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Purpose – Social relations play an important role in a real community. Interaction patterns reveal relations among actors (such as persons, groups, firms), which can be merged to produce valuable information such as a network structure. This paper aims to present a new approach to extract inter‐firm networks from the web for further analysis. Design/methodology/approach – In this study extraction of relations between a pair of firms is obtained by using a search engine and text processing. Because names of firms co‐appear coincidentally on the web, an advanced algorithm is proposed, which is characterised by the addition of keywords (“relation keywords”) to a query. The relation keywords are obtained from the web using a Jaccard coefficient. Findings – As an application, a network of 60 firms in Japan is extracted including IT, communication, broadcasting, and electronics firms from the web and comprehensive evaluations of this approach are shown. The alliance and lawsuit relations are easily obtainable from the web using the algorithm. By adding relation keywords to named pairs of firms as a query, It is possible to collect target pages from the top of web pages more precisely than by only using the named pairs as a query. Practical implications – This study proposes a new approach for extracting inter‐firm networks from the web. The obtained network is useful in several ways. It is possible to find a cluster of firms and characterise a firm by its cluster. Business experts often make such inferences based on firm relations and firm groups. For that reason the firm network might enhance inferential abilities on the business domain. Also we might use obtained networks to recommend business partners based on structural advantages. The authors' intuition is that extracting a social network might provide information that is only recognisable from the network point of view. For example, the centrality of each firm is identified only after generating a social network. Originality/value – This study is a first attempt to extract inter‐firm networks from the web using a search engine. The approach is also applicable to other actors, such as famous persons, organisations or other multiple relational entities.

The purpose of this guest editorial is to introduce the papers in this special issue.

A brief introduction about the issue of web‐mining applications in e‐commerce and e‐services is provided, along with a summary of the main contributions of the papers that are included in the special issue.

The value of web‐mining techniques can be enhanced through applying them to real environments such as e‐commerce and e‐services. The research fields of web mining, e‐commerce and e‐services can also be expanded.

An overview of the special issue and related research is provided in this paper.

This study aims to investigate the relative weight of financial and non-financial performance measures used to evaluate production managers (such as shop floor managers or foremen) in a modern manufacturing setting.

Using survey data from Japanese factories, the paper examines the association between the choice of profit, cost, and non-financial performance measures with two characteristics of manufacturing systems: interdependence and multi-tasking.

The results indicate that interdependence has a significant and positive association with the importance of profit information, while multi-tasking is associated negatively with the importance of profit information, and positively with non-financial information for performance evaluation.

In recent years, a significant shift has been observed in Japanese production management with many companies now focusing on profit information instead of cost information. For example, the past studies show that large Japanese manufacturing companies are now using micro-profit centres and include profit information when evaluating factories. However, little empirical evidence is available on performance measurement at the shop floor foreman level, and even less is known about the importance of profit information in the evaluation of these lower level managers.