Time Management Strategies for Research Productivity

Researchers function in a complex environment and carry multiple role responsibilities. This environment is prone to various distractions that can derail productivity and decrease efficiency. Effective time management allows researchers to maintain focus on their work, contributing to research productivity. Thus, improving time management skills is essential to developing and sustaining a successful program of research. This article presents time management strategies addressing behaviors surrounding time assessment, planning, and monitoring. Herein, the Western Journal of Nursing Research editorial board recommends strategies to enhance time management, including setting realistic goals, prioritizing, and optimizing planning. Involving a team, problem-solving barriers, and early management of potential distractions can facilitate maintaining focus on a research program. Continually evaluating the effectiveness of time management strategies allows researchers to identify areas of improvement and recognize progress

Research Collaborations and Scientific productivity among the Research Universities in South Africa

This study presents the share of 5 most productive South African institutions for the main stream scientific out put covering the 10 year periods of 1995-2004. This paper discusses the distribution of publications by institutions, Index of specialization, collaboration and pattern of co-authorship. The result shows that South African authors collaborate more frequently with international authors with a percentage of (73.99%) than did so for national collaboration which amount to (26.01%). This was confirmed statistically at the confidence level of P-value 0.025. A further non-parametric chi-square statistical analysis illustrated that there are significant differences in the proportion of co-authorship among the 5 institutions (p-value0.005)

Research and Productivity

We model research as a signal on an unknown parameter of a technology. We distinguish applied from basic research and show that firms in the same industry can optimally choose different research portfolios, and that basic research can seem to have a higher rate of return than applied research, even though it really doesn't -- essentially, firms on a 'fast track' upgrading policy opt for basic research but fast and slow-track upgrading policies can coexist in a long-run equilibrium. We also derive the lag structure for how R&D affects the firm's stock of knowledge. To a first approximation, the lags decay geometrically (as is typically assumed in practice) but the rate of decay is endogenous, and depends on how fast the firm is upgrading its technology.

Accounting for Research and Productivity Growth Across Industries

What factors underlie industry differences in research intensity and productivity growth? We develop a multi-sector endogenous growth model allowing for industry specific parameters in the production functions for output and knowledge, and in consumer preferences. We find that industry differences in both productivity growth and R&D intensity mainly reflect differences in "technological opportunities", interpreted as parameters of knowledge production. These include the capital intensity of R&D, knowledge spillovers, and diminishing returns to R&D. Among these parameters, we find that the degree of diminishing returns to R&D is the dominant factor when the model is calibrated to account for crossindustry differences in the US.Multisector growth, total factor productivity, R&D intensity, technological opportunity

An investigation on the skewness patterns and fractal nature of research productivity distributions at field and discipline level

The paper provides an empirical examination of how research productivity distributions differ across scientific fields and disciplines. Productivity is measured using the FSS indicator, which embeds both quantity and impact of output. The population studied consists of over 31,000 scientists in 180 fields (10 aggregate disciplines) of a national research system. The Characteristic Scores and Scale technique is used to investigate the distribution patterns for the different fields and disciplines. Research productivity distributions are found to be asymmetrical at the field level, although the degree of skewness varies substantially among the fields within the aggregate disciplines. We also examine whether the field productivity distributions show a fractal nature, which reveals an exception more than a rule. Differently, for the disciplines, the partitions of the distributions show skewed patterns that are highly similar

Industry funding of university research and scientific productivity.

University research provides valuable inputs to industrial innovation. It is therefore not surprising that private sector firms increasingly seek direct access through funding public R&D. This development, however, spurred concerns about possible negative long-run effects on scientific performance. While previous research mainly focused on a potential crowding-out of scientific publications through commercialization activities such as patenting or the formation of spin-off companies, we study the effects of direct funding from industry on professors’ publication and patenting efforts. Our analysis on a sample of 678 professors at 46 higher education institutions in Germany shows that a higher share of industry funding of a professor’s research budget results in a lower publication outcome both in terms of quantity and quality in subsequent years. For patents, we find that industry funding increases their quality measured by patent citations.scientific productivity; research funding; academic patents; technology transfer;