The relationships between e-shopping and store shopping in the shopping process of search goods

Internet facilitates hybrid shopping processes by enabling consumers to acquire information, experience product, and conduct transaction using different media (e.g., internet, store, and catalog) at different locations at different times. Although several studies have explored how internet transactions and store sales influence each other, few investigated transportation implications of the hybrid shopping process of single products. Using 540 internet users in the Minneapolis-St. Paul metropolitan area, USA, this study decomposed their shopping processes of a group of search goods (books, CDs, VCDs, videotapes, and album) to understand the relationships of e-shopping and store shopping. We found the media for product awareness, information search, and product trial are important predictors of transaction medium; and the awareness medium is the most important. Further, 17% of store buyers used internet for information search and/or product trial, and about 10% of internet buyers made trips to store to acquire information and/or experience product. The findings carry implications for marketing strategies and travel demand analysis.     

The interactions between e-shopping and traditional in-store shopping: an application of structural equations model

As the proliferation of e-commerce leads to ever greater numbers of on-line transactions, transportation planners are interested in the impacts of e-shopping on our strained transportation systems. Although the substitution effect of e-shopping is appealing, previous studies provided mixed results on its impact. Using 539 adult internet users in the Minneapolis-St Paul metropolitan area, this study applied a structural equations model to investigate the interactions among online purchases, in-store shopping, and product information search via internet. We found that online searching frequency has positive impacts on both online and in-store shopping frequencies and online buying positively affects in-store shopping. In particular, the marginal effects of online-buying frequency and online-searching frequency on in-store shopping frequency were estimated at 0.153 and 0.189, respectively. Since the internet as a shopping channel tends to have a complementary effect on in-store shopping, the rise of e-shopping is not likely to be a solution but a challenge to travel reduction.     

Explore the relationship between online shopping and shopping trips: An analysis with the 2009 NHTS data

The rapid growth of ecommerce brings great changes to the transportation system. However, most existing studies focus on the impact of ecommerce on freight system. Its impact on personal trips is relatively less studied. It is reasonable to argue that online shopping reduces the need of shopping trips by making goods accessible via door-to-door deliveries. On the other hand, online shopping may also create more shopping trips as online shoppers travel to stores to experience, compare or pick up the goods. Understanding the connections between online shopping and shopping trips is critical for transportation planners to prepare for changes that information technology will continue to bring to this nation in the future. Using the 2009 National Household Travel Survey (NHTS) data and a structural equation model (SEM), this paper disentangles the bidirectional connections between online shopping and shopping trips. Results show that online shopping encourages shopping trips while shopping trips tend to suppress the online shopping propensity. Besides, both online shopping and shopping trips are influenced by exogenous factors such as shoppers’ demographic features, regional specific factors and household attributes. A closer examination at the state level further confirms model validity while disclosing spatial variation in their relationship.     

Impact of different shopping stages on shopping-related travel behaviour: analyses of the Netherlands Mobility Panel data

From the moment e-shopping emerged, there have been speculations about its impact on personal mobility. A fair amount of research has already been carried out on Internet shopping itself as well as on its consequences for mobility. Most studies focus on the overall impact of online shopping on personal mobility. However, little is known about how personal shopping mobility can be characterised when differentiating its constituent stages, being browsing/orienting, comparing, selecting and purchasing products, and how this is affected by e-shopping. This will be the main topic of this paper. We will investigate this using recently collected data from the Netherlands Mobility Panel [in Dutch: MobiliteitsPanel Nederland (MPN)]. It is the unique combination of reported shopping trips in the three-day travel diary, the large amount of personal and household characteristics combined with the detailed information from the e-shopping questionnaire that enables us to perform this research. Using factor analysis, we explore the underlying factors related to the browsing and selection behaviour prior to the purchase of a product. Using these factors as a starting point, we apply cluster analysis resulting in three homogeneous groups of shoppers with different pre-purchase shopping behaviour. The groups differ clearly with respect to personal and household characteristics, in the frequency with which they buy and sell products online and in their perception of (dis-)advantages of online shopping. Once relevant groups have been distinguished and characterised, differences in shopping-related mobility between them are studied in two different ways. Firstly, we analyse statements from shoppers on how their shopping-related mobility has changed. Secondly, we analyse shopping trips reported in the three-day travel diary. Only one group, which consists of shoppers that rely on the Internet to search for product information, compare prices and get new product ideas, states that their shopping-related travel behaviour has changed since they started shopping online. Approximately 50% of all shoppers experienced no difference in their shopping mobility. The analysis of actual shopping mobility using the travel diary data showed only minor differences in shopping-related travel behaviour between the identified groups. Finally, we fit a multi-variate linear regression model of shopping trip distance to determine if (e)-shopping characteristics influence trip distances. The frequency with which people shop online as well as some stated changes in shopping-related travel behaviour (shopping in a similar manner and shopping longer) turn out to influence non-grocery shopping trip distance. No significant influence could be found of shopping cluster membership on shopping trip distances.

     

Transport effects of e-commerce: what can be learned after years of research?

This paper offers an extensive review of conceptual and quantitative studies on the implications of business-to-consumer (b2c) e-commerce on mobility. To create a more comprehensive understanding of the mobility implications we also discuss the complementary side: freight transport. Most studies conducted thus far have looked at the consequences of b2c e-commerce for either personal travel or goods movement, but not for both. The added value of this review article is that it not only explores the conclusions drawn in the wide-ranging published research, but also attempts to review the sampling strategies, definitions, assumptions and methodologies that lead to the diverse conclusions. For example, the paper discusses the differences in how “e-shopping” is defined (whether it includes browsing or only purchasing) and with what frequency a respondent e-shops (however it is defined) in order to be considered an “e-shopper”. The review describes how product differentiation is necessary to scrutinize the mobility effects of e-commerce. It points to studies which tend to have a dual conclusion. We try to observe whether complementary effects are given the same level of attention as substitution effects. Each of these factors can have sizable impacts on the quantitative conclusions reached. Our aim is that, by calling attention to these issues, the conclusions of studies will be discussed in a rigorous way to improve our knowledge of the transportation impacts of online shopping.     

Shopping online and/or in-store? A structural equation model of the relationships between e-shopping and in-store shopping

Searching product information and buying goods online are becoming increasingly popular activities, which would seem likely to affect shopping trips. However, little empirical evidence about the relationships between e-shopping and in-store shopping is available. The aim of this study is to describe how the frequencies of online searching, online buying, and non-daily shopping trips relate to each other, and how they are influenced by such factors as attitudes, behaviour, and land use features. Questionnaire data were collected from 826 respondents residing in four municipalities (one urban, three suburban) in the centre of the Netherlands. Structural equation modelling was used to examine the variables’ multiple and complex relationships. The results show that searching online positively affects the frequency of shopping trips, which in its turn positively influences buying online. An indirect positive effect of time-pressure on online buying was found and an indirect negative effect of online searching on shopping duration. These findings suggest that, for some people, e-shopping could be task-oriented (a time-saving strategy), and leisure-oriented for others. Urban residents shop online more often than suburban residents, because they tend to have a faster Internet connection. The more shopping opportunities one can reach within 10 min by bicycle, the less often one searches online.     

Modeling the relationships among urban passenger travel carbon dioxide emissions,transportation demand and supply,population density,and proxy policy variables

To support the development of policies that reduce greenhouse gas (GHG) emissions by encouraging reduced travel and increased use of efficient transportation modes, it is necessary to better understand the explanatory effects that transportation, population density, and policy variables have on passenger travel related CO₂ emissions. This study presents the development of a model of CO₂ emissions per capita as a function of various explanatory variables using data on 146 urbanized areas in the United States. The model takes into account selectivity bias resulting from the fact that adopting policies aimed at reducing emissions in an urbanized area may be partly driven by the presence of environmental concerns in that area. The results indicate that population density, transit share, freeway lane-miles per capita, private vehicle occupancy, and average travel time have a statistically significant explanatory effect on passenger travel related CO₂ emissions. In addition, the presence of automobile emissions inspection programs, which serves as a proxy indicator of other policies addressing environmental concerns and which could influence travelers in making environmentally favorable travel choices, markedly changes the manner in which transportation variables explain CO₂ emission levels.     

E‐Shopping and its Relationship with In‐store Shopping: Empirical Evidence from the Netherlands and the USA

Abstract

Despite considerable examination of the impact of telecommunications on travel, little empirical evidence sheds light on the impact of e‐shopping on travel—a recent and increasingly popular form of telecommunications. This paper analyses determinants of online buying and their relationship with in‐store shopping, using empirical data obtained from Minneapolis, USA, and Utrecht, the Netherlands. Based on chi‐square tests and logistic and ordinary least‐squares regressions, the results indicate that online buying is affected by sociodemographics and spatial characteristics of people, their Internet experience, and their attitudes towards in‐store shopping. US respondents who prefer to see products in person are less likely to buy online. Dutch respondents are more likely to buy online as travel times to shops are shorter. At first sight, this counterintuitive result might be related to an urban, innovative lifestyle that supports e‐shopping. A more detailed analysis of Dutch online buyers reveals that they make more shopping trips than non‐online buyers and have a shorter shopping duration. The results indicate that the relationship between online buying and in‐store shopping is not one of substitution but of complementarity.     

Travel,work, and telecommunications: A view of the electronics revolution and its potential impacts

Considerations of the impacts of electronic technologies on transportation usually focus on substitution of communications for travel, especially telecommuting. This topic is reviewed briefly, followed by consideration of electronic technology-induced changes in the structure of firms, work by individuals, and consumption. Today's organization of the work place on the basis of time-at-a-place measurements dates from early in the Industrial Revolution; the communications control of production dates from the introduction of the telegraph. Recent and upcoming communications developments may relax time and place requirements while intensifying communications control. Resulting changes in production and consumption may challenge transportation developments in coming decades.     

Granger-causality between transportation and GDP: A panel data approach

This paper investigates the Granger-causality relationship between income and transportation of EU-15 countries using a panel data set covering the period 1970–2008. In the study, inland freight transportation per capita in ton-km (TRP), inland passenger transportation per capita in passenger-km (PAS), and road sector gasoline fuel consumption per capita in kg of oil equivalent (GAS) are used as transportation proxies and GDP per capita is used as measure of income. Our findings indicate that the dominant type of Granger-causality is bidirectional. Instances of one-way or no Granger-causality were found to correspond with countries with the lowest income per capita ranks in 1970 and/or in 2008. Although we conclude that there is an endogenous relationship between income and transportation, this is not observed until after an economy has completed its transition in terms of economic development.     

Long-term trends in domestic US passenger travel: the past 110 years and the next 90

Based upon a long-term historical data set of US passenger travel, a model is estimated to project aggregate transportation trends through 2100. One of the two model components projects total mobility (passenger-km traveled) per capita based on per person GDP and the expected utility of travel mode choices (logsum). The second model component has the functional form of a logit model, which assigns the projected travel demand to competing transportation modes. An iterative procedure ensures the average amount of travel time per person to remain at a pre-specified level through modifying the estimated value of time. The outputs from this model can be used as a first-order estimate of a future benchmark against which the effectiveness of various transportation policy measures or the impact of autonomous behavioral change can be assessed.     

Hitting the sweet spot: Variability in commute lengths and vehicle emissions across a diverse state

In this paper we consider travel across Virginia and identify sustainability “sweet spots” where commute lengths and vehicle emissions per mile combine to maximize green travel in terms of total CO₂ emissions associated with commuting. The analysis is conducted across local voter precincts (N = 2373 in the state) because they are a useful proxy for neighborhoods and well-sized for implementing policy designed to encourage sustainable travel behavior. Virginia is especially appropriate for an examination of variability in sustainable travel behavior and technologies because the state’s transportation, demographic, and political patterns are particularly diverse and have been changing rapidly. We identify four Virginia precinct-based sustainability clusters: Sweet Spots, Emerging Sweet Spots, Neutral and Non-sustaining. A model of demographic differences among the clusters shows that sustainability outcomes, understood in terms of both local commute behavior and vehicle emissions, are significantly associated with the diverse demography and politics of the state. We also look at changes in transportation sustainability and socio-demographic trends within the clusters over the past half-decade, showing that differences in sustainability and demographic metrics are actually accelerating within the state over time. We conclude with a discussion of the implications of the differences among the clusters for developing and implementing effective transportation sustainability policies across the state.     

Resolving the property right of transportation emissions through public–private partnerships

The application of public–private partnerships (P3’s) in the transportation sector has grown in popularity worldwide. Despite this important shift in the provision of transportation service, there are clear gaps in knowledge about the impacts of P3 projects, especially on emissions from transportation systems as a whole. Not only should policy makers evaluate the emissions impacts from P3 projects, but they should also think about innovative models that address or charge for emissions into P3 contracts. This addition to P3 contracts could provide a new solution to the long-existing property right paradox: who owns (is responsible for) emissions from transportation systems? This study attempts to fill the research gap by analyzing these innovative models. Using the road network of Fresno, California, as our case study, we offer a number of interesting insights for policy makers. First, average peak emissions costs range from 1.37 cents per mile (the do-nothing case) to 1.20 cents per mile (profit-maximizing cases) per vehicle. Although emissions costs from the P3 projects are lowest for the profit-maximizing cases, the system-wide emissions costs of these cases are highest because of spillover effects. Second, charging project owners for the emissions costs of P3 projects is not an effective way to reduce emissions or the total costs of travel, especially on a VMT basis. Instead, the public sector should implement emissions-included social cost-based price ceilings. When employing these limits, project owners could still be charged for the emissions costs. Finally, using total travel time as the only objective function for evaluating P3 projects can be misleading. Several P3 projects have shown better outcomes using total travel cost with the inclusion of emissions and fuel consumption costs, instead of using total travel time as the only objective function.     

Shopping without travel or travel without shopping? an investigation of electronic home shopping

This study explores the growth of electronic home shopping in terms of likely transportation and communication interactions. Although opportunities exist to shop from home today, most consumers initiate travel trips to stores or markets. Widespread use of automobiles has facilitated the retailing configurations we know today but the development of new electronic networks could change this. This study establishes a baseline to explore shopping activities using two‐day travel activity data from a large U.S. metropolitan area. It is found that people who telework from home today spend more time engaged in shopping activities than other workers. Potentially, their saved work travel is converted into new trips. In the future, saved shopping travel might be converted into other types of travel, and modelling results show that for busy working women, there is a latent demand for maintenance‐related activities. The study results suggest that electronic home shopping will bring into play complex interactions between communications and transportation.     

Incorporating online shopping into travel demand modelling: challenges,progress, and opportunities

There is a large body of literature, spanning multiple disciplines, concerned with the relationship between traditional (physical) shopping and associated travel behaviour. However, despite the recent rapid growth of digital retailing and online shopping, the impact on travel behaviour remain poorly understood. Although the issue of the substitution and complementarity between conventional and virtual retail channels has been extensively explored, few attempts have been made to extend this work so as to incorporate virtual retail channels into modelling frameworks that can link shopping and mobility decisions. Here, we review the existing literature base with a focus on most relevant dimensions for personal mobility. How online activity can be incorporated into operational transport demand models and benefits of such effort are discussed. Existing frameworks of shopping demand are flexible and can, in principle, be extended to incorporate virtual shopping and the associated additional complexities. However, there are significant challenges associated with lack of standard ontologies for crucial concepts and insufficiencies in traditional data collection methods. Also, supply-side questions facing businesses and policy-makers are changing as retailing goes through a digital transformation. Opportunities and priorities need to be defined for future research directions for an assessment of existing tools and frameworks.     

Carsharing’s life-cycle impacts on energy use and greenhouse gas emissions

This paper examines the life-cycle inventory impacts on energy use and greenhouse gas (GHG) emissions as a result of candidate travelers adopting carsharing in US settings. Here, households residing in relatively dense urban neighborhoods with good access to transit and traveling relatively few miles in private vehicles (roughly 10% of the U.S. population) are considered candidates for carsharing. This analysis recognizes cradle-to-grave impacts of carsharing on vehicle ownership levels, travel distances, fleet fuel economy (partly due to faster turnover), parking demand (and associated infrastructure), and alternative modes. Results suggest that current carsharing members reduce their average individual transportation energy use and GHG emissions by approximately 51% upon joining a carsharing organization. Collectively, these individual-level effects translate to roughly 5% savings in all household transport-related energy use and GHG emissions in the U.S. These energy and emissions savings can be primarily attributed to mode shifts and avoided travel, followed by savings in parking infrastructure demands and fuel consumption. When indirect rebound effects are accounted for (assuming travel-cost savings is then spent on other goods and services), net savings are expected to be 3% across all U.S. households.     

Revisiting the relationship between traffic congestion and the economy: a longitudinal examination of U.S. metropolitan areas

Conventional transportation practices typically focus on alleviating traffic congestion affecting motorists during peak travel periods. One of the underlying assumptions is that traffic congestion, particularly during these peak periods, is harmful to a region’s economy. This paper seeks to answer a seemingly straightforward question: is the fear of the negative economic effects of traffic congestion justified, or is congestion merely a nuisance with little economic impact? This research analyzed 30 years of data for 89 US metropolitan statistical areas (MSAs) to evaluate the economic impacts of traffic congestion at the regional level. Employing a two-stage, least squares panel regression model, we controlled for endogeneity using instrumental variables and assessed the association between traffic congestion and per capita gross domestic product (GDP) as well as between traffic congestion and job growth for an 11-year time period. We then investigated the relationship between traffic congestion and per capita income for those same 11 years as well as for the thirty-year time period (1982–2011) when traffic congestion data were available. Controlling for the key variables found to be significant in the existing literature, our results suggest that the potential negative impact of traffic congestion on the economy does not deserve the attention it receives. Economic productivity is not significantly negatively impacted by high levels of traffic congestion. In fact, the results suggest a positive association between traffic congestion and per capita GDP as well as between traffic congestion and job growth at the MSA level. There was a statistically insignificant effect on per capita income. There may be valid reasons to continue the fight against congestion, but the idea that congestion will stifle the economy does not appear to be one of them.

     

Specification of a tour-based neighborhood shopping model

This paper presents a state-of-the practice neighborhood shopping travel demand model. The model structure is designed to incorporate decisions across five dimensions of shopping travel, including decisions of: (1) household tour frequency; (2) participating party; (3) shopping tour type; (4) mode, and (5) destination choices using a tour-based nested-logit model. As a neighborhood model, we have also captured the interrelated effects of three main factors associated with shopping travel decisions both within and outside of the neighborhood, including the residential location within the neighborhood, the neighborhood regional setting and the household structure. The model was validated using the travel data collected in three neighborhoods located in the Puget Sound region, WA. Results show that household socio-demographics have significant effects on the decisions for household tour frequency, mode and destination choices, while the characteristics of the traveling party have considerable impacts on the decisions for tour type. The level of service and the zone attractions influence decisions about mode and destination choices. The day of week variable (weekday versus weekend) is statistically significant in all models, indicating that weekday shopping travel decisions differ from weekend, across all five dimensions of interest. The paper concludes with a discussion about how the model can be used to examine policy-related neighborhood issues (e.g. accessibility).     

Public perceptions of toll roads: A survey of the Texas perspective

Like many U.S. states, Texas is experiencing shortfalls in transportation funding, along with growing needs for system improvements. Accordingly, the Texas Department of Transportation (TxDOT) is turning to tolling to bridge the funding gap. To assist planning efforts and effectively direct public information, a telephone survey of 2111 Texans was undertaken statewide to gauge public opinion on tolling issues.Some issues yielded a definite consensus among survey respondents. Over 70% agreed on attending to existing roads first, keeping existing roads toll-free, reducing tolls after construction, using revenues within the same region, charging higher tolls for trucks, not imposing SOV tolls, and maintaining the same toll rates during rush-hours. Some opinions varied by region. Austinites were more likely to support additional transportation spending, while residents of the Lower Rio Grande Valley were less supportive of raising the gas tax and of public/private partnerships. Opinions also varied with survey design. In eight places in the survey, optional text was provided or question order was modified to intentionally influence response. For two questions, support for tolling was decreased when information on personal transportation costs and higher gas tax rates in other states was offered. Ordered probit and binomial and multinomial logit models were estimated to assess the impact of demographic and travel characteristics on respondent opinions, and results for key issues are presented here. Opinions across demographic groups also were examined. The survey was successful at measuring opinions on several key tolling issues and should prove a useful tool for transportation planners and policymakers.     

Impacts of information technology on personal travel and commercial vehicle operations: research challenges and opportunities

Travel, like many other aspects of daily life is being transformed by the information technology (IT) revolution. Accessibility can no longer be measured only in terms of travel time, distance or generalized travel cost. IT gives people virtual accessibility to a rapidly growing range of activities. E-commerce has become a catalyst for structural changes in the freight transportation industry and is changing where freight moves, the size of typical shipments and the time within which goods must be delivered. In this paper, we explore some of the potential effects of IT on transportation, both personal and freight.