THE ECO FACTOR IN FREIGHT TRANSPORTATION DEMAND

Transcription

1 THE ECO FACTOR IN FREIGHT TRANSPORTATION DEMAND By Thomas Laitila 1,2 and Kerstin Westin 1,3 1 Transportation Research Unit 2 Department of Statistics 3. Department of Social and Economic Geography University of Umeå, 1 Introduction Just-In-Time (JIT) is a philosophy in business logistics that aims at reducing production costs by avoiding unnecessary logistics activities. Examples of such unnecessary activities are redundant transports, warehousing, and excessive capital costs. JIT stands for production of each unit at the exact time when it is needed or demanded. By a demandoriented production, costs for warehousing and inventories, for both production and delivery, can be reduced. JIT is an accepted phenomenon in society at large as well as in industry. JIT-transports have come to signify fast, safe, frequent and flexible transports, but also transports that require minute planning and sophisticated computer-based logistics. The possibility of achieving substantial economic benefits from efficient logistics and JIT has induced more and more companies to make changes in the key activities of logistics: transportation, inventory, and order processing. The result of adopting a JIT-concept in business can be seen in several manufacturing and service companies. The modern grocery store has no real storage room any more; the deliveries come around several times a week and incoming goods are almost immediately placed on shelves in the store. Manufacturing companies tend to reduce their inventories of assembly parts to last for two or three days. An application of JIT-concept in production highlights the importance of certain transportation characteristics of factors, that are essential for functioning logistics chain; high frequency, high demand on time accuracy, high demands on goods safety, short delivery time, and accurate information on deviation from set schedule (Tarkowski and Ireståhl, 1988).

2 Studies of freight customers have shown that delivery time, safety and regularity/frequency guarantees are important considerations (for example TRANSEK, 1990; Westin, 1994). Small, frequent goods deliveries that arrive in time and in undamaged condition are what customers rate most highly. At the same time, the environmental aspects of transportation are becoming more emphasized. Environmental questions are the focus of many public discussions, and the problems connected with increasing traffic volume often relate to negative environmental effects. ECO-certification has become common for many haulage companies and individual freight carriers. ECO-certification and so-called "green transport" has in many cases become a marketing argument. Recent studies of consumer product demand have revealed the effect of ECO-factors. This has urged many suppliers to provide the markets with ECO-products, i.e. environment friendly products. There are, at least in Sweden, some late indications that ECO-factors prevail as important determinants for freight transport decision. Freight transport industries and many manufacturers aiming for an environment friendly profile have reported this. However, there is a lack of research studies of the importance of ECO-factors for freight transportation demand. Is environmental concern also included along with the more traditional factors affecting the choice and evaluation of a freight carrier? In the project The importance of environmental considerations for freight transport, financed by the Swedish National Road Administration, the objective is to examine the significance of environmental concern, here described as the ECO-factor, for a company's choice of freight carrier, and whether there are regional variations. The starting-point is to describe and measure the practical environmental commitment of the various freight companies, and to estimate how important the ECO-factor is for customers choosing a freight carrier. How does ECOcertification affect goods transport? Does a transport customer in a region with high traffic density assess the ECO-factor differently from, say, a customer in northern Sweden? Differing assessments may lead to differing choices of carrier; measures based on the assumption that transport customers attach certain significance to their cost may have an impact only in some regions, while customers in other regions may behave differently. At the same time, freight transport is not restricted to regional limits: in the case of interregional transport one customer's decision can have consequences for other regions where local customers base their decisions on other criteria. This paper presents a study aiming for measuring the importance of ECO-factors in freight transport demand. In the study, consumers of freight transports are studied and their valuations of transport factors are measured through stated choice experiments. The population of freight transport customers is segmented with respect to their line of business. Also, measures of regional variation are attempted for. The objective of the paper is to discuss choice of methods for measuring the importance of the ECO-factor in transport customers choice of transport operator and transport mode. In addition, problems related to measuring and describing the ECO-factor are discussed.

3 2 Models of freight transport demand Several theoretical and empirical disaggregate models of freight transport demand have been suggested in the literature since the late seventies. Allen (1977) studies transport demand within the theory of the firm and, transport is treated as just one of the factors affecting e.g. profit. Daughety (1979) and Winston (1981) introduce the concept of decision under uncertainty into models of transport demand. Transport decisions is derived from utility maximization conditional on risk considerations of different decision alternatives. The transport customer may experience immediate and/or long-term economical losses from bad transport solutions. The customer has to decide on expected performances of transport alternatives whereby random expected utility models need to be considered for modeling. Daughety (1979) defines a stochastic profit function in terms of shipment sizes to different markets and/or by different modes conditional on market prices, transportation costs, costs induced by the service of the transport and, costs of production. A utility function on profits is assumed and the decision problem is to maximize utility with respect to shipment sizes to markets and by modes. The model suggested by Daughety (1979) generally imply shipments to a number of markets and by a number of different modes, a strategy analogous to strategies for minimization of expected costs found in other areas. However, if the risk taken is small, e.g. small and medium shipment sizes of low value goods, the model imply a single market and transport mode solution. Thus, in such cases, mode choice models like MNL or nested logit may be applied. Winston (1981) defines a utility function in terms of modal attributes, e.g. costs and service attributes. The performance of a mode is unknown and the customer maximizes expected utility. For empirical application Winston adds a random disturbance term and defines a random expected utility model in which expected utilities may be correlated between modes. One major contribution by Winston is the notion of the difference between a shipper and a receiver mode choice problem. The simultaneous consideration of mode and shipment size in Daughety (1979) has been studied in later works as well. Examples are McFadden, Winston and Boersch-Supan (1985) and Abdelwahab and Sargious (1992). These papers consider the single market case whereas Daughety (1979) treats the multiple market case. (See also Zlatoper and Austria, 1989.) JIT factors can easily be introduced within the approaches taken by e.g. Daughety (1979) and Winston (1981). These authors consider service variables as sources of uncertainty and JIT factors can be interpreted as such service variables. The inclusion of ECO factors into an economic representation of the mode choice problem is more complicated, however, and to our knowledge there has been no such attempt reported in the literature. Generally, deciding on environmental friendly transports adds extra costs although the performance of the logistic system is not improved (with exceptions for effects on the

4 environment, naturally). Eco factors can therefore not be introduced into the models simply by treating them as some extra mode attributes. The rational for a customer to choose an expensive environment friendly mode alternative can be found in the demand of the product supplied to the market. Thus, the mode choice has to be linked to market demand of the product supplied. It is possible that Daughety s (1979) model can be used if market segments of green products are treated as separate markets. Aggregate data like market share observations can be used for the analysis of freight transport demand. However, disaggregate data has a number of advantages over aggregate data for the analysis of the behavior of individual decision-makers (e.g. Winston, 1983). A study using disaggregate data allows more specific characterization of the decision problem faced by the freight transport customer. The case considered in our study thus motivate the use of disaggregate data. Theory implies the comparison of different transport mode alternatives with respect to their characteristics or attributes. It is therefore important to measure all the alternatives considered by the decision-maker. Furthermore, it is also important to measure the characteristics of all the alternatives considered. Thus, the measurement problem within a survey of actual behavior of freight transport customers is huge. Wynter (1995) utilize a stated preference (SP) technique (e.g. Hensher, 1994) in a study of road freight transports in France. Applying SP techniques to our problem gives the advantage of control over characteristics of transportation modes. The measurement problems associated with a disaggregate study of revealed preferences is thereby circumvented. A disadvantage is that SP data reflects hypothetical behavior and not real life behavior. However, McFadden (1998) notes that SP techniques may perform well if the topic considered is close to real life decisions made by the respondent. 3 Measuring ECO factor importance 3.1 Freight transport in Sweden In 1997 approximately 500 million tons of goods was transported within Sweden. The goods transport performance amounted to millions of tonkm (SIKA, 1998). As in most European countries today, the goods volumes and transport performance by rail and shipping is constant or even diminishing, and the growth in the transport sector is in road transports. In the past 10 years the transport performance has increased by 18 percent, and the relatively largest increase was noted for truck transports. Approximately 20 percent of the total domestic energy are consumed by the transport sector, and it is mainly oil products that are used. Trucks are run on diesel fuel, and to some extent petrol. A few vehicles run on bio-fuels, but this is still at an experimental stage. Road transports affects the environment in a number of mostly negative - ways. The use of petroleum conduces to the greenhouse effect by emission of CO 2. The emission of nitro-oxides (NO X ) aggravates the acid problem in lakes and soil, over-fertilization, and

5 also leads to ozone development. Road traffic also causes emission of unhealthy or harmful inhaleable particles. These particles emanate from road materials such as asphalt, from tires, from motor oils and vehicle fuels, and from incomplete combustion. In addition, road traffic causes noise and accidents. The problems that arise from increased road traffic have, together with an increased general environmental concern and awareness, encouraged customers to demand environmentally friendly transports. It is no longer sufficient to call for ecologically produced products, the whole chain of production including transports has to be ecological. Freight transport customers have until recently emphasized traditional JIT-factors, but there seems to be a trend towards accentuating environmental aspects. For many companies an environmental or ecological profile is a marketing advantage. In addition to quality control and accrediting, companies also engage in series of environmental management systems, such as ISO or EMAS. These emerging demands are being met by a growing number of transportation companies. As of January 1999 about 10 major Swedish companies engaged in private or for-hire freight transportation were ISO-certified. The practical environmental management work that has been initiated by several brokers and truck owners covers different categories of measures for limiting the negative environmental impacts caused by the transport sector. Some measures aim at changing driving behavior, others measures are directed towards logistics, vehicle technique and performance, or fuel. 3.2 Design of survey In order to estimate the value of environmental concern in transportation services, a survey of the freight transportation consumers is conducted. Freight transports differ from each other depending on type of goods and transported distance. Three types of goods are represented to get an accurate representation of different types of transport assignments. The first comprises assembled cargo ( speditionsgods ) and miscellaneous which is generally small-lot sizes of all kinds of goods, transported by brokers such as ASG and BTL. The second type consists of food products including brewery products, and the third includes construction materials, mainly sand and gravel. Almost half of the number of shipments of assembled cargo in 1997 was short-distance transports, i.e. local transports up to 25 km (SCB, 1998). Transports of food products are to a large extent long distant, due to the geographic concentration of food production and warehouses. Transport of food products amounts to less than 10 percent of the total transported volume, but are included in the survey since they require special transport arrangements, and in general strongly JIT-oriented. Slightly more than 50 percent of the transports are transports of construction materials, and they are mainly local. Table 1 shows the types of transports that are included in the survey.

6 Assembled cargo Food products Construction material Table 1. Survey design companies, transport distance and sample size SNI-code Local, < 25 km Regional, km Interregional, >100 km No. of interviews (n) Population (N) 17-22, 24- X X X , , 16 X X , 452 X X The population of transport customers consists of companies that have frequent shipments of goods to or from their company. The sampling is a two step procedure. To ensure that there is some regularity in the transport activities, only companies with 5 employees or more are chosen. The sample of these transport customers is drawn from the Företagsregister at Statistics Sweden, and is defined according to economic activity (SNIcode). In the second step the companies logistic manager, or the person responsible for transportation, is contacted by phone. They are asked if they ship goods by truck or rail with some regularity. In the second step those who answer in affirmative, are informed about the study, and asked to fill out a questionnaire that will be mailed to them. At this stage the respondents are also asked whether their main transports are local, regional or inter-regional. The questionnaire sent to the respective company is dependent on type of transport, as the design of the questionnaire varies with respect to transport distance and type of industry (economic activity) for each company. The questionnaire consists of two parts. In the first part, the respondent is presented a number of hypothetical transport assignments, where volume and distance is given. The transport is defined by six factors; transport mode, cost of transport, delivery frequency, environmental impact, delivery time, and time accuracy. The respondent is asked to choose which one of two proposed assignments he or she prefers (pair-wise comparison). The factor transport mode varies for companies with inter-regional transport, and they are presented the choice of truck or rail. For regional and local transports only truck is available. The levels of the factors also vary with transport distance. Transport cost is described in three levels; (i) average cost given goods volume and distance, (ii) a level 20 to 30 percent lower than the average, and (iii) a level 20 to 30 percent higher. The deviations correspond to discounts and variations that brokers apply. Delivery frequency is described in three levels, but vary with type of transport from being stated in number of shipments per week (assembled cargo and food products) or tons per time unit (construction materials). Environmental impact is presented in three levels; (i) no specified environment management, (ii) a NO X emission of 6 g/kwh, and (iii) a NO X emission of 5.5 g / kwh. Finally, time accuracy is varied on two levels, where high accuracy indicates no or very low deviations from stated time, and low is a higher deviation. The logistics managers of the companies are presented a number of transport situations, which are described, by a number of attributes/factors. These factors are varied on at least

7 two levels. The factors represent transportation cost, transport mode, the traditional JITcharacteristics delivery-time, frequency, and time accuracy. These factors have been tested in other studies and have proved to be measurable by SP-technique. In addition, a factor denoting environmental concern is added. This factor, called the ECO-factor, is an attempt to describe environmental or ecological behavior in a summarized way, i.e. ranging from no concern to adopted environmental management program. 4 Discussion The study aims for an indication of the extent of environmental concern made by customers of freight transport. The design used allows a study of differences among customers within different lines of businesses as well as differences among customers within different regional locations. Information collected through the questionnaire adds extra opportunities of analyzing characteristics of firms making environmental concerns. Thus, it is expected that results will give an informative picture of the importance of ECOfactors for freight transport demand. It is obvious that there are addressable theoretical and empirical problems associated with the measurement of the importance of ECO-factors. A theoretical problem is how ECOfactors enter the utility function forming the base upon which decisions on transportation variables are made. The theory presented by Daughety (1979) can in some cases be adapted by treating a market segment of green products as a separate market. This approach does not work in general however. Alternatively, a more general theory may origin in adding an extra argument in an utility function defined on profits. The extra argument should be some kind of index of the environmental concerns taken in the decisions on transportation alternatives. Extra costs introduced by more expensive environmental friendly transports are compensated by goodwill and consumers perception of the environmental friendly profile of the company.

8 Bibliography Abdelwahab, W. and M. Sargious (1992). Modelling the demand for freight transport: A new approach, Journal of Transportation Economics and Policy 26, pp Allen, W.B. (1977). The demand for freight transportation: A micro approach. Transportation Research 11, pp Daughety, A.F. (1979). Freight transport demand revisited: A microeconomic view of multimodal, multicharactersitic service uncertainty and the demand for freight transport, Transportation Research B13, pp Hensher, D. (1994). Stated Preference analysis of travel choices: The state of practice. Transportation 21, p McFadden, D. (1998). Measuring Willingness-To-Pay for Transportation Improvements. In: Gärling, T., Laitila, T. and K. Westin (Eds.), Theoretical Foundations of Travel Choice Modeling, Pergamon, Amsterdam, pp McFadden, D., Winston, C. and A. Boersch-Supan (1985). Joint estimation of freight transportation decisions under nonrandom sampling. In: Daughety A.F. (Ed.), Analytical Studies in Transport Economics, Academic Press, New York, pp SCB (1998). Statistiska Meddelanden, T 30 SM SIKA (1998). Transporter och kommunikationer. Årsbok Statens Institut för Kommunikationsanalys, Värnamo Tarkowski, J. And B. Ireståhl (1988). Transportadministration. Studentlitteratur. TRANSEK (1990). Godskunders värdeingar (Transprtation consumers valuation). Banverket, Planeringsavdelningen. Westin, K. (1994). Valuation of Goods Transportation Characteristics. Geographical Reports 12. Academic thesis, University of Umeå. Winston, C. (1981). A disaggregate model of the demand for intercity freight transportation, Econometrica 49, pp Wynter, L.M. (1995). Stated preference survey for calculating values of time of road freight transport in France, Transportation Research Record 1477, pp Zlatoper, T.J. and Z. Austria (1989). Freight transportation demand: A survey of recent econometric studies, Transportation 16, pp