Profile information and business outcomes of providers in electronic service marketplaces : an empirical investigation

Electronic service marketplaces (ESMs) have become major exchange platforms for the online outsourcing of different services &ndash; especially software development &ndash; to providers. Provider profiles on ESMs encompass extensive information regarding the activities and transactions of providers and they are a main source of information for customers. Such profile information significantly facilitates the relationship development between customers and providers. The existing literature has focused on the impact of the ratings of providers, but so far has not investigated the impact of the other available profile information. Building on the integrated information response model, this study investigates how information presented by providers as well as information provided by the ESM influences the business outcomes of the providers. Based on data collected from one of the major ESMs, we found that profile information indeed has a significant impact on the business outcomes of providers.<br /

A novel approach to investigate the impact of the built environment on physical activity among young adults

Introduction It is now well established that the built environment can facilitate or hinder physical activity (PA), including walking and cycling for transport purposes. However, the greatest majority of the evidence relies on self-reported measures of PA. Questionnaires have a low level of accuracy compared to devices such as accelerometers and pedometers which serve to objectively measure PA. With rapid technological advancements including the widespread availability of Global Positioning System (GPS) technology and GPS-equipped smartphones, the opportunities have widened for researchers and practitioners to investigate people’s PA. These technologies are especially useful to study PA in young people, as they are often less willing to participate in studies using conventional methods of data collection (e.g. surveys, accelerometers). This study introduces a custom-designed smartphone app to collect PA data during transport and, shows how the data collected by the app can provide us with insights about young people’s transport-related PA in relation to the built environment and trip characteristics. Methods We designed and implemented a smartphone app for both iOS and Android platforms which captures all movements of its users. The app includes post-processing algorithms that among other functions, detect the types of activities within a trip. For example, a trip from A to B may consist of multiple modal activities (e.g. walking, public transport, walking). In this study, we present an algorithm to extract/calculate the details of users’ single modal activities. Data from 170 university students in Brisbane, Australia was collected using the app for an average of three days per participant. The data includes 2353 single modal activities. We conducted descriptive analysis and developed a multiple regression model to reveal the impact of built environment attributes and trip characteristics on transport-related PA. Results Among other findings, the study results show that a high proportion of walking distance over the total distance of a trip was associated with a high access to public transport and having few trips per day. In addition, education trips involved more walking distances compared to other types of trips. Discussion This study proposes a new and effective approach to collect accurate and detailed data on young people’s PA using a smartphone app. This study provides empirical support on how smartphone apps can aid household travel surveys and collect detailed data on PA patterns at low cost. Understanding PA during travel is relevant to support investments and programs that support sustainable modes of transport, such as walking and cycling. Support/Funding Source This research was partially funded by Queensland Department of Transport and Main Roads (TMR), under the TAP agreement with the University of Queensland, Centre for Transport Strategy

Can Smartphone Travel Surveys Improve our Understanding of Young People’s Travel Behaviour?

Smartphone travel surveys are becoming of central importance in complementing traditional survey methods, especially for collecting detailed, accurate travel data of special groups, such as young adults. Previous studies have shown the application of smartphone travel surveys in various contexts and discussed their advantages. As occurs with their conventional survey counterparts, the quality of the data collected through these surveys is adversely affected by participants’ non‐response and the resulting biases. Moreover, selective, intermittent use of relevant apps during a survey can significantly decrease the reliability of the collected data. However, little is known about the usage patterns of travel survey apps when conducting surveys, the impact of such patterns on the reliability of the collected data and how such data can complement the data collected through traditional survey methods. Accordingly, this study aims to imp rove the current understanding of how young adults, as a potential target group of smartphone travel survey s, use a smartphone travel survey app, and how they compare their experience of participating in such a survey with a traditional, web‐based travel survey. In this study, a three‐stage survey was designed and used to collect data. In the first stage, the survey participants were asked to report their detailed travel activities over two days in a week, through a web‐based travel diary. After a one week break, the participants were asked to use a smartphone travel survey, namely, the Advanced Travel Logging Application for Smartphones II (ATLAS II), for two days over a week to record their travel activities. ATLAS II is an automated prompted recall travel survey which automatically records survey participants’ travel activities while the app is running in the background. Finally, in the third stage, the participants were asked to compare their experience with the tw o different survey methods and respond to a questionnaire about their experience, perceptions and survey participation attitudes. The first two stages provided the participants with a real experience of participating in a traditional, web ‐based travel survey and a smartphone travel survey, before they were asked about their personal perceptions and attitudes in the last stage. The survey participants were recruited in Brisbane, Australia. In the first stage, 175 participants reported their trips through the web‐based travel diary. In the second stage, 170 participants recorded and uploaded their trips through ATLAS II. Overall, 126 participants completed all three stages of the survey. The data collected in the first two stages are cleaned, segmented into single modal trip legs, and used to analyse the reliability of the data collected by the smartphone survey method. The reliability of the smartphone travel survey data is examined by evaluating the differences between t he two methods, in terms of the reported trips in different categories of travel behaviour. These categories are defined based on the mode, purpose, duration and distance of trip legs. Furthermore, these data are used along with the data collected in the last stage to develop a model of the impact of survey app usage patterns and participants’ perceptions of a survey app on the reliability of smartphone travel survey results. The results of this study contribute to our knowledge about strengths and weaknesses of the two survey methods and ho w to design and use smartphone travel surveys to more efficiently complement the data collected by traditional survey methods

Who Gets the Job? Synthesis of Literature Findings on Provider Success in Crowdsourcing Marketplaces

Background: Over the past decade, crowdsourcing marketplaces — online exchange platforms which facilitate commercial outsourcing of services — have witnessed a dramatic growth in the number of participants (service providers and customers) and the value of outsourced services. Deciding about the most appropriate provider is a key challenge for customers in crowdsourcing marketplaces because available information about providers may be incomplete and sometimes irrelevant for customer decisions. Ineffective information impedes many service providers to develop long-term relationships with customers, obtain projects on a regular basis and survive on crowdsourcing marketplaces. Previous studies have investigated the impact of a range of factors on customers’ choice decisions and providers’ success, given the important role of customer–provider relationship development for long-term success on crowdsourcing marketplaces. Method: This paper reviews the literature of crowdsourcing marketplaces with the aim of developing a comprehensive list of factors that influence customers’ choice decisions and providers’ success. Results: We found 31 conceptually distinct profile information components/factors that determine customers’ choices and providers’ business outcomes on crowdsourcing marketplaces. Conclusion: We classified these 31 factors into five major categories: 1) prior relationship between a customer and a provider or a customer’s invitation, 2) providers’ bidding behavior, 3) crowdsourcing marketplace or auction characteristics, 4) providers’ profile information, and 5) customer characteristics. The main factors in each category, associated considerations, related literature gaps and avenues for future research are discussed in detail

Relationship between heavy vehicle periodic inspections, crash contributing factors and crash severity

Heavy vehicle crashes are a major contributor to road-related fatalities. Representing only 3% of the total number of registered vehicles and 8% of the total vehicle kilometers traveled, heavy vehicles are involved in 18% of fatal and serious injury crashes in Australia. Given the contributing role of vehicle defects in many heavy vehicle crashes, vehicle inspection schemes have been implemented to more effectively manage heavy vehicle safety. However, there is little empirical research about the impact of periodic heavy vehicle inspections on vehicle defects and crash casualties. Hence, this research investigates the efficacy and effectiveness of periodic heavy vehicle inspections by examining their impact on the factors contributing to heavy vehicle crashes as well as the severity of these crashes. Accordingly, a partial least squares path model (PLSPM) is proposed and evaluated using the data of periodic heavy vehicle inspections and heavy vehicle crashes in Queensland, for the period of 2011-2013. The PLS-PM results are also compared with the results of potential, alternative analysis methods to provide further insights about potential applications of PLS-PM in transportation research. Although the scheme cannot be evaluated completely through the proposed analysis approach, the findings of this study contribute to the causal theory and practice of heavy vehicle inspection protocols, especially in relation to vehicle defects and road safety outcomes

A time series analysis of periodic heavy vehicle inspections and road safety outcomes in Queensland

Heavy vehicle crashes cause significant economic and social costs. Although most crashes are considered to be related to driver errors, the impact of vehicle defects is evident in many crashes (Blower et al., 2010). Hence, different vehicle inspection schemes, including Queensland’s certificate of inspection (COI), have been implemented around the world to more effectively manage the safety of heavy vehicles (Keall and Newstead, 2013). This study investigates the trends in and potential impact of COI on heavy vehicle crashes, relying on longitudinal data provided by Queensland’s Department of Transport and Main Roads for the period of 2009-2014

Parking Information Systems

Pre-trip information about parking significantly impacts users’ decision-making and results in more efficient use of parking and the traffic network. Parking Information Systems (PIS) are increasingly being used to provide drivers with real-time information about parking availability and navigate them to a vacant space – in its simplest form – to assist them with their trip planning. PIS may also include routing, fee collection and payment management, reservation, and availability forecasting features. PIS are integrated into Advanced Traveler Information Systems as part of emerging solutions for smart and more sustainable traffic network management. A typical parking information system consists of four main elements, including detection (monitoring) mechanism, data collection and processing unit (control center), information dissemination (display) mechanism, and communication technologies. Smart sensors and technologies are being used by PIS to monitor and relay real-time data on parking utilization to data warehouses and processing units to provide current information for parking decisions. Intelligent algorithms are also being used in advanced PIS. These algorithms can optimize the choice of parking for users, considering their objectives and constraints, such as price, availability likelihood and distance to final destination. Well-developed PIS are becoming an important management tool for cities to enable more efficient use of parking space, reduce cruising for parking, and enhance user experience

The Impact of Periodic Heavy Vehicle Inspection on Vehicle Defects: Evidence from Periodic and Roadside Inspections in Queensland

Heavy vehicle crashes are associated with significant economic and social costs. In a twelve months period ending June 2015, heavy vehicles were involved in 182 fatal crashes with 213 deaths in Australia (BITRE, 2015). The crash fatalities of the Australian freight industry constitutes almost one third of all work-related crash fatalities (Raftery, Grigo, &amp; Woolley, 2011). Representing only 3% of the total number of registered vehicles and 8% of the total vehicle kilometres travelled, heavy vehicles are involved in 18% of fatal and serious injury crashes (Mooren, Grzebieta, Williamson, Olivier, &amp; Friswell, 2014). Although most crashes are considered to be related to driver errors, the impact of vehicle defects is evident in many crashes (Blower, Green, &amp; Matteson, 2010). Hence, different vehicle inspection schemes, including Queensland’s certificate of inspection (COI) scheme, have been implemented around the world to more effectively manage the safety of heavy vehicles (Keall &amp; Newstead, 2013). The COI scheme enforces any heavy vehicle registered in Queensland to undergo a periodic inspection every 6 or 12 months, depending on the vehicle’s type. However, there is little empirical research about the impact of periodic heavy vehicle inspections on vehicle defects, number of crashes and crash casualties (Mooren et al., 2014). Accordingly, this research aims at investigating the effectiveness of periodic heavy vehicle inspections, specifically by examining the impact of the COI scheme on heavy vehicle defects in Queensland. To address this objective, the current study seeks to evaluate potential differences between the results of random roadside inspections and periodic inspections of heavy vehicles, using the data provided by Queensland’s Department of Transport and Main Roads for the period of 2012-2013. Negative binomial regression is used to analyse the data. Although the scheme cannot be evaluated completely through the proposed analysis approach, such an evaluation can provide empirical evidence for the effectiveness of periodic heavy vehicle inspection in reducing the number of vehicle defects. The initial exploratory analysis results indicate a large impact of the periodic heavy vehicle inspections on reducing vehicle defects. While 85,447 out of 180,252 vehicles (i.e., 47.4%) inspected under the COI scheme failed the inspections due to defects, only 2,737 out of 38,145 vehicles (i.e., 7.2%) inspected randomly failed the inspections. This is despite the fact that the previous studies have consistently found high rates of vehicle defects in roadside heavy vehicle inspections (Blower et al., 2010). The findings of this study have theoretical and practical implications in the context of the effectiveness of vehicle inspection protocols on vehicle defects and resulting road safety

Performance based Parking Management

Performance-based standards are an innovative method to manage parking and a conceptual means to review and change how we envision parking in the city. The challenge becomes to reshape how we think of parking space, one of the largest urban land uses, and apply methods of adapting other mobility uses to parking slots. A performance-based approach is often more flexible, require fewer regulations, speed up the approval process, and encourage a greater dialogue amongst stakeholders, as opposed to traditional prescriptive planning. As the foundation of a performance-based parking management framework, performance measures are proposed in this study, centered around land use, building and transportation. These measures, including but not limited to land use cost-effectiveness, average duration, capacity, spill-over level, walkability index, and enforcement efficiency, provide a flexible, yet powerful means to manage parking more efficiently. Performance standards are critical in changing the future of parking by improving accessibility for a range of mobility opportunities and enhancing parking sustainability

A Time Series analysis of periodic heavy vehicle inspections and road safety outcomes in Queensland

Heavy vehicle crashes cause significant economic and social costs. Although most crashes are considered to be related to driver errors, the impact of vehicle defects is evident in many crashes (Blower et al., 2010). Hence, different vehicle inspection schemes, including Queensland’s certificate of inspection (COI), have been implemented around the world to more effectively manage the safety of heavy vehicles (Keall and Newstead, 2013). This study investigates the trends in and potential impact of COI on heavy vehicle crashes, relying on longitudinal data provided by Queensland’s Department of Transport and Main Roads for the period of 2009-2014