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We detail the evolution of open interaction coding schemes that have long been used to capture behavioral indicators of the power and prestige order in status characteristics research. Although the theoretical variables ostensibly measured with these methods are few and explicit, the implementation of open interaction coding is not standardized and different projects have keyed on different specific behaviors. We argue that open interaction coding could benefit from the utilization of a more refined and standardized coding scheme. We offer precise operational definitions and some illustrations from our own recent projects in hopes of fostering more transparency in future research.

Platform, open/user innovation, and ecosystem strategies embrace and enable interactions with external entities. Firms pursuing these approaches conduct business and interact with environments differently than those pursuing traditional closed strategies. This chapter considers these strategies together highlighting similarities and differences between platform, open/user innovation, and ecosystem strategies. We focus on managerial and organizational challenges for organizations pursuing these strategies and identify four institutional logic shifts associated with these strategic transitions: (1) increasing external focus, (2) moving to greater openness, (3) focusing on enabling interactions, and (4) adopting interaction-centric metrics. As mature incumbent organizations adopt these strategies, there may be tensions and multiple conflicting institutional logics. Additionally, we consider four strategic leadership topics and how they relate to platform, open/user innovation, and ecosystem strategies: (1) executive orientation and experience, (2) top management teams, (3) board-management relations, and (4) executive compensation. We discuss theoretical implications, and consider future directions and research opportunities.

The purpose of this paper is to present a framework for empirically studying knowledge creation (KC) with phenomenological approach and propose that understanding interaction as play conceptualized by Hans-Georg Gadamer allows examining KC starting from the idea of a human being interacting in the events of co-creation. The presented framework is used to examine KC in a community of librarians and teachers collaborating to promote children’s joy of reading.

An ethnographic approach is applied to investigate knowledge-creating interaction in a working community. The triangulated data consist of ethnographic observations and video recordings of the community’s gatherings, its members’ interviews and produced documents.

The phenomenological conceptions of temporality of a human being and play are suitable for understanding being in the knowledge-creating interaction, as they give means to understand the meaningfulness of the past experiences, but promote an open attitude toward the future possibilities in a way which promotes KC. Studying interactive events allows understanding how KC can be examined as a collective accomplishment. The playful mode of being in the event was seen as a way to use the limited time available for interaction effectively.

The empirical study was conducted in one community, and further research is needed to test the developed approach in other contexts.

The results may be utilized to develop organizational circumstances, which promote KC by acknowledging the meaningfulness of interaction.

The study presents a novel way to conceptualize and examine KC as an experience and an event with phenomenological approach.

The authors review experimental procedures employed in studies of status and organization processes in task groups. Early studies employed face-to-face interaction in groups in both naturalistic and laboratory settings. The creation of an abstract interaction experiment that varied initial conditions in place for actors increased validity in theory tests. Recent studies have employed face-to-face groups to increase the range of situations to improve both internal and external validity. The authors include a brief history of how experiments have increased the range of explanatory application. The authors illustrate questions related to external validity with examples from research the authors and others have conducted.

Properties of experimental design are described. The authors employ aspects of the standard experiment in the expectation states research program to highlight designs used in studying task groups. The authors discuss features of face-to-face discussion studies designed to test aspects of expectation states theories. Errors in execution of data collection and principles of good design are explicated.

The authors identify procedures that may affect the quality of data in open interaction situations. Means to reduce errors and improve data quality are identified. The authors list issues that may affect data quality and suggest several ways to improve design and reporting of face-to-face studies.

The authors' effort to create a design road map for face-to-face studies will improve the quality of data collection and analysis. This will broaden the scope of research situations and improve the range of external validity of studies of status and organization of task groups.

The peer-to-peer perspective on open data is an interesting topic to research, taking into account that data-driven innovations and related startups are often developed independently by civic and private stakeholders in a highly collaborative manner and are tentatively beginning to directly compete with traditional e-government solutions, providing arguably better services to citizens and businesses. In this regard, the paper aims to further debate on the potential of such independent data-driven collaboration not only to transform the traditional mechanisms of public sector innovations but also provide more democratic ways to ensure greater transparency of government and its responsibility before the society.

The research is based on a cross-country case study, resorting to the content analysis of three demonstrative cases in the development of open data-driven projects, which specifically promote peer-to-peer communication between its stakeholders. In this regard, the case study itself relies heavily on the analysis of rich empirical data that the author collected during his field studies in the Northern European region in 2015–2017, particularly in Estonia, Finland and Sweden. The practical research itself consists of three major parts, which reflect peer-to-peer perspectives of correspondingly civic, public and private stakeholders through manifested examples of related independent projects in the area.

The paper's results demonstrate that the use of peer-to-peer mechanisms in advancing related public sector reforms allows to transform the traditional understanding of e-government phenomena in a conceptually new way. E-government or its last more political interpretation – from the perspective of its peers could be regarded not necessarily as a platform to provide digital public services but as a source of raw material for various third party projects in, respectively, civic, government and business peer-to-peer dimensions of such reforms. As a result, open data provides an interesting playground to change the very nature of public sector innovations in the area.

The choice of countries for research was motivated by purposive and convenience sampling because all these countries are situated in one region, have both similarities and differences in historical, political and socioeconomic backgrounds and, therefore, provide an ideal playground to investigate open data as a context dependable phenomenon. In this regard, the unique political and socioeconomic contexts of these countries provide an interesting playground to debate on the potential of social democracy, egalitarian society and social equality, i.e. public values that are deeply embedded into the fabric of societies there, to benefit the open data movement in a fundamental manner.

This paper reports on unique practical approaches for peer-to-peer collaboration and cooperation in advancing open data-driven platforms among stakeholders. The results of the case studies in three Nordic countries, which are currently among global leaders in advancing the concept of open government, are presented in an intrinsically illustrative manner, which could help practitioners and policymakers to understand better the potential of such a peer-to-peer perspective on open data. In this regard, the models proposed, of citizen-to-citizen, business-to-business, government-to-government interactions, could be interesting to a wide audience of e-government stakeholders in many nations.

The paper also enters into philosophical debates about societal implications of digital peer-to-peer data-driven communication among people. Recent efforts to digitize almost every part of social life, starting from popularization of solutions for distant work and ending to online access to various public services, incentivize individual members of civil society to communicate in an inherently peer-to-peer way. This fact will definitely increase the demand for related digital services. Social distancing in a digital context will allow to paradoxically emancipate technically savvy and entrepreneurial people in creating new services, including using open data, which could meet the demand.

The research is intrinsically of an empirical character because recent e-government reforms in the public sector in many countries, including in the open data area, provide rich practical knowledge to test the limits of new technologies to advance society in socioeconomic and, more importantly, political development. In this regard, this paper provides the first research in analyzing open data from a unique peer-to-peer perspective with an ultimate goal of the whole investigation to draw the attention of other e-government scholars and initiate debates on the collaborative nature of the phenomena to empower civil society and ensure transparency of government.

The purpose of this study is to identify factors that foster or prevent sense of belonging among frontline and middle managers in social and health-care services in Finland.

The data have been collected among social and health-care managers (n = 135; 64 per cent nursing managers) through two open-ended questions in a questionnaire concerning sense of community. The results of the open-ended questions have been analyzed using qualitative content analysis.

Among managers, six categories of factors that foster sense of belonging (open interaction, effective conversation culture, support and encouragement, common values, a shared vision of the work and its objectives and structure of leadership) and five categories of factors that prevent sense of belonging (negative work atmosphere, lack of common time, structural solutions in the organization, problems that occur in the organizational level and problems related to leadership and management) have been identified.

The resulting information can be used to develop sense of belonging among managers at all levels of organization (horizontal and vertical).

Paying attention to the quantity and quality of interaction and to structural solutions in the organization can affect the sense of belonging among frontline managers and middle managers.

A Novartis social business in India completely separated the activities of its social and business units—the former engaging in raising the health awareness of villagers and encouraging them to visit free health camps, while the latter developed affordable medicine delivered directly to village pharmacies. Connections between these units were made through open and fluid market-type mechanisms, and by appealing to the needs and interests of villagers with incentives. This synchronized business model was developed partly because Novartis believed in villagers' self-initiated behavior for health improvements, which made it not interfere into marginalized institutions, and more significantly because it used its internalized control and coordination systems with clear goals of social contribution in operating the business unit. Consequently, Novartis achieved economies of scale, business sustainability, and social contribution.

The purpose of the paper is to study the explainability of expected and unexpected trade volume and open interest as information flow, and the asymmetric effects of unexpected shocks to the information flow on volatility in Indian commodity markets.

After having dissected into expected and unexpected components, the effects of trade volume and open interest on volatility are tested. A new interaction term is also added to measure asymmetry. Four commodities, namely, cumin, soy oil and pepper in food commodity category and guar seed in non-food commodity category are selected for the present study. These four commodities are selected based on their economic and trading importance, i.e. weight in the index and trading volume (liquidity).

It is mostly found that unexpected volatility is positively related to the volatility, and the effect of the unexpected component is more than the expected component of the trading volume. The expected open interest is negatively related to volatility while the unexpected open interest is found to be positively related in all the commodities. The effects of unexpected component are higher than the expected open interest. The effects of positive unexpected shocks to the trade volume are more than those of negative unexpected shocks. The evidence of asymmetry in unexpected shocks to open interest is inconclusive. However, the inclusion of volume of trade and open interest could not vanish away the volatility. This indicates that the trading volume and open interest are not the variable with mixed distribution. Thus, it contrasts the assumption of mixed distribution hypothesis, and they do not proxy the flow of information.

It is the unexpected information flow that matters more than the expected one. Positive unexpected shocks to trade volume are more influential than the negative shocks. However, trade volume and open interest are not good proxy of information flow in the Indian commodity markets. This study would definitely broaden the horizon of managers and policymakers to understand the volatility better.

The paper is unique in terms of understanding the effect of expected and unexpected trade volume and open interest and the asymmetric effects of unexpected shocks to volume and open interest in the Indian commodity markets.

This paper aims to investigate which organizational measures can facilitate the use of open data. Implementation of open government data initiatives is commonly supply-driven, as it is difficult to predict the possible uses and users of data. Nonetheless, the value of open data materializes only upon its use – either to achieve societal benefits or economic value.

First, a list of organizational measures to facilitate open data use from the literature is collated. Then, four case studies to examine the challenges faced in practice when implementing them are carried out. The case sample includes two types of organizations (statistical agency and municipality) in two country settings (Sweden and The Netherlands).

Public organizations find it challenging to set up support for open data users having various requirements and skills. Most public organizations have no or limited interaction with data users and are often selective with regards to with whom and how to communicate.

Given the fragmented and emerging state of research on open data use and engagement, to date no systematic framework existed which would be dedicated to user engagement strategies. The authors systematized the literature and identified the themes pertaining to this issue. Their contribution is a list of measures for public organizations to improve open data use.

An important deliverable of this research is the list of possible organizational measures, which can be used by public managers to plan their open data engagement strategies. The authors suggest that data publishers adopt a problem-oriented approach for selecting which data to publish and put more efforts into stimulating stakeholder participation.

The novelty of this study lies in the fact that it addresses a previously overlooked area of open data research, namely, the use of open data and ways to stimulate it.

Existing overviews of barriers for openly sharing and using government data are often conceptual or based on a limited number of cases. Furthermore, it is unclear what categories of barriers are most obstructive for attaining open data objectives. This paper aims to categorize and prioritize barriers for openly sharing and using government data based on many existing Open Government Data Initiatives (OGDIs).

This study analyzes 171 survey responses concerning existing OGDIs worldwide.

The authors found that the most critical OGDI barrier categories concern (in order of most to least critical): functionality and support; inclusiveness; economy, policy and process; data interpretation; data quality and resources; legislation and access; and sustainability. Policymakers should prioritize solving functionality and support barriers and inclusiveness barriers because the authors found that these are the most obstructive in attaining OGDI objectives.

The prioritization of open data barriers calls for three main actions by practitioners to reduce the barrier impact: open data portal developers should develop advanced tools to support data search, analysis, visualization, interpretation and interaction; open data experts and teachers should train potential users, and especially those currently excluded from OGDIs because of a lack of digital skills; and government agencies that provide open data should put user-centered design and the user experience central to better support open data users.

This study contributes to the open data literature by proposing a new, empirically based barrier categorization and prioritization based a large number of existing OGDIs.