Learning from Multi-Stakeholder Networks: Issue-Focussed Stakeholder Management

From an analysis of the role of companies in multi-stakeholder networks and a critical review of stakeholder theory, it is argued that companies practise two different types of stakeholder management: they focus on their organization’s welfare (organization-focussed stakeholder management) or on an issue that affects their relationship with other societal groups and organizations (issue-focussed stakeholder management). These two approaches supplement each other. It is demonstrated that issue-focussed stakeholder management dominates in multi-stakeholder networks, because it enables corporations to address complex problems and challenges in cooperation with stakeholders. Since deliberation is the key to issue-focussed stakeholder management, it helps to cope with numerous and at times contradictory stakeholder demands and enhances the legitimacy of corporate activities. The research for this article was facilitated by the ESC Rennes Management Research Fund.     

Distributed Visual Language Environments for Cooperation and Learning: Applications and Intelligent Support

An increasing number of collaborative learning environments is based on shared workspace systems using two-dimensional graph-structured visual representations such as argumentation networks and concept maps. We propose an integrated framework that allows for flexibly specifying a wide range of visual languages and plugging in components for operational semantics, adequate feedback and intelligent support. The generic application CardBoard provides card-based user interaction and collaboration by means of different languages in shared workspaces. To enhance modifiability, the interfaces between the distributed heterogeneous system components, particularly between intelligent components and user interfaces, have been standardised.     

Recognizing Business Ethics: Practical and Ethical Challenges in Awarding Prizes for Good Corporate Behaviour

There seems to be a proliferation of prizes and rankings for ethical business over the past decade. Our principal aims in this article are twofold: to initiate an academic discussion of the epistemic and normative stakes in business-ethics competitions; and to help organizers of such competitions to think through some of these issues and the design options for dealing with them. We have been able to find no substantive literature – academic or otherwise – that addresses either of these two broad topics and audiences. Our modest aim, therefore, is to suggest an agenda of issues, and to begin to explore and analyse some of the possible arguments for and against various philosophical or practical solutions. Part I explores the challenges facing a prize-organizing committee, including problems derived from what Rawls calls the “fact of pluralism” in democratic societies (reasonable people will always disagree over some basic values, including those relevant to evaluating business practices), and epistemic issues about how we can justify qualitative judgments on the basis of incomplete quantitative data. We also try to identify risks and opportunity costs for ethics-prize granters. In Part II we spell out (a) a range of design options and (b) some advice about how any particular prize-awarding committee might select among these options to best achieve its goals (which typically involve highlighting and publicizing best practices for ethical business).     

远程教育“三维”学习环境创设的实践与研究

任何学习活动都会发生在特定的环境中,创设有效的学习环境是保证教学及学习活动发生的基础和关键,尤其是对教与学处于准分离状态的现代远程教育而言尤为重要。通过实践,本文对三维学习环境的内涵进行了分析,总结了学习环境设计原则及呈现特征,并对学习环境创设策略进行了实践研究。     

Machine learning for enterprises: Applications,algorithm selection,and challenges

Machine learning holds great promise for lowering product and service costs, speeding up business processes, and serving customers better. It is recognized as one of the most important application areas in this era of unprecedented technological development, and its adoption is gaining momentum across almost all industries. In view of this, we offer a brief discussion of categories of machine learning and then present three types of machine-learning usage at enterprises. We then discuss the trade-off between the accuracy and interpretability of machine-learning algorithms, a crucial consideration in selecting the right algorithm for the task at hand. We next outline three cases of machine-learning development in financial services. Finally, we discuss challenges all managers must confront in deploying machine-learning applications.     

Are Market Orientation and Learning Orientation Necessary for Superior Organizational Performance?

There exists contradictory theoretical arguments and counter-intuitive empirical results regarding the market orientation, learning orientation and organizational performance nexus. We ask, can we simplify relations in this nexus? This study analyzes data from Australian organisations and employs non-nested encompassing tests. Contrary to recent findings extolling the virtues of a learning orientation, our results suggest that a market orientation may be the pre-eminent strategy to achieve superior organizational performance.     

A Learning Framework for Customer Integration: Know-How Acquisition, Dissemination and Utilization

Successful product innovation has increasingly been recognized as an outcome of integrating customers in the new product development process. Despite the attention of this research subject, the comprehension of how to learn from customers is still limited in scope and in depth. This research investigates ‘learning’ in the customer integration context and discusses a conceptual framework from learning theory with customer know-how acquisition, dissemination and utilization as critical steps. The paper reports a comparative case study of new product development projects in a business-to-business context. The findings show empirical support for the developed framework and demonstrate the importance of a differentiated consideration of the three steps. They lead to determinants for successful customer know-how integration in new product development projects.