scholarly journals Value Modeling for Ecosystem Analysis

Computers ◽  
2019 ◽  
Vol 8 (3) ◽  
pp. 68 ◽  
Author(s):  
Alejandro Arreola González ◽  
Matthias Pfaff ◽  
Helmut Krcmar

Scholars have proposed many approaches to represent and analyze value creation. Value creation in ecosystems such as platform ecosystems often relies on a specific structure of partner alignment. Value modeling techniques can improve the understanding of how ecosystem risks and non-generic complementarities determine value creation and the alignment structures required. First, we conceptualize ecosystem analysis as a tool for alignment in the context of business innovation. Then, we carry out a structured literature review to identify existing techniques, which could support ecosystem analysis. Further, we provide a comprehensive overview of the value modeling techniques and integrate our ecosystem analysis conceptualization with existing classification frameworks. This integrative framework allows researchers and scholars to identify techniques that suit specific needs in terms of internal alignment reach, tooling, innovation phase and ecosystem analysis. Our results show limited support for ecosystem analysis. Still we are able to identify techniques that can provide a useful conceptual or tooling basis to enable ecosystem analysis.

2019 ◽  
Vol 31 (1) ◽  
pp. 427-473 ◽  
Author(s):  
David Dann ◽  
Timm Teubner ◽  
Christof Weinhardt

PurposeA growing body of research from various domains has investigated Airbnb, a two-sided market platform for peer-based accommodation sharing. The authors suggest that it is due time to take a step back and assess the current state of affairs. This paper aims to conflate and synthesize research on Airbnb.Design/methodology/approachTo facilitate research on Airbnb and its underlying principles in electronic commerce, the authors present a structured literature review on Airbnb.FindingsThe findings are based on 118 articles from the fields of tourism, information and management, law and economics between 2013 and 2018. Based on this broad basis, the authors find that: research on Airbnb is highly diverse in terms of domains, methods and scope; motives for using Airbnb are manifold (e.g. financial, social and environmental); trust and reputation are considered crucial by almost all scholars; the platform’s variety is reflected in prices; and the majority of work is based on surveys and empirical data while experiments are scarce.Practical implicationsBased on the present assessment of studied topics, domains, methods and combinations thereof, the authors suggest that research should move toward building atop of a common ground of data structures and vocabulary, and that attention should focus on the identified gaps and hitherto scarcely used combinations. The set of under-represented areas includes cross-cultural investigations, field experiments and audit studies, the consideration of dynamic processes (e.g. based on panel data), Airbnb’s “experiences” and automated pricing algorithms and the rating distribution’s skewness.Originality/valueThis study provides a comprehensive overview of work on the accommodation sharing platform Airbnb, to the best of the auhtors’ knowledge, representing the first systematic literature review. The authors hope that researchers and practitioners alike will find this review useful as a reference for future research on Airbnb and as a guide for the development of innovative applications based on the platform’s peculiarities and paradigms in electronic commerce practice. From a practical perspective, the general tenor suggests that hotel and tourism operators may benefit from: focusing on their core advantages over Airbnb and differentiating features and aligning their marketing communication with their users’ aspirations.


2022 ◽  
Vol 6 (1) ◽  
pp. 10
Author(s):  
Matej Vuković ◽  
Stefan Thalmann

Industry 4.0 radically alters manufacturing organization and management, fostering collection and analysis of increasing amounts of data. Advanced data analytics, such as machine learning (ML), are essential for implementing Industry 4.0 and obtaining insights regarding production, better decision support, and enhanced manufacturing quality and sustainability. ML outperforms traditional approaches in many cases, but its complexity leads to unclear bases for decisions. Thus, acceptance of ML and, concomitantly, Industry 4.0, is hindered due to increasing requirements of fairness, accountability, and transparency, especially in sensitive-use cases. ML does not augment organizational knowledge, which is highly desired by manufacturing experts. Causal discovery promises a solution by providing insights on causal relationships that go beyond traditional ML’s statistical dependency. Causal discovery has a theoretical background and been successfully applied in medicine, genetics, and ecology. However, in manufacturing, only experimental and scattered applications are known; no comprehensive overview about how causal discovery can be applied in manufacturing is available. This paper investigates the state and development of research on causal discovery in manufacturing by focusing on motivations for application, common application scenarios and approaches, impacts, and implementation challenges. Based on the structured literature review, four core areas are identified, and a research agenda is proposed.


2016 ◽  
Vol 4 (2) ◽  
pp. 23-41 ◽  
Author(s):  
Marcos Mazzieri ◽  
Eduardo Dantas Soares

The term Big Data is being used widely by companies and researchers who consider your relevant functionalities or applications to create value and business innovation. However some questions arise about what is this phenomenon and, more precisely, how it occurs and under what conditions it can create value and innovation in business. In our view, the lack of depth related to the principles involved in Big Data and the very absence of a conceptual definition, made it difficult to answer these questions that have been the basis for our research. To answer these questions we did a bibliometric study and extensive literature review. The bibliometric studies were realized based in articles and citation of Web of Knowledge database. The main result of our research is the providing a conceptual definition for the term Big Data. Also, we propose which principles discovered can contribute with other researches  that intend value creation by Big Data. Finally we propose see the value creation through Big Data using the  Resource Based View as the main theory used for discuss that theme.


2019 ◽  
pp. 121-143
Author(s):  
Riccardo Resciniti ◽  
Federica De Vanna

The rise of e-commerce has brought considerable changes to the relationship between firms and consumers, especially within international business. Hence, understanding the use of such means for entering foreign markets has become critical for companies. However, the research on this issue is new and so it is important to evaluate what has been studied in the past. In this study, we conduct a systematic review of e-commerce and internationalisation studies to explicate how firms use e-commerce to enter new markets and to export. The studies are classified by theories and methods used in the literature. Moreover, we draw upon the internationalisation decision process (antecedents-modalities-consequences) to propose an integrative framework for understanding the role of e-commerce in internationalisation


2021 ◽  
Vol 13 (6) ◽  
pp. 3357 ◽  
Author(s):  
Amal Benkarim ◽  
Daniel Imbeau

The vast majority of works published on Lean focus on the evaluation of tools and/or the strategies needed for its implementation. Although many authors highlight the degree of employee commitment as one of the key aspects of Lean, what has gone largely unnoticed in the literature, is that few studies have examined in-depth the concept of organizational commitment in connection with Lean. With this narrative literature review article, our main objective is (1) to identify and analyze an extensive body of literature that addresses the Lean Manufacturing approach and how it relates to employee commitment, emphasizing affective commitment as the main type of organizational commitment positively associated with Lean, and (2) to highlight the management practices required to encourage this kind of commitment and promote the success and sustainability of Lean. This paper aims to provide a comprehensive overview that can help researchers and practitioners interested in Lean better understand the importance of employee commitment in this type of approach, and as well, to identify related research questions.


Mathematics ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 765
Author(s):  
Lorena Popa ◽  
Lavinia Sida

The aim of this paper is to provide a suitable definition for the concept of fuzzy inner product space. In order to achieve this, we firstly focused on various approaches from the already-existent literature. Due to the emergence of various studies on fuzzy inner product spaces, it is necessary to make a comprehensive overview of the published papers on the aforementioned subject in order to facilitate subsequent research. Then we considered another approach to the notion of fuzzy inner product starting from P. Majundar and S.K. Samanta’s definition. In fact, we changed their definition and we proved some new properties of the fuzzy inner product function. We also proved that this fuzzy inner product generates a fuzzy norm of the type Nădăban-Dzitac. Finally, some challenges are given.


2019 ◽  
Vol 62 (5) ◽  
pp. 436-443 ◽  
Author(s):  
Heitor O. Santos ◽  
Scott Howell ◽  
Conrad P. Earnest ◽  
Filipe J. Teixeira

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