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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.
Toward a notation for modeling value driver trees: Classification development and research agenda
(2024)
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.
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.
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.
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.
Collective dynamic capabilities in innovation ecosystems - an analysis of the multi-actor process
(2023)
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.
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.
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 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.
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.
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.
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.
Tactical planning measures for sustainable and efficient international transportation networks
(2021)
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.
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.
What sparks academic engagement with society? A comparison of incentives appealing to motives
(2021)
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.
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.
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.
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.
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.
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 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.
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.
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.
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.
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.
Performing in Community-Academic Health Partnerships: Interplay of Clear, Difficult and Valued Goals
(2020)
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.
A major requirement for credit scoring models is to provide a maximally accurate risk prediction. Additionally, regulators demand these models to be transparent and auditable. Thus, in credit scoring, very simple predictive models such as logistic regression or decision trees are still widely used and the superior predictive power of modern machine learning algorithms cannot be fully leveraged. Significant potential is therefore missed, leading to higher reserves or more credit defaults. This paper works out different dimensions that have to be considered for making credit scoring models understandable and presents a framework for making ``black box'' machine learning models transparent, auditable and explainable. Following this framework, we present an overview of techniques, demonstrate how they can be applied in credit scoring and how results compare to the interpretability of score cards. A real world case study shows that a comparable degree of interpretability can be achieved while machine learning techniques keep their ability to improve predictive power.
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.
Gamification has been used in a wide variety of subject-specific education contexts. Examples of such usage in the Supply Chain Management (SCM) context include the oft-played beer distribution game, developed by MIT Sloan School of Management (Forrester, 1961), which simulates the coordination of typical problems in supply chain processes, promoting information sharing and collaboration throughout a supply chain (Sterman, 1984). Purchasing and Supply Management (PSM), a subset of this wider SCM area, focuses on the direct relationships between organisational buyers and suppliers, covering aspects such as establishing trust, identifying and selecting suitable suppliers, managing supplier performance and the overall relationship. A systematic review of the PSM gamified learning literature establishes that there has been limited research to date and that which there is tends to focus on quantitative representations of managing overall supply and demand, using wider SCM elements. This suggests that there are opportunities to gamify PSM learning, in particular focusing on the human element in PSM and developing soft skills, as strong buyer-supplier relationships can generate significant benefits to both parties. To provide a more focused PSM contribution, a second systematic literature review distils the relevant principles, techniques and processes to inform the development of two gamified PSM learning activities. Negotiation and supplier relationship management rely heavily on personal interactions and are both seen as key activities at different stages of the PSM process. The development of the two gamified learning activities is strengthened by being underpinned by a synthesis of the literature review’s key findings, ensuring they are domain-meaningful abstractions of reality, contain rewards and rankings based on clear objectives and have appealing gameplay. It is hoped that this paper provides a platform for future domain specific PSM research and will be of use to educators in this field in developing their own gamified learning.
Nowadays, the human-centric discipline of purchasing and supply management (PSM) is of strategic importance for firms’ success. Within the discipline, scholars address PSM professionals’ skills and provide practitioners with academic insights. Due to changes in the industry environment, changes in the working environment and the task of purchasing professionals are assumed. This paper aims to contribute to the PSM professional skills literature by defining current PSM professionals’ skill gaps as the difference between the acquired skill level and perceived skill importance. Findings show that current PSM professionals feel to be underqualified to abstract the full potential of professional relationships, as buyer-supplier relationships, due to current PSM professionals’ skill gaps.
The global development towards the Fourth Industrial Revolution, the so-called Industry 4.0, is steaming forwards. Where cyber-physical systems connect the physical and digital world, allowing for demand identification, without the need for direct human intervention. Further, Artificial Intelligence supports various parts of operative and strategic purchasing. The new purchasing environment forces purchasing professionals to develop new skills. Research is needed to identify appropriate skill sets. Based on a World-Café method with 82 purchasing professionals, a list of 32 essential future skills in purchasing is composed. Further, the identified skills are ranked and assigned to the roles of the direct and indirect material purchasers.