Marketers are adopting increasingly sophisticated ways to engage with customers throughout their journeys. We extend prior perspectives on the customer journey by introducing the role of digital signals that consumers emit throughout their activities. We argue that the ability to detect and act on consumer digital signals is a source of competitive advantage for firms. Technology enables firms to collect, interpret, and act on these signals to better manage the customer journey. While some consumers' desire for privacy can restrict the opportunities technology provides marketers, other consumers' desire for personalization can encourage the use of technology to inform marketing efforts. We posit that this difference in consumers' willingness to emit observable signals may hinge on the strength of their relationship with the firm. We next discuss factors that may shift consumer preferences and consequently affect the technology-enabled opportunities available to firms. We conclude with a research agenda that focuses on consumers, firms, and regulators.
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http://dx.doi.org/10.1007/s11747-022-00839-w | DOI Listing |
Eur Radiol Exp
January 2025
Department of Neuroradiology, University hospital RWTH Aachen, Aachen, Germany.
Background: To define optimal parameters for the evaluation of vessel visibility in intracranial stents (ICS) and flow diverters (FD) using photon-counting detector computed tomography angiography (PCD-CTA) with spectral reconstructions.
Methods: We retrospectively analyzed consecutive patients with implanted ICS or FD, who received a PCD-CTA between April 2023 and March 2024. Polyenergetic, virtual monoenergetic, pure lumen, and iodine reconstructions with different keV levels (40, 60, and 80) and reconstruction kernels (body vascular [Bv]48, Bv56, Bv64, Bv72, and Bv76) were evaluated by two radiologists with regions of interests and Likert scales.
J Neurosci
January 2025
Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
Action potentials (spikes) are regenerated at each node of Ranvier during saltatory transmission along a myelinated axon. The high density of voltage-gated sodium channels required by nodes to reliably transmit spikes increases the risk of ectopic spike generation in the axon. Here we show that ectopic spiking is avoided because K1 channels prevent nodes from responding to slow depolarization; instead, axons respond selectively to rapid depolarization because K1 channels implement a high-pass filter.
View Article and Find Full Text PDFAnal Chem
January 2025
School of Chemistry and Chemical Engineering, State Key Laboratory of Digital Medical Engineering, Southeast University, Nanjing 211189, China.
Formamidopyrimidine DNA glycosylase (Fpg) and flap endonuclease 1 (FEN1) are essential to sustaining genomic stability and integrity, while the abnormal activities of Fpg and FEN1 may lead to various diseases and cancers. The development of simple methods for simultaneously monitoring Fpg and FEN1 is highly desirable. Herein, we construct a multiple cyclic ligation-promoted exponential recombinase polymerase amplification (RPA) platform for sensitive and simultaneous monitoring of Fpg and FEN1 in cells and clinical tissues.
View Article and Find Full Text PDFJ Med Internet Res
January 2025
Department of Computer Science and Software Engineering, United Arab Emirates University, Al Ain, United Arab Emirates.
Background: Neuroimaging segmentation is increasingly important for diagnosing and planning treatments for neurological diseases. Manual segmentation is time-consuming, apart from being prone to human error and variability. Transformers are a promising deep learning approach for automated medical image segmentation.
View Article and Find Full Text PDFFront Artif Intell
January 2025
Language Intelligence and Information Retrieval (LIIR) Lab, Department of Computer Science, KU Leuven, Leuven, Belgium.
The digitization of healthcare records has revolutionized medical research and patient care, with electronic health records (EHRs) containing a wealth of structured and unstructured data. Extracting valuable information from unstructured clinical text presents a significant challenge, necessitating automated tools for efficient data mining. Natural language processing (NLP) methods have been pivotal in this endeavor, aiming to extract crucial clinical concepts embedded within free-form text.
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