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Over the past 50 years, a substantial interest has been put to research on how innovation spreads within social networks over time (see Rogers, 1962, 2010). Our initial aim was to examine innovation diffusion in industrial networks. We operationalized the research through a case study of an advertising network by using systematic combining as the approach (Dubois & Gadde, 2002, 2014). From the initial focus of innovation diffusion, the rematching of data and theory led us to focus on the barriers of innovation diffusion. By doing so, we found out that multilevel strategizing appears to be an important phenomenon in understanding dynamics of innovation diffusion within industrial networks. Specifically, strategizing occurs in two levels: (1) the groups within the network compete for position, and (2) actors within a group compete for position by trying to differentiate themselves from other group actors. A strategic mismatch between the two levels leads the network to become decelerated or even static in diffusing new innovations (Abrahamsen, Henneberg, & Naudè, 2012). Uncovering these findings would not have been possible without the use of systematic combining and the constant matching between theoretical and empirical domains.

This study aims to develop the alleviating bullwhip effects framework (ABEF) replenishment rules, and bullwhip, inventory fluctuations and customer service fulfilment rates were examined. In addition, automated smoothing and replenishment rules can alleviate supply chain bullwhip effects. This study aims to understand the current artificial intelligence (AI) implementation practice in alleviating bullwhip effects in supply chain management. This study aimed to develop a system for writing reviews using a systematic approach.

The methodology for the present study consists of three parts: Part 1 deals with the systematic review process. In Part 2, the study applies social network analysis (SNA) to the fourth phase of the systematic review process. In Part 3, the author discusses developing research clusters to analyse the research state more granularly. Systematic literature reviews synthesize scientific evidence through repeatable, transparent and rigorous procedures. By using this approach, you can better interpret and understand the data. The author used two databases (EBSCO and World of Science) for unbiased analysis. In addition, systematic reviews follow preferred reporting items for systematic reviews and meta-analyses.

The study uses UCINET6 software to analyse the data. The study found that specific topics received high centrality (more attention) from scholars when it came to the study topic. Contrary to this, others experienced low centrality scores when using NETDRAW visualization graphs and dynamic capability clusters. Comprehensive analyses are used for the study’s comparison of clusters.

This study used a journal publication as the only source of information. Peer-reviewed journal papers were eliminated for their lack of rigorousness in evaluating the state of practice. This paper discusses the bullwhip effect of digital technology on supply chain management. Considering the increasing use of “AI” in their publications, other publications dealing with sensor integration could also have been excluded. To discuss the top five and bottom five topics, the author used magazines and tables.

The study explores the practical implications of smoothing the bullwhip effect through AI systems, collaboration, leadership and digital skills. Artificial intelligence is rapidly becoming a preferred tool in the supply chain, so management must understand the opportunities and challenges associated with its implementation. Furthermore, managers should consider how AI can influence supply chain collaboration concerning trust and forecasting to smooth the bullwhip effect.

Digital leadership and addressing the digital skills gap are also essential for the success of AI systems. According to the framework, it is necessary to balance AI performance and accountability. As a result of the framework and structured management approach, the author can examine the implications of AI along the supply chain.

The study uses a systematic literature review based on SNA to analyse how AI can alleviate the bullwhip effects of supply chain disruption and identify the focused and the most important AI topics related to the bullwhip phenomena. SNA uses qualitative and quantitative methodologies to identify research trends, strengths, gaps and future directions for research. Salient topics for reviewing papers were identified. Centrality metrics were used to analyse the contemporary topic’s importance, including degree, betweenness and eigenvector centrality. ABEF is presented in the study.

Microfoundations have received increasing attention in several management disciplines. This study aims to outline the uniqueness of microfoundations research in innovation, look at where it comes from and where it is going and provide rich opportunities for future work.

To advance research in this area, this study conducted a systematic literature review combining mixed methods and creating a mapping framework to take stock of progress in the innovation microfoundations research field.

This study shows how distinct subfields have formed around key ideas expressed in subsets of seminal articles, shedding light on the relational nature of knowledge creation – uncovering these subfields’ characteristics, evolution and future trajectories.

This study develops a framework that reflects a critical analysis of the microfoundations of innovation within dos three research levels – individual, process and interaction and structure – and highlights the research gaps and potential research questions for future research that reflect the broad spectrum of approaches in the microfoundations of innovation literature.

The aim of this work is to provide a theoretical model that can help companies to develop a unique approach to achieve both corporate environmental sustainability (CES) and successful customer experience management (CEM).

A two-phase study achieved the research aim. The first phase consisted of the analysis of contemporary theoretical contributions with a focus on CES and CEM. In the second phase, taking a qualitative approach, the key dimensions identified in the initial analysis were investigated to explore the dominant perceptions of practitioners and to hone the theoretical categories.

Five innovative pathways emerged from the study to inform decision-making while maintaining the dual objectives of CES and successful CEM. These pathways are combined to offer a strategic tool for managers and for research advances. This original integrated model also offers six novel theoretical propositions that describe how to shape corporate decisions to achieve environmental sustainability in CEM.

Firms can benefit from an approach that integrates CES and CEM to develop a new mindset for an innovative and valuable decision-making process and to design more captivating experiences for customers. Nevertheless, the efficacy and generalizability of the theoretical framework and propositions require empirical testing.

This paper makes an original contribution to the environmental sustainability and marketing literature by bringing together all elements in these fields of research in a conceptual model. Moreover, this paper proposes theoretical propositions that advance knowledge of the subject and offer ideas for future research and managers.

The paper offers a comprehensive understanding of how digital transformation affects business models and how firms operate and compete effectively and successfully in a digital economy.

The research adopted an abductive approach (Dubois and Gadde, 2002) through constant movement between theory and empirical evidence. A systematic literature review led the first conceptual development and examples of practices from cultural heritage sectors were used in the theorizing process.

This paper depicts a digital model framework through a set of assumptions about how an organization creates and delivers value in an interconnected way by orchestrating new interactive processes, and providing experience propositions to customers, and about how value is framed in terms of economic, social and cultural outcomes.

The study contributes to the scientific debate by discussing the role of digital business models as enhancements more rather than replacements of traditional business models; it frames a digital business model as consisting of three main pillars: value orchestration, experience propositions and value sharing.

This paper aims to present a methodology for volumetric error compensation. This technique is applied to an Objet Eden350V 3D printer and involves a custom measurement strategy.

The kinematic model of the printer is explained, and its error model is simplified to 18 independent error functions. Each error function is defined by a cubic Legendre polynomial. The coefficients of the polynomials are obtained through a Levenberg–Marquardt optimization process. This optimization process compares, in an iterative algorithm, nominal coordinates with actual values of the cloud of points. The points are built in the faces of a gauge artefact as conical sockets defining one unique point for each socket. These points are measured by a coordinate measuring machine self-centring measurement process.

Most of the errors of the 3D printer are systematic. It is possible to obtain an improvement of 70 per cent in terms of global mean error reduction in single points within a volume of 120 × 120 × 40 mm. The forecast of the final error compensation fully matches the actual final error.

This methodology can be used for accuracy improvement in additive manufacturing machines.

Unlike the calculation of geometric errors, the proposed parametric determination through optimization of the error model allows global error reduction, which decreases all sort of systematic errors concurrently. The proposed measurement strategy allows high reliability, high speed and operator independence in the measurement process, which increases efficiency and reduces the cost. The proposed methodology is easily translated to other rapid prototyping machines and allows scalability when replicating artefacts covering any working volume.

Social commerce (SC) is a new genre in electronic commerce (e-commerce) that has great potential. This study proposes a new research framework to address deficiencies in existing social commerce research frameworks (e.g. the information model).

In the era of Industrial Revolution 4.0 technologies and new social commerce (s-commerce) models, the authors believe that there is an immediate need for a new research framework. The authors analysed the progress of the s-commerce paradigm between 2003 and 2023 by applying longitudinal science mapping. The authors then developed a research framework based on the themes in the strategic diagrams and evolution map.

From 2003 to 2010, studies on s-commerce mainly focused on social networking sites, virtual communities, social shopping and analytic approaches. From 2011 to 2015, it shifted to s-commerce, consumer behaviour, Web 2.0, artificial intelligence, social technologies, online shopping, user studies, data gathering methods, applications, service-based social commerce constructs, e-commerce and cognitive factors. Social commerce remained the primary research paradigm from 2017 to 2023.

The SC framework may be analogous to popular research frameworks such as technology-organisation-environment (T-O-E) and stimulus-organism-response (S-O-R). Based on this SC framework, researchers may gain a better understanding by determining the factors of the social, commercial, technological and behavioural dimensions.

The authors redefined s-commerce and developed an SC framework. Practical guidelines for the SC framework and an exemplary research model are presented. Overall, this study offers a new research agenda for the extant understanding of s-commerce, with the SC framework as the next frontier of the theoretical advancements and applications of s-commerce.

Operations and supply chain management (OSCM) is a theoretically and philosophically fragmented field. Researchers must consider how they use theory and explain empirical phenomena. This paper aims to use critical realism to introduce more coherence into this fragmented field.

This paper draws on existing critical realism and abduction literature and this study uses a research process from two PhD projects to investigate critical realism’s role in OSCM research. This paper uses a narrative approach to collect data over a long timeframe, capturing data not commonly used in OSCM research.

Research that struggles to bridge the gap between theory and data benefits from critical realism, which provides a philosophy and associated methods to identify a suitable theory and guide researchers when they encounter obstacles. While clear steps often outline established methods, researchers are sometimes unable to identify when their research process has reached an obstacle. This paper argues that such obstacles can be treated as “crossroads” offering new research opportunities when correctly evaluated and addressed.

Importantly, researchers should be able to reflect upon their own research processes, enabling a better understanding of these processes and the discovery of new research directions. Researchers can use critical realism, abduction and systematic combining to bridge the divide between theory and data in OSCM.

This paper contributes to the field’s discussion regarding the roles of critical realism and abduction, synthesizing multiple academic sources, highlighting critical realism’s importance and providing a novel means of addressing difficulties in navigating an eclectic research area. This paper offers a philosophical alternate to the field, which is often instead considered from a positivistic standpoint. The paper is valuable to researchers in the OSCM field, who can use the research to improve their selection of data and theories, as well as their understanding of their own research processes.

The purpose of this study is to convey lessons learned from a long-term research project and present a coherent approach for researching relevant areas, ranging from ontology to quality.

A PhD process is used as a case to present conceptual ideas on performing research in logistics/supply chain management (SCM).

The research integrates different views on knowledge and the world and how to perform research in logistics/SCM. Models explaining micro and macro abduction, and the relationship between research, the context and researcher subjectivity are suggested.

Knowledge on why and how critical realism can be used in logistics/SCM research is advanced. Abduction is presented as a micro/macro process, which should not have any specific “finish line”, and is supported with both ontological and epistemological arguments.

Research in logistics/SCM can be improved by connecting different aspects of viewing and creating knowledge. Reflecting on how exactly a publication is related to a project, researchers can better describe how they contribute to knowledge creation, and also understand the relationship between micro and macro abduction.

Through presenting an approach to knowledge creation in the context of a PhD thesis, this research distinguishes itself in a field with a growing need to define its own views of the world and of knowledge. The paper advances current understanding of knowledge creation in logistics/SCM, expanding on earlier models and presenting a broader view of the research process and the associated dilemmas. The paper also contains novel considerations of the differences between publication types and how these affect the presentation of the research.

This study aims to understand and a lay a foundation of how analytics has been used in depression management, this study conducts a systematic literature review using two techniques – text mining and manual review. The proposed methodology would aid researchers in identifying key concepts and research gaps, which in turn, will help them to establish the theoretical background supporting their empirical research objective.

This paper explores a hybrid methodology for literature review (HMLR), using text mining prior to systematic manual review.

The proposed rapid methodology is an effective tool to automate and speed up the process required to identify key and emerging concepts and research gaps in any specific research domain while conducting a systematic literature review. It assists in populating a research knowledge graph that does not reach all semantic depths of the examined domain yet provides some science-specific structure.

This study presents a new methodology for conducting a literature review for empirical research articles. This study has explored an “HMLR” that combines text mining and manual systematic literature review. Depending on the purpose of the research, these two techniques can be used in tandem to undertake a comprehensive literature review, by combining pieces of complex textual data together and revealing areas where research might be lacking.