Performance measurement systems and their relation to strategic learning: A case study in a software-developing organization

Authors have often suggested that expert systems for measuring and assessing intangible and tangible resources fulfill strategic learning purposes. This role requires further theoretical discussion and empirical investigation since strategic learning does not automatically result from the implementation of performance measurement systems (PMS). PMS can be used for internal or external control purposes in addition their development and usage can lead to strategic learning processes. Depending on how PMS are conceptualized they can be related to different modes of learning. Thus, this article links different types of PMS enactment with specific modes of learning. Strategic learning is thereby defined as specific mode within the organizational learning approach by Bateson (1972) and Argyris and Schön (1978). Orlikowski's work on technologies (2000) provides a framework for the different types of PMS enactment. A strategic learning process initiated by the development of PMS is illustrated through a case study in the software development industry.     

Embedded markets: A dialogue between F.A. Hayek and Karl Polanyi

The recent economic crisis has once more underscored the close connection between markets and social life, thrusting this point at the centre of the analysis of economic and political activity and has once more asked the question of whether and how individuals are embedded in both. Here I argue that an analysis and partial reconciliation of the positions of F.A. Hayek and Karl Polanyi on the topic can help in this debate.     

Creating positive habits in water conservation: the case of the Queensland Water Commission and the Target 140 campaign

This case study reports the activities of the Queensland Water Commission (QWC) in securing the water supply for Brisbane and surrounding South East Queensland (SEQ) in response to the worst drought on record. The case focuses on residential water use and examines a three year period from 2006 to 2009. The focus of the study is the interventions of 2007, which centres on the Target 140 campaign. In 2007, the QWC faced with critically low dam levels identified household consumption as responsible for 70% of water use. The eight month Target 140 campaign targeted household users, aiming to change the water use habits of SEQ residents. The campaign achieved not only immediate reductions in water use but also contributed to long term behavioural and attitudinal change. The aim of the campaign was to reduce water consumption from 180 litres (l) /person/day to a target of 140 l /person/day by the end of 2007. This was achieved with water consumption dropping to an average of 129 l/person/day during the campaign and saving over 20 billon litres of water. In 2009, despite the drought broken for over a year and the water consumption target lifted to 200 l /person/day residents were continuing to consume water, on average, less than 140 l /person/day. The outcome was a capstone result for the QWC, and the Target 140 campaign went on to achieve international industry recognition. This case study demonstrates how attitudinal change, goal setting and feedback were key components of the change strategy and outlines the tactics used during the campaign. Furthermore, the case study discusses these mechanisms for change in terms of a theoretical understanding. Copyright © 2011 John Wiley & Sons, Ltd.     

Machine learning for pricing American options in high-dimensional Markovian and non-Markovian models

In this paper we propose two efficient techniques which allow one to compute the price of American basket options. In particular, we consider a basket of assets that follow a multi-dimensional Black–Scholes dynamics. The proposed techniques, called GPR Tree (GRP-Tree) and GPR Exact Integration (GPR-EI), are both based on Machine Learning, exploited together with binomial trees or with a closed form formula for integration. Moreover, these two methods solve the backward dynamic programing problem considering a Bermudan approximation of the American option. On the exercise dates, the value of the option is first computed as the maximum between the exercise value and the continuation value and then approximated by means of Gaussian Process Regression. The two methods mainly differ in the approach used to compute the continuation value: a single step of the binomial tree or integration according to the probability density of the process. Numerical results show that these two methods are accurate and reliable in handling American options on very large baskets of assets. Moreover we also consider the rough Bergomi model, which provides stochastic volatility with memory. Despite that this model is only bidimensional, the whole history of the process impacts on the price, and how to handle all this information is not obvious at all. To this aim, we present how to adapt the GPR-Tree and GPR-EI methods and we focus on pricing American options in this non-Markovian framework.     

“Less is more” or “more is better”? The effect of asymmetric information distribution on market efficiency and wealth inequality

Journal of Economic Interaction and Coordination - We provide experimental and empirical evidence on the role of information distribution and accuracy in solving market inefficiency and the related...     

On the Relative Optimality of Environmental Policy Instruments: An Application of the Work of Alberto Alesina

We study the issue of optimality of policies devoted to environmental goals, building upon the recent and interesting work by Alesina and Passarelli (2010) and extending their analysis to the more general framework set up by Weitzman (The Review of Economic Studies 41: 477-491, 1974). We illustrate instruments that governments have at their disposal to reduce polluting emissions, and we point out the economic implications that may arise from the overlapping regulation through both instruments in the European context. We review the literature on political determination of environmental regulation. On the basis of existing literature, we show that political factors are more important than economic ones in explaining why particular instruments are implemented for certain problems (Hepburn et al. Climate Policy 6: 137–160, 2006). We recognize Alesina’s contribution which states that environmental policy, and the decision to adopt one tool instead of another, is subject to a complex political process. Governments are subject to pressure from politicians, households, and firms because their decisions imply winners and losers. Then, we focus in detail on the work by Alesina and Passarelli (2010) who consider which policy tool and at what level would be chosen by majority voting to reduce polluting emissions; they find out that even if a tax is in general superior to quantity based mechanisms (quotas and tradable permits), the majority may strategically choose a quantity mode in order to charge the minority a larger share of the cost for polluting emissions reduction. We extend Alesina’s analysis, focusing on the optimality of price-based mechanisms, since it is not always the case that price instruments are more efficient than quantity instruments. To this aim, we explicitly make use of Weitzman results (The Review of Economic Studies 41: 477–491, 1974), which suggest that if costs are highly nonlinear compared to benefits, then price-type regulation is more efficient, while if costs are close to linear, then quantity-type regulation is more efficient. We cast Alesina’s analysis in the European context, analyzing potential voting outcomes, assuming that EU countries can be arranged according to different criteria. We find that depending on the empirical distribution of voting countries, Alesina’s voting procedure leads to interesting different outcomes.     

Updating and Estimating a Social Accounting Matrix Using Cross Entropy Methods

The problem in estimating a social accounting matrix (SAM) for a recent year is to find an efficient and cost-effective way to incorporate and reconcile information from a variety of sources, including data from prior years. Based on information theory, the paper presents a flexible 'cross entropy' (CE) approach to estimating a consistent SAM starting from inconsistent data estimated with error, a common experience in many countries. The method represents an efficient information processing rule-using only and all information available. It allows incorporating errors in variables, inequality constraints, and prior knowledge about any part of the SAM. An example is presented, applying the CE approach to data from Mozambique, using a Monte Carlo approach to compare the CE approach to the standard RAS method and to evaluate the gains in precision from utilizing additional information.     

Nonlinear economic growth: Some theory and cross-country evidence

This paper aims to test the existence of different growth regimes, that is of different relationships between growth rate and income level. We propose a simple nonlinear growth model and test its empirical implications by estimating Markov transition matrices and stochastic kernels. We show that growth is indeed nonlinear: a first phase of slow or zero growth is followed by a take-off and, finally, by a phase of deceleration. We discuss the relevance of these results with respect to the issue of convergence and reversibility of development, in the light of models of structural change and technological diffusion.