Summary Using dynamic theory and methods, we investigate the phenomenon of older workers who withdraw from paid work while still healthy. We focus on intention to retire as the penultimate stage in the retirement process. We extend socio‐emotional selectivity theory to explain the growth of intention to retire. Older workers have a rising perception of time running out but good health allows for an ongoing choice between remaining in work or active retirement. While, in general, older people in poor health have a greater intention to retire than those in good health, we hypothesize that the passage of time motivates the healthy to increase their intention to retire, especially when manager support is low. We examine longitudinal data consisting of three waves of survey responses (2011, 2012, and 2013) from 495 workers in their 50th year and older. We employ growth curve analysis (random coefficient modeling). The findings show that over a 2‐year period, in contrast to other older workers whose retirement intention remains stable, individuals in consistently good health but with low manager support demonstrate a growth in intention to retire. That is, we identify the “queue jumpers”: those workers who speeded up their retirement process relative to other older workers.

In the digitized World, information is entangled in a mesh of unstructured web. Finding and retrieving relevant web resources to suit the user's information requirement is a challenge. Moreover, understanding and adapting to cater to different user information requirements is also an uphill task. To achieve the desired outcome, it is needed to have user accepted technology. Therefore, web information retrieval systems, especially search engines, should be user centered.Technology Acceptance Model (TAM) provides a basis with which one traces how external variables influence belief, attitude, and intention to use. Two cognitive beliefs are posited by TAM; perceived usefulness and perceived ease of use. This empirical study explores the influence of Users and Environment characteristics on a modern web information retrieval system. This paper analyzes the variables to determine perceptions of usefulness, attitude and preferences leading towards frequent factors to influence typical TAM results.

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