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The building design processes today are complex, involving many disciplines and issues like collaboration, concurrency and collocation. Several studies have focused on understanding and modeling formal information exchange in these processes. Few past studies have also identified the importance of informal information exchanges in the design process and proposed passive solutions for facilitating this exchange. The purpose of this paper is to term the informal information as ad hoc information and explores if components of ad hoc information exchanges can be actively managed.

An MDM-based framework integrating product, process and people dependencies is proposed and a prototype platform to implement this framework is developed. The demonstration on the usage of this platform to identify information paths during collaboration and hence manage ad hoc information exchanges is presented through an example problem.

Based on the effectiveness of the prototype platform in identifying information paths for design queries, it is concluded that the proposed framework is useful for actively managing some components of ad hoc information exchange.

This research enables the design manager/participants to make a more informed decision on requesting and releasing design information.

The purpose of this paper is to examine the usability of the dimensional view of data in the context of its presumed learnability.

In total, 303 participants were asked to solve 12 analytical problems in an experiment using the dimensional view of data for half of the problems and an operational view of data for the other half. Inferential statistics and structural equation modeling were performed with participants’ objective results and affective reactions.

Showing that the order of exposure to the two views of data impacts the overall usability of ad hoc querying, the study provided evidence for the learnability potential of the dimensional view of data. Furthermore, the study showed that affective reactions to the different views of data follow objective usability parameters in a way that can be explained using models from affective computing research.

The paper proposes a list of guidelines for use of the dimensional view of data in business analytics.

This study is the first to confirm the learnability of the dimensional view of data and the first to take a deeper look at affective reactions to an ad hoc business analytics solution. Also, it is one of few studies that examined the usability of different views of data directly on these views, rather than using paper representations of data models.

As business globalisation and internet usage continue to grow, the internet‐based version of data warehouse systems (DWS) is expected to improve traditional DWS. However applying the web‐based interfaces to client‐server‐based DWS structures may cause problems such as inflexibility, inefficiency, loss of scalability, and threats to security. These arise due to the complexity of manipulation and management of heterogeneous data with various categories of decisional tasks. This paper seeks to develop a flexible mechanism by applying Extensible Markup Language as a foundation for an internet‐based DWS and to overcome the weaknesses of solely client‐server‐based DWS architecture.

For better control and security the proposed architecture utilises an embedded pull‐push mechanism to propagate the distributed decision information. This research also justifies the feasibility of the proposed mechanism by implementing a prototype, evaluating its performance, and conducting a real business case study.

The results indicate that the mechanism can not only improve DWS scalability and efficiency, but also enhance security.

The proposed architecture provides a support mechanism for business intelligence to efficiently and flexibly help companies make the right decisions in real time, grasp business opportunities and gain competitive advantage.

Relatively little microcomputer software has been designed specifically for the storage and retrieval of bibliographic data. Information retrieval packages for mainframes and minicomputers have been scaled down to run on microcomputers, however, these programs are expensive, unwieldy, and inflexible. For this reason, microcomputer database management systems (DBMS) are often used as an alternative. In this article, criteria for evaluating DBMS used for the storage and retrieval of bibliographic data are discussed. Two popular types of microcomputer DBMS, file management systems and relational database management systems, are evaluated with respect to these criteria. File management systems are appropriate when a relatively small number of simple records are to be stored, and retrieval time for multi‐valued data items is not a critical factor. Relational database management systems are indicated when large numbers of complex records are to be stored, and retrieval time for multi‐valued data items is critical. However, successful use of relational database management systems often requires programming skills.

There is a tremendous explosion in the amount of data that organizations generate, collect and store. Managers are beginning to recognize the value of this asset, and are increasingly relying on intelligent systems to access, analyze, summarize, and interpret information from large and multiple data sources. These systems help them make critical business decisions faster or with a greater degree of confidence. Data mining is a promising new technology that helps bring business intelligence into these systems. While there is a plethora of data mining techniques and tools available, they present inherent problems for end‐users such as complexity, required technical expertise, lack of flexibility and interoperability, etc. These problems can be mitigated by deploying software agents to assist end‐users in their problem solving endeavors. This paper presents the design and development of an intelligent software agent based data analysis and mining environment called IDM, which is utilized in decision making activities.

This article seeks to address the interface between individual learning facilitators that use course management systems (CMS) data to support decision‐making and course design and institutional infrastructure providers that are responsible for institutional business intelligence.

The design of a data warehouse is proposed that draw data from institutional transactional systems to provide decision support to individual action researchers. A prototype data warehouse is built to evaluate by means of a case study the usefulness validity of analyses performed.

Many facilitators of learning draw manually the same type of queries from CMS data for purposes of action research. On the other hand, more and more HEI infrastructure providers create data warehouses to support many kinds of decision‐making. It is possible and valuable to follow a business intelligence approach to facilitate the queries drawn by individual action researchers from course management systems (CMSs).

The expectation exists that as the technology on which CMSs, as well as business intelligence tools are built evolves, the creation of full‐scale business intelligence will become more feasible and scalable.

This article addresses the gap between individual action researchers that use CMS data to support decision making and course design, on the one hand, and institutional infrastructure providers that are responsible for institutional business intelligence on the other hand. Research questions are asked and addressed and processes are designed to manage business measurements consistently.

This paper seeks to propose a business intelligence (BI) and enterprise resource planning (ERP) integrated framework that adds value to enterprise systems.

A conceptual approach is taken.

ERP systems integrate all facets of the business and make data available in real time. BI tools are capable of accessing data directly from ERP modules.

The value‐added system proposed allows enterprise‐wide transaction data to be collected and analyzed for organizational decision‐making processes.

The purpose of this paper is to review extant literature on social media marketing (SMM) in B2B service markets, by scrutinizing and categorizing potential benefits for firms. The study, in particular, empirically investigates the adoption of social media (SM) tools by firms operating in two conservative B2B service industries.

A systematic literature review is carried out driving to a deeper understanding of the current state of knowledge on SM in B2B services. Leading peer-review international journals are scrutinized performing ad-hoc queries on the Scopus database using pre-defined keywords. Moreover, a quantitative research is conducted on 60 firms, i.e. tanker shipping companies and ocean carriers, providing empirical insights on their SM activity on three SM platforms, i.e., Facebook, Twitter, and LinkedIn.

The outcomes from sample firms shed lights on the adoption rate of the most diffused SM tools, the size of the digital networks of stakeholders (number of followers), the intensity of the communication activity (number of posts, shares, photos, videos), and the level of customer engagement (number of likes and shares).

Research findings suggest to managers that SMM might be an easy-accessible and low-cost option for keeping the pace of sectorial transformations and creating a competitive advantage even in conservative sectors.

The paper, by investigating B2B service sectors, addresses an interesting gap in SMM literature as prior studies mostly focused on B2C industries and manufacturing contexts.

The purpose of this paper is to investigate and prove the feasibility of a semantic web (SW) based approach to textual encoding. It aims to discuss benefits and novel possibilities with respect to traditional XML‐based approaches.

The markup process can be seen as a task of knowledge representation where elements such as words, sentences and pages are instances of conceptual classes forming a semantic network. An ontology web language ontology for textual encoding has been developed, capturing structural and grammatical aspects. Different approaches and tools to query the encoded text are investigated.

resource description framework (RDF) is powerful and expressive enough to fulfil tasks traditionally done in XML as well as to enable new possibilities such as collaborative and distributed textual encoding and the use of ontology‐based reasoning in text processing and querying. While the encoding of overlapping hierarchies through the use of existing approaches is often complex and leads to idiosyncratic solutions, this problem is naturally solved using SW languages.

To make the approach suitable for widespread adoption, further work is required both in ontologies modelling and in applications (e.g. markup editing).

The prototype implementation imports existing encoded texts, transforms them into RDF‐based markups and uses SW query languages to answer cross‐hierarchy queries. Existing tools (reasoners, search and query engines, etc.) can be used immediately.

This methodology enables distributed interoperability and reuse of previous encoded results and opens the way to novel collaborative textual markup scenarios.

To provide a more requirements‐driven workload model for eXtensible Markup Language (XML) benchmark over the electronic data exchange and management in collaborative commerce.

A three‐component workload requirements model is formulated. They are the XML object model, the XML query operation model, and the control model. The object model extended from W3C data model gives a set of more generic data and document model. The query model enhanced from current and common benchmarks gives a more generalized set of standard and open queries against XML data and documents. The control model compiled from TPC and industry standards gives a set of more systematic experimental variables and performance metrics to set up and conduct an XML benchmark.

The long‐standing research issues of domain dependency and application irreproducibility of XML benchmarks are addressed, tackled and offered with a novel and computer‐aided alternative. Precision and cost‐effectiveness through a synthetic, standard, and scalable set of requirements‐driven workload model are presented.

XML constructs, constraints, and controls are investigated both in terms of data and documents. Workload formulation from the requirements analysis is explored. In‐depth schema, query, and control model to provide scalability and portability can be applied is developed.

Enterprise information integration over heterogeneous data sources has to be achieved through XML. Performance measurement and evaluation on XML is vital. With a more generic and generalized design, XML benchmark can become the key to the success of B2Bi interoperability and performance.

An origin of requirements‐driven benchmark modeling over collaborative commerce is presented. A novel extension on W3C XML model is created. A innovative enhancement from current XML benchmarks' query model is developed.