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To overcome the shortcomings of traditional industry classification systems such as the Standard Industrial Classification Standard Industrial Classification, North American Industry Classification System North American Industry Classification System, and Global Industry Classification Standard Global Industry Classification Standard, the authors explore industry classifications using machine learning methods as an application of interpretable artificial intelligence (AI).

The authors propose a text-based industry classification combined with a machine learning technique by extracting distinguishable features from business descriptions in financial reports. The proposed method can reduce the dimensions of word vectors to avoid the curse of dimensionality when measuring the similarities of firms.

Using the proposed method, the sample firms form clusters of distinctive industries, thus overcoming the limitations of existing classifications. The method also clarifies industry boundaries based on lower-dimensional information. The graphical closeness between industries can reflect the industry-level relationship as well as the closeness between individual firms.

The authors’ work contributes to the industry classification literature by empirically investigating the effectiveness of machine learning methods. The text mining method resolves issues concerning the timeliness of traditional industry classifications by capturing new information in annual reports. In addition, the authors’ approach can solve the computing concerns of high dimensionality.

This paper aims to discuss how collaborative classification works in online music information retrieval systems and its impacts on the construction, fixation and orientation of the social uses of popular music on the internet.

Using a comparative method, the paper examines the logic behind music classification in Recommender Systems by studying the case of Last.fm, one of the most popular web sites of this type on the web. Data collected about users' ritual classifications are compared with the classification used by the music industry, represented by the AllMusic web site.

The paper identifies the differences between the criteria used for the collaborative classification of popular music, which is defined by users, and the traditional standards of commercial classification, used by the cultural industries, and discusses why commercial and non‐commercial classification methods vary.

Collaborative ritual classification reveals a shift in the demand for cultural information that may affect the way in which this demand is organized, as well as the classification criteria for works on the digital music market.

Collective creation of a music classification in recommender systems represents a new model of cultural mediation that might change the way of building new uses, tastes and patterns of musical consumption in online environments.

The paper highlights the way in which the classification process might influence the behavior of the users of music information retrieval systems, and vice versa.

The title for this paper was selected advisedly, for it will serve to correct a popular misconception about the part the Chemical Industries Association plays in the collection and dissemination of statistics about the chemical industry.

Spare parts management plays a relevant role for equipment-intensive companies. An important step of such process is the spare parts classification, enabling properly managing different items by taking into account their peculiarities. The purpose of this paper is to review the state of the art of classification of spare parts for manufacturing equipment by presenting an extensive literature analysis followed by an industrial assessment, with the final aim to identify eventual discrepancies.

Not only is the attention put on the literature about the subject, but also on an on-field analysis, that is presented comprehending an extensive survey and two in-depth exploratory case studies. The copper mining sector was chosen being representative for the case of capital intensive plants where the cost of maintenance has relevant weight on the total operating cost.

The paper highlights the status of the scientific literature on spare parts classification by showing the current situation in the real industrial world. The paper depicts the existing barriers that leave gaps between theory and real practice for the application of an effective multi-criteria spare parts classification.

The paper provides a review of the theory on spare parts classification methods and criteria, as well as empirical evidences especially for what concern current situation and barriers for an effective implementation in the industrial environment. The paper should be of interest to both academics and practitioners, since it provides original insights on the discrepancies between scientific and industrial world.

This study focuses on intra-industry determinants of acquisition performance. Seven years of printed research on acquisitions from 10 top-tier business journals is categorized on the basis of R&D intensity – that is, per industry classification: high-, medium-, and low-technology – and determinants of acquisition performance. Instead of broadly generalizing acquisition performance determinants across industries, this study focuses on how the practice of enhancing acquisition performance is different per industry classification and what acquiring firms need to take into account.

After three decades of reform and opening up, China’s economy has experienced huge changes. Against the background of economic globalization, foreign direct investment (FDI) plays an important role in China’s economy. China has become one of the world’s largest FDI inflow countries, which has had an important impact on its economic development. FDI has preferred the industrial sector, which also has serious environmental pollution. This study will consider vertical and horizontal FDI location choice theory and conduct theoretical analysis concerning the FDI location choice within the industrial sectors, as well as empirical analysis to test the distribution of FDI in pollution-intense industries. Furthermore, the “Catalog of Industries for Foreign Investment” is one of China’s important industrial policies to guide foreign investment. Since being implemented in 1995, it has made five adjustments. The analysis of the distribution of FDI in the polluting industries and the impact of the change process will provide advice instructive for the government to amend the catalog.

This paper aims to review existing restaurant classifications within the literature in the restaurant management field. The authors discuss intra-industry ramifications of the limited use of recognized typologies and the need to prescriptively guide the description of restaurant context in the literature to communicate the internal and external validity of findings.

Restaurant categories from accepted typologies are used as keywords to collect 345 empirical studies from ten relevant journals serving the global restaurant management discipline. Content analysis of titles, abstracts and methodology sections is used to examine three propositions regarding the standardization, rationalization and efficiency of restaurant classification in imparting restaurant context in published works.

Findings show inconsistent use of existing typologies and limited use of effective restaurant descriptors to inform users about the situational context in which data were gathered or hypotheses were tested. There is a general preference for categories commonly associated with those of the National Restaurant Association.

Researchers should standardize descriptions of restaurants in manuscript titles, abstracts and methods sections, thereby enhancing integration of international research, the ability to conduct macro-level industry studies, and communication of findings to practitioners for operational use.

Recommendations are offered to optimize the use of restaurant classification so that the content of empirical studies may be more effectively accessed, digested and compared, thereby enhancing the communication of advances in the restaurant management body of knowledge to practitioners and other researchers.

The purpose of this paper is to consider the supply of audit firm industry specialisation in the market for statutory audits of publicly traded companies in Australia. The purpose of this study is to seek to gain a better understanding of the dynamics within the market for industry specialist audit services.

A structured interview process is used to investigate certain issues with the suppliers of industry specialist audit services (in this case all the then Big 5).

This paper found that industry specialisation involves the Big 5 audit firms developing a specialised knowledge of what clients do within any given industry and the issues and audit risks they face. The Big 5 have industry “focus” groups that are responsible for providing “leading edge” practices to their clients. According to many of the auditor interview respondents, the large number of Australian Stock Exchange (ASX) classifications has meant that audit firms have sought a more manageable means of partitioning their practices into different industry focus groups. The ASX classifications were described by some of those interviewed as being irrelevant. This raises questions regarding prior auditor industry specialisation research that has relied on these classifications.

The study does suffer from two limitations. First, the research only questioned the Big 5 firms, despite evidence that non‐Big 5 firms can create specialisations. Second, the study's data is relatively dated being collected in the late 1990s, so there is a possibility the findings may now be out of date, particularly given as indicated before, specialisation premiums are not generalisable across time.

The paper demonstrates the criticality of the relationship between audit market participants in developing an underlying framework that can universally explain the interactions that occur in the market for specialised audits.

The purpose of this paper is to identify the present structure of the Korean disaster-safety industry and propose ways to promote it.

The background of the emergence of the disaster and safety industry in Korea is reviewed, and business networks of 91 companies belonging to the disaster and safety industry in Korea are identified and analysed through a network analysis.

Korean Government is struggling to nurture the disaster and safety industry as it has been on last few decades. This paper finds that the current industry has an ambiguous market structure, and the industry tends to depend highly on the demand of public institutions.

The concept of the disaster and safety industry is not well established in other countries except for Korea. If Korea successfully fosters its disaster and safety industry through its proper understanding, it would bring both disaster risk reduction and economic benefits.

This paper analyses the market structure of the disaster and safety industry, which is uniquely emerging in Korea and rarely designated as an industry in other countries.

The transition from the standard industrial classification (SIC) system to the North American industrial classification system (NAICS) will not be rapid, but its effects will be profound for business researchers and information professionals. Most government agencies are already in the midst of this six‐year transition and, although private information producers are not compelled to switch from SIC to NAICS, most are planning to do so. The far‐reaching impact of NAICS on business information will affect libraries of all types. This article describes the challenges and costs associated with this change and makes recommendations for materials and training.