@article{53969,
author = {{Hajipour, Vahid and Tavana, Madjid and Di Caprio, Debora and Akhgar, Majid and Jabbari, Yasaman}},
issn = {{0307-904X}},
journal = {{Applied Mathematical Modelling}},
pages = {{673--699}},
publisher = {{Elsevier BV}},
title = {{{An optimization model for traceable closed-loop supply chain networks}}},
doi = {{10.1016/j.apm.2019.03.007}},
volume = {{71}},
year = {{2019}},
}
@article{53966,
author = {{Tavana, Madjid and Khosrojerdi, Ghasem and Mina, Hassan and Rahman, Amirah}},
issn = {{0149-7189}},
journal = {{Evaluation and Program Planning}},
publisher = {{Elsevier BV}},
title = {{{A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process}}},
doi = {{10.1016/j.evalprogplan.2019.101703}},
volume = {{77}},
year = {{2019}},
}
@article{49472,
author = {{Herrenkind, B. and Nastjuk, I. and Brendel, A.B. and Trang, Simon Thanh-Nam and Kolbe, L.M.}},
journal = {{Transportation Research Part D: Transport and Environment}},
pages = {{214–233}},
title = {{{Young People’s Travel Behavior – Using the Life-Oriented Approach to Understand the Acceptance of Autonomous Driving}}},
volume = {{74}},
year = {{2019}},
}
@article{49471,
author = {{Trang, Simon Thanh-Nam and Brendel, A.}},
journal = {{Information Systems Frontiers}},
number = {{6}},
pages = {{1265–1284}},
title = {{{A meta-analysis of deterrence theory in information security policy compliance research}}},
volume = {{21}},
year = {{2019}},
}
@article{35756,
abstract = {{
Purpose
Leveraging social action theory, social network theory and the notion of network externality, the purpose of this paper is to model two different return on investment (ROI) measures: the networked ROI which captures the network effect originating from a social media investment, and the discrete ROI which focuses social media discrete returns from individual users.
Design/methodology/approach
A field experiment was set up over a period of three months to test the effects of two variants of an advertisement campaign (a social vs a discrete ad) on the modeled networked and discrete ROIs.
Findings
The authors find that emphasizing discrete user actions leads to lower network gains, but higher monetary returns while the social action emphasis produces higher network gains, but lower monetary returns. The study further suggests that social action focus is preferable for brand promotion and engagement, whereas the discrete action focus is suitable for boosting sales and website traffic.
Practical implications
Several potential implications for social media researchers and marketers are also discussed.
Originality/value
The authors for the first time showed that that the social media returns are derived not only from individual actions taken by the user (e.g. likes and shares) but also from users’ social interdependencies and the additional exposure that results from network effects.
}},
author = {{Khan, Gohar and Mohaisen, Manar and Trier, Matthias}},
issn = {{1066-2243}},
journal = {{Internet Research}},
keywords = {{Economics and Econometrics, Sociology and Political Science, Communication}},
number = {{2}},
pages = {{631--652}},
publisher = {{Emerald}},
title = {{{The network ROI}}},
doi = {{10.1108/intr-07-2018-0346}},
volume = {{30}},
year = {{2019}},
}
@article{49473,
author = {{Herrenkind, B. and Brendel, A.B. and Nastjuk, I. and Greve, M. and Kolbe, L.M.}},
journal = {{Transportation Research Part D: Transport and Environment}},
pages = {{255–276}},
title = {{{Investigating end-user acceptance of autonomous electric buses to accelerate diffusion}}},
volume = {{74}},
year = {{2019}},
}
@inproceedings{2490,
author = {{Szopinski, Daniel and Kundisch, Dennis}},
booktitle = {{2nd Business Model Conference}},
location = {{Florence, Italy}},
title = {{{Business model idea generation: An exploratory study on changing perspectives}}},
year = {{2018}},
}
@inproceedings{2491,
author = {{Szopinski, Daniel}},
booktitle = {{2nd Business Model Conference}},
location = {{Florence, Italy}},
title = {{{How to teach business model innovation to 300+ students: An experience report}}},
year = {{2018}},
}
@inproceedings{2558,
author = {{Bohn, Nicolai and Kundisch, Dennis}},
booktitle = {{Proceedings of the 25th European Conference on Information Systems (ECIS)}},
location = {{Portsmouth, UK}},
title = {{{The Role of Technology Pivots in Software Startups: Antecedents and Consequences}}},
year = {{2018}},
}
@techreport{2821,
author = {{Kundisch, Dennis and Beverungen, Daniel}},
pages = {{22--27}},
title = {{{Als Wirtschaftsinformatiker die digitale Transformation in Organisationen gestalten}}},
year = {{2018}},
}
@inproceedings{2832,
author = {{Schlangenotto, Darius and Kundisch, Dennis and Poniatowski, Martin}},
booktitle = {{Proceedings of the 24th Americas Conference on Information Systems (AMCIS)}},
location = {{New Orleans, USA}},
title = {{{What Drives Paid Search Success: A Systematic Literature Review}}},
year = {{2018}},
}
@inproceedings{2861,
abstract = {{The Digital Transformation alters business models in all fields of application, but not all industries transform at the same speed. While recent innovations in smart products, big data, and machine learn-ing have profoundly transformed business models in the high-tech sector, less digitalized industries—like agriculture—have only begun to capitalize on these technologies. Inspired by predictive mainte-nance strategies for industrial equipment, the purpose of this paper is to design, implement, and evaluate a predictive maintenance method for agricultural machines that predicts future defects of a machine’s components, based on a data-driven analysis of service records. An evaluation with 3,407 real-world service records proves that the method predicts damaged parts with a mean accuracy of 86.34%. The artifact is an exaptation of previous design knowledge from high-tech industries to agriculture—a sector in which machines move through rough territory and adverse weather conditions, are utilized exten-sively for short periods, and do not provide sensor data to service providers. Deployed on a platform, the prediction method enables co-creating a predictive maintenance service that helps farmers to avoid resources shortages during harvest seasons, while service providers can plan and conduct maintenance service preemptively and with increased efficiency. }},
author = {{Lüttenberg, Hedda and Bartelheimer, Christian and Beverungen, Daniel}},
location = {{Portsmouth, UK}},
title = {{{Designing Predictive Maintenance for Agricultural Machines}}},
year = {{2018}},
}
@inproceedings{2564,
author = {{Gutt, Dominik}},
booktitle = {{Proceedings of the 25th European Conference on Information Systems (ECIS)}},
location = {{Portsmouth, UK}},
title = {{{In the Eye of the Beholder? – Empirically Decomposing Different Economic Implications of the Online Rating Variance}}},
year = {{2018}},
}
@article{2652,
author = {{Schlangenotto, Darius and Kundisch, Dennis and Wünderlich, Nancy}},
journal = {{Electronic Markets}},
number = {{4}},
pages = {{407--421}},
title = {{{Is Paid Search Overrated? When Bricks-and-Mortar-Only Retailers Should Not Use Paid Search}}},
volume = {{28}},
year = {{2018}},
}
@inproceedings{2660,
author = {{Neumann, Jürgen and Gutt, Dominik and Kundisch, Dennis}},
booktitle = {{Conference Abstracts of the Symposium on Statistical Challenges in Electronic Commerce Research (SCECR)}},
location = {{Rotterdam, Netherland}},
title = {{{The Traveling Reviewer Problem - Exploring the Relationship Between Offline Locations and Online Rating Behavior}}},
year = {{2018}},
}
@inproceedings{2678,
author = {{Piasecki, David and Schlangenotto, Darius}},
booktitle = {{Multikonferenz Wirtschaftsinformatik 2018 (MKWI)}},
location = {{Lüneburg}},
title = {{{Can Companies Freeride on Public Interest Events? The Effect of Peak Days on Paid Search Advertising during the UEFA Euro 2016}}},
year = {{2018}},
}
@inproceedings{2679,
author = {{Bohn, Nicolai and Kundisch, Dennis}},
booktitle = {{Tagungsband Multikonferenz Wirtschaftsinformatik 2018 (MKWI)}},
location = {{Lüneburg}},
title = {{{Much more than "same solution using a different technology"}}},
year = {{2018}},
}
@inproceedings{2680,
author = {{Görzen, Thomas}},
booktitle = {{Tagungsband Multikonferenz Wirtschaftsinformatik 2018 (MKWI)}},
location = {{Lüneburg}},
title = {{{Trust the Experienced? Investigating the Effect of Experience on Decision Making in the Crowd}}},
year = {{2018}},
}
@inproceedings{2681,
author = {{Görzen, Thomas and Laux, Florian}},
booktitle = {{Tagungsband Multikonferenz Wirtschaftsinformatik 2018 (MKWI)}},
location = {{Lüneburg}},
title = {{{Extracting the Wisdom from the Crowd: A Comparison of Approaches to Aggregating Collective Intelligence}}},
year = {{2018}},
}
@inproceedings{2682,
author = {{Schlangenotto, Darius}},
booktitle = {{Tagungsband Multikonferenz Wirtschaftsinformatik 2018 (MKWI)}},
location = {{Lüneburg}},
title = {{{With or Without You? The Influence of Search Partners on Consumer Behavior in Paid Search}}},
year = {{2018}},
}