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The prevailing conceptualization of information system (IS) capabilities, rooted in the resource-based view (RBV) framework, tends to focus on unique firm resources. In the digital age, as emphasized by dynamic capabilities (DC), resource reconfiguration is critical in maintaining strategic advantage. This paper focuses on big data analytics capabilities (BDAC) from a DC perspective to present a novel conceptualization of BDAC–DC. We examine its effects on product, business model and business process innovation, including the effects of enterprise architecture (EA) on the BDAC business model innovation relationship.

This research presents a novel DC-based BDAC conceptualization, operationalized as a hierarchical construct. A survey-based approach is used for data collection and data analysis is done using partial least squares structural equation modeling (PLS-SEM).

The novel conceptualization and the effects of BDAC DC on BDA sensing-seizing and reconfiguration capacities support BDAC’s functional and evolutionary roleplay. Empirical results confirm the positive effects of BDAC–DC on first-order value targets (innovation) and the moderating effects of EA.

The novel BDAC–DC conceptualization has several implications for BDAC, DC, EA and business value research. Practicing managers must adopt a multifaceted approach to BDAC development by considering non-technical and organizational factors, collaborate with their business counterparts to explore unique big data ideas, initiate proof-of-concept projects to secure support and allocate resources synchronously, considering a multidimensional view of the process, product and business model innovation.

Practicing managers must adopt a multifaceted approach to BDAC development by considering non-technical and organizational factors, collaborate with their business counterparts to explore unique big data ideas, initiate proof-of-concept projects to secure support and allocate resources synchronously, considering a multidimensional view of the process, product and business model innovation for synergistic outcomes.

To the best of our knowledge, this research is the first attempt toward DC-based BDAC conceptualization, empirical validation of first-order effects on various forms of innovation and the often-overlooked role of critical EA capability.

The purpose of this paper is to measure the business value of IT (BVIT) and illustrate the relationship between IT practices and BVIT.

The paper uses a case study approach to collect the subject firm data over a period of one year. The data are about various IT systems used in the firm and their associated capital and operational cost components. The derived data are then compared with industry benchmarks.

The IT practices employed by the firm enable it to achieve a BVIT which is higher than the industry norm, from both strategic and operational perspectives.

In this study, a year’s worth of data from a single firm is considered. The temporal frame of the research data limits the generalization of the results. To improve the generalizability, data from many years and across many firms may be used.

The paper provides insights to managers to identify the measures of BVIT. Further, managers can make necessary interventions based on IT practices to derive IT capabilities which, in turn, impact the firm’s performance.

The contribution of the work is manifold: illustration of the relationship between IT practices and BVIT; illustration of a methodology to evaluate firm-level BVIT; and an approach to collect IT expenses – both capital and operational level.

This study aims to investigate the decisions related to business aspects of cloud computing and discuss the research density, models/techniques used and identify opportunities for future work.

In this paper, 155 research articles shortlisted through a systematic review were analyzed and a classification framework was developed. Using this framework, the research density is discussed and a detailed review of four widely researched decision themes is provided.

It was found that current research on business aspects is spread across 23 decision themes. The distribution, however, is skewed with 50 per cent pertaining to just four themes, namely, pricing, markets, sourcing and adoption. Simulation appears to be the preferred modeling approach. Decision themes in consumer behavior, sustainability, auditing and culture offer opportunities for future research.

The classification framework organizes extant research on applied models and allows researchers to identify potential avenues for application, improvement and development of models to support business decisions. The review is limited to academic articles and does not include industry reports.

Practitioners can readily understand various perspectives relevant to a decision theme such as pricing or sourcing, seek and use associated models such as simulation, optimization and game theory to support their decision-making.

Most of the extant review paper deal with cloud computing technology. This study is the first systematic review on the models applied to business aspects of cloud computing. This study provides a classification framework and explicitly lists associated decision themes, models/techniques and opportunities.