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The ecosystem concept has attracted attention in information system research to explain business competition, innovation and many other emerging phenomena. Existing studies focus more on a single ecosystem type or a single ecosystem goal and pay little attention to the ecosystem’s evolution. The objective of the study is to investigate the factors that impact the evolution of the information ecosystem (IE) to gain a better understanding of strategic thinking.

The IE involves many actors, so the multi-case study approach is conducted with purposeful sampling to recruit all the significant ecosystem actors. The collected qualitative data are analyzed by coding data, exploring data relationships and structuring pattern steps; institutional theory is used as a theoretical framework.

The results demonstrate that industry practices, laws and regulations, new actors and the mimetic pressure of outsourcers drive the growth of the ecosystem. Strategy intention, cost pressure and normative pressure all contribute to the IE’s evolution.

The concept of ecosystems has attracted attention in information system research. The study investigates the factors contributing to the evolution of the IE from an institutional theory perspective. Our suggestion is that new players can find a niche in offering information technology (IT)/ information services (IS)-related solutions to survive in the ecosystem; however, they need to pay attention to the normative pressure.

The purpose of this paper is to understand value cocreation in service ecosystems from a multilevel perspective, uncovering value cocreation factors and outcomes at the micro, meso, and macro levels.

A Grounded Theory approach based on semi-structured interviews is adopted. The sample design was defined to enable the ecosystem analysis at its different levels. At the macro level was the Portuguese Health Information ecosystem. Embedded meso level units of analysis comprised eight health care organizations. A total of 48 interviews with citizens and health care practitioners were conducted at the micro level.

Study results enable a detailed understanding of the nature and dynamics of value cocreation in service ecosystems from a multilevel perspective. First, value cocreation factors are identified (resource access, resource sharing, resource recombination, resource monitoring, and governance/institutions generation). These factors enable actors to integrate resources in multiple dynamic interactions to cocreate value outcomes, which involve both population well-being and ecosystem viability. Study results show that these value cocreation factors and outcomes differ across levels, but they are also embedded and interdependent.

The findings have important implications for organizations that are ecosystem actors (like the Portuguese Ministry of Health) for understanding synergies among value cocreation factors and outcomes at the different levels. This provides orientations to better integrate different actor roles, technology, and information while facilitating ecosystem coordination and co-evolution.

This study responds to the need for a multilevel understanding of value cocreation in service ecosystems. It also illuminates how keystone players in the ecosystem should manage their value propositions to promote resource integration for each actor, fostering resource density and ecosystem viability. It also bridges the high-level conceptual perspective of Service-Dominant logic with specific empirical findings in the very important context of health care.

The purpose of this study is to identify and discuss the role of intelligent materials in the emergence of new business models based on the Internet of Things (IoT). The study suggests new areas for further research to better understand the influences of material intelligence on the business models in industry-wide service ecosystems.

The study uses data from an earlier study of intelligent materials in the steel industry networks. The insights are based on 34 qualitative interviews among 15 organizations in the industry. The data are reanalyzed for this study.

The observations from the steel industry show how material intelligence can be harnessed for value creation in IoT-based business ecosystems. The results suggest that not all “things” connected to the IoT need to be intelligent, if information related to the things are collected, stored and shared for collaborative value creation among the actors involved in the business ecosystem.

The study discusses how IoT deployments allow businesses to benefit from the velocity and variety of information associated with things and guides future research to study the ways in which value is created through IoT-enabled business models.

Rather than focusing on improving the efficiency of the supply network, the study presents new paths for competitive advantages in the new IoT ecosystems.

The study contributes to the mounting research on the IoT by identifying and discussing the critical aspects of how IoT can transform business models and supply networks within end-to-end ecosystems.

Data economy is a recent phenomenon, raised by digital transformation and platformisation, which has enabled the concentration of data that can be used in economic purposes. However, there is a lack of clear procedures and ethical rules on how data economy ecosystems are governed. As a response to the current situation, there has been criticism and demands for the governance of data use to prevent unethical consequences that have already manifested. Thus, ethical governance of the data economy ecosystems is needed. The purpose of this paper is to introduce a new ethical governance model for data economy ecosystems. The proposed model offers a more balanced solution for the current situation where a few global large-scale enterprises dominate the data market and may use oligopolistic power over other stakeholders.

This is a conceptual article that covers theory-based discourse ethical reflection of data economy ecosystems governance. The study is based on the premise of the discourse ethics where inclusion of all stakeholders is needed for creating a transparent and ethical data economy.

This article offers self-regulation tool for data economy ecosystems by discourse ethical approach which is designed in the governance model. The model aims to balance data “markets” by offering more transparent, democratic and equal system than currently.

By offering a new ethically justified governance model, we may create a trust structure where rules are visible and all stakeholders are treated fairly.

The purpose of this paper is to explain how ecosystems and platforms have evolved to manage customer information and to identify the management, research and teaching implications of this evolution.

This paper is based on research and industrial experience of two of the co-authors in customer relationship management, further developed with other co-authors in the field of business models, the research and teaching experience of the university authors and cross-functional literature reviews in the areas of strategy, marketing, economics, organizational behaviour and information management.

This paper shows that digitalization, cloud computing and new information-based platforms are beginning to change how customer information is being managed, creating new opportunities for improving marketing, customer relationship management and business strategy.

The impact of platforms on the management of customer information needs to be confirmed by primary empirical research.

This paper identifies the need for senior marketing management to examine closely how internal and external/public customer information platforms may enhance their capability for managing customers and setting new strategic directions.

The emergence of giant multi-sided platforms has clear implications for data protection and privacy, which need to be explored more in research.

This paper highlights the move to customer information platforms and identifies how senior managers should consider them as an option for better customer information management and as a basis for new business strategies.

The purpose of this paper is to propose a new ecological-issues-centered accounting research agenda, at the crossroads of accounting research and conservation science.

Based on a case study of the Natural Capital Project, the research examines the efforts and challenges of conservation practitioners regarding the use of evaluative information systems for conservation (EISC) in complex social and ecological contexts. It discusses why and how, to address these challenges, EISC promoters would benefit from theoretical and empirical insights coming from accounting research.

The paper suggests that the use of new information systems centered on organized collective action for biodiversity conservation should be regarded as a new type of accounting for the management of ecosystems, complementary to organization-centered biodiversity accounting and to ecosystem accounting at the national scale. A research agenda inspired by critical accounting should be developed for EISC design and use by: critically analyzing the organizational models currently underlying the use of new calculative practices for ecosystems; and developing new analytical and practical avenues on the basis of more explicit and powerful theories adapted to collective action for conservation perimeters.

The paper shows the importance of combining three domains of research and practice that are usually disconnected: the design and use of innovative information systems in biodiversity conservation research and practice; accounting research; and theories and conceptual models of collective action to resolve ecological challenges.

While providing users with important innovation resources, an enterprise's open innovation community also encounters numerous challenges. The purpose of this study is to develop and implement a set of evaluation systems that can identify the ecological characteristics of open innovation communities. The ultimate goal is to provide guidance for the construction and establishment of these communities.

Firstly, from the perspective of information ecology, according to the connotation requirements of the four information elements of “people, information, technology and environment” in the information ecosystem, this paper determines the evaluation indicators of enterprise's open innovation community from the aspects of integrity and dynamics. Then, based on the improved analytic hierarchy process, the weight of each index is calculated, and a complete evaluation system of open innovation community is established. Finally, the fuzzy comprehensive evaluation method is used to conduct empirical research on Haier Open Partnership (HOPE) platform, analyze its ecological situation and existing problems and put forward the corresponding construction recommendations.

The application of HOPE platform shows that the evaluation index system built in this study has good applicability, and the whole research process and research method have certain reference value for future studies. At the same time, the study found that the HOPE platform has good ecological characteristics, but there are also some problems. This study can directly promote the construction of the platform.

This paper, for the first time, combines the information ecology theory with the open innovation community. The results demonstrate that the open innovation community is an information ecosystem, which can be evaluated ecologically. Furthermore, to ensure the calculation's scientific accuracy, the index weight is determined by constructing a judgment matrix based on expert questionnaires.

This study aims to investigate how, in forming their policy towards open data (OD), art museums interact with the OD ecosystems they are part of, comprising internal and external components such as cultural policy, legal frameworks, user groups and economic conditions and incentives.

The authors structure their research as a multiple case study based on three OD ecosystems, each defined by a mid-sized European art museum at its centre. Qualitative analysis of the case studies proceeds from interviews with museum management staff and policy-related agencies in three European countries, in addition to document analysis.

The results of this study suggest that museums are sensitive towards their environments and respond to their ecosystem based on what is communicated within their networks. However, museums are not effective in communicating with their users, limiting the informational interdependence necessary for well-functioning OD ecosystems. EU policy appears to be a driving force along with national financial incentives, though institutional conditions are limiting progress. Advancing the field relies instead on an epistemological shift to understand the museum as part of a larger information network.

As the first comparative case study of art museum OD ecosystems that the authors are aware of, the study provides a qualitative analysis of the complex dynamics impacting OD policy within the mid-sized art museum. The authors identify specific dynamics that are thus far restricting further development of the OD ecosystem of the mid-sized European art museum.

Big Data (BD) is not only a quintessential part of many economic activities but also has evolved into a veritable business ecosystem. However, most Big Data ecosystem (BDE) models have a technical, bottom-up focus and mostly lack the capability for a broad socioeconomic analysis. This paper identifies the Millennium Ecosystem Assessment (MA) as a useful, operational framework and uses a metaphorical analogy to adapt it for the BDE. The top-down approach adopted here allows for seeing the big picture of the BD ecosystem. Meeting “end-user needs” is the main objective of the proposed BDE framework.

The methodology of this paper consists of two parts. First, the MA is adapted for the BDE through a metaphorical analogy. Then, to operationalize and validate the proposed framework, it is applied to an emerging BD ecosystem.

In total, four types of services are offered in the BD ecosystem: provisioning information and products; regulating; cultural and supporting services. Direct and indirect drivers of change impact ecosystem processes such as BD service provision. Based on the assessment results, interventions can be devised to remedy problems, sustain the ecosystem or accelerate growth. The proposed BDE assessment framework is applied to an emerging BDE as an example of operationalization and validation of the proposed BDE framework.

The strengths of the proposed BDE framework is that, in contrast to existing frameworks that are technical and bottom-up, it is constructed top-down by a metaphorical analogy from the proven MA framework. It is a generic framework with the ultimate objective of meeting the “end-user needs” and does not focus on a single sector or firm. Also, the proposed BDE framework is multi-faceted and considers broad socioeconomic issues such as regulating, cultural and supporting services and drivers of change.

This paper aims to analyse the open data business models (ODBMs) as a source of knowledge and innovation to generate economic and social value. A framework for understanding ODBMs is presented. First, the knowledge structure of the ODBMs literature is identified. Second, a conceptual model for analysing the ODBMs is proposed. And finally, the future trends in ODBMs research are discussed.

In this paper, co-word analysis is performed to identify the topics related with ODBMs.

The ODBMs structure of knowledge is articulated in five themes: business model, smart city, business ecosystem, decision-making and innovation. Based on these results, a five-step model for analysing ODBMs is proposed. Finally, a discussion of the future trends of ODBMs focussed on a knowledge management perspective, open data ecosystems and business intelligence is presented.

The paper presents a picture of what, where, for whom and for what ODBMs have been studied and develops a new model to explain the value creation process of ODBMs. Taking a step further, applying the principles and models of knowledge management and business intelligence to ODBMs is also recommended in order to transfer and transform open data into valuable knowledge that can be used for developing apps. In that context, the importance of encouraging collaboration between different agents in the so-called open data ecosystem is presented.