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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 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.
Assessing serious games within purchasing and supply management education: an in-class experiment
(2021)
Supply chains often match the supply of labour to uncertain demand by using precarious workprecarious workers. This increases flexibility and lowers costs for the supply chain by shifting risk to the workers and costs to society. Supply chains are maximizing profits, often literally, on the backs of their workers by creating serious negative externalities for society. We address this issue using a powerpower perspective because powerpower is asymmetrically oriented against workers in many supply chain contexts. This allows us to identify examples of how to reverse this trend and shift powerpower back to workers. The goal is to get to where stakeholders understand the costs and limited benefits of precarity, where we can separate the notion of flexibility from low costs, and where through a combination of incentives, policy, social norms of ethical behaviour, and consumer action, we can get to a better place than where we are now.
An important, often overlooked group of workers that HR managers have trouble reaching are those intentionally disconnected from personal digital devices. That is, workers in manufacturing facilities, distribution centers, secure areas, or locations where employers ban workers from bringing their own devices. We explore the engagement problem for these intentionally disconnected workers. We outline a disruptive HR strategy in these work contexts. We then focus on implementation, testing a simple digital platform prototype that can serve as an entry for existing, disruptive HR management engagement tools (e.g. chatbots, HR analytics) in these settings. Our exploratory findings suggest engagement is a problem for these workers and these simple tools can be an effective strategy to help HR managers improve engagement. We conclude that simple digital solutions aimed at engaging this underserved segment of the workforce can have disruptive yet positive effects for workers, HR managers and shareholders.
This study investigates the role of individual differences in channel choice and switching behavior in a multichannel environment using latent class analysis on data from 1512 customers. Psychographic variables from five domains (risk attitudes, cognitive ability, motivation, personality, and decision-making style) serve as covariates for multichannel customer behavior. We identify six segments that differ significantly on six psychographic variables (readiness to take risks, need for cognition, autotelic and instrumental need for touch, and rational and intuitive decision-making styles). The results advance the theory-building of multichannel customer behavior and present insights for proactively managing customer journeys of distinct segments.
Toward a notation for modeling value driver trees: Classification development and research agenda
(2024)
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.
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.
The urge for personalisation and the rise of technological advancements
in the 21st century is pushing for more innovative marketing strategies. As such, this dissertation examines the impact of personality-tailored
campaigns (PTC) and how it affects purchasing decisions among
Generation Z, focusing on theoretical and practical implications.
A conceptual framework for the process of personality-tailored marketing has been developed to provide tangible value for businesses of
various industries in particular the fragrance, smartphone, and food
industry.
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.
Collective dynamic capabilities in innovation ecosystems - an analysis of the multi-actor process
(2023)
Experimental learning & reflection: how it promotes competence development in business education
(2019)
This research case study presents a novel way to study the development and growth of a multi-sided disruptive platform built on digital technologies. The corresponding business model unfolds industry-changing dynamics eventually changing competition logic in established markets. Despite the appeal of those models, developing and managing such a multi-sided disruptive platform is challenging because multiple platform sides need to be strategically aligned to develop along a disruptive path. Hence, scholars and practitioners are increasingly debating about the dynamics arising in the development and growth of such platforms. The focal case study discusses a research project which contributes to those debates:
This case study discusses how we used topic modeling and qualitative content analysis to make sense of a large amount of historical data from and about multiple platform sides to understand the strategic management and alignment mechanisms that unfolded over time. We discuss how we studied an entrant that was spun off from an established catalog retailer and is steering a multi-sided disruptive platform in the German fashion retail industry. We present how we faced the challenges of collecting data from multiple platform sides and how we used topic modeling to overcome data asphyxiation (i.e. difficulties in making sense of an overwhelming amount of qualitative data). Readers of this case study are equipped with practical insights about a) studying the development of multi-sided platforms over time, and b) using topic modeling and qualitative content analysis as complementing methodological approaches.
Automated regression tests are a key enabler for applying popular continuous software engineering techniques. This paper focuses on testing BPMN-based Process-Driven Applications (PDA). When evolving PDAs, the affected test cases must be identified and co-evolved as well. In this process, affected test cases can be overlooked, misunderstandings may occur during communication between different roles involved, and implementation errors can arise. Regardless of possible error sources, the entire test migration process is time-consuming. This paper presents a new semi-automated test migration process for PDAs. The concept builds on previous work on creating regression tests using a no-code approach. Our approach identifies the modifications of the PDA and classifies their impact on previously defined tests. The classification indicates whether existing test code can be migrated automatically or whether a manual revision becomes necessary. During an AB/BA experiment, the concept and the developed prototype proved a more efficient test migration process and a higher test quality.
Background
Community–academic health partnerships (CAHPs) have become increasingly common to bridge the knowledge-to-practice gap in health care. Because working in such partnerships can be excessively challenging, insights into the individual-level enablers of high performance will enable better management of CAHPs.
Purpose
Steered by the goal-setting theory, this study examined the relations between goal clarity, goal stress, goal importance, and their interactions on perceived project performance among individuals working in CAHPs’ constituting projects.
Methodology
Using a convergent mixed-method research design, online survey data were collected from 268 participants working in a variety of CAHP projects in three German-speaking countries. We tested the hypotheses using structural equation modeling, after which thematic analysis was carried out on the 209 open-ended responses.
Results
CAHP project performance was positively associated with goal clarity and negatively associated with goal stress. A three-way interaction analysis showed that when goal importance was high, the relationship between goal clarity and project performance remained positive regardless of the level of goal stress. The qualitative data corroborate this finding.
Conclusion
In CAHP projects, high goal importance offsets the negative effect of goal stress on project performance, indicating that workers who perceive the project goals as important can manage the stress associated with demanding goals better.
Practice Implications
To achieve high project performance in CAHPs, organizational and project leaders should (a) set clear project goals, (b) facilitate project workers in dealing with stress resulting from overly demanding goals, and (c) emphasize the importance of the project goals, especially when goal stress is high.
Purpose
Combining the goal-setting and job demands-resources (JD-R) theories, we examine how two project resources, collaborative project leadership and financial project resources, enhance high project performance in community-academic health partnerships.
Design/methodology/approach
With a sequential explanatory mixed-method research design, data were collected through a survey (N = 318) and semi-structured interviews (N = 21). A hypothesised three-path mediation model was tested using structural equation modelling with bootstrapping. Qualitative data were examined using thematic analysis.
Findings
Project workers’ hope, goal-commitment and -stress: (1) fully mediate the hypothesised relationship between highly collaborative project leadership and high project performance; and (2) partially mediate the relationship between financial project resources and high project performance. The qualitative data corroborate and deepen these findings, revealing the crucial role of hope as a cognitive-motivational facilitator in project workers’ ability to cope with challenges.
Practical implications
Project leaders should promote project workers’ goal commitment, reduce their goal stress and boost project performance by securing financial project resources or reinforcing workers’ hope, e.g. by fostering collaborative project leadership.
Originality/value
The findings contribute to the project management and JD-R literature by considering the joint effects of project workers’ hope and two commonly studied project resources (collaborative project leadership and financial project resources) on high project performance. Moreover, we demonstrate the importance of the goal-setting and JD-R theories for understanding complex health-promotion projects connecting academic to community work.
To deepen our understanding of how project leaders can lead effectively in different community-academic health partnerships (CAHPs), we conducted an inductive, qualitative study through semi-structured interviews (N = 32) and analyzed the data with Grounded Theory approaches. By presenting a process model illustrating the cycle of effective leaders(hip) in CAHP projects, we contribute to the literature on CAHP, leadership development, and complexity leadership theory in three ways. Firstly, the model depicts the strategies enabling leaders to navigate typical project challenges and perform leadership tasks effectively. Secondly, we distill four beneficial qualities (i.e., adopting a proactive attitude, having an open and adaptive mindset, relying on peer learning and support, and emphasizing self-growth and reflexivity) which CAHP project leaders require to develop themselves into effective leaders. Thirdly, we illustrate leaders' dynamic developmental logics and processes of effective leadership and their contributions to better project functioning in diverse CAHPs.
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.
Startups have the potential to transform industries as they follow partly divergent business strategies and have the ability to develop new innovative products. The evolving fields of digitalization, sustainability and urbanization highlight the direction of change. Due to enormous time pressure and lack of knowledge, corporations rely heavily on external sources of knowledge to increase innovativeness. Therein, startups take a special role. Joint R&D projects, investments or strategic buyer-supplier agreements with startups grant corporations access to their innovative technologies. This paper gives insights into the organization of search processes to identify innovative startups and highlights approaches to initiate collaborations. Therefore, a multiple-case study among automotive OEMs and suppliers was conducted. The research ends with organizational structures, an identification process, and various instruments developed for the identification of startup innovations. Furthermore, propositions are made for a successful collaboration between startups and established corporations, displaying the role of purchasing in startup management, the need to take fast decisions, secure technical support by experts within their organization and build strong relationships with partners within their supply chain and new partners, as for example venture capitalists.
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.
Innovative business models for data-driven B2B platforms evolve rapidly based on the prospects of digital technology. In addition to the platform provider, service providers on the supply side of the digital platform - the so-called complementors - play an important role in the process of value creation. This paper highlights the complementors’ perspective on the different facets of complementor relationship management (CoRM) and answers the following research questions: From the perspective of a complementor, what are the main fields of CoRM for data-driven B2B platforms? What factors of influence comprise the reason complementors join a platform?
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.
In the so-called ecosystem economy, new platform-based business models evolve rap-idly based on the prospects of digital technology. In the B2B context especially, data-driven platforms are highly relevant. Thus far, little research has been conducted on service providers, the so-called complementors of data-driven platforms. Therefore, this paper represents just a starting point for gaining deeper insights into the different facets of complementor management. For empirical evidence, we draw on semi-structured expert interviews with platform managers. The findings outline the distinct characteristics of open and closed platforms which need to be taken into account for complementor management. Moreover, the paper reveals a number of differences in managing suppliers compared to managing complementors. In addition, our study shows that the key factors influencing complementor management include platform openness, partnership intensity, strategic fit, and market structure respectively poten-tial.
In the so-called ecosystem economy, new platform-based business models evolve rapidly based on the prospects of digital technology. Thus far, little research has been conducted on the supply side of digital platforms which also explains the lack of empirical evidence. We develop a framework, categorise complementors, and analyse the main factors of influence for the evaluation and selection of complementors. For our analysis, we consider both industrial IoT platforms as well as financial services platforms. In addition, we use an explorative research design and conduct semi-structured interviews to contribute to this research field. Top-level managers of digi-tal platforms in both industries were interviewed as experts. In addition, the study also considered secondary data to increases the overall reliability and validity in terms of triangulation. As a result, our study reveals both a number of similarities and differences with regard to complementor management for industrial IoT- and financial services platforms.
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.
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.
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.
Specifying roles in purchasing and supply management in the era of Industry 4.0: A Delphi study
(2021)
New technologies and systems within the field of purchasing and supply management (PSM) call forth responsibilities and require expertise. Moving towards Industry 4.0 in purchasing, increasing attention on specialization within talent and skills, where human capital is needed to exploit the full potential of technologies. Based on an internet-based real-time Delhi study with 47 experts within the PSM field, six future purchasing roles have been defined and elaborated. These future roles connect to the maturing and emerging technologies within the purchasing field and provide a guideline to further develop towards Industry 4.0 in purchasing based on a human-centered evolutionary approach.
Identifying Start-Up Partners: Which Search Practices and Combination Strategies are Effective?
(2021)
Start-ups are an important source of novel knowledge and product ideas for incumbents. We investigate which search strategies are positively related to the successful search for start-ups. We identify search instruments and their various uses: intensive or broad; stand-alone or combinatory. Finding 11 search practices in the literature, we evaluate how these practices were used by 97 respondents from a cross-industry and cross-national sample. Our results show that searching broadly and intensively is positively related to a successful search for start-ups and to firms’ radical innovation capability. Specific tools that are positively related to search success are online contacts, desk research, external scouting partners, and start-up pitch events. Decision tree analysis provides effective combinations of search practices that innovation managers and purchasing managers can use. Employing these search practice combinations, we make incumbents aware of the routines used in distant knowledge search. These practices are dynamic capabilities that help them to remain successful in high-velocity markets. In identifying these search practices, we contribute to the literature on innovation routines and dynamic capability research.
Purpose
Procurement professionals widely use purchasing portfolio models to tailor purchasing strategies to different product groups’ needs. However, the application of these approaches in hospitals and the impact of a pandemic shock remain largely unknown. This paper aims to assess hospital purchasers’ procurement strategies during the COVID-19 pandemic, the effects of factor-market rivalry (FMR) on strategies and the effectiveness of purchasing portfolio categorizations in this situation.
Design/methodology/approach
This qualitative study of hospital purchasing in the Netherlands is supported by secondary data from official government publications. Semi-structured interviews were conducted with 13 hospital purchasers at large hospitals. An interpretative approach is used to analyze the interviews and present the results.
Findings
The findings reveal that product scarcity forces purchasers to treat them as (temporary) bottleneck items at the hospital level. The strategies adopted largely aligned with expected behavior based on Kraljic’s commodity management model. Adding the FMR perspective to the model helped to further cluster crisis strategies into meaningful categories. Besides inventory management, increasing supply, reducing demand and increasing resource coordination were the other common strategies. An important finding is that purchasers and governments serve as gatekeepers in channeling FMR, thereby reducing potential harmful competition between and within hospitals.
Social implications
The devastating experience of the COVID-19 pandemic is unveiling critical weaknesses of public health-care provision in times of crisis. This study assesses the strategies hospital purchasers apply to counteract shortages in the supply chain. The findings of this study emphasize the importance of gatekeepers in times of crisis and present strategies purchasers can take to assure the supply of resources.
Originality/value
No research has been conducted on purchasing portfolio models and FMR implications for hospitals during pandemics. Therefore, the authors offer several insights: increasing the supply risk creates temporary bottleneck strategies, letting purchasers adopt a short-term perspective and emphasizing the high mobility of commodities in the Kraljic commodity matrix. Additionally, despite more collaboration uncovered in other studies regarding COVID-19, strong rivalry arose at the beginning of the pandemic, leading to increased competition and less collaboration. Given such increased FMR, procurement managers and governments become important gatekeepers to balance resource allocation during pandemics both within and between hospitals.