2.1 Definition of the Term Acceptance

Existing literature offers a myriad of different definitions and classifications of the concept of acceptance. The ambiguous use of the term acceptance is problematic since a clear definition is needed before it can be evaluated and understood how acceptance is formed (Adell et al., 2018). If there exists no clear definition, there is a severe risk of misinterpretation and misjudgment of research results concerning users’ acceptance. This subchapter is therefore dedicated to the definition of the term acceptance.

Studying the acceptance of a target group is an important task because acceptance is a critical success factor for the realization of innovations (Geldmacher et al., 2017). Acceptance constitutes “a psychological process that starts with pure interest in an innovation and leads toward the (regular) use of this innovation” (Geldmacher et al., 2017, p. 272). Notably, the actual start and end of the acceptance process depend heavily on the specific definition. Several definitions refer to different stages of acceptance: some definitions require system use as a result of acceptance, others only refer to a positive attitude as the end of the acceptance process. Due to this variety of nuances, the different stages of acceptance will be discussed in the following.

2.1.1 Stages of Acceptance

Existing definitions on acceptance vary considerably regarding the degree of commitment required for the specific innovation under study. Different stages of acceptance can be identified ranging from stages with low commitment required to characterize acceptance (e.g. usefulness) to stages where high commitment is required to characterize acceptance (actual system use). Figure 2.1 illustrates the different stages of acceptance, which are related to the constructs of the technology acceptance model (usefulness, attitude, intention to use and actual system use; to be later discussed in subchapter 5.1.3).

Figure 2.1
figure 1

Stages of acceptance

Full size image

Defining acceptance by the usefulness

The most elementary stage of acceptance is usefulness, i.e. the benefits or gain that users expect to obtain by adopting an innovation. Some authors refer to usefulness to define acceptance, as they claim that users accept a system or a technology when they find it useful. For example, Nielsen (1993, p. 24) states that acceptance is “basically the question whether the system is good enough to satisfy all the needs and requirements of the users and other potential stakeholders”. An example for this first acceptance stage would be if an organization (or its transport manager) considers alternative fuels as useful to reduce their carbon footprint. However, this explanation of acceptance falls very short as considering a system as useful does not imply that an individual would actually use this system.

Defining acceptance by the attitude

The next stage of acceptance involves having a positive attitude about an innovation. Attitude can be described as “a psychological tendency that is expressed by evaluating a particular entity with some degree of favor or disfavor” (Eagly and Chaiken, 1993, p. 1). Some authors state that having a positive opinion and mindset towards a system or technology implies that the system/technology is accepted. For example, Risser and Lehner (1998, p. 8) describe that “acceptance refers to what the objects or contents for which acceptance is measured are associated to; what do those objects or contents imply for the asked person”. Compared to the first stage of acceptance which is bound up with rational considerations about the usability of an innovation, this second stage of acceptance is additionally driven by the users’ emotions towards the innovation, which are reflected in their attitude (Adell et al., 2018). This second stage of acceptance is also referred to as attitudinal acceptance (Ausserer and Risser, 2005). Attitudinal acceptance is a consequence of considering the usefulness of an innovation. An example for attitudinal acceptance would be if an organization appreciates alternative fuels as effective and viable option to reduce their carbon footprint, but they think they do not need alternative fuels for their company. Therefore, the second acceptance stage is still not related to the use of an innovation (Ausserer and Risser, 2005).

Defining acceptance by the intention to use

The third stage of acceptance is related to the will to use an innovation or a technology, which is also called the intention to use. Some authors equate acceptance with intention to use, for example Chismar and Wiley-Patton (2003). The intention to use can either rest on practical experience of the system or on theoretical knowledge and judgment (Adell et al., 2018). The latter is also known as “a priori acceptance”, i.e. the evaluation of a system or technology before having actual contact to the system/technology (Payre et al., 2014). The intention to use an innovation is a consequence of attitudinal acceptance. An example for this acceptance stage would be if an organization is willing to use alternative fuels though they are not using them at currently (and possibly have no experience with alternative fuels).

Defining acceptance by the actual system use

The last stage of acceptance involves full commitment to an innovation, as the innovation is already in practical use at this stage. Several authors stipulate that acceptance only occurs in combination with actual system use, for example Dillon and Morris (1996) state that acceptance must be demonstrable by the employment of the technology under study. This type of acceptance is also referred to as behavioral acceptance, because acceptance is expressed by actual behavior (Schmalfuß et al., 2017). Actual system use is a consequence of the intention to use an innovation. An example for this last acceptance stage would be if an organization actually uses alternative fuels.

2.1.2 Further Differentiation of Acceptance

Beside the above described classification of acceptance stages, there are some further ways to differentiate various types of acceptance. To better grasp the concept of acceptance, some common differentiations that frequently occur in the literature will be discussed in the following.

The classification of attitudinal and behavioral acceptance has already been introduced above: attitudinal acceptance is based on the opinion and emotion regarding the innovation, while behavioral acceptance is based on observable behavior such as actual system use (Sadvandi and Halkias, 2019). Attitudinal and behavioral acceptance related to transport (e.g. intelligent transport systems or automated driving) is for example differentiated in Ausserer and Risser (2005), Schmalfuß et al. (2017), Xu et al. (2018) or Sadvandi and Halkias (2019).

Another type of acceptance frequently mentioned in the literature is conditional acceptance. Conditional acceptance suggests that acceptance depends upon specific conditions or requirements. Ziefle et al. (2015) evaluate the conditional acceptance of electric mobility in public transport and find that safety and security issues are a precondition for acceptance. Conditional acceptance in context of transport can be found in Grisolía and López del Pino (2008) or Ziefle et al. (2015).

Similar to conditional acceptance, contextual acceptance refers to acceptance which depends on situational factors and the context (Adell et al., 2018). Saad (2004) states that situational context plays an important role to induce behavioral change. An example for contextual acceptance would be if multimodal freight transport is accepted for regular transport services, but not in the context of time-critical express deliveries.

The concept of a priori acceptance has already been explained above: it is the acceptance without any practical experience of the technology or system. Payre et al. (2014), Brookhuis et al. (2019) and Kaye et al. (2020) study the a priori acceptance of automated cars and driver assistance systems. The counterpart of a priori acceptance is a posteriori acceptance, which means acceptance after having tried a technology or system (Adell et al., 2018). Schmid and Graf (2016) suggest that a priori and a posteriori acceptance of a navigation display for aviation are diverging.

2.1.3 Defining Acceptance in Context of Sustainable Freight Transport

As illustrated in the preceding Subchapters 2.1.1 and 2.1.2, there are manifold ways to define and view acceptance. Common to all of the above described definitions is that the user (either potential or factual) of a system or technology makes a judgement about the system or technology. To specify how the concept of acceptance is understood in this thesis, a definition of acceptance in context of sustainable freight transport will be given now. Based on the considerations of different types of acceptance elaborated above, the following definition of acceptance is proposed for this thesis:

Acceptance is the extent to which an organization is willing to implement a sustainable freight transport strategy and, when available, to incorporate the strategy in the logistics companies’ transport operations.

This definition accounts for several key aspects of acceptance, which ensures that acceptance is a functional construct when developing and promoting sustainable transport strategies. First of all, the definition stresses a user-centric view, as logistics companies are the users of sustainable transport strategies, i.e. they are those players that realize sustainable freight transport. It is the logistics companies’ perception and understanding of sustainable transport strategies which is relevant for the implementation of these strategies, and not the actual effects that are bound up with the strategies (Schade and Baum, 2007). For example, if logistics companies do not perceive it beneficial to collaborate in a PI network, then the PI will fail, although it is proven by pilot studies (e.g. Sarraj et al., 2014) that there are benefits. It is also important to view the benefits from the logistics companies’ perspective, since the organizational perspective often deviates from the societal/political perspective (Adell et al., 2018). For example, organizations value profitability very high, while the societal/political perspective also emphasizes the ecological benefits.

By referring to “the extent of acceptance”, this definition acknowledges that the different stages of acceptance as described above exist. It thereby reflects the continuous nature of the construct acceptance. For a low-carbon freight transport system it is important that sustainable strategies are realized in practice, which emphasizes those stages of acceptance which are related to behavioral changes, namely intention to use and actual system use (Adell et al., 2018). Due to the fact that sustainable transport strategies can only bring positive effects when they are actually used, the definition focuses on the latter two acceptance stages (intention to use and actual system use). Xu et al. (2018) argue that the determinants of attitudinal acceptance are not necessarily the same as the determinants for actual use of a technology. Attitudinal acceptance does not materialize the actual uptake of an innovation and is therefore not targeted by the definition.

2.2 Definition and Classification of Policy Measures

Policy measures are instruments used by governmental authorities to effect or prevent a particular societal change (Vedung, 2010). In context of this thesis, the desired societal change is the implementation of sustainable transport strategies in the logistics industry. Policy measures to promote sustainable freight transport belong to the wide group of environmental policy instruments. Environmental policy instruments have been previously defined as “the set of techniques by which governmental authorities wield their power in attempting to affect society- in terms of values and beliefs, action and organization- in such a way as to improve, or to prevent the deterioration of, the quality of the natural environment” (Mickwitz, 2003, p. 419). This definition is useful to explain policy measures for sustainable freight transport. Hence, it can be substantiated that policy measures for sustainable freight transport aim to affect logistics companies in terms of values and beliefs, action and organization, such that the negative environmental impact of freight transport is mitigated.

A plethora of different policy measures exists, likewise there are a variety of classification schemes (Vedung, 2010). Essentially, policy measures can be classified according to the level of intervention, i.e. the degree of authoritative force they involve (Weber et al., 2014). Figure 2.2 shows that there is a difference between hard policy measures and soft policy measures. The former are mandatory and quite restrictive, as they force a specific behavior (high intervention level), while the latter are less restrictive and rely on voluntary behavioral change (low intervention level). Policy instrument theories typically refer to three main types of measures, namely regulation (“sticks”), economic incentives (“carrots”) and information instruments (“sermons”) (Bax, 2011).

Figure 2.2
figure 2

Classification of policy measures

Full size image

An alternative approach is to differentiate between technology push instruments and market-pull instruments (Vollenbroek, 2002; Horbach et al., 2012). Technology-push measures promote technological advancement, for example by research and development programs. Market-Pull measures aim to increase the demand for sustainable innovations, e.g. through awareness campaigns or eco-labelling (Al-Saleh and Mahroum, 2015). The technology-push and market-pull typology has, however, been criticized as both push and pull rely heavily on subsidization and are not necessarily sustainably efficient (Taylor, 2008). Hereafter, the popular typology of sticks, carrots and sermons (Figure 2.2) will be used to discuss the variety of potential policy measures. Each measure will be presented in detail in the following subsections.

2.2.1 Regulation (Sticks)

Regulations limit users’ opportunities to follow a specific behavior, e.g. by setting standards, technology controls, bans or permits or by introducing zoning and other input restrictions or output quotas (Mickwitz, 2003; Perman et al., 2003). Regulations may be derived from official legislative acts, such as directives, but they may be also derived from so-called “soft law” such as action plans, policy targets, guidelines and other policy documents (Bax, 2011). Regulation measures are mandatory by nature as they imply rules of conduct and prescribe a particular behavior. Thereby, they are also referred to as “command and control”. The advantage of regulations is that they allow governmental authorities to enforce the desired behavior by law, thus there is high confidence about the target groups’ compliance with the restrictions (Taylor et al., 2012). Monitoring and enforcing the compliance may however be costly and onerous, therefore regulations are typically part of a policy mix which includes other instruments as well (Simeonova and Diaz-Bone, 2005). Regulations often involve negative connotations, as they are associated with threats of unfavorable sanctions such as punishments, fines, etc. (Vedung, 2010). Despite that, setting regulations is quite a frequently used intervention option in many industrialized regions (Mickwitz, 2003).

2.2.2 Economic Incentives (Carrots)

Economic policy measures, also called monetary policy measures, are designed to promote the market uptake of a particular behavior. This may happen by influencing the money, time or effort that has to be spent to pursue this behavior (Vedung, 2010). Economic incentives make a particular behavior cheaper or more costly for the involved market players. A major difference compared to regulations is that the target group is not forced to adopt the desired behavior in the case of economic / monetary incentives. Instead, there is still the freedom to choose whether to change the behavior or not (Perman et al., 2003). For example, if governments offer subsidies for companies, the companies are not obliged to claim these subsidies, they can decide independently if the subsidy is worth changing a particular behavior or taking a particular action desired by the government. Monetary disincentives function in a similar manner (Vedung, 2010). For example, if governments raise a tax to prevent a particular behavior, they do not prohibit this behavior, they simply make the behavior more expensive and thus still leave the freedom to choose up to the market players. An alternative type of economic incentive is to create a market for environmental resources, e.g. through tradable emissions certificates or through the introduction of resource quotas (Opschoor, 1994).

Economic incentives are known to be more cost-effective than command and control measures, however it is less predictable whether economic incentives will suffice since it is uncertain whether the addressed target group will react to the market measures provided (Gunningham and Sinclair, 1999). Economic incentives can also have unintended side effects, for example distributional effects which negatively affect the poor or distortions pushing up prices (Taylor et al., 2012).

2.2.3 Information (Sermons)

Education and information measures aim for knowledge transfer to persuade target groups to change their behavior. They are therefore also called “suasive policy measures” (Mickwitz, 2003). Different means of communication are available to inform about current problems, possible solutions and actions required to tackle these problems, as well as reasoned arguments to convince the target group to adopt the desired behavior. Among the diverse set of communication options there are printed materials (flyers, booklets, brochures, etc.), training programs (courses, lecture series, information talks, etc.) or demonstration programs (Vedung, 2010). All these instruments are suitable to inform about recommended actions and behavior suggested to achieve a policy goal. Information measures also include instruments where the public authority authorizes private actors to distribute environmental information. This is the case with eco-labelling or environmental management systems, which are also suitable to convince market players of sustainable behavior (Mickwitz, 2003).

Similar to the economic incentives, no mandatory obligation results from education and information instruments- target groups still have the freedom to choose whether they follow the behavior advised according to the education measures (Vedung, 2010). A main difference compared to economic incentives is that no resources are given to or taken from the target groups to influence their behavior. Information and education measures are therefore relatively non-intrusive and non-coercive in nature (Gunningham and Sinclair, 1999) and constitute the least restrictive type of policy measures. At the same time, information measures are the instrument with the lowest reliability, because they are based on voluntariness and awareness of the target group (Taylor et al., 2012). Despite that, the use of information measures has recently gained popularity in Europe as it is regarded a contemporary way to elicit the desired behavior simply by allowing for an improved understanding of the consequences of the target groups’ actions (Bax, 2011).