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The aim of this paper is to examine empirically the relevance of the theory of deferred action for knowledge management systems (KMS) design in practice.

The study adopts a case study approach to examine knowledge work and knowledge management in virtual teamwork in a large UK telecommunications company to understand the occurrence of emergent knowledge and how it is managed by virtual team leaders. The section in the company studied is described as a “knowledge intensive organization” dealing with the company's e‐commerce activities.

The analysis confirms the complex adaptive system hypothesis – a complex system adapts to its environment through self‐organization. The data reveal the behaviour of the virtual team to be self‐organizing and adaptive to its environment. It confirms the knowledge tacitness hypothesis and social embeddedness of knowledge hypothesis as important determinants of knowledge sharing. Specifically, the data reveal the main issues concerning knowledge sharing practices of virtual team workers and the crucial team leader's role in the effectiveness of the teams' capability to develop social links to externalise and share tacit knowledge to accomplish tasks.

In this paper, the authors contribute “emergent knowledge” as a third category of organizational knowledge in addition to the existing tacit and explicit knowledge that needs to be considered when designing KMS. It also derives socio‐technical systems design principles based on the theory of deferred action, and a tentative development process with metrics is then proposed for KMS design that caters for emergent, tacit, and explicit knowledge.

Existing models such as the SECI model do not acknowledge emergent knowledge or its conversion into explicit knowledge. The theory of deferred action is invoked to derive design principles, termed deferred systems design principles, to depict how explicit knowledge, tacit knowledge, and emergent knowledge can be represented to design knowledge management systems for “emergent organizations”.

The study contributes to the limited research and lack of consideration of emergent knowledge as an integral part of organizational knowledge, especially in an era of emergent organizations.

The purpose of this paper is to address the problem of designing artificial complex adaptive systems, like information systems and organisations, by developing a proof‐of‐concept conceptual proto‐agent model.

The paper develops an exploratory proto‐agent model and evaluates its suitability for implementation as agent‐based simulation.

The paper focuses on understanding the effect of emergence when designing artificial complex adaptive systems and produces a proto‐agent model that identified agents and their behavioural rules for modelling.

In deferred action, agents act in emergent organisation to achieve predetermined goals. Since emergence cannot be predicted, information systems and organisation design approaches that cater for emergent organisation are required.

The deferred action construct is a synthesis of planned approaches and contingency approaches to design information systems. It recognises the effect of emergence on information systems.

This paper aims to examine the contextual issues relating to the problem of developing web‐based information systems for emergent organisations.

The study employs an action research approach to understand and develop an analytical development tool for web developers. It postulates that existing methods are inadequate in coping with sudden and unexpected changing characteristics within the organisation. The theory of deferred action is used as the basis for the development of an emergent analytical development tool. Many tools for managing change in a continuously changing organisation are susceptible to inadequacy.

The insights proposed are believed to assist designers in developing functional and relevant approaches within dynamic organisational contexts.

The analytical development matrix assists web developers in emergent organisations to develop web‐based information systems.

This paper posits a critical analysis of digitalisation initiatives of emerging economies with a focus on India. It suggests granular policy measures towards realising the dream of a competitive, empowered and knowledge-based society. To this extent, the paper juxtaposes and compares policy measures undertaken by several governments to facilitate digitalisation in their country. The policy measures embarked upon have been critically analysed in terms of their relevance, challenges for their implementation and adoption at the back of the prevailing social and economic fabric of the country. At the same time, attempts have been made to benchmark it against the best practice standards weighed in by the industry studies. The paper has also laid down a robust agenda for future research that can be replicated for any country.

This is a viewpoint study based upon public data and documentary sources within India as well as publications of several countries and international agencies. Research projects of numerous multinational companies working in the area of digitalisation has been accessed and analysed as well in the study.

The findings of this study have policy implications for governments in several emerging economies who have embarked on the path of digitising their economy with the larger objectives of reaping its larger benefits but have to deal with the challenges of inadequate resources to create an effective ecosystem to facilitate such a transition.

The study highlights the implications of challenges of gaps of physical and socioeconomic infrastructure in driving digitalisation, highlighting granular policy measures for public managers and policy makers to address them.

From the theoretical perspectives of both multi-agent systems and smart business networks, empirical studies analyzing agent-based inter-organizational systems (ABIOS) in a real-life business setting are rare. The purpose of this paper is to investigate the impact of ABIOS on the performance of business networks.

This study presents a theoretical conceptual model portraying the influence of ABIOS on clients’ coordination structure and information architecture; and the impact of those structural alterations on business network performance in terms of the coordination, agility, and informational performances. To validate the model, a cross-case analysis was conducted in three logistics cases, namely, warehousing, freight forwarding, and intermodal transportation.

The application of ABIOS requires adjustments to the information architecture or the coordination structure, or both. Subsequently, those structural adjustments will stimulate improvements in the coordination, agility, and informational performances.

The assessment of the clients’ performance improvement is done at the company level not at an aggregate network level. Moreover, the study only covers cases from the logistics sector.

This study explains the structural consequences of ABIOS applications. The adoption of an inter-organizational system is a strategic decision that requires support from multi-stakeholders. While the applications of ABIOS can offer performance improvement opportunities, adjustments must be made to the existing coordination structure or the information architecture, or both.

This study contributes to the smart business network literature and the ABIOS literature by presenting a validated conceptual model explaining the interplay among ABIOS, the coordination structure, informational structure, and business network performance, namely, the coordination, agility, and informational performances.

The purpose of this paper is to provide useful insights underlying the popularity of search engine technologies within a social media-intensive environment.

The degree of social interaction for social media platforms that integrate search engine technologies as part of the homepage and related experience is very mixed on part of its users. Through Barnard’ theory of authority acceptance, social media and its popularity may be examined by the ability of its users to create effective messages that can be broadcasted to many, yet controlled by individual. The hypotheses tested the interaction of social media and search engine with gender and technological ease-of-use factors.

The statistical evidence suggested that significant technological and ease-of-use aspects of search engines are not meaningful, based on gender alone. Males may slightly be prone to take advantage of such technologies, but their search and use patterns are not much varied from their female counterparts. Social media, generally more fully captured authority in individual search patterns, and a number of interactions among gender status, search engine characteristics, and social media were found to be significant and profound. The testing of these hypotheses directly reflect the complexities of unique needs among users of search engines within a social media environment.

Search engine technologies with a social media context has allowed for the development of a modern, user-driven internet experience that has been powered by users’ imagination and is designed to at least partially satisfy users’ need for self-directed engagement. Organizations are well advised to provide a mindful, less controlled, and more interactive presence of potential users, especially through an increasingly mobile presence.

Individuals as well as organizations are rapidly discovering that it is becoming easier to share and distribute their content, especially for more creative and innovative content, among all of its users. As businesses continue to focus on the quality of one’s own content, individuals are increasingly taking advantage of some tools to exert more control over their experiences and what they are willing to share, resulting in more user-based partnerships will formulate. As the transition of traditional forms of marketing to newer forms of integrated marketing, the future for search engines as marketing tools by social media users appears to be very promising in adding contextual content within users’ homepage.

Although very significant and applicable, there have been no formal justifications for the use of Monte‐Carlo models and Markov chains in evaluating hospital admission decisions or concrete data supporting their use. For these reasons, this research was designed to provide a deeper understanding of these models. The purpose of this paper is to examine the usefulness of a computerized Monte‐Carlo simulation of admission decisions under the constraints of emergency departments.

The authors construct a simple decision tree using the expected utility method to represent the complex admission decision process terms of quality adjusted life years (QALY) then show the advantages of using a Monte‐Carlo simulation in evaluating admission decisions in a cohort simulation, using a decision tree and a Markov chain.

After showing that the Monte‐Carlo simulation outperforms an expected utility method without a simulation, the authors develop a decision tree with such a model. real cohort simulation data are used to demonstrate that the integration of a Monte‐Carlo simulation shows which patients should be admitted.

This paper may encourage researchers to use Monte‐Carlo simulation in evaluating admission decision implications. The authors also propose applying the model when using a computer simulation that deals with various CVD symptoms in clinical cohorts.

Aside from demonstrating the value of a Monte‐Carlo simulation as a powerful analysis tool, the paper's findings may prompt researchers to conduct a decision analysis with a Monte‐Carlo simulation in the healthcare environment.

Using a meta-regression analysis, we quantitatively review the empirical literature on the relation between effective tax rate (ETR) and firm size. Accounting literature offers two competing theories on this relation: The political cost theory, suggesting a positive size-ETR relation, and the political power theory, suggesting a negative size-ETR relation. Using a unique data set of 56 studies that do not show a clear tendency towards either of the two theories, we contribute to the discussion on the size-ETR relation in three ways: First, applying meta-regression analysis on a US meta-data set, we provide evidence supporting the political cost theory. Second, our analysis reveals factors that are possible sources of variation and bias in previous empirical studies; these findings can improve future empirical and analytical models. Third, we extend our analysis to a cross-country meta-data set; this extension enables us to investigate explanations for the two competing theories in more detail. We find that Hofstede’s cultural dimensions theory, a transparency index and a corruption index explain variation in the size-ETR relation. Independent of the two theories, we also find that tax planning aspects potentially affect the size-ETR relation. To our knowledge, these explanations have not yet been investigated in our research context.