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A structured method for smart city project selection
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2021 | International Journal of Information Management | Citations: 2
Authors: Wu, Yenchun Jim; Chen, Jeng-Chung

Abstract: The concept of a smart city, based on advanced information and communications te ... Expand

Abstract: The concept of a smart city, based on advanced information and communications technology (ICT), emerged to mitigate the impact of rapid urbanization and was considered feasible. However, the selection of technology and policy for providing better services to citizens and ensuring sustainable development is a multiple-objective decision process that is usually performed by experts in relevant domains. The major goal of this study is to propose a structural method for policy selection, which consists of three phases. In the first phase, the modified Delphi method is used to determine the elements of the decision by surveying panel members for their opinions. In the second phase, an analytic hierarchy process is used to ascertain the priority of each alternative according to the goal of the decision. In the third phase, zero-one goal programming models are developed to select a feasible portfolio based on the political goal and the annual budget. We conducted an empirical study to demonstrate and validate that the proposed model can induce the municipality to consider citizens’ requirements, identify the strengths and weaknesses of proposed policies, and select a feasible project portfolio in response to public expectations. In addition, the study found that a feasible portfolio, including consideration of citizens, business, and the environment, enables the public perceptions of government performance within the resource constraints of the organization. Collapse

Semantic filters: goal programming

Topics: smart city evaluation criteria information management decision making database system

Methods: survey trade-off analysis method analytic hierarchy process case study delphi study
Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities
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2021 | International Journal of Information Management | Citations: 0
Authors: Zekić-Sušac, Marijana; Mitrović, Saša; Has, Adela

Abstract: Energy efficiency of public sector is an important issue in the context of smart ... Expand

Abstract: Energy efficiency of public sector is an important issue in the context of smart cities due to the fact that buildings are the largest energy consumers, especially public buildings such as educational, health, government and other public institutions that have a large usage frequency. However, recent developments of machine learning within Big Data environment have not been exploited enough in this domain. This paper aims to answer the question of how to incorporate Big Data platform and machine learning into an intelligent system for managing energy efficiency of public sector as a substantial part of the smart city concept. Deep neural networks, Rpart regression tree and Random forest with variable reduction procedures were used to create prediction models of specific energy consumption of Croatian public sector buildings. The most accurate model was produced by Random forest method, and a comparison of important predictors extracted by all three methods has been conducted. The models could be implemented in the suggested intelligent system named MERIDA which integrates Big Data collection and predictive models of energy consumption for each energy source in public buildings, and enables their synergy into a managing platform for improving energy efficiency of the public sector within Big Data environment. The paper also discusses technological requirements for developing such a platform that could be used by public administration to plan reconstruction measures of public buildings, to reduce energy consumption and cost, as well as to connect such smart public buildings as part of smart cities. Such digital transformation of energy management can increase energy efficiency of public administration, its higher quality of service and healthier environment. Collapse

Semantic filters: goal programming

Topics: internet of things smart city mobile system decision making big data

Methods: machine learning machine learning method random forest classification decision tree classification computational algorithm
Project Staff Scheduling with Theory of Coalition
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2019 | Group Decision and Negotiation | Citations: 0
Authors: Arık, Oğuzhan Ahmet; Köse, Erkan; Forrest, Jeffrey Yi-Lin

Abstract: Project scheduling has been still one of the hottest topics in the management ar ... Expand

Abstract: Project scheduling has been still one of the hottest topics in the management area. The goal of traditional project management is to complete the project at the earliest possible time in accordance with the available resources without violating priority relations of the activities involved. Unlike traditional project management, this study deals with the possibility of a coalition among the staff available to accomplish tasks of the project. The tasks can be fulfilled by more than one staff members. Staff’s coalition shortens the completion time of the tasks. A natural problem that arises in this case is how to share the income generated. The other side of the problem is concerned with the project owner who wants the project to be completed as early as possible. In this study, a mathematical model proposal is dealt with in order to realize the goals of both the project owner and the staffs as much as possible within the complex structure of the situation. Collapse

Semantic filters: goal programming

Topics: shapley additive explanation IT project IT development project research and development

Methods: trade-off analysis method goal programming mathematical model optimization model
MAKE THE BEST OUT OF WHAT YOU HAVE – A LITERATURE REVIEW ON PROCESS PRIORITIZATION

2019 | European Conference On Information Systems | Citations: 0
Authors: Fischer, Marcus; Fuchs, Kevin

Abstract: As digitalization alters industries and societies sustainably, companies increa ... Expand

Abstract: As digitalization alters industries and societies sustainably, companies increasingly rely on optimized processes. Determined and separated by their strategies, companies consist of various key and support processes that differ in regard to characteristics such as importance, dysfunctionality, and feasibility. Because companies face limited organizational resources, they must consider these characteristics as well as strategical implications when prioritizing processes for improvement. Business Process Management (BPM) is a means to improve agility, responsiveness, and quality. Most BPM concepts view process prioritization as implicit and hardly provide explanations about the conditions, strategies, and consequences pertaining to the phenomenon. This article conducts a systematic literature review to determine the current state of research on process prioritization and sketches out avenues for future research. Our results suggest that the current body of literature focuses primarily on methods for process prioritization, while lacking ample answers to the questions of why, when, and with what consequences. Consequently, future research must develop theories and explanations as a foundation for more holistic concepts and generalizable implications. Collapse

Semantic filters: goal programming

Topics: database system decision making critical success factor organizational value system support

Methods: literature study structured literature research synthesis qualitative content analysis trade-off analysis method
Spatial modelling of climate change in Irish forestry

2017 | Americas Conference on Information Systems | Citations: 1
Authors: Keenan, Peter; Carroll, Paula; Conway, Henry; Lee, Stephen

Abstract: Climate change is a growing concern in the Forestry Industry. Trees are adapted ... Expand

Abstract: Climate change is a growing concern in the Forestry Industry. Trees are adapted to growing in certain conditions and changes in these conditions can lead to changes in productivity. Coillte, Ireland’s national forestry company, have data that shows the productivity at different locations of various tree species under different climatic scenarios. In this study, we attempt to incorporate this spatial data into Coillte’s strategic planning system. Our approach integrates GIS data with recursive linear programming (LP) and involves creating decision variables that reflected the composition of a forest. This approach allows us to reflect the changing growth rates of tree species in the LP model, where the model aims to maximise the Net Present Value (NPV) of the forest over a planning horizon. The goal of the study is to compare varying values of NPV under different climate change scenarios. Collapse

Semantic filters: goal programming

Topics: climate change business model strategic management

Methods: linear optimization design artifact goal programming trade-off analysis method experiment
Prioritization and Aggregation of Intuitionistic Preference Relations: A Multiplicative-Transitivity-Based Transformation from Intuitionistic Judgment Data to Priority Weights
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2017 | Group Decision and Negotiation | Citations: 0
Authors: Zhang, Yibin; Li, Kevin W.; Wang, Zhou-Jing

Abstract: This article proposes a goal programming framework for deriving intuitionistic f ... Expand

Abstract: This article proposes a goal programming framework for deriving intuitionistic fuzzy weights from intuitionistic preference relations (IPRs). A new multiplicative transitivity is put forward to define consistent IPRs. By analyzing the relationship between intuitionistic fuzzy weights and multiplicative consistency, a transformation formula is introduced to convert normalized intuitionistic fuzzy weights into multiplicative consistent IPRs. By minimizing the absolute deviation between the original judgment and the converted multiplicative consistent IPR, two linear goal programming models are developed to obtain intuitionistic fuzzy weights from IPRs for both individual and group decisions. In the context of multicriteria decision making with a hierarchical structure, a linear program is established to obtain a unified criterion weight vector, which is then used to aggregate local intuitionistic fuzzy weights into global priority weights for final alternative ranking. Two numerical examples are furnished to show the validity and applicability of the proposed models. Collapse

Semantic filters: goal programming

Topics: supply chain management

Methods: trade-off analysis method goal programming cross sectional research computational algorithm optimization model
Organizational implications of a comprehensive approach for cloud-storage sourcing
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2017 | Information Systems Frontiers | Citations: 0
Authors: Krishnaswamy, Venkataraghavan; Sundarraj, R. P.

Abstract: Cloud-computing facilitates consumers to source online storage-services on a pay ... Expand

Abstract: Cloud-computing facilitates consumers to source online storage-services on a pay-as-you-go basis. The sourcing of storage-as-a-service (STaaS) requires a decision maker to contend with several elements such as pricing structure, application characteristics and quality-of-service requirements, in addition to tactical considerations such as risk propensity and supplier diversification. This makes STaaS sourcing a complex task. Discussion on STaaS sourcing models addressing these aspects and their utility to decision-makers is, however, scant. In this paper, we propose a two-stage holistic approach based on Data Envelopment Analysis (DEA) and Goal programming (GP). We derive insights provided by these models from 10800 runs using market-based data. We also use an experiment to assess our hypothesis concerning the impact of task complexity on decision-quality. Both these experiments have implications for different business scenarios in the STaaS market, and for decision-making. We discuss these managerial implications, and present a prototype Decision Support System (DSS) to aid STaaS selection. Collapse

Semantic filters: goal programming

Topics: decision support system decision making price management IS sourcing website

Methods: experiment design artifact trade-off analysis method experimental design data envelopment analysis
Deriving Weights from Interval Multiplicative Preference Relations in Group Decision Making
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2014 | Group Decision and Negotiation | Citations: 0
Authors: Xu, Zeshui; Cai, Xiaoqiang

Abstract: In this article, we investigate group decision making problems with interval mul ... Expand

Abstract: In this article, we investigate group decision making problems with interval multiplicative preference relations (including complete interval multiplicative preference relations and incomplete interval multiplicative preference relations). On the basis of the number of judgments and the consistency degree of each interval multiplicative preference relation, we first give a combined weighting method to derive the weights of decision makers. Then, we establish two linear programming models to derive the weight intervals of alternatives from all individual consistent interval multiplicative preference relations and utilize the continuous ordered weighted averaging operator or the continuous ordered weighted geometric operator to aggregate all the values in each weight interval. In addition, we establish a more general model to check the consistency of all individual interval multiplicative preference relations. In the cases where the optimal objective value of the model is not zero, we can get the optimal weights of alternatives directly, and then utilize these optimal weights and the optimal deviation values derived from the model to construct consistent interval multiplicative preference relations. Furthermore, we discuss some special cases of the established models and illustrate our models with a practical example. Collapse

Semantic filters: goal programming

Topics: decision making internet technology

Methods: linear optimization goal programming trade-off analysis method optimization model
A decision support system for procurement risk management in the presence of spot market
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2013 | Decision Support Systems | Citations: 4
Authors: Hong, Zhen; Lee, CKM

Abstract: In the presence of spot market, this paper presents a decision support system to ... Expand

Abstract: In the presence of spot market, this paper presents a decision support system to model risks for procurement processes and to design a robust purchasing plan, including supplier selection and order allocation. Taking advantages of contract supplier and spot market, the buyer can better meet business requirements in this dynamic business environment. However, there are limitations of existing methods for modeling multiple correlated risks to support decision makers for allocating orders among multiple suppliers in the presence of spot market. Therefore, Monte Carlo simulation algorithm termed as Expected Profit–Supply at Risk (A-EPSaR) is proposed to quantify each supplier's risk so as to let decision maker realize the trade-off between profit and risk. The goal programming model helps to allocate orders among the supplier pool and the contract-spot allocation model can assign orders between the spot market and the supplier pool, respectively. The significance of this paper is to propose a novel decision support framework which helps the buyer to make optimal and robust procurement decision including supplier selection and order allocation among multiple supplier sources in the existence of correlated demand, yield and spot price uncertainties. A case study is used to illustrate the performance of the proposed framework and the proposed methods show the promising result. Collapse

Semantic filters: goal programming

Topics: procurement management risk management decision making flash memory device decision support system

Methods: descriptive statistic simulation computational algorithm trade-off analysis method goal programming
An Integrated Group Decision Making Support Model for Corporate Financing Decisions
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2013 | Group Decision and Negotiation | Citations: 0
Authors: Tsai, Wen-Hsien; Yang, Ching-Chien; Leu, Jun-Der; Lee, Ya-Fen; Yang, Chih-Hao

Abstract: The essential goal of corporate finance is to maximize corporate value while red ... Expand

Abstract: The essential goal of corporate finance is to maximize corporate value while reducing a firm’s financial risks. Corporate financing decision is a kind of multi-criteria based group decision making that embodies major approaches to handle qualitative criteria and quantitative limitations. However, in literature related to financing decision making, very little research uses decision making trial and evaluation laboratory (DEMATEL) and analytic network process (ANP) methods to consider the impact and dependency of its factors, or uses Goal programming (GP) to find the satisfactory financing decision under the related financial constraints. This study proposes an integrated group decision making support (GDMS) model to assist corporate financing group decision makers (DMs) in obtaining a satisfactory group solution. ANP, DEMATEL and GP are combined in this GDMS model. By using this model, the group DMs can systemically structure a multi-criteria network framework and derive priority weights of those criteria, and then deal with the quantitative financial constraints for a satisfactory group solution. An illustrative case is demonstrated for the effectiveness and practicability of this GDMS model. Collapse

Semantic filters: goal programming

Topics: decision making brainstorming

Methods: trade-off analysis method goal programming analytic network process nominal group technique

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Found 28 articles

A structured method for smart city project selection

Machine learning based system for managing energy efficiency of public sector as an approach towards smart cities

Project Staff Scheduling with Theory of Coalition

MAKE THE BEST OUT OF WHAT YOU HAVE – A LITERATURE REVIEW ON PROCESS PRIORITIZATION

Spatial modelling of climate change in Irish forestry

Prioritization and Aggregation of Intuitionistic Preference Relations: A Multiplicative-Transitivity-Based Transformation from Intuitionistic Judgment Data to Priority Weights

Organizational implications of a comprehensive approach for cloud-storage sourcing

Deriving Weights from Interval Multiplicative Preference Relations in Group Decision Making

A decision support system for procurement risk management in the presence of spot market

An Integrated Group Decision Making Support Model for Corporate Financing Decisions