Leading digital transformation (DT) is challenging due to the unforeseen hurdles that arise through the novelty of digital technologies and the broad scope of organisational change. Even those with a wealth of experience and skills may struggle to respond adequately to inherently novel situations. While skills and experience are necessary for leading DT, continuously acquiring technology and business knowledge is equally important for navigating unfamiliar situations that DT often presents. As such, knowledge represents the missing link that warrants equal attention in driving successful DT. We examined the different knowledge types that digital leaders require to effectively navigate DT. Drawing on the IT innovation and DT literatures, we developed the DT knowledge framework with six knowledge types. We analysed these knowledge types in 138 interview excerpts of chief technology officers (CTOs), chief information officers (CIOs) and chief digital officers (CDOs) leading DT taken from 128 industry articles. We find that technology know-what-that is, knowing what technologies are available and their capabilities-and business know-how-that is, knowing how to execute organisational change needed for DT, are the two most important knowledge types. We further unpacked the dimensions of each of these knowledge types and offered recommendations for practitioners through our novel knowledge perspective on DT leadership. We also discuss the implications of our knowledge perspective for advancing DT scholarship.

Transparency-the observability of activities, behaviors, and performance-is often treated as a panacea for modern management. Yet there is a conundrum in the literature, with some studies suggesting that transparency may benefit group creativity and others suggesting that privacy may do so. A similar conundrum exists regarding the effects of different social capital types-structural holes vs. network cohesion-on group creativity. Enterprise social media (ESM) provide a unique opportunity to solve these conundrums by allowing groups to be "transparent" (non-group members can observe and/or participate in group activities) or "private" (group members and activities are hidden from the community) and enabling groups to develop distinct social capital structures. Using data from 28,083 written interactions produced by 109 transparent and 106 private groups in an ESM of a multinational design firm, we found strong support for our contingency hypotheses that both transparent and private groups may produce high levels of creative dialogues, yet in different forms. Specifically, expansion-focused creative dialogues- those focused on combining or expanding existing concepts-emerge in transparent groups, but only when the group's social capital is characterized by structural holes. Conversely, we found that reframing-focused dialogues-those focused on challenging and rethinking-emerge in private groups but only when the group's social capital is characterized by network cohesion. Theoretically, these findings can help to solve the conundrums in the literature on group creativity and shed light on the role of ESM use in this context. Practically, our findings offer a critical reflection o contemporary initiatives for increasing transparency, whether through physical design or digital transformation.

Advice-giving systems such as decision support systems and recommender systems (RS) utilize algorithms to provide users with decision support by generating ‘advice’ ranging from tailored alerts for situational exception events to product recommendations based on preferences. Related extant research of user perceptions and behaviors has predominantly taken a system-level view, whereas limited attention has been given to the impact of message design on recommendation acceptance and system use intentions. Here, a comprehensive model was developed and tested to explore the presentation choices (i.e., recommendation message characteristics) that influenced users’ confidence in—and likely acceptance of—recommendations generated by the RS. Our findings indicate that the problem and solution-related information specificity of the recommendation increase both user intention and the actual acceptance of recommendations while decreasing the decision-making time; a shorter decision-making time was also observed when the recommendation was structured in a problem-to-solution sequence. Finally, information specificity was correlated with information sufficiency and transparency, confirming prior research with support for the links between user beliefs, user attitudes, and behavioral intentions. Implications for theory and practice are also discussed.

Simple decisions about how to use collaboration tools can set teams on a path toward either incremental or breakthrough innovations.

Artificial Intelligence (AI) technologies can act as persuaders when implemented in workplace tools and infrastructure. How users process and react to interacting with features of such AI technologies in the workplace remains ill-understood. Literature in human-AI interaction suggests that cues in the user interface can dictate how users process information communicated by an AI and how receptive they are to being persuaded to change or reinforce their behaviors. Literature from human-AI interaction and an existing systematic framework of the study and design of persuasive technology from human-computer interaction can be applied to examining how users interact with persuasive AI in workplace tools and infrastructure. This paper aims to illustrate the application of such a systematic framework for persuasive technology to the study of persuasive AI technologies in the workplace context. Adapted from the persuasive technology framework, an illustrative vignette of a widely used workplace AI-powered tool is offered to further demonstrate features and principles of systems that include a persuasive AI component.

In early 2020, reports emerged about the coronavirus disease of 2019 (COVID-19) pandemic having a negative effect on the productivity of female researchers who spent their time in lockdown taking care of their families but a positive effect on the productivity of male researchers who spent it writing more papers. We wondered if the pandemic had affected caregivers (mostly female) in the information systems (IS) discipline in the same way. If we found that it did, we hoped to be able to suggest what actions caregivers might take in response. As an approximate way to distinguish caregivers from non-caregivers in our analysis, we used gender. Our analysis yielded mixed results, but those results do suggest that the COVID-19 pandemic has had some negative impacts on IS researchers who are caregivers. We offer several recommendations to caregiving IS researchers for mitigating the effect that the pandemic has on their professional lives.

This paper reports the findings of a Systematic Literature Review of extant literature on Recommender Systems (RS) and message design. By identifying, analyzing and synthesizing relevant studies, we aim to generate a contemporary mapping of studies related to user-RS interaction, extend the body of knowledge regarding effective recommendation messages, inform practitioners about the effect of recommendation message design choices on the user's experience, and motivate researchers to conduct related future research on new RS message factors identified in the literature. To conduct this SLR, 132 papers were collected and analyzed; after assessing their relevance and quality, 41 papers were selected, classified, interpreted and synthesized under a strict methodology producing the results reported in this paper, and concluding with a concept matrix outlining opportunities for future research on how to optimize the design of RS in support of a managerial decision-making context.

This paper explores the adoption of a group-based Enterprise Social Media (ESM) tool (i.e., Microsoft Teams) in the context of a mid-sized undergraduate course in Information and Technology Management (ITM), thereby providing insights into the use and design of tools for group-based learning settings. The study used a mixed-methods approach—interviews, surveys, and server-side (i.e., objective) data—to investigate the effects of three core ESM affordances (i.e., editability, persistence, and visibility) on students’ perceptions of ESM functionality and efficiency, and in turn, on ESM-enabled perceived team productivity as well as the students’ level of system usage. Through leveraging a combination of qualitative and quantitative (both unobtrusive and self-reported) data, this paper aims to provide insights into the use of ESMs in group-based classrooms which is a theme of great importance given the need for high-quality online education experiences, especially during the current pandemic.

Spring 2020 is unlikely to fade into memory anytime soon, if ever. The dramatic disruptions to everyday life resulting from the various degrees of societal lockdowns experienced across the globe will have long-term repercussions for many individuals, occupations, organizations, and societies. One observation repeated in both the popular and academic presses is that the burden of the lockdown was not equitably distributed. Specifically, working women with school-aged children seemed to face even greater hurdles in managing their households and careers than did men (Alon et al., 2020; Collins et al., 2020; Motoko, 2020; Madbavkar et al., 2020). The delicate family-work balance that these working women had managed to build during what we might now nostalgically refer to “normal” times had been shattered. To extend the balance metaphor, the scale was not just broken, it was no longer measuring anything meaningful.

Social network theory has produced conflicting results regarding the link between different social network structures-bridging versus bonding-and idea generation. To address this conundrum, we conduct a naturally occurring quasi-experiment of 126 open and 108 closed groups within an Enterprise Social Media (ESM) system of a multinational enterprise. Our findings show that idea generation occurs when the type of social network structure-bridging or bonding-is matched to a group's openness or closedness, respectively. We further show that the reverse is counterproductive: when closed groups display bridging ties and open groups display bonding ties, idea generation is significantly undermined. Theoretically, these findings clarify the conditions and mechanisms by which both bridging and bonding can result in idea generation and provide a deeper understanding of the use of ESM for idea generation. Practically, our findings provide valuable and actionable insights regarding the use of ESM for idea generation in groups.

The current paper reports on the results of a pilot study to explore the impact of message design on users' likelihood to accept system-generated recommendations as well as their intention to use the recommendation system (RS). We aim to extend the RS literature, which has hitherto focused on system design elements, but has generally overlooked the importance of message design, a key element in facilitating effective attention and information processing, particularly in the context of managerial decision-making.

Teamwork is at the heart of most organizations today. Given increased pressures for organizations to be flexible, and adaptable, teams are organizing in novel ways, using novel technologies to be increasingly agile. One of these technologies that are increasingly used by distributed teams is Enterprise Social Media (ESM): web-based applications utilized by organizations for enabling communication and collaboration between distributed employees. ESM feature unique affordances that facilitate collaboration, including interactions that are generative: group conversations that entail the creation of innovative concepts and resolutions. These types of interactions are an important attraction for companies deciding to implement ESM. There is a unique opportunity offered for researchers in the field of HCI to study such generative interactions, as all contributions to an ESM platform are made visible, and therefore are available for analysis. Our goal in this preliminary study is to understand the nature of group generative interactions through their linguistic indicators. In this study, we utilize data from an ESM platform used by a multinational organization. Using a 1% sub sample of all logged group interactions, we apply machine-learning to classify text as generative or non-generative and extract the linguistic antecedents for the classified generative content. Our results show a promising method for investigating the linguistic indicators of generative content and provide a proof of concept for investigating group interactions in unobtrusive ways. Additionally, our results would also be able to provide an analytics tool for managers to measure the extent to which text-based tools, such as ESM, effectively nudge employees towards generative behaviors.

Over the last decade, the role of social media in enabling the digital enterprise has been rapidly growing. In order for digital enterprises to embrace the opportunities afforded by social media technologies, including the use of social media for both inward- and external-facing communications and collaborations, several issues need to be addressed. The panelists will discuss contemporary issues and potential strategies to help establish a roadmap for social media research in the context of digital enterprises and digital transformation.

Online reviews have become a critical component of consumers' Web-based search queries and help them minimize uncertainty and risk associated with purchase decisions. Not only do customers perceive online reviews to be more "real", but also online reviews enable opportunities for interactivity between consumers, which makes them a popular source of information when consumers make (online) purchase decisions. In this study, we examine the impact of online reviews on consumers' beliefs, brand attitudes, and purchase intention by theoretically extending the information adoption model (IAM) with constructs from consumer research. To do so, we used data from a scenario- based online experiment and manipulated three review characteristics (currency, accuracy, and credibility) using carefully selected TripAdvisor reviews. Using a partial-least squares approach (PLS) to structural equation model (SEM), we found strong empirical support for our hypotheses that review quality and reviewer credibility drive information usefulness and that information usefulness, in turn, drives consumers' attitudes toward and their intention to purchase from a brand. Using PLS multi-group analysis, we further explored the moderating role of review valence—positive versus negative—and found significant differences in the importance of the drivers of information usefulness and its consequents. We discuss our study's implications for theory and practice.

The proliferation of enterprise social media (ESM) has created opportunities for employees to self-organize around common goals or interests. However, little is known about the different user classes that exist in ESM and the factors that drive contributions to ESM communities. Using multilevel analyses of secondary data from the ESM of a global organization, we find that (1) although ESM communities reflect a core-periphery structure similar to that identified in other forms of online communities, nearly two-thirds of the users represent promoters-a distinct class of users who use the platform primarily to post promotional content without viewing existing content created by others; and (2) despite individual differences in user type, the actual contribution to an ESM community is the result of an intricate interaction between a user's disposition for participation and a set of group characteristics. Our findings suggest that recognizing the unique contribution patterns of different user groups is key to understanding participation in ESM communities.

Effective workgroups engage in team boundary spanning, that is, using communication ties as conduits to critical external resources. The proliferation of enterprise social media (ESM) and the associated increase in visibility of people, content, and interactions, has resulted in a widespread assumption that unlimited visibility improves boundary spanning. Consequently, the ESM literature has generally ignored the sentry functions of teams and failed to examine the possible strategic nature of visibility choices by ESM groups. Using log and content data from 655 ESM-based workgroups at a multinational enterprise, we contribute a deeper understanding of the distinct ways that ESM visibility-bounded or unbounded-is leveraged strategically to evoke diverse network structures, which in turn have implications for distinct boundary-spanning activities. Practically, these findings show that ESM present a unique opportunity for workgroups to simultaneously sustain multiple virtual spaces-with varying levels of visibility-through which they can manage their diverse boundary-spanning goals.

For work teams to be effective, maintaining communication ties with other individuals and teams elsewhere in the organization—an activity typically referred to as team boundary spanning—is necessary for obtaining resources critical to project success. Within the literature on boundary spanning, the positive relationship between a team’s boundary-spanning activities and their performance has been validated repeatedly, but primarily through the use of self-reports from managers and team members. Thus, neither objective data exists to support these claims nor a longitudinal understanding of how various boundary-spanning activities may play different roles at various stages of project work. Similarly, with the proliferating use of enterprise social media (ESM) technologies in organizations, the empirical link between the increased visibility of communication ties in ESM and more effective boundary spanning has been largely assumed, but has received only limited empirical validation. In this study, drawing on log and content data from 169 projects in an ESM of a large multi-national corporation, we aim to objectively assess the effect of boundary spanning on project success as well as provide a qualitative path model of the evolution of boundary-spanning activities throughout the lifecycle of a project through a comparison of successful versus unsuccessful projects. Implications for theory and practice are discussed.