Public Management and Policy Networks

In this article we address the elaboration of the central concepts of a theory of networks and of network management. We suggest that the network approach builds on several theoretical traditions. After this we clarify the theoretical concepts and axioms of the policy network approach and argue that this framework has important explanatory power both on the level of strategic interaction processes as well as on the level of institutional relations. We argue that government's special resources and its unique legitimacy as representative of the common Interest make it the outstanding candidate for fulfilling the role of network manager, a role which means arranging and facilitating interaction processes within networks In such a way that problems of under or non representation are properly addressed and interests are articulated and dealt with in an open, transparent and balanced manner.     

Teamworking and Lean revisited: a reply to Carter et al.

This paper is a reply to Carter et al.’s response to an earlier paper of ours in this journal on the subject of teamworking under Lean in the UK public services . Our reply covers the following issues which Carter et al. have raised: the literature we used to structure our findings; the way in which we used concepts such as autonomy and teamworking; our research methods and approach; how Carter et al.’s newly available data on teamworking might be interpreted; and how data drawn from an official employee attitude survey might best be understood. On the basis of this, we conclude that Carter et al.’s paper fails to meet its objectives. On some things, the authors are simply wrong; on others, they grossly misrepresent our position; on still others, their interpretations are, at best, highly questionable.     

The external networking behaviour of public managers - the missing link of weak ties

There has been an increasing focus on managerial external networking behaviour within public administration. While most previous quantitative research has analysed such behaviour one dimensionally, we suggest a two-dimensional conceptualization based on the concepts of weak and strong ties. Utilizing measures resembling previous research, we explore the utility of the approach in an exploratory study of Danish local government. Our findings suggest that the two dimensions of external networking behaviour are distinct. We discuss our approach compared to previous approaches and argue that a conceptualization based on the distinction between strong and weak ties provides a promising framework for future research.     

ISO9001:2000中"过程方法"的理解和实施

文章结合ISO9000:2000系列标准的要求,就“过程”及“过程方法”的概念、过程方法的含义、过程方法的实施要点进行了系统、详尽的阐述。     

Communicative power: A linguistic approach to the study of the microdynamics of organizations

This article addresses the question of how communicative power is exercised in an organizational setting which is characterized according to its members as a “feminine” culture type (Hofstede, 1980, Organizational Dynamics, 9(1), 42–63). The purpose is threefold: firstly, to operationalize the concepts of “dominance” and “control” in an organizational setting by using a linguistic approach; secondly, to investigate the contribution of a linguistic approach to organizational research in exploring social interaction and, thirdly, to discuss some practical and theoretical implications for managerial work. The linguistic approach, involving a microanalysis, provided an analytical basis for understanding the fine web of interaction in the organization. In this way it served as an instrument for rendering visible the various steps in the interpretation, and the links between them. Against our theoretically grounded expectations, the empirical results suggest that the distribution of power cannot alone explain the extent to which institutional and cultural resources can be mobilized and organizations changed.     

Model combinations through revised base rates

Standard selection criteria for forecasting models focus on information that is calculated for each series independently, disregarding the general tendencies and performance of the candidate models. In this paper, we propose a new way to perform statistical model selection and model combination that incorporates the base rates of the candidate forecasting models, which are then revised so that the per-series information is taken into account. We examine two schemes that are based on the precision and sensitivity information from the contingency table of the base rates. We apply our approach on pools of either exponential smoothing or ARMA models, considering both simulated and real time series, and show that our schemes work better than standard statistical benchmarks. We test the significance and sensitivity of our results, discuss the connection of our approach to other cross-learning approaches, and offer insights regarding implications for theory and practice.     

Nowcasting China’s GDP Using a Bayesian Approach

Real time nowcasting is an assessment of current-quarter GDP from timely released economic and financial series before the GDP figure is disseminated. Providing a reliable current quarter nowcast in real time based on the most recently released economic and financial monthly data is crucial for central banks to make policy decisions and longer-term forecasting exercises. In this study, we use dynamic factor models to bridge monthly information with quarterly GDP and achieve reduction in the dimensionality of the monthly data. We develop a Bayesian approach to provide a way to deal with the unbalanced features of the dataset and to estimate latent common factors. We demonstrate the validity of our approach through simulation studies, and explore the applicability of our approach through an empirical study in nowcasting the China’s GDP using 117 monthly data series of several categories in the Chinese market. The simulation studies and empirical study indicate that our Bayesian approach may be a viable option for nowcasting the China’s GDP.     

Panel data analysis of U.S. coal productivity

We analyze labor productivity in coal mining in the United States using indices of productivity change associated with the concepts of panel data modeling. This approach is valuable when there is extensive heterogeneity in production units, as with coal mines. We find substantial returns to scale for coal mining in all geographical regions, and find that smooth technical progress is exhibited by estimates of the fixed effects for coal mining. We carry out a variety of diagnostic analyses of our basic model and primary modeling assumptions, using recently proposed methods for addressing ‘errors-in-variables’ and ‘weak instrument bias’ problems in linear and nonlinear models.     

Assessment of OECD Better Life Index by incorporating public opinion

Well-being has a multidimensional nature as it depends on multifaceted factors such as material conditions and quality of life. The Organization for Economic Co-operation and Development (OECD) has developed the Better Life Index (BLI) as part of the OECD Better Life initiative to facilitate the better understanding of what drives well-being of people. The BLI is a three-level hierarchical composite indicator that covers several socio-economic aspects. In this paper, considering the entire hierarchical structure of the index, we introduce a bottom-up procedure for the aggregation of the components at each level. We formulate the assessment of BLI as a multiple objective programming (MOP) problem that facilitates the implementation of different concepts to derive different aggregation schemes. We incorporate the data from previous years into the normalization process of the indicators, to take into account the discrepancy on their observed values and smooth their deviations across the years. Also, we consider the public opinion about well-being that is captured from the worldwide responses in the web platform of OECD BLI. We incorporate the public opinion into the assessment models in the form of weight restrictions. In this way, we reduce the effect of compensation that might be imposed by the adopted modelling approach. We apply our methodology to the data of 38 countries (35 OECD and 3 non-OECD economies) for the year 2017. Our findings illustrate that the public opinion in the form of weight restrictions can effectively drive the optimization process and depict the collective preferences to the BLI scores.     

Introducing Environmental Variables in Nonparametric Frontier Models: a Probabilistic Approach

This paper proposes a general formulation of a nonparametric frontier model introducing external environmental factors that might influence the production process but are neither inputs nor outputs under the control of the producer. A representation is proposed in terms of a probabilistic model which defines the data generating process. Our approach extends the basic ideas from Cazals et al. (2002) to the full multivariate case. We introduce the concepts of conditional efficiency measure and of conditional efficiency measure of order-m. Afterwards we suggest a practical way for computing the nonparametric estimators. Finally, a simple methodology to investigate the influence of these external factors on the production process is proposed. Numerical illustrations through some simulated examples and through a real data set on Mutual Funds show the usefulness of the approach.JEL Classification: C13, C14, D20     

Product attributes and models of multiple discreteness

Demand for product characteristics is examined within the context of models that allow for both corner and interior solutions corresponding to zero and non-zero demand. Product attribute information is associated with marginal utility and curvature (satiation) parameters of various utility functions. Empirical applications demonstrate the need for incorporating characteristics in a fairly general way. We also compare our approach to an ideal point and pure Lancasterian versions of our nonlinear utility model. The data support our model over either the ideal point or Lancasterian variants.     

Bridging macroeconomic data between statistical classifications: the count-seed RAS approach

ABSTRACT

In applications, it is often necessary to link heavily aggregated macroeconomic datasets adhering to different statistical classifications. We propose a simple data reclassification procedure for those cases in which a bridge matrix grounded in microdata is not available. The essential requirement of our approach, which we refer to as count-seed RAS, is that there exists a time period or a geographical entity similar to the one of interest for which the relevant economic variable is observed according to both classifications. From this information, a bridge matrix is constructed using bi-proportional methods to rescale a seed matrix based on a qualitative correspondence table from official sources. We test the procedure in two case studies and by Monte Carlo methods. We find that, in terms of reclassification accuracy, it performs noticeably better than other expeditious methods. The analytical framework underlying our approach may prove a useful way of conceptualizing data reclassification problems.     

Arbitrage concepts under trading restrictions in discrete-time financial markets

In a discrete-time setting, we study arbitrage concepts in the presence of convex trading constraints. We show that solvability of portfolio optimization problems is equivalent to absence of arbitrage of the first kind, a condition weaker than classical absence of arbitrage opportunities. We center our analysis on this characterization of market viability and derive versions of the fundamental theorems of asset pricing based on portfolio optimization arguments. By considering specifically a discrete-time setup, we simplify existing results and proofs that rely on semimartingale theory, thus allowing for a clear understanding of the foundational economic concepts involved. We exemplify these concepts, as well as some unexpected situations, in the context of one-period factor models with arbitrage opportunities under borrowing constraints.     

Using past contribution patterns to forecast fundraising outcomes in crowdfunding

The crowdfunding mechanism has proven to be a practical way of raising funds, especially with the widespread use of the Internet. However, one limitation of current crowdfunding platforms is that it is hard for creators and backers to anticipate the success of a campaign. This paper tackles this limitation. We take a two-pronged approach to building our forecasting model. First, we explore the nature and heterogeneity of contribution dynamics in crowdfunding campaigns and compare them across two natural groups (successful and unsuccessful campaigns). We then use insights generated from our exploratory analysis and draw upon the general laws of motion for stochastic processes in order to introduce a new dynamic model for predicting crowdfunding outcomes. Our model incorporates the history and dynamics of both the focal crowdfunding campaign and other campaigns for predicting outcomes. We compare our model to other parametric and semi-parametric benchmark models, and show substantial improvements.     

Exploring the Conceptual Expansion within the Field of Organizational Behaviour: Organizational Climate and Organizational Culture

Developments within social and exact sciences take place because scientists engage in scientific practices that allow them to further expand and refine the scientific concepts within their scientific disciplines. There is disagreement among scientists as to what the essential practices are that allow scientific concepts within a scientific discipline to expand and evolve. One group looks at conceptual expansion as something that is being constrained by rational practices. Another group, however, suggests that conceptual expansion proceeds along the lines of ‘everything goes’. The goal of this paper is to test whether scientific concepts expand in a rational way within the field of organizational behaviour. We will use organizational climate and culture as examples. The essence of this study consists of two core concepts: one within organizational climate and one within organizational culture. It appears that several conceptual variations are added around these core concepts. The variations are constrained by rational scientific practices. In other terms, there is evidence that the field of organizational behaviour develops rationally     

Context-dependent accountability strategies to improve the transfer of training: A proposed theoretical model and research propositions

The transfer of training continues to be a primary concern for organizations, yet important gaps in the literature remain. Thus, we extend recent work by Tews and Burke-Smalley (in press), which integrates accountability concepts from Schlenker (1997), along with Yelon and Ford's (1999) context-dependent transfer approach, to create a theoretical model and specific research propositions to help guide the field forward. We suggest that an accountability approach to training transfer, which simultaneously considers relevant work-context dimensions (e.g., skill type and supervision type) can be used to adopt appropriate accountability strategies that enhance trainees' transfer of learning back to their jobs. More specifically, by targeting variables that promote accountability – trainees' role clarity, ownership perceptions, and perceived control over their learning transfer – our work provides a useful theoretical model to guide scholars and practitioners in order to facilitate transfer in different workplace contexts. Implications for research and practice are also discussed.     

Forecasting with Bayesian Vector Autoregressions Estimated Using Professional Forecasts

We propose a Bayesian shrinkage approach for vector autoregressions (VARs) that uses short‐term survey forecasts as an additional source of information about model parameters. In particular, we augment the vector of dependent variables by their survey nowcasts, and claim that each variable modelled in the VAR and its nowcast are likely to depend in a similar way on the lagged dependent variables. In an application to macroeconomic data, we find that the forecasts obtained from a VAR fitted by our new shrinkage approach typically yield smaller mean squared forecast errors than the forecasts obtained from a range of benchmark methods. Copyright © 2015 John Wiley & Sons, Ltd.     

The Situations of Urban Inquiry: Thinking Problematically about the City

In the context of debates about the epistemological and ontological coherence of concepts of critical urban studies, we argue that urban concepts should be conceptualized problematically. We do so by aligning Michel Foucault's genealogical work on problematization with John Dewey's pragmatist understanding of problem formation and responsiveness. This approach brings into view the degree to which debates about urban futures are shaped by a variety of critical perspectives that extend beyond the academy and activism. We elaborate this argument through examples of global urban policy formation and practices of neighbourhood change. Approaching urban concepts problematically suggests a move away from the idea of critique as a form of scholastic correction towards an appreciation of the contested fields of practice in and through which critical understandings of urban problems emerge.     

Urban Informality and the State: Geographical Translations and Conceptual Alliances

Understandings of informality commonly derive from research undertaken in states perceived as lacking the capacity to regulate the practices of their populations. This Interventions forum aims to expand the geographical parameters of empirical research on urban informality. A more global approach, we argue, also necessitates questioning assumptions that undergird this concept—in particular the underlying conception of the state. In this vein, this collection of papers aims to rethink theories of the state through the lens of informality, and vice versa, to inform and refine the concept of informality through a more thorough understanding of states. In so doing, the contributions engage with concepts that have been central both to theories of the state and to the study of informality, namely governance, agency, legitimacy, sovereignty and legality. Following this introduction setting out our theoretical approach, the Interventions forum unites five empirical studies that discuss the nexus of informality and states in contexts that have been researched less extensively from this perspective, each tackling one of the above‐mentioned concepts. Based on these different entry points, the papers provide novel angles on a state‐theoretical understanding of informality. A concluding essay brings these approaches together, reflecting on the possibilities of translating concepts to different sites.     

What helps? Women engineers' accounts of staying on

We have considerable understanding of the obstacles that women engineers encounter and the reasons that they leave the field, but we know less about what enables them to remain. Adopting an interpretivist approach, this article examines how a group of British women engineers in two FTSE 100 companies account for “staying on” in their male‐dominated work settings. We delineate four specific forms of help that facilitate women's retention in the field. We argue that exposure to help leads to women developing a habitus that enables them to continue working in engineering. To conclude, we draw on our findings to outline HR practices that will facilitate supportive relationships in the workplace and pave the way towards developing more positive organisational climates.