Innis Lecture: Can the Theory of Incentives Explain Decentralization?

This survey presents within a single model three theories of decentralization of decision-making within organizations based on private information and incentives. Renegotiation, collusion, and limits on communication are three sufficient conditions for decentralization to be optimal.

Contentious Contracts

This paper offers an explanation of rationally contracts where incompeteness refers to unforeseen contingencies. Agents enter a relationship with two-sided moral hazard in which a commitment to discard parts of the joint resources may be ex ante efficient.

Relative Uncertainty and Additively Representable Set Rankings

This paper proposes a definition of relative uncertainty aversion for decision models under complete uncertainty. It is shown that, for a large class of decision rules characterized by a set of plausible axioms, the new criterion yields a complete ranking of those rules with respect to the relative degree of uncertainty aversion they represent. In addition, we address a combinatorial question that arises in this context, and we examine conditions for the additive representability of our rules.

Integrating design attributes, knowledge and uncertainty in aerospace sector

The delivery of integrated product and service solutions is growing in the aerospace industry, driven by the potential of increasing profits. Such solutions require a life cycle view at the design phase in order to support the delivery of the equipment. The influence of uncertainty associated with design for services is increasingly a challenge due to information and knowledge constraints. There is a lack of frameworks that aim to define and quantify relationship between information and knowledge with uncertainty. Driven by this gap, the paper presents a framework to illustrate the link between uncertainty and knowledge within the design context for services in the aerospace industry. The paper combines industrial interaction and literature review to initially define the design attributes, the associated knowledge requirements and the uncertainties experienced. The framework is then applied in three cases through development of causal loop models (CLMs), which are validated by industrial and academic experts. The concepts and inter-linkages are developed with the intention of developing a software prototype. Future recommendations are also included. © 2014 CIRP.

Investment Under Demand Uncertainty: the Newsboy Problem Revisited.

In this article we study the effect of uncertainty on an entrepreneur who must choose the capacity of his business before knowing the demand for his product. The unit profit of operation is known with certainty but there is no flexibility in our one-period framework. We show how the introduction of global uncertainty reduces the investment of the risk neutral entrepreneur and, even more, that the risk averse one. We also show how marginal increases in risk reduce the optimal capacity of both the risk neutral and the risk averse entrepreneur, without any restriction on the concave utility function and with limited restrictions on the definition of a mean preserving spread. These general results are explained by the fact that the newsboy has a piecewise-linear, and concave, monetary payoff witha kink endogenously determined at the level of optimal capacity. Our results are compared with those in the two literatures on price uncertainty and demand uncertainty, and particularly, with the recent contributions of Eeckhoudt, Gollier and Schlesinger (1991, 1995).

The Macroeconomic Effects of Infrequent Information with Adjustment Costs

In the last decade, the potential macroeconomic effects of intermittent large adjustments in microeconomic decision variables such as prices, investment, consumption of durables or employment – a behavior which may be justified by the presence of kinked adjustment costs – have been studied in models where economic agents continuously observe the optimal level of their decision variable. In this paper, we develop a simple model which introduces infrequent information in a kinked adjustment cost model by assuming that agents do not observe continuously the frictionless optimal level of the control variable. Periodic releases of macroeconomic statistics or dividend announcements are examples of such infrequent information arrivals. We first solve for the optimal individual decision rule, that is found to be both state and time dependent. We then develop an aggregation framework to study the macroeconomic implications of such optimal individual decision rules. Our model has the distinct characteristic that a vast number of agents tend to act together, and more so when uncertainty is large. The average effect of an aggregate shock is inversely related to its size and to aggregate uncertainty. We show that these results differ substantially from the ones obtained with full information adjustment cost models.

Cognition in Seemingly Riskless Choices and Judgments.

We instillate rational cognition and learning in seemingly riskless choices and judgments. Preferences and possibilities are given in a stochastic sense and based on revisable expectations. the theory predicts experimental preference reversals and passes a sharp econometric test of the status quo bias drawn from a field study.

Investment Under Demand Uncertainty: the Newsboy Problem Revisited.

In this article we study the effect of uncertainty on an entrepreneur who must choose the capacity of his business before knowing the demand for his product. The unit profit of operation is known with certainty but there is no flexibility in our one-period framework. We show how the introduction of global uncertainty reduces the investment of the risk neutral entrepreneur and, even more, that the risk averse one. We also show how marginal increases in risk reduce the optimal capacity of both the risk neutral and the risk averse entrepreneur, without any restriction on the concave utility function and with limited restrictions on the definition of a mean preserving spread. These general results are explained by the fact that the newsboy has a piecewise-linear, and concave, monetary payoff witha kink endogenously determined at the level of optimal capacity. Our results are compared with those in the two literatures on price uncertainty and demand uncertainty, and particularly, with the recent contributions of Eeckhoudt, Gollier and Schlesinger (1991, 1995).

Moral Hazard and Marshallian Inefficiency: Evidence from Tunisia.

In the presence of moral hazard, received agency theory predicts the Marshallian inefficiency of agricultural tenancy contracts, meaning that inputs per hectare on sharecropped land will differ from that on owned land. in this paper, we test for the presence of Marshallian inefficiency using a unique data set collected in the Tunisian village of El Oulja in 1993.

Becoming “Librarian 2.0” : the skills, knowledge, and attributes required by library and information science professionals in a Web 2.0 world (and beyond)

In 2005, Stephen Abram, vice president of Innovation at SirsiDynix, challenged library and information science (LIS) professionals to start becoming “librarian 2.0.” In the last few years, discussion and debate about the “core competencies” needed by librarian 2.0 have appeared in the “biblioblogosphere” (blogs written by LIS professionals). However, beyond these informal blog discussions few systematic and empirically based studies have taken place. This article will discuss a research project that fills this gap. Funded by the Australian Learning and Teaching Council, the project identifies the key skills, knowledge, and attributes required by “librarian 2.0.” Eighty-one members of the Australian LIS profession participated in a series of focus groups. Eight themes emerged as being critical to “librarian 2.0”: technology, communication, teamwork, user focus, business savvy, evidence based practice, learning and education, and personal traits. This article will provide a detailed discussion on each of these themes. The study’s findings also suggest that “librarian 2.0” is a state of mind, and that the Australian LIS profession is undergoing a significant shift in “attitude.”

The internetalisation of information, knowledge and interaction components of the firm’s internationalisation process

Transcending traditional national borders, the Internet is an evolving technology that has opened up many new international market opportunities. However, ambiguity remains, with limited research and understanding of how the Internet influences the firm’s internationalisation process components. As a consequence, there has been a call for further investigation of the phenomenon. Thus, the purpose of this study was to investigate the Internet’s impact on the internationalisation process components, specifically, information availability, information usage, interactive communication and international market growth. Analysis was undertaken using structural equation modelling. Findings highlight the mediating impact of the Internet on information and knowledge transference in the internationalisation process. Contributions of the study test conceptualisations and give statistical validation of interrelationships, while illuminating the Internet’s impact on firm internationalisation.

External knowledge and query strategies in active learning: A study in clinical information extraction

This paper presents a new active learning query strategy for information extraction, called Domain Knowledge Informativeness (DKI). Active learning is often used to reduce the amount of annotation effort required to obtain training data for machine learning algorithms. A key component of an active learning approach is the query strategy, which is used to iteratively select samples for annotation. Knowledge resources have been used in information extraction as a means to derive additional features for sample representation. DKI is, however, the first query strategy that exploits such resources to inform sample selection. To evaluate the merits of DKI, in particular with respect to the reduction in annotation effort that the new query strategy allows to achieve, we conduct a comprehensive empirical comparison of active learning query strategies for information extraction within the clinical domain. The clinical domain was chosen for this work because of the availability of extensive structured knowledge resources which have often been exploited for feature generation. In addition, the clinical domain offers a compelling use case for active learning because of the necessary high costs and hurdles associated with obtaining annotations in this domain. Our experimental findings demonstrated that 1) amongst existing query strategies, the ones based on the classification model’s confidence are a better choice for clinical data as they perform equally well with a much lighter computational load, and 2) significant reductions in annotation effort are achievable by exploiting knowledge resources within active learning query strategies, with up to 14% less tokens and concepts to manually annotate than with state-of-the-art query strategies.