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The proliferation of (big) data provides numerous opportunities for service advances in practice, yet research on using data to advance service is at a nascent stage in the literature. Many studies have discussed phenomenological benefits of data to service. However, limited research describes managerial issues behind such benefits, although a holistic understanding of the issues is essential in using data to advance service in practice and provides a basis for future research. The purpose of this paper is to address this research gap.

“Using data to advance service” is about change in organizations. Thus, this study uses action research methods of creating real change in organizations together with practitioners, thereby adding to scientific knowledge about practice. The authors participated in five service design projects with industry and government that used different data sets to design new services.

Drawing on lessons learned from the five projects, this study empirically identifies 11 managerial issues that should be considered in data-use for advancing service. In addition, by integrating the issues and relevant literature, this study offers theoretical implications for future research.

“Using data to advance service” is a research topic that emerged originally from practice. Action research or case studies on this topic are valuable in understanding practice and in identifying research priorities by discovering the gap between theory and practice. This study used action research over many years to observe real-world challenges and to make academic research relevant to the challenges. The authors believe that the empirical findings will help improve service practices of data-use and stimulate future research.

The purpose of the study is to map previous and current construction procurement research to further develop the research in the Nordic counties.

Mapping of previous and current research based on search in national database. The analysis is based on research perspectives, empirical contexts and research methods.

That the blind spots are partly overlapping, but that there is potential for knowledge transfer in some areas. There is also the potential for a Nordic research program on one or several of the blind spots.

The study is limited to PhD and licentiate-thesis reports in Norway and Sweden. Further research should include the other Nordic countries and a more extensive literature review including journal articles to broaden the scope. Findings have implications on collaborative Nordic research initiatives, knowledge transfer and in a longer perspective on the level of procurement knowledge in industry and society.

Findings provide a base for future research collaborations, initiatives and applications.

Findings provide a comprehensive understanding of construction procurement research in the Nordic countries, starting with Norway and Sweden. This understanding is needed for developing research collaborations and applications.

The purpose of this research is to support the customization ability for industrial house building companies striving to offer individualized products but with a strategy which includes a production facility. This is accomplished by analyzing the as-is state in terms of existing engineering assets and by proposing a to-be state using the design platform and product lifecycle management (PLM) support.

This study is based on design research methodology and collected data are in-depth interviews, document reviews and workshops and method development. The theoretical baseline is product platforms and the design platform.

The analysis showed that despite use of a platform, inherent assets are disorganized. Still, the identified object-based engineering assets were possible to include in a conceptual proposal for better management, both in the process and product view, using an asset relationship matrix and a PLM system.

The results should be applicable for industrial house building and off-site construction companies and offers an approach to identify and manage their assets and platforms which are crucial to stay competitive.

Previous research on design platforms has focused on engineer-to-order companies within the mechanical industry. The contribution of this paper lies in the application and support of the design platform for industrial house building and the introduction of PLM system support.

Competitive tendering in South Africa is often associated with procurement based on the lowest fee tendered. Previous research on this topic did not provide in-depth examinations of how pricing within consulting engineering companies was affected by competitive tendering nor did it illuminate the extent to which professional services were impacted by competitive tendering. This paper aims to examine the implications of competitive tendering on pricing and delivery of consulting engineering services in South Africa.

A survey research strategy with a questionnaire as the research instrument elicited qualitative data from 28 experienced consulting engineers in South Africa. Thematic analysis was used to analyse qualitative data from the questionnaires.

Three key themes were identified, namely: considerations when determining consulting engineering fees on competitively tendered projects; the impact of reduced fees due to competitive tendering on the delivery of consulting engineering services; and interventions to prevent unsustainably “low” professional fees. Many consulting engineers in South Africa still determine fees using fee scales, while other considerations include resources, project complexity, risk, etc. Most participants asserted that design optimisation/value engineering, training, meetings and construction monitoring were adversely impacted by “low” fees.

This paper provides in-depth qualitative feedback from experienced consulting engineers (most having more than 20 years’ experience) on a topical issue in the South African construction industry. Thematic analysis was a novel method of analysis that was not used previously in this area of study.

The paper presents a research methodology that could be used to carry out a systematic literature review on the current state of the art of the technological development in the field of the digitalization and unphysicalization of supply chains (SCs). A three-dimensional conceptual framework focusing on the relationship between Digital Technologies (DTs), business processes and SC performance is presented. The study identifies the emerging practices and areas of SC management that could be positively affected by the implementation of DTs. With this in mind, the emerging practices have a high probability to be considered future best practices.

A systematic literature review was conducted on DTs in SC management. The methodology used aims to algorithmically and objectively standardize the information incorporated into thousands of scientific documents. Selected papers were analyzed to investigate the recent literature on SC digitalization and unphysicalization. A total of 87 DTs were selected to be analyzed and subsequently grouped into 11 macro-categories. 17 business processes linked to SC management are taken into account and 17 different impacts on SC management are presented. From a set of 1,585 papers, 5,060 emerging practices were collected and singularly summarized combining DT, business process and impact on SC performance.

A unique analytical perspective provided represents an important evolution when trying to organize the current literature on SC management. The widely used DTs in the practices and the most considered business processes and impacts are highlighted and described. The three-dimensional conceptual framework is graphically represented to allow for the emergence of the best combinations of DT, business process and impact on SC performance. These combinations suggest the most promising areas for the implementation of the emerging practices for SC digitalization and unphysicalization. Additional findings identify and define the most important contexts in which Big Data contributes to SC performance.

The research methodology used is offering progress through which to systemize the current practices as well as detect the potential of digitalization and unphysicalization under the three-dimensional conceptual framework. The paper provides a structured proposal for promising future research directions, assuming that the five research gaps as findings of this research could be the basis for prescriptions, as well as a future research agenda and theory development. Moreover, this research contributes to current managerial issues concerning SC management, referred to data and information management, efficiency and productivity of SC processes, market performance, SC relationship management and risk management in SC.

The purpose of this paper is to explore how gamification may be used for project stakeholder engagement.

The paper presents the results of a systematic literature review of extant research concerning the gamification of projects. Based on this, an agenda for future studies is outlined.

Extant research on the gamification of projects is scarce and scattered among various disciplines, but the engineering fields dominate. The research performed does indicate that gamification may be used for involving stakeholders in projects, primarily by promoting learning, but also by engaging them, motivating action and solving problems.

In several cases, extant research display poor quality in research design and a lack in cross-disciplinary perspectives, which means that more research is needed. The users’ perspective is often lacking. Furthermore, the ideas gamification might be “hidden” within other technologies.

The findings of this research may assist project management practitioners in the endeavor of adopting gamification principles to better involve stakeholders.

The study fills a gap in summarizing the research on how gamification may be used to promote project stakeholder engagement. Based on this, it proposes a research agenda for future research on the use of gamification to promote project stakeholder engagement.

Co-creation and co-invention are two diverse spheres in modern-day supply chains. Despite literature suggesting the existence of similar coherence between these concepts, the availability of published theory favoring these ideal lacks justification. This research aims to investigate the correlation and convergence of these well-known concepts to support a combined impact on research.

Comprehensive review of published literature using mathematical and statistical tools to measure inherent interrelationships and publication impacts in literature handling co-creation and co-invention.

An exploratory quantitative and qualitative analysis reveals the conundrums existing in distribution, keyword and adoption of research in the global and scientific community. The research favors a positive correlation existing between concepts such as co-ordination, collaboration, open-innovation, value creation with supply chain management and its development with rising importance of big data and block-chain technologies. Analysis reveals knowledge development with increased user-based interaction, better utilization of resources and enhanced productivity to support the mutual adaptation of co-creation and co-invention.

Outcomes will be a beacon for researchers to develop models and frameworks. Results derived will aid in improving customer participation, enhance decision making in product development, augment value creation and knowledge and resource sharing leading toward innovation.

Results will provide a detailed outline of the development and implementation of concepts in both developed and developing countries. Outcomes will also serve as a framework for marketing heads, graphic designers, website designers, supplier management and customer management in the service industry, production supervisors and customer management personnel in manufacturing industries.

This study aims to identify the major factors influencing the consumers to prefer milk products and also to analyze the awareness level of the Indian consumers.

In this study, the data is obtained through a structured questionnaire from Indian consumers considering convenience sampling under the nonprobability sampling technique. The consumer preference is explained using a multiple-regression model followed by analysis of variance (ANOVA), which shed insight on the significant differences between the variables that influence consumer preference for dairy products.

Investigation is done to analyze the factors influencing the consumers' buying behavior toward milk and its products. The results showed that quality, health consciousness, price and availability are the most influencing factors to buy milk products. Quantity of milk showed a significant relationship between age, monthly income and family size.

This study helps marketing managers to frame the marketing strategies based on consumer preference, quality, health consciousness, price and availability. The research outcome will not only be advantageous for the entrepreneurial perspective but also takes care of consumer likeliness. Though the research reveals the opinion of Indian consumers, it limits the likeliness of the western world. Because of the scarcity of resources, several dairy products are unexplored, which could pave the future scope of research.

The novelty of this study is to identify the quality, health consciousness, price and availability are the most influencing factors to buy milk products considering ANOVA and the multiple regression model.

The purpose of this paper is to investigate and quantify the impact of product complexity, including architectural complexity, on operator learning, productivity and quality performance in both assembly and disassembly operations. This topic has not been extensively investigated in previous research.

An extensive experimental campaign involving 84 operators was conducted to repeatedly assemble and disassemble six different products of varying complexity to construct productivity and quality learning curves. Data from the experiment were analysed using statistical methods.

The human learning factor of productivity increases superlinearly with the increasing architectural complexity of products, i.e. from centralised to distributed architectures, both in assembly and disassembly, regardless of the level of overall product complexity. On the other hand, the human learning factor of quality performance decreases superlinearly as the architectural complexity of products increases. The intrinsic characteristics of product architecture are the reasons for this difference in learning factor.

The results of the study suggest that considering product complexity, particularly architectural complexity, in the design and planning of manufacturing processes can optimise operator learning, productivity and quality performance, and inform decisions about improving manufacturing operations.

While previous research has focussed on the effects of complexity on process time and defect generation, this study is amongst the first to investigate and quantify the effects of product complexity, including architectural complexity, on operator learning using an extensive experimental campaign.

Due to the recent development of Big Data and artificial intelligence (AI) technology solutions in customer relationship management (CRM), this paper provides a systematic overview of the field, thus unveiling gaps and providing promising paths for future research.

A total of 212 peer-reviewed articles published between 1989 and 2020 were extracted from the Scopus database, and 2 bibliometric techniques were used: bibliographic coupling and keywords’ co-occurrence.

Outcomes of the bibliometric analysis enabled the authors to identify three main subfields of the AI literature within the CRM domain (Big Data and CRM as a database, AI and machine learning techniques applied to CRM activities and strategic management of AI–CRM integrations) and capture promising paths for future development for each of these subfields. This study also develops a three-step conceptual model for AI implementation in CRM, which can support, on one hand, scholars in further deepening the knowledge in this field and, on the other hand, managers in planning an appropriate and coherent strategy.

To the best of the authors’ knowledge, this study is the first to systematise and discuss the literature regarding the relationship between AI and CRM based on bibliometric analysis. Thus, both academics and practitioners can benefit from the study, as it unveils recent important directions in CRM management research and practices.