Conference Program

Serious games are tools for measuring, evaluating, and developing leadership skills through the decisions taken by participants on leadership training. We analyse decision-making skills in relation to 29 leadership skills measured through FLIGBY, a Flow-developing serious game. Our empirical research explores the intuitive versus the analytical decision-making approaches’ connections to other leadership skills demonstrated by 734 leaders and managers: through a series of complex management decisions made in the game. Participants gain deeper insights into their skill sets, experience the immediate consequences of their decisions, and enhance their personal competitiveness by developing their leadership skills. The novelty of our research lies in analysing the relationship between Flow theory, leadership skills, and particularly decision-making skills. We highlight which leadership skills are most relevant to analytical and intuitive thinking skills. Our results show that both decision-making approaches could support the Flow-promoting leadership style, however intuitive thinking has a stronger relationship with it.

Decision support systems (DSS) have been traditionally developed to assist with unstructured and semi-structured problems. Early DSS researchers explored a broad range of techniques for supporting human cognition as part of decision making. Cognition during decision making was viewed in terms of two competing, and sometimes cooperating, systems: one that was automatic and fast, and one that was deliberative and slow. The aim of this research is to trace historical studies on cognitive aspects of decision support and determine the theoretical underpinnings of DSS support for cognition. We analysed articles drawing on the seminal literature to derive the relevant dimensions, including the classical Gorry & Scott Morton (1989) framework. This analysis identified opportunities for future research relevant to providing better support for cognition by highlighting some design parameters for information systems.

Data on past and current decisions can be utilised to enhance the decision-making process by automating decisions or making problem solving more intuitive. Data is either extracted from distributed sources and repositories, or obtained with the regression analysis from holistically assessed alternatives and human judgements. One of possible advanced approaches to encourage intuitive decision-making aims at inferring criteria weights of the decision model with regard to correlations between preferential parameters, in such a way that objective inner information on alternatives is consolidated with personal knowledge and experience. This is relevant because the task of specifying criteria weights is cognitively demanding and represents a key aspect of each decision model. The paper first discusses the notation and infrastructure to exchange decision models and handle preferential information underlying the mechanisms of indirect weight derivation. As the main contribution of the research, a method for the inference of criteria weights from veto-related information is proposed, with which selective strengths of veto degrees are calculated to compare the magnitudes of veto, while strengths of veto assessments are used to determine the influence of veto on the deterioration of rankings or categories into which alternatives are sorted, respectively. Strengths of non-compensatory veto criteria are then projected into compensatory weights. The experimental study reveals the characteristics of indirectly derived criteria weights and the influence of veto. Several quality factors are considered, such as the validity of weights, accuracy of results, richness of information and ability to discriminate conflicting alternatives. Weights are also compared to standard ROC and RS surrogate weights. The approach is generalised to both common decision-making problematics of ranking and sorting.

Instead of a comprehensive analysis, company executives often listen to their intuitions or rely on their past experience, hence, intuition does play a critical role in management. In a sample of 234 Hungarian companies, we looked at the relationship between the decision-making approaches used and corporate performance and attitudes toward change. It turned out that decision-making based on past experience and intuitions are generally associated with better business results and better operational performance based on cost-effectiveness. In addition, we have seen evidence that companies that are more prepared for change and have greater capacity to manage change more effectively use an intuitive decision-making approach than those that are less responsive.

In 2017, the European Journal of Information Systems (EJIS) published an article titled ‘Stimulating dialog between information systems research and practice’. The genesis of this piece centred on the need for IS research to make practicable research insights accessible to practitioners and to provide a means for practitioners to ‘hear and be heard’. The resulting IT artefact – Science2Practice (now rebranded as AIS InPractice (AIP)) – presented a forum for researchers to have their academic publications summarised and published in practitioner ready insights. Almost 5 years on, this research looks to explore how the initiative supports its primary mission of communicating research to, and associated dialog with, practitioners through adopting a primary data collection via a systems investigation of the AIP website. The findings reveal a somewhat underwhelming artefact with opportunities missed to engage practitioners. Future research opportunities that could reinvigorate the AIP initiative are discussed.

This study investigates the willingness to pay (WTP) for the real COVID-19 vaccine and the effects of losses and gains framing for a hypothetical COVID-19 pill. The way how a message concerning a risky situation is formulated will impact decisions. However, personal characteristics, like attitude to risk, also strongly impact this decision. In this study, risk attitudes are measured through the DOSPERT Scale. As many studies proved, the intention to be vaccinated is not just related to risk preferences, but also strongly influenced by socioemotional factors. The extent to which friends and relatives are vaccinated in our social circles as well as the concern for both others and for ourselves influence this decision. Using an online survey (n = 345), personal pricing and acceptance of both real and hypothetical COVID-19 medicines were studied. The results of the descriptive and inference statistics concerning how the message frame impacts pricing are ambiguous, but the significant effects of environmental and individual factors are confirmed.

Driven by funding and publishing requirements to open and reuse data, Research Data Management (RDM) has become a crucial part of a researcher’s role. However, this key task is often completed by researchers, who sometimes make decisions, without having the necessary support, skills, or know-how, resulting in very few research datasets being fit for reuse. The objective of this review is to identify the challenges in researcher RDM practices that impact the sharing/reusing of their research data. Within this review, the literature is analysed using a concept-centric matrix approach (c.f. Webster and Watson, 2002) which serves as a frame to organise emerging concepts and reveal patterns in the data. In total four thematic areas emerge from our coding of the selected literature, as follows: (i) alignment of research management and data management, (ii) resourcing, (iii) researcher openness; and (iv) research data governance. Despite the growing field of RDM in general, there is a limited understanding of RDM practices, most of which is anecdotal. This highlights a significant requirement for further investigation as well as practical tools (e.g. decision aids) and training to assuage clearly unmet needs. For instance, data management templates and guidance provided by funding bodies do not distinguish between the sequential stages of the research data lifecycle and specific issues relating to the governance of research data; an area where researcher skills can be deficient. Indeed, this provides a clear opportunity for the Information Systems (IS) community to better support researchers to implement good RDM practices.

There are several tools available to support management decisions. A significant proportion of them use quantified data to measure economic performance. To interpret these data, we need mathematical competencies, which we acquire during our studies, yet it is accompanied by a number of failures. Many people stick to the explanations of “I don’t have a math brain” and don’t think deeper into the reason for the failure. What is happening, why is our relationship with mathematics changing after the first contact in early ages? This research used statistical analysis based on the data of an online questionnaire to identify the factors behind the mathematical performance. Based on the results presented, the initial relationship is strong and successful. Later, this relationship deteriorates, and the process can be closely correlated with the educational successes achieved. The analysis of the pattern, this has been the same for generations, it can be stated that it is inherited. How can this be changed? How can we preserve initial success and put math at the service of developing problem-solving and decision-making skills? Many people understand the function of mathematics, that it teaches them to think, which is important for decision-making. However, as studies become more complex, we are still moving away from it, even though the importance of mathematics is not being questioned.