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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.
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.
Multi‐sided platforms are becoming increasingly relevant in understanding industry changes. The literature has focused on the inception and growth of platforms, neglecting how entrants develop and grow disruptive platforms. To address this shortcoming, we study 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 conduct a longitudinal study on how the entrant leverages the relationships with its multiple platform sides during 2014–2019 by analyzing secondary data using topic modeling and qualitative content analysis. We propose three levers: (1) “guarded inception,” which is the collaboration with a knowledgeable partner unaffected by disruption to quickly overcome the chicken‐and‐egg problem; (2) “activating force multipliers,” which is the strategic orchestration of complementors being contractually tied to the entrant and working to extend the entrant's value network. Enabled by these two levers, the entrant was (3) “building on others” to develop the platform along a disruptive path while circumventing internal limitations and external resistance. We contribute to the intersection of the literature strands on platform and disruptive innovation by showing how the entrant strategically leveraged its different platform sides over time to develop and grow a disruptive platform.
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.
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.
Purpose:
Industrial revolutions have been induced by technological advances, but fundamentally changed business and society. To gain a comprehensive understanding of the fourth industrial revolution (I4.0) and derive guidelines for business strategy, it is, therefore, necessary to explore it as a multi-facet phenomenon. Most literature on I4.0, however, takes up a predominantly technical view. This paper aims to report on a project discussing a holistic view on I4.0 and its implications, covering technology, business, society and people.
Design/methodology/approach:
Two consecutive group discussions in form of academic world cafés have been conducted. The first workshop gathered multi-disciplinary experts from academia, whose results were further validated in a subsequent workshop including industry representatives. A voting procedure was used to capture participants perspectives.
Findings:
The paper develops a holistic I4.0 vision, focusing on five core technologies, their business potential, societal requests and people implications. Based on the model a checklist has been developed, which firms can use a tool to analyze their firm’s situation and draft their industry 4.0 business strategy.
Originality/value:
Rather than focusing on technology alone – which by itself is unlikely to make up for a revolution – this research integrates the entire system. In this way, a tool-set for strategy design results.
The Relevance of Problem-based Learning for Policy Development in University-Business Cooperation
(2016)