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Modal choice preferences in short-distance hinterland container transport
RTBM-00286; No of Pages 8 Research in Transportation Business & Management xxx (2017) xxx–xxx
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Research in Transportation Business & Management
Modal choice preferences in short-distance hinterland container transport Dries Meers ⁎, Cathy Macharis, Tom Vermeiren, Tom van Lier Vrije Universiteit Brussel, MOBI Research Group, Pleinlaan 2, B-1050 Brussels, Belgium
a r t i c l e
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Article history: Received 14 September 2016 Received in revised form 16 February 2017 Accepted 16 February 2017 Available online xxxx Keywords: Container transport Modal choice Short distance Modal shift Choice-based conjoint experiment Intermodal transport
a b s t r a c t Short distance inland container transport to Western European seaports provides opportunities for additional modal shift to intermodal transport, thanks to the concentration of transport flows transported to the immediate hinterland of these ports. The literature on modal choice behavior, however, fails to explain the (relatively low) success of this market segment. In this paper, a choice-based conjoint experiment is conducted to increase the insight on the preferences of modal choice decision-makers in Belgium, active in the considered market segment. The findings of the experiment suggest that, to enhance a further modal shift, operators should try to provide daily services at a competitive price, with a focus on providing more reliable services than road transport. Additional efforts should be made to correctly inform decision-makers on the available intermodal services. © 2017 Elsevier Ltd. All rights reserved.
1. Introduction Intermodal transport has been promoted by regional, national and international policies throughout Europe. As advocated by inter alia the European Commission, intermodal transport proves to be a more environmentally friendly alternative to road transport in many cases (Kreutzberger, Macharis, Vereecken, & Woxenius, 2003), although this statement cannot be generalized to all cases (López-Navarro, 2014). Another important reason for stimulating intermodal transport can be found in the effort to ease port congestion. The main focus of the European Commission's modal shift efforts lay in the long distance transport segment, with the explicit goal to shift 50% of road freight over 300 km to other transport modes by 2050 (European Commission, 2011). The b300 km distance segment nevertheless corresponds to 44% of the ton-km and 89% of the total tons transported in Europe. Tavasszy and van Meijeren (2011), however, show that existing and promising intermodal transport cases below this 300 km ‘threshold’ distance also exist. An example is that of maritime-based intermodal container transport services to and from north-western European seaports in the Rotterdam-Le Havre range. Particularly intermodal barge transport can be a competitive alternative for short distance road transport in The Netherlands (Ministerie van
Abbreviations: 3PL, third party logistics company; CBC, choice-based conjoint; HB, hierarchical Bayes; IWT, inland waterway transport; LSP, logistics service provider; RLH, root likelihood; RP, revealed preference; SP, stated preference; SSS, short sea shipping. ⁎ Corresponding author. E-mail address: [email protected] (D. Meers).
Verkeer en Waterstaat, 1994), Belgium (Meers, Vermeiren, & Macharis, 2014) and France (Frémont & Franc, 2010). But also in other countries, the feasibility of short distance intermodal services through innovation has been investigated, employing for instance double-stack trains (Resor & Blaze, 2004) or a light-combi concept (Bärthel & Woxenius, 2004). As already stated by Trip and Bontekoning (2002), the key to successful short distance services mainly lies in reducing transshipment costs and time, which should be combined with sufficient transport volumes. Notwithstanding clear markets exist for short distance intermodal container transport – defined here as transport for which the roadonly alternative transport distance is under 300 km – most research projects funded by the European Commission focus on medium- to long-distance transport opportunities. The modal choice literature also mainly focuses on this market segment (Reis, 2014), although exceptions, often focusing on the inland leg of maritime chains, exist (e.g. Feo-Valero, García-Menéndez, Sáez-Carramolino and Furió-Pruñonosa, 2011). Reis (2014) tries to relate short distance intermodal successes to the modal choice literature, but concludes that this literature fails to explain them. This paper addresses one very specific market focusing on modal choice behavior in one of the ‘successful’ short distance transport markets for intermodal container transport, where earlier research in this market mainly deals with a variety of loading units and transport distances (e.g. Beuthe & Bouffioux, 2008). A choice-based conjoint experiment, elaborated in Section 3, was set up to investigate the preferences of shippers and logistics service providers for container transport in Belgium, to assess how the ‘classic’ modal choice determinants, as
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Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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identified in the modal choice literature, are valued in the short-distance segment. The case study setting is described in Section 4. The findings from the experiment are discussed in Section 5. Section 6 presents the conclusions.
2. Literature review To disentangle the transport service requirements of decisionmakers in transport planning, an extensive modal choice literature has developed over the past decades, building on the works of, inter alia, McGinnis (1979, 1989, 1990). Older studies have been extensively described and analyzed in the review papers of Cullinane and Toy (2000), Meixell and Norbis (2008), Flodén, Bärthel, and Sorkina (2010) and Feo-Valero, García-Menéndez and Garrido-Hidalgo (2011). Crucial aspects, needing consideration, recognized in these review papers are: the identification of influential modal choice attributes, the mode and carrier selection process and the decision-maker. In their literature review, Cullinane and Toy (2000) compose a list 15 modal choice criteria categories, each comprising one or several modal choice attributes. Following the reviews of Cullinane and Toy (2000), Feo-Valero, García-Menéndez and Garrido-Hidalgo (2011) and Flodén et al. (2010) and recent modal choice studies (Arencibia, Feo-Valero, García-Menéndez, & Román, 2015; Feo, Espino, & García, 2011; Feo-Valero, García-Menéndez, Sáez-Carramolino, et al., 2011; Feo-Valero, García-Menéndez, & del Saz-Salazar, 2014; Nugroho, Whiteing, & de Jong, 2016) it was decided to include the modal choice attributes of price, transit time, transit time reliability and transport frequency as main criteria in this study. Obviously, parameters such as shipment size and product characteristics can impact these required service levels (Feo-Valero et al., 2014). Different methodologies can be used to disentangle the preferences regarding these modal choice attributes. Stated preference (SP) and revealed preference (RP) experiments are commonly used to obtain data for disaggregated transport demand models, using utility and cost functions. There is also the discussion on the actor group that should be questioned and which should be considered as the main transport mode decision-maker. In this type of studies, two types of decisionmakers are questioned, being freight forwarders or hauliers on the one hand, managing the freight, and shippers on the other hand, which can be represented by retailers, producers, distributors etc. FeoValero, García-Menéndez and Garrido-Hidalgo (2011) find that most studies focus on the shippers as decision-makers, although some studies opt to consider both groups, as arguments can be made in favor of both. In this perspective, Patterson, Ewing, and Haider (2010) find that third party logistics companies (3PLs) are more biased against intermodal transport services, compared to shippers. Holguín-Veras, Xu, de Jong, and Maurer (2011) find that mode choice decisions mainly depend on the interaction between both actor groups and the shipment size. In this study, shippers, logistics service providers (LSPs) and shipping agents are included as decision-makers. The main share of the respondents questioned are however shippers, as the transport market studied is dominated by merchant haulage. As stated in the introduction, this paper aims to focus on modal choice decisions in the market segment of short distance container transport in Belgium. Reis (2014), tested if modal choice variables from medium- to long-distance transport services can explain behavior in the short distance segment, but he concludes that these variables can hardly justify the choice of a freight forwarder for the intermodal transport services. Only transport price can explain the choice for intermodal services in his case study. Earlier studies already pointed out that modal choice preferences can change according to the transport distance travelled. Rotaris, Danielis, Sarman, and Marcucci (2012), for instance, argue that shippers with a need for fast transport are in general located close their main market, valuing time higher for short distance transport.
The unique focus on containerized goods is in this case study a consequence of their ‘ease’ to shift from road to intermodal transport services. Also Blauwens, Vandaele, Van de Voorde, Vernimmen, and Witlox (2006) focus on containerized shipments in the hinterland transport market of seaports. They use an inventory-theoretic framework to evaluate the effectiveness of modal shift policy measures. FeoValero, García-Menéndez, Sáez-Carramolino, et al. (2011) also focus on the inland leg, but in a long distance corridor where rail and road compete. According to their findings, frequency plays a crucial role in the competitiveness of rail transport, as it can compete with road-only transport on transport cost. Beuthe and Bouffioux (2008) looked at a variety of goods flows, including goods transported in containers. Based on a SP experiment, they calculate monetary values for different quality attributes, and find that the valuation of all included criteria differs rather strongly when comparing transport of containers to, for instance, semi-trailers. The corresponding weights in decision making that were derived for container transport, calculated as a measure of importance, are 71% for cost, 10% for transport time, 7% for reliability and 4% for frequency. Focusing on the short distance transport market (b300 km), cost is weighted higher with 75%, before reliability with 8%, transport time with 4% and 3% for frequency. Apart from the study of Beuthe and Bouffioux (2008), also the surveys of Grosso (2011), Vannieuwenhuyse, Gelders, and Pintelon (2003) and Vermeiren (2013) focus partly on the Belgian transport market. An interesting finding from Vannieuwenhuyse et al. (2003) was that users of a certain transport mode award higher performance scores to a transport mode than non-users do. Vermeiren (2013), using a SP experiment, finds that cost is a decisive factor for maritimebased container transport on medium and long distance stretches, even when CO2 savings can be realized. Also the frequency of service comes out as an influential attribute. 3. Methodology A choice-based conjoint (CBC) experiment was conducted to estimate decision-makers' preferences for the main modal choice criteria, discussed above, that define transport services. The use of disaggregate models, which are based on individual behavior, takes into account characteristics of the decision-maker. The rationale here is that decision-makers will choose the alternative (or concept) that maximizes utility and thus suits their (implicit) service requirements best. In the CBC experiment, a fixed number of tasks are presented to a respondent, where he has to choose the alternative that matches his requirements best. The alternatives presented in a choice task are differentiated by their attribute levels. The analysis afterwards allows evaluating the trade-offs between the attributes made by the respondents of the experiment. The survey was administered by Sawtooth software and was sent to a respondents list by email. The first choice made in the survey design concerns the choice of attributes to be considered by the decision-makers. As described above, four attributes were included in the survey. A selective number of attributes makes the choice tasks straightforward and limits the necessary number of choice tasks in the survey reducing the effort required from participants, as it is acknowledged to be difficult to find sufficient suitable respondents (Beuthe & Bouffioux, 2008). Indeed, Hair, Black, Babin, and Anderson (2010) suggest to use a maximum of six attributes for an efficient design. Transport mode was not included as an attribute to avoid that respondents would link service level characteristics to the corresponding alternatives. The attributes finally included in the survey are: • Transport price: the transport price of a door-to-door (or door-toport/port-to-door) transport of one container, including loading and unloading • Transport time: the transit time of a transport, starting from loading
Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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until unloading, including waiting times • Transport reliability: the share of transports where the pick-up/delivery does not takes place within the demanded time window (too late/ too early) • Transport frequency: number of departures and thus possibilities to organize the transport service (per day/week). When testing the CBC design with two companies, it was suggested to inverse the definition of reliability. Therefore, it was decided, to include reliability as the share of shipments arriving outside the expected time window, rather corresponding to the notion of unreliability instead of punctuality. The attribute was however still presented as ‘reliability’ in the experiment. For each attribute, three levels were included, corresponding to realistic service levels of different transport modes operating in Belgium (Table 1). No prohibitions were included and the attribute order, as shown to the respondents, was randomized. Sawtooth advices to include 8–15 choice tasks (Sawtooth Software, 2014), but to keep the experiment accessible, each respondent was asked to complete eight choice tasks, each including four alternatives (e.g. Table 2). This lower burden of eight tasks is justified, as the number of attributes and levels is limited. By including four alternatives, level overlap in each choice task was achieved. This is useful, in case respondents always opt for the alternative displaying a certain attribute level (e.g. €300), considering it the only ‘reasonable’ alternative. This approach however allows attribute levels to appear twice in the same choice task, so that information regarding the trade-off between other attribute levels can still be derived in most cases. Hair et al. (2010) recommend including only three alternatives per task, but given the low number of attributes, attribute levels and tasks, the tasks remained clear despite including four alternatives in each task. A ‘none option’ was not included in the experiment. Of the eight choice tasks presented to each respondent, one task was the same for all respondents and represented a ‘realistic’ choice option (corresponding to the choice of road versus intermodal transport). This fixed task was also used to identify inconsistent respondents, as an alternative with all worst attribute levels was included. Regarding the randomized tasks, complete enumeration was chosen, as overlap was already achieved by including four alternatives. Finally, the efficiency of the design was tested using ordinary least squares and it was decided to aim for approximately 50 respondents. In the reviewed literature, 38 to 392 respondents were questioned, with 8 to 18 choice tasks per respondent. Clearly, more attributes and attribute levels demand more respondents and/or choice tasks. To model the preferences of the decision-makers, the hierarchical Bayes (HB) approach was chosen to gain insight in these preferences. HB estimation allows estimating part-worth utilities at the individual level, which might prove useful considering a heterogeneous sample of shippers, transport operators, LSPs and shipping agents. This estimation of part-worths was already described by Allenby and Ginter (1995) and Lenk, DeSarbo, Green, and Young (1996). Finally, the estimated utilities were rescaled after the analysis, to allow comparison of utilities between different attribute levels using a common interval scale, as suggested by Lebeau, Van Mierlo, Lebeau, Mairesse, and Macharis (2012).
Table 1 Transport attributes and variations included in the survey. Attribute
Attribute levels
Transport price (€) Transport time (h) Transport reliability (%) Transport frequency (# departures)
300–325–350 3–6–9 5–15–25 3× per week–1× per day–N1 per day
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Table 2 A respondent choosing for the fourth alternative filled out the task at random or misinterpreted the reliability attribute.
Transport time Transport price Reliability Frequency
Option 1
Option 2
Option 3
Option 4
3h € 300 15% 3× per week
9h € 325 5% 1× per day
6h € 325 5% N1× per day
9h € 350 25% 1× per day
4. Case study 4.1. Setting The case study focuses on transport operations taking place within Belgium, questioning companies that are active in Flanders. Only containerized shipments are considered and these are predominantly transported in maritime-based chains when focusing on domestic transport operations in Belgium. As a consequence of the size and shape of the country, few domestic transport operations cover distances over 300 km, being the distance-based scope of this research. The 2013 modal split of freight transport in Belgium, when expressed in tonne-kilometres, was dominated by road transport (73%) while the shares of inland waterway transport (16%) and rail transport (11%) are considerably lower (Eurostat, 2016). Detailed figures for container transport are not available, but based on 2014 data of DGSEI (2016), only 8% of the tonnes and tonne-kilometres transported by (heavy) road vehicles was container transport. 70% of the container road transport, expressed in tonne-kilometre, had its origin or destination in the district where the ports of Antwerp and Zeebrugge are located. The share of maritime-based flows is expected to be even higher when drayage operations would be included. This indicates that most of containerised road transport is indeed linked to maritime transport chains, while all scheduled domestic inland waterway – and rail transport of containers in Belgium is to and from seaports. Hinterland container transport to/from the port of Antwerp in 2015 was dominated by road transport (58%), but with a relatively high share for inland waterways (35%) and a smaller share for rail (7%) (Port of Antwerp, 2016a). On a yearly basis, 9.65 million TEU was transhipped in the port of Antwerp, 1.57 million TEU in Zeebrugge and 0.02 million TEU in Ghent in 2015. As can be witnessed in Fig. 1, these containers can be transported to/from intermodal terminals in three main corridors: a western corridor, a central corridor and an eastern corridor. On the eastern corridor, the biggest volumes are transhipped, but several Belgian terminals also (partly) serve foreign markets. The transport quality for domestic container transport depends on the performance on the four modal choice criteria that are included in the experiment. Current intermodal transport services can provide price-competitive solutions in many cases when focusing solely on the inland leg of maritime chains. Especially the regions along the three corridors can benefit from the presence of a number of terminals, providing pricecompetitive transport solutions compared to road-only transport (Meers & Macharis, 2014). Despite traffic congestion in many urban areas, roadonly transport does provide faster solutions in most cases, when compared to intermodal transport (Pekin, Macharis, Meers, & Rietveld, 2013). The frequency of inland waterway and rail services depends of the transport demand and ranges from no regular services up to eleven scheduled services a week (Port of Antwerp, 2016b). The reliability of transport time, finally, is strongly case dependent and linked to incidental congestion. 4.2. The sample Three groups of respondents were targeted in the experiment, namely transport operators and LSPs (group 1), shippers (group 2) and shipping agents (group 3). The main focus, however, was on shippers given the domination of merchant haulage. As it is important to
Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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Fig. 1. Belgian intermodal terminal landscape.
question the right person in an organization, it was preferred to directly contact the transport planner or the logistics- or general managers. To gather enough respondents, three types of sampling were used in this study. First, a shipping agent's federation and a shippers' association helped in sending out the online survey to their members. Second, respondents were derived using a search on LinkedIn, using transport/logistics manager/planner as search terms and Logistics group memberships. Finally, personal contacts and snowball sampling were used to reach the planned number of respondents. The multiple sample technique generated at least 277 survey requests. In total 148 respondents accessed the questionnaire. For several reasons, such as incompleteness or inconsistency, this number had to be reduced to 50. When possible, useful information was still obtained from the incomplete or inconsistent questionnaires. In a first part of the survey, general information was obtained from the respondents. In the sample, 21% of the respondents worked in a transportation company or as an LSP, 74% as a shipper and 6% as a shipping agent. 68% of these companies had N100 employees, and only 6% 10 or less, with 8% providing no information. Regarding the first respondents group, 73% owned a fleet of which 88% had road transport vehicles and 25% had inland waterway transport (IWT) means. Of the shippers, 13% owned a fleet, of which 100% had road transport means and 20% had IWT transport means. The goods shipped in the containers mainly had values above €10,000, only 10% had lower values, while 14% of the respondents were not aware of the total value of the transported goods. The product
category most transported within the sample was food (21%), before other goods (15%) and machines (13%). 5. Results 5.1. Modal shift barriers, mode and route decision-makers After the CBC experiment, the respondents were asked to answer some additional questions regarding their current modal split, barriers to the use of intermodal transport and the involvement of different actors in mode and route decisions. It is clear that road transport is the main mode used by the respondents, while each intermodal option is used by about one third of the respondents (Fig. 2). Of all respondents, however, 51% currently uses one or more of the intermodal transport options for a part of their transports and in total, 75% of the respondents uses one or more other modes besides road transport. Of those that are currently not using intermodal transport solutions, a striking 42% never considered using intermodal transport alternatives. The respondents were given possible reasons why they were not, or to a lesser extent, using intermodal transport solutions (Fig. 3). Shipping agents were left out, due to their limited participation in the survey. The three main reasons given by shippers and the group of transport operators and LSPs are the slow transport speed, the low service frequency and the lack of service offer. Clearly the last two reasons are strongly linked. It is striking that speed is a major barrier to use intermodal solutions, as many shipments are the inland legs of maritime transport
Fig. 2. Transport options deployed by the respondents' companies. SSS stands for Short Sea Shipping.
Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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Fig. 3. Share of respondents giving indicated reasons for not – or less – using intermodal transport solutions. (8) and (27) indicate the number of respondents that gave reasons for not – or less – using intermodal transport. Not all respondents in the sample thus completed this question.
chains, which take weeks to arrive in Belgian ports. The proportion of shippers that indicated reliability, lack of flexibility and price as reasons not to use intermodal transport outweighs the proportion of transport companies following a similar reasoning. Therefore, it appears that shippers rate the service performance of intermodal transport solutions worse than transport operators and LSPs, which is contradictory to the findings of Patterson et al. (2010). Besides, 14% of the respondents indicate that an information gap is still to be overcome, despite the efforts made to promote the use of alternative transport modes. A last part of the survey focused on who is involved in making the final decision. Fig. 4 shows that at least 50% of all respondent groups mention that the sender or the receiver is involved in the mode choice decision. Shipping agents clearly receive lower scores, but it should be noted that shipping agents are not always involved in the organization of transport. Besides, it seems striking that each respondent group attributes their selves a larger role in the decision-making process on average than the other respondent groups do. Fig. 5 shows a similar graph, but focuses on the route choice decision. Here, both respondent groups seem to agree upon the transport operators or LSPs as being highly involved in the route choice. The role of the shipper is less clear, and the big difference in the influence of the receiver and sender group can partly be related to the fact that some shippers own a fleet and organize the transport all by their selves. 5.2. Utilities When neglecting the fixed choice task, the four alternatives presented in each choice task were chosen almost an equal number of times by the 50 respondents, each having a share between 23.45% and 25.88%, which suggests that the respondents considered all alternatives when making their choice. First, a basic model was estimated, using hierarchical Bayes for the part-worth utility estimations. The percent certainty of the model
estimation was used as an indication for how much better the estimated model is than chance. This measure is calculated as the difference between the log likelihood of the model and the log likelihood of a chance model, divided by the negative log likelihood of a chance model. This value varies between 0 and 1, with 1 indicating a perfect fit (Sawtooth Software, 2009). According to Orme (2011), this pct. certainty level is within the acceptable 0.60–0.83 range. Also the root likelihood (RLH), gives an indication on the goodness of fit. The initial based model gave robust results (see simulation A in Table 3), but showed however an inconsistency for the attribute reliability which appeared to rather increase the utility when the service level was lowered, while the other utility levels all decreased with a decreasing service level (simulation A in Fig. 6). Including constraints, to arrange utilities in ‘logical’ orders, did not prove to be a solution as it did not bring satisfying results, regarding the goodness of fit. After careful analysis of each of the respondents' individual choices, it was noted that clearly 18 respondents consistently interpreted the variations in the reliability factor, contrary to 19 participants who appeared wrongly inversing the reliability construct. These respondents could be identified, as an additional question after the CBC asked the respondents whether they used threshold levels in considering choice tasks. Respondents could for instance neglect all choice alternatives with a transport cost of €350, choosing only among the €300 and €325 options, as the €350 was too expensive to consider (ignoring the other attribute levels of that same alternative). Besides, by the inclusion of four alternatives per task, respondents could choose ‘wrong’ alternatives. This also helped in identifying respondents who misinterpreted the reliability attribute levels. Table 2 provides an example. Of the four alternatives given, the second and third alternative gives in any case better or equally good service levels than the fourth alternative. This misinterpretation of the reliability attribute was probably due to the expression of reliability as the share of shipments arriving outside the expected time window. As the surveys were distributed online, there was no possibility to aid the decision-makers in filling out the
Fig. 4. Actors involved in the modal choice decision making according to the respondents. n.n. indicates that the respondent did not know who was involved in the modal choice decision, n.a. indicates that this question was not applicable to the respondent. The shipping agents were not included in this figure due to their limited number in the sample, but were included in the analysis.
Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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Fig. 5. Actors involved in the route choice according to the respondents.
survey. The remaining 13 participants could not be categorized based on their observed choice behavior in one of the above groups. As a solution, the HB analysis has been repeated for each group separately. Table 3 generates the percent certainty and RLH for each group and Fig. 6 plots the utilities. The HB analysis showed for the first two groups increased percent certainties, while the percent certainty for the third group slightly decreased, probably as a consequence of the groups' heterogeneity. The three groups yield a similar utility estimate for price, time and frequency as can be noted by their converging lines. Obviously, the reliability line follows an opposite trend for group B2 inversing the reliability construct. Lines of the different groups do not converge, indicating different weights attached to reliability in the transport decision, (partly) as a consequence of the misinterpretation of the reliability attribute. Utility lines of price and time appear having a similar inclination indicating that both factors are valued with a similar magnitude in the transport decision. Contrary to studies on long distance transport reporting that price is leading, our study on the short distance shows that the importance of speed increases when considering short distances, which corresponds to the findings of Rotaris et al. (2012). This statement is also supported by the share of respondents that indicated that long transport times are a major reason not to use intermodal transport services (Fig. 3), probably contributing to the limited market share of intermodal transport. Besides, some companies can be located in Belgium, and in particular close to the port, to decrease transport times and profit from fast deliveries. Important to mention here is that the utilities should be interpreted in a relative way making levels comparable, but not attributes in general. The incline of the frequency utility is less, indicating a lower impact on the transport decision. Particularly, at least one departure per day appears to be sufficient, as the utility of a daily frequency is approximately as high as the utility of the possibility to organize transports at multiple times a day. The graph nevertheless suggests that a lower frequency is not preferred, which corresponds to the findings of Vermeiren (2013). Focusing again on reliability, big differences in utilities are estimated for groups B1 and B2. The high and low utility levels of these groups are partly a consequence of the subdivision of the respondent sample. The maximum utilities of groups B1 and B2 would probably be lower and their minimum utilities probably higher, when the respondents of group B3 could be allotted correctly to groups B1 and B2. The interpretation problem of the reliability attribute levels makes it however much more difficult to formulate strong conclusions regarding the considered service levels. This result nevertheless matches the respondents' answers on whether there were service levels presented that lead to the exclusion of alternatives independent of the other attribute levels presented in the same alternative. Only 22% indicated that all presented service levels could be acceptable, while 20% did not consider all transport time levels, 26% not all price levels, 34% not all frequency levels and 68% not all reliability levels. This suggests that the sample of decisionmakers is rather heterogeneous and that more than half of the respondents found one or more of the reliability levels unacceptable. Shifting goods from road to intermodal on short distances requires thus foremost a price and time competitive intermodal alternative. An efficient organization of the intermodal transport will be essential to compete on time, which increases in importance on these shorter distances. Schedule reliability and frequency clearly also impact the
decision behavior. However, variations in the number of daily departures appear to have less impact when assuming at least one departure per day. Regarding the possibilities for modal shift from road to intermodal transport, it seems that the difference could be made by focusing on reliability and increasing service frequency to a daily departure for fixed transport services. Given the fact that barges and trains are considered ‘slow modes’, as compared to road transport, there seems to be very limited potential for competing with road transport times. It would however be useful, to use the outcome of this experiment in the modelling of modal choice and for the calculation of the willingness-to-pay for the different attributes in this Belgian case. This was however not done, due to the misinterpretation of the reliability by a part of the respondents. Utility estimations per actor group were not calculated, following the subdivision in respondent groups B1 to B3, which left too small samples sizes to make significant analyses. 6. Conclusion This paper presented the results of a SP experiment on modal choice requirements for short distance container transport in Belgium. The analysis focused on the service level criteria of transport cost, - time, reliability and - frequency. 6.1. Research implications The findings suggest that, considering the attribute levels included in the analysis, price is less dominant in modal choice decisions than was expected from the literature review. In particular, minimum reliability service levels are required to consider transport alternatives. This does not fully correspond to the findings of Vermeiren (2013), who focuses on container transport to/from Western European seaports on medium to long distance transport and finds that cost is decisive. As follow-up of this study, the results of the CBC survey can also be used to model transport decisions on the Belgian scale to estimate the real potential for intermodal services on the considered market segment. Unfortunately, this study did not allow categorizing transport buyers into subgroups based on their decision behavior. The subdivision into a group of transport users focusing on transport costs, a second group combining cost and quality criteria and a third group hardly using intermodal transport due to quality requirements, as suggested by Tsamboulas and Kapros (2000), might be a valuable starting point. A second avenue for further research is on disentangling the possible link between the valuation of travel time and location preferences. Regarding the practical organization of the CBC experiment, it might be
Table 3 Simulations' characteristics. Simulation
# respondents
Percent certainty
RLH
A: all respondents B1: inverse reliability B2: correct reliability B3: uncertain reliability RLH = root likelihood
50 19 18 13
0.762 0.830 0.819 0.728
0.720 0.791 0.779 0.686
Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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Fig. 6. Utilities of the four attributes in the four simulations.
recommended to rely only upon face-to-face interviews, to reduce the risk of misinterpretations. 6.2. Business implications For the further stimulation of intermodal transport in Belgium, it is recommended to focus on increasing the frequency up to daily services, as regarding transport time, intermodal transport cannot compete to road-only transport. Nevertheless, both insufficient frequency and long transport times remain a barrier to the use of intermodal transport. Obviously, price should still be considered, as it is an important criterion. The questionnaire also revealed that decision-makers not always have access to the right information to opt for intermodal transport, and that many of the decision-makers that are currently not using intermodal transport services, never even considered to use intermodal alternatives. A mental shift is required to achieve an actual modal shift to the alternative transport modes. Finally, further research could compare current outcomes to modal choice preferences in markets, which are not dominated by merchant haulage. Acknowledgements This work was supported by the Flemish Government through the Steunpunt MOBILO. The authors would also like to thank the respondents of the survey, the organizations who helped in distributing the survey, Dr. Philippe Lebeau for his input and recommendations regarding the CBC experiment and two anonymous reviewers for their valuable comments on earlier versions of this paper.
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Research in Transportation Business & Management
Modal choice preferences in short-distance hinterland container transport Dries Meers ⁎, Cathy Macharis, Tom Vermeiren, Tom van Lier Vrije Universiteit Brussel, MOBI Research Group, Pleinlaan 2, B-1050 Brussels, Belgium
a r t i c l e
i n f o
Article history: Received 14 September 2016 Received in revised form 16 February 2017 Accepted 16 February 2017 Available online xxxx Keywords: Container transport Modal choice Short distance Modal shift Choice-based conjoint experiment Intermodal transport
a b s t r a c t Short distance inland container transport to Western European seaports provides opportunities for additional modal shift to intermodal transport, thanks to the concentration of transport flows transported to the immediate hinterland of these ports. The literature on modal choice behavior, however, fails to explain the (relatively low) success of this market segment. In this paper, a choice-based conjoint experiment is conducted to increase the insight on the preferences of modal choice decision-makers in Belgium, active in the considered market segment. The findings of the experiment suggest that, to enhance a further modal shift, operators should try to provide daily services at a competitive price, with a focus on providing more reliable services than road transport. Additional efforts should be made to correctly inform decision-makers on the available intermodal services. © 2017 Elsevier Ltd. All rights reserved.
1. Introduction Intermodal transport has been promoted by regional, national and international policies throughout Europe. As advocated by inter alia the European Commission, intermodal transport proves to be a more environmentally friendly alternative to road transport in many cases (Kreutzberger, Macharis, Vereecken, & Woxenius, 2003), although this statement cannot be generalized to all cases (López-Navarro, 2014). Another important reason for stimulating intermodal transport can be found in the effort to ease port congestion. The main focus of the European Commission's modal shift efforts lay in the long distance transport segment, with the explicit goal to shift 50% of road freight over 300 km to other transport modes by 2050 (European Commission, 2011). The b300 km distance segment nevertheless corresponds to 44% of the ton-km and 89% of the total tons transported in Europe. Tavasszy and van Meijeren (2011), however, show that existing and promising intermodal transport cases below this 300 km ‘threshold’ distance also exist. An example is that of maritime-based intermodal container transport services to and from north-western European seaports in the Rotterdam-Le Havre range. Particularly intermodal barge transport can be a competitive alternative for short distance road transport in The Netherlands (Ministerie van
Abbreviations: 3PL, third party logistics company; CBC, choice-based conjoint; HB, hierarchical Bayes; IWT, inland waterway transport; LSP, logistics service provider; RLH, root likelihood; RP, revealed preference; SP, stated preference; SSS, short sea shipping. ⁎ Corresponding author. E-mail address: [email protected] (D. Meers).
Verkeer en Waterstaat, 1994), Belgium (Meers, Vermeiren, & Macharis, 2014) and France (Frémont & Franc, 2010). But also in other countries, the feasibility of short distance intermodal services through innovation has been investigated, employing for instance double-stack trains (Resor & Blaze, 2004) or a light-combi concept (Bärthel & Woxenius, 2004). As already stated by Trip and Bontekoning (2002), the key to successful short distance services mainly lies in reducing transshipment costs and time, which should be combined with sufficient transport volumes. Notwithstanding clear markets exist for short distance intermodal container transport – defined here as transport for which the roadonly alternative transport distance is under 300 km – most research projects funded by the European Commission focus on medium- to long-distance transport opportunities. The modal choice literature also mainly focuses on this market segment (Reis, 2014), although exceptions, often focusing on the inland leg of maritime chains, exist (e.g. Feo-Valero, García-Menéndez, Sáez-Carramolino and Furió-Pruñonosa, 2011). Reis (2014) tries to relate short distance intermodal successes to the modal choice literature, but concludes that this literature fails to explain them. This paper addresses one very specific market focusing on modal choice behavior in one of the ‘successful’ short distance transport markets for intermodal container transport, where earlier research in this market mainly deals with a variety of loading units and transport distances (e.g. Beuthe & Bouffioux, 2008). A choice-based conjoint experiment, elaborated in Section 3, was set up to investigate the preferences of shippers and logistics service providers for container transport in Belgium, to assess how the ‘classic’ modal choice determinants, as
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identified in the modal choice literature, are valued in the short-distance segment. The case study setting is described in Section 4. The findings from the experiment are discussed in Section 5. Section 6 presents the conclusions.
2. Literature review To disentangle the transport service requirements of decisionmakers in transport planning, an extensive modal choice literature has developed over the past decades, building on the works of, inter alia, McGinnis (1979, 1989, 1990). Older studies have been extensively described and analyzed in the review papers of Cullinane and Toy (2000), Meixell and Norbis (2008), Flodén, Bärthel, and Sorkina (2010) and Feo-Valero, García-Menéndez and Garrido-Hidalgo (2011). Crucial aspects, needing consideration, recognized in these review papers are: the identification of influential modal choice attributes, the mode and carrier selection process and the decision-maker. In their literature review, Cullinane and Toy (2000) compose a list 15 modal choice criteria categories, each comprising one or several modal choice attributes. Following the reviews of Cullinane and Toy (2000), Feo-Valero, García-Menéndez and Garrido-Hidalgo (2011) and Flodén et al. (2010) and recent modal choice studies (Arencibia, Feo-Valero, García-Menéndez, & Román, 2015; Feo, Espino, & García, 2011; Feo-Valero, García-Menéndez, Sáez-Carramolino, et al., 2011; Feo-Valero, García-Menéndez, & del Saz-Salazar, 2014; Nugroho, Whiteing, & de Jong, 2016) it was decided to include the modal choice attributes of price, transit time, transit time reliability and transport frequency as main criteria in this study. Obviously, parameters such as shipment size and product characteristics can impact these required service levels (Feo-Valero et al., 2014). Different methodologies can be used to disentangle the preferences regarding these modal choice attributes. Stated preference (SP) and revealed preference (RP) experiments are commonly used to obtain data for disaggregated transport demand models, using utility and cost functions. There is also the discussion on the actor group that should be questioned and which should be considered as the main transport mode decision-maker. In this type of studies, two types of decisionmakers are questioned, being freight forwarders or hauliers on the one hand, managing the freight, and shippers on the other hand, which can be represented by retailers, producers, distributors etc. FeoValero, García-Menéndez and Garrido-Hidalgo (2011) find that most studies focus on the shippers as decision-makers, although some studies opt to consider both groups, as arguments can be made in favor of both. In this perspective, Patterson, Ewing, and Haider (2010) find that third party logistics companies (3PLs) are more biased against intermodal transport services, compared to shippers. Holguín-Veras, Xu, de Jong, and Maurer (2011) find that mode choice decisions mainly depend on the interaction between both actor groups and the shipment size. In this study, shippers, logistics service providers (LSPs) and shipping agents are included as decision-makers. The main share of the respondents questioned are however shippers, as the transport market studied is dominated by merchant haulage. As stated in the introduction, this paper aims to focus on modal choice decisions in the market segment of short distance container transport in Belgium. Reis (2014), tested if modal choice variables from medium- to long-distance transport services can explain behavior in the short distance segment, but he concludes that these variables can hardly justify the choice of a freight forwarder for the intermodal transport services. Only transport price can explain the choice for intermodal services in his case study. Earlier studies already pointed out that modal choice preferences can change according to the transport distance travelled. Rotaris, Danielis, Sarman, and Marcucci (2012), for instance, argue that shippers with a need for fast transport are in general located close their main market, valuing time higher for short distance transport.
The unique focus on containerized goods is in this case study a consequence of their ‘ease’ to shift from road to intermodal transport services. Also Blauwens, Vandaele, Van de Voorde, Vernimmen, and Witlox (2006) focus on containerized shipments in the hinterland transport market of seaports. They use an inventory-theoretic framework to evaluate the effectiveness of modal shift policy measures. FeoValero, García-Menéndez, Sáez-Carramolino, et al. (2011) also focus on the inland leg, but in a long distance corridor where rail and road compete. According to their findings, frequency plays a crucial role in the competitiveness of rail transport, as it can compete with road-only transport on transport cost. Beuthe and Bouffioux (2008) looked at a variety of goods flows, including goods transported in containers. Based on a SP experiment, they calculate monetary values for different quality attributes, and find that the valuation of all included criteria differs rather strongly when comparing transport of containers to, for instance, semi-trailers. The corresponding weights in decision making that were derived for container transport, calculated as a measure of importance, are 71% for cost, 10% for transport time, 7% for reliability and 4% for frequency. Focusing on the short distance transport market (b300 km), cost is weighted higher with 75%, before reliability with 8%, transport time with 4% and 3% for frequency. Apart from the study of Beuthe and Bouffioux (2008), also the surveys of Grosso (2011), Vannieuwenhuyse, Gelders, and Pintelon (2003) and Vermeiren (2013) focus partly on the Belgian transport market. An interesting finding from Vannieuwenhuyse et al. (2003) was that users of a certain transport mode award higher performance scores to a transport mode than non-users do. Vermeiren (2013), using a SP experiment, finds that cost is a decisive factor for maritimebased container transport on medium and long distance stretches, even when CO2 savings can be realized. Also the frequency of service comes out as an influential attribute. 3. Methodology A choice-based conjoint (CBC) experiment was conducted to estimate decision-makers' preferences for the main modal choice criteria, discussed above, that define transport services. The use of disaggregate models, which are based on individual behavior, takes into account characteristics of the decision-maker. The rationale here is that decision-makers will choose the alternative (or concept) that maximizes utility and thus suits their (implicit) service requirements best. In the CBC experiment, a fixed number of tasks are presented to a respondent, where he has to choose the alternative that matches his requirements best. The alternatives presented in a choice task are differentiated by their attribute levels. The analysis afterwards allows evaluating the trade-offs between the attributes made by the respondents of the experiment. The survey was administered by Sawtooth software and was sent to a respondents list by email. The first choice made in the survey design concerns the choice of attributes to be considered by the decision-makers. As described above, four attributes were included in the survey. A selective number of attributes makes the choice tasks straightforward and limits the necessary number of choice tasks in the survey reducing the effort required from participants, as it is acknowledged to be difficult to find sufficient suitable respondents (Beuthe & Bouffioux, 2008). Indeed, Hair, Black, Babin, and Anderson (2010) suggest to use a maximum of six attributes for an efficient design. Transport mode was not included as an attribute to avoid that respondents would link service level characteristics to the corresponding alternatives. The attributes finally included in the survey are: • Transport price: the transport price of a door-to-door (or door-toport/port-to-door) transport of one container, including loading and unloading • Transport time: the transit time of a transport, starting from loading
Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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until unloading, including waiting times • Transport reliability: the share of transports where the pick-up/delivery does not takes place within the demanded time window (too late/ too early) • Transport frequency: number of departures and thus possibilities to organize the transport service (per day/week). When testing the CBC design with two companies, it was suggested to inverse the definition of reliability. Therefore, it was decided, to include reliability as the share of shipments arriving outside the expected time window, rather corresponding to the notion of unreliability instead of punctuality. The attribute was however still presented as ‘reliability’ in the experiment. For each attribute, three levels were included, corresponding to realistic service levels of different transport modes operating in Belgium (Table 1). No prohibitions were included and the attribute order, as shown to the respondents, was randomized. Sawtooth advices to include 8–15 choice tasks (Sawtooth Software, 2014), but to keep the experiment accessible, each respondent was asked to complete eight choice tasks, each including four alternatives (e.g. Table 2). This lower burden of eight tasks is justified, as the number of attributes and levels is limited. By including four alternatives, level overlap in each choice task was achieved. This is useful, in case respondents always opt for the alternative displaying a certain attribute level (e.g. €300), considering it the only ‘reasonable’ alternative. This approach however allows attribute levels to appear twice in the same choice task, so that information regarding the trade-off between other attribute levels can still be derived in most cases. Hair et al. (2010) recommend including only three alternatives per task, but given the low number of attributes, attribute levels and tasks, the tasks remained clear despite including four alternatives in each task. A ‘none option’ was not included in the experiment. Of the eight choice tasks presented to each respondent, one task was the same for all respondents and represented a ‘realistic’ choice option (corresponding to the choice of road versus intermodal transport). This fixed task was also used to identify inconsistent respondents, as an alternative with all worst attribute levels was included. Regarding the randomized tasks, complete enumeration was chosen, as overlap was already achieved by including four alternatives. Finally, the efficiency of the design was tested using ordinary least squares and it was decided to aim for approximately 50 respondents. In the reviewed literature, 38 to 392 respondents were questioned, with 8 to 18 choice tasks per respondent. Clearly, more attributes and attribute levels demand more respondents and/or choice tasks. To model the preferences of the decision-makers, the hierarchical Bayes (HB) approach was chosen to gain insight in these preferences. HB estimation allows estimating part-worth utilities at the individual level, which might prove useful considering a heterogeneous sample of shippers, transport operators, LSPs and shipping agents. This estimation of part-worths was already described by Allenby and Ginter (1995) and Lenk, DeSarbo, Green, and Young (1996). Finally, the estimated utilities were rescaled after the analysis, to allow comparison of utilities between different attribute levels using a common interval scale, as suggested by Lebeau, Van Mierlo, Lebeau, Mairesse, and Macharis (2012).
Table 1 Transport attributes and variations included in the survey. Attribute
Attribute levels
Transport price (€) Transport time (h) Transport reliability (%) Transport frequency (# departures)
300–325–350 3–6–9 5–15–25 3× per week–1× per day–N1 per day
3
Table 2 A respondent choosing for the fourth alternative filled out the task at random or misinterpreted the reliability attribute.
Transport time Transport price Reliability Frequency
Option 1
Option 2
Option 3
Option 4
3h € 300 15% 3× per week
9h € 325 5% 1× per day
6h € 325 5% N1× per day
9h € 350 25% 1× per day
4. Case study 4.1. Setting The case study focuses on transport operations taking place within Belgium, questioning companies that are active in Flanders. Only containerized shipments are considered and these are predominantly transported in maritime-based chains when focusing on domestic transport operations in Belgium. As a consequence of the size and shape of the country, few domestic transport operations cover distances over 300 km, being the distance-based scope of this research. The 2013 modal split of freight transport in Belgium, when expressed in tonne-kilometres, was dominated by road transport (73%) while the shares of inland waterway transport (16%) and rail transport (11%) are considerably lower (Eurostat, 2016). Detailed figures for container transport are not available, but based on 2014 data of DGSEI (2016), only 8% of the tonnes and tonne-kilometres transported by (heavy) road vehicles was container transport. 70% of the container road transport, expressed in tonne-kilometre, had its origin or destination in the district where the ports of Antwerp and Zeebrugge are located. The share of maritime-based flows is expected to be even higher when drayage operations would be included. This indicates that most of containerised road transport is indeed linked to maritime transport chains, while all scheduled domestic inland waterway – and rail transport of containers in Belgium is to and from seaports. Hinterland container transport to/from the port of Antwerp in 2015 was dominated by road transport (58%), but with a relatively high share for inland waterways (35%) and a smaller share for rail (7%) (Port of Antwerp, 2016a). On a yearly basis, 9.65 million TEU was transhipped in the port of Antwerp, 1.57 million TEU in Zeebrugge and 0.02 million TEU in Ghent in 2015. As can be witnessed in Fig. 1, these containers can be transported to/from intermodal terminals in three main corridors: a western corridor, a central corridor and an eastern corridor. On the eastern corridor, the biggest volumes are transhipped, but several Belgian terminals also (partly) serve foreign markets. The transport quality for domestic container transport depends on the performance on the four modal choice criteria that are included in the experiment. Current intermodal transport services can provide price-competitive solutions in many cases when focusing solely on the inland leg of maritime chains. Especially the regions along the three corridors can benefit from the presence of a number of terminals, providing pricecompetitive transport solutions compared to road-only transport (Meers & Macharis, 2014). Despite traffic congestion in many urban areas, roadonly transport does provide faster solutions in most cases, when compared to intermodal transport (Pekin, Macharis, Meers, & Rietveld, 2013). The frequency of inland waterway and rail services depends of the transport demand and ranges from no regular services up to eleven scheduled services a week (Port of Antwerp, 2016b). The reliability of transport time, finally, is strongly case dependent and linked to incidental congestion. 4.2. The sample Three groups of respondents were targeted in the experiment, namely transport operators and LSPs (group 1), shippers (group 2) and shipping agents (group 3). The main focus, however, was on shippers given the domination of merchant haulage. As it is important to
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Fig. 1. Belgian intermodal terminal landscape.
question the right person in an organization, it was preferred to directly contact the transport planner or the logistics- or general managers. To gather enough respondents, three types of sampling were used in this study. First, a shipping agent's federation and a shippers' association helped in sending out the online survey to their members. Second, respondents were derived using a search on LinkedIn, using transport/logistics manager/planner as search terms and Logistics group memberships. Finally, personal contacts and snowball sampling were used to reach the planned number of respondents. The multiple sample technique generated at least 277 survey requests. In total 148 respondents accessed the questionnaire. For several reasons, such as incompleteness or inconsistency, this number had to be reduced to 50. When possible, useful information was still obtained from the incomplete or inconsistent questionnaires. In a first part of the survey, general information was obtained from the respondents. In the sample, 21% of the respondents worked in a transportation company or as an LSP, 74% as a shipper and 6% as a shipping agent. 68% of these companies had N100 employees, and only 6% 10 or less, with 8% providing no information. Regarding the first respondents group, 73% owned a fleet of which 88% had road transport vehicles and 25% had inland waterway transport (IWT) means. Of the shippers, 13% owned a fleet, of which 100% had road transport means and 20% had IWT transport means. The goods shipped in the containers mainly had values above €10,000, only 10% had lower values, while 14% of the respondents were not aware of the total value of the transported goods. The product
category most transported within the sample was food (21%), before other goods (15%) and machines (13%). 5. Results 5.1. Modal shift barriers, mode and route decision-makers After the CBC experiment, the respondents were asked to answer some additional questions regarding their current modal split, barriers to the use of intermodal transport and the involvement of different actors in mode and route decisions. It is clear that road transport is the main mode used by the respondents, while each intermodal option is used by about one third of the respondents (Fig. 2). Of all respondents, however, 51% currently uses one or more of the intermodal transport options for a part of their transports and in total, 75% of the respondents uses one or more other modes besides road transport. Of those that are currently not using intermodal transport solutions, a striking 42% never considered using intermodal transport alternatives. The respondents were given possible reasons why they were not, or to a lesser extent, using intermodal transport solutions (Fig. 3). Shipping agents were left out, due to their limited participation in the survey. The three main reasons given by shippers and the group of transport operators and LSPs are the slow transport speed, the low service frequency and the lack of service offer. Clearly the last two reasons are strongly linked. It is striking that speed is a major barrier to use intermodal solutions, as many shipments are the inland legs of maritime transport
Fig. 2. Transport options deployed by the respondents' companies. SSS stands for Short Sea Shipping.
Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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Fig. 3. Share of respondents giving indicated reasons for not – or less – using intermodal transport solutions. (8) and (27) indicate the number of respondents that gave reasons for not – or less – using intermodal transport. Not all respondents in the sample thus completed this question.
chains, which take weeks to arrive in Belgian ports. The proportion of shippers that indicated reliability, lack of flexibility and price as reasons not to use intermodal transport outweighs the proportion of transport companies following a similar reasoning. Therefore, it appears that shippers rate the service performance of intermodal transport solutions worse than transport operators and LSPs, which is contradictory to the findings of Patterson et al. (2010). Besides, 14% of the respondents indicate that an information gap is still to be overcome, despite the efforts made to promote the use of alternative transport modes. A last part of the survey focused on who is involved in making the final decision. Fig. 4 shows that at least 50% of all respondent groups mention that the sender or the receiver is involved in the mode choice decision. Shipping agents clearly receive lower scores, but it should be noted that shipping agents are not always involved in the organization of transport. Besides, it seems striking that each respondent group attributes their selves a larger role in the decision-making process on average than the other respondent groups do. Fig. 5 shows a similar graph, but focuses on the route choice decision. Here, both respondent groups seem to agree upon the transport operators or LSPs as being highly involved in the route choice. The role of the shipper is less clear, and the big difference in the influence of the receiver and sender group can partly be related to the fact that some shippers own a fleet and organize the transport all by their selves. 5.2. Utilities When neglecting the fixed choice task, the four alternatives presented in each choice task were chosen almost an equal number of times by the 50 respondents, each having a share between 23.45% and 25.88%, which suggests that the respondents considered all alternatives when making their choice. First, a basic model was estimated, using hierarchical Bayes for the part-worth utility estimations. The percent certainty of the model
estimation was used as an indication for how much better the estimated model is than chance. This measure is calculated as the difference between the log likelihood of the model and the log likelihood of a chance model, divided by the negative log likelihood of a chance model. This value varies between 0 and 1, with 1 indicating a perfect fit (Sawtooth Software, 2009). According to Orme (2011), this pct. certainty level is within the acceptable 0.60–0.83 range. Also the root likelihood (RLH), gives an indication on the goodness of fit. The initial based model gave robust results (see simulation A in Table 3), but showed however an inconsistency for the attribute reliability which appeared to rather increase the utility when the service level was lowered, while the other utility levels all decreased with a decreasing service level (simulation A in Fig. 6). Including constraints, to arrange utilities in ‘logical’ orders, did not prove to be a solution as it did not bring satisfying results, regarding the goodness of fit. After careful analysis of each of the respondents' individual choices, it was noted that clearly 18 respondents consistently interpreted the variations in the reliability factor, contrary to 19 participants who appeared wrongly inversing the reliability construct. These respondents could be identified, as an additional question after the CBC asked the respondents whether they used threshold levels in considering choice tasks. Respondents could for instance neglect all choice alternatives with a transport cost of €350, choosing only among the €300 and €325 options, as the €350 was too expensive to consider (ignoring the other attribute levels of that same alternative). Besides, by the inclusion of four alternatives per task, respondents could choose ‘wrong’ alternatives. This also helped in identifying respondents who misinterpreted the reliability attribute levels. Table 2 provides an example. Of the four alternatives given, the second and third alternative gives in any case better or equally good service levels than the fourth alternative. This misinterpretation of the reliability attribute was probably due to the expression of reliability as the share of shipments arriving outside the expected time window. As the surveys were distributed online, there was no possibility to aid the decision-makers in filling out the
Fig. 4. Actors involved in the modal choice decision making according to the respondents. n.n. indicates that the respondent did not know who was involved in the modal choice decision, n.a. indicates that this question was not applicable to the respondent. The shipping agents were not included in this figure due to their limited number in the sample, but were included in the analysis.
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Fig. 5. Actors involved in the route choice according to the respondents.
survey. The remaining 13 participants could not be categorized based on their observed choice behavior in one of the above groups. As a solution, the HB analysis has been repeated for each group separately. Table 3 generates the percent certainty and RLH for each group and Fig. 6 plots the utilities. The HB analysis showed for the first two groups increased percent certainties, while the percent certainty for the third group slightly decreased, probably as a consequence of the groups' heterogeneity. The three groups yield a similar utility estimate for price, time and frequency as can be noted by their converging lines. Obviously, the reliability line follows an opposite trend for group B2 inversing the reliability construct. Lines of the different groups do not converge, indicating different weights attached to reliability in the transport decision, (partly) as a consequence of the misinterpretation of the reliability attribute. Utility lines of price and time appear having a similar inclination indicating that both factors are valued with a similar magnitude in the transport decision. Contrary to studies on long distance transport reporting that price is leading, our study on the short distance shows that the importance of speed increases when considering short distances, which corresponds to the findings of Rotaris et al. (2012). This statement is also supported by the share of respondents that indicated that long transport times are a major reason not to use intermodal transport services (Fig. 3), probably contributing to the limited market share of intermodal transport. Besides, some companies can be located in Belgium, and in particular close to the port, to decrease transport times and profit from fast deliveries. Important to mention here is that the utilities should be interpreted in a relative way making levels comparable, but not attributes in general. The incline of the frequency utility is less, indicating a lower impact on the transport decision. Particularly, at least one departure per day appears to be sufficient, as the utility of a daily frequency is approximately as high as the utility of the possibility to organize transports at multiple times a day. The graph nevertheless suggests that a lower frequency is not preferred, which corresponds to the findings of Vermeiren (2013). Focusing again on reliability, big differences in utilities are estimated for groups B1 and B2. The high and low utility levels of these groups are partly a consequence of the subdivision of the respondent sample. The maximum utilities of groups B1 and B2 would probably be lower and their minimum utilities probably higher, when the respondents of group B3 could be allotted correctly to groups B1 and B2. The interpretation problem of the reliability attribute levels makes it however much more difficult to formulate strong conclusions regarding the considered service levels. This result nevertheless matches the respondents' answers on whether there were service levels presented that lead to the exclusion of alternatives independent of the other attribute levels presented in the same alternative. Only 22% indicated that all presented service levels could be acceptable, while 20% did not consider all transport time levels, 26% not all price levels, 34% not all frequency levels and 68% not all reliability levels. This suggests that the sample of decisionmakers is rather heterogeneous and that more than half of the respondents found one or more of the reliability levels unacceptable. Shifting goods from road to intermodal on short distances requires thus foremost a price and time competitive intermodal alternative. An efficient organization of the intermodal transport will be essential to compete on time, which increases in importance on these shorter distances. Schedule reliability and frequency clearly also impact the
decision behavior. However, variations in the number of daily departures appear to have less impact when assuming at least one departure per day. Regarding the possibilities for modal shift from road to intermodal transport, it seems that the difference could be made by focusing on reliability and increasing service frequency to a daily departure for fixed transport services. Given the fact that barges and trains are considered ‘slow modes’, as compared to road transport, there seems to be very limited potential for competing with road transport times. It would however be useful, to use the outcome of this experiment in the modelling of modal choice and for the calculation of the willingness-to-pay for the different attributes in this Belgian case. This was however not done, due to the misinterpretation of the reliability by a part of the respondents. Utility estimations per actor group were not calculated, following the subdivision in respondent groups B1 to B3, which left too small samples sizes to make significant analyses. 6. Conclusion This paper presented the results of a SP experiment on modal choice requirements for short distance container transport in Belgium. The analysis focused on the service level criteria of transport cost, - time, reliability and - frequency. 6.1. Research implications The findings suggest that, considering the attribute levels included in the analysis, price is less dominant in modal choice decisions than was expected from the literature review. In particular, minimum reliability service levels are required to consider transport alternatives. This does not fully correspond to the findings of Vermeiren (2013), who focuses on container transport to/from Western European seaports on medium to long distance transport and finds that cost is decisive. As follow-up of this study, the results of the CBC survey can also be used to model transport decisions on the Belgian scale to estimate the real potential for intermodal services on the considered market segment. Unfortunately, this study did not allow categorizing transport buyers into subgroups based on their decision behavior. The subdivision into a group of transport users focusing on transport costs, a second group combining cost and quality criteria and a third group hardly using intermodal transport due to quality requirements, as suggested by Tsamboulas and Kapros (2000), might be a valuable starting point. A second avenue for further research is on disentangling the possible link between the valuation of travel time and location preferences. Regarding the practical organization of the CBC experiment, it might be
Table 3 Simulations' characteristics. Simulation
# respondents
Percent certainty
RLH
A: all respondents B1: inverse reliability B2: correct reliability B3: uncertain reliability RLH = root likelihood
50 19 18 13
0.762 0.830 0.819 0.728
0.720 0.791 0.779 0.686
Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011
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Fig. 6. Utilities of the four attributes in the four simulations.
recommended to rely only upon face-to-face interviews, to reduce the risk of misinterpretations. 6.2. Business implications For the further stimulation of intermodal transport in Belgium, it is recommended to focus on increasing the frequency up to daily services, as regarding transport time, intermodal transport cannot compete to road-only transport. Nevertheless, both insufficient frequency and long transport times remain a barrier to the use of intermodal transport. Obviously, price should still be considered, as it is an important criterion. The questionnaire also revealed that decision-makers not always have access to the right information to opt for intermodal transport, and that many of the decision-makers that are currently not using intermodal transport services, never even considered to use intermodal alternatives. A mental shift is required to achieve an actual modal shift to the alternative transport modes. Finally, further research could compare current outcomes to modal choice preferences in markets, which are not dominated by merchant haulage. Acknowledgements This work was supported by the Flemish Government through the Steunpunt MOBILO. The authors would also like to thank the respondents of the survey, the organizations who helped in distributing the survey, Dr. Philippe Lebeau for his input and recommendations regarding the CBC experiment and two anonymous reviewers for their valuable comments on earlier versions of this paper.
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Please cite this article as: Meers, D., et al., Modal choice preferences in short-distance hinterland container transport, Research in Transportation Business & Management (2017), http://dx.doi.org/10.1016/j.rtbm.2017.02.011