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Empirical studies based on detailed, theory-based analyses are essential for a deep understanding of technology adoption. This study provides an overview of blockchain applications in logistics management, employing a comprehensive theoretical framework. Blockchain is considered a critical digital infrastructure for logistics operations due to its distinctive characteristics, including decentralization, transparency, immutability, real-time information sharing, reliability, and end-to-end visibility. These characteristics address many contemporary logistics challenges. The study introduces a research model that integrates the fit-viability model (FVM) and task technology fit theory (TTF), demonstrating blockchain's suitability for enhancing logistics operational functions and sustainability performance. To validate the model, data were collected from logistics managers of 576 companies and analyzed using partial least squares (PLS) regression. This research offers valuable insights for managers, policymakers, and decision-makers on practical challenges and potential solutions in logistics through the application of blockchain. Furthermore, the study demonstrates that the implementation of blockchain can improve the alignment, resilience, transparency, integration, and sustainability of logistics tasks.

The TikTok platform has become widely popular among younger generations and has influenced various industries and aspects of life. This systematic literature review, using bibliometric methods, aims to examine the evolution of TikTok research from its initial development to its current status. A total of 402 journal articles from 2019 to 2022 were systematically selected from the Web of Science Core Collection. Descriptive statistical analysis identified the most contributing academic institutions, nations, journals, scholars, and influential studies. Using CiteSpace, three visualization types were implemented: cluster views, timezone views, and timeline views. The study results indicate that several TikTok research clusters exist, which summarize important topics such as the platform's overall impact on society, politics, culture, as well as human-centric issues such as social attachment, functional tics, and their implications for public health. According to the co-word analysis, TikTok research revolves around body consciousness, social behavior, consumer behavior, and news media. The comprehensive mapping of TikTok research provides valuable insights into the current state of knowledge and identifies numerous relevant technical and social areas for future investigation. As the first bibliometric review of TikTok research, this study offers an important foundation for future scholarly inquiry in various areas.

The proper management of healthcare data is a complex endeavor that needs to balance the requirements and interests of many stakeholders. Previous research has identified and detailed many innovative blockchain-based use cases, but the current state of healthcare data management is still far from perfect. In this paper we present the findings from a panel discussion with healthcare professionals, who elaborate on the current situation in healthcare data management as well as the future role that blockchain can play in this sector. Based on the findings of this panel, we structure the research field of healthcare data management in a comprehensive framework and provide numerous avenues for future research. The outcome is a framework that highlights the important role of patients and their sensitive data, structured into several areas. From a patients’ perspective, we specifically elaborate on trust and privacy as well as the expected benefits. Additionally, four important data properties are identified: integrity, security, sharing and transfer, and interoperability. We outline the importance of the respective areas and derive several timely and important research questions that form the foundation of a future research agenda for blockchain-driven innovation in healthcare data management.

The energy use of Bitcoin is fiercely debated among academics, practitioners, and the general public. This debate is often biased and characterized by a lack of understanding. Therefore, I start this paper with a discussion of the fundamentals of Bitcoin, which includes the clarification of widely held misconceptions. Next, I illustrate how Bitcoin is related to energy and describe the underlying incentive mechanism. In the main body of the paper, I discuss various components of Bitcoin’s energy use, including the amount, composition, and geographical distribution of the energy, as well as emerging positive and negative effects. These components are then combined into a comprehensive framework that provides a solid foundation for future academic research and presents practitioners with the big picture of how and why Bitcoin requires energy and whether this can be justified from an environmental point of view.

Purpose – The purpose of the paper is to critically evaluate the applicability of bio certification in farmers' activity to reduce unfair trading practices in the food supply chain. The secondary purposes are describing the economic reasons of using bio certification and perspectives of using web trading platforms among food producers. Design/methodology/approach – Data collection included face-to-face interviews with 15 Austrian and German farmers who operate on bio food markets as well as a quantitative survey regarding their assessment of unfair trading practices. This study presents both quantitative and qualitative analyses. Findings – Bio certification is more likely unable to eliminate or mitigate unfair trading practices in the food supply chain, however bio certification is able to increase efficiency of farmers together with other web tools. Originality/value – The study is the first to empirically investigate the applicability of bio certifications, its advantages and impact on unfair trading practices in the food supply chain. It focuses on small and medium-sized food producers and farmers. The research also reveals the perspectives of using web trading platforms in farming activity.

The metaverse represents an immersive digital environment that has garnered significant attention as a result of its potential to revolutionize various industry sectors and its profound societal impact. While academic interest in the metaverse has surged, a dearth of comprehensive review articles employing bibliometric techniques remains. This study seeks to address this gap by analyzing 595 metaverse-related journal articles using bibliometric and topic modeling techniques, marking the first of its kind to investigate the bibliometric profile of metaverse research. The findings reveal exponential growth in metaverse research since 2020, identifying major trends, prolific authors, and the most active journals in the field. A keyword co-occurrence analysis further uncovers four significant clusters of metaverse-related interests, highlighting its unique facets and underscoring its far-reaching implications across various sectors, including education, healthcare, retail, and tourism. This study emphasizes the need for more research and collaboration in advancing the metaverse field and presents 27 research questions for future investigation. This comprehensive analysis serves as a foundation for understanding the current state of metaverse research and its potential trajectory.

In this paper, we use the widely popular business model canvas, which was previously adapted for the blockchain environment, to assess the experiences and perceptions of Slovenian small and medium-sized companies (SMEs) pertaining to blockchain technologies. The results reveal that SMEs expect applications built on blockchain technologies to have a highly positive effect on numerous aspects of their business model. This positive evaluation is even stronger among companies that already have experience with blockchain technologies.

Research on digital businesses builds upon a well-established set of theories, models, and frameworks. A frequently used approach within the paradigm of common variance theory is to first create a theory-based model and then test it using a multivariate method. Cross-sectional data is often used to test the overall fit of the model and the significance of its parameters, yet this approach fails to take into account the important role of temporal dynamics and the potential change of parameters over time, which constitutes an important research gap. For example, the popular Technology Acceptance Model (TAM) provides a snapshot in time, but cannot explain the postulated temporal patterns of the Diffusion of Innovations (DOI) theory. In this exploratory paper, we call for a theoretical and methodological paradigm shift and introduce process theory as a complement to the popular variance theory. This theory considers how entities change over time and create important network effects. Additionally, we illustrate how agent-based modeling (ABM) in combination with Structural Equation Modeling (SEM) can help to create models that combine the rigor of multivariate statistical methods with the capability of process theory to account for changes over time. Using ABM within the process theory paradigm can help to create meaningful models that are capable of incorporating temporal dynamics.

Blockchain technology can play a crucial role to facilitate the transition from a linear to a circular economy. This article evaluates those enablers that influence technology adoption in the circular economy. A comprehensive literature review and feedback from experts revealed nineteen critical enablers. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) methodology was used to determine the cause-and-effect relationships between them. The findings identified five critical causal enablers: transparency, security, smart contracts, traceability, and enhanced collaboration. Effect enablers were identified as immutability, decentralization, privacy, automation, information sharing, and enhanced regulation.

The digital transformation of core marketing activities substantially impacts relations between consumers and companies. Novel technologies are usually complex, making their underlying functionality as well as the desirable and undesirable implications hard to grasp for ordinary consumers. Cryptocurrencies are a prominent yet controversial and poorly understood example of an innovation that may transform companies’ future marketing activities. In this study, we investigate how easily consumers’ attitudes toward cryptocurrencies can be shaped by splitting a convenience sample of 100 consumers into two equal groups and exposing them to true, but biased, information about cryptocurrencies (including market forecasts), respectively, highlighting either the advantages or disadvantages of the technology. We subsequently found a significant difference in the trust, security and risk perceptions between the two groups; specifically, more positive attitudes pertaining to trust, security, risk and financial gains prevailed in the group exposed to positively-skewed information, while perceptions regarding trust, risk and the sustainability of cryptocurrencies were weaker among the group exposed to negatively-skewed information. These findings reveal some important insights into how easily consumer attitudes toward new technologies can be shaped through the presentation of lopsided information and call for further in-depth research in this important yet under-researched field.

The disruptive impact of blockchain technologies can be felt across numerous industries as it threatens to disrupt existing business models and economic structures. To better understand this impact, academic researchers regularly apply well-established theories and methods. The vast majority of these approaches are based on multivariate methods that rely on average behavior and treat extreme cases as outliers. However, as recent history has shown, current developments in blockchain and cryptocurrencies are frequently characterized by aberrant behavior and unexpected events that shape individuals’ perceptions, market behavior, and public policymaking. In this paper, I apply various scenario tools to identify such extreme scenarios and illustrate their underlying structure as bundles of interdependent factors. Using the case of Bitcoin, I illustrate that the identification of extreme positive and negative scenarios is complex and heavily depends on underlying economic assumptions. I present three scenarios in which Bitcoin is characterized as a financial savior, as a severe threat to economic stability, or as a substitute to overcome several shortcomings of the existing financial system. The research questions that can be derived from these scenarios bridge behavioral and design science research and provide a fertile ground for impactful future research.

Never in history have global supply-chain relationships in high-tech electronics firms been more sophisticated, complicated, and almost always tied in some major aspect to China. This research examines how interorganizational (IO) cooperation impacts performance and what role relationship learning and information technology (IT) integration play in the value-creation process for Chinese suppliers in business-to-business (B2B) supply chains. We examine this issue using data collected from face-to-face interviews with supply chain managers and executives from 1,004 Chinese high-tech electronic component suppliers. The results strongly support the hypothesis that IO cooperation improves a supplier's performance regarding both its major customer and overall marketplace. Relationship learning and IT integration are important mediating variables that drive performance. The strongest effect in our study was the influence of IO cooperation on relationship learning. A unique aspect of this study is that it focuses on a large sample of a specific supplier type—high-tech Chinese suppliers. This, combined with the fact that the sampled companies were involved in manufacturing 13 different product groups, greatly increases the generalizability of the results.

The proliferation of sophisticated e-commerce platforms coupled with mobile applications has ignited growth in business-to-consumer (B2C) commerce, reshaped organizational structures, and revamped value creation processes. Simultaneously, new technologies have altered the dynamics of brand marketing, enabling a broader reach and more personalized targeting aimed at increasing brand trust and enhancing customer loyalty. Today, the Internet allows marketers to penetrate deeper into their existing markets, create new online marketplaces and to generate new demand. This dynamic market engagement uses new technologies to target consumers more effectively. In this conceptual paper, we discuss how blockchain technology can potentially impact a firm's marketing activities. More specifically, we illustrate how blockchain technology acts as incremental innovation, empowering the consumer-centric paradigm. Moreover, blockchain technology fosters disintermediation, aids in combatting click fraud, reinforces trust and transparency, enables enhanced privacy protection, empowers security, and enables creative loyalty programs. We present six propositions that will guide future blockchain-related research in the area of marketing.

Background: Companies partaking in modern supply chains face numerous intra- and interorganizational barriers when it comes to the adoption of blockchain technology. Empirical research is missing that explores how exactly these barriers can be overcome. In this paper we first explore barriers that organizations need to overcome to successfully deploy blockchain technology. In a second step, we investigate the agrifood industry and highlight differences in coping strategies between incumbents and start-ups. Methods: We conducted a quantitative survey with 190 supply chain experts to identify barriers and an in-depth qualitative study that included 10 expert interviews to better understand the current situation in agrifood organizations. Results: The findings from the quantitative study show that the most relevant organizational barrier to blockchain adoption is the widespread lack of understanding of the technology and its potential benefits. In the qualitative study we illustrate how various intra- and interorganizational barriers can be overcome and how the resources and capabilities differ between incumbents and start-ups. Conclusions: Our results provide academics with a better understanding of the relevant barriers and bridges of blockchain adoption. Practitioners benefit from learning about the resources and capabilities they need to deploy in order to benefit from blockchain technology.

The emergence of blockchain technology has sparked significant attention from the supply chain management (SCM) and logistics communities. In this paper, we present the results from a thorough bibliometric review that analytically and objectively identifies the intellectual structure of this field, the seminal papers, and the most influential scholars. We employ a knowledge domain visualization technique to generate insights that go beyond other review studies on blockchain research within logistics and SCM. The analysis starts with selecting a total of 628 papers from Scopus and the Web of Science that were published during 2016–2020. The bibliometric analysis output demonstrates that the number of blockchain papers has rapidly increased since 2017. The most productive researchers are from the USA, China, and India. The top academic institutions contributing to the literature are also identified. Based on network analyses, we found that the literature concentrates mainly on the conceptualization of blockchain; its potentials for supply chain sustainability; its adoption triggers and barriers; and its role in supporting supply chain agility, trust, protection of intellectual property, and food/perishable supply chains. Besides systematically mapping the literature, we identify several research gaps and propose numerous actionable research directions for the future. This study enriches the extant blockchain literature, provides a timely snapshot of the current state of research, and examines the knowledge structure of blockchain research in logistics and SCM with the help of evidence-based scientometric methods.

Background: Researchers in logistics and supply chain management apply a multitude of methods. So far, however, the potential of textual data science has not been fully exploited to automatically analyze large chunks of textual data and to extract relevant insights. Methods: In this paper, we use data from 19 qualitative interviews with supply chain experts and illustrate how the following methods can be applied: (1) word clouds, (2) sentiment analysis, (3) topic models, (4) correspondence analysis, and (5) multidimensional scaling. Results: Word clouds show the most frequent words in a body of text. Sentiment analysis can be used to calculate polarity scores based on the sentiments that the respondents had in their interviews. Topic models cluster the texts based on dominating topics. Correspondence analysis shows the associations between the words being used and the respective managers. Multidimensional scaling allows researchers to visualize the similarities between the interviews and yields clusters of managers, which can also be used to highlight differences between companies. Conclusions: Textual data science can be applied to mine qualitative data and to extract novel knowledge. This can yield interesting insights that can supplement existing research approaches in logistics and supply chain research.

Blockchain is predicted to disrupt industries, economies, and societies. The properties of distributed ledgers allow the creation of immutable data structures that facilitate shared access in real time and enable a plethora of innovative applications. However, blockchain is not a uniform technology but rather a bundle of evolving components whose implications are notoriously hard to predict. At present, it is not clear how current trends will evolve, with technical evolution, legislation, and public policy being three contingency factors that make ongoing disruptive transformations particularly hard to predict. In light of blockchain’s potential disruptive impact, it is surprising that scenario analysis has hitherto been largely ignored in academic research. Therefore, in this paper, we introduce the technique, clarify several misconceptions, and provide examples illustrating how this method can help to overcome the limitations of existing technology impact research. We conclude that if applied correctly, scenario analysis represents the ideal tool to rigorously explore uncertain future developments and to create a comprehensive foundation for future research.

Modern supply chains have evolved into highly complex value networks and turned into a vital source of competitive advantage. However, it has become increasingly challenging to verify the source of raw materials and maintain visibility of products and merchandise while they are moving through the value chain network. The application of the Internet of Things (IoT) can help companies to observe, track, and monitor products, activities, and processes within their respective value chain networks. Other applications of IoT include product monitoring to optimize operations in warehousing‚ manufacturing, and transportation. In combination with IoT, Blockchain technology can enable a broad range of different application scenarios to enhance value chain transparency and to increase B2B trust. When combined, IoT and Blockchain technology have the potential to increase the effectiveness and efficiency of modern supply chains. The contribution of this paper is twofold. First, we illustrate how the deployment of Blockchain technology in combination with IoT infrastructure can streamline and benefit modern supply chains and enhance value chain networks. Second, we derive six research propositions outlining how Blockchain technology can impact key features of the IoT (i.e., scalability, security, immutability and auditing, information flows, traceability and interoperability, quality) and thus lay the foundation for future research projects.

Integrating triple bottom line (TBL) goals into supply chains (SCs) is a challenging task which necessitates the careful coordination of numerous stakeholders’ individual interests. Recent technological advancements can impact TBL sustainability by changing the design, structure, and management of modern SCs. Blockchain technology enables immutable data records and facilitates a shared data view along the supply chain. The Physical Internet (PI) is an overarching framework that can be applied to create a layered and comprehensive view of the SC. In this conceptual paper, I define and combine these technologies and derive several high-level research areas and research questions (RQ) to investigate adoption and management as well as structural SC issues. I suggest a theory-based research agenda for the years to come that exploits the strengths of rigorous academic research, while remaining relevant for industry. Furthermore, I suggest various well-established theories to tackle the respective research questions and provide specific directions for future research.

Recently there has been a renewed interest in formative measurement and its role in properly specified models. Formative measurement models are difficult to identify, and hence to estimate and test. Existing solutions to the identification problem are shown to not adequately represent the formative constructs of interest. We propose a new two-step approach to operationalizing a formatively measured construct that allows a closely-matched common factor equivalent to be included in any structural equation model. We provide an artificial example and an original empirical study of privacy to illustrate our approach. Detailed proofs are given in an appendix.