The importance of telematic information and logistics indicators for the management of the quality of transport services

IF 1.6 Q3 ENGINEERING, INDUSTRIAL
R. Sałek
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引用次数: 3

Abstract

Abstract Transport companies, whose activities have a significant impact on the economy of the whole of Europe, constantly face new market challenges. The high demand for transport services, even in the time of the Covid-19 pandemic, and the introduction of new regulations by the European Union authorities mean that these enterprises have to increase their efforts on competitive foreign markets. Telematics systems play a crucial role in this battle as they enable the acquisition and processing of data characterizing processes in road transport. In this article, the author undertakes the issue of logistic indicators in theoretical frames, as well as their classification and characteristics as the main source of information about processes. This is followed by the analysis of data obtained from a transport company using a telematics system to manage transport processes in the context of ensuring the quality of services. The aim of the study is to demonstrate the significance of selected logistics indicators in terms of improving the quality of transport services. Statistical analysis is used to study the relationships and impact of individual measures in 2019-2020 as a forecasting tool. The result of the research is finding an appropriate link between the measures and using this knowledge as an opportunity to improve the quality of services.
远程信息处理信息和物流指标对运输服务质量管理的重要性
运输公司的活动对整个欧洲的经济产生重大影响,不断面临新的市场挑战。即使在2019冠状病毒病大流行期间,对运输服务的高需求,以及欧盟当局出台的新法规,意味着这些企业必须加大在竞争激烈的国外市场上的努力。远程信息处理系统在这场战斗中发挥着至关重要的作用,因为它们能够获取和处理表征道路运输过程的数据。在本文中,作者在理论框架中对物流指标进行了研究,并对作为流程信息主要来源的物流指标进行了分类和特征分析。接下来是分析从运输公司获得的数据,使用远程信息处理系统在确保服务质量的背景下管理运输过程。本研究的目的是证明所选物流指标在提高运输服务质量方面的重要性。采用统计分析作为预测工具,研究2019-2020年单项措施之间的关系及影响。研究的结果是找到各项措施之间的适当联系,并利用这种知识作为提高服务质量的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Production Engineering Archives
Production Engineering Archives Engineering-Industrial and Manufacturing Engineering
CiteScore
6.10
自引率
13.00%
发文量
50
审稿时长
6 weeks
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