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Although more women are entering managerial and professional jobs with increasingly appropriate academic and experience credentials for upward mobility, few of them make it to senior management or executive ranks (Morrison & Von Glinow, 1990). They encounter a glass ceiling (Morrison, White & Van Velsor, 1987), an almost impenetrable barrier, which prevents them from reaching the top levels.

Managerial success as an academic concept has not been researched and explored adequately in the management literature. The purpose of this research paper is to identify and analyze a set of success indicators that the working managers value most in their professional life. Further, these selective managerial success indicators were prioritized for different managerial hierarchies in the Indian context.

The data analysis was carried out using the analytical hierarchy process (AHP) technique as the basis for the comparisons of the success indicators for various levels of managerial hierarchy as well as for the representing variables under each success indicator.

The results established the prioritization of the managerial success indicators for the senior, middle, and junior levels of managerial hierarchy. The aggregative analyses for the entire data set also prioritized the variables under each success indicator studied in this research.

The study has practical implications for the top management in terms of providing them with the definitive success indicators of the working professionals, hence helping them achieve success by suitably facilitating these factors. The recruitment specialists can select the incumbent managers with the individualized characteristics identified in this study that facilitate professional success.

This research has addressed a relatively unexplored area of managerial success in the Indian context and outlined a framework for the prioritization of success factors by the Indian managerial community.

The purpose of this paper is to investigate a farm manager’s personal characteristics (personality, age, education, objectives, experience, etc.) as drivers of debt payback success and rates. Traditionally bankers have used historic business statistics, and equity levels, to assess loans and credit worthiness. It is hypothesised that a managers’ personal characteristics are likely to be a better predictor of future debt payback performance.

The literature was searched to isolate the managers’ personal variables likely to determine debt payback. The information led to defining a quantitative model based on the theory of planned behaviour (TPB) which was hypothesised as determining payback rates where a choice was available. A postal random stratified survey of NZ owner operator farm managers provided the data to test the model and define its parameters using regressions, structural equation modelling and statistical comparisons.

The modelling results make it clear a manager’s personal characteristics are highly correlated with debt payback and, logically, are very likely to be the drivers. Four random effects equations and a comparison of high- and low-debt payback managers led to this conclusion.

Bankers should use the managers’ personal characteristics, as defined in the regressions, alongside traditional measures when assessing farm business loan requests. This approach is opposite to the traditional methods using mainly historic data.

The use of the TPB in assessing debt payback is a new and novel approach showing how enduring personal characteristics can be used in assessing proposals, and particularly, entrepreneurs’ adventurist investments in situations where historic data are not available.