Technology and Innovation Commons^™

Ftc Titans #17576 2025 Engineering Portfolio, Aparna Sadhanagiri, '26, Noah David, '26, Neev Patel, '25, Michael Meng, '25, Andrew Sun, '27, Ian Wang, '27

Distinguished Student Work

"FTC Robotics is a program for students to engage with designing, building, and driving an 18x18x18' robot to compete in local, regional, and state competitions. The TITANS #17576 were founded in 2019 and continue to be high-performing competitors and active members of the local STEM community. We have used STEM education and robotics to inspire over 54K people across the globe in the 24/25 season, using avenues such as publishing resources, creating STEM programs for all ages, and connecting with professionals in the field. This past season, the team was awarded the 3rd Place Inspire Award for overall excellence at …

The Economic And Environmental Impact Of Shinkansen And High-Speed Rail Infrastructure: A Comparative Analysis Of Economic Growth And Carbon Emissions Reduction, Dillan R. Victory

SPARK Symposium Presentations

The development of Japan's high-speed rail system, the Shinkansen, has played a pivotal role in the country's post-war economic resurgence. Introduced in 1964 with the Tokaidō Shinkansen, this transformative infrastructure investment significantly reduced travel times, bolstered economic activity around station hubs, and facilitated regional development by enabling urban decentralization. This paper explores the long-term economic benefits of high-speed rail, including its impact on land value, business expansion, and carbon emissions. The case study of the Linear Chuo Shinkansen, Japan's latest maglev project, underscores both the economic promise and the political resistance to expansion, particularly in regions such as Shizuoka.

Using …

Uncovering Libraries Instagram Engagement, Kenneth Saito

Library Research Scholars Program Spring 2025

The Binghamton University Libraries utilizes its Instagram platform to engage its audience to share information regarding its resources and services. Current research suggests elements such as color grading, scenic backgrounds, and maintaining a proper online social media presence affect how Instagram users engage with content. However, additional elements such as audience type and how they engage with content may factor into the Libraries’ reach on their platform. This project seeks to identify how the Libraries Instagram platform can maximize engagement based on their audience needs and identified interaction behavior. A literature review determined that a qualitative survey is the best …

Transformative Impact Of Ai And Digital Technologies On The Fintech Industry: A Comprehensive Review, Soudeh Pazouki, Behdad Jamshidi, Armia Jalali, Arya Tafreshi

Finance Faculty Publications

This paper examines the impact of artificial intelligence (AI) and digital technologies on the financial technology (FinTech) industry and demonstrates how AI- enabled strategies are increasing the ability of businesses not only to grow, but also to better serve their customers through operational efficiencies. But as immersive as the technological advancements may be, they present challenges in connection with increasingly complicated licensing regulations and a constantly evolving technological landscape. We examine the way AI and algorithms are streamlining workflows, enhancing productivity and expanding access to financial resources for traditionally under – served populations. The paper also discusses the macroeconomic implications …

Fares On Fairness: Using A Total Error Framework To Examine The Role Of Measurement And Representation In Training Data On Model Fairness And Bias, Patrick Oliver Schenk, Christoph Kern, Trent D. Buskirk

Information Technology & Decision Sciences Faculty Publications

Data-driven decisions, often based on predictions from machine learning (ML) models are becoming ubiquitous. For these decisions to be just, the underlying ML models must be fair, i.e., work equally well for all parts of the population such as groups defined by gender or age. What are the logical next steps if, however, a trained model is accurate but not fair? How can we guide the whole data pipeline such that we avoid training unfair models based on inadequate data, recognizing possible sources of unfairness early on? How can the concepts of data-based sources of unfairness that exist in the …

Comparing Funders' Altruism Versus Self-Interest: Leveraging The Context Of Crisis, Dan Liu, Guangzhi Shang, Cynthia Fan Yang

Journal of International Technology and Information Management

While reward-based crowdfunding has widespread popularity, the motivations driving funders, balancing self-interest and altruism, have remained puzzling. Prior research has been constrained by examination methods and produced mixed findings regarding the weight of altruism versus self-interest among funders. Our study takes a fresh perspective, delving into funder behavior amid a major crisis—the tumultuous backdrop of the COVID-19 pandemic. Our findings reveal that funders not only display an increased willingness to contribute but also significantly amplify their contributions, particularly to projects in crisis-affected regions, irrespective of external incentives like rewards. This underscores the prevalence of altruistic motives among funders in challenging …

Understanding The Determinants Of Blockchain Adoption: An Empirical Study, Amarpreet Kohli, Nihar Kumthekar, Piyush Shah, Rebecca Jauch

Journal of International Technology and Information Management

Blockchain technology (BT) has the potential to enhance security and robustness of transactions through a distributed ledger bookkeeping process. This study employs technology-organization-environment (TOE) framework and threat-rigidity theory (TRT) to examine whether perceived disruption caused by COVID-19 pandemic significantly impacted the adoption of BT, and inclination to adopt BT in the US. The COVID-19 pandemic provided a unique backdrop, as it affected businesses across all industries, sizes, and geographies. Results show a non-significant effect of perceived pandemic disruption on the current stage of BT adoption and intention to adopt BT. However, disruption readiness positively influences the current stage of BT …

Comparing Vr And Tv In Nigeria And The U.S.: Impacts On Empathy, Engagement, And Enjoyment, Jinhee Yoo, Eugene A. Ohu, Radosław Mącik

Journal of International Technology and Information Management

This study (N = 170), involving participants from Nigeria and the U.S., investigated how different technologies (TV and VR) affect users' empathy (α = .93), engagement (α = .93), enjoyment (α = .93), preferences, and likelihood of technology use. Participants watched an animated documentary titled “Is Anna OK?” at two different time points, utilizing VR (Oculus Rift S) and TV, following which they completed measuring empathy, engagement, enjoyment, device preference, and usage likelihood. Analysis via one-way ANOVA and chi-square tests revealed that VR users reported significantly higher empathy and enjoyment compared to TV viewers, particularly on second viewing. Combining both …

Technology And Coding The Great Equalizer: A Case Study Of A Formerly Incarcerated Leader, Joni Schwartz

Publications and Research

Providing meaningful educational and employment opportunities for returning incarcerated citizens from marginalized communities contributes to a more sustainable future for all. This chapter examines the barriers faced by returning incarcerated citizens in employment and presents a case study of a Dario Peña, who is a formerly incarcerated citizen. Peña's lived experience, leadership preparation, vision, and bottom-up leadership made him a leader for the Justice through Code program, which aims to provide prisoners and returning citizens with professional skills to create a sustainable career in the tech industry. Anchored in Critical Race Theory (CRT), this chapter delves into structural inequalities like …

Analysing The Us—China “Ai Cold War” Narrative, Yujia He, Richard Heeks

Patterson School of Diplomacy and International Commerce Faculty Publications

Discussions about artificial intelligence (AI) are gaining prominence in the recent revival of “cold war” narratives comparing US-China relations today to the historical rivalry between the US and the Soviet Union. Drawing on a review of existing academic and policy literature engaging with the “AI cold war” narrative, this paper examines how the narrative is justified, and numerous ways that it can be challenged. It finds that the framing is largely driven by the securitisation of AI, as state actors and policy pundits view AI innovations’ dual-use capabilities as key to national security and ideological competition. However, critics posit that …

Adaptation For Whom? Understanding The Impacts Of Dyke Policies On Small-Scale Farmers In Ca Mau Province Of Vietnam, Nguyen Minh Quang, Nguyen Van Minh, Nguyen Vo Chau Ngan, Martha B. Lerski

Publications and Research

Low-lying deltas worldwide are extremely vulnerable to sea-level rise. As the risks of climate-induced flooding become increasingly clear, the thirst for infrastructure-driven adaptation increases. This highlights a patent need to understand the impacts of engineering adaptation solutions, especially those targeting built structures such as dykes and sluices, on farmers from a bottom-up, farmer-centred perspective. The study addresses this call by examining cases where dyke policies, while successful in some dimensions, have undermined small-scale farmer livelihoods in Ca Mau ― Vietnam’s southernmost rural province. It identifies areas in need of attention and adds empirical data related to this group of farmers. …

Why Ai Monitoring Faces Resistance And What Healthcare Organizations Can Do About It: An Emotion-Based Perspective, Karl Werder, Lan Cao, Eun Hee Park, Balasubramaniam Ramesh

Information Technology & Decision Sciences Faculty Publications

Continuous monitoring of patients' health facilitated by artificial intelligence (AI) has enhanced the quality of health care, that is, the ability to access effective care. However, AI monitoring often encounters resistance to adoption by decision makers. Healthcare organizations frequently assume that the resistance stems from patients' rational evaluation of the technology's costs and benefits. Recent research challenges this assumption and suggests that the resistance to AI monitoring is influenced by the emotional experiences of patients and their surrogate decision makers. We develop a framework from an emotional perspective, provide important implications for healthcare organizations, and offer recommendations to help reduce …

Omnichannel Retailing: An Exploratory Study Of Limiting The Customer Journey In A Digital-First Context, Terence L. Holmes, Edward C. Brewer, Elizabeth Patterson

Atlantic Marketing Journal

A recent retail trend is the rise of “digital-first” firms, where their merchandise is sold primarily via online efforts. In this exploratory study we describe our investigation of the customer journey for a digital-first seller of cosmetics and personal care products. We collected qualitative and quantitative data from a customer survey and follow-up interviews. Results indicate that personal connections and actual product use are the two most important touchpoints customers consider in first discovering the seller and then building a relationship with the brand. We describe practical applications of the findings and suggest ideas for future research.

Teaching Social Marketing Concepts Through Prosocial Behavior Lenses, Bela Florenthal

Atlantic Marketing Journal

This study investigates the educational value of a prosocial project embedded in a college-level marketing course. Framed through a humanistic and holistic lens, the initiative integrated acts of kindness (AOKs) to engage students in real-world application of social marketing concepts. Using a mixed-methods approach, data were collected through student reflections and surveys, revealing high levels of cognitive, emotional, and behavioral engagement. Students developed empathy, compassion, and self-awareness, reinforcing the importance of integrating experiential learning into business education. The project also addressed AACSB’s emphasis on societal impact and aligned with the UN’s Sustainable Development Goals by promoting emotional well-being and civic …

Startup Equity To Stock Exchange: Key Drivers In Venture-Backed Ipo Journeys, Aryaman Shiv Khosla

CMC Senior Theses

This study investigates the components that shape the probability of a venture capital (VC) backed company’s ability to transition from private to public markets through an Initial Public Offering (IPO). The study employs logistic regression models to analyze firm-specific and funding-related determinants of IPO likelihood. Key predictors in this study include total VC funding, number of VC rounds, average deal size growth, size of first round, average days between rounds, company age, number of employees, and primary industry sector. The findings reveal that higher total funding increases IPO likelihood, highlighting the critical role of robust capital access in fueling growth …

Skip-Level Meetings: Perspectives Of Skipped First-Tier U.S. Tech Leaders, Samuel Blacher

Dissertations

Although significant research exists on numerous intersecting theories, such as adaptive leadership, leadership communication, and employee voice, and although they are discussed in business publications and widely yet inconsistently implemented in industry, skip-level meetings are little scholarly studied. Such meetings offer benefits for employees, direct (skipped) managers, and skip-level leaders, and through them, to organizations, yet they also hold risks and pitfalls, and are influenced by various contextual factors, such as stakeholders’ national culture and age. This exploratory qualitative study employed elements of interpretive phenomenology, followed by thematic analysis, to examine the experiences, perceptions, and emotions of a diverse set …

Multimodal Wearable Intelligence For Dementia Care In Healthcare 4.0: A Survey, Po Yang, Gaoshan Bi, Jun Qi, Xulong Wang, Yun Yang, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

As a new revolution of Ubiquitous Computing and Internet of Things, multimodal wearable intelligence technique is rapidly becoming a new research topic in both academic and industrial fields. Owning to the rapid spread of wearable and mobile devices, this technique is evolving healthcare from traditional hub-based systems to more personalised healthcare systems. This trend is well-aligned with recent "Healthcare 4.0" which is a continuous process of transforming the entire healthcare value chain to be preventive, precise, predictive and personalised, with significant benefits to elder care. But empowering the utility of multimodal wearable intelligence technique for elderly care like people with …

A Two-Phase Learning Approach Integrated With Multi-Source Features For Cloud Service Qos Prediction, Fuzan Chen, Jing Yang, Haiyang Feng, Harris Wu, Minqiang Li

Information Technology & Decision Sciences Faculty Publications

Quality of Service (QoS) is a key factor for users when choosing cloud services. However, QoS values are often unavailable due to insufficient user evaluations or provider data. To address this, we propose a new QoS prediction method, Multi-source Feature Two-phase Learning (MFTL). MFTL incorporates multiple sources of features influencing QoS and uses a two-phase learning framework to make effective use of these features. In the first phase, coarse-grained learning is performed using a neighborhood-integrated matrix factorization model, along with a strategy for selecting high-quality neighbors for target users. In the second phase, reinforcement learning through a deep neural network …

A Spoofing Speech Detection Method Combining Multi-Scale Features And Cross-Layer Identification, Hongyan Yuan, Linjuan Zhang, Baoning Niu, Xianrong Zheng

Information Technology & Decision Sciences Faculty Publications

Pre-trained self-supervised speech models can extract general acoustic features, providing feature inputs for various speech downstream tasks. Spoofing speech detection, which is a pressing issue in the age of generative AI, requires both global information and local features of speech. The multi-layer transformer structure in pre-trained speech models can effectively capture temporal information and global context in speech, but there is still room for improvement in handling local features. To address this issue, a speech spoofing detection method that integrates multi-scale features and cross-layer information is proposed. The method introduces a multi-scale feature adapter (MSFA), which enhances the model’s ability …

Optimal Control Of Queueing Systems With Error-Prone Servers, Junqi Hu, Sigrún Andradóttir, Hayriye Ayhan

Information Technology & Decision Sciences Faculty Publications

Consider a Markovian tandem line with finite intermediate buffers and an equal number of stations and servers. Servers are flexible but noncollaborative, so that a job can be processed by at most one server at any time. When a job is being processed, it can be damaged and wasted depending on the proficiency of the server. We identify the dynamic server assignment policy that maximizes the long-run average throughput of the system with two stations and two servers. We find that the optimal policy is either a single or a double threshold policy on the number of jobs in the …