Supporting Business Model Idea Generation Through Machine-generated Ideas: A Design Theory - John, Thomas (Proceedings of the 37th International Conference on Information Systems (ICIS), Dublin, Ireland)
Successful business model innovation is impossible without innovative business model ideas. When generating such ideas, humans make use of two properties of the human cognitive system: First, their ability to build up knowledge (i.e., raw material for new ideas), and second, their ability to flexibly recombine that knowledge. While these properties enable humans to generate innovative ideas, the amounts of knowledge and cognitive flexibility that humans can possess are limited, which in turn limits human idea generation capability. With business model idea generators, a new class of information systems is proposed that can contribute to alleviating the limits that constrain human idea generation. The ideas that such idea generators produce can complement human business model ideas, thereby increase the probability for high-quality ideas, and eventually raise the odds of successful business model innovation. The contribution is a design theory that describes the architecture of the proposed idea generators.

Does Sentiment Among Users in Online Social Networks Polarize or Balance Out? A Sociological Perspective Using Social Network Analysis - Trier, Matthias; Hillmann, Robert (Understanding Complex Systems)

Business Model Modeling Languages as Tools for Innovation: Theory and Empirical Evidence - John, Thomas

Vergleichende Betrachtung von Software-Werkzeugen zur Geschäftsmodellentwicklung - Strotmeyer, Sebastian; John, Thomas; Kundisch, Dennis (Multikonferenz Wirtschaftsinformatik (MKWI))

Disentangling the Relationship Between the Adoption of In-Memory Computing and Firm Performance - Fay, Maria; Müller, Oliver; vom Brocke, Jan (European Conference on Information Systems)
Recent growth in data volume, variety, and velocity led to an increased demand for high-performance data processing and analytics solutions. In-memory computing (IMC) enables organizations to boost their information processing capacity, and is widely acknowledged to be one of the leading strategic technologies in the field of enterprise systems. The majority of technology vendors now have IMC technologies in their portfolio, and the interest of companies in adopting such solutions in order to benefit from big data is increasing. Although there is first research on the business value of IMC in the form of case studies, there is a lack of large-scale quantitative evidence on the positive effect of such solutions on firm performance. Based on a unique panel data set of IMC adoption information and financial firm performance data for a sample of companies from the Fortune 500 list this study aims at explaining the relationship between the adoption of IMC solutions and firm performance. In this research-in-progress paper we discuss the theoretical background of our work, describe the proposed research design, and develop five hypotheses for later testing. Our work aims at contributing to the research streams on IT business value and business analytics by helping to better understand the nature of the interdependencies between IMC adoption and firm performance.

Identifying and quantifying cultural factors that matter to the IT workforce: An approach based on automated content analysis - Schmiedel, Theresa; Müller, Oliver; Debortoli, Stefan; vom Brocke, Jan (European Conference on Information Systems)
Organizational culture represents a key success factor in highly competitive environments, such as, the IT sector. Thus, IT companies need to understand what makes up a culture that fosters employee performance. While existing research typically uses self-report questionnaires to study the relation of culture and the success of companies, the validity of this approach is often discussed and researchers call for new ways of studying culture. Therefore, our research goal is to present an alternative ap-proach to culture analysis for examining which cultural factors matter to the IT workforce. Our study builds on 112,610 online reviews of Fortune 500 IT companies collected from Glassdoor, an online platform on which current and former employees can anonymously review companies and their man-agement. We perform an automated content analysis to identify cultural factors that employees em-phasize in their reviews. Through a regression analysis on numerical employee satisfaction ratings, we find that a culture of learning and performance orientation contributes to employee motivation, while a culture of assertiveness and gender inegalitarianism has a strong negative influence on em-ployees’ satisfaction in the IT workforce. Future research can apply our approach as an alternative method to quantifying culture and its impact on other variables.

Towards an importance-performance analysis of factors affecting e-business diffusion in the wood industry - Trang, S.; Zander, S.; de Visser, B.; Kolbe, L. M. (Journal of Cleaner Production)

Drivers of network governance: a multitheoretic perspective with insights from case studies in the German wood industry - Zander, S.; Trang, S.; Kolbe, L. M. (Journal of Cleaner Production)

A secured context-aware tourism recommender system using artificial bee colony and simulated annealing - Roy, Arup; Tavana, Madjid; Banerjee, Soumya; Caprio, Debora Di (International Journal of Applied Management Science)

Robust efficiency measurement with common set of weights under varying degrees of conservatism and data uncertainty - Aghayi, Nazila; Tavana, Madjid; Raayatpanah, Mohammad Ali (European J. of Industrial Engineering)

Optimistic and pessimistic performance and congestion analysis in fuzzy data envelopment analysis - Khodabakhshi, Mohamad; Tavana, Madjid; Abootaleb, Fatemeh Baghbani (International Journal of Logistics Systems and Management)

Autonomous vehicles: challenges, opportunities, and future implications for transportation policies - Bagloee, Saeed Asadi; Tavana, Madjid; Asadi, Mohsen; Oliver, Tracey (Journal of Modern Transportation)

A bi-objective inventory optimization model under inflation and discount using tuned Pareto-based algorithms: NSGA-II, NRGA, and MOPSO - Mousavi, Seyed Mohsen; Sadeghi, Javad; Niaki, Seyed Taghi Akhavan; Tavana, Madjid (Applied Soft Computing)

An Improved Method for Edge Detection and Image Segmentation Using Fuzzy Cellular Automata - Shahverdi, Reza; Tavana, Madjid; Ebrahimnejad, Ali; Zahedi, Khadijeh; Omranpour, Hesam (Cybernetics and Systems)

An integrated data envelopment analysis and free disposal hull framework for cost-efficiency measurement using rough sets - Khanjani Shiraz, Rashed; Fukuyama, Hirofumi; Tavana, Madjid; Di Caprio, Debora (Applied Soft Computing)

An optimal sequential information acquisition model subject to a heuristic assimilation constraint - Di Caprio, Debora; Santos-Arteaga, Francisco J.; Tavana, Madjid (Benchmarking: An International Journal)

An integrated data envelopment analysis and simulation method for group consensus ranking - Ebrahimnejad, Ali; Tavana, Madjid; Santos-Arteaga, Francisco J. (Mathematics and Computers in Simulation)

A conceptual analytic network model for evaluating and selecting third-party reverse logistics providers - Tavana, Madjid; Zareinejad, Mohsen; Santos-Arteaga, Francisco J.; Kaviani, Mohamad Amin (The International Journal of Advanced Manufacturing Technology)

Solving Geometric Programming Problems with Normal, Linear and Zigzag Uncertainty Distributions - Khanjani Shiraz, Rashed; Tavana, Madjid; Di Caprio, Debora; Fukuyama, Hirofumi (Journal of Optimization Theory and Applications)

Multi-objective multi-layer congested facility location-allocation problem optimization with Pareto-based meta-heuristics - Hajipour, Vahid; Fattahi, Parviz; Tavana, Madjid; Di Caprio, Debora (Applied Mathematical Modelling)