A Bibliometric Study on Authorship Trends and Research Themes in Knowledge Management Literature

This is the author accepted manuscript. The final version is available from IFKAD via the link in this record.The aim of the study is to identify the contribution of authors in the domain of Knowledge Management (KM). The underlying data is from two leading KM journals, namely, the Journal of Knowledge Management (JKM) and the Journal of Intellectual Capital (JIC). We downloaded articles from Thomson Reuters Web of Science (WoS),with JKM and JIC-specific searches resulting in 508 and 73 citing articles respectively. The timeframe of analysis was 2009-2016. This dataset was used to create co-citation network visualisations to provide insights into the clusters of authors and research topics. Measures such as Betweenness centrality and hubs-authorities (HITS) were used to identify significant authors and their key themes of interest. More specifically, network analysis identified six dominant research themes, it revealed a total of 14,422 authors being cited (depicted as nodes in the visualisation) with a total of 1,023,123 citations (edges). Based on the findings of this study, the paper will explore the specific themes and the intellectual turning points in KM research and its evolution. Our bibliometric analysis has practical significance for researchers since it recognises the dominant research areas, and by extension, it identifies those that are still in their infancy; the latter having the potential of representing an interesting research gap. The limitation of the study is that the underlying data is only from two journals (albeit, from the top two journals in KM), which may lead to partially biased results. In future, the aim is to also leverage the analysis to more KM journals, e.g., the top ten journals within the Serenko & Bontis (2013) most updated list

Mupirocin resistance in Staphylococcus aureus: A systematic review and meta-analysis

Objectives: Staphylococcus aureus is one of the most common pathogens causing nosocomial and community-acquired infections associated with high morbidity and mortality. Mupirocin has been increasingly used for treatment of methicillin-susceptible S. aureus (MSSA) and methicillin-resistant S. aureus (MRSA) infections. The aim of this study was to determine the prevalence of mupirocin-resistant S. aureus (MuRSA), mupirocin-resistant MRSA (MuRMRSA), high-level MuRSA (HLMuRSA) and high-level MuRMRSA (HLMuRMRSA) worldwide. Methods: Online databases including Medline, Embase and Web of Science were searched (2000�2018) to identify studies addressing the prevalence of MuRSA, MuRMRSA, HLMuRSA and HLMuRMRSA. STATA v. software was used to interpret the data. Results: Of the 2243 records identified from the databases, 30 and 63 studies fulfilled the eligibility criteria for MuRSA and MuRMRSA, respectively. Finally, 27 and 60 studies were included separately for HLMuRSA and HLMuRMRSA, respectively. The analyses revealed pooled and averaged prevalences of MuRSA, MuRMRSA, HLMuRSA and HLMuRMRSA of 7.6 95% confidence interval (CI) 6.2�9.0%, 13.8% (95% CI 12.0�15.6%), 8.5% (95% CI 6.3�10.7%) and 8.1% (95% CI 6.8�9.4%), respectively. Conclusion: Overall, these results show a global increase in the prevalence of HLMuRSA and HLMuRMRSA among clinical S. aureus isolates over time. However, there was only a significant increase in the prevalence of MuRMRSA compared with the other categories, especially MuRSA. Since mupirocin remains the most effective antibiotic for MSSA and MRSA decolonisation both in patients and healthcare personnel, a reduction of its effectiveness presents a risk for invasive infection. Monitoring of mupirocin resistance development remains critical. © 2019 International Society for Antimicrobial Chemotherap

Global genotype distribution of human clinical isolates of New Delhi metallo-β-lactamase-producing Klebsiella pneumoniae; A systematic review

Background and Aim: The global rise of antimicrobial resistance among bacterial strains is a rapidly growing challenge and is becoming a major public health concern. This study documents the worldwide spread and genotype distribution of human clinical isolates of New Delhi metallo-β-lactamase-producing Klebsiella pneumoniae (NPKP). Methods: Several international databases, including Web of Science, Embase and Medline were searched (2010 - 2019) to identify studies addressing the frequency of NPKP regionally or worldwide. Results: Of 4779 articles identified, 202 studies fulfilled the eligibility criteria and were included in our analysis. The frequency of NPKP in Asia, Europe, America, Africa and Oceania was 64.6, 20.1, 9.0, 5.6 and 0.4, respectively. The most prevalent sequence types (STs) among NPKP were ST11, ST290, ST147, ST340, ST15, ST278 and ST14 based on published studies. Conclusion: The dissemination of blaNDM variants in different STs among NPKP in the various region of world is a serious concern to public health. The prevalence of NPKP should be controlled by comprehensive infection control measures and optimization of antibiotic therapy. © 202

Promoting menstrual health among persian adolescent girls from low socioeconomic backgrounds: a quasi-experimental study

<p>Abstract</p> <p>Background</p> <p>Research in the past decade has revealed average to poor menstrual health among many Iranian girls. The present study investigated the effectiveness of a health promotion project on improving menstrual health in adolescent girls in Iran.</p> <p>Methods</p> <p>A quasi-experimental study was conducted to evaluate the effectiveness of the health intervention program. A total of 698 students (study participants and controls) in several schools in Mazandaran province, Iran were included. The project comprised 10 two-hour educational sessions. Educational topics included the significance of adolescence, physical and emotional changes during adolescence, pubertal and menstruation health and premenstrual syndrome. A self-administered questionnaire measuring demographic characteristics, behaviors during menstruation, menstrual patterns, sources of information about menstruation and personal health data was administered. The questionnaire was administered to all participating students after the experimental group received the training.</p> <p>Results</p> <p>Among the most significant results was the impact of educational sessions on bathing and genital hygiene. A total of 61.6% in the experimental group compared with 49.3% in the control group engaged in usual bathing during menstruation (p = 0.002). Individual health status was significantly statistically correlated with menstrual health. Attitude towards menstruation was also significantly related to menstrual health.</p> <p>Conclusions</p> <p>The present study confirms that educational interventions, such as the health promotion project in this study, can be quite effective in promoting menstrual health.</p

Assessing and Selecting Sustainable and Resilient Suppliers in Agri-Food Supply Chains Using Artificial Intelligence: A Short Review

[EN] The supplier evaluation and selection process is critical to increase the sustainability and resilience of the agri-food supply chain. Therefore, in this sector, it is necessary to consider sustainability and resilience criteria in the supplier evaluation and selection process. The use of arti¿cial intelligence techniques allows managing of a lot of information and the reduction of uncertainty for decision making. The objective of this article is to analyze articles that address the selection of suppliers in agrifood supply chains that pursue to increase their sustainability and resilience by using arti¿cial intelligence techniques to analyze the techniques and criteria used and draw conclusions.Authors of this publication acknowledge the contribution of the Project 691249, RUC-APS "Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems" (www.ruc-aps.eu), funded by the European Union under their funding scheme H2020-MSCA-RISE-2015.Zavala-Alcívar, A.; Verdecho Sáez, MJ.; Alfaro Saiz, JJ. (2020). Assessing and Selecting Sustainable and Resilient Suppliers in Agri-Food Supply Chains Using Artificial Intelligence: A Short Review. IFIP Advances in Information and Communication Technology. 598:501-510. https://doi.org/10.1007/978-3-030-62412-5_41S501510598Brandenburg, M., Govindan, K., Sarkis, J., Seuring, S.: Quantitative models for sustainable supply chain management: developments and directions. Eur. J. Oper. Res. 233, 299–312 (2014)Ocampo, L.A., Abad, G.K.M., Cabusas, K.G.L., Padon, M.L.A., Sevilla, N.C.: Recent approaches to supplier selection: a review of literature within 2006–2016. Int. J. Integr. Supply Manage. 12, 22–68 (2018)Valipour, S., Safaei, A.: A resilience approach for supplier selection: using Fuzzy analytic network process and grey VIKOR techniques. J. Clean. Prod. 161, 431–451 (2017)Amindoust, A.: A resilient-sustainable based supplier selection model using a hybrid intelligent method. Comput. Ind. Eng. 126, 122–135 (2018)Zavala-Alcívar, A., Verdecho, M.-J., Alfaro-Saiz, J.-J.: A conceptual framework to manage resilience and increase sustainability in the supply chain. Sustainability 12(16), 6300 (2020)Villalobos, J.R., Soto-Silva, W.E., González-Araya, M.C., González-Ramirez, R.G.: Research directions in technology development to support real-time decisions of fresh produce logistics: A review and research agenda. Comput. Electron. Agric. 167, 105092 (2019)Ristono, A., Santoso, P.B., Tama, I.P.: A literature review of design of criteria for supplier selection. J. Ind. Eng. Manage. 11, 680–696 (2018)Torres-Ruiz, A., Ravindran, A.R.: Multiple criteria framework for the sustainability risk assessment of a supplier portfolio. J. Clean. Prod. 172, 4478–4493 (2018)Setak, M., Sharifi, S., Alimohammadian, A.: Supplier selection and order allocation models in supply chain management: a review. World Appl. Sci. J. 18, 55–72 (2012)Ravindran, A.R., Warsing, D.P.: Supplier selection models and methods. In: Supply Chain Engineering: Models and Applications. Taylor and Francis Group, Boca Raton, Florida (2013)De Boer, L., Labro, E., Morlacchi, P.: A review of methods supporting supplier selection. Eur. J. Purch. Supply Manage. 7, 75–89 (2011)De Felice, F., Deldoost, M.H., Faizollahi, M., Petrillo, A.: Performance measurement model for the supplier selection based on AHP. Int. J. Eng. Bus. Manag. 7, 1–13 (2015)Zimmer, K., Fröhling, M., Schultmann, F.: Sustainable supplier management – a review of models supporting sustainable supplier selection, monitoring and development. Int. J. Prod. Res. 54, 1412–1442 (2016)Christopher, M., Peck, H.: Building the resilient supply chain. Int. J. Logist. Manag. 15, 1–14 (2014)Ali, A., Mahfouz, A., Arisha, A.: Analysing supply chain resilience: integrating the constructs in a concept mapping framework via a systematic literature review. Supply Chain Manage. 22, 16–39 (2017)Verdecho, M., Alarcón-Valero, F., Pérez-Perales, D., et al.: A methodology to select suppliers to increase sustainability within supply chains. Cent. Eur. J. Oper. Res. (2020). https://doi.org/10.1007/s10100-019-00668-3Rabelo, L., Bhide, S., Gutierrez, E.: Artificial Intelligence: Advances in Research and Applications. Nova Science Publishers, Inc., Department of Industrial Engineering and Management Systems, University of Central Florida, Orlando, FL, United States (2017)Denyer, D., Tranfield, D.: Producing a systematic review. In: The Sage Handbook of Organizational Research Methods. SAGE Publications Ltd., pp. 671–689 (2019)Chen, Y.-J.: Structured methodology for supplier selection and evaluation in a supply chain. Inf. Sci. (Ny) 181, 1651–1670 (2011)Hamdi, F., Ghorbel, A., Masmoudi, F., Dupont, L.: Optimization of a supply portfolio in the context of supply chain risk management: literature review. J. Intell. Manuf. 29(4), 763–788 (2015). https://doi.org/10.1007/s10845-015-1128-3Kumar, V., Srinivasan, S., Das, S.: Optimal solution for supplier selection based on SMART fuzzy case base approach. In: 2014 Joint 7th International Conference on Soft Computing and Intelligent Systems. SCIS 2014 and 15th International Symposium on Advanced Intelligent Systems. ISIS 2014, Institute of Electrical and Electronics Engineers Inc., Department of Computer Science, IISJ Yokohama, Tokai Chiba, Japan, pp. 386–391 (2014)Jahani, A., Murad, M.A.A., bin Sulaiman, M.N., Selamat, M.H.: An agent-based supplier selection framework: Fuzzy case-based reasoning perspective. Strateg. Outsourcing 8, 180–205 (2015)Wang, Q.: Hybrid knowledge-based flexible supplier selection. In: 8th International Conference on Management of e-Commerce and e-Government. ICMeCG 2014. Institute of Electrical and Electronics Engineers Inc., Department of Information Management, Shanghai Finance University, Shanghai, China, pp. 235–239 (2014)Bai, C., Sarkis, J.: Green supplier development: analytical evaluation using rough set theory. J. Clean. Prod. 18, 1200–1210 (2010)Bai, C., Sarkis, J.: Integrating sustainability into supplier selection with grey system and rough set methodologies. Int. J. Prod. Econ. 124, 252–264 (2010)Guo, F., Lu, Q.: Partner selection optimization model of agricultural enterprises in supply chain. Adv. J. Food Sci. Technol. 5, 1285–1291 (2013)Azadnia, A.H., Saman, M.Z.M., Wong, K.Y.: Sustainable supplier selection and order lot-sizing: an integrated multi-objective decision-making process. Int. J. Prod. Res. 53, 383–408 (2015)Miranda-Ackerman, M.A., Azzaro-Pantel, C., Aguilar-Lasserre, A.A.: A green supply chain network design framework for the processed food industry: application to the orange juice agrofood cluster. Comput. Ind. Eng. 109, 369–389 (2017)Hajikhani, A., Khalilzadeh, M., Sadjadi, S.J.: A fuzzy multi-objective multi-product supplier selection and order-allocation problem in supply chain under coverage and price considerations: an urban agricultural case study. Sci. Iran. 25, 431–449 (2018)Zhang, H., Cui, Y.: A model combining a Bayesian network with a modified genetic algorithm for green supplier selection. Simulation 95, 1165–1183 (2019)Yadav, S., Garg, D., Luthra, S.: Selection of third-party logistics services for internet of things-based agriculture supply chain management. Int. J. Logist. Syst. Manage. 35, 204–230 (2020)Yazdani, M., Wang, Z.X., Chan, F.T.S.: A decision support model based on the combined structure of DEMATEL, QFD and fuzzy values. Soft. Comput. 24(16), 12449–12468 (2020). https://doi.org/10.1007/s00500-020-04685-2Zhang, H., Feng, H., Cui, Y., Wang, Y.: A fuzzy Bayesian network model for quality control in O2O e-commerce. Int. J. Comput. Commun. Control 15(1), (2020). article number 1003. https://doi.org/10.15837/ijccc.2020.1.3783Amiri, S.A.H.S., Zahedi, A., Kazemi, M., Soroor, J., Hajiaghaei-Keshteli, M.: Determination of the optimal sales level of perishable goods in a two-echelon supply chain network. Comput. Ind. Eng. 139, 106156 (2020)Roy, S., et al.: A framework for sustainable supplier selection with transportation criteria. Int. J. Sustain. Eng. 13(2), 77–92 (2020)Parkouhi, S.V., Ghadikolaei, A.S., Lajimi, H.F.: Resilient supplier selection and segmentation in grey environment. J. Clean. Prod. 207, 1123–1137 (2019)Camarinha-Matos, L.M., Afsarmanesh, H., Galeano, N., Molina, A.: Collaborative networked organizations – concepts and practice in manufacturing enterprises. Comput. Ind. Eng. 57, 46–60 (2009)Lezoche, M., Panetto, H., Kacprzyk, J., Hernandez, J., Díaz, M.A.: Agri-food 4.0: a survey of the supply chains and technologies for the future agriculture. Comput. Ind. 117, 103187 (2020)Alikhani, R., Torabi, S., Altay, N.: Strategic supplier selection under sustainability and risk criteria. Int. J. Prod. Econ. 208, 69–82 (2019

Researcher’s mobility in location and disciplinary focus: Bibliometric data utilization for Finland-based scholars for the duration of 2008-2018

Scientific discoveries are a result of global collaboration and often collaborations are multidisciplinary in nature. A core element of these successful collaborations will materialize trough researcher’s mobility in location and disciplinary focus. Researchers experience a numerous opportunity to practice locational mobility throughout their carriers as well as conducting a multidisciplinary research. Both changes have short- and long-term impact on individual researchers and science, technology and innovation system which has immediate interest for public and private research and development funding mechanisms. With advancement in data science tools and increasing of computational capacities, we are able to utilize bibliometric data for calculating researcher’s mobility on location and disciplinary focus over time. We looked at Finland as a case and by incorporating the analytical procedures, the processed data is capable to deliver insights for researchers mobilities between cities over time as well as disciplinary change over the course of time. The dataset is consists of identified Finland based scholar’s mobility (location and disciplinary focus) over the courses of 10 years (2008-2018). Clarivate Analytics’s Web of Science (WoS) is selected as the data source for compiling the dataset. We consider the WoS to be a more appropriate database for our compiled data set for several reasons. First, as a global citation database and comprehensive platform with over 159 million records and over 1.7 billion cited references, the WoS can track ideas across time and disciplines. Second, comparative and longitudinal studies have shown a consistent and reasonably stable quarterly growth for both publications and citations in the WoS Core Collection database. Third, WoS data structure is favorable so to consistently construct the scholars change of affiliation and subject category focus much accurately compared to other indexing services. We used the ”Advance Search” in the Web of Science and selected Core Collection database in order to search for all publication types between 2008-2018 where at least one of the authors has been based in Finland. From the raw bibliometric data retrieved, certain procedure took place so analyze, filter, clean and process the change of authors’ affiliation over their career trajectory also picking up the occasions where disciplinary focus has changed in authors publication profile. This dataset can reveal hidden dynamics on scholar’s career progress. The dataset (if) combined with funding information and mission-oriented policies can evaluate the long-lasting effect of instruments in mobilizing researchers, steering research agendas and consequently the resulted impacts. The final data set is provided in four individual XLSX files

Chemo-mechanical modelling of swelling and crosslinking reaction kinetics in alginate hydrogels: A novel theory and its numerical implementation

Hydrogels are mechanically stabilized through the action of external agents which induce the formation of crosslinks in the polymer network as a consequence of transport and reactive mechanisms. Crosslinking increases the stiffness of the construct, produces inelastic deforma-tions in the polymer network and interacts with the swelling capacity of hydrogels. The control of this process is hence crucial for fulfilling functional criteria in several technological fields, like drug-delivery or bioprinting. Nevertheless, experimental approaches for monitoring the crosslinking kinetics with the required resolution are currently missing. The development of new computational models in the field might open the way to novel investigation tools. This paper presents a thermodynamically consistent chemo-mechanical model in large deformation for reactive-diffusive mechanisms occurring during crosslinking in alginate hydrogels. The system accounts for shrinking and swelling effects, fluid movements, as well as the reaction kinetics of calcium-induced crosslinking. Crosslinks alter mechanical and diffusive properties in the hydrogel. Moreover, on the basis of thermodynamic arguments, internal stresses directly affect the crosslinking kinetics, revealing a two-way coupling between mechanics and chemistry. The model is implemented in a finite element framework, considering a monolithic coupling between chemical transport and mechanics. The computational framework allows characterizing the (experimentally inaccessible) heterogeneous distribution of mechano-chemical quantities and properties in the hydrogel. Parametric campaigns of simulations are presented to investigate hydrogels' behaviour and compare numerical outcomes with available experimental evidence