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Monitoring Changes Over a Training Macrocycle in Regional Age‐Group Swimmers

., 2012 ). These differences may be due to the characteristics of the stimuli used, the methodology applied and swimmers’ anthropometric characteristics ( Craig and Pendergast, 1979 ; Morais et al., 2012 ). Additionally, in accordance with a previous study ( Anderson et al., 2006 ), a SL decline and a SR increase from the beginning to the middle of the macrocycle were observed. However, with the posterior increase of anaerobic workouts, the SR increased (until week 9) as well as the SI1 (weeks 9‐12) and the SI3 (weeks 2‐12 and 9‐12), evidencing a technical quality

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Airline Service Quality Dimensions and Customer Loyalty: Empirical Evidence from Air Passengers’ in Lagos State

Abstract

Air travellers are increasingly becoming more demanding in terms of their expectations of the quality of service offered by airline carriers. Hence, operators must improve service delivery to retain their loyalty. This study investigates the relationship between airline service quality dimensions and customer loyalty among air passengers in Lagos state. Causal research design was adopted to examine the aforementioned relationship. Convenience sampling technique was used to survey 600 air travellers. Data collected from the respondents were analysed by using Pearson correlation analysis and Anova. The findings reveal that the service quality and its dimensions are positive and significantly related to each other, overall service quality and customer loyalty. The results of the study indicate no significant difference between customers’ travelling for different motives in their perception of the quality of services. It was also discovered that flight frequency was insignificantly connected to customer loyalty. In line with the above findings, the study concludes that the airline service quality improvement initiatives should begin with recognition of customers’ needs. Correspondingly, airline operators should cultivate strategies to fulfil their service promise along the service quality dimensions, most important to air travellers to enhance customer loyalty.

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Knowledge Areas Necessary for Successful NCAA Division III Certified Athletic Trainers: NCAA Division III Certified Athletic Trainers' Perceptions

-efficacy, imagery use, and adherence to rehabilitation by injured athletes. J Sport Rehabil , 2005. 14(2), 150-167. Peer, K.S., Rakich, J.S. Accreditation and continuous quality improvement in athletic training education. J Athl Training , 2000. 35(2), 188-193. Robbins, J.E., Rosenfeld, L.B. Athletes' perceptions of social support provided by their head coach, assistant coach, and athletic trainer, pre-injury and during rehabilitation. Journal of Sport Behavior , 2001. 24(3), 277-297. Rockwell, M

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Breathing Air Purification for Hyperbaric Purposes, Part II

military applications, Gdynia 2009 7. Gerber T: Statistical process control-quality improvement with the use of Statistica-Stat Soft package, Cracow 2000 8. Kłos R: Data obtaining and designing experiments in diving technique, PHR No.4 (13), Gdynia 2005 9. Kłos R: PHR Model Outcomes 10. Pietraszek J. Experiment Planning-Possibility or Necessity-Stat Soft, Cracow 2004 11. Szczęśniak B, Zasadzień M, Wapienik Ł. The use of PARETO analysis and ISHIKAWA diagram in analysis of causes of rejections

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Analysis of the Breathing Air Production Process for Hyperbaric Purposes

in marine rescue services of the Polish Navy. Warsaw: lack of the author’s name, 2014. 9. Woźniak A. Analysis of the process of production of breathing air for hyperbaric purposes. Gdynia: PTMiTH, 2017. ISBN 978-83-938-322-4-8. 10. Woźniak A. Breathing air purification for hyperbaric purposes p.II. Polish Hyperbaric Research. 1, 2015, 50, pp. 31-46. DOI:10.1515/phr-2015-0023. 11. Montgomery D.C. Statistical quality control. 6th Edition. New York : John Wiley & Sons Inc., 2009. ISBN 978-0-470-16992-6. 12. Gerber A. Statistical process control-quality

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Effectiveness evaluation of sources of supply and systems filter in production process of breathing air

B ibliography 1. Allen T.T.2006 Introduction engineering statistics and six sigma London: Springer Ltd., 2006; 2. Antosz K. The application of R@R methods in the analysis of selected measurement systems Technologia i Automatyzacja Montażu 3/2012; ISSN 1230-7661, pp. 57-61; 3. ADivP-04 Diving Gas Quality ed.A ver.1 2013; 4. Gerber T: Statistical process control-quality improvement with the use of Statistica-Stat Soft package, Cracow 2000 ISBN 83-912346-2-2; 5. Instruction regarding maritime military rescue of the Polish Navy. 1361

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