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The purpose of this paper is to focus on studying the impact of collaborative technologies on firm performance. The methodology used analyzes the influence of collaborative technologies not only directly but through an intermediary variable. This variable represents different intranet use orientations (e‐information, e‐communication and e‐transaction).

A structured questionnaire consisting of close‐ended questions was developed. Face‐to‐face surveys were conducted on a sample comprising 310 Spanish firms in May 2005. Research hypotheses were tested through ANOVA and hierarchical regression analyses.

Empirical results show that distinct collaborative technologies are associated with different intranet use orientations and demonstrate there is a positive relationship between e‐information and organizational performance. That is, the use of collaborative technologies with an informational orientation contributes to increased organizational performance. In addition, the existence of complementarities between e‐information and e‐communication were found. Thus, firms using collaborative technologies for e‐information in conjunction with e‐communication achieve better performance. The collaborative technology that has the greatest impact on firm performance is in fact the less employed.

This study confirms collaborative technologies are oriented to different, but compatible, uses. However, only certain uses present complementarities and have a direct impact on firm performance.

The application of technology to customer relationship management (CRM) initiatives (e‐CRM) is one of the fastest growing technological developments. However, there is sufficient evidence to show that many CRM initiatives do not achieve the desired result. One of the reasons for this is the lack of clarity that surrounds the classification and selection considerations of CRM applications. Identifies and discusses key factors that need to be considered when electronic CRM solutions are to be implemented. Among other findings, proposes perspectives from which e‐CRM implementation may be viewed in addition to identifying three integration dimensions applicable to e‐CRM solutions. Concludes that, while e‐CRM applications could enhance the delivery of a CRM strategy, such applications should be chosen carefully to fit in with organisational culture, process and legacy IT systems. The financial and human resource cost as well as the amount of time required for implementation of a CRM application should also be key factors in the selection of e‐CRM applications.

This paper aims to discuss how collaborative classification works in online music information retrieval systems and its impacts on the construction, fixation and orientation of the social uses of popular music on the internet.

Using a comparative method, the paper examines the logic behind music classification in Recommender Systems by studying the case of Last.fm, one of the most popular web sites of this type on the web. Data collected about users' ritual classifications are compared with the classification used by the music industry, represented by the AllMusic web site.

The paper identifies the differences between the criteria used for the collaborative classification of popular music, which is defined by users, and the traditional standards of commercial classification, used by the cultural industries, and discusses why commercial and non‐commercial classification methods vary.

Collaborative ritual classification reveals a shift in the demand for cultural information that may affect the way in which this demand is organized, as well as the classification criteria for works on the digital music market.

Collective creation of a music classification in recommender systems represents a new model of cultural mediation that might change the way of building new uses, tastes and patterns of musical consumption in online environments.

The paper highlights the way in which the classification process might influence the behavior of the users of music information retrieval systems, and vice versa.

Buyer companies’ engagement with suppliers varies according to their specific business needs. Prior models of supplier classification are based on the dimensions like product specification or criticality of purchase. As the supply chains are embracing collaboration among partners to respond to the dynamic market conditions, it is prudent to study the changes adopted by buyer companies for supplier classification. The paper aims to discuss these issues.

This is an exploratory research for identifying the criteria used for supplier classification based on the interviews of practitioners from buyer multinational manufacturing companies operating in India. The content analysis of the subjective responses led to the identification of distinctive criteria.

Although, many of the practitioners were unaware of the model per se, they labelled their suppliers as per the types stated in the Kraljic model. They mentioned twenty six criteria for supplier classification; five of which do not have any reference in the extant literature. The degree of presence of these criteria provides a multi-criteria framework for supplier classification that has been further extended based on prior models.

The exploratory nature of the study, its confinement to Indian milieu and small sample size could limit the generality and exhaustiveness of the findings.

The framework and its extension can be used by practitioners in assessing and classifying their suppliers for strengthening supply chain collaboration.

This research unveils five new criteria used by buyer companies for supplier classification. The multi-criteria framework for supplier classification and its extension give new insights into the supplier characteristics significant for supply chain collaboration.

The purpose of this paper is geared towards the capture and analysis of network traffic using an array ofmachine learning (ML) and deep learning (DL) techniques to classify network traffic into different classes and predict network traffic parameters.

The classifier models include k-nearest neighbour (KNN), multilayer perceptron (MLP) and support vector machine (SVM), while the regression models studied are multiple linear regression (MLR) as well as MLP. The analytics were performed on both a local server and a servlet hosted on the international business machines cloud. Moreover, the local server could aggregate data from multiple devices on the network and perform collaborative ML to predict network parameters. With optimised hyperparameters, analytical models were incorporated in the cloud hosted Java servlets that operate on a client–server basis where the back-end communicates with Cloudant databases.

Regarding classification, it was found that KNN performs significantly better than MLP and SVM with a comparative precision gain of approximately 7%, when classifying both Wi-Fi and long term evolution (LTE) traffic.

Collaborative regression models using traffic collected from two devices were experimented and resulted in an increased average accuracy of 0.50% for all variables, with a multivariate MLP model.

Collaborative spaces such as Fab Labs, Living Labs, coworking spaces, hackerspaces, makerspaces, etc. are localized spaces that offer open access to resources. The purpose of this paper is to explain what motivates participants in such spaces, according to different innovation logics.

The paper is based on qualitative studies of 43 collaborative spaces in Paris and Barcelona.

This paper proposes a typology of different collaborative spaces to understand what motivates their participants. The classification is based on the innovation approach of each type of space: methods and techniques of ideation, social innovation, open innovation and user-driven innovation.

The classification of collaborative spaces clearly identifies different innovation approaches. However, it might result to be too simplistic and may not represent all spaces under the same denomination.

This paper provides some guidelines for managers who run or intend to open a collaborative space. In bottom-up innovation modes, to increase the commitment of the participants, managers should provide the tools and resources needed to successfully achieve the goals of the members’ projects. In top-down innovation modes, managers should rather focus on designing an attractive and rewarding process of ideation.

This paper contributes to the understanding of collaborative spaces; it shows that participants’ engagement is related to the nature of the innovation activities that take place in collaborative spaces, and it compares different types of spaces to explain their differences and similarities.

The purpose of this paper is to analyse the inconsistent use of terminology in international collaboration, and develop a clearer typology that reflects the commercial and practical realities of modern business.

A critique of existing typologies provided the basis for the development of a more practical framework. The new typology was populated with the most prominent collaborative forms to emerge from the analysis of academic research and commercial practice.

“Structure” and “purpose” emerged as the most logical determinants in differentiating and classifying collaborative forms. Actual commercial ventures mapped on to the new typology demonstrate a good fit between these two considerations and the collaboration strategies adopted.

This work contributes much needed clarity in differentiating and classifying forms of collaboration. The key determinants of structure and purpose reflect more accurately the commercial and practical realities of modern business, and offer practitioners and researchers a logical means of mapping and analyzing collaboration strategy.

The purpose of this paper is to propose an intelligent infrastructure for the reconciliation of knowledge management and e‐collaboration systems.

Literature on e‐collaboration, information management, knowledge management, learning process, and intellectual capital is mobilised in order to build the conceptual framework.

This paper presents a conceptual framework including a set of concepts and guidelines that can be used to specify an efficient knowledge infrastructure for networked enterprises.

Results from this study uphold the emerging research area of knowledge management in e‐collaboration systems. The proposed framework derived purely from theory and conceptual analysis; more work needs to be done in order to validate and experiment with the framework. Future research remains be carried out to apply the framework on a broader scale, and in particular to determine its applicability relative to various collaboration patterns and current technology development.

Results from this study are important for networked enterprises, especially knowledge‐intensive enterprises, who intend to build e‐collaboration systems to organize their knowledge base and to share it with their partners.

This paper is one of the first to address collaborative knowledge management in e‐collaboration systems with a focus on the promotion of learning process and the creation of intellectual capital.

In the last two decades, a proliferation of business process management (BPM) modeling languages, standards and software systems has given rise to much confusion and obstacles to adoption. Since new BPM languages and notation terminologies were not well defined, duplicate features are common. This paper seeks to make sense of the myriad BPM standards, organising them in a classification framework, and to identify key industry trends.

An extensive literature review is conducted and relevant BPM notations, languages and standards are referenced against the proposed BPM Standards Classification Framework, which lists each standard's distinct features, strengths and weaknesses.

The paper is unaware of any classification of BPM languages. An attempt is made to classify BPM languages, standards and notations into four main groups: execution, interchange, graphical, and diagnosis standards. At the present time, there is a lack of established diagnosis standards. It is hoped that such a classification facilitates the meaningful adoption of BPM languages, standards and notations.

The paper differentiates BPM standards, thereby resolving common misconceptions; establishes the need for diagnosis standards; identifies the strengths and limitations of current standards; and highlights current knowledge gaps and future trends. Researchers and practitioners may wish to position their work around this review.

Currently, to the best of one's knowledge, such an overview and such an analysis of BPM standards have not so far been undertaken.

The purpose of this paper is to examine the role of warrant in daily classification design in general and in negotiating disparate classification goals in particular.

This paper synthesizes classification research on forms of warrant and uses examples of classification decisions from ethnographic engagement with designers to illustrate how forms of warrant interact in daily classification decisions.

Different forms of warrant, though associated with incompatible theories of classification design, coexist in daily classification decisions. A secondary warrant might be employed to augment the primary warrant of a system, such as to decide among equally valid terms, or to overturn a decision based on the primary warrant, such as when ethical impacts are prioritized above user preference.

This paper calls for empirical research using the application of warrant as an object of analysis.

The paper connects a ubiquitous and observable element of classification design – the application of warrant – to longstanding divisions in classification theory. This paper demonstrates how the analysis of daily classification design can illuminate the interaction between disparate philosophies of classification.