@inproceedings{35660, abstract = {{Effective customer loyalty programs are essential for every company. Small and medium sized brick-and- mortar stores, such as bakeries, butcher and flower shops, often share a common overarching loyalty program, organized by a third-party provider. Furthermore, these small shops have limited resources and often cannot afford complex BI tools. Out of these reasons we investigated how traditional brick-and- mortar stores can benefit from an expansion of service functionalities of a loyalty card provider. To answer this question, we cooperated with a cross-industry customer loyalty program in a polycentric region. The loyalty program was transformed from simple card-based solution to a mobile app for customers and a web- application for shop owners. The new solution offers additional BI services for performing data analytics and strengthening the position of brick-and-mortar stores. Participating shops can work together in order to increase sales and align marketing campaigns. Therefore, shopping data from 12 years, 55 shops, and 19,000 customers was analyzed.}}, author = {{Kucklick, Jan-Peter and Kamm, Michael Reiner and Schneider, Johannes and vom Brocke, Jan}}, booktitle = {{Proceedings of the 53rd Hawaii International Conference on System Sciences}}, keywords = {{brick-and-mortar stores, business intelligence, case study, loyalty program}}, title = {{{Extending Loyalty Programs with BI Functionalities A Case Study for Brick-and-Mortar Stores}}}, year = {{2020}}, } @article{35662, abstract = {{While the analysis and usage of data are increasing in importance, the application of sophisticated BI solutions in small stores is limited by available technical capabilities and financial resources. This study investigates how brick-and-mortar stores can benefit from an expansion of service functionalities of a cross-industry loyalty card provider. Digitalizing the loyalty program created new opportunities, while the analysis of shopping data of 13 years, 19,000 customers, and 55 shops empowered data-based decision support.}}, author = {{Kamm, Michael Reiner and Kucklick, Jan-Peter and Schneider, Johannes and vom Brocke, Jan}}, issn = {{1058-0530}}, journal = {{Information Systems Management}}, keywords = {{Customer loyalty, case study, brick-and-mortar stores, business intelligence, loyalty programs}}, number = {{4}}, pages = {{270--286}}, publisher = {{Informa UK Limited}}, title = {{{Data mining for small shops: Empowering brick-and-mortar stores through BI functionalities of a loyalty program1}}}, doi = {{10.1080/10580530.2020.1855486}}, volume = {{38}}, year = {{2020}}, } @article{4695, author = {{Debortoli, Stefan and Müller, Oliver and vom Brocke, Jan}}, isbn = {{0910-8327 (Print)$\backslash$n0910-8327 (Linking)}}, issn = {{18670202}}, journal = {{Business and Information Systems Engineering}}, keywords = {{Big data, Business intelligence, Competencies, Latent semantic analysis, Text mining}}, number = {{5}}, pages = {{289----300}}, title = {{{Comparing business intelligence and big data skills: A text mining study using job advertisements}}}, doi = {{10.1007/s12599-014-0344-2}}, year = {{2014}}, } @article{4696, author = {{vom Brocke, Jan and Debortoli, Stefan and Reuter, Nadine and Müller, Oliver}}, issn = {{15293181}}, journal = {{Communications of the Association for Information Systems}}, keywords = {{Advanced business analytics, Big Data, Business intelligence, IT business value, In-memory technology, OLAP, OLTP, Realtime analytics, Sentiment analysis}}, pages = {{151----167}}, title = {{{How In-Memory Technology Can Create Business Value: Lessons Learned from Hilti}}}, doi = {{10.17705/1CAIS.03407}}, year = {{2014}}, }