Can we estimate accurately fare evasion without a survey? Results from a data comparison approach in Lyon using fare collection data, fare inspection data and counting data

International audienceIn a context of worldwide urbanization and increasing awareness for environmental issues, it is undeniable that public transport will play an important role in the cities of the future. This will require increased attractiveness of public transit and adequate funding. In this regard, fare evasion could be considered as a threat that needs to be quantified accurately. To do this, transit operators often rely on on-site surveys that are limited in terms of spatiotemporal coverage. Yet, new data sources such as farebox transactions, fare inspection logs and automated passenger counter are now available and little research examines how they could help in estimating the fare irregularity rate. In this paper, we initiate research in this direction. To do this, we followed the operator’s viewpoint and used a comparative approach to analyse the potential of those new data sources. We introduced a classification of fare irregularities and then applied data fusion methods to derive two fare irregularity rates. Results are then compared to a survey and the area of relevance of each data source is discussed. The research is done with data from the public transport network of Lyon which is an interesting case study because different access control types coexist (open and closed environment). The research results suggest that the fare inspection logs might have significant limitations to measure accurately the level of fare evasion. They also suggest that the merging of automated count and farebox transactions is a more promising direction of research. Still, it will probably not be enough to completely replace on-site manual survey. These findings can help operators in identifying the pros and cons of all data sources and implement new measurement methods

Can we estimate accurately fare evasion without a survey? Results from a data comparison approach in Lyon using fare collection data, fare inspection data and counting data

In a context of worldwide urbanization and increasing awareness for environmental issues, it is undeniable that public transport will play an important role in the cities of the future. This will require increased attractiveness of public transit and adequate funding. In this regard, fare evasion could be considered as a threat that needs to be quantified accurately. To do this, transit operators often rely on on-site surveys that are limited in terms of spatiotemporal coverage. Yet, new data sources such as farebox transactions, fare inspection logs and automated passenger counter are now available and little research examines how they could help in estimating the fare irregularity rate. In this paper, we initiate research in this direction. To do this, we followed the operator’s viewpoint and used a comparative approach to analyse the potential of those new data sources. We introduced a classification of fare irregularities and then applied data fusion methods to derive two fare irregularity rates. Results are then compared to a survey and the area of relevance of each data source is discussed. The research is done with data from the public transport network of Lyon which is an interesting case study because different access control types coexist (open and closed environment). The research results suggest that the fare inspection logs might have significant limitations to measure accurately the level of fare evasion. They also suggest that the merging of automated count and farebox transactions is a more promising direction of research. Still, it will probably not be enough to completely replace on-site manual survey. These findings can help operators in identifying the pros and cons of all data sources and implement new measurement methods

Factors affecting job performance: an emprical approach

The main aim of this study is to investigate impact of job satisfaction, organization commitment, work engagement and work environment on academic and non-academic staffs in universities in Lagos, Nigeria. The study indicates a strong significance of the variables in explaining employees’ performance within the context of universities in Lagos, Nigeria. The study adopts quantitative research method of primary source was utilized to collect the data from two hundred and seventy-one academic and nonacademic staff respondents by using probability sampling technique and data collected and analyzed by using Statistical Package for Social Science (SPSS). The scope is centered on academic and non-academic staffs which warranted distribution and collection of questionnaires among academic and non-academic staffs of eight selected universities within Lagos state universities which are Anchor University, Augustine University, Caleb University, Christopher University, Lagos State University (LASU), National Open University (NOUN), Pan African University, University of Lagos(UNILAG). The questionnaire is designed with a close-ended question. The data were analyzed using different statistical techniques such as reliability survey, descriptive of variable analysis, correlation analysis (Pearson Correlation Analysis) and regression analysis (Multiple Regression Analysis). The regression results indicate that all independent variables which are job satisfaction, Organization commitment, Work engagement and Work environment are positively correlated with the dependent variable which is Job performance. However, the study concludes that for effective Job performance to be enhanced, the level of motivation needs to be improved. This would determine the sustainability or otherwise of organizational goals either private or public sectors