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Faculty
How do they do it? Understanding business model innovation in the context of disruptive innovation
(2018)
Hiding the Complexity of LBS
(2009)
In the context of Continuous Software Engineering, it is acknowledged as best practice to develop new features on the mainline rather than on separate feature branches. Unfinished work is then usually prevented from going live by some kind of feature toggle. However, there is no concept of feature toggles for Process-Driven Applications (PDA) so far. PDAs are hybrid systems consisting not only of classical source code but also of a machine-interpretable business process model. This paper elaborates on a feature development approach that covers both the business process model and the accompanying source code artifacts of a PDA. The proposed solution, Toggles for Process-Driven Applications (T4PDA), equipped with an easy to use modeling tool extension, enables the developer to safely commit unfinished work on model and source code to the project’s mainline. It will be kept inactive during productive deployments unless the feature is finally released. During an AB/BA crossover design experiment, the T4PDA approach, including the provided tool support, showed higher software quality, a faster development process, and contented developers.
Professional roles, including specific skills for each role, are a step towards higher professionalism and maturity within purchasing and supply management (PSM). The global development towards increasing digitalization, Industry 4.0, globalization, and increasing attention for corporate social responsibility force change within the purchasing organizations. Here, PSM's professional roles and skills are a good starting point to manage these changes by redefining professional roles organized by specific skills and responsibilities. For this reason, based on a systematic literature review and three World Cafés with 29 purchasing professionals, this study compiles a list of Industry 4.0 professional roles and skills in PSM.
In-depth analysis of customer journeys to broaden the understanding of customer behaviors and expectations in order to improve the customer experience is considered highly relevant in modern business practices. Recent studies predominantly focus on retrospective analysis of customer data, whereas more forward-directed concepts, namely predictions, are rarely addressed. Additionally, the integration of robotic process automation (RPA) to potentially increase the efficiency of customer journey analysis is not discussed in the current field of research. To fill this research gap, this paper introduces “customer journey mining”. Process mining techniques are applied to leverage digital customer data for accurate prediction of customer movements through individual journeys, creating valuable insights for improving the customer experience. Striving for improved efficiency, the potential interplay of RPA and customer journey mining is examined accordingly. The research methodology followed is based on a design science research process. An initially defined customer journey mining artifact is operationalized through an illustrative case study. This operationalization is achieved by analyzing a log file of an online travel agency functioning as an orientation for researchers and practitioners while also evaluating the initially defined framework. The data is used to train seven distinct prediction models to forecast the touchpoint a customer is most likely to visit next. Gradient-boosted trees yield the highest prediction accuracy with 43.1%. The findings further indicate technical suitability for RPA implementation, while financial viability is unlikely.
Experimental learning & reflection: how it promotes competence development in business education
(2019)
This study investigates the impact of Large Language Model (LLM) parameters, specifically
temperature and top P, on Supply Chain Risk Detection (SCRD). With a heightened focus
on Supply Chain Risk Management (SCRM) using AI, the research employs a Design of
Experiments (DoE) approach. The results reveal optimal temperature values for valid
assessments in SCRD applications. The study emphasizes the importance of tailored LLM
parameter settings, contributing insights for future research and practical applications in
enhancing supply chain resilience. Suggestions for incorporating Response Surface
Methodology (RSM) and refining the process are proposed for further investigation.
Ecosystem Emergence and Founding Conditions - Lessions Learned from an Imprinting Perspective
(2022)
The rise of ecosystem prominence has provided several definitions of how we understand ecosystems nowadays. In this context, several scholars have considered influencing factors for ecosystem emergence. This paper addresses this consideration and analyzes the salient characteristics of different ecosystem types and their potential persistence since ecosystem founding to improve the understanding of emergence. We applied a three-step approach (1) identifying ecosystem types based on bibliometric analysis, (2) exploring salient characteristics per ecosystem type using qualitative content analysis and (3) deriving founding conditions from the salient characteristics following a conceptual approach. Based on a bibliometric analysis, we identified business/innovation, entrepreneurial and service ecosystems. In a second step, we developed salient characteristics within the themes of structure, power constellation/interdependencies and governance by inductive coding. As we identified a significant difference in alignment structure, we analyzed if alignment structure persists since ecosystem origin and explains why ecosystems differ. We analyzed potential pairings between alignment structure and their respective founding condition for every ecosystem type. With the alignment structures’ persistence, we can better understand why ecosystem types differ.
To increase maturity within purchasing and supply management (PSM), future purchasing skills are needed based on the technological development towards Industry 4.0. Past research, eg, the work of Bals, Schulze, Kelly, and Stek (2019), started to address this issue based on literature review and interview studies. However, a detailed description of these skills is missing. Utilizing a real-time Delhi study with 45 experts within the PSM field, nine future purchasing skills have been elaborated. Identified skills connect to the maturing and emerging technologies within purchasing and provide a guideline towards Industry 4.0 in purchasing based on a human-centric perspective.
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.
Buying firms lack transparency about the supplier relationships in their networks. The applica-tion of dedicated tools such as Supply Network Mapping (SNM) can help to visualize and analyze these relationships. However, the impact of such tools on the purchasing performance has not been explored yet. Moreover, companies with different competitive strategies might have different motivations to use these tools. Therefore, this paper tests the impact of supplier relationship information and SNM on the purchasing performance on a large sample of 624 purchasers. A multi-group analysis in structural equation modeling estimates the impact of a cost leadership versus a differentiation strategy on cost saving and innovation performance. We show that information quality and SNM indeed improve the purchasing performance. Moreover, cost leaders use SNM if they know their supplier relationships with sub-suppliers, while innovation leaders use it if they know their supplier relationships with other customers. Hence, our results prove the usefulness of the SNM tool and give recommendations for its use depending on a company’s competitive strategy.
Particularly in times of disruptive changes, companies need an early warning system for risks in their supply chains to gain relevant information in a timely manner. Furthermore, they require suitable action plans and strategies to help react when a risk occurs. Based on an in-depth case study at an automotive parts supplier producing electronic systems and lighting components, this paper develops a holistic supply chain risk management framework. After investigating the specific supply chain risks to support critical parts management, standardised processes and procedures are developed to improve the preventive supply chain risk strategy cycle, as well as the reactive critical parts management cycle.
Complementor relationship management for Data-driven B2B platforms: Towards a Holistic approach
(2021)
In the so-called ecosystem economy, new platform-based business models evolve rapidly based on the prospects of digital technology. Especially in the B2B context, data-driven platforms are highly relevant. Thus far, little research has been conducted on the supply side of data-driven platforms and especially on service providers, the so-called complementors. Therefore, this paper offers insights into the various facets of complementor relationship management (CoRM). The paper aims to develop a framework for the management of complementors of data-driven B2B platforms. For empirical evidence, we draw on 14 semi-structured expert interviews with platform managers and complementors. The findings outline two big areas of CoRM and discuss distinct characteristics of partner management and technology management. For partner management the differentiation into open and closed platform needs to be taken into account for complementor relationship management. Moreover, our study reveals the key factors of technology management which lead from platform infrastructure to digital applications like digital twins or predictive maintenance.
This paper evaluates based on current literature, whether the versioning strategies “branch by feature” and “develop on mainline” can be used for developing new software features in connection with Continuous Delivery. The strategies will be introduced and possible applications for Continuous Delivery will be demonstrated and rated. A solution recommendation is finally given. It becomes evident that develop on mainline is the more recommendable method in form of “features toggles” or in case of bigger changes in form of “branch by abstraction” within the context of Continuous Delivery.
Disruption, Machine Learning, Internet of Things, Augmented Reality, Industry 4.0 and Rapid Prototyping are just a selection of the buzzwords that come up in connection with the rapid changes in the professional world and society brought about by digitalisation. As frequently occurs when buzzwords are used, their exact meaning is unknown, or remains unquestioned, but the use of them is nevertheless excessive. In this way, the buzzword ‘digital native’ assumes that an entire generation has a command of digital skills simply because they were born into this world and use digital media naturally. Which skills profiles this generation, and therefore a majority of today’s students, actually command, remains vague however, and is rarely explored systematically. The same is true of the specific formulation of necessary skills profiles in the digital world for higher education graduates. In the debate around higher education institutions, the description of the swift digital transition (with or without buzzwords) is not usually followed by a revision of existing curricula. This article describes strategic considerations for a better fit between the skills demanded of students and the challenges of the digital world.
BPMN-based Process-Driven Applications (PDA) require less coding since they are not only based on source code, but also on executable process models. Automated testing of such model-driven applications gains growing relevance, and it becomes a key enabler if we want to found their development on continuous integration (CI) techniques.While process analysts are typically responsible for test case specifications from a business perspective, technically skilled process engineers take the responsibility for implementing the required test code. This is time-consuming and, due to their often different skills and backgrounds, might result in communication problems such as information losses and misunderstandings. This paper presents a new approach which enables an analyst to generate executable tests for PDAs without the need for manual coding. It consists of a sophisticated model analysis, a wizard-based specification of test cases, and a subsequent code generation. The resulting tests can easily be integrated into CI pipelines.The concept is underpinned by a user-friendly tool which has been evaluated in case studies and in real-world implementation projects from different industry sectors. During the evaluation, the prototype proved a more efficient test creation process and a higher test quality.
Assessing serious games within purchasing and supply management education: an in-class experiment
(2021)
AI-based chatbots as enabler for efficient external knowledge management in public administration
(2024)
This study addresses the pressing issue of staff shortages in German public administrations through the lens of digitalization, focusing on the potential of AI-based chatbots to solve this problem by replacing human labour. Employing a Design Science Research Process (DSRP) methodology, the research synthesizes theoretical foundations and regulatory frameworks to develop a robust chatbot concept. The artifact presented is a comprehensive architectural framework integrating user-centric design, linguistic processing, and regulatory compliance. The proposed artifact navigates complex federal structures and diverse IT infrastructures, promoting accessibility and inclusivity. Implications suggest enhanced efficiency and accessibility in public service delivery for potentially increasing citizen satisfaction and decreasing employee workload. The study underscores the importance of legal compliance and the evolving regulatory landscape in AI deployment. Future research will involve prototyping and evaluating the artifact's performance and applicability throughout the course of the DSRP, thus contributing to the advancement of digital transformation in public administrations.
This paper focusses on effective teaching and learning methods in the context of a larger project that aims to align objectives in higher education with employer requirements in the field of purchasing and supply management (PSM). The reason is that little is known about which specific skills and competencies of PSM professionals are needed outside academia and which learning objective higher education should incorporate to meet the practical PSM requirements of firms and organisations. Practice as well as literature share the understanding that PSM professionals need a well-balanced mixture of knowledge and soft-skills: the merely explicit know-what (codified knowledge), know-why (theory), know-how (method) and inter- & intrapersonal soft skills.
For a long time, a large number of top managers in listed companies have regarded communication with their shareholders as a necessary evil and now, in times of activist investors, are faced not only with the great challenges of opening up to shareholders and revealing their own corporate strategy, but also at the same time have to withstand the massive external pressure from activist investors, who are rarely majority shareholders. To achieve this, it is essential that a complete rethink-ing of the communication strategy of those responsible for the company takes place.
This paper uses the findings from a literature review and series of expert interviews to develop a richer and Purchasing and Supply Management (PSM) context-specific perspective of the different key techniques, tools and principles that can be used to develop gamified learning to enhance the skills required by PSM professionals in dealing with current and future challenges, such as the transformation to Industry 4.0. It also provides further details of the different stages of implementing gamified learning, which can enhance the success of any such provision.
A COMPREHENSIVE ACTIVE-BASED LEARNING ENVIRONMENT FOR MANAGEMENT EDUCATION: AN EVALUATIVE STUDY
(2017)
There seems to be a strong distinction between what most business schools prepare their students for and what practicing managers actually do in their professional life [1]. Business education, in general, sees management as analytical and scientific, when empirical evidences indicate that the practicing manager repertoire is comprised not only of analysis but mainly of the development of solutions to illdefined problems [2].
Moreover, the globalization of the economy and the shift from a manufacturing to an informationbased society have led to significant changes in the conditions of work; with post-industrial economies
living an era of continuous market change and creative destruction [3], [4]. This scenario increases the array of responsibilities of higher education institutions which, in addition to providing disciplinary knowledge, should develop in students non-disciplinary competences such as decision-making, problem-solving, interpersonal communication, etc. As argued by Zlatkin-Troitschanskaia, et al. [5],
the development of such competences - sometimes referred as transversal or generic - are increasingly relevant in a society facing constant changes, since they are adaptable to various contexts enhancing the relevancy and the employability of students.
Under this perspective, a change in management education is needed. It should be oriented less on the training of business analysts and more on preparing future managers for solving the ill-designed
problems of real business practice. It is suggested that the focus of business education should move from ‘simply’ providing a body of domain-specific knowledge to give students the opportunity to apply
that knowledge under realistic contexts which better resembling management practice and foster the development of generic competences. In that respect, literature suggested that active-based learning
methods are best fitted for the ‘task’ [6]. More specifically, it points out to a series of ‘desirable’ elements that should be present if one wants to accurately replicate a management learning
environment. This author condensed those elements to form a theoretical proposition: that to build powerful management learning environments one needs to offer students the opportunity to
collectively engage in a series of continuous real-world experiences in a process permeated by careful reflection in and on the action.