Globalisation and connectedness: A network approach to international business

There have been recent calls for the field of International Business to retool its routines by becoming genuinely interdisciplinary. This paper takes such an approach by using recent advances in the fields of evolutionary economics and applying them to IB. Evolutionary economists are now viewing the economy as an actual network. Consequently, one the key analytical tools in this approach is network analysis. Some of the basic methods in network analysis are reviewed. The paper then looks at how using these tools might be of use in IB studies. In particular, it outlines fruitful research paths in the areas of globalisation and regionalisation, and the measurement of performance in multi-national firms and alliances. In each case, propositions are put forward which can be analytically tested with the use of network analysis. The paper concludes with a brief outline of a research agenda which utilises this approach in International Business studies.

A combined neural network and DEA for measuring efficiency of large scale datasets

Data Envelopment Analysis (DEA) is one of the most widely used methods in the measurement of the efficiency and productivity of Decision Making Units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper proposes a neural network back-propagation Data Envelopment Analysis to address this problem for the very large scale datasets now emerging in practice. Neural network requirements for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of large datasets. Finally, the back-propagation DEA algorithm is applied to five large datasets and compared with the results obtained by conventional DEA.

Outlier detection in scatterometer data:Neural network approaches

Satellite-borne scatterometers are used to measure backscattered micro-wave radiation from the ocean surface. This data may be used to infer surface wind vectors where no direct measurements exist. Inherent in this data are outliers owing to aberrations on the water surface and measurement errors within the equipment. We present two techniques for identifying outliers using neural networks; the outliers may then be removed to improve models derived from the data. Firstly the generative topographic mapping (GTM) is used to create a probability density model; data with low probability under the model may be classed as outliers. In the second part of the paper, a sensor model with input-dependent noise is used and outliers are identified based on their probability under this model. GTM was successfully modified to incorporate prior knowledge of the shape of the observation manifold; however, GTM could not learn the double skinned nature of the observation manifold. To learn this double skinned manifold necessitated the use of a sensor model which imposes strong constraints on the mapping. The results using GTM with a fixed noise level suggested the noise level may vary as a function of wind speed. This was confirmed by experiments using a sensor model with input-dependent noise, where the variation in noise is most sensitive to the wind speed input. Both models successfully identified gross outliers with the largest differences between models occurring at low wind speeds. © 2003 Elsevier Science Ltd. All rights reserved.

Measurement of implicit leadership theories and their effect on leadership processes and outcomes

The leadership categorisation theory suggests that followers rely on a hierarchical cognitive structure in perceiving leaders and the leadership process, which consists of three levels; superordinate, basic and subordinate. The predominant view is that followers rely on Implicit Leadership Theories (ILTs) at the basic level in making judgments about managers. The thesis examines whether this presumption is true by proposing and testing two competing conceptualisations; namely the congruence between the basic level ILTs (general leader) and actual manager perceptions, and subordinate level ILTs (job-specific leader) and actual manager. The conceptualisation at the job-specific level builds on context-related assertions of the ILT explanatory models: leadership categorisation, information processing and connectionist network theories. Further, the thesis addresses the effects of ILT congruence at the group level. The hypothesised model suggests that Leader-Member Exchange (LMX) will act as a mediator between ILT congruence and outcomes. Three studies examined the proposed model. The first was cross-sectional with 175 students reporting on work experience during a 1-year industrial placement. The second was longitudinal and had a sample of 343 students engaging in a business simulation in groups with formal leadership. The final study was a cross-sectional survey in several organisations with a sample of 178. A novel approach was taken to congruence analysis; the hypothesised models were tested using Latent Congruence Modelling (LCM), which accounts for measurement error and overcomes the majority of limitations of traditional approaches. The first two studies confirm the traditional theorised view that employees rely on basic-level ILTs in making judgments about their managers with important implications, and show that LMX mediates the relationship between ILT congruence and work-related outcomes (performance, job satisfaction, well-being, task satisfaction, intragroup conflict, group satisfaction, team realness, team-member exchange, group performance). The third study confirms this with conflict, well-being, self-rated performance and commitment as outcomes.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Green supply chain performance measurement using fuzzy ANP-based balanced scorecard:a collaborative decision-making approach

The purpose of this paper is to delineate a green supply chain (GSC) performance measurement framework using an intra-organisational collaborative decision-making (CDM) approach. A fuzzy analytic network process (ANP)-based green-balanced scorecard (GrBSc) has been used within the CDM approach to assist in arriving at a consistent, accurate and timely data flow across all cross-functional areas of a business. A green causal relationship is established and linked to the fuzzy ANP approach. The causal relationship involves organisational commitment, eco-design, GSC process, social performance and sustainable performance constructs. Sub-constructs and sub-sub-constructs are also identified and linked to the causal relationship to form a network. The fuzzy ANP approach suitably handles the vagueness of the linguistics information of the CDM approach. The CDM approach is implemented in a UK-based carpet-manufacturing firm. The performance measurement approach, in addition to the traditional financial performance and accounting measures, aids in firms decision-making with regard to the overall organisational goals. The implemented approach assists the firm in identifying further requirements of the collaborative data across the supply-cain and information about customers and markets. Overall, the CDM-based GrBSc approach assists managers in deciding if the suppliers performances meet the industry and environment standards with effective human resource. © 2013 Taylor & Francis.

Neural network DEA for measuring the efficiency of mutual funds

Efficiency in the mutual fund (MF), is one of the issues that has attracted many investors in countries with advanced financial market for many years. Due to the need for frequent study of MF's efficiency in short-term periods, investors need a method that not only has high accuracy, but also high speed. Data envelopment analysis (DEA) is proven to be one of the most widely used methods in the measurement of the efficiency and productivity of decision making units (DMUs). DEA for a large dataset with many inputs/outputs would require huge computer resources in terms of memory and CPU time. This paper uses neural network back-ropagation DEA in measurement of mutual funds efficiency and shows the requirements, in the proposed method, for computer memory and CPU time are far less than that needed by conventional DEA methods and can therefore be a useful tool in measuring the efficiency of a large set of MFs. Copyright © 2014 Inderscience Enterprises Ltd.

Quality Measurement of Business Web Application

With the development of the Internet culture applications are becoming simpler and simpler, users need less IT knowledge than earlier; from the ‘reader’ status they have reached that of the content creator and editor. In our days, the effects of the web are becoming stronger and stronger— computer-aided work is conventional almost everywhere. The spread of the Internet applications has several reasons: first of all, their accessibility is widespread; second, their use is not limited to only one computer or network on which they have been installed. Also, the quantity of accessible information now and earlier is not even comparable. Not counting the applications which need high broadband or high counting capacity (for example video editing), Internet applications are reaching the functionality of the thick clients associates. The most serious disadvantage of Internet applications – for security reasons — is that the resources of the client computer are not fully accessible or accessible only to a restricted extent. Still thick clients do have some advantages: better multimedia perdormance with more flexibility due to local resources and the possibility for offline working.

Estimation of uncertainty in three-dimensional coordinate measurement by comparison with calibrated points

This paper details a method of estimating the uncertainty of dimensional measurement for a three-dimensional coordinate measurement machine. An experimental procedure was developed to compare three-dimensional coordinate measurements with calibrated reference points. The reference standard used to calibrate these reference points was a fringe counting interferometer with a multilateration-like technique employed to establish three-dimensional coordinates. This is an extension of the established technique of comparing measured lengths with calibrated lengths. Specifically a distributed coordinate measurement device was tested which consisted of a network of Rotary-Laser Automatic Theodolites (R-LATs), this system is known commercially as indoor GPS (iGPS). The method was found to be practical and was used to estimate that the uncertainty of measurement for the basic iGPS system is approximately 1 mm at a 95% confidence level throughout a measurement volume of approximately 10 m × 10 m × 1.5 m. © 2010 IOP Publishing Ltd.

A comparison of two distributed large-volume measurement systems:the mobile spatial co-ordinate measuring system and the indoor global positioning system

Advances in the area of industrial metrology have generated new technologies that are capable of measuring components with complex geometry and large dimensions. However, no standard or best-practice guides are available for the majority of such systems. Therefore, these new systems require appropriate testing and verification in order for the users to understand their full potential prior to their deployment in a real manufacturing environment. This is a crucial stage, especially when more than one system can be used for a specific measurement task. In this paper, two relatively new large-volume measurement systems, the mobile spatial co-ordinate measuring system (MScMS) and the indoor global positioning system (iGPS), are reviewed. These two systems utilize different technologies: the MScMS is based on ultrasound and radiofrequency signal transmission and the iGPS uses laser technology. Both systems have components with small dimensions that are distributed around the measuring area to form a network of sensors allowing rapid dimensional measurements to be performed in relation to large-size objects, with typical dimensions of several decametres. The portability, reconfigurability, and ease of installation make these systems attractive for many industries that manufacture large-scale products. In this paper, the major technical aspects of the two systems are briefly described and compared. Initial results of the tests performed to establish the repeatability and reproducibility of these systems are also presented. © IMechE 2009.

Ionized cluster beam deposition: Modeling, cluster size measurement and applications

Clusters are aggregations of atoms or molecules, generally intermediate in size between individual atoms and aggregates that are large enough to be called bulk matter. Clusters can also be called nanoparticles, because their size is on the order of nanometers or tens of nanometers. A new field has begun to take shape called nanostructured materials which takes advantage of these atom clusters. The ultra-small size of building blocks leads to dramatically different properties and it is anticipated that such atomically engineered materials will be able to be tailored to perform as no previous material could.^ The idea of ionized cluster beam (ICB) thin film deposition technique was first proposed by Takagi in 1972. It was based upon using a supersonic jet source to produce, ionize and accelerate beams of atomic clusters onto substrates in a vacuum environment. Conditions for formation of cluster beams suitable for thin film deposition have only recently been established following twenty years of effort. Zinc clusters over 1,000 atoms in average size have been synthesized both in our lab and that of Gspann. More recently, other methods of synthesizing clusters and nanoparticles, using different types of cluster sources, have come under development.^ In this work, we studied different aspects of nanoparticle beams. The work includes refinement of a model of the cluster formation mechanism, development of a new real-time, in situ cluster size measurement method, and study of the use of ICB in the fabrication of semiconductor devices.^ The formation process of the vaporized-metal cluster beam was simulated and investigated using classical nucleation theory and one dimensional gas flow equations. Zinc cluster sizes predicted at the nozzle exit are in good quantitative agreement with experimental results in our laboratory.^ A novel in situ real-time mass, energy and velocity measurement apparatus has been designed, built and tested. This small size time-of-flight mass spectrometer is suitable to be used in our cluster deposition systems and does not suffer from problems related to other methods of cluster size measurement like: requirement for specialized ionizing lasers, inductive electrical or electromagnetic coupling, dependency on the assumption of homogeneous nucleation, limits on the size measurement and non real-time capability. Measured ion energies using the electrostatic energy analyzer are in good accordance with values obtained from computer simulation. The velocity (v) is measured by pulsing the cluster beam and measuring the time of delay between the pulse and analyzer output current. The mass of a particle is calculated from m = (2E/v$\sp2).$ The error in the measured value of background gas mass is on the order of 28% of the mass of one N$\sb2$ molecule which is negligible for the measurement of large size clusters. This resolution in cluster size measurement is very acceptable for our purposes.^ Selective area deposition onto conducting patterns overlying insulating substrates was demonstrated using intense, fully-ionized cluster beams. Parameters influencing the selectivity are ion energy, repelling voltage, the ratio of the conductor to insulator dimension, and substrate thickness. ^

Verification of the indoor gps system by comparison with points calibrated using a network of laser tracker measurements

This paper details a method of determining the uncertainty of dimensional measurement for a three dimensional coordinate measurement machine. An experimental procedure was developed to compare three dimensional coordinate measurements with calibrated reference points. The reference standard used to calibrate these reference points was a fringe counting interferometer with the multilateration technique employed to establish three dimensional coordinates. This is an extension of the established technique of comparing measured lengths with calibrated lengths. Specifically a distributed coordinate measurement device was tested which consisted of a network of Rotary-Laser Automatic Theodolites (R-LATs), this system is known commercially as indoor GPS (iGPS). The method was found to be practical and able to establish that the expanded uncertainty of the basic iGPS system was approximately 1 mm at a 95% confidence level. © Springer-Verlag Berlin Heidelberg 2010.

Seawater carbonate chemistry and biological processes during experiments with coral Oculina arbuscula, 2010

Anthropogenic elevation of atmospheric pCO2 is predicted to cause the pH of surface seawater to decline by 0.3-0.4 units by 2100 AD, causing a 50% reduction in seawater [CO3] and undersaturation with respect to aragonite in high-latitude surface waters. We investigated the impact of CO2-induced ocean acidification on the temperate scleractinian coral Oculina arbuscula by rearing colonies for 60 days in experimental seawaters bubbled with air-CO2 gas mixtures of 409, 606, 903, and 2,856 ppm pCO2, yielding average aragonite saturation states (Omega aragonite) of 2.6, 2.3, 1.6, and 0.8. Measurement of calcification (via buoyant weighing) and linear extension (relative to a 137Ba/138Ba spike) revealed that skeletal accretion was only minimally impaired by reductions in Omega aragonite from 2.6 to 1.6, although major reductions were observed at 0.8 (undersaturation). Notably, the corals continued accreting new skeletal material even in undersaturated conditions, although at reduced rates. Correlation between rates of linear extension and calcification suggests that reduced calcification under Omega aragonite = 0.8 resulted from reduced aragonite accretion, rather than from localized dissolution. Accretion of pure aragonite under each Omega aragonite discounts the possibility that these corals will begin producing calcite, a less soluble form of CaCO3, as the oceans acidify. The corals' nonlinear response to reduced Omega aragonite and their ability to accrete new skeletal material in undersaturated conditions suggest that they strongly control the biomineralization process. However, our data suggest that a threshold seawater [CO3] exists, below which calcification within this species (and possibly others) becomes impaired. Indeed, the strong negative response of O. arbuscula to Omega aragonite= 0.8 indicates that their response to future pCO2-induced ocean acidification could be both abrupt and severe once the critical Omega aragoniteis reached.

The difficulty of measuring culture and diversity. Comparison of three international models of cultural measurement: FCS-2009, ESSnet-2012 and CAB-2015

The growing interest in quantifying the cultural and creative industries, visualize the economic contribution of activities related to culture demands first of all the construction of internationally comparable analysis frameworks. Currently there are three major bodies which address this issue and whose comparative study is the focus of this article: the UNESCO Framework for Cultural Statistics (FCS-2009), the European Framework for Cultural Statistics (ESSnet-Culture 2012) and the methodological resource of the “Convenio Andrés Bello” group for working with the Satellite Accounts on Culture in Ibero-America (CAB-2015). Cultural sector measurements provide the information necessary for correct planning of cultural policies which in turn leads to sustaining industries and promoting cultural diversity. The text identifies the existing differences in the three models and three levels of analysis, the sectors, the cultural activities and the criteria that each one uses in order to determine the distribution of the activities by sector. The end result leaves the impossibility of comparing cultural statistics of countries that implement different frameworks.

Measuring the Diversity and the Integration of Film Production in Mercosur: A Social Network Analysis

Based on an original and comprehensive database of all feature fiction films produced in Mercosur between 2004 and 2012, the paper analyses whether the Mercosur film industry has evolved towards an integrated and culturally more diverse market. It provides a summary of policy opportunities in terms of integration and diversity, emphasizing the limiter role played by regional policies. It then shows that although the Mercosur film industry remains rather disintegrated, it tends to become more integrated and culturally more diverse. From a methodological point of view, the combination of Social Network Analysis and the Stirling Model opens up interesting research tracks to analyse creative industries in terms of their market integration and their cultural diversity.