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Article
Publication date: 14 June 2021

Sergey Yablonsky

To be more effective, artificial intelligence (AI) requires a broad overall view of the design and transformation of enterprise architecture and capabilities. Maturity models…

1093

Abstract

Purpose

To be more effective, artificial intelligence (AI) requires a broad overall view of the design and transformation of enterprise architecture and capabilities. Maturity models (MMs) are the recognized tools to identify strengths and weaknesses of certain domains of an organization. They consist of multiple, archetypal levels of maturity of a certain domain and can be used for organizational assessment and development. In the case of AI, quite a few numbers of MMs have been proposed. Generally, the links between AI technology, AI usage and organizational performance stay unclear. To address these gaps, this paper aims to introduce the complete details of the AI maturity model (AIMM) for AI-driven platform companies. The associated AI-Driven Platform Enterprise Maturity framework proposed here can help to achieve most of the AI-driven platform companies' objectives.

Design/methodology/approach

Qualitative research is performed in two stages. In the first stage, a review of the existing literature is performed to identify the types, barriers, drivers, challenges and opportunities of MMs in AI, Advanced Analytics and Big Data domains. In the second stage, a research framework is proposed to align company value chain with AI technologies and levels of the platform enterprise maturity.

Findings

The paper proposes a new five level AI-Driven Platform Enterprise Maturity framework by constructing a formal organizational value chain taxonomy model that explains a vast group of MM phenomena related with the AI-Driven Platform Enterprises. In addition, this study proposes a clear and precise description and structuring of the information in the multidimensional Platform, AI, Advanced Analytics and Big Data domains. The AI-Driven Platform Enterprise Maturity framework assists in identification, creation, assessment and disclosure research of AI-driven platform business organizations.

Research limitations/implications

This research is focused on the basic dimensions of AI value chain. The full reference model of AI consists of much more concepts. In the last few years, AI has achieved a notable drive that, if connected appropriately, may deliver the best of expectations over many application sectors across the field. For this to occur shortly in machine learning, especially in deep neural networks, the entire community stands in front of the barrier of explainability. Paradigms underlying this problem fall within the so-called eXplainable AI (XAI) field, which is widely acknowledged as a crucial feature for the practical deployment of AI models in industry. Our prospects lead toward the concept of a methodology for the large-scale implementation of AI methods in platform organizations with fairness, model explainability and accountability at its core.

Practical implications

AI-driven platform enterprise maturity framework can be used for better communicate to clients the value of AI capabilities through the lens of changing human-machine interactions and in the context of legal, ethical and societal norms.

Social implications

The authors discuss AI in the enterprise platform stack including talent platform, human capital management and recruiting.

Originality/value

The AI value chain and AI-Driven Platform Enterprise Maturity framework are original and represent an effective tools for assessing AI-driven platform enterprises.

Article
Publication date: 3 April 2020

Sergey Yablonsky

Ecosystems that support digital businesses maximize the economic value of network connections. This forces a shift toward platforms and ecosystems that are collaborative by nature…

1754

Abstract

Purpose

Ecosystems that support digital businesses maximize the economic value of network connections. This forces a shift toward platforms and ecosystems that are collaborative by nature by applying business models with multiple actors playing multiple roles. The purpose of this study is to show how the main concepts emerging from research on digital platform ecosystems (DPEs) could be organized in a taxonomy-based framework with different levels or dimensions of analysis. This study discusses some of the contingencies at these different levels and argues that future research needs to study DPEs across multiple levels of analysis. While this integrative framework allows the comparison, contrast and integration of various perspectives at different levels of analysis, further theorizing will be needed to advance the DPE research. The multidimensional framework proposed here involves the use of a multimethodological approach that incorporates a synergy of businesses, technological innovations and management methods to provide support for research in interrelationships across platform ecosystems (PEs) on a regular basis.

Design/methodology/approach

This paper proposes a new PE framework by constructing a formal taxonomy model that explains a vast group of phenomena produced by the PEs.

Findings

In addition to illustrating the PE taxonomy framework, this study also proposes a clear and precise description and structuring of the information in the ecosystem domain. The PE framework assists in identification, creation, assessment and disclosure research of platform business ecosystems.

Research limitations/implications

Because of the large number of taxonomy concepts (over 200), only main taxonomy fragments are shown in the paper.

Practical implications

The outcomes of this research could be used for planning, oversight and control over ecosystem management and the use of ecosystem’s knowledge-related resources for research purposes.

Originality/value

The PE framework is original and represents an effective tool for observing PEs.

Details

Kybernetes, vol. 49 no. 7
Type: Research Article
ISSN: 0368-492X

Keywords

Article
Publication date: 21 March 2023

Neeraj Singh and Sanjeev Kapoor

Although Agtech firms have promoted digital platforms for retailing farm supplies (RFS), farmers are sceptical while purchasing them online. As a result, they struggle to generate…

Abstract

Purpose

Although Agtech firms have promoted digital platforms for retailing farm supplies (RFS), farmers are sceptical while purchasing them online. As a result, they struggle to generate a sustained demand. Among other approaches, these platforms onboard complementors to become full-stack farming solution providers. Whether platform complementarity can induce farmers' trust remains ambiguous. Literature on network externality theory highlights that complementarity positively affects the perceived value for buyers. The sociotechnical systems literature indicates that perceived value is an antecedent of user trust. In this vein, the authors ask: Does perceived complementarity affect farmers' trust in the RFS platform? Alternatively, the Agtech firms augment the platform's look and feel to make the digital retail setting appear “normal” to farmers. The extant research on the social cognitive theory indicates that a retail setting conforming with the generalised expectancy of buyers harbours their trust. Against this backdrop, the authors ask whether situational normality affects farmers' trust in the RFS platform.

Design/methodology/approach

The study is based on a questionnaire survey of 212 Indian farmers using RFS platforms. The data were analysed using structural equation modelling (SEM) analysis.

Findings

This study establishes that platforms' complementarity and situational normality ameliorate farmer trust. The authors also identify the socioeconomic factors shaping the farmers' trust in platforms.

Research limitations/implications

The present study has taken all RFS together as a single umbrella category, which can be considered a limitation. Also, the study is based on the cross-sectional survey of RFS platform users; the farmers' attitudes are dynamic in nature and evolve over time; however, the temporal factors shaping the farmer attitudes have not been considered in this study.

Originality/value

The study establishes the epistemological relationship between complementarity, situational normality and farmers' trust in agricultural platforms.

Details

Journal of Agribusiness in Developing and Emerging Economies, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2044-0839

Keywords

Abstract

Details

Marketing in Customer Technology Environments
Type: Book
ISBN: 978-1-83909-601-3

Article
Publication date: 2 January 2023

Yanqing Shi, Hongye Cao and Si Chen

Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of…

Abstract

Purpose

Online question-and-answer (Q&A) communities serve as important channels for knowledge diffusion. The purpose of this study is to investigate the dynamic development process of online knowledge systems and explore the final or progressive state of system development. By measuring the nonlinear characteristics of knowledge systems from the perspective of complexity science, the authors aim to enrich the perspective and method of the research on the dynamics of knowledge systems, and to deeply understand the behavior rules of knowledge systems.

Design/methodology/approach

The authors collected data from the programming-related Q&A site Stack Overflow for a ten-year period (2008–2017) and included 48,373 tags in the analyses. The number of tags is taken as the time series, the correlation dimension and the maximum Lyapunov index are used to examine the chaos of the system and the Volterra series multistep forecast method is used to predict the system state.

Findings

There are strange attractors in the system, the whole system is complex but bounded and its evolution is bound to approach a relatively stable range. Empirical analyses indicate that chaos exists in the process of knowledge sharing in this social labeling system, and the period of change over time is about one week.

Originality/value

This study contributes to revealing the evolutionary cycle of knowledge stock in online knowledge systems and further indicates how this dynamic evolution can help in the setting of platform mechanics and resource inputs.

Details

Aslib Journal of Information Management, vol. 76 no. 1
Type: Research Article
ISSN: 2050-3806

Keywords

Case study
Publication date: 28 November 2022

Deepa Kumari and Ritu Srivastava

The learning outcomes are as follows:1. enable students to appreciate how a platform company can navigate through diminishing network effects;2. enable students to foresee the…

Abstract

Learning outcomes

The learning outcomes are as follows:

1. enable students to appreciate how a platform company can navigate through diminishing network effects;

2. enable students to foresee the downside of scaling up a platform business;

3. enable students to appreciate the trade-off between an efficiency-centric and a novelty-centric business model for platform businesses; and

4. enable students to create a platform business model canvas for a company.

Case overview/synopsis

The teaching case discusses the dilemma of Akshay Chaturvedi, the founder of Leverage Edu, an artificial intelligence-enabled platform for students seeking admission to foreign universities. It had received nearly US$9.6m in funding until December 2021.

Chaturvedi wanted to make the best use of his funds, but was torn between turning Leverage Edu into an “efficient platform” and transforming it into a “novelty-centric platform”. The teaching note attempts to resolve Chaturvedi’s dilemma by analyzing competitors using the platform canvas model and determining how Chaturvedi could create and use network effects to Leverage Edu’s advantage. The case is based on secondary data that is freely available in the public domain.

Complexity academic level

This case is intended for MBA Entrepreneurship students taking a platform business elective. It can also be used in faculty and management development programs under the banner “Technology and Platform Businesses”.

Supplementary materials

Teaching notes are available for educators only.

Subject code

CSS 3: Entrepreneurship.

Details

Emerald Emerging Markets Case Studies, vol. 12 no. 4
Type: Case Study
ISSN:

Keywords

Article
Publication date: 5 May 2015

Mingzhi Dong, Fabio Santagata, Robert Sokolovskij, Jia Wei, Cadmus Yuan and Guoqi Zhang

This study aims to provide a flexible and cost-effective solution of 3D heterogeneous integration for applications such as micro-electro-mechanical system (MEMS) applications and…

Abstract

Purpose

This study aims to provide a flexible and cost-effective solution of 3D heterogeneous integration for applications such as micro-electro-mechanical system (MEMS) applications and smart sensor systems.

Design/methodology/approach

A novel 3D system-in-package (SiP) based on stacked silicon submount technology was successfully developed and well-demonstrated by the fabrication and assembly process of a selected smart lighting module.

Findings

The stacked module consists of multiple layers of silicon submounts which can be designed and fabricated in parallel. The bonding and interconnecting process is quite simple and does not require complicated equipment. The 3D stacking design offers higher silicon efficiency and miniaturized package form factor. The submount wafer can be assembled and tested at the wafer level, thus reducing the cost and improving the yield.

Research limitations/implications

The embedding design presented in this paper is applicable for modules with limited number of passives. When it comes to cases with more passive devices, new process needs to be developed to achieve fast, inexpensive and reliable assembly.

Originality/value

The presented 3D SiP design is novel for applications such as smart lighting, Internet of Things, MEMS systems, etc.

Details

Microelectronics International, vol. 32 no. 2
Type: Research Article
ISSN: 1356-5362

Keywords

Article
Publication date: 1 July 1968

The Secretary of State—

Abstract

The Secretary of State—

Details

Managerial Law, vol. 4 no. 4
Type: Research Article
ISSN: 0309-0558

Abstract

Details

Platforms Everywhere: Transforming Organizations by Integrating Ecosystems in Business Design
Type: Book
ISBN: 978-1-80117-795-5

Article
Publication date: 5 June 2023

Nicholas Roberts and Inchan Kim

Although digital platforms have become important to organizations and society, little is known about how platforms evolve over time. This is particularly true for early-stage…

Abstract

Purpose

Although digital platforms have become important to organizations and society, little is known about how platforms evolve over time. This is particularly true for early-stage platforms provided by entrepreneurial firms competing in nascent markets. This study aims to investigate the relationship between a platform provider's mission and the evolution of its digital platform.

Design/methodology/approach

This study conducted an exploratory, multi-case study of startups in the emerging health/fitness wearables market over the period 2007 to 2016.

Findings

This study emerged two organizational mission constructs – consistency and specificity – and two evolutionary dynamics of digital platforms – unity and evolution rate. It also considered unity and evolution rate in terms of features created by the platform provider and features connected by external parties. This study found relationships between aspects of mission consistency and platform unity and identified relationships between aspects of mission specificity and platform evolution rates.

Originality/value

This study formalized findings into a set of theoretical propositions, thereby enriching the understanding of the relationship between organizational mission and digital platform evolution in nascent markets. This study provides new constructs and relationships that can be tested and refined in future research.

Details

Internet Research, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1066-2243

Keywords

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