Practitioner Research Insights: Applications of Science and Technology to Real-World Innovations
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ItemManaging AI Bias: Executive Perspectives( 2022-01-04)Artificial intelligence (AI) applications are taking the world by storm. Yet increasingly, these solutions are coming under fire as being “biased”. This presentation describes the actions taken by three successful digital leaders to overcome this issue and ensure that the resulting decision information is fair and explainable. Their advice is part of a much larger study we have conducted to understand the actions “digitally mature” organizations take to separate themselves from “digitally developing” companies. The goal of our studies is to help digitally developing organizations―the great majority― catch up.
ItemDigital Transformation Powered by Big Data Analytics: The Case of Retail Grocery Business( 2022-01-04)Companies are investing in big data analytics capabilities as they look for ways to understand and innovate their business models by leveraging digital transformation. We explore this phenomenon from the perspective of retail grocery business where evolving consumer attitudes and behaviors, rapid technological advances, new competitive pressures, laser thin margins, and the COVID-19 pandemic have accelerated the pace of digital transformation. We specifically analyze the role of big data analytics capabilities of the top five grocery companies in the United States in light of their digital transformation initiatives. We find that retailers are making major investments in big data analytics capabilities to power all aspects of their digital ecosystem—the online shopping experience for the digital consumer, digital store operations, pickup and delivery mechanisms—to enhance shopping experience, customer loyalty, revenue, and ultimately profit.
ItemDecision Analytics in Practice: Improving Data Analytics in Pulsed Power Environments Through Diagnostic and Subsystem Clustering( 2022-01-04)Modern day processes depend heavily on data-driven techniques that use large datasets clustered into relevant groups help them achieve higher efficiency, better utilization of the operation, and improved decision making. However, building these datasets and clustering by similar products is challenging in research environments that produce many novel and highly complex low-volume technologies. In this work, the author develops an algorithm that calculates the similarity between multiple low-volume products from a research environment using a real-world data set. The algorithm is applied to pulse power operations data, which routinely performs novel experiments for inertial confinement fusion, radiation effects, and nuclear stockpile stewardship. The author shows that the algorithm is successful in calculating similarity between experiments of varying complexity such that comparable shots can be used for further analysis. Furthermore, it has been able to identify experiments not traditionally seen as identical.
ItemClio: Digital Transformation of Legal Practice - At COVID-19 Speed( 2022-01-04)Professional services firms face evolving client needs and can better meet these needs through digital transformation. We offer the case of Clio, a leading provider of cloud-based legal technology for law firms to better serve their clients. In this role, Clio provides an example of how digital transformation happens – both before and after the dramatic transformation triggered by the COVID-19 shutdowns. With the onset of COVID-19, the company recognized that remote client access and services, previously embraced by early adopters, would now become essential for all law firms’ survival. The company’s response resulted in dramatic growth and the transition from a customer base of early adopters to customers spanning most of the innovation adoption curve. Clio’s success throughout this period is attributable to three core elements of the company’s strategy: (1) Deep, culturally-rooted commitment to customer success, (2) Research-based understanding of the needs of both law firms and their clients, and (3) Industry thought leadership and assistance. These elements generalize beyond Clio and the pandemic and will help guide any organization seeking to become not just a vendor but an essential partner to its customers.
ItemAnalyzing Commercial Collaboration Attractiveness in YouTube Based on Micro-Analytical Content Labeling and Audience Retention( 2022-01-04)For creators of online video content, it is essential to understand how the audience reacts to different details within the content and how those reactions affect their viewing behavior, such as rewatching or skipping a moment or closing the video altogether. Understanding detailed viewing in terms of audience retention statistics is crucial for commercial collaborative content, as online video hosting such as YouTube freely allows commercial collaboration of different kinds, unlike many TV channels, for example. This paper proposes a research agenda for micro labeling commercial collaborative content to understand how to make it increase – not ruin – audience retention. We employ sport entertainment media as a case example but derive implications for not only media channel owners but also to marketers, influencer personalities and platform developers.