Purpose: The technological developments have implied that companies store increasingly more data. However, data quality maintenance work is often neglected, and poor quality business data constitute a significant cost factor for many companies. This paper argues that perfect data quality should not be the goal, but instead the data quality should be improved to only a certain level. The paper focuses on how to identify the optimal data quality level.Design/methodology/approach: The paper starts with a review of data quality literature. On this basis, the paper proposes a definition of the optimal data maintenance effort and a classification of costs inflicted by poor quality data. These propositions are investigated by a case study.Findings: The paper proposes: (1) a definition of the optimal data maintenance effort and (2) a classification of costs inflicted by poor quality data. A case study illustrates the usefulness of these propositions.Research limitations/implications: The paper provides definitions in relation to the costs of poor quality data and the data quality maintenance effort. Future research may build on these definitions. To further develop the contributions of the paper, more studies are needed.

PurposeThis paper seeks to explore the impact of different negotiation strategies on the negotiation setting in different buyer‐supplier relationships. So far, the extant supply chain management (SCM) literature has only briefly touched this subject, though such a study has been advocated on previous notes in the SCM literature.Design/methodology/approachA qualitative research methodology was chosen in order to investigate a focal firm's negotiations with five of its suppliers. A total of 25 hours of interviews and 15 hours of observations were carried out at the focal firm and with a number of the firms' tier one suppliers in order to investigate the subject at hand.FindingsExplanation is given of when the use of different negotiation strategies can be considered expedient in different relational settings, pairing a distributive negotiation strategy with arm's length relationships, while integrative negotiation strategies remain a more ambiguous exercise. Valuable insight concerning the impact of different negotiation strategies on the negotiation setting are advanced, which, in turn, leads to a questioning of previous research conclusions regarding the application of distributive negotiation strategies in strategic partnerships. The reason for such questioning is due to a limited focal perspective applied in previous research on negotiations in SCM.Research limitations/implicationsFuture research should statistically and analytically validate the research in order to reject or confirm the reached conclusions.Originality/valueThe paper is the first to specifically investigate the role of negotiation strategies in the academic discipline of SCM from a qualitative angle using participant observations and interviews.

Purpose -The purpose of this paper is to identify Nordic doctoral dissertations in logistics and supply chain management (SCM) published from the years 2002 to 2008. The paper then seeks to analyze the identified dissertations by categorizing them in various dimensions, including but not limited to subject, methodology, and type of contribution. Subsequently, the paper compares the analysis of the dissertations with results obtained in a previous study that also concerned Nordic dissertations only published from 1990 to 2001, effectively opening up for longitudinal interpretations. Design/methodology/approach -The paper is based on reviews of 70 Nordic doctoral dissertations within logistics and SCM published at relevant Nordic research institutions. All dissertations were reviewed according to a priori determined categories adopted from a similar, previous study in order to strengthen the validity of the longitudinal comparison. Findings -This paper identifies a clear and significant trend towards: more dissertations based on a collection of articles than monographs; more dissertations focusing on manufacturing companies and fewer on carriers; a shift from a focal company perspective to more dyadic and supply chain-related research and finally; and a decreasing focus on the philosophy in science.Research limitations/implications -Despite the thorough method applied, there is possibility that a few dissertations might not have been identified in this paper. Originality/value -This paper is a continuation of documenting the progress of doctoral work in logistics and SCM within the Nordic countries from the years 2002 to 2008.

PurposeThe purpose of this paper is to develop a differentiated approach to the cost management system of total cost of ownership (TCO), a system based on cost data. Existing TCO‐related literature has investigated the tool from a focal buyer perspective but has consequently neglected to study TCO from an inter‐organisational perspective.Design/methodology/approachAn explorative single case‐study approach is used, involving a large, industrial Danish manufacturing company. Interviews were conducted with relevant representatives from both the purchasing division and a range of the division's suppliers and observations made.FindingsThis paper indicates that a differentiated approach to TCO might be necessary, as suppliers might react negatively to the focal company presenting TCO data in negotiations. A matrix is proposed involving two dimensions: the nature of the relationship and the complexity of cost drivers.Research limitations/implicationsThis study involves a single case study and is therefore not capable of enumerating frequencies. Future research should test the applicability of the findings in other spatial contexts.Practical implicationsIndustrial managers should be aware that a differentiated approach to TCO is capable of solving problems pertaining to the current TCO “one‐size‐fits‐all” approach.Originality/valueThis is the first paper, known to the authors, to investigate the TCO concept from an inter‐organisational perspective.

PurposeThe development of IT has enabled organizations to collect and store many times more data than they were able to just decades ago. This means that companies are now faced with managing huge amounts of data, which represents new challenges in ensuring high data quality. The purpose of this paper is to identify barriers to obtaining high master data quality.Design/methodology/approachThis paper defines relevant master data quality barriers and investigates their mutual importance through organizing data quality barriers identified in literature into a framework for analysis of data quality. The importance of the different classes of data quality barriers is investigated by a large questionnaire study, including answers from 787 Danish manufacturing companies.FindingsBased on a literature review, the paper identifies 12 master data quality barriers. The relevance and completeness of this classification is investigated by a large questionnaire study, which also clarifies the mutual importance of the defined barriers and the differences in importance in small, medium, and large companies.Research limitations/implicationsThe defined classification of data quality barriers provides a point of departure for future research by pointing to relevant areas for investigation of data quality problems. The limitations of the study are that it focuses only on manufacturing companies and master data (i.e. not transaction data).Practical implicationsThe classification of data quality barriers can give companies increased awareness of why they experience data quality problems. In addition, the paper suggests giving primary focus to organizational issues rather than perceiving poor data quality as an IT problem.Originality/valueCompared to extant classifications of data quality barriers, the contribution of this paper represents a more detailed and complete picture of what the barriers are in relation to data quality. Furthermore, the presented classification has been investigated by a large questionnaire study, for which reason it is founded on a more solid empirical basis than existing classifications.