@incollection{BensbergBuscherCzarnecki2019, author = {Bensberg, Frank and Buscher, Gandalf and Czarnecki, Christian}, title = {Digital transformation and IT topics in the consulting industry: a labor market perspective}, series = {Advances in consulting research : recent findings and practical cases}, booktitle = {Advances in consulting research : recent findings and practical cases}, editor = {Nissen, Volker}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-95998-6}, doi = {10.1007/978-3-319-95999-3_16}, pages = {341 -- 357}, year = {2019}, abstract = {Information technologies, such as big data analytics, cloud computing, cyber physical systems, robotic process automation, and the internet of things, provide a sustainable impetus for the structural development of business sectors as well as the digitalization of markets, enterprises, and processes. Within the consulting industry, the proliferation of these technologies opened up the new segment of digital transformation, which focuses on setting up, controlling, and implementing projects for enterprises from a broad range of sectors. These recent developments raise the question, which requirements evolve for IT consultants as important success factors of those digital transformation projects. Therefore, this empirical contribution provides indications regarding the qualifications and competences necessary for IT consultants in the era of digital transformation from a labor market perspective. On the one hand, this knowledge base is interesting for the academic education of consultants, since it supports a market-oriented design of adequate training measures. On the other hand, insights into the competence requirements for consultants are considered relevant for skill and talent management processes in consulting practice. Assuming that consulting companies pursue a strategic human resource management approach, labor market information may also be useful to discover strategic behavioral patterns.}, language = {en} } @incollection{SchneiderWisselinkNoelleetal.2020, author = {Schneider, Dominik and Wisselink, Frank and N{\"o}lle, Nikolai and Czarnecki, Christian}, title = {Influence of artificial intelligence on commercial interactions in the consumer market}, series = {Automatisierung und Personalisierung von Dienstleistungen : Methoden - Potenziale - Einsatzfelder}, booktitle = {Automatisierung und Personalisierung von Dienstleistungen : Methoden - Potenziale - Einsatzfelder}, editor = {Bruhn, Manfred and Hadwich, Karsten}, publisher = {Springer Gabler}, address = {Wiesbaden}, isbn = {978-3-658-30167-5 (Print)}, doi = {10.1007/978-3-658-30168-2_7}, pages = {183 -- 205}, year = {2020}, abstract = {Recently, novel AI-based services have emerged in the consumer market. AI-based services can affect the way consumers take commercial decisions. Research on the influence of AI on commercial interactions is in its infancy. In this chapter, a framework creating a first overview of the influence of AI on commercial interactions is introduced. This framework summarizes the findings of comparing numerous customer journeys of novel AI-based services with corresponding non-AI equivalents.}, language = {en} } @incollection{CroonCzarnecki2021, author = {Croon, Philipp and Czarnecki, Christian}, title = {Liability for loss or damages caused by RPA}, series = {Robotic process automation : Management, technology, applications}, booktitle = {Robotic process automation : Management, technology, applications}, editor = {Czarnecki, Christian and Fettke, Peter}, publisher = {De Gruyter}, address = {Oldenbourg}, isbn = {9783110676778}, doi = {10.1515/9783110676693-202}, pages = {135 -- 151}, year = {2021}, abstract = {Intelligent autonomous software robots replacing human activities and performing administrative processes are reality in today's corporate world. This includes, for example, decisions about invoice payments, identification of customers for a marketing campaign, and answering customer complaints. What happens if such a software robot causes a damage? Due to the complete absence of human activities, the question is not trivial. It could even happen that no one is liable for a damage towards a third party, which could create an uncalculatable legal risk for business partners. Furthermore, the implementation and operation of those software robots involves various stakeholders, which result in the unsolvable endeavor of identifying the originator of a damage. Overall it is advisable to all involved parties to carefully consider the legal situation. This chapter discusses the liability of software robots from an interdisciplinary perspective. Based on different technical scenarios the legal aspects of liability are discussed.}, language = {en} } @incollection{BensbergAuthCzarnecki2021, author = {Bensberg, Frank and Auth, Gunnar and Czarnecki, Christian}, title = {Finding the perfect RPA match : a criteria-based selection method for RPA solutions}, series = {Robotic process automation : Management, technology, applications}, booktitle = {Robotic process automation : Management, technology, applications}, editor = {Czarnecki, Christian and Fettke, Peter}, publisher = {De Gruyter}, address = {Oldenbourg}, isbn = {978-3-11-067677-8}, doi = {10.1515/9783110676693-201}, pages = {47 -- 75}, year = {2021}, abstract = {The benefits of robotic process automation (RPA) are highly related to the usage of commercial off-the-shelf (COTS) software products that can be easily implemented and customized by business units. But, how to find the best fitting RPA product for a specific situation that creates the expected benefits? This question is related to the general area of software evaluation and selection. In the face of more than 75 RPA products currently on the market, guidance considering those specifics is required. Therefore, this chapter proposes a criteria-based selection method specifically for RPA. The method includes a quantitative evaluation of costs and benefits as well as a qualitative utility analysis based on functional criteria. By using the visualization of financial implications (VOFI) method, an application-oriented structure is provided that opposes the total cost of ownership to the time savings times salary (TSTS). For the utility analysis a detailed list of functional criteria for RPA is offered. The whole method is based on a multi-vocal review of scientific and non-scholarly literature including publications by business practitioners, consultants, and vendors. The application of the method is illustrated by a concrete RPA example. The illustrated structures, templates, and criteria can be directly utilized by practitioners in their real-life RPA implementations. In addition, a normative decision process for selecting RPA alternatives is proposed before the chapter closes with a discussion and outlook.}, language = {en} } @incollection{CzarneckiFettke2021, author = {Czarnecki, Christian and Fettke, Peter}, title = {Robotic process automation : Positioning, structuring, and framing the work}, series = {Robotic process automation : Management, technology, applications}, booktitle = {Robotic process automation : Management, technology, applications}, editor = {Czarnecki, Christian and Fettke, Peter}, publisher = {De Gruyter}, address = {Oldenbourg}, isbn = {978-3-11-067668-6 (Print)}, doi = {10.1515/9783110676693-202}, pages = {3 -- 24}, year = {2021}, abstract = {Robotic process automation (RPA) has attracted increasing attention in research and practice. This chapter positions, structures, and frames the topic as an introduction to this book. RPA is understood as a broad concept that comprises a variety of concrete solutions. From a management perspective RPA offers an innovative approach for realizing automation potentials, whereas from a technical perspective the implementation based on software products and the impact of artificial intelligence (AI) and machine learning (ML) are relevant. RPA is industry-independent and can be used, for example, in finance, telecommunications, and the public sector. With respect to RPA this chapter discusses definitions, related approaches, a structuring framework, a research framework, and an inside as well as outside architectural view. Furthermore, it provides an overview of the book combined with short summaries of each chapter.}, language = {en} } @incollection{CzarneckiHongSchmitzetal.2021, author = {Czarnecki, Christian and Hong, Chin-Gi and Schmitz, Manfred and Dietze, Christian}, title = {Enabling digital transformation through cognitive robotic process automation at Deutsche Telekom Services Europe}, series = {Digitalization Cases Vol. 2 : Mastering digital transformation for global business}, booktitle = {Digitalization Cases Vol. 2 : Mastering digital transformation for global business}, editor = {Urbach, Nils and R{\"o}glinger, Maximilian and Kautz, Karlheinz and Alias, Rose Alinda and Saunders, Carol and Wiener, Martin}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-80002-4 (Print)}, doi = {10.1007/978-3-030-80003-1}, pages = {123 -- 138}, year = {2021}, abstract = {Subject of this case is Deutsche Telekom Services Europe (DTSE), a service center for administrative processes. Due to the high volume of repetitive tasks (e.g., 100k manual uploads of offer documents into SAP per year), automation was identified as an important strategic target with a high management attention and commitment. DTSE has to work with various backend application systems without any possibility to change those systems. Furthermore, the complexity of administrative processes differed. When it comes to the transfer of unstructured data (e.g., offer documents) to structured data (e.g., MS Excel files), further cognitive technologies were needed.}, language = {en} } @incollection{StriebingMuellerSchraudneretal.2022, author = {Striebing, Clemens and M{\"u}ller, J{\"o}rg and Schraudner, Martina and Gewinner, Irina Valerie and Guerrero Morales, Patricia and Hochfeld, Katharina and Hoffman, Shekinah and Kmec, Julie A. and Nguyen, Huu Minh and Schneider, Jannick and Sheridan, Jennifer and Steuer-Dankert, Linda and Trimble O'Connor, Lindsey and Vandevelde-Rougale, Agn{\`e}s}, title = {Promoting diversity and combatting discrimination in research organizations: a practitioner's guide}, series = {Diversity and discrimination in research organizations}, booktitle = {Diversity and discrimination in research organizations}, publisher = {Emerald Publishing Limited}, address = {Bingley}, isbn = {978-1-80117-959-1 (Print)}, doi = {10.1108/978-1-80117-956-020221012}, pages = {421 -- 442}, year = {2022}, abstract = {The essay is addressed to practitioners in research management and from academic leadership. It describes which measures can contribute to creating an inclusive climate for research teams and preventing and effectively dealing with discrimination. The practical recommendations consider the policy and organizational levels, as well as the individual perspective of research managers. Following a series of basic recommendations, six lessons learned are formulated, derived from the contributions to the edited collection on "Diversity and Discrimination in Research Organizations."}, language = {en} } @incollection{SteuerDankertLeichtScholten2022, author = {Steuer-Dankert, Linda and Leicht-Scholten, Carmen}, title = {Perceiving diversity : an explorative approach in a complex research organization.}, series = {Diversity and discrimination in research organizations}, booktitle = {Diversity and discrimination in research organizations}, publisher = {Emerald Publishing Limited}, address = {Bingley}, isbn = {978-1-80117-959-1 (Print)}, doi = {10.1108/978-1-80117-956-020221010}, pages = {365 -- 392}, year = {2022}, abstract = {Diversity management is seen as a decisive factor for ensuring the development of socially responsible innovations (Beacham and Shambaugh, 2011; Sonntag, 2014; L{\´o}pez, 2015; Uebernickel et al., 2015). However, many diversity management approaches fail due to a one-sided consideration of diversity (Thomas and Ely, 2019) and a lacking linkage between the prevailing organizational culture and the perception of diversity in the respective organization. Reflecting the importance of diverse perspectives, research institutions have a special responsibility to actively deal with diversity, as they are publicly funded institutions that drive socially relevant development and educate future generations of developers, leaders and decision-makers. Nevertheless, only a few studies have so far dealt with the influence of the special framework conditions of the science system on diversity management. Focusing on the interdependency of the organizational culture and diversity management especially in a university research environment, this chapter aims in a first step to provide a theoretical perspective on the framework conditions of a complex research organization in Germany in order to understand the system-specific factors influencing diversity management. In a second step, an exploratory cluster analysis is presented, investigating the perception of diversity and possible influencing factors moderating this perception in a scientific organization. Combining both steps, the results show specific mechanisms and structures of the university research environment that have an impact on diversity management and rigidify structural barriers preventing an increase of diversity. The quantitative study also points out that the management level takes on a special role model function in the scientific system and thus has an influence on the perception of diversity. Consequently, when developing diversity management approaches in research organizations, it is necessary to consider the top-down direction of action, the special nature of organizational structures in the university research environment as well as the special role of the professorial level as role model for the scientific staff.}, language = {en} } @incollection{HinkeVervierBrauneretal.2022, author = {Hinke, Christian and Vervier, Luisa and Brauner, Philipp and Schneider, Sebastian and Steuer-Dankert, Linda and Ziefle, Martina and Leicht-Scholten, Carmen}, title = {Capability configuration in next generation manufacturing}, series = {Forecasting next generation manufacturing : digital shadows, human-machine collaboration, and data-driven business models}, booktitle = {Forecasting next generation manufacturing : digital shadows, human-machine collaboration, and data-driven business models}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-07733-3}, doi = {10.1007/978-3-031-07734-0_6}, pages = {95 -- 106}, year = {2022}, abstract = {Industrial production systems are facing radical change in multiple dimensions. This change is caused by technological developments and the digital transformation of production, as well as the call for political and social change to facilitate a transformation toward sustainability. These changes affect both the capabilities of production systems and companies and the design of higher education and educational programs. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these concepts, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the capabilities dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we discuss the benefits of capturing expert knowledge and making it accessible to newcomers, especially in highly specialized industries. The experts argue that in order to cope with the challenges and circumstances of today's world, students must already during their education at university learn how to work with AI and other technologies. This means that study programs must change and that universities must adapt their structural aspects to meet the needs of the students.}, language = {en} } @incollection{BraunerVervierBrillowskietal.2022, author = {Brauner, Philipp and Vervier, Luisa and Brillowski, Florian and Dammers, Hannah and Steuer-Dankert, Linda and Schneider, Sebastian and Baier, Ralph and Ziefle, Martina and Gries, Thomas and Leicht-Scholten, Carmen and Mertens, Alexander and Nagel, Saskia K.}, title = {Organization Routines in Next Generation Manufacturing}, series = {Forecasting Next Generation Manufacturing}, booktitle = {Forecasting Next Generation Manufacturing}, publisher = {Springer}, address = {Cham}, isbn = {978-3-031-07734-0}, doi = {10.1007/978-3-031-07734-0_5}, pages = {75 -- 94}, year = {2022}, abstract = {Next Generation Manufacturing promises significant improvements in performance, productivity, and value creation. In addition to the desired and projected improvements regarding the planning, production, and usage cycles of products, this digital transformation will have a huge impact on work, workers, and workplace design. Given the high uncertainty in the likelihood of occurrence and the technical, economic, and societal impacts of these changes, we conducted a technology foresight study, in the form of a real-time Delphi analysis, to derive reliable future scenarios featuring the next generation of manufacturing systems. This chapter presents the organization dimension and describes each projection in detail, offering current case study examples and discussing related research, as well as implications for policy makers and firms. Specifically, we highlight seven areas in which the digital transformation of production will change how we work, how we organize the work within a company, how we evaluate these changes, and how employment and labor rights will be affected across company boundaries. The experts are unsure whether the use of collaborative robots in factories will replace traditional robots by 2030. They believe that the use of hybrid intelligence will supplement human decision-making processes in production environments. Furthermore, they predict that artificial intelligence will lead to changes in management processes, leadership, and the elimination of hierarchies. However, to ensure that social and normative aspects are incorporated into the AI algorithms, restricting measurement of individual performance will be necessary. Additionally, AI-based decision support can significantly contribute toward new, socially accepted modes of leadership. Finally, the experts believe that there will be a reduction in the workforce by the year 2030.}, language = {en} }