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The CIIS Research Seminar Series runs Mondays, 12.30 - 14.00, biweekly throughout the semester.

Given the current pandemic, we will organize the seminar series as a virtual series using Zoom.

Everybody interested is welcome to attend the sessions! If you have questions, please send an email to werder(at)

Currently planned seminar talks (speakers and order may change on short notice):


Research Seminar Series Winter 2022/23
Date Room Speaker Title & Abstract

October, 13th, 2022

Thursday, 11:30 CEST

Seminarraum -1.502


Jose Benitez

(EDHEC Business School, France)

Title: Impact of social media technologies on new product development performance: Theory and empirical evidence.

Abstract: New product development (NPD) performance can be attributed to developing products that match customers' needs. With an unprecedented explosion in social media technologies, with a different nature than other IT systems, social media users can interact with firms to share information to develop products that match customers' needs. This study introduces and conceptualizes the concepts of social media capability and social knowledge co-creation. Social media capability is the firm's ability to select, manage, and leverage internal (e.g., Meta Workplace) and external (e.g., Twitter) social media to support business activities. Social knowledge co-creation refers to the new knowledge joint creation between firms and employees and customers using internal and external social media. Integrating the IT-enabled organizational capabilities perspective with the social media affordances literature, we propose a research model on the impact of social media capability and social knowledge co-creation on NPD performance. We hypothesize that social media capability can enable firms to co-create internal knowledge between employees, functional departments, and business units via internal social media and external knowledge with customers via external social media. We also argue that social knowledge co-creation with employees and customers helps develop a portfolio of NPD dynamic capabilities: market orientation, coordination capability, absorptive capacity, collective mind, and business flexibility. The research model was tested on a sample of large European firms using a combination of survey and secondary data. We find that social media capability enhances NPD performance by enabling firms to co-create knowledge with employees and customers and developing NPD dynamic capabilities. This study makes two important contributions. First, we theorize, operationalize, and measure social media capability as a distinct, firm-level cross-functional capability and social knowledge co-creation as a new knowledge creation joint process performed among firms, employees, and customers using social media technologies. Second, we theorize and demonstrate how social media capability improves NPD performance by co-creating knowledge with employees and customers and developing NPD dynamic capabilities to help firms develop new products that match customers' needs.

November, 7th, 2022

Monday, 16:00 CEST



Hao Yan

(Arizona State University, US)

Title: Knowledge constrained learning and anomaly detection based on high-dimensional data

Abstract: As the sensing technology developed, high-dimensional data such as images and signals are very common in manufacturing systems, health care, and energy systems. Combining Domain knowledge for system modeling and anomaly detection is an important research problem in many research fields. This work focuses on incorporating the domain knowledge about the HD data for anomaly detection and system modeling. First, we will discuss how the knowledge about the system background and anomaly component can guide for better sequential sampling and anomaly detection in the high-dimensional space. Second, we will discuss the extension of the knowledge constrained modeling into probabilistic deep learning models to accommodate both aleatoric and epistemic uncertainties. The algorithms will be validated in both simulation and several case studies including manufacturing anomaly detection, medical image segmentation, energy prediction, etc. 

November, 25th, 2022

Friday, 12:30 CEST

Room 3.02, Pohlighaus (Building 411)


Aron Lindberg

(Stevens Institute of Technology, US)

Title: From Apps to Ecosystem: Platform Development-In-Reverse at Autodesk

Abstract: Most platforms are developed before the applications that connect to the platform, and as such platforms can specify interfaces which then set the stage for how attendant applications are developed. However, not all platforms are developed in this manner—at times the applications already exist, and a platform core is developed to interconnect a set of such applications. This paper reports on a case study of how a major software development company—Autodesk—has been establishing a platform ecosystem out of already existing applications, both internal and external to the company. Through conceptualizing the platform ecosystem through the lens of modular architectures, we characterize how Autodesk used experimental practices to identify relevant interdependencies between applications and create connections among those applications to better support customer workflows. This exploratory process involved successful and unsuccessful “handshakes” and led to key architectural stages describing the emergent ecosystem’s architectural development. The company went through a process of first establishing ad hoc connections between modules, then creating standardized interfaces between existing applications, and last imbuing interfaces with computational capacities used to format complex data in the necessary ways to fit particular workflows. Based on our theorizing we suggest that traditional perspectives on software development, which roughly follow a “plan-execute-validate” paradigm, are not sufficient for understanding how platform ecosystems emerge out of collections of already existing applications.

December, 5th, 2022

Monday, 12:30 CEST



Chen Zhang

(Tsinghua University, China)

Title: Thompson Sampling based Partially Observable Online Change Detection for Exponential Families

Abstract: This talk explores machine learning to address a problem of Partially Observable Multi-sensor Sequential Change Detection (POMSCD), where only a subset of variables can be observed to monitor a multivariate process for change-point detection at each online learning round. POMSCD is much more challenging because the learner not only needs to detect on-the-fly whether a change occurs based on partially observed historical data, but also needs to cleverly choose a subset of informative variables to observe in the next learning round, to maximize the overall sequential change detection performance. In this talk, we present a holistic framework for POMSCD for data from exponential family distributions. The framework first proposes a general composite decomposition for exponential-family distributed data by projecting its natural parameter onto normal bases and abnormal bases, which enables efficient inference for sparse changes. Then the inference results are used for detection scheme construction and different types of test statistics can be compacted. By further designing the test statistic as the reward function in the combinatorial multi-armed bandit (CMAB) problem, a Thompson sampling based sensor allocation strategy is constructed to select the most anomalous variables. Examples of Gaussian, Poisson, and binomial distributed data streams are discussed to evaluate the performance of our proposed method.

January, 16th, 2023

Monday, 12:30 CEST

Room 3.02, Pohlighaus (Building 411)

Andreas Drechsler

(Victoria University of Wellington, NZ)

Title: Scoping around and Reflecting on Boundary Conditions in Information Systems Research: the Case of Research on Small and Medium Organisations

Abstract: This talk proposes an approach to carefully scope an IS research project around and continuously reflect on suitable boundary conditions depending on the project’s topic and goals, and illustrates the approach for research in the context of small and medium organisations (SMOs). SMOs are a suitable illustrative example for the importance of boundary conditions as SMOs are of a fundamentally different nature compared to large organisations, yet IS research often implicitly assumes the latter as their context. Insufficient attention to boundary conditions may lead to IS research drawing on unsuitable theories, or making unreflected or too wide claims for accuracy or applicability. The approach builds on the extant boundary condition literature but makes the existing recommendations and guidelines more actionable for IS research throughout the entire research lifecycle. The approach also integrates extant thinking around boundary conditions for explanatory research with similar considerations from the design-oriented research literature.Other researchers can use the approach to explicitly scope their research around suitable boundary conditions at the beginning and reflect on them throughout their project. The approach also enables researchers to carefully take into account the boundary conditions (or the lack thereof) of any theory they draw on and to include or exclude certain classes of their units of analysis or design contexts of interest (e.g., organisations or individuals) more clearly from their sample. Ultimately, researchers should thus be able to produce research outcomes that can make stronger validity or fitness claims for more clearly delineated classes of their chosen unit of analysis or design contexts.

January, 30th, 2023

Monday, 12:30 CEST



Irina Heimbach

(WHU Otto Beisheim School of Management, DE)

Title: The Rise of Conversational Reviews: The Effects of Solicitation Medium Anthropomorphism on Product Rating Valence

Abstract: Companies are increasingly introducing “conversational reviews”—reviews solicited via chatbots—to gain user feedback. However, little is known about how chatbot-mediated solicitation influences rating valence compared to conventional online forms. Therefore, we conceptualized these review solicitation media on the continuum of anthropomorphism and investigated how various levels of anthropomorphism affect rating valence, showing that more anthropomorphic media lead to more positive reviews. The effect of anthropomorphism is stronger for low-quality products and remains robust across review solicitors (sellers vs. platforms). Further, we showed that moderate levels of anthropomorphism lead to increased interaction enjoyment, while high levels increase social presence, thus inflating the rating valence. Our study is among the first to investigate chatbots as a new form of technology to solicit online reviews, providing insights to inform various stakeholders of the advantages and drawbacks of anthropomorphic technology in customer feedback solicitation.