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Strengths-Based Workplace Inclusion for Ageing Employees: An Appreciative Inquiry (AI) Study of Recognition and Belonging in Singapore

Year: 2026
Type: article
Abstract: HRMARS - Demographic ageing and extended working-life policies have intensified the importance of workplace inclusion for ageing employees. Although many organisations promote diversity and inclusion, workplace systems often continue to reflect deficit-oriented assumptions that associate ageing with declining relevance or reduced adaptability. This study examines how strengths-based workplace inclusion can be fostered for ageing employees in Singapore through an Appreciative Inquiry (AI) approach. Conceptual grounding for the study is provided through Recognition Theory, Positive Organisational Scholarship and AI, which collectively explain how recognition, belonging and strengths-based organisational practices contribute to workplace inclusion. Guided by the AI five-dimensional process, in which the define stage is established during framing through the research questions and affirmative topic, the study then progresses through discovery, dream, design and destiny. Data are generated through narrative interviews in semi-structured format and focus group discussions involving ageing employees, human resource practitioners and relevant stakeholders through a secure online meeting platform with audio recording subject to informed consent and approved ethical procedures. Two pilot interviews are conducted for protocol refinement only and are excluded from the final analysis. The findings are expected to show that workplace inclusion extends beyond formal diversity policies and is strengthened through recognition of strengths, respectful treatment, opportunities for lifelong learning and growth, meaningful participation, intergenerational collaboration and supportive leadership. The study contributes by reframing workplace inclusion through a strengths-based lens that positions ageing employees as valued contributors to organisational success.
Language: English
Subfield: Demography
Open Access status: diamond
OpenAlex ID: W7166329053
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