Artificial intelligence for decision-making and the future of work

2023 | International Journal of Information Management | Citations: 0

Authors: Dennehy, Denis; Griva, Anastasia; Pouloudi, Nancy; Mäntymäki, Matti; Pappas, Ilias

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Topics: artificial intelligence human computer interaction human in the loop data governance data quality

Methods: chatbot case study theory development analytic hierarchy process trade-off analysis method

Theories: institutional theory

"YOU CAN'T ALWAYS GET WHAT YOU WANT": EXAMINING EMPLOYEES' PREFERENCES AND JOB SATISFACTION IN AGILE TRANSFORMATIONS

2023 | European Conference On Information Systems | Citations: 0

Authors: Fischer, Mareike; Heinz, Matthias; Schlereth, Christian; Rosenkranz, Christoph

Abstract: Agile transformations cause fundamental changes to work designs. To better unde ... Expand

Abstract: Agile transformations cause fundamental changes to work designs. To better understand resistance to transformations, we shed light on employee preferences and the consequences of team and work organization changes for job satisfaction. Using the stated preference method "pairwise comparisonbased preference measurement", we examine our hypothesis on job satisfaction in agile vs. traditional team and work organization. Furthermore, we relate job satisfaction to the gap between perceived and preferred forms of such organizations. In summary, we identified team organization as the most important dimension in agile transformations. For requirements engineering, the distance between employee preferences and the perceived status quo was particularly large. Further, we found evidence that a larger distance between team and work organization preferences and perceptions negatively influenced job satisfaction. Collapse

Topics: job satisfaction marketing management IT personell turnover business model new product development

Methods: survey statistical hypothesis test linear regression analysis conjoint analysis Student's t-test

An Assessment of the Barriers Impacting Responsible Artificial Intelligence

2023 | Information Systems Frontiers | Citations: 0

Authors: Merhi, Mohammad I.

Abstract: Responsible Artificial Intelligence (AI) has recently gained a lot of attention, ... Expand

Abstract: Responsible Artificial Intelligence (AI) has recently gained a lot of attention, especially in the last few years. Scholars have conducted systematic literature reviews to gain more knowledge about responsible AI. However, no study has collected and evaluated the most significant barriers to responsible AI. We filled this gap in the literature by identifying eleven barriers and categorized them, using the Technology-Organization-Environment framework, into three categories. We collected data from seven experts and used the analytical hierarchy process to evaluate the importance of the barriers. The results indicated that technology, as a category, is the most important. The findings also recommended that data quality is the most vital among all eleven barriers. We offered eleven propositions as a theoretical contribution for future researchers in terms of conceptual development. We discussed the implications of the findings for research and practice. Collapse

Topics: responsible artificial intelligence data quality artificial intelligence systems implementation organizational context

Methods: analytic hierarchy process trade-off analysis method literature study structured literature research theoretical contribution

Theories: theory of everything technology organization environment framework

An evaluation of the critical success factors impacting artificial intelligence implementation

2023 | International Journal of Information Management | Citations: 0

Authors: Merhi, Mohammad I.

Abstract: AI systems offer organizations great benefits causing decision-makers to invest ... Expand

Abstract: AI systems offer organizations great benefits causing decision-makers to invest more in these systems. The ad­ vantages of AI cannot be achieved without successful implementation. Thus, it is crucial to recognize the factors impacting the successful implementation of AI. It is also important to assess and rank these factors by their importance to assist decision-makers in implementing these systems and increasing the success rate. Due to its importance, scholars called for studies to expand our knowledge in this critical area. This paper identifies, ex­ tracts, and assesses the most critical factors that influence the implementation of AI systems. This study identifies nineteen factors and categorizes them into four categories: organization, technology, process, and environment. The analytical hierarchy process is used to evaluate the factors and the categories. The analysis offers two types of results, at the category level and the level of the factors. The results indicate that technology is the most significant of the four categories. The results also suggest that ethics is the most crucial factor among all nineteen factors. The order of all factors and discussions of the implications of the findings for practice and research are presented in the paper. Collapse

Topics: artificial intelligence top management support critical success factor organizational culture systems implementation

Methods: trade-off analysis method analytic hierarchy process

Applying the AHP to Conflict Resolution: A Russia—NATO Case Study

2023 | Group Decision and Negotiation | Citations: 0

Authors: Minutolo, Marcel C.; Vargas, Luis G.; Guiora, Amos N.; Ray, Madhury

Abstract: In this paper, we apply the Analytic Hierarchy Process approach to conflict reso ... Expand

Abstract: In this paper, we apply the Analytic Hierarchy Process approach to conflict resolution in the context of the Russia–Ukraine conflict. We build models that illustrate the evaluation criteria, strategic and sub-criteria, and concessions for each party in this negotiation. Ratings are used to evaluate the degree to which concessions contribute or take away from successful resolution of the conflict. Afterwards, gain ratios are built to determine the benefit-cost scores so that concessions may be traded that result in equitable solutions. The approach presented here demonstrates for the first time why all concessions that parties to a conflict may offer might not trade all at once. A Max–Min optimization approach is used to maximize the gain to both parties of the conflict while minimizing the disparity in gain between the two. Collapse

Topics: evaluation criteria

Methods: trade-off analysis method analytic hierarchy process multiple criteria decision making sensitivity analysis linear optimization

Theories: theory of economic growth

A Combined Weighting Based Large Scale Group Decision Making Framework for MOOC Group Recommendation

2023 | Group Decision and Negotiation | Citations: 0

Authors: Zhang, Chonghui; Su, Weihua; Chen, Sichao; Zeng, Shouzhen; Liao, Huchang

Abstract: Massive open online courses (MOOC) are free learning courses based on online pla ... Expand

Abstract: Massive open online courses (MOOC) are free learning courses based on online platforms for higher education, which not only promote the open sharing of learning resources, but also lead to serious information overload. However, there are many courses on MOOCs, and it can be difficult for users to choose courses that match their individual or group preferences. Therefore, a combined weighting based large-scale group decision-making approach is proposed to implement MOOC group recommendations. First, based on the MOOC operation mode, we decompose the course content into three stages, namely pre-class, in-class, and post-class, and then the curriculum-arrangement-movement- performance evaluation framework is constructed. Second, the probabilistic linguistic criteria importance through intercriteria correlation method is employed to obtain the objective weighting of the criterion. Meanwhile, the word embedding model is utilized to vectorize online reviews, and the subjective weighting of the criteria are acquired by calculating the text similarity. The combined weighting then can be obtained by fusing the subjective and objective weighting. Based on this, the PL-MULTIMIIRA approach and Borda rule is employed to rank the alternatives for group recommendation, and an easy-to-use formula for group satisfaction is proposed to evaluate the effect of the proposed method. Furthermore, a case study is conducted to group recommendations for statistical MOOCs. Finally, the robustness and effectiveness of the proposed approach were verified through sensitivity analysis as well as comparative analysis. Collapse

Topics: online review online learning system user-generated content decision making recommender system

Methods: descriptive statistic GloVe cluster analysis trade-off analysis method computational algorithm

Proper and improper uses of MCDA methods in energy systems analysis

2022 | Decision Support Systems | Citations: 0

Authors: Cinelli, Marco; Burgherr, Peter; Kadziński, Miłosz; Słowiński, Roman

Abstract: Over the past few decades, the strategies to perform energy systems analysis hav ... Expand

Abstract: Over the past few decades, the strategies to perform energy systems analysis have evolved into multiple criteriabased frameworks. However, there still remains a lack of guidance on how to select the most suitable Multiple Criteria Decision Analysis (MCDA) method. These methods provide different decision recommendations for the Decision Makers, including ranking, sorting, choice, and clustering of the alternatives (e.g., technologies or scenarios) under evaluation. They deal with a variety of data typologies and preferences, and lead Decision Makers in shaping the energy systems of the future. Here, we evaluate the MCDA methods used in 56 case studies performing energy systems analysis at different scales. We find that close to 60% of these studies chose an MCDA method that was not the most adequate for the respective decision problem. In particular, this concerned the use of weighting methods (e.g., Analytical Hierarchy Process) in MCDA approaches not suited for this type of weights, sub-optimal selection of MCDA techniques for specific types of problem statements, and lack of handling rather evident interactions in preference models. Our analysis demonstrates that these deficiencies can be overcome by using a recently developed methodology and software that support Decision Makers and analysts in selecting the most suitable MCDA method for a given type of decision-making problem. Collapse

Topics: decision making decision support system systems analysis database system energy information system

Methods: case study survey design trade-off analysis method analytic hierarchy process literature study

Blockchain-Based Supply Chain Management: Understanding the Determinants of Adoption in the Context of Organizations

2022 | Information Systems Management | Citations: 0

Authors: Gökalp, Ebru; Gökalp, Mert Onuralp; Çoban, Selin

Abstract: This study investigates the importance of the determinants affecting the adoptio ... Expand

Abstract: This study investigates the importance of the determinants affecting the adoption and usage of blockchain-based SCM systems in the context of organizations. Hence, an SLR method was followed to uncover critical determinants in the literature. Then, a research model, including 14 key determinants, was developed based on the TOE Framework. Subsequently, the AHP method was applied to rank the adoption determinants. The findings reveal that environment-related determinants are more critical than technology-related or organization-related determinants. Collapse

Topics: blockchain supply chain management system supply chain management database system top management support

Methods: trade-off analysis method analytic hierarchy process sensitivity analysis survey structured literature research

Theories: theory of everything technology acceptance theory

An interactive decision support system for real-time ambulance relocation with priority guidelines

2022 | Decision Support Systems | Citations: 0

Authors: Hajiali, Mahdi; Teimoury, Ebrahim; Rabiee, Meysam; Delen, Dursun

Abstract: Changes in demand patterns and unexpected events are the two primary sources of ... Expand

Abstract: Changes in demand patterns and unexpected events are the two primary sources of delays in healthcare emer­ gency operations. To mitigate such delays, researchers proposed the movement of idle ambulances between emergency bases as one of the effective ways to improve the areal coverage of future demands. In this study, we have developed a model-driven decision support system that simultaneously seeks to maximize demand coverage while minimizing travel time by optimally relocating emergency response vehicles. The developed mathematical model partitions and prioritizes demand into four categories and continuously updates them over time. Furthermore, it dynamically calculates the number of coverages in different regions based on the current location of idle ambulances. Also, we developed a real-time risk assessment DSS for recommended relocations, which could be utilized as a reference by the EMS user while implementing suggested relocation decisions. A real case study is used to validate the proposed DSS, and its final output is compared to the existing operational policy. The findings show that the average workload added to each ambulance due to relocations has significantly improved the response time and coverage ratio. Compared to the existing operational policy, the developed decision support system decreased the time to respond to calls, which was deemed to be more than to offsets the increase in travel time due to relocation. Furthermore, the system also reduced the total working time of all ambulances by about 9% per shift. Collapse

Topics: decision support system user interface usability laptop computer programming language

Methods: mathematical model case study trade-off analysis method analytic hierarchy process simulation

Exploring Design Requirements of Fleet Telematics Systems Supporting Road Freight Transportation: A Digital Service Side Perspective

2022 | International Conference on Business Informatics | Citations: 0

Authors: Heinbach, Christoph; Kammler, Friedemann; Thomas, Oliver

Abstract: Road freight operators (RFOs) optimize their fleet management processes using fl ... Expand

Abstract: Road freight operators (RFOs) optimize their fleet management processes using fleet telematics systems (FTSs). Therefore, the selection of FTSs by RFOs is driven by transport specifications from the customer side leading to substantial search costs. However, FTSs vary significantly in their design requirements to assist road freight operations. Hence, we analyze 74 web pages from FTSs of existing telematics vendors to elicit 31 design requirements (DRs) which we aggregated into nine requirement sets (RSs). Subsequently, 42 practitioners from five digital road freight service enterprises experienced in using FTSs validate the DRs and evaluate their importance with RSs following the Analytical Hierarchy Process (AHP) method. The results reveal that DRs and RSs promoting driver monitoring and IT integration are perceived more important than items promoting fleet and logistics support. Our contribution sheds light on an emerging topic in logistics and establishes a knowledge base that guides the design of future FTSs. Collapse

Topics: knowledge base web page logistics management system integration anonymity

Methods: survey trade-off analysis method design requirement analytic hierarchy process descriptive statistic