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.     

Correction of errors in Vetschera's (2004) model of behavioral uncertainty and investment

Modelling of behavioural uncertainty has been a concern for researchers for some time. This paper briefly reviews modelling related to uncertainty and the focuses on the model presented by Vetschera (2004). A model of decision behaviour has been developed in the paper with regard to investment and cooperation taking into account the uncertainty and lack of information. The model is an important contribution for it focuses on situations that are not usual to the normal principle agent problems. The present review however reveals some errors in the paper. Sometimes errors may appear editorial but the same errors may lead the interested reader or researcher to inappropriate paths, particularly those who may fail to follow an argument or comprehend the underlying meanings of the equations and analytical solutions. In this manner, further work on this important topic may be hindered if researchers accept forms as presented in the paper literally as facts to further work. The main contribution of this paper is that it presents the correct forms of the mathematical aspects and procedures of the Vetschera (2004) paper. Copyright © 2007 John Wiley & Sons, Ltd.     

Inconsistencies in Macroeconomic Data

In recent years large inconsistencies have appeared in the national accounts, causing a number of problems for forecasters and policy-makers. This paper briefly summarizes these problems and discusses some of the responses available to improve the statistics. It focuses on a simple mathematical procedure which can provide coherent accounts even when the reliability of the data which is being balanced is unknown. Some of the main results of applying such a procedure are then outlined and these are compared with the CSO's recent balanced accounts exercise. The paper concludes that, although the broad macroeconomic picture for real (as opposed to financial) variables is little changed by balancing, continued balancing exercises would be worthwhile because they reduce the uncertainty surrounding forecasts and hence policy-making.     

Decision making and planning under low levels of predictability

This special section aims to demonstrate the limited predictability and high level of uncertainty in practically all important areas of our lives, and the implications of this. It summarizes the huge body of solid empirical evidence accumulated over the past several decades that proves the disastrous consequences of inaccurate forecasts in areas ranging from the economy and business to floods and medicine. The big problem is, however, that the great majority of people, decision and policy makers alike, still believe not only that accurate forecasting is possible, but also that uncertainty can be reliably assessed. Reality, however, shows otherwise, as this special section proves. This paper discusses forecasting accuracy and uncertainty, and distinguishes three distinct types of predictions: those relying on patterns for forecasting, those utilizing relationships as their basis, and those for which human judgment is the major determinant of the forecast. In addition, the major problems and challenges facing forecasters and the reasons why uncertainty cannot be assessed reliably are discussed using four large data sets. There is also a summary of the eleven papers included in this special section, as well as some concluding remarks emphasizing the need to be rational and realistic about our expectations and avoid the common delusions related to forecasting.     

Cooperative choice and its framing effect under threshold uncertainty in a provision point mechanism

This paper explores how threshold uncertainty affects cooperative behaviors in the provision of public goods and the prevention of public bads. The following facts motivate our study. First, environmental (resource) problems are either framed as public bads prevention or public goods provision. Second, the occurrence of these problems is characterized by thresholds that are interchangeably represented as “nonconvexity,” “bifurcation,” “bi-stability,” or “catastrophes.” Third, the threshold location is mostly unknown. We employ a provision point mechanism with threshold uncertainty and analyze the responses of cooperative behaviors to uncertainty and to the framing for each type of social preferences categorized by a value orientation test. We find that aggregate framing effects are negligible, although the response to the frame is the opposite depending on the type of social preferences. “Cooperative” subjects become more cooperative in negative frames than in positive frames, whereas “individualistic” subjects are less cooperative in negative frames than in positive ones. This finding implies that the insignificance of aggregate framing effects arises from behavioral asymmetry. We also find that the percentage of cooperative choices non-monotonically varies with the degree of threshold uncertainty, irrespective of framing and value orientation. Specifically, the degree of cooperation is highest at intermediate levels of threshold uncertainty and decreases as the uncertainty becomes sufficiently large.     

Allowing for uncertainty in exogenous shocks to CGE models: the case of a new renewable energy sector

The paper explores the importance of allowing for uncertainty in the magnitude of exogenous shocks in Computable General Equilibrium (CGE) models. The shock examined is the introduction of a new onshore wind sector in North East Scotland. A simple analytical model is developed to show how, a priori, the size of the new sector (the model shock) is uncertain and asymmetrically distributed as a result of spatial correlation in costs and returns across potential development locations. The importance of allowing for this uncertainty is tested by comparing the results from a CGE model where the sector size is assumed known with certainty to those from a model where the sector size is a random variable with an asymmetric distribution. The results show the extent to which allowing for uncertainty can influence the magnitude of estimated impacts with some variables more sensitive to the uncertainty than others.     

Periodic learning about a hidden state variable

In active learning models the value function is necessarily convex in the priors. Hence, in combination with a concave objective, the decision problem need not become concave so that nonregularity problems are inherent. This paper considers an objective that unambiguously implies a quasi-convex decision problem and highlights the effect of the inherent nonregularities on active learning. A trigger policy for learning is shown to be optimal: the minimum amount of learning is optimal until uncertainty surpasses a critical value. At this trigger point the maximum amount of learning is chosen, uncertainty falls temporarily, and the cycle then repeats itself.     

Solid waste planning under uncertainty using evolutionary simulation-optimization

A key aspect of effective public planning design is to minimize the impact of negative outcomes that can arise from the violation of pre-established system constraint criteria. These planning situations can be especially complicated when several components within the studied system are either unknown or contain considerable stochastic uncertainty. In this paper, the concept of outcome minimization through the use of penalty functions is combined with grey programming (GP) into an evolutionary simulation-optimization (ESO) procedure in order to solve solid waste management problems containing significant sources of uncertainty. By employing outcome minimization concurrently with GP and ESO, it can be shown that plans that meet, or come close to meeting, required system criteria can be efficiently created. The efficacy of the procedure is demonstrated through its application to a solid waste planning case from the Municipality of Hamilton-Wentworth in the Province of Ontario, Canada. Since ESO techniques can be adapted to a wide variety of problem types in which some or all of the system components are stochastic, the practicality of this approach can be adapted to many operational and strategic planning situations containing significant sources of uncertainty.     

Set-valued solution concepts using interval-type payoffs for interval games

Uncertainty is a daily presence in the real world. It affects our decision making and may have influence on cooperation. Often uncertainty is so severe that we can only predict some upper and lower bounds for the outcome of our actions, i.e., payoffs lie in some intervals. A suitable game theoretic model to support decision making in collaborative situations with interval data is that of cooperative interval games. Solution concepts that associate with each cooperative interval game sets of interval allocations with appealing properties provide a natural way to capture the uncertainty of coalition values into the players’ payoffs. In this paper, some set-valued solution concepts using interval payoffs, namely the interval core, the interval dominance core and the interval stable sets for cooperative interval games, are introduced and studied. The main results contained in the paper are a necessary and sufficient condition for the non-emptiness of the interval core of a cooperative interval game and the relations between the interval core, the interval dominance core and the interval stable sets of such a game.     

Testing for unit roots in the presence of uncertainty over both the trend and initial condition

In this paper we provide a joint treatment of two major problems that surround testing for a unit root in practice: uncertainty as to whether or not a linear deterministic trend is present in the data, and uncertainty as to whether the initial condition of the process is (asymptotically) negligible or not. We suggest decision rules based on the union of rejections of four standard unit root tests (OLS and quasi-differenced demeaned and detrended ADF unit root tests), along with information regarding the magnitude of the trend and initial condition, to allow simultaneously for both trend and initial condition uncertainty.     

Input price uncertainty and the production-location decision : A Critique and Synthesis

This paper compares the recent work of Hsu and Mai with other recently published and soon to be published work incorporating input price uncertainty in production-location problems. It also clarifies, strengthens, and corrects some results contained in recently published papers.     

Ranking sectors using fuzzy output multipliers

Using input–output analysis to model the effects of changes in industry final demands is fraught with problems, many of which relate to the fundamental limitations of the concomitant linear framework. A further issue concerns the accuracy of the results, a consequence of the uncertainty surrounding the values of multipliers. Such uncertainty can create problems where the values of output multipliers are used to inform resource directions. This paper utilizes (and develops) a fuzzy input–output model and investigates the ranking of industries based on fuzzy output multipliers. The non-triviality of the fuzzy model is exposited in a general problem, where imprecision is defined by a proportional level of imprecision (fuzziness) in the technical coefficients. Through a nascent method for ranking fuzzy numbers, comparisons are made between the fuzzy and more traditional (non-fuzzy) analysis.     

In quest of useful models for educational systems

Analytical flow models are examined as a means for describing the performance of an educational system. Enrollment functions based on specified input functions are developed for a single grade for four special cases. A standard form for approximation is introduced and its use described. This leads to the proposition that complex systems can be fabricated of modules defined in terms of these standard approximations. Applications of this approach, and problems expected in its use, are discussed, including the question of quality of the educational process. The paper concludes with some brief comments on measurement and evaluation of performance.     

Uncertainty and Economic Sociology:

A BSTRACT . The paper discusses the role of uncertainty in economic sociology, aiming to clarify some controversial issues in the related literature. Initially, some conceptual remarks are made about the relation between economic sociology, neoclassical economics, and rational choice theory. Next, in light of the existing literature on uncertainty and economic sociology, we distinguish between complexity and different types of uncertainty. We also identify different versions of the maximization hypothesis and examine their relations to the different types of uncertainty. Then we defend a concept of fundamental uncertainty that emphasizes the role of institutions. A theory that combines fundamental uncertainty and institutions should emphasize not only the existence of behavior in accordance with institutions, but also the possibility of creative, bold, unconventional behavior, discussed next, as people may use the knowledge provided by institutions to go against the tide. Finally, we suggest that the primary distinction should be that between approaches to economic issues, not between disciplines.     

Model uncertainty and policy evaluation: Some theory and empirics

This paper explores ways to integrate model uncertainty into policy evaluation. We describe a general framework that includes both model averaging methods as well as some measures that describe whether policies and their consequences are model dependent. These general ideas are then applied to assess simple monetary policy rules for some standard New Keynesian specifications. We conclude that the original Taylor rule has good robustness properties, but may reasonably be challenged in overall quality with respect to stabilization by alternative simple rules, even when these rules employ parameters that are set without accounting for model uncertainty.     

Gauging the uncertainty of the economic outlook using historical forecasting errors: The Federal Reserve’s approach

The Federal Open Market Committee (FOMC) of the U.S. Federal Reserve regularly publishes participants’ qualitative assessments of forecast uncertainty, expressed relative to that seen on average in the past. The benchmarks used for these historical comparisons are the average root mean squared forecast errors (RMSEs) made by various private and government forecasters over the past twenty years. This paper documents how these benchmarks are constructed and discusses some of their properties. We draw several conclusions. First, if past performance is a reasonable guide to future accuracy, considerable uncertainty surrounds macroeconomic projections. Second, different forecasters have similar accuracy. Third, estimates of uncertainty about future real activity and interest rates are now considerably greater than prior to the financial crisis; in contrast, estimates of inflation accuracy have changed little. Finally, fan charts, constructed under certain assumptions and viewed in conjunction with the FOMC’s qualitative assessments, provide a reasonable approximation to future uncertainty.     

Uncertain outlays in time-to-build problems

In this paper we analyze investment projects in which there is uncertainty in the total investment cost in addition to uncertainty in the completed project value. We deal with an uncertain time-to-build. Uncertainties in investment cost are quite common in long-term, large-scale, path-breaking undertakings such as some R&D projects. We find that the inclusion of uncertainty in investment cost tends to mitigate the impacts of the uncertainty of completed project value. The implications of the results are significant. First, when uncertainty of investment cost is ignored, the value of the project is underestimated and a tendency toward underinvestment will result; and second, the existence of uncertainty in investment cost will cause long-term projects to require larger declines in value before discontinuation of investment should occur.     

The influence of environmental and organizational factors on innovation adoptions: Consequences for performance in public sector organizations

Although technical and administrative innovations have received much academic interest in recent years, our understanding of why some organizations adopt these innovations and others do not is still underdeveloped. This paper examines organizational and environmental factors that may explain the adoption of innovations in public sector organizations. Furthermore, how technical and administrative innovations affect firm performance is also examined. Regarding organizational factors, we analyze strategy and firm size. Regarding environmental factors, we analyze the effect of uncertainty and market concentration. Hypotheses are developed and tested using a combination of archival and survey data from the public healthcare sector. Our results suggest that environmental and organizational factors have inconsistent effects on the adoption of administrative and technical innovations in public sector organizations. Our findings also show that high adopters of both types of innovations are more sensitive to environmental factors than organizational factors. Furthermore, our paper shows that organizations that combine technical and administrative innovations increase their performance.     

Economic policy uncertainty,investor sentiment and financial stability—an empirical study based on the time varying parameter-vector autoregression model

This paper applies the time varying parameter-vector autoregression model to explore the dynamic relationship between economic policy uncertainty, investor sentiment and financial stability in China in different periods and at different time points. The empirical results show that economic policy uncertainty has an obvious negative impact on investor sentiment before 2012 and financial stability in the short term, and the influence of economic policy uncertainty on investor sentiment is greater than that of economic policy uncertainty on financial stability. These influences were more significant during the period of the global financial crisis in 2008. Moreover, investor sentiment had a positive and gradually increasing effect on financial stability, while after 2010, the positive impact gradually weakened. Furthermore, economic policy uncertainty is negatively affected by financial stability, and the effect of financial stability on investor sentiment is positive. In terms of mediating effects, economic policy uncertainty has an indirect impact on financial stability through investor sentiment and vice versa. This paper provides a new solution to economic problems explored in behavioral finance research. Additionally, Chinese government agencies can achieve the goal of preventing financial crises and maintaining financial stability by monitoring investor sentiment and implementing targeted economic policies.

     

On the asymptotic behavior of stochastic economic processes : Two examples from intertemporal allocation under uncertainty

Some of the recently developed models to deal with economic problems involving uncertainty are based on simplifying assumptions on the nature of the stochastic law of the environment influencing economic decisions. Relying on the theory of martingales, we derive some general results on the asymptotic behavior of two dynamic processes that are of interest in the theory of intertemporal resource allocation. The first example is related to the ‘turnpike’ theory of optimal allocation. The second is addressed to the question of allocation of a scarce resource by using prices when the supply of the resource is random.