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The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The purpose of the current study is to investigate occupational stereotypes among a professional sample of recruiters and other employees on the two fundamental dimensions of warmth and competence.

The authors conducted a survey to collect professionals´ (mostly recruiters´) ratings of preselected occupations. Participants were asked to rate warmth and competence attributes. Factor and cluster analysis were employed to investigate the two-dimensional structure of the warmth/competence space and how and whether occupations cluster as predicted by the stereotype content model (SCM).

Almost all occupations showed a clear two-factorial structure, corresponding to the warmth/competence dimensions. A five-cluster solution was deemed appropriate as depicting how occupations disperse on these dimensions. Implications for stereotyping research, the design of hiring discrimination experiments, and HRM are discussed.

In contrast to previous related research, in which participants select the included occupations themselves, the authors included prespecified common occupations, which should be important for representativeness. In addition, previous research has been conducted in the United States, while the authors conduct this study in a European context (Sweden). Finally, instead of studying students or participants with unspecified work experience, the authors focus on professionals (mostly recruiters).

This paper investigates the development of efficiency and the progress of banking integration in the European Union by checking for convergence among banks of European and Eurozone countries as well as contrasting the results with those of United States banks.

Initially, we employ the two-stage semi-parametric double bootstrap DEA method, which absorbs the effects of possible integration barriers in the measurement of efficiency. Afterwards, we apply a panel data model, in order to investigate the process of banking integration by testing for convergence and for convergent clusters in banking efficiency.

Our main findings show that the bank efficiency of the US is considerably higher than that of the Eurozone and the European Union. Although there is no evidence of convergence across the banking groups, our results indicate the presence of club convergence. We also conclude that the US banking system is closer to convergence than the Eurozone and the European Union banks. Nevertheless, this outcome is subject to change in the future due to the fact that Eurozone and European Union banks' speed of convergence is higher than that of US banks.

Our survey is unique in trying to check for convergence while controlling for country-specific and bank-specific factors that affect the efficiency of European and Eurozone banks. Moreover, recent literature does not compare the convergence of efficiency of Eurozone, European and US banking. Finally, in our paper special consideration was given to the comparison of commercial, cooperative and savings banks, as subsets of our banking groups.

There are two aims of this research: one is to prove the interactive effect of supply chain integration (SCI) on performance and the other is to ascertain gaps in performance among levels of SCI. The population of this research is international freight forwarders and the collected data is used in testing hypotheses through various analytical methods such as factor analysis, Cronbach’s alpha, cluster analysis, ANOVA, MANOVA, ANCOVA, post hoc analysis and regression analysis. First, the interaction between internal integration and external integration improves customer performance and financial performance. The forwarders improve internal processes following information acquired from customers and the information is shared with logistics service providers, followed by high performance. Second, gaps in performance among levels of SCI are verified. Managers of the forwarders make strategic decision making on the basis of their recognition of environment and, as a result, the forwarders enjoy different performance.

This research empirically analyzes gaps in performance among development stages of integration in supply chain management (SCM). The used variables are integration such as internal and external and performance such as cost and service. The population is international freight forwarders in the Republic of Korea and the sample frame is the membership list of the Korean International Freight Forwarders Association. The used methodology in this research is various: Cronbach’s alpha, factor analysis, cluster analysis, analysis of variance and post hoc analysis. It is important to ascertain the position in which they are included and the position is concerned with internal integration and external integration because the aim of this research is to ascertain where the forwarders are in development stages of integration. According to prior research, development stages of integration are regarded as the flow from internal to external. However, this research suggests that development stages of integration do not explain the flow of the stages but explain the strategic choice concerned with their current decision-making.

The purpose of this paper is to explore mechanisms of supply chain inclusion in Base of the Pyramid (BOP) settings. It distinguishes micro-, small- and medium-sized enterprises (MSME)-led local supply chains on the one hand and multinational enterprises (MNEs)-led global supply chains on the other hand. This paper aims to answer the following research question: Which mechanisms of supply chain inclusion are employed empirically by MSMEs and how can these mechanisms influence social impact creation in MNE-led global supply chains?

A large-scale empirical study of MSMEs operating in BOP markets is performed and a cluster analysis conducted to systematically categorize supply chain inclusion. The cluster analysis and current literature yield theory-based implications for MNE-led global supply chains.

The cluster analysis reveals three meaningful clusters of supply chain inclusion in BOP markets and highlights two main aspects. They include direct vs indirect mechanisms of inclusion and diversity in supplier relationships with local organizations aimed at either “sourcing” local capabilities needed for inclusion or “outsourcing” the inclusion. Based on these aspects, two scenarios are proposed and evaluated for local-global supply chain symbiosis.

This study aims to contribute to the existing literature with a more fine-grained understanding of the inclusion of BOP actors in local supply chains and by proposing alternative trajectories for global supply chain inclusion.

The findings outline several important decisions that managers need to make to include BOP actors in supply chain activities.

This paper contributes a novel, combined perspective of local supply chains (MSMEs) and global supply chains (MNEs).

The purpose of this study is to explore the link between aggregate production efficiency and the extent of linguistic clustering in Indonesia.

The author draws on the stochastic frontier model and applies it to the data on Indonesian provinces to compute the effects of various determinants on these provinces' aggregate production efficiency. The key determinant is the spatial index of linguistic clustering that the author believes has never been applied before in this context.

Linguistic clustering is an important determinant of aggregate production efficiency. Linguistic diversity is positively associated with productive efficiency if members of a specific linguistic group are not clustered beyond a certain level.

To the best of the author’s knowledge, this is the first study that links the spatial index of linguistic clustering (because of Massey and Danton) to production efficiency. In other words, the contribution of this study is to introduce a geographical dimension to the mainstream analysis of the association between ethnic diversity and economic performance.