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This paper aims to analyse the open data business models (ODBMs) as a source of knowledge and innovation to generate economic and social value. A framework for understanding ODBMs is presented. First, the knowledge structure of the ODBMs literature is identified. Second, a conceptual model for analysing the ODBMs is proposed. And finally, the future trends in ODBMs research are discussed.

In this paper, co-word analysis is performed to identify the topics related with ODBMs.

The ODBMs structure of knowledge is articulated in five themes: business model, smart city, business ecosystem, decision-making and innovation. Based on these results, a five-step model for analysing ODBMs is proposed. Finally, a discussion of the future trends of ODBMs focussed on a knowledge management perspective, open data ecosystems and business intelligence is presented.

The paper presents a picture of what, where, for whom and for what ODBMs have been studied and develops a new model to explain the value creation process of ODBMs. Taking a step further, applying the principles and models of knowledge management and business intelligence to ODBMs is also recommended in order to transfer and transform open data into valuable knowledge that can be used for developing apps. In that context, the importance of encouraging collaboration between different agents in the so-called open data ecosystem is presented.

Electronic product catalogues and brochures are gaining popularity, but there is little agreement on content, format, and searching methods. This limits their usability and integration with existing construction software tools. This paper examines a product‐modelling approach to delivering building product information and describes a proposed multi‐tier client‐server environment. ISO/STEP and IAI/IFC building product models are considered to facilitate representation, exchange, and sharing of product information. The proposed architecture incorporates scalability with middleware components that would provide single or few points of entry to integrated product information. This paper is part of a research project that builds on the results of related projects including Construct IT Strategy, PROCAT‐GEN, Active Catalog, COMBINE, and ARROW, towards implementing the required software components.

Looks at strategic logistics management and technology strategies for manufacturing and groups the contents under four main headings: logistical future; information challenge; 21st century manufacturing; 21st century service industries. Aims to look at the many challenges facing logistics practitioners and researchers.

This special “Anbar Abstracts” issue of Work Study is split into six sections covering abstracts under the following headings: Operational research and statistics; Project management, method study and work measurement; Business process re‐engineering; Design of work; Performance, productivity and motivation; Stock control and supply chain management.

This special “Anbar Abstracts” issue of Industrial Management & Data Systems is split into six sections covering abstracts under the following headings: Manufacturing strategy and production; Business process management ; Research and development; Industrial design; Quality management; Information systems.

Looks (in this special issue), at technology strategies in manufacturing and how it may pan out in the next decade, covering logistical future; information challenge; 21st century manufacturing; and 21st century service industries. Posits feelings about product life and the “throw away lifestyle” of the modern era. Discusses core business of companies and a possible scenario for them. Itemizes differing industries from the automotive to information systems, computes, the Internet and airlines. Lambasts companies’ approaches to “pooh‐pooh” modern thinking and urges modern thinkers to eschew the “Luddite” reaction to change.

Disruptive technologies are accelerating global growth. Artificial intelligence (AI) has the potential to transform the idea of delivering value to end users. On the other hand, the growth of Industry 5.0 has given rise to the concept of humanizing technology, and AI is a promising technology with the potential to contribute to business success. Nevertheless, the idea of value creation in the field of AI is novel, so it is necessary to define the meaning of value by understanding the context of AI applicability in different environments and industries. In this chapter, the author uses the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) procedure to conduct an SLR that provides interesting insights into the focus, industries, and methodologies and approaches used in existing research. Following the initial literature review on the state of the art of AI and value creation, the author also offers a reflection on the strategic implications of AI in the field of marketing, postulating a macrovalue creation framework that addresses the existence of implications on three different levels: emerging markets, Sustainable Development Goals, and adoption issues. Therefore, this chapter examines the value creation perspectives of AI to understand the current research focus and future directions.

Any manufacturing information system today must be able to both “reconfigure” and “reengineer” operations in a cost‐effective way. The objective of this paper is to propose an enterprise resource planning (ERP) system based on the re‐configurable characteristics of material objects (MO) and finance objects (FO). The implementation of this information system is based on the object technologsy concept, which composes enterprise applications in reusable software components made up of relevant manufacturing data. By analyzing the factors and the methods of integration of MO and FO, it can be shown that the proposed approach is more appropriate for the design and implementation of an ERP system, and that it is particularly suitable for small and medium‐sized enterprises (SMEs). The results demonstrate a flattened organizational structure, better communication, and enhanced workflow reconfiguration.

Discusses retailing in the light of new technology. The section is broken down into four topics: Overcoming the hurdles in global retailing; Radical Internet stirs up retailing; Banking on the Internet; Southwest Airlines’ home gate.

Getting the right information at the right time is one of the success factors of product development. However, there exist a great variety of data formats which make the bi‐directional data interchange among various development groups inefficient and costly. Due to the lack of adequate product and engineering data, design practitioners may find it difficult to transform the customer’s requirements to a value‐added product. This paper attempts to propose a hybrid database approach (HDA) to support effective data exchange among a case based reasoning knowledge repository and a corporate relational database model, presenting an integrated view of a company’s knowledge sources so as to enable better decision‐making by providing immediate access to key business information. To introduce machine learning capability to the whole system, case based reasoning (CBR) is embraced to capture past experience and knowledge for case matching in terms of product development issues. The significance of this research is the provision of a cross‐platform data exchange system, which is able to facilitate the creation of a conducive product development environment.