Improving Performance by Encouraging Users to Consider Different Levels of Action Identification (LAI)

2023 | International Conference on Information Systems | Citations: 0

Authors: Tzur, Aviram; Te’Eni, Dov; Zalmanson, Lior

Abstract: Action Identification Theory proposes that individuals perceive their actions a ... Expand

Abstract: Action Identification Theory proposes that individuals perceive their actions at different levels of abstraction and how this perception can significantly impact their behavior. The paper argues that prompting users to shift between different levels of action identification during their interaction with an information system can improve their performance. The experimental work includes a laboratory experiment and a think-aloud study that explores the effect of users' attention to different levels of action identification and the cognitive fit between on-screen representation and mental models on performance improvement. The discussion analyzes the results and outlines future research plans and expected contributions to the field. This study highlights the importance of considering the user's cognitive processes when designing information systems and suggests potential ways to enhance their performance. Collapse

Topics: human computer interaction usability decision making problem solving

Methods: experimental group experiment cognitive walkthrough laboratory experiment statistical hypothesis test

Theories: cognitive fit theory

A constraint programming model for making recommendations in personal process management: A design science research approach

2022 | Decision Support Systems | Citations: 0

Authors: Oruç, Sercan; Eren, P. Erhan; Koçyiğit, Altan

Abstract: Decision-making in everyday life has an essential role in effectively completing ... Expand

Abstract: Decision-making in everyday life has an essential role in effectively completing personal tasks and processes. The complexity of these processes and the resulting cognitive load of managing them may vary significantly. To decrease the cognitive load created by such decision-making efforts and to obtain better outcomes, recom­ mendation systems carry significant potential. In order to investigate the benefits provided by decision support systems (DSS) in personal process management (PPM), we first build a constraint programming (CP) model and a prototype context-aware-mobile application employing this CP model. Then, we evaluate the application and the model via two exemplary real-world scenarios. The scenarios form the core of the experiments conducted with 50 participants. We compare the participants’ planning performances with and without the PPM system with quantitative metrics such as planning times and scenario objective values. In addition, System Usability Scale (SUS) questionnaires and open-ended questions provide qualitative evaluation results. Throughout the study, we apply the Design Science Research methodology to rigorously conduct research activities by proof of concept, proof of use, and proof of value. The empirical results clearly show that our proposed model for PPM is effective, and the developed prototype solution generates positive participant comments as well as a high SUS score. Overall, the prototype PPM system with CP implementation leads to better planning in less time in the planning phase, and it lets the user do fast replanning in the execution phase, which is invaluable in dynamically changing situations such as daily activities. Collapse

Topics: usability decision support system mobile application decision support mobile system

Methods: design artifact experiment survey personal interview reference modelling

Prescriptive analytics: Literature review and research challenges

2020 | International Journal of Information Management | Citations: 15

Authors: Lepenioti, Katerina; Bousdekis, Alexandros; Apostolou, Dimitris; Mentzas, Gregoris

Abstract: Business analytics aims to enable organizations to make quicker, better, and mor ... Expand

Abstract: Business analytics aims to enable organizations to make quicker, better, and more intelligent decisions with the aim to create business value. To date, the major focus in the academic and industrial realms is on descriptive and predictive analytics. Nevertheless, prescriptive analytics, which seeks to find the best course of action for the future, has been increasingly gathering the research interest. Prescriptive analytics is often considered as the next step towards increasing data analytics maturity and leading to optimized decision making ahead of time for business performance improvement. This paper investigates the existing literature pertaining to prescriptive analytics and prominent methods for its implementation, provides clarity on the research field of prescriptive analytics, synthesizes the literature review in order to identify the existing research challenges, and outlines directions for future research. Collapse

Topics: distributed computing artificial intelligence analytical information system business process management process mining

Methods: machine learning computational algorithm literature study optimization model literature sample

Constraint programming for flexible Service Function Chaining deployment

2019 | HICSS | Citations: 0

Authors: Liu, Tong; Callegati, Franco; Cerroni, Walter; Contoli, Chiara; Gabbrielli, Maurizio; Giallorenzo, Saverio

Abstract: Network Function Virtualization (NFV) and Software Defined Networking (SDN) are t ... Expand

Abstract: Network Function Virtualization (NFV) and Software Defined Networking (SDN) are technologies that recently acquired a great momentum thanks to their promise of being a flexible and cost-effective solution for replacing hardware-based, vendor-dependent network middleboxes with software appliances running on general purpose hardware in the cloud. Delivering end-to-end networking services across multiple NFV/SDN network domains by implementing the so-called Service Function Chain (SFC) i.e., a sequence of Virtual Network Functions (VNF) that composes the service, is a challenging task. Collapse

Topics: Google+ user satisfaction artificial intelligence programming language lean manufacturing

Methods: experiment constraint programming modeling language minimum spanning tree problem mixed-integer programming

Robust Platelet Logistics Planning in Disaster Relief Operations Under Uncertainty: a Coordinated Approach

2018 | Information Systems Frontiers | Citations: 4

Authors: Kamyabniya, Afshin; Lotfi, M. M.; Naderpour, Mohsen; Yih, Yuehwern

Abstract: Resource sharing, as a coordination mechanism, can mitigate disruptions in suppl ... Expand

Abstract: Resource sharing, as a coordination mechanism, can mitigate disruptions in supply and changes in demand. It is particularly crucial for platelets because they have a short lifespan and need to be transferred and allocated within a limited time to prevent waste or shortages. Thus, a coordinated model comprised of a mixed vertical-horizontal structure, for the logistics of platelets, is proposed for disaster relief operations in the response phase. The aim of this research is to reduce the wastage and shortage of platelets due to their critical role in wound healing. We present a bi-objective location-allocation robust possibilistic programming model for designing a two-layer coordinated organization strategy for multi-type blood-derived platelets under demand uncertainty. Computational results, derived using a heuristic ε-constraint algorithm, are reported and discussed to show the applicability of the proposed model. The experimental results indicate that surpluses and shortages in platelets remarkably declined following instigation of a coordinated disaster relief operation. Collapse

Topics: logistics management supply chain management earthquake natural hazard

Methods: computational algorithm sensitivity analysis optimization model constraint programming case study

A Product-Service System Configurator for Repurposing used Electric Vehicle Batteries

2018 | European Conference On Information Systems | Citations: 0

Authors: Voscort, Johannes; Monhof, Markus

Abstract: High initial costs are one of the major obstacles for the diffusion of electric ... Expand

Abstract: High initial costs are one of the major obstacles for the diffusion of electric vehicles (i.e., electric cars). The repurposing of used electric vehicle batteries (EVBs) is seen as a possibility to lower the total costs of ownership of the vehicles and therefore to foster electric car sales. However, the decision how to repurpose used EVBs requires severe information system (IS) support. In particular, in this article, the configuration task of providing used EVBs as product-service systems (PSSs), which would hardly be possible without IS support, is addressed. Collapse

Topics: usability user interface recommender system system support

Methods: design artifact constraint programming

An empirical study of Bayesian network parameter learning with monotonic influence constraints

2016 | Decision Support Systems | Citations: 0

Authors: Zhou, Yun; Fenton, Norman; Zhu, Cheng

Abstract: Learning the conditional probability table (CPT) parameters of Bayesian networks ... Expand

Abstract: Learning the conditional probability table (CPT) parameters of Bayesian networks (BNs) is a key challenge in real-world decision support applications, especially when there are limited data available. A conventional way to address this challenge is to introduce domain knowledge/expert judgments that are encoded as qualitative parameter constraints. In this paper we focus on a class of constraints which is naturally encoded in the edges of BNs with monotonic influences. Experimental results indicate that such monotonic influence constraints are widespread in practical BNs (all BNs used in the study contain such monotonic influences). To exploit expert knowledge about such constraints we have developed an improved constrained optimization algorithm, which achieves good parameter learning performance using these constraints, especially when data are limited. Specifically, this algorithm outperforms the previous state-of-the-art and is also robust to errors in labelling the monotonic influences. The method is applied to a real world medical decision support BN where we had access to expert-provided constraints and real hospital data. The results suggest that incorporating expert judgments about monotonic influence constraints can lead to more accurate BNs for decision support and risk analysis. Collapse

Topics: decision support earthquake Perl missing data

Methods: computational algorithm experiment simulation case study constraint programming

A schema aware ETL workflow generator

2014 | Information Systems Frontiers | Citations: 0

Authors: Du, Naiqiao; Ye, Xiaojun; Wang, Jianmin

Abstract: Extract, Transform and Load (ETL) processes organized as workflows play an impor ... Expand

Abstract: Extract, Transform and Load (ETL) processes organized as workflows play an important role in data warehousing. As ETL workflows are usually complex, various ETL facilities have been developed to address their control-flow process modeling and execution control. To evaluate the quality of ETL facilities, Synthetic ETL workflow test cases, consisting of control-flow and data-flow aspects are needed to check ETL facility functionalities at construction time and to validate the correctness and performance of ETL facilities at run time. Although there are some synthetic workflow and data set test case generation approaches existed in literatures, little work is done to consider both aspects at the same time specifically for ETL workflow generators. To address this issue, this paper proposes a schema aware ETL workflow generator with which users can characterize their ETL workflows by various parameters and get ETL workflow test cases with control-flow of ETL activities, complied schemas and associated recordsets. Our generator consists of three steps. First, with type and ratio of individual activities and their connection characteristic parameter specification, the generator will produce ETL activities and form ETL skeleton which determine how generated activities are cooperated with each other. Second, with schema transformation characteristic parameter specification, e.g. ranges of numbers of attributes, the generator will resolve attribute dependencies and refine input/output schemas with complied attributes and their data types. In the last step, recordsets are generated following cardinality specifications. ETL workflows in specific patterns are produced in the experiment in order to show the ability of our generator. Also experiments to generate thousands of ETL workflow test cases in seconds have been done to verify the usability of the generator. Collapse

Topics: extract transform load process database system user requirement structured query language usability

Methods: computational algorithm experiment integer programming design science literature study

A decision support system for sustainable energy supply combining multi-objective and multi-attribute analysis: An Australian case study

2014 | Decision Support Systems | Citations: 0

Authors: Mattiussi, Alessandro; Rosano, Michele; Simeoni, Patrizia

Abstract: A framework for an energy supply decision support system (DSS) for sustainable p ... Expand

Abstract: A framework for an energy supply decision support system (DSS) for sustainable plant design and production is presented in this paper, utilising an innovative use of multi-objective and multi-attribute decision-making (MODM, MADM) modelling together with impact assessment (IA) of the emission outputs. The mathematical model has been applied within an eco-industrial park (EIP) setting and includes three steps. First, an assessment of the total EIP emissions' inventory and impacts is conducted; the second step, focusing on the sustainability benefits of combined heating and power (CHP) plants and photovoltaic technologies, developed a multi-objective mathematical model including both economic and environmental objectives in a Pareto-frontier optimisation analysis. Four different scenarios involving combinations of CHP plants (internal combustion engine, gas turbine, micro-turbines and fuel cells) and two types of PV plant (monocrystalline and polycrystalline) were evaluated. The third step utilises a MADM methodology – the analytic hierarchy process (AHP) – for selecting the best alternative among the Pareto-frontier efficient solutions. This model has been applied to a case study of an EIP located in Perth (Kwinana Industrial Area—KIA), Western Australia. Collapse

Topics: decision support system decision making database system problem solving

Methods: simulation case study mathematical model qualitative interview computational algorithm

Multi-objective operating room scheduling considering desiderata of the surgical team

2013 | Decision Support Systems | Citations: 0

Authors: Meskens, Nadine; Duvivier, David; Hanset, Arnauld

Abstract: Optimizing the daily operating room schedule can be problematic because of the m ... Expand

Abstract: Optimizing the daily operating room schedule can be problematic because of the many constraints that need to be taken into account, and solving this issue within a reasonable time span is difficult. The originality of the present study is the consideration of the surgical team's wishes in the establishment of an operating room schedule. To resolve the operating room scheduling problem, we took advantage of the “expressive power” of the constraint programming paradigm to include multiple real-life constraints in our model, such as availability, staff preferences, and affinities among staff members. The aim of this research was to optimize use of the operating room by minimizing the makespan, minimizing overtime hours, and maximizing affinities among members of the surgical team. We developed a “generic” model that includes most of the problems encountered in the literature as well as constraints apparent in our hospital. The results achieved when using this model in a real-life situation are presented at the end of the paper. Collapse

Topics: human resource management Java database system Microsoft Windows operating system

Methods: experiment constraint programming field study