TY - GEN A1 - Baaken, Thomas T1 - Lessons Learned from 20 Years of Regional Development Science and Boundary Spanning! KW - Boundary Spanning Y1 - 2023 ER - TY - GEN A1 - Baaken, Thomas T1 - Identifying new Potential: Cooperation opens up the Future! KW - Cooperation Future Y1 - 2023 ER - TY - GEN A1 - Damwerth, Philipp A1 - Bach, Norbert A1 - Buchholz, Wolfgang T1 - Build to last: An analysis of the impact of founding conditions on ecosystem emergence Y1 - 2023 ER - TY - GEN A1 - Damwerth, Philipp A1 - Bach, Norbert A1 - Buchholz, Wolfgang A1 - Rosculete, Maria-Ana T1 - Collective dynamic capabilities in innovation ecosystems - an analysis of the multi-actor process Y1 - 2023 ER - TY - CHAP A1 - Eschenbächer, Jens A1 - Dircksen, Michael A1 - Kühl, Linus A1 - Wiethölter, Jost T1 - Initial approach for AI-based real time global risk assessment in SCM T2 - Proceedings of the 27th International Symposium on Logistics Y1 - 2023 UR - https://www.islconf.org/wp-content/uploads/2023/07/ISL_2023_Final_Proceedings.pdf SN - 13 978-0-85358-352-3 SP - 75 EP - 76 ER - TY - CHAP A1 - Eschenbächer, Jens A1 - Wiethölter, Jost A1 - Kühl, Linus T1 - Data-driven supply chain analysis: Development and potential analysis of a model-based damage prediction approach and its integration into SCM T2 - Proceedings of the 27th International Symposium on Logistics N2 - Against the setting of an increasing need for innovation and low margins, companies in the logistics sector are facing highly competitive pressure. One field with high potential for optimization lies within damage quotas. The use of big data analytics or data mining represents a promising approach to face this challenge. However, within supply chain management, data mining is hardly being researched on regarding damage quotas and thus not being utilized to its full possible extend. At the current time it seems to predominantly be used for route and utilization optimization while the analysis of delivery damages is hardly considered. The aim of this research is therefore to showcase an initial approach for data mining in logistics to predict delivery damage probabilities and to validate this by means of a multiple case study research. To create a sound basis for evaluation, the groundwork is laid out based on CRISP-DM by the analysis of reference data (German road-cargo market). As a central result it is noted that data mining can systematically be used to help reducing the damages by forecasting the probabilities of damages occurring during transport in dependence of different factors. The approach can be utilized across different markets as long as sufficient data tracking delivery damages is being collected within a company. Challenges arise in the field of air- and sea-freight. Y1 - 2023 UR - https://www.islconf.org/wp-content/uploads/2023/07/ISL_2023_Final_Proceedings.pdf SN - 13 978-0-85358-352-3 SP - 136 EP - 144 ER - TY - JOUR A1 - Fisher, Sandra A1 - Bonaccio, Silvia A1 - Connelly, Catherine T1 - Reactions of Applicants with Disabilities to Technology-Enabled Recruitment and Selection: A Research Agenda JF - International Journal of Selection and Assessment Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:836-opus-177102 ER - TY - CHAP A1 - Kindsgrab, Kai A1 - Dircksen, Michael A1 - Zadek, Hartmut ED - Glistau, Elke ED - Trojahn, Sebastian T1 - Effects of CO2e measures for the transport logistics sector T2 - 16th International Doctoral Students Workshop on Logistics, Supply Chain and Production Management Y1 - 2023 UR - https://opendata.uni-halle.de/handle/1981185920/105332 SN - 978-3-948749-37-8 U6 - http://dx.doi.org/10.25673/103379 PB - Otto von Guericke University Library CY - Magdeburg ER - TY - JOUR A1 - Nakabuye, Zaina A1 - Mayanja, Jamiah A1 - Bimbona, Sarah A1 - Wasserman, Michael T1 - Technology orientation and export performance: the moderating role of supply chain agility JF - Modern Supply Chain Research and Applications N2 - Purpose The purpose of this paper is to investigate the relationships between technology orientations and export performance of small and medium-sized enterprises (SMEs). Design/methodology/approach A quantitative research design was adopted for this study. The paper formulates hypotheses from the literature review. These hypotheses are tested using structural equation modeling with data collected from 231 SMEs in Uganda. Data were analyzed using SPSS version 23 and AMOS. Findings The findings of this study showed technology orientation has a positive and significant relationship with the performance of Ugandan SMEs and that supply chain agility moderates technology orientation and export performance. Research limitations/implications The study discusses the findings, advances limitations and managerial implications. It also suggests future research avenues. It proposes some recommendations to help Ugandan SMEs to form flexible supply chains, use the latest technology and create strong relationship ties with their partners in the supply chain. Practical implications The study suggests that managers of Ugandan SMEs should use the latest technology in production, marketing, logistics and supply chain management which will enable them to respond quickly to customer tastes and preferences leading to higher levels of export performance. Originality/value This study contributes to the literature on strategic management showing the reliability of scales used and the confirmatory of the factor structure. This study shows that in strategic management technology, orientation is critical in increasing export performance. This study has extended the resource-based view (RBV) and dynamic capabilities theories. Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:hbz:836-opus-174624 SN - 2631-3871 VL - 5 IS - 4 SP - 230 EP - 264 ER - TY - CHAP A1 - Rokos, Constantina T1 - Virtual Exchange Collaborative Practices Using Project and Research-Based Learning: Embracing the Complexities and Challenges to Maximize Students' Global Intercultural Competencies T2 - Handbook of Research on Facilitating Collaborative Learning Through Digital Content and Learning Technologies Y1 - 2023 SP - 1 EP - 19 PB - IGI ER -