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Given the increased stakeholder focus on sustainability, companies are facing the challenge of systematically collecting and processing sustainability information. Identifying sustainability indicators will become imperative for small and medium-sized enterprises (SME), especially in the extremely segmented and highly specialized food industry – entailing opportunities, but also costs and risks. This article is a management approach and a basis for discussing the classification of sustainability reporting systems in existing Information Technology (IT) infrastructures from an economical point of view. Supported by a case study from the meat industry, the authors discuss to what extent sustainability information is reflected by an existing Enterprise Resource Planning (ERP) System, or which investments would be required for companies to facilitate the communication of sustainability data. Additionally and as a result, the article gives a schematic explanation how process changes can be evaluated economically by capturing and processing sustainability information, and thus how to decide in favor of or against a certain level of IT-based environmental information processing functionality.

PurposeThe aim of this paper is to identify key issues and successful patterns of collaborative customer relationship management (CRM) in financial services networks.Design/methodology/approachThe study takes the form of a multi‐case analysis.FindingsThe paper finds that key issues of CRM in financial services networks are redundant competencies of partnering companies, privacy constraints, CRM process integration, customer information exchange, and CRM systems integration. To address these issues, partnering companies have to agree on clear responsibilities in collaborative processes. Data privacy protection laws require that customer data transfer between partnering companies has the explicit approval of customers. For process integration, companies have to agree on process standards and a joint integration architecture. Web services and internet‐based standards can be used for inter‐organizational systems integration. Data integration requires the development of a joint data model. Either a unique customer identification number or a matching algorithm must be used to consolidate customer data records of partnering companies.Research limitations/implicationsBecause of the limited number of case studies, generalizability is limited. The findings can serve as a starting point for researchers seeking to further explore the topic with quantitative methods.Practical implicationsThe findings can be used by financial services networks to improve their collaborative CRM approaches.Originality/valueThe importance of collaborative CRM in business networks is likely to increase due to the continuing deconstruction of value chains not only in the financial services industry, but in other industries as well. Nevertheless, the topic has not received much attention in research.

Intro -- Table of Contents -- 1 Introduction -- References -- I Keynotes as to Core Issues -- 2 Research Ethics in the Digital Age: Fundamentals and Problems -- 1 Introduction -- 2 Fundamental questions concerning research ethics -- 3 Problems in research ethics -- 4 Problems with interdisciplinarity -- 5 The digital age -- 6 Research ethics - an impairment to progress? -- 7 The integrated approach to research ethics in the digital age -- References -- 3 What's Responsible for the Retraction Boom? -- 1 Introduction -- 2 What's Responsible for the Retraction Boom? -- 3 Conclusion -- References -- 4 Data Protection Laws, Research Ethics and Social Sciences -- 1 Introduction -- 2 Data Protection vs. Freedom of Science -- 3 Basic Principles of (European) Data Protection Law -- 3.1 Personal Data -- 3.2 Principle of data minimisation -- 3.3 Legal Basis for Data Processing -- 3.4 Informed Consent -- 3.5 Sensitive Data -- 4 Two Case Studies -- 4.1 The "Tastes, Ties and Time" Project -- 4.2 Behavioural Research on Facebook -- 5 Research Ethics and Data Protection Laws -- 6 Résumé -- References -- Laws -- 5 Crowd-Based Documentation of Plagiarism: The VroniPlag Wiki Experience -- 1 A short history -- 2 The crowd -- 3 Documentation in VroniPlag Wiki -- 3.1 Tools for plagiarism detection -- 3.2 Non-public documentation -- 3.3 Overview and breakdown of documented cases -- 3.4 How cases are found -- 4 Mass plagiarism in medicine and other misconduct -- 5 Multiple publications of articles -- 6 Incentives for plagiarism -- 7 Dangers of plagiarism -- References -- 6 The Empowerment of Users: Rethinking Educational Practice Online -- 1 Introduction -- 2 Promises of user/learner involvement in online education -- 2.1 Openness: OER, MOOC, etc. -- 2.2 User generation of content -- 2.3 Independence of learning behaviour

The aim of the book is to discuss the multiple issues of a digital research ethic in its interdisciplinary diversity. Digitization and mediatization alter social behavior and cultural traditions, thereby generating new objects of study and new research questions for the social sciences and humanities. Furthermore, mediatization and digitization increase the data volume and accessibility of (quantitative) research and proliferate methodological opportunities for scientific analyses. Hence, they profoundly affect research practices in multiple ways. While consequences concerning the subjects, objects, and addressees of research in the social sciences and humanities have rarely been reflected upon, this reflection lies at the center of the book.

PurposeThe bursting of the e‐bubble affected expectations with regard to mobile initiatives and willingness to invest in them very negatively. Business managers request detailed and thorough analyses prior to engaging in mobile initiatives. The paper aims to present a method, with which mobile business can be introduced to the customer relationship management (CRM) field.Design/methodology/approachThe paper follows the design science paradigm as outlined by March and Smith, and Hevner et al.FindingsThe findings provide a framework for the definition of a mobile CRM strategy derived from the corporate strategy, suggest a method for the identification and exploitation of the mobilization potential in CRM processes in line with the strategy, and provide guidance for the design of mobile information systems to support these processes.Research limitations/implicationsThe proposed method extends the body of available methods with a method for the introduction of mobile ISs into marketing, sales and service organizations. As design research, it does not strive for statistical generalization. The level of detail given in the elements of the method is to be increased in further research.Practical implicationsThe method helps to reduce risk and uncertainty of mobile CRM initiatives, since it provides a structured and consistent procedure for the definition of goals, the identification of potentials for the fulfillment of these goals as well as recommendations for the systematic exploitation of these potentials.Originality/valueWith the application of this structured method, an organization should be able to avoid the pitfalls of technology‐driven information technology initiatives which various companies have experienced, particularly with mobile technologies.

PurposeProcesses in customer relationship management (CRM) are classified as knowledge‐intensive processes. This paper seeks to provide a framework for knowledge management (KM) support of CRM processes and to show how this framework was applied in three action research cases.Design/methodology/approachIn a long‐term cooperation with several leading companies the authors developed a framework for customer knowledge management (CKM) and applied this framework in several action research cases. Additionally, further case studies have been conducted which support the framework. A selection of three action research cases is presented.FindingsSix core processes of CRM and four building blocks of KM to support these processes we identified. Each of these cases demonstrates the application of the framework and the implementation of the appropriate subset of CKM.Research limitations/implicationsThe cases support the CKM model. All cases presented here come from the financial services industry, thus the framework still needs to be applied in other industry segments as well.Practical implicationsThe cases evaluate the applicability, utility and efficacy of the CKM framework and show how it can help to make managerial decisions concerning the KM support of CRM processes.Originality/valueThe paper provides a framework classifying the processes in CRM and the KM building blocks to support these processes. To researchers it provides an evaluation of the presented framework and shows potential fields for further research. It also gives practical advice to managers who plan CRM initiatives.