Multinationals and human resource practices in Ireland: a rejection of the 'new conformance thesis': a reply

This paper reports on a study of 398 people employed in two UK service organizations: a hospital and two divisions of a high street bank. The main purpose of the study was to determine the degree to which dispositional factors (predisposition to trust and trait anxiety) and situational factors (seven aspects of the job environment) predicted a person's reported trust in their managers. Two types of managers were investigated: a person's immediate line manager and ‘senior managers in their industry’. It was hypothesized that the dispositional factors would have a greater influence on trust in managers in the industry and that situational factors would have a greater influence on trust in one's immediate line manager. The first hypothesis was supported, but the second was not. It was found that trust in both types of managers was best predicted by a combination of general disposition to trust (not trait anxiety) and situational factors: five of the seven situational factors had a role in predicting intention to trust. This reflects the complexity involved in predicting trust at work and the managerial challenge of creating a trusting culture.     

Neoliberalization,Housing Institutions and Variegated Gentrification: How the ‘Third Wave’ Broke in Amsterdam

Neil Smith argues that in the last two decades gentrification has become a generalized global urban phenomenon. His theory is at a high level of abstraction, as it links urban gentrification to globalization, financial capitalism and neoliberalization. With these global processes, all cities have experienced ‘third wave’ gentrification. The theory, however, leaves little room for variegations of gentrification, apart from characterizing geographical differences as idiosyncrasies or as minor variations. This downplays the role of intervening mechanisms that impinge upon the pursuit and social outcomes of gentrification. This article aims to amend abstract theory by looking at Amsterdam from a historical institutional perspective. In Amsterdam, gentrification was particularly made possible by a process of neoliberalization within the housing system. However, as institutional change is incremental and based on layering and conversion, many older institutional arrangements remain in place. These arrangements tend to slow gentrification and assuage social consequences. Nevertheless, neoliberal modifications to the housing system have been accelerating the pursuit of gentrification. Current policies will very likely lead to exclusionary displacement.     

Offshore Outsourcing: Implications for International Business and Strategic Management Theory and Practice

abstract    In this essay, I discuss the implications of the debate over offshoring for our collective understanding of international business and management theories. I review several core theories in international business expansion and management strategy to assess which elements of these theories may need to be re-specified in light of the offshoring phenomenon and which aspects remain relevant. I then present normative implications and recommendations for public policy and corporate strategy, drawing from emerging insights regarding the global responsibilities of corporations. I suggest that international labour and environmental standards and corporate codes of conduct could mitigate some of the most intense concerns raised about offshoring but conclude that offshoring is likely to present challenges to societies, corporations, and stakeholders for many decades.     

Three Corrected Score Tests for Generalized Linear Models with Dispersion Covariates

We develop three corrected score tests for generalized linear models with dispersion covariates, thus generalizing the results of Cordeiro , Ferrari and Paula (1993) and Cribari-Neto and Ferrari (1995) . We present, in matrix notation, general formulae for the coefficients which define the corrected statistics. The formulae only require simple operations on matrices and can be used to obtain analytically closed-form corrections for score test statistics in a variety of special generalized linear models with dispersion covariates. They also have advantages for numerical purposes since our formulae are readily computable using a language supporting numerical linear algebra. Two examples, namely, iid sampling without covariates on the mean or dispersion parameter oand one-way classification models, are given. We also present some simulations where the three corrected tests perform better than the usual score test, the likelihood ratio test and its Bartlett corrected version. Finally, we present a numerical example for a data set discussed by Simonoff and Tsai (1994) .     

Behavioral agency and corporate entrepreneurship: CEO equity incentives & competitive behavior

Scholars have long studied drivers of entrepreneurial behavior among established firms. Yet little is known about how individual factors shape a firm’s choice to pursue entrepreneurship. We draw on behavioral agency theory to explore the role of equity incentives in driving corporate entrepreneurship. Our findings suggest CEOs avoid corporate entrepreneurial behaviors as their option wealth increases. However industry dynamics also prove to be an important contingency when predicting the effects of both restricted stock and stock options on the likelihood that the CEO engages in corporate entrepreneurship. Our findings provide a theoretical platform for predicting dimensions of entrepreneurial behavior and highlight effects of CEO equity ownership.

     

Real‐time forecast combinations for the oil price

Baumeister and Kilian (Journal of Business and Economic Statistics, 2015, 33(3), 338–351) combine forecasts from six empirical models to predict real oil prices. In this paper, we broadly reproduce their main economic findings, employing their preferred measures of the real oil price and other real‐time variables. Mindful of the importance of Brent crude oil as a global price benchmark, we extend consideration to the North Sea‐based measure and update the evaluation sample to 2017:12. We model the oil price futures curve using a factor‐based Nelson–Siegel specification estimated in real time to fill in missing values for oil price futures in the raw data. We find that the combined forecasts for Brent are as effective as for other oil price measures. The extended sample using the oil price measures adopted by Baumeister and Kilian yields similar results to those reported in their paper. Also, the futures‐based model improves forecast accuracy at longer horizons.     

Dispatching and routing of emergency vehicles in disaster mitigation using data fusion

The aim of this paper is to develop a robust methodology for the dispatching and routing of emergency vehicles (EVs) in a post-disaster environment with the support of data fusion. In this work, we consider an earthquake scenario with a large number of casualties needing medical attention. Given an influx of information (regarding casualties, road, traffic conditions, etc.), data are fused to provide estimates of the entities under consideration. We use this information to dispatch and route EVs to casualty pickup locations, followed by delivery to appropriate hospitals. Key factors here include patient priorities, clustering criteria, and distance. Similarly, factors affecting the dispatching of EVs from patient locations to hospitals include waiting time at hospital emergency rooms, hospital capacity, and distance. Routes must be generated for EVs by accounting for real-world road networks, existing road damage, congestion, and related issues. We develop a dispatching and routing simulation model, and utilize a case study to evaluate the performance of our proposed methodology.     

Defining efficient policies in a general equilibrium model: a multi-objective approach

Macroeconomic policy makers are typically concerned with several indicators of economic performance. We thus propose to tackle the design of macroeconomic policy using Multicriteria Decision Making (MCDM) techniques. More specifically, we employ Multi-objective Programming (MP) to seek so-called efficient policies. The MP approach is combined with a computable general equilibrium (CGE) model. We chose use of a CGE model since it has the dual advantage of being consistent with standard economic theory while allowing one to measure the effect(s) of a specific policy with real data. Applying the proposed methodology to Spain (via the 1995 Social Accounting Matrix) we first quantified the trade-offs between two specific policy objectives: growth and inflation, when designing fiscal policy. We then constructed a frontier of efficient policies involving real growth and inflation. In doing so, we found that policy in 1995 Spain displayed some degree of inefficiency with respect to these two policy objectives. We then offer two sets of policy recommendations that, ostensibly, could have helped Spain at the time. The first deals with efficiency independent of the importance given to both growth and inflation by policy makers (we label this set: general policy recommendations). A second set depends on which policy objective is seen as more important by policy makers: increasing growth or controlling inflation (we label this one: objective-specific recommendations).     

Linking improved knowledge management to operational and organizational performance

This research empirically examines the importance of knowledge management processes to operational and overall organizational performance (OPERF). Specifically, results indicate that a shared interpretation of knowledge among operational personnel mediates how knowledge is disseminated and used to design and implement a unified operational response to that knowledge. Further, results collected in a logistics operations (LO) context support a strong positive relationship between this knowledge management process and operational and organizational performance. Importantly, psychometric measures for organizational performance collected from managerial respondents were strongly correlated with secondary financial data for participating firms obtained from Compustat, thus supporting a link about operational performance and hard organizational performance data.