoption helps firms in their achievement of digital innovation. Moreover, digital resilience’s role is also important in the current digitalized world; thus, we used digital resilience as mediator in this research.

Big data driven innovation for sustaining SME supply chain operation in post COVID-19 scenario: Moderating role of SME technology leadership

Due to the COVID-19 pandemic, there is an unprecedented crisis for businesses. The small and medium enterprises (SMEs) have been impacted even more, due to their limited resources. Extant literature has prescribed many treatments on how SMEs could survive in post COVID-19 situation, but studies did not analyse how big data driven innovation could improve supply chain management (SCM) process in the post COVID-19 pandemic under the moderating influence of SME technology leadership support. Thus, there is a research gap in this important domain. The aim of this study is to examine the impact of big data driven innovation and technology capability of the SME on its supply chain system. The study also investigates the moderating role of SME technology leadership support on SME performance in the post COVID-19 scenario. With the help of literature and resource-based view (RBV) and dynamic capability view (DCV) theory, a theoretical model has been developed conceptually. Later the model is validated using structural equation modelling (SEM) technique with 327 usable respondents from SMEs from India. The study found that both big data driven innovation and the techno-functional capability of SME impacts supply chain capability which in turn impacts the SME performance in the post COVID-19 scenario. The study also finds that there will be a moderating impact of SME technology leadership support on SME performance.

A Case Of Affordances-Collaborative Governance Using Smartphones

This study attempts to explore the contextual factors that play a significant role in promoting collaborative governance using mobile phones in developing countries. The study utilises review of academic literature and experts’ opinion to identify critical conversion factors and their interrelationship. Affordance Theory is used as a theoretical lens to identify eight significant factors covering development of infrastructure, citizen up-skilling, cost of access, ease of use, reliable infrastructure, ensured privacy & security, process accountability and a standardised m-governance policy. A combination of Total Interpretative Structure Modelling (TISM) and Cross-impact matrix multiplication applied to classification (MICMAC) analysis is employed to prioritise these conversion factors and classify them based on their dependence and driving power. A priority-based hierarchical model is proposed for establishing a sustainable m-governance ecosystem.

A systematic literature review towards a conceptual framework for enablers and barriers of an enterprise data science strategy

While embracing digitalization that is further accentuated by the Covid-19 pandemic, the real business outcome is achieved through a robust and well-crafted ‘Data Science Strategy’ (DSS), as significant constituent of Enterprise Digital Strategy. Extant literature has studied the challenges in adoption of components of ‘Data Science’ in discrete for various industry sectors and domains. There is dearth of studies on comprehensive ‘Data Science’ adoption as an umbrella constituting all of its components. The study conducts a “Systematic Literature Review (SLR)” on enablers and barriers affecting the implementation and success of DSS in enterprises. The SLR comprised of 113 published articles during the period 1998 and 2021. In this SLR, we address the gap by synthesizing and proposing a novel framework of ‘Enablers and Barriers’ influencing the success of DSS in enterprises. The proposed framework of ‘Data Science Strategy’ can help organizations taking the right steps towards successful implementation of ‘Data Science’ projects.

Achieving a 'Good AI Society': Comparing the Aims and Progress of the EU and the US

Over the past few years, there has been a proliferation of artificial intelligence (AI) strategies, released by governments around the world, that seek to maximise the benefits of AI and minimise potential harms. This article provides a comparative analysis of the European Union (EU) and the United States' (US) AI strategies and considers (i) the visions of a 'Good AI Society' that are forwarded in key policy documents and their opportunity costs, (ii) the extent to which the implementation of each vision is living up to stated aims and (iii) the consequences that these differing visions of a 'Good AI Society' have for transatlantic cooperation. The article concludes by comparing the ethical desirability of each vision and identifies areas where the EU, and especially the US, need to improve in order to achieve ethical outcomes and deepen cooperation.

Dark side of instant messaging: an empirical investigation from technology and society perspective

Purpose

The purpose of this study is to examine the dark side of instant messaging from the technological and societal perspectives.

Design/methodology/approach

With the help of literature review and different theories, a model has been developed conceptually. Later the model has been validated using statistical method. The authors have used 304 responses from the survey method, and this sample has been used to statistically validate the conceptual model.

Findings

This paper has been able to explicitly investigate and identify how different instant messaging platforms such as WhatsApp, WeChat in the form of electronic word of mouth (e-WOM) are contributing toward increase of mob lynching cases. The paper also highlights the important to have effective and enforceable regulation to regulate instant messaging services to the citizens.

Research limitations/implications

The findings cannot be generalized as the data is collected from India only. Moreover, the study is cross-sectional in nature. To get the comprehensive results, a longitudinal study needs to be conducted. This study considered seven constructs with one moderator. Having more predictors with other boundary conditions might have increased the explanative power of the model.

Practical implications

Instant messaging platforms such as WhatsApp, WeChat and so on are disseminating quick unverified information to the common people. This information sometimes is disseminated in inappropriate and exaggerated forms. This makes the instant messaging (WhatsApp) users' sentiment readily heated in some cases. They take such an action as mob lynching. This study determines the predictors of mob lynching along with the moderator impact of instant messaging in the society.

Originality/value

There are only a few studies those have explored the dark side of instant messaging. The proposed theoretical model is a unique model, which shows the predictors of mob lynching along with the negative consequences of the instant messaging (WhatsApp) in the society. From this perspective, this study can be considered as a unique study.

Digital transformation and entrepreneurship process in SMEs of India: a moderating role of adoption of AI-CRM capability and strategic planning

Purpose

The purpose of this study is to identify the determinants that could impact corporate digital entrepreneurship for the small and medium enterprises (SMEs) of India. The study also investigates the moderating role that adopting artificial intelligence (AI)-customer relationship management (CRM) capability and strategic planning has in corporate digital entrepreneurship.

Design/methodology/approach

With the inputs from literature and theories, a model has been developed conceptually. The model has been validated by partial least squares structural equation modeling technique with consideration of 315 usable respondents. The effects of the moderators have also been investigated by multigroup analysis.

Findings

The study highlights that perceived usefulness, perceived ease of use and willingness to change significantly impact corporate digital entrepreneurship for the SMEs of India. The study also highlights that the two moderators have significant impacts on the relationships between corporate digital entrepreneurship and its predictors.

Research limitations/implications

This study has developed a unique model, which provides effective inputs to the entrepreneurs of SMEs of emerging economies. These inputs will help entrepreneurs to frame their policies to improve the existing traditional practices and processes that could be transformed into more digitalization for improving efficiency of their corporate digital entrepreneurial activities.

Originality/value

There are no studies which investigated how perceived usefulness, perceived ease of use and willingness to change could impact corporate digital entrepreneurship with the moderating effects of adoption of AI-CRM capability and strategic planning, as concerns SMEs of emerging economies. In this regard, this study is deemed to be a unique attempt.

Responsible Artificial Intelligence (AI) for Value Formation and Market Performance in Healthcare: the Mediating Role of Patient's Cognitive Engagement

The Healthcare sector has been at the forefront of the adoption of artificial intelligence (AI) technologies. Owing to the nature of the services and the vulnerability of a large section of end-users, the topic of responsible AI has become the subject of widespread study and discussion. We conduct a mixed-method study to identify the constituents of responsible AI in the healthcare sector and investigate its role in value formation and market performance. The study context is India, where AI technologies are in the developing phase. The results from 12 in-depth interviews enrich the more nuanced understanding of how different facets of responsible AI guide healthcare firms in evidence-based medicine and improved patient centered care. PLS-SEM analysis of 290 survey responses validates the theoretical framework and establishes responsible AI as a third-order factor. The 174 dyadic data findings also confirm the mediation mechanism of the patient's cognitive engagement with responsible AI-solutions and perceived value, which leads to market performance.

Design and behavior science in government-to-citizens cognitive-communication: a study towards an inclusive framework

Purpose

The purpose of this paper is to describe the application of design and behavior science collectively in refining the government to citizens’ (G2C) cognitive-communication by using artificial intelligence (AI) artifacts. It investigates the citizens’ behavior intention to use AI cognitive-communication channels in e-government services.

Design/methodology/approach

This study reveals the potential of unification in design and behavior science paradigms when integrated into AI artifacts in measuring the constructive outcome of proposed architecture that embraces the perceived risk and trust in citizens’ usage behavior intentions. To evaluate the practical relevance of design science paradigm, action research was incorporated by developing an app as an exemplified scenario.

Findings

The weaknesses of traditional G2C channel communication obliterated by AI virtual agents. This study proposes a five-layer architecture model created with citizens-centered design highlighting the improved relevance for G2C cognitive-communication. The behavior model supports citizens’ usage behavior intentions through trust as a positive attribute and negative attribute as a perceived risk.

Research limitations/implications

This study contributes to the knowledge of design science paradigm particularly to AI-based cognitive G2C communication. The architecture serves for deploying virtual agents to automate the public officials for decision-making processes. The authors have constructed a cognitive-communication model and have examined the relationships among the extents of cognitive-communication model. This channel has the potential to significantly transform G2C cognitive and intelligent communication.

Practical implications

This cognitive-communication channel has the potential to significantly transform the communication between government and citizens. Such a model can be an interest of developers, researchers and government policymakers in a holistic approach drawn from theory and methods of both design and behavior science to create a successful communication scenario.

Social implications

Advances in technology are not without social implications. The study results can dramatically improve the efficiencies of government workplaces and can augment the human working. It will help to reduce the government services discriminations among the citizens and contribute to society through social inclusion.

Originality/value

This study addresses the duality in information system research by first defining the theoretical framework for G2C cognitive-communication architecture and then developing a research model drawn upon a citizens’ service usage behavioral theory. It will also contribute to providing important perceptions of AI practices in the public sector.

Adoption of artificial intelligence integrated CRM system: an empirical study of Indian organizations

Purpose

The purpose of this study is to explore the behavioral intention of the employees to adopt artificial intelligence (AI) integrated customer relationship management (CRM) system in Indian organizations.

Design/methodology/approach

To identify the factors impacting the behavioral intention of the employees to adopt AI integrated CRM system in Indian organizations helps of literature review and theories have been taken. Thereafter, some hypotheses have been formulated followed by the development of a theoretical model conceptually. The model has been tested statistically for validation using a survey by considering 308 usable respondents.

Findings

The results of this study show that perceived usefulness and perceived ease of use directly impact the behavioral intention of the employees to adopt an AI integrated CRM system in organizations. Also, these two exogenous factors impact the behavioral intention of the employees to adopt an AI integrated CRM system mediating through two intermediate variables such as utilitarian attitude (UTA) and hedonic attitude (HEA). The proposed model has achieved predictive power of 67%.

Research limitations/implications

By the help of the technology acceptance model and motivational theory, the predictors of behavioral intention to adopt AI integrated CRM systems in organizations were identified. The effectiveness of the model was strengthened by the consideration of two employee-centric attitudinal attributes such as UTA and HEA, which is claimed to have provided contributions to the extant literature. The proposed theoretical model claims a special theoretical contribution as no extant literature considered the effects of leadership support as a moderator for the adoption of an AI integrated CRM system in Indian organizations.

Practical implications

The model implies that the employees using AI integrated CRM system in organizations must be made aware of the usefulness of the system and the employees must not face any complexity to use the system. For this, the managers of the concerned organizations must create a conducive atmosphere congenial for the employees to use the AI integrated CRM system in the organizations.

Originality/value

Studies covering exploration of the adoption of AI integrated CRM systems in Indian organizations are found to be in a rudimentary stage and in that respect, this study claims to have possessed its uniqueness.