Establishing Relationships Between Risk Management and Knowledge Transfer

Risk management (RM) and Knowledge management (KM) have mostly been treated as separate management philosophies. Risk management is a widely taught topic in academia and is practiced in industry. Knowledge management is being taught at increasingly more colleges and many companies are discovering a need for managing knowledge. This dissertation shows that some research has been conducted to apply the principles of knowledge management in establishing risk management plans. To a lesser extent there has been research conducted to apply the philosophies of risk management to identifying knowledge gaps and maintaining corporate knowledge. Both risk management and knowledge management are broad fields. The literature review uncovers the planning, identification, analyzing, handling, documenting, and monitoring of risks as key areas of consideration for risk management. It additionally reveals knowledge transfer in the form of lessons learned, best practices and near misses as a focal investigation point for knowledge management. The question answered in this dissertation is Does knowledge transfer have a positive impact on risk management capabilities? A conceptual model of the relationships across knowledge transfer and risk management was built and six hypotheses were identified and statistically tested using data collected from the project environment. A data collection instrument was developed, vetted through peer review, and distributed using the Internet. Ninety complete responses were collected and provided the raw data to statistically test the validity of the measures and the hypotheses. The results support the general hypothesis that an increase in knowledge transfer will have a positive impact on risk management capabilities in projects. Another significant result is the amount, direction, and strengths of the significant statistical correlations found in this research across the measures of inter- and intra-knowledge transfer in projects and project risk management. The results of this research show that of the knowledge transfer methods considered in this study (i.e., best practices, lessons learned, and near misses) best practices have the highest number of significant statistical correlations across the measures used, including the strongest correlation found in this investigation. Additionally, it was also noted in the results that inter-knowledge transfer was significantly correlated with 70% more risk management measures than intra knowledge transfer. These results have implications for academics and engineering managers and suggest areas for future research

Who Creates Jobs? Small vs. Large vs. Young

The view that small businesses create the most jobs remains appealing to policymakers and small business advocates. Using data from the Census Bureau Business Dynamics Statistics and Longitudinal Business Database, we explore the many issues at the core of this ongoing debate. We find that the relationship between firm size and employment growth is sensitive to these issues. However, our main finding is that once we control for firm age there is no systematic relationship between firm size and growth. Our findings highlight the important role of business startups and young businesses in U.S. job creation.

Measuring the Dynamics of Young and Small Businesses: Integrating the Employer and Nonemployer Universes

We develop a preliminary version of an Integrated Longitudinal Business Database (ILBD) that combines administrative records and survey data for all employer and nonemployer business units in the United States. Unlike other large-scale business databases, the ILBD tracks business transitions from nonemployer to employer status. This feature of the ILBD opens a new frontier for the study of business formation, early lifecycle dynamics and the precursors to job creation in the U.S. economy. There are 5.4 million nonfarm business firms with employees as of 2000 and another 15.5 million with no employees. Our analysis focuses on 40 industries that account for nearly half of nonemployers and 36 percent of nonemployer revenues. Within these industries, nonemployers account for 14 percent of business revenues. About 220,000 of the seven million nonemployers in our selected industries hire workers and migrate to the employer universe over a three-year horizon. These Migrants account for 20 percent of revenue among young employers (three years or less since first hire). Compared to other nonemployers, the revenue of Migrants grows very rapidly in the year prior to and the year of transition to employer status.

Mom-and-Pop Meet Big-Box: Complements or Substitutes?

In part due to the popular perception that Big-Boxes displace smaller, often family owned (a.k.a. Mom-and-Pop) retail establishments, several empirical studies have examined the evidence on how Big-Boxes’ impact local retail employment but no clear consensus has emerged. To help shed light on this debate, we exploit establishment-level data with detailed location information from a single metropolitan area to quantify the impact of Big-Box store entry and growth on nearby single unit and local chain stores. We incorporate a rich set of controls for local retail market conditions as well as whether or not the Big-Boxes are in the same sector as the smaller stores. We find a substantial negative impact of Big-Box entry and growth on the employment growth at both single unit and especially smaller chain stores – but only when the Big-Box activity is both in the immediate area and in the same detailed industry.

The Spread of ICT and Productivity Growth: Is Europe really lagging behind in the New Economy?

The economic performance of some OECD countries over the past decade, most notably the United States, has renewed the interest of analysts and policy makers on economic growth and on how policy can eventually support it. This report sheds some light on this issue by relying on harmonised macro and sectoral data for OECD countries and a unique cross-country firm-level dataset. This allows to address a number of issues. What are the key factors explaining differences in output and productivity performances across OECD countries? What is the role of ICT-producing industry and the ICT-driven capital deepening in explaining the different growth patterns of countries? Does the adoption of IC technologies require organisational changes and/or changes in the composition of inputs? What is the contribution of new firms to overall productivity growth in general and in ICT-related sectors? Do ICT-industries show stronger firm and employment turnover rates? Is there any relationship between the spread of ICT and institutional features of the product and labour markets? For example, do stringent regulations on start-ups (as well as those affecting incumbents) affect the diffusion of ICT? Do differences in labour market policy and institutions explain different patterns of adoption of new technologies?Macro data clearly point to widening disparities in growth performance across the OECD countries, even on the basis of cyclically-adjusted series. These disparities are related to differences in labour utilisation rather than to widening differences in labour productivity growth rates: i.e. higher growth rates in output per capita observed in a number of countries have been accompanied by improvements in the utilisation of labour, while sluggish employment in others (mainly in continental Europe) have not been fully compensated by higher labour productivity growth, thereby leading to a further slowdown in output growth. However, observed changes in growth patterns in some countries are also the result of the information and communication technology (ICT) revolution. In particular, it is argued that those countries that have developed an ICT-producing industry -- and/or where other industries have been quick in adopting highly productive ICT equipment -- have been able to shift to higher output and productivity growth paths. In this respect, the United States and some smaller countries (e.g. Australia, Ireland) have benefited the most from this ICT revolution, while most large European economies are still lagging behind. The sectoral and micro analysis also reveals important cross-country differences. The U.S. economy seems to be better able to acquire comparative advantage in rapidly growing ICT market segments than most of its trading partners. At the micro level, there seems to be a different degree of "market experimentation" in the United States compared with Europe, even if aggregate firm turnover rates are similar. The findings suggest that in the U.S. new firms tend to be smaller (relative to average incumbent) and less productive when compared with their European counterparts, but, if successful, they also tend to grow much more rapidly.The micro evidence reported in the paper offers additional elements in our discussion of a growth-enhancing policy setting. Our results seem to suggest that certain institutional and regulatory settings may reduce the degree of market experimentation of new firms. This, in turn, could lower the speed with which a country shifts to a new technology, thereby offering an interpretation to the observed differences in innovation and adoption across the Atlantic. For example, low administrative costs of start-ups and not unduly strict regulations on labour adjustments in the United States, may stimulate potential entrepreneurs to start on a small scale, test the market and, if successful with their business plan, expand rapidly to reach the minimum efficient scale. In contrast, higher entry and adjustment costs in Europe may stimulate a pre-market selection of business plans with less market experimentation. Our econometric results lend some support to these considerations. By using pooled data (country, industry and time) we find that stringent regulatory settings in the product and labour markets contribute to hinder innovation activity and the adoption of leading technologies

Private Equity and Employment

Private equity critics claim that leveraged buyouts bring huge job losses. To investigate this claim, we construct and analyze a new dataset that covers U.S. private equity transactions from 1980 to 2005. We track 3,200 target firms and their 150,000 establishments before and after acquisition, comparing outcomes to controls similar in terms of industry, size, age, and prior growth. Relative to controls, employment at target establishments declines 3 percent over two years post buyout and 6 percent over five years. The job losses are concentrated among public-to-private buyouts, and transactions involving firms in the service and retail sectors. But target firms also create more new jobs at new establishments, and they acquire and divest establishments more rapidly. When we consider these additional adjustment margins, net relative job losses at target firms are less than 1 percent of initial employment. In contrast, the sum of gross job creation and destruction at target firms exceeds that of controls by 13 percent of employment over two years. In short, private equity buyouts catalyze the creative destruction process in the labor market, with only a modest net impact on employment. The creative destruction response mainly involves a more rapid reallocation of jobs across establishments within target firms.

Job Growth in Early Transition: Comparing Two Paths

Small start-up firms are the engine of job creation in early transition and yet little is known about the characteristics of this new sector. We seek to identify patterns of job growth in this sector in terms of niches left from central planning and ask about differences in job creation across two different transition economies: Estonia, which experienced rapid destruction of the pre-existing firms, and the Czech Republic, which reduced the old sector gradually. We find job growth within industries to be quantitatively more important than job growth due to across-industry reallocation. Furthermore, the industrial composition of startups is strikingly similar in the two countries. We offer convergence to "western" industry firm-size distributions as an explanation. We also find regularities in wage evolution across new and old firms, including small differences in job quality across the two transition paths.http://deepblue.lib.umich.edu/bitstream/2027.42/39888/3/wp503.pd