Technology flows, outsourcing and productivity:an analysis of UK trade and FDI

The literature on technology spillovers from trade and FDI is ambiguous in its findings. This may in part be because of the assumption in much of the work that trade and FDI flows are homogeneous in their determinants and thus in their effects. We develop a taxonomy of trade and FDI determinants based on R&D intensity and unit labour cost differentials, and test for the presence of spillovers from inward investment and imports on an extensive sample of UK manufacturing plants. We find that both trade and FDI have measurable spillover effects, but the sign and extent of these effects varies depending on the technological and factor cost differentials between the recipient and host economies. There is therefore an identifiable link between the determinants and effects of trade and FDI which the previous literature has not explored.

Majority and minority influence using the afterimage paradigm:a replication with an unambiguous blue slide

This study re-examines the afterimage paradigm which claims to show that a minority produces a conversion in a task involving afterimage judgements (more private influence than public influence) as opposed to mere compliance produced by a majority. Subsequent failures to replicate this finding have suggested that the changes in the afterimages could be attributed to increased attention due to an ambiguous stimulus coupled with subject suspiciousness. This study attempted to replicate the original experiment but with an unambiguous stimulus in order to remove potential biases. The results showed shifts in afterimages consistent with the increased attention hypothesis for a minority and majority and these were unaffected by the level of suspiciousness reported by the subjects. Additional data shows that no shifts were found in a no-influence control condition showing that shifts were related to exposure to a deviant source and not to response repetition.

Improper use of formative endogenous variables

Researchers often develop and test conceptual models containing formative variables. In many cases, these formative variables are specified as being endogenous. This article provides a clarification of formative variable theory, distinguishing between the formative latent variable and the formative composite variable. When an endogenous latent variable relies on formative indicators for measurement, empirical studies can say nothing about the relationship between exogenous variables and the endogenous formative latent variable: conclusions can only be drawn regarding the exogenous variables' relationships with a composite variable. The authors also show the dangers associated with developing theory about antecedents to endogenous formative variables at the (aggregate) formative latent variable level. Modeling relationships with endogenous formative variables at the (disaggregate) indicator level informs richer theory development, and encourages more precise empirical testing. When antecedents' relationships with endogenous formative variables are modeled at the formative latent variable level rather than the formative indicator level, theory construction can verge on the superficial, and empirical findings can be ambiguous in substantive meaning.

Efficiency measurement in fuzzy additive data envelopment analysis

Performance evaluation in conventional data envelopment analysis (DEA) requires crisp numerical values. However, the observed values of the input and output data in real-world problems are often imprecise or vague. These imprecise and vague data can be represented by linguistic terms characterised by fuzzy numbers in DEA to reflect the decision-makers' intuition and subjective judgements. This paper extends the conventional DEA models to a fuzzy framework by proposing a new fuzzy additive DEA model for evaluating the efficiency of a set of decision-making units (DMUs) with fuzzy inputs and outputs. The contribution of this paper is threefold: (1) we consider ambiguous, uncertain and imprecise input and output data in DEA, (2) we propose a new fuzzy additive DEA model derived from the a-level approach and (3) we demonstrate the practical aspects of our model with two numerical examples and show its comparability with five different fuzzy DEA methods in the literature. Copyright © 2011 Inderscience Enterprises Ltd.

A taxonomy and review of the fuzzy data envelopment analysis literature:two decades in the making

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. In this study, we provide a taxonomy and review of the fuzzy DEA methods. We present a classification scheme with four primary categories, namely, the tolerance approach, the a-level based approach, the fuzzy ranking approach and the possibility approach. We discuss each classification scheme and group the fuzzy DEA papers published in the literature over the past 20 years. To the best of our knowledge, this paper appears to be the only review and complete source of references on fuzzy DEA. © 2011 Elsevier B.V. All rights reserved.

An analysis of the role of soft systems methodology in the change process and the contribution of the facilitator within this process

This research aims to examine the effectiveness of Soft Systems Methodology (SSM) to enable systemic change within local goverment and local NHS environments and to examine the role of the facilitator within this process. Checkland's Mode 2 variant of Soft Systems Methodology was applied on an experimental basis in two environments, Herefordshire Health Authority and Sand well Health Authority. The Herefordshire application used SSM in the design of an Integrated Care Pathway for stroke patients. In Sandwell, SSM was deployed to assist in the design of an Infonnation Management and Technology (IM&T) Strategy for the boundary-spanning Sandwell Partnership. Both of these environments were experiencing significant organisational change as the experiments unfurled. The explicit objectives of the research were: To examine the evolution and development of SSM and to contribute to its further development. To apply the Soft Systems Methodology to change processes within the NHS. To evaluate the potential role of SSM in this wider process of change. To assess the role of the researcher as a facilitator within this process. To develop a critical framework through which the impact of SSM on change might be understood and assessed. In developing these objectives, it became apparent that there was a gap in knowledge relating to SSM. This gap concerns the evaluation of the role of the approach in the change process. The case studies highlighted issues in stakeholder selection and management; the communicative assumptions in SSM; the ambiguous role of the facilitator; and the impact of highly politicised problem environments on the effectiveness of the methodology in the process of change. An augmented variant on SSM that integrates an appropriate (social constructivist) evaluation method is outlined, together with a series of hypotheses about the operationalisation of this proposed method.

Living with uncertainty in the age of runtime models

Uncertainty can be defined as the difference between information that is represented in an executing system and the information that is both measurable and available about the system at a certain point in its life-time. A software system can be exposed to multiple sources of uncertainty produced by, for example, ambiguous requirements and unpredictable execution environments. A runtime model is a dynamic knowledge base that abstracts useful information about the system, its operational context and the extent to which the system meets its stakeholders' needs. A software system can successfully operate in multiple dynamic contexts by using runtime models that augment information available at design-time with information monitored at runtime. This chapter explores the role of runtime models as a means to cope with uncertainty. To this end, we introduce a well-suited terminology about models, runtime models and uncertainty and present a state-of-the-art summary on model-based techniques for addressing uncertainty both at development- and runtime. Using a case study about robot systems we discuss how current techniques and the MAPE-K loop can be used together to tackle uncertainty. Furthermore, we propose possible extensions of the MAPE-K loop architecture with runtime models to further handle uncertainty at runtime. The chapter concludes by identifying key challenges, and enabling technologies for using runtime models to address uncertainty, and also identifies closely related research communities that can foster ideas for resolving the challenges raised. © 2014 Springer International Publishing.

Performance measurement with fuzzy data envelopment analysis

The intensity of global competition and ever-increasing economic uncertainties has led organizations to search for more efficient and effective ways to manage their business operations. Data envelopment analysis (DEA) has been widely used as a conceptually simple yet powerful tool for evaluating organizational productivity and performance. Fuzzy DEA (FDEA) is a promising extension of the conventional DEA proposed for dealing with imprecise and ambiguous data in performance measurement problems. This book is the first volume in the literature to present the state-of-the-art developments and applications of FDEA. It is designed for students, educators, researchers, consultants and practicing managers in business, industry, and government with a basic understanding of the DEA and fuzzy logic concepts.

Religious compliance in Islamic financial institutions

The central goal of this research is to explore the approach of the Islamic banking industry in defining and implementing religious compliance at regulatory, institutional, and individual level within the Islamic Banking and Finance (IBF) industry. It also examines the discrepancies, ambiguities and paradoxes that are exhibited in the individual and institutional behaviour in relation to the infusion and enactment of religious exigencies into compliance processes in IBF. Through the combined lenses of institutional work and a sensemaking perspective, this research portrays the practice of infusion of Islamic law in Islamic banks as being ambiguous and drifting down to the institutional and actor levels. In instances of both well-codified and non-codified regulatory frameworks for Shariah compliance, institutional rules ambiguity, rules interpretation and enactment ambiguities were found to be prevalent. The individual IBF professionals performed retrospective and prospective actions to adjust the role and rules boundaries both in the case of a Muslim and a non-Muslim country. The sensitizing concept of religious compliance is the primary theoretical contribution of this research and provides a tool to understand the nature of what constitutes Shariah compliance and the dynamics of its implementation. It helps to explain the empirical consequences of the lack of a clear definition of Shariah compliance in the regulatory frameworks and standards available for the industry. It also addresses the calls to have a clear reference on what constitute Shariah compliance in IBF as proposed in previous studies (Hayat, Butter, & Kock, 2013; Maurer, 2003, 2012; Pitluck, 2012). The methodological and theoretical perspective of this research are unique in the use of multi-level analysis and approaches that blend micro and macro perspectives of the research field, to illuminate and provide a more complete picture of religious compliance infusion and enactment in IBF.

The state of the art in fuzzy data envelopment analysis

Data envelopment analysis (DEA) is a methodology for measuring the relative efficiencies of a set of decision making units (DMUs) that use multiple inputs to produce multiple outputs. Crisp input and output data are fundamentally indispensable in conventional DEA. However, the observed values of the input and output data in real-world problems are sometimes imprecise or vague. Many researchers have proposed various fuzzy methods for dealing with the imprecise and ambiguous data in DEA. This chapter provides a taxonomy and review of the fuzzy DEA (FDEA) methods. We present a classification scheme with six categories, namely, the tolerance approach, the α-level based approach, the fuzzy ranking approach, the possibility approach, the fuzzy arithmetic, and the fuzzy random/type-2 fuzzy set. We discuss each classification scheme and group the FDEA papers published in the literature over the past 30 years. © 2014 Springer-Verlag Berlin Heidelberg.

Introduction to the Maple Power Tool Intpakx

The paper has been presented at the 12th International Conference on Applications of Computer Algebra, Varna, Bulgaria, June, 2006

Determinants of civil society influence:the case of international development and humanitarian NGOs in the Czech Republic and Hungary

Accession to the EU has had ambiguous effects on civil society organizations (CSOs) in the East Central European countries. A general observation is that accession has not led to the systematic empowerment of CSOs in terms of growing influence on national policy making. This article investigates the determinants of successful CSO advocacy by looking at international development and humanitarian NGOs (NGDOs) in the Czech Republic and Hungary. Reforms in the past decade in the Czech Republic have created an international development policy largely in line with NGDO interests, while Hungary’s ministry of foreign affairs seems to have been unresponsive to reform demands from civil society. The article argues that there is clear evidence of NGDO influence in the Czech Republic on international development policy, which is because of the fact that Czech NGDOs have been able solve problems of collective actions, while the Hungarian NGDO sector remains fragmented. They also have relatively stronger capacities, can rely on greater public support and can thus present more legitimate demands towards their government.

Automatic Translation of MSC Diagrams into Petri Nets

Development-engineers use in their work languages intended for software or hardware systems design, and test engineers utilize languages effective in verification, analysis of the systems properties and testing. Automatic interfaces between languages of these kinds are necessary in order to avoid ambiguous understanding of specification of models of the systems and inconsistencies in the initial requirements for the systems development. Algorithm of automatic translation of MSC (Message Sequence Chart) diagrams compliant with MSC’2000 standard into Petri Nets is suggested in this paper. Each input MSC diagram is translated into Petri Net (PN), obtained PNs are sequentially composed in order to synthesize a whole system in one final combined PN. The principle of such composition is defined through the basic element of MSC language — conditions. While translating reference table is developed for maintenance of consistent coordination between the input system’s descriptions in MSC language and in PN format. This table is necessary to present the results of analysis and verification on PN in suitable for the development-engineer format of MSC diagrams. The proof of algorithm correctness is based on the use of process algebra ACP. The most significant feature of the given algorithm is the way of handling of conditions. The direction for future work is the development of integral, partially or completely automated technological process, which will allow designing system, testing and verifying its various properties in the one frame.

On an ODE Relevant for the General Theory of the Hyperbolic Cauchy Problem

2000 Mathematics Subject Classification: 34E20, 35L80, 35L15.

Carbon efficiency evaluation:an analytical framework using fuzzy DEA

Data Envelopment Analysis (DEA) is a powerful analytical technique for measuring the relative efficiency of alternatives based on their inputs and outputs. The alternatives can be in the form of countries who attempt to enhance their productivity and environmental efficiencies concurrently. However, when desirable outputs such as productivity increases, undesirable outputs increase as well (e.g. carbon emissions), thus making the performance evaluation questionable. In addition, traditional environmental efficiency has been typically measured by crisp input and output (desirable and undesirable). However, the input and output data, such as CO2 emissions, in real-world evaluation problems are often imprecise or ambiguous. This paper proposes a DEA-based framework where the input and output data are characterized by symmetrical and asymmetrical fuzzy numbers. The proposed method allows the environmental evaluation to be assessed at different levels of certainty. The validity of the proposed model has been tested and its usefulness is illustrated using two numerical examples. An application of energy efficiency among 23 European Union (EU) member countries is further presented to show the applicability and efficacy of the proposed approach under asymmetric fuzzy numbers.