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Conference Program


June 15 Wednesday

  • 8:30-9:15 – Registration
  • 9:15 – Richard Szanto & Ciara Heavin – Opening
  • 9:30 – M. N. Ravishankar – Keynote
  • 10:30 – Coffee break
  • 11:00 – 1st Session – Intuitive decision models (detailed program can be found below)

11:00 – Intuitive decision models

  • Agnes Wimmer, Zoltan Buzady, Anita Csesznak & Peter Szentesi (2022) Intuitive and analytical decision-making skills analysed through a flow developing serious game, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073863 

    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.

  • Gloria Phillips-Wren, Mary Daly & Frada Burstein (2022) Support for cognition in decision support systems: an exploratory historical review, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2070946

    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.

  • Andrej Bregar: Use of data analytics to build intuitive decision models – an approach to indirect derivation of criteria weights based on discordance related preferential information, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073639 

    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.

  • Richárd Szántó: Intuitive decision-making and firm performance, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2080796

    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.

  • 12:30 – Lunchbreak
  • 13:30 – 2nd Session – Decision support systems (detailed program can be found below)

13:30 – Decision support systems

  • Frederic Adam, Richard Harris, Eugene Dempsey, Deirdre Murray, Simon Woodworth, Paidi O Raghallaigh: Towards a blueprint for Decision Support in Connected Health: Scenarios in Maternal and Child health

    This paper explores the potential of connected health solutions to solve the problems currently facing healthcare systems around the world with a particular interest in their decision support capabilities. Leveraging three selected projects in which we have been involved in the area of maternal and child health, the paper proposes a blueprint for connected health decisions in a variety of settings, namely: home-based, community-based, ward-based scenarios as well as the specific scenario of low-income countries. This blueprint can be used to frame discussions on connected health solutions and discuss their decision support potential.
  • Stefan Daschner & Robert Obermaier (2022) Algorithm aversion? On the influence of advice accuracy on trust in algorithmic advice, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2070951

    There is empirical evidence that decision makers show negative behaviours towards algorithmic advice compared to human advice, termed as algorithm aversion. Taking a trust theoretical perspective, this study broadens the quite monolithic view on behaviour to its cognitive antecedent: cognitive trust, i.e. trusting beliefs and trusting intentions. We examine initial trust (cognitive trust and behaviour) as well as its development after performance feedback by conducting an online experiment that asked participants to forecast the expected demand for a product. Advice accuracy was manipulated by ± 5 % relative to the participant’s initial forecasting accuracy determined in a pre-test. Results show that initial behaviour towards algorithmic advice is not influenced by cognitive trust. Furthermore, the decision maker’s initial forecasting accuracy indicates a threshold between near-perfect and bad advice. When advice accuracy is at this threshold, we observe behavioural algorithm appreciation, particularly due to higher trusting integrity beliefs in algorithmic advice.
  • Zsombor Szádoczki & Szabolcs Duleba (2022) Distance-based aggregation in group AHP, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2070952

    The aggregation of evaluators’ preferences is a key problem in group decision making. We examine the recently proposed distance-based techniques and compare their efficiency to the traditional aggregation of individual preferences (AIP) methods in simulated Analytic Hierarchy Process (AHP) cases. We use the Kendall W statistic to measure the rank correlation among the individual priority vectors of the group and the common priority vector for the different aggregation approaches. Extensive simulations (altogether 88000 cases) show that both the Euclidean Distance-Based Aggregation Method (EDBAM) and the Aitchison Distance-Based Aggregation Method significantly outperform the traditional techniques in case of smaller and mid-sized priority vectors (at most six items to be compared). However, EDBAM outperform the AIP methods for all dimensions that is conventionally used in AHP, and its computation time is also low.
  • Peter Keenan & Ciara Heavin (2022) DSS research: a bibliometric analysis by gender, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2070953

    This research-in-progress article uses a bibliometric approach to explore the research landscape by the gender of publishing authors in the Decision Support Systems (DSS) field over 10 years, from 2011 to 2020. The Web of Science (WOS) provides a valuable information resource on academic disciplines as it contains both the articles published and the articles cited. This research presents information on the gender breakdown of authors publishing on the topic of DSS globally. We examined publication trends over time, considering the main categories and research areas by authors’ gender. As a result, some initial recommendations to guide future research efforts of both DSS academics and practitioners are provided.
  • 15:00 – Coffee break
  • 15:30 – 3rd Session – Applications and case studies (detailed program can be found below)

15:30 – Applications and case studies

  • Aonghus Sugrue (2022) Build it, and they will come…Or will they?, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073635

    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.

  • Anita Kolnhofer Derecskei, Gyöngyi Csongrádi: How do the framing effects, environmental factors and personal risk perceptions influence our decision about a hypothetical COVID-19 pill? 

    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.

  • Gail Birkbeck, Tadhg Nagle, David Sammon: Challenges in Research Data Management Practices: A Literature Analysis, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2074653

    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.

  • Máté Farkas-Kis: Decision Making in The Shadow of Mathematical Education, Journal of Decision Systems, DOI: 

    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.

  • 17:15 – Meet the editors

June 16 Thursday

  • 9:00 – Réka Vas – Keynote – How to Make Data Work for Higher Education? Is Higher Education Lagging Behind?
  • 10:00 – Coffee break
  • 10:30 – 1st Session – Decision making for a sustainable global society (detailed program can be found below)

10:30 – Decision making for a sustainable global society

  • Patrick Humphreys & Miguel Imas (2022) Decision support for social innovation enabling sustainable development, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073634

    This paper offers a unique and powerful bottom-up methodology for social innovation promoting and securing Sustainable development goals (SDG’s) in a wide variety of social innovation contexts founded on a bottom-up approach : it identifies four sustainable development enabling factors, (SDEFs) that make social innovation contributions to sustainability in all its forms. We Employ three level (micro, meso, macro) model of social Innovation. In the first four sections of the paper, we show how the SDEF’s constitute social innovation success factors at the micro level, underpinning in ancient history, the enduing success of the Silk Road network of trade and, in recent history we reveal their role underpinning entrepreneurial innovation clusters bottom up. Yje concluding section shows how social innovation achievements implementing the SDEFs at the micro level can inform successful expansion into new contexts via adaptation and exaptation at the meso level and top-down facilitation at the macro level.
  • Fergal Carton, Huanhuan Xiong, JB McCarthy: Digital factors supporting decision making in the financial well-being of social housing residents, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073638

    The failure of the financial services market to take into account the sustainability of their credit-oriented products for lower income citizens has resulted in high levels of financial exclusion in European countries. In addition, the increasing role of IT in banking and commerce reduces “friction”, thus potentially exacerbating the indebtedness of sections of the community who rely on that friction to limit impulsiveness in expenditure. The recent emergence of apps providing real-time decision support at the point of sale, opening up access to consumer credit through “buy-now, pay-later” apps, may nudge households further into unsecured debt. This paper draws on quantitative and qualitative research from social housing tenants in Ireland, exploring the relationship between digital access to financial resources and financial well-being. We find that using the mobile phone to check a bank balance is associated with decisions around financial commitments (not running out) and resilience (having savings, being able to withstand a shock). Using the internet to check a bank balance is correlated with not having financial difficulties. However, paying bills via mobile phone is correlated with not having money left over at the end of the month and not saving, suggesting an increasing impulsiveness in decision making. IT-enabled banking and commerce have positive and negative implications for day-to-day money management and expenditure decisions. We therefore suggest further multi-disciplinary research on the opportunities for information technology to inform policy and practice around prudent money management decision making for consumers.
  • Mária Farkas & Réka Matolay (2022) Decision support for corporate sustainability: systems and stakeholders, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073864

    Decision support systems for corporate environmental management and ecological sustainability are proliferating, this paper explores their directions in a multifaceted literature via an integrative literature review. Besides delineating the interrelated areas of decision support systems for sustainability, we study the role of internal stakeholders in their implementation. In our review, we examine a relatively mature field (Environmental Decision Support System, EDSS) and an emerging field (Green Information System, Green IS), and their potential interplays. The importance of stakeholder inclusion in general, and the participation of end-users in the design and implementation of decision support systems, in particular, are analysed in the EDSS literature. The Green IS has a prospective future in decision support with its capacity to capture corporate environmental performance. Green IS literature, however, has just recently identified the significance of employee participation: barriers and potentials to engage employees have already been identified but still to be explored.
  • Fandjio Yonzou Cédric Cabral, Mbiada Mbiada Patrick Joël, Pettang Nana Ursula Joyce Merveilles, Manjia Marcelline Blanche, Kouamou Georges Edouard & Pettang Chrispin (2022) Using AI as a support tool for bridging construction informal sector mechanisms to sustainable development requirements, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073859

    Over 85% of Cameroonians use building informal sector mechanisms which involve a disorganized and varied workforce, types and qualities of materials from various origins with unclear supply networks, supported by a wide range of funding sources. Although previous work enabled us to master these mechanisms, their complexity is accentuated by sustainable development requirements and sanitary measures. Sustainability concept deals with fields to respond to social, economic and environmental challenges but its operationality in building encounters many difficulties due to informal mechanisms complexity. Dealing with this environment recommend taking advantage of Building Information Modeling, especially the assets of artificial intelligence (AI) to get appropriate, rapid, and diversified assistance. In this paper, we propose a concept of intelligent building sites management combining knowledge base, information system capitalizing on previous best practices and achievements to organize several construction sites in real-time with all requirements including those of SD goals and covid-19.
  • 12:00 – Panel discussion – Decision making for a sustainable global society
  • 12:45 – Lunchbreak
  • 13:45 – Most innovative paper award
  • 14:00 – 2nd Session – Data-driven decision making (detailed program can be found below)

14:00 – Data-driven decision making

  • Arif Wibisono, David Sammon & Ciara Heavin (2022) Data availability issues: decisions as patterns of action, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2070945

    This research investigates how an organisational unit organises workaround-centric data activities (WCDA) to cope with data availability issues (in the context of their centralised and decentralised systems landscape). To unpack these often-invisible WCDA patterns of action, we present a field study of a Quality Assurance (QA) unit of an Indonesian sugar plantation company. We use open coding and a narrative network (NN) approach to complete our analysis. Our findings reveal that data availability issues produce three patterns of action: dual inspection, prudent control, and mindful handling. An organisation can build plausible pictures for governing data by better understanding these visualised patterns. Lastly, we discuss the pros and cons of these patterns of action in the context of data governance.
  • Nuria Mollá, Ciara Heavin & Alejandro Rabasa (2022) Data-driven decision making: new opportunities for DSS in data stream contexts, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2071404

    Traditionally, Decision Support Systems (DSS) data were stored statically and persistently in a database. Increasing volume and intensity of information and data streams create new opportunities and challenges for DSS experts, data scientists, and decision makers. Novel data stream contexts require that we move beyond static DSS modelling techniques to support data-driven decision-making. Implementing incremental and/or adaptive algorithms may help to solve some of the challenges arising from data streams. This research investigates the use of these algorithms to better understand how their performance compares with more traditional approaches. We show that an adaptive DSS engine has the potential to identify errors and improve the accuracy of the model. We briefly identify how this approach could be applied to unexpected highly uncertain decision scenarios. Future research considers new opportunities to pursue a multidisciplinary approach to adaptive DSS design, development, and implementation leveraging emerging machine learning techniques in tackling complex decision problems.
  • Arif Wibisono, David Sammon, Ciara Heavin: Opening the workaround black box: an organisational routines perspective, Journal of Decision Systems, DOI:

    Workarounds are adaptive processes occurring in a centralised system environment. As adaptations, they expose organisations to potential data issues, for example data availability, data accuracy, and data leak. Hence organisations need to manage workaround, one way to achieve this is to classify them. However, classifying workarounds is challenging because they are unique and situational. This study aims to develop a workaround classification by leveraging the theory of organisational routines. By adopting the theory’s ontology, we emphasise the duality of structure (ostensive) and agency (performative). Due to our need for parsimony, we construct a truth table to progress our assumptions around workarounds. Our analysis shapes the statement of two organisational routines infused definitions of a workaround. This definition facilitates a new workaround typology based on organisational routines. By opening the black box, we can leverage a novel approach to classifying workarounds. This classification provides researchers with alternate building blocks for further theory development in workarounds.
  • Michael Joseph Walsh, John McAvoy, David Sammon: Grounding Data Governance Motivations: A Review of the Literature, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073637

    The purpose of this review paper is to understand why organisations choose to implement data governance (DG) programmes. A better understanding of the motivations for DG implementation will facilitate in assessing the effectiveness of DG programmes. A search of the literature was performed and 628 publications were examined; of these 55 were deemed to be relevant to the research, and were selected for analysis and coding using a grounded theory approach. Our analysis found 131 organisational motivations for implementing DG, which were then grouped into 23 categories. We use the Khatri and Brown (2010) DG framework to organise these categories across the five decision domains. The motivations are predominantly associated with operations and technology. This presents a challenge for organisations implementing DG, where an over-focus on technology could lessen the business imperative, and DG needs to be much more than an operational plan for managing the data asset. DG requires a holistic approach to succeed and this suggests that all decision domains are considered adequately.
  • 15:15 – Coffee break
  • 15:45 – 3rd Session – Applications and case studies (detailed program can be found below)

15:45 – Applications and case studies

  • Stanislaw Drosio (2022) Development and evaluation of ontology for decision support in Polish crisis management system, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073858

    The article presents a summary of research and development process of Domain Ontology for Crisis Management (DO4CM). The main goal of this work is to make decisions more effective within the framework of standard procedures implemented by government and local administration in response to emerging crisis and discontinuities. Presented ontology has been validated and verified during exercises carried out by actual crisis management structures and in co-ordination with non-governmental organisations supporting the growth of Polish state strategic resilience.
  • Viktor Andonovikj, Pavle Boskoski, Bojan Evkoski, Tjaša Redek & Biljana Mileva Boshkoska (2022) Community analysis in Slovenian labour network 2010-2020, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2070944

    There is little evidence on the right approach on how to delineate the sub-networks in a labour market. The subject of research in this paper is computational influence identification of the labour force transitions between different professional occupations in the Slovenian labour network from 2010 to 2020. We use community detection algorithm to identify occupation groups and apply influence analysis on the Slovenian labour network from 2010 to 2020. This directly supports the decision-makers and employment services in identifying job opportunities for job-seekers based. The main conribution is using influence analysis to detect occupations and communities that had the most significant impact on the Slovenian labour market. The research is the first work to successfully apply community and influence analysis in the Slovenian labour network to the best of our knowledge. The paper carries several important implications, primarily highlighting the usage of existing data to increase employment levels.
  • Marcelline Blanche Manjia, Ursula Joyce Merveilles Nana​ Pettang, Pola Ouambo, Cédric Cabral Fandjio, F.H. Abanda & Chrispin Pettang (2022) Integration and impact of BIM in the rehabilitation of buildings in developing countries, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2074345

    Building Information Modelling (BIM) has been recommended as one of the paradigms to efficiently manage asset information especially for maintenance purposes. Although still emerging, BIM benefits in cost and time savings are already being reaped in developed countries, yet its applications in developing countries are scarce. This study investigates a BIM method used in the rehabilitation of buildings in Cameroon, an African country still in its infancy in BIM adoption and compares the approach to the conventional sequential approach of project delivery. The method was implemented on rehabilitation of buildings at the Douala seaport in Cameroon. The results obtained revealed savings of 22% and 31% on costs and time respectively. These findings serve as a hope to developing countries to embrace BIM in their projects. Given this study used buildings in the Douala seaport, it is recommended that future studies should examine BIM for other projects in Cameroon.
  • 17:00 – Walking tour to Castle of Buda
  • In the evening – Gala dinner at Manna Restaurant

In the evening – Gala dinner at Manna Restaurant

June 17 Friday morning

  • 9:00 – György Somogyi Keynote – Decision-making on the investment market – latest perspectives on helping private investors make decisions about their money
  • 10:00 – Coffee break
  • 10:30 – 1st Session – Digitization and digital transformation

10:30 – Digitization and digital transformation

  • Julia Caulfield & Ashish Kumar Jha (2022) Stadiums and Digitalization: An Exploratory Study of Digitalization in Sports Stadiums, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073629

    While we have seen many technological innovations in the way most sports are administered or played, stadium interaction had been largely unchanged till recently. However, with increasing technological intervention in stadiums, it is natural to ask questions on the initiatives that spectators prefer. This paper attempts to create a comprehensive study of such technological initiatives in modern stadiums across different sports. We have collected data from stadiums, categorised them and analysed spectator willingness to pay for these initiatives. We find that age and frequency of stadium visits are the most important characteristics that define the willingness of spectators to pay for high technology initiatives in stadiums. Our study is one of the few in the domain that presents both spectator and stadium side issues in enhancing digital initiatives in stadiums. It would enable future managers of stadiums to better plan and target right initiatives.
  • Patrick McCarthy, David Sammon, Ibrahim Alhassan: “Doing” digital transformation: Theorising the practitioner voice, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2074650

    The objective of this theory-building research is to explore the defining characteristics of “doing” Digital Transformation (DT) and present a holistic account of the practitioner practices that characterise “doing” DT. For the purposes of this research “doing” DT is defined as leveraging digital technologies to significantly alter an organisational design in order to enhance customer engagement. To fulfil this objective, we select 16 key informants (digital transformation leaders) based on their organisational perspective (Business or IT) and role (Strategic or Operational), which facilitates hearing 4 types of practitioner voices. Following an inductive open coding approach, 350 excerpts were coded, leading to the emergence of 95 concepts, which were further grouped into 14 categories. In this paper we focus our write-up on the 6 most frequently occurring categories that are shaped by all four key informant groups (practitioner voices). This paper is unique in providing a holistic categorisation of the defining characteristics of “doing” DT, while also providing 24 “Practitioner Priorities”. These “Practitioner Priorities” sharpens the focus of academia and practice, highlighting the “role of people”, “role of data” and “role of technology” when “doing” DT.
  • Naimah Alrasheedi, David Sammon, Stephen McCarthy: Understanding the Characteristics of Workforce Transformation in a Digital Transformation Context, Journal of Decision Systems, DOI: 10.1080/12460125.2022.2073636

    Current literature has increased our knowledge of particular aspects of Workforce Transformation (WT), yet we need a comprehensive picture of its characteristics within a Digital Transformation (DT) context. Therefore, the objective of this review paper is to present the defining characteristics of WT. We fulfil this objective through a systematic review of 70 empirical papers published in leading journals listed on the CABS Academic Journal Guide (between 2010 and 2022). Following an inductive open coding approach, we identified six characteristics of WT: (1) “Actors and Digital Competency”; (2) “Digital Culture”; (3) “Digitally Engaged Workspace”; (4) “Empowerment, Engagement, and Motivation”; (5) “Improvisation and Collaborative Visioning”; and (6) “Transformational Leadership and Governance”. Our review suggests that empirical research around WT has focused more on the characteristic most frequently linked to “Empowerment, Engagement, and Motivation” where “Actors and Digital Competency” and, “Improvisation and Collaborative Visioning” have received lesser attention. Based on these characteristics, we detail a future research agenda that proposes the need to examine the relationship between WT characteristics and DT outcomes.
  • 11:30 – IFIP W 8.3 business meeting / Closing remarks
  • 12:30 – Lunch

Keynote Speakers

György Somogyi

György studied international management at Corvinus University, Budapest and at the UCD Smurfit Graduate Business School in Dublin. He has a background in management consulting and banking, having spent 8 years as a strategic consultant. In 2020, he joined Dorsum as a senior innovation expert, and later that year became appointed Head of Business Competence Center, responsible for business advisory and pre-sales activities within Dorsum as well as developing new banking and asset management software solutions and digitalization related research.

M.N. Ravishankar

M.N. Ravishankar is Professor of Globalisation & Technology and Associate Dean (Research) at the School of Business and Economics, Loughborough University. He is currently involved in research projects that explore digital innovations and entrepreneurship, and their social and economic impacts. Ravi has published peer-reviewed articles on the management of digital innovations, social entrepreneurship, and global technology sourcing. His research has appeared in scholarly journals such as Information Systems Research, European Journal of Information Systems, Journal of Information Technology, Journal of Strategic Information Systems, Information Systems Journal and Journal of World Business. He is serving as Senior Editor at Information Systems Journal, Associate Editor at Information & Management, Associate Editor at International Journal of Information Management, and Editorial Board member at IEEE Transactions on Engineering Management and Management & Organization Review.

Réka Vas

Reka Vas is Vice Rector for Education and associate professor in Management Information Systems at Corvinus University of Budapest. She received her Master’s degree in Economics in 2002, and her PhD in Management and Organizational Sciences in 2008, at Corvinus University. Her research collaborations have appeared in Lecture Notes in Computer Science (2020, 2019), International Journal of Manpower (2018); IEEE Transactions on Emerging Topics in Computing (2016), International Journal of Mobile and Blended Learning (2012,2011).

In addition, Réka was involved in the EU-Funded Leonardo da Vinci Ontohr (www.ontohr.eu), Med-Assess (www.med-assess.eu), and Ontotech (www.ontotech.eu) projects. From 2013-2017 Réka served on the Board of Management and Supervisory Board of the FP7 Marie Curie Initial Training Network (ITN) Eduworks (http://www.eduworks-network.eu) a project aimed at the socio-economic and psychological dynamics of labour supply and demand matching processes at aggregated and disaggregated levels. Currently she is involved in machine learning projects with LEGO aimed at improving manufacturing processes. On the education side Réka coordinated the development of “Data Science in Business” bachelor program to be launched Fall 2023 and is currently responsible for the coordination of university wide project aimed at establishing quality standards and procedures of teaching excellence at Corvinus University of Budapest.

Committee Members

General Chair

Richárd Szántó, Corvinus University of Budapest

Strategic Planning Committee

  • Frederic Adam, University College Cork, Ireland
  • Frada Burstein, Monash University, Australia
  • Ciara Heavin, University College Cork, Ireland
  • Biljana Mileva Boshkoska, Jožef Stefan Institute, Slovenia 
  • Gloria Phillips-Wren, Loyola University Maryland, USA
  • Ana Respicio, Lisbon University, Portugal
  • Richárd Szántó, Corvinus University of Budapest (Incoming Chair)

Local Organizing Committee

Sándor Bozóki, Corvinus University of Budapest (Chair)

Doctoral Consortium

  • Frederic Adam, University College Cork, Ireland
  • Gloria Phillips-Wren, Loyola University Maryland, USA

Programme Chairs

  • Sándor Bozóki, Corvinus University of Budapest
  • Ciara Heavin, University College Cork, Ireland
  • Biljana Mileva Boshkoska, Jožef Stefan Institute, Slovenia
  • Richárd Szántó, Corvinus University of Budapest

Programme Committee

  • Frederic Adam, University College Cork, Ireland
  • Imad Bani-Hani, Linnaeus University, Sweden
  • Nina Begičević Ređep, University of Zagreb, Faculty of Organization and Informatics, Croatia
  • Marko Bohanec, Jožef Stefan Institute, Slovenia
  • Patrick Brézillon, University Pierre and Marie Curie, Paris, France
  • Alexander Brodsky, George Mason University, Virginia, USA
  • Frada Burstein, Monash University, Australia
  • Federico Cabitza, University of Milano-Bicocca, Italy
  • Bojan Cestnik, Temida, d.o.o., Ljubljana, Slovenia
  • Sven Carlsson, Lund University, Sweden
  • João Clímaco, University of Coimbra, Portugal
  • Csaba Csaki, Corvinus University of Budapest, Hungary
  • Vesna Čančer, University of Maribor, Faculty of Economics and Business, Maribor, Slovenia
  • Mary Daly, University College Cork, Ireland
  • Fatima Dargam, SimTech Simulation Technology, Austria
  • Marko Debeljak, Jožef Stefan Institute, Slovenia
  • Pavlos Delias, Eastern Macedonia and Thrace Institute of Technology, Polytechnion Kritis, Greece
  • Boris Delibašić, University of Belgrade, Faculty of Organizational Sciences, Serbia
  • Luís Dias, University of Coimbra, Portugal
  • Daniela Fogli, University of Brescia, Italy
  • Martin J. Geiger, Helmut Schmidt University, Germany
  • Ciara Heavin, University College Cork, Ireland
  • Patrick Humphreys, London School of Economics, UK
  • Miłosz Kadziński, Poznań University of Technology, Poland
  • Marc Kilgour, Wilfrid Laurier University, Canada
  • Mirjana Kljajić Borštner, University of Maribor, Faculty of Organisational Sciences, Slovenia
  • Vladimir Kuzmanovski, Jožef Stefan Institute, Slovenia
  • Isabelle Linden, University of Namur, Belgium
  • Shaofeng Liu, University of Plymouth, UK
  • Suzana Loshkovska, Ss. Cyril and Methodius University, Republic of Macedonia
  • Gjorgji Madjarov, Ss. Cyril and Methodius University, Republic of Macedonia
  • Biljana Mileva Boshkoska, Jožef Stefan Institute, Slovenia
  • Tadhg Nagle, University College Cork, Ireland
  • Daniel Edmund O’Leary, University of Southern Carolina, USA
  • Dijana Oreški, University of Zagreb, Faculty of Organization and Informatics, Croatia
  • Jason Papathanasiou, University of Macedonia, Greece
  • Tanja Pavleska, Jožef Stefan Institute, Slovenia
  • Chrispin Pettang, Ecole Polytechnique de Yaoundé, Cameroon
  • Gloria Phillips-Wren, Loyola University Maryland, USA
  • Vili Podgorelec, University of Maribor, Faculty of Electrical Engineering and Computer Science, Maribor, Slovenia
  • Jean-Charles Pomerol, University Pierre and Marie Curie, Paris, France
  • Vladislav Rajkovič, University of Maribor, Faculty of Organisational Sciences, Slovenia
  • Ana Respicio, Lisbon University, Portugal
  • Marko Robnik Šikonja, University of Ljubljana, Faculty of Computer and Information Science, Slovenia
  • Ricardo Rodriguez Ulloa, Instituto Andino de Sistemas, Lima, Peru
  • Elena Rokou, Creative Decisions Foundation, USA
  • David Sammon, University College Cork, Ireland
  • Roman Słowiński, Poznań University of Technology, Poland
  • Stanisław Stanek, General Tadeusz Kosciuszko Military University of Land Forces, Wrocław, Poland
  • Aneta Trajanov, Jožef Stefan Institute, Slovenia
  • Rudolf Vetschera, University of Vienna, Austria
  • Simon Woodworth, University College Cork, Ireland
  • Erica Yang, STFC Rutherford Appleton Lab, UK
  • Lidija Zadnik Stirn, University of Ljubljana, Biotechnical Faculty, Slovenia
  • Pascale Zaraté, Université Toulouse 1 Capitole, France
  • Martin Žnidaršič, Jožef Stefan Institute, Slovenia
  • Blaž Zupan, University of Ljubljana, Faculty of Computer and Information Science, Slovenia


  • Best Paper Award
  • Best Poster Presentation Award


Publication of the IFIP DSS 2022 Conference Proceedings (links available here following the conference):

  • Published as a supplement of the Journal of Decision Systems (Taylor & Francis)
  • Local proceedings of abstracts and posters
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GEN.:2024.07.15. - 05:16:28