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The use of augmented reality (AR) in outbound logistics is associated with potentially strong stimuli for cost savings and throughput time. Nevertheless, the benefits of AR compared to conventional methods require a holistic analysis for investment decision making. Until now, research has only assessed case-study-related potentials and selected aspects of the technology. This paper answers the following research questions: How can the economic efficiency of AR in the packing process be quantified by utilizing a holistic model of value drivers? How can AR be technically implemented for packing processes in outbound logistics? What economic profit results from the use of AR technology in a case company’s packing process?
The presented model enables the investment decision to be supported based on economic value added (EVA), thereby providing an assessment of value drivers in packing systems. Cost drivers are identified on the basis of the Supply Chain Operations Reference (SCOR) process model. The technical and economic validation of the model was carried out by means of an empirical study: Expert interviews were conducted for validating the model elements. Data collection by a prototype at a mechanical-engineering company was used to calculate the value contribution. The mapping of cause-effect relationships within the framework of EVA driver trees has proven itself in both the expert interviews and the prototype validation. The field experiment at the case company demonstrated a positive value contribution of AR, in particular regarding employee productivity, length and variance of throughput time, quality aspects, volume utilization, and quantity of packing material used.
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.
Virtual reality (VR) is starting to realize some of its promise as a tool to improve training effectiveness. However, research on VR for training and development is limited. Existing theories and models relating to organizational training and learning are infrequently used in the VR literature. A greater understanding of why VR works in the training context would help training designers create effective programs that leverage this continuously developing technology. This paper provides a typology of VR technologies specifically relevant to HR and integrates HR training frameworks and theory into findings on VR training from these other literatures. We specifically focus on immersive VR technology and seek to better understand reasons for the effectiveness of VR technologies for both training and assessment. We review findings, integrate related streams of research, and offer guideposts for those contemplating VR implementation in four important areas: training reactions in a VR context, VR-specific learning outcomes, opportunities for assessment using VR, and the effect of VR on training transfer. We conclude the paper by identifying a VR-training agenda for HR researchers.
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.
External sources of knowledge have become a necessary extension to internal innovation activities (Monteiro, Mol and Birkinshaw, 2017; Rosenkopf and Nerkar, 2001). Collaborations with customers, suppliers, universities or even competitors are a promising way to extend the own knowledge base in order to increase the firm´s innovativeness (Felin and Zenger, 2014; Laursen and Salter, 2006). onsidering this potential set of external partners, suppliers seem to have the largest impact on product innovation (Un, Cuervo-Cazurra and Asakawa, 2010). Yet, suppliers’ innovative potential is limited as described in a case study by Gassmann, Zeschky, Wolff, and Stahl (2010), which further shows how a new venture supplier, commonly referred to as “startup”, has succeed at providing a truly innovative idea (a haptic feedback control device for automobiles). Therefore, startups as a specific knowledge provider have received growing attention (Weiblen and Chesbrough, 2015; Zaremba, Bode and Wagner, 2016). By collaborating with startups, corporations hope to benefit from the startups´ entrepreneurial characteristics, such as alertness, creativity, flexibility and willingness to take risks (Audretsch, Segarra and Teruel, 2014; Criscuolo, Nicolaou and Salter, 2012; Marion, Friar and Simpson, 2012).
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.
Process-Driven Applications (PDA) require less coding, for their business logic is defined by a business process model which can be executed by a process engine. However, inconsistencies between process model and dependent source code artifacts cause runtime errors and reduce development productivity. This paper targets at making the development of PDAs more efficient: It proposes a broader approach to statical analysis which also covers consistency constraints between model and code. When integrated into common analysis tools or a continuous integration pipeline, defects like broken code references or data-flow anomalies can be detected at an early stage without launching the entire application and its process interpretation engine. The approach is demonstrated by a prototype called viadee Process Application Validator (vPAV), which was developed for BPMN-based process models. The prototype has already been used in various BPM projects, attesting high benefit and potential.
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.
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.
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.
Process-Driven Applications flourish through the interaction between an executable BPMN process model, human tasks, and external software services. All these components operate on shared process data, so it is even more important to check the correct data flow. However, data flow is in most cases not explicitly defined but hidden in model elements, form declarations, and program code. This paper elaborates on data-flow anomalies acting as indicators for potential errors and how such anomalies can be uncovered despite implicit and hidden data-flow definitions. By considering an integrated view, it goes beyond other approaches which are restricted to separate data-flow analysis of either process model or source code. The main idea is to merge call graphs representing programmed services into a control-flow representation of the process model, to label the resulting graph with associated data operations, and to detect anomalies in that labeled graph using a dedicated data-flow analysis. The applicability of the solution is demonstrated by a prototype designed for the Camunda BPM platform.
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.
Globalization, digitalization and increasingly shortened lifecycles of consumer and business goods require companies to be continuously innovative. Under these domains of innovation, disruptive innovation has developed as a popular term amongst scholars and practitioners alike (Christensen, Raynor, & McDonald, 2015). In fact, the concept of disruptive technolo-gies was introduced to explain the failure of incumbent businesses in times of change (Bower & Christensen, 1995). Later, research broadened the concept towards disruptive innovations thereby going beyond technologies alone (Yu & Hang, 2010). Indeed, recent literature stresses the embracing business model that needs to be designed appropriately to make use of the technology and push it forward in the process of disruption. Subse-quently, current research concludes that disruption in its core is a “business model problem, not a technology problem” (Christensen, 2006).
Despite the recognition of the relevance of a firm’s business model for disruption, a clarifi-cation of the business model concept in the disruptive innovation process appears to be necessary in two dimensions. First, there is only limited knowledge regarding the actual design of (potential) disruptive business models. Second, from a dynamic perspective, less is known about how organizations manage the process of disruptive innovation until their business model yields a disruptive effect in the market.
The PhD research project aims at shedding light on the role of the firm’s business model in regard to the concept of disruptive innovation. Insights from this research project will not only add to a deeper understanding of disruptive innovation from a theoretical perspective but also deliver guidance for managers facing an increasingly changing environment.
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.
Experimental learning & reflection: how it promotes competence development in business education
(2019)
Mediale Lernangebote können dazu beitragen, Bildungsprozesse anzuregen (Kerres, 2018, S. 139). Sie tun es aber nicht per se. Es gibt demnach nicht eine beste Lehrmethode (Kerres, 2018, S. 139).
Der Aufwand für das Erstellen von Videos lohnt sich insbesondere dann, wenn keine Präsenzveranstaltungen – aus welchem Grund auch immer – angeboten werden können.
Heutzutage ist es leider immer noch wichtig, dass das Erledigen der Aufgaben für die Studierenden lohnend ist. Dies kann umgesetzt werden, indem die Studierenden entweder Klausurpunkte für das korrekte Erledigen der Aufgaben erhalten oder indem das erfolgreiche Absolvieren z.B. der Online-Tests als Leistungsnachweis anerkannt wird.
Die wöchentlichen Aufgaben stellen sicher, dass sich die Studierenden regelmäßig, in Etappen und selbständig mit den Inhalten auseinandersetzen und so das Erlernte langfristiger im Gedächtnis bleibt. Zudem erhalten sie, bedingt durch die automatische Korrektur, sofort eine Rückmeldung, was sicherlich motivationsfördernd ist.
Die Lehrenden haben mit Hilfe der digitalen Instrumente den Vorteil, dass sie diese lernfördernden Instrumente auch in sehr großen Lerngruppen ohne großen zusätzlichen Aufwand einsetzen können.
How do they do it? Understanding business model innovation in the context of disruptive innovation
(2018)
Study programme development is one of the most challenging processes
at universities since all faculty is involved. And in our experience, the redesign of already existing programmes seems to be even more difficult: Whereas innovative forces want to pick up new trends (e.g. digitalisation or other new teaching concepts) more conservative forces emphasises on values and refer to existing experience. Both positions are important and contextually right. Thus, the presented format provides a gradual framework to bridge the gap between both sides in an interactive and creative process.
Both sides are invited to negotiate the best possible result by using an unusual approach for university discussions, the benefit analysis method known e.g. from economics. After the negotiating activity, it should be obvious that a change of perspective is also helpful, if not necessary, to create a new or updated study programme. The practiced approach helps as well to recognise which limits for study programme development remain when visionary ideas are measured against reality.
This paper investigates the role of Dynamic Capabilities (DCs) in the process of Resource Recombination (RR) and thereby elaborates the
framework conditions for the recombination of resources in firms from the dynamic capability perspective. Investigating the role of a specific
set of DCs in the process of RR, this research addresses some existing shortcomings in the dynamic capability literature, where there is a
crucial need to better understand the inter-relationship between capabilities, the resource base of the firm, and innovation in the form of RRs.
Addressing this issue, this paper contributes to the resource and competence based research by presenting a conceptual model of the factors
influencing RR in firms. The findings suggest that regarding their role and effects towards RR in firms two different types of DCs can be
distinguished: Potential Building and Value Realizing DCs.
„Innovation für Society“
(2019)