High Acceptance Multi Criteria Decision Making - HAM

Everything humans do is based on explicitly or implicitly made decisions. Therefore, the quality of decisions we make has a direct impact on our welfare. This fundamental insight led to the development of several decision support methodologies, which aim at helping decision makers in improving the quality of their decisions. While the theoretical benefits from applying these methodologies are promising, their application is not common within practice. This discrepancy between theory and practical acceptance is subject to the HAM project. The project`s overall goal is to develop a model which explains user acceptance of decision support systems (DSS) and to explore how user acceptance can be positively influenced. To be more concrete we believe that especially trust is a prerequisite for the acceptance of a DSS since there is no easy way for the user to check the accuracy of a proposition made by a DSS. To explore this hypothesis and other factors potentially influencing the acceptance of DSS, the Technology Acceptance Model supplemented with trust will form the theoretical basis to develop a Decision Support Acceptance Model (DSAM). This model will be used to evaluate several measures which we hypothesize are appropriate for building trust in and achieving acceptance of DSS. Within our preliminary work, we have already proposed some technology characteristics and methods potentially adequate for building trust in DSS. In summary, the HAM project is exploratory in nature, we focus on humans and their perception of DSS. Additionally, generalizability of the DSAM is a major goal of the project. Due to this, we don`t address any special industry or a special target group of decision makers. Therefore private funding of the HAM project isn`t possible yet, but we are planning follow-up projects together with private partners to develop practically useable decision support methodologies based on the knowledge gained through the HAM project. To achieve the project`s goal, we will follow a quantitative research approach. Experiments will be conducted to identify the variables determining the acceptance of DSS and to evaluate our proposed drivers for building trust in DSS. The HAM project is the first aiming at exploring the acceptance of DSS and at identifying measures increasing trust in and acceptance of DSS. This knowledge will be used to build new decision support methods which are based on sound mathematical and theoretical models on the one hand and which are intuitive, trustworthy and acceptable on the other hand. In short, we believe that the proposed project is highly innovative, due to the fact we are the first exploring approaches to improve and to support decision making while considering trust, the perception of technology and the human nature in general.

The project was set up to investigate the effects of trust to the adoption of decision support systems. Such systems are intended to support a manager in making difficult (e.g. strategic) decisions. This can be achieved by offering different services to the decision maker ranging from simple graphical representations to complex mathematical optimization models. Because of the inherent complexity of these models, such a decision support system is often perceived as a black box to the decision maker. This is an artefact whose inner working principles are unknown to the user. We showed that an amount of trust is required to adopt such a system, depending on the decision at hand and its associated risk. We also showed that trust can be distinguished into direct and indirect trust. While direct trust refers to information I know directly about the artefact at hand (like knowledge about the working principles), indirect trust only allows transitive conclusions (like: reputation about an artefact). These two dimensions can also be called knowledge based (direct) trust and heuristic-based (indirect) trust, respectively.We build a model taking account of these different kinds of trust and how they are influenced by the decision aid, the decision maker, the decision problem and the decision environment.As a result we showed the validity of the Model and showed that heuristic-based trust is more powerful in generating trust, but more complex to achieve whereas knowledge-based trust is in principle easier to gain but has also two major constraints. These are (i) feasibility: many decision support systems are closed systems therefore their inner working principles are not available and (ii) time: most managers do not have the time to study a decision support system in-depth.