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The information systems discipline is developing at a tremendous pace, producing right things but also wrong ones — even modernisms. In want of more structure it is on the look‐out for identity. Let us take stock of the situation in some important areas:

Information Management (IM) is a field subject to great interest. However, it is obvious that IM is not an idea which could function in the long run as a focus point in practice and theory. There is, in our view, a division: IM as a profession for ‘production managers’ in information‐intensive companies and IM as part of Human Resource Management, concerned with the question of how information workers can function more effectively within an organisation.

Achieving goals of better integrated and responsive government services requires moving away from stand alone applications toward more comprehensive, integrated architectures. As a result there is a mounting pressure to integrate disparate systems to support information exchange and cross‐agency business processes. There are substantial barriers that governments must overcome to achieve these goals and to profit from enterprise application integration (EAI).

In the research presented here we develop and test a methodology aimed at overcoming the barriers blocking adoption of EAI. This methodology is based on a discrete‐event simulation of public sector structure, business processes and applications in combination with an EAI perspective.

The testing suggests that our methodology helps to provide insight into the myriad of existing applications, and the implications of EAI. Moreover, it helps to identify novel options, gain stakeholder commitment, let them agree on the sharing of EAI costs, and finally it supports collaborative decision‐making between public agencies.

The approach is found to be useful for making the business case for EAI projects, and gaining stakeholder commitment prior to implementation.

The joint addressing of the barriers of public sector reform including the transformation of the public sector structure, gaining of stakeholders' commitment, understanding EAI technology and dependencies between cross‐agency business processes, and a fair division of costs and benefits over stakeholders.

In the twenty-first century, as the D3 technological revolutions of jobs, which include digitalisation, decarbonisation and decentralisation, is running in most businesses, we are faced with a new generation of fast processing, including decision-making of machines instead of humans. This matter opens a new gate of new and upgraded business infrastructure, especially for small and medium enterprises (SMEs), to replace artificial intelligence (AI) and neural networks instead of human employees. Incorporating the Internet of Things (IoT) into business processes is essential for SME growth. Big data analytics may use big data to communicate with their markets and consumers, enhance efficiency, cut costs, validate choices and spot trends by retrieving, analysing and managing data. So, in this regard, it seems simultaneous with the rise of intelligent networks that AI appears in human communities more tangible and efficient.

Summarizes some of the key findings of academic papers presented at the First World Congress on the Management of Electronic Commerce, which took place in January, 2000, in Hamilton, Ontario, Canada, sponsored by McMaster University. The conference was attended by 243 delegates from more than 25 countries. Outlines two meta‐management issues including: the importance of taking a strategic approach to Internet ventures as well as considering infrastructure design during implementation. Several of the papers presented fell into three broad functional categories including operations, human resources and marketing. Finally, a summary of internationalization and education implications is discussed.

Expert systems technology as an area of artificial intelligence is coming to the field of structural mechanics. A number of expert systems have been developed or are under development. This paper consists of two parts. A brief discussion of the basics of expert systems and their concepts is given in the first part. The second part reviews the prototype of expert systems developed as an aid for finite element analysis and design optimization. Twelve different expert systems are described. A partial list of books on expert systems in general is given in the Appendix.

Traditional definitions of decision support systems emphasise their support role in individual decision making and utilise notions of rational choice. By considering decisions as an organisational activity, the interpretation of decision support systems use in organisations can move beyond this technical rational understanding, to include potential political and legitimating roles for these systems. These three possible interpretations are discussed in relation to the implementation of a large decision support system in a local government context described by Dutton (1981). In its technical role, the system was used as part of a rational planning agenda. However, the system was clearly also used politically, to promote particular interests and as a lever in negotiations between various groups. Part of the appeal of the decision support system was the appearance of rationality and technical neutrality that it gave to the planning and decision making process, and the legitimation it provided with external constituents. The paper concludes that an unquestioning acceptance of the technical received view of decision support system use is limiting, and that a more reflective approach to their development, implementation and use is required.

E‐commerce enables new kinds of business models to coordinate a value chain. Coordination of the value chain can be accomplished using direct communication or with the help of intermediaries such as brokers, dealers and auctions. The role of electronic intermediaries is becoming increasingly more important. The introduction of new business models in a value chain is a cumbersome process, due to the complexity of the value chain, unclear implications, different goals and interests of the stakeholders and unclear business models. Therefore, there is a need for a business engineering methodology that supports the design and development of new business models by helping the identification of these new business models and by providing insight into the implications of these business models. A business engineering methodology is presented that supports the identification and evaluation of various alternative value chain configurations. The goal of this methodology is to give stakeholders insight into their current, and possible alternative, situations by means of visualization, to evaluate the added value of business models using simulation and to gain experience with the new business models using gaming.

Introduction The history of business computer systems development indicates a trend towards the increasing awareness of the potential for man‐machine synergy in some form. Until the early 1970s, the principal impact of computing had been upon the lower organisational levels and on the more structured tasks of the organisation, but from that time on there has been an increasing movement towards amalgamating computer power and management science in an attempt to aid the decision maker facing complex and unstructured decision tasks. More recently, such a blend has come to be termed a decision support system.