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Existing research on innovation has mainly focused on how to promote technological innovation in megaprojects and management innovation (MI) in megaprojects is still an unknown research field. The purposes of this study are to examine the effect of MI on megaproject performance and how the top management team (TMT) regulatory focus affects the use of MI in projects. At the same time, the moderating effects of project uncertainties are also tested.

On the basis of an explorative/exploitative ambidextrous analysis framework, this study divides MI into two dimensions: explorative and exploitative MI, and integrates the theoretical perspectives of the TMT regulatory focus and project uncertainties into a research model. Taking 314 responses from megaprojects’ TMTs in China as research data, this study empirically tests the above model.

Results show that exploratory MI has a U-shaped relationship with megaproject performance; whereas exploitative MI has an inverted U-shaped relationship with megaproject performance. The TMT promotion focus has a positive effect on exploratory and exploitative MI; and the TMT prevention focus has a negative effect on exploratory MI but has a positive effect on exploitative MI. Project uncertainties have a positive moderating effect on the positive relationship between TMT promotion focus and exploratory MI, whereas it has a negative moderating effect on the negative relationship between the TMT prevention focus and exploratory MI.

By empirically measuring the relationship between two types of MIs and megaproject performance, this study clarifies the differential mechanism of the effect of different MIs on megaproject performance. This study also examines the MI of megaprojects from the perspective of the TMT regulatory focus and expounds how changes in uncertainties affect the relationship between the TMT regulatory focus and MI.

The motivation to participate in crowdsourcing (CS) platforms is an emerging challenge. Although researchers and practitioners have focused on crowd motivation in the past, the results obtained through such practices have not been satisfactory. Researchers have left unexplored research areas related to CS pillars, such as the evolution of the crowd’s primary motivations, seekers applying effective policies and incentives, platform design challenges and addressing task complexity using the synchronicity of the crowd. Researchers are now more inclined to address these issues by focusing on sustaining the crowd’s motivation; however, sustaining the crowd’s motivation has many challenges.

To fill this gap, this study conducted a systematic literature review (SLR) to investigate and map the challenges and factors affecting sustained motivation during CS with the overcoming implications. Studies that satisfied the inclusion criteria were published between 2010 and 2021.

Important sustainable factors are extracted using the grounded theory that has sustained participation and the factors' cohesion leads to the identification of challenges that the pillars of CS face. Crowds being the most vital part of CS contests face the challenge of engagement. The results reported the factors that affect the crowd’s primary and post-intentions, perceived value of incentives and social and communal interaction. Seekers face the challenge of knowledge and understanding; the results identify the reason behind the crowd’s demotivation and the impact of theories and factors on the crowd's psychological needs which helped in sustaining participation. Similarly, the platforms face the challenge of being successful and demanding, the results identify the latest technologies, designs and features that seekers proclaim and need the platforms designer's attention. The identified task challenges are completion and achievement; the authors have identified the impact of trait of task and solving mechanisms that have sustained participation.

The study identifies, explores and summarizes the challenges on CS pillars researchers are facing now to sustain contributions by keeping participants motivated during online campaigns. Similarly, the study highlights the implication to overcome the challenges by identifying and prioritizing the areas concerning sustainability through the adoption of innovative methods or policies that can guarantee sustained participation.

Waiting time, as an important predictor of queue abandonment and patient satisfaction, is important for resource utilization and patient experience management. Medical institutions have given top priority to reforming the appointment system for many years; however, whether the increased information transparency brought about by the appointment scheduling mechanism could improve patient waiting time is not well understood. In this study, the authors examine the effects of information transparency in reducing patient waiting time from an uncertainty perspective.

Leveraging a quasi-natural experiment in a tertiary academic hospital, the authors analyze over one million observational patient visit records and design the propensity score matching plus the difference in difference (PSM-DID) model and hierarchical linear modeling (HLM) to address this issue.

The authors confirm that, on average, improved information transparency significantly reduces the waiting time for patients by approximately 6.43 min, a 4.90% reduction. The authors identify three types of uncertainties (resource, process and outcome uncertainty) in the patient visit process that affect patients' waiting time. Moreover, information transparency moderates the relationship between three sources of uncertainties and waiting time.

The authors’ work not only provides important theoretical explanations for the patient-level factors of in-clinic waiting time and the reasons for information technology (IT)-enabled appointment scheduling by time slot (ITASS) to shorten patient waiting time and improve patient experience but also provides potential solutions for further exploration of measures to reduce patient waiting time.

This study aims to extend understanding of individual innovation by examining how learning strategies and relational dynamics influence the generation and promotion of innovative ideas. By investigating the extent to which the relationship between learning strategies and innovation varies as a function of a social factor (i.e. leader–member exchange), this research strengthens the conceptual model of individual innovation by integrating cognitive, behavioral and environmental factors.

Data collected from 667 working adults met satisfactory standards of construct reliability, and confirmatory factor analyses were used to verify sufficient convergent and discriminant construct validity. A first-stage moderated-mediation model was used to measure the direct and indirect effects of the independent variable on the dependent variable, as well as the effect of the moderating variable.

Leader–member exchange positively moderated the relationship between behavioral learning strategies and idea generation, but not the relationship between cognitive learning strategies and idea generation. Furthermore, idea generation mediated the relationship between the interaction (i.e. behavioral learning strategies × leader–member exchange) and idea promotion. Idea generation also mediated the relationship between cognitive learning strategies and idea promotion.

This research extends the generalizability of social cognitive theory within individual innovation processes and provides a greater understanding of how relational dynamics strengthen employee innovation through behavioral learning strategies. Support for the hypothesized moderated-mediation model empirically validates how organizational leaders can leverage relational dynamics and learning strategies to elicit the conceptualization and championing of innovative ideas in the workplace.

In response to the COVID-19 pandemic, many employees had to switch to remote work. While some adjusted successfully to this transition, others have struggled. Leveraging information systems (IS) to adjust to major exogenous shocks is called digital resilience. The purpose of this paper is to understand what we can learn about employees' digital resilience from externally enforced transitions to remote work.

As digital resilience is challenging to measure, this study uses an embedded mixed methods approach. The authors conducted a qualitative analysis of 40 employees' statements on their remote work experience during the first six months of the pandemic and complemented these findings with scale-based digital resilience scores.

The authors find that employees' digital resilience largely depends on the amount of technical equipment and support they receive from their organizations as well as their ability and willingness to learn how to adequately use and communicate through information and communication technologies. Being self-disciplined and self-responsible positively affects digital resilience, while social isolation threatens it. Organizations can foster digital resilience building by encouraging digital networking, building a digital culture and netiquette, and treating digital resilience as a sociotechnical phenomenon.

This is one of the first empirical studies of digital resilience on a human level. It sheds light on the missing link between IS-enabled resilience and transitions to remote work. Specifically, it provides original insights into its development and manifestation in a remote work context during the COVID-19 pandemic. For researchers, it provides novel guidance on choosing appropriate measurement instruments to capture digital resilience.