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Digitalization, innovation and changing customer requirements drive the continuous improvement of an organization's business processes. IT demand management (ITDM) as a methodology supports the holistic governance of IT and the corresponding business process change (BPC), by allocating resources to meet a company's requirements and strategic objectives. As ITDM decision-makers are not fully aware of how the as-is business processes operate and interact, making informed decisions that positively impact the to-be process is a key challenge.

In this paper, the authors address this challenge by developing a novel approach that integrates process mining and ITDM. To this end, the authors conduct an action research study where the researchers participated in the design, creation and evaluation of the approach. The proposed approach is illustrated using two sample demands of an insurance claims process. These demands are used to construct the artefact in multiple research circles and to validate the approach in practice. The authors applied learning and reflection methods for incrementally adjusting this study’s approach.

The study shows that the utilization of process mining activities during process changes on an operational level contributes to (1) increasing accuracy and efficiency of ITDM; (2) timely identification of potential risks and dependencies and (3) support of testing and acceptance of IT demands.

The implementation of this study’s approach improved ITDM practice. It appropriately addressed the information needs of decision-makers and unveiled the effects and consequences of process changes. Furthermore, providing a clearer picture of the process dependencies clarified the responsibilities and the interfaces at the intra- and inter-process level.

Digital transformation (DT) harnessing the potential of emerging technology creates opportunities and challenges for organizations worldwide. Senior executives view DT as a key initiative for future competitiveness, a view shared by academic researchers. What may challenge the organization is that the vision may be present while preparedness may be lacking. Organizational preparedness depends on managers and employees charged with implementing DT and their perceptions on preparedness are often not aligned with senior executives.

In this research, the authors explore the perceptions of managers and employees on DT preparedness in an organization by gathering data from 579 participants. This study uses an innovative approach to qualitative data analysis using interactive topic modeling.

Findings in this qualitative study provide valuable insights on the perceptions of these individuals and helps understand (a) how they view DT preparedness and (b) may behave in this context. In general DT is well understood, however managers are not keen to change work processes to take advantage of the new digital tools and there appears that generational gap is a barrier to successful DT.

Senior executives play a central role communicating the DT vision necessary to inspire managers and employees. As organizations continue to invest large sums of money to explore value creation for customers and stakeholders by leveraging digital technologies, the information systems (IS) discipline can take the lead by asking the question, what can be done to improve the understanding of DT implementation in an organization?

Design-thinking (DT) in education has attracted significant interest from practitioners and academics, as it proffers new-age thinking to transform learning processes. This paper synthesises extant literature and identifies the current intellectual frontiers.

First, a systematic-literature-review was undertaken employing a robust process of selecting papers (from 1986 to 2022) by reading titles, abstracts and keywords based on a required criterion, backward–forward chaining and strict quality evaluations. Next, a bibliometric analysis was undertaken using VOSviewer. Finally, text analysis using RStudio was done to trace the implications of past work and future directions.

At first, we identify and explain 12 clusters through bibliometric coupling that include “interdisciplinary-area”, “futuristic-learning”, “design-process” and “design-education”, amongst others. We explain each of these clusters later in the text. Science, Technology, Engineering, Arts and Mathematics (STEAM), management education, design and change, teacher training, entrepreneurship education and technology, digital learning, gifted education and course development) Secondly, through co-word-analysis, we identify and explain four additional clusters that include “business education and pedagogy”, “content and learning environment”, “participants and outcome” and finally, “thinking-processes”. Based on this finding, we believe that the future holds a very positive presence sentiment for design thinking and education (DT&E) in changing the 21st century learning.

For investigating many contemporary challenges related to DT&E, like virtual reality experiential learning, sustainability education, organisational learning and management training, etc. have been outlined.

Academics may come up with new or improved courses for the implementation of DT in educational settings and policymakers may inculcate design labs in the curricula to fortify academic excellence. Managers who would employ DT in their training, development and policy design, amongst others, could end up gaining a competitive advantage in the marketplace.

This study conducted a comprehensive review of the field, which to our limited knowledge, no prior studies have been done so far. Besides, the study also outlines interesting research questions for future research.

Research on market information use in product innovation suggests that firms utilize two key strategic decision-making processes: incremental and comprehensive. Drawing from organizational information processing theory, literature implies that these processes operate differently. However, this assumption remains untested. Moreover, the degree to which a comprehensive process affects the innovation strategy outcomes depends on market information time sensitivity (MITS) and analyzability. To-date, no study has tested these assertions, either. Finally, it is suggested that meaningful market strategy is a key driver of new product success and it is important to understand how decision-making processes influence it under differing time sensitivity and analyzability.

Based on survey data from 250 Chinese firms, authors use structural equation modeling to test the hypotheses.

The results generally support authors’ contentions. More specifically, marketing strategy outcomes are influenced by marketing strategy incrementality (MSI) and marketing strategy comprehensiveness (MSC) differently. Further, time sensitivity moderates the effect of both MSI and MSC on outcomes, except for the effect of MSI on decision quality. Finally, analyzability moderates the relationships between decision making processes and certain strategy outcomes such as between MSI and meaningfulness.

Drawing from information processing theory, authors argue that incremental and comprehensive marketing strategy decision making for new product operate differentially under the same conditions. Further, the effects of these decision processes on outcomes depend on time sensitivity and analyzability of market information. Finally, auhtors argue that meaningful market strategy is a driver of success. The authors find support for most of our hypotheses and provide directions for future research.

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.

This study aims to provide a systematic review of consumer privacy literature in the context of smartphones and undertake a comprehensive analysis of academic research on this evolving research area.

This review synthesises antecedents, consequences and mediators reported in consumer privacy literature and presents these factors in a conceptual framework to demonstrate the consumer privacy phenomenon.

Based on the synthesis of constructs reported in the existing literature, a conceptual framework is proposed highlighting antecedents, mediators and outcomes of experiential marketing efforts. Finally, this study deciphers overlooked areas of consumer privacy in the context of smartphone research and provides insightful directions to advance research in this domain in terms of theory development, context, characteristics and methodology.

This study significantly contributes to consumer behaviour literature, specifically consumer privacy literature.