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Retail design concepts are complex designs meeting functional and aesthetic demands from various constraint generators. However, the literature on this topic is sparse and offers only little support for store designers to deal with such challenges. To address this issue, the purpose of this paper is to identify the most important constraint generators, investigating the types of constraints they generate, and providing guidelines for how to deal with constraint elicitation.

The three contributions mentioned above are developed through discussions of the literature and eight case studies of fashion store design projects.

The paper shows that the influence of the constraint generators decreases during the design process except for supplier-generated constraints, which increase in the final stages of the design process. The paper argues that constraints should be elicited close to their occurrence, and that doing so requires a solid understanding of relevant constraint generators.

The paper provides a structured basis for further research and identifies areas warranting further study. Although, the paper’s focus is on fashion store design, the findings may, to some degree, be applicable to other types of store design projects.

The understandings provided by this paper may help designers to deal proactively with constraints, reducing the use of resources to alter design proposals.

The paper: defines the most important constraint generators from the perspective of retail store designers, clarifies the types of constraints they generate, and provides guidelines for how to deal with constraint elicitation.

Product configurators are expert systems that support product customization by defining how predefined entities and their properties may be combined. Developers of configuration systems act as designers, although they do not often recognize that they are performing as such. Moreover, exploring solution spaces is typically not integral to configuration projects, as this task is typically perceived as mapping existing knowledge to the configurator. This article argues that developing configurators may be understood by distinguishing between the problem and solution spaces using design thinking (DT).

A multiple-case-study approach with four configuration projects is adopted to study two projects involving DT and compare them to two similar projects not involving DT. Data collection depended on multiple data sources via workshops and semi-structured interviews.

First, DT methods and concept–knowledge (C-K) theory are integrated into configuration projects. Second, the application of DT during configurator development is presented through workshops and interviews, which demonstrates the benefits of DT in overcoming existing challenges.

The case studies demonstrate the successful implementation of DT in developing configurators. However, a limited number of cases in only one company limits the generalizability of the results.

The framework's individual steps create a structured approach to supporting industrial companies with a toolbox of DT techniques and methods for configuration projects.

The results show that the application of DT to configuration projects can improve user motivation, stakeholder satisfaction and knowledge acquisition.

The digital transition process is an important strategic initiative for manufacturing companies to ensure continued competitiveness. The purpose is to investigate the relationship between firms' additive manufacturing (AM) readiness and product and process innovation and how this process is mediated by firms' make-or-buy decisions regarding performing AM processes internally or buying AM services from external partners.

The paper is based on a questionnaire survey including full answers from 157 small- and medium-sized manufacturing companies.

Results show a positive relationship between AM readiness and both product and process innovation. Results also reveal that firms with higher readiness invest more in in-house AM, which in turn promotes innovation. There was no significant association between AM readiness and the use of external AM services. Nonetheless, buying external AM services is still associated positively with innovation.

Data in the questionnaire survey are provided by single respondents from each company and are only based on Danish respondents.

The results indicate that firms' product and process innovation benefits from higher AM readiness derive from increased investment in in-house AM rather than from increased use of external AM services. This also signifies that firms with lower levels of AM readiness buy external AM services and derive the innovation benefits hereof.

The paper delivers new, empirically found knowledge about how small- and medium-sized manufacturing can improve innovation by both making and buying AM services.

Numerous data quality (DQ) definitions in the form of sets of DQ dimensions are found in the literature. The great differences across such DQ classifications (DQCs) imply a lack of clarity about what DQ is. For an improved foundation for future research, this paper aims to clarify the ways in which DQCs differ and provide guidelines for dealing with this variance.

A literature review identifies DQCs in conference and journal articles, which are analyzed to reveal the types of differences across these. On this basis, guidelines for future research are developed.

The literature review found 110 unique DQCs in journals and conference articles. The analysis of these articles identified seven distinct types of differences across DQCs. This gave rise to the development of seven guidelines for future DQ research.

By identifying differences across DQCs and providing a set of guidelines, this paper may promote that future research, to a greater extent, will converge around common understandings of DQ.

Awareness of the identified types of differences across DQCs may support managers when planning and conducting DQ improvement projects.

The literature review did not identify articles, which, based on systematic searches, identify and analyze existing DQCs. Thus, this paper provides new knowledge on the variance across DQCs, as well as guidelines for addressing this.

The purpose of this paper is to advance the understanding of how Industry 4.0 related technologies affect the relocation of manufacturing abroad by small and medium-sized enterprises.

This paper contains an empirical analysis of how Industry 4.0 related technologies affect the cost-driven relocation of manufacturing abroad based on 191 comprehensive and full responses to a questionnaire survey distributed in 2018 among small- and medium-sized Danish manufacturers.

This paper builds upon data, which reveals that companies' pursuit of cost-focused competitive strategies is positively correlated with relocating manufacturing abroad. However, the data also shows that the more Industry 4.0-ready decision-makers are, the less cost-focused strategy drives manufacturing abroad. Furthermore, perceived barriers to Industry 4.0 related technologies promote the cost-driven relocation of manufacturing abroad whereas perceived drivers decrease this phenomenon.

This paper is based on the answers given by a single respondent from each company and only on Danish respondents.

The results indicate a need to invest resources to obtain a better knowledge of Industry 4.0 related technologies when used in processes involved in decisions about where to locate manufacturing.

This paper contains new, empirically founded information about how Industry 4.0 related technologies affect the cost-driven relocation of manufacturing abroad from the perspective of small- and medium-sized manufacturers.

Additive manufacturing (AM) is one technology among the many under the umbrella of Industry 4.0 technologies. AM is developing rapidly, and extant research reveals that the technology contains possibilities for firms to develop competitive advantages, but that it also poses several challenges to overcome before such benefits can be achieved. To provide further insight into this topic, this paper aims to analyse how a business association can disseminate knowledge and experience about AM to its members.

The paper is based on 13 interviews from 11 different organisations within an embedded single-case study of a Danish non-profit business association.

The paper identifies 12 motivational factors for joining the association as well as seven perceived challenges in the current setup of the association. The paper demonstrates that barriers to the use of AM can be reduced through participation in a business association.

The paper is based on a single-case study design and does not provide a foundation for statistical generalisations. The challenges identified are biased towards the companies that are members and do not represent companies that either consciously or unconsciously are not part of the association.

Being aware of the barriers for AM is important to optimize the benefits of joining a business association. However, operating such an association with the purpose of disseminating AM knowledge involves the inherent dilemma of protecting knowledge for the individual members, and at the same time, fostering knowledge sharing.

The paper provides novel data on how a business association can help mitigate perceived barriers to using AM.

Information technology (IT), combined with complementary resources, can contribute to companies' competitive positioning. However, to assess the contribution of IT to value with respect to the contribution of complementary resources, it is crucial to understand the means by which IT creates value.

This paper synthesizes empirical research on the inherent capabilities of IT and their moderating role to build an integrative model.

We found that IT creates value through three inherent capabilities: transactional, exchange and codification capabilities. These capabilities can be regarded as moderators of the relationship between IT and competitive advantage. This moderating role of IT in competitive positioning is illustrated by examples from previous empirical publications.

The paper contributes to IT business value (ITBV) literature by developing an integrative model that (1) conceptualizes an aspect of IT value creation, which, thus far, has received only limited attention (namely, inherent capabilities) and (2) illustrates the moderating role of these capabilities in competitive positioning.

Inherent capabilities provide the theoretical foundation for a nuanced understanding of IT contribution with respect to complementary resources. This understanding may support IT executives in deriving adequate measurements and, thus, account for the differential effects of IT.

Compared to the literature, the proposed model represents a more coherent and holistic perspective of ITBV. Thus, the model may constitute a foundation for future ITBV research and promote more detailed analytic perspectives of ITBV.

The 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.

This 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.

Based 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.

The 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).

The 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.

Compared 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.

While few would disagree that high data quality is a precondition for the efficiency of a company, this remains an area to which many companies do not give adequate attention. Thus, this paper aims to identify which are the most important barriers preventing companies from achieving high data quality. By improving awareness of barriers on which to concentrate, companies are put in a better position to achieve high quality data.

First, a literature review of data quality and data quality barriers is carried out. Based on this literature review, the paper identifies a set of overall barriers to ensuring high data quality. The significance of these barriers is investigated by a questionnaire study, which includes responses from 90 Danish companies. Because of the fundamental difference between master data and transaction data, the questionnaire is limited to focusing only on master data.

The results of the survey indicate that a lack of delegation of responsibilities for maintaining master data is the single aspect which has the largest impact on master data quality. Also, the survey shows that the vast majority of the companies believe that poor master data quality does have significant negative effects.

The contributions of this paper represent a step towards an improved understanding of how to increase the level of master data quality in companies. This knowledge may have a positive impact on the data quality in companies. However, since the study presented in this paper appears to be the first of its kind, the conclusions drawn need further investigation by other research studies in the future.

This paper identifies the main barriers for ensuring high master data quality and investigates which of these factors are the most important. By focusing on these barriers, companies will have better chances of increasing their data quality.

The study presented in this paper appears to be the first of its kind, and it represents an important step towards understanding better why companies find it difficult to achieve satisfactory data quality levels.

Several studies have documented that information technology (IT) projects often do not successfully meet defined objectives regarding time, budget, and functionality. There can be multiple causes for this, and an important factor in this context is the extent to which a company is ready for an IT project. To help understand this dynamic, this paper seeks to present a framework for analyzing “IT readiness” in small‐ and medium‐sized enterprises (SMEs).

Based on a literature review, the paper defines a framework for assessing and changing the IT readiness of a SME. The framework is illustrated and investigated by three case studies.

The case studies show that the framework of IT readiness in SMEs is useful for assessing company readiness and supporting the management of a project.

The framework and case studies provide an improved understanding of how to evaluate the readiness of a SME for an IT project.

The framework for IT readiness provides a solid basis for SMEs who plan to engage in an IT project and help to increase the chances of success.

The framework presented in the paper constitutes an operational model for choosing IT projects and making SMEs ready to engage in IT projects.