How can contributors to open-source communities be trusted? On the assumption,inference, and substitution of trust

Open-source communities that focus on content rely squarely on the contributions of invisible strangers in cyberspace. How do such communities handle the problem of trusting that strangers have good intentions and adequate competence? This question is explored in relation to communities in which such trust is a vital issue: peer production of software (FreeBSD and Mozilla in particular) and encyclopaedia entries (Wikipedia in particular). In the context of open-source software, it is argued that trust was inferred from an underlying ‘hacker ethic’, which already existed. The Wikipedian project, by contrast, had to create an appropriate ethic along the way. In the interim, the assumption simply had to be that potential contributors were trustworthy; they were granted ‘substantial trust’. Subsequently, projects from both communities introduced rules and regulations which partly substituted for the need to perceive contributors as trustworthy. They faced a design choice in the continuum between a high-discretion design (granting a large amount of trust to contributors) and a low-discretion design (leaving only a small amount of trust to contributors). It is found that open-source designs for software and encyclopaedias are likely to converge in the future towards a mid-level of discretion. In such a design the anonymous user is no longer invested with unquestioning trust.     

Contextual integrity’s decision heuristic and the tracking by social network sites

The findings of our experiments showed that social network sites (SNSs) such as Google Plus, Facebook, and Twitter, have the ability to acquire knowledge about their users’ movements not only within SNSs but also beyond SNS boundaries, particularly among websites that embedded SNS widgets such as Google’s Plus One button, Facebook’s Like button, and Twitter’s Tweet button. In this paper, we analysed the privacy implication of such a practice from a moral perspective by applying Helen Nissenbaum’s decision heuristic derived from her contextual integrity framework in order to answer the question of whether or not an online user’s privacy is being violated by this practice.     

‘What are these researchers doing in my Wikipedia?’: ethical premises and practical judgment in internet-based ethnography

The article ties together codified ethical premises, proceedings of ethical reasoning, and field-specific ethical reflections so to inform the ethnography of an Internet-based collaborative project. It argues that instead of only obeying formal statutes, practical judgment has to account for multiple understandings of ethical issues in the research field as well as for the self-determination of reflexive participants. The article reflects on the heuristics that guided the decisions of a 4-year participant observation in the English-language and German-language editions of Wikipedia. Employing a microsociological perspective, it interrogates the technological, social, and legal implications of publicness and information sensitivity as core ethical concerns among Wikipedia authors. The first problem area of managing accessibility and anonymity contrasts the handling of the technologically available records of activities, disclosures of personal information, and the legal obligations to credit authorship with the authors’ right to work anonymously and the need to shield their identity. The second area confronts the contingent addressability of editors with the demand to assure and maintain informed consent. Taking into account these problem areas, the ethical reasoning on the one hand proposes options for observing and documenting episodes. On the other, it provides advice on the feasibility and the necessity of obtaining informed consent.     

Explanation and trust: what to tell the user in security and AI?

There is a common problem in artificial intelligence (AI) and information security. In AI, an expert system needs to be able to justify and explain a decision to the user. In information security, experts need to be able to explain to the public why a system is secure. In both cases, an important goal of explanation is to acquire or maintain the users’ trust. In this paper, I investigate the relation between explanation and trust in the context of computing science. This analysis draws on literature study and concept analysis, using elements from system theory as well as actor-network theory. I apply the conceptual framework to both AI and information security, and show the benefit of the framework for both fields by means of examples. The main focus is on expert systems (AI) and electronic voting systems (security). Finally, I discuss consequences of the analysis for ethics in terms of (un)informed consent and dissent, and the associated division of responsibilities.     

Organisational ‘know-where’ and ‘know-when’: re-framing configurations and distributions of knowledge in organisations

This paper explores varying configurations of knowledge in organisations. A multi-dimensional framework of distinctive forms of knowledge is used to highlight different patterns of organisational knowledge, demonstrating their heterogeneity and variability – over time, in terms of depth of expertise, and their distribution within and between organisations. Common knowledge that is shared across an organisation accounts for only a small proportion of organisational knowledge, indicating that strategies to exploit this resource for competitive advantage will be constrained unless mechanisms are developed that enable access to and transfer of knowledge that is not yet shared or common.     

Anatomy of use-inspired researchers: From Pasteur’s Quadrant to Pasteur’s Cube model

Pasteur’s Quadrant model, published by Stokes in 1997, presents a two-dimensional abstract conceptual framework that proved immensely helpful to study and discuss institutional and policy arrangements in science. However, during the last 10 years the PQ model was also applied in a series of large-scale, survey-based studies worldwide to classify individual modern-day researchers according to their research orientation and performance.This paper argues that such applications are inadequate to capture key characteristics of individual researchers, especially those within the heterogeneous ‘Pasteur type’ group who engage in ‘use-inspired’ basic scientific research. Addressing this shortcoming, Pasteur’s Cube (PC) model introduces a new heuristic tool. Departing from a three-dimensional conceptual framework of research-related activities, the model enables a range of typologies to describe and study the large variety of academics at today’s research-intensive universities. The PC model’s analytical robustness was tested empirically in two interrelated ‘proof of concept’ studies: an exploratory survey among 150 European universities and a follow-up case study of Leiden University in the Netherlands. Both studies, collecting data for the years 2010–2015, applied a metrics-based taxonomy to classify individual academic researchers according to four performance categories: scientific publication output, research collaboration with the business sector, patents filings, and being engaging in entrepreneurial activities.The collective results of both studies provide more clarity on relevant subgroups of use-inspired researchers. The PC model can be used to guide empirical, metrics-based investigations of research activities and productivities, applies this approach to two case studies, and demonstrates the utility of the method while also reinforcing and enriching the growing body of literature showing that cross-sectoral and cross-functional research activities are more scientifically productive than research carried out in isolation of the context of use. Introducing the ‘Crossover Collaborator’ subtype helps to explain why Pasteur type researchers tend to outperform other types of researchers in terms of publication output and citation impact.     

Employees’ trust and their knowledge sharing and integration: the mediating roles of organizational identification and organization-based self-esteem

We propose that the effect of trust on knowledge sharing (KS) and knowledge integration (KI) is mediated by organizational identification (OI) and organization-based self-esteem (OBSE). We focus on the relationship among different foci of trust and take into consideration that trust is a culturally dependent variable. We draw from a large-scale questionnaire survey with 50 Chinese companies and find support for our hypotheses in general. The study finds that employees’ trust within the organization is a multifaceted construct that includes their trust in the organization, trust in the supervisor and trust in peers. Trust with these different foci positively impact KS and KI. However, such effects are largely indirect and we find support for our expectation that OI and OBSE function as mediators. We conclude that trust in itself is a precondition but not sufficient condition for the actualization of KS and KI.     

The ‘Hungarian sappho’: some comments and comparisons

A brief and constructive criticism is offered of the recent study (see preceding paper) which successfully adopted and adapted the Sussex SAPPHO ‘pair comparison’ technique to the investigation of twelve success-failure pairs in the Hungarian electronics industry. Despite some differences in methodology and differences in the industrial and political environments in which the two studies were made, the results of the Hungarian SAPPHO and the Sussex SAPPHO are remarkably similar.     

Customers’ acceptance of artificially intelligent service robots: The influence of trust and culture

This study addresses two critical research gaps in human-robot interaction (HRI): the limited systematic research on the role of trust in customers’ acceptance of artificially intelligent (AI) robots; and the lack of understanding of robot acceptance under different cultural backgrounds. Drawing on the AIDUA framework, this study examines the impacts of trust and moderating effects of both national (the U.S. and China) and individual culture on customers’ intentions to use AI robots in hospitality services by developing a theoretical model. The model is tested on data collected using online data collection platforms from 491 U.S. and 495 Chinese respondents. PLS-SEM and the bootstrapping method were used to test the hypothesized relationships and analyze the moderating effects of culture, respectively. The findings suggest that trust in interaction with AI robots is a significant higher-order construct that influences the intention of use. Furthermore, uncertainty avoidance, long-term orientation, and power distance have been found to exhibit significant moderation effects. The results of this study extend the theoretical frameworks in HRI and provide detailed guidance to promote AI robot applications across different cultures.     

From Imitation to Innovation:A Strategic Adjustment in China’s S&T Development

I. S&T Innovation Capacity as aStrategic Resource for SustainableDevelopment.Over the past two decades, China’s economy haswitnessed burgeoning growth at an average rate of9.4% per year, and by 2004, its per capita GDP sur-passed US$1,000, marking the beginning of the take-offstage of China’s industrialization. In line with nationalrealities, however, China cannot completely follow thetraditional route of industrialization taken by developedcountries. Instead, a brand-new road should b…     

‘Risky business’: Perceptions of e-business risk by UK small and medium sized enterprises (SMEs)

This paper explores the risk perceptions of key stakeholders in SMEs when making decisions on technology investments. Current literature focuses on the nature of the technology from a technical perspective and its associated benefits to the SME. We seek to make a contribution that builds on the small but growing work, which views investment technology decisions as the outcome of a process of both objective and subjective risk assessment. Evidence presented in this paper suggests that subjective elements play an important part in assessing technology risks. Our empirical findings are that both e-business experience and the role of the decision-maker within the firm influences risk perception, whereas, sector differences are more modest. One implication of our findings is that policy interventions should be more sensitive and targeted at different types of stakeholders – owners, IT professionals and other individuals rather than on the sector in which the SME operates.     

Unpacking ‘lessons learned’: investigating failures and considering alternative solutions

One of the most common ways to share project knowledge is to capture the positive and negative aspects of projects in the form of lessons learned (LL). If effectively used, this process can assist project managers in reusing project knowledge and preventing future projects from repeating mistakes. Nevertheless, the process of capturing, storing, reviewing and reusing LL often remains suboptimal. Despite the potential for rich knowledge capture, lessons are often documented as simple, line-item statements devoid of context. Findings from an empirical investigation across four cases revealed a range of reasons related to the perceived quality, process and visibility of LL that lead to their limited use and application. Drawn from the cross-case analysis, this paper investigates an integrated approach to LL involving the use of a collaborative Web-based tool, which is easily accessible, intelligible and user-friendly, allowing more effective sharing of project knowledge and overcoming existing problems with LL.