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The purpose of this paper is to find and prioritize human factors affecting entrepreneurial resilience.

The statistical population consists of prominent Iranian university professors in this field, and the statistical sample is ten of them randomly. A researcher-made questionnaire was used for data collection. After a comprehensive review of the theoretical foundations, the research model was formed with 5 main indices and 21 sub-indices. Fuzzy decision-making trial and evaluation laboratory (DEMATEL)-based (DANP) technique and MATLAB software was used for analysis.

Indicators of Values and Beliefs (A3) and Motivation Index (E5) as Influential Indicators and indicators of personal attributes (S1), formal and informal relationships (R²) and human capital (C4) are effective indicators of entrepreneurial resilience. In the final rankings, formal and informal relationships had the highest weight with 0.263 and the lowest with priority and motivation index with 0.080. In addition to the final rankings of the sub-indices, the indicators of first-hand experience, recognition of opportunities and consulting services were given the highest weight.

This study proposes that resilience is a real-life process and not just a list of each characteristic. All human beings have an innate ability to be resilient, but resilience is a learned and learned behavior, and the emphasis of experts is on the learning of various resilience skills.

This study contributes to the field of entrepreneurship by examining the institutional backgrounds of entrepreneurship resilience.

The vaccine supply chain (VSC) performance remains under stress during pandemic outbreaks than conventional vaccination drives due to desired vaccination coverage. Therefore, it is essential to identify the crucial performance objectives (POs) and their interrelationship structure and prioritize them to improve performance in a pandemic VSC.

This study combines the decision-making trial and evaluation laboratory based analytic network process (DANP) method with spherical fuzzy sets (SFS) to explore critical POs of the pandemic VSC in the balanced scorecard framework. The SFS theory tackles the uncertainty of POs and DANP interlaced causal relationships among crucial POs to the pandemic VSC while ranking them for prioritization.

This work identifies 32 issues associated with pandemic VSC and maps them against 13 POs. Effective communication, adequate health financing and operating cost optimization are the most critical POs, and operational issues listed under them must be prioritized to improve the overall VSC performance for future pandemics. The relationship structure among these POs is also summarized using the balanced scorecard framework in a strategy map.

The strategy map proposed in this study can help practitioners to address the causality among different POs and underlying issues for the sudden expansion of vaccination programs during pandemics from an economic, social and operational perspective.

To the best of the authors’ knowledge, this is the first empirical study to suggest improving the VSC performance during the pandemic by focusing on the causative relationship and priority of different detected POs.

In this research, extracting the innovation drivers of successful crowdfunding from the literature review, screening them for the entrepreneurial small- and medium-sized enterprises (SMEs), analysing the cause-and-effect relationship amongst them and presenting a basic causal conceptual model and eventually determining the importance/weight of each relevant driver were the primary purposes of this research. As a result, the authors have also designed a score function to measure the future innovative crowdfunding score for SMEs.

A multi-layer multi-criteria decision-making (MCDM) approach has been designed and employed to achieve research objectives. After extracting the initial list of drivers, Fuzzy Delphi was applied to screen the relevant innovation drivers of successful crowdfunding for entrepreneurial SMEs. Decision-making trial and evaluation laboratory (DEMATEL) was used to analyse the cause-and-effect relationship amongst the drivers and illustrate a basic conceptual model. Analytical network process (ANP) and Stepwise Weight Assessment Ratio Analysis (SWARA) were applied to determine the importance of the drivers and by aggregating them to measure the innovative crowdfunding score.

Initially, 28 innovation drivers of successful crowdfunding were extracted from the literature. Then by employing the first-round Delphi fuzzy method amongst 15 international entrepreneurs in SMEs, the relevant drivers, including eleven items, were screened and selected. Then by implementing the DEMATEL method, the relationship amongst these screened drivers was identified, and seven drivers were determined as causes and the rest as effects. Subsequently, a conceptual model based on the causal analysis of the drivers from the DEMATEL method was designed. Eventually, by aggregating the weight of drivers emanated from SWARA, DEMATEL and DANP, the score function for measuring the situation of an SME was designed.

According to the crowdfunding scores in this research from entrepreneurs of SMEs, influential factors in developing countries were recognised as two times more prominent in developing countries. This might be rooted in the circumstances of developing countries where many startups and SMEs are emerging in vast areas and different fields due to investment in innovation management. In these countries, the authorities and officials support these companies to empower their capabilities and innovative ideas to (1) deal with the severe competitive market and (2) benefit from them as potential economic engines. Therefore, crowdfunding platforms and public initiatives can be considered one of the most effective government supports, which may involve financial risks.

To the best knowledge of the authors, investigating the innovation drivers of successful crowdfunding via quantitative analysis by multi-layer decision-making approaches has not been considered previously. Moreover, the authors have designed a crowdfunding score function to determine the situation of an entrepreneurial SME in this area. A combination of different MCDM methods, including Fuzzy Delphi, SWARA, DEMATEL, ANP and DANP, to investigate the innovation drivers of successful crowdfunding in SMEs has not been considered previously.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

The study aims to determine the impact of sustainable manufacturing on environmental performance through government regulation and eco-innovation in Indonesian small and medium-sized enterprises (SMEs).

The results indicate sustainable manufacturing plays a significant role in SMEs' environmental performance and regulations, and eco-innovation can moderate it. It also reveals that government regulation has a positive and significant effect on environmental performance. Moreover, eco-innovation has a positive and significant effect on environmental performance.

The findings of this study indicate that SMEs can embrace sustainable manufacturing practices and achieve their long-term sustainability goals by adhering to regulations, collaborating with stakeholders and implementing eco-friendly innovations.

This research uncovers ground-breaking perspectives on the evolution of scientific knowledge about the impact of eco-innovation, regulatory measures and sustainable manufacturing practices on the environmental performance of SMEs.

Data breaches in the US healthcare sector have more than tripled in the last decade across all states. However, to this day, no established framework ranks all states from most to least at risk for healthcare data breaches. This gap has led to a lack of proper risk identification and understanding of cyber environments at state levels.

Based on the security action cycle, the National Institute of Standards and Technology (NIST) cybersecurity framework, the risk-planning model, and the multicriteria decision-making (MCDM) literature, the paper offers an integrated multicriteria framework for prioritization in cybersecurity to address this lack and other prioritization issues in risk management in the field. The study used historical breach data between 2015 and 2021.

The findings showed that California, Texas, New York, Florida, Indiana, Pennsylvania, Massachusetts, Minnesota, Ohio, and Georgia are the states most at risk for healthcare data breaches.

The findings highlight each US state faces a different level of healthcare risk. The findings are informative for patients, crucial for privacy officers in understanding the nuances of their risk environment, and important for policy-makers who must grasp the grave disconnect between existing issues and legislative practices. Furthermore, the study suggests an association between positioning state risk and such factors as population and wealth, both avenues for future research.

Theoretically, the paper offers an integrated framework, whose basis in established security models in both academia and industry practice enables utilizing it in various prioritization scenarios in the field of cybersecurity. It further emphasizes the importance of risk identification and brings attention to different healthcare cybersecurity environments among the different US states.

This research analyzes online consumer reviews and ratings to assess e-retail order fulfillment performance. The study aims to (1) identify consumer journey touchpoints in the order fulfillment process and (2) determine their relative importance for the consumer experience.

Text mining and analytics were employed to examine over 100 m online purchase orders, along with associated consumer reviews and ratings from Amazon US. Using natural language processing techniques, the corpus of reviews was structured to pinpoint touchpoints related to order fulfillment. Reviews were then classified according to their stance (either positive or negative) toward these touchpoints. Finally, the classes were correlated with consumer rating, measured by the number of stars, to determine the relative importance of each touchpoint.

The study reveals 12 touchpoints within the order fulfillment process, which are split into three groups: delivery, packaging and returns. These touchpoints significantly influence star ratings: positive experiences elevate them, while negative ones reduce them. The findings provide a quantifiable measure of these effects, articulated in terms of star ratings, which directly reflect the influence of experiences on consumer evaluations.

The dataset utilized in this study is from the US market, which limits the generalizability of the findings to other markets. Moreover, the novel methodology used to map and quantify customer journey touchpoints requires further refinement.

In e-retail and logistics, comprehending touchpoints in the order fulfillment process is pivotal. This understanding helps improve consumer interactions and enhance satisfaction. Such insights not only drive higher conversion rates but also guide informed managerial decisions, particularly in service development.

Drawing upon consumer-generated data, this research identifies a cohesive set of touchpoints within the order fulfillment process and quantitatively evaluates their influence on consumer experience using star ratings as a metric.

Tourism is one of the upcoming service industry in India with high potentials for future growth, particularly in rural areas. Many potential barriers are affecting the growth of tourism in rural India. Therefore, it is essential to explore and prioritize the barriers to tourism growth in rural India.

Qualitative and quantitative responses from “16” experts related to tourism and hospitality management from central India are collected for this study. An integrated Multi-Criteria Decision Making (MCDM) based framework is adopted to identify and relate significant barriers to tourism growth in India.

The result of the study identified many significant barriers and their importance to tourism growth in rural India.

The findings of this study add to the knowledge base of tourism research in line with the previous literature. This study offers an in-depth understanding of barriers focusing on rural tourism growth and devising both the plan of action and the suggestive measures in dealing with rural tourism.

The study provides a robust framework by integrating Interpretive Structural Modelling(ISM) and Decision Making Trial and Evaluation Laboratory (DEMATEL) to explore and prioritizing the critical barriers to rural tourism growth in India. The results of this study can help the decision-maker to fundamentally improve the economy of India through the growth of rural tourism.