Theorising plays a foundational role in Information Systems (IS) research. While the field has made important advances through theory borrowing, via adaptation and instantiation, as well as through contextualisation of established frameworks and models, comparatively little attention has been devoted to the elaboration of existing theories through structured, logic-driven approaches. This commentary problematises that imbalance and advances the concept of deductive theory elaboration as a valuable, yet underutilised, form of theorising in behavioural IS research. We define deductive theory elaboration as a process that extends existing theories by introducing conceptual modifications to their constructs, relationships, or boundary conditions prior to empirical testing. We distinguish this approach from related forms of theorising and propose a four-step framework supported by a repertoire of elaboration patterns for both variance and process theories. We also offer practical reporting guidelines to promote transparency and rigour in elaboration-based contributions. Our aim is to encourage more systematic elaboration efforts to enhance the precision, generalisability, and cumulative potential of IS theories, an optimistic vision of how behavioural IS research can evolve to meet the conceptual challenges of a rapidly transforming digital landscape.

In high performance computing environments, we observe an ongoing increase in the available number of cores. For example, the current TOP500 list reveals that nine clusters have more than 1 million cores. This development calls for re-emphasizing performance (scalability) analysis and speedup laws as suggested in the literature (e.g., Amdahl's law and Gustafson's law), with a focus on asymptotic performance. Understanding speedup and efficiency issues of algorithmic parallelism is useful for several purposes, including the optimization of system operations, temporal predictions on the execution of a program, the analysis of asymptotic properties, and the determination of speedup bounds. However, the literature is fragmented and shows a large diversity and heterogeneity of speedup models and laws. These phenomena make it challenging to obtain an overview of the models and their relationships, to identify the determinants of performance in a given algorithmic and computational context, and, finally, to determine the applicability of performance models and laws to a particular parallel computing setting. In this work, I provide a generic speedup (and thus also efficiency) model for homogeneous computing environments. My approach generalizes many prominent models suggested in the literature and allows showing that they can be considered special cases of a unifying approach. The genericity of the unifying speedup model is achieved through parameterization. Considering combinations of parameter ranges, I identify six different asymptotic speedup cases and eight different asymptotic efficiency cases. Jointly applying these speedup and efficiency cases, I derive eleven scalability cases, from which I build a scalability typology. Researchers can draw upon my suggested typology to classify their speedup model and to determine the asymptotic behavior when the number of parallel processing units increases. Also, the description of two computational experiments demonstrates the practical application of the model and the typology. In addition, my results may be used and extended in future research to address various extensions of my setting.

We consider Max-min Share (MmS) fair allocations of indivisible chores (items with negative utilities). We show that allocation of chores and classical allocation of goods (items with positive utilities) have some fundamental connections but also differences which prevent a straightforward application of algorithms for goods in the chores setting and vice-versa. We prove that an MmS allocation does not need to exist for chores and computing an MmS allocation - if it exists - is strongly NP-hard. In view of these non-existence and complexity results, we present a polynomial-time 2-approximation algorithm for MmS fairness for chores. We then introduce a new fairness concept called optimal MmS that represents the best possible allocation in terms of MmS that is guaranteed to exist. We use connections to parallel machine scheduling to give (1) a polynomial-time approximation scheme for computing an optimal MmS allocation when the number of agents is fixed and (2) an effective and efficient heuristic with an ex-post worst-case analysis.

The business value of investments in Information Systems (IS) has been, and is predicted to remain, one of the major research topics for IS researchers. While the vast majority of research papers on IS business value find empirical evidence in favour of both the operational and strategic relevance of IS, the fundamental question of the causal relationship between IS investments and business value remains partly unexplained. Three research tasks are essential requisites on the path towards addressing this epistemological question: the synthesis of existing knowledge, the identification of a lack of knowledge and the proposition of paths for closing the knowledge gaps. This paper considers each of these tasks. Research findings include that correlations between IS investments and productivity vary widely among companies and that the mismeasurement of IS investment impact may be rooted in delayed effects. Key limitations of current research are based on the ambiguity and fuzziness of IS business value, the neglected disaggregation of IS investments, and the unexplained process of creating internal and competitive value. Addressing the limitations we suggest research paths, such as the identification of synergy opportunities of IS assets, and the explanation of relationships between IS innovation and change in IS capabilities.

Remote voting through the Internet provides convenience and access to the electorate. At the same time, the security concerns facing any distributed application are magnified when the task is so crucial to democratic society. In addition, some of the electoral process loses transparency when it is encapsulated in information technology. In this paper, we examine the public record of three recent elections that used Internet voting. Our specific goal is to identify any potential flaws that security experts would recognize, but that may have not been identified in the rush to implement technology. To do this, we present a multiple exploratory case study, looking at elections conducted between 2006 and 2007 in Estonia, The Netherlands, and Switzerland. These elections were selected as particularly interesting and accessible, and each presents its own technical and security challenges. The electoral environment, technical design, and process for each election are described, including reconstruction of details which are implied but not specified within the source material. We found that all three elections warrant significant concern about voter security, verifiability, and transparency. Usability, our fourth area of focus, seems to have been well-addressed in these elections. While our analysis is based on public documents and previously published reports, therefore lacking access to any confidential materials held by electoral officials, this comparative analysis provides interesting insight and consistent questions across all these cases. Effective review of Internet voting requires an aggressive stance towards identifying potential security and operational flaws, and we encourage the use of third-party reviews with critical technology skills during design, programming, and voting to reduce the changes of failure or fraud that would undermine public confidence.