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While the Internet promises to radically change businesses in all industries, European companies have not yet embraced electronic trading with the enthusiasm of their North American counterparts. Only a few pioneers have successfully established Web services that are fully integrated into the enterprise's business processes and hence create business value. One of these pioneers is transtec, a German medium‐sized manufacturer and direct distributor of computer systems, storage solutions and computer accessories. The transtec case is an example of a successful Web‐portfolio based electronic commerce application. It illustrates how essential it is to create transparency by integrating the entire system architecture with internal and external communication and business processes. Having started with a general corporate information system and a comprehensive electronic product catalogue, transtec's Web presence evolved to become one of the best performing online order‐systems in Germany.

Electronic commerce has been recognised as a source of fundamental change to the conduct of business. Exploitation by business of this innovative approach to payments will necessitate wide‐scale adoption of new processes and technologies and may require new thinking on how organizations adopt innovations. Primarily, these innovations will be interactive and inter‐organizational, i.e. a successful cash substitute will require the concurrent participation of many different organizations, as well as consumers. Current theoretical models of adoption may not cater for this type of innovation. This paper compares four diverse pilot implementations of smart‐card payment systems with Rogers' (1995) attributes of innovations, adoption processes and adoption decision approaches for organizations. In general, Rogers' models do not reflect the levels of complexity and diversity found in practice. Extensions of the models are proposed.

In their article, Cuellar, Truex, and Takeda (2019) criticize the process for evaluating scholarly output, counting articles in ranked venues' (CARV) (p. 188). In their view, CARV limits the open exchange of ideas and, thereby, democratic discourse, which leads to unwanted performative effects and, ultimately, inhibits the growth of the information systems (IS) field. They propose the scholarly capital model (SCM) as a preferable mechanism that evaluators should employ to assess scholarly capital instead of scholarly output. In this rejoinder, we argue that CARV does not claim to measure output quality; it neither limits quality in the IS field nor the IS field's growth, and mingling the effects of CARV with debates on quality or growth could be misleading. Replacing CARV would not change the game, only its rules. We posit that we all entered academia voluntarily knowing its rules and argue that colleagues facing P&T committees should recognize and focus on the specific (CARV-based or not) criteria of their institutions' committees. While we expect that a new method will replace CARV in the not so distant future, we are convinced that, until then, a CARV-based environment offers ample opportunity to advance quality and growth of the IS field.

Business, management and business ethics literature pay little attention to the topic of AI robots. The broad spectrum of potential ethical issues pertains to using driverless cars, AI robots in care homes, and in the military, such as Lethal Autonomous Weapon Systems. However, there is a scarcity of in-depth theoretical, methodological or empirical studies that address these ethical issues, for instance, the impact of morality and where accountability resides in AI robots' use. To address this dearth, this study offers a conceptual framework that interpretively develops the ethical implications of AI robot applications, drawing on descriptive and normative ethical theory. The new framework elaborates on how the locus of morality (human to AI agency) and moral intensity combine within context-specific AI robot applications, and how this might influence accountability thinking. Our theorization indicates that in situations of escalating AI agency and situational moral intensity, accountability is widely dispersed between actors and institutions. 'Accountability clusters' are outlined to illustrate interrelationships between the locus of morality, moral intensity and accountability and how these invoke different categorical responses: (i) illegal, (ii) immoral, (iii) permissible and (iv) supererogatory pertaining to using AI robots. These enable discussion of the ethical implications of using AI robots, and associated accountability challenges for a constellation of actors – from designer, individual/organizational users to the normative and regulative approaches of industrial/governmental bodies and inter-governmental regimes.