Browsing by Author "Koliousis, Ioannis"
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Item Open Access An AHP enabled port selection multi-source decision support system and validation: insights from the ENIRISST project(Springer, 2023-05-18) Georgoulas, Dimitrios; Koliousis, Ioannis; Papadimitriou, StratosAnalytical Hierarchy Process (AHP) is a robust procedure for ranking options and supporting multi-criteria decision making that determine the port that a shipping operator will select, while designing the most cost-effective route. An important decision that may turn out to be decisive for a company’s survival. We developed an AHP based decision support system, as part of a wider Research and data Infrastructure system, that enables practitioners’ decision making based on their subjective experience and within realistic time constraints. We test the approach using two regional ports and the throughput results confirmed the initial expectations.Item Open Access AI based decision making: combining strategies to improve operational performance(Taylor and Francis, 2021-08-30) Al-Surmi, Abdulrahman; Bashiri, Mahdi; Koliousis, IoannisThis study investigates the strategic alignment between marketing and information technology (IT) strategies and provides production and operations decision makers a model for improving operational performance. Based on a comprehensive literature review, the combined strategies were used to develop a novel decision-making framework. The hypothesised relationships of an SEM model are validated with data collected from 242 managers from various industries. An artificial intelligence (AI)–based method is developed using artificial neural networks (ANN) feeding into a decision-making framework which explores the optimality of the combined strategies. The results indicate that (a) IT strategy is positively mediated by marketing strategy on performance and (b) the organisational structure moderates the mediation of marketing strategy on performance. The analysis confirms that the extracted strategies based on the proposed framework have superior performance compared to existing strategies. This paper contributes to the literature by conceptualising and empirically testing the mediation role of marketing strategy on IT strategy, performance and operational decision-making. The use of a novel three-phase decision-making framework which uses AI processes improves operational efficiency, increases insights and enhances the decision accuracy of complex problems at the strategic level in industries such as manufacturing. It could help operations executives to apply effective decisions.Item Open Access Blockchain agency theory(Elsevier, 2023-03-13) Onjewu, Adah-Kole Emmanuel; Walton, Nigel; Koliousis, IoannisLongstanding assumptions underlying strategic alliances, such as agency theory, are actively being revoked by dynamics in the new economy. The mechanism of inter-firm cooperation is increasingly being altered by radical developments in blockchains and artificial intelligence among other technologies. To capture and address this shift, this review takes a problematisation approach and focuses wholly on the pertinence of agency theory. First, it begins by acknowledging the established corpus in the area before, second, appraising the seven long-held assumptions in the principal-agent relationship encompassing (1) self-interest, (2) conflicting goals, (3) bounded rationality, (4) information asymmetry, (5) pre-eminence of efficiency, (6) risk aversion and (7) information as a commodity. Third, to add a fresh perspective, the review proceeds to proffer seven assumptions to advance a novel ‘Blockchain Agency Theory’ that would better describe new attributes and relaxed agency behaviour in blockchain alliances. These counter assumptions are (1) common interests, (2) congruent goals, (3) unbounded rationality, (4) information symmetry, (5) smart contracts, (6) mean risk and (7) information availability. In the fourth part, the prior audience of principals and agents is appraised and this culminates into, fifth, a consideration of a new audience of blockchain agency in algocratic environments. Altogether, the seven new assumptions extend and provoke new agency thinking among scholars and blockchain practitioners alike.Item Metadata only Can we increase the granularity in understanding global value chains: an integration of academic and practice perspectives to enhance future developments(Inderscience, 2023) Prataviera, Lorenzo Bruno; Bosio, Davide; Koliousis, IoannisValue chains are increasingly fragmented globally, and companies and governments struggle with understanding where value is added. Both scholars and practitioners developed models, but recent challenges are calling for original approaches to develop instruments to map and evaluate global value chains (GVCs) footprint. We carried out a Structured Literature Review (SLR) to summarize the existing academic knowledge about GVCs mapping and also examined the related practitioners’ materials. We then investigated what data sources are currently available to collect data about global trade flows, and involved practitioners in the discussion to collect insights that could improve the current understanding. We aim at offering guidance in this process, highlighting what future directions should be pursued to increase the models’ descriptive and explanatory power. For example, customs data is largely available. Original models could be developed, and GVCs could be studied leveraging rich and granular customs data rather than traditional macro-economic data.Item Open Access Critical analysis of the impact of big data analytics on supply chain operations(Taylor & Francis, 2022-05-16) Hasan, Ruaa; Kamal, Muhammad Mustafa; Daowd, Ahmad; Eldabi, Tillal; Koliousis, Ioannis; Papadopoulos, ThanosUndoubtedly, due to the increasingly competitive pressures and the stride of varying demands, volatility and disturbance have become the standard in today’s global markets. The spread of Covid-19 is a prime example of that. Supply chain managers are urged to rethink their competitive strategies to make use of Big Data Analytics (BDA), due to the increasing uncertainty in both demand and supply side, the competition among the supply chain partners and the need to identify ways to offer personalised products and services. With many supply chain executives recognising the need of ‘improving with data’, supply chain businesses need to equip themselves with sophisticated BDA methods/techniques to create valuable insights from big data, thus, enhancing the decision-making process and optimising the efficiency of Supply Chain Operations (SCO). This paper proposes the building blocks of a theoretical framework for understanding the impact of BDA on SCO. The framework is based on a Systematic Literature Review (SLR) on BDA and SCO, underpinned by Task-Technology-Fit theory and Institutional Theory. The paper contributes to the literature by building a platform for future work on investigating factors driving and inhibiting BDA impact on SCO.