Spatial co-localisation of firms and entrepreneurial dynamics

In this conceptual paper, I propose an interpretation of business dynamics in terms of the spatial co-localisation of firms—considered as an intelligent cognitive system—in a circumscribed area in order to form clusters of various types. I interpret clustering by adopting the methodology of multi-agent combinatory systems: that is, systems formed by collectivities of agents (firms) in which an internal feedback recombines the micro behaviours of the agents (localisation) in order to produce a macro effect (cluster) which, in turn, modifies the attractiveness of the area and conditions the subsequent localisations. I also present the idea that if a cluster has fitness advantages for new firms, then usually new entrepreneurs are formed within it and the cluster widens, due to the endogenous genesis of new firms.     

The measurement of human capital: a multivariate macro-approach

We examine the human capital status of 123 countries by employing factor analysis on various national human capital indicators for the period 2000–2008 to construct two new measures. The first measure is based on advanced human capital, while the second is based on basic human capital. Our measures differ substantially from indicators used in previous studies on human capital and also lead to different rankings of countries. As rankings are not that informative without further information, we analyzed the distance between each country and the sample mean. Differences between countries are much more pronounced for our measure on advanced human capital than for our measure on basic human capital. Using cluster analysis, we classified the countries in four homogenous groups.     

Sequential Malmquist Indices of Productivity Growth: An Application to OECD Industrial Activities

The paper applies both the standard DEA methodology with contemporaneous frontiers and DEA with sequential frontiers to study changes in productivity and efficiency in manufacturing for a sample of eleven OECD countries over a twenty-year period. It uses a decomposition of the industrial Malmquist productivity indices to locate the sources of productivity growth: 'technical progress' and 'catching up.' The alternative indices are interrelated in a unifying framework that provides an interpretation to their difference. We argue that for manufacturing industries, in which technological regress is unlikely to occur, DEA with sequential frontiers provides a more adequate measure for the contribution of technical changes than standard DEA.     

Indeterminacy problems and the interpretation of factor analysis results

Abstract  This paper reviews indeterminacy problems for the factor analysis model and their consequences for the interpretation of the results. Two types of indeterminacy are discerned: indeterminacy of the parameters in the model (the number of factors, the specific variances and the factorloadings) and the indeterminacy of the factors, given the parameters in the model. It is argued that parameter indeterminacy is partly to be overcome, provided that a strong underlying theory for the subject matter under research is present. Factor indeterminacy remains a major stumbling-block for the interpretation of results. The G uttman criterion is advocated as a measure of factor indeterminacy.     

Issues in the analysis of co-authorship networks

Scientific collaboration is a complex phenomenon that improves the sharing of competences and the production of new scientific knowledge. Social Network Analysis is often used to describe the scientific collaboration patterns defined by co-authorship relationships. Different phases of the analysis of collaboration are related to: data collection, network boundary setting, relational data matrix definition, data analysis and interpretation of results. The aim of this paper is to point out some issues that arise in these different phases, highlighting: (i) the use of local archives versus international bibliographic databases; (ii) the use of different approaches for setting boundaries in a whole-network; (iii) the definition of a co-authorship data matrix (binary and weighted ties) and (iv) the analysis and the interpretation of network measures for co-authorship data. We discuss the different choices that can be made in these phases within an illustrative example on real data which is referred to scientific collaboration among researchers affiliated to an academic institution. In particular, we compare global and actor-level network measures computed from binary and weighted co-authorship networks in different disciplines.     

Internationalization of cluster initiatives in Russia: empirical evidence

In the last few years, Russia has supported the establishment of cluster initiatives to strengthen economic development, open channels for knowledge transfer, raise the national technology base, and integrate domestic manufacturing more prominently into global value chains. This paper studies 25 pilot cluster initiatives which received financial support within the national programme. The analysis shows that privately funded initiatives tend to use the cluster format as an efficient way to organize economic activities. Publicly funded cluster initiatives, in contrast, are more likely to engage in R&D partnerships with institutes in technologically advanced regions, such as Western Europe or South-East Asia, and thereby act as transfer channels to strengthen the region’s technology base. Also, industries that build on analytical knowledge are more likely to engage in partnerships than industries that use local and tacit knowledge. Still, the cluster management organizations struggle greatly to appoint adequately skilled staff and to cope with limited financial resources, as these are the biggest barriers for cluster internationalization, while cultural differences and geographical distance were of much less importance.     

Strategic compensation in South Korea's publicly traded firms

This strategic compensation model based on contingency theory of organizations proposes that a fit between the organization's business environment and compensation system will affect the firm's performance (Rockmore, 1991; Rockmore and Scarpello, 1994). This proposition was tested with a set of Korean sample data of seventy-five publicly traded companies within thirty-four three-digit Standard Industrial Classification codes.

The cluster analysis applied to the 7-item task environment uncertainty components resulted in two group classifications that face relatively ‘more certain’ and ‘more uncertain’ environments. Principal component factor analysis of the 8-item compensation system components resulted in three compensation system factors and subsequent cluster analysis classified firm pay plans into two clusters, which we labelled ‘more traditional’ and ‘more innovative’. Discriminant analysis confirmed the resulting classifications of both task environment and compensation system types. With both ROA and EPS measures, significantly more ‘fits’ (firms in stable environment that use traditional compensation system or firms in uncertain environment that use innovative compensation system) showed financial gains compared with ‘nonfits’. This financial impact of the contingency was more salient for those firms that face uncertain environment. The same results were obtained when ANOVA was performed.     

On evolutionarily stable behavior in contests

It is argued in this paper that the solution concept of an evolutionary stable strategy (ESS) is an adequate analysis tool for contest theory. Moreover, it is shown that in a contest ESS always differs from Nash equilibrium, the hitherto dominant solution concept in contest theory. Finally, an interpretation of finite population ESS contest behavior in terms of Nash behavior is supplied.Received: 10 February 2002, Accepted: 8 July 2002, JEL Classification: C79, D72, D 74Wolfgang Leininger: I have benefited from the comments and suggestions of Burkhard Hehenkamp and two anonymous referees.     

Factor analysis of the Big Five Questionnaire using polychoric correlations in children

Although the Big Five Questionnaire for children (BFQ-C) (C. Barbaranelli et al., Manuale del BFQ-C. Big Five Questionnaire Children, O.S. Organizazioni, Firenze, 1998) is an ordinal scale, its dimensionality has often been studied using factor analysis with Pearson correlations. In contrast, the present study takes this ordinal metric into account and examines the dimensionality of the scale using factor analysis based on a matrix of polychoric correlations. The sample comprised 852 subjects (40.90% boys and 59.10% girls). As in previous studies the results obtained through exploratory factor analysis revealed a five-factor structure (extraversion, agreeableness, conscientiousness, emotional instability and openness). However, the results of the confirmatory factor analysis were consistent with both a four and five-factor structure, the former showing a slightly better fit and adequate theoretical interpretation. These data confirm the need for further research as to whether the factor ‘Openness’ should be maintained as an independent factor (five-factor model), or whether it would be best to omit it and distribute its items among the factors ‘Extraversion’ and ‘Conscientiousness’ (four-factor model).     

Some Informational Aspects of Conservatism

Abstract

When two value estimates are about equally likely, conservatism dictates reporting the less optimistic one (e.g. Lower of Cost or Market). We use an analytical model to investigate informational implications of this dictum, and identify types of environments where the conservative accounting treatment is more informative than a predetermined choice. The bias induced by the conservative choice is found to be adequately moderate, never excessive. It benefits users of the financial statements that take the reported figures at face value whenever upside errors are more costly (possibly only slightly more costly) than similar downside errors. Sophisticated users, who know how to give the reports the best possible interpretation, benefit from the lower variability, not from the bias. These latter benefits are least ambiguous when upside errors and downside errors are about equally costly.     

Factor vector autoregressive estimation: a new approach

In this paper a new approach to factor vector autoregressive estimation, based on Stock and Watson (Implications of dynamic factor models for VAR analysis, NBER Working Paper, no. 11467, 2005), is introduced. In addition to sharing all the relevant features of the Stock–Watson approach, in its static formulation, the proposed method has the advantage of allowing for a more clear-cut interpretation of the global factors, as well as for the identification of all idiosyncratic shocks. An application to large-scale macroeconometric modelling is also provided. The authors are grateful to an anonymous referee for constructive comments and to MIUR (PRIN project 2005) for financial support.     

Factors shaping the international knowledge connectivity of industrial clusters: a comparative study of two Latin American cases

Abstract

Recent research has emphasized that success of industrial clusters is not only driven by intra-cluster knowledge sharing (‘local buzz’) but also by externally sourced knowledge (‘global knowledge pipelines’). This article examines the factors that determine the channels through which clusters connect with global knowledge pipelines depending on the structure of the global value chain within which they are inserted, their knowledge base and their stage of evolution. Building on a comparative case study of the salmon farming cluster in Chile and the software cluster in Costa Rica, we adopt an evolutionary perspective based on historical analysis to better understand how the configuration of clusters’ international knowledge linkages shifts over time. Our findings suggest that (i) the more hierarchical the global value chain structure, the less room for knowledge co-creation between local and foreign actors; (ii) clusters relying on analytical knowledge bases opt for more formal and coordinated links with high involvement of public actors, whereas in clusters relying on synthetic knowledge bases, international knowledge interaction is based on less formal links mainly between business actors; and (iii) as clusters evolve the channels through which they connect with foreign knowledge increase in number and new ‘hybrid’ varieties develop.     

Asymptotically perfect and relative convergence of productivity

In this paper we examine the extent to which countries are converging in per capita productivity levels. We propose to use cluster analysis in order to allow for the endogenous selection of converging countries. We formally define convergence in a time series analytical context, derive the necessary and sufficient conditions for convergence, and introduce a cluster analytical procedure that distinguishes several convergence clubs by testing for these conditions using a multivariate test for stationarity. We find a large number of relatively small convergence clubs, which suggests that convergence might not be such a widespread phenomenon. Copyright © 2000 John Wiley & Sons, Ltd.     

Assessing the impact of JIT using economic theory

This paper combines ideas that are well founded in the production and inventory management literature, with analytical approaches that have been long established in the economic theory literature, to reveal and explore production-function characteristic differences between JIT producers and non-JIT producers among electronic firms in Ontario, Canada. The methodology employed is the estimation of the CES-TL total cost system. Our primary conclusion is that JIT firms are more cost-efficient and appear to be distinct from the non-JIT group. This conclusion is supported by: (1) the fact that, in most cases, the elasticities calculated from the two groups of firms are significantly different; (2) the fact that the cost elasticity with respect to output is lower for the JIT firms than for the non-JIT firms, indicating that the former are better able to capture economies of scale and density; (3) the difference between the elasticities of factor productivity, with respect to output changes, shows the JIT firms as being more labor- and materials-saving than the non-JIT firms.     

Factor‐Based Identification‐Robust Interference in IV Regressions

Robust methods for instrumental variable inference have received considerable attention recently. Their analysis has raised a variety of problematic issues such as size/power trade‐offs resulting from weak or many instruments. We show that information reduction methods provide a useful and practical solution to this and related problems. Formally, we propose factor‐based modifications to three popular weak‐instrument‐robust statistics, and illustrate their validity asymptotically and in finite samples. Results are derived using asymptotic settings that are commonly used in both the factor and weak‐instrument literature. For the Anderson–Rubin statistic, we also provide analytical finite‐sample results that do not require any underlying factor structure. An illustrative Monte Carlo study reveals the following. Factor‐based tests control size regardless of instruments and factor quality. All factor‐based tests are systematically more powerful than standard counterparts. With informative instruments and in contrast to standard tests: (i) power of factor‐based tests is not affected by k even when large; and (ii) weak factor structure does not cost power. An empirical study on a New Keynesian macroeconomic model suggests that our factor‐based methods can bridge a number of gaps between structural and statistical modeling. Copyright © 2015 John Wiley & Sons, Ltd.     

Uncomfortable truths – teamworking under lean in the UK

A recent contribution in this journal – Procter, S. and Radnor, Z. (2014) ‘Teamworking under Lean in UK public services: lean teams and team targets in Her Majesty’s Revenue and Customs (HMRC)’ International Journal of Human Resource Management, 25:21, 2978–2995 – provides an account of teamworking in the UK Civil Service, specifically Her Majesty’s Revenue and Customs (HMRC), focused on the relationship between recently implemented lean work organisation and teams and teamworking. Procter and Radnor claim in this work that it delivers a ‘more nuanced’ analysis of lean in this government department and, it follows, of the lean phenomenon more generally. Our riposte critiques their article on several grounds. It suffers from problems of logic and construction, conceptual confusion and definitional imprecision. Methodological difficulties and inconsistent evidence contribute additionally to analytical weakness. Included in our response are empirical findings on teamworking at HMRC that challenge Procter and Radnor’s evidential basis and further reveal the shortcomings of their interpretation.     

A model for predicting determinants factors for NEETs rates: Support for the decision-makers

The purpose of this paper is to analyze the determining factors of the high levels of NEETs both in EU member states and in partner countries, to support policy steering and increase socio-economic cohesion. The use of longitudinal data (2005–2020) from Eurostat and World Bank databases and selected and the testing of a number of 19 factors likely to influence the rate of NEETs show us that the effectiveness of public policy solutions focused on this category of population increases when complex factors and not singular elements are targeted. From a methodological point of view, we will use MARS models and fixed effects panel models. To account for countries’ heterogeneity, these models are applied to homogeneous groups of countries, identified through cluster analysis. Social cohesion and sustainability measures for policy steering have higher chances if the action of the responsible institutions targets both meso and macro levels, if it acts not only on a factor but also on the causes that favor its manifestation. Our analysis demonstrated that the measures aimed at increasing the chances of NEETs in order to facilitate their access to education, the labor market, and social inclusion must be coordinated with those of support for combating poverty and any type of exclusion, the support given to employers (subsidizing jobs, for example), the family and the community to which the young person belongs or local authorities. Also, the research results show us that there are more common elements between countries when we analyze the factors likely to increase the rate of NEETs than when we focus on their analysis by geographical criteria, based on EU membership status or EU partner status, etc.     

Constructing measures for school process variables: the potential of multilevel confirmatory factor analysis

This article investigates the potential of multilevel confirmatory factor analysis compared to using conventional confirmatory factor analysis, as regards the construction of measures for school process variables within educational effectiveness research. Since both techniques have not been systematically compared within educational research, we propose to contrast several aspects: factor structure, pattern of factor loadings, communalities of the indicators, variance extracted by the factors, internal consistency of the factors, and inter-factor correlations. To this end, teacher questionnaire data are used to construct measures for school process variables. Our results show no substantial differences when comparing both techniques at the teacher level. However, when contrasting the different levels within the more complex technique, we notice a fairly large discrepancy between the teacher-level results and the school-level results.     

Customer green orientation and process innovation alignment: A configuration approach in the global manufacturing industry

Research suggests that manufacturers increasingly innovate processes to meet customer's green requirements; however, little is known about the impact on performance and the contextual conditions, under which they are effective. Grounded on configuration approach, this study develops taxonomies of manufacturing firms based on the degree of customer's green orientation and process innovation. This study argues that performance differences between these clusters, highlight managerial implications for sustainable development. The empirical data used in this study were drawn from Global Manufacturing Research Group (GMRG) survey project (with data collected from 629 manufacturing firms from nine countries). Our results show that customer green innovation taxonomies influence differently on environmental measures, costs, and financial performance. The study proposes three clusters: Process active, Green minimalist, and Green proactive. The main differences between manufacturers are based on the level of investments in joint green improvement initiatives and customer direct investments in green activities. Firms that belong to the Process active cluster, who are first within the industry to deploy new processes and update the latest process development, gained significant improvement in financial measures such as market share and profits. Whereas Green minimalist cluster lagged behind, Green proactive manufacturers aligned in both capabilities to experience higher payoffs in sustainable performance measures and efficiency. The findings provide a step‐by‐step decision‐making process and offer guidance for supply chain managers who have to stretch their needs to align the innovation processes to enhance their sustainable performance.     

知识溢出、产业集群与企业选址

由于知识的外部性,知识溢出这个新的区位因子正逐渐构成企业空间竞争的新变量,成为企业选址的关键因素之一。企业是否选址产业集群,实质上是对集群内知识溢出所带来的正负效应的权衡。一方面,知识溢出具有典型的局域性特征,吸引企业选址同一区域,强化了集群现象;另一方面,作为知识溢出载体的产业集群,通过本地生产网络、合作创新、人才流动、非正式交流等机制促进了知识的流动,在为企业减少创新成本的同时,也增加了集群内企业知识损失的风险。因此,不同特征的企业有不同的选址行为:处于学习和模仿创新阶段的中小企业趋于选址集群内,但是对具有一定规模和较强研发技术能力的企业而言,为了防止信息的泄露,往往定位于集群之外。