Sabyasachi Sinha and Naveen Kumar Malik
Data from HCL company and their corporate entrepreneurship activities were sourced using interviews and discussions. Secondary data was collected from the company website and…
Abstract
Research methodology
Data from HCL company and their corporate entrepreneurship activities were sourced using interviews and discussions. Secondary data was collected from the company website and other information available in the public domain.
Case overview/synopsis
This case narrates activities undertaken by the Enterprise Technology Office (ETO) of HCL Technologies Infrastructure Service Division to build the Corporate Entrepreneurship function. Around 2015–2016, the ETO started engaging with multiple people and organizations associated with the technology ecosystem outside the firm boundary for novel technologies and solutions. These entities included venture capitalists and start-ups. The ETO also began engaging with internal teams and existing customers to promote the identified novel technologies and innovative solutions. The ETO function grew organically by hiring resources from internal and external pools. ETO also undertook specific programs to increase the involvement of internal teams in their initiatives, like the Joint Exploration Program. ETO explored several options to further the ecosystem innovation strategy and institutionalize corporate entrepreneurship activities. The ETO team deliberated on ways to align the stakeholder goals and evaluate if technology could play a role.
Complexity academic level
This case can be used in any course on “Managing Corporate Entrepreneurship and Innovation,” “Strategic Management of Technology Enterprises” or any course focused on managing technology and innovation for graduate (MBA) or executive participants.
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Laxmi Pandit Vishwakarma and Rajesh Kumar Singh
Introduction: Artificial intelligence (AI) is being extensively used to solve complex problems in the industry. AI provides several benefits such as providing visibility in the…
Abstract
Introduction: Artificial intelligence (AI) is being extensively used to solve complex problems in the industry. AI provides several benefits such as providing visibility in the processes, reducing time, improving accuracy, saving time, helping in the decision-making process, etc. Due to the range of benefits of AI technologies, organisations readily adopt this technology. However, there are several challenges that the organisation faces during the implementation of AI. These challenges are in context to human resource (HR) development for successful implementation of AI across different functions and are discussed in this chapter.
Purpose: Although we know that AI technology is widely accepted in human resource management (HRM) due to its various benefits. But the organisations face many challenges during the implementation of AI. The focus of the study is to explore the literature on AI in HRM, identify the challenges of implementing AI and provide potential future research direction based on a systematic literature review.
Methodology: To explore the literature on AI in HRM, the study undertakes a systematic literature review. The study identifies, analyse and classifies the literature to provide a holistic view of HR challenges in implementing AI. The study is built on a review of 47 documents, including the articles, book chapters and conference papers using the Scopus database for the past 10 years (2012–27 January 2022).
Findings: The study provides an overview of the documents published in Scopus in this area through a systematic literature review. The study reveals that a significant amount of growth in the publication has been shown in the past 10 years. The maximum and continuous growth is shown after 2017. The maximum number of papers are published in India, the USA and China. The study identifies major eight challenges of AI implementation in HRM. The study also provides a secondary case to deep dive in this area based on a systematic literature review.
Research Limitation/Implication: The challenges identified in the study are not empirically tested. Each of the identified challenges should be empirically examined. This study has expanded the body of knowledge of AI in HRM. This study will help the academicians and practitioners work on the identified challenges and help the organisations ease in adopting AI.
Originality/Value: This study represents the first work that integrates AI implementation challenges in HRM.
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Yatan Pal Singh Balhara, Abhishek Ghosh, Siddharth Sarkar, Jayant Mahadevan, Arghya Pal, Venkata Lakshmi Narasimha, Dheeraj Kattula, Sambhu Prasad, Arpit Parmar, Preethy Kathiresan, Anirudha Basu, Gayatri Bhatia, Raghav Shah, Naveen Kumar Dhagudu, Richa Tripathi and Balaji Bharadwaj
This study aims to offer an overview of the models of clinical care of the patients with dual disorders in India.
Abstract
Purpose
This study aims to offer an overview of the models of clinical care of the patients with dual disorders in India.
Design/methodology/approach
All the members of the Dual Diagnosis India Network (DDIN) who shared the clinical care delivery at their center were invited to share the details of their model. In addition, an invite was also sent to those members who could not attend the online session but were interested in contributing the required information about their model. The information shared by the respondents was collated. The different models were then categorized based on their features.
Findings
Following the categorization of the clinical care services organization across different settings, five different models emerged. These were specialized dual diagnosis clinic; services for dual disorders offered as substance use disorder (SUD) treatment services within general psychiatry care; services for dual disorders in general psychiatry care; services for dual disorders offered as SUD treatment services separated from general psychiatry care; and services for dual disorders offered in general psychiatry services combined with exclusive SUD treatment services.
Originality/value
Currently, there is limited literature on models of dual disorders from the low- and middle-income countries. The authors believe that the documentation of these models from India shall be of help while setting up services for dual disorders in other health-care settings. This study can be a valuable resource for making informed choices while setting up new services.
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R. Naveen Kumar, M. Janani, R. Pavithra and A. John William
This research paper examines the transformative impact of technological integration on the governance of tourist destinations, focusing particularly on the smart destination…
Abstract
Purpose
This research paper examines the transformative impact of technological integration on the governance of tourist destinations, focusing particularly on the smart destination governance paradigm. It researches into the specific context of India’s adoption of smart tourism technologies, addressing the significant challenges posed by cybersecurity concerns. The study aims to explore how technological integration, innovation, accessibility and the use of social media collectively influence the governance mechanisms of smart destinations, contributing to their sustainability, efficiency and attractiveness to tourists.
Design/methodology/approach
The study employed purposive sampling to collect data from tourists visiting key attractions across India, including Hampi, Mysore Palace, Coorg, Udupi, Jog Falls, Gokarna, Badami Caves, Bandipur National Park and Dandeli. To overcome initial hesitations from participants, targeted questionnaires were administered to 50 tourists at each location, total of 450 participants. The collected data were then analysed using statistical software packages SPSS and AMOS to examine the relationships between technological integration, innovation, accessibility, social media and smart destination governance.
Findings
The empirical analysis revealed significant and positive relationships between the factors studied and smart destination governance. Specifically, technology (b = 0.538, t = 13.284, p-value = 0.012), innovation (b = 0.713, t = 12.467, p-value = 0.003), accessibility (b = 0.549, t = 9.284, p-value = 0.000) and social media (b = 0.683, t = 10.284, p-value = 0.015) were found to significantly contribute to the governance of smart destinations. Collectively, these factors account for 52.7% of the variance in smart destination governance, indicating a substantial impact on the management and operational aspects of tourist destinations.
Research limitations/implications
The study introduces a Smart Destination Governance Framework emphasizing collaborative structures, user-driven services, social innovation and local community involvement. This framework outlines the importance of stakeholder dynamics, accessibility, social innovation and strategic social media use. While the framework provides valuable theoretical insights and strategies for adapting to various disturbances, the research is limited by its focus on specific tourist destinations in India, which may affect the generalizability of the findings to other contexts. Further research is encouraged to validate the framework in different geographical and cultural settings.
Practical implications
The findings offer actionable strategies for tourism stakeholders aiming to enhance smart destination governance. These include the strategic adoption of technology, addressing cybersecurity issues, integrating technology with sustainability, involving local communities, improving accessibility, leveraging social media for marketing, implementing resilience in smart destinations and prioritizing continuous visitor experience improvement. The study underscores the critical role of stakeholder engagement and social innovation in achieving improved accessibility measures and overall destination attractiveness.
Social implications
The study emphasizes the role of technological integration, innovation, accessibility and social media in smart destination governance, aiming to improve tourist experiences, promote inclusivity and foster community involvement. It also highlights the need to balance modernization with cultural preservation.
Originality/value
This research contributes to the academic discourse on smart destination governance by providing empirical evidence of the significant impact of technological integration, innovation, accessibility and social media. It offers a novel Smart Destination Governance Framework that highlights the importance of collaborative efforts, social innovation and stakeholder engagement in enhancing the governance of tourist destinations. The study’s findings and proposed strategies provide valuable insights for policymakers, destination managers and tourism practitioners seeking to navigate the complexities of smart destination governance in the digital era.
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Introduction: Many organisations nowadays use artificial intelligence (AI) in human resource (HR) activities like talent acquisition, onboarding of new employees, learning and…
Abstract
Introduction: Many organisations nowadays use artificial intelligence (AI) in human resource (HR) activities like talent acquisition, onboarding of new employees, learning and development, succession planning, retention of employees, and automation of administrative tasks. When AI is integrated with HR practices, it helps HR personnel to focus more on the strategic aspects of the HR function and relieve them from routine HR activities.
Purpose: The readiness of employees to accept any change depends on organisational facilitation to change, employee willingness to accept the change, the requirement for change, situational factors, etc. This research studies the factors influencing employees’ change readiness towards acceptance of AI in HR practices. The researchers also strive to develop a conceptual technology adoption model for AI in HR practices by studying the earlier models. Finally, the research explores the acceptance of AI by various service sector employees and identifies whether there is any difference in their acceptance of AI based on demographic variables.
Methodology: A conceptual framework was derived using a combination of previous models, including the Technology Readiness Index (TRI), Change Readiness Scale, Technology Acceptance Model (TAM), Technology, Organization, and Environment (TOE) model, and change readiness scale. A structured questionnaire was designed and distributed to 228 respondents from the service sector based on the conceptual framework. An exploratory factor analysis (EFA) was used to determine the elements that influence employees’ level of change readiness.
Findings: The exploratory results on data collected from 228 respondents show that the model can be used for further research if a confirmatory factor analysis and validity and reliability test are performed. Employees are aware of AI and how it is used in HR practices, based on the study results. Moreover, while most respondents favour using AI in their company’s HR practices, they are wary of some aspects of AI.
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Naveen Joshi, Vijaya Lakshmi R. and Jitendra Kumar Singh
This study aims to explore the collective influence of several factors, namely, thermal radiation, Brownian motion, magnetic field and variable viscosity parameter, on the…
Abstract
Purpose
This study aims to explore the collective influence of several factors, namely, thermal radiation, Brownian motion, magnetic field and variable viscosity parameter, on the boundary layer flow, heat and mass transfer of an electrically steering nanofluid over a radially stretching exterior subjected to convective heating. In addition, the impacts of thermal and solutal buoyancy forces and activation energy are taken into account. The enlarging velocity is assumed to vary linearly with radial distance.
Design/methodology/approach
Through the similarity transformation technique, the governing highly nonlinear partial differential equations are transformed into a set of nonlinear ordinary differential equations, which are then numerically solved using the Runge–Kutta–Fehlberg method with a shooting technique.
Findings
Graphical depictions are provided to analyze the velocity, temperature and nanoparticle concentration fields under the influence of various pertinent parameters. Furthermore, local skin friction, local Nusselt and Sherwood numbers are quantitatively presented and discussed. A comparison with previous results demonstrates good agreement.
Originality/value
This study uniquely integrates multiple factors influencing boundary layer flow in electrically conducting nanofluids, offering a nuanced understanding of heat and mass transfer over radially stretching surfaces. By using advanced numerical methods, it provides valuable insights and quantitative data that can inform practical applications in engineering and materials science.
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Shivani Agarwal, Apoorv Gupta and Puja Roshani
Introduction: Artificial intelligence (AI) has now become an integral part of every aspect of the corporate sector. AI may be a massive branch of computing connected to building…
Abstract
Introduction: Artificial intelligence (AI) has now become an integral part of every aspect of the corporate sector. AI may be a massive branch of computing connected to building devices smart enough and capable of performing tasks that usually require human intelligence. Integrating AI with human resources (HR) practices will improve organisations, as these applications can analyse, predict, and diagnose to support HR teams for taking better decisions.
Purpose: This chapter throws light upon the current scenario of awareness of AI and machine learning (ML) and their impact on the industry of HR. This chapter tries to describe the usage of AI in our current world and the impact of AI in the field of HRM in organisations.
Methodology: The true possibility of AI and ML in HRM has been analysed with the help of pie charts, bar charts, and histograms with the segmenting of results and interpretations. Various frequently asked questions have been answered, and a sample population has also been surveyed on their viewpoints regarding specific areas.
Findings: This chapter concludes that HR experts see the best potential in analytics, attendance, recruitment, attendance management, and compensation/payroll. AI will significantly diversify the HR sector. HR professionals need to think outside of their function.
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Emrah Ekici and Marina Y. Ruseva
The authors examine the role of stock liquidity in CEO equity compensation design. For a sample of publicly traded firms from 2007 to 2020, the authors find that greater stock…
Abstract
The authors examine the role of stock liquidity in CEO equity compensation design. For a sample of publicly traded firms from 2007 to 2020, the authors find that greater stock liquidity is associated with a higher proportion of stock awards relative to the proportion of options in CEO equity compensation. The results of this study suggest that stock price informativeness on the grant date has a differential effect on the preference for the type of equity compensation awarded to CEOs. The empirical results are supported by multivariate analyses using alternative measures of stock liquidity and a two-stage least squares (2SLS) specification that alleviates endogeneity concerns. Furthermore, the authors document that the firm-specific increase in the proportion of stock awards compared to the proportion of stock options is associated with a firm-specific increase in stock liquidity. Collectively, the analyses suggest that stock liquidity as a measure of stock price informativeness contributes to the choice of CEO equity compensation design.