Oliver Gassmann
Title
Prof. Dr.
Last Name
Gassmann
First name
Oliver
Email
oliver.gassmann@unisg.ch
Phone
+41 71 224 72 21
Web Site
524 results
Now showing 1 - 10 of 524
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Item type:Publication, New perspectives for better R&D performance: lessons learned from leading pharma companies(Elsevier BV, 2026-05-07); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Ganzheitliche Leistungsmessung im Spitzensport(2026-02) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Der Weg ist das Ziel(2026-10); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Wenn KI den Laden schmeißt(2026-02-22)Type:journal articleJournal:Harvard Business ManagerVolume:2026Issue:3 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, How to Successfully Scale B2B Marketplaces(2026-05); Business-to business (B2B) marketplaces are experiencing a resurgence, promising to simplify global sourcing amid increasing geopolitical tensions, trade tariffs and supply chain disruptions. However, managers mistakenly apply business-to-consumer (B2C) marketplace scaling techniques within B2B contexts. Based on case studies of two pioneering B2B marketplaces, we highlight how B2C-platform thinking leads managers into scaling traps. The cases underscore the importance of setting a viable focus, deliberate product building, as well as physical selling and right-touch service, to establish and scale B2B marketplaces in traditional industries.Type:journal articleJournal:MIS Quarterly ExecutiveVolume:25Issue:2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Dancing titans: Dual orchestration and governance in industrial digital platforms for B2B value co-creationThe digitization of industrial ecosystems positions B2B industrial digital platforms as central to value co-creation and co-capture. While B2C platform governance is well-researched, few studies examine how manufacturing firms and platform providers collaboratively govern digital business models (DBMs) in B2B platform settings. Our study addresses this gap through a multiple case study of five platform providers and five B2B manufacturers, drawing on 33 semi-structured interviews and document analysis. We introduce the concept of dual orchestration-a governance approach in which platform providers and manufacturers jointly assume and adapt orchestration roles across DBM phases. We develop the Platform DBM Process Model (Figure 1), which illustrates how governance dynamics and relational mechanismstransparency, reciprocity, commitment, proximity, and coopetition-enable dual orchestration through joint role adaptation. We present the Dual Orchestration Governance Framework for Industrial Platform DBMs (Figure 2), integrating DBM phases, relational issues, and governance mechanisms to theorize dual orchestration as a dynamic co-governance process. The study contributes to platform governance theory by specifying the structural and relational features of dual orchestration and by providing an empirically grounded account of its evolution.Type:journal articleJournal:TechnovationVolume:151Scopus© Citations 5 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A case study assessing the impact of M&A and licensing on FDA drug approvals of leading pharmaceutical companies(Elsevier, 2025); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Benchmarking R&D success rates of leading pharmaceutical companies: an empirical analysis of FDA approvals (2006–2022)(Elsevier, 2025-02); ; ; Hartl, DominikPrevious analyses provide an industry benchmark of 10% for the success rate in clinical development. However, prior analyses were limited by a narrow timeframe, a diverse research focus, biases in phase-to-phase transition methodology or a focus on specific use cases. We calculated unbiased input:output ratios (Phase I to FDA new drug approval) to analyze the likelihood of first approval using data from clinicaltrials.gov, encompassing a total of 2092 active ingredients, 19 927 clinical trials conducted by 18 leading pharmaceutical companies (2006–2022) and 274 new drug approvals. Our study reveals an average likelihood of first approval rate of 14.3% across leading research-based pharmaceutical companies, broadly ranging from 8% to 23%.Type:journal articleJournal:Drug Discovery TodayVolume:30Issue:2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The R&D productivity challenge: transforming the pharmaceutical ecosystem(2025); ; - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Less trust, more truth: Implications and design choices for business models and platform ecosystems in the age of Web3Business model literature, while insightful, primarily focuses on the Internet and Web 2.0 contexts. The emergence of pioneering digital technologies, especially the Web3 anchored by blockchain, necessitates reevaluating business model paradigms, particularly those of platform business models within related ecosystems. This study delves into blockchain's unique affordances, investigating how they mold novel Web3 business model patterns and integrate into specific platform ecosystems. We scrutinize the characteristics, trajectories, and synergies of value creation and capture. Using a mixed-methods approach involving 171 interviews and a subsequent sample of 126 Web3 ventures, we delineate a taxonomy of Web3 business model dimensions, clustering emergent decentralized platform ecosystems into pertinent archetypes. Our theoretical model delineates how blockchain affordances influence these configurations, emphasizing the dynamic between a platform's nucleus and its fringes. We highlight Web3 platform design choices leaning towards data sovereignty, emphasizing how the degree of blockchain integration within platform governance—leading to information symmetry and platform disintermediation—transitions digital trust to what we term as digital truth.Type:journal articleJournal:Technological Forecasting and Social ChangeVolume:211Scopus© Citations 13