Book Chapters

Permanent URI for this collection https://rda.sliit.lk/handle/123456789/4200

The book chapters authored by SLIIT researchers are included in this collection. Access to full texts may be restricted depending on the access and licensing terms.

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2025 - 20265

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Start date: 2025

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Now showing 1 - 5 of 5
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    Sustaining Employee Engagement During the COVID-19 Pandemic and Beyond
    (Emerald Group Publishing Ltd., 2025) Gunawardhana, N; Weerarathna, R.S; Malkanthi R.R.M.N; Dumalka S.W.S; Chathurangi W.H.W.M
    This chapter explores the variables that influenced employee engagement in response to the challenges posed by the COVID-19 pandemic and the economic crisis in Sri Lanka. Structured interviews were conducted in this longitudinal qualitative study to gather primary data. The study focused on 20 executive-level personnel from a selected bank, who were interviewed in multiple phases. The researchers utilized word cloud analysis to qualitatively assess word frequency, facilitating a comprehensive exploration of participants’ experiences and perspectives over time. The findings from the study suggest that Human Resources (HR) managers can employ various tactics to maintain employee engagement during health or economic crises, such as decentralization, flexibility, travel arrangements, IT facilities, work flexibility, disaster resilience plans, employee recognition, empathy, stress management, communication and problem-solving. Also, financial support, recreational activities, trust and transparency are essential for building employee engagement during any economic downturn.
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    Introduction to Compensation Management
    (IGI Global, 2025-01-01) Rajapakshe, W
    This chapter examines compensation management, emphasizing its vital role in modern organizations. It defines compensation management, distinguishing between direct (salaries, bonuses) and indirect (benefits, non- monetary rewards) forms. The chapter highlights its importance in attracting, retaining, and motivating talent, linking these outcomes to performance and sustainability. It explores how compensation reflects and reinforces culture and values, shaping behavior and commitment. The evolution from an operational to a strategic HR function is outlined, showing alignment with goals such as innovation and efficiency. The role of compensation in managing change, supporting globalization, and embracing diversity is discussed, illustrating adaptability to complex environments. Key principles of effective compensation management and a six- step process—from job analysis to wage and salary implementation—are presented, underscoring its contribution to a motivated, engaged, high- performing workforce aligned with strategy.
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    Designing a Compensation Strategy
    (IGI Global, 2025-01-01) Rajapakshe, W
    This chapter provides a comprehensive analysis of compensation design as a strategic lever for organizational success. It examines strategic compensation planning, highlighting the alignment of pay systems with business objectives to motivate desired behaviors, enhance productivity, and support long- term goals. Factors affecting employee compensation—including internal equity, external competitiveness, performance, skills, experience, and market benchmarks—are explored to inform effective pay decisions. The chapter distinguishes job evaluation from performance appraisal, emphasizing its role in establishing fair, transparent pay structures. Key features and methods of job evaluation—ranking, classification, point- factor, and factor comparison—are discussed, offering practical guidance for designing compensation systems that attract and retain talent, reinforce performance, and sustain competitive advantage in evolving business environments.
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    The Impact of Artificial Intelligence on Modern Hiring
    (IGI Global, 2025-08-07) Rajapakshe, W
    This study explores the transformative impact of AI on talent acquisition, highlighting its evolution within HRM and redefining recruitment in the digital era. It examines AI's integration across key recruitment functions, including resume screening, chatbots, interview scheduling, and predictive analytics for candidate suitability. The research reviews core technologies such as Natural Language Processing (NLP), Machine Learning (ML), Robotic Process Automation (RPA), and facial recognition. While AI enhances efficiency, reduces bias, and supports data-driven decisions, it also introduces ethical and regulatory challenges related to fairness, privacy, and transparency. The study draws upon theoretical models like the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Diffusion of Innovation (DOI) to contextualize AI adoption. Finally, it presents a comparative analysis of global trends and Sri Lanka's local context, offering insights into the factors influencing AI adoption in recruitment and the future of digital HR practices.
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    AI and Inclusive Democracy: Transforming Governance for Equitable Societies
    (CRC Press, 2026) Harasgama, K. S.; Arora, V; Singh, M; Qureshi, T
    The interaction of artificial intelligence (AI) and democracy today is a confluence of opportunities for advancement around foundational values. The development of AI technologies, by leaps and bounds, holds the promise to enhance democratic processes by increasing efficiency in decision-making, streamlining governance, and stimulating civic engagement. Concerns are raised in issues of data privacy, algorithmic bias, and concentration of power in technology corporations, situations that call for very robust regulatory mechanisms if democratic values are to be upheld. The fact that AI can, therefore, lead to increased socioeconomic inequalities, manipulate public opinion, and threaten democratic institutions directly requires a proactive stance toward grappling with ethical, legal, and social implications. Governance of the various issues arising from the intersection of AI and democracy is a complex task that requires the cooperation of policymakers, technologists, ethicists, and representatives of civil society. They should strive to find the right balance between innovation and responsibility. Effective governance models need to ensure that AI systems retain and operate on the principles of fairness, transparency, and human rights. This paper discusses the challenges of AI and democracy considering electoral politics, cyber threats, psychographic profiling, and its regulation.