Sociomateriality (or sociomaterialism) allows us to approach the information technology (IT) capability research from an angle that has been rarely visited by information systems scholars. While relevant studies presume that humans and materials are distinct and largely independent, sociomateriality emphasizes agency that represents the relational, emergent, and shifting capacity realized through the association of actors (both humans and materials). The objective of this paper is to explore the value of conducting IT capability research through the theoretical lens of sociomaterialism. For this, we expand the imbrication metaphor introduced in an early study to explain the formation and advancement of a firm's IT capability from the sociomaterial perspective. Then, the key building blocks of IT capability of an organization are conceptualized based on the combination of existing studies and the expanded imbrication metaphor. Lastly, the effectiveness of formulating IT capability as a third-order construct that substantiates the entanglement concept of sociomaterialism is examined in comparison with that of traditional modeling approaches. We confirm the value of sociomaterialism in conceptualizing IT capability and subsequently in unraveling the true contribution of IT capability toward strengthening business performance. The findings also have practical implications in which IT capability is a function of IT management capability as well as IT personnel capability and IT infrastructure capability.
The use of formative measurement in the field of Information Systems has increased, arguably due to statistical tools (e.g., PLS) that can test such models. However, in the literature, there exist two contradictory views on the potential deficiency of formative measurement. While opponents who are critical of formative measurement argue that there are native weaknesses of the formative approach in model estimation, proponents who are in favor of using formative measurement counter that opponents' research methods in measurement model specification are flawed. The goal of this work is to empirically test these opposing views on whether the alleged estimation instability of formative measurement is due to measurement model misspecification or simply the shortcoming of formative measurement. To assess the integrity of arguments of both parties, we adopt a research design in which four different cases are tested in terms of interpretational confounding and external consistency. We find that regardless of whether there is a specification issue, formative measures can lead to misleading outcomes. Based on the results, we offer guidelines that researchers may adopt in planning and executing data analysis with structural equation modeling. Given that the use of formative measurement is at a critical juncture in the IS field, we believe that the guidelines in this research note are important to promote appropriate use of the approach rather than relegate it to a bandwagon effect.
A number of theoretical models have been presented in group support systems (GSS) literature, which suggest that various GSS structures such as anonymity and simultaneity, influence group interaction, which in turn influences group productivity and meeting outcomes. Examples of such theories include the adaptive structuration theory and the balance of forces model and they could generally be described as dynamic or procedural in nature. Much of the empirical research that tests such theories, however, is deterministic in that it often compares final outcomes between various levels of technological support without measuring and testing (1) the influence that the technological structures have on group interaction and group dynamics, and (2) the corresponding influence that group interaction has on meeting outcomes. This paper reports a study that examines the validity of such dynamic theories by examining the relationships between GSS structures, group dynamics, and meeting outcomes over time. Four process constructs (production blocking, free riding, sucker effect, and evaluation apprehension) and three meeting outcome constructs (group cohesion, affective reward, and self-reported learning) were initially selected for the study. Structural equation modeling was used to analyze longitudinal survey data gathered from an experiment conducted with naturally occurring groups. The model tested was found to be valid and GSS was found to be effective in reducing process losses. However, the findings also revealed that process losses vary in the degree to which they influence meeting outcomes and certain meeting outcomes, such as affective reward, were found to be heavily influenced by other meeting outcomes, such as group cohesion and self-reported learning. Theoretical implications of the study and methodology are discussed.