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We conducted a systematic review to explore the potential for the application of blockchain technologies for supply chain resilience in a small-scale agri-food business context.

As part of the research methodology, scientific databases such as Web of Science, Google Scholar and Scopus were used to find relevant articles for this review.

The systematic review of articles (n = 57) found that the use of blockchain technology in the small-scale agri-food business sector can reduce the risk of food fraud by assuring the provenance of food products.

Only a few papers were directly from a small-scale agribusiness context. Key challenges that limit the implementation of blockchain and other distributed ledger technologies include concerns over the disclosure of proprietary information and trade secrets, incomplete or inaccurate information, economic and technical difficulties, low levels of trust in the technology, risk of human error and poor governance of process-related issues.

The application of blockchain technology ensures that the risks and costs associated with non-compliance, product recalls and product loss are reduced. Improved communication and information sharing can increase resilience and better support provenance claims and traceability. Better customer relationships can be built, increasing supply chain efficiency and resilience.

This paper examines the role of a sustainability business model in clarifying a firm's sustainability value articulation (SVA) to achieve sustainability outcomes and examining the moderating role of supplier involvement practices SIP and technology systems integration (TSI) in attaining sustainability outcomes.

Drawing upon the foundational principles of business model innovation, specifically articulation and implementation, the authors formulated a theoretical construct and empirically validate it through analysis of data collected from 692 manufacturing firms dispersed across 23 countries.

The research shows that focusing on SVA significantly improves how a company implements sustainability efforts internally (ISI) and externally (ESI), leading to better social and environmental outcomes. It also highlights that SIP improve the relationship between SVA, ESI and ISI. Similarly, TSI boosts the effect of internal and external sustainability efforts on both social (SOP) and environmental performance (EnP).

While acknowledging the inherent constraints of survey-based research methodologies, this study offers a theoretical and verified approach for manufacturers to achieve comprehensive sustainability. It emphasizes the need for clear, actionable sustainability goals that can be met through both internal operations and external partnerships.

This study clarifies how manufacturers can implement sustainable business models, emphasizing the importance of clear sustainability goals and initiatives both within and outside the company. It highlights the dual aspects of supplier engagement through operational tactics (ESI) and strategic collaborations (SIP).

This study reveals a thrilling truth: when companies champion clear sustainability goals, they unlock powerful strategies that revolutionize practices within their walls and in their external dealings. It is not just about going green; it is about weaving financial prosperity, social responsibility and environmental stewardship into the very fabric of their business models. But there is more – by cleverly engaging suppliers and harnessing cutting-edge technology, companies are not just participants in the green revolution; they are leading it, crafting a world where business thrives alongside the planet and its people.

This research stands out for its empirical analysis of how manufacturing firms implement sustainability innovations at the plant level, an area previously underexplored despite extensive theoretical work on sustainability-centric business models.

Experiencing more frequent, system-wide disruptions, such as pandemics and geopolitical conflicts, supply chains can be largely destabilized by a lack of materials, services or components. Supply chain resilience (SCRES) constitutes the network ability to recover after and survive during such unexpected events. To enhance the understanding of SCRES as a system-wide quality, this study tests a comprehensive SCRES model with data from multiple industries.

The study proposes a theoretical framework conceptualizing SCRES as system quality, extending the classical proactive/reactive taxonomy by multiple system states consisting of the supply system properties, behaviors and responses to disruptions. Underlying hypotheses were tested using an online survey. The sample consists of 219 responses from German industries. Maximum likelihood structural equation modeling (ML-SEM) and moderation analysis were used for analyzing the survey data. The study was particularly designed to elaborate on supply chain theory.

Two pathways of parallel SCRES building were identified: proactive preparedness via anticipation and reactive responsiveness via agility. Both system responses are primarily built simultaneously rather than successively. The present study further provides empirical evidence on the central role of visibility and velocity in achieving comprehensive SCRES, while flexibility only exerts short-term support after a disruption. The study additionally points to potential “spillover effects” such as the vital role of proactive SCRES in achieving reactive responsiveness.

The present study confirms and expands existing theories on SCRES. While stressing the multidimensionality of SCRES, it theorizes the (inter-)temporal evolution of a system and offers practical guidelines for SCRES building in various industrial contexts. It thus supports the transformation toward more resilient and viable supply chains, contributing to the increasing efforts of middle-range theory building to achieve an overarching theory. The study also points to potential future research avenues.

A quantitative theoretical model is proposed to measure how productivity performance can be affected by strategic decisions related to specific competitive priorities.

This study proposes the Primary Transformation Model (PTM) and an equation to measure cause-and-effect relationships between productivity and competitive priorities.

The interdependence between productivity and competitive priorities was studied using the PTM and the proposed model indicates that strategies that improve external performance also impact internal productivity. It was also observed that the compatibility between competitive priorities depends on the initial manufacturing conditions and the implementation method adopted.

The proposed model is theoretical and, as such, is an abstraction of reality and does not consider all possible aspects. It consists of a novel approach that still requires further empirical testing. The PTM provides insights about the trade-offs between productivity and strategic objectives, as well, contributes to the ongoing research on manufacturing strategy and can be further developed in future studies.

The main practical implication is to allow companies to relate their strategic decisions to their productivity performance.

This research also contributes to societal issues by enabling firms to better align strategic objectives and operations, which ultimately allows offering products more suited to the needs of customers, thus making better use of the required resources and favoring economic growth.

The model proposed allows objective assessment of actions aiming at operational efficiency and effectiveness, in addition to providing insights into cause-and-effect relationships between productivity and competitive priorities. The model can also be used in empirical investigations on manufacturing strategy.

This study aims to examine the blockchain landscape in supply chain management by drawing insights from academic and industry literature. It identifies the key drivers, categorizes the products involved and highlights the business values achieved by early adopters of blockchain technology within the supply chain domain. Additionally, it explores fingerprinting techniques to establish a robust connection between physical products and the blockchain ledger.

The authors combined the interpretive sensemaking systematic literature review to offer insights into how organizations interpreted their business challenges and adopted blockchain technology in their specific supply chain context; content analysis (using Leximancer automated text mining software) for concept mapping visualization, facilitating the identification of key themes, trends and relationships, and qualitative thematic analysis (NVivo) for data organization, coding and enhancing the depth and efficiency of analysis.

The findings highlight the transformative potential of blockchain technology and offer valuable insights into its implementation in optimizing supply chain operations. Furthermore, it emphasizes the importance of product provenance information to consumers, with blockchain technology offering certainty and increasing customer loyalty toward brands that prioritize transparency.

This research has several limitations that should be acknowledged. First, there is a possibility that some relevant investigations may have been missed or omitted, which could impact the findings. In addition, the limited availability of literature on blockchain adoption in supply chains may restrict the scope of the conclusions. The evolving nature of blockchain adoption in supply chains also poses a limitation. As the technology is in its infancy, the authors expect that a rapidly emerging body of literature will provide more extensive evidence-based general conclusions in the future. Another limitation is the lack of information contrasting academic and industry research, which could have provided more balanced insights into the technology’s advancement. The authors attributed this limitation to the narrow collaborations between academia and industry in the field of blockchain for supply chain management.

Practitioners recognize the potential of blockchain in addressing industry-specific challenges, such as ensuring transparency and data provenance. Understanding the benefits achieved by early adopters can serve as a starting point for companies considering blockchain adoption. Blockchain technology can verify product origin, enable truthful certifications and comply with established standards, reinforcing trust among stakeholders and customers. Thus, implementing blockchain solutions can enhance brand reputation and consumer confidence by ensuring product authenticity and quality. Based on the results, companies can align their strategies and initiatives with their needs and expectations.

In essence, the integration of blockchain technology within supply chain provenance initiatives not only influences economic aspects but also brings substantial social impacts by reinforcing consumer trust, encouraging sustainable and ethical practices, combating product counterfeiting, empowering stakeholders and contributing to a more responsible, transparent and progressive socioeconomic environment.

This study consolidates current knowledge on blockchain’s capacity and identifies the specific drivers and business values associated with early blockchain adoption in supply chain provenance. Furthermore, it underscores the critical role of product fingerprinting techniques in supporting blockchain for supply chain provenance, facilitating more robust and efficient supply chain operations.

Despite the popularity of the entrepreneurial ecosystem (EE) concept, research on its value-adding activities receives less attention. Thus, in this article, the authors investigate the role of EEs in supporting global value chain (GVC) activities.

The authors employ the fuzzy-set qualitative comparative analysis (fsQCA) technique to identify practical configurations of EE’s framework and systemic conditions spurring GVC activities in 80 countries.

The findings suggest different configurations of EE`s framework and systemic conditions necessary for various GVC activities regarding input-output structure, geographical scope, upgrading, and forward and backward participation.

This study contributes to the extant literature by pioneering the EE approach to explaining GVC development. Moreover, the findings provide novel insights for understanding the EE – GVC interplay. As a result, the study offers a more nuanced understanding of how the EE supports GVC activities.

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.

Blockchain (BC) is a technological innovation that emphasizes the opposite paradigm compared to the available technology. This paradigm enables changing the firm’s business models (BMs) and has been elaborated by many experts. However, the discussion is scattered in various sources, particularly academic journals. This study aims to investigate the literature on the coexistence of BCs and BMs and depict the currently available situation that has not been discussed.

This study investigated articles focusing on the coexistence of BCs and BMs through heterogeneous academic databases, namely, Emerald, ProQuest, Taylor & Francis, ScienceDirect and Scopus. The systematic approach and development of inclusion criteria used in this study resulted in 52 key articles for further review. This systematic review followed the PRISMA framework and a timeframe between 2012 and 2022.

This study classifies literature based on specific themes, the integration of BC (interaction and evolution) and BM innovation (innovativeness, new value system and system logic), including the research design. As expected, the literature on BCs and BMs appears to be focused on particular themes since this topic appears to have grown. This study identifies gaps in the literature and describes future research to accommodate the study discrepancy.

The major limitation of this study is the research bias. Such a bias might occur due to the misinterpretations of researchers in this study. In the process of devising databases and keywords, this study identified the potential for misinterpretation. This study sought to use rigid protocols through a manual approach to mitigate the potential bias. A research bias also has the potential to arise in the literature classification. A literature categorization is performed back and forth, by referring to the theory or concept of a particular topic. The next limitation is limited access to scientific databases. This study drew upon several reputable scientific journal databases. However, the researcher considered the journal selection to be built upon a journal’s accessibility, multi-disciplinary nature and data size compared to other journals. It allows the analysis results to be biased, as they do not represent all available databases. However, the study used the available formal access to maintain the integrity of this research.

This study conducts a systematic review that discusses the coexistence of BCs and BMs. Furthermore, it provides a profound understanding of the discussion carried out through certain themes and the outlook for the future.

Supply chain vulnerability (SCV) analysis is vital for manufacturers globally because it creates a pathway for building resilient supply chains in uncertain environments. This study aims to identify drivers of SCV in the Indian manufacturing sector.

Sixteen drivers were identified from the literature review and followed by expert interviews. Interpretive structural modeling was used to determine the hierarchical structural relationship among identified SCV factors.

It was found that risk is not a board room agenda. Misaligned performance measures with incentives and lack of risk dashboard are the causal factors of SCV. Supply chain security, centralized production and distribution and lack of trust in the supply chain were driven factors.

This provides new insights to assess and prioritize initiatives for supply chain sustainability in terms of continuing business operations. The structural model provides a systemic view of SCV and helps reduce vulnerability.

A positive outlook on the impact of Industry 4.0 (I4.0) on sustainability prevails in the literature. However, some studies have highlighted potential areas of concern that have not yet been systematically addressed. The goal of this study is to challenge the assumption of a sustainable Fourth Industrial Revolution by (1) identifying the possible unintended negative impacts of I4.0 technologies on sustainability; (2) highlighting the underlying motivations and potential actions to mitigate such impacts; and (3) developing and evaluating alternative assumptions on the impacts of I4.0 technologies on sustainability.

Building on a problematization approach, a systematic literature review was conducted to develop potential alternative assumptions about the negative impacts of I4.0 on sustainability. Then, a Delphi study was carried out with 43 experts from academia and practice to evaluate the alternative assumptions. Two rounds of data collection were performed until reaching the convergence or stability of the responses.

The results highlight various unintended negative effects on environmental and social aspects that challenge the literature. The reasons behind the high/low probability of occurrence, the severity of each impact in the next five years and corrective actions are also identified. Unintended negative environmental effects are less controversial than social effects and are therefore more likely to generate widely accepted theoretical propositions. Finally, the alternative hypothesis ground is partially accepted by the panel, indicating that the problematization process has effectively opened up new perspectives for analysis.

This study is one of the few to systematically problematize the assumptions of the I4.0 and sustainability literature, generating research propositions that reveal several avenues for future research.