The Delphi study produced 21 challenges that were evaluated according to relevance, impact, timeframe, significance, and importance. The analysis of our data displays a diversity of challenges, which can be roughly distinguished into those pertaining to the IS discipline and its development (meta challenges for developing the IS discipline), and those pertaining to the actual problems the discipline could solve (IS research challenges). Within the category of IS research challenges, we identify four common themes that are appropriate to further structure the research challenges. In what follows, we first discuss the meta challenges and then turn to the IS research challenges identified through our analysis.
Meta Challenges for Developing the IS Discipline
Six out of the top ten challenges that were identified relate to issues concerning the development of the IS discipline itself (cf. Table 6). As the most important one the respondents identified “proving relevance of IS research” (rank 1 in overall importance, rank 3 in that it is a grand challenge, and rank 4 in impact). Further challenges include “identifying IS as an academic discipline” (rank 4), “rethink the theoretical foundations of the IS discipline” (rank 5), “mastering the methodological breadth/richness” (rank 6), “adapting IS teaching to current IS research developments” (rank 9), “increasing theoretical/methodological sophistication” (rank 10), and “streamlining and providing equal quality standards for different strands of IS research” (rank 15). These challenges relate to themes recurrently discussed in the IS field, such as relevance, theoretical foundations, methods, and IS identity. Moreover, the study highlights challenges related to IS teaching. Overall, the results suggest a tendency to formulate generic challenges. It has been asserted that the IS discipline is still in its infancy with regard to its level of specialization, compared to other disciplines (Schwartz 2014). Table 7 provides an overview of those challenges pertaining to further developing the academic IS field.
It is interesting to see that “proving relevance of IS research” was identified as a highly important challenge (rank 1 in overall importance, rank 3 in being a grand challenge, and rank 4 in impact). However, as we investigate the community of inquirers, it is not surprising that the respondents are self-referential. Many scholars have pointed out that the IS discipline should focus on topics that are relevant to practitioners and should provide knowledge that can be implemented and is accessible (Benbasat and Zmud 2003; Rosemann and Vessey 2008). Our findings suggest that the old debate about rigor and relevance in IS research is still ongoing.
Two challenges relate to the theoretical foundation of IS, namely “rethink the theoretical foundations of the IS discipline”, and “increasing theoretical/methodological sophistication”. The study thus confirms prior work, which has discussed the lack of foundational IS theory and which calls to develop theory in IS (Watson 2001). Currently, IS tends to borrow theory from a number of reference disciplines. We interpret this as a call to further develop the theoretical core of our discipline (Urquhart and Fernández 2013; Seidel and Urquhart 2013).
The respondents identify “mastering the methodological breadths and richness of the IS discipline” as a grand challenge. IS is methodologically plural, and researchers draw on different paradigms such as interpretivism, positivism, and critical realism, and apply a multitude of different research methods (Benbasat and Weber 1996). While prior debates have suggested that IS should favor certain methods and certain research approaches (Lyytinen et al. 2007; Österle et al. 2010), our study suggests that the community of inquirers appreciates a diversity of methods and paradigms, and sees a challenge in better understanding how they relate to and complement each other. This is consistent with the idea of “disciplined methodological pluralism” (Landry and Banville 1992). We would agree with this view, and reference the dialectic of design-oriented research and behavioral research (Gregor and Hevner 2013).
“Identifying IS as an academic discipline” was ranked fourth in importance, and thus confirms the debate that has been coined as the IS identity crisis (Benbasat and Zmud 2003). While some may consider the debate an old chestnut (Seidel and Watson 2014), it still appears to be alive. It has been suggested that the IS discipline may model other disciplines, such as medicine, and follow a strategy of unification and specialization (Schwartz 2014). Identifying grand challenges may contribute to such a development, help fostering the identity of the discipline, and allocate resources to where they are most needed.
“Adapting IS teaching to current IS research developments” was identified as the ninth most important challenge. The respondents thus see a gap between research and teaching, and this gap may be explained by the comparably high dynamics of our field. While the alignment between teaching and research is at the core of university education, we often struggle to update textbooks and curricula under consideration of the latest developments in our discipline. Another problem may be seen in the lack of foundational theory – IS is still a young field. As a discipline, we should evaluate new institutional arrangements for IS teaching. Apart from textbooks, recent contributions can be provided to students in the form of journal, conference, or newspaper articles, seminars provide appropriate settings to discuss current topics, and IS can be used in order to improve collaboration in teaching. We must walk the talk, and our students need to be exposed to practical problems – after all, IS is an applied discipline that seeks to improve practice.
IS Research Challenges
The identified IS research challenges fall into the four categories of socio-technical challenges,
IS infrastructure challenges,
societal and ecological challenges, and social and affective challenges. Table 8 provides an overview of IS research challenges, that is, challenges related to problems that might be solved through IS research.
Five out of 21 challenges relate to challenges of integrating social and technical aspects of systems design, use, and impact: “integrating human and machine problem solving” (rank 2), “leveraging knowledge from data, with the related management of high data volumes” (rank 3), “supporting effective collaboration and learning through evolving media repertoires” (rank 8), “developing model-driven methods and tools for the full-scale automated generation of implementation-ready IS” (rank 11), and “aligning organizational objectives with IT by developing and establishing efficient communication means” (rank 12). These results reflect the foundation of IS in socio-technical systems (Bostrom et al. 2009; Bostrom and Heine 1977). Relevant contributions to the IS body of knowledge require the simultaneous consideration of the technical and the social subsystem (Gregor 2006). The identified challenges concern questions of how IS can contribute and support human activities such as problem solving, collaboration, communication, and learning as well as how technological and social subsystems can be successfully integrated.
It is interesting to see that fundamental topics such as the alignment of organizational objectives and IT (Reich and Benbasat 2000; Becker et al. 2015), which have been on the agenda for more than two decades (Henderson and Venkatraman 1993), are indeed still seen as a challenge. This supports the argument that IS is still lacking foundational theory and applicable knowledge in important fields.
IS Infrastructure Challenges
Four of the identified challenges relate to IS infrastructures: “providing ubiquitous access to IS services” (rank 7), “integrating information systems in one single virtual space” (rank 13), “embedding systems in real-life environments” (rank 16), and “developing universal methods for the translation between different coding systems” (rank 17). IS infrastructures afford action possibilities for groups of users (Markus and Silver 2008; Volkoff and Strong 2013). Consequently, IS must investigate (a) how such infrastructures are developed and (b) what action possibilities they proffer to what group of users. This has important implications for practice: First, organizations, when implementing IT infrastructures, must carefully consider which groups will use these infrastructures for which purposes. Second, existent infrastructures can be re-evaluated in the light of new, emergent action goals.
Societal and Ecological Challenges
Three of the identified challenges relate to important social challenges: “developing effective IS for emergency management” (rank 18), “raising collective consciousness” (rank 20), and “utilizing energy informatics” (rank 21). This is consistent with a general tendency in IS research towards increased sensitivity for societal problems (e.g., Elliot 2011; Melville 2010; vom Brocke et al. 2013), reflected in recent special issues on Green IS (e.g., MIS Quarterly, Journal of Strategic Information Systems) or conference themes such as “Building a Better World through Information Systems” at ICIS 2014 or “Reshaping Society Through Information Systems Design” at ICIS 2013. We contend that IS has much to offer to solve global challenges as the IS field is concerned with nothing less than the “central task of managing the information of mankind” (Schwartz 2014, p. 3).
Social and Affective Challenges
Two further challenges refer to the social and affective aspects of IS: “leveraging the ‘fun’ in information systems applications” (rank 14) and “making different IT generations work together” (rank 19). Prior IS research has not considered these issues in much depth. Incorporating affective aspects related to the design, use, and impact of information systems is an emergent field, and efficiency gains through concepts such as gamification (e.g., Andonova 2013) or IT consumerization (e.g., Köffer et al. 2014) have been considered only recently. For instance, the field of NeuroIS has been proposed to systematically investigate affective effects through the measurement and analysis of neuro-physiological data (Dimoka et al. 2012; Riedl et al. 2010). Studying the social and affective aspects thus calls for interdisciplinary research that affords the IS discipline to draw on theories from reference disciplines or, in the best case, collaborate with scholars from these disciplines. The example of NeuroIS is a commendable example, where well-established methods from the field of neuroscience, which is traditionally rooted in the natural science of biology, are now used to study IS-related phenomena, typically based on experimental research.