Managing Urgent Complex AI Projects: The Case of AISys at CityPort

The COVID-19 pandemic introduced significant challenges to supply chains and some organizations turned to AI projects to meet these challenges. AI projects can entail many forms of complexity and extant research is only beginning to explore how to manage them successfully. Projects with pandemic-induced urgency likewise require careful management attention, especially when coupled with complexity. In this paper, we examine the case of AISys, an AI-based system designed and built for CityPort, a multimodal port in North America, during the early weeks of the COVID-19 pandemic. AISys aimed to identify cargo critical to addressing the pandemic. We propose a theoretical framework based on team-level theories of stress and coping to understand the role of project stressors urgency and complexity in the successful management of this AI project, and how a project team used coping resources and employed specific coping strategies to overcome these stressors. Preliminary results support our theoretical framework

Gamification and Affective Response: Explaining Longitudinal IT-Based Self-Tracking Use Patterns

IT-based self-tracking to monitor fitness, health, work, and education has become increasingly pervasive. Yet, it is challenging to maintain longitudinal engagement. Gamification is often considered as an effective technique to facilitate sustained use by promoting user satisfaction and engagement. However, existing studies exhibit mixed results regarding the influence of gamification techniques. Further, there is a lack of understanding of users’ affective responses, which is proposed to be one important mechanism explaining the effects of gamification. This study aims to explore users’ experiences with gamified IT-based self-tracking by drawing on Zhang’s (2013) affective response model. Collecting data through interviews and ecological assessment techniques, we will employ a grounded theory approach to enhance our understanding of users’ affective responses to gamified fitness trackers and their influence on longitudinal use patterns

IT-Based Self-Monitoring Interventions to Promote Physical Activity and Weight Loss: A Meta-Analysis of Change-from-Baseline Effects

IT-based self-monitoring (ITSM) has attracted increasing interest as a strategy for chronic disease self-management and day-to-day fitness promotion. Despite the increasing popularity of various self-monitoring technologies such as fitness trackers and biosensors, their effectiveness is less certain. The objective of the current review is to determine the effectiveness of ITSM interventions on two types of key chronic care outcomes: weight management and physical activity. A systematic review employing a meta-analysis identified 42 ITSM studies that report change-from-baseline effects on weight and physical activity-related outcomes. Overall, a small effect size is found for body weight, BMI, waist circumferences, and step-based physical activity. The effect estimates on time-based physical activity are moderate. However, the effects on physical activity show variability and potential publication bias. A post-hoc analysis of the effects of ITSM on self-efficacy exhibit a small yet significant effect size, which shows the potential mediating role of patients’ psychological outcomes on the ultimate behavioral outcomes. In summary, ITSM is a potentially useful approach to manage weight and physical activity. Further study is needed to determine the source of heterogeneity as well as the types of ITSM interventions that are effective for weight, physical activity, but also other chronic care outcomes

Analysis of massive online medical consultation service data to understand physicians’ economic return: observational data mining study

Background: Online health care consultation has become increasingly popular and is considered a potential solution to health care resource shortages and inefficient resource distribution. However, many online medical consultation platforms are struggling to attract and retain patients who are willing to pay, and health care providers on the platform have the additional challenge of standing out in a crowd of physicians who can provide comparable services. Objective: This study used machine learning (ML) approaches to mine massive service data to (1) identify the important features that are associated with patient payment, as opposed to free trial–only appointments; (2) explore the relative importance of these features; and (3) understand how these features interact, linearly or nonlinearly, in relation to payment. Methods: The dataset is from the largest China-based online medical consultation platform, which covers 1,582,564 consultation records between patient-physician pairs from 2009 to 2018. ML techniques (ie, hyperparameter tuning, model training, and validation) were applied with four classifiers—logistic regression, decision tree (DT), random forest, and gradient boost—to identify the most important features and their relative importance for predicting paid vs free-only appointments. Results: After applying the ML feature selection procedures, we identified 11 key features on the platform, which are potentially useful to predict payment. For the binary ML classification task (paid vs free services), the 11 features as a whole system achieved very good prediction performance across all four classifiers. DT analysis further identified five distinct subgroups of patients delineated by five top-ranked features: previous offline connection, total dialog, physician response rate, patient privacy concern, and social return. These subgroups interact with the physician differently, resulting in different payment outcomes. Conclusions: The results show that, compared with features related to physician reputation, service-related features, such as service delivery quality (eg, consultation dialog intensity and physician response rate), patient source (eg, online vs offline returning patients), and patient involvement (eg, provide social returns and reveal previous treatment), appear to contribute more to the patient’s payment decision. Promoting multiple timely responses in patient-provider interactions is essential to encourage payment

“We use Scrum, but …”: Agile modifications and project success

While the Agile-Scrum (scrum) framework has specific guidelines, these guidelines are often adapted by practitioners. This research aims to understand how scrum changes in practice and how these changes impact various aspects of project success. Through interviews with representatives from 11 organizations who use scrum for software development, we found variability in the application of the guidelines, namely, that only a small number of guidelines are systematically followed, and that some guidelines are rarely followed consistently. Examining these method deviations and mapping them to specific dimensions of project success, four patterns emerged. Further, we uncovered practices that are often followed but were not part of the original Scrum guidelines, including how organizations scale scrum projects. These insights into how scrum is used in practice can help industry professionals determine how to best adapt scrum. They also serve as a promising agenda for research on the application of the scrum framework in industry

Managing artificial intelligence projects: Key insights from an AI consulting firm

While organisations are increasingly interested in artificial intelligence (AI), many AI projects encounter significant issues or even fail. To gain a deeper understanding of the issues that arise during these projects and the practices that contribute to addressing them, we study the case of Consult, a North American AI consulting firm that helps organisations leverage the power of AI by providing custom solutions. The management of AI projects at Consult is a multi-method approach that draws on elements from traditional project management, agile practices, and AI workflow practices. While the combination of these elements enables Consult to be effective in delivering AI projects to their customers, our analysis reveals that managing AI projects in this way draw upon three core logics, that is, commonly shared norms, values, and prescribed behaviours which influence actors\u27 understanding of how work should be done. We identify that the simultaneous presence of these three logics—a traditional project management logic, an agile logic, and an AI workflow logic—gives rise to conflicts and issues in managing AI projects at Consult, and successfully managing these AI projects involves resolving conflicts that arise between them. From our case findings, we derive four strategies to help organisations better manage their AI projects

Using information technology (IT) to add value to the learning process: pre-conditions for success

An undergraduate management professor and her technology assistant use an Information Technology based project to explore how IT can be used to create value-added learning experiences. Undergraduate students from three international universities participated in the project. Structural constraints and the processes key in overcoming these constraints are discussed. Recommendations are made with the intention of helping similar projects in the future

Impact of Smartphone Multitasking on Walking Behavior: Is Cognitive Absorption the Key?

Smartphones have revolutionized multitasking across various aspects of life but can also pose risks, particularly to pedestrian safety. Research shows pedestrians\u27 smartphone use during road crossings contributes to accidents and fatalities. Studies reveal that slower walking speed and decreased awareness due to smartphone multitasking heightens collision risks. This study investigates the relation between smartphone multitasking behavior and walking behavior of pedestrians, exploring the mediating role of deep task engagement or cognitive absorption. The experiment utilized a smart garment to capture real time physiological data along with self-report measures to gauge the impacts of smartphone multitasking. Participants undertook tasks with different multitasking levels while walking in a gymnasium. Results suggest certain task types increase cognitive absorption, highlighting the need for pedestrian caution during specific multitasking activities. Furthermore, heightened cognitive absorption reduces walking cadence. This study enhances comprehension of cognitive absorption during smartphone multitasking, shedding light on its influence on walking behavior

Encouraging Sustainable Energy Use in the Office with Persuasive Mobile Information Systems

Faced with growing pressures to be more environmentally sustainable, many companies are increasingly exploring innovative ways to incorporate “green” practices into their business processes. We focus on employees and their potential contributions to organization-wide sustainability goals through their pro-environmental behaviours. This article reports on current progress with a multi-year study targeting the use of mobile media to encourage pro-environmental behaviours. To do so, we provide employees with feedback on their computer-based energy usage. We discuss our combined design science and experimental approach to developing and studying a mobile application with embedded persuasive characteristics. Our future interventions will use this persuasive media platform to examine the impact of social-psychological theories on encouraging more sustainable energy use by employees