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The purpose of this study is to systematically review the existing literature on the blood supply chain (BSC) from a network design perspective and highlight the research gaps in this area. Moreover, it also aims to pinpoint new research opportunities based on the recent innovative technologies for the BSC network design.

The study gives a comprehensive systematic review of the BSC network design studies until October 2021. This review was carried out in accordance with preferred reporting items for systematic reviews and meta-analyses (PRISMA). In the literature review, a total of 87 studies were analyzed under six main categories as model structure, application model, solution approach, problem type, the parties of the supply chain and innovative technologies.

The results of the study present the researchers’ tendencies and preferences when designing their BSC network models.

The study presents a guide for researchers and practitioners on BSC from the point of view of network design and encourages adopting innovative technologies in their BSC network designs.

The study provides a comprehensive systematic review of related studies from the BSC network design perspective and explores research gaps in the collection and distribution processes. Furthermore, it addresses innovative research opportunities by using innovative technologies in the area of BSC network design.

The objective of this study is to investigate the role of blockchain in reducing the impact of barriers to humanitarian supply chain management (HSCM) using a list of blockchain benefits.

A decision aid was used to explore the suitability of blockchain in humanitarian supply chains. To achieve that, first, a list of barriers to HSCM was identified. Then, the intuitionistic fuzzy decision-making trial and evaluation laboratory (IF–DEMATEL) method was utilized to determine the relationships and the level of interdependencies among the criteria. Finally, the intuitionistic fuzzyanalytic network process (IF–ANP) technique was employed, as it successfully handles dependencies among the criteria.

The findings of this study suggest that interorganizational barriers are the most suitable ones, the impacts of which blockchain may alleviate. This study further suggests that trust turned out to be the most significant benefit criterion for the analysis.

The readers should construe the findings of this study with caution since it was carried out using the data collected from the experts of a particular country. Moreover, the proposed decision aid contemplates a limited set of criteria to assess a possible role of blockchain in overcoming the barriers to HSCM.

The findings of this study can assist humanitarian supply chain managers to make more judicious assessments on whether they implement the blockchain in humanitarian supply chain operations. Specifically, this research may help decision makers to identify the certain barriers, the impact of which may be reduced by using the blockchain. The findings of this research will also help various decision makers make more rational decisions and allocate their resources more effectively.

To the best of authors’ knowledge, no single study exists to investigate the role of blockchain in reducing the impact of barriers to HSCM using an intuitionistic fuzzy multi-criteria decision-making approach.

The objective of this study is to assess quantitatively how feasible blockchain is for various industries, such as logistics and supply chain, health, energy, finance, automotive, pharmaceutical and agriculture and food using a comprehensive list of indicators.

A decision aid was applied to the problem of identifying the feasibility of blockchain in Turkish industries. To this end, first, a set of indicators was identified. Then, the fuzzy AHP and fuzzy TOPSIS were utilized to assess the feasibility comparatively using the data gathered from a group of experts. Finally, a scenario analysis was conducted to ensure the consistency of our evaluation.

The findings of this study suggest that comparatively, logistics and supply chain, finance and health industries are the most feasible industries for blockchain. This study further suggests that blockchain is the least feasible for the automotive industry compared to the rest of the identified industries.

It is cumbersome to find out the respondents who have sufficient knowledge of both blockchain and the identified industries. Even if we took the utmost care in identifying the right respondents, we limited our search to the biggest industrial hubs of Turkey.

The findings of this research may help various decision-makers employed in governments, conglomerates, software and consulting firms and national research institutions make more informed decisions and allocate their resources more effectively.

To this date, the current studies have solely investigated possible research opportunities in blockchain and demonstrated several blockchain applications in stand-alone cases. To the best of our knowledge, however, no single study exists that evaluates the feasibility of blockchain comparatively and holistically among a group of industries using various indicators.

The main purpose of this paper is to investigate the relationships between seven antecedent factors (R&D strategy, top management support (TMS), customer focus (CF), organizational learning capability (OLC), creative capability (CC), organizational collaboration (OC), and supplier relationship (SR)), two innovation types (product and process), and firm performance (FP).

The paper formulates 16 hypotheses from the literature review. These hypotheses are tested using structural equation modeling with data collected from 270 managers of small and medium‐sized enterprises (SMEs) located in Turkish science and technology parks (STPs).

The findings indicate that both of product and process innovation have a strong and positive association with FP. While antecedents such as R&D strategy, TMS, CF, CC, and SR have significant impact on product innovation, other antecedents such as OLC and OC have a significant and positive impact on process innovation.

The results of this study could be used by any managers of SMEs located in STPs to improve successful innovation projects. The results also provide companies operating in Turkish STPs with useful information on how their policies and actions might affect firm innovation.

The paper provides a clarification of the reasons that may be behind a positive, a negative, or a non‐significant effect of the many antecedents on the product and process in SMEs located in Turkish STPs.

This paper seeks to provide new solutions to cargo companies’ service quality efforts by integrating different scientific methodologies.

Strengths and weaknesses of logistics services of a well known cargo company in Turkey are defined by using a service quality scale (SERVQUAL), service quality attributes are categorized using the Kano model in order to see how well these attributes are able to satisfy customer needs, and findings are transferred to quality function deployment (QFD).

The findings of the Kano model show that ten of the 27 service quality attributes can be categorized as “attractive”, implying the maximum effect on consumer satisfaction. Through the customer priority level of QFD, the three most important service quality attributes are found to be: VIP Service, informing customers about delivery time before sending, and taking deliveries from customers’ addresses. Also, strengthening information technology infrastructure is the most important technical requirement to focus with the highest technical importance level.

The study involves only one cargo company, it concerns just Trabzon city center branch offices and its sample includes only individual customers instead of individual and institutional customers together.

Offering a case study, the paper presents a guide for cargo companies to employ different scientific methodologies in their service quality development efforts.

Intending to offer scientific approaches to cargo companies as a tool of development in their practical procedures, the paper tries to bridge the current gap between academicians and practitioners and adds to the relatively limited theoretical literature.

The purpose of this paper is to explore the teaching performance of Turkish Business Schools (BSs). It also aims to determine the degree of importance of factors affecting the teaching performance of Turkish BSs. The final objective is to test the functionality and applicability of the model.

This study presents a ranking approach based on grey relational analysis (GRA). While evaluating the BSs, data were collected for 19 Turkish BSs in terms of five main criteria such as OSS score; Number of faculty members; Number of students per faculty member; the mean of KPSS score; and the standard deviation of KPSS score. In the analysis, three weighted methods were integrated into the GRA in order to weight the criteria.

According to this result, the main factor influencing the teaching performance of Turkish BSs is the OSS score. This study can also confirm that the results obtained from the ranking orders using the proposed methods are reliable and these results can help decision makers to identify the best alternative.

In order to provide benchmarking data more effectively, in future, it would be helpful to collect data from both foundation and state universities with a research focus. Moreover, as an interesting suggestion for future research, fuzzy environment may be further integrated into the framework of GRA.

In contrast to prior research, this study makes comparisons based on the scores of national exams instead of different bibliometric indicators. Furthermore, there are no studies which have used GRA and these weighted methods as combined in education sector.

Blockchain, a groundbreaking technology that recently surfaced, is under thorough scrutiny due to its prospective utility across different sectors. This research aims to delve into and assess the cognitive elements that impact the integration of blockchain technology (BT) within library environments.

Utilizing the Stimulus–Organism–Response (SOR) theory, this research aims to facilitate the implementation of BT within academic institution libraries and provide valuable insights for managerial decision-making. A two-staged deep learning structural equation modelling artificial neural network (ANN) analysis was conducted on 583 computer experts affiliated with academic institutions across various countries to gather relevant information.

The research model can correspondingly expound 71% and 60% of the variance in trust and adoption intention of BT in libraries, where ANN results indicate that perceived possession is the primary predictor, with a technical capability factor that has a normalized significance of 84%. The study successfully identified the relationship of each variable of our conceptual model.

Unlike the SOR theory framework that uses a linear model and theoretically assumes that all relationships are significant, to the best of the authors’ knowledge, it is the first study to validate ANN and SEM in a library context successfully. The results of the two-step PLS–SEM and ANN technique demonstrate that the usage of ANN validates the PLS–SEM analysis. ANN can represent complicated linear and nonlinear connections with higher prediction accuracy than SEM approaches. Also, an importance-performance Map analysis of the PLS–SEM data offers a more detailed insight into each factor's significance and performance.