Bidding for Firms with Unknown Characteristics

When a region successfully attracts a firm by offering subsidies, the firm often commits itself to performance targets in terms of employment. In this paper, we interpret these firm‐specific targets as a consequence of incomplete information. We analyze a model of two regions that compete for a firm, assuming that the firm's productivity is ex ante unknown. We show that performance targets often induce overemployment in high‐productivity firms, and that tax credits are often superior to lump‐sum payments. Moreover, when regions differ in wage rates, the low‐wage region wins the bid and has a higher surplus than under complete information. Finally, we show that, under incomplete information, bidding might not lead to efficient firm location.     

KfW/ZEW CO2 Panel: Vermeiden oder kaufen – Deutsche Unternehmen im Emissionshandel

The European Emission Trading Scheme (EU-ETS) is the first large-scale and inter-regional trading scheme for greenhouse gas emissions. It is seen as the central instrument of European climate policy. After a first testing-phase (2005–2007), the second trading period of the EU-ETS had started in 2008, with stronger incentives for investment in low-carbon technologies and carbon dioxide abatement. However, there is hardly any evidence how emissions trading fares in practice. The KfW/ZEW CO₂ Barometer shows that trading of emission permits is actively used by 75 percent of German companies, but the price-signals that stem from the EU-ETS were relatively weak so far—too weak to set strong incentives for carbon dioxide emission reductions on the company-level. Also in the case of the ‘clean development mechanism’ (CDM) which was introduced to promote emission reductions in developing counties, there is need for further development.     

Managing Dispersed Knowledge: Organizational Problems,Managerial Strategies,and Their Effectiveness

While there has been much progress in understanding organizational knowledge and knowledge management practices, some questions still remain unresolved. This paper argues that at least one important driver of knowledge‐related organizational problems has been rather neglected so far: that is, the dispersed nature of organizational knowledge. The paper analyses the organizational problems and managerial responses arising from dispersed knowledge. It identifies three drivers by which the dispersedness of knowledge leads to management problems: namely, it creates large numbers, asymmetries, and uncertainty. A number of managerial strategies for dealing with the different components of the problems created by the dispersedness of knowledge are identified and their effectiveness analysed, thereby informing managers as to how best to deal with dispersed knowledge. The analysis of uncertainty‐related implications of dispersed knowledge uncovers an overlooked distinction that is helpful for understanding dispersed knowledge and its managerial implications. This is the distinction between uncertainty and ambiguity, i.e. a strong form of uncertainty that cannot be remedied by the standard strategy of increasing the information available.     

Robust min–max portfolio strategies for rival forecast and risk scenarios

We consider an extension of the Markowitz mean–variance optimization framework to multiple return and risk scenarios. It is well known that asset return forecasts and risk estimates are inherently inaccurate. The method proposed provides a means for considering rival representations of the future. The optimal portfolio is computed, simultaneously with the worst case, to take account of all rival scenarios. This is a min-max strategy which is essentially equivalent to a robust pooling of the scenarios. Robustness is ensured by the noninferiority of min–max. For example, a basic worst-case optimal return is guaranteed in view of multiple return scenarios. If robustness happens to have too high a cost, guided by the min–max pooling, it is also possible to explore other pooling alternatives. A min–max algorithm is used to solve the problem and illustrate the robust character of min–max with return and risk scenarios. We study the properties of the min–max risk–return frontier and compare with the potentially suboptimal worst-case where the investment strategy and the worst case are computed separately.     

Learning and development opportunities as a tool for the retention of volunteers: a motivational perspective

The growing reliance on volunteers in Australia has heightened the need for non‐profit organisations to retain these valuable resources. However, the current literature on volunteer retention is limited. One potential way volunteers can be retained is by providing learning and development opportunities (LDOs). This study investigates the relationship between volunteer perceptions of LDOs, their motivations for volunteering, and retention. Analyses revealed significant main effects for LDOs and volunteer motivations on retention and several interactive effects demonstrating that LDOs can have differential effects on retention depending on the reasons for volunteering.