Introduction
A major demographic trend in the United Kingdom is the rapid ageing of its population (Barton, Sturge and Harker, 2024). Rapid population ageing emerges when the percentage of elderly citizens develops in numbers faster than younger workers because of prolonged life spans and extremely low birth rates. The growing number of elderly people affects numerous economic sectors especially labour markets along with employment structures and workplace practices(Parliament.uk, 2022). This report evaluates and identifies the ageing population as the most significant demographic trend by analyzing its impact on employment opportunities and employment patterns and its effect on work practices and organisational operation strategies.
The population of elderly people is increasing significantly: Justification and Overview.
Significant improvements in healthcare combined with better nutrition and living standards and better healthcare have together increased human longevity, which drives an increase in life expectancy (Kaplan and Milstein, 2019). The population percentage consisting of people aged 65 and above experienced significant growth rates. For instance in 2022, the percentage of people in UK aged 65 and above was 19% and is projected to increase to 27% in 2072 (Barton, Sturge and Harker, 2024). The population changes demonstrate deeper social impacts, which affect planning strategies alongside public policy outcomes. The reduction in younger workers creates an unfavourable ratio between working-age individuals and retirees, which may stress social security programs and pension plans (Scott, 2021). This economic trend stands as a critical social transformation because it restructures the entire economic framework. The main drawback of such emphasis on aging workforce challenges neglects to fully explore the advantages, which come from working with experienced employees. According to Becker and Fiske (2022), although there may be an additional need for healthcare and age-related services, it is important to note that ageing employees can significantly contribute to organisational performance by leveraging on their experience when provided with suitable working conditions. Besides, there may be resistance from employers and employees towards flexible working arrangements and retirement plans particularly those accustomed to traditional work approaches (Kossek and Kelliher, 2022). Strategies should encompass balanced policy interventions because older people’s dual positive and negative impacts require recognition for creating flexible approaches that stay inclusive and responsive.
Implications for Labour Markets and Employment
Employee demographics linked to ageing have multiple influences on both labour availability and resource allocation in the workplace (Becker and Fiske, 2022). Working-age employees leave the workforce due to retirement, which causes workforce reduction that might lead to skilled personnel shortage. Organisations need to develop modern recruitment methods for younger employees and retention methods for their experienced workers because of this workforce situation (Acuity International, 2024). Human capital theory holds great importance in this particular situation (Gillies, 2015). According to the theory, employees remain crucial business assets and investing in their training can lead to improved skills and knowledge (CIPD, 2017). Organisations that maintain ongoing workforce development programs reduce age-related labour challenges by ensuring both younger and elderly employees contribute effectively to productivity and innovation.
A major drawback develops from the difficulties that arise when trying to unite employees from different age groups inside the same organizational structure (Boatman, 2025). Teamwork suffers because employees possess different work approaches and varying skill levels with technology and adaptability resulting in performance reductions. Organisations implement flexible work plans and phased retirement systems that combine various employee requirements without diminishing team unity (Austin-Egole, Iheriohanma and Chinedu, 2020). Modern workplace efforts have not prevented inconsistent work results from emerging when traditional operational methods persist in specific sectors.
Secure your future with our high-quality paper—order now!
You can talk to the writer using our messaging system and keep track of how your assignment is going.
Order Now WhatsAppHigher costs related to health absences and the implementation of new occupational wellness programs could exert additional financial and operational burdens on the organisations (Nagata et al., 2018). Moreover, there may be a need for policymakers to review labour regulations and pension schemes to accommodate younger demographics. Moreover, there may be a need for the development of a comprehensive human resource management strategy, which combines sustainability with fairness, to find a balance between an older workforce’s advantages and workforce decline’s challenges (Manpreet Kailay and Kamalpreet Kaur Paposa, 2024).
Transformations in the World of Work
The growing number of older people in society has led to major reforms throughout the workplace environment (Barton, Sturge and Harker, 2024). Modern organisations face an obligation to redesign workplace operations because of changing workforce requirements for older workers. Organizations have implemented flexibility programs such as remote work, staggered shifts and part-time roles to allow ageing employees to balance their work responsibilities and personal demands (SHRM, 2024). Employees within financial and technological industries now have remote working opportunities hence decreasing commuting challenges and boosting work-life balance. Employers now focus on lifelong professional development because the demand for continuous learning has grown due to fast-changing technology, which assists workers in keeping pace with rapid technological changes(Mustafa and Lleshi, 2024).
Specialized programs focusing on ergonomic office redesigns combined with specialized software training along with health and wellness initiatives have gained popularity in recent times (Zerguine et al., 2023). Manufacturing industry re-skilling programs together with safety improvements and equipment modifications result in better productivity and lower workplace injuries for older workers. The implementation of age-friendly policies faces a key drawback because different sectors show varying degrees of resource capability to execute full-scale age-friendly strategies (Zerguine et al., 2023). The implementation of flexible work schedules strengthens job satisfaction yet fails to address all aspects of generational difference and change resistance issues at the workplace and improve contentment levels but they do not completely address workplace difficulties arising from age-based distinctions or employee reluctance to change (Indradewa and Prasetio, 2023). Such cases reveal the importance of integrating new policies with managerial culture development to genuinely respect all workforce members regardless of their age group.
Conclusion
In conclusion, the ageing population stands as the most significant demographic trend, with far-reaching implications for economic planning together with labour markets and workplace practices. The aging demographic pattern creates workforce deficit problems and difficulties with integration as well as higher public spending challenges. Nevertheless, the ageing population presents opportunities for harnessing the experience of elderly employees including through knowledge transfer to younger employees and enhancing operational efficiency. Policy interventions require balanced approaches to simultaneously promote inclusivity together with continuous learning while establishing flexible employment arrangements to overcome these limitations. The sustainable growth of our economic system depends on accepting both risks and potentials, which emerge from an ageing population structure.
Introduction
The development of new technologies has brought significant changes to how organizations acquire and select their employees. Employers use artificial intelligence, remote interviewing platforms and social media recruitment techniques to transform their candidate selection methods (Agouridis, 2023). These innovations have emerged in response to the need for efficiency, cost reduction, and broader access to global talent pools. Organisations employ AI-tracking systems to analyse numerous job applications using artificial intelligence while virtual interviewing platforms enable recruiters to reach diverse candidates across the world (Pantelakis, 2023). The technological advancements enhance process efficiency and simultaneously deliver improved employee present both opportunities and challenges which organizations must thoroughly assess to maintain fair recruitment procedures.
AI-Powered Applicant Tracking Systems
AI-powered applicant tracking systems (ATS) are increasingly used to automate resume screening and candidate shortlisting, significantly transforming the recruitment process (Psico-smart, 2020). The systems employ complex algorithms to assess candidate applications through historical hiring parameters, which aligns with the Technology Acceptance Model principles (TAM) (Charness and Boot, 2020). The Technology Acceptance Model proves that users will embrace new technology tools and achieve success with their use if they consider them beneficial and easy to operate. ATS operate to analyze and process large numbers of applications with speed, which leads to decreased workload for human resource professionals. Large multinational firms use ATS systems as part of their recruitment process to examine expansive job candidate databases, which results in the efficient identification of suitable applicants (Henderson, 2024). This speeds up the hiring process, and minimizes the likelihood of human errors, and biased candidate selection.
The primary challenge with AI-based ATS systems consists of inheriting and worsening the biases that exist within the recruitment process (Malik, 2024). Any discriminative elements contained in previous hiring practices can become integrated into algorithm-based systems because those systems use historical data for training purposes. ATS systems may enable the systematic exclusion of specific demographic groups and job applicants from minority backgrounds creating a less diverse workforce (Albaroudi, Mansouri and Alameer, 2024). The evaluation system uses criteria that may not adequately measure candidate potential or skills because it depends on strict keyword rules and standardized evaluation methods. Organisations face difficulties in identifying and solving unintended biases because the algorithmic decision-making processes frequently lack transparency (Gov.uk, 2024). Although AI-powered ATS systems provide greater efficiency and cost, reduction there is a need for organisations to remain vigilant. Organisations need to routinely check their ATS systems and maintain algorithm accuracy while following current diversity and inclusion guidelines to efficiently utilize technology for both recruitment results and fairness (Caccavale, 2023).
Remote and Video Interviewing Platforms
Remote and video interviewing platforms have revolutionised the selection process by enabling virtual interviews that save time and reduce travel expenses (Garg, 2024). The platforms support effective communication as per the Media Richness Theory since they let users transmit verbal cues together with visible signs through their interface (Mammadov, 2022). Candidate evaluation depends on enriched communication because interviewers get better observations of nonverbal behaviour and body language and assessments of overall engagement.
Technological start-ups along with global businesses rely on communication platforms including Zoom and Microsoft Teams and Google Meet for conducting their job interviews (Devoteam, 2024). The aforementioned tools support live interactions between interviewers and candidates along with built-in recording functionalities, which enhance transparency. Organisations also use these platforms for recruitment because they simplify the process through their ability to schedule and reach candidates hence bridging distance barriers (Oracle, 2022). The broader talent selection capabilities provide special advantages to industries that need superior employees to succeed.
Nevertheless, technological progress in recruitment comes with particular constraints, which affect its usage. The process becomes less fair because video interviewing excludes people who lack internet access or modern technology devices (Sołek-Borowska and Wilczewska, 2018). Software glitches together with poor connectivity may interfere with evaluators’ assessment of candidate abilities. Thus, while remote and video interviewing platforms offer substantial benefits in terms of efficiency and access, organisations must address these challenges to ensure an equitable selection process for all candidate (Dulloo, 2023).
Social Media Recruitment and Digital Employer Branding
Social media technologies have reformed hiring methods by allowing organizations to expand their talent pools while building their employer brand reputation (Hanu, Amegbe and Mensah, 2021). By leveraging principles from Social Network Theory, companies use LinkedIn Facebook and Twitter platforms to contact active as well as passive job seekers through their interconnected platform features (Carpentier, Van Hoye and Weijters, 2019). Targeted marketing campaigns along with professional connection platforms and organization culture displays permit employers to find candidates outside mainstream recruiting methods. This method helps employers find prospects who pursue other career paths while remaining receptive to advantageous new career opportunities.
Social media recruitment provides organizations with the chance to develop their employer brand more effectively (Universum, 2024). Organisations make the most out of these platforms by posting employee testimonials while conveying their core values and showing off their workplace culture through interesting content. The open and interactive social media recruitment system makes organisations more appealing to job seekers so they view them as an employer of choice (Laukkarinen, 2023). Through social media platforms, recruiters and applicants achieve direct communication, which helps them speed up their hiring process through immediate response and feedback exchange.
Despite these advantages, overreliance on digital recruitment methods presents notable challenges (Zahra Zahedi Nejad, Mehdi Sabokro and Eeva-Liisa Oikarinen, 2024). Social media inactivity from candidates leads to unintentional job opportunity exclusion thus creating a restricted pool of potential candidates that ultimately promotes bias (Krska, 2022). The use of personal data extracted from online profiles has raised specific privacy issues regarding the collection and usage of personal data from online profiles. The review of candidates’ social media beyond their professional networking profiles creates discomfort, which makes them uneasy during the job application process. Organisations should use social media recruitment strategically to benefit from its outreach and branding advantages while protecting fairness and inclusivity and sustaining ethical data protection (Wowor et al., 2022).
Conclusion
Organisations benefit from technological advancements in recruitment because they obtain superior operational efficiency together with economic savings along with a wider reach of potential candidates. AI systems together with remote interviews and social media recruitment tools create new candidate assessment methods while helping organizations reach diverse talent sources. For business companies, the advantages of faster application processing decreased operational spending and better organizational reputation exist. These AI advantages require employers to balance them with problems including biased algorithms and technological barriers alongside privacy challenges. Organisations should develop robust policies together with ongoing review systems to guarantee these technologies will be used transparently yet inclusively at all times. Employers who adopt active management strategies for innovations can unlock their advantages while mitigating associated risks, thereby fostering more effective and equitable recruitment practices.
Change is an inevitable aspect of organisational growth and development, often necessitated by evolving market conditions, technological advancements, and shifts in workforce dynamics (Hubbart, 2023). Managers are essential for making sure organisational changes happen effectively while maintaining low employee resistance. The Change Management Model developed by Kurt Lewin serves as a major tool for directing change initiatives (Malik, 2022). Lewin’s model emerged during the 1940s and continues to serve modern businesses through its organized framework for organizational development. Lewin’s model begins with Unfreeze followed by Change and then ends with Refreeze and targets essential psychological as well as operational transformation elements (Awati, 2022). This report assesses both positive and negative aspects of Lewin’s model from a contemporary people management perspective and its practicality in modern workplaces. Lewin’s model demonstrates practical use in everyday implementations such as Apple’s Intel processor change to M1 chips, which showcases how strategic change can be implemented successfully (Apple, 2020). The simplicity of the model along with its structured methodology delivers many benefits however, these benefits are limited since the model works on a linear process and does not accommodate continuous change dynamics.
Unfreeze
The first stage of Lewin’s model, Unfreeze, involves breaking down existing behaviours, mindsets, and processes to prepare individuals and organisations for transformation. The Unfreeze stage holds significant importance because it lets people understand why change is needed and encourages stakeholder buy-in. The success of the current state of unfreezing requires teamwork through excellent communication maintenance alongside employee involvement as well as leader support.
Apple needed an extensive unfreezing process during its move from Intel-based processors to Apple Silicon. The change demanded employees and developers to learn new system designs hence necessitating the establishment of multiple employee engagement and training initiatives. Apple executed detailed communication efforts together with developer assistance methods to equip both their internal departments and outside development organizations for transitioning to the new platform. The proactive approach decreased both workforce uncertainty and opposition to change.
The main drawback of this change stage lies in its requirement for complete disruption to enact progress. Today’s business rapidness often brings gradual change rather than discrete shifts, which limits the practicality of forced unfreezing operations. Agile organisations using this model encounter difficulties since they need ongoing transformation rather than a single preparatory stage. Therefore, while Unfreeze is valuable in traditional change initiatives, it may be less effective in dynamic industries that require ongoing flexibility.
Change: Implementing the Transformation
During the second stage Change employees focus on deploying new processes together with new behaviours and new organizational structures (Awati, 2022). Leaders must deliver clear communication and demonstrate new behaviour patterns in addition to providing support systems, which help staff members adapt to workplace changes (Musaigwa, 2023). Employee engagement and continuous learning represent contemporary people management approaches, which correspond to this stage.
The implementation phase presents a valuable awareness of how emotions and psychological factors affect change processes. According to Lewin, employees face uncertainty together with resistance to change but observe that leadership backing along with the strategic approach to change management will help the staff cope better (Malik, 2022).
Apple implemented an effective M1 rollout by starting with MacBook models before expanding the new chip technology to other product series (Apple, 2020). The company gave comprehensive technical help and platform guidance to help workers and development teams shift smoothly into their new mode of operation. The launch process and ongoing feedback sessions operated by Apple integrated stakeholders into the new technology apparatus while maintaining operational stability (Kelly, 2021).
A major drawback of this stage occurs because it implicitly predicts that change occurs in a progressively linear manner (McPheat, 2023). Organisations need to return to previous change steps when change processes run into actual difficulties throughout their implementation (Awati, 2022). Alternative change management models like Kotter’s 8-Step Model include feedback cycles that help organizations adjust their methods when facing new obstacles (Sharma, 2022). Contemporary work environments demand customized approaches to change management because they include expectations from diverse workforce members that require individualized methods instead of standardized approaches (McHarris, 2024). Thus, while Lewin’s Change phase remains relevant, it benefits from integration with more flexible methodologies.
Refreeze: Embedding the New State
The final stage, refreeze, ensures that changes are institutionalised within the organisation, preventing regression to previous behaviours (Awati, 2022). This phase is critical in solidifying new practices through reinforcement mechanisms such as performance incentives, policy updates, and continuous monitoring.
Apple successfully refroze its new processor ecosystem by embedding the changes within its long-term business strategy (Simonite, 2020). The company reinforced its shift to Apple Silicon by discontinuing Intel-based products and ensuring software compatibility across all devices. Additionally, Apple incentivised developers to optimise applications for the M1 chip by providing exclusive support and marketing opportunities (Simonite, 2020). By reinforcing positive behaviours, Apple created a stable environment where employees and developers fully embraced the transition.
One major drawback of the Refreeze stage emerges from its basic organizational stability methodology (Awati, 2022). Contemporary business operations seldom maintain consistent stability due to continuous changes in their environments. Businesses in technology and finance domains experience brief periods of stability before rapidly needing to respond to market changes since their competitive environments never rest (Knudsen et al., 2021). Instead of viewing change as a finite process, modern organisations need to embrace a culture of continuous learning and innovation, challenging the finality implied by Lewin’s model (Raza, 2019).
Conclusion
The Change Management Model by Kurt Lewin presents organizations with a structured approach to transformation that links well to the psychological aspects of adapting to change. The three-stage approach presented in the Lewin Model enables staff preparation while offering complete support during and after the transition process. The M1 chip implementation at Apple illustrates how structured change management allows organizations to execute successful transformations by resolving both worker and shareholder concerns. The model’s weaknesses stem from its rigidity as well as its reliance on fixed conditions due to which it works better with industries that function without constant transformation needs. Organisations can boost their capacity to handle continuous change through a combination of Lewin’s model with iterative and agile management approaches. Numerous organizations utilize Lewin’s model because it serves as a core framework for informing people while guiding the successful implementation of organizational transformation practices.
Introduction
In today’s diverse and globalised work environment, equal opportunity employment remains a critical goal for organisations (Sharma, 2016). An employer cannot achieve genuine equal opportunity status unless it develops formal procedures to combat unconscious bias that emerges from both managers and workers. Unconscious bias constitutes subtle automatic prejudices, which affect how decision-makers perform their roles and impact different phases of recruitment, promotion, and performance assessment mechanisms. Research conducted by Cherry (2023) demonstrates that implicit biases generate discriminatory behaviours that negatively affect minority groups. The mitigation of such biases requires structured interventions. This paper critically evaluates the essential role that formal workplace standards play in achieving workplace equality. The report explores three basic elements, which include structured recruitment methods, training about unconscious bias and technology-driven solutions. It also explains the advantages of these interventions while assessing their limitations to prove that complete ongoing interventions create genuine equality opportunities in organizations.
Structured Hiring and Promotion Processes
Unconscious bias reduction requires organizations to establish standardized procedures for their hiring and promotions (Gino and Coffman, 2021). Organisations that aim to decrease bias within their operations establish standardized recruitment practices. Standardised recruitment procedures use anonymized applications together with competency tests and multiple evaluator panels from diverse backgrounds (CIPD, 2022). The exclusion of personal identifiers from recruitment applications during anonymised recruitment helps decrease both conscious and unconscious prejudice from affecting selection decisions. CIPD (2022) posits that when processes are structured and transparent they encourage equitable employment decisions. Standardisation upholds fairness and establishes consistent decision-making because it requires all candidates to demonstrate their skills against uniform criteria.
A major drawback of this method stems from its rigid nature. Standardized recruitment procedures receive criticism because they tend to ignore non-traditional competencies and exclusive background elements that cannot adapt to standardized requirements (Kroll, Veit and Ziegler, 2021). The filtering system could eliminate individuals who think differently from standardized measurement criteria for competence. Although diverse interview panels reduce personal biases among the panellists, they do not eliminate the potential for unconscious biases shared by panel members (Barber, 2024). Despite their value in achieving equal opportunity in hiring processes, the structured methods need continuous review for flexibility and full inclusion.
Unconscious Bias Training and Education
Organisations use unconscious bias training as an essential tool, which helps in preventing implicit prejudices (Gino and Coffman, 2021). The training system educates managers and staff on the presence of unconscious bias as well as its effects. These programs use standardized implicit association tests together with interactive work sessions that show how participants can detect their hidden biases and develop methods to reduce them (Shah and Bohlen, 2023). According to Onyeador, Hudson and Lewis (2021), bias training programs at Google and other multinational companies have shown research-driven success through sustained employee training thus reducing implicit biases over time.
Despite these benefits, there is a critical limitation to bias training programs. The effects from single training sessions are likely to disappear when there is no reinforcement strategy in place (NIH, 2021). Research by Mattias Lindvall-Östling (2024) shows that biases can grow worse when the training methods are poorly implemented because they activate defensive conduct and promote the reinforcement of stereotypes. Training session participation often depends on voluntary attendance and participant motivation and therefore fails to guarantee achievement of intended organizational-wide behaviour adjustments (Salamon et al., 2021). The success of unconscious bias training depends on sustained reinforcement strategies, which merge into daily workplace practices through strong follow-up systems to deliver long-lasting effects.
Technology-Driven Bias Reduction Strategies
Technology solutions provide innovative methods for decreasing unconscious bias specifically in recruitment and performance management processes (Stockbridge, 2024). The adoption of AI-powered ATS (Applicant Tracking Systems) along with blind recruitment software continues to rise because they enable standardized candidate evaluation procedures (Madanchian, 2024). Such technology-based tools remove personal identifiers from applications, which allows recruiters to judge candidates through their qualifications and experience. Organisations have achieved better diversity results by using ATS programs that eliminate human-centred biases (Madanchian, 2024). Studies by Rodgers et al. (2022) indicate that technology when ethically designed can function as an impartial decision-making tool. Organisations use digital performance management tools to maintain uniform evaluation standards that minimize the intrinsic biases, which usually occur in traditional performance assessment processes.
However, a critical perspective is necessary when evaluating technology-driven strategies. These tools deliver their results according to both data accuracy and algorithm development quality (Li, Chen and Shang, 2021). When historical data used for system training contains biases, the technology will likely worsen current inequality patterns. For example, Amazon discontinued AI-based hiring software because it showed systematic preference toward males thus revealing the limitations of technology-based solutions (Dastin, 2018). Modern technology systems lack the capabilities to handle subtle context-specific elements, which human supervisors can detect throughout their decision-making process. The ability of technology to evaluate context-based characteristics remains beyond its operational capacity. Standardized processes using technology alongside human oversight and ongoing algorithmic audits become essential to prevent the creation of new biases (Lee, Resnick and Barton, 2019).
Conclusion
Workplace equality requires established procedures to address unconscious bias and to achieve full equal opportunity in the workplace. Three primary methods of addressing bias include structured hiring processes together, unconscious bias training programs and technological systems. However, each of these measures has inherent limitations including rigidity, short-lived outcomes and possible data biases, which need continuous oversight. Published literature emphasises that organizations must use multi-dimensional holistic methods to achieve sustainable transformations. Organisations must remain committed to ongoing evaluation and refinement of their practices to build workplaces that embrace fair treatment for all employees.
Reference list
Acuity International (2024). Aging Workforce: Adapting Business Practices for Success. [online] Available at: https://acuityinternational.com/blog/aging-workforce/ [Accessed 5 Feb. 2025].
Agouridis, A. (2023). How AI is Transforming the World of Recruitment. [online] jobylon. Available at: https://www.jobylon.com/blog/how-ai-is-transforming-the-world-of-recruitment [Accessed 5 Feb. 2025].
Albaroudi, E., Mansouri, T. and Alameer, A. (2024). A Comprehensive Review of AI Techniques for Addressing Algorithmic Bias in Job Hiring. AI, [online] 5(1), pp.383–404. Available at: https://www.mdpi.com/2673-2688/5/1/19.
Apple (2020). Apple unleashes M1. [online] Apple Newsroom. Available at: https://www.apple.com/newsroom/2020/11/apple-unleashes-m1/ [Accessed 5 Feb. 2025].
Austin-Egole, I.S., Iheriohanma, E.B.J. and Chinedu, N. (2020). Flexible Working Arrangements and Organizational Performance: An Overview. [online] ResearchGate. Available at: https://www.researchgate.net/publication/341651202_Flexible_Working_Arrangements_and_Organizational_Performance_An_Overview.
Awati, R. (2022). What Is Unfreeze, Change, Refreeze (Kurt Lewin Change Management Model)? – Definition from WhatIs.com. [online] TechTarget. Available at: https://www.techtarget.com/whatis/definition/Kurt-Lewins-Change-Management-Model-Unfreeze-Change-Refreeze [Accessed 5 Feb. 2025].
Barber, L. (2024). Making Too Many Wrong Hires? Hiring Bias May Be to Blame. [online] VidCruiter. Available at: https://vidcruiter.com/video-interviewing/hiring-biases/ [Accessed 5 Feb. 2025].
Barton, C., Sturge, G. and Harker, R. (2024). The UK’s changing population. [online] House of Commons Library. Available at: https://commonslibrary.parliament.uk/the-uks-changing-population/.
Becker, T. and Fiske, S.T. (2022). Workplace and Job Factors. [online] www.ncbi.nlm.nih.gov. National Academies Press (US). Available at: https://www.ncbi.nlm.nih.gov/books/NBK588534/.
Boatman, A. (2025). Multigenerational Workforce: Benefits, Challenges, and 9 Best Practices. [online] AIHR. Available at: https://www.aihr.com/blog/multigenerational-workforce/ [Accessed 5 Feb. 2025].
Caccavale, J. (2023). Technology’s Impact on Recruitment and Selection: Navigating the Pros and Cons. [online] www.beapplied.com. Available at: https://www.beapplied.com/post/how-does-recruitment-software-technology-affect-recruitment-and-selection [Accessed 5 Feb. 2025].
Carpentier, M., Van Hoye, G. and Weijters, B. (2019). Attracting applicants through the organization’s social media page: Signaling employer brand personality. Journal of Vocational Behavior, 115, p.103326. doi:https://doi.org/10.1016/j.jvb.2019.103326.
Charness, N. and Boot, W. (2020). Technology Acceptance Model – an overview | ScienceDirect Topics. [online] Sciencedirect.com. Available at: https://www.sciencedirect.com/topics/social-sciences/technology-acceptance-model [Accessed 5 Feb. 2025].
Cherry, K. (2023). How Does Implicit Bias Influence Behavior? [online] Verywell Mind. Available at: https://www.verywellmind.com/implicit-bias-overview-4178401 [Accessed 5 Feb. 2025].
CIPD (2017). Human capital theory: assessing the evidence for the value and importance of people to organisational success in partnership with. [online] CIPD, pp.1–96. Available at: https://www.cipd.org/globalassets/media/knowledge/knowledge-hub/reports/human-capital-theory-assessing-the-evidence_tcm18-22292.pdf.
CIPD (2022). A guide to inclusive recruitment for employers. [online] CIPD. Available at: https://www.cipd.org/en/knowledge/guides/inclusive-employers/ [Accessed 5 Feb. 2025].
Dastin, J. (2018). Amazon Scraps Secret AI Recruiting Tool That Showed Bias against Women. [online] Reuters. Available at: https://www.reuters.com/article/world/insight-amazon-scraps-secret-ai-recruiting-tool-that-showed-bias-against-women-idUSKCN1MK0AG/ [Accessed 5 Feb. 2025].
Devoteam. (2024). Comparing Zoom, Microsoft Teams and Google Meet. [online] Available at: https://www.devoteam.com/expert-view/comparing-zoom-microsoft-teams-and-google-meet/ [Accessed 5 Feb. 2025].
Dulloo, R. (2023). Beyond Face-to-Face: Delving into Candidates’ Perspectives on Virtual Interviews. ResearchGate. [online] doi:https://doi.org/10.48047/ecb/2023.12.si5.238.
Garg, A. (2024). How Automated Video Interviews Are Revolutionizing Hiring. [online] Ducknowl. Available at: https://ducknowl.com/rise-of-automated-video-interviews/ [Accessed 5 Feb. 2025].
Gillies, D. (2015). Human Capital Theory in Education. Encyclopedia of Educational Philosophy and Theory, pp.1–5. doi:https://doi.org/10.1007/978-981-287-532-7_254-1.
Gino, F. and Coffman, K. (2021). Unconscious Bias Training That Works. [online] Harvard Business Review. Available at: https://hbr.org/2021/09/unconscious-bias-training-that-works [Accessed 5 Feb. 2025].
Gov.uk (2024). Landscape Summary: Bias in Algorithmic Decision-Making What is bias in algorithmic decision-making, how can we identify it, and how can we mitigate it? [online] Available at: https://assets.publishing.service.gov.uk/media/5d31c30a40f0b64a8099e21d/Landscape_Summary_-_Bias_in_Algorithmic_Decision-Making.pdf [Accessed 5 Feb. 2025].
Hanu, C., Amegbe, H. and Mensah, P. (2021). Your Future Employer: Employer Branding, Reputation, and Social Media. African Journal of Inter/Multidisciplinary Studies, 3(1), pp.1–18. doi:https://doi.org/10.51415/ajims.v3i1.860.
Henderson, R. (2024). What Is An ATS? 8 Things You Need To Know About Applicant Tracking Systems. [online] Jobscan Blog. Available at: https://www.jobscan.co/blog/8-things-you-need-to-know-about-applicant-tracking-systems/ [Accessed 5 Feb. 2025].
Hubbart, J.A. (2023). Organizational Change: the Challenge of Change Aversion. Administrative Sciences, [online] 13(7), pp.162–162. doi:https://doi.org/10.3390/admsci13070162.
Indradewa, R. and Prasetio, A.A. (2023). The influence of flexible working arrangements and work-life balance on job satisfaction: A double-layered… [online] ResearchGate. Available at: https://www.researchgate.net/publication/377067488_The_influence_of_flexible_working_arrangements_and_work-life_balance_on_job_satisfaction_A_double-layered_moderated_mediation_model.
Kaplan, R.M. and Milstein, A. (2019). Contributions of Health Care to Longevity: A Review of 4 Estimation Methods. The Annals of Family Medicine, 17(3), pp.267–272. doi:https://doi.org/10.1370/afm.2362.
Kelly, S.M. (2021). Apple’s rivals may never be able to catch up to its powerful new chip. [online] CNN. Available at: https://edition.cnn.com/2021/05/21/tech/apple-m1-chip/index.html [Accessed 5 Feb. 2025].
Knudsen, E.S., Lien, L.B., Timmermans, B., Belik, I. and Pandey, S. (2021). Stability in turbulent times? The effect of digitalization on the sustainability of competitive advantage. Journal of Business Research, [online] 128, pp.360–369. doi:https://doi.org/10.1016/j.jbusres.2021.02.008.
Kossek, E.E. and Kelliher, C. (2022). Making Flexibility More I-Deal: Advancing Work-Life Equality Collectively. Group & Organization Management, 48(1), p.105960112210988. doi:https://doi.org/10.1177/10596011221098823.
Kroll, E., Veit, S. and Ziegler, M. (2021). The Discriminatory Potential of Modern Recruitment Trends—A Mixed-Method Study From Germany. Frontiers in Psychology, [online] 12(12). doi:https://doi.org/10.3389/fpsyg.2021.634376.
Krska, A. (2022). Help or Hindrance: How social media affects the selection and Help or Hindrance: How social media affects the selection and hiring processes of businesses hiring processes of businesses. [online] Available at: https://scholarworks.uark.edu/cgi/viewcontent.cgi?article=1019&context=mgmtuht.
Laukkarinen, M. (2023). Social media as a place to see and be seen: Exploring factors affecting job attainment via social media. The Information Society, [online] 39(4), pp.1–14. doi:https://doi.org/10.1080/01972243.2023.2199418.
Lee, N.T., Resnick, P. and Barton, G. (2019). Algorithmic bias detection and mitigation: Best practices and policies to reduce consumer harms. [online] Brookings. Available at: https://www.brookings.edu/articles/algorithmic-bias-detection-and-mitigation-best-practices-and-policies-to-reduce-consumer-harms/ [Accessed 5 Feb. 2025].
Li, C., Chen, Y. and Shang, Y. (2021). A review of industrial big data for decision making in intelligent manufacturing. Engineering Science and Technology, an International Journal, [online] 29. Available at: https://www.sciencedirect.com/science/article/pii/S2215098621001336.
Madanchian, M. (2024). From Recruitment to Retention: AI Tools for Human Resource Decision-Making. Applied Sciences, 14(24), p.11750. doi:https://doi.org/10.3390/app142411750.
Malik, A. (2024). AI Bias In Recruitment: Ethical Implications And Transparency. Forbes. [online] 12 Aug. Available at: https://www.forbes.com/councils/forbestechcouncil/2023/09/25/ai-bias-in-recruitment-ethical-implications-and-transparency/ [Accessed 5 Feb. 2025].
Malik, P. (2022). Lewin’s 3-Stage Model of Change Theory: Overview. [online] WhatFix. Available at: https://whatfix.com/blog/lewins-change-model/ [Accessed 5 Feb. 2025].
Mammadov, R. (2022). Media Choice in Times of Uncertainty —Media Richness Theory in Context of Media Choice in Times of Political and Economic Crisis. Advances in Journalism and Communication, 10(02), pp.53–69. doi:https://doi.org/10.4236/ajc.2022.102005.
Manpreet Kailay and Kamalpreet Kaur Paposa (2024). Sustainable Human Resource Management in the Hospital Sector: A Review of Literature. Journal of health management. doi:https://doi.org/10.1177/09720634231216062.
Mattias Lindvall-Östling (2024). ‘If you are aware of something, you can do something about it’: Investigating the lasting effects of an implicit bias training activity.. Teaching and teacher education, 140, pp.104484–104484. doi:https://doi.org/10.1016/j.tate.2024.104484.
McHarris, N. (2024). How Change Management Can Drive Inclusion in the Workplace. [online] Prosci.com. Available at: https://www.prosci.com/blog/inclusion-in-workplace [Accessed 5 Feb. 2025].
McPheat, S. (2023). Advantages and Disadvantages of Lewin’s Change Model. [online] Leadership and Management Training Courses UK | MTD Training. Available at: https://www.mtdtraining.com/blog/advantages-disadvantages-lewins-change-model.htm [Accessed 5 Feb. 2025].
Musaigwa, M. (2023). The Role of Leadership in Managing Change. [online] ResearchGate. Available at: https://www.researchgate.net/publication/375562628_The_Role_of_Leadership_in_Managing_Change [Accessed 5 Feb. 2025].
Mustafa, B. and Lleshi, S. (2024). The impact of lifelong learning and investments in employee development on employee productivity and performance. Multidisciplinary Reviews, 7(8), pp.2024175–2024175. doi:https://doi.org/10.31893/multirev.2024175.
Nagata, T., Mori, K., Ohtani, M., Nagata, M., Kajiki, S., Fujino, Y., Matsuda, S. and Loeppke, R. (2018). Total Health-Related Costs Due to Absenteeism, Presenteeism, and Medical and Pharmaceutical Expenses in Japanese Employers. Journal of Occupational and Environmental Medicine, [online] 60(5), pp.e273–e280. doi:https://doi.org/10.1097/jom.0000000000001291.
NIH (2021). Is Implicit Bias Training Effective? [online] PubMed. Bethesda (MD): National Institutes of Health (NIH). Available at: https://www.ncbi.nlm.nih.gov/books/NBK603840/.
Onyeador, I.N., Hudson, S.T.J. and Lewis, N.A. (2021). Moving Beyond Implicit Bias Training: Policy Insights for Increasing Organizational Diversity. Policy Insights from the Behavioral and Brain Sciences, [online] 8(1), pp.19–26. doi:https://doi.org/10.1177/2372732220983840.
Oracle (2022). What is an Applicant Tracking System ? [online] Oracle.com. Available at: https://www.oracle.com/ke/human-capital-management/recruiting/what-is-applicant-tracking-system/ [Accessed 5 Feb. 2025].
Pantelakis, A. (2023). The benefits of using AI applicant tracking systems. [online] Recruiting Resources: How to Recruit and Hire Better. Available at: https://resources.workable.com/stories-and-insights/ai-applicant-tracking [Accessed 5 Feb. 2025].
Parliament.uk. (2022). Post-pandemic economic growth: UK labour markets – Business, Energy and Industrial Strategy Committee. [online] Available at: https://publications.parliament.uk/pa/cm5803/cmselect/cmbeis/306/report.html [Accessed 5 Feb. 2025].
Psico-smart (2020). The Impact of Artificial Intelligence on Applicant Tracking Systems: Trends and Innovations. [online] Psico-smart.com. Available at: https://psico-smart.com/en/blogs/blog-the-impact-of-artificial-intelligence-on-applicant-tracking-systems-trends-and-innovations-173707 [Accessed 5 Feb. 2025].
Raza, M. (2019). Lewin’s 3 Stage Model of Change Explained. [online] bmc. Available at: https://www.bmc.com/blogs/lewin-three-stage-model-change/ [Accessed 5 Feb. 2025].
Rodgers, W., Murray, J.M., Stefanidis, A., Degbey, W.Y. and Tarba, S.Y. (2022). An artificial intelligence algorithmic approach to ethical decision-making in human resource management processes. Human Resource Management Review, 33(1), p.100925. doi:https://doi.org/10.1016/j.hrmr.2022.100925.
Salamon, J., Blume, B.D., Orosz, G. and Nagy, T. (2021). The interplay between the level of voluntary participation and supervisor support on trainee motivation and transfer. Human Resource Development Quarterly, 32(4). doi:https://doi.org/10.1002/hrdq.21428.
Scott, A.J. (2021). The longevity economy. The Lancet Healthy Longevity, [online] 2(12), pp.e828–e835. doi:https://doi.org/10.1016/S2666-7568(21)00250-6.
Shah, H.S. and Bohlen, J. (2023). Implicit bias. [online] PubMed. Available at: https://www.ncbi.nlm.nih.gov/books/NBK589697/.
Sharma, A. (2016). Managing diversity and equality in the workplace. Cogent Business & Management, [online] 3(1), pp.1–14. doi:https://doi.org/10.1080/23311975.2016.1212682.
Sharma, K. (2022). 10 Proven Change Management Models. [online] Whatfix Digital Adoption Blog | Insights, News, Tips, Trends – Whatfix Blog. Available at: https://whatfix.com/blog/10-change-management-models/ [Accessed 5 Feb. 2025].
SHRM (2024). Managing Flexible Work Arrangements. [online] www.shrm.org. Available at: https://www.shrm.org/mena/topics-tools/tools/toolkits/managing-flexible-work-arrangements [Accessed 5 Feb. 2025].
Simonite, T. (2020). With Its Own Chips, Apple Aims to Define the Future of PCs. [online] Wired. Available at: https://www.wired.com/story/own-chips-apple-aims-define-future-pcs/ [Accessed 5 Feb. 2025].
Sołek-Borowska, C. and Wilczewska, M. (2018). New Technologies in the Recruitment Process. Economics and Culture, [online] 15(2), pp.25–33. doi:https://doi.org/10.2478/jec-2018-0017.
Stockbridge, M. (2024). Ways to Eliminate Bias in Recruitment Using Tech. [online] Aquent Talent. Available at: https://aquenttalent.com/blog/ways-to-eliminate-bias-in-recruitment-using-tech [Accessed 5 Feb. 2025].
Universum (2024). Employer Branding on Social Media: Tips and Benefits. [online] Universumglobal.com. Available at: https://universumglobal.com/resources/blog/employer-branding-on-social-media-tips-and-benefits/ [Accessed 5 Feb. 2025].
Wowor, M.C., Mandagi, D.W., Lule, B. and Ambalao, S.S. (2022). The Role of Social Media in Employee Recruitment: a Systematic Literature Review. Jurnal Multidisiplin Madani, [online] 2(12), pp.4118–4125. doi:https://doi.org/10.55927/mudima.v2i12.1957.
Zahra Zahedi Nejad, Mehdi Sabokro and Eeva-Liisa Oikarinen (2024). Challenges in adopting and using online recruitment tools from employers’ perspective. International journal of organizational analysis. doi:https://doi.org/10.1108/ijoa-10-2023-4050.
Zerguine, H., Healy, G.N., Goode, A.D., Zischke, J., Abbott, A., Gunning, L. and Johnston, V. (2023). Online office ergonomics training programs: A scoping review examining design and user-related outcomes. Safety Science, 158, p.106000. doi:https://doi.org/10.1016/j.ssci.2022.106000.
Must Read:
